The notion of sustainability, in its three-fold meaning (economic, environmental, and social), is being adopted more and more by companies. Today it is widely accepted that sustainability cannot be achieved by firms in isolation, but requires the collaboration of all supply chain players. This issue is particularly relevant in industrial contexts where the supply chains are complex in terms of structure and number of players, such as the construction industry. Thus, the aim of the paper is to explore the sustainability practices adopted in the construction industry, with a particular attention to the role of environmental collaboration of supply chain partners in achieving sustainability. By means of multiple case study-based research, we investigate sustainability practices on a sample of construction companies of Italy, thus identifying three main sustainability approaches, which differ in both the strategic orientation towards sustainability and the level of implementation in design, purchasing, and governance processes, as well as the main variables driving the adoption of these approaches.

This paper presents the application of an innovative system for increasing visibility along an Engineer-To-Order supply chain. The system has been applied in a leading Italian company that manufactures vessels and tube heat exchangers. By means of this method, the company shares information about its shop floor activities with other actors in the supply chain, i.e. clients and suppliers. The system elements are as follows: Radio-frequency identification transponders (to identify either components, operators, tooling machines (e.g. welding machines) or production phases), a Wi-Fi network (to communicate data) and a web-based application that is accessible by the company’s clients. This paper shows the methodology that is used to define the system’s architecture and the technical solutions adopted. Benefits in terms of reduction in costs for monitoring and control have been observed. Moreover, customers perceived the increased visibility of the production process to be a valuable service.

Purpose: This paper investigated the organizational adoption of big data analytics (BDA) in the context of supply chain planning (SCP) to conceptualize how resources are orchestrated for organizational BDA adoption and to elucidate how resources and capabilities intervene with the resource management process during BDA adoption.Design/methodology/approach: This research elaborated on the resource orchestration theory and technology innovation adoption literature to shed light on BDA adoption with multiple case studies.Findings: A framework for the resource orchestration process in BDA adoption is presented. The authors associated the development and deployment of relevant individual, technological and organizational resources and capabilities with the phases of organizational BDA adoption and implementation. The authors highlighted that organizational BDA adoption can be initiated before consolidating the full resource portfolio. Resource acquisition, capability development and internalization of competences can take place alongside BDA adoption through structured processes and governance mechanisms.Practical implications: A relevant discussion identifying the capability gap and provides insight into potential paths of organizational BDA adoption is presented.Social implications: The authors call for attention from policymakers and academics to reflect on the changes in the expected capabilities of supply chain planners to facilitate industry-wide BDA transition.Originality/value: This study opens the black box of organizational BDA adoption by emphasizing and scrutinizing the role of resource management actions.

Purpose: This paper aims to examine how the extant publication has related big data analytics (BDA) to supply chain planning (SCP). The paper presents a conceptual model based on the reviewed articles and the dominant research gaps and outlines the research directions for future advancement.Design/methodology/approach: Based on a systematic literature review, this study analysed 72 journal articles and reported the descriptive and thematic analysis in assessing the established body of knowledge.Findings: This study reveals the fact that literature on relating BDA to SCP has an ambiguous use of BDA-related terminologies and a siloed view on SCP processes that primarily focuses on the short-term. Looking at the big data sources, the objective of adopting BDA and changes to SCP, we identified three roles of big data and BDA for SCP: supportive facilitator, source of empowerment and game-changer. It bridges the conversation between BDA technology for SCP and its management issues in organisations and supply chains according to the technology-organisation-environmental framework.Research limitations/implications: This paper presents a comprehensive examination of existing literature on relating BDA to SCP. The resulted themes and research opportunities will help to advance the understanding of how BDA will reshape the future of SCP and how to manage BDA adoption towards a big data-driven SCP.Originality/value: This study is unique in its discussion on how BDA will reshape SCP integrating the technical and managerial perspectives, which have not been discussed to date.

Materials Requirement Planning (MRP) technique is widely employed by most manufacturing companies, even though field applications point out some weaknesses, including ignored production capacity constraints and fixed lead-times. These weaknesses often lead to infeasible production schedules, which trigger fluctuating workloads over time, significant adjustment effort and eventually unpredictably long lead times. This paper introduces a capacity-oriented MRP procedure that combines the traditional MRP procedure with an approach based on linear programming: in this way, requirement of lead times pre-determined a priori outside the MRP procedure is overcome. The new procedure is then applied to a real-life company and results highlight that feasible plans of orders are generated without requiring lead-times as input and without relevant computational burden.

Purpose: The purpose of this paper was to investigate what types of supply chain strategies (SCS) are implemented within luxury fashion companies, according to the drivers that regulate competitiveness in this sector (brand positioning, distribution channel, type and line of product). Moreover, the objective was to define which key performance indicators (KPIs) should be measured according to the chosen strategy, and finally to evaluate the alignment of luxury fashion companies with the proposed indicators.Design/methodology/approach: The literature review was the first step performed. Thereafter, a case study was conducted and the sample, composed of six companies, was selected, a questionnaire was then developed to guide the interviews, after which the data were collected. From the data, a primary case analysis was conducted, from which cross-case patterns were also researched.Findings: From the results obtained, it was possible to state that companies involved in the case study adopted different SCS within the same company according to the drivers that regulate the sector competitiveness. As a result, the product line was shown to be the only driver that affected both the alignment between the expected and implemented SCS, respectively, and the alignment with the selected KPIs.Originality/value: The paper provides valuable insights to companies that are trying to align SCS and KPIs. The close link between these aspects had not yet been explored previously. In particular, there were no indications about the KPIs that have to be measured for a specific SCS.