nep-ppm New Economics Papers
on Project, Program and Portfolio Management
Issue of 2017‒05‒07
four papers chosen by
Arvi Kuura
Tartu Ülikool

  1. Profit-oriented scheduling of resource-constrained projects with flexible capacity constraints By Schnabel, André; Kellenbrink, Carolin; Helber, Stefan
  2. Estimating the Gains from New Rail Transit Investment: A Machine Learning Tree Approach By Seungwoo Chin; Matthew E. Kahn; Hyungsik Roger Moon
  3. The Promises and Pains in Procurement Reforms in the Philippines By Navarro, Adoracion M.; Tanghal, Juan Alfonso O.
  4. An innovation system framework for system innovation policy: the case of Strategic Innovation Programs (SIPs) in Sweden By Coenen, Lars; Grillitsch, Markus; Hansen, Teis; Moodysson, Jerker

  1. By: Schnabel, André; Kellenbrink, Carolin; Helber, Stefan
    Abstract: We consider a novel generalization of the resource-constrained project scheduling problem (RCPSP). Unlike many established approaches for the RCPSP that aim to minimize the makespan of the project for given static capacity constraints, we consider the important real-life aspect that capacity constraints can often be systematically modified by temporarily assigning costly additional production resources or using overtime. We furthermore assume that the revenue of the project decreases as its makespan increases and try to find a schedule with a profit-maximizing makespan. Like the RCPSP, the problem is $\mathcalNP$-hard, but unlike the RCPSP it turns out that an optimal schedule does not have to be among the set of so-called active schedules. Scheduling such a project is a formidable task, both from a practical and a theoretical perspective. We develop, describe, and evaluate alternative solution encodings and schedule decoding mechanisms to solve this problem within a genetic algorithm framework and we compare them to both optimal reference values and the results of a commercial local search solver called LocalSolver.
    Keywords: Project scheduling; encodings; heuristics; local-search; genetic algorithm; RCPSP; overtime
    JEL: C61 C44 M11
    Date: 2017–04
  2. By: Seungwoo Chin; Matthew E. Kahn; Hyungsik Roger Moon
    Abstract: Urban rail transit investments are expensive and irreversible. Since people differ with respect to their demand for trips, their value of time, and the types of real estate they live in, such projects are likely to offer heterogeneous benefits to residents of a city. Using the opening of a major new subway in Seoul, we contrast hedonic estimates based on multivariate hedonic methods with a machine learning approach that allows us to estimate these heterogeneous effects. While a majority of the "treated" apartment types appreciate in value, other types decline in value. We explore potential mechanisms. We also cross-validate our estimates by studying what types of new housing units developers build in the treated areas close to the new train lines.
    JEL: R21 R4
    Date: 2017–04
  3. By: Navarro, Adoracion M.; Tanghal, Juan Alfonso O.
    Abstract: This study examines procurement policy issues in light of recent concerns on delays in project implementation and underspending of government agencies. In the 2014 and 2015 reports of the Department of Budget and Management, procurement is cited as a reason for underspending. Likewise, government agencies with major underspending concerns noted "public procurement issues" as a recurring reason for the low disbursement outturn. In an attempt to make procurement less of a hurdle, Congress currently proposes to grant emergency powers to the president and do away with competitive bidding as the default mode in implementing transportation projects. However, procurement data analysis shows that in civil works procurement, the bid failure rate tends to be higher under the alternative mode of procurement than under the competitive mode, a result which does not support Congress' proposal. Key lessons from experience are also investigated through interviews with various government agencies in the implementation and execution of the Philippine procurement process. The numerous key informant interviews greatly revealed the difficulties encountered and good practices implemented under the current legislative framework. To address procurement issues, the study recommends: (1) pursuing deliberate investments in and having a political will for systems change and organizational culture change, (2) greater investment in planning and other preparatory activities before the actual procurement, (3) innovation orientation in public procurement, and (4) value-for-money procurement.
    Date: 2017
  4. By: Coenen, Lars (CIRCLE, Lund University); Grillitsch, Markus (CIRCLE, Lund University); Hansen, Teis (CIRCLE, Lund University); Moodysson, Jerker (Jönköping Business School)
    Abstract: This orientation towards grand societal challenges can be seen as a new wave or paradigm for innovation policy. Such policy is geared to the achievement of systems wide transformations and often referred to as system innovation policy. Even if policies start to be aimed at system innovation, it is unclear how to implement such policies. While insights from transition studies have provided novel and useful rationales for system innovation policy, these studies provide less guidance as to which policy instruments are effective in addressing system innovation. To translate and concretize the challenges of system innovation towards scope for policy action, we relate these challenges to three generic dimensions of innovation systems, i.e. (1) interests and capabilities of actors, (2) networks and network dynamics and (3) institutions and institutional change. These dimensions will allow us to analyze whether and how innovation policy instruments can be used to foster and expedite system innovation. We illustrate its use to identify and assess system innovation policy in practice focusing on the Strategic Innovation Program, a recent policy initiative by Vinnova, Sweden’s Innovation Agency, targeting system innovation.
    Keywords: System innovation; transition theory; innovation systems; policy; strategic innovation porgrammes
    JEL: O30 O33 O38
    Date: 2017–04–27

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