research brief objectives

Educational resources and simple solutions for your research journey

What Are Research Objectives and How to Write Them (with Examples)

Table of Contents

Introduction

Research is at the center of everything researchers do, and setting clear, well-defined research objectives plays a pivotal role in guiding scholars toward their desired outcomes. Research papers are essential instruments for researchers to effectively communicate their work. Among the many sections that constitute a research paper, the introduction plays a key role in providing a background and setting the context. 1 Research objectives, which define the aims of the study, are usually stated in the introduction. Every study has a research question that the authors are trying to answer, and the objective is an active statement about how the study will answer this research question. These objectives help guide the development and design of the study and steer the research in the appropriate direction; if this is not clearly defined, a project can fail!

Research studies have a research question, research hypothesis, and one or more research objectives. A research question is what a study aims to answer, and a research hypothesis is a predictive statement about the relationship between two or more variables, which the study sets out to prove or disprove. Objectives are specific, measurable goals that the study aims to achieve. The difference between these three is illustrated by the following example:

• Research question : How does low-intensity pulsed ultrasound (LIPUS) compare with a placebo device in managing the symptoms of skeletally mature patients with patellar tendinopathy?
• Research hypothesis : Pain levels are reduced in patients who receive daily active-LIPUS (treatment) for 12 weeks compared with individuals who receive inactive-LIPUS (placebo).
• Research objective : To investigate the clinical efficacy of LIPUS in the management of patellar tendinopathy symptoms.

This article discusses the importance of clear, well-thought out objectives and suggests methods to write them clearly.

What is the introduction in research papers?

Research objectives are usually included in the introduction section. This section is the first that the readers will read so it is essential that it conveys the subject matter appropriately and is well written to create a good first impression. A good introduction sets the tone of the paper and clearly outlines the contents so that the readers get a quick snapshot of what to expect.

A good introduction should aim to: 2,3

• Indicate the main subject area, its importance, and cite previous literature on the subject
• Define the gap(s) in existing research, ask a research question, and state the objectives
• Announce the present research and outline its novelty and significance
• Avoid repeating the Abstract, providing unnecessary information, and claiming novelty without accurate supporting information.

Why are research objectives important?

Objectives can help you stay focused and steer your research in the required direction. They help define and limit the scope of your research, which is important to efficiently manage your resources and time. The objectives help to create and maintain the overall structure, and specify two main things—the variables and the methods of quantifying the variables.

A good research objective:

• defines the scope of the study
• gives direction to the research
• helps maintain focus and avoid diversions from the topic
• minimizes wastage of resources like time, money, and energy

Types of research objectives

Research objectives can be broadly classified into general and specific objectives . 4 General objectives state what the research expects to achieve overall while specific objectives break this down into smaller, logically connected parts, each of which addresses various parts of the research problem. General objectives are the main goals of the study and are usually fewer in number while specific objectives are more in number because they address several aspects of the research problem.

Example (general objective): To investigate the factors influencing the financial performance of firms listed in the New York Stock Exchange market.

Example (specific objective): To assess the influence of firm size on the financial performance of firms listed in the New York Stock Exchange market.

In addition to this broad classification, research objectives can be grouped into several categories depending on the research problem, as given in Table 1.

Table 1: Types of research objectives

Characteristics of research objectives

Research objectives must start with the word “To” because this helps readers identify the objective in the absence of headings and appropriate sectioning in research papers. 5,6

• A good objective is SMART (mostly applicable to specific objectives):
• Specific—clear about the what, why, when, and how
• Measurable—identifies the main variables of the study and quantifies the targets
• Achievable—attainable using the available time and resources
• Realistic—accurately addresses the scope of the problem
• Time-bound—identifies the time in which each step will be completed
• Research objectives clarify the purpose of research.
• They help understand the relationship and dissimilarities between variables.
• They provide a direction that helps the research to reach a definite conclusion.

How to write research objectives?

Research objectives can be written using the following steps: 7

• State your main research question clearly and concisely.
• Describe the ultimate goal of your study, which is similar to the research question but states the intended outcomes more definitively.
• Divide this main goal into subcategories to develop your objectives.
• Limit the number of objectives (1-2 general; 3-4 specific)
• Assess each objective using the SMART
• Start each objective with an action verb like assess, compare, determine, evaluate, etc., which makes the research appear more actionable.
• Use specific language without making the sentence data heavy.
• The most common section to add the objectives is the introduction and after the problem statement.
• Add the objectives to the abstract (if there is one).
• State the general objective first, followed by the specific objectives.

Formulating research objectives

Formulating research objectives has the following five steps, which could help researchers develop a clear objective: 8

• Identify the research problem.
• Review past studies on subjects similar to your problem statement, that is, studies that use similar methods, variables, etc.
• Identify the research gaps the current study should cover based on your literature review. These gaps could be theoretical, methodological, or conceptual.
• Define the research question(s) based on the gaps identified.
• Revise/relate the research problem based on the defined research question and the gaps identified. This is to confirm that there is an actual need for a study on the subject based on the gaps in literature.
• Identify and write the general and specific objectives.
• Incorporate the objectives into the study.

Advantages of research objectives

Adding clear research objectives has the following advantages: 4,8

• Maintains the focus and direction of the research
• Optimizes allocation of resources with minimal wastage
• Acts as a foundation for defining appropriate research questions and hypotheses
• Provides measurable outcomes that can help evaluate the success of the research
• Determines the feasibility of the research by helping to assess the availability of required resources
• Ensures relevance of the study to the subject and its contribution to existing literature

Disadvantages of research objectives

Research objectives also have few disadvantages, as listed below: 8

• Absence of clearly defined objectives can lead to ambiguity in the research process
• Unintentional bias could affect the validity and accuracy of the research findings

Key takeaways

• Research objectives are concise statements that describe what the research is aiming to achieve.
• They define the scope and direction of the research and maintain focus.
• The objectives should be SMART—specific, measurable, achievable, realistic, and time-bound.
• Clear research objectives help avoid collection of data or resources not required for the study.
• Well-formulated specific objectives help develop the overall research methodology, including data collection, analysis, interpretation, and utilization.
• Research objectives should cover all aspects of the problem statement in a coherent way.
• They should be clearly stated using action verbs.

Frequently asked questions on research objectives

Q: what’s the difference between research objectives and aims 9.

A: Research aims are statements that reflect the broad goal(s) of the study and outline the general direction of the research. They are not specific but clearly define the focus of the study.

Example: This research aims to explore employee experiences of digital transformation in retail HR.

Research objectives focus on the action to be taken to achieve the aims. They make the aims more practical and should be specific and actionable.

Example: To observe the retail HR employees throughout the digital transformation.

Q: What are the examples of research objectives, both general and specific?

A: Here are a few examples of research objectives:

• To identify the antiviral chemical constituents in Mumbukura gitoniensis (general)
• To carry out solvent extraction of dried flowers of Mumbukura gitoniensis and isolate the constituents. (specific)
• To determine the antiviral activity of each of the isolated compounds. (specific)
• To examine the extent, range, and method of coral reef rehabilitation projects in five shallow reef areas adjacent to popular tourist destinations in the Philippines.
• To investigate species richness of mammal communities in five protected areas over the past 20 years.
• To evaluate the potential application of AI techniques for estimating best-corrected visual acuity from fundus photographs with and without ancillary information.
• To investigate whether sport influences psychological parameters in the personality of asthmatic children.

Q: How do I develop research objectives?

A: Developing research objectives begins with defining the problem statement clearly, as illustrated by Figure 1. Objectives specify how the research question will be answered and they determine what is to be measured to test the hypothesis.

Q: Are research objectives measurable?

A: The word “measurable” implies that something is quantifiable. In terms of research objectives, this means that the source and method of collecting data are identified and that all these aspects are feasible for the research. Some metrics can be created to measure your progress toward achieving your objectives.

Q: Can research objectives change during the study?

A: Revising research objectives during the study is acceptable in situations when the selected methodology is not progressing toward achieving the objective, or if there are challenges pertaining to resources, etc. One thing to keep in mind is the time and resources you would have to complete your research after revising the objectives. Thus, as long as your problem statement and hypotheses are unchanged, minor revisions to the research objectives are acceptable.

Q: What is the difference between research questions and research objectives? 10

Q: Are research objectives the same as hypotheses?

A: No, hypotheses are predictive theories that are expressed in general terms. Research objectives, which are more specific, are developed from hypotheses and aim to test them. A hypothesis can be tested using several methods and each method will have different objectives because the methodology to be used could be different. A hypothesis is developed based on observation and reasoning; it is a calculated prediction about why a particular phenomenon is occurring. To test this prediction, different research objectives are formulated. Here’s a simple example of both a research hypothesis and research objective.

Research hypothesis : Employees who arrive at work earlier are more productive.

Research objective : To assess whether employees who arrive at work earlier are more productive.

To summarize, research objectives are an important part of research studies and should be written clearly to effectively communicate your research. We hope this article has given you a brief insight into the importance of using clearly defined research objectives and how to formulate them.

• Farrugia P, Petrisor BA, Farrokhyar F, Bhandari M. Practical tips for surgical research: Research questions, hypotheses and objectives. Can J Surg. 2010 Aug;53(4):278-81.
• Abbadia J. How to write an introduction for a research paper. Mind the Graph website. Accessed June 14, 2023. https://mindthegraph.com/blog/how-to-write-an-introduction-for-a-research-paper/
• Writing a scientific paper: Introduction. UCI libraries website. Accessed June 15, 2023. https://guides.lib.uci.edu/c.php?g=334338&p=2249903
• Research objectives—Types, examples and writing guide. Researchmethod.net website. Accessed June 17, 2023. https://researchmethod.net/research-objectives/#:~:text=They%20provide%20a%20clear%20direction,track%20and%20achieve%20their%20goals .
• Bartle P. SMART Characteristics of good objectives. Community empowerment collective website. Accessed June 16, 2023. https://cec.vcn.bc.ca/cmp/modules/pd-smar.htm
• Research objectives. Studyprobe website. Accessed June 18, 2023. https://www.studyprobe.in/2022/08/research-objectives.html
• Corredor F. How to write objectives in a research paper. wikiHow website. Accessed June 18, 2023. https://www.wikihow.com/Write-Objectives-in-a-Research-Proposal
• Research objectives: Definition, types, characteristics, advantages. AccountingNest website. Accessed June 15, 2023. https://www.accountingnest.com/articles/research/research-objectives
• Phair D., Shaeffer A. Research aims, objectives & questions. GradCoach website. Accessed June 20, 2023. https://gradcoach.com/research-aims-objectives-questions/
• Understanding the difference between research questions and objectives. Accessed June 21, 2023. https://board.researchersjob.com/blog/research-questions-and-objectives

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7 Essential Steps: How to Write a Research Brief That Gets Results

• Author Survey Point Team
• Published February 17, 2024

In this blog, we’ll explore seven essential steps to learn how to write a research brief that not only guides your project but also resonates with your audience. Research briefs are the unsung heroes of successful projects. Whether you’re a seasoned researcher or a newbie, crafting a well-structured brief can significantly impact the quality of your work.

Crafting a research brief that yields results is crucial. Explore the seven essential steps to write an effective research brief, ensuring success in your projects. Learn from experts and avoid common pitfalls.

Embarking on a research journey requires a well-crafted roadmap. A research brief serves as the compass, guiding you through the intricate terrain of data and insights. In this article, we will explore the seven essential steps to create a research brief that not only meets but exceeds expectations, ensuring the desired results.

Table of Contents

The Importance of Research Briefs

Why Research Briefs Matter

Research briefs are the cornerstone of successful projects. They set the tone, define objectives, and guide researchers toward meaningful outcomes. A well-structured brief not only saves time but also ensures the collected data aligns with the project goals.

How to Write a Research Brief: Understanding Your Objective

Defining Clear Research Goals

The first step in creating a research brief is understanding the project’s objective. Clearly define what you aim to achieve, ensuring every subsequent decision aligns with this overarching goal. Clarity at this stage is paramount.

Target Audience Analysis

Identifying and Understanding Your Audience

Knowing your audience is key to effective communication. Dive deep into demographic details, preferences, and behaviors. Tailor your research brief to resonate with the intended audience, enhancing its impact.

Crafting a Clear Research Question

Formulating Effective Research Queries

A well-defined research question is the compass that guides your entire project. Craft a question that is clear, concise, and directly aligns with your objectives. This foundational step ensures focused and purposeful research.

Literature Review

Building a Solid Foundation

Before venturing into uncharted territories, review existing literature. This not only provides valuable insights but also prevents redundancy. Acknowledge the work of others and identify gaps your research can fill.

Research Methodology

Choosing the Right Approach

Selecting the appropriate research methodology is pivotal. Whether qualitative or quantitative, the chosen approach should align with your objectives. Justify your choice, considering the nature of your research question.

How to Write a Research Brief: Data Collection

Ensuring Quality Information

Collecting data is where the rubber meets the road. Implement a robust data collection strategy, ensuring the information gathered is relevant, accurate, and aligns with your research question. Quality over quantity is the mantra.

Analysis and Interpretation

Extracting Meaningful Insights

Analysis is the heart of research. Interpret the collected data, drawing meaningful conclusions. Your insights should directly contribute to answering your research question and, consequently, achieving your objective.

Crafting a Compelling Title

Making Your Research Brief Stand Out

A captivating title is the first impression your research brief makes. It should be concise, intriguing, and reflective of the study’s essence. Crafting a compelling title sets the stage for your audience’s engagement.

The Power of Effective Communication

Conveying Your Message Clearly

Beyond the data, effective communication is crucial. Present your findings in a clear, concise manner. Utilize visuals, charts, and graphs to enhance understanding. Make your research brief accessible to a broad audience.

Common Pitfalls to Avoid

Mistakes That Can Derail Your Research

Avoiding common pitfalls is as important as following the right steps. Identify and steer clear of potential pitfalls that could compromise the integrity and effectiveness of your research brief. Learn from others’ mistakes to enhance your own success.

Real-life Success Stories

Learnings from Notable Research Briefs

Drawing inspiration from successful research briefs can provide valuable insights. Explore real-life success stories, understand the strategies employed, and apply these lessons to elevate the impact of your own research briefs.

How to Write a Research Brief: FAQ

Can I write multiple research questions? Certainly, but ensure they all align with your main objective. Quality over quantity is crucial in research.

How do I choose between qualitative and quantitative methods? Consider the nature of your research question. Qualitative methods delve into depth, while quantitative methods focus on breadth.

Is a literature review necessary for all research briefs? Yes, a literature review establishes the context for your research and prevents duplication of efforts.

How do I make my title captivating? A captivating title is concise, intriguing, and reflective of your study’s essence. Use language that sparks curiosity.

What are common pitfalls in research briefs? Common pitfalls include unclear objectives, biased data collection, and inadequate analysis. Be vigilant to avoid these pitfalls.

Can I use the same research methodology for every project? Adapt your research methodology to align with each project’s unique objectives. There’s no one-size-fits-all approach.

Wrapping Up the Research Brief Journey In conclusion, crafting a research brief that gets results requires a strategic approach. By following the seven essential steps outlined in this article, you can navigate the complexities of research with confidence. Remember, a well-prepared brief not only guides your journey but ensures the destination is one of success.

Survey Point Team

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How to write an effective research brief

Whether you’re launching a simple survey or planning a large-scale project the quality of your brief will hugely impact on the value you get from the research. While it can take a little time and effort creating a research brief, it will undoubtedly be time well spent – getting you better results and return on your investment and saving you valuable resources on further clarification. At best, a poor brief will be a time drain on you and your team. At worst, the findings will fail to meet your objectives, costing you time and money.

We’ve seen a lot of research briefs over the years. Some of which have been well thought through and clear, helping us prepare a detailed proposal and deliver an effective project and subsequent results. And others which have been not so good, lacking clarity or detail.

Using this experience, we’ve put together a ‘how to’ guide on writing an effective research brief, to help you ensure success on your next project.

1. Preparation is key

As with any project, before you start it’s crucial you think through what you want and need to deliver. Here are some things you should consider:

• Why are you conducting the research? What exactly are you looking to understand?
• Who are you looking to understand better? Who do you need to speak to answer your research questions?
• Who are your internal stakeholders? Have you discussed the project needs with the people in your organisation who will use the findings or who are invested in the research?
• How will the findings be used?
• When do you need the findings?
• Have you agreed a budget with either your procurement team, or the relevant person in your organisation?

2. Be clear on your objectives

This is one of the most important parts of your brief to convey to the reader what you want out of the project and ensure you get results which deliver.

Projects should have around three or four overarching aims which set out what the project ultimately wants to achieve.

These might be things like:

• Assess the impact of……
• Examine views of…..
• Evaluate the effectiveness of….

In addition to project objectives, you should also include the key questions you want the research to answer. These should support you in meeting the aims of the research.

For example, if the project aim is to assess the impact of an intervention, your research questions might include:

• Who did the intervention target?
• What did the project deliver?
• What elements were successful, and why?
• What were the main enablers and barriers?

3. Remember your audience

Research agencies or organisations who will be responding to your brief might not know anything about your business. So, make sure you include enough background information in your brief to enable them to understand your needs and deliver effectively. And avoid use of jargon or acronyms which could lead to errors or confusion.

4. Structure your research brief

Before you start to populate your brief it’s worth considering all the information and sections you need to include, to structure your thinking and ensure you don’t miss anything important.

This might include some, or all, of the following:

• Background info
• Introduction
• Aims and objectives
• Research Question(s)
• Issues / Risks
• Methodology
• Timing and Outputs
• Project Management

5. Make it thorough, yet succinct

While it’s crucial to include all the relevant information to enable bidders to respond effectively, no one wants to read reams and reams of information. To avoid the key information getting lost in the details use annexes to add supplementary information which could be useful.

6. Consider how prescriptive you want to be on the methodology

The extent to which you want to specify the methodology will depend on the project you aim to deliver. There are benefits and risks to being overly prescriptive or offering free reign. If you outline in precise detail how you want the research to be conducted, you will hamper any original ideas from those invited to tender and might limit the impact on the research. Whereas, if you’re less prescriptive, allowing room for creativity, you risk not getting the project or results you want, or receiving proposals on a scale which you can’t resource.

Generally, it is useful to allow those invited to tender some scope to develop the methodology they propose to use. Exceptions might be where previous work has to be very precisely replicated or some other very precise commitment about the nature of findings has been given to stakeholders.

7. Define your timelines

As a minimum, you need to include when you want the project to start and end. But you should also include the timetable for procurement. When planning this, don’t underestimate the time and resource needed to run a procurement exercise. Make sure your evaluators are available when you need them and have enough time blocked out in their diary.

You’ll likely also want to include milestones for when you expect outputs to be delivered, such as deadlines for a draft report (providing opportunity for review and feedback) and the final report; allowing sufficient time between the two to enable your stakeholders to consult, for you to feedback and for the contractor to revise the report.

8. Set expectations on cost

You will most likely have budgetary constraints, with a figure for what you are prepared to spend. To save you and your bidders time, and to set realistic expectations, you should include an indication within your brief. This will prevent you receiving proposals which are way out of the ballpark; enable bidders to plan a project which delivers on (or at least close to) budget; and will prevent any nasty surprises, further down the line.

By following these tips you’ll be well on your way to creating an effective research brief which delivers on time and on budget.

If you’d like more guidance download our “step-by-step” guide, which includes a template and information for what to include in each section to ensure success.

Download the guide now.

Research Aims, Objectives & Questions

The “Golden Thread” Explained Simply (+ Examples)

By: David Phair (PhD) and Alexandra Shaeffer (PhD) | June 2022

The research aims , objectives and research questions (collectively called the “golden thread”) are arguably the most important thing you need to get right when you’re crafting a research proposal , dissertation or thesis . We receive questions almost every day about this “holy trinity” of research and there’s certainly a lot of confusion out there, so we’ve crafted this post to help you navigate your way through the fog.

Overview: The Golden Thread

• What is the golden thread
• What are research aims ( examples )
• What are research objectives ( examples )
• What are research questions ( examples )
• The importance of alignment in the golden thread

What is the “golden thread”?  

The golden thread simply refers to the collective research aims , research objectives , and research questions for any given project (i.e., a dissertation, thesis, or research paper ). These three elements are bundled together because it’s extremely important that they align with each other, and that the entire research project aligns with them.

Importantly, the golden thread needs to weave its way through the entirety of any research project , from start to end. In other words, it needs to be very clearly defined right at the beginning of the project (the topic ideation and proposal stage) and it needs to inform almost every decision throughout the rest of the project. For example, your research design and methodology will be heavily influenced by the golden thread (we’ll explain this in more detail later), as well as your literature review.

The research aims, objectives and research questions (the golden thread) define the focus and scope ( the delimitations ) of your research project. In other words, they help ringfence your dissertation or thesis to a relatively narrow domain, so that you can “go deep” and really dig into a specific problem or opportunity. They also help keep you on track , as they act as a litmus test for relevance. In other words, if you’re ever unsure whether to include something in your document, simply ask yourself the question, “does this contribute toward my research aims, objectives or questions?”. If it doesn’t, chances are you can drop it.

Alright, enough of the fluffy, conceptual stuff. Let’s get down to business and look at what exactly the research aims, objectives and questions are and outline a few examples to bring these concepts to life.

Research Aims: What are they?

Simply put, the research aim(s) is a statement that reflects the broad overarching goal (s) of the research project. Research aims are fairly high-level (low resolution) as they outline the general direction of the research and what it’s trying to achieve .

Research Aims: Examples  

True to the name, research aims usually start with the wording “this research aims to…”, “this research seeks to…”, and so on. For example:

“This research aims to explore employee experiences of digital transformation in retail HR.”   “This study sets out to assess the interaction between student support and self-care on well-being in engineering graduate students”  

As you can see, these research aims provide a high-level description of what the study is about and what it seeks to achieve. They’re not hyper-specific or action-oriented, but they’re clear about what the study’s focus is and what is being investigated.

Need a helping hand?

Research Objectives: What are they?

The research objectives take the research aims and make them more practical and actionable . In other words, the research objectives showcase the steps that the researcher will take to achieve the research aims.

The research objectives need to be far more specific (higher resolution) and actionable than the research aims. In fact, it’s always a good idea to craft your research objectives using the “SMART” criteria. In other words, they should be specific, measurable, achievable, relevant and time-bound”.

Research Objectives: Examples  

Let’s look at two examples of research objectives. We’ll stick with the topic and research aims we mentioned previously.  

For the digital transformation topic:

To observe the retail HR employees throughout the digital transformation. To assess employee perceptions of digital transformation in retail HR. To identify the barriers and facilitators of digital transformation in retail HR.

And for the student wellness topic:

To determine whether student self-care predicts the well-being score of engineering graduate students. To determine whether student support predicts the well-being score of engineering students. To assess the interaction between student self-care and student support when predicting well-being in engineering graduate students.

  As you can see, these research objectives clearly align with the previously mentioned research aims and effectively translate the low-resolution aims into (comparatively) higher-resolution objectives and action points . They give the research project a clear focus and present something that resembles a research-based “to-do” list.

Research Questions: What are they?

Finally, we arrive at the all-important research questions. The research questions are, as the name suggests, the key questions that your study will seek to answer . Simply put, they are the core purpose of your dissertation, thesis, or research project. You’ll present them at the beginning of your document (either in the introduction chapter or literature review chapter) and you’ll answer them at the end of your document (typically in the discussion and conclusion chapters).  

The research questions will be the driving force throughout the research process. For example, in the literature review chapter, you’ll assess the relevance of any given resource based on whether it helps you move towards answering your research questions. Similarly, your methodology and research design will be heavily influenced by the nature of your research questions. For instance, research questions that are exploratory in nature will usually make use of a qualitative approach, whereas questions that relate to measurement or relationship testing will make use of a quantitative approach.  

Let’s look at some examples of research questions to make this more tangible.

Research Questions: Examples  

Again, we’ll stick with the research aims and research objectives we mentioned previously.  

For the digital transformation topic (which would be qualitative in nature):

How do employees perceive digital transformation in retail HR? What are the barriers and facilitators of digital transformation in retail HR?  

And for the student wellness topic (which would be quantitative in nature):

Does student self-care predict the well-being scores of engineering graduate students? Does student support predict the well-being scores of engineering students? Do student self-care and student support interact when predicting well-being in engineering graduate students?  

You’ll probably notice that there’s quite a formulaic approach to this. In other words, the research questions are basically the research objectives “converted” into question format. While that is true most of the time, it’s not always the case. For example, the first research objective for the digital transformation topic was more or less a step on the path toward the other objectives, and as such, it didn’t warrant its own research question.  

So, don’t rush your research questions and sloppily reword your objectives as questions. Carefully think about what exactly you’re trying to achieve (i.e. your research aim) and the objectives you’ve set out, then craft a set of well-aligned research questions . Also, keep in mind that this can be a somewhat iterative process , where you go back and tweak research objectives and aims to ensure tight alignment throughout the golden thread.

The importance of strong alignment 

Alignment is the keyword here and we have to stress its importance . Simply put, you need to make sure that there is a very tight alignment between all three pieces of the golden thread. If your research aims and research questions don’t align, for example, your project will be pulling in different directions and will lack focus . This is a common problem students face and can cause many headaches (and tears), so be warned.

Take the time to carefully craft your research aims, objectives and research questions before you run off down the research path. Ideally, get your research supervisor/advisor to review and comment on your golden thread before you invest significant time into your project, and certainly before you start collecting data .  

Recap: The golden thread

In this post, we unpacked the golden thread of research, consisting of the research aims , research objectives and research questions . You can jump back to any section using the links below.

As always, feel free to leave a comment below – we always love to hear from you. Also, if you’re interested in 1-on-1 support, take a look at our private coaching service here.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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39 Comments

Thank you very much for your great effort put. As an Undergraduate taking Demographic Research & Methodology, I’ve been trying so hard to understand clearly what is a Research Question, Research Aim and the Objectives in a research and the relationship between them etc. But as for now I’m thankful that you’ve solved my problem.

Well appreciated. This has helped me greatly in doing my dissertation.

An so delighted with this wonderful information thank you a lot.

so impressive i have benefited a lot looking forward to learn more on research.

I am very happy to have carefully gone through this well researched article.

Infact,I used to be phobia about anything research, because of my poor understanding of the concepts.

Now,I get to know that my research question is the same as my research objective(s) rephrased in question format.

I please I would need a follow up on the subject,as I intends to join the team of researchers. Thanks once again.

Thanks so much. This was really helpful.

I know you pepole have tried to break things into more understandable and easy format. And God bless you. Keep it up

i found this document so useful towards my study in research methods. thanks so much.

This is my 2nd read topic in your course and I should commend the simplified explanations of each part. I’m beginning to understand and absorb the use of each part of a dissertation/thesis. I’ll keep on reading your free course and might be able to avail the training course! Kudos!

Thank you! Better put that my lecture and helped to easily understand the basics which I feel often get brushed over when beginning dissertation work.

This is quite helpful. I like how the Golden thread has been explained and the needed alignment.

This is quite helpful. I really appreciate!

The article made it simple for researcher students to differentiate between three concepts.

Very innovative and educational in approach to conducting research.

I am very impressed with all these terminology, as I am a fresh student for post graduate, I am highly guided and I promised to continue making consultation when the need arise. Thanks a lot.

A very helpful piece. thanks, I really appreciate it .

Very well explained, and it might be helpful to many people like me.

Wish i had found this (and other) resource(s) at the beginning of my PhD journey… not in my writing up year… 😩 Anyways… just a quick question as i’m having some issues ordering my “golden thread”…. does it matter in what order you mention them? i.e., is it always first aims, then objectives, and finally the questions? or can you first mention the research questions and then the aims and objectives?

Thank you for a very simple explanation that builds upon the concepts in a very logical manner. Just prior to this, I read the research hypothesis article, which was equally very good. This met my primary objective.

My secondary objective was to understand the difference between research questions and research hypothesis, and in which context to use which one. However, I am still not clear on this. Can you kindly please guide?

In research, a research question is a clear and specific inquiry that the researcher wants to answer, while a research hypothesis is a tentative statement or prediction about the relationship between variables or the expected outcome of the study. Research questions are broader and guide the overall study, while hypotheses are specific and testable statements used in quantitative research. Research questions identify the problem, while hypotheses provide a focus for testing in the study.

Exactly what I need in this research journey, I look forward to more of your coaching videos.

This helped a lot. Thanks so much for the effort put into explaining it.

What data source in writing dissertation/Thesis requires?

What is data source covers when writing dessertation/thesis

This is quite useful thanks

I’m excited and thankful. I got so much value which will help me progress in my thesis.

where are the locations of the reserch statement, research objective and research question in a reserach paper? Can you write an ouline that defines their places in the researh paper?

Very helpful and important tips on Aims, Objectives and Questions.

Thank you so much for making research aim, research objectives and research question so clear. This will be helpful to me as i continue with my thesis.

Thanks much for this content. I learned a lot. And I am inspired to learn more. I am still struggling with my preparation for dissertation outline/proposal. But I consistently follow contents and tutorials and the new FB of GRAD Coach. Hope to really become confident in writing my dissertation and successfully defend it.

As a researcher and lecturer, I find splitting research goals into research aims, objectives, and questions is unnecessarily bureaucratic and confusing for students. For most biomedical research projects, including ‘real research’, 1-3 research questions will suffice (numbers may differ by discipline).

Awesome! Very important resources and presented in an informative way to easily understand the golden thread. Indeed, thank you so much.

Well explained

The blog article on research aims, objectives, and questions by Grad Coach is a clear and insightful guide that aligns with my experiences in academic research. The article effectively breaks down the often complex concepts of research aims and objectives, providing a straightforward and accessible explanation. Drawing from my own research endeavors, I appreciate the practical tips offered, such as the need for specificity and clarity when formulating research questions. The article serves as a valuable resource for students and researchers, offering a concise roadmap for crafting well-defined research goals and objectives. Whether you’re a novice or an experienced researcher, this article provides practical insights that contribute to the foundational aspects of a successful research endeavor.

A great thanks for you. it is really amazing explanation. I grasp a lot and one step up to research knowledge.

I really found these tips helpful. Thank you very much Grad Coach.

I found this article helpful. Thanks for sharing this.

thank you so much, the explanation and examples are really helpful

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Handy Tips To Write A Clear Research Objectives With Examples

Introduction.

Research objectives play a crucial role in any research study. They provide a clear direction and purpose for the research, guiding the researcher in their investigation. Understanding research objectives is essential for conducting a successful study and achieving meaningful results.

In this comprehensive review, we will delve into the definition of research objectives, exploring their characteristics, types, and examples. We will also discuss the relationship between research objectives and research questions, as well as provide insights into how to write effective research objectives. Additionally, we will examine the role of research objectives in research methodology and highlight the importance of them in a study. By the end of this review, you will have a comprehensive understanding of research objectives and their significance in the research process.

Definition of Research Objectives: What Are They?

A research objective is defined as a clear and concise statement that outlines the specific goals and aims of a research study. These objectives are designed to be specific, measurable, achievable, relevant, and time-bound (SMART), ensuring they provide a structured pathway to accomplishing the intended outcomes of the project. Each objective serves as a foundational element that summarizes the purpose of your study, guiding the research activities and helping to measure progress toward the study’s goals. Additionally, research objectives are integral components of the research framework , establishing a clear direction that aligns with the overall research questions and hypotheses. This alignment helps to ensure that the study remains focused and relevant, facilitating the systematic collection, analysis, and interpretation of data.

Characteristics of Effective Research Objectives

Characteristics of research objectives include:

• Specific: Research objectives should be clear about the what, why, when, and how of the study.
• Measurable: Research objectives should identify the main variables of the study that can be measured or observed.
• Relevant: Research objectives should be relevant to the research topic and contribute to the overall understanding of the subject.
• Feasible: Research objectives should be achievable within the constraints of time, resources, and expertise available.
• Logical: Research objectives should follow a logical sequence and build upon each other to achieve the overall research goal.
• Observable: Research objectives should be observable or measurable in order to assess the progress and success of the research project.
• Unambiguous: Research objectives should be clear and unambiguous, leaving no room for interpretation or confusion.
• Measurable: Research objectives should be measurable, allowing for the collection of data and analysis of results.

By incorporating these characteristics into research objectives, researchers can ensure that their study is focused, achievable, and contributes to the body of knowledge in their field.

Types of Research Objectives

Research objective can be broadly classified into general and specific objectives. General objectives are broad statements that define the overall purpose of the research. They provide a broad direction for the study and help in setting the context. Specific objectives, on the other hand, are detailed objectives that describe what will be researched during the study. They are more focused and provide specific outcomes that the researcher aims to achieve. Specific objectives are derived from the general objectives and help in breaking down the research into smaller, manageable parts. The specific objectives should be clear, measurable, and achievable. They should be designed in a way that allows the researcher to answer the research questions and address the research problem.

In addition to general and specific objectives, research objective can also be categorized as descriptive or analytical objectives. Descriptive objectives focus on describing the characteristics or phenomena of a particular subject or population. They involve surveys, observations, and data collection to provide a detailed understanding of the subject. Analytical objectives, on the other hand, aim to analyze the relationships between variables or factors. They involve data analysis and interpretation to gain insights and draw conclusions.

Both descriptive and analytical objectives are important in research as they serve different purposes and contribute to a comprehensive understanding of the research topic.

Examples of Research Objectives

Here are some examples of research objectives in different fields:

1. Objective: To identify key characteristics and styles of Renaissance art.

This objective focuses on exploring the characteristics and styles of art during the Renaissance period. The research may involve analyzing various artworks, studying historical documents, and interviewing experts in the field.

2. Objective: To analyze modern art trends and their impact on society.

This objective aims to examine the current trends in modern art and understand how they influence society. The research may involve analyzing artworks, conducting surveys or interviews with artists and art enthusiasts, and studying the social and cultural implications of modern art.

3. Objective: To investigate the effects of exercise on mental health.

This objective focuses on studying the relationship between exercise and mental health. The research may involve conducting experiments or surveys to assess the impact of exercise on factors such as stress, anxiety, and depression.

4. Objective: To explore the factors influencing consumer purchasing decisions in the fashion industry.

This objective aims to understand the various factors that influence consumers’ purchasing decisions in the fashion industry. The research may involve conducting surveys, analyzing consumer behavior data, and studying the impact of marketing strategies on consumer choices.

5. Objective: To examine the effectiveness of a new drug in treating a specific medical condition.

This objective focuses on evaluating the effectiveness of a newly developed drug in treating a particular medical condition. The research may involve conducting clinical trials, analyzing patient data, and comparing the outcomes of the new drug with existing treatment options.

These examples demonstrate the diversity of research objectives across different disciplines. Each objective is specific, measurable, and achievable, providing a clear direction for the research study.

Aligning Research Objectives with Research Questions

Research objectives and research questions are essential components of a research project. Research objective describe what you intend your research project to accomplish. They summarize the approach and purpose of the project and provide a clear direction for the research. Research questions, on the other hand, are the starting point of any good research. They guide the overall direction of the research and help identify and focus on the research gaps .

The main difference between research questions and objectives is their form. Research questions are stated in a question form, while objectives are specific, measurable, and achievable goals that you aim to accomplish within a specified timeframe. Research questions are broad statements that provide a roadmap for the research, while objectives break down the research aim into smaller, actionable steps.

Research objectives and research questions work together to form the ‘golden thread’ of a research project. The research aim specifies what the study will answer, while the objectives and questions specify how the study will answer it. They provide a clear focus and scope for the research project, helping researchers stay on track and ensure that their study is meaningful and relevant.

When writing research objectives and questions, it is important to be clear, concise, and specific. Each objective or question should address a specific aspect of the research and contribute to the overall goal of the study. They should also be measurable, meaning that their achievement can be assessed and evaluated. Additionally, research objectives and questions should be achievable within the given timeframe and resources of the research project. By clearly defining the objectives and questions, researchers can effectively plan and execute their research, leading to valuable insights and contributions to the field.

Guidelines for Writing Clear Research Objectives

Writing research objective is a crucial step in any research project. The objectives provide a clear direction and purpose for the study, guiding the researcher in their data collection and analysis. Here are some tips on how to write effective research objective:

1. Be clear and specific

Research objective should be written in a clear and specific manner. Avoid vague or ambiguous language that can lead to confusion. Clearly state what you intend to achieve through your research.

2. Use action verbs

Start your research objective with action verbs that describe the desired outcome. Action verbs such as ‘investigate’, ‘analyze’, ‘compare’, ‘evaluate’, or ‘identify’ help to convey the purpose of the study.

3. Align with research questions or hypotheses

Ensure that your research objectives are aligned with your research questions or hypotheses. The objectives should address the main goals of your study and provide a framework for answering your research questions or testing your hypotheses.

4. Be realistic and achievable

Set research objectives that are realistic and achievable within the scope of your study. Consider the available resources, time constraints, and feasibility of your objectives. Unrealistic objectives can lead to frustration and hinder the progress of your research.

5. Consider the significance and relevance

Reflect on the significance and relevance of your research objectives. How will achieving these objectives contribute to the existing knowledge or address a gap in the literature? Ensure that your objectives have a clear purpose and value.

6. Seek feedback

It is beneficial to seek feedback on your research objectives from colleagues, mentors, or experts in your field. They can provide valuable insights and suggestions for improving the clarity and effectiveness of your objectives.

7. Revise and refine

Research objectives are not set in stone. As you progress in your research, you may need to revise and refine your objectives to align with new findings or changes in the research context. Regularly review and update your objectives to ensure they remain relevant and focused.

By following these tips, you can write research objectives that are clear, focused, and aligned with your research goals. Well-defined objectives will guide your research process and help you achieve meaningful outcomes.

The Role of Research Objectives in Research Methodology

Research objectives play a crucial role in the research methodology . In research methodology, research objectives are formulated based on the research questions or problem statement. These objectives help in defining the scope and focus of the study, ensuring that the research is conducted in a systematic and organized manner.

The research objectives in research methodology act as a roadmap for the research project. They help in identifying the key variables to be studied, determining the research design and methodology, and selecting the appropriate data collection methods .

Furthermore, research objectives in research methodology assist in evaluating the success of the study. By setting clear objectives, researchers can assess whether the desired outcomes have been achieved and determine the effectiveness of the research methods employed. It is important to note that research objectives in research methodology should be aligned with the overall research aim. They should address the specific aspects or components of the research aim and provide a framework for achieving the desired outcomes.

Understanding The Dynamic of Research Objectives in Your Study

The research objectives of a study play a crucial role in guiding the research process, ensuring that the study is focused, purposeful, and contributes to the advancement of knowledge in the field. It is important to note that the research objectives may evolve or change as the study progresses. As new information is gathered and analyzed, the researcher may need to revise the objectives to ensure that they remain relevant and achievable.

In summary, research objectives are essential components in writing an effective research paper . They provide a roadmap for the research process, guiding the researcher in their investigation and helping to ensure that the study is purposeful and meaningful. By understanding and effectively utilizing research objectives, researchers can enhance the quality and impact of their research endeavors.

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How to write a great qualitative research brief

It’s fast becoming the norm that clients come to us without a written brief. Sure, they know what they want to achieve, what their objectives are, but they don’t know how to write a qualitative research brief (or they’ve not got the time!).

I’m always the first to put my hands up and offer to help them write it. It takes the pressure off them and means that you are more immersed in the project, so it’s a win-win.

I’m going to share with you my thoughts on what makes a good qualitative research brief and why it’s so necessary to get it right (in case that isn’t obvious enough). Start with the wrong brief and you’re heading down the wrong path from the get-go. Not only will you set the wrong course, but you’ll probably cost the project incorrectly and even propose the wrong methods. There’s a handy briefing template you can download at the end of this blog that will help you focus on key points.

Before I dive into the specifics, here are three key things to consider:

Framing and re-framing

First and foremost, the brief frames the client’s problem or challenge, and it establishes the fundamental question(s) they want answering. More often than not, research briefs are framed through the lens of the business, when in fact, they should be through the lens of the consumer. Reframing is perhaps better to be done by the researcher/agency as they can see outside the business more readily than the client. The phrase, ‘wood for the trees’ is poignant.

Short and simple

Research briefs don’t need to be long and exhaustive. In fact, the shorter and more precise the better. This often shows the brief has been thought about and refined. A shorter brief also makes it easier for stakeholders of all kinds to ‘get it’.

Adopt the right tone

Like any written document that has its readers, a qualitative research brief needs to adopt the appropriate tone, be it a formal business one or a more relaxed consumer-friendly version. Most businesses are jam-packed with technical jargon so handle this with care and remove where possible so that everyone can be sure of being (and staying) on the same page.

OK, now to the details. Here’s what your qualitative research brief should include:

Provide a summary of the primary business the client is in, and clearly explain why the business exists, what its mission and vision are, and what the competitive set are. You should also look to include information about which markets the study should explore.

What research pre-exists and is shareable

We sometimes call this a ‘research amnesty’. It is vitally important we have sight of any pre-existing research so as not to duplicate any findings that already exist. No matter what form the research/insight is, throw it at us and we’ll read through it to create a detailed picture of the business/brand.

Research objectives

This is where you set about describing what the core research task is. For example, the research objective might be to find out what your customers think of your recently launched product or service. Set out specific research objectives to clarify the key questions you need to answer and the information you need to gather to address the challenge.

Now you’re starting to motor and get into the details around the questions that need to be answered, or the spaces you’re going to explore. Remember, qualitative research helps understand why people do what they do, so write the objectives through that lens and think about the behaviours, motivations, thoughts and feelings you want to understand.

Business objectives

Driving their research objective may be a more strategic business objective that is framed differently. Quite simply, it outlines why you are being asked to do this. For example, does the research support modifying a service or product or intended to deliver growth?

Stakeholder team

Which parties/departments (internal and/or external) will be involved with and have a vested interest in this research study. They might be a sponsor, collaborator or a third-party that needs an actionable outcome. Detail their requirements and comment on their level and method of involvement.

Target audience to research

Who do you need to talk to?

Are they current customers, lapsed customers or those of a competitor? Are demographics relevant, such as age, gender, income, occupation, location, company size, etc? Is social profiling relevant, or their personal attributes and proficiencies?

The target audience could include:

• Who you want researched and how many (sample size)?
• Source: Will the client be providing a customer list, or do you need to recommend the best way to source respondents such as panels, free-finding or social media?

Methodology

Based on the objectives, which qualitative research methods are best deployed and why. Are you proposing a combination of methods as is usually the case? Should the research be conducted face-to-face, by telephone or even online?

Consider internal milestones such as meetings and decision-making deadlines.

Timescale could include:

• Timescale for the procurement process, the start of the research and when you want the findings
• Whether you want to receive top-line findings in advance of the main findings
• Leaving time to receive a draft set of findings for you to review before receiving the final deliverables.

Do you have a specific research budget in mind, including incentives and recruitment?

Can you provide guidance on the available budget, even if it is only a ball-park figure?

Budget could include:

• An indication of available budget; stipulate whether or not this includes VAT.
• A breakdown of how recruitment and incentives.
• Payment terms (if standard)

Deliverables (what/how/when)

Do you want the findings in a written report format or as a presentation? You may want to have both or to have a meeting with us to discuss the findings.

Deliverables could include:

• Your preferred format for the findings — for example, a report in Word or a presentation in PowerPoint, hardcopy and/or electronic, etc
• Do you want the researcher to present the findings, either in-person or remotely?
• Is there anything else you expect the research team to provide?

If there are any pre-existing hunches, assumptions or hypotheses then now is a good time to share them with us. If they come out part-way through the project they may result in a re-brief and re-costing exercise, which is something to be avoided.

Materials the client will provide

Provide a detailed breakdown of the materials, assets and stimulus that the client will provide.

Examples might include:

• Visual brand identity assets
• Market reports/intelligence
• Information about competitors
• Stimulus materials
• Concepts and mockups

What does success look like?

Cast yourself into the future and imagine you are looking back at the successful project. What made it so successful, what was so good about it. Did it make you ‘famous’, if so why?

What does failure look like?

What are the failure factors of this project and what would team it unsuccessful? Another way to think about this would be to ask the question ‘Why might this project fail?’

Client contacts and roles

Who are the immediate client team responsible for running this project, including day-to-day contact details and email addresses. It’s also a good idea to address what time/input the client has to invest in the project as you may find they don’t want to be involved in the way you hope.

There you have it. There are of course more things to consider and more detail to add pending the size/scale/risk of the project, but hopefully, this will get you started. There are many mistakes you can make in executing qualitative research, this is just one. Here are a few others to be mindful of when it comes to online qualitative research and research communities.

If you need a briefing template you can download one of the ones we use here . Hope it helps!

If you have any questions, or have a brief you’d like help with…

Feel free to contact us .

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• Defining Research Objectives: How To  Write Them

Almost all industries use research for growth and development. Research objectives are how researchers ensure that their study has direction and makes a significant contribution to growing an industry or niche.

Research objectives provide a clear and concise statement of what the researcher wants to find out. As a researcher, you need to clearly outline and define research objectives to guide the research process and ensure that the study is relevant and generates the impact you want.

In this article, we will explore research objectives and how to leverage them to achieve successful research studies.

What Are Research Objectives?

Research objectives are what you want to achieve through your research study. They guide your research process and help you focus on the most important aspects of your topic.

You can also define the scope of your study and set realistic and attainable study goals with research objectives. For example, with clear research objectives, your study focuses on the specific goals you want to achieve and prevents you from spending time and resources collecting unnecessary data.

However, sticking to research objectives isn’t always easy, especially in broad or unconventional research. This is why most researchers follow the SMART criteria when defining their research objectives.

Understanding SMART Criteria in Research

Think of research objectives as a roadmap to achieving your research goals, with the SMART criteria as your navigator on the map.

SMART stands for Specific, Measurable, Achievable, Relevant, and Time-bound. These criteria help you ensure that your research objectives are clear, specific, realistic, meaningful, and time-bound.

Here’s a breakdown of the SMART Criteria:

Specific : Your research objectives should be clear: what do you want to achieve, why do you want to achieve it, and how do you plan to achieve it? Avoid vague or broad statements that don’t provide enough direction for your research.

Measurable : Your research objectives should have metrics that help you track your progress and measure your results. Also, ensure the metrics are measurable with data to verify them.

Achievable : Your research objectives should be within your research scope, timeframe, and budget. Also, set goals that are challenging but not impossible.

Relevant: Your research objectives should be in line with the goal and significance of your study. Also, ensure that the objectives address a specific issue or knowledge gap that is interesting and relevant to your industry or niche.

Time-bound : Your research objectives should have a specific deadline or timeframe for completion. This will help you carefully set a schedule for your research activities and milestones and monitor your study progress.

Characteristics of Effective Research Objectives

Clarity : Your objectives should be clear and unambiguous so that anyone who reads them can understand what you intend to do. Avoid vague or general terms that could be taken out of context.

Specificity : Your objectives should be specific and address the research questions that you have formulated. Do not use broad or narrow objectives as they may restrict your field of research or make your research irrelevant.

Measurability : Define your metrics with indicators or metrics that help you determine if you’ve accomplished your goals or not. This will ensure you are tracking the research progress and making interventions when needed.

Also, do use objectives that are subjective or based on personal opinions, as they may be difficult to accurately verify and measure.

Achievability : Your objectives should be realistic and attainable, given the resources and time available for your research project. You should set objectives that match your skills and capabilities, they can be difficult but not so hard that they are realistically unachievable.

For example, setting very difficult make you lose confidence, and abandon your research. Also, setting very simple objectives could demotivate you and prevent you from closing the knowledge gap or making significant contributions to your field with your research.

Relevance : Your objectives should be relevant to your research topic and contribute to the existing knowledge in your field. Avoid objectives that are unrelated or insignificant, as they may waste your time or resources.

Time-bound : Your objectives should be time-bound and specify when you will complete them. Have a realistic and flexible timeframe for achieving your objectives, and track your progress with it. 

Steps to Writing Research Objectives

Identify the research questions.

The first step in writing effective research objectives is to identify the research questions that you are trying to answer. Research questions help you narrow down your topic and identify the gaps or problems that you want to address with your research.

For example, if you are interested in the impact of technology on children’s development, your research questions could be:

• What is the relationship between technology use and academic performance among children?
• Are children who use technology more likely to do better in school than those who do not?
• What is the social and psychological impact of technology use on children?

Brainstorm Objectives

Once you have your research questions, you can brainstorm possible objectives that relate to them. Objectives are more specific than research questions, and they tell you what you want to achieve or learn in your research.

You can use verbs such as analyze, compare, evaluate, explore, investigate, etc. to express your objectives. Also, try to generate as many objectives as possible, without worrying about their quality or feasibility at this stage.

Prioritize Objectives

Once you’ve brainstormed your objectives, you’ll need to prioritize them based on their relevance and feasibility. Relevance is how relevant the objective is to your research topic and how well it fits into your overall research objective.

Feasibility is how realistic and feasible the objective is compared to the time, money, and expertise you have. You can create a matrix or ranking system to organize your objectives and pick the ones that matter the most.

Refine Objectives

The next step is to refine and revise your objectives to ensure clarity and specificity. Start by ensuring that your objectives are consistent and coherent with each other and with your research questions. 

Make Objectives SMART

A useful way to refine your objectives is to make them SMART, which stands for specific, measurable, achievable, relevant, and time-bound. 

• Specific : Objectives should clearly state what you hope to achieve.
• Measurable : They should be able to be quantified or evaluated.
• Achievable : realistic and within the scope of the research study.
• Relevant : They should be directly related to the research questions.
• Time-bound : specific timeframe for research completion.

Review and Finalize Objectives

The final step is to review your objectives for coherence and alignment with your research questions and aim. Ensure your objectives are logically connected and consistent with each other and with the purpose of your study.

You also need to check that your objectives are not too broad or too narrow, too easy or too hard, too many or too few. You can use a checklist or a rubric to evaluate your objectives and make modifications.

Examples of Well-Written Research Objectives

Example 1- Psychology

Research question: What are the effects of social media use on teenagers’ mental health?

Objective : To determine the relationship between the amount of time teenagers in the US spend on social media and their levels of anxiety and depression before and after using social media.

What Makes the Research Objective SMART?

The research objective is specific because it clearly states what the researcher hopes to achieve. It is measurable because it can be quantified by measuring the levels of anxiety and depression in teenagers. 

Also, the objective is achievable because the researcher can collect enough data to answer the research question. It is relevant because it is directly related to the research question. It is time-bound because it has a specific deadline for completion.

Example 2- Marketing

Research question : How can a company increase its brand awareness by 10%?

Objective : To develop a marketing strategy that will increase the company’s sales by 10% within the next quarter.

How Is this Research Objective SMART?

The research states what the researcher hopes to achieve ( Specific ). You can also measure the company’s reach before and after the marketing plan is implemented ( Measurable ).

The research objective is also achievable because you can develop a marketing plan that will increase awareness by 10% within the timeframe. The objective is directly related to the research question ( Relevant ). It is also time-bound because it has a specific deadline for completion.

Research objectives are a well-designed roadmap to completing and achieving your overall research goal. 

However, research goals are only effective if they are well-defined and backed up with the best practices such as the SMART criteria. Properly defining research objectives will help you plan and conduct your research project effectively and efficiently.

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• research goals
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• SMART research objectives
• Moradeke Owa

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• Aims and Objectives – A Guide for Academic Writing
• Doing a PhD

One of the most important aspects of a thesis, dissertation or research paper is the correct formulation of the aims and objectives. This is because your aims and objectives will establish the scope, depth and direction that your research will ultimately take. An effective set of aims and objectives will give your research focus and your reader clarity, with your aims indicating what is to be achieved, and your objectives indicating how it will be achieved.

Introduction

There is no getting away from the importance of the aims and objectives in determining the success of your research project. Unfortunately, however, it is an aspect that many students struggle with, and ultimately end up doing poorly. Given their importance, if you suspect that there is even the smallest possibility that you belong to this group of students, we strongly recommend you read this page in full.

This page describes what research aims and objectives are, how they differ from each other, how to write them correctly, and the common mistakes students make and how to avoid them. An example of a good aim and objectives from a past thesis has also been deconstructed to help your understanding.

What Are Aims and Objectives?

Research aims.

A research aim describes the main goal or the overarching purpose of your research project.

In doing so, it acts as a focal point for your research and provides your readers with clarity as to what your study is all about. Because of this, research aims are almost always located within its own subsection under the introduction section of a research document, regardless of whether it’s a thesis , a dissertation, or a research paper .

A research aim is usually formulated as a broad statement of the main goal of the research and can range in length from a single sentence to a short paragraph. Although the exact format may vary according to preference, they should all describe why your research is needed (i.e. the context), what it sets out to accomplish (the actual aim) and, briefly, how it intends to accomplish it (overview of your objectives).

To give an example, we have extracted the following research aim from a real PhD thesis:

Example of a Research Aim

The role of diametrical cup deformation as a factor to unsatisfactory implant performance has not been widely reported. The aim of this thesis was to gain an understanding of the diametrical deformation behaviour of acetabular cups and shells following impaction into the reamed acetabulum. The influence of a range of factors on deformation was investigated to ascertain if cup and shell deformation may be high enough to potentially contribute to early failure and high wear rates in metal-on-metal implants.

Note: Extracted with permission from thesis titled “T he Impact And Deformation Of Press-Fit Metal Acetabular Components ” produced by Dr H Hothi of previously Queen Mary University of London.

Research Objectives

Where a research aim specifies what your study will answer, research objectives specify how your study will answer it.

They divide your research aim into several smaller parts, each of which represents a key section of your research project. As a result, almost all research objectives take the form of a numbered list, with each item usually receiving its own chapter in a dissertation or thesis.

Following the example of the research aim shared above, here are it’s real research objectives as an example:

Example of a Research Objective

• Develop finite element models using explicit dynamics to mimic mallet blows during cup/shell insertion, initially using simplified experimentally validated foam models to represent the acetabulum.
• Investigate the number, velocity and position of impacts needed to insert a cup.
• Determine the relationship between the size of interference between the cup and cavity and deformation for different cup types.
• Investigate the influence of non-uniform cup support and varying the orientation of the component in the cavity on deformation.
• Examine the influence of errors during reaming of the acetabulum which introduce ovality to the cavity.
• Determine the relationship between changes in the geometry of the component and deformation for different cup designs.
• Develop three dimensional pelvis models with non-uniform bone material properties from a range of patients with varying bone quality.
• Use the key parameters that influence deformation, as identified in the foam models to determine the range of deformations that may occur clinically using the anatomic models and if these deformations are clinically significant.

It’s worth noting that researchers sometimes use research questions instead of research objectives, or in other cases both. From a high-level perspective, research questions and research objectives make the same statements, but just in different formats.

Taking the first three research objectives as an example, they can be restructured into research questions as follows:

Restructuring Research Objectives as Research Questions

• Can finite element models using simplified experimentally validated foam models to represent the acetabulum together with explicit dynamics be used to mimic mallet blows during cup/shell insertion?
• What is the number, velocity and position of impacts needed to insert a cup?
• What is the relationship between the size of interference between the cup and cavity and deformation for different cup types?

Difference Between Aims and Objectives

Hopefully the above explanations make clear the differences between aims and objectives, but to clarify:

• The research aim focus on what the research project is intended to achieve; research objectives focus on how the aim will be achieved.
• Research aims are relatively broad; research objectives are specific.
• Research aims focus on a project’s long-term outcomes; research objectives focus on its immediate, short-term outcomes.
• A research aim can be written in a single sentence or short paragraph; research objectives should be written as a numbered list.

How to Write Aims and Objectives

Before we discuss how to write a clear set of research aims and objectives, we should make it clear that there is no single way they must be written. Each researcher will approach their aims and objectives slightly differently, and often your supervisor will influence the formulation of yours on the basis of their own preferences.

Regardless, there are some basic principles that you should observe for good practice; these principles are described below.

Your aim should be made up of three parts that answer the below questions:

• Why is this research required?
• What is this research about?
• How are you going to do it?

The easiest way to achieve this would be to address each question in its own sentence, although it does not matter whether you combine them or write multiple sentences for each, the key is to address each one.

The first question, why , provides context to your research project, the second question, what , describes the aim of your research, and the last question, how , acts as an introduction to your objectives which will immediately follow.

Scroll through the image set below to see the ‘why, what and how’ associated with our research aim example.

Note: Your research aims need not be limited to one. Some individuals per to define one broad ‘overarching aim’ of a project and then adopt two or three specific research aims for their thesis or dissertation. Remember, however, that in order for your assessors to consider your research project complete, you will need to prove you have fulfilled all of the aims you set out to achieve. Therefore, while having more than one research aim is not necessarily disadvantageous, consider whether a single overarching one will do.

Research Objectives

Each of your research objectives should be SMART :

• Specific – is there any ambiguity in the action you are going to undertake, or is it focused and well-defined?
• Measurable – how will you measure progress and determine when you have achieved the action?
• Achievable – do you have the support, resources and facilities required to carry out the action?
• Relevant – is the action essential to the achievement of your research aim?
• Timebound – can you realistically complete the action in the available time alongside your other research tasks?

In addition to being SMART, your research objectives should start with a verb that helps communicate your intent. Common research verbs include:

Table of Research Verbs to Use in Aims and Objectives

Last, format your objectives into a numbered list. This is because when you write your thesis or dissertation, you will at times need to make reference to a specific research objective; structuring your research objectives in a numbered list will provide a clear way of doing this.

To bring all this together, let’s compare the first research objective in the previous example with the above guidance:

Checking Research Objective Example Against Recommended Approach

Research Objective:

1. Develop finite element models using explicit dynamics to mimic mallet blows during cup/shell insertion, initially using simplified experimentally validated foam models to represent the acetabulum.

Checking Against Recommended Approach:

Q: Is it specific? A: Yes, it is clear what the student intends to do (produce a finite element model), why they intend to do it (mimic cup/shell blows) and their parameters have been well-defined ( using simplified experimentally validated foam models to represent the acetabulum ).

Q: Is it measurable? A: Yes, it is clear that the research objective will be achieved once the finite element model is complete.

Q: Is it achievable? A: Yes, provided the student has access to a computer lab, modelling software and laboratory data.

Q: Is it relevant? A: Yes, mimicking impacts to a cup/shell is fundamental to the overall aim of understanding how they deform when impacted upon.

Q: Is it timebound? A: Yes, it is possible to create a limited-scope finite element model in a relatively short time, especially if you already have experience in modelling.

Q: Does it start with a verb? A: Yes, it starts with ‘develop’, which makes the intent of the objective immediately clear.

Q: Is it a numbered list? A: Yes, it is the first research objective in a list of eight.

Mistakes in Writing Research Aims and Objectives

1. making your research aim too broad.

Having a research aim too broad becomes very difficult to achieve. Normally, this occurs when a student develops their research aim before they have a good understanding of what they want to research. Remember that at the end of your project and during your viva defence , you will have to prove that you have achieved your research aims; if they are too broad, this will be an almost impossible task. In the early stages of your research project, your priority should be to narrow your study to a specific area. A good way to do this is to take the time to study existing literature, question their current approaches, findings and limitations, and consider whether there are any recurring gaps that could be investigated .

Note: Achieving a set of aims does not necessarily mean proving or disproving a theory or hypothesis, even if your research aim was to, but having done enough work to provide a useful and original insight into the principles that underlie your research aim.

2. Making Your Research Objectives Too Ambitious

Be realistic about what you can achieve in the time you have available. It is natural to want to set ambitious research objectives that require sophisticated data collection and analysis, but only completing this with six months before the end of your PhD registration period is not a worthwhile trade-off.

3. Formulating Repetitive Research Objectives

Each research objective should have its own purpose and distinct measurable outcome. To this effect, a common mistake is to form research objectives which have large amounts of overlap. This makes it difficult to determine when an objective is truly complete, and also presents challenges in estimating the duration of objectives when creating your project timeline. It also makes it difficult to structure your thesis into unique chapters, making it more challenging for you to write and for your audience to read.

Fortunately, this oversight can be easily avoided by using SMART objectives.

Hopefully, you now have a good idea of how to create an effective set of aims and objectives for your research project, whether it be a thesis, dissertation or research paper. While it may be tempting to dive directly into your research, spending time on getting your aims and objectives right will give your research clear direction. This won’t only reduce the likelihood of problems arising later down the line, but will also lead to a more thorough and coherent research project.

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Intelligence

How to structure a good research brief.

Like many other things in life,  you get out of a research project what you put into it.  The time you spend at the beginning of a project, thinking about  exactly  what you want to get from the research, is  crucial  and will reap you rewards when the end results are delivered.

A  written research brief  is a great tool to give the researcher/ agency a clear understanding of what is required from them during the research and what you hope to achieve from it. When writing a brief, there is quite a straightforward structure you can use to help shape your thinking…

Provide sufficient background information on your organisation and the context surrounding the proposed research project.

2. The ‘why’ before ‘how’

Include an understanding of ‘ why ’ the research is needed and what are the results going to be used for. This is one of the most important elements of a research brief. Planning  ‘how’  the research is going to be conducted  should not  be thought about until the  ‘why’  is delivered and fully understood.  (The ‘why’ will often even shape the ‘how’!)

3. Research objectives

Research objectives are  absolutely key  as they provide the foundations of an  effective research project . Take the time to think about  exactly  what you want to learn from the research and display this through  clear, well thought-out  research objectives. This will then result in a sound, actionable piece of research for your organisation.

4. Target audience

Give as much information as possible on the types of people you want to include within the research as well as any supporting information you may have about these people.  For example , the definition of any target groups, their preferred size, geographical distribution etc.

5. Budget and timings

It  may  feel uncomfortable at first but sharing your budget for research in the briefing document can save  a lot  of time and effort by ensuring that the researcher/ agency crafts a realistic approach to the project. Alongside this, knowing the timings for  when  the results are required may also have an impact on the method for the research so these should again be outlined in the initial brief.

6. Any other competitors  (if applicable)

Ensure you let the researcher/ agency know if the project is being submitted to more than one competitor and, if so, how many they will be competing with.  The Market Research Society  recommends approaching no more than  three or four  agencies for quotations. In addition, all of the researchers/ agencies should be treated equally, given the same information and their proposals for the project should not be shared with one another.

Following this devised framework will offer you a  solid  foundation for a successful research brief, ensuring you get what you need from the research and it provides you with as much benefit as possible.

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A good market research brief helps agencies lead successful projects. Learn what to include and how to write a detailed brief with our template guide.

A market research brief is a client document outlining all the relevant information that a research agency needs to understand the client’s specific research needs to propose the most suitable course of action.

A clear, informed brief will ensure the market researcher can deliver the most effective research possible. It also streamlines the project by reducing the need for back and forth between your company and the researcher. A good brief will leave no confusion and provide a meaningful framework for you and the researcher, maximising the accuracy and reliability of insights collected.

Start your project faster with our market research brief template!

In this article, we’ve broken down the key components of a well-written brief, with examples. Using this template guide, you can confidently equip the researcher with the right information to deliver exemplary research for your next project.

Business Background/ Project Background

This section of the brief introduces your company to the market researcher, giving them a more informed overview of your brand, product/service, and target market. You should provide all available context to ensure you and the researcher are on the same page with the project.

Relevant information to add in this section includes: company details, company mission/vision, industry status and trends, market performance history, competitive context, any existing research.

Business Objectives/ Marketing Objectives

Your business objectives/marketing objectives should answer why you are being asked to conduct the research. The researcher should be able to grasp the existing problems/issues your company is looking to address in the research.

For example, this could involve sales, competition, customer satisfaction, or product innovation, to name a few.

Research Objectives

Research objectives address the specific questions you would like the research to cover, including what insights you wish to gain. This is where you should detail what actions your company is planning to take based on the research you are commissioning.

Your research objective is one of the most important elements of your brief, as it dictates how your study will be conducted and the quality of results.

Target Market

Who will this research focus on? This is where you should state respondents’ demographic and profiling information, along with any pre-existing segments you want to target. Be specific, but also be aware that the more restrictive the criteria are, the higher the sample cost will be. Extensive limitations are also realistically harder to meet.

For example:

• Market: Canada
• Sample size: 200 – 1000
• Demographics: Household income of $150k and above a year
• Markets: Malaysia (priority), Thailand, Singapore
• Sample size: N=200 (Product Variant Selector) + N=500 (Conjoint)
• Demographics: 16 – 50 years old
• National representation: Age, gender and location
• Target definition: Bought electronics online in the past 12 months
• Reads on: 16 – 30-year olds vs. 31 – 50-year olds
• Market: South America
• Sample size: 1800
• Target definition: Main and joint grocery buyers
• 5 target groups: Income, urban/rural, age, family status, shopping frequency (divide each into 3 subgroups, e.g. low, medium, high).

Action Standards/ Decision Rules

Action standards outline which criteria will determine the decisions you make following research. These should detail specific numerical scores and any company benchmarks which need to be met in your research results for decision-making to go ahead. Clear and detailed action standards will allow you to make decisions faster and more confidently following research.

Nestlé’s 60/40 action standard which prioritises preference and nutrition, by aiming “to make products that achieve at least 60% consumer taste preference with the added ‘plus’ of nutritional advantage”.

Pricing is seen as credible by at least 40% of the target market.

Product has at least 50% acceptance from the target market.

Methodology

You should only include methodology if you are certain of the approach you want to take. If you do not know which methodology you should use, leave this section blank for agency recommendations.

Monadic test : Monadic testing introduces survey respondents to individual concepts, products in isolation. It is usually used in studies where independent findings for each stimulus are required, unlike in comparison testing, where several stimuli are tested side-by-side. Each product/concept is displayed and evaluated separately, providing more accurate and meaningful results for specific items.

Discrete choice modelling : Sometimes referred to as choice-based conjoint, discrete choice is a more robust technique consistent with random utility theory and has been proven to simulate customers’ actual behaviour in the marketplace. The output on relative importance of attributes and value by level is aligned to the output from conjoint analysis (partworth analysis).

Qualitative research : Qualitative forms of research focus on non-numerical and unstructured data, such as participant observation, direct observation, unstructured interviews, and case studies.

Quantitative research : Numbers and measurable forms of data make up quantitative research, focusing on ‘how many’, ‘how often’, and ‘how much’, e.g. conjoint analysis , MaxDiff , Gabor-Granger , Van Westendorp .

Deliverables

Deliverables should clearly outline project expectations – both from your company and the agency. This should cover who is responsible for everything required to undertake research, including survey inputs and outputs, materials, reporting, reviewing, and any additional requirements.

• PowerPoint presentation
• Crosstabs of data
• Raw datasets
• Excel simulator
• Online dashboard
• “Typing tool” for future research

Timing and Cost

Timing covers the due dates for key milestones of your research project, most importantly, for your preliminary and final reports. Cost should include your project budget, along with any potential additional costs/constraints.

Contacts and Responsibilities

This section states all stakeholders involved in the project, their role and responsibilities, and their contact details. You should ensure that these are easy to locate on your brief, for quick reference by the agency and easier communication.

Ready-to-use market research brief template with examples

Start your research project faster and get better results. Using this template, you can confidently equip the researcher with the right information to deliver exemplary research for your next project.

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The Importance Of Research Objectives

Imagine you’re a student planning a vacation in a foreign country. You’re on a tight budget and need to draw…

Imagine you’re a student planning a vacation in a foreign country. You’re on a tight budget and need to draw up a pocket-friendly plan. Where do you begin? The first step is to do your research.

Before that, you make a mental list of your objectives—finding reasonably-priced hotels, traveling safely and finding ways of communicating with someone back home. These objectives help you focus sharply during your research and be aware of the finer details of your trip.

More often than not, research is a part of our daily lives. Whether it’s to pick a restaurant for your next birthday dinner or to prepare a presentation at work, good research is the foundation of effective learning. Read on to understand the meaning, importance and examples of research objectives.

Why Do We Need Research?

What are the objectives of research, what goes into a research plan.

Research is a careful and detailed study of a particular problem or concern, using scientific methods. An in-depth analysis of information creates space for generating new questions, concepts and understandings. The main objective of research is to explore the unknown and unlock new possibilities. It’s an essential component of success.

Over the years, businesses have started emphasizing the need for research. You’ve probably noticed organizations hiring research managers and analysts. The primary purpose of business research is to determine the goals and opportunities of an organization. It’s critical in making business decisions and appropriately allocating available resources.

Here are a few benefits of research that’ll explain why it is a vital aspect of our professional lives:

Expands Your Knowledge Base

One of the greatest benefits of research is to learn and gain a deeper understanding. The deeper you dig into a topic, the more well-versed you are. Furthermore, research has the power to help you build on any personal experience you have on the subject.

Keeps You Up To Date

Research encourages you to discover the most recent information available. Updated information prevents you from falling behind and helps you present accurate information. You’re better equipped to develop ideas or talk about a topic when you’re armed with the latest inputs.

Builds Your Credibility

Research provides you with a good foundation upon which you can develop your thoughts and ideas. People take you more seriously when your suggestions are backed by research. You can speak with greater confidence because you know that the information is accurate.

Sparks Connections

Take any leading nonprofit organization, you’ll see how they have a strong research arm supported by real-life stories. Research also becomes the base upon which real-life connections and impact can be made. It even helps you communicate better with others and conveys why you’re pursuing something.

Encourages Curiosity

As we’ve already established, research is mostly about using existing information to create new ideas and opinions. In the process, it sparks curiosity as you’re encouraged to explore and gain deeper insights into a subject. Curiosity leads to higher levels of positivity and lower levels of anxiety.

Well-defined objectives of research are an essential component of successful research engagement. If you want to drive all aspects of your research methodology such as data collection, design, analysis and recommendation, you need to lay down the objectives of research methodology. In other words, the objectives of research should address the underlying purpose of investigation and analysis. It should outline the steps you’d take to achieve desirable outcomes. Research objectives help you stay focused and adjust your expectations as you progress.

The objectives of research should be closely related to the problem statement, giving way to specific and achievable goals. Here are the four types of research objectives for you to explore:

General Objective

Also known as secondary objectives, general objectives provide a detailed view of the aim of a study. In other words, you get a general overview of what you want to achieve by the end of your study. For example, if you want to study an organization’s contribution to environmental sustainability, your general objective could be: a study of sustainable practices and the use of renewable energy by the organization.

Specific Objectives

Specific objectives define the primary aim of the study. Typically, general objectives provide the foundation for identifying specific objectives. In other words, when general objectives are broken down into smaller and logically connected objectives, they’re known as specific objectives. They help define the who, what, why, when and how aspects of your project. Once you identify the main objective of research, it’s easier to develop and pursue a plan of action.

Let’s take the example of ‘a study of an organization’s contribution to environmental sustainability’ again. The specific objectives will look like this:

To determine through history how the organization has changed its practices and adopted new solutions

To assess how the new practices, technology and strategies will contribute to the overall effectiveness

Once you’ve identified the objectives of research, it’s time to organize your thoughts and streamline your research goals. Here are a few effective tips to develop a powerful research plan and improve your business performance.

Set SMART Goals

Your research objectives should be SMART—Specific, Measurable, Achievable, Realistic and Time-constrained. When you focus on utilizing available resources and setting realistic timeframes and milestones, it’s easier to prioritize objectives. Continuously track your progress and check whether you need to revise your expectations or targets. This way, you’re in greater control over the process.

Create A Plan

Create a plan that’ll help you select appropriate methods to collect accurate information. A well-structured plan allows you to use logical and creative approaches towards problem-solving. The complexity of information and your skills are bound to influence your plan, which is why you need to make room for flexibility. The availability of resources will also play a big role in influencing your decisions.

Collect And Collate

After you’ve created a plan for the research process, make a list of the data you’re going to collect and the methods you’ll use. Not only will it help make sense of your insights but also keep track of your approach. The information you collect should be:

Logical, rigorous and objective

Can be reproduced by other people working on the same subject

Free of errors and highlighting necessary details

Current and updated

Includes everything required to support your argument/suggestions

Analyze And Keep Ready

Data analysis is the most crucial part of the process and there are many ways in which the information can be utilized. Four types of data analysis are often seen in a professional environment. While they may be divided into separate categories, they’re linked to each other.

Descriptive Analysis:

The most commonly used data analysis, descriptive analysis simply summarizes past data. For example, Key Performance Indicators (KPIs) use descriptive analysis. It establishes certain benchmarks after studying how someone has been performing in the past.

Diagnostic Analysis:

The next step is to identify why something happened. Diagnostic analysis uses the information gathered through descriptive analysis and helps find the underlying causes of an outcome. For example, if a marketing initiative was successful, you deep-dive into the strategies that worked.

Predictive Analysis:

It attempts to answer ‘what’s likely to happen’. Predictive analysis makes use of past data to predict future outcomes. However, the accuracy of predictions depends on the quality of the data provided. Risk assessment is an ideal example of using predictive analysis.

Prescriptive Analysis: 

The most sought-after type of data analysis, prescriptive analysis combines the insights of all of the previous analyses. It’s a huge organizational commitment as it requires plenty of effort and resources. A great example of prescriptive analysis is Artificial Intelligence (AI), which consumes large amounts of data. You need to be prepared to commit to this type of analysis.

Review And Interpret

Once you’ve collected and collated your data, it’s time to review it and draw accurate conclusions. Here are a few ways to improve the review process:

Identify the fundamental issues, opportunities and problems and make note of recurring trends if any

Make a list of your insights and check which is the most or the least common. In short, keep track of the frequency of each insight

Conduct a SWOT analysis and identify the strengths, weaknesses, opportunities and threats

Write down your conclusions and recommendations of the research

When we think about research, we often associate it with academicians and students. but the truth is research is for everybody who is willing to learn and enhance their knowledge. If you want to master the art of strategically upgrading your knowledge, Harappa Education’s Learning Expertly course has all the answers. Not only will it help you look at things from a fresh perspective but also show you how to acquire new information with greater efficiency. The Growth Mindset framework will teach you how to believe in your abilities to grow and improve. The Learning Transfer framework will help you apply your learnings from one context to another. Begin the journey of tactful learning and self-improvement today!

Explore Harappa Diaries to learn more about topics related to the THINK Habit such as  Learning From Experience ,  Critical Thinking  & What is  Brainstorming  to think clearly and rationally.

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• Knowledge Base
• Starting the research process
• 10 Research Question Examples to Guide Your Research Project

10 Research Question Examples to Guide your Research Project

Published on October 30, 2022 by Shona McCombes . Revised on October 19, 2023.

The research question is one of the most important parts of your research paper , thesis or dissertation . It’s important to spend some time assessing and refining your question before you get started.

The exact form of your question will depend on a few things, such as the length of your project, the type of research you’re conducting, the topic , and the research problem . However, all research questions should be focused, specific, and relevant to a timely social or scholarly issue.

Once you’ve read our guide on how to write a research question , you can use these examples to craft your own.

Note that the design of your research question can depend on what method you are pursuing. Here are a few options for qualitative, quantitative, and statistical research questions.

Other interesting articles

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

Methodology

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

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McCombes, S. (2023, October 19). 10 Research Question Examples to Guide your Research Project. Scribbr. Retrieved June 20, 2024, from https://www.scribbr.com/research-process/research-question-examples/

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Research brief: Meaning, Components, Importance & Ways to Prepare

June 12, 2023 | By Hitesh Bhasin | Filed Under: Marketing

Have you ever faced a situation where a researcher has not exactly given the results that you require? Have you ever discussed research as what you want precisely and been disappointed to find that there is a disparity in your expectation and the outcomes? This is because of a failure in communication , that is particular an insufficient brief.

This is where we exactly wish to discuss research brief.

A research brief is a statement that comes from the sponsor, who sets the objectives and background. This is to enable the researcher to plan the research and conduct an appropriate study on it. Research Brief can be as good as a market research study and is very important to a researcher.

It provides good insight and influences on the choice of methodology to be adopted in the research. It also provides an objective to which the project links itself.

It is a short and non-technical summary of a discussion paper that is purely intended for decision-makers with a concentration on the paper’s policy-relevant findings.

Table of Contents

Components of a Research Brief

Some sponsors deliver the brief orally by developing many detail points at the time of initial discussion with the researcher. On the other hand, the brief can also be completely thought through and committed to a paper.

This is very important when many research agencies need to submit proposals. Whether the research brief is oral or written, it should pay attention to the following points:

• Problem Background – This is a short record of the events which has actually led to the study. This provides an insight into the researcher a better viewpoint and understanding of the objective of the project.
• Problem Description – The researcher requires details in depth to perform the research. When the scope of the research is described properly, the research process gets easier. It becomes helpful for the sponsor to monitor the progress of the research.
• Market Analysis – The researcher needs to know the geographical areas of the research. Hence this should be part of the research brief.
• Objective Statement – The object of the researcher should be put statement. The researcher should gather the details from the sponsor and then provide a view of what has to be achieved.
• Time and Budget – The research brief should mention the time and budget constraints of the research.

Importance of Research Brief

Now, why is research brief important? It is like the way you set a foundation for a building; research brief provides a strong foundation for the research process.

Writing a research brief is important to the success of any market research project. However, it can be difficult to craft the perfect brief that meets the necessity of both the client and the researcher but eventually leads to the desired outcomes.

It helps a researcher to identify a problem to be researched, the exact background of the problem, the required details to address the problem, time and budget constraints within which the research is supposed to be designed.

Example of Research Brief

Keeping the above points in mind, let us take a small example of the way to write a market research brief.

To write a market research brief, it clarifies the research requirement and also makes sure that the ideas are well articulated. It helps to write a better research proposal , conduct user research, and achieve the desired outcome.

Background:

Describe the problem that is required to solve. Include applicable background and the challenge during the research.

Business and Project Objectives:

Explain the business objectives. For example: to increase sales /profit. Try to be specific as you can.

Also, describe the purpose of research and the expected outcomes. What is the decision that you require to make?

Market Objectives:

Market research objective typically follows from the above two objectives. Hence you will need to summarise the aim and information of the research. This will help to mention the questions required for answering.

Stakeholders:

Here, you will need to consider the participant who will sign-off and act on the research outcomes listed.

Research Methods, scope, sample, and guidelines:

Here, you will explain what is required. This will help you to focus on what is important and also have a piece of knowledge of the research investment. Here, more focus is given on the scope of the work and type of research . The inputs and the sample are also analyzed.

Research outcomes:

Here, you will require to define the delivery part of the research.

Ways to prepare Research Brief

Having discussed the basic of research brief, the following points will give you a brief idea of the ways to prepare yourself to write an effective research brief.

• Start with a summary of the current situation. Also, define in clear words as what you are already aware of. It would be more useful if you could include more details on your thought about the responsibility for the project on you and the research agency.
• After a summary, set up the business and research objectives . For business objectives, you need to mention the overall strategy and what is the importance of the current research. For research objectives, list the issues and topics that are likely to discover. List the problems to solve. Based on the research agency design, define clearly the business and research objectives. Having a clear objective will help you to assess the quality and also focus on the research agency’s report.
• Next, you may suggest about the ways about data collection . You can decide on a suitable research methodology that you think will be best fit the project.
• List what the outcomes of the project and the deliverables are. Like for example, you might just want to advise on survey design . For this, statistically robust data would be ideal. Or sometimes, you might write a full report with data, interpretation, recommendations, etc. Whatever it is, be clear as what is required. Suggest a timetable and mention the deadline to receive proposals and other deliverables.

Research Brief Template

Given below the template for research brief:

Research Brief: Project Name

#1 background.

In this area, give the background of the research brief.

#2 Business objectives

In this area, define the business objectives. Ideally, for a better understanding and readability, it would be good if the points are bulleted.

#3 Marketing objectives

In this area, type your marketing objectives. In case you have any other kind of objectives apart from marketing, you could change the section title.

In this area, define the research target here. Here, name all the target groups that will be a part of the research and the reason for it. Capture any other applicable details of the target group .

In this area, mention the Budget information. Mentioning a range of budget is fine. Also, indicate an upper limit in case you have any.

In this area, mention the timeline of the research. The approximate time as when this work would be over. Also, when can you provide the final analysis?

#6 Deliverables

In this area, mention the report requirements. For example, whether a detail report is required or just a presentation.

#7 Contact information

In this area, mention the contact information for questions or clarification. It could be Client company name or Individual name, title, e-mail id, phone number, and mailing address.

Liked this post? Check out the complete series on Market research

Related posts:

• What is Brand Brief? Components of Brand Brief and Examples
• Causal Research – Meaning, Explanation, Examples, Components
• What is a Design Brief and How to Write it in 9 Easy Steps?
• Qualitative Research: Meaning, and Features of Qualitative Research
• Advertising Message – Definition, Meaning, Importance and Components
• Research Ethics – Importance and Principles of Ethics in Research
• Market Space – Definition, Meaning, Characteristics, Components
• Sales Agreement – Meaning, Components and Samples
• How to Write Research Proposal? Research Proposal Format
• 7 Key Differences between Research Method and Research Methodology

About Hitesh Bhasin

Hitesh Bhasin is the CEO of Marketing91 and has over a decade of experience in the marketing field. He is an accomplished author of thousands of insightful articles, including in-depth analyses of brands and companies. Holding an MBA in Marketing, Hitesh manages several offline ventures, where he applies all the concepts of Marketing that he writes about.

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Research objective

A research objective, also known as a goal or an objective, is a sentence or question that summarizes the purpose of your study or test. In other words, it’s an idea you want to understand deeper by performing research. Objectives should be the driving force behind every task you assign and each question that you ask. These objectives should be centered on specific features or processes of your product. By having a solid understanding of the information you need when running your usability study, you’ll be able to better stay on track throughout your development process.

How do I write a research objective? 

Before you write your objective, you need a problem statement , which you can source from your support team and the frequent customer issues they encounter, negative customer reviews , or feedback from social media. From there, your objective might look like, “Do people find value in this new product idea?” or “How do our competitors describe their offerings compared to us?”

Many UX researchers agree that the more specific the objectives, the easier it is to write tasks and questions. Subsequently, it’ll also be easier to extract answers later on in the analysis. In addition, your objective doesn’t have to spark one angle alone; it could have the potential to inspire multiple test directions. For instance, take this research objective, “I want to understand and resolve the barriers customers face when looking for answers about products and services on our website.”

From this one objective, potential study angles could be: 

• Content quality: Learn whether the FAQ questions anticipate users’ needs and if the answers are sufficiently detailed and directive. 
• FAQ accessibility: Can customers easily find the FAQ section? What access points should we consider?
• FAQ concept test: Is the design approach we’re considering for the proposed redesign understandable? What can we do to optimize it?

As you can see, the above objective can be branched out to address content, usability, and design. For further inspiration, collaborate with the product’s stakeholders. You can start the conversation at a high level by determining what features or processes they want test participants to review, like a navigation menu or website messaging. 

And before you put a stamp of approval on a research objective, ask for feedback from your team. Two researchers could write very different test plans when an objective is unclear or misaligned. For example, one researcher may hone in on design while another focuses on usability. Meanwhile, another may keep their objective more broad while another writes on that’s more detailed. And while the findings from either case would be insightful, they might not match up with what the team actually needs to learn. So to summarize, start the process with a problem statement, loop in stakeholders early if applicable, and ensure your team is aligned on your objective(s). 

When should I write a research objective—and how should they be prioritized? 

Writing and refining your research objective should come after you have a clear problem statement and before you decide on a research method and test plan to execute your study. 

After you’ve written a rough draft of your research objective, the ink might not even be dry when stakeholders could get involved by offering you an abundance of objectives. To figure out what to tackle first, ask your stakeholders to prioritize their needs. This step could happen via email or in a meeting, but another method could be to list out all of the possible objectives in a Google form and have everyone rearrange the list into their ideal order. 

And if stakeholders haven’t handed you a list of objectives and you’re on your own for brainstorming and prioritizing, opt for the objective that’s tied to a KPI—from increasing website conversions to driving more daily active users in your SaaS product. This will help you size up the relevance and impact your research has on the metrics your business is measuring. The added benefit here is when you’re asked about the impact of that research, you can tie back your ROI calculations to tangible and relatable objectives that you know the business is tracking.

How many research objectives do I need? 

The type of research you do will depend on the stage of product development you’re in. Each stage of development has different research objectives—and different questions that need to be answered. And once you’ve decided on a problem statement, you could either have one or multiple research objectives that tie back to that statement. Typically, this means that you’ll want to select one to three objectives; the less you have, the more manageable your test (and timeline) will be. 

For more, the UserTesting template library is a great place to start for common questions that you need answers to or inspiration for your research objective.

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• Research Note
• Open access
• Published: 20 June 2024

FDG-PET/CT-based respiration-gated lung segmentation and quantification of lung inflammation in COPD patients

• Ayse Dudu Altintas Dogan   ORCID: orcid.org/0000-0001-6953-9969 1 , 2 , 3 , 4 ,
• Thomas Quist Christensen 5 , 8 ,
• Torben Tranborg Jensen 2 ,
• Claus Bogh Juhl 2 , 6 ,
• Ole Hilberg 3 , 4 ,
• Else-Marie Bladbjerg 3 , 7 &
• Søren Hess 3 , 5 , 9 , 10  

BMC Research Notes volume  17 , Article number:  170 ( 2024 ) Cite this article

Metrics details

Objective and results description

The study objective was to investigate the potential of quantitative measures of pulmonary inflammation by [18 F]Fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) as a surrogate marker of inflammation in COPD. Patients treated with anti-inflammatory Liraglutide were compared to placebo and correlated with inflammatory markers. 27 COPD-patients (14 receiving Liraglutide treatment and 13 receiving placebo) underwent 4D-respiratory-gated FDG-PET/CT before and after treatment. Two raters independently segmented the lungs from CT images and measured activity in whole lung, mean standard uptake values (SUVmean) corrected for lean-body-mass in the phase-matched PET images of the whole segmented lung volume, and total lesion glycolysis (TLG; SUVmean multiplied by volume). Inter-rater reliability was analyzed with Bland-Altman analysis and correlation plots. We found no differences in metabolic activity in the lungs between the two groups as a surrogate of pulmonary inflammation, and no changes in inflammation markers. The purpose of the research and brief summary of main findings. The degree of and changes in pulmonary inflammation in chronic obstructive pulmonary disease (COPD) may be difficult to ascertain. Measuring metabolic activity as a surrogate marker of inflammation by FDG-PET/CT may be useful, but data on its use in COPD including reproducibility is still limited, especially with respiration-gated technique, which should improve quantification in the lungs. We assessed several quantitative measures of metabolic activity and correlated them with inflammation markers, and we assessed reproducibility of the methods. We found no differences in metabolic activity between the two groups (before and after 40 weeks treatment with Liraglutide vs. placebo). Bland-Altman analysis showed good agreement between the two raters.

Trial registration

The study was conducted between February 2018 and March 2020 at the Department of Pulmonary Diseases at Hospital South West Jutland and Lillebaelt Hospital, Denmark, and registered from March 2018 at clinicaltrials.gov with trial registration number NCT03466021.

Peer Review reports

Introduction

[ 18 F]-fluorodeoxyglucose positron emission tomography computerized tomography (FDG-PET/CT) is a well-established molecular imaging technique with an increasing role in infectious and inflammatory diseases. It assesses glucose metabolism as a surrogate marker of disease activity on the molecular level [ 1 ].

Chronic obstructive pulmonary diseases (COPD) affect millions of people worldwide with chronic inflammation in airway and lungs, airway limitation and significant morbidity and healthcare utilization. Inflammation plays a significant role, and quantification of inflammatory markers are essential in stable phases and during exacerbations in COPD [ 2 ].

Glucagon-Like-Peptide 1 receptor agonists (GLP-1 RA) are used in treatment of diabetes type 2 and for the purpose of weight loss. Among other tissues, GLP-1 receptors are expressed in the lungs and exhibit anti-inflammatory properties by reducing circulating inflammatory markers thereby reducing COPD morbidity and mortality in mice and among patients, GLP-1 RA reduce respiratory diseases including COPD exacerbations [ 3 , 4 ].

Objective and non-invasive assessment of response to medical treatment in inflammatory diseases may be challenging. FDG-PET/CT is already widely employed to assess inflammation in clinical settings and response evaluation in oncology, but there are only few results regarding response evaluation in inflammatory diseases. However, earlier studies did assess the use of FDG-PET/CT to access inflammation at various stages or to differentiate various subtypes of COPD, but studies were small and exploratory. To the best of our knowledge, this is the first RCT with a well-defined patient population with FDG-PET/CT to assess the effect of intervention.

The rationale to employ respiratory gating is the inherent challenges with movement in the lung region during the long acquisition times of PET/CT. Especially the high activity in the liver could influence the overall quantification of the expected low and diffuse lung uptake if the motion during respiration is not accounted for. Further by applying 4D-respiratory-gated PET/CT we assured alignment of CT and PET during the complete respiratory cycle, which results in improved attenuation and scatter correction and that the delineation of the lungs from CT images would accurately be transferrable to quantify lung uptake in the PET images. All of this resulted in a more robust quantification of lung FDG uptake.

We aimed to investigate if respiration gated quantitative FDG-PET/CT measures, as surrogate for pulmonary inflammation, as well as markers of systemic inflammation are reduced in patients with COPD treated with GLP-1 RA for 40 weeks. Further, we assessed the reproducibility of the FDG-PET/CT measures.

Materials & methods

We conducted a prospective, randomized, placebo-controlled, double blinded, two-center, parallel-group trial between February 2018 and March 2020 at The Department of Medicine, Section of Pulmonary Diseases, Esbjerg Hospital and Lillebaelt Hospital, University Hospital of Southern Denmark, Denmark.

We randomized 40 obese participants with COPD for treatment with Liraglutide 3.0 mg per day or placebo in a 1:1 manner and followed them for 44 weeks as previously described [ 5 ]. We included people with COPD defined as forced expiratory volume in one second relative to forced vital capacity (FEV1/FVC) < 70% after maximal bronchodilation in accordance with Global Initiative for Chronic Obstructive Lung Disease guidelines.

Participants were former smokers with 20 or more pack-years history of smoking and were 40–75 years of age. BMI above 27 kg/m2 was defined as inclusion criteria.

Exclusion criteria were treatment with systemic corticosteroids; diabetes mellitus of any type; interstitial pulmonary disease; asthma or asthma-COPD Overlap Syndrome (ACOS), severe hepatic, renal, or heart disease; history of pancreatitis; pregnancy or breastfeeding. As part of the study setup, we performed an FDG-PET/CT of the thorax at baseline (scan 1) and at end of medication at week 40 (scan 2) to assess any changes in pulmonary tracer uptake as a marker of inflammatory activity. Blood samples were assessed for inflammatory markers at baseline and after 40 weeks. We also conducted scans in three healthy controls and two patients with clinical COPD exacerbation.

FDG-PET/CT was performed according to department protocol based on EANM guidelines, i.e. patients fasted for at least 6 h prior to administration of a weight-adjusted dose of 4 MBq/kg FDG (min. 200 MBq-max. 400 MBq). Plasma glucose levels were routinely measured with an allowed maximum of 8 mmol/L (150 mg/dL). Time between injection and PET/CT acquisition was within 60 +/- 5 min. The 4D-respiratory-gated FDG-PET/CT was performed on a Discovery 710 (GE Healthcare, Milwaukee, Wisconsin, USA) using the real-time position management (RPM) respiratory gating system (Varian Medical Systems Inc., Palo Alto, CA) to monitor the participant’s respiration during acquisition.

Following the CT scan, a PET acquisition was performed over the same lung area comprised of two or three bed positions with 6 min. pr. bed and a slice overlap of 16 slices (34%) with scan field of view of 70 cm saved into list-mode files. Corrections for attenuation, randoms, deadtime, normalization and scatter were performed inside the iterative loop.

After PET reconstructions, the individual phases were summed into a single respiratory phase, using the Q.Freeze 1.0 algorithm. The best alignment between CT and PET images was ensured.

Analysis with regard to quantitative measurements were carried out using a GE Advantage Server 2.0 (GE Healthcare, Milwaukee, Wisconsin, USA). The analysis comprised segmenting both lungs by first applying a threshold with a maximum value of -600 Hounsfield units and manually masking out sections in the threshold that was not part of the lungs. The whole segmented lungs were then transferred as a VOI to the PET series, and the mean activity concentration was extracted. From this activity concentration, standard uptake values (SUVs) were calculated as SUV corrected for body weight (SUVbw) and SUV corrected for lean body mass (SUL). We calculated Total Lesion Glycolysis (TLG) normalizing mean SUVs for lung volume. A nuclear medicine specialist (SH) assessed all PET/CT scans visually.

In this part of the study, our aim was to quantify disease activity in the lungs at baseline and after treatment with Liraglutide 3.0 mg in terms of SUL, SUVbw and TLG. We measured systemic inflammation using the markers C-reactive protein (CRP) (Cardiophase hsCRP, Siemens Healthcare Diagnostic Products, Germany), interleukin-6 (IL-6), and monocyte chemoattractant protein-1 (MCP-1) (IL-6 and MCP-1 Quantikine ELISA kits, R&D Systems, UK).

To validate our findings from the scans, we performed the same gating and segmentation procedures in three controls, i.e. patients with no known pulmonary disorders. Finally, we performed segmentation, but not gating, in two patients with well-known exacerbation of COPD.

To investigate the reproducibility of lung segmentation and measures of pulmonary metabolic activity, a medical doctor (AD) and a physicist (TC) blinded to all information independently performed segmentation of the lungs in all study participants at scans 1 and 2. For analysis of inter-reader reliability Bland-Altman plots with 95% limits of agreement (LOA) and coefficient of variation (CV) where generated along with correlation plots with linear fit and calculated Pearson squared correlation coefficient (r 2 ) and sum of squared error (SSE). We used Wilcoxon rank sum test for statistical analysis and random effect models for calculating average group differences. The level of significance was < 5%.

Of 40 participants, 27 completed the study with both scans; 14 in the Liraglutide arm and 13 in the placebo arm. Baseline group characteristics including anthropometrics, lung function, lung volumina, disease burden and morbidity are listed in Table  1 . For further clinical results from the study, please consult [ 5 ].

We calculated results for differences between the Liraglutide and placebo group in measurements of SUL, SUVbw, and TLG. We observed no differences between baseline values of SUL, SUVbw, and TLG. At week 40, SUL was significantly higher in the Liraglutide group than in the placebo group, Table  2 .

Using mixed effect models, we estimated the effect of treatment on FDG-PET/CT parameters at week 40, separately for both raters. We calculated average group differences, defined as the difference between the average value of a measure in the Liraglutide group and the average value of the same measure in the placebo group at week 40 (scan 2).

We found no significant differences in SUL, SUVbw or TLG between the Liraglutide and placebo group after treatment (all p -values above 0.3). Results are given in Table  3 .

Figure  1 summarizes results for activity concentration, SUVbw, SUL, and TLG for Liraglutide and placebo groups at scan 2 and for COPD exacerbations and controls. We found no significant differences in any PET parameters when comparing the three controls to either Liraglutide or placebo groups. When we compared the results from the two patients with clinical COPD exacerbation to controls and the Liraglutide or placebo groups, we found a tendency towards higher values in patients with clinical COPD exacerbations. Results were most pronounced for overall tracer uptake and less pronounced for median values of SUVbw, SUL, and TLG.

Results for activity concentration, SUVbw, SUL, and TLG for Liraglutide ( N  = 17) and placebo ( N  = 13) (scan 2) for COPD exacerbations ( N  = 2) and controls ( N  = 3) (no known pulmonary disease)

When the uncorrected activity concentration were measured in the different groups, only the COPD group displayed a different and increased uptake value. When adjusting for the decay corrected injected activity and patient weight in SUVBw and SUL, this increased value in the COPD group was not found and measurements between groups was not significantly different although the placebo group had a tendency of lower values. Especially when adjusting for lean body mass in the SUL measurements the Liraglutide, COPD and control groups were almost identical, which was probably due to its correction for a non-equal distribution of male and female participants in the COPD and control group.

The TLG measurements took into consideration the total segmented lung volume of the measurements, which on average was found to be different for the different groups. However, this does not seem to be a reliable indicator of decease progress as no significant differences was found between the groups.

Both raters calculated equal values for SUL (0.31 in the Liraglutide group and 0.26 in the placebo group) and for SUVbw (0.49 and 0.43, respectively in the Liraglutide and placebo groups). The values for TLG differed more as shown in Table  2 . Bland-Altman analysis also showed good agreement between the two raters regarding activity concentration in the lungs (Figs.  2 and 3 ).

Bland-Altman plots and correlation plots for activity concentration at scan 1

Scan 1 activity concentration

Bland-Altman plots and correlation plots for activity concentration at scan 2

Scan 2 activity concentration

Inflammatory markers were measured in 30 completers (Liraglutide group, n  = 17; placebo group, n  = 13). Baseline concentrations of CRP and IL-6 were slightly elevated compared with normal ranges with median values of 3.69 and 4.37 mg/L for CRP and 5.05 and 4.38 pg/mL for IL-6 in the Liraglutide and placebo group, respectively. The normal ranges of inflammatory markers are given based on the laboratory’s normal ranges: CRP < 3 mg/L; MCP-1 = 72–295 pg/ml; IL-6 = 0.351–3.48 pg/ml (Table  4 ). Also MCP-1 levels were high in the normal range (72–295 pg/mL) with median values of 281 and 306 pg/mL in Liraglutide and placebo groups, respectively. We observed no between-group differences for median values of MCP-1, CRP, and IL-6 at baseline or after intervention at week 40 (Mann Whitney test). Further, we found no within-group changes in CRP, IL-6 and MCP-1 from baseline to week 40 in treatment or placebo groups (Table  4 ).

As part of a randomized clinical trial, 27 obese participants with COPD were scanned with FDG-PET/CT to quantify disease activity at baseline and after 40 weeks of treatment with Liraglutide 3.0 mg in terms of SUL, SUVbw, and TLG. We found no significant treatment effects for any of these parameters. As for plasma inflammation markers, we found no significant between-group effects and no changes from baseline to end of medication.

We compared our findings with uptake measures from three controls and two COPD patients with exacerbation. We found no difference in PET-based metabolic activity between project patients (Liraglutide and placebo) and controls. In patients with COPD exacerbation, we found higher values for tracer uptake resulting in higher values for SUL, SUVbw and TLG.

Bland-Altman plots showed that lung segmentation and the derived quantifications were reproducible.

Due to reported anti-inflammatory properties of GLP-1 RA, we expected the Liraglutide group to exhibit a reduction in systemic inflammatory markers. Similarly, we expected reduced PET-based metabolic activity in the lungs as a surrogate for inflammatory activity. Some previous studies on FDG-PET/CT found increased FDG lung uptake in COPD patients or current smokers compared to never-smokers as well as a correlation between FDG lung uptake and CRP. This inflammatory response in the airways with active neutrophils showed the potential of FDG as a surrogate marker of pulmonary inflammation [ 6 ]. Other studies found a correlation between metabolic activity in the intercostal accessory respiration muscles as a surrogate marker of COPD severity or increased FDG uptake in right ventricle indicating cor pulmonale secondary to pulmonary hypertension with increased severity of COPD [ 7 ].

However, we could not reproduce any of these findings in our study, for neither the inflammatory markers nor the PET-findings, and one explanation may be our study population; the inflammation markers were only slightly elevated or high in the normal range perhaps reflecting limited chronic disease activity. In addition, we measured inflammation markers in stable phases and not under exacerbations, where they are usually elevated. We cannot exclude statistical type II errors due to the relatively low number of study completers. Finally, differences in underlying methodology between the studies hamper direct comparison.

An indicator that the lack of positive findings in our primary study population may be due to overall low-level inflammation is the finding in the two patients with active COPD exacerbation, i.e. a tendency towards higher FDG-uptake in the lungs suggesting higher overall metabolism that may be due to generalized inflammation. However, motion artefacts may have influenced these results. Normal breathing motion causes motion blur artefacts in PET images. Ungated measurements may lead to falsely increased activity from liver activity measured as part of the lungs due to respiration motion. Our primary series were gated with limited impact from liver activity, but in the patients with COPD, the lack of gating may have influenced the overall lung activity. Respiration-gated PET approaches are employed to reduce the blurring effects in some clinical settings. In fact, others have found similarly equivocal results regarding whole lung quantification and proposed that the activity in whole lung may be too insensitive to detect lung inflammation at all [ 8 ]. To the best of our knowledge, there is no data on the reproducibility of respiration- gated segmentation in lung inflammation.

Limitations

There might be different limitations in our study:

The sample size is relatively small and furthermore the number of participants completing both scans were only 27 compared to the 40 patients included and randomized based on our power calculation.

The study population may not have been be severely affected by COPD. We scanned the participants and measured circulating inflammation markers in stable phases of COPD, which might neglect a potential increase in inflammation in acute phases of the disease. A higher degree of disease burden in terms MRC dyspnea scale, eosinophils, number of exacerbations and the level of inflammatory markers under exacerbations could have affected the results positively, as indicated by the two COPD patients with exacerbation.

The rationale for using respiration gating was an attempt to alleviate the potential effects of blurring from thoracic or abdominal movements from breathing which may cause a spillover of activity from the liver. The significance and impact of the methodology in this context remains unclear.

The anti-inflammatory effect of Liraglutide also remains unconvincing in this setting and treatment with a more potent GLP-1 RA, eventually for a longer period, might have more anti-inflammatory effects.

In contrast to other studies, we were not able to demonstrate differences in pulmonary inflammation using FDG-PET/CT in people with COPD before and after treatment with Liraglutide. With reference to the anti-inflammatory effects of Liraglutide and the promising role of FDG-PET/CT in the diagnosis of infectious and inflammatory diseases, we expected to find decreased uptake following treatment with Liraglutide. However, this was not the case. The inflammatory response may depend on the severity of COPD at the time of the scan (stable COPD versus exacerbation), and the patient population may simply have been in too stable stages. Based on our results, general application of FDG-PET/CT (with or without respiratory gating) in COPD cannot be recommended in relatively stable phases but whether FDG-PET-CT has a role in subset of COPD patients (e.g. more inflammatory active COPD or exacerbation) still needs further investigation.

Data availability

Datasets from the study are stored online in REDCap database. Data are available for the corresponding author and some of the other authors. Access to data is possible by contacting the authors.

Some of the datasets, especially regarding FDG-PET/CT are also are also stored in AV Server regarding calculations about PET parameters.

Data are also stored as written Case Report Forms (CRF) at the respective trial sites in locked rooms for 5 years.

The CRF are checked and monitored by the Good Clinical Practice Unit at University of Southern Denmark.

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Acknowledgements

The authors would like to thank:

OPEN (Open Patient data Explorative Network) for providing support on the establishment and maintenance of our REDCap database and for statistical support.

Unit for Thrombosis Research, Department of Clinical Biochemistry for handling blood sampling and biochemical measurements.

The study nurses at Hospital South West Jutland and Hospital Lillebælt for excellent technical assistance.

Jeppe Gram, MD., Ph.D. for invaluable scientific advises.

Novo Nordisk as a part of the Investigator Sponsored Studies Program provides study medication and running costs.

Partial financial support was received from Karola Jørgensens Forskningsfond, University Hospital of Southern Denmark, Esbjerg, Denmark.

Partial financial support was received from Research council of Hospital South West Jutland, University hospital of Southern Denmark.

Partial financial support was received from the Region of Southern Denmark.

Open access funding provided by University of Southern Denmark

Author information

Authors and affiliations.

Department of Medicine, Regional Hospital Horsens, Sundvej 30, 8700, Horsens, Denmark

Ayse Dudu Altintas Dogan

Department of Medicine, Hospital South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark

Ayse Dudu Altintas Dogan, Torben Tranborg Jensen & Claus Bogh Juhl

Department of Regional Health Research, Faculty of Health Sciences, University of Southern Denmark, Esbjerg, Denmark

Ayse Dudu Altintas Dogan, Ole Hilberg, Else-Marie Bladbjerg & Søren Hess

Department of Medicine, Lillebaelt Hospital, University Hospital of Southern Denmark, Vejle, Denmark

Ayse Dudu Altintas Dogan & Ole Hilberg

Department of Radiology and Nuclear Medicine, Hospital South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark

Thomas Quist Christensen & Søren Hess

Steno Diabetes Center, Odense, Denmark

Claus Bogh Juhl

Department of Clinical Diagnostics, Unit for Thrombosis Research, Hospital South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark

Else-Marie Bladbjerg

Department of Clinical Engineering, Region of Southern Denmark, Esbjerg, Denmark

Thomas Quist Christensen

IRIS – Imaging Research Initiative Southwest, Esbjerg, Denmark

Department of Nuclear Medicine, Odense University Hospital, Odense, Denmark

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Contributions

All authors contributed to the study conceptualization and methodology. Ayse Dudu Altintas Dogan, Claus Bogh Juhl, Else-Marie Bladbjerg, Søren Hess and Thomas Quist Christensen performed data curation, formal analysis, investigation and project administration. FDG-PET/CT scans were reported by Søren Hess and analyzed by Thomas Quist Christensen and Ayse Dudu Altintas Dogan.

Ayse Dudu Altintas Dogan wrote the original draft of the manuscript. Thomas Quist Christensen wrote most of methodology. All authors reviewed and edited on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Ayse Dudu Altintas Dogan .

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The trial was conducted in accordance with the declaration of Helsinki after approval by the Scientific Ethics Committee of The Region of Southern Denmark (j. no S-20170147) and Eudract (j. no. 2017-003551-32). The study was reported at clinicaltrials.gov (NCT03466021) and monitored according to Good Clinical Practice (GCP) by the GCP Unit of Odense University Hospital, Odense, Denmark. Informed consent was obtained from all individual participants included in the study

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Competing interests.

CBJ serves as a speaker for Novo Nordisk, but has no financial interest in the current study. Study medication and running costs were provided by Novo Nordisk as a part of the Investigator Sponsored Studies Program. The authors have no relevant financial or non-financial interests to disclose.

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Dogan, A.D.A., Christensen, T.Q., Jensen, T.T. et al. FDG-PET/CT-based respiration-gated lung segmentation and quantification of lung inflammation in COPD patients. BMC Res Notes 17 , 170 (2024). https://doi.org/10.1186/s13104-024-06820-w

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Aggregate Effects of the Adoption of AI

AI is holding out the prospect of substantial productivity improvements. While the potential of AI may be large, it is uncertain how much of that potential will be realized and how fast it will occur. Recent estimates of the medium-term AI impact on labor productivity range from negligible to larger than the 1990s IT impact. But should AI meaningfully affect medium-term productivity growth, monetary policy is likely to respond by accommodating the increase in potential output. On the other hand, recalling the 1990s IT diffusion, one should not be too surprised that, even though AI is apparently everywhere, it hasn't yet noticeably improved one's experience with chatbots.

AI has received a lot of attention lately, especially generative AI that can create new content, such as ChatGPT for text. How will AI affect the productive potential of the economy? How will it affect labor markets? How soon can we expect AI adoption to show up in aggregate GDP growth? These are questions that are of interest for monetary policymakers to the extent that they affect the estimates of potential output growth and long-run interest rates in the economy.

Being at the early stages of AI adoption, the answers to the questions above will of course be highly speculative. In this article, I focus on three recent studies that have tried to provide estimates of the impact of AI adoption on the U.S. economy's productivity:

• The 2023 article " Machines of Mind: The Case for an AI-Powered Productivity Boom " by Martin Neil Baily, Erik Brynjolfsson and Anton Korinek
• The 2023 report " The Potentially Large Effects of Artificial Intelligence on Economic Growth " by Joseph Briggs and Devesh Kodnami
• The 2024 working paper " The Simple Macroeconomics of AI " by Daron Acemoglu

These studies use a common conceptual framework, and they rely on an overlapping collection of primary research on the potential applications and benefits from AI. However, even within this common framework, the studies come to widely different conclusions on how much AI will potentially increase productivity over the next 10 years. These conclusions range from less than 1 percent to 20 percent, which would correspond to annual growth rates of 0.1 to 2.0 percent.

For perspective, labor productivity over the last 10 years — a period of relatively low productivity growth — has averaged about 1.5 percent per year. Labor productivity growth following World War II peaked in the late 1950s and late 1990s, with average annual growth rates of about 3 percent, as seen in Figure 1. 1 Thus, even if AI-induced growth adds to an underlying growth rate of 1.5 percent, the overall impact ranges from negligible to bringing growth close to post-WWII peaks.

A Framework to Evaluate the Impact of AI

The common conceptual framework of the studies I use starts with an estimate of the range of occupations potentially affected by AI. It then estimates how much AI will improve the labor efficiency in these occupations.

There is a limited number of studies on labor efficiency increases among early AI adopters. 2 For example, one study has found that coders can fulfill their tasks twice as fast with the support of AI, and another study found that the performance of novice call center employees improves by 30 percent . 3

On one hand, one would expect early adopters of AI to pick low-hanging fruit and find the most immediate gains. On the other hand, however, AI adopters may well become better over time at finding efficient applications of AI. Based on the available evidence, AI applications will make overall labor about 30 percent more efficient on average. But how many occupations will benefit from the application of AI?

The Department of Labor maintains the O*NET database for occupations in the U.S. The database provides a verbal description of each occupation and a classification of tasks performed and of worker qualifications required. Several studies have classified occupations in this database as to whether AI can potentially perform some or all the tasks required. One study argues that about 80 percent of all occupations could see at least 10 percent of their tasks benefit from the application of AI. 4

This provides the starting point for an estimate of potential AI applications. We next need estimates of the share of tasks amenable to the application of AI and the timeframe within which the potential can be exploited. Then, we need to weight the contributions of different occupations to aggregate labor, which is usually done using relative wages. Finally, we need to recognize that an increase in labor efficiency does not translate directly to an increase in labor productivity, since there are diminishing marginal returns to labor. As a first-order approximation, we frequently use the labor income share in value added as a measure of the labor elasticity of output. Depending on these adjustments, the three studies I listed argue that AI can potentially increase the effective output contributions of labor by 5 percent to 60 percent over the next 10 years.

Combining the potential labor efficiency gains with the potential occupational base to which they might apply, we get that labor productivity could increase between 1.5 percent and 18 percent over the next 10 years. This ranges from barely noticeable to substantial.

What Are Some Potential Qualifications?

Naturally, there are a number of qualifications that are important to note when estimating the potential impact of AI on labor productivity. The following discusses some significant qualifications regarding this exercise.

Labor Reallocation

A differential increase of labor efficiency across occupations will likely lead to a reallocation of labor towards occupations that become relatively more efficient. This indirect effect will further increase labor productivity. However, if we assume that the economy starts with an efficient allocation of labor across occupations, this will have only second-order effects.

Labor Complements vs Labor Displacement

We have assumed that the application of AI is complementary to labor. That is, we assume it enhances the effectiveness of labor and does not displace it. This is the opposite of the concerns expressed in recent years that automation is displacing medium-wage occupations that mostly perform routine cognitive tasks.

The three studies do not take a strong stance on the potential displacement of workers and/or occupations. If AI can completely substitute for the tasks performed by labor in an occupation, labor is likely to be displaced. This will result in a further increase of labor productivity. Whether this will lead to temporary or permanent employment reductions is an open question. On an optimistic note, labor productivity has more than quadrupled in the post-WWII period, while employment almost tripled.

Capital Accumulation

Once labor becomes more efficient, it becomes more attractive to pair it with additional capital. Thus, induced capital accumulation may lead to further increases in labor productivity. However, the studies on the efficiency gains from the application of AI to various tasks already include increased capital. In fact, in the National Income and Product Accounts , the development of AI should be represented as investment in intellectual property products. Thus, the additional productivity gains from induced capital accumulation may already be included in the current estimates for efficiency gains.

Impact on Baseline Labor Productivity Growth

The impact of AI on baseline labor productivity growth is not obvious. The estimates above assume a one-time permanent increase of labor productivity in a class of occupations, independent of other changes to labor productivity.

But labor productivity in the U.S. has been steadily increasing, even though the growth rate of 1.5 percent has been relatively low over the last 20 years. Will AI-induced productivity growth simply come on top of this underlying productivity growth? Will it reduce some of the underlying productivity growth because we are shifting to a new paradigm? Or will AI change the ability to innovate and not only result in a level shift of productivity, but a permanent change in the trend growth rate? We do not know.

When Will AI Show Up in Aggregate Growth?

Not only is it uncertain by how much AI will eventually impact productivity, but it is also uncertain how fast its impact will show up in aggregate statistics. Consider again the two high-growth episodes in the U.S. economy — the late 1950s and the late 1990s — when average annual labor productivity growth was around 3 percent. There is no obvious single cause for the early high-growth period, though one reasonable story attributes it to the release of pent-up innovations in the U.S. consumer goods sector after being held back by low demand in the Great Depression and during World War II. The second high-growth period, however, is usually attributed to the widespread application of IT advances.

In either case, it took 10 to 20 years before the initial innovations resulted in widespread applications that showed up in aggregate labor productivity. I now illustrate the implications of delayed adoption for aggregate labor productivity using a simple diffusion model that has been applied in a variety of settings, including the spread of pandemics.

Think of the economy as chugging along at 1.5 percent labor productivity growth, and then AI appears. Assume that AI eventually increases labor productivity for a part of the labor force relative to the baseline productivity path, but that the application of AI slowly diffuses to that sector.

The two important parameters discussed above are the effective share of employment eventually affected by AI and by how much AI increases labor efficiency in the sector. We'll assume that the share affected by AI is 25 percent and that labor efficiency increases by a factor of 1.4. Thus, eventually average labor productivity will increase 10 percent relative to the baseline path, somewhere in the middle of the three studies noted above. This is the solid blue line relative to the purple line in Figure 2a. I would note that the implied AI-specific productivity improvement factor of 1.4 is higher than the average from currently available studies.

Now suppose that the application of AI gradually diffuses through the economy. The diffusion is such that the rate at which the share of AI adopters is increasing is proportional to the share of those who have not yet adopted AI. Thus, the growth rate starts out high and then declines over time. But initially there is only a very small share of AI adopters, so the base to which the high growth rate applies is small, and the aggregate impact is small.

Over time, as the share of AI adopters is increasing, the impact of new AI adopters is also increasing, and the aggregate growth rate is increasing until it reaches its peak when about half of potential AI adopters have adopted. From then on, the declining growth rate dominates, and aggregate productivity is declining. The solid blue line in Figure 2b plots the share of potential AI adopters over time. I assume that half of the potential improvements have taken place after 20 years. This is in line with the two growth episodes just discussed.

The solid blue line in Figure 2c plots the implied instantaneous aggregate labor productivity growth rate. Average labor productivity growth picks up noticeably after 10 years and reaches a peak of close to 2.7 percent when the AI-improved share of employment is 12.5 percent. The symmetric 10-year moving average of the growth rate (the dashed blue line) reaches a peak of about 2.3 percent, still below the two historical peak growth episodes.

Now suppose that AI spreads faster in the economy. The green lines in the preceding figures represent a diffusion path where half of the potential AI improvements take place within 10 years, rather than 20 years. As you can see, the paths just shift to the left by 10 years — that is, peak growth now occurs after 10 years — but the magnitudes of the effects are the same.

What Does It Mean for Monetary Policy?

We should acknowledge that there is a huge amount of uncertainty about the impact of AI on the timing and magnitude of labor productivity changes. No matter how many anecdotes we have on particular AI applications, we have to see it in aggregate data to matter for monetary policy. To paraphrase Duke Ellington, it don't mean a thing if it ain't got that swing in aggregate labor productivity.

If there are no employment effects, labor productivity growth represents potential output growth or trend output growth. The usual position of monetary policy is to respond to deviations of output from potential output, not to changes in potential output, at least for as long as inflation is close to target. For example, productivity and output growth accelerated in the late 1990s. In response, the Federal Open Market Committee under then-chairman Alan Greenspan considered this to reflect an increase in trend growth rate of potential output and therefore did not counter with raising interest rates. 5

At the same time, standard economic theory predicts that interest rates are related to expected consumption growth. If expected consumption growth increases — that is, future consumption increases more relative to current consumption — then interest rates should increase so that households willingly postpone consumption. Consumption is likely to increase with increased potential output, thus a higher growth rate of potential output should be associated with a higher equilibrium interest rate.

In a standard economic growth model, short-run interest rates move with the output growth rate. For a reasonable calibration of the model, the interest rate changes one for one with the growth rate. Thus, a 1 percentage point increase of the growth rate would be associated with a 1 percentage point increase of the short-run interest rate. But note that, for the baseline case when half of potential AI applications are adopted after 20 years, the growth rate only starts to increase noticeably after 15 years in the baseline setup, as seen in Figure 2c. Nevertheless, the short-run interest rate should increase 1.2 percentage points once the growth rate reaches its peak.

Long-term interest rates move less, but earlier. In Figure 2d, we plot the change for a long-term interest rate with a 10-year horizon (that is, the average of 10-year future short rates). While the short rate only moves with the contemporaneous growth rate, the long rate moves in anticipation of future growth rates and increases by 0.5 percentage points after 12 years. For the alternative case when AI adoption proceeds faster, the short rate increases earlier, and the 10-year interest rate increases immediately by 0.5 percentage points. We can think of the long rate providing an advance signal on future short rates.

In the context of recent policy discussions, the short rate associated with trend output/consumption growth represents r*, the interest rate that would be appropriate when there are no deviations of output from potential and inflation is at its target. 6 Thus, a persistent increase of r* due to an increase of trend output growth should lead to persistently higher policy rates. This argument was also made in the late 1990s in response to the perceived increase in trend output growth, but it did not carry the day then. This may simply reflect the difficulty for monetary policymakers to infer changes in underlying trends in real time when data are constantly revised, and the economy is buffeted by large temporary shocks.

Andreas Hornstein is a senior advisor in the Research Department at the Federal Reserve Bank of Richmond.

Productivity growth (even for annual data) is highly volatile. To reveal any long-term trends, we therefore plot 10-year moving averages of the annual growth rates.

For the names of some of these studies, see the papers I'm reviewing in this article.

See the 2023 working papers " The Impact of AI on Developer Productivity: Evidence From GitHub Copilot " by Sida Peng, Eirini Kalliamvakou, Peter Cihon and Mert Demirer and " Generative AI at Work " by Erik Brynjolfsson, Danielle Li and Lindsay Raymond.

See the 2023 working paper " GPTs Are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models " by Tyna Eloundou, Sam Manning, Pamela Mishkin and Daniel Rock.

For a description of monetary policy in the late 1990s, see the 2002 paper " The Phases of U.S. Monetary Policy: 1987 to 2001 " by Marvin Goodfriend and the 2010 paper " FOMC Learning and Productivity Growth (1985-2003): A Reading of the Record " by Richard Anderson and Kevin Kliesen.

See the 2023 article " The Stars Our Destination: An Update for Our R* Model " by Thomas Lubik and Christian Matthes.

To cite this Economic Brief, please use the following format: Hornstein, Andreas. (June 2024) "Aggregate Effects of the Adoption of AI." Federal Reserve Bank of Richmond Economic Brief , No. 24-19.

This article may be photocopied or reprinted in its entirety. Please credit the author, source, and the Federal Reserve Bank of Richmond and include the italicized statement below.

Views expressed in this article are those of the author and not necessarily those of the Federal Reserve Bank of Richmond or the Federal Reserve System.

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There’s a widespread understanding that managing corporate culture is key to business success. Yet few companies articulate their culture in such a way that the words become an organizational reality that molds employee behavior as intended.

All too often a culture is described as a set of anodyne norms, principles, or values, which do not offer decision-makers guidance on how to make difficult choices when faced with conflicting but equally defensible courses of action.

The trick to making a desired culture come alive is to debate and articulate it using dilemmas. If you identify the tough dilemmas your employees routinely face and clearly state how they should be resolved—“In this company, when we come across this dilemma, we turn left”—then your desired culture will take root and influence the behavior of the team.

To develop a culture that works, follow six rules: Ground your culture in the dilemmas you are likely to confront, dilemma-test your values, communicate your values in colorful terms, hire people who fit, let culture drive strategy, and know when to pull back from a value statement.

Start by thinking about the dilemmas your people will face.

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The problem.

There’s a widespread understanding that managing corporate culture is key to business success. Yet few companies articulate their corporate culture in such a way that the words become an organizational reality that molds employee behavior as intended.

What Usually Happens

How to fix it.

Follow six rules: Ground your culture in the dilemmas you are likely to confront, dilemma-test your values, communicate your values in colorful terms, hire people who fit, let culture drive strategy, and know when to pull back from a value.

At the beginning of my career, I worked for the health-care-software specialist HBOC. One day, a woman from human resources came into the cafeteria with a roll of tape and began sticking posters on the walls. They proclaimed in royal blue the company’s values: “Transparency, Respect, Integrity, Honesty.” The next day we received wallet-sized plastic cards with the same words and were asked to memorize them so that we could incorporate them into our actions. The following year, when management was indicted on 17 counts of conspiracy and fraud, we learned what the company’s values really were.

• EM Erin Meyer is a professor at INSEAD, where she directs the executive education program Leading Across Borders and Cultures. She is the author of The Culture Map: Breaking Through the Invisible Boundaries of Global Business (PublicAffairs, 2014) and coauthor (with Reed Hastings) of No Rules Rules: Netflix and the Culture of Reinvention (Penguin, 2020). ErinMeyerINSEAD

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A Brief History of AI

This post is part of Lifehacker’s “Living With AI” series: We investigate the current state of AI, walk through how it can be useful (and how it can’t), and evaluate where this revolutionary tech is heading next. Read more here .

You wouldn’t be blamed for thinking AI really kicked off in the past couple years. But AI has been a long time in the making, including most of the 20th century. It's difficult to pick up a phone or laptop today without seeing some type of AI feature, but that's only because of working going back nearly one hundred years.

AI’s conceptual beginnings

Of course, people have been wondering if we could make machines that think for as long as we’ve had machines. The modern concept came from Alan Turing, a renowned mathematician well known for his work in deciphering Nazi Germany’s “unbreakable” code produced by their Enigma machine during World War II. As the New York Times highlights , Turing essentially predicted what the computer could—and would—become, imagining it as “one machine for all possible tasks.”

But it was what Turing wrote in “Computing Machinery and Intelligence” that changed things forever: The computer scientist posed the question, “Can machines think?” but also argued this framing was the wrong approach to take. Instead, he proposed a thought-experiment called “ The Imitation Game .” Imagine you have three people: a man (A), a woman (B), and an interrogator, separated into three rooms. The interrogator’s goal is to determine which player is the man and which is the woman using only text-based communication. If both players were truthful in their answers, it’s not such a difficult task. But if one or both decides to lie, it becomes much more challenging.

But the point of the Imitation Game isn’t to test a human’s deduction ability. Rather, Turing asks you to imagine a machine taking the place of player A or B. Could the machine effectively trick the interrogator into thinking it was human?

Kick-starting the idea of neural networks

Turing was the most influential spark for the concept of AI, but it was Frank Rosenblatt who actually kick-started the technology’s practice , even if he never saw it come to fruition. Rosenblatt created the “Perceptron,” a computer modeled after how neurons work in the brain, with the ability to teach itself new skills. The computer has a single layer neural network, and it works like this: You have the machine make a prediction about something—say, whether a punch card is marked on the left or the right. If the computer is wrong, it adjusts to be more accurate. Over thousands or even millions of attempts, it “learns” the right answers instead of having to predict them.

That design is based on neurons: You have an input, such as a piece of information you want the computer to recognize. The neuron takes the data and, based on its previous knowledge, produces a corresponding output. If that output is wrong, you tell the computer, and adjust the “weight” of the neuron to produce an outcome you hope is closer to the desired output. Over time, you find the right weight, and the computer will have successfully “learned.”

Unfortunately, despite some promising attempts, the Perceptron simply couldn’t follow through on Rosenblatt’s theories and claims, and interest in both it and the practice of artificial intelligence dried up. As we know today, however, Rosenblatt wasn’t wrong: His machine was just too simple. The perceptron’s neural network had only one layer, which isn’t enough to enable machine learning on any meaningful level.

Many layers makes machine learning work

That’s what Geoffrey Hinton discovered in the 1980s : Where Turing posited the idea, and Rosenblatt created the first machines, Hinton pushed AI into its current iteration by theorizing that nature had cracked neural network-based AI already in the human brain. He and other researchers, like Yann LeCun and Yoshua Bengio, proved that neural networks built upon multiple layers and a huge number of connections can enable machine learning.

Through the 1990s and 2000s, researchers would slowly prove neural networks’ potential. LeCun, for example, created a neural net that could recognize handwritten characters . But it was still slow going: While the theories were right on the money, computers weren’t powerful enough to handle the amount of data necessary to see AI’s full potential. Moore’s Law finds a way, of course, and around 2012 , both hardware and data sets had advanced to the point that machine learning took off : Suddenly, researchers could train neural nets to do things they never could before, and we started to see AI in action in everything from smart assistants to self-driving cars.

And then, in late 2022, ChatGPT blew up , showing both professionals, enthusiasts, and the general public what AI could really do, and we’ve been on a wild ride ever since. We don’t know what the future of AI actually has in store: All we can do is look at how far the tech has come, what we can do with it now, and imagine where we go from here.

Living with AI

To that end, take a look through our collection of articles all about living with AI . We define AI terms you need to know , walk you through building AI tools without needing to know how to code , talk about how to use AI responsibly for work , and discuss the ethics of generating AI art .