One of the most challenging decisions that a manager must confront is whether to continue or abandon a troubled project. Published studies suggest that failing software projects are often allowed to continue for too long before appropriate management action is taken to discontinue or redirect the efforts. The level of sunk cost associated with such projects has been offered as one explanation for this escalation of commitment behavior. What prior studies fail to consider is how concepts from risk-taking theory (such as risk propensity and risk perception) affect decision makers' willingness to continue a project under conditions of sunk cost. To better understand factors that may cause decision makers to continue such projects, this study examines the level of sunk cost together with the risk propensity and risk perception of decision makers. These factors are assessed for cross-cultural robustness using matching laboratory experiments carried out in three cultures (Finland, the Netherlands, and Singapore). With a wider set of explanatory factors than prior studies, we could account for a higher amount of variance in decision makers' willingness to continue a project. The level of sunk cost and the risk perception of decision makers contributed significantly to their willingness to continue a project. Moreover, the risk propensity of decision makers was inversely related to risk perception. This inverse relationship was significantly stronger in Singapore (a low uncertainty avoidance culture) than in Finland and the Netherlands (high uncertainty avoidance cultures). These results reveal that some factors behind decision makers' willingness to continue a project are consistent across cultures while others may be culture-sensitive. Implications of these results for further research and practice are discussed.

A cross-cultural study on escalation of commitment behavior in software projects

data types Sorting and searching parallel and distributed algorithms 3. [AR] Computer Architecture

/pdf/guide-to-the-software-engineering-body-of-knowledge-4x9ajlpq2m.pdf

Guide to the Software Engineering Body of Knowledge

Drawing both from the IS literature on software project risk management and the contingency research in Organization Theory literature, the present study develops an integrative contingency model of software project risk management. Adopting a profile deviation perspective of fit, the outcome of a software development project (Performance) is hypothesized to be influenced by the fit between the project's risk (Risk Exposure) and how project risk is managed (Risk Management Profile). The research model was tested with longitudinal data obtained from project leaders and key users of 75 software projects. The results support the contingency model proposed and suggest that in order to increase project performance a project's risk management profile needs to vary according to the project's risk exposure. Specifically, high-risk projects were found to call for high information processing capacity approaches in their management. However, the most appropriate management approach was found to depend on the performance criterion used. When meeting project budgets was the performance criterion, successful high-risk projects had high levels of internal integration, as well as high levels of formal planning. When system quality was the performance criterion, successful high-risk projects had high levels of user participation.

https://www.jstor.org/stable/info/40398504

An Integrative Contingency Model of Software Project Risk Management

Software risk management can be defined as an attempt to formalize risk oriented correlates of development success into a readily applicable set of principles and practices. By using a survey instrument we investigate this claim further. The investigation addresses the following questions: 1) What are the components of software development risk? 2) how does risk management mitigate risk components, and 3) what environmental factors if any influence them? Using principal component analysis we identify six software risk components: 1) scheduling and timing risks, 2) functionality risks, 3) subcontracting risks, 4) requirements management, 5) resource usage and performance risks, and 6) personnel management risks. By using one-way ANOVA with multiple comparisons we examine how risk management (or the lack of it) and environmental factors (such as development methods, manager's experience) influence each risk component. The analysis shows that awareness of the importance of risk management and systematic practices to manage risks have an effect on scheduling risks, requirements management risks, and personnel management risks. Environmental contingencies were observed to affect all risk components. This suggests that software risks can be best managed by combining specific risk management considerations with a detailed understanding of the environmental context and with sound managerial practices, such as relying on experienced and well-educated project managers and launching correctly sized projects.

Components of software development risk: how to address them? A project manager survey

Understanding software project risk: a cluster analysis

Software risk management can be defined as an attempt to formalise risk oriented correlates of development success into a readily applicable set of principles and practices. Earlier research suggests that it can reduce the likelihood of a system failure. Using a survey instrument we investigate this claim further. The investigation addresses the following questions: (1) which characteristics of risk management practices; and (2) which other environmental and process factors (such as development methods, manager's experience) relate to improved performance in managing software risks? Our findings support in general the claim that the use of risk management methods improves system development performance. Yet, little support was found for the claim that specific risk management methods are instrumental in attacking specific software risks. Overall, risks are better managed with combined measures of having experienced project managers, selecting a correct project size, and investing in and obtaining experience in risk management deliberations.

https://link.springer.com/content/pdf/10.1057%2Fpalgrave.ejis.3000253.pdf

K Lyytinen

Papers

Can software risk management improve system development: an exploratory study