Vol.:(0123456789) 1 3 Information Systems Frontiers https://doi.org/10.1007/s10796-023-10393-7 IoT‑Based Information System on Cold‑Chain Logistics Service Quality (ICCLSQ) Management in Logistics 4.0 Yuk Ming Tang 1,2  · Ka Yin Chau 2  · Wei Ting Kuo 1  · Xiao Xiao Liu 2 Accepted: 26 March 2023 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023 Abstract This study aims to develop a model to assess the impact of IoT technologies on cold-chain logistics service quality manage- ment and information of fresh product e-commerce in logistics 4.0. With eight primary characteristics and 40 dimension- related variables, we created a theoretical framework of IoT-based Cold-chain Logistics Service Quality (ICCLSQ) manage- ment through a structural equation model. A follow-up online poll of 522 previous fresh product purchasers who experienced features of logistics 4.0 was undertaken to assess customer expectations regarding the quality of information management and logistics service qualities in fresh product e-commerce. Statistical analysis was undertaken to investigate the attribute correlations and linear regressions were performed for analysis. Customers’ pleasure, return motivation, security and privacy are the four-logistics service quality scale dimensions in fresh products information management. The new theoretical model enables a better understanding of the LSQ factors that afect customer satisfaction on the information management of fresh product e-commerce enterprises, as well as enhancing the deployment of their services in light of Logistics 4.0. Keywords Theoretical model · Fresh product · Information management · E-commerce · Logistics service quality · Internet of Things (IoT) · Logistics 4.0 1 Introduction The rapid growth of the Internet of Things (IoT), virtual reality (VR), and metaverse technologies enable custom- ers to purchase fresh food and other products through vari- ous e-commerce channels without the strict restrictions as before. These technologies are particularly essential for fresh products as consumers may request fresh items at any time and always expect to receive them as soon as possible. Big data, refrigeration technology, and artifcial intelligence (AI) technologies provide critical fundamentals for the develop- ment of information management systems for quick e-com- merce of fresh products delivery. According to the global trend and consumer behavior of using e-commerce and other social channels for consumption, the industry is expected to develop at an average rate of 35% per year and 63.8% of consumers make fresh product purchases more than once a week, demonstrating that buyers have developed a habit of obtaining fresh items online (iResearch, 2020). Not only are consumers being pushed to use mobile internet and 5G tech- nology, more diverse products, high-quality standards, and higher expectations for more efective delivery and logis- tics services quality, but the current environment and social distancing measures have also pushed consumers to change their purchasing behavior, necessitating the development of efective information management. The production, shipping, and storage hazards of material loss have a signifcant impact on the quality of fresh foods. In order to ensure product qual- ity and minimize product loss, cold chain logistics, which is based on refrigeration technology, requires the logistics system to always be in a low-temperature environment in all stages of production, storage, transit, and sales (Li, 2021). To increase the actual shelf life of fresh products, cold chain * Yuk Ming Tang yukming.tang@polyu.edu.hk Ka Yin Chau gavinchau@cityu.mo Wei Ting Kuo david.kuo@polyu.edu.hk Xiao Xiao Liu nicoleliuxiaoxiao@163.com 1 Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, Hong Kong 2 Faculty of Business, City University of Macau, Macau, China