The Impact of On-Demand Collective Transport Services on Sustainability: A Comparison of Various Service Options in a Rural and an Urban Area of Switzerland

Purpose The rising of the sharing economy (SE) has lowered the barrier of purchase price to accessing many different products, thus changing the consumer decision paradigm. This paper addresses the challenge of assessing the life cycle impacts of SE systems in the context of this new consumer decision-making process. The paper proposes a methodological framework to integrate consumer preferences into the Dynamic Life Cycle Assessment (dynamic-LCA) of SE systems. Methods In the proposed consumer preference integrated dynamic-LCA (C-DLCA) methodological framework, system dynamics (SD) is used to combine consumer preference and the principal method, dynamic-LCA, which follows the ISO 14040 LCA framework. Choice-based conjoint analysis (CBCA) is chosen as the stated preference tool to measure consumer preference based on SE alternatives, attributes and attribute levels. CBCA integrates discrete choice experiments (DCE) and conjoint analysis features. Random utility theory is selected to interpret the CBCA results by employing multinomial logistics as the estimation procedure to derive the utilities. Derived utilities are connected in iterative modelling in the SD and LCA. Dynamic-LCA results are determined based on dynamic process inventory and DCE outcomes and then interpreted aligned with the SD policy scenarios. Results and discussion The C-DLCA framework is applied to assess the GHG changes of the transition to car-based shared mobility in roundtrips to work in the USA. Carpooling and ridesourcing are selected as the shared mobility alternatives based on different occupancy behaviours. Powertrain system and body style are employed as the fleet technology attributes and the latter as an endogenous variable. Dynamic-LCA results are generated considering the high battery electrical vehicle (BEV) adoption as the policy scenario, and results are measured against a service-based functional unit, passenger-kilometre. The model outcomes show a significant reduction in aggregated personal mobility-related dynamic-GHG emissions by transitioning to car-based shared mobility. In contrast to the use phase GHG emissions, the production phase emissions show an increase. The results highlight the importance of integrating consumer preference and temporality in the SE environmental assessments. Conclusions The proposed C-DLCA framework is the first approach to combine consumer preferences, SD and LCA in a single formulation. The structured and practical integration of conjoint analysis, SD and LCA methods added some standardisation to the dynamic-LCAs of the SE systems, and the applicability is demonstrated. The C-DLCA framework is a fundamental structure to connect consumer preferences and temporal effects in LCAs that is expandable based on research scope.

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