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This paper aims to propose a framework for building a flexible supply chain business model using an object‐oriented approach.

The proposed modeling framework has used the de facto object‐oriented modeling standard, Unified Modeling Language (UML), for building a supply chain model. To compensate for the potential weakness of the pure object‐oriented model and UML, the framework integrates business rules with its model.

This paper provides information about several sources, which are the bases of modeling a supply chain. The paper regards a supply chain as five view models with four business domains and each domain consists of functions, resources, processes, interactions and business rules.

A typical manufacturing supply chain is considered as a target system to apply this design methodology. The paper does not handle a real case study as an application example.

This paper newly added the category of “Business Process Reengineering (BPR)‐driven” models to the traditional taxonomy of supply chain models and proposed an object‐oriented business model (OOBM) for a supply chain as one of the BPR‐driven models. It is hoped that this modeling approach is highly usable and adds value to an analyst, practitioner, and designer in the field of supply chain.

Despite intense research interest in supply chain management (SCM) over two decades, there is still uncertainty as to what SCM is and how behavioural determinants have an impact on it. The purpose of this study is to explore the linkages between the behavioural and marketing determinants of SCM and their impact on commitment and process integration.

The approach takes the form of descriptive research leading into causal research, using survey data and testing relationships with Structural Equation Modelling.

The study found that there are significant behavioural dimensions in SCM and identified the impact of those dimensions on supply chain commitment and process integration. One noticeable finding of this study was the nature of supply chain commitment within Confucian culture.

Data for the study were drawn from one single industry, so the findings are indicative but not representative of all supply chains. Also, the results cannot be generalised to other countries and industries. However, this study acts as a starting‐point to understand how behavioural and marketing determinants may impact supply chain commitment and business process integration. A series of future studies may follow this study to develop a comprehensive understanding of the nature, structures and strategies of supply chain commitment in Confucian culture.

This study will enable supply chain managers to understand the role of behavioural and marketing factors in managing supply chains. The root of Confucian culture lies in Asia, and Asia is an integral part of global supply chains. An understanding of Confucian dynamics will enable practitioners to manage these supply chains efficiently.

This paper contributes to an understanding of the behavioural/soft determinants in managing supply chains, particularly in Asia. This study also highlights the role of Confucian dynamism in shaping supply chain commitment. Both these areas had previously been under‐researched.

Additive manufacturing (AM) involves the renewal of production systems and also has implications for firms’ supply chains. Innovations related to AM supply chains are, so far, insufficiently understood, but their success will require firms’ awareness of their systemic nature and their firm-specific implications. The purpose of this paper is to explore the supply chain innovations dealing with AM in business-to-business supply chains.

An exploratory qualitative research design is used. Interviews were conducted in 20 firms, workshops were organized to map AM-related processes and activities, and supply chain innovations were analyzed.

This study reveals practical changes in supply chains and requirements for AM-related supply chain innovations. While earlier research has centered on technology or firm-specific AM implementations, this study shows that fully leveraging AM will require innovations at the level of the supply chain, including innovations in business processes, technology and structure, as well as supportive changes in the business environment. These innovations occur in different parts of the AM supply chain and are emphasized differently within different firm types.

This research was conducted in one country in the context of the machine building and process industry with a limited data set, which limits the generalizability of the results. The results offer an analytical framework and identify new research avenues for exploring the innovations in partial or complete AM supply chains.

The results offer a framework to assess the current state and future needs in AM-related supply chain innovations. Practical ideas are proposed to enhance AM adoption throughout firms’ supply chains. These results are important to managers because they can help them position their firms and guide the activities and collaborations with other firms in the AM supply chain.

This study draws attention to the supply chain innovations required when firms adopt AM in their processes. The generic supply chain innovation framework is enhanced by adding the business context as a necessary component. Implementation of AM is shown to depend on the context both at the level of the supply chain and the firm’s unique role in the supply chain. The holistic view taken reveals that successful AM technology adoption requires broad involvement from different firms across the supply chain.

Despite the increasing interests in supply chain management (SCM) within academy and industrial environment, there is still a lack of academic literature concerning topics such as methodologies to guide and support supply chain integration. The paper aims to discuss these issues.

This article presents the application of a diagnosis method in a Brazilian company from the sugar and ethanol industry to identify the level of supply chain integration. The diagnosis method is based on Cooper, Lambert and Pagh reference model for SCM. The method involves nine referential axes established from the eighth key business processes of the reference model.

It was pre-tested and supplemented with findings from interviews with academics and practitioners. Additionally, an illustration application was conducted in three relevant companies.

The application results were useful for refining the method that can be considered as a diagnosis instrument to permit companies to evaluate its supply chain integration.

Despite the ongoing calls for the incorporation of the cloud utility model, the effect of the cloud on elements of supply chain performance is still an evolving area of research. The purpose of this paper is to develop the architecture of a cloud-based supply chain management (C-SCM) ecosystem and explore how it enhances supply chain responsiveness (SCR).

First, the authors discuss the potential benefits that cloud computing can yield, compared to existing mature SCM information systems and solutions through a comprehensive literature review. The authors conceptualise SCR in terms of the level of visibility in the supply chain, supply chain flexibility and rapid detection and reaction to changes, and then the authors build the detailed architecture of a C-SCM system. The proposed ecosystem introduces a view of SCM and the associated practices when transferred to cloud environments. The potential to enhance SCR through the cloud is explored with scenarios on a case of supply chain operations in fashion retail industry.

The findings show that the proposed system can enhance all three dimensions of SCR. Implications for supply chain practice and how companies can migrate to a cloud supply chain are drawn.

Given that the development, creation and delivery of goods and services are increasingly becoming a joint effort of several parties in a supply chain, the authors contribute to the existing literature by introducing a comprehensive C-SCM system and show how companies can enhance their SCR.

Interorganizational business process standards (IBPS) are IT-enabled process specifications that standardize, streamline, and improve business processes related to interorganizational relationships. There has been much interest in IBPS as organizations from different industries implement these process standards that lead to successful organizational outcomes by integrating and standardizing intra- and inter-organizational business processes. These process standards enable data analytics capabilities by facilitating new sources of interorganizational process data. The purpose of this paper is to unearth employees’ reactions to a new type of supply chain process innovations that involved an implementation of new IBPS, a supply chain management (SCM) system, and associated analytics capabilities.

The authors gathered and analyzed qualitative data for a year from the employees of a healthcare supplier, a high-tech manufacturing organization, during the implementation of a SCM system and RosettaNet-based IBPS.

In what the authors termed the initiation stage, there was quite a bit of confusion and unrest among employees regarding the relevance of the new process standards and associated analytics capabilities. With the passage of time, in the institutionalization stage, although the situation improved slightly, employees found workarounds that allowed them to appropriate just part of specific processes and the analytics capabilities. Finally, once routinized, employees felt comfortable in the situation but still did not appropriate the new supply chain processes faithfully. Overall, employees’ reactions toward the SCM system and associated analytics capabilities were different from their reactions toward the new business processes.

The paper contributes to the literature by offering novel insights on how employees react to and appropriate process innovations that change their work processes.

This study conceptualizes the digital transformation (DT) strategy in a supply chain context, identifies its drivers from intra- and inter-organizational perspectives and examines the effect of the DT strategy on the strategic agility and financial performance of Chinese manufacturing firms.

The authors constructed a theoretical model by synthesizing the diffusion of innovation and organizational information processing theory (OIPT) and provided a set of hypotheses. The authors empirically tested the arguments using partial least squares structural equation modeling using data from a sample of 200 manufacturing firms in China.

The findings indicate that while supply chain connectivity positively affects DT adoption and DT routinization, data analytics capability and organizational learning positively influence DT adoption but not DT routinization. The mediation analysis also shows that DT strategy has significant direct effects on financial performance and a stronger indirect influence on financial performance via improved strategic agility.

This study responds to repeated calls for a new understanding of supply chain DT strategy. In addition, the study offers important contributions to the literature by identifying the potential discord between the existing DT strategy and the supply chain context and proposes a new framework that provides essential theoretical underpinnings.

This study enriches the literature by conceptualizing and validating the dimensions, driving factors and performance implications of DT strategy in strategic supply chain management.

The purpose of this paper is to show how the functionality of electronic marketplaces can facilitate collaborative supply chain planning. Supply chain planning processes are identified and analysed using a supply chain management focus. The paper also gives a brief introduction to a framework for supply chain management and to the typical structure of electronic marketplaces. Furthermore, three collaborative supply chain planning scenarios are defined, and it is shown how collaborative supply chain planning typically could be implemented on an electronic marketplace by the means of a Web‐based demonstration. As such, the paper shows how electronic marketplaces can be used to enable supply chain integration.

Big data poses as a valuable opportunity to further improve decision making in supply chain management (SCM). However, the understanding and application of big data seem rather elusive and only partially explored. The purpose of this paper is to create further guidance in understanding big data and to explore applications from a business process perspective.

This paper is based on a sequential mixed-method. First, a Delphi study was designed to gain insights regarding the terminology of big data and to identify and rank applications of big data in SCM using an adjusted supply chain operations reference (SCOR) process framework. This was followed by a questionnaire-survey among supply chain executives to elucidate the Delphi study findings and to assess the practical use of big data.

First, big data terminology seems to be more about data collection than of data management and data utilization. Second, the application of big data is most applicable for logistics, service and planning processes than of sourcing, manufacturing and return. Third, supply chain executives seem to have a slow adoption of big data.

The Delphi study is explorative by nature and the questionnaire-survey rather small in scale; therefore, findings have limited generalizability.

The findings can help supply chain managers gain a clearer understanding of the domain of big data and guide them in where to deploy big data initiatives.

This study is the first to assess big data in the SCOR process framework and to rank applications of big data as a mean to guide the SCM community to where big data is most beneficial.