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on Project, Program and Portfolio Management |
| By: | Tite, Caroline N J; Pontin, David; Dacre, Nicholas |
| Abstract: | Sustainability is focussed on avoiding the long-term depletion of natural resources. Under the terms of a government plan to tackle climate change, a driver for improved sustainability is the cut of greenhouse gas emissions in the UK to almost zero by 2050. With this type of change, new themes are continuously being developed which drive complex projects, such as the development of new power generation methods, which encompass challenging lead times and demanding requirements. Consideration of the implementation of strategies and key concepts, which may engender sustainability within complex projects therefore presents an opportunity for further critical debate, review, and application through a project management lens. Sustainability incorporation in project management has been documented in academic literature, with this emerging field providing new challenges. For example, project management education can provide a holistic base for the inculcation of sustainability factors to a range of industries, including complex projects. Likewise, practitioner interest and approaches to sustainability in project management are being driven by the recently Chartered Association for Project Management (APM). Whilst this body makes a significant contribution to the UK economy across many sectors, it also addresses ongoing sustainability challenges. Therefore, by drawing on research and practitioner developments, the authors argue that by connecting with the next generation through practice simulation approaches, and embedding sustainability issues within project management tools and methods, improved focus on sustainability in complex project management may be achieved. |
| Date: | 2021–02–22 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:b4gya&r=all |
| By: | Kockum, Fredrick; Dacre, Nicholas |
| Abstract: | The era of Big Data has provided business organisations opportunities to improve their management processes. This developmental paper is adopting a mixed-method research approach where qualitative data will underpin a quantitative questionnaire. The early insights are based on an initial eleven qualitative interviews and conceptualised in the following three statements: (i) Project practitioners need to increase their data literacy; (ii) Project practitioners are not utilising the available Big Data based on the 3 Vs; Volume, Velocity and Variety; (iii) Project practitioners need to utilise the structured available data to augment the decision-making process to represent the complex environment of Big Data, the study adopts Complexity Theory as a theoretical framework. When completed, the research will demonstrate the results through System Dynamics modelling. |
| Date: | 2021–01–14 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:k3h9r&r=all |
| By: | Dacre, Nicholas; Kockum, Fredrik; Senyo, PK |
| Abstract: | Large scale projects increasingly operate in complicated settings whilst drawing on an array of complex data-points, which require precise analysis for accurate control and interventions to mitigate possible project failure. Coupled with a growing tendency to rely on new information systems and processes in change projects, 90% of megaprojects globally fail to achieve their planned objectives. Renewed interest in the concept of Artificial Intelligence (AI) against a backdrop of disruptive technological innovations, seeks to enhance project managers’ cognitive capacity through the project lifecycle and enhance project excellence. However, despite growing interest there remains limited empirical insights on project managers’ ability to leverage AI for cognitive load enhancement in complex settings. As such this research adopts an exploratory sequential linear mixed methods approach to address unresolved empirical issues on transient adaptations of AI in complex projects, and the impact on cognitive load enhancement. Initial thematic findings from semi-structured interviews with domain experts, suggest that in order to leverage AI technologies and processes for sustainable cognitive load enhancement with complex data over time, project managers require improved knowledge and access to relevant technologies that mediate data processes in complex projects, but equally reflect application across different project phases. These initial findings support further hypothesis testing through a larger quantitative study incorporating structural equation modelling to examine the relationship between artificial intelligence and project managers’ cognitive load with project data in complex contexts. |
| Date: | 2020–09–02 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:pagbm&r=all |
| By: | Blumenthal, Benjamin |
| Abstract: | Politicians are expected to implement projects that benefit their constituents. These projects’ benefits sometimes partially accrue to interest groups and not entirely to voters. Since these projects are costly to implement, this provides an incentive for interest groups to intervene in the policy-making process by offering legislative subsidies to politicians. In addition, voters are frequently ill-equipped to scrutinise politicians’ actions and can often only imperfectly monitor them. This paper shows how these considerations interact in a stylised two-periods political agency model with moral hazard and adverse selection. I show how and when voters benefit from the existence of self-interested interest groups and of their involvement in the policy-making process. I also consider how voters monitor politicians in the presence of interest groups that might capture projects’ benefits. |
| Date: | 2021–04–05 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:ydfbs&r=all |
| By: | Bobtcheff, Catherine; Mariotti, Thomas; Levy, Raphaël |
| Abstract: | Two players receiving independent signals on a risky project with common value compete to be the rst to innovate. We characterize the equilibrium of this preemption game as the publicity of signals varies. Private signals create a winner's curse: investing rst implies that the rival has abstained from investing, possibly because he has privately received adverse information about the project. Since players want to gather more evidence in support of the project as a compensation, they invest later when signals are more likely to be private. Because of preemption, the NPV of investment is zero at equilibrium regardless of the publicity of signals. However, for a conservative planner who cares about avoiding unprotable investments, this implies that investment arises too early at equilibrium, and such a planner then prefers signals to be private. This provides a rationale against the mandatory disclosure of negative results in science, notably when competition is severe. Our results suggest that policy interventions should primarily tackle winner-takes-all competition, and regulate transparency only once competition is suciently mild. |
| Date: | 2021–04 |
| URL: | http://d.repec.org/n?u=RePEc:tse:wpaper:125474&r=all |