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Not many authors have attempted to classify projects according to any specific scheme, and those who have tried rarely offered extensive empirical evidence. From a theoretical perspective, a traditional distinction between radical and incremental innovation has often been used in the literature of innovation, and has created the basis for many classical contingency studies. Similar concepts, however, did not become standard in the literature of projects, and it seems that theory development in project management is still in its early years. As a result, most project management literature still assumes that all projects are fundamentally similar and that "one size fits all." The purpose of this exploratory research is to show how different types of projects are managed in different ways, and to explore the domain of traditional contingency theory in the more modern world of projects. This two-step research is using a combination of qualitative and quantitative methods and two data sets to suggest a conceptual, two-dimensional construct model for the classification of technical projects and for the investigation of project contingencies. Within this framework, projects are classified into four levels of technological uncertainty, and into three levels of system complexity, according to a hierarchy of systems and subsystems. The study provides two types of implications. For project leadership it shows why and how management should adapt a more project-specific style. For theory development, it offers a collection of insights that seem relevant to the world of projects as temporary organizations, but are, at times, different from classical structural contingency theory paradigms in enduring organizations. While still exploratory in nature, this study attempts to suggest new inroads to the future study of modern project domains.Project Management, Contingency Theory, Project Types, Project Classification, Technological Uncertainty, System Complexity

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In times of increased competition and globalization, project success becomes even more critical to business performance, and yet many projects still suffer delays, overruns, and even failure. Ironically, however, risk management tools and techniques, which have been developed to improve project success, are used too little, and many still wonder how helpful they are. In this paper we present the results of an empirical study devoted to this question. Based on data collected on over 100 projects performed in Israel in a variety of industries, we examine the extent of usage of some risk management practices, such as risk identification, probabilistic risk analysis, planning for uncertainty and trade-off analysis, the difference in application across different types of projects, and their impact on various project success dimensions. Our findings suggest that risk management practices are still not widely used. Only a limited number of projects in our study have used any kind of risk management practices and many have only used some, but not all the available tools. When used, risk management practices seem to be working, and appear to be related to project success. We also found that risk management practices were more applicable to higher risk projects. The impact of risk management is mainly on better meeting time and budget goals and less on product performance and specification. In this case, we also found some differences according levels of technological uncertainty. Our conclusion is that risk management is still at its infancy and that at this time, more awareness to the application, training, tool development, and research on risk management is needed.

Although the causes for project success and failure have been the subject of many studies, no conclusive evidence or common agreement has been achieved so far. One criticism involves the universalistic approach used often in project management studies, according to which all projects are assumed to be similar. A second problem is the issue of subjectiveness, and sometimes weakly defined success measures; yet another concern is the limited number of managerial variables examined by previous research. In the present study we use a project-specific typological approach, a multidimensional criteria for assessing project success, and a multivariate statistical analysis method. According to our typology projects were classified according to their technological uncertainty at project initiation and their system scope which is their location on a hierarchical ladder of systems and subsystems. For each of the 127 projects in our study that were executed in Israel, we recorded 360 managerial variables and 13 success measures. The use of a very detailed data and multivariate methods such as canonical correlation and eigenvector analysis enables us to account for all the interactions between managerial and success variables and to address a handful of perspectives, often left unanalyzed by previous research. Assessing the variants of managerial variables and their impact on project success for various types of projects, serves also a step toward the establishment of a typological theory of projects. Although some success factors are common to all projects, our study identified projectspecific lists of factors, indicating for example, that high-uncertainty projects must be managed differently than low-uncertainty projects, and high-scope projects differently than low-scope projects.

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