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To understand non-compliance behaviors in investment goods in pandemic preparedness and resilience, we resort to a form of bounded rationality that people suffer from a lack of self-control due to "present bias{''

Motivated by the emerging mixed autonomous paradigm in cobotic order picking operations, we investigate the optimal information design to navigate human workers (HWs) who cooperate with autonomous mobile robots (AMRs) within an intralogistics system. We incorporate asymmetric information between AMRs and HWs in a routing game where connected AMRs are informed of the congestion state while HWs rely on information provided by the system. The system designs a communication policy aiming to navigate HWs away from congestion. Without strategic communications, we show that the deployment of AMRs cannot mitigate congestion unless the automation level reaches a threshold. Interestingly, we illustrate a substitution effect between automation and strategic communications when information distortion is mild. In contrast, severe information distortion complements automation due to exacerbated congestion. Furthermore, an in-house AMR fleet is economically more efficient than a third-party logistics service. Consequently, in-house automation can be achieved with mild information distortion, while severe information distortion is required to complement the lack of efficiency in the third-party AMR fleet. With simulated numerical examples to complement the analytical results, we provide managerial insights concerning the optimal information policies under different levels of automation, guiding warehouse managers in their communications with workers to achieve the best performance of the cobotic system.

Since December 2019, the COVID-19 outbreak has spread in over 100 countries and regions at a stunning pace. To prevent humanitarian health hazards such as COVID-19, people are strongly suggested to purchase and use Personal Protective Equipments (PPEs) for self-protection. However, the fraction of the population who refused to comply with the PPEs is high (and also much higher in some regions than others). In this paper, we focus on an empirically tested behavioral explanation for the compliance obstacle (a lack of self-control) based on the present-bias effect, which means the trend to give a higher valuation to a present reward but a lower valuation to a future reward (O’Donoghue & Rabin, 2006). Since the utility of PPEs is realized in the future, a consumer may postpone his purchase decision but finally abandon his purchase plan in the future period due to this present-bias effect. The key take-away we focus on is that advance selling can be beneficial to the consumers as a commitment device (Bryan et al., 2010). However, the effect of advance selling may be limited, especially for consumers with low valuation, and can only encourage a part of consumers to purchase PPEs. Advance selling alone cannot fully address the compliance obstacles in PPEs. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Since December 2019, the COVID-19 outbreak has spread in over 100 countries and regions at a stunning pace. To prevent humanitarian health hazards such as COVID-19, people are strongly suggested to purchase and use Personal Protective Equipments (PPEs) for self-protection. However, the fraction of the population who refused to comply with the PPEs is high (and also much higher in some regions than others). In this paper, we focus on an empirically tested behavioral explanation for the compliance obstacle (a lack of self-control) based on the present-bias effect, which means the trend to give a higher valuation to a present reward but a lower valuation to a future reward (O’Donoghue & Rabin, 2006). Since the utility of PPEs is realized in the future, a consumer may postpone his purchase decision but finally abandon his purchase plan in the future period due to this present-bias effect. The key take-away we focus on is that advance selling can be beneficial to the consumers as a commitment device (Bryan et al., 2010). However, the effect of advance selling may be limited, especially for consumers with low valuation, and can only encourage a part of consumers to purchase PPEs. Advance selling alone cannot fully address the compliance obstacles in PPEs. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The substitution and complement of ride-sourcing services and public transit services greatly affect the mobility and accessibility of a multi-modal transportation system. Since the transportation network company (TNC) (operator of ride-sourcing) concerns the profit and the government (operator of public transit) promotes social welfare, the two policy-makers will both cooperate and compete with each other to enhance their benefits. In this paper, we develop a bi-level game-theoretic approach to model the cooperative and competitive relationship between the TNC and the government. In the upper level, the two policy-makers design a cooperative plan such that the government provides subsidies to public transit riders who use ride-sourcing to solve first- or last-mile problems. In the lower level, they attempt to optimize operational strategies to compete with each other for achieving their objectives. The outcome of the bi-level game depends on passengers’ choices among alternative travel modes, which is characterized by an aggregate multi-modal market. Based on the proposed game-theoretic approach, we analytically and numerically examine the impact of the competition with passenger-side subsidies on the multi-modal system, and the existence of optimal strategies that lead to a win–win situation for both the policy-makers. We find that a socially-optimal subsidy level may exist. In areas with high public transit accessibility, a good-intentioned subsidy that boosts first- or last-mile ride-sourcing services can reduce the TNC's profit. Our research highlights the value of a carefully designed subsidy structure that benefits both the TNC (profit) and the society (social welfare), especially in areas with low public transit accessibilities. © 2021 Elsevier Ltd

The substitution and complement of ride-sourcing services and public transit services greatly affect the mobility and accessibility of a multi-modal transportation system. Since the transportation network company (TNC) (operator of ride-sourcing) concerns the profit and the government (operator of public transit) promotes social welfare, the two policy-makers will both cooperate and compete with each other to enhance their benefits. In this paper, we develop a bi-level game-theoretic approach to model the cooperative and competitive relationship between the TNC and the government. In the upper level, the two policy-makers design a cooperative plan such that the government provides subsidies to public transit riders who use ride-sourcing to solve first- or last-mile problems. In the lower level, they attempt to optimize operational strategies to compete with each other for achieving their objectives. The outcome of the bi-level game depends on passengers’ choices among alternative travel modes, which is characterized by an aggregate multi-modal market. Based on the proposed game-theoretic approach, we analytically and numerically examine the impact of the competition with passenger-side subsidies on the multi-modal system, and the existence of optimal strategies that lead to a win–win situation for both the policy-makers. We find that a socially-optimal subsidy level may exist. In areas with high public transit accessibility, a good-intentioned subsidy that boosts first- or last-mile ride-sourcing services can reduce the TNC's profit. Our research highlights the value of a carefully designed subsidy structure that benefits both the TNC (profit) and the society (social welfare), especially in areas with low public transit accessibilities. © 2021 Elsevier Ltd

The substitution and complement of ride-sourcing services and public transit services greatly affect the mobility and accessibility of a multi-modal transportation system. Since the transportation network company (TNC) (operator of ride-sourcing) concerns the profit and the government (operator of public transit) promotes social welfare, the two policy-makers will both cooperate and compete with each other to enhance their benefits. In this paper, we develop a bi-level game-theoretic approach to model the cooperative and competitive relationship between the TNC and the government. In the upper level, the two policy-makers design a cooperative plan such that the government provides subsidies to public transit riders who use ride-sourcing to solve first- or last-mile problems. In the lower level, they attempt to optimize operational strategies to compete with each other for achieving their objectives. The outcome of the bi-level game depends on passengers’ choices among alternative travel modes, which is characterized by an aggregate multi-modal market. Based on the proposed game-theoretic approach, we analytically and numerically examine the impact of the competition with passenger-side subsidies on the multi-modal system, and the existence of optimal strategies that lead to a win–win situation for both the policy-makers. We find that a socially-optimal subsidy level may exist. In areas with high public transit accessibility, a good-intentioned subsidy that boosts first- or last-mile ride-sourcing services can reduce the TNC's profit. Our research highlights the value of a carefully designed subsidy structure that benefits both the TNC (profit) and the society (social welfare), especially in areas with low public transit accessibilities. © 2021 Elsevier Ltd