Purpose: This study aims to demonstrate that the Dynamic Performance Management (DPM) framework, integrating performance management with system dynamics modelling, enables decision-makers to identify sustainable strategies in online food delivery platforms, thereby avoiding company failure. Design/methodology/approach: This study undertakes a multistep methodological approach. After the literature review, a retrospective case study approach was used. To build the DPM framework and the system dynamics simulation model, primary and secondary data were collected and analysed. Findings: This study by adopting the DPM perspective highlights the critical role performance drivers play to assess the viability of alternative growth strategies in food delivery digital platforms. As such, the findings complement extant studies which highlighted the need for adopting a dynamic perspective in Performance Measurement and Management (PMM), particularly in complex and turbulent environments. Findings also highlight that in food delivery platforms, network effects may result insufficient to reach a critical volume of users and factors such as key drivers impacting platform attractiveness must be considered to design effective PMM. Research limitations/implications: Future studies may apply the DPM framework here suggested to multiple digital platforms, to validate this study's findings. Practical implications: This paper offers a guidance to practitioners and scholars to design effective PMM in food delivery digital platforms. Originality/value: This study offers an innovative perspective to analyse the interdependences among main mechanisms underpinning the performance of food delivery platforms. As such, it contributes to enrich prior PMM literature and addresses the call for more empirical and theoretical PMM contributions in fast-changing and turbulent environments.
Bivona E. (2023). Determinants of performance drivers in online food delivery platforms: a dynamic performance management perspective. THE INTERNATIONAL JOURNAL OF PRODUCTIVITY AND PERFORMANCE MANAGEMENT, 72(9) [10.1108/IJPPM-10-2021-0606].
Determinants of performance drivers in online food delivery platforms: a dynamic performance management perspective
Bivona E.
Primo
Membro del Collaboration Group
2023-11-10
Abstract
Purpose: This study aims to demonstrate that the Dynamic Performance Management (DPM) framework, integrating performance management with system dynamics modelling, enables decision-makers to identify sustainable strategies in online food delivery platforms, thereby avoiding company failure. Design/methodology/approach: This study undertakes a multistep methodological approach. After the literature review, a retrospective case study approach was used. To build the DPM framework and the system dynamics simulation model, primary and secondary data were collected and analysed. Findings: This study by adopting the DPM perspective highlights the critical role performance drivers play to assess the viability of alternative growth strategies in food delivery digital platforms. As such, the findings complement extant studies which highlighted the need for adopting a dynamic perspective in Performance Measurement and Management (PMM), particularly in complex and turbulent environments. Findings also highlight that in food delivery platforms, network effects may result insufficient to reach a critical volume of users and factors such as key drivers impacting platform attractiveness must be considered to design effective PMM. Research limitations/implications: Future studies may apply the DPM framework here suggested to multiple digital platforms, to validate this study's findings. Practical implications: This paper offers a guidance to practitioners and scholars to design effective PMM in food delivery digital platforms. Originality/value: This study offers an innovative perspective to analyse the interdependences among main mechanisms underpinning the performance of food delivery platforms. As such, it contributes to enrich prior PMM literature and addresses the call for more empirical and theoretical PMM contributions in fast-changing and turbulent environments.File | Dimensione | Formato | |
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