An adjustable robust optimization model for the resource-constrained project scheduling problem with uncertain activity durations

This paper addresses the resource-constrained project scheduling problem with uncertain activity durations. An adaptive robust optimization model is proposed to derive the resource allocation decisions that minimize the worst-case makespan, under general polyhedral uncertainty sets. The properties of the model are analyzed, assuming that the activity durations are subject to interval uncertainty where the level of robustness is controlled by a protection factor related to the risk aversion of the decision maker. A general decomposition approach is proposed to solve the robust counterpart of the resource-constrained project scheduling problem, further tailored to address the uncertainty set with the protection factor. An extensive computational study is presented on benchmark instances adapted from the PSPLIB.     

How Software Project Risk Affects Project Performance: An Investigation of the Dimensions of Risk and an Exploratory Model*

To reduce the high failure rate of software projects, managers need better tools to assess and manage software project risk. In order to create such tools, however, information systems researchers must first develop a better understanding of the dimensions of software project risk and how they can affect project performance. Progress in this area has been hindered by: (1) a lack of validated instruments for measuring software project risk that tap into the dimensions of risk that are seen as important by software project managers, and (2) a lack of theory to explain the linkages between various dimensions of software project risk and project performance. In this study, six dimensions of software project risk were identified and reliable and valid measures were developed for each. Guided by sociotechnical systems theory, an exploratory model was developed and tested. The results show that social subsystem risk influences technical subsystem risk, which, in turn, influences the level of project management risk, and ultimately, project performance. The implications of these findings for research and practice are discussed.     

The multicriteria selection of products in technological diversification strategies: an application to the Spanish automotive industry based on AHP

The economic recession, the dynamism and complexity of the markets and the generalised globalisation of the world economy have forced many companies to rethink and reorganise their industrial strategies. Through identifying and taking advantage of the key technologies of a company, this work presents a new and original methodology for dealing with a general technological diversification process. The methodology, which includes an innovative cognitive perspective and its corresponding decisional tool (decision support system) has been used to select the best product in a process of technological diversification that, along with the key technologies, identifies the sub-levels consonant to the sub-technologies and applications to sectors and products. The multicriteria selection tool employed in the proposed methodology, based on the analytic hierarchy process, allows the integration of multiple scenarios, actors and criteria, both tangible and intangible. The methodology has been applied to a case study in the Spanish automotive auxiliary sector.