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A new evaluation and decision making framework investigating the elimination-by-aspects model in the context of transportation projects' investment choices

Author

Listed:
  • R Khraibani

    (UCP - Université de Cergy Pontoise - Université Paris-Seine)

  • A de Palma

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • N Picard

    (UCP - Université de Cergy Pontoise - Université Paris-Seine)

  • I Kaysi

    (AUB - American University of Beirut)

Abstract

The Transportation Elimination-by-Aspects (TEBA) framework, a new evaluation and decision making framework (and methodology) for large transportation projects, is proposed to elicit, structure and quantify the preferences of stakeholder groups across project alternatives. The decision rule used for group decision making within TEBA is the individual non-compensatory model of choice elimination by aspects (EBA). TEBA is designed to bring out the decision rule employed by decision makers when ranking the options presented, incorporate various criteria types and ease communication of relevant information related to options and criteria for multiple stakeholder groups. It is a platform for democratizing the decision making process. The TEBA framework was tested using a case study investigating alternative land connections between Beirut and Damascus. Key results showed that (1) stakeholders have employed EBA in making decisions, (2) a defined group of decision makers will rank options differently when provided with modified sets of criteria, (3) the public sector and general public groups ranked Impact on Employment among the top criteria, (4) the most important criterion per group from EBA was as expected; (5) the EBA analysis suggested that only 3 to 4 criteria are significant in reaching a decision; (6) aggregation of user assigned weights masked relative importance of criteria in some cases; and (7) analysis of user assigned weights and Minimum Threshold (MT) values suggest higher risk perception with increased criterion importance. Policy implications include recommendation to reach out to stakeholders for input on decisions, including the " people " but refrain from relying on criteria weights assigned by " experts " and reduce the " experts " ' role in decision making. Also, it is recommended to model the decision making in a probabilistic framework rather than a deterministic " one score " approach, seek to identify a consensus ranking, place particular attention on determining the values of the criteria that emerged as " top " at the evaluation stage and continue to emphasize risk measures.

Suggested Citation

  • R Khraibani & A de Palma & N Picard & I Kaysi, 2016. "A new evaluation and decision making framework investigating the elimination-by-aspects model in the context of transportation projects' investment choices," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01291343, HAL.
  • Handle: RePEc:hal:cesptp:hal-01291343
    DOI: 10.1016/j.tranpol.2016.02.005
    Note: View the original document on HAL open archive server: https://enpc.hal.science/hal-01291343v1
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    Cited by:

    1. Jinrui Pan & Jason Shachat & Sijia Wei, 2022. "Cognitive Stress and Learning Economic Order Quantity Inventory Management: An Experimental Investigation," Decision Analysis, INFORMS, vol. 19(3), pages 229-254, September.
    2. te Boveldt, Geert & Van Raemdonck, Koen & Macharis, Cathy, 2018. "A new railway tunnel under Brussels? Assessing political feasibility and desirability with competence-based multi criteria analysis," Transport Policy, Elsevier, vol. 66(C), pages 30-39.
    3. Valentina Zozulya & Olga Romanchenko & Andrey Zuykov & Inga Zozulya, 2017. "The Features of Management of Innovation Risks at Pre-investment Stage of the Project in Modern Economic Realities," International Review of Management and Marketing, Econjournals, vol. 7(2), pages 43-48.
    4. Bari, Chintaman S. & Chandra, Satish & Dhamaniya, Ashish & Arkatkar, Shriniwas & Navandar, Yogeshwar V., 2021. "Service time variability at manual operated tollbooths under mixed traffic environment: Towards level-of-service thresholds," Transport Policy, Elsevier, vol. 106(C), pages 11-24.
    5. Bekius, Femke & de Kwaasteniet, Vincent & Teisman, Geert, 2024. "Durability of decisions explained by actor-strategies in games: A multiple case study analysis," Transport Policy, Elsevier, vol. 154(C), pages 222-236.

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    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • H43 - Public Economics - - Publicly Provided Goods - - - Project Evaluation; Social Discount Rate
    • L91 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Transportation: General
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning

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