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Abstract

This chapter takes a multifaceted look at China's sustainable and smart supply chains. It examines China's impact on the environment and stresses the importance of a green transition. Sustainable logistics and supply chain management are examined as a potential source of market segmentation and competitive positioning in the context of novel business models. Case studies can illustrate how new technologies such as blockchain, artificial intelligence, the internet of things, and big data may improve supply chain performance and sustainability. Additionally, the chapter examines the function of green finance in promoting sustainability, logistics cost management measures, and the altering role of logistics managers. Impacts of China's Industry 5.0, agile logistics, service supply chains, and SCM analytics are discussed to round out the chapter. Anyone interested in China's transition toward more sustainable, intelligent supply networks may find useful information here.

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Engaged to a Robot? The Role of AI in Service

Ming-Hui Huang, Roland T. Rust (2021)

This article develops a strategic framework for using artificial intelligence (AI) to engage customers for different service benefits. This framework lays out guidelines of how to use different AIs to engage customers based on considerations of nature of service task, service offering, service strategy, and service process. AI develops from mechanical, to thinking, and to feeling. As AI advances to a higher intelligence level, more human service employees and human intelligence (HI) at the intelligence levels lower than that level should be used less. Thus, at the current level of AI development, mechanical service should be performed mostly by mechanical AI, thinking service by both thinking AI and HI, and feeling service mostly by HI. Mechanical AI should be used for standardization when service is routine and transactional, for cost leadership, and mostly at the service delivery stage. Thinking AI should be used for personalization when service is data-rich and utilitarian, for quality leadership, and mostly at the service creation stage. Feeling AI should be used for relationalization when service is relational and high touch, for relationship leadership, and mostly at the service interaction stage. We illustrate various AI applications for the three major AI benefits, providing managerial guidelines for service providers to leverage the advantages of AI as well as future research implications for service researchers to investigate AI in service from modeling, consumer, and policy perspectives.