Research and Teaching Opportunities in Project Management

Hall, Nicholas G.

doi:10.1287/educ.2016.0146

Cited by 25 publications

(9 citation statements)

References 210 publications

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“…Brown et al (2009) and Gutin et al (2014) study a related problem in which one agent attempts to hinder another agent's project by delaying its activities. Hall (2016) also highlights secret project management as a novel area offering numerous interesting research questions.…”

Section: Relevant Work From the Literature On Project Planningmentioning

confidence: 99%

Deciding on scheduling, secrecy, and patenting during the new product development process: The relevance of project planning models

Hermans

Leus

Looy

2023

Omega

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Section: Relevant Work From the Literature On Project Planningmentioning

confidence: 99%

Deciding on scheduling, secrecy, and patenting during the new product development process: The relevance of project planning models

Hermans

Leus

Looy

2023

Omega

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“…We next highlight another application of the methodology developed in this study and use it to illustrate the relative benefits of project expediting (or “project crashing”) across CMI projects with varying percent‐done and project risk (Hall 2016). Many project managers are likely to be faced with the reality of a finite amount of resources, whether those resources be money, engineers, or something else; that is, if one activity is to be sped up, it may result in another activity being slowed (Tibben‐Lembke and Mitchell 2007).…”

Section: Application Of the Model To CMI Projectsmentioning

confidence: 99%

“…Our paper is also related to the literature on project management. Hall (2016) provides a comprehensive survey of current research in this area. The project management literature has explored resource allocation and project selection decisions (Chien 2002), funding criteria in sequential R&D projects (Roberts and Weitzman 1981), option valuation (Huchzermeier and Loch 2001), and project risk management (Sommer 2008).…”

Section: Introductionmentioning

confidence: 99%

Capacity Investment under Bayesian Information Updates at Reporting Periods: Model and Application

Vedantam

Iyer

2021

Production and Operations Management

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We consider capacity addition decisions by a new product manufacturer faced with uncertain technology alternatives. The manufacturing capacity addition and technology development occurs in parallel, with preliminary results from a technology project's success providing valuable information to the manufacturer in adding capacity. We solve a stochastic dynamic program with Bayesian updates to obtain the manufacturer's expected profit‐maximizing capacity investment decision. Our model and applications are motivated by the Critical Materials Institute (CMI) (funded by the Department of Energy), which manages research projects focused on mitigating critical material constraints, vital to renewable energy technologies such as direct‐drive wind turbines, electric vehicles, and energy‐efficient lighting. We capture three unique aspects of the problem: first, the learning from project progress depends on task‐based stochastic outcomes and a project's percent‐done. Second, the underlying technology's profitability is based on a model of competition. Third, we evaluate the impact of progress across a portfolio of projects based on a manufacturer's capacity addition. We develop a heuristic that produces results that are close to optimal and can thus be used for large problem sizes. The managerial insights from an application of our model to CMI projects include: (i) technology projects that report the percent‐done of a project earlier increase expected manufacturer profit; (ii) careful choice of “safe bets,” that is, technologies with low profitability but a high probability of success, can increase expected manufacturer profit; (iii) a portfolio of projects can increase profits significantly over separate project evaluation; and (iv) dynamic management of project resources can increase overall profit.

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“…Although contractors of project activities are all independent entities, Hall (2016) points out that if contractors cooperate by sharing resources and coordinating scheduling, they can gain more revenue or save costs. Bergantiños and Sânchez (2002) study the distribution of cost caused by the delay of a project among the firms involved, based on cooperative game theory.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Revenue sharing for resource reallocation among project activity contractors

et al. 2020

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Outsourcing project activities to contractors has become more and more popular in recent years, and activity contractors can increase the revenue of a project through cooperation. In this paper we consider cooperation between activity contractors through resource reallocation, and address two main issues. First, we seek to find the optimal scheme for resource reallocation among contractors. To this end, a linear programming model is established, and some properties of the optimal resource reallocation scheme are discussed. Second, we propose several revenue sharing schemes for contractors based on a cooperative game theory framework. Three schemes are introduced and compared: a scheme in the core, the Shapley value, and a proportional revenue sharing scheme. We show that the cooperative game of activity contractors in a general project network does not necessarily have a nonempty core. However, we identify a special class of project network for which the core of the cooperative game of activity contractors always exists and an allocation in the core is proposed based on shadow prices. The managerial insights we obtain in this paper are as follows. (i) Contractors should cooperate.

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Research and Teaching Opportunities in Project Management

Cited by 25 publications

References 210 publications

Deciding on scheduling, secrecy, and patenting during the new product development process: The relevance of project planning models

Deciding on scheduling, secrecy, and patenting during the new product development process: The relevance of project planning models

Capacity Investment under Bayesian Information Updates at Reporting Periods: Model and Application

Revenue sharing for resource reallocation among project activity contractors

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