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Research strategy sets the general direction of research. It is one of the elements of research methodology and includes the process in which research is carried out. The right research strategy must be selected based on research objectives as well as questions, the amount of resources available and time, the philosophical foundations of the researcher, and the scope of existing knowledge about the studied area (Wedawatta G., Ingirige B., Amaratunga D. 2011, p. 3-4).

• 1 Types of research strategies
• 2 Quantitative and qualitative research strategies
• 3 Criteria to choose a research strategy
• 4 Research strategy impact on limitations of the research results
• 5 References

Types of research strategies

There are different research strategies, but they are largely convergent. Therefore, it is important to choose the most favorable strategy for a particular study. Part of the research strategies used in management and business are (Wedawatta G., Ingirige B., Amaratunga D. 2011, p. 4):

• experiment,
• action research,
• case study,
• grounded theory,
• ethnography,
• cross sectional studies.

Surveys are used to obtain data that will guide research groups (from choosing samples to questions and topics). It is a successful method that helps generate a large amount of data from many people. Respondents can be selected based on a different number of features, such as: sex, age, race, sexuality, social class or demographic questions. These questions are usually placed first in the survey. Such information may be needed by a researcher who does not know which focus groups to use (homogeneous or heterogeneous) (Hesse-Biber S., Leavy P. 2011, p. 173).

The experiment is a detailed study using the general empirical method. Processes and phenomena are tested in controlled, rigorous conditions. The main principle in each experiment is to change the selected individual component in the test procedure, the remaining components are fixed - they do not change. During a given experiment, the researcher introduces a new factor to the process, modifying its rate. This factor is called an independent variable or an experimental factor. On the other hand, factors changed under the influence of an independent variable are dependent variables (Novikov A., Novikov D. 2013, p. 56-56).

Action research

Action research is systematic research that helps people solve everyday problems, looking for effective solutions. The aim of this research is to involve complex dynamics in all social contexts. Continuous cycles of designed research seek to solve problems that occur in specific situations and locations, which allows for obtaining measures that increase efficiency and effectiveness of work , in: social organizations and agencies, human and health services, companies, schools. Thanks to this, it builds knowledge that strengthens social and professional practices and increases the well-being of people who take part in it (Stringer E. 2014, p. 1).

Case study is one of the most popular research methods used by researchers in industrial marketing . The reason for this may partly be the nature of the subject. The main object of the study are relationships and organizations that have a complex structure and are difficult to access than (for example) consumer markets. The study of a single or small number of entities brings a lot of qualitative data that can be described as a case study, providing insight into their nature of phenomena (Easton G. 2010, p. 118).

Grounded theory

Grounded theory is recognized as a qualitative research method. It aims to develop a theory that is based on the systematic collection and analysis of data. From other quantitative methods, it is distinguished by a specific approach to the development of theory. Grounded theory believes that there should be a continuous relationship between two activities: collecting and analyzing data. It allows the appearance of rich and original results, closely related to data, and offers well-marked data analysis procedures. It guarantees the researchers self-confidence, because they can indicate a large number of cases in the data that are associated with the concept produced (Urquhart C., Lehmann† H., Myers M. 2010, p. 357-358)

Ethnography

Ethnography favors nuanced, contextually rich and involved nuanced examples of qualitative social research, the driving force of the produced data are daily interactions. It includes a combination of different field techniques (interviews, observations, audiovisual recording, note taking, research of autochthonous literature) inscribed in the participants' observation. It is based on the conviction and trust that data is created thanks to the deep interaction between researchers. Ethnographers often treat data as a gift from informers with all the mutual consequences that suggest the exchange of these gifts (Falzon M. 2016, p. 1).

Cross sectional studies

Cross sectional study is one of the types of observational studies. At the same time, the researcher measures the exposure and the result of the study participants in it. Participants of the study are selected according to the inclusion and exclusion criteria adopted for a given study. After selecting the participants, the researcher assesses the exposure and results following the task. Cross-sectional studies are used to assess the incidence of diseases in clinical samples and for population studies (Setia M. 2016, p. 261)

Quantitative and qualitative research strategies

Qualitative and quantitative research strategies are two different approaches to conducting research.

Quantitative research is a method of gathering and analyzing numerical data to understand patterns and trends. This approach is often used in social sciences and natural sciences to examine cause-and-effect relationships, and it relies on statistical analysis of data. Surveys, experiments, and observational studies are some examples of quantitative research methods.

On the other hand, qualitative research is a method of gathering and analyzing non-numerical data, such as words, images, and observations. It is often used in fields such as sociology, anthropology, and psychology, and it aims to understand the meaning and experiences of individuals and groups. Some examples of qualitative research methods include ethnography, case study, and grounded theory.

Both qualitative and quantitative research strategies have their own advantages and disadvantages, and the choice of which approach to use will depend on the research question and the overall goals of the study. In some cases, a mixed-methods approach, which combines both qualitative and quantitative methods, may be most appropriate.

Criteria to choose a research strategy

There are several criteria to consider when choosing a research strategy. These include:

• Relevance : The research strategy should be relevant to the research question and the purpose of the study.
• Feasibility : The research strategy should be feasible to implement within the given time and budget constraints.
• Validity : The research strategy should be able to provide valid and reliable results that can be generalized to the population of interest .
• Ethical considerations : The research strategy should take into account any ethical considerations, such as informed consent and the protection of participants' rights.
• Study design : The research strategy should be appropriate for the study design, whether it be quantitative, qualitative or mixed-methods.
• Data collection methods : The research strategy should include appropriate methods for collecting and analyzing data, such as surveys, interviews, or experiments.
• The sample size : The research strategy should consider the sample size to be able to generalize the results to the population of interest.
• The resources available : The research strategy should be compatible with the resources available to the researcher, such as time, budget, and personnel.

Ultimately, the choice of research strategy will depend on the specific research question and the overall goals of the study.

Research strategy impact on limitations of the research results

The research strategy chosen can have a significant impact on the limitations of the research results. Each approach has its own strengths and weaknesses, and the choice of strategy can influence the reliability and validity of the data, as well as the generalizability of the findings.

For example, quantitative research is often considered to be more objective and reliable than qualitative research because it relies on numerical data and statistical analysis. However, quantitative research can be limited by the specific research question and the methods used, and the results may not fully capture the complexity of social phenomena.

On the other hand, qualitative research can provide rich, in-depth data that can give a detailed understanding of a particular phenomenon. However, qualitative research can be more subjective and may be influenced by the researcher's own biases. Additionally, the sample size in qualitative research is usually small, which can limit the generalizability of the findings.

A mixed-methods approach can overcome some of the limitations of both qualitative and quantitative research by combining the strengths of both methods. However, it also requires more resources and can be more complex to implement.

In summary, the limitations of the research results are closely tied to the research strategy chosen. Therefore, it is important to consider the strengths and weaknesses of different approaches when choosing a research strategy and to be aware of the limitations of the research results.

• Easton G. (2010), Critical realism in case study research , Industrial Marketing Management, nr. 39, p. 118-128
• Falzon M. (2016), Multi-sited Ethnography: Theory, Praxis and Locality in Contemporary Research , Taylor & Francis Group, London, p. 1
• Gravetter F., Forzano L. (2017), Research Methods for the Behavioral Sciences , Cengage Learning, USA
• Hesse-Biber S., Leavy P. (2011), The Practice of Qualitative Research , SAGE Publications, USA, p. 173
• Novikov A., Novikov D. (2013), Research Methodology: From Philosophy of Science to Research Design , CRC Press, Boca Raton, p. 56-56
• Rainer A. (2011), The longitudinal, chronological case study research strategy: A definition, and an example from IBM Hursley Park , Information and Software Technology , Volume 53, Issue 7, p. 730-746
• Setia M. (2016), Methodology Series Module 3: Cross-sectional Studies , Indian J Dermatol, nr 61, p. 261-264
• Stringer E. (2014), Action Research , SAGE Publications, USA, p. 1
• Urquhart C., Lehmann† H., Myers M. (2010), Putting the ‘theory’ back into grounded theory: guidelines for grounded theory studies in information systems , Info Systems J, nr 20, p. 357-358
• Whitley B., Kite M. , Adams H. (2013), Principles of Research in Behavioral Science , Routledge, New York
• Wedawatta G., Ingirige B., Amaratunga D. (2011), Case study as a research strategy: Investigating extreme weather resilience of construction SMEs in the UK , the University of Salford, Manchester, p. 3-4

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What Is Strategy?

• Michael E. Porter

Today’s dynamic markets and technologies have called into question the sustainability of competitive advantage. Under pressure to improve productivity, quality, and speed, managers have embraced tools such as TQM, benchmarking, and re-engineering. Dramatic operational improvements have resulted, but rarely have these gains translated into sustainable profitability. And gradually, the tools have taken the place of strategy. In his five-part article, Michael Porter explores how that shift has led to the rise of mutually destructive competitive battles that damage the profitability of many companies. As managers push to improve on all fronts, they move further away from viable competitive positions. Porter argues that operational effectiveness, although necessary to superior performance, is not sufficient, because its techniques are easy to imitate. In contrast, the essence of strategy is choosing a unique and valuable position rooted in systems of activities that are much more difficult to match. Porter thus traces the economic basis of competitive advantage down to the level of the specific activities a company performs. Using cases such as Ikea and Vanguard, he shows how making trade-offs among activities is critical to the sustainability of a strategy. Whereas managers often focus on individual components of success such as core competencies or critical resources, Porter shows how managing fit across all of a company’s activities enhances both competitive advantage and sustainability. While stressing the role of leadership in making and enforcing clear strategic choices, Porter also offers advice on how companies can reconnect with strategies that have become blurred over time.

For starters, it’s not the same as operational effectiveness.

For almost two decades, managers have been learning to play by a new set of rules. Companies must be flexible to respond rapidly to competitive and market changes. They must benchmark continuously to achieve best practice. They must outsource aggressively to gain efficiencies. And they must nurture a few core competencies in race to stay ahead of rivals.

• Michael E. Porter is the Bishop William Lawrence University Professor at Harvard Business School. He has served as an adviser to governments and campaigns around the world on the advancement of social policy and economic policy, including Mitt Romney’s presidential campaign. His latest paper is  The Role of Business in Society . He is an academic adviser to the Leadership Now Project.

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Article publication date: 17 November 2020

Issue publication date: 15 December 2020

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

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This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

The term strategy has become diluted and unhelpful in the process of organizations’ pursuit of competitive advantage. This briefing looks at addressing the issues around the term strategy.

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(2020), "Understanding strategy: How the definition of strategy matters for competitive advantage", Strategic Direction , Vol. 36 No. 12, pp. 35-37. https://doi.org/10.1108/SD-10-2020-0180

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Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

• Qualitative vs. quantitative : Will your data take the form of words or numbers?
• Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
• Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

• For quantitative data, you can use statistical analysis methods to test relationships between variables.
• For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

• From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
• Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

• During an experiment .
• Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

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

• Chi square test of independence
• Statistical power
• Descriptive statistics
• Degrees of freedom
• Pearson correlation
• Null hypothesis
• Double-blind study
• Case-control study
• Research ethics
• Data collection
• Hypothesis testing
• Structured interviews

Research bias

• Hawthorne effect
• Unconscious bias
• Recall bias
• Halo effect
• Self-serving bias
• Information bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Phase #2: Clearly Define Your Research Strategy

Read about the 5 Phases of an effective marketing research process here Phase 1: Research Inventory Phase 2: Clearly Define 2014 Research Strategy

A Research Strategy is a step-by-step plan of action that gives direction to your thoughts and efforts, enabling you to conduct research systematically and on schedule to produce quality results and detailed reporting. This enables one to stay focused, reduce frustration, enhance quality and most importantly, save time and resources. The Research Strategy is the nuts and bolts of your application, describing the rationale for your research and the experiments you will do to accomplish your desired goals. This post will discuss an extremely important phase in the process; clearly defining your research strategy.

In phase 1 we focused on inventory of all research, current and past. This week we will use that data to identifying specific research targets for both customer segments and feedback criteria.

This defined research strategy will also act as a reference point for benchmarking purposes so your company can see if it yielded the desired results. It requires the clear communication of targets and criteria ensuring all relevant stakeholders move in the same direction.

Identify gaps in existing data

A good place to start this process is to first examine the results of Phase 1 where you took an inventory of existing data and current research projects. With this framework you can identify gaps in data sets and create a research strategy that will compliment your company’s existing information.

Include all departments to maximize resources

Understanding the needs of your company’s individual departments, like marketing , communications , human resources and others, will help you to avoid repetitive research efforts which are both a waste of resources and damaging to communication channels with your clients. So determine data needs by department to make sure everyone is involved, to insure the highest possible value to your research investment.

Map out your customer’s life cycle

Another approach is to map out the customer’s life cycle in three steps.

• information seeking
• purchase decision
• product use

With these three steps you can visualize when you are attempting to reach your customers and evaluate whether or not the timing is appropriate for the specific information you’re trying to collect. You can also set the frequency at which you are requesting feedback or information from your customers; it is wise to avoid over-saturating a customer base with research inquiries.

What are your company’s priorities?

Once you’ve identified a need for data by examining your research inventory (established in Phase 1) and you’ve mapped out the customer life cycle to pinpoint the ideal timing for a research project, consider your company’s overall priorities to determine if a research project will help accomplish your goals. If so, then you’ve done your due diligence and moving forward with a research project is a prudent way to increase the likelihood of future success. As we’ve mentioned before, due to an ever-changing environment and variables it is impossible to predict with absolute certainty how a market will react to your product or service. However, an educated perspective of your consumer base will always improve your chances of achieving company-wide goals.

Our series will continue with – Phase #3: Conduct Research . We will discuss effective ways to communicate with your target respondents and keys to developing a successful research instrument.

Jenny Dinnen is President of Sales and Marketing at MacKenzie Corporation. Driven to maximize customer's value and exceed expectations, Jenny carries a can-do attitude wherever she goes. She maintains open communication channels with both her clients and her staff to ensure all goals and objectives are being met in an expeditious manner. Jenny is a big-picture thinker who leads MacKenzie in developing strategies for growth while maintaining a focus on the core services that have made the company a success. Basically, when something needs to get done, go see Jenny. Before joining MacKenzie, Jenny worked at HD Supply as a Marketing Manager and Household Auto Finance in their marketing department. Jenny received her undergrad degree in Marketing from the University of Colorado (Boulder) and her MBA from the University of Redlands.

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Customers that leave a brand for a competitor usually have specific reasons for doing so; whether tangible or intangible. In the case of a lost customer, it’s extremely valuable to understand WHY and WHAT (if anything) would bring that customer back. Sometimes nothing can be done and the customer is simply lost; but other times a simple adjustment can make a big difference. It might feel awkward at first, but reaching out to lost customers is actually beneficial in more than a few ways. For starters, you show customers that you care about them and that you still value their opinion. This is a strong gesture and it’s a way to passively reengage consumers who might consider returning.

Digital platforms, both social and shopping, have forever changed the consumer experience. At the same time, in-person experiences are still relevant and need to be aligned with the online experiences to provide a seamless, fluid flow between the real and digital worlds. Furthermore, consumers want personalized experiences that adjust as quickly as their preferences and favorite trends. This can be an overwhelming ordeal, or it can be as straightforward as direct and open two-way communication with your customers. This is the power of an ongoing Voice of Customer satisfaction program. By understand what your customers want, listening to how they feel your brand is performing, and being open to improvement suggestions, you will have all the data-driven insights you need win customer loyalty.

In addition to marketing reach and visibility, it’s important to consider the impact of specific brand messages. If the goal is to shape or reinforce brand image, customer feedback is the only way to measure marketing effectiveness. If the goal is to motivate action, such as visiting a website or purchasing a particular item, then sales tracking is one way to measure marketing effectiveness. However, transaction data doesn’t address purchase decision drivers so it’s difficult to attribute a sale to a particular marketing campaign. Again, direct customer feedback is required to identify their decision drivers.

For up-and-coming brands, or even established brands looking to expand their products/services, it’s important to answer the question, “Are consumers aware of our brand?” This is the first step in developing a strong, long-term marketing strategy and will provide a reliable benchmark for future reference. By segmenting awareness and perception data, you’ll have a clear indication of your current standing within specific markets and customer demographics.

It’s easy to become narrow-sighted and overly focused on one objective to the point where surrounding activity is unnoticed; especially with the rapid progression of technology and emerging consumer trends. The most successful brands will occasionally take a step back for a high-level, impartial look at the overall market landscape for a refreshed perspective on how their business fits into the bigger picture. Detailed Market Mapping not only acts as a preventative measure by exposing threats and potential danger, it will also uncover secondary variables that may be flying under the radar. This dual-benefit will swing the competitive balance in your favor by equipping your organization with the insights needed to make confident decisions; both short-term and long-term.

There’s no way to predict the future with absolute certainty but there are ways of applying market insights to improve success probabilities. Rather than conducting a series of trial-and-error initiatives, conducting research prior to forward-thinking strategic development will support informed decision making today and establish benchmarks for comparative analysis in the future. Just like having a map on a road trip, Market Mapping defines the surrounding area so decision makers can see where they’re going, stay on track and safely reach their destination. A clearly illustrated framework of your competitive environment enables your team to run through possible scenarios and how the market might react under specific circumstances.

Consumers are complex and unique individuals whose purchase decisions are influenced by a broader spectrum of attributes than the traditional price, product, placement, and positioning. Of course these are still relevant, but modern consumers are looking for more. Factors that may not seem to align at first glance are now connected (i.e. Health Concerns and Retail). The Market Mapping process will not only uncover the pieces it will act as a guide to reveal how the pieces fit together. Brands that understand their surroundings and create action plans based on market insights are best equipped to take proactive rather than reactive measures.

Understanding the past is a great place to start when strategically planning for the future. Consider market conditions and consumer preferences as they exist today, then examine the historical timeline of economic, social, political and technological shifts that have impacted your industry. By highlighting the environmental factors that have shaped consumer behavior, your brand will be equipped with consumer insights explaining the why, how and when of significant market shifts.

Imagine each existing dataset is a brick. If the bricks are haphazardly tossed in a pile then standing on that pile won’t be easy, But if the bricks are organized and positioned in a way that they work together, then there’s a foundation to not only stand on but to build on. Treat your existing data inventory as building materials rather than the byproducts of past efforts. No matter when or why data was collected, it still holds considerable value. After completing the Data Inventory Assessment, ensuing efforts will continue building on a solid foundation rather than merely adding more bricks to the pile.

Every company has its missing puzzle pieces, but not every company is willing to do something about it. Actively searching to identify the gaps in what you know about your customers and your market is an important part of strategic brand development. There’s also the benefit of ensuring that any steps taken are covering new ground rather than repeating what’s already been done. Pursuing the missing pieces will build upon the bigger picture and add cohesive value, but the only way to pursue the missing pieces is by knowing with certainty which pieces are missing.

By organizing and analyzing the existing customer data, brands will gain a clear picture what is quantifiably known at that point in time. This process will also itemize the types of data being held and it will establish benchmarks for future comparative analytics. Identifying the metrics that are most beneficial to current goals and objectives will produce the actionable insights needed to guide decision making.

Market research and data analytics are commonly applied on a “need-to-know” basis; meaning individual projects or initiatives are launched to address a specific set of questions for short-term application. After serving their intended purpose, these data files usually go into the vault and are rarely (if ever) seen again. But our Data Inventory Assessment digs into this data vault and offers a second life to the dormant files within.

Research Strategy

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• Mina Tajvidi 3 &
• Azhdar Karami 3 , 4  

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This chapter sets out the various steps that are necessary in executing this study and thereby satisfying its objectives. It aims to explain in detail all aspects of the research, with particular reference to all of the key theoretical and practical issues involved. This chapter discusses the research design and methodology and the survey. Various research philosophies and approaches presented in literature will be discussed with focuses on their application to this study. This chapter is composed of seven sections which cover the research objectives and questions, research philosophy, research approach, research strategies, research choices, research time horizons, and research techniques and procedures. Each sub-section of this chapter covers one of these aspects of the research. The first sub-section addresses the objective and questions of the study. The first sub-section addresses the objective and questions of the study. The second sub-section presents the research methods and strategy and includes research philosophy, research approach, research design, data collection process and constructing the questionnaire. The third sub-section addresses the conceptual framework and research variables. The fourth sub-section presents the characteristics of SMEs. The fifth sub-section reveals the proposed model and hypotheses. The sixth sub-section presents the research choice and data analysis.

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Tajvidi, M., Karami, A. (2015). Research Strategy. In: Product Development Strategy. Palgrave Macmillan, London. https://doi.org/10.1057/9781137501394_3

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