The Entrepreneur ship Paradigm (I): A Philosophical Look at Its Research Methodologies

Entrepreneurship research is still developing as a management science. This is especially visible when entrepreneurship research is compared to the disciplines from which it emerged, and it needs to develop its own methods and theories. Entrepreneurship research uses concepts garnered from diverse disciplines, which requires consideration of the central questions and the appropriate tools with which to study them. Several recommendations for research methods for an entrepreneurship paradigm are made: (1) less physics envy - avoid reductionism in entrepreneurship research and focus on the research as a whole through case studies; (2) fewer theoretical models and more empirical models - the present empirical knowledge of entrepreneurship research is inadequate for building robust theories; (3) less concern with sophisticated statistical analyses - entrepreneurial ventures begin with unique events and understanding them is one of the aims of entrepreneurship research. No amount of complex statistical analysis will substitute for field studies of the unique events; (4) more field research - entrepreneurship research will not get to the heart of the startup process unless it observed happening in the field; (5) more longitudinal studies - entrepreneurship is a process that evolves with time and doing only cross-sectional studies would cause much of the richness that comes from longitudinal studies to be lost; (6) dedicated researchers - better quality empirical research is needed that is exploratory or grounded and to achieve this more researchers are needed; (7) original field-derived data bases - it is difficult to do valid research on data bases that others have built since there may be unknown pitfalls, therefore entrepreneurship research should create its own data sets built from raw data; and (8) less obsession with revolutionary science - it is better to stress excellence in research, rather than glorifying extraordinary science and depreciating ordinary science. Excellent routine science is often more valuable than revolutionary science. (SFL)