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EMBA Project Methodology Alexey Verbetsky July 2013 Plan, research and write up a Project that improves understanding of a significant Managerial, Business, or Organisational matter and provides recommendations or findings upon which Action can be determined • Personal Interests & Strengths • Own Organisation & Colleagues • The Literature (journals, books & reports) • EMBA Modules & Instructors Is the Issue Important and Coherent? • Past Projects Discuss with Others: Colleagues, Managers etc. Check the Literature: What Work Have Others Done on the Issue that Concerns You? Define a Broad Area of Interest e.g. ‘Strategy in Multinational Companies’ Current Problems or Difficulties Define Strategic Questions e.g. ‘What Should We do to Improve the Company’s Competitive Position in International Markets?’ Your Job is to Identify Research Question(s) e.g. ‘What are the Factors Influencing the Company’s Competitive Position in International Markets?’ and ‘How do We Measure/Assess the Company’s Competitive Position in International Markets?’ http://papers.ssrn.com/sol3/DisplayAbstractSearch.cfm Usual roadmap – key stages Problem definition, research scope and objectives Finalizing the research questions and strategy Literature review and initial conclusions Data Collection Data analysis and interpretation Developing conclusions Finalizing the document with logical links Illustrative Structure 15% Introduction 10% Background on the sector 20% Literature review 20% Methodology 5% Data Description 15% Data Analysis and Interpretation 5% Summary conclusions 10% Recommendations extra 2% Reflection Introduction – sub-sections • • • • • • • Rationale for the study Research aims and objectives Research strategy Methodology - summary Key results and conclusions Practical aspect of the project Limitations of the study Possible research aims and objectives • • • • • • Develop a system of practical recommendations Design an algorithm (Action Plan) of process implementation Propose new methodology, framework, theory Analyze the existing alternative methodologies Compare the various approaches and theories Study the best practices Context of Research – Market Analysis Subsections (world – Russian economy – sector) “Rich picture” – the context (players, links, expert views on developments etc) PEST, SWOT – in Appendices Quotations! Diagrams! Frameworks from assignments! Logical links: relevance and strategic/practical importance of the study; focus of the literature review, methods of data analysis Literature review • 70+ sources recommended • Both analytical/business reports and research papers • Well-structured sections with short summaries • Clear links to the study after each piece of analysis/framework description • Initial conclusions (summary section that is directly linked to the next Chapter) Methodology • Sub-sections: research strategy, research instruments, data collection process, research novelty, limitations, suggestions for further research • Research parameters: paradigm, qual/quant, etc • Illustrate the use and the sequence of instruments and approaches • Clearly explained and possibly justified instruments • Results of each stage of the study • Clear links to literature review and data used Developing the questionnaire 1. Formulating the expected results (what do we need to get) 2. Identifying the sample (what groups are we going to ask) 3. Structuring the questionnaire and detailing each section 4. Choosing the type of survey administration 5. Choosing the measurement type and scale 6. Design of the questionnaire (plus the cover letter to respondents) 7. Testing (e.g., pilot) and adjusting the instrument Developing the questionnaire Data: organization and processing • Clearly explained sources and types of the data used • Structured section on data presentation (a table) • Primary and secondary data • Qualitative and quantitative data • Instruments for data processing • The analysis should clearly lead to the conclusions and then to recommendations Conclusions and Recommendations • Two separate sections (or even chapters) • No new ideas, sources, etc. • Summary of the project findings • Explaining how the research activities helped achieve the results • Recommendations structured according to your propositions/research questions • Clear links to the other parts of the document Recommendations • Structure by groups of users (top management, owners, etc.) • Be practical and specific (avoid phrases like “look for synergies”, “increase efficiency”, “establish good relations with…”) • Assess feasibility (“hire additional consultants”, “launch marketing campaign”) • Whenever possible, provide an Action Plan Important elements of the study • Novelty of the research (link to the literature) new data used new research methods applied new object studied new criteria developed • Practical aspect of the research recommendations for implementation feasibility Action Plan Practical results are extremely important – please describe in details Practical result… recommendations model action plan strategy solving specific problem organizational structure motivation system methodology etc. …aimed to improve efficiency increase productivity ensure quality achieve profits optimization (reorganization) develop corporate culture create innovation potential build image (brand) etc. Quantitative/Qualitative research Quantitative research Relatively more objective Measuring the parameters that describe the phenomenon under study Numerical data collected and processed with statistical instruments Qualitative research Relatively more subjective The personality of the researcher influences the results obtained Understanding and interpreting phenomenon under study Positivist and Interpretivist Paradigms Positivist (Objectivist) Quantitative data are usually used Large samples Related to hypotheses testing The data are concrete and objective The research is done in artificial environment High level of reliability Potentially low level of validity Generalization: from sample to universe Interpretivist (Subjectivist) Qualitative data are usually used Small samples Related to generation of theories Data are unstructured and subjective The research is done in natural environment Low level of reliability High level of validity Generalization: from one sample to another sample Triangulation as a source of objectivity • Triangulation of data: time of collection, various sources • Triangulation of views: research participants could have different opinions depending on the focus • Triangulation of theoretical base: using more than one theory (model, framework) tin your project • Triangulation of methodological approach: using more than one method of data collection and processing (secondary vs. primary data, quantitative and qualitative methods, etc.) Project Methodology: Quantitative data Exploratory work – data identification Data collection Data description - Methodology Data processing Conclusions and Recommendations Quantitative research is concerned with counting and measuring things, producing in particular estimates of averages and differences between groups Quantitative research is "a formal, objective, systematic process in which numerical data are utilised to obtain information about the world“ (Burns and Grove cited by Cormack 1991 p.140) Objectivity, deductiveness, generalisability and numbers are often associated with quantitative research Deduction – researcher starts with a theory, generates hypotheses and formally tests these with data Positivism – dominant philosophy underlying quantitative scientific methods It assumes that phenomena are measurable using the deductive principles of the scientific method Methodologies under this paradigm are referred to as quantitative Methodological Choices research paradigm positivism deductive experiment survey research approaches research strategies time horizons data collection methods cross sectional sampling secondary data observation interviews questionnaires case study grounded theory longitudinal action research inductive adapted from Saunders et al. (2002, p. 83) Development of a theory that is subjected to a rigorous test Hypothesis Researcher independence Get a feel of what is going on Interview Try to make sense of findings Develop theory interpretivism Data validity and reliability • Validity: determines whether the research truly measures what it was intended to measure • Reliability: • the degree to which a measurement, given repeatedly, remains the same • the stability of a measurement over time • the similarity of measurements within a given time period Other characteristics of data • Relevance • Level of disaggregation • Dynamics • Comparability • Consistency Successful data analysis requires Understanding a variety of data analysis methods Planning data analysis early in a project and making revisions in the plan as the work develops Understanding which methods will best answer the study questions posed, given the data that have been collected Once the analysis is finished, recognizing how weaknesses in the data or the analysis affect the conclusions that can properly be drawn Secondary data – any information collected for the purposes not related to your research Documents (both published and unpublished) – articles, Internet-reviews, etc. Business and government reports, official statistics, etc. Results of specific past surveys, numerical data (e.g., company database, cash receipts) Primary data Information collected specifically for the research under the project Qualitative data collection – focus groups, in-depth interviews, observation with protocols Quantitative data collection – questionnaires (surveys); documenting the views of the respondents on the issues illustrated within the questionnaire (both face-to-face and distant) Clearly organize the presentation of data processing results – e.g., by groups of respondents Sales volume goes down External reasons Economic crisis Changes in customer preferences Internal reasons Improper strategy Inefficient management Lack of skills and competences Activities by competitors Operational problems Activities by state/regulators Marketing mistakes Ishikawa (fishbone) diagram How to measure attitude Ranking Rating Sorting Choice Measuring attitude Ranking – respondents put the objects in order by a factor proposed within the questionnaire Rating – respondents assign specific numerical value to a statement or an object Sorting – grouping the objects by a factor proposed by the researcher Choice – choosing among two or more alternatives Types of variables • Nominal (classifying) - e.g., color, town • Ordinal - e.g. larger/smaller • Interval (Relative) - e.g. length, duration Histogram as the simplest way to describe the distribution Horizontal bar chart Examples of nominal data collection 1. Please state your gender male female Daily turnover of consumer is… [ ] Between 100 – 200 2. Please indicate your favorite brand: Sony Panasonic Samsung Sharp [ ] Between 200 – 300 [ ] Above 300 3. Do you agree that the image of the company is important for your choice: agree disagree Ordinal scales Rank the following attributes (1 - 5), on their importance in a microwave oven Company Name Functions Price Comfort Design The most important attribute is ranked 1 by the respondents and the least important is ranked 5 Instead of numbers, letters or symbols too can be used to rate in a ordinal scale Such scale makes no attempt to measure the degree of favorability of different rankings Interval or Rating scales: Thermometer How do you rate your present refrigerator for the following qualities Company Name Less Known 1 2 3 4 5 Well Known Functions Few 1 2 3 4 5 Many Price Low 1 2 3 4 5 High Design Poor 1 2 3 4 5 Good Overall Satisfaction Very dissatisfied 1 2 3 4 5 Very satisfied Likert Scales Survey administration Survey Self-administered By the researcher Filling the e-form Phone By fax Face-to-face structural interview Personal mailing Sampling ■ When undertaking any survey, it is essential that you obtain data from people that are as representative as possible of the group that you are studying ■ Your survey data will only be regarded as useful if it is considered that your respondents are typical of the population as a whole Sample size depends on: ■ Methodology selected ■ Degree of accuracy required for the study (how much error can be tolerated) ■ Extent to which there is variation in the population with regard to key characteristics of the study ■ Likely response rate (which itself will depend on sampling method selected) ■ Time and money available Reliability – consistency of response ■ A person would answer the same way, if given the question on different occasions ■ Ambiguous wording may produce unreliable responses Validity - A valid question is one that measures what we think it does ■ Does the question actually measure what we are asking? Or is it affected by other factors? ■ For example, does an IQ test actually measure intelligence? (or is the score affected by cultural background, social class etc) Qualitative data collection and processing Focus groups - informal discussions in which a moderator probes peoples' attitudes on a specific topic; the group is “typical” in accordance with the desired socio-demographic parameters In-depth interviews – unstructured personal conversation with respondent with detailed discussions (recording recommended) Protocol analysis – placing a respondent in a decision-making situation; respondent is asked to provide detailed description of factors that have been considered during the process Observation – describing and registering various types of data by observing the process Case study ■ Intensive analysis of an individual unit (e.g., a company, • team, or project) – practical, problem-solving orientation; generation and testing of hypotheses; holistic approach that uses multiple theories and methods Content analysis • ■ Research methodology that examines words or phrases within a wide range of texts. Researchers quantify and analyze the presence, meanings and relationships of such words and concepts, then make inferences about the messages within the texts Key methods of quantitative analysis Tables with shares/distribution of data; Correlation analysis (e.g., calculating Pierson correlation coefficients measuring interdependencies between variables); Regression analysis that provides quantification of dependencies (with the ultimate goal of modeling these dependencies in order to forecast certain variables); Analysis of variation - comparing means for groups Cluster Analysis - justifying the classification of objects by groups (clusters) Example of model construction 1. Document the assumptions on how the factors influence the parameter under study Demand P Parameter under study Factors = f (x, y, z, …) Independent variables 2. Compile a detailed list of possible factors – use the results of the literature review 3. Identify the factors relevant in your case (either through expert opinion or statistically) Factors influencing consumer choice Demand Usefulness Quality Social value Entertainment … … … … Image … Indicators – questions for the interviews/surveys Price … Linear regressions Regression modeling: looking for dependencies X3 Y X2 X1 Y = b0 + b1X1 + b2X2 + . . . + bnXn+ Y – dependent variable, Xi – independent variables, - error Factor analysis Main applications: ■ To reduce the number of variables ■ To detect structure in the relationships between variables (to classify them) ■ Note that cluster analysis groups cases; factor analysis groups variables Hypotheses Hypotheses are propositions about relationships between variables or differences between groups For example: do patients treated with drug A show greater improvement than those treated with Drug B Creating a testable hypothesis We tend to start from a general, vague question Need to turn this into something specific and appropriate Two things we need to specify: Independent variable (the aspect of the environment that we are interested in) Dependent variable (the behaviour that we are interested in) A framework for assessing the quality of qualitative research Credibility Does the way you present your findings give the impression that they are well grounded? Validity Does the work reflect the reality of the issue or situation being investigated? Quality of your findings Reliability Would it be possible for the work to be repeated and obtain the same or similar results? Generalisability How applicable are the findings to the wider world outside the one you have considered? Checklist Обоснуйте актуальность планируемого исследования (для кого и почему) В чем состоит научное и практическое значение данного исследования? В чем будет заключаться основной вклад планируемого исследования? Объясните, как планируемого исследование связано с существующими знаниями в области менеджмента, экономики и т.д.; Каким образом литературный обзор связан с целями и задачами, а также с методологией исследования? Какая ключевая гипотеза была выдвинута и почему? Обоснуйте выбор методологии и информационной базы исследования; Какие методы или процедуры анализа информации Вы планируете применить и почему? Что Вы планируете получить в результате исследования (прогноз результатов)? Какие допущения и ограничивающие обстоятельства присущи данному исследованию и как это повлияло на выбор методологии исследования?