As is known, sustainability issues represent one of the main challenges companies have to face. Among all, the fashion industry is considered one of the most impactful, both in terms of resource utilization and pollution. Fashion renting is a recent business model for companies to reduce their environmental footprint, following a circular economy approach. The study aims to develop and discuss the proposed hybrid approach to effectively support fashion companies in designing new business models, taking into account both the customer and the company perspective. On the one hand, agent-based modeling (ABM) allow us to represent customers’ behaviour and interaction. On the other hand, discrete event simulation (DES) paradigm is used to model fashion renting processes. Because customers’ attitude to that service reflects its successful implementation, motivators and barriers have been investigated to be included in the model. The practical implication is defining a model to support fashion companies in designing rental business models before implementing them. From a theoretical point of view, it overcomes the literature gap about the definition of a unique model for fashion renting, including processes, customers and interactions between agents. Follow-up research will include the presentation of simulation results.

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.

This work deals with a comparison between electroplating and Physical Vapor Deposition (PVD) finishing technologies applied in the fashion industry, with a special focus on their environmental impacts. The goal of this work is to present and validate a Decision Support System (DSS) allowing companies to identify, through Life Cycle Assessment (LCA) analysis, which of the two types of finishing processes is more suitable in comparison with specific KPIs. After an investigation on the literature and an industrial background regarding the two technologies, the model and, in particular, the sequence of activities that were conducted, are presented. Since LCA is an articulated process, requiring specific and adequate skills that are often unavailable within companies operating in this specific sector, a tool that facilitates LCA execution is a requisite. This tool, though potential publicity will facilitate the adoption of these approaches and sustainability as a driver in the selection of different production process strategies.

Industry 4.0 has introduced a data-driven model of production and management of goods and services. This manufacturing paradigm leverages the potential of the Internet of Things (IoT), but finding the information necessary to drive manufacturing processes can be challenging. In this context, the authors propose an innovative approach based on axiomatic design to design RDF knowledge graphs from which to extract the information needed by decision makers. This approach derives from the possibility of providing RDF knowledge graphs with an equivalent matrix representation based on axiomatic design. It allows the selection of the most reliable data sources, thereby optimizing the knowledge graph construction process using matrix algebra, minimizing redundancy and improving the efficiency of query response. The goal of the presented methodology is to address the five critical aspects of Big Data (volume, velocity, variety, value, and veracity) by preordering the knowledge graph according to the information needs of business decision makers, thereby optimizing the use of the immense wealth of information made available by the Web in design.

As widely known, Product Lifecycle Management (PLM) is a set of business solutions and tools for the management of the entire lifecycle of a product, from its conception to its disposal. Despite PLM was born in traditional contexts, recently it is increasingly used in other sectors such as the fashion industry, even if it shows several features that distances it from the traditional approach to PLM deployment. Request for customized products, rapid changes in customer’s preference and the consequent shorter product lifecycles make the fashion environment very complex. Within this scenario, PLM has the potential to enable fashion industry to reduce time to market and to increase competitiveness in the global scenario, but quite often clear guidelines are not available. Literature is not exhaustive, as we can’t find articles covering the whole set of functionalities. Quite often only few features have been mentioned and the same functionalities have been differently called. To overcome this gap, the purpose of this research is the definition of a framework on PLM functionalities in fashion, classified according to the macro-processes where they are involved. The result is an overview of the PLM functionalities organized in macro-processes, moving from the development of the creative idea to the arrival in the stores, validated by experts of PLM software houses working within the fashion industry. From a managerial point of view, it represents a clear guideline to support companies and vendors to identify the whole range of PLM functionalities and the processes positively involved during their implementation.