literature review on motivation and job performance

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• Published: 09 May 2024

Detecting causal relationships between work motivation and job performance: a meta-analytic review of cross-lagged studies

• Nan Wang 1   na1 ,
• Yuxiang Luan 2   na1 &

Humanities and Social Sciences Communications volume  11 , Article number:  595 ( 2024 ) Cite this article

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• Business and management

Given that competing hypotheses about the causal relationship between work motivation and job performance exist, the current research utilized meta-analytic structural equation modeling (MASEM) methodology to detect the causal relationships between work motivation and job performance. In particular, completing hypotheses were checked by applying longitudinal data that include 84 correlations ( n  = 4389) from 11 independent studies measuring both work motivation and job performance over two waves. We find that the effect of motivation (T1) on performance (T2), with performance (T1) controlled, was positive and significant ( β  = 0.143). However, the effect of performance (T1) on motivation (T2), with motivation (T1) controlled, was not significant. These findings remain stable and robust across different measures of job performance (task performance versus organizational citizenship behavior), different measures of work motivation (engagement versus other motivations), and different time lags (1–6 months versus 7–12 months), suggesting that work motivation is more likely to cause job performance than vice versa. Practical and theoretical contributions are discussed.

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Introduction.

Job performance is defined as “scalable actions, behavior, and outcomes that employees engage in or bring about that are linked with and contribute to organizational goals” (Viswesvaran and Ones, 2000 , p. 216), is a core concept in the applied psychological field (Campbell and Wiernik, 2015 ; Choi et al., 2022 ; Giancaspro et al., 2022 ; Hermanto and Srimulyani, 2022 ; Motowidlo, 2003 ). Employees’ job performance is important for both organization and the employee. For an organization, job performance is the vital antecedent of organizational performance (Almatrooshi et al., 2016 ); for an employee, job performance is a predictor of turnover (Bycio et al., 1990 ; Martin et al., 1981 ), and wellbeing (Bakker and Oerlemans, 2011 ; Ford et al., 2011 ). Considering the importance of job performance in the applied psychological field, it is not surprising that researchers have devoted significant effort to researching job performance, especially its antecedents.

Prior meta-analyses identified a series of antecedents of job performance, such as job satisfaction (Iaffaldano and Muchinsky, 1985 ; Judge et al., 2001 ; LePine et al., 2002 ), organizational commitment (Jaramillo et al., 2005 ; Mathieu and Zajac, 1990 ), and work motivation (Cerasoli et al., 2014 ; Van den Broeck et al., 2021 ; Van Iddekinge et al., 2018 ). Among these factors, motivation, which refers to the force that drives the direction, intensity, and persistence of employee behavior (Pinder, 2014 ), is a medium to strong predictor of performance (Cerasoli et al. 2014 ). Although the early meta-analyses (e.g., Cerasoli et al., 2014 ; Van Iddekinge et al., 2018 ) confirmed the significant correlations between work motivation and job performance, the accurate causal relationship between work motivation and job performance remains unclear. Does work motivation cause job performance? Does reverse causality exist? Or there is a reciprocal relationship between them? Unfortunately, previous meta-analyses (e.g., Cerasoli et al., 2014 ; Van Iddekinge et al., 2018 ), which are based on cross-temporal data rather than longitudinal cross-lagged panel data, could not address this research gap.

We propose four competing hypotheses to explain the causal relationship between them. First, work motivation causes job performance. Second, job performance causes work motivation. Third, work motivation causes job performance and vice versa (reciprocal model). Finally, work motivation and job performance are causally unrelated. In the Theory and Hypotheses part, we will describe these hypotheses in detail.

By checking all four hypotheses, the current study aims to reveal the causal relationship between work motivation and job performance. A single primary study could not accomplish our research goal due to the distorting of statistical artifacts (e.g., sampling error and measurement error; Hunter and Schmidt, 2004 ). For instance, the relationships of interest may vary when sampling from different organizations because of sampling error, which would harm the accuracy of the results. Fortunately, the meta-analysis methodology could help us to correct the statistical artifacts and thereby provide solid and reliable empirical evidence for the theory. As such, we utilize a meta-analysis methodology that allows us to aggregate cross-lagged panel data to test the four hypotheses.

This article provides the first meta-analysis that estimates the longitudinal effects between work motivation and job performance, contributing to both theory and practice. In terms of theory, this study will provide solid evidence for the causal relationship between work motivation and job performance, contributing to motivation and performance literature. In relation to practice, the results of our study will provide guidance for human resource management. For instance, if we find that motivation causes performance, using human resource practice (e.g., performance appraisal and training) that will influence motivation to improve performance will be reasonable; whereas if other results were found, perhaps we will reconsider the effectiveness of the current human resource practices.

Theory and hypotheses

In this part, we will review work motivation and job performance and their measurements. Then, we will develop the hypotheses between them. Finally, as a meta-analysis, we will propose a research question about the moderators that might influence the relationships between motivation and performance.

Before the 1970s, organizational psychologists primarily directed their attention toward job satisfaction, often sidelining the exploration of work performance (Organ, 2018 ). However, the tide turned in the 1980s, when scholars began conceptualizing individual job performance as a distinct construct (Campbell and Wiernik, 2015 ). Job performance is commonly characterized by two key forms: task performance and organizational citizenship behavior (OCB), providing a structured framework for evaluating employee contributions (Hoffman et al., 2007 ; Sidorenkov and Borokhovski, 2021 ; Young et al., 2021 ). Notably, performance should not be conflated with efficiency and productivity. While performance encompasses a broader term, often associated with achieving various levels or outcomes potentially under myriad conditions, both efficiency and productivity are intricately tied to the concept of optimizing resource utilization and maximizing output production (Campbell and Wiernik, 2015 ).

Task performance refers to the effectiveness with which job incumbents perform activities that contribute to the organization’s technical core (Borman and Motowidlo, 1997 , p. 99). Notably, this concept is also identified as “in-role performance/behavior” in the literature (Koopmans et al., 2011 ; Raja and Johns, 2010 ). In-role performance essentially encapsulates behaviors aimed at fulfilling formal tasks, duties, and responsibilities, often detailed in job descriptions (Becker and Kernan, 2003 ; Williams and Anderson, 1991 ). Contrarily, early meta-analyses have amalgamated related concepts, acknowledging their overlapping domains (Riketta, 2008 ; Young et al., 2021 ). OCB is delineated as “individual behavior that is discretionary, not directly or explicitly recognized by the formal reward system, and that in the aggregate promotes the effective functioning of the organization” (Organ, 1988 , p. 4). Contextual performance, reflecting actions extending beyond formal job descriptions and enhancing organizational effectiveness (MacKenzie et al., 1991 ), is frequently paralleled with OCB in meta-analytic practices (Riketta, 2008 ; Young et al., 2021 ). A noteworthy correlation between task performance and OCB (ρ = 0.74) is illuminated through a meta-analysis by Hoffman et al. ( 2007 ). While some scholars propose that performance can exhibit counterproductive facets (Campbell and Wiernik, 2015 ), meta-analysis unveils only a moderate relationship between OCB and counterproductive work behavior and reveals somewhat disparate relationship patterns with their antecedents (Dalal, 2005 ). Therefore, in this study, we study two fundamental dimensions of job performance: task performance and OCB.

Motivation reflects why people do something. It is widely researched in the work and educational psychological field (Anesukanjanakul et al., 2019 ; Christenson et al., 2012 ; Fishbach and Woolley, 2022 ; Hartinah et al., 2020 ; Muawanah et al., 2020 ). Work motivation stands distinct amidst a spectrum of related concepts. Firstly, it is imperative to differentiate motivation from personality. Personality, defined as a construct embodying a set of “traits and styles displayed by an individual, represents (a) dispositions, that is, natural tendencies or personal inclinations of the person, and (b) aspects wherein the individual deviates from the ‘standard normal person’ in their society” (Bergner, 2020 , p.4). Personality acts as a distal antecedent to performance, influencing it indirectly through the medium of motivation (Judge and Ilies, 2002 ; Kanfer et al., 2017 ). Secondly, while interrelated, goal pursuit and motivation are distinctive concepts. For example, if employees aim to earn money, their motivations are characterized as external. Conversely, intrinsically motivated employees engage in work for the enjoyment derived from the process itself, potentially without being driven by explicit work goals (Deci et al., 2017 ). Thirdly, motivation is different from attitude. Job attitudes (e.g., job satisfaction) reflect the evaluations of one’s job (Judge and Kammeyer-Mueller, 2012 ). Motivation may not necessarily include the evaluation of the job. For instance, engaged people, who usually put a great deal of effort into their work (Bakker et al., 2014 ), may not include the evaluation of the job. Actually, attitudes may likely be influenced by motivations, indicating they are different concepts (Judge and Kammeyer-Mueller, 2012 ).

As work motivation is a very grand concept, many psychological and organizational theories try to measure motivation by using different scales. For instance, in the perspective of the Job Demands–Resources (JD-R) Theory (Bakker, 2011 ; Bakker and Demerouti, 2017 ), work engagement is regarded as the motivation factor that links job resources and job performance; in the perspective of the Self-determination Theory (SDT), motivation (e.g., intrinsic motivation and extrinsic motivation) is the antecedent of job performance (Deci et al., 2017 ; Deci and Ryan, 2000 ). In the review process, we notice that work engagement is one of the most widely-used measurements of motivation when researching the work motivation-job performance linkage.

Hypotheses between motivation and performance

The first potential causal relationship is that work motivation causes job performance. This argument is shown in Fig. 1 . This Argument is supported by many well-established theories and empirical evidence. To start, in the JD-R theory (Bakker, 2011 ; Bakker and Demerouti, 2007 ; Bakker and Demerouti, 2017 ), engaged (well-motivated) people will accomplish job performance because they will experience more positive emotions which may increase the creation of new ideas and resources and they will be healthy and be energetic at work. The correlational relationship was confirmed by a prior meta-analysis as it found a medium correlation ( ρ  = 0.48) between engagement and job performance (Neuber et al., 2021 ). Then, from the perspective of SDT (Deci et al., 2017 ; Deci and Ryan, 2000 ; Gagné and Deci, 2005 ), motivation also influences performance. In particular, intrinsically motivated employees will be creative and productive, increasing their job performance. An early meta-analysis finds a moderate correlation between intrinsic motivation and performance ( ρ  = 0.28) (Cerasoli et al., 2014 ). Finally, motivation may influence performance directly by determining the level of effort and persistence an individual will exert in the face of obstacles (Kanfer, 1990 ). Motivation may also influence performance indirectly, as motivated individuals are more likely to set challenging goals and commit to achieving them, leading to higher performance (Locke and Latham, 2006 ). Together, it seems obvious that work motivation will cause subsequent job performance. When using the cross-lagged panel research design to test this hypothesis, the subsequent performance will be predicted by the previous motivation after controlling the auto-correlation effect. As such, the following hypothesis is proposed:

An illustration of arguments for a “motivation-causing-performance” process. This figure is covered by the Creative Commons Attribution 4.0 International License.

Hypothesis 1 : Work motivation causes job performance. In particular, work motivation (T1) is the significant predictor of job performance (T2) after controlling the auto-correlation effect of job performance (T1).

As illustrated in Fig. 2 , the second potential causal relationship is that performance causes motivation. As SDT suggested, feedback will influence motivation (Deci et al., 1999 ). Employees who achieve job performance may receive positive feedback (e.g., pay and recognition) from their organizations and leaders (Riketta, 2008 ), increasing their work motivation. Applying longitudinal data, Presbitero ( 2017 ) provided indirect evidence that improvements in reward management yielded a positive change in the level of motivation (measured by engagement). Therefore, we hypothesize the following:

An illustration of arguments for a “performance-causing-motivation” process. This figure is covered by the Creative Commons Attribution 4.0 International License.

Hypothesis 2 : Job performance causes work motivation. In particular, job performance (T1) is the significant predictor of work motivation (T2) after controlling the auto-correlation effect of work motivation (T1).

According to Fig. 3 , the third hypothesis is that motivation causes performance and performance causes motivation simultaneously. Combining Hypotheses 1 and 2, we could conclude this reciprocal hypothesis. Utilizing cross-lagged panel data, early studies found reciprocal relationships between (a) self-efficacy and academic performance (Talsma et al., 2018 ) and (b) job characteristics and emotional exhaustion (Konze et al., 2017 ). That is to say, there might be a reciprocal relationship between variables. Thus, we derive the following hypotheses:

An illustration of arguments for a simultaneous reciprocity between work motivation and job performance. This figure is covered by the Creative Commons Attribution 4.0 International License.

Hypothesis 3 : There is a reciprocal causal relationship between work motivation and job performance. In particular, work motivation (T1) is the significant predictor of job performance (T2) after controlling the auto-correlation effect of job performance (T1) and vice versa.

As presented in Fig. 4 , the final potential causal relationship is that performance and motivation are causally unrelated. Performance and motivation may be causally unrelated due to cross-temporal research design and common method bias (Podsakoff et al., 2003 ). For instance, when work motivation and job performance are measured at the same time point and rated by one person, their correlation may inflate due to common method bias and thereby draw inaccurate causality. Therefore, we put the following hypothesis:

An illustration of arguments for a causally unrelated relationship between work motivation and job performance. This figure is covered by the Creative Commons Attribution 4.0 International License.

Hypothesis 4 : Work motivation and job performance are causally unrelated. In particular, work motivation (T1) is not a significant predictor of job performance (T2) after controlling the auto-correlation effect of job performance (T1), whereas job performance (T1) is also not the significant predictor of work motivation (T2) after controlling the auto-correlation effect of work motivation (T1).

We also propose a research question about the potential moderators that may influence the relationship of interest. Following early longitudinal meta-analyses (Riketta, 2008 ; Talsma et al., 2018 ), three moderators are considered, namely, performance measurements, motivation measurements, and length of time lag (shorter vs. longer time lags between two waves).

Firstly, as we illustrated in the Introduction part, there are two measurements of work performance, namely, task performance and OCB. We would like to explore the potential moderating role of job performance measurements (task performance versus OCB). This exploration is pivotal. Theoretically, performance should envelop two dimensions: task performance and OCB (Koopmans et al., 2011 ). However, a disparity exists in organizational recognition and reward systems, wherein task performance is formally acknowledged, while OCB is not (Organ, 2018 ). The impact of such discrepancies on their respective relationships with performance remains nebulous. Undertaking a meta-analysis to probe into these moderating variables will not only deepen our understanding of the nexus between motivation and performance but also furnish supplementary evidence to buttress their interconnection.

Secondly, the motivation measurement is taken into consideration. In particular, many longitudinal studies (e.g., Shimazu et al., 2018 ; Nawrocka et al., 2021 ) use work engagement to measure motivation. Although theoretical frameworks suggest that these measures might reflect motivation, various measures of motivation may exhibit distinct relationships with performance. Despite the absence of cross-lagged meta-analyses, insights can potentially be derived from cross-temporal meta-analyses. For example, Cerasoli et al. ( 2014 ) identified a correlation of 0.26 between intrinsic motivation and performance, while Corbeanu and Iliescu ( 2023 ) observed a correlation of 0.37 between work engagement and performance. Consequently, we question whether the measurement of motivation exerts a significant moderating effect. Given that work engagement is the most prevalently utilized measure, we draw comparisons between the results pertaining to work engagement and those associated with other forms of motivation.

Finally, it is unclear how long the time lag process (i.e., the length of time between two measurement waves) will influence the relationship of interest. In the present study, time lags varied from 1 to 12 months (refer to the coding information for details). On the one hand, the relationship between motivation and performance may depend on time. For instance, even with strong motivation, employees may require time to learn and adapt to new tasks, affecting performance enhancement. Furthermore, the delay in receiving feedback or recognition, especially in long-term projects, may decelerate the positive influence of performance on motivation.

On the other hand, there may exist an optimal time lag interval in cross-lagged analysis, as suggested by Dormann and Griffin ( 2015 ). When the time lag falls short of this optimal point, the cross-lagged effect size diminishes sharply; inversely, if the time lag exceeds it, the effect size likewise declines. Aligning with prior meta-analysis efforts (Riketta, 2008 ), we categorize the time lag into two groups, namely, 1–6 months and 7–12 months, to explore the possible moderating influence of the time lag. The efficacy of a 6-month time lag design remains uncertain. Nevertheless, a design that maintains a 6-month interval at each end—presenting a symmetrical six-month span—prompts a subgroup analysis within the meta-analysis, increasing the likelihood of discerning potential moderating impacts. To sum up, we seek to answer the following research question:

Research Question 1 : Do the causal relationship between work motivation and job performance vary due to (a) job performance measurement (task performance versus OCB), (b) work motivation measurement (work commitment versus other motivations), and (c) time lag (1–6 months versus 7–12 months)?

Literature search

To locate the studies that might include the cross-lagged data about work motivation and job performance, following early meta-analyses (Neuber et al., 2021 ; Riketta, 2008 ; Van Iddekinge et al., 2018 ), the authors searched the following keywords: (a) motivation ( motivation or engagement ), (b) performance ( performance , job performance , task performance , or organization citizenship behavior ), and (c) cross-lagged ( longitudinal or cross-lagged) utilizing Web of Science and Google Scholar databases. The authors (W and L) seek to include studies published from 2000 to 2022. The search was conducted in January 2023 and encompassed English-language research materials. We did not restrict the types of research sources, including journal articles, book chapters, and dissertations. Authors W and L performed the search using the Title, Abstract, and Keywords. After removing duplicates, the authors initially obtained 120 potential articles that used longitudinal data.

Inclusion criteria and coding

After reviewing some early published longitudinal meta-analyses (Maricuțoiu et al., 2017 ; Riketta, 2008 ; Talsma et al., 2018 ), the authors made the following inclusion criteria. First, samples should come from organizations because the current study focuses on work motivation and job performance. As such, students’ or athletes’ samples were removed.

Second, studies should provide a full correlation matrix that includes six correlations and measure motivation and performance at two (or more) measurement waves. Six correlations are two synchronous correlations, the two cross-lagged correlations, and the two stabilities correlations (Kenny, 1975 ). In particular, two synchronous correlations are correlations (a) between motivation (T1) and performance (T1) and (b) between motivation (T2) and performance (T2). Two cross-lagged correlations are correlations (a) between motivation (T1) and performance (T2) and (b) between performance (T1) and motivation (T2). Two stabilities correlations are correlations (a) between motivation (T1) and motivation (T2) and (b) between performance (T1) and performance (T2).

After reading all potential studies ( k  = 120) and excluding studies that were not able to meet the inclusion criteria, the final database contained 11 studies that included 84 correlations ( n  = 4389). Considering the challenges in obtaining samples and findings from early meta-analyses (Riketta, 2008 , with 16 studies; Talsma et al., 2018 , with 11 studies), a sample of 11 studies is likely sufficient for conducting a cross-lagged meta-analysis. Two authors coded the following information: bibliographic references (authors and publication year), sample description (sample size and country), research design (interval between two measurement waves), effect sizes, and the reliabilities (i.e., Cronbach’s α) of all scales. The authors discussed the differences in the coding information until the intercoder agreement was researched 100%. Among the examined studies, 8 utilized a self-reported method for measuring performance, 2 adopted a leader-reported method, and 1 study employed an objective indicator, specifically the results of performance appraisals. The majority of these studies ( k  = 10) originated from companies, with only one emanating from an educational organization. The samples in the 11 studies encompass a wide range of industries, including banking, auditing, and social services. The diversity in this study stems from the primary authors’ intentional strategy to collect data from a variety of industries. This approach enables a comprehensive insight into the nature of professional settings and employee motivation across different sectors. Geographically, most samples were drawn from Europe (k = 9), while the remaining were from East Asia (k = 2). A PRISMA flowchart (see Fig. 5 ) presents the process of literature search.

An illustrative demonstration of literature search procedures and inclusion criteria. This figure is covered by the Creative Commons Attribution 4.0 International License.

Before analyzing, publication bias is taken into consideration. We used the Trim-and-Fill method and Eggs’ Regression method to detect potential publication bias. This analysis was conducted utilizing metafor package (Viechtbauer, 2010 ) in R. The results were shown in Table 1 .

Generally speaking, there are two steps in a meta-analytic structural equation modeling analysis (Bergh et al., 2016 ; Viswesvaran and Ones, 1995 ). The first one is to build a meta-analytic correlation matrix. The second one is to use this matrix to conduct path analysis. In the current study, to build a meta-analytic correlation matrix, we employed the Hunter-Schmidt methods’ meta-analysis technology to aggregate effect sizes (Hunter and Schmidt, 2004 ). In particular, reliabilities (i.e., Cronbach’s α) were used to correct measurement errors. The random effect meta-analysis method was utilized to correct sampling errors. This analysis was accomplished using the psychmeta package (Dahlke and Wiernik, 2019 ) in R. The results of the meta-analytic correlation matrix for path analysis were shown in Table 2 . To answer research question 1, Table 2 also includes correlations that are grouped by performance measurements, motivation measurements, and time lags.

Then, this meta-analytic correlation matrix was used to conduct path analysis, the results were shown in Table 3 . This analysis was accomplished using MPLUS software (Muthén and Muthén, 2017 ). Specifically, to conduct path analysis, the maximum likelihood estimation (MLE) was used. Besides, the sum of the sample sizes was employed as the inputted sample size (Riketta, 2008 ).

As Table 1 shows, the results suggest there is not a significant publication bias. First, using the Trim-and-Fill method, only one asymmetric effect size was located (i.e., the correlation between performance T1 and performance T2). After inputting this “missed” correlation, the averaged correlation only decreased by 0.02, suggesting the publication bias is not serious. Second, utilizing the Eggs’ Regression method, all the p-values are bigger than 0.05, confirming the publication bias is not significant. Together, the overall publication bias is not serious.

Table 2 depicts the averaged correlation (r) and true score correlation (ρ) of interest. For instance, the ρ between motivation (T1) and motivation (T2) is 0.80, whereas the ρ between performance (T1) and performance (T2) is 0.54.

As Table 3 presents, overall, work motivation appears to be a predictor of job performance, whereas job performance appears to be a predictor of work motivation. In particular, the path coefficient (i.e., M1 → P2) from motivation (T1) to performance (P2) is positive and significant ( β  = 0.143, p  < 0.001). However, the path coefficient (i.e., P1 → M2) from performance (T1) to motivation (P2) is not significant ( β  = −0.014, p  > 0.050). As such, H1 was supported, whereas H2, H3, and H4 were rejected. We draw Fig. 6 to explain the causal relationship between work motivation and job performance.

An illustration of estimated causal relationship between work motivation and job performance following MASEM analysis. This figure is covered by the Creative Commons Attribution 4.0 International License.

To answer research question 1, as Table 3 shows, neither the performance measure, motivation measure, nor time lag influence the causal relationship between motivation and performance. In particular, all the path coefficients (i.e., M1 → P2) from motivation (T1) to performance (P2) are positive and significant. However, the path coefficients (i.e., P1 → M2) from performance (T1) to motivation (P2) are negative or insignificant, supporting H1. The moderating effect was determined using z-tests to compare the two effect sizes. For example, when examining the moderating role of the performance measure, there was no significant difference in path coefficients for M1 → P2 (β1 = 0.129, β2 = 0.085; z = 1.4, p  = 0.08). Similarly, for path coefficients P1 → M2, no significant difference was observed (β1 = −0.016, β2 = −0.052; z  = 1.14, p  = 0.13). Additionally, we did not observe any significant moderating effect for either motivation measures or time lag. Together, the causal relationship is motivation causes subsequent performance rather than vice versa. Besides, this relationship is not influenced by the three potential moderators.

In this part, we will first discuss our findings. Then, we will discuss the theoretical and practical implications. Finally, the limitations and future directions will be discussed.

To start, we will discuss the magnitude of correlations. Cohen ( 2013 ) suggested that a correlation at 0.1 is small, at 0.3 is medium, whereas at 0.5 is large. Applying this standard, we find that the magnitudes of correlations of interest are from medium to large. For instance, the ρ between motivation (T1) and motivation (T2) is 0.80 which is large, whereas the ρ between performance (T1) and performance (T2) is 0.54 which is medium. Besides, the correlation ( ρ  = 0.34) between motivation (T1) and performance (T1) is bigger than the correlation ( ρ  = 0.31) between motivation (T1) and performance (T2). One plausible explanation is that the former is measured at the same time point whereas the latter is measured at different time points. Two constructs measuring at the same time point may suffer from common method bias and their correlation may inflate (Podsakoff et al., 2003 ). Besides, early meta-analyses also found the correlations between motivation and performance are medium. For instance, Cerasoli et al. ( 2014 ) found a correlation between intrinsic motivation and performance is 0.26. Similarly, Borst et al. ( 2019 ) found medium correlations between engagement and in-role performance and ex-role performance (range from 0.31 to 0.46). To sum up, the overall correlations between motivation and performance are medium.

Then, we found that work motivation causes job performance rather than vice versa. This finding rejects the reciprocal and causally unrelated model. This finding is in line with many experiment studies (e.g., Amabile, 1985 ; Hendijani et al., 2016 ; Kovjanic et al., 2013 ) which found that motivation influenced performance. Combining the findings of both longitudinal and experimental studies, evidence suggests that work motivation appears to be a predictor of job performance.

However, what makes us surprised is that job performance cannot predict work motivation based on cross-lagged data. One possible explanation is there might be mediators that fully mediate the relationship between job performance and subsequent work motivation. For instance, in the perspective of SDT (Deci et al., 2017 ; Deci and Ryan, 2000 ), basic psychological needs (i.e., competence, autonomy, and relatedness) are the antecedents of motivation. Employees who accomplished their job performance are likely to fulfill the need for competence and thereby influence motivation. Thus, job performance (T1) may not directly influence work motivation (T2) but through the mediating role of basic psychological needs. In the JD-R theory (Bakker, 2011 ; Bakker and Demerouti, 2017 ), there could also have mediators between performance and motivation. These mediators are job resources (e.g., leader support). Employees who achieve performance may influence job resources (e.g., leader support) and thereby influence their motivation. In the current cross-lagged panel meta-analysis, these potential mediators (e.g., basic psychological needs and leader support) could not be tested. Therefore, we do not find job performance (T1) causes work motivation (T2).

Finally, three moderators (i.e., performance measure, motivation measure, and time lag) do not influence the causal relationship between motivation and performance. First, for performance measures, one explanation is that both task performance and OCB captured the nature of job performance. Second, for motivation measures, one explanation is that different measures of motivation both reflect the definition of motivation (Pinder, 2014 ). For instance, employees could work hard by being driven by both work engagement (Bakker, 2011 ) and intrinsic motivation (Deci et al., 2017 ). In other words, despite different measures of motivation being used, these concepts all capture the characteristics of motivation, indicating a consensus conclusion.

It’s important to acknowledge that various studies have employed distinct measures to gauge motivation, including psychological capital and self-efficacy, among others. Psychological capital can indeed serve as a reflection of motivation. Comprising four subdimensions—self-efficacy, hope, resilience, and optimism—psychological capital embodies the internal forces (motivation) that drive individuals to confront challenges (Newman et al., 2014 ). These components collectively capture the essence of motivation by epitomizing the underlying reasons that initiate and direct behavior. Therefore, they are integral in understanding the multifaceted nature of motivation. Additionally, our moderation analysis contributes further insights, suggesting that despite the nuanced complexities of motivation measures, they didn’t exhibit a substantial moderating impact on the outcomes. This finding underscores the importance of considering these motivational aspects not just as isolated factors but as integral components that interact with other elements in human behavior and response mechanisms.

For time lag, an early meta-analysis study finds a significant moderating role in the length of time lag (Riketta, 2008 ) which is different from the current study. In the current study, we noticed that the length of time lag is between 1 month and 12 months. However, we still lack the knowledge of whether this causal relationship will change over a longer period of time (e.g., more than 12 months). Together, three moderators do not influence the causal relationship between work motivation and job performance, strengthening the confidence in our findings.

Theoretical and practical implications

The current study is the first meta-analysis that uses longitudinal data to test the causal relationship between work motivation and job performance, making some theoretical implications. First, utilizing meta-analysis methodology, we reconciled four competing hypotheses about the causal relationship between work motivation and job performance, contributing to work motivation and job performance literature. Second, the current study contributes to SDT literature. SDT suggests that work motivation will influence human behavior and job performance (Deci et al., 2017 ). The current study provides solid evidence for the argument of SDT by using longitudinal data. Besides, the current study collected data from multiple organizations, making the findings have high external validity. Finally, the current study provided evidence for the JD-R theory, as we found engagement causes job performance rather than vice versa using a cross-lagged research design. Drawing on this finding, some results (e.g., Yu et al., 2020 ; Almawali et al., 2021 ), in JD-R literature using a cross-temporal research design, should be explained with caution.

The current study is also essential to practice. First, as the current study provides solid causal evidence for the motivation-performance linkage, it provides knowledge for human performance management. That is, human performance practices (e.g., compensation management and performance management) that influence employee motivation, will influence employee performance. Second, our knowledge suggests that some motivation-based leadership (e.g., empowering leadership) is useful as motivation predicts job performance in the long run. Finally, since we do not find job performance could predict subsequent work performance, practitioners should try to find some try practices to strengthen feedback mechanisms between them, making employees increase their performance continuously.

Limitations and future directions

There are some limitations in the current study. First, in the current study, both motivation and performance are measured by self-reported scales, which may trigger common method bias (Podsakoff et al., 2003 ). This effect is stronger when two constructs are measured at the same time point. For instance, the ρ between job performance (T1) and work motivation (T1) may inflate due to common method bias. Future studies could try to measure performance utilizing more objective indicators. Second, due to the cross-lagged research design, it allows for only tentative causal conclusions and cannot rule out some alternative causal explanations (Riketta, 2008 ). Future studies could try to use instrumental variables to rule out alternative causal explanations (Saridakis et al., 2020 ). Third, the present study employed the MASEM method to carry out path analyses. However, the generalizability of this method to other populations may be limited when dealing with heterogeneous correlation matrices (Cheung, 2018 ). Upon the accumulation of more homogeneous evidence, future research could replicate this study. Fourth, during our search process, we did not impose geographical constraints on the origin of primary studies. However, we observed that the majority of the samples predominantly come from Europe ( k  = 9). This brings to light the potential influence of culture on the relationship between motivation and performance. In countries characterized by high individualism, values such as personal achievement and autonomy are emphasized (Hofstede et al. 2010 ). In such cultures, motivation is frequently linked to personal goals and achievements, which may intensify the association between personal-focused motivation and performance. Nonetheless, our current dataset limits our ability to definitively assess these cultural effects. Future research should aim to explore the impact of cultural factors on the motivation-performance dynamics. Finally, our study faced certain constraints regarding data availability, particularly concerning specific motivation metrics such as extrinsic motivation, which were not obtainable from the primary studies. Future research could enhance and validate the findings of this study by employing a broader range of motivation measures. This expanded approach will not only reinforce the comprehensiveness and reliability of the results but also provide a more nuanced understanding of motivational dynamics.

Conclusions

This meta-analysis is the first one to detect the accurate causal relationship between work motivation and job performance using longitudinal data. The evidence supports the effects of work motivation on job performance and does not support the reverse effects. The reciprocal model and causally unrelated model are also not supported. The results appear reasonably robust, as the finding that work motivation predicts job performance was consistent across the examined moderators of job performance measure, motivation measure, and time lag length. This study contributes to motivation and performance literature. Besides, our findings are important for human resource management and leadership. Future studies could try to use instrumental variables to get a more accurate causal relationship.

Data availability

All data used to conduct the meta-analytic review are included in the supplemental file.

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Wang, N., Luan, Y. & Ma, R. Detecting causal relationships between work motivation and job performance: a meta-analytic review of cross-lagged studies. Humanit Soc Sci Commun 11 , 595 (2024). https://doi.org/10.1057/s41599-024-03038-w

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EMPLOYEE MOTIVATION, JOB SATISFACTION, AND EMPLOYEE PERFORMANCE: A LITERATURE REVIEW

• Imam Hidayat Universitas Trisaksi, Jakarta, Indonesia
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The purpose of this paper is to provide a structured literature review on the constructs of employee motivation, job satisfaction, employee performance, and empirical evidence on the relationship between motivation, job satisfaction, and performance. 20 (twenty) papers published during 2017-2021 that investigates employee motivation, job satisfaction, employee performance, and the relationship between employee motivation, job satisfaction, and employee performance were reviewed. The results of the review show that employee motivation and job satisfaction have positive and significant effect on employee performance or in other word employee motivation and job satisfaction are the determinants of employee performance.

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• DOI: 10.54099/ijebm.v1i2.360
• Corpus ID: 260460370

The Influence of Leadership Style on Employee Performance: A Systematic Literature Review

• Muhizan Tamimi , Sopi Sopiah
• Published in International Journal of… 30 November 2022
• Business, Psychology

38 References

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• Open access
• Published: 04 September 2021

Employee motivation and job performance: a study of basic school teachers in Ghana

• Joseph Ato Forson   ORCID: orcid.org/0000-0002-5997-5713 1 ,
• Eric Ofosu-Dwamena 2 ,
• Rosemary Afrakomah Opoku 3 &
• Samuel Evergreen Adjavon   ORCID: orcid.org/0000-0002-2713-3327 4  

Future Business Journal volume  7 , Article number:  30 ( 2021 ) Cite this article

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Motivation as a meaningful construct is a desire to satisfy a certain want and is a central pillar at the workplace. Thus, motivating employees adequately is a challenge as it has what it takes to define employee satisfaction at the workplace. In this study, we examine the relationship between job motivation factors and performance among teachers of basic schools in Ghana. The study employs a quantitative approach on a sample of 254 teachers from a population of 678 in the Effutu Municipality of Ghana, of which 159 questionnaires were duly answered and returned (representing 62.6% return rate). Using multiple regression and ANOVA, the study finds compensation package, job design and environment and performance management system as significant factors in determining teacher’s motivation in the municipality. Thus, these motivation factors were significant predictors on performance when regressed at a decomposed and aggregated levels. These findings support the self-determination theory, more specifically on the explanations advanced under the controlled and autonomous motivation factors. Significant differences were also observed in teachers’ performance among one of the age cohorts. The study urges the municipal directorate of education to make more room for young teacher trainees and interns who are at the formative stage of their careers to be engaged to augment the experienced staff strength. More should be done to make the profession attain some level of autonomy in the discharge of duty to breed the next genre of innovative educators in the municipality.

Introduction

Motivation as a meaningful construct is a central pillar at the workplace. Thus, motivating employees adequately is a challenge as it has what it takes to define employee satisfaction at the workplace. Quite a number of studies have been devoted to the link between motivation and its constituent factors and employee performance in different organizations [ 7 , 46 ]. Our study draws inspiration from the self-determination theory (SDT) advanced by Deci et al. [ 14 ] as a framework that can be applied to teachers motivation and performance in basic schools in Ghana. It is worth noting that SDT differentiates between controlled motivation and autonomous motivation. The latter is evident when individuals are faced with pressure and control. The former on the other hand emphasizes on the volitional nature of the behavior of individuals. The SDT provides evidence that suggests that motivation fuels performance [ 14 , 57 ].

In Ghana, the subject of motivation has always been at the apex of national agenda and is evident in the number of strike actions in the public service. In the early part of the 2000s, teachers were part of the public servants whose agitation for improved condition of service did not go unnoticed. Forson and Opoku [ 16 ] had stated that teachers’ emolument accounted for less than 35% of the public service wage bill although teachers were perceived to be in the majority in terms of numbers. This phenomenon did spark a wave of attrition of trained teachers to other sectors of the Ghanaian economy. The teaching profession as a matter of fact became a launched pad for the youth. It should be said that the nature of the school setting is basically a function of internal management and leadership. The head teacher or director of education as the Chief Executive needs to appreciate and recognize that results can be obtained through people. In today’s world, organizations are concerned with what should be done to achieve sustained high level of performance through people who are innovative thinkers [ 4 , 17 , 41 ]. These include paying more attention to how individuals can best be motivated and provision of an atmosphere that helps individuals to deliver on their mandates in accordance with the expectations of management [ 25 ]. This means that an educational manager or an individual engaged as a teacher cannot do this job without knowing what motivates people. The building of motivating factors into organizational roles and the entire process of leading people should be contingent on knowledge of motivation. Koontz and Weinrich [ 25 ] agree that the educational managers’ job is not to manipulate people but rather to recognize what motivates people.

A national debate ensued on the significant role played by teachers in nation building and the need to address the shortfall in the condition of service of teachers to motivate them to perform. Wider consultative meetings were held with stakeholders in the teaching fraternity and the outcome and the panacea was the introduction of a uniform pay structure based on qualification. The legislative arm of government passed Act 737 in 2007 that saw the birth of the Fair Wages Salary Commission (FWSC). The mandate of the commission was to ensure a fair and systematic implementation of government pay policy [ 18 ]. Although this has stabilized the teaching profession in terms of the level of attrition, concerns on how this inducement translate into teacher’s performance seem to dominate national discourse especially in the face of fallen standard of education in Ghana. Such concerns have raised questions such as the following: (1) Does pay rise correlate with performance? (2) Are there other factors that ought to be considered in the nexus between motivation and performance? (3) Are there any significant differences in the level of performance among various age cohorts (4) Do educational background motivate teachers to perform better? These and other questions are addressed in this study.

The objective of this paper is to examine the link between job motivation factors and performance among basic school teachers in Ghana. This is against the backdrop that teachers have for some time now complained about condition of service and with the passage of FWSC bill, one would have thought that would have impacted on performance of teachers as it has been proven that motivation leads to satisfaction and ultimately to high performance. The standard of education continues to be a major concern in the educational setup of Ghana.

We organize the paper as follows: section one is the introduction that sets the tone for the paper. The problem is defined in this section, and the necessary questions that warrant redress are asked. We continue with a brief literature review on the concept of motivation, leading to the development of a conceptual framework and hypothesis based on the self-determination theory (SDT). Section two focuses on the method deployed, with emphasis on the aim, design and setting of the study. The theoretical equation for the multiple regression is brought to the fore here. Section three is the results and discussion, and section four concludes with policy implications.

The concept of motivation and self-determination theory (SDT)

Maslow [ 33 ] is credited for being part of the early contributors of human motivation concept. Maslow classifies human needs that motivate them into two: (1) homeostasis and (2) finding that appetites (preferential choices among foods). The former refers to the body’s automatic efforts to maintain a constant, normal state of the blood stream. The latter concept, on the other hand, is of the view that if the body lacks some chemical, the individual will tend (in an imperfect way) to develop a specific appetite or partial hunger for that missing food element. Thus, Maslow was of the view that any of the physiological needs and the consummatory behavior involved with them serve as channels for all sorts of other needs. Relating this assertion to teachers and the need for a salary pay rise, it should be pointed out that a person who thinks he is hungry may actually be seeking more for comfort, or dependence and managers in the educational sector ought to know this. Contemporary researches have expanded on the theory of motivation as advanced by Maslow [ 33 , 34 ]. For an organization to thrive and be efficient, certain conditions ought to be available in order for managers to get the best out of its human resources (workers/employees). Employees of an organization are the greatest asset in a dynamic and competitive environment [ 49 ]. In the words of Martin [ 32 ], if an organization wants to be effective and aims to sustain the success for a longer period of time, it is important for it to have a motivated workforce made up of employees ready to learn. The last three decades have witnessed an avalanche of studies that emphasizes on the point that employee motivation is essential for the success of a business [ 2 ].

In exploring further on this connection, Mifflin [ 35 ] delved into the fundamental meaning of the word “motivation” and pointed out that it is a Latin word which means to move. Therefore, it is near impossible to move peoples’ behavior in an organization unless such move is triggered by certain incentives. Robins and Coulter [ 49 ] explained the term motivation as the desire and willingness to exert high level of inspiration to reach organizational goals, conditioned by the efforts ability to satisfy some individual need. In this study, we define motivation simply as the act of moving people triggered by the provision of some incentives to achieve a desired goal.

In the words of Deci and Ryan [ 13 ], the SDT focuses on human beings inherent desire to bring change and progress as they advance to their fullest potential. Several studies have applied the SDT in various research areas that includes education, medicine and other organizational context. The SDT is of the view that individuals are by nature active entities who will do everything possible to be integrated into the wider social environment in an attempt to be responsive to the behavior consistent with existing self. The theory according to Trépanier et al. [ 57 ] defines social context as the workplace which facilitate or frustrate ones striving toward self-determination.

The SDT theory has two major forms of motivation which may be differentiated on the basis of its nature and quality according to Howard et al. [ 22 ]. When employees engage in interesting activities or in pursuance of their needs, such a form of motivation is ascribed as autonomous motivation. Such a form of motivation facilitates employees’ vitality and energy including satisfaction and well-being [ 14 ]. When employees engage in activities out of pressure as a result of external factors such as attaining rewards including threat of being punished, or even endogenous sources of such pressure as maintaining self-esteem, want of approval, image management or avoiding guilt, such a form of motivation can be ascribed as controlled motivation. Gillet et al. [ 20 ] explain that people with controlled motivational behavior do so out of reason as long as these contingencies exist and thus it predicts maladaptive work outcomes (e.g., exhaustion of personal energy) and turnover intentions.

SDT and job performance

According to Motowildo et al. [ 38 ], job performance is a construct that elicits behavior related to achievement with evaluative components. Most studies on this relationship have emphasized on the role of autonomous and intrinsic motivation on performance with the argument that individuals autonomously motivated have certain inherent values and behaviors and thus give off optimal performance. The theory of self-determination explains that autonomous motivation should be the necessary ingredient for better performance. That is, when individuals are better informed about the purpose of their job and have a sense of ownership and the degree of freedom to operate (autonomy), the possibility of they performing better at work may be high. The source of such motivation according to Deci et al. [ 14 ] may be from one’s interest and values. It is purpose-driven, amplifies energy, enjoyable and provides enough rationalization for tasks to be accomplished effectively. Moreover, the intrinsic component of autonomous motivation has been linked with job performance in related literature and types of performance [ 7 ].

Empirically, there are evidence to suggest that autonomous motivation is linked with performance. Evidence pertaining to controlled motivation is less dispositive. Proponents of the SDT have argued that controlled motivation (e.g., performance management systems) could reduce employee functioning because action derived from personal values and interest may be disconnected, therefore leading to negative effects on performance [ 48 ]. Counter argument posits that controlled motivation may foster employee willingness to complete tasks in an attempt to avoid guilt or punishment or to earn external reward which may come in the form of compensation package [ 27 ]. In this study, we focus on both the controlled and autonomous motivational factors. More specifically, we focus on Herzberg et al. [ 21 ] motivators validated by Harvard Business Review in 2003 which were made up of two motivators: (1) intrinsic factors such as achievement, recognition for achievement, the work itself, growth, responsibility and advancement, and (2) extrinsic factors such as supervision, working conditions, payment, interpersonal relationship, appreciation and company policy. Therefore, the bundle of motivators used in this study are similar to the aforementioned ones and may include performance management systems, external rewards that come in the form of compensation packages, job environment and training and development [ 30 ]. We explain these constructs further with the empirical evidence leading to the development of the conceptual framework.

• Compensation package

Rasheed et al. [ 44 ] posit that package of compensation offered to teachers in institutions of higher learning has to be made based on several factors that may include the experience that underpins the abilities of the teacher, qualifications and perhaps market rates. This is supported by Bohlander et al. [ 6 ] who argued that teachers compensation ought to be the most central concern for managers and administrators of schools in stimulating them. Most of these research studies are premised on the fact that compensation should be designed to meet the needs of teachers and has be fashioned in the form of tangible rewards. In corroborating this assertion, Marlow et al. [ 31 ] observed that low condition of service defined by salary creates stress among teachers in schools. Thus, teachers’ condition of service should be market competitive in order to get higher motivation and to maintain them. Other studies have found that salary levels have been the main challenge for education managers and are the reason for the high attrition and that education planners and managers should pay attention to the design of compensation packages.

Job design and working environment

The needs of teachers on the job ought to be planned properly. The workload on teachers should not be such that it will de-motivate [ 44 ], p. 103. Teachers at all levels should have a learning environment, and educational administrators should make a point to treat existing human resource (teachers) with maximum respect devoid of any discrimination.

Nowadays, job design is the central focus of managers and human resource researchers. Thus, a well-designed job has what it takes in getting interest of employees. On the contrary, poorly designed job breeds boredom among employees. Davidson [ 12 ] makes an important observation and remarked in his research that when teachers are overloaded and burdened with so many non-teaching activities, it portends as a hindrance in the job design. Other scholars such as Clarke and Keating [ 9 ] have argued that the working environment of an educational institution affects teachers’ motivation. Clarke and Keating [ 9 ] found students to be the main reason why teachers are motivated in schools. His emphasis was on talented and hardworking students who boost the morale of teachers. Students who do not produce the desired results, on the other hand, de-motivate teachers. Moreover, class size is another important consideration in motivating teachers. Other variants of the job design and environment are captured in Ofoegbu [ 39 ] research in which he argued that institutions provide support in the form of resources to the teachers in the form of computers with Internet connections. Moreover, other factors such as the provision of e-libraries and research equipment, and other logistics for students may also serve as an effective motivator for teachers.

Performance management system

Management of teachers and educational administrators in all levels of education should focus on implementing basic performance management systems to continually appraise teachers’ accomplishments. For instance, the use of a so-called 360-degree feedback system is important where students’ feedback is attended to with the attention it deserves.

Stafyarakis [ 53 ] corroborated this and asserted that ‘Annual Confidential Reports’ have become obsolete. Yet there has been an emergence of a scientific approach on the field of performance management as time goes on. In discussing this further, Milliman [ 37 ] is of the view that although there are many practices available in this field, but a performance management system based on 360-degree feedback approach is the most effective.

Contrary to the norm that teachers are most motivated by the intrinsic factors and least motivated by the monetary aspects of teaching, Rao [ 43 ] demonstrates that poor appraisal systems, lack of recognition and lack of respect from the head and other co-workers are some common reasons of distress and de-motivation among teachers in educational institutions. The lack of recognition from supervisors is one of the many reasons why teachers would want to leave the teaching profession Stafyarakis [ 53 ].

Moreover, Rasheed et al. [ 45 ] points out that teachers are much concerned about students’ feedback; hence, feedback from the students should be given a proper weightage and in appraising and managing teachers’ performance in the institutions of higher education. Jordan [ 23 ] stressed that the feedback of students is a major issue of that motivates teachers and therefore teachers should be given feedback from their students in scientific manners.

Training and development

It is of significance that educational administrators focus on training activities as an essential means of both motivating employees and sustaining the survival of that organization according to Photanan [ 42 ] and Bohlander et al. [ 6 ]. Leslie [ 28 ] identified professional growth as basic motivator for teachers. He stressed that the professional learning platform available to a teacher is the basic path of his/her career development [ 29 ].

Conceptual framework and hypothesis development

In this section, the study harmonizes the components of the SDT theory into a conceptual framework on motivation and performance connection. The framework developed in this research may be useful as a guide by academicians and practitioners in understanding the mechanisms through which motivational factors affect job performance among teachers in the Effutu Municipality of Ghana. On elucidating on what a framework is, Chinn and Kramer [ 8 ] explained that a framework can be seen as a complex mental formulation of experience. Further clarification was given to distinguish conceptual framework from a theoretical framework. They assert that while theoretical framework is the theory on which the study is based, the conceptual framework deals with the operationalization of the theory. Put in another way, it represents the position of the researcher on the problem at hand and at the same time gives direction to the study. It may be entirely new, or an adoption of, or adaptation of, a model used in previous research with modification to fit the context of the inquiry [ 8 ].

The framework developed in this research has three components: the first component looks at the factors necessary to induce motivation among teachers. The second component focuses on motivation as a concept. The last component which is on job performance looks at the link between the aggregate motivational factors and performance. The extant literature survey on motivational factors and performance provides all the necessary ingredients for the construction of the framework. First, the extant literature shows that motivation as a concept is simply the act of moving people triggered by the provision of some incentives to achieve a desired goal. The triggers of motivation may include such factors such as compensation packages, job design and working environment, performance management system and training and development which are controlled and autonomous factors as crucial elements for motivation.

The second component of the framework is the aggregate motivation, which is the interaction of the controlled and autonomous factors of motivation. Motivation according to Reeve (2001) refers to the excitement level, the determination and the way a person works hard at his work setting. Ricks et al. [ 47 ] explicating on the thesis of motivation was of the view that motivation is an internal aspiration of a man that compels him to reach an objective or the goal set for him.

The third component of the framework is performance. According to Culture IQ [ 11 ] and Motowildo et al. [ 38 ], job performance is the assessment of whether an employee has done their job well. It is an individual evaluation (one measured based on a single person’s effort). In the words of Viswesvaran and Ones [ 58 ], p. 216, the term job performance is used in reference to actions that are scalable, behavior and outcomes that employees engage in or bring about that are linked with and contribute to the goals of an organization. It is linked to both employee- and organizational-level outcomes. A distinctive feature of the framework developed in this research is that it shows the interaction between autonomous and controlled factors and motivation and how it affects the performance of teachers in Fig.  1 .

Source : Created by the authors

A Conceptual model of the relationship between Motivation and Teachers’ Performance.

It can be visibly seen from the framework that teachers motivation may be defined by both controlled and intrinsic motivational factors that may include those that fall under compensation packages, working environment, performance management system and training and development of teachers [ 44 ]. Yet the performance of teachers in itself motivates management and policy makers to institute compensation packages, improved psychological aura through enhanced working environment and job design and implementing appropriate performance management policy for a continued performance enhancement. It should also be emphasized here that these job satisfaction factors may pass as job motivational factors and theorize that a highly motivated teacher may be related to the level of satisfaction.

Scholars such as Thus Milda et al. [ 36 ] and Spector [ 52 ] collectively share the opinion that teachers differ from typical employees in various ways. Therefore, instruments that usually measure such job satisfaction and motivation dimensions as appreciation, communication, coworkers, fringe benefits, job conditions, nature of work, organization itself, organizations’ policies and procedures, pay, personal growth, promotion opportunities, recognition, security, supervision may not always match with teachers’ motivation aspects on the teaching field. However, some of these factors according to some researchers can be used in understanding motivation and performance among teachers. The consensus on these dimensions is especially on supervision, work itself, promotion and recognition being important dimensions of teachers’ motivation at work [ 50 , 51 , 56 ]. In addition, several researchers have used the same measurement or dimension but with different wording (synonym). For instance, Kreitner and Kinici [ 26 ] define job satisfaction with the synonym “motivation” which they argue contains “those psychological processes that cause the arousal, direction and persistence of voluntary actions that are goal directed” Motivation depends on certain intrinsic, as well as extrinsic factors which in collaboration results in fully committed employees. Based on this relationship, we hypothesize that:

Hypothesis 1

Teachers’ compensation package, job environment and design, performance management systems, training and development significantly affect teachers’ motivation.

In a similar manner, Board [ 5 ] asserted that tangible incentives are effective in increasing performance for task not done before, to encourage “thinking smarter” and to support both quality and quantity to achieve goals. Incentives, rewards and recognitions are the prime factors that impact on employee motivation. Aarabi et al. [ 1 ] confirmed this assertion by making use of factors such as payment, job security, promotion, freedom, friendly environment, and training and employee job performance to measure the term organizational motivation with positive relationship found on these factors. On rewards (which comes in various forms, e.g., income/pay, bonus, fringe benefits among others ) and recognition/appreciation, according to other researchers keep high spirit among employees which boost employee’s morale which may have a direct impact on performance and output. The study hypothesizes that:

Hypothesis 2

Teacher’s motivation positively affects their performance.

The aim, design and setting of the study

The paper aims to examine the link between motivation factors and performance among basic school teachers in Ghana. Data for this study were collected from primary. Primary data were sourced from the field of study through questionnaire administration. The researchers sought for permission from the municipal directorate of education to engage with teachers within the municipality. A written permission was granted, and questionnaires were administered to all basic schools’ teachers in the municipality.

At the preparatory stage, the questionnaires designed were tested to make sure participants understood the demands of the questions in the questionnaires. Informal interviews method has been adopted to make sure that additional information that could not have been gathered through the use of questionnaires was captured. The formal interviews using questionnaires ensured that we stayed focused on the background objective that formed the basis of the study.

Sampling technique and data analysis

On the determination of the sample size, different authors have differing views, but in most cases, the recommendation is that it should be large. Stevens [ 54 ] recommends at least 15 participants per predictor for reliable equation in the case of factor analysis. Tabachnick and Fidel [ 55 ] provides a formula for calculating sample size requirements, taking into consideration the number of independent variables that one wish to use: N  > 50 + 8  m (where m  = number of independent variables). In line with these and other requirements like Yamane [ 60 ], the exact sample size will be determined and questionnaires distributed accordingly to the selected public and private schools in the Effutu Municipality.

The human resource unit of the educational directorate of education in the municipality has indicated that there are over 678 teachers teaching at various levels in the municipality [ 15 ]. Thus, the 678 teachers become the population in the municipality. Using Yamane [ 60 ] and validating with other sampling size technique, a sample size of 254 has been adopted with a 0.5 level of precision. Thus, 254 questionnaires were distributed among the various schools, but 159 were filled and returned (representing 62.6% return rate).

Quantitative data are analyzed by means of a software called Statistical Package for Social Sciences (SPSS version 20). This is necessitated by the fact that the analyzed quantitative data ought to be presented by graphs to give quick visual impression of what it entails.

The scale measurement of the questionnaires included nominal scale, ordinal and intervals. Questionnaires used were segmented to capture the demographic characteristics of the respondents and the constructs that feeds into the multi-level latent variables using a five-point Likert scale (see [ 19 , 24 ]). A verification was done to assess the suitability of the data for factor analysis with the expectation that Kaiser–Meyer–Olkin Measure of Sampling Adequacy ( \({\mathrm{i.e}}., {\rm KMo}\ge 0.6)\) and Bartlett’s Test of Sphericity value are significant ( p  = 0.05), which was the case for our sample data. In measuring some of the latent variables, the study developed a 9-scale item on compensation package with the following loadings (e.g., how high is your qualification and pay ( \(\alpha =0.72)\) , “is your experience linked to your current pay?” ( \(\alpha =0.80)\) , “are you satisfied with the market premium” ( \(\alpha =0.75)\) etc.). All items were rated on a five-point Likert scale ranging from 1 = “not important” to 5 = “very important.” A confirmatory factor analysis (CFA) indicates that the hypothesized correlated 3-factor structure fits well with the responds of the participants ( \({\chi }^{2}/df = 2.01, {\rm RMR}=0.05,{\rm RMSEA}=0.06,{\rm TLC}=0.94,{\rm CFI}=0.94)\) .

Job design and working environment was measured by a 7-item scale based on questions such as “how do you perceive your workload” ( \(\alpha =0.88)\) , “does your work type offer learning environment?” ( \(\alpha =0.83),\) “Are you inspired by your working environment?” ( \(\alpha =0.87)\) , “Talented student boost morale” ( \(\alpha =0.84)\) etc. Similarly, all items were rated on a five-point Likert scale ranging from 1 = “not important” to 5 = “very important.” A confirmatory factor analysis reveals that the hypothesized one-factor structure fits well with the data ( \({\chi }^{2}/df = 3.06, {\rm RMR}=0.05,{\rm RMSEA}=0.06,{\rm TLC}=0.94,{\rm CFI}=0.94)\) .

Performance management system was assessed using a 9-item scale based on these inferences (e.g., “number of times supervisor visits” ( \(\alpha =0.69)\) , “how often are you visited by the municipal director of education” ( \(\alpha =0.78)\) , “work recognition” ( \(\alpha =0.72)\) , etc.). All constructs were rated as 1 = “not important” to 5 = “very important.” A confirmatory factor analysis reveals that the hypothesized two-factor structure was in line with the data ( \({\chi }^{2}/df=2.86, {\rm RMR}=0.05,{\rm RMSEA}=0.06,{\rm TLC}=0.94,{\rm CFI}=0.94)\) .

The last but not the least concept explored was job performance. It was assessed on a 12-item scale based on the inferences such as (e.g., “are pupils treated with respect?” ( \(\alpha\) =0.77), “do you help pupils work on their social-emotional skills?” ( \(\alpha\) = 0.69), “are you fair and consistent with pupils” ( \(\alpha\) = 0.87), etc.). All items were rated on a five-point Likert scale ranging from 1 = “not important” to 5 = “very important.” A confirmatory factor analysis reveals that the hypothesized two-factor structure was in line with the data ( \({\chi }^{2}/df = 2.06, {\rm RMR} = 0.05,{\rm RMSEA} = 0.06,{\rm TLC} = 0.94,{\rm CFI} = 0.93)\) . The study proceeds to make use of the proposed measurement models to assess the relationship outlined in the conceptual model in Fig.  1 .

Hypothesized theoretical equation

Based on the conceptual model in Fig.  1 , the study makes a number of hypothesis on the relation between motivational factors and motivation itself and subsequently the link between motivation and performance. Consequently, the study model leads to two structural equations as presented below:

where JM = job motivation, CP = compensation package, JDWE = job design and working environment, PMS = performance management system, TD = training and development, JP = job performance.

Results and discussion

The study begins with a frequency distribution and descriptive statistics to capture the responses of teachers regarding the itemized construct identified in the conceptual model. Beginning with these two is borne out of the fact that the data category used in the study included categorical, ordinal and nominal variables which may be difficult to have a summary descriptive statistic.

With the understanding that every statistical approach is guided by certain principles or in most cases what has come to be known as assumptions, a diagnostic check was undertaken. Multicollinearity and singularity, for instance, look at the relationship among the independent variables. Thus, multicollinearity exists when the independent variables are highly correlated (r = 0.5 and above). The study was particular about these assumptions because multiple regression abhors them (singularity and multicollinearity). Issues concerning outliers (i.e., very high and low scores) was dealt with given the fact that multiple regression is sensitive to them. On normality, the results of the Kolmogorov–Smirnov statics were used to assess the distribution of scores. The test result was insignificant (i.e., sig. value of more than 0.05), which pointed to normality. Having done these, the study was sure there were no errors in the data and that the descriptive phase of the data used can begin.

Consistent with the general distribution of gender in the demographic characteristics of Ghana, about 63 of the teachers were female (39.6%) with 59.1% made up of male and 1.3% being transgender. The transgender teachers were foreign teachers who were here on an exchange program. Most of the teachers in the sample taught at the primary level (46.5%), followed by junior high level (43.4%) and kindergarten (8.8%), respectively. About 34.6% of the respondent responded they have taught between 6 and 10 years and 22.0% had spent between 11 and 20 years teaching. In terms of educational background, about 50.3% of the respondent have had first degree, with the remaining 49.7% being holders of teachers Cert. A or Diploma from the training colleges, and master’s degree of the returned samples. The average number of years participants have taught was observed to be 2.34 years with a corresponding standard deviation of 1.010. We present the demographic characteristics of our participants in Table 1 .

As shown in Table 2 , the compensation package scale has good internal consistency, with a Cronbach alpha coefficient reported to be around 0.725. According to Pallant [ 40 ], Cronbach alpha values above 0.7 are considered acceptable; however, values above 0.8 are preferable. Therefore, the threshold value of 0.725 means our scale is internally consistent and acceptable. Similarly, the job design and working environment scale recorded a Cronbach alpha coefficient of 0.793.

Performance management on the other hand had a Cronbach alpha coefficient of 0.70, yet training and development recorded a lower Cronbach alpha of 0.53, which meant it lacked internal consistency. The study had to drop training and development as factor for job motivation and proceed with the others. Job performance, however conspicuously recorded a Cronbach alpha of 0.83. In terms of the output from the correlation matrix, it can be visibly seen that the scales computed were not highly correlated and fallen below the threshold of 0.8 as recommended (see [ 40 ], p. 56). Both the assumption of singularity and multicollinearity by extension have not been violated (see Durbin Watson results) and thus the study can proceed to run the regression as per the set objectives and the conceptual model.

We go further to examine the causal effect of the factors identified as triggers of motivation on teachers’ level of motivation using ordinary least square method with multiple regression as the exact approach. Having gained credence from the test of reliability and validity, examining the causal effect becomes imperative. Using the baseline model in Eq. ( 1 ), the study concurrently runs the regression with the output shown in Tables 2 , 3 and 4 .

In model one, the study regresses compensation package with the dependent variable without controlling for other related factors. By implication what the results in model (1) seeks to explain is that, as the value of compensation package for teachers increases by 73 percentage points in the municipality, the mean of job motivation increases by that same margin. The high compensation is evidenced by government of Ghana reform in salary structure and bolstered by the effort of the Member of Parliament (MP) through the sharing of teaching and learning materials (TLMs) in the municipality. By this gesture by the MP, teachers feel appreciated and derive high motivation. Moreover, the presence of a university (University of Education, Winneba) has helped to deepen the level of motivation. The model has cross-variable variance of 52 percentage and with close to about 48 percentage unexplained as inferred from the coefficients of both coefficient of determination ( R 2 ) and adjusted coefficient of determination. Generally, the model is jointly significant ( F  = 170, p  < 0.01) with a corresponding tolerance and variable inflationary factor (VIF) of 1.

In model (2), the study varies the variables used with the inclusion of job design and working environment to examine how well the model can be through it cross-variable variance. Controlling for job design and environment shows a significant drop in the coefficient of compensation package from 0.73 to 0.53 although highly significant. Job design and environment recorded a coefficient of 0.49 which meant this indicator increases teachers’ satisfaction and thus motivation by 49 percentage points. In explaining this phenomenon, one would say that jobs that are rich in positive behavioral essentials such as autonomy, task significance and identity and feedback contribute to employees’ motivation. Government has since the introduction of its flagship program on free senior high education emphasized the significance of education across all the strata. The autonomy of heads of unit was by this directive curtailed. Heads of unit were barred from initiating policies to ease their operations. This finding is supported in the literature [ 7 , 30 , 46 ] and is aligned with the SDT. For example, head teachers who had levied pupils with printing fees were sanctioned for such initiative. Thus, by this gesture, the autonomy of the profession was in doubt and this explains why the level of motivation when this parameter is mentioned is low. With this addition, model (2) marginally sees an improvement of 0.73 in the cross-variable variance which is a significant. Model (2) was jointly significant ( F  = 170, p  < 0.01).

All the identified job motivation variables are concurrently used in model (3) to infer whether there was going to be a significant increase in the coefficient of determination and a drop in the residue. As a confirmation to the priori assumption, there was a marginal improvement of the explanatory strength of the model (R 2  = 0.88). However, the model witnessed significant drop in the coefficients. Thus, compensation package dropped further from 0.53 to 0.42 and job design and environment from 0.49 to 0.34.

It is important to note that the value of Durbin Watson test results when all the identified factors are brought together in model (3) indicate a no autocorrelation in the model which validates the earlier point of having dealt with critical assumptions that borders on autocorrelation. Moreover, both our VIF and tolerance were within the acceptable level. For instance, models (1)–(3) had a VIF score less than or equal to 1, which meant there were no issues concerning a possibility of high multicollinearity. For tolerance, there are no clear-cut cut-off point, but there is a suggestion of a tolerance greater than 0.40 according to Allison [ 3 ]. Yet Weisburd and Britt [ 59 ] are of the view that anything below 0.2 is an indication of serious multicollinearity. Inferring from these, it therefore goes to suggest that the tolerance levels of above 1 meant no multicollinearity.

In examining the relationship between the aggregated motivational factors and performance, the study brings to the fore the following findings as shown in Table 3 . The study presents four (4) different models on the relationship between motivation and performance. Model (1) regresses the aggregate motivational factors on job performance, and the findings are quite interesting to note. The job performance indicator is increased by 46% for every unit increase in motivation. This relationship can further be explained to mean a teacher within the municipality with a sense of satisfaction with his/her teaching job may feel more inclined to be at post no matter what the prevailing circumstances are. The snowball effect of this phenomenon is the reduction in absenteeism with a corresponding curb on teachers’ turnover. Although the coefficient of determination which explains the cross-variable variance is by far lower than expected ( R 2  = 0.214), the model is jointly significant ( F  = 41.44, p  < 0.01). The VIF and tolerance levels are within acceptable threshold with a Durbin Watson of 2.04 that signals a no concern of autocorrelation in the model.

Models (2)–(4) regress the decomposed job motivation factors on performance to ascertain their level of significance, and indeed, as theorized, these factors were positively significant except with lower coefficient of determinations ( R 2 ). To explain the relation in model (2), it is important to note that compensation is the output and the benefit that a teacher within the municipality receives in the form of pay, or even any form of exchanges (in kind or in cash) to increase performance. The Member of Parliament for the area as part of effort to ensure teachers are well compensated shared over 700 laptops to teachers within the municipality for effective teaching and learning. This certainly explains why the attrition rate in the municipality is low vis-à-vis high morale of teachers which largely explains the level of motivation and satisfaction.

Model (3) touches on the psychological state the teacher finds him or herself owed to the nature and state of the job. This may include the job environment and the degree of specialization. Yet in model (4), there is an exponential increase in the coefficient of performance management systems as it increases job performance within the municipality by 51 percentage point. It should be noted that performance management sets expectations for teachers’ performance and thus motivates them to work harder in ways expected by the municipal directorate of education under GES. The results in model (5) confirm earlier ones, but the inclusion of the other variables as control seems to have increased the coefficients of the various motivational factors. This partly explains the performance of the municipality in the central region in successive BECE.

Further investigation is made to understand which of the age groups is responsible for the ensuing level of performance in the municipality. To do this, the study relies on one-way analysis of variance (ANOVA). Here, the mean scores of more than two groups are compared using a continuous variable as the dependent variable. Having transformed the ordinal variables to continuous, it makes it quite straightforward to do this. Using the categorical independent variable of age which has more than three categories and the job performance variable which we have transformed to be continuous variable, the study undertakes a one-way between groups ANOVA with post hoc tests. Teachers were divided into four groups according to their ages (group 1: 20–30 yrs.; group 2: 31–40 yrs.; group 3: 41–50 yrs.; group 4: above 51 yrs.). There was a statistically significant difference at the \(p<0.10\) level in job performance scores for the four age groups: F (4, 159) = 0.042, p  = 0.10. Despite reaching statistical significance for one of the groups, the actual difference in mean scores between the groups was quite small. The effect size was calculated using eta squared (eta squared = 179.1/8513 = 0.02) which in Cohen’s ([ 10 ], pp. 248–7) terms is considered far too small a size. Note should be taking that Cohen categorizes 0.01 as a small effect, 0.06 as a medium effect and 0.14 as a large effect. Post hoc comparisons using the Tukey HSD test indicated that the mean score for group 1 (56.12, SD = 4.26) is significantly different from the other three groups which were insignificant. The result has theoretical soundness. Group 1 was made up of young teachers who had either returned from training colleges after completion or on internship and thus had cause to perform for a possibility of being retained or given a very good report since internship supervision forms part of the trainees’ assessment.

In this study, we examined among a host of autonomous and controlled motivational factors and their relationship to performance among basic schools’ teachers in the Effutu Municipality of Ghana. A conceptual model was developed with the necessary hypotheses formulated. Using multiple regression and one-way analysis of variance (ANOVA), the causal effect as shown in the model is tested.

The study finds compensation package, job design and environment and performance management system to be positively significant factors in explaining teacher’s motivation in the municipality. These job motivation factors were significant predictors on job performance. The aggregated job motivation indicator when regressed on job performance reveals a positive and significant effect. Based on the results from the ANOVA, the study recommends the municipal directorate of education to make more room for young teacher trainees who are at the formative stage of their career to be engaged to augment the experienced staff strength. More should be done to make the profession attain some level of autonomy in the discharge of duty to breed the next genre of innovative educators in the municipality. A limitation of the study is its inability to treat job motivation as a mediatory variable as captured in the framework. The study recommends future research to explore this connection.

Availability of data and material

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Abbreviations

Analysis of variance

Self-determination theory

Single spine salary structure

Fair wages salary commission

Teaching and learning materials

Member of parliament

Job motivation

Job performance

Kaiser–Meyer–Olkin

Confirmatory factor analysis

Standardized root mean square residual

Root mean square error of approximation

Statistical package for social science

Variable inflationary factor

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Acknowledgements

The authors would like to acknowledge the support of the Effutu Directorate of Education, particularly the Municipal Director of Education for the support during the data collection stage. We thank all the basic school teachers in the municipality who devoted time to fill and return questionnaires sent to them. We are also grateful to the Directorate for the secondary materials given to the team.

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JAF contributed 50%, EOD contributed 25%, RAO contributed 20%, and SEA contributed 5%, respectively. All authors have read and approved the manuscript.

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Forson, J.A., Ofosu-Dwamena, E., Opoku, R.A. et al. Employee motivation and job performance: a study of basic school teachers in Ghana. Futur Bus J 7 , 30 (2021). https://doi.org/10.1186/s43093-021-00077-6

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Effects of Motivational and Behavioral Factors on Job Productivity: An Empirical Investigation from Academic Librarians in Pakistan

Khurram shahzad.

1 Department of Library, Senior Librarian, Government College University Lahore, Lahore 54000, Pakistan

Shakeel Ahmad Khan

2 Department of Information Management, Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan

3 Central Library, Prince Sultan University, Riyadh 11586, Saudi Arabia

Omer Shabbir

4 Human Resource Department, Prince Sultan University, Riyadh 11586, Saudi Arabia

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The authors confirm that the data supporting the findings of this study are available within the article.

The major objective of the current study was to find out the impact of motivational factors on the job outcomes of librarians working in HEC-recognized university libraries in Pakistan. A survey research method followed by predictive correlational design was applied to test the constructed hypotheses in this study. The population of the study was library professionals working in the university libraries of Lahore, Pakistan. There were 13 public sector universities and 21 private sector universities. The census sampling technique was used to collect data from the respondents of the 34 universities. Data were collected with the help of a questionnaire. Out of 225 respondents, 189 completed questionnaires were received. Hence, the response rate was 84%. The gathered data were analyzed through SPSS software. Descriptive and inferential statistical tests were applied to find out the impact of motivational and behavioral factors on the job outcomes of information professionals. The findings of the study showed that different types of motivation influenced information professionals to carry out innovative and value-added services in the workplace. Rewards, a sense of honor, an amicable work environment, and autonomy were the key categories of motivation that encouraged information professionals to undertake efficient job performance. Recommendations provided through a framework based on the findings of the study will prove to be a benchmark for policymakers, human resource managers, and heads of institutions in order to formulate such techniques that might motivate information professionals for the implementation of user-centric services.

1. Introduction

Motivation is known as the reason for the initiation of a behavior that stimulates the meeting of organizational objectives [ 1 ]. It involves an employee working to achieve organizational goals as a result of their initiative [ 2 ]. It is a revolutionary drive that urges a professional working in an academic setting to produce satisfactory results and productive performance [ 3 ].

The theory of motivation involves the attitude of individuals that is shaped in response to extrinsic and intrinsic factors. Intrinsic motivation takes place due to the personal interest of an individual towards a task [ 4 ], whereas extrinsic motivation occurs as the result of a response to an external reward [ 5 ]. Extrinsic motivation is significant in terms of increasing job performance [ 6 ] and producing outcomes [ 7 ].

The autonomy of library professionals in the workplace has a strong relationship with effective job performance. Different motivational factors including good remuneration, sufficient resources, the implementation of emerging tools, recreational opportunities, and pleasant mutual relations in the workplace provide job satisfaction to university library professionals [ 8 ]. Innovative changes have taken place in libraries due to the revolution in information technology, and university library professionals in present times are expected to initiate value-added services to provide the community with the latest methods, and this mission may be accomplished if library workforces are motivated. The workplace of academic librarians boosts their morale and motivates them towards adopting a dynamic approach to the provision of user services [ 9 ].

Job satisfaction is the most crucial element for executing the functions of an organization effectively and efficiently [ 10 , 11 , 12 , 13 , 14 ]. For the attainment of job performance from the academic library workforce, employees’ needs should be satisfied and they should be motivated to work collectively for the accomplishment of the common goals of the institutions [ 15 ]. Several factors, including a reasonable salary, a pleasant work environment, appreciation from employers for completed tasks, promotions, the consistent provision of incentives, empowerment, authority, and amicable relations among colleagues, play a fruitful role in enhancing the work output and the satisfaction level of academic library employees [ 16 ].

A university library is a microcosm of the university; therefore, internally motivated staff need to be recruited so that the organization can achieve its objectives [ 17 ]. Both intrinsic and extrinsic factors drive academic library staff to provide the best results in all tasks that are assigned by the top management of the universities [ 18 ]. Transformational leadership in academic libraries proves to be highly significant in improving the motivational level of library professionals, which contributes to positive job performance [ 19 ].

2. Statement of the Problem

The library profession is very challenging and continuously evolving. It demands the timely motivation of library professionals to achieve organizational objectives. This study intends to measure the impact of motivational factors on the job performance of academic library professionals in Pakistan. With advancements in technological tools, library services are changing rapidly. Therefore, library professionals may not satisfy the information and research needs of their users unless they are motivated through different incentives and rewards. User-centric services may be provided if the library staff is internally motivated and satisfied with their work conditions. For the attainment of exceptional job performance, staff motivation is of great significance. Innovative library services may not be provided to the end-users without motivated and skilled library staff.

3. Literature Review

3.1. motivation.

The term “motivation” originated from the Latin word “movere”. It means to go ahead or to meet a specific need [ 20 ]. It is related to the ability that causes dynamic changes in an individual’s attitude [ 21 ]. It relates to the efforts of an individual to show a willingness to work towards a task as a result of specific incentives provided to them [ 22 ]. It is also known as inspiration, which is provided to an individual by an organization for the delivery of efficient results.

Motivation is willpower that motivates library professionals to develop high goals for growing personally and professionally [ 23 ]. Motivation aims to influence the library workforce through certain incentives for carrying out job functions enthusiastically. Motivated employees are more likely to play a leading role in the attainment of organizational goals [ 24 ]. Motivated library staff working in academic libraries may produce better results and work output through value-added services [ 25 ].

3.2. Employee Motivation in the Academic Setting

Motivational factors have a powerful influence on employees’ minds as they better understand their role in the organization. They work with high spirits for bringing innovation during different operations at the workplace [ 26 ]. Internally and externally motivated employees continuously enhance their professional skills and align their personal goals with organizational goals to show maximum efficiency [ 27 ]. Employees’ needs, psychological traits, and expectations should be considered carefully by employers for receiving the best output and work results [ 28 ]. The performance of employees usually depends upon motivation and satisfaction with their job [ 29 ].

Empowerment is a great source of motivation that provides authority to employees for working independently and performing efficiently [ 30 ]. Good working conditions have a direct impact on employees’ motivation towards their job as a positive spirit of teamwork is created [ 31 , 32 ]. The level of commitment is increased if the staff are well motivated [ 33 ].

3.3. Job Satisfaction in Academic Libraries

Job satisfaction refers to employees’ expectations for benefits from the job [ 34 ]. A positive mental state as a result of a pleasant work experience is known as job satisfaction [ 35 ]. Job satisfaction provides a sense of security and protection to the workforce of an organization [ 36 , 37 , 38 ].

Independence and authority to make decisions in performing different tasks related to the job give joy and satisfaction to the employees [ 39 ]. Security, the nature of the job, and amicable work conditions provide satisfaction and happiness to the workers [ 40 , 41 ]. Job satisfaction has a positive impact on the working attitudes of the employees [ 42 ]. A lack of satisfactory salary packages is a great hindrance to the job satisfaction of the employees [ 21 ].

The life satisfaction of library professionals also depends upon job satisfaction. A good job provides satisfactory living conditions [ 43 ]. Efficient leadership in academic libraries provides job satisfaction to the library workforce [ 44 ]. Effective human resource management (HRM) is a great tool in the provision of job satisfaction to library employees [ 45 ].

3.4. Job Performance of the Library Workforce

Job performance is related to work output which plays an essential role in the uplift of organizations [ 46 ]. It shows that workforces successfully complete assigned goals through modern-driven approaches [ 47 ].

Job security affects librarians’ performance a great deal in academic libraries so it has a significant relationship with job performance [ 48 ]. The facilities of university libraries are a great source for increasing the work performance of librarians [ 49 ]. Different human resource management styles affect the job performance of the library workforce. Therefore, the role of the management should be considered carefully for producing productive result outcomes for the academic library staff [ 50 ]. For the efficient functioning of academic libraries, the creative output of library professionals is of paramount significance [ 51 , 52 ].

3.5. Motivational Factors to Enhance Work Output and Satisfaction Level of Academic Librarians

State-of-the-art facilities provided to library staff in the universities enhance their satisfaction and job performance [ 9 ]. Motivation occurs in academic library staff through the provision of regular incentives from the policymakers of the institutions because such incentives and honorariums boost their morale [ 14 ].

The provision of adequate facilities during the job improves staff performance in university libraries [ 53 , 54 ]. The satisfaction of different needs of academic library staff including basic needs, physiological needs, esteem needs, and psychological needs is beneficial in improving performance [ 54 ]. Field trips, recreational activities, the availability of required tools, and balanced work hours create positive passion among library staff [ 55 ]. Service benefits need to be provided to the library staff so that they may carry out additional services for the prosperity of the universities [ 56 ].

The implementation of IT in university libraries is a constant factor of motivation for librarians to enhance job performance [ 55 ]. This revolution in the field of librarianship is a significant driver in motivating university library professionals to initiate user-centric services by adopting the latest technological tools [ 57 , 58 ].

Factors of self-interest, positive attitude towards the job, and passion to learn and improve are fruitful tools to enhance work performance [ 59 ]. Willpower and self-determination prove dynamic factors in motivating library staff [ 60 ]. The passion for self-development to lead in the field brings productive results for the universities [ 55 ].

The good attitude of the seniors, the fair distribution of rewards, the passion for team spirit, and comfortable job conditions are motivational factors to improve the job performance of the academic librarians of the universities [ 33 , 58 ]. Appreciation from the employers to the university library staff stimulates them to work dedicatedly to enhance productivity [ 31 ]. For organizational effectiveness; the economic and social conditions of the academic library staff should be improved [ 61 , 62 ].

3.6. Impact of Motivation on the Job Performance of Librarians

Babalola and Nwalo [ 63 ] noted that motivation develops the work output of the workforce. Gobari et al. [ 64 ] assumed that motivation is the most effective tool that inspires workers to perform well in return for awards, incentives, appreciation, and honors. Cherry [ 65 ] argued that motivation has a positive impact on job performance and it brings fruitful results to organizations. Nnaeto and Ndoh [ 66 ] mentioned that optimal efficiency in organizations may be achieved if the workforce is empowered and motivated through different methods. Otagburuagu [ 67 ] reported that rewards and recognitions inspired library staff to work for the institutions with a dedicated attitude. Kaluarachchi and Gamlath [ 68 ] found that enhanced motivation produced effective results for the organization.

Pawirosumarto et al. [ 69 ] mentioned that the dedicated attitude of the library had a positive impact on their job performance. The proliferation of information technologies had made library users digitally literate, so library professionals needed to implement the latest tools for the provision of smart library services. Kaba [ 70 ] claimed that personal autonomy positively affected the work productivity of university librarians. Khoreva and Wechtler [ 71 ] concluded that internal motivation guided library staff towards productive results in the organizations. Anasi [ 72 ] concluded through his study that there was a positive relationship between motivation and the fruitful job output of academic librarians. Performance was measured in terms of the implementation of emerging technologies in the libraries. Paais and Pattiruhu [ 73 ] investigated the effects of motivation on employees’ satisfaction and job performance. They concluded that organizational culture and work motivation were positively associated with job performance. They further highlighted that effective leadership played a fruitful role in increasing the satisfaction level of the employees with their jobs. Knezevic et al. [ 74 ] discussed the importance of human resources for attaining productive work performance. They showed that motivated and skilled employees were true assets as they played a vital role in uplifting their institutions. Campbell and Goulding [ 75 ] stated that intrinsically and extrinsically motivated library staff carry out creative performance in university libraries. Jovanovic et al. [ 76 ] revealed through an empirical investigation that the organizational environment had a great impact on the job satisfaction level of the employees. Therefore, a comfortable work atmosphere needed to be provided to attain optimum productivity.

3.7. Analysis of National Studies

Rigor studies focusing on the topic of the ‘impact of motivational factors upon job performance in university libraries’ have not been conducted. This area is still unexplored in the setting of Pakistan; however, very few related studies have been conducted on the topic. Bhatti and Qureshi [ 77 ] concluded in their study that library staff should be actively engaged in the decision-making process to develop motivation and a high level of satisfaction with the job. Zafar et al. [ 47 ] revealed through their research that job satisfaction was related to the inner happiness of the employees due to certain benefits provided to them by employers in return for excellent services at the workplace. According to them, job skills and work conditions play a great role in providing satisfaction to the library staff. In recent research conducted by Ahmad et al. [ 78 ], it was found that the satisfaction of the physiological needs of the library staff brought improvement in job outcomes and enhanced productivity and efficiency. Bashir et al. [ 79 ] surveyed the effects of motivation on job output in the telecommunication sector. They revealed that healthy work–life conditions provided motivation to the workforce, and they became dedicated towards the assigned duty. Comfortable work conditions and service benefits positively impacted staff efficiency. Job satisfaction played a positive role in increasing the work output of employees. Khurram and Khan [ 80 ] concluded through a systematic review study that motivation was a great force that changed the mindset of library staff and encouraged them to apply the latest technologies in their universities.

4. Research Hypotheses

Motivational factors have a significant positive impact on the job performance level of academic librarians.

Motivational factors have a significant impact on the job satisfaction level of librarians.

The expectation of benefits has a significant positive impact on the job outcomes of library professionals working in academic libraries.

The expectation of benefits has a significant positive impact on the satisfaction level of librarians working in academic libraries.

5. Theoretical Framework

This study is based upon two theories known as the motivation theory and the expectancy theory. Hypotheses of the study have been developed through different constructs of these two theories. Motivation theory is related to internal elements which include self-inspiration, personal interest, and external elements which consist of incentives, rewards, and recognition. Expectancy theory is related to expectancy (effort), instrumentality (performance), and valence (reward). Authors shaped the theoretical framework ( Figure 1 ) having used relevant constructs to test formulated hypotheses for finding out the impact of motivational factors on the job performance of academic librarians working in the university libraries of Lahore, Pakistan. The researchers used the variables of willpower, sense of honor, freedom, self-interest, and appreciation in the element of motivation. The variables of inner happiness, psychological ownership, professional learning opportunities, protection of rights, and institutional support were applied to the element of satisfaction, whereas in the element of performance, sub-categories consisting of satisfactory job output, efficient work outcomes, innovative work style, the implementation of emerging technologies, and increases in practical skills were used. The impact of independent variables on the dependent variables was measured through the application of inferential statistical tests.

Theoretical framework of the study.

6. Materials and Methods

A survey research method followed by predictive correlational design was applied to test the developed hypotheses in this study. Correlational research “is a research method that gives the researcher the opportunity to describe the relationship between two measured variables; whether two variables are correlated” [ 81 ]. This design facilitates researchers to make predictions from one variable to another [ 82 ].

The population of the study was university library professionals working in the university libraries of Lahore, Pakistan. There were 13 public sector universities and 21 private sector universities. The census sampling technique was used to collect data from the respondents. Library professionals with at least a Master’s degree were the participants of the study. Data were collected with the help of a questionnaire. The questionnaire was distributed among all library professionals working in these universities. The data of the working librarians were attained through professional directories and institutional websites.

The questionnaire was developed in light of a comprehensive literature analysis keeping in view the constructs of the already-developed hypotheses. A peer-review process was used to check the validity of the questionnaire. The tool was refined in light of feedback obtained by experts in the field. The reliability of the questionnaire was checked via a pilot testing process through the distribution of the questionnaire among 25 participants.

The questionnaire was distributed among 225 participants. Out of 225 respondents, 189 duly filled questionnaires were received. Hence, the response rate was 84%. The gathered data were analyzed through SPSS software. Descriptive tests of frequency, mean, standard deviation, and inferential statistical tests of regression were applied to find out the impact of motivation on the job outcomes of information professionals.

7. Data Analysis and Results

7.1. demographic information of the respondents.

The results of the study revealed that the majority of the participants (n = 147) were male and (n = 42) respondents were female ( Table 1 ).

Descriptive analysis of demographic information of respondents (N = 189).

The findings showed that most of the respondents (n = 67) were aged between 31–35. In total, 49 respondents belonged to the age group 26–30. A total of 39 respondents were in the age group 36–40, 22 respondents were above 40 years old, and 16 respondents were aged between 20–25 ( Table 1 ).

The majority of the respondents (n = 127) had an MLIS qualification. In total, 55 respondents had an M. Phil. degree in LIS, whereas only 7 respondents had earned the degree of Ph.D. ( Table 1 ).

The results indicated that the majority of the participants (n = 106) were working in public sector universities and 83 respondents were employed in private sector universities. The findings of the study showed that the majority of the respondents (n = 54) had professional job experience of 1–5 years. A total of 42 respondents had professional work experience of 11–15 years. In total, 77 respondents had professional experience of 6–10 years, 36 respondents had experience of between 16 to 20 years, and 20 respondents had above 20 years’ experience ( Table 1 ).

The results revealed that the majority of the respondents (n = 59) were librarians, 36 respondents were chief librarians, 31 respondents were senior librarians, 29 respondents were deputy librarians, 17 respondents were deputy chief librarians, and 17 were assistant librarians ( Table 1 ).

7.2. Descriptive Analysis of Different Statements Related to the Study’s Key Variables

The findings of the study displayed that different variables of motivation impacted upon job productivity and satisfaction levels positively. These motivational factors included willpower, a sense of honor, freedom, self-interest, and appreciation. These factors had a positive relationship with job productivity and satisfaction levels according to the respondents’ opinions. The opinions of the participants were measured using different statements related to motivation, satisfaction, and job performance through descriptive analysis in SPSS software. A five-point Likert scale was used to measure mean and standard deviation regarding different statements about the key variables of the study. Most of the respondents agreed that motivational factors enhanced their job productivity. Table 2 shows mean responses with standard deviation received for different statements related to motivation, satisfaction, and performance. The top three mean scores were received for the statements, “Sense of honor leads to psychological ownership” (M = 4.29); “freedom of the employees protects rights”; “motivational factors move towards satisfactory job output”; “motivation is valuable in increasing the practical skills of the library staff” (M = 4.13), and “self-interest encourages the workforce”; “motivational drivers lead towards efficient work outcomes”; “motivational elements stimulate workers to adopt an innovative work style” (M = 4.11).

Descriptive analysis of respondents’ opinions about different statements related to the study’s key variables (N = 189).

Note (s): Scale used: strongly agree = 5, agree = 4, no opinion = 3, disagree= 2, strongly disagree = 1.

The study revealed that most of the respondents agreed that different elements provided them satisfaction, and they became more dedicated to the delivery of efficient library services. The elements of satisfaction included inner happiness, psychological ownership, professional learning opportunities, protection of rights, and institutional support. The results of the study showed that innovative job performance was carried out as a result of motivation and satisfaction with the job.

7.3. Impact of Motivational Factors on the Job Performance of University Librarians

A linear regression test was applied through SPSS software to find out the impact of motivational factors (IV) on the job performance (DV) of library professionals carrying out services in the university libraries of Punjab, Pakistan. Table 3 shows the results of linear regression analysis for the impact of motivation on the job performance of university librarians. The strength of the relationship is reflected through R 2 , which is 0.263. The beta value of the independent variable is 0.513, which shows a significant impact of the independent variable (motivational factors) upon the dependent variable (job performance). The results show that the Sig. value is p < 0.01. Therefore, it can be concluded that motivation has a strong relationship with job performance in academic libraries. Hence, H1a is not rejected.

Impact of motivational factors on job performance.

a. Dependent variable: work output. b. R 2 = 0.263.

7.4. Impact of Motivational Factors on the Job Satisfaction Level of University Librarians

A linear regression test was applied through SPSS software to find out the impact of motivational factors (IV) on the job satisfaction level (DV) of library professionals carrying out services in the university libraries of Lahore, Pakistan. Table 4 shows the results of linear regression analysis for the impact of motivational factors on the job satisfaction level of university librarians. The strength of the relationship is reflected through R 2 , which is 0.261. The beta value of the independent variable is 0.515, which shows a significant impact of the independent variable (motivational factors) upon the dependent variable (job satisfaction level). The results reveal that the Sig. value is p < 0.02. Therefore, it can be concluded that motivational factors have a strong relationship with the job satisfaction level of academic libraries. Hence, H1b is not rejected.

Impact of motivational factors on job satisfaction level.

a. Dependent variable: work output. b. R 2 = 0.261.

7.5. Impact of Expectation of Benefits on Work Performance of Academic Librarians of Pakistan

Through Statistical Package for Social Science software (Version 26.0), a linear regression statistical test was utilized to investigate the impact of expectation of benefits motivation (IV) upon the work performance (DV) of professional library staff working in the university libraries of Pakistan. Table 5 shows results for the impact of the expectation of benefits on the work outcome of university library professionals. The strength of the impact is shown through R 2 , which is 0.265. The beta value of the regressor variable is 0.515, which shows a significant impact of the independent variable (expectation of benefits) upon the response variable (work output). The results show that the Sig. value is p < 0.01. Therefore, it can be declared that the expectation of benefits has a strong impact on the work output of university librarians. Hence, H2a is not rejected.

Impact of expectation of benefits on work output.

a. Dependent variable: work output. b. R 2 = 0.265.

7.6. Impact of Expectation of Benefits on the Job Satisfaction Level of Academic Librarians in Pakistan

SPSS software was utilized to apply a regression test to measure the impact of the expectation of benefits motivation (IV) on the job satisfaction level (DV) of professional library workforces in the universities. Table 6 presents the impact of the expectation of benefits on the job satisfaction level of university library professionals. R 2 is 0.196, which shows the strength of the impact. The beta value of the independent variable is 0.442, which shows a significant impact of the independent variable (expectation of benefits) upon the measured variable (job satisfaction level). The results display that the Sig. value is p < 0.01. Therefore, it can be inferred that expectation of benefits has a powerful impact on the job satisfaction level of university library professionals. Hence, H2b is accepted based on the retrieved results of the scientific evidence.

Impact of expectation of benefits on job satisfaction level.

a. Dependent variable: job satisfaction level. b. R 2 = 0.196.

8. Discussion

The findings of the study showed that motivation is a necessary predictor of innovative job outcomes and satisfaction with the job. Motivation is a necessary component for inspiring library workforces to provide user-centric services and to enhance their level of satisfaction with their duty. The results revealed that willpower, appreciation, self-interest, freedom, and a sense of honor have a significant positive impact on productive job output. Inner happiness, psychological ownership, professional learning opportunities, protection of rights, and institutional support provided satisfaction to the library staff, and they became more dedicated to compliance with their organizational tasks. The majority of the respondents agreed that satisfactory job output, the delivery of efficient work outcomes, the adoption of innovative workstyles, the implementation of emerging technologies, and increases in practical skills were highly essential in the present age. These results are similar to the findings of the studies investigated by Babalola and Nwalo; Gobari et al.; Nnaeto and Ndoh; Anasi; and Campbell and Goulding [ 63 , 64 , 66 , 72 , 75 ].

Library administration should meet the different needs of the staff members to meet organizational goals. It was indicated by Kaluarachchi and Gamlath; Pawirosumarto et al.; Kaba; and Khoreva and Wechtler [ 68 , 69 , 70 , 71 ] that motivated library staff carried out innovative job performance. Intrinsically and extrinsically demotivated library staff may not perform productive tasks enthusiastically. Different motivational factors have a significant positive effect on the job performance of academic librarians in universities. Library staff should be motivated well by the senior management of universities for the attainment of creative performance.

The results of the study have revealed that internally satisfied employees play a vital role in the uplift of institutions. Motivated and satisfied library staff members carry out services through modern-driven techniques and tools. They play a leading role in the organization and initiate customized services according to the changing needs of library users. Different motivational factors, including financial benefits, a positive workplace environment, comfortable work routines, job promotion opportunities, awards, special incentives, and transformative leadership boost the satisfaction level of librarians towards the job. Internally dissatisfied staff may not perform innovative services effectively and efficiently.

The findings of the study have shown that motivational and behavioral factors have a positive relationship with innovative job productivity. Willpower, appreciation, self-interest, freedom, and a sense of honor are important factors that motivate librarians to implement emerging technological tools in academic libraries. Motivation provides workforces to enhance their professional skill sets; therefore, skilled staff proves a great asset to their organizations. These results are consistent with the findings of the studies conducted by Paais and Pattiruhu [ 73 ]; Bashir et al. [ 79 ]; Knezevic et al. [ 74 ]; and Jovanovic et al. [ 76 ].

The study has used the human motivation theory of McClelland and Vroom’s expectancy theory for presenting a broader picture of the motivators affecting job productivity and the level of satisfaction of the library staff working in academic settings. Based on hypotheses tested through inferential statistical tests, the study has proposed a framework ( Figure 2 ) for increasing the motivational level of library staff towards their jobs. Motivation and satisfaction are significant drivers in initiating user-centric services in university libraries. Table 7 provides an overview of the results of the investigation.

Framework to enhance the motivational level of academic librarians for innovative performance.

Summary of hypotheses results.

The provided framework ( Figure 2 ) is very fruitful for policymakers, university administrations, head librarians, and other stakeholders as it has practical implications. Policymakers may use the given framework as a baseline to turn library staff into a motivated skilled workforce for the delivery of smart user services in academic institutions. Based on the findings of this study, a legal document may be developed by policymakers consisting of standardized protocols and policies, for enhancing the motivation and satisfaction level of librarians. Internal motivation may be imparted to librarians through continued professional development (CPD) opportunities. For external motivation, different incentives need to be offered. A documented policy duly approved by policymakers based upon core factors to motivate librarians to efficient job performance to uplift library services in institutions will provide a benchmark and guidelines for university administrators to take practical measures for creating motivation among library staff to enhance job satisfaction levels for innovative performance.

The investigation has shown that academic librarians should be motivated through different methods. Their needs should be satisfied. They should be empowered so that they might work with psychological ownership. The willpower of librarians should be increased through different training sessions. The workforce working in university libraries should be provided with appreciation, recognition, and rewards. The self-interest of librarians towards job tasks should be aroused. Library professionals should be provided autonomy to work independently with a sense of honor. Fruitful steps need to be taken to increase the inner happiness of library staff. The rights of the library workforce should be protected, and they should be provided institutional support in all circumstances. Motivation and satisfaction play a useful role in the provision of innovative job output, the delivery of efficient work outcomes, the adoption of exceptional workstyles, increases in practical expertise, and the implementation of emerging technologies. Educational institutions should take care of the different needs of their library employees so that they might implement value-added services to facilitate end-users effectively and efficiently.

9. Conclusions

Motivational factors have a significant positive impact on job performance and the satisfaction level of librarians. Different modes of motivation stimulate the human resource of the library to carry out productive services for the uplift of the parent organization. The expectation of benefits (time-scale promotions, best employee award, empowerment, comfortable job conditions, adequate salary package, state-of-the-art facilities, special incentives and honorariums, adequate counseling and coaching, job security, recreational activities, the availability of required tools, and service benefits) also plays a vital role in efficient work performance and increasing the job satisfaction level of library professionals performing services in universities. When workforces are provided benefits by organizers, productive outcomes are received, and the inner happiness of the employees also increases.

The study has contributed significant literature to the existing body of knowledge by testing the effects of motivational and behavioral factors on the job productivity of academic librarians in Pakistan through empirical investigation based upon a theoretical framework. Hypotheses were developed based on the constructs of two theories called the human motivation theory and expectancy theory of motivation. Based on the results of the tested hypotheses, it may be concluded that motivational factors have a positive impact on innovative job performance. Without motivated library staff, user-centric services may not be delivered in university libraries. The study has identified a positive relationship between motivational factors with job innovation among university librarians.

10. Implications of the Study

This research has theoretical implications for the researchers for further enhancing and modifying the theory of motivation. It also provides practical implications for policymakers and human resource managers to work on the motivation of their human resources for achieving efficient outcomes.

11. Limitations and Future Research

• This study has been conducted through a predictive correlational research design. The respondents were not interviewed using a qualitative approach.
• The current research provides numerical data obtained from only university librarians and not from college and school librarians.
• The present study includes the population only from Lahore, Pakistan. Other cities have not been included due to a shortage of time and financial resources.
• The study applied constructs from McClelland’s human motivation theory and Vroom’s expectancy theory.
• The study’s findings may not be generalized to other parts of the world keeping in view the population of only one city’s universities in this study.

Acknowledgments

The authors would like to acknowledge the support of Prince Sultan University for paying the Article Processing Charges (APC) of this publication.

Funding Statement

No funding was acquired for this research.

Author Contributions

Conceptualization, K.S., S.A.K. and A.I.; methodology, K.S. and S.A.K.; validation, A.I. and O.S.; formal analysis, K.S., A.I. and S.A.K.; investigation, K.S. and A.I.; resources, A.I. and O.S.; data curation, S.A.K. and A.I.; writing—original draft preparation, K.S, S.A.K., A.I. and O.S.; writing—review and editing, K.S. and A.I.; visualization, K.S., A.I. and O.S.; supervision, S.A.K.; project administration, S.A.K. and A.I.; funding acquisition, O.S. and A.I. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not Applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

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Open Access

Peer-reviewed

Research Article

Unveiling the Nexus: Influence of learning motivation on organizational performance and innovative climate of Chinese firms

Roles Conceptualization, Data curation

Affiliation Development and Planning Division, Chengdu University, Chengdu, Sichuan, China

Roles Formal analysis, Investigation

Affiliation School of Continuing Education, Chengdu University, Chengdu, Sichuan, China

Roles Investigation, Methodology

Roles Methodology, Software

Roles Conceptualization, Writing – original draft

Roles Data curation, Writing – original draft

* E-mail: [email protected]

• Yu Zhang, 
• Caizhi Liao, 
• Jialei Liu, 
• Yihe Zhang, 
• Shiquan Gui, 

• Published: May 31, 2024
• https://doi.org/10.1371/journal.pone.0304729
• Reader Comments

This study delves into the interplay between learning motivation, organizational performance, and the innovative climate within Chinese firms. It is a subject of frequent discussion in literature but there is little concrete evidence supporting this viewpoint within the context of small and medium size enterprises in China. Drawing upon a comprehensive review of existing literature and empirical data gathered, this research aims to uncover the connections between employee learning motivation and its impact on the organizational dynamics in the context of Chinese firms. A cross sectional survey is used to collect the data of 115 Chinese firms and structural equation modelling (SEM) is used for empirical analysis. The results show that success of firms in terms of innovation is significantly influenced by organizational learning motivation. Moreover, innovative environment of the firms increases the overall performance of the organizations. It is also found that factors affecting the innovations have a significant impact on organizational performance. The findings of the study suggest that firms should develop organizational learning motivation to boost their innovation capability and overall performance. This study offers insights and recommendations for organizations and policymakers seeking to harness the potential of learning motivation to drive sustainable growth, competitiveness, and innovation in Chinese firms.

Citation: Zhang Y, Liao C, Liu J, Zhang Y, Gui S, Wei Q (2024) Unveiling the Nexus: Influence of learning motivation on organizational performance and innovative climate of Chinese firms. PLoS ONE 19(5): e0304729. https://doi.org/10.1371/journal.pone.0304729

Editor: Kashif Ali, University of Central Punjab, PAKISTAN

Received: November 30, 2023; Accepted: May 16, 2024; Published: May 31, 2024

Copyright: © 2024 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: This paper is funded by Chengdu Children's Friendly City Construction Research Institute: Investigation on the Current Situation of Psychological Capital of Primary and Secondary School Students in Chengdu (Project No: ETYH-2023-B19). The funder had no role in study design, data collection and analysis, decision to publish, and preparation of this manuscript.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

The learning motivation of an organization can be defined as "a field toward to the study of cognitive and social processes of knowledge in organizations that are imbricated in organizational and work practices" [ 1 ]. It refers to the drive, desire, or willingness of individuals within an organization to engage in learning activities, acquire new knowledge, develop skills, and improve performance within the organizational context [ 2 , 3 ]. Organizational learning motivation is crucial as it directly impacts the willingness of employees to engage in learning activities, acquire new knowledge, and apply these skills to enhance individual and collective performance [ 4 , 5 ]. Organizations can maximize their competitive advantage by placing a high priority on learning in such settings [ 6 ]. Organizational learning is essential for enabling organizations to produce, distribute, and integrate knowledge and experience while promoting continual learning. The organizational characteristics that encourage learnings are included in the capacity for organizational learning [ 7 ]. This capability includes all organizational and administrative practices that aid in learning [ 4 ]. It is a collection of procedures that improve capacity of an organization to sustain and improve performances or a set of operational procedures that promotes learning [ 8 ].

There is an established relationship in the literature, between organizational learning and organizational performance. Organizational performance is the measure of how effectively an organization achieves its objectives and goals. It encompasses various aspects of an organization’s functioning, including its efficiency, productivity, profitability, quality of products or services, customer satisfaction, innovation, and overall success in meeting stakeholder expectations [ 9 ]. Key components that contribute to assessing organizational performance include metrics such as revenue growth, profitability, return on investment, and cost efficiency [ 10 ]. Assessing the morale, motivation, and commitment of employees, which can significantly impact productivity, innovation, and overall organizational success [ 4 , 6 ].

Innovative climate in firms is also an aspect that affects the learning motivation and organizational performance of the firms. The innovative climate of a firm includes the environment, culture, and conditions within an organization that foster and encourage creativity, experimentation, and the development of new ideas, products, processes, or services [ 11 ]. It is the collective mindset, values, practices, and structures that shape how innovation is perceived, supported, and implemented across the organization [ 12 ]. An innovative climate thrives on a culture that encourages creative thinking, where employees feel empowered to share ideas without fear of criticism. It also embraces calculated risk-taking, understanding that not all innovations will succeed but valuing the lessons learned from experimentation [ 7 ]. An environment that promotes open communication, collaboration, and cross-functional teamwork fosters the exchange of ideas and perspectives. This diversity of thought often leads to more innovative solutions to challenges. A culture that values learning and ongoing development nurtures an environment where employees are encouraged to explore new skills, knowledge, and trends [ 12 , 13 ].

The relationship among organizational learning motivation, innovative climate, and the performance of firms is complex and interconnected. Organizational learning motivation is a key driver of an innovative climate [ 14 ]. When employees are motivated to learn and develop their skills, they are more likely to come up with new ideas, embrace change, and contribute to the organization’s innovation culture [ 8 ]. An organization that promotes learning motivation creates an environment where employees feel encouraged to take risks, experiment, and think creatively, which are crucial elements of an innovative climate [ 15 ]. On the other side, an innovative climate is positively associated with the performance of firms. When an organization fosters a culture of innovation, it tends to develop new products or services that meet customer needs, gain a competitive advantage, improve processes and operations, leading to increased efficiency [ 5 ]. Organizational learning motivation leads to an innovative climate, which, in turn, enhances the performance of firms [ 10 ]. Higher performance can further motivate employees to learn, innovate, and maintain a positive innovative climate [ 8 ]. As the organization’s performance improves, it can invest in resources, training, and tools that promote learning and innovation, further strengthening the cycle [ 11 – 16 ].

There is extensive literature on this topic but there are still several unanswered questions that warrant further investigation. While it is known that learning motivation influences organizational performance and innovative climate, the specific mechanisms through which this occurs remain unclear. Further research is needed to identify the factors that may enhance or inhibit the relationship between learning motivation and organizational outcomes like experimentation, risk, interaction, and dialogue. Despite the theoretical advances, there is a need for research that translates findings into actionable strategies and best practices for Chinese firms. It means that while there is existing theoretical knowledge about topics like learning motivation and organizational performance, there is a gap in translating this knowledge into practical, implementable strategies for Chinese firms. This translation is necessary because theoretical knowledge, while valuable, may not always directly translate into effective actions or practices that can be applied in real-world business settings. To achieve this translation requires several steps like understanding the context. Researchers need to understand the specific context of Chinese firms, including cultural, economic, and regulatory factors that may impact the applicability of theoretical findings. Then there is need to identify the key challenges faced by Chinese firms in implementing theoretical concepts and develop strategies that specifically address these challenges. Based on theoretical insights and empirical evidence, researchers can develop actionable recommendations and best practices that are tailored to the unique needs and circumstances of Chinese firms. Finally, these actionable strategies and best practices should be disseminated to Chinese firms through channels such as academic journals, conferences, and industry publications, and efforts should be made to facilitate their implementation through training programs and consulting services.

Studies that explore the practical implications of enhancing learning motivation for organizational performance and innovation management can provide valuable guidance for managers and policymakers [ 17 , 18 ]. Addressing these unanswered questions can lead to more effective strategies for fostering learning, innovation, and sustainable growth. The problem addressed in the research paper likely focuses on understanding the relationship between learning motivation, organizational performance, and innovative climate within Chinese firms. The study aims to explore how learning motivation among employees influences overall organizational performance and examines how motivated employees contribute to achieving organizational goals and objectives. Another aspect is examining the role of learning motivation in fostering an innovative climate. This involves assessing the impact of motivated employees on creativity, idea generation, knowledge sharing, and the implementation of innovative practices and technologies. The paper also discusses the practical implications of its findings for Chinese firms aimed at enhancing learning motivation and fostering a culture of innovation. This study can provide insights into how to cultivate a culture that encourages creativity, experimentation, and the adoption of new ideas and technologies. Research in this area can contribute to the theoretical understanding of organizational learning motivation, organizational performance and innovative climate. Overall, this study provides valuable insights that can inform both academic theory and practical strategies for organizational development and success in today’s competitive global marketplace.

The research problem of the study could be formulated as that despite the acknowledged importance of organizational learning and innovation for sustained competitive advantage, there remains a gap in understanding how individual learning motivation influences organizational performance and the innovative climate within Chinese firms. The research gap in the study likely revolves around the specific challenges faced by Chinese organizations in fostering and maintaining high levels of learning motivation among their employees. Chinese organizations may face challenges in aligning their organizational culture with a culture that promotes learning and innovation. Traditional Chinese culture values stability and conformity, which may inhibit risk-taking and innovation. The effectiveness of learning motivation strategies may be impacted by the quality and nature of China’s educational system. Issues such as rote learning and exam-focused education could hinder employees’ intrinsic motivation to learn and innovate. Moreover, Chinese organizations may struggle with leadership styles that do not encourage or support a culture of learning and innovation. Autocratic leadership, which is common in Chinese organizations, may stifle creativity and risk-taking. Limited resources, both financial and human, could pose challenges for Chinese organizations in implementing effective learning motivation strategies. This could include constraints on training budgets, lack of access to learning opportunities, or insufficient time for employees to engage in learning activities. In addition, the pace of technological change in China may require employees to continuously learn new skills and adapt to new technologies. Organizations that fail to facilitate this ongoing learning process may struggle to maintain a competitive edge and with increasing globalization, Chinese organizations are facing greater competition from international firms. This places pressure on organizations to innovate and adapt quickly, which may require a high level of learning motivation among employees. This study seeks to address this gap by examining the relationship between learning motivation, organizational performance, and the innovative climate in Chinese firms. Moreover, the significance of the study lies in its potential to contribute to both theory and practice in several ways. This study provides valuable insights into the role of learning motivation in driving organizational performance and fostering an innovative climate, particularly within the context of Chinese firms. This can help advance theoretical understanding of the mechanisms through which individual motivation impacts organizational outcomes. By focusing on Chinese firms, the findings offer practical implications for managers and policymakers in Chinese firms, providing them with evidence-based strategies to enhance learning motivation among employees, improve organizational performance, and promote a more innovative climate. Finally, the study adds to the growing body of literature on organizational learning and innovation, offering new perspectives and insights that can stimulate further research in this important area.

This study has the objective to explore the impact organizational learning motivation including its aspects experimentations, risk, interaction, and dialogue that are most effective in different organizational contexts and these are little focused in the earlier literature related to Chinese firms. Extending this finding would explore the ways in which learning motivation influences the organizational performance. Moreover, this study also has the objective to consider the impact of aspects of innovation performance like efficiency and efficacy on performance of Chinese firms by collecting the primary data and applying the econometric techniques for empirical analysis. It is found that learning motivation of employees positively influences the innovations and performance of workers in Chinese firms.

2. Theoretical foundations

The theoretical relationship among organizational learning motivation, innovation capacity and organizational performance is grounded in several perspectives. Social learning theory posits that individuals learn through observation, imitation, and social interaction. Within organizations, employees’ learning motivations can be influenced by observing the behaviors and outcomes of others. When employees witness colleagues being rewarded or recognized for their learning efforts, they are more likely to be motivated to engage in similar learning activities. This social reinforcement of learning motivation contributes to improved individual and organizational performance [ 19 ]. Expectancy theory suggests that individuals are motivated to engage in behaviors when they believe that their efforts will lead to desired outcomes. In the context of organizational learning, employees who are motivated to learn are more likely to believe that their learning efforts will result in improved job performance, career advancement, and personal development. This belief in the expectancy of positive outcomes drives employees to invest time and effort in learning activities, ultimately enhancing organizational performance [ 20 ]. Goal setting theory emphasizes the importance of setting specific, challenging goals to motivate individuals and improve performance. Organizational learning motivation can be facilitated by setting clear learning goals and providing employees with the necessary resources and support to achieve them. When employees are motivated to attain these learning goals, they are more likely to acquire new knowledge and skills that contribute to enhanced job performance and organizational effectiveness [ 21 ]. Self-determination theory proposes that individuals are intrinsically motivated to pursue activities that fulfill their psychological needs for autonomy, competence, and relatedness. In the context of organizational learning, employees are more likely to be motivated when they have opportunities to autonomously choose learning activities that align with their interests and goals, when they feel competent in their ability to learn and apply new knowledge, and when they experience a sense of connection and belongingness within the organization. Meeting these psychological needs for motivation fosters a positive learning environment and leads to improved organizational performance [ 22 ]. The resource-based view of the firm suggests that organizational learning capabilities, including the motivation of employees to learn and adapt, are a source of competitive advantage. Organizations that invest in fostering a learning culture and motivating employees to continuously improve their knowledge and skills are better positioned to adapt to changing market [ 23 ]. The knowledge-based view emphasizes the role of knowledge creation, sharing, and utilization as critical drivers of organizational innovation. Organizational learning motivations facilitate the acquisition and development of new knowledge and skills among employees, which are essential for generating innovative ideas, processes, and products. As employees engage in learning activities and accumulate knowledge, they are better equipped to identify opportunities for innovation and contribute to the organization’s overall innovation capacity [ 24 ]. Learning organization theory suggests that organizations capable of continuously learning and adapting are more likely to innovate and achieve long-term success. Organizational learning motivations play a central role in cultivating a learning-oriented culture and mindset within the organization, where employees are encouraged to experiment, take risks, and learn from both successes and failures. This culture of learning fosters an environment conducive to innovation, where employees feel empowered to generate and implement novel ideas to address organizational challenges and opportunities [ 11 ]. Innovation diffusion theory highlights the importance of individual and organizational learning processes in the adoption and implementation of innovations. Organizational learning motivations drive the dissemination of new knowledge and best practices throughout the organization, facilitating the adoption of innovative ideas and technologies. As employees become motivated to learn and apply new knowledge, they become champions and advocates for innovation within their respective teams and departments, leading to widespread adoption and integration of innovative practices across the organization [ 25 ]. Absorptive capacity theory suggests that organizations must have the ability to recognize, assimilate, and apply external knowledge to innovate effectively. Organizational learning motivations contribute to the development of absorptive capacity by enhancing employees’ skills in identifying relevant external knowledge sources, evaluating the quality and applicability of incoming information, and integrating new knowledge into existing organizational routines and processes. By fostering a culture of continuous learning and knowledge exchange, organizations can enhance their absorptive capacity and leverage external knowledge to drive innovation [ 26 ]. The Triple Helix model posits that innovation is driven by interactions between academia, industry, and government. Organizational performance is enhanced when these stakeholders collaborate effectively to create and transfer knowledge, develop new technologies, and stimulate economic growth. Innovation capacity serves as a catalyst for collaboration within the Triple Helix framework, as organizations with strong innovation capacities are better positioned to leverage external knowledge and expertise, forge strategic partnerships, and participate in collaborative innovation ecosystems, ultimately leading to improved performance outcomes [ 27 ].

3. Conceptual framework

A conceptual framework outlining the relationship among organizational learning motivation, innovation capacity and organizational performance can be structured as shown in the following Fig 1 . At the individual level, the study considers the concept of learning motivation, which is influenced by different factors while learning motivation is expected to drive individual learning behavior and the acquisition of new knowledge and skills. At the organizational level, the study focuses on two key outcomes: organizational performance and the innovative climate. Organizational performance is a multifaceted construct that includes financial performance, operational efficiency, and overall effectiveness. The innovative climate refers to the organizational culture and practices that support and encourage innovation among employees. The study also proposes that individual learning motivation can influence organizational performance and the innovative climate through mediating mechanisms. Resource-Based view theory suggests that a firm’s unique resources and capabilities are key drivers of competitive advantage and, consequently, organizational performance. According to this theory, firms with valuable, rare, and difficult-to-imitate resources are more likely to outperform competitors. Moreover, agency theory examines the relationship between principals (e.g., shareholders) and agents (e.g., managers) in an organization. It suggests that conflicts of interest between principals and agents can impact organizational performance. For example, managers may prioritize their own interests over those of shareholders, leading to suboptimal performance. The Fig 1 highlights the conceptual framework of the study.

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https://doi.org/10.1371/journal.pone.0304729.g001

Organizational learning motivation refers to the collective drive and willingness of individuals within an organization to engage in learning activities, acquire new knowledge, and develop skills that contribute to personal and organizational growth. When employees are motivated to learn and grow, they are more likely to be engaged in their work, resulting in higher levels of commitment, productivity, and job satisfaction [ 28 ]. Engaged employees are also more inclined to contribute discretionary effort, proactively seek opportunities for improvement, and collaborate effectively with colleagues, all of which contribute to improved organizational performance. Organizational learning motivation also drives employees to actively seek out new information, engage in training and development initiatives, and apply their learning to solve problems, innovate, and make informed decisions [ 29 ]. The acquisition and application of relevant knowledge and skills enhance employees’ capabilities, performance, and contributions to organizational goals. When employees are motivated to learn and develop, they contribute to the organization’s ability to achieve its strategic objectives, respond effectively to changing market conditions, and sustain competitive advantage over time [ 30 ]. Social Cognitive theory emphasizes the role of social factors in learning and motivation. According to social cognitive theory, individuals can learn by observing others (social learning) and by receiving feedback and reinforcement from others (social reinforcement). Social cognitive theory also emphasizes the role of self-efficacy beliefs in motivation, suggesting that individuals are more likely to be motivated to learn when they believe they have the ability to succeed.

Innovation capacity refers to the organization’s ability to generate, develop, and implement innovative ideas, practices, and solutions that create value for customers and stakeholders. This process contributes to the accumulation of a diverse range of knowledge and expertise within the organization, providing a rich foundation for innovation [ 31 ]. Employees who are motivated to learn are more likely to stay updated with industry trends, emerging technologies, and best practices, thereby fueling the organization’s ability to generate innovative ideas and solutions. Motivated learners are more inclined to engage in creative thinking and problem-solving activities. By fostering a culture of experimentation, curiosity, and risk-taking, organizational learning motivation encourages employees to explore new possibilities, challenge conventional wisdom, and think outside the box [ 32 ]. This creative mindset is essential for generating novel ideas, designs, and approaches that drive innovation and address complex challenges faced by the organization. Moreover, organizational learning motivation enhances the organization’s adaptability and flexibility in response to changing market conditions, customer preferences, and competitive pressures [ 33 ]. Motivated employees are more willing to embrace change, adapt to new technologies and methodologies, and experiment with alternative approaches to problem-solving. This adaptability enables the organization to continuously evolve and adjust its strategies, processes, and products in line with emerging opportunities and threats, thereby maintaining a competitive edge in the marketplace [ 34 ]. Learning-motivated employees are more likely to collaborate with colleagues from diverse backgrounds, departments, and disciplines. By sharing knowledge, exchanging ideas, and leveraging each other’s strengths and expertise, employees can generate synergies and cross-pollinate insights that stimulate innovation [ 35 ]. Collaborative learning environments foster creativity, spark new perspectives, and facilitate the co-creation of innovative solutions that draw upon a wide range of perspectives and expertise within the organization. Diffusion of Innovation theory explains how innovations spread within a social system. In the context of organizational climate, it suggests that an organization’s climate can either facilitate or inhibit the adoption and implementation of new ideas and practices. While complexity theory views organizations as complex adaptive systems that constantly evolve and adapt to their environment. In this view, an innovative climate emerges from the interactions between individuals, teams, and the larger organizational system. Moreover, creative problem solving theory focuses on the cognitive processes involved in generating creative solutions to problems. An innovative climate provides the conditions necessary for individuals to engage in creative problem-solving, such as autonomy, resources, and support from others. In addition, organizational learning theory emphasizes the importance of continuous learning and adaptation for organizational success. An innovative climate fosters organizational learning by encouraging experimentation and reflection on outcomes.

3.1. Literature review and hypotheses

The learning aptitude of the organization defined as "the ability of an organization to process knowledge, i.e., the ability to create, acquire, transfer and integrate knowledge and, also, to modify the behavior to reflect the new cognitive situation, with the aim at improving organizational performance" [ 16 ]. The idea of learning competency of organization, that includes both real and vague resources as well as aptitudes that support reasonable advantage, acts as a catalyst in organizational learning process [ 17 ]. This in turn helps the organizational learning process to advance [ 18 ]. While organizational learning ability refers to the organization’s power to fascinate and alter new information before using it to quickly produce innovative goods that have a competitive advantage [ 19 ]. In addition, aptitude for learning ability of organization functions as together an intrinsic administrative characteristic and a managerial attribute [ 7 ]. Furthermore, apart from its role in easing the learning process within organizations, it actively contributes to the learning process itself and characterize it as the removal of limitations or impediments within the organizational learning process [ 20 , 35 ].

To encourage creation of organizational awareness, organizations should set up procedures and enact policies. These processes include internalization, socialization, and externalization along with variety of management techniques that support a learning environment [ 8 ]. “These practices are the foundation of organizational learning capability, which can be characterized as a set of management practices that facilitate the learning process or as a set of mechanisms that improve the organization’s ability to sustain and improve its performance” [ 8 , 18 ].

The characteristics that support organizational learning were examined by earlier studies [ 7 ]. In order to achieve this, they created a scale that had five dimensions: The aspects include a propensity for risk, engagement with the outside world, conversation, and collaborative decision-making. The scale has furthermore been used in earlier investigations [ 6 , 8 , 20 – 22 ] and this study likewise makes use of these scales. Experimentation refers to how much fresh ideas and recommendations are accepted and managed within the business [ 6 ]. It is associated with endorsing novel concepts, offering positive feedback to employee initiatives, and fostering and facilitating change. Additionally, it includes looking for imaginative answers to difficulties that are based on the prospective use of various techniques and processes. One way to institutionalize organizational learning within the organization is through experimentation [ 5 , 36 ].

Competition, social and economic systems, and policies are only a few examples of the external environment that a company interacts with. These elements have an impact on the business but are beyond of its direct control. This dimension includes metrics related to information exchange and employee involvement with the outside world, as well as the collection and transmission of external environmental data [ 7 ]. The transmission of knowledge, the development of skills, and active engagement in internal problem-solving are the three ways that learning occurs in uncertain contexts [ 23 ]. The level of tolerance an organization has for ambiguity, uncertainty, and mistakes determines its propensity to take risks. Organizations that see inaccuracies as intolerable do not foster learning, as prospective blunders may in fact promote learning. the ability to take chances without endangering the company and the willingness to face new challenges are all indicators of a person’s propensity to take risks [ 7 , 23 , 24 ]. An organization can apply modifications to support organizational learning, hence nurturing specific characteristics such as participative decision-making [ 11 ].

According to the literature, organizational learning and creativity frequently go side by side [ 25 , 37 ]. The development of behaviors and abilities necessary for innovation is fostered by organizational learning, which is frequently seen in efforts focused on product creation [ 26 ]. Researchers that study innovation place a strong emphasis on the heroine that organizational erudition processes play in the creation of new goods. Therefore, it is clear that organizational learning is a prerequisite for any technological breakthrough [ 27 ]. Organizational learning, according to studies in this area [ 4 , 18 , 28 ], has a positive impact on creative performance. The first step in fostering innovation is for people to gather the most recent knowledge and then spread it throughout the company. Organizational learning and creativity are said to be closely related [ 19 ].

• H1 : Organizational learning has a beneficial impact on organizational innovative performance.

Innovations are embraced either in reaction to shifts within internal and external contexts or as a proactive measure to shape those surroundings. SMEs are particularly well-positioned for innovation due to the inherent challenge of expanding and realizing their full capabilities [ 29 , 37 ]. The essence of innovation lies in the conversion and utilization of knowledge within organizations, a process that encompasses the sharing of both knowledge and information among workforces [ 4 , 30 ]. In present analysis, inventive performance is assessed through two distinct dimensions: efficacy and efficiency, a framework initially developed by the study [ 12 ]. These playwrights introduced a measurement scale for assessing artifact novelty performance, known as "innovative performance," which underwent rigorous psychometric testing and validation within the context of biotechnology firms. Efficacy seeks to evaluate the economic influence of modernization on the organization, specifically gauging the success or outcomes resulting from innovation efforts. Meanwhile, efficiency pertains to the process through which these outcomes are attained [ 8 , 38 ].

According to earlier studies [ 14 , 30 ], creative firms have the capacity to quickly adjust to environmental difficulties, leading to improved performance. Innovation improves the efficiency of SMEs [ 31 ]. The nature of the invention, the age of the organization, and the cultural context in which it functions are just a few examples of the many factors that might affect performance. The findings show that organizational learning has a stronger effect on creativity and performance in smaller firms than it does in larger ones [ 11 , 39 ]. Organizational learning efforts have a greater influence on creativity in smaller organizations since there are less established organizational practices there. Using the setting of SMEs, the study [ 32 ] conducted to observe the impact of market direction, learning coordination, and modernization. According to the study’s results, learning helps to promote creativity and that advancement has a positive effect on organizational enactment. In addition, most businesses—including small and medium-sized ones, which make up a significant component of most economies—introduce new goods regularly, regardless of their level of innovation [ 33 ]. Comprehending consumer needs, monitoring competitor actions, staying attuned to technological advancements, and adhering to the principles of organizational knowledge can collectively enable organizations to harness the advantages of innovation [ 9 ]. SMEs can derive enhancements in product quality and increased sales of their manufactured products by embarking on both product innovations and market entry strategies [ 34 ]. Innovation stands as a pivotal tool for augmenting market share and conferring a competitive edge upon a company [ 1 , 13 ]. This optimistic effect on a firm’s enactment culminates in an improved market position, resulting in a distinctive viable advantage and larger overall performance. Consequently, the following hypothesis is postulated:

• H2 : Innovative performance exerts a positive impact on organizational performance.

Factors that promote organizational learning play a pivotal role in enhancing organizational performance in various ways. When organizations foster a culture of knowledge sharing and transfer, employees exchange information, best practices, and lessons learned [ 11 ]. This dissemination of knowledge across departments or teams enhances collective expertise, improves decision-making, and avoids redundant efforts, thus optimizing overall efficiency and performance [ 34 , 40 ]. Promoting a learning culture encourages a mindset of continuous improvement. Employees are motivated to identify inefficiencies, suggest innovative solutions, and implement changes that lead to enhanced processes, better products/services, and increased productivity, ultimately contributing to improved performance metrics [ 35 ]. Organizations that prioritize learning adapt more effectively to changing environments. Employees equipped with new skills and knowledge are better prepared to navigate uncertainties, embrace change, and respond proactively to market shifts, improving the organization’s ability to stay competitive and perform well in dynamic settings [ 5 , 36 ]. Learning organizations encourage creativity and innovation. By empowering employees to explore new ideas, experiment, and take calculated risks, they foster a climate conducive to innovation [ 21 , 37 ]. This innovation leads to the development of new products, services, or processes that can positively impact performance by opening new market opportunities or improving operational efficiency [ 14 , 18 ]. Organizations that invest in learning and development initiatives tend to have higher employee engagement and retention rates. Employees appreciate opportunities for growth, skill enhancement, and career development [ 24 ]. Engaged employees are more committed, productive, and contribute positively to organizational performance [ 22 ]. A learning-focused environment emphasizes learning from mistakes and using them as opportunities for growth. As employees acquire new knowledge and skills, they make fewer errors, make more informed decisions, and approach problem-solving more effectively, thus positively impacting overall organizational performance [ 9 , 32 ]. Factors promoting organizational learning create a cycle of improvement and growth within the organization. By nurturing a culture of learning, organizations empower their employees, improve operational efficiency, foster innovation, and increase adaptability, all of which collectively contribute to improved organizational performance and sustained success.

• H3 : The factors that promote organizational learning have a positive impact on organizational performance.

The organizational learning capability is made up of four parts: experimentation, propensity to risk, interaction with the external environment, and dialogue. Effective performance has features of both effectiveness and efficiency. Organizational performance, on the other hand, is a one-dimensional concept. The empirical relationship is mentioned in the following Fig 2 .

https://docs.google.com/document/d/1xej1bG-7xIIvenG5J8oXO5_bThehM8to/edit?usp=sharing&ouid=109167264099591876564&rtpof=true&sd=true .

https://doi.org/10.1371/journal.pone.0304729.g002

4. Methodology

The research follows a quantitative technique and uses a survey methodology inside a cross-sectional design. It is distinguished by its descriptive and causal nature about its objectives. The inclusion of constructs has been crucial in forming the data collection tool. It is standard practice in behavioral research for researchers to use two or more measurements to evaluate a particular construct or scale [ 11 ], achieving precise measurements with a single unit can be difficult. In order to ensure both soundness and consistency in the measurements, the study adheres the recommendation and attempts to use pre-tested constructs from prior empirical research whenever practical [ 38 , 41 ].

4.1. Data and sampling

On the basis of accessibility and convenience, the sample was selected. Considering the significant economic significance of manufacturing sector in China, this study selected both 115 small and medium enterprises of China. The selection of the research sample was deliberate, based on accessibility and convenience. The aim was to select a sample of small and medium-sized enterprises across the country. Thus, enterprises were chosen that could contribute to the research objectives. The majority of these enterprises having number of employees in the range of 20–100. The sample size was determined following Hair’s [ 27 , 28 ] recommendations. To achieve a statistical significance of 80% and attain an R2 value of 0.25 at a significance level of 95%, considering a total of 4 variables in the model, a minimum of 45 observations [ 27 , 28 , 42 – 45 ] was deemed necessary. A sample of 115 Chinese SMEs was sought in order to lessen the impact of random factors. The firms in the sample are largely involved in manufacturing and majority of the businesses in the sample were started between the years of 1992 and 2009. The data is collected from senior executives of the firms. A preliminary meeting was arranged with the executives of all of the chosen firms taking part in the study to obtain data. A letter introducing the research was given to them at the meeting. Upon receiving positive responses to the study invitation, the questionnaire was forwarded to the HR representatives of the companies. Approval for the research was obtained from the top management of the participating organizations. The appropriate times for data collection were then established. The data is collected from February 1, 2023 to April 30, 2023. A written consent was gained from respondents prior to fill the survey. The response was received via print form and electronic surveys. The characteristics of respondents are given in the following Table 1 .

https://doi.org/10.1371/journal.pone.0304729.t001

4.2. Measurement

The four factors that make up the notion of organizational learning capability are engaged with the external environment, propensity to risk, and dialogue. The statements for evaluation were created using a seven-point Likert scale, with 1 denoting "completely disagree" and 7 denoting "completely agree". Two components make up the creative performance construct: efficacy, which has seven indicators, and efficiency, which has four indicators. To assess the construct of organizational performance, four indicators were employed, comprising two of financial performance (profitability and return on investment) and two linked to market performance (customer loyalty and sales growth). When financial statement data is either not available or does not allow for precise judgments between organizations, indirect measures of organizational enactment then similar to those were used in earlier studies [ 14 , 35 , 46 ]. The justification for using subjective scales stems from both the unwillingness of businesses to provide accurate performance records and the typical reluctance of managers to divulge objective performance statistics. The Confirmatory Factor Analysis (CFA) was used to analyze the data and evaluate the validity and reliability of the components. The Smart PLS Program was used as the operational tool for the subsequent Structural Equation Modelling (SEM) procedure. The structural model, which follows the methodology described by the study [ 39 , 1 , 47 – 50 ], illustrates the connections between the variables and quantifies the explained variation. This analytical method was embraced in order to explore the relationships between factors under analysis and verify a model for determining how organizational learning affects innovative performance and how that in turn affects organizational performance. Separate computations were made in order to evaluate the dependability of each construct. PLS-SEM is a popular statistical technique used for analyzing structural relationships between latent variables in empirical research. In summary, smart PLS is used to apply SEM to determine the relationship of considered variables for this study.

Cronbach’s alpha (CA) is a regularly used dependability method, and values above 0.7 are typically regarded as satisfactory. Hence, alongside Cronbach’s alpha (CA), we also utilized composite reliability (CR) and average variance extracted (AVE). Internal consistency is determined by composite reliability (CR), with values over 0.70 being advised. The reliability measure AVE, on the other hand, shows the percentage of the variance in indicators that can be accounted for by the latent hypothesis and values for AVE greater than 0.5. The discriminant validity indicates the independence of constructs or latent variables from one another, was a crucial factor taken into account while evaluating the models fit [ 1 ]. By comparing the associations between the constructs to the square root of the Average Variance Extracted (AVE) for each construct, the Fornell and Larcker [ 50 ] criterion was used in the first stage. Each construct’s square root of the AVE must be greater than its correlation with other constructs in order for discriminant validity to be established. These criteria check that item factor loadings are higher on the relevant constructs than on other constructs to support discriminant validity. The t-test values should be greater than or equal to 1.96, were taken into account by the study to determine the significance of the models [ 1 ]. Furthermore, the p-value must be lower than 0.05. To evaluate the utility of the constructs in the model, the effect size also known as the Cohen indicator or f2. The effect sizes of 0.02, 0.15, and 0.35 are categorized as small, medium, and big, respectively [ 41 – 43 ]. The study next looked at the results of the structural model and tested the hypotheses after evaluating the goodness-of-fit indicators.

5. Estimated results

Table 2 shows the outcomes of calculating coefficients such AVE (Average Variance Extracted), CC (Composite Reliability), and CA (Cronbach’s Alpha).

https://doi.org/10.1371/journal.pone.0304729.t002

Regarding the AVE values, it’s important to note that merely the second-order paradigm of organizational learning exhibited a value below 0.5, with an AVE of 0.429. However, this particular analysis should be interpreted cautiously, given that the second-order construct comprises all four dimensions of the first order. It’s worth mentioning that an AVE value below 0.5 is not an absolute issue, as some other authors [ 44 ] have considered such values acceptable. When examining the Composite Reliability (CR), it is noteworthy that all dimensions scored above 0.70, indicating good internal consistency. Furthermore, looking at the standards of Cronbach’s Alpha (CA), all exceeded 0.7, reinforcing the notion of good reliability. According to the reliability findings, it can be said that the constructions showed sufficient levels of dependability to assessment of the fundamental model. The R-squared (R2) statistic is used to gauge how well the structural model accounts for endogenous variable variation. R2 levels can be characterized as considerable, moderate, or weak, with values close to 0.75, 0.50, and 0.25, respectively. Cohen proposed that R2 = 2% is a minor effect in the social sciences and behavioral disciplines, R2 = 13% is an average effect, and R2 = 26% is a large effect. As can be seen in Table 2 , every R 2 value was greater than 26%, suggesting a significant effect, which is an indication of a good model.

To prove discriminant validity, the study applied Fornell and Larcker’s criteria for discriminant analysis. Through this method, it is determined whether a model’s indicators are unique to one construct or can be distinguished from those of other constructs. The square root of the AVE is greater than the correlations with other latent variables, which is evidence that the model has discriminant validity. Meeting these requirements demonstrates discriminant validity, proving that various measurements relate to various concepts. Discriminant validity was evaluated across all dimensions in accordance with Fornell & Larcker’s criteria. The square root of the AVE was found to be greater than the correlations with other latent variables. In light of these evaluations, it can be said that the model’s constructs show both reliability and validity. The t-test values for each claim were carefully examined using the criterion of 1.96 [ 1 ] and p-value > 0.05. There was no need for any revisions at this point because every assertion complied with these requirements. According to Fornell and Larcker’s [ 50 ] criterion, Table 3 shows the results of discriminant validity.

https://doi.org/10.1371/journal.pone.0304729.t003

https://doi.org/10.1371/journal.pone.0304729.t004

The goodness of fit is traditionally intended to assess the overall quality of a model. After findings the goodness of fitness, we can estimate the structural equation model and findings are shown in Fig 1 . The choice of Partial Least Squares Structural Equation Modeling (PLS-SEM) as the analytical method can be justified on several grounds. PLS-SEM is particularly suitable for models with complex relationships and multiple latent variables, as is the case in this study. It allows for the estimation of both the measurement model (relationships between observed and latent variables) and the structural model (relationships between latent variables) simultaneously, making it ideal for studying the interplay between learning motivation, organizational performance, and the innovative climate. PLS-SEM is known for its ability to handle small sample sizes effectively, which is often the case in organizational research, especially in the context of Chinese firms where data collection can be challenging. PLS-SEM requires a smaller sample size compared to other SEM approaches, making it a practical choice for this study. PLS-SEM is well-suited for prediction-oriented research, where the focus is on understanding and predicting the relationships between variables rather than testing complex causal relationships. In this study, the aim is to predict how learning motivation influences organizational performance and the innovative climate, making PLS-SEM a suitable choice. PLS-SEM offers greater flexibility in model specification compared to other SEM approaches. It allows researchers to include both formative and reflective constructs in the model, which is beneficial when studying complex phenomena such as learning motivation and organizational outcomes. This approach accommodates differences in measurement models and structural relationships across different cultural contexts, allowing for a more nuanced analysis of the impact of learning motivation in Chinese firms. PLS-SEM is a robust analytical method that aligns well with the objectives and requirements of the study, making it a suitable choice for analyzing the impact of learning motivation on organizational performance and the innovative climate of Chinese firms. While PLS-SEM may be considered less robust for confirmatory analysis compared to covariance-based SEM, its ability to handle complex models, small sample sizes, and prediction-oriented research makes it well-suited for exploratory and theory-building studies. The Fig 3 shows the empirical analysis of structural equation model.

https://docs.google.com/document/d/1ngt-s12u2QFTq8WTmhegLS9tSKtGd3no/edit?usp=sharing&ouid=109167264099591876564&rtpof=true&sd=true .

https://doi.org/10.1371/journal.pone.0304729.g003

The results suggest that the relationships proposed within the second-order construct of organizational learning capability and its first-order variables, namely experimentation, interaction with the external environment, propensity to risk, and dialogue hold validity within the context of organizational learning capability. Organizational learning is the cooperative creation of new shared meanings through communication, equitable involvement, and a readiness to accept divergent opinions. Shared experiences and unrestricted access to information define it. In these situations, productive conversations are essential to the organizational learning process. Notably, "Dialogue" had the greatest impact on the organizational learning capabilities of all the dimensions. By establishing routines for communication among various groups or levels of the hierarchy, bureaucratic processes are reduced, which promotes greater consistency and innovation. This is because people come to share a common thought process and have a better awareness of the issues and objectives of the organization [ 45 , 51 ]. The findings also point to the prevalence of work teams, which are frequently made up of individuals from other industries. The exchange of open knowledge inside these work teams may produce new results [ 46 , 52 ]. This demonstrates how information sharing and cross-functional cooperation may help firms to innovate. Notably, the efficacy dimension exhibited the highest factor loading, indicating a strong association with innovations introduced in the market. This suggests that the effectiveness of innovation efforts, particularly in terms of introducing new products to the market, played an essential role in the overall assessment of innovative performance. It appears that the small and medium-sized companies are primarily focused on staying competitive in the market by continuously innovating their product offerings to align with the evolving demands of a sector that consistently seeks novelty. These companies operate in an industry marked by a diverse range of products with exceedingly short lifecycles, largely dependent on ever-changing fashion trends. The cost and duration of innovative project have a significant impact on the efficiency dimension, which has a significant value. This shows that these businesses place a high priority on time and cost control while creating creative projects. Given that these businesses often face competition from larger corporations, it’s apparent that they prioritize cost-effectiveness to remain competitive. Additionally, the rapid changes in fashion trends are another factor contributing to this focus on efficiency. In an industry characterized by fast-changing trends, organizations need to develop products that can quickly adapt to these shifts and endure in the marketplace for short-term periods. Table 5 displays the results of the hypotheses testing in the study, which further elucidate these dynamics.

https://doi.org/10.1371/journal.pone.0304729.t005

Table 5 demonstrates a positive and significant correlation between organizational learning motivation and innovation performance. According to the standards set by the study [ 40 ], the T-values which exceeded 1.96, indicates that the coefficients are resilient.

6. Discussion

These findings of the study confirm the Hypothesis 1, according to which firms perform more innovatively when organizational learning is made easier. Earlier studies [ 35 , 47 , 53 – 55 ] highlight the crucial role of learning in helping firms to attain agility and flexibility in the innovation process. In fact, a firm with excellent knowledge integration and acquisition skills is more likely to succeed in both product and process innovation, leading to better results in the creation of new goods. A company is likely to do well in terms of product and process innovation if it can successfully incorporate new information into its current knowledge base through a variety of techniques. Simply put, an organization’s performance in innovation is likely to be more impressive the higher its capacity for organizational learning. Organizational learning motivation encourages employees to seek out new knowledge and skills, which can stimulate creativity and innovative thinking. When employees are motivated to learn and explore new ideas, they are more likely to come up with innovative solutions to problems. A strong learning culture within an organization promotes knowledge sharing among employees. When employees are motivated to learn from each other, they are more likely to share their knowledge and experiences, leading to a more innovative and collaborative work environment. It also helps employees to develop a mindset that is open to change and new ways of doing things. This adaptability is crucial for innovation, as it allows organizations to respond effectively to changing market conditions and emerging trends [ 47 ]. Learning motivation encourages employees to continuously improve their skills and knowledge. This focus on continuous improvement can lead to incremental innovations that enhance organizational performance over time. A culture of learning and experimentation encourages employees to take risks and try out new ideas. This willingness to experiment is essential for innovation, as it allows organizations to test new concepts and approaches without fear of failure [ 32 ]. Organizations that prioritize learning and development tend to have higher levels of employee engagement and satisfaction [ 42 ]. Engaged and satisfied employees are more likely to be innovative and contribute positively to organizational performance. Overall, the positive relationship between organizational learning motivation and innovative performance highlights the importance of creating a learning culture within an organization [ 31 ]. By fostering a culture that values learning, organizations can drive innovation and improve their overall performance.

The findings for Hypothesis 2, states that innovation performance influences organizational performance with a favorable and significant relationship. These results underline the standing of innovation in improving organizational enactment and lend credence to the view that innovation is a major factor in an organization’s long-term success. Many studies have looked at the connection between innovation and performance, and they regularly show that there is an advantageous relationship. For example, studies [ 9 , 30 , 56 – 59 ] have demonstrated that innovation contributes to increased organizational performance, highlighting the importance of innovation in achieving positive organizational outcomes. The aspiration of firms to improve their organizational performance and obtain a reasonable edge drives the adoption of innovations [ 60 – 62 ]. Companies recognize that the extent to which they prioritize innovation corresponds with their ability to secure additional competitive advantages and expand their market share. Innovations serve as a pivotal factor for SMEs to establish a strong market status and, consequently, to bolster their marketplace presence and influence [ 31 , 63 – 65 ]. SMEs that excel in organizational learning are better equipped to discern market events and trends. Consequently, these learning organizations tend to be more adaptable and swift in their responses to new challenges compared to their competitors. This agility allows them to maintain competitive advantages over the long term [ 18 , 66 – 68 ].

It can be argued that innovation performance directly contributes to a company’s competitive advantage. Organizations that consistently innovate are able to differentiate themselves from competitors, attract customers, and capture market share. This can lead to increased revenue and profitability, which are key components of organizational performance [ 46 ]. Innovation often leads to improvements in productivity and efficiency. New technologies, processes, or products developed through innovation can help organizations streamline their operations, reduce costs, and increase output. This can result in higher levels of organizational performance as measured by metrics such as return on investment (ROI) and operational efficiency [ 64 ]. Innovation can open up new markets and business opportunities for organizations. By developing new products or services that meet the needs of previously untapped customer segments, organizations can expand their market reach and grow their business. This can have a positive impact on organizational performance by increasing market share and revenue [ 35 ]. Organizations that are known for innovation often enjoy a strong reputation in the marketplace. This can lead to increased customer loyalty, positive brand perception, and a competitive edge. A strong reputation can contribute to organizational performance by attracting top talent, fostering partnerships, and enhancing shareholder value [ 49 ]. Innovation can help organizations manage risk by diversifying their product or service offerings and revenue streams. By continually innovating, organizations can reduce their dependence on a single product or market, making them more resilient to economic downturns or industry disruptions. Organizations that prioritize innovation are more likely to achieve sustainable growth and success in the long run.

There is a positive correlation between the learning motivation of organizations and their performance. As a result, the findings also support Hypothesis 3, which states that organizational learning characteristics have a favorable impact on overall performance of firms. Organizational learning motivation is shown to be correlated with organizational performance [ 69 , 70 ]. But it is important to preserve in mind that innovation is a proven factor in determining how well a business performs [ 30 , 71 ]. It is possible to infer that innovation mediates the link between knowledge and organizational performance. In other words, the advantages of organizational learning may be realized through the innovation process, which will ultimately affect organizational performance. To put it another way, organizational learning motivation affects innovation performance, which in turn affects organizational performance [ 1 , 72 ]. This demonstrates the intricacy of the connections between organizational learning, advancement, and performance, which can differ between and within organizations and in different circumstances. In the long run, learning is necessary for greater performance [ 43 , 73 ]. As a result, organizational learning is frequently seen as a key component of success within a corporation. Moreover, it is emphasized that the ability to learn faster than one’s rivals might be a source of long-term competitive advantage [ 27 , 31 , 74 ].

The earlier study not only highlights the positive influence of organizational knowledge on performance but also emphasizes the arbitrating role of innovation in this association. Several studies propose that organizational learning equips a company with the capabilities needed to enhance innovation, and that revolution, in turn, has optimistic effect on overall performance [ 34 , 48 , 75 , 76 ]. Therefore, organizations that prioritize innovations should also promote organizational learning, as this can help optimize the effect of innovative performance on overall organizational performance. This underscores the interconnectedness of learning, innovation, and organizational success [ 49 – 51 , 77 ]. The outcomes of this investigation support the notion that organizational learning capability is essential for fostering creativity. SMEs should therefore emphasize and improve their organizational learning procedures if they want to advance their enactment through innovation [ 52 , 78 ]. This finding is especially important for smaller businesses and those operating in extremely dynamic and chaotic situations. For long-term success and competitiveness in such environments, the capacity to learn, adapt, and innovate becomes even more essential. The performance of the surveyed organizations was positively impacted by the elements that support organizational learning [ 53 ]. It is obvious that having a strong capacity for learning is essential for innovation and, in turn, enhances organizational success. These findings offer valuable insights to managers, particularly within the context of SMEs, by emphasizing the importance of incorporating displays of organizational learning ability into their supervision tools. This enables the effective implementation of conditions that promote learning within organizations, ultimately enhancing their innovative capacity and overall performance [ 54 , 79 , 80 ].

7. Implications

7.1. theoretical implications.

Theoretical implications of this research contribute to several key areas of social learning theory, goal setting theory, and organizational theory. This research deepens the understanding of these theories explaining the relationship between learning motivation and organizational performance within the context of firms. It provides theoretical insights into how individual-level factors, such as motivation, influence broader organizational outcomes, shedding light on the mechanisms through which employee behaviors and attitudes impact organizational effectiveness. The research has implications for human resource management practices related to employee motivation, training, and development. By identifying the factors that drive learning motivation and their impact on performance and innovative climate, organizations can develop more effective strategies for recruiting, retaining, and motivating employees, as well as designing training and development programs that align with organizational goals. The research also contributes to the literature on innovation management by highlighting the importance of learning motivation in fostering an innovative climate within firms. The research also extends theoretical frameworks of organizational learning by examining how learning motivation influences organizational performance and innovative climate. It contributes to our understanding of the dynamics of learning within organizations, including the mechanisms through which learning motivation drives knowledge acquisition, sharing, and application, as well as the factors that facilitate or inhibit a culture of continuous learning and improvement.

7.2. Practical implications

The findings of this study provide some useful insights for managers of SMEs. It underlines the significance of concentrating on the elements that support organizational learning since these elements both directly and indirectly affect both innovation and organizational success. Within the company, it is indispensable to have a broad-mindedness for vagueness, hesitation, and mistakes. The results emphasize how important it is to listen to fresh ideas and comments from staff members. Innovation is a crucial requirement for survival and ongoing success in the cutthroat atmosphere. Therefore, in order to succeed in this competitive corporate environment, managers need actively promote a culture of learning and innovation. The "Dialogue" component stands out as having the greatest influence on organizational learning. Improving communication is essential for improving knowledge sharing inside the organization. By using cross-functional work teams, managers may formally establish procedures to encourage the exchange of best practices between departments and among employees. Additionally, managers can support original and imaginative methods for problem solving. Promoting the acquisition of new information is vital for SMEs. This may be done by encouraging staff members to routinely attend fairs and exhibitions by highlighting the benefits of networking, learning about new technologies and trends, and gaining insights into competitors, which will help them to acquire fresh perspectives and encounter new things outside of the organization. SMEs can provide financial support for registration fees, travel, and accommodation to make it easier for staff to attend these events. Encourage staff who attend these events to share their insights and learning with the rest of the team through presentations, reports, or informal discussions. Attending fairs and exhibitions exposes staff to new products, technologies, and trends in the industry, which can stimulate innovation and new ideas within the organization. These events provide opportunities to network with industry peers, potential partners, and suppliers, which can lead to collaborations and business opportunities. Attending these events can contribute to the professional development of staff, enhancing their knowledge and skills, which can benefit the organization. By staying informed about the latest industry developments, SMEs can gain a competitive edge over rivals who may not be as well-informed. Incorporating these techniques and fostering a culture of open communication and information sharing may promote organizational learning and, as a result, lead to increased innovation and performance in SMEs.

7.3. Limitations and future research

Despite the study’s strict adherence to the recommended methodology, there are a few limitations that should be considered while analyzing the results. The research focused exclusively on SMEs located in China, potentially limiting the generalizability of the findings. Relying on a single respondent as the primary data source may introduce bias, and employing a social desirability scale could provide deeper insights into responses. It is advised that future studies should examine contingency elements that affect organizational effectiveness and creativity. Studies might also look on the differences in innovation across the industrial and service industries. Additionally, longitudinal research should be taken into consideration in order to evaluate how organizational performance and learning capabilities change over time. The relationship between learning capacity and performance over time may be supported by longitudinal data, and one component of this relationship is an examination of the relationships between financial and non-financial performances.

8. Conclusion

The purpose of this study was to explore the relation among organizational learning motivation, overall organizational performance and innovative performance of SMEs. The findings demonstrate that organizational learning motivation influence the organizational performance in context of innovations. The link between organizational learning and innovation performance demonstrates that learning is the basis for the creation of new products and processes since these innovations are impacted by factors that foster the learning process inside these SMEs. This highlights how essential organizational learning is to encouraging innovation, which may therefore have a positive impact on a company’s success.

The results of the study provide insightful theoretical information and may inspire more investigation in the area. The work advances the evaluation of learning capacities by showing important theoretical implications that are not readily observable. Additionally, by examining the connections between the organizational learning, innovations, and performance within a single model and using units that have been verified in global contexts, this study is an addition to the body of literature. This paper offers empirical support for these linkages, demonstrating their significance and beneficial nature, particularly for SMEs in China. This is especially significant in the empirical research of this field, which makes this study an important addition to our knowledge of organizational dynamics and performance in such settings.

The fast paced nature of the fashion sector supports an innovative culture. The ongoing testing of novel strategies for more effective management and product development is encouraged by this culture. It forces businesses to embrace this cutting-edge viewpoint, which increases their openness to implementing novel practices and technology. The industry’s dedication to innovation is driven by its need to remain competitive and adaptable in the ever-changing fashion landscape.

Supporting information

https://doi.org/10.1371/journal.pone.0304729.s001

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The Relationship Between “Job Satisfaction” and “Job Performance”: A Meta-analysis

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• Published: 24 August 2021
• Volume 23 , pages 21–42, ( 2022 )

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• Ali Katebi 1 ,
• Mohammad Hossain HajiZadeh 1 ,
• Ali Bordbar 1 &
• Amir Masoud Salehi 1  

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The purpose of this meta-analytic research is to obtain a clear and unified result for the relationship between job satisfaction and job performance, as previous research has shown contradictions in this regard. A total of 913 articles in both English and Persian languages were obtained from four databases, and finally, 113 articles with 123 independent data were selected and analyzed. The random-effects model was adopted based on results, and the analysis resulted a medium, positive, and significant relationship between job performance and job satisfaction ( r  = 0.339; 95% CI = 0.303 to 0.374; P  = 0.000). Finally, the country of India was identified as a moderator variable. The publication, language, selection, and citation biases have been examined in this study. Increasing and improving the job performance of employees have always been an important issue for organizations. The results of this study can be useful for managers in different industries, especially for Indian professionals in both public and private sectors, to better plan and manage the satisfaction and the performance of their employees. Also, Indian scholars can use these results to localize the global research in this regard.

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Acknowledgements

We would like to express our special thanks and gratitude to prof. Gholamreza Asadollahfardi for sharing his pearls of wisdom and experience with us to improve this research. We are immensely grateful to him for his comments on an earlier version of the manuscript. His insightful comments and suggestions have truly shined a light on our path and helped us to achieve better and brighter intuition.

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Ali Katebi, Mohammad Hossain HajiZadeh, Ali Bordbar & Amir Masoud Salehi

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Katebi, A., HajiZadeh, M.H., Bordbar, A. et al. The Relationship Between “Job Satisfaction” and “Job Performance”: A Meta-analysis. Glob J Flex Syst Manag 23 , 21–42 (2022). https://doi.org/10.1007/s40171-021-00280-y

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Received : 22 September 2020

Accepted : 25 June 2021

Published : 24 August 2021

Issue Date : March 2022

DOI : https://doi.org/10.1007/s40171-021-00280-y

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