Researching and writing a dissertation

‘The focus on the research process makes this book very valuable for students It offers valuable guidelines on how to refine a research topic and write a critical review.’ Garance Maréchal, The University of Liverpool Management School ‘Broad coverage with good illustrative examples… well written, with a humorous touch.’ Diane O’Sullivan, Glamorgan Business School Researching and Writing a Dissertation is a concise, engaging and pragmatic introduction for business students who have to write a dissertation or research paper during their studies A dissertation is a substantial part of a business qualification and as a student you may be looking for support and guidance as you embark on such a sustained piece of academic work This book takes an extremely practical, skills-based approach to both researching and writing a dissertation This fully updated new edition guides the development of your dissertation, step-by-step – starting with how to choose your topic and carry out a critical literature review, through to framing your arguments and writing up your findings KEY FEATURES: • • • • • • New to this edition: an extra chapter focused entirely on using the latest technology and software to aid your research Six basic steps to help you build your dissertation Examples throughout of what to – and what not to do! Exercises with suggested answers to encourage the development of essential skills Explanations of how a dissertation is assessed Acknowledges the reality that project work is rarely sequential and advises on how to juggle several stages at once Researching and Writing a Dissertation AN Essential Guide FOR BUSINESS STUDENTS Colin Fisher ThirD Edition Fisher Colin Fisher is Professor of Managerial Ethics and Values at Nottingham Business School, Nottingham Trent University, and has helped hundreds of students through their master’s, MBA and doctoral projects Researching and Writing a Dissertation Laxmi Rao, studying for a master’s degree in IT Management from Mälardalen University, Sweden An essential guide for business students ‘I found this book very useful, well structured and easy to read It covers all the key areas of writing in an academic way, and the chapter on doing a literature review was particularly helpful for my dissertation.’ Third Edition www.pearson-books.com CVR_FISH3431_03_SE_CVR.indd 18/12/09 11:17:22 Researching and Writing a Dissertation We work with leading authors to develop the strongest educational materials in management, bringing cutting-edge thinking and best learning practice to a global market Under a range of well-known imprints, including Financial Times Prentice Hall, we craft high-quality print and electronic publications which help readers to understand and apply their content, whether studying or at work To find out more about the complete range of our publishing, please visit us on the World Wide Web at: www.pearsoned.co.uk Researching and Writing a Dissertation An essential guide for business students Third edition Colin Fisher with John Buglear and Diannah Lowry Alistair Mutch Carole Tansley Pearson Education Limited Edinburgh Gate Harlow Essex CM20 2JE England and Associated Companies throughout the world Visit us on the World Wide Web at: www.pearsoned.co.uk First published 2004 Second edition 2007 Third edition 2010 © Pearson Education Limited 2004, 2010 The right of Colin Fisher to be identified as author of this work has been asserted by him in accordance with the Copyright, Designs and Patents Act 1988 All rights reserved No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without either the prior written permission of the publisher or a licence permitting restricted copying in the United Kingdom issued by the Copyright Licensing Agency Ltd, Saffron House, 6–10 Kirby Street, London EC1N 8TS All trademarks used herein are the property of their respective owners The use of any trademark in this text does not vest in the author or publisher any trademark ownership rights in such trademarks, nor does the use of such trademarks imply any affiliation with or endorsement of this book by such owners ISBN: 978-0-273-72343-1 British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data Fisher, C M (Colin M.) Researching and writing a dissertation : an essential guide for business students / Colin Fisher with John Buglear [et al.] 3rd ed p cm Includes bibliographical references and index ISBN 978-0-273-72343-1 (pbk.) Dissertations, Academic Business Research Report writing I Buglear, John II Title LB2369.F537 2010 808'.02 dc22 2009042463 10 14 13 12 11 10 Typeset in typesize/font by 30 Printed by Ashford Colour Press Ltd., Gosport The publisher's policy is to use paper manufactured from sustainable forests Contents Acknowledgements ix Introduction Who is this guide for? What does doing a dissertation involve? The process of doing a dissertation What does working at Master’s level mean? The assessment criteria The learning outcomes and assessment criteria Jargon, ‘isms’ and ‘ologies’ How to use this guide Suggested reading Other recommended books References 3 11 12 15 27 28 29 29 Choosing a topic and designing the project 31 Introduction Choosing a topic Criteria for choosing a topic A six-stage process for choosing your topic Designing your project Modes of knowledge The researcher’s role Methodological stance Breadth or depth Choice of research methods Ethical considerations Writing the research proposal Summary Suggested reading References 32 33 33 35 42 42 48 49 69 71 72 84 87 88 88 vi Contents Writing a critical literature review Introduction The sources Searching for literature Mapping and describing the literature Describing the literature Assessing the quality of an article or book Forensic critique Soundness of arguments Evaluating arguments Radical critique The critical approach by Alistair Mutch Developing a radical critique Summary Suggested reading References 91 92 94 97 100 100 106 108 108 111 119 119 122 131 131 131 Concepts, conceptual frameworks and theories 133 Introduction The roles of theory and conceptual frameworks Developing conceptual frameworks Defining concepts Conceptual frameworks Theories Seeking inspiration: using your ‘intellectual baggage’ Examples of the use of conceptual frameworks An example of conceptualising and theorising in a study of organisational cultures Another example Summary Suggested reading References 134 136 139 140 141 148 149 155 Collecting and analysing research material Introduction Discoverers Structure of the chapter 155 159 164 164 164 167 168 169 173 Contents The range of research methods Interviews Panels Questionnaires Documentary research Observational research Deciding whether to use open or pre-structured methods Planning and setting milestones Exploratory research methods Collecting the material Interpretative approaches Analysing the material Survey research: pre-coded and structured research methods Collecting the material Analysing the material: basic statistical analysis of data by Diannah Lowry Summary Suggested reading References Interpreting the research material Introduction Choosing an interpretive grid Styles of interpretive grid and the problem of ‘universals’ Realism Nominalism Critical realism Mixing interpretive grids The validity and authenticity of research material Saying what you mean Saying what is valid Improving the validity of research findings Dialectical critique Framing conclusions and recommendations Problems of implementation Accepting the limitations Summary Suggested reading References vii 174 174 175 176 177 177 181 181 182 182 187 196 207 207 226 240 241 241 243 244 248 250 252 257 261 265 267 267 271 276 280 285 288 290 290 291 291 viii Contents Framing arguments and writing up Introduction Structuring your dissertation Writing a thesis, not just a dissertation Constructing arguments Constructing dialectical arguments Supporting your arguments Style guide Dissertation, report and paper specifications Style hints Summary Suggested reading References Using software for research 293 294 295 298 299 301 304 316 316 318 327 328 328 329 Introduction Using Minitab and SPSS to analyse survey results by John Buglear Software for analysing qualitative material by Carole Tansley Summary References 330 415 426 426 Index 427 331 Acknowledgements I tried the patience of my friends at Nottingham Business School by constant requests for feedback They replied with good humour, useful feedback and new material I wish to thank Alistair Mutch, Diannah Lowry, John Buglear and Carole Tansley especially for writing whole sections of this book John and Carole have written completely new sections for this third edition All the contributions by colleagues are acknowledged in the text Among other colleagues, and ex-colleagues who have moved to other universities, I wish to thank are Jim Stewart, Tony Woodall, Val Caven, Denise Fletcher, Sue Kirk, Suzanne Tietze and John Leopold Many thanks also to Christos Athanasoulis for his helpful advice Tony Watson deserves particular thanks It was only when I was writing the first edition of the book that I realised what an influence he has been on my thinking in the twenty and more years we had worked together at Nottingham Business School Nevertheless, neither he nor any other colleague is responsible for errors or misunderstandings that might have found their way into this guide Much of any practical wisdom to be found in this guide comes from the many postgraduate students I have worked with at Nottingham Business School when they were doing their dissertations Many thanks are due to them In particular I want to thank Alastair Allen who allowed me to use some of his research material to illustrate points about conceptual framework building Finally, I would like to thank the reviewers (both academic and student) who made valuable comments and suggestions on the second edition which have helped to shape and revise this third edition In particular: Lecturers ● ● ● ● ● ● Dr Garance Marechal, University of Liverpool Management School Michael Le Duc, Malardalen University, Sweden Caroline Hodgson, Hope Business School, Liverpool Hope University Diane O’Sullivan, University of Glamorgan Business School Dr Jennifer Tomlinson, Leeds University Business School Howard Jackson, University of Huddersfield Business School 422 Chapter • Using software for research Figure 7.134 Hierarchical coding Free nodes are useful to allocate when we are not sure of the whole picture and are trying to capture emerging themes which we might explore in greater depth later through more empirical research or which we might decide to set aside, at least for the moment unless more information becomes available which shows that this is a concept or theme worthy of raising in importance As the researcher continues to compare the concepts being examined with those that have already been coded, they will begin to get a sense of hierarchies of codes Alternatively, the researcher might already be working with a model in mind and know which concepts are relevant and how they are related to each other In both these cases the researcher can use what are called ‘tree nodes’ As can be seen from the NVivo screenshot in Figure 7.134, these are nodes that are catalogued in a hierarchical structure, moving from a general category at the top (the parent node) to more specific categories (child nodes) later, thus beginning to identify hierarchies of relationships between concepts This can reduce the number of concepts to be handled and provide a stronger conceptual basis to the themes discovered Axial coding As the researcher is working inductively, trying to develop ideas, concepts and theories from the data, ‘axial coding’ will then commence This coding process involves examining each category in terms of the context in which it occurs, any conditions which it may have caused, any actions and interactional strategies by which it is managed or handled, and the consequences which arise from the category By examining these factors, it becomes possible to link categories and to verify the linkages by testing Software for analysing qualitative material 423 them against the data It enables the researcher to ‘ground’ their theory on the data The final result of axial coding is a very rich description of the phenomenon being researched Axial coding is the process of relating codes (categories and properties) to each other, via a combination of inductive and deductive thinking Borgatti (2006) advises that to simplify this process, rather than look for any and all kinds of relations, grounded theorists emphasise causal relationships, and fit things into a basic frame of generic relationships The frame consists of the following elements: ● ● ● ● ● ● Phenomenon This is the concept that holds the bits together In grounded theory it is sometimes the outcome of interest, or it can be the subject Causal conditions These are the events or variables that lead to the occurrence or development of the phenomenon It is a set of causes and their properties Context Hard to distinguish from the causal conditions It is the specific locations (values) of background variables, a set of conditions influencing the action/strategy Researchers often make a distinction between active variables (causes) and background variables (context) It has more to with what the researcher finds more interesting (causes) and less interesting (context) than with distinctions out in the material Intervening conditions Similar to context We can identify context with moderating variables and intervening conditions with mediating variables But it is not clear that grounded theorists cleanly distinguish between these two Action strategies The purposeful, goal-oriented activities that agents perform in response to the phenomenon and intervening conditions Consequences These are the consequences of the action strategies, intended and unintended In the extract on p 420 above, it seems obvious that the phenomenon of interest is pain, the causal condition is arthritis, the action strategy is taking drugs, and the consequence is pain relief Note that grounded theorists not show much interest in the consequences of the phenomenon itself The final stage is ‘selective coding’, involving the integration of the categorised material into a theory which accounts for the phenomenon being researched This integration is done by selecting one of the categories as the focus of interest and making it the ‘core category’ or ‘storyline’ around which the rest of the categories are organised This creates a theoretical framework, which is validated against the data So in our example, the ‘storyline’ could be about how pain develops or is controlled by taking particular drugs, what causes relief and what impact not relieving the pain has on the person being studied 424 Chapter • Using software for research Analysis of qualitative data Within-case displays Explanations and causality Cross-case analysis Analysis of qualitative data The nature of qualitative data Causal models Drawing conclusions Doing qualitative Varieties of qualitative research research 20/06/2005 – a1 Design issues Collecting the data Figure 7.135 Example of a mind map Data displays Continually producing data displays is important as the research progresses Data can be displayed in a variety of ways but doing so involves placing selected or reduced data in a condensed, organised format such as a matrix, a network or a map so that it can be examined and data can be linked by connecting segments to one another to form categories, clusters of networks of information or produce theoretical models It is an important part of qualitative research, involving as it does the development of systematic, conceptually coherent explanations of findings and enabling the testing of any propositions or hypotheses A theoretical framework or frameworks can then be constructed (or, if working deductively, you can focus on concepts already in the theoretical model and look for patterns and appearances) Mind-mapping software can be useful for this, as it can enable the speedy brainstorming and capture of ideas, and the organisation of ideas in a map, and facilitate the attachment of relevant information, the creation of visually rich maps with graphics and colours and the drawing of relationships between important issues (and the software transfers to Microsoft PowerPoint slides and Word documents) Figure 7.135 shows how the maps can be built up Practical tips on using software for qualitative analysis Over the many years that I have gathered and analysed qualitative research material in the area of organisational behaviour I have found there are a number of aspects which need to be taken into consideration: ● ● Apart from a word-processing package, it is not essential to have any of these packages They just help with the organising process overall While it is useful to have access to so many different software packages one must take care that the sourcing and learning about the use of such Software for analysing qualitative material ● ● ● ● ● 425 packages does not take valuable time one should be spending doing the actual research Software and hardware can be expensive Check out if the institution you are studying with provides free access to relevant software packages – and the tutors (virtual or real!) to show you how to use them As part of the ongoing analysis, it recommended that the researcher produces memos These written, reflective commentaries will contain detailed thoughts and observations and link them to the research as a basis for deeper understanding These can be either to oneself for future consideration or to send to others, such as a tutor If these memos are stored in an analysis software package, they too can be coded, added to and changed However, not become fixated on the collection of material into databases rather than getting on with the analysis In the analysis process not allocate codes ad infinitum I know one student who did this and ended up with over 500 codes and no idea how to pull them all together as she did not analyse as she went along You need to understand the diversity of the sort of material you are working with and match the functionality of the data analysis software, for example: – If you are working inductively then you need software which enables fast search and retrieval, easy coding and revision and a good graphic display If you are working deductively, say working with hypotheses, then you will need good theory-building capability – If you envisage that you will be adding to/annotating some of the material (codes, memos, etc.), rather than having a static collection of materials (documentation, etc.), make sure the database you are using allows revising as you go along rather than having to re-create records – Take account of how flexible the software is with regard to coding ‘chunks’ of data Do you need to be able to code just one word, as well as sentences, paragraphs or whole pages or files? Then check out the functionality of the software in this case, as well as being able to identify the source of the document when you have undertaken a report of annotated text per code – If you are collecting data from many sources or doing cross-case analyses of multiple cases, then your software needs to be good at making links between phenomena and you may need to sort these into different patterns or configurations and ‘tag’ and sort them using the software’s functionality – Decide how you would like the coded items to be displayed By list? By matrix? By hierarchical tree diagram? – If you think you will continue your studies then not see this as a one-off event, but envisage that you will be using your database and the software again, for another research project or a qualification 426 Chapter • Using software for research Homepage URLs for the software mentioned in this section EndNote www.endnote.com Metamorph www.thunderstone.com/texis/site/pages/Metamorph.html NVivo www.qsrinternational.com/ Research Manager www.adeptscience.co.uk/ Sonar www.virginiasystems.com/ The Text Collector www.jaedworks.com/hypercard/scripts/ text-collector.html Wordcruncher www.hamilton-locke.com/Products.html ● ● ● ● ● ● ● Summary ● ● Consider using software packages to help you analyse your material qualitatively or quantitatively – but be careful Deciding whether the effort needed to master the software and input the research material is justified within the short amount of time available for a part-time Master’s dissertation is a fine judgement References Borgatti, S (2006) Introduction to grounded theory Available at www.analytictech.com/mb870/ introtoGT.htm (accessed 10 July 2006) Bryman, A and Cramer, D (2004) Quantitative data analysis with SPSS 12 and 13: A guide for social scientists, London: Routledge Buglear, J (2005) Quantitative methods for business: The A to Z of QM Oxford: Elsevier Jankowicz, A.D (1995) Business Research Projects London: Chapman & Hall Joiner, B., Cryer, J and Ryan, B.F (2004) Minitab handbook, New York: Brooks Cole McKenzie, J and Goldman, R (2004) The Student Guide to MINITAB Release 14, Reading, Mass: Addison-Wesley Miles, MB, and Huberman, A.M (1994) Qualitative Data Analysis: An Expanded Sourcebook, London: Sage Pallant, J (2007) SPSS survival manual, Buckingham: Open University Press Strauss, A.L and Corbin, J (1990) Basics of Qualitative Research: Grounded Theory, Procedures and Techniques, Newbury Park, Calif.: Sage Index abduction 300 academic jargon 313 academic journals non-peer-reviewed 95 peer-reviewed 95 academic monographs 95 access negotiating 73–8 to personnel or case records 74 action research 24, 47, 63–5, 66 definitions 65 typical projects 65 writing up project 297 activity sampling 180–1 actor network theory 259–60 ad hominem arguments 114–15 aims of dissertation ‘airport bookstall’ books 95 Ajanta caves 134, 135 Allen, A 153–4 Alvesson, M 122 analysing material software see software for analysing research material anonymity 80 ANOVA (F-statistic) 234 aporia 124 appendices 320 arguments ad hominem 114–15 challenging opponent’s point by extension or contradiction 112 changing meaning of term 114 construction 299–303 dialectical arguments 301–3 evaluating 111–19 forming most common flaws 111–15 proof by inconsequent argument 112 soundness 108–10 supporting 304–14 authority 304 evidence 304, 306–7 persuasive style 307–14 use of logically unsound argument 113 use of persuaders 115 assessment criteria 11–14 attitude questions, Likert scales 214–15 authenticity see validity and authenticity of research material Autoform 75 authority, arguing from 304 axial coding 422–3 balanced scorecard 146 Bales, R.F., scheme of categories 179 bar charts construction using MINITAB 344–8 boxplot 353–7 cluster bar chart 350 histogram 350–3 scatter diagram 356–9, stack bar chart 348–50 construction using SPSS 383–8 clustered bar chart 388 stack bar chart 388–9 behaviourism 19, 51 Belbin, R.M 274, 275 Bentham, J 126 Bhaskar, R 261 bibliographies 323 databases 98–9 software for recording and managing 417–18 Billig, M 276 binding 327 bivariate analysis MINITAB 362–71 SPSS 402–15 books 94–5 entry in list of references 325 Borgatti, S 420, 423 Boston Consulting Group strategic matrix 144 Bouckaert, G 204 boxes 321 boxplots MINITAB 353–7 SPSS 391–5 Buglear, J 329–426 bullet points 319 Burrell, G 26 cabbala 26, 149–50 Calás, M 129 428 Index case studies 69–71, factors to consider 70–1, and generalisations 70 interviews, realist compared with interpretative 72 pattern matching 205 use of conceptual framework 205 writing up and analysis 70, 204–7 descriptive approach 206 theoretical approach 205 Castells, M 122 categories Bales’ scheme 179 use of 179–80 category variable 228 CTV in car parks, example of critical realist interpretative grid 264 checklists question format 211 use of 178 chi-squared test 237–40 and cross-tabulation 237–9 null hypothesis 238 choosing a topic see topic, choosing citation see style guide, citation and referencing Clark, E 159–63 clichés 321 cluster bar chart 350, 388 coding 199–201, 420–3 axial coding 422–3 hierarchical coding 421–2 stages 420–3 open coding 420–2 collation, code and theory building software 416 collection of research material Contact Summary Form 418 production of field notes 418 software tools for recording and managing bibliographies 417–18 Comte, Auguste 19 concepts defining 140–1 conceptual frameworks 133–65 cause and effect 141–2 concepts as stages in process 142–3 developing 6, 139–54 defining concepts 140–1 example 153–4 theories 148–9 exchange and equilibrium 145–6 grounded approach 137, 139 hierarchical relationships 143 maps and coordinates 144–5 mistakes when creating 148 pairs and opposites 145 similarity 146–7 structural approach 137, 139 uses in case studies 205 examples 155–63, when to create 136–9 conclusions 109 drawing framing 285–90 research conclusions 285 strategic conclusions 285 conference papers, entry in list of references 326 confidentiality 80–1 confidentiality agreements 74 conflicts of interest 83 consent form 75–8 consent, informed 74–8 construct validity 272–3 constructionism 22 Contact Summary Form 418 content analysis 201–3 continuous variable 227–8 corporate social responsibility and financial performance exhibit 255–6 correlation analysis 234–6 correlation coefficient 235 correlation matrix 236 negative correlation 235 positive correlation 234 zero correlation 235 Criminal Records Bureau (CRB) 75 critical incident technique 192–3 uses 193 critical knowledge 44 critical literature review 91–132 assessing quality of article or book 106–8 description or analysis 107 precision of writing 107 provenance 106 references 106 research evidence 107–8 ‘forensic critique’ 108–19 evaluating arguments 111–19 most common flaws in argument 111–19 soundness of arguments 108–10 mapping and describing literature 100–6 argument justifying shortlist of theories, concepts etc 104 argument re literature chosen 102 critical account of chosen concepts, theories and arguments 104–5 note taking 105–6 overview of chosen literature 102–4 preparation of map 100–2 marking 93 purpose 92–3 radical critique 119–31 developing 122–5 Michael Foucault and genealogies 127–9 Index sources 94–100 bibliographic databases 98–9 books 94–5 building up list of references 100 dissertations 96 electronic journals 98 electronic library resources 97–8 electronic resources 98–100 financial and marketing databases 99–100 full-text databases 98–9 journals 95 libraries 97–8, 100 newspapers in electronic formats 99 searching for literature 97–100 World Wide Web 95–6 writing critical realism 21–2, 56–8, 122 critical realist grids 252, 261–4 critical social research 65–7 typical projects 67 Cronbach’s Alpha 215 cross-tabulations and chi-squared test 237–9 use of software 230 Dallas, M 25 data, analysis see statistical analysis of data Data Protection Act (1988) 81–2 data storage 81–2 Dawson, P 60 deception 79–80 deconstructionism 25–6 deduction 109–10, 300 deframing 195, 197 Delphi technique 176 Derrida, J 25 designing project see project design diagrams 321 dialectical analysis 123 dialectical arguments, construction 301–3 dialectical critique 276–7, 280–5 diaries 188–9 dichotomous questions 211 différance 25 digital voice recorders 184 disciplinary knowledge 43 discourse 121 discourse analysis 181, 203–4, 260–1 discovery 169–73 by exploration 169, 170–1 by surveying 169–70, 171–3 see also research methods discrete variable 227–8 disinterestedness 78–9 dispositional and trans-disciplinary knowledge 44 dissertation specification 317 dissertations, as source of material 96 distribution of questionnaire 217 429 documentary research, comparison of unstructured (open) and structured (pre-coded) 176–7 Downes, B 57 duality 145 Duberley, J 252, 268 ease of reading 314 Eco, U 100, 245, 250 ecological validity 275 electronic journals 98 electronic library resources 97–8 electronic resources 98–100 entry in list of references 326 elite interviews 80 Ellinger, A.D 192 emotionally toned words, use of 111 enactment 63 Endnote 417 engaged research 46 epistemological realism 252–6 ethical approval 73 ethical considerations 72–84 access to personnel or case records 74 analysis and reporting stages 82–3 anonymity 80 confidentiality 80–1 confidentiality agreements 74 conflicts of interest 83 data collection stage 78–83 deception 79–80 disinterestedness 78–9 informed consent 74–8 misuse of research 83 NHS 83–4 objectivity 82 permission to use video or voice recorders 81 practitioner/researcher 82 reporting stage 82–3 right to privacy 73–4 storage of data 81–2 ethnography 63, 170–1 ethnomethodologists 63 evaluation research 45–6 evidence, arguing from 304–7 explorers 169, 170–1 external validity 274–5 F-statistic 234 factual statements, distinguishing from opinion 113 false consciousness 65, 123–4 feminism 121 field notes, production of 418 financial and marketing databases 99–100 Fisher, C 57, 310–11, 320 Flesch reading ease scale 314 focus groups 175–6 footnotes 320 430 Index force field analysis 145 foreign languages 321 Foucault, M 121, 124, 126, 127–9 frameworks conceptual see conceptual frameworks definition 141 Frankfurt School 120–1 free nodes 421 front cover 316, 317 full-text databases 98–9 Gantt chart 87 Gellner, E 59–60 generalisations 70 Gibbons, M et al 43 Giddens, A 122 Gill, J 16, 68 Glaser, B.G 137 gnosticism 18–19 Gordon, W 175 grammar 322–3 greenfield sites and HRM, exhibit 253–4 grids, interpretative 244–67 choosing 248–67 critical realist 252, 261–4 mixing 265–7 nominalist 252, 257–61 realist 252–6 styles and universals 250–67 see also maps Griffiths, M 24 grounded theorists 63 Guba, E.G 273–4, 275, 276 Habermas, J 120–1, 124 Hallier, J 253–4, 275 Harvard Business Review 95 Harvard system of referencing 100 Harvey, D 26 headings 318 Hegelian dialectic 301–2 hermeneutic circle 27 hermeneutics 27, 62–3 hermeticism 26–7 hierarchical coding 422 histograms 229 MINITAB 350–3 SPSS 389–91 Huberman, A.M 21–2, 205, 418 hypotheses realist research 51–5 collection of data to test 54 measures for variables 53 negative results 54 type error 54 hypothetical questions 216 hypothetico-deductive method 52–4 Iaffaldano, M 54 ideas, getting 10 identity 121 induction 110, 300 inference words 109 informed consent 74–8 inspiration 149–52 ‘intellectual craftsmanship’ 9–11 internal validity 273–4 interpretation of research material 6, 243–92 conclusions – framing 285–90 research conclusions 285 strategic conclusions 285 grids 244–67 choosing 248–67 critical realist 252, 261–4 mixing 265–7 nominalist 252, 257–61 realist 252–6 styles and universals 250–67 maps 244–7 recommendations 285–6 problems of implementation 288–90 validity and authenticity 267–85 construct or measurement validity 272–3 ecological validity 275 external or population validity 274–5 improving 276–85 internal validity 273–4 interpretative research 47, 58–63 combined with realist research 67–8 ethnographers 63 ethnomethodologists 63 grounded theorists 63 hermeneutics 62–3 interpretivist projects, typical 63 link between understanding and action 58–9 phenomenology 62 processual perspective 60 reflective practitioners 63 interpretivism 22–3 views on 67 interviews 182, 183–7 areas of questioning 183 audio-recording 184 closed questions 186 common problems 186–7 comparison of unstructured and structured 175 elite 80 location 184–5, 186–7 open questions 186 organising 183–4 planning 183 projective techniques 187 realist compared with interpretative 72 reflective questions 186 schedule 184 Index selecting interviewees 184 semi-structured – steering 185–6 telephone 185 use of pre-coded questions 183 IT skills 35 ivory tower research 45 Jankowicz, A.D 182, 330 jargon 114, 313, 321–2 Johnson, P 16, 68, 252, 268 journals 95 entry in list of references 325 justice, seeking 46–7 Kanter, R.M 121 Kaplan, R.S., balanced scorecard 146 Katzell, R.A et al 54 Kelly, G., personal construct theory 193 Keynes, J.M 136 knowledge, modes of see modes of knowledge Kolb, D.A et al, learning cycle theory 142–3 Langmaid, R 175 language, of managers and academics 42–3 Latour, B 259–60 layout 318 leading questions 216 learning cycle theory (Kolb) 142–3 learning outcomes for dissertation module 11, 12–13 Leopold, J.W 254, 275 Lewin, K 145 libraries 97–8, 99, 100 life histories 189 Likert scales 214–15 Lincoln, Y.S 273–4, 275, 276 list of references 324–6 books 325 conference papers 326 journal articles 325 official publications 325 Web and other electronic resources 326 literature review purpose 140 see also critical literature review McClean, A 191–2 McKinsey ‘7 S’ model 146–7 McNulty, T 155–9 management jargon 313 managerial autobiography 22 maps 244–7 see also grids margin of error 222–6 adjustment factor 224 choice of acceptable 224 nomogram 223, 225 procedure if unacceptable 224 sample size 207–8 margins 318 Marshall, J 191–2 Marx, Karl 24 Marxism 120, 121, 123 Maslow, A., hierarchy of needs 143 material, interpretation material collection 6, 182–96 interpretative approaches 187–96 critical incident technique 192–3 deframing 195, 197 diaries 188–9 life historie 189 metaphors 191–2 personal construct theory 193–5, 196 shadowing 188 storytelling 190–1 survey research: pre-coded and structured research methods see questionnaire-based survey see also interviews material from exploratory research analysing 196–207 coding 199–201 content analysis 201–3 discourse analysis 203–4 writing case studies and accounts 204–7 mathematical models 19–20 mean 231 measures of dispersion range 231 standard deviation 231 variance 232 mechanisms 57–8, 59 median value 230–1, metaphors 191–2 method of research choice of 71–2, and research methodology 71 methodological approaches to research 17 action research 24 critical realism 21–2 hermeticism 26–7 interpretavism 22–3 managerial autobiography 22 phenomenology 22–3 positivism 19–20 postmodernism 25–6 realism 20–1 standpoint research 24 methodological pluralism 67–8 methodology 8, 49–69 action research 47, 63–5, 66 critical realism 56–8 critical social research 65–7 interpretative research 47, 58–63 combined with realist research 67–8 meaning of 49–50 realist research 50–5 combined with interpretative approach 67–8 431 432 Index Microsoft Word, Show readability 319 Miles, M.B 21–2, 205, 418 Milgram, S 79 Mills, C Wright 9–11 MINITAB 330, 331–71 bivariate analysis 362–71 data entry, editing and storage 332–40 description 332 tabulation, diagrams and summary measures 340–62 bar charts 344–8 tabulation data 340–4 website 371 Mintzberg, H 286–7 Mirchandani, K 24 misuse of research 83 mode of distribution 229 modes of knowledge 42–4 critical knowledge 44 disciplinary knowledge 43 dispositional and trans-disciplinary knowledge 44 technical rational knowledge 43–4 More, E 255–6, 273 Morgan, G 301 Muchinsky, P 54 multiple choice question 211–12 Mutch, A 119–22, 306–7 needs, Maslow’s hierarchy 143 negation 123 newspapers in electronic formats 99 NHS research, ethical considerations 83–4 Nietzsche, F 127 nominal variable 228 nominalist grids 252, 257–61 non-peer-reviewed publications 95, 106 Northcote Parklinson, C 52 Norton, D.P., balanced scorecard 146 null hypothesis 233 numbering 319 NVIVO 417, 419, 421 objective of dissertation observational research 177–81 activity sampling (highly structured) 180–1 categories (medium structure) 179–80, semi-structured 178 unstructured 177–8 use of checklists 178 official publications, entry in list of references 325 one-tailed test 233 open coding 420–2 open questions 216 opinion, distinguishing from factual statements 113 ordinal variable 228 orthodoxy 18–19 outcomes 57–8, 59 panels comparison of unstructured (open) and structured (pre-coded) 175 Delphi technique 176 focus groups 175–6 panoptican 125, 126 paper or report specification 316–17 paragraphs 319 linking word 319 Parker, M 126 participant information sheet 75–8 participant research 46 Pascal, B 226 pattern matching 205 Pawson, R 56, 264 PDAs 418 peer-reviewed journals 106 Peirce, C.S 299 Perry, C 320 personal construct theory 193–5, 196 personal pronoun, use of 320 personnel records, access to 74 persuaders, use of 115 persuasive style 307–14 Peters, T.J 37 phenomenology 22–3, 62 Pollert, A 121 Pollitt, 204 Popper, K 52 population validity 274–5 positivism 19–20 views on 67 postmodernism 25–6, 121 practitioner/researcher 82 premises 108 presuming questions 217 privacy, right to 73–4 probability sampling 208 process of doing a dissertation, summary 4–7 processual perspective, interpretative research 60 project, definition project design 5, 42–84 breadth or depth 69–71 case studies 69–71 choice of research method 71–2 consent form 75–78 ethical considerations 72–84 access to personnel or case records 74 analysis and reporting stages 82–3 anonymity 80 confidentiality 80–1 confidentiality agreements 74 conflicts of interest 83 data collection stage 78–83 deception 79–80 disinterestedness 78–9 informed consent 74–8 Index misuse of research 83 negotiating access 83–4 objectivity 82 permission to use video or voice recorders 81 practitioner/researcher 82 reporting stage 82–3 right of privacy 73–4 storage of data 81–2 methodological pluralism 67–8 methodology 49–69 action research 47, 63–5, 66 critical realism 56–8 critical social research 65–7 interpretative research 47, 58–63 combined with realist research 67–8 realist research 50–5 combined with interpretative approach 67–8 modes of knowledge 42–8 critical knowledge 44 disciplinary knowledge 43 dispositional and trans-disciplinary knowledge 44 technical rational knowledge 43–4 participant information sheet 75–8 random surveys 69 research engagement, levels of 45–7 engaged research 46 evaluation research 45–6 ivory tower research 45 participant research 46 seeking justice 46–7 researcher’s role 48–9 proof by inconsequent argument 112 provenance of article or book 106 QAA (Quality Assurance Agency), descriptor for Master’s degree 11–12 qualitative material, software for analysis see software for analysing qualitative material quality of article or book, assessing 106–19 description or analysis 107 precision of writing 107 provenance 106 references 106 research evidence 107–8 questionnaire-based survey 207–26 analysis see statistical analysis of data attitudes, Likert scales 214–15 comparison of unstructured (open) and structured (pre-coded) questionnaire 176–7, designing questionnaire 210–17 checklists 211 demographic information 211 dichotomous questions 211 hypothetical questions 216 leading questions 216 length 210 Likert scales 214–15 433 multiple choice questions 211–12 open questions 216 presuming questions 217 question formats 211–12 ranking questions 213–14 rating scales 212–13 semantic differential 215–16 types of question to avoid 216 distribution of questionnaire 217 drafting and piloting questionnaire 217 margin of error 222–6 adjustment factor 224 choice of acceptable 224 nomogram 223, 225 procedure if unacceptable 224 markers’ attitudes towards 225 probability sampling 208 quota sampling 208 sample size 207–8 margin of error 207–8 sampling frame 208–10 staff appraisal questionnaire – attitudes towards 218–22 systematic sample 208 use of email and Web 209–10 questions, strategic compared with research 36 quota sampling 208 quotes 320 radical critique 119–29 definition 122 developing 122–5 Michael Foucault and genealogies 127–9 random surveys 69 range 231 ranking questions 312–14 rating scales 212–13 realism 56–8, 252–6 realism, critical 21–2, 122 realist research 20–1, 50–5 combined with interpretative approach 67–8 hypotheses 51–5 collection of data to test 54 measures for variables 53 negative results 54 type error 54 typical projects 55 recommendations 285 problems of implementation 288–9 Reddin, W.J 144 Reed, M 122 referencing see style guide, citation and referencing reflexive critique 276 reflexivity 23 reflective practitioners 63 relevance tree 39 Research Manager 417 434 Index research engagement, levels of 45–7 engaged research 46 evaluation research 45–6 ivory tower research 45 participant research 46 seeking justice 46–7 research material see material research methods 71–2 comparison of unstructured (open) and structured (pre-coded) documentary research 175 interviews 175 observational research 177–81 panels 175 questionnaires 176–7 summary 174, 175 deciding whether to use open or pre-structured methods 181 planning and setting milestones 181–2 range of 174–82 times required for activities 182 see also discovery; methodological approaches to research; survey research: pre-coded and structured research methods research methods – exploratory 182–207 analysing material 196–207 coding 199–201 content analysis 201–3 discourse analysis 203–4 writing case studies and accounts 204–7 collecting material 182–96 critical incident technique 192–3 deframing 195, 197 diaries 188–9 interpretative approaches 187–96 life histories 189 metaphors 191–2 personal construct theory 193–5, 196 shadowing 188 storytelling 190–1 see also interviews research proposal writing 84–7 Watson Box 84–5, 86 research questions 37–8 compared with strategic questions 36 framing 40 researcher’s role, project design 48–9 resources 35 literature 35 Revans, R 64 rhetoric 307–11 rhetorical devices 308–11 rhetorical figures 310–11 right to privacy 73–4 Robinson, F 96 Rorty, R 245 Roy, D 188–9 Rutter, M 180 Sahay, S 260 sample size 207–8 margin of error 207–8 sampling frame 208–10 Savage, M et al 122 scatter diagrams MINITAB 356–9 SPSS 395–7 Schütz, A 62 Scott, D et al 46–7 seeking justice 46–7 semantic differential question 215–16 sense making, theory of 258 shadowing 188 Silverman, D 177, 201–2 skills required for studying at Master’s level 8–9 dealing with complex and ambiguous matters learning to learn methodology theorising Smircich, L 129 software 35 referencing 326–7 software for analysing qualitative material 415–26 coding of segments of relevant text 420–3 collation, code and theory building software 416 data displays 424 NVIVO 417, 419, 421 practical tips 424–5 text-based managers 416 theory building 419–20 tips for choosing 416–17 word processing tools 416 word-retrieving tools 416 software for analysing research material 330–426 MINITAB 330, 331–71 bivariate analysis 362–71 data entry, editing and storage 332–40 description 332 tabulation, diagrams and summary measures 340–62 SPSS 330, 371–415 bivariate analysis 402–15 data entry, editing and storage 372–9 description 371 tabulation, diagrams and summary measures 380–402 software for recording and managing bibliographies 417–18 Sokal, A 126 Somers, M.J et al 54 Soulsby, A 159–63 SPSS 330, 371–415 bivariate analysis 402–15 data entry, editing and storage 372–9 description 371 tabulation, diagrams and summary measures 380–402 Index bar charts 383–9 boxplots 391–5 histograms 389–91 scatter diagram 395–7 simple tabulation of data 380–2 website 371, 413 stack bar chart 348–50, 388–9 staff appraisal questionnaire – attitudes towards 218–22 standard deviation 231 standpoint research 24 statistical analysis of data 226–40 comparing samples and tests of significance 232–40 ANOVA (F-statistic) 234 chi-squared test 237–40 correlation analysis 234–6 cross-tabulation and chi-squared test 237–9 null hypothesis 233 one-tailed test 233 significant difference 232–3 statistical tests for categorical data 237–40 statistical tests for quantitative data 233–6 t-test 233–4 conversion of variables 228–9 summarising data 229–32 categorical data 229 histograms 229 mean 231 median value 230–1 mode of distribution 229 quantitive data 230 range 231 software 229 standard deviation 231–2 tables 229 variance 232 types of variable 227–9 category 228 continuous 227–8 discrete 227–8 independent compared with dependent 229 nominal 228 ordinal 228 see also software for analysing research material statistical generalisations 70 statistics 50 descriptive compared with inferential 226 Stewart, J 213 storage of data 81–2 storytelling 190 strategic exchange 145 strategic questions 36 compared with research questions 36 Strauss, A.L 137 structuring dissertation 295–7 writing up action research project 297 style guide 316–27, appendices 320 435 binding 327 bullet points 319 citation and referencing 323–7 footnote system 323 Harvard system 323 list of references 324–6 references in text 323–4 referencing software 326–7 Vancouver system 323 clichés 321 contents of bound dissertation 317 dissertation specification 317 footnotes 320 foreign languages 321 front cover 316, 317 grammar 322–3 headings and sub-headings 318 layout 318 numbering 319 paper or report specification 316–17 paragraphs 319 personal pronoun, use of 320 quotes 320 submission of dissertation 317 tables, diagrams and boxes 321 tenses 320 title page 318 typing 318 vocabulary and jargon 321–2 sub-headings 318 submission of dissertation 317 Subramaniyam, V 263 survey research 169–70, 171–3 analysis of data see statistical analysis of data pre-coded and structured research methods 207–40 collecting material see questionnaire-based survey systematic sample 208 t-test 233–4 tables 229, 321 Tansley, Carole 415–26 tautology 113 technical rational knowledge 43–4 telephone interviews 185 tenses 320 text-based managers 416 textbooks 94 theoretical generalisations 70 theories 148–9 definition 148 theorising stages of 134 theory building with qualitative analysis software 419–20 theory of probability 226 theory of sense making 274 thesis, definition 3, 298 Thorngate, W 290 436 Index Tietze, S 260–1, 272 Tilley, N 21, 57, 264 title page 318 topic, choosing 5, 33–42 criteria 33–5 access 34 breadth of research questions 34 durability 34 interest and relevance 33–4 micro politics 35 resources 35 risk and security 35 topic adequacy 34 morphological analysis 41 six-stage process 34–42 brainstorm issues, puzzles and questions 37–8 conduction reconnaissance 40 determination of scope 37 framing research questions 40 identifying broad topic and academic discipline 35–7 map and structure of issues 38–9 triggers 57–8 Trismegistus, Hermes 26 type error 54 type error 54 typing 318 universals, meaning of term 250–1 validity and authenticity of research material 267–85 construct or measurement validity 272–3 ecological validity 275 external or population validity 274–5 improving 276–85 collaborative resources 277 dialectical critique 276–7, 280–5 plural structure 277–8 reflexive critique 276 risk to one’s own values 277 theory, practice, transformation 278 internal validity 273–4 Van de Ven, A.H 44 variables conversion 228–9 types of 227–9 category 228 continuous 227–8 discrete 227–8 independent compared with dependent 229 nominal 228 ordinal 228 variance 232 video, permission to use 81 vocabulary 321–2 voice recorders, permission to use 81 Waddington, C.H 123 Walsham, G 259–60 Waterman, Jr R 37 Watkins, K.E 192 Watson Box 84–5, 86 Watson, T.J 70, 171 strategic exchange 145 Web resources, entry in list of references 326 Webley, S 255–6, 273 Weick, K.E 63, 258, 274 Wildavsky, A 289 Wilmott, H 122 Wilson, S.R et al (1989) 192 Winter, R 276–8 word-retrieving tools 416 World Wide Web 95–6 writing research proposal 84–7 Watson Box 84–5, 86 writing thesis/dissertation 298–316 constructing arguments 299–303 dialectical arguments 301–3 ease of reading 314 jargon 313 supporting arguments 304–14 authority 304 evidence 304–7 persuasive style 307–14 see also style guide writing up dissertation Yin, R.K 69–70, 205, 253 ... concepts and structure them in ways that give a useful theoretical shape to the dissertation; design and apply appropriate research methods and analyse the research material systematically; frame, and. .. process of researching and writing a dissertation These stages in turn reflect the six criteria that typify the standards that dissertations are marked against The guide contains a chapter for each... Interpretative approaches Analysing the material Survey research: pre-coded and structured research methods Collecting the material Analysing the material: basic statistical analysis of data by Diannah Lowry