International Journal of Information Systems and Supply Chain Management 

About: International Journal of Information Systems and Supply Chain Management is an academic journal published by IGI Global. The journal publishes majorly in the area(s): Supply chain & Supply chain management. It has an ISSN identifier of 1935-5726. Over the lifetime, 318 publications have been published receiving 2736 citations. The journal is also known as: IJISSCM.

Supply Chain Risk Management: Literature Review and Future Research

Abstract: Supply chain risk management has increasingly becoming a more popular research area recently. Various papers, with different focus and approaches, have been published since a few years ago. This paper aims to survey supply chain risk management (SCRM) literature. Paper published in relevant journals from 2000 to 2007 are analysed and classified into five categories: conceptual, descriptive, empirical, exploratory cross-sectional, and exploratory longitudinal. We also looked at the papers in terms of the types of risks, the unit of analysis, the industry sectors, and the risk management process or strategies addressed. The literature review will provide the basis for outlining future research opportunities in this field.

Applicability of ARIMA Models in Wholesale Vegetable Market: An Investigation

Abstract: To investigate the applicability of ARIMA models in wholesale vegetable market models are built taking sales data of one perishable vegetable from Ahmedabad wholesales market in India. It is found that these models can be applied to forecast the demand with Mean Absolute Percentage Error MAPE in the range of 20%. This error is acceptable in fresh produce market where the demand and prices are highly unstable. The model is successfully validated using sales data of another vegetable from the same market. This model can facilitate the farmers and wholesalers in effective decision making.

A Blockchain Model for Less Container Load Operations in China

Abstract: In recent years, with the growth of international trade and development of economies, the volume of container throughput at China's ports has grown rapidly. Yet, the business process for the Less Container Load LCL transport industry in most ports of China still remain complicated and inefficient. In this article, the authors see numerous opportunities for process improvement by integrating the information among the various actors using the blockchain concept. In this paper, the authors propose to build a LCL Export Platform LEP using the blockchain concept to optimize the LCL operations for international trading, by integrating and sharing information among forwarder agencies and their clients.

Facing the Challenges of RFID Data Management

Abstract: Radio frequency identification (RFID) has generated vast amounts of interest in the supply chain, logistics, and the manufacturing area. RFID can be used to significantly improve the efficiency of business processes by providing automatic data identification and capture. Enormous data would be collected as items leave a trail of data while moving through different locations. Some important challenges such as false read, data overload, real-time acquisition of data, data security, and privacy must be dealt with. Good quality data is needed because business decisions depend on these data. Other important issues are that business processes must change drastically as a result of implementing RFID, and data must be shared between suppliers and retailers. The main objective of this article is focused on data management challenges of RFID, and it provides potential solutions for each identified risk.

Big Data and Predictive Analysis is Key to Superior Supply Chain Performance: A South African Experience

Abstract: The study considers samples from the South African engineering companies who are strategic suppliers to mining and minerals industry and further explores the uncertainties persisting in the supply chain network. Further investigation was done to understand the role of big data and predictive analysis BDPA in managing the supply uncertainties. The paper finally uses partial least square regression analysis to study the relationship among buyer-supplier relationship, big data and predictive analysis and supply chain performance. The analysis supported the second and third hypothesis. Therefore, it is established that firstly, there is a positive relationship between big data, predictive analysis and supply chain performance and secondly, there is a positive relationship between and big data, predictive analysis and buyer-supplier relationship. The study is a unique contribution to the current literature by shedding light on the practical problems persisting in the South African context.