Browsing by Author "Wang W"

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Connecting land. A transdisciplinary workshop to envision a nature-connecting human habitat
(Taylor and Francis Group, 2023) Giusti M; Wang W; Marriott T
The design of the human habitat can either promote or oppose healthy living, sustainable lifestyles, and the ability to value nature in people. The goal of this paper is to provide some insights to shape a transdisciplinary agenda for future human habitats that are socially and ecologically sustainable. This is what Connecting Land is. Through a planned workshop, 19 professionals from a variety of complementary backgrounds create a vision for Connecting Land and then discuss policy actions required to achieve such a vision. The produced vision highlights a physically and emotionally healthy community that celebrates local nature in their traditions and rituals. Nature experiences are next door and symbiosis with nature is the constant background of the inhabitants' habits. The policy actions emerging from the workshop suggest that achieving Connecting Land requires integrated policies that simultaneously address children's experience-based education, the elimination of physical barriers to nature access, and legal actions to establish the rights of natural elements. To this goal, synergies between the design of natural landscapes, children's education, and short and long-term people's wellbeing are worth further exploration in both academia and practice. Sustainable human habitats that promote a healthy and sustainable culture do not need to be utopian.
Decision Market Based Learning For Multi-agent Contextual Bandit Problems
(International Foundation for Autonomous Agents and Multiagent Systems, 2024-01-01) Wang W; Pfeiffer T
Information is often stored in a distributed and proprietary form, and agents who own this information are often self-interested and require incentives to reveal it. Suitable mechanisms are required to elicit and aggregate such distributed information for decision-making. In this study, we use simulations to investigate the use of decision markets as mechanisms in a multi-agent learning system to aggregate distributed information for decision-making in a contextual bandit problem.
The Value Cocreation Influence Mechanism of Network Freight Transport Platform in IoT-Based Environments: Under the Service-Dominant Logic
(John Wiley and Sons, 2021-05-24) Bai P; Wu Q; Li Q; Zhang L; Jiang Y; Chen B; Wang W
The Internet of Things (IoT) has brought many benefits to the development of industries, from manufacturing to services. In the context of IoT, the network freight transport platform is equivalent to an integrator, integrating the scattered resources such as carriers and shippers in the supply chain, providing a solution, improving the use efficiency of vehicles, effectively reducing logistics cost, and creating value for the freight transport platform and bilateral customers. The purpose of this research is to explain the influence mechanism of transport demand subjects' participation in value cocreation (VCC) under the service-dominant logic (SDL). We proposed a conceptual framework and 10 hypotheses and used SEM to measure the direct and mediating relationship among SDL, transport demand subject (TDS) participation, relational embeddedness (RE), platform VCC, and TDS value in the online business environment. The findings show that (1) SDL, TDS participation, and RE do not directly affect the TDS value, but indirectly through platform VCC; (2) SDL affects platform VCC not only directly but also indirectly through TDS participation and RE; (3) TDS participation affects platform VCC not only directly but also indirectly through RE; (4) RE indirectly affects TDS value by affecting platform VCC; and (5) platform VCC plays a mediating role in SDL, TDS participation, RE, and TDS value. Hence, transport enterprises should pay attention to the innovation concept, guide TDS participation, jointly improve platform VCC, give play to the network effect of the freight transport platform, and achieve TDS value through the deepening of TDS relationship embedding.