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Fast-growing online retail market provides convenience for customers. But it makes competition among online retailers fiercer as well. Online retailers need to improve online shoppers’ satisfaction level for the purpose of keeping their loyalty. As an important component in online retail market, logistics service affects online shoppers’ satisfaction level. By applying expectation confirmation theory, the purpose of this paper is to explore how customized logistics services (CLS) influences online shoppers’ satisfaction level and whether the relationship between them is moderated by product type.

Data were collected from Tmall.com, the biggest online retail market in China. Exploratory factor analysis and two-way ANOVA were conducted to analyze the data.

The results indicate that CLS positively impacts online shoppers’ satisfaction level. But product type does not have moderate effect on the relationship between CLS and online shoppers’ satisfaction level.

Online retail market grows fast. As the number of retailers keeps increasing, competition in this market becomes fiercer. In order to attract new shoppers and increase shoppers’ loyalty, online retailers must make shopper satisfied with their purchase. CLS positively impacts online shoppers’ satisfaction level, online retailers should offer shoppers CLS.

This study examines how customized logistics influences customer satisfaction, and extends literatures related to online customer satisfaction by integrating the factor CLS and opens the way for other studies related to logistics service customization. Furthermore, this study discusses how IoT will improve online retailers’ abilities in providing CLS.

Monitoring the real-time temperature, humidity, and physical position status of goods is vital in the cold chain. Diverse logistics technologies and systems have been adopted in the cold chain for monitoring perishable goods. However, these technologies and systems are independent from each other. Data and information in them are not integrated so that information control is not effective. The paper aims to discuss these issues.

By integrating Internet of Things and tracking technologies, this paper proposes an intelligent tracking system, which is designed to achieve effective and fast live monitoring of goods in the cold chain at the lowest cost and with the largest network capacity and simplest protocols.

Structure and information platform design mechanism are introduced. The key part of this system is a wireless sensor network built on Zigbee. Wireless sensors located in cold storages or refrigerated trucks are able to collect and transmit live data quickly and efficiently.

Users of the proposed system can easily monitor goods transported in cold chains. In addition, the system assigns specific servers to save historical data for inquiries.