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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.

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.

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.

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.

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.

The purpose of this paper is to analyze the impact of learning in a project‐driven organization and demonstrate analytically how the learning, which takes place during the execution of successive projects, and the forgetting that takes place during the dormant time between the project executions, can impact performance and productivity in the future.

A learn‐forget model was developed using the learning curve concept prevalent in many manufacturing processes. The model assumes that learning occurs while project tasks are being performed and forgetting takes place during dormant times between the successive implementations. The log‐linear model was adapted, with both learning and forgetting rates being a function of the doubling or tripling of output. Forgetting is inhibited through the use of knowledge transfer tools such as use of close‐out documents or content management platforms. The model is applied to a simulated project environment where a number of projects are executed sequentially, and the results are evaluated using the reduction in total duration and return on investment.

Computational results demonstrate that the learning and forgetting rates and level of project close‐out effort impact project performance, in the form of reduction in duration, much more significantly compared to the impact of the length of dormant times between the project initiations. Furthermore, even in a slow learning environment, using close‐out reports as a knowledge transfer tool, managers can achieve more than a 40 percent reduction in duration after several successive implementations.

Although the theoretical development is applicable to a general organizational setting, the empirical testing of the model is done in project‐driven organizations where projects are implemented on an ongoing basis.

Managers can significantly benefit from the findings of this study. It is shown that the accumulated learning which represents knowledge generated during the implementation of a project, if transferred successfully, improves productivity and enables faster implementation. In a project‐driven organization an almost 80 percent reduction in total duration is achievable with the use of close‐out documents. This result promotes the importance of the learning process and managers should enable their team members to learn as much as they can while implementing a task and to document it methodically.

This study constitutes an initial effort to illustrate quantitatively how the level of learning and forgetting impact performance in a project‐driven organization. This study is also original in that it methodically demonstrates the importance of spending time during the phase‐out, documenting the project artifacts, that enables knowledge transfer, and thus improves performance.