Information systems (IS) impact supply chain management (SCM) on processes such as planning, sourcing, and delivering, and at levels ranging from tactical operations to organisational strategy. The vast scope of IS and SCM relationships have resulted in diverse and disintegrated research on the topic. This paper offers a systematic literature analysis at the intersection of supply chain and information systems (SCIS), aiming to provide a classification for existing areas of research. This research is based on an analysis of more than 1500 articles published in peer-reviewed journals over the past four decades to classify topics and methods and to identify major trends and distinguish important research themes. The classification of the literature has identified major clusters of research in SCIS, and suggestions are made for future research in each of the identified clusters. In general, the findings point out that there is a dearth of research on topics such as ‘impact of IT on vertical disintegration of supply chains,’ ‘implications of new technologies for supply chains,’ and ‘concerns related to trust, governance, ownership, privacy, and security of data in supply chains.’ This work provides both researchers and practitioners with an insightful description of the current state of research in SCIS and related future trends in research and practice.

This paper investigates the affordances of ChatGPT in higher education and examines how artificial intelligence (AI) technologies may reshape the learning function in higher education. This study utilizes a grounded theory approach to analyze data collected from six sessions of panel discussions with participants from US universities. The study presents findings in the form of a framework encompassing four categories of affordances that “mitigate challenges in traditional learning environments,” “enhance effective educational practices,” “transform traditional learning approaches,” and “negatively impact current effective educational practices.” The framework, including the affordances and sub-affordances, illustrates the potential impact of this technology on the learning function of higher education. This research contributes to the literature by establishing a foundation for understanding ChatGPT’s role in higher education and fostering further inquiry. Additionally, the findings can assist higher education decision-makers in formulating policies and strategies to capitalize on the opportunities presented by AI tools like ChatGPT while mitigating potential risks.

Product design is an innovative process that, through the stages of problem statement, concept, and initial and detailed design, meets the needs of customers, the requirements of companies, and their limitations. In the current process of product design and development, formulating design objectives plays a crucial role in objective setting, project implementation, product needs and requirements specification, and performing activities validation. Currently, the role of the design and development stages in the sustainability of products, identifying strategies for improving this stage is of particular significance, and paying attention to the product planning and definition process group and focusing on establishing sustainability principles in the target book and defining new attributes can be regarded as one of the sustainable product development strategies. Consequently, this research is a case study in the field of applying the sustainability principles in the target book as one of the deliverables at the stage of product planning. The present study proposes strategies towards developing the attributes of the target book as a tool for exerting sustainability pillars in the process of design and development by means of surveying automotive industry experts, applying the DEMATEL and Fuzzy ANP combined method, and evaluating and determining new attributes.

In today’s competitive world, customers expect their demands to be met at the shortest possible time, while manufacturers aspire to deliver the orders within a convenient time and at a minimum cost. Thus, manufacturers are compelled to seek ways of lowering the costs of their services in order to satisfy customers and survive the competition in their respective industries. This research paper investigates a multi-product problem in a two-echelon supply chain consisting of a single manufacturer and several retailers. The main objective of this research is to develop and present a multi-product optimization model in which retailers receive their orders through discrete delivery and surplus manufactured goods are stored in the manufacturer’s warehouse. The objective function of the mathematical model in the economic dimension includes the minimization of the total supply chain costs and the maximization of profit. The retailers in this model place new orders when their inventory level drops to zero, and the manufacturer responds to the retailers’ orders at the same time as it begins processing each product. After delivering the last set of orders, the manufacturer stores surplus items in its warehouse in case the retailers place new orders. This optimization problem is modeled using mixed integer nonlinear programming, while numerical scenarios are coded using the MATLAB software which helps estimate the total cost within a short time. Finally, a sensitivity analysis is performed to determine the effects of a number of factors on the total cost, including problem parameters, demand and production rates, the production quantity, and the number of times the manufacturing machines are operated at each production cycle.

Replicability represents the cornerstone of reliable development in science. In this paper, we develop a framework for enhancing current data-collection practices’ replicability in survey research in information systems. To develop the framework, we built on literature, benchmarks of various scientific associations, and a review of policies and best practices in leading business journals. The framework identifies best practices for transparently collecting data, sharing data and methods, and developing high-quality evidence. We analyzed 82 recently published survey research in nine IS journals as a sample that represents high-quality IS research to identify their replicability and found that not one papers provided enough details for replication. We conclude by discussing our framework’s implications for researchers, journals, and scientific institutions and the role that these entities can play in enhancing IS research’s replicability.

Guest editorial: “Digital transformation of healthcare and finance: the role of blockchain, fintech and AI” - Author: Utkarsh Shrivastava, Mohammad Daneshvar Kakhki, Jiahe Song, Matthew M. Ross