Case and field research studies continue to be rarely published in operations management journals, in spite of increased interest in reporting such types of studies and results. This paper documents the advantages and rigor of caserfield research and argues that these methods are preferred to the more traditional rationalist methods of optimization, simulation, and statistical modeling for building new operations management theories. In the process of describing the constructs of inference and generalizability with reference to case research, we find the existing definitions inadequate and thus extend and refine them to better discriminate between alternate research methodologies. We also elaborate on methods for increasing the generalizability of both rationalist and caserfield research studies. A major conclusion is that these alternate research methods are not mutually exclusive and, if combined, can offer greater potential for enhancing new theories than either method alone. q 1998 Elsevier Science B.V. All rights reserved.Keywords: Building operations management theory; Case and field research; Rationalist methods 0272-6963r98r$19.00 q

Recently, there have been numerous calls for more empirical field‐based research to be conducted in operations management (OM). Knowledge of how operations systems work can be enhanced significantly through contact with the “real‐world” conditions that OM models seek to describe. Case study research is a primary means of exploring field conditions but is an unfamiliar methodology for many in OM. Moreover, the case study method is viewed with scepticism by those who consider it to be a weak form of research, one that lacks rigor and objectivity.Here, we offer an introduction to the case study method for OM researchers who may have little background in field based research. We provide an outline of the procedure and cite some excellent sources that cover case study design, data analysis and the philosophical rationale for the methodology. We also identify some recent examples of OM case studies that illustrate our points. We then contrast the various uses for case study research and their different design and theory requirements. An appendix provides a listing of case studies that have appeared in some OM journals in recent years, classifying the studies by their research purpose.However, regardless of their purposes, case study research need to be conducted in a manner that assures maximum measurement reliability and theory validity. We describe some of the steps that must be taken to ensure that a study is as rigorous as possible. We also argue that, properly conducted, a case study is a truly scientific research approach. We conclude by pointing out some areas of OM research where case studies might be particularly valuable.

Identifies the significant role of conceptual research methods in theory building and contrasts it with the theory‐testing research currently prevalent in operations management. The research stages of description, explanation and testing are used to distinguish between theory building and theory testing. Short‐circuiting any one of these stages results in dysfunctional research activities which produce war stories, black boxes, or ivory‐tower prescriptions. Defines some terms relevant to conceptual research methods and describes different conceptual classification schemes. Finally, discusses the differences between conceptual models, frameworks, and theories and illustrates each method with examples from the literature.

Citation analysis combined with a network analysis of co‐citation data from three major operations management (OM) journals is used to reveal the evolution of the intellectual structure of the OM field between 1980 and 2006. This spans the entire time since the beginning of research journals specific to the field. Employing a bibliometric citation/co‐citation analysis to investigate the foundations of the discipline enables a robust, quantitative approach to uncovering the evolution of research in OM. The study finds that the intellectual structure of the field made statistically significant changes between the 1980s, the 1990s, and the 2000s and evolved from a pre‐occupation with narrow, tactical topics toward more strategic, macrotopics, including new research methods and techniques. A factor analysis identifies the 12 top knowledge groups in the field and how they change over the decades. Illustrations of the structure of the co‐citations representing the field are generated from a spring‐embedded algorithm that is an improvement over the standard multi‐dimensional scaling (MDS) approach to illustrating the knowledge groups.

EXECUTIVESUMMARYDue to the heritage and history of operations management, its research methodologies have been confined mainly to that of quantitative modeling and, on occasion, statistical analysis. The field has been changing dramatically in recent years. Firms now face numerous worldwide competitive challenges. many of which require major improvements in the operations function. Yet, the research methodologies in operations have largely remained stagnant. The paradigm on which these methodologies are based, while useful, limits the kinds of questions researchers can address.This paper presents a review and critique of the research in operations, itemizing the shortcomings identified by researchers in the field. These researchers suggest a new research agenda with an integrative view of operations' role in organizations, a wider application of alternative research methodologies, greater emphasis on benefit to the operations manager, cross-disciplinary research with other functional areas, a heavier emphasis on sociotechnical analysis over the entire production system, and empirical field studies. Some of the alternative research methodologies mentioned include longitudinal studies, field experiments, action research, and field studies.Following a description of the nature of research, three stages in the research cycle are identified: description, explanation, and testing. Although research can deal with any stage in this cycle, the majority of attention currently seems to focus on the explanation stage. The paper then discusses historical trends in the philosophy of science, starting with positivism, expanding into empiricism, and then leading to post-positivism.The impacts of each of these trends on research in operations (which remains largely in the positivist mode) are described. Discussion of the importance of a plurality of research methods concludes the section.A framework for research paradigms is then developed based on two key dimensions of research methodologies: the rational versus existential structure of the research process and the natural versus artificial basis for the information used in the research. These dimensions are then further explored in terms of thirteen characteristic measures. Next, research methodologies commonly used in other fields as well as operations are described in reference to this framework. Methodologies include those traditional to operations such as normative and descriptive modeling, simulation, surveys, case and field studies as well as those more common to other fields such as action research, historical analysis, expert panels, scenarios, interviewing, introspection, and hermeneutics. Examples from operations or allied fields are given to illustrate the methodologies.Past research publications in operations are plotted on the framework to see the limitations of our current paradigms relative to the richness of other fields. We tind that operations methodologies tend to ManuscriptJournal of Operations Management lie on the more rational end of the framework while s...