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The process of redesigning is one of the essential steps in upcycling, which comprises ideation, reconstruction and fitting. This paper aims to study the best practice of upcycling in the clothing industry. This study is an attempt to standardise upcycling/redesign process.

An exploratory approach was adopted to perform the research. This study draws on the multiple organisations involved in the upcycling of clothes. The organisations chosen for this study are located in Sweden and Romania using the snowball technique. Semi-structured interviews, direct and participatory observation approaches were used to collect information. The collected data are systematically analysed using NVivo 10 software.

This paper provides empirical insights into the diverse practices of upcycling. Process, product and demand-based were three fundamental approaches to performing the redesigning process. The fabric quality and durability, variations in size, colour and pattern, skills and efforts required in the extraction of parts and environmental consciousness and awareness were the main factors influencing upcycling process.

The use of the European case may miss best practices from the other region. This study may help scholars to understand the method of upcycling. A practitioner of upcycling can use the findings to improve and standardise the existing process. This research is beneficial for society, as this leads to the reduction of textile wastage.

This paper conceptualises some of the best practices of clothes redesign. This provides a good insight for the organisation for the improvement in the redesign business.

Global value chains (GVCs) have been challenged by several emerging macro-trends during the last years. Among them, sustainability of production and consumption patterns is becoming a central theme given the necessity to mitigate the degradation of the environment and the over-exploitation of scarce natural resources. In this respect, scholars and practitioners increasingly propose the circular economy (CE) approach as a systemic solution to overcome the conventional linear “take–make–use–dispose” model underlying the structure of contemporary global economy. However, the international business (IB) community has introduced the topic of CE only marginally in its debate. The aim of the present study is to fill this research gap identifying the opportunities for integrating IB and CE principles. Thus, the main objective is to investigate whether and how the adoption of the CE paradigm by multinational enterprises (MNEs) may affect activities, geographical configuration, and governance of their relevant GVCs.

The authors address the issue from a conceptual point of view, identifying direct and indirect impacts of CE adoption on GVC, relative enablers, and possible broader implications. Lastly, the authors propose some reflections for future investigations.

Anchored in the Natural Resource-Based View (NRBV) and Dynamic Capabilities theory, this study examines blockchain’s role in facilitating firms' transition to a circular economy (CE), aiming to provide a robust framework for understanding the interplay between blockchain, CE and sustainability.

The study uses an interpretivistic approach and semi-structured interviews to explore how blockchain can drive the transition to a CE.

The study shows blockchain can expedite the shift to a CE through pollution prevention, product stewardship and sustainable development, by leveraging dynamic capabilities (DC). It emphasizes blockchain as a micro foundation of DCs, with these capabilities enabling NRBV strategic capabilities.

This study investigates the intersection of blockchain and CE, offering empirical validation for a robust conceptual framework and revealing the societal impact of the CE transition.

Emerging from the COVID-19 pandemic, the Philippines has undergone the “new normal” transition, creating a strategic recovery effort to reinvigorate the industry. In tourism, these transitions aim to safeguard employees' and guests' health and safety, ensure continuity of business operations, boost tourism confidence leading to satisfaction, and establish a resilient and sustainable tourism industry in the postpandemic era. Hence, this chapter employs a system thinking leveraging a causal loop diagram (CLD) to construct a comprehensive roadmap for Philippine tourism's postpandemic resurgence through the system thinking lens. The CLD visually illustrates the inter-related factors influencing the recovery process, encompassing collaborative engagements, innovations, economic revitalization, and health and safety protocols. By analyzing the causal relationships among these variables, this chapter explicates the dynamic and interconnected nature of the postpandemic recovery leading to the recovery of the Philippine tourism industry, especially in the context of thinking small. Through this chapter, thinking small could involve a shift toward localized solutions and community-focused initiatives that allow them to foster local economies, build resilience, and create a more inclusive and sustainable postpandemic recovery.

An important consideration in the recovery strategies and performance of any given returned product is to make appropriate decisions for post-use. This paper aims to examine how the small and medium manufacturing enterprises can utilise a model-driven collaborative decision support system to evaluate product recovery strategies and performance.

An optimisation model using a genetic algorithm (GA) approach is developed to assess product recovery plans for any returned products based on the decisions of component reuse, remanufacture and recycle potentials. The model evaluates the key decisions of cost, time, quality and waste, and proposes an optimal recovery plan for manufacturer. A case study was also conducted using the proposed model to evaluate and examine different air compressor piston-types with recovery strategies.

Assessing a product recovery plan for any product is a challenge to the manufacturer due to higher operating costs associated with recovery. The nature of this challenge is complex. In this study, the results indicate that a developed optimisation model using a GA can assess the utilisation value of used products by considering suitable recovery strategies for the components and/or parts to be appropriately reused, remanufactured and recycled upon return.

The developed model assesses utilisation values of returns by considering both key decisions associated with returned products, and aspects of complexity of operational processes.

This research contributes to the practical understanding of product recovery strategies and extended producer responsibility using a case study. Also, the significance of this research is to provide a simple method of proposing an optimal recovery plan for any given returned product within a decision support system. Another innovation of the developed model is that an optimal recovery plan considers the trade-off decisions of cost, time, quality and waste aspects.

The purpose of this paper is to integrate sustainability and economic factors into a framework for understanding the reshoring decision.

This paper integrates sustainability and economic factors into a reshoring framework through using the theoretical perspectives of the natural resource-based view (NRBV) and transaction cost economics (TCE), and carrying out case study research with a number of firms involved in reshoring in the German automotive industry.

Through adopting a multi-theory approach, the framework captures the complexities of the reshoring decision and illustrates that reshoring is not a location decision alone, but encompasses a range of sourcing options such as local production in-house, using a local supplier or addressing sustainability problems with the offshore operation. The importance of sustainability capability development as a basis of extending the range of reshoring sourcing options available is highlighted.

Using the NRBV has allowed to develop value creating drivers in the context of reshoring. Integrating the logic of TCE with this analysis provided an understanding of how cost reducing drivers were present alongside the value creating drivers for reshoring at the case companies. Beyond previous frameworks integrating the RBV and TCE, bringing in the NRBV allowed us to highlight the importance of sustainability capability development as a basis of extending the range of reshoring sourcing options available. While this study’s cases were in the automotive industry in Germany, future research could sample for further geographies and industries to cover varying regulatory pressures for sustainability as well as sustainability-related industry initiatives.

The framework can provide guidance to managers on the conditions that favour the selection of each sourcing option when making the reshoring decision.

Although there are frameworks in the literature that explain the reshoring decision, limited attention has been given to integrating sustainability issues into the analysis. The findings here contribute important insights into the complementary and contradictory prescriptions of the NRBV and TCE in reshoring decisions, and several propositions are offered outlining these relationships. The resulting framework provides an integrated approach for managerial decision-making beyond economic factors alone.

The purpose of this study is to investigate the influence of design for lean six sigma (DFLSS) on operational functions of the innovation management model by appraising an innovation management assessment framework.

An empirical approach for evaluating causal relationships among various constructs in the model phases that identify optimum pathways in achieving commercial success was adopted. A quantitative analysis of survey data were collected from large, medium and small organiations, including incubators in ANZ (Australia, New Zealand) and TMSV (Thailand, Malaysia, Sri Lanka and Vietnam).

The structural equation modelling recursive path analysis results of the model provide empirical evidence and pathways through the various constructs considered in the model. All these pathways lead to delivering optimum commercialization success (CS). Furthermore, DFLSS is confirmed as an enabler and has direct one-to-one and indirect influence on all the operational function constructs of the model including commercial success.

This study had a relatively small sample size of completed responses obtained from the population and a constrained ability to compare commercialization success (CS) between the two regions in the dataset. Future studies could be conducted on a global scale to increase responses.

The research findings enabled the development of important and practical guidelines for managers and innovation practitioners engaged in planning and management of innovation.

This research offers a holistic approach for integrating DFLSS with stage gate phases of innovation management assessment framework, supported by empirical evidence, to aid organizations in effectively managing the innovation process and achieving greater success in commercialization.

Online customer reviews is an important information resource for product innovation. This study aims to investigate the impact of online customer reviews on iterative innovation of software products and the moderating roles of product complexity in the process of online reviews influencing product iterative innovation.

To empirically test the hypotheses, this paper built a panel data of 500 software products from 2019 to 2021 and applied Poisson regression analysis.

Empirically results reveal that both sentiment and quantity of online customer reviews have positive effects on iteration innovation of software products. In addition, the authors find that product complexity negatively moderates the relationship between online reviews and iterative innovation.

This study suggests that firms can acquire valuable information from customers’ online reviews for product iterative innovation and improvement. However, for high-complexity products, it may be difficult for enterprises to obtain useful information for iterative innovation from online reviews. On the other hand, this study provides a reference for firms to choose more useful online reviews from the perspective of sentiment.

This paper provides a new finding that there is a positive relationship between online customer reviews and iterative innovation of software products. Moreover, the authors also provide a deeper understanding of how online customer reviews affects iterative innovation by examining the moderating roles of product complexity.

Mismanagement of municipal solid waste (MSW) has led to resource depletion, ecosystem degradation and socio-economic risks, emphasizing the necessity to promote sustainable circular economy (SuCE) practices. This article identifies relevant enablers and unveils their interconnected roles in facilitating a municipal solid waste management (MSWM) system aligned with the principles of SuCE.

To identify pertinent enablers for MSWM systems based on SuCE principles, the study conducted a literature review and engaged experts from waste management sectors and academia to consolidate the final list of enablers. Following this, the study investigated the inter-relationships among these enablers using both Interpretive Structural Modeling (ISM) integrated and fuzzy Matrix Impact Cross-Reference Multiplication Applied to a Classification (fuzzy MICMAC) with MATLAB.

The study identified a comprehensive set of 23 enablers and categorized them into four control measures instrumental for the effective integration of SuCE principles in the context of the Indian MSWM system. Notably, the analysis highlighted that “authoritative pressure” and “policy transformation” are the highly influential enablers.

The study emphasizes actionable implications for stakeholders in the Indian MSWM sector. Policymakers and governmental bodies can enforce “authoritative pressure,” “policy transformation” and “budget allocation”. Meanwhile, managers can focus on “promotion of SuCE awareness”, “formalizing the informal workforce”, “infrastructure modernization”, “stakeholder engagement and alignment”, “segregation strategy”, “disruption preparedness”, and “local-based strategy”.

This study proposed a unique ISM diagraph and cluster of enablers to enhance the novelty of the study.

The purpose of this study is to examine how Industry 4.0 (I4.0) implementation might improve marketing performance (MP). Early adopters now have the chance to capitalize on the advantages of this successful implementation owing to the transition to I4.0. To improve MP, businesses must be able to identify and manage their effective implementation of I4.0 technologies, which are essential to improve industrial performance.

A survey was created and sent to 311 samples of manufacturing companies. To investigate the hypothesis created in this context, the study includes a survey-based analysis. To present the study’s findings, partial least squares-structural equation modeling has been used.

According to the findings, it can be concluded that an efficient implementation of Industry 4.0 (EII) can improve MP by positively impacting consumer loyalty and increasing customer loyalty (CL) positively enhancing by product customization (PC). The study’s key results, however, are how both PC and CL affect MP.

The intensive production technologies that are at the center of I4.0 will be better understood by professionals thanks to this study. The Internet of Things, artificial intelligence, additive manufacturing, sophisticated robots and many more are examples of these technologies. I4.0’s application strengthens efficiency and high-quality production. The I4.0 concept is gaining popularity in both developed and emerging countries due to its higher performance. Additionally, business people are actively working to implement I4.0 and make it a big success.

The study identifies the successful adoption of I4.0 that has a substantial impact on businesses’ MP. However, there is a lack of noteworthy studies that can concentrate on the marketing reach with I4.0 deployment. As a result, the goal of the current research is to comprehend how I4.0 will affect MP.