Overcoming managers’ myopic decisions in a waste collection company: Lessons from a system dynamics-based research

Enzo Bivona, Francesco Ceresia, Giovanni Tumminello

Risultato della ricerca: Article

Abstract

Purpose The purpose of this paper is to show how the changing interrelationships between fleet management, human resources and outsourcer capacity areas are likely to counterbalance managerial policies, thereby generating a performance decay. The use of system dynamics modelling in a waste collection company offered an effective contribution to support decision makers to overcoming myopic decisions. Design/methodology/approach Literature review and a case study analysis (including interviews with company actors and data gathering) offered the basis to build a system dynamics model. The model built was then used to run simulations sessions to assess alternative investments decisions. Findings Simulation results show that understanding cause-and-effect relationships between company sub-systems can help managers to shift the focus of their decision process from a single department to the whole business system. Further, the paper offers three alternative scenarios (myopic, reactive and proactive) from which to learn how to design effective long-term sustainable policies. Research limitations/implications - The simulation model was developed based on a literature review and a single-case study. Although it offers a useful contribution in the investigated case, to generalise its results, additional application to waste collection companies would be desirable. Practical implications - The findings of the study have implications for public decision makers and those scholars investigating how to discourage the adoption of myopic decisions in complex environments. Originality/value To the best of our knowledge, only few studies investigated how the fleet management is likely to impact on the performance of waste collection companies. This study offers a contribution in this direction.
Lingua originaleEnglish
pagine (da-a)1023-1041
Numero di pagine19
RivistaJournal of Modelling in Management
Volume14
Stato di pubblicazionePublished - 2019

All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Strategy and Management
  • Management Science and Operations Research

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