Purpose The purpose of this study is twofold. The first is to provide a structured review of the vast amount of outsourcing literature that has accumulated in the past two decades using a decision support framework. The second purpose is to statistically analyze the contents of the studies to identify commonalities as well as gaps, in order to suggest directions for future research. Design/methodology/approach The contents of more than 200 publications are analyzed using a variety of approaches. A decision support framework is used to first classify whether the studies address outsourcing benefits, risks, motivations or factors. Next, each classification is further described by the type of benefits, risks, etc. Additional relevant contents such as type of organization, and the location of the outsourcing practice are also considered. Multivariate analyses consisting of cross tabulations, chi-square testing and cluster analysis are used for categorizing the studies with the aim of identifying relationships among the studies which are not apparent when they are considered individually. Findings A number of trends and relationships are identified. For example, most studies focus on US for-profit organizations and are typically theoretical, discussing benefits, risks and motivators. On the other hand, the research on outsourcing practices of non-profit organizations, where objectives for outsourcing are typically politically driven, is found to be scarce. Furthermore, the results of the cluster analysis indicate that the studies can be grouped into six clusters where the five small clusters are characterized by strong relationships with a few variables while the large cluster is characterized by variables that are not addressed in the studies. Practical implications Outsourcing has become commonplace in today's businesses. In addition to outsourcing in profit seeking organizations, there is considerable outsourcing effort in governmental and non-profit organizations also. It is not easy for managers who are exploring outsourcing opportunities for the very first time and academicians who want to build upon existing studies to search the literature to find what they are looking for. This study addresses this difficulty by providing different classifications of the literature based on a variety of research criteria. Originality/value This study is a first attempt to organize the outsourcing literature using statistical as well as decision support tools. Using cluster analysis and discriminant analysis to explore the relationships among the contents of the studies is a new approach.
All Science Journal Classification (ASJC) codes
- Strategy and Management
- Decision support systems
- Multivariate analysis