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Eco-innovation is emerging as one of the most important constructs that improve environmental sustainability of firms. However, it has been shown that companies alone cannot adequately develop eco-innovation activities, which is why they require the implementation of external collaboration activities with intermediaries, suppliers and stakeholders to achieve a higher level of eco-innovation activities and improve business performance of manufacturing firms. Therefore, this research fills this gap by exploring the importance of the relationship between collaboration and eco-innovation.

The research is conducted through an extensive literature review with a research model consisting of 5 measurement scales, 24 items and 4 hypotheses. A self-administered questionnaire was distributed to a sample of 460 firms in Mexico, analyzing the data set through confirmatory factor analysis and structural equation models.

The results obtained from this study suggest that collaboration has significant positive effects both on the eco-innovation of products, processes and management, as well as on the business performance of companies in the automotive industry.

The findings of this study have important implications both for the public administration (e.g. development of policies to support companies and financing programs) and for the managers of companies in the automotive industry (e.g. training program for employees and collaboration with other firms).

This paper fills a research gap by expanding the limited body of knowledge that relates collaboration eco-innovation and business performance, which is why this research aims to fill this existing gap in the literature and explore the relationship between collaboration, eco-innovation and business performance.

Intellectual capital (IC) plays a crucial role in today’s volatile business landscape, yet its measurement remains complex. To better navigate these challenges, the authors propose the Integrated Intellectual Capital Measurement (IICM) model, an innovative, robust and comprehensive framework designed to capture IC amid business uncertainty. This study focuses on IC measurement models, typically reliant on secondary data, thus distinguishing it from conventional IC studies.

The authors conducted a systematic literature review (SLR) and bibliometric analysis across Web of Science, Scopus and EBSCO Business Source Ultimate in February 2023. This yielded 2,709 IC measurement studies, from which the authors selected 27 quantitative papers published from 1985 to 2023.

The analysis revealed no single, universally accepted approach for measuring IC, with company attributes such as size, industry and location significantly influencing IC measurement methods. A key finding is human capital’s critical yet underrepresented role in firm competitiveness, which the IICM model aims to elevate.

This is the first SLR focused on IC measurement amid business uncertainty, providing insights for better management and navigating turbulence. The authors envisage future research exploring the interplay between IC components, technology, innovation and network-building strategies for business resilience. Additionally, there is a need to understand better the IC’s impact on specific industries (automotive, transportation and hospitality), Social Development Goals and digital transformation performance.

The purpose of the study is to test if it, by the use of a survey methodology, is possible to measure managers' awareness on, and specifically if there exist preconceived beliefs on, overall equipment effectiveness (OEE) results. The paper presents the design of the survey methodology as well as a test of the survey in one case company.

Actual OEE logs from a case company are collected and a survey on the data is designed and managers at the same case company are asked to answer the survey. The survey results are followed-up by an interview study in order to get deeper insights to both the results of the survey as well as the OEE strategy at the case company.

The findings show that the managers at this particular case company, on a general level, does not suffer too much from preconceived beliefs. However, it is clear that the managers have a preconceived belief that lack of material is logged as a loss much more often than what it actually is.

The test has only been performed with data from one case company within the automotive manufacturing industry and only the managers at that case company has been active in the test.

The survey methodology can be replicated and used by other companies to find out how aware their employees are on their OEE results and if possible preconceived beliefs exists.

To the authors' knowledge, this is the first attempt at measuring if preconceived beliefs on OEE results exist.

This study aims to provide a measurement model, and the underlying constructs and items, for Logistics 4.0 in manufacturing companies. Industry 4.0 technology for logistics processes has been termed Logistics 4.0. Logistics 4.0 and its elements have seen varied conceptualizations in the literature. The literature has mainly focused on conceptual and theoretical studies, which supports the notion that Logistics 4.0 is a relatively young area of research. Refinement of constructs and building consensus perspectives and definitions is necessary for practical and theoretical advances in this area.

Based on a detailed literature review and practitioner focus group interviews, items of Logistics 4.0 for manufacturing enterprises were further validated by using a large-scale survey with practicing experts from organizations located in Central Europe, the Northeastern United States of America and Northern Thailand. Exploratory and confirmatory factor analyses were used to define a measurement model for Logistics 4.0.

Based on 239 responses the exploratory and confirmatory factor analyses resulted in nine items and three factors for the final Logistics 4.0 measurement model. It combines “the leveraging of increased organizational capabilities” (factor 1) with “the rise of interconnection and material flow transparency” (factor 2) and “the setting up of autonomization in logistics processes” (factor 3).

Practitioners can use the proposed measurement model to assess their current level of maturity regarding the implementation of Logistics 4.0 practices. They can map the current state and derive appropriate implementation plans as well as benchmark against best practices across or between industries based on these metrics.

Logistics 4.0 is a relatively young research area, which necessitates greater development through empirical validation. To the best of the authors knowledge, an empirically validated multidimensional construct to measure Logistics 4.0 in manufacturing companies does not exist.

The study aims to propose a circular economy-based reverse logistics (CERL) that emphasises the mediation effect of reverse logistics (RL) on sustainable resource commitment and financial performance.

The structural equation modelling (SEM) approach has been applied to analyse the data acquired through the survey method that included 113 vendors of automotive supplies of the 1st and 2nd levels.

The results confirm that CERL acts as an essential intervening entity between resources and financial performance. The findings of the study have provided research and development (R&D) opportunities for the industries to find alternative revenue streams and generate profit from resource investment whilst upholding environmental standards through reverse logistic practices.

Reverse logistic practices are the key components of a circular business model and a sustainable supply chain. The manufacturing companies need to explore critical enablers that can contribute to business productivity and financial growth.

The study has validated a CERL model that portrays the circular economy's resilient relationship with RL practices.

The purpose of this paper is to introduce, summarize and combine the results of 11 articles in a special issue on the implementation of Industry 4.0. Industry 4.0 emerged as a phenomenon about a decade ago. That is why, it is interesting now to explore the implementation of the concept. In doing so, four research questions are addressed: (1) What is Industry 4.0? (2) How to implement Industry 4.0? (3) How to assess the implementation status of Industry 4.0? (4) What is the current implementation status of Industry 4.0?

Subgroups of articles are formed, around one or more research questions involving the implementation of Industry 4.0. The articles are carefully analyzed to provide comprehensive answers.

By comparing definitions systematically, the authors show important aspects for defining Industry 4.0. The articles in the special issue explore several cases of manufacturing companies that implemented Industry 4.0. In addition, systematic approaches to aid implementation are described: an approach to combine case-study results to solve new implementation problems, approaches to assess readiness or maturity of companies regarding Industry 4.0 and surveys showing the status of implementation in larger samples of companies as well as showing relationships between company characteristics and type of implementation. Small and large firms differ considerably in their process of implementing Industry 4.0, for example.

This special issue discusses implementation of Industry 4.0. The issue is limited to 11 articles, each of which with its own strengths and limitations.

The practical relevance of the issue is that it focuses on the implementation of Industry 4.0. Cases showing successful implementation, measurement instruments to assess degree of implementation and advice how to build a database with cases together with large-scale studies on the state of implementation do provide a wealth of information with a large managerial relevance.

The paper introduces an original take on Industry 4.0 by focusing on implementation. The special issue contains both literature reviews, articles describing case studies of implementation, articles developing systematic measurement instruments to assess degree of implementation and some articles reporting large-scale studies on the state of implementation of Industry 4.0 and thereby combine several perspectives on implementation of Industry 4.0.

The studies focusing on inbound logistics in the automobile industry have been limited because of the relatively small portion of logistics cost. But now it is recognized as one of the critical factors for efficient execution of supply chain management (SCM). The survey of suppliers in the automobile industry conducted in this study indicated significant relationships among logistics performance, logistics outsourcing, and performance evaluation level. This research is three-fold. First, current status of part supplier's logistics was analyzed by interviews with inbound logistics providers and suppliers. Second, management type of logistics was analyzed. There were three kinds of logistics -two kinds of logistics outsourcing and direct control by the supplier. Each type of logistics management showed differences about performance. Third, logistics performance evaluation and its relation with the actual logistics performance were presented. Comparable performance evaluation factors were selected, and it is shown that they had a correlation with actual performance.

This study aims to examine the concept of brand equity and willingness to buy second-hand products in the automobile context. The customer-based brand equity model is used as a theoretical lens to examine after-sales services, brand credibility and brand loyalty as drivers of brand equity and willingness to buy the second-hand product.

A survey questionnaire based on convenience sampling is used to collect the data from the car owners. A total of 433 survey responses were used to empirically test the measures and propositions by using structural equation modeling (SEM).

The findings suggest that after-sales services are a key factor in developing brand credibility and brand loyalty. Results are also in support of the positive and significant impact of brand credibility and brand loyalty on brand equity and willingness to buy second-hand products.

Brand equity represents a differential response and preference to marketing efforts that a product obtains as a result of its brand identification. Although practitioners are actively engaged to position themselves as a unique, attractive and strong brand, little is known about the equity of the brand in the case of second-hand products. This study provides an alternate branding view to the academic scholars and to the marketing manager as this study explicitly probes into the effect of after-sales services in developing brand credibility, brand loyalty, brand equity and wiliness to buy second-hand product as an outcome.

Logistics and supply chain management has been elevated to a strategic level whereby firms can simultaneously achieve differentiation and low cost for sustained competitive advantage. Empirical studies have often concentrated on logistics management in developed Western countries, displaying a bias towards the USA. This study applies the competency approach to explore logistics in Taiwan. A survey of 1,200 manufacturing firms was undertaken in order to examine the relationships between logistics competency, logistics performance, and financial performance, using exploratory factor analysis and the structural equation modelling technique. Four logistics competencies, namely, integration and knowledge competency, customer focused logistics competency, measurement competency, and agility competency were identified. The research findings revealed that (1) logistics competency was significantly related to logistics performance but not significantly associated with financial performance, and (2) logistics performance was positively associated with financial performance. These findings also implied that logistics competency has an indirect effect on financial performance through logistics performance. This finding confirmed the “world-class” logistics competencies (i.e. positioning, integration, agility, and measurement) as identified by MSUGLRT (1995). In addition, it suggests that logistics competency in a huge geographic area such as America can have the same effect in a smaller geographic area such as Taiwan.

Cross-docking is a supply chain distribution and logistics strategy for which less-than-truckload shipments are consolidated into full-truckload shipments. Goods are stored up to a maximum of 24 hours in a cross-docking terminal. In this chapter, we build on the literature review by Ladier and Alpan (2016), who reviewed cross-docking research and conducted interviews with cross-docking managers to find research gaps and provide recommendations for future research. We conduct a systematic literature review, following the framework by Ladier and Alpan (2016), on cross-docking literature from 2015 up to 2020. We focus on papers that consider the intersection of research and industry, e.g., case studies or studies presenting real-world data. We investigate whether the research has changed according to the recommendations of Ladier and Alpan (2016). Additionally, we examine the adoption of Industry 4.0 practices in cross-docking research, e.g., related to features of the physical internet, the Internet of Things and cyber-physical systems in cross-docking methodologies or case studies. We conclude that only small adaptations have been done based on the recommendations of Ladier and Alpan (2016), but we see growing attention for Industry 4.0 concepts in cross-docking, especially for physical internet hubs.