Prelims

Half Title Page

Bad to Good

Achieving High Quality and Impact in Your Research

Endorsements

As the editor of a respectable academic Marketing journal, I identify very closely with the research issues pointed out by Professor Woodside, and also strongly believe that he is moving in the right direction to ameliorate the identified problems. Woodside is a hugely experienced researcher and editor, immensely respected in the management and marketing world. His insights and wisdom are ignored at a researcher’s peril – there is a strong wind of change blowing through business research, and this book offers a clear guide to help weather the storm by conducting genuinely useful research.

– Professor Roger Marshall, Auckland University of Technology, New Zealand

A highly practical and readable book on bad practices in research and how to fix them. I particularly appreciated the focus on the following: mismatch between theory and research; non-response bias; and single outcome dependent variable. Bad to Good is a must read for scholars of any age and especially for doctoral students.

– Jagdish N. Sheth, Charles H. Kellstadt Professor of Marketing, Emory University, USA

The book is a ‘must read’ for all business researchers who want to stay on top of recent developments in quantitative research methods. Based on complexity theory tenets, the book illustrates the flaws of mainstream use of regression analysis and structural equation modeling in the development of useful theories. Examples from various fields impressively demonstrate the increase in quality of research findings coming with the use of configurational analysis.

– Dr. Hans Mühlbacher, Professor of Marketing, International University of Monaco

This is a landmark contribution to the renewal of research methodology. The bulk of research in business and management is still misguided by the positivist paradigm from the 1600s, dominated by surveys and hypothetico-deductive techniques and the claim that such research is ‘rigorous’. Unfortunately it is better characterized as ‘rigid’ and ‘ritualistic’ and it seldom has relevance for practitioners. Arch Woodside is a brave thinker who advocates a move to a complexity paradigm and that we need cases to do so and to generate theory on a more general and abstract level.

– Evert Gummesson, Emeritus Professor, Stockholm Business School, Stockholm University, Sweden

Title Page

Bad to Good

Achieving High Quality and Impact in Your Research

Edited by

Arch G. Woodside

Boston College, Chestnut Hill, MA, USA

United Kingdom – North America – Japan – India – Malaysia – China

Copyright Page

Emerald Group Publishing Limited

Howard House, Wagon Lane, Bingley BD16 1WA, UK

First edition 2016

Copyright © 2016 Emerald Group Publishing Limited

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British Library Cataloguing in Publication Data

A catalogue record for this book is available from the British Library

ISBN: 978-1-78635-334-4 (Print)

ISBN: 978-1-78635-333-7 (Online)

List of Contributors

Dedication

The Editor, Arch G. Woodside, expresses gratitude to Andy Boynton, Dean, Carroll School of Management, Boston College, for substantial course-teaching release during 2014–16 for research and writing resulting in this book.

Bad to Good is dedicated to my colleagues, the Carroll School of Management, Boston College, and to my wife, friend, and colleague, Carol Murphey Megehee.

Preface

Most of the articles in most of the scholarly journals in finance, management, marketing, and organizational studies include empirical positivistic methods and findings – and each of these empirical articles likely includes 3–10 or more bad practices that this book describes. The introductory chapter includes how to design-in good practices in theory, data collection procedures, analysis, and interpretations to avoid these bad practices. Given that bad practices in research are ingrained in the career training of scholars in sub-disciplines of business/management (e.g., through reading articles exhibiting bad practices usually without discussions of the severe weaknesses in these studies and by research courses stressing the use of regression analysis and structural equation modeling), this book is likely to have little impact. However, scholars and executives supporting good practices should not lose hope. The relevant literature includes a few brilliant contributions that can serve as beacons for eliminating the current pervasive bad practices and for performing highly competent research.