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The purpose is to understand how the role of quality functions might evolve amidst digitalisation and an increased focus on services. This study focuses on customer feedback and how it can function as activation triggers for developing absorptive capacity, as well as how it relates to the value creation processes.

Following a qualitative research design, the authors gathered primary data from interviews with quality managers at 17 UK and Swedish firms and triangulated it with secondary information from the firms' web pages.

The findings show that customer feedback-based activation triggers can support development of absorptive capacity in the quality function if there are established processes for acting on customer feedback. This is often the case for codified feedback, which normally concerns products. However, digitalisation offers new opportunities of engaging in value co-creation, and firms need to develop digital capabilities to manage new technologies and data analytic tools. For personalised feedback (the main category of service-related feedback), established processes are missing.

This study work contributes to knowledge about how quality functions respond to customer feedback on both products and services. It clarifies why the quality function sometimes struggles to contribute to service quality as much as to product quality. From a theory development perspective, the authors contribute to understanding customer feedback-based activation triggers, how they lead to development of absorptive capacity and their relation to value co-creation on a functional level.

“Internet of things” is a broad term used to describe network connectivity to physical objects. Called connectable or smart objects, they are embedded in electronic circuits and software that make them capable of detecting, collecting and transmitting data and information. This paper aims to examine the influence of the attributes of “internet of things” products in the functional and emotional experience of purchase intention.

The study used a model adapted from Yaping et al. (2014), with adjustment for the constructs “emotional experience”, “functional experience” and “purchase intention”. The survey consisted of a sample of 747 valid questionnaires regarding users of “internet of things” products, through a structured questionnaire with 36 assertions, which were answered based on the Likert scale. The quantitative research approach followed an exploratory descriptive phase followed by the application of structural equation modeling.

Results validated most of the relationships of the model, with high levels of significance. In addition, there was a greater influence of emotional experience than functional on purchase intention for the selected sample, which mainly consisted of young people.

In short, the study confirmed the statistical significance of the structural paths, indicating that the proposed model is consistent, and with an appropriate adjustment can be applied in future research.

This paper aims to propose an interpretive framework to understand how machine learning (ML) affects the way companies interact with their ecosystem and how the introduction of digital technologies affects the value co-creation (VCC) process.

This study bases on configuration theory, which entails two main methodological phases. In the first phase the authors define the theoretically-derived interpretive framework through a literature review. In the second phase the authors adopt a case study methodology to inductively analyze the theoretically-derived domains and their relationships within a configuration.

ML enables multi-directional knowledge flows among value co-creators and expands the scope of VCC beyond the boundaries of the firm-client relationship. However, it determines a substantive imbalance in knowledge management power among the actors involved in VCC. ML positively impacts value co-creators’ performance but also requires significant organizational changes. To benefit from VCC via ML, value co-creators must be aligned in terms of digital maturity.

The paper answers the call for more theoretical and empirical research on the impact of the introduction of Industry 4.0 technology in companies and their ecosystem. It intends to improve the understanding of how ML technology affects the determinants and the process of VCC by providing both a static and dynamic analysis of the topic.

The objective of this study is to examine current business and management research on “Industry 4.0 base technologies” and “business models” to shed light on this vast literature and to point out future research agenda.

The authors conducted a bibliometric analysis of scientific publications based on 482 documents collected from the Scopus database and a co-citation analysis to provide an overview of business model studies related to Industry 4.0 base technologies. After that a qualitative analysis of the articles was also conducted to identify research trends and trajectories.

The results reveal the existence of five research themes: smart products (cluster 1); business model innovation (cluster 2); technological platforms (cluster 3); value creation and appropriation (cluster 4); and digital business models (cluster 5). A qualitative analysis of the articles was also conducted to identify research trends and trajectories.

First, the dataset was collected through Scopus. The authors are aware that other databases, such as Web of Science, can be used to deepen the focus of quantitative bibliometric analysis. Second, the authors based this analysis on the Industry 4.0 base technologies identified by Frank et al. (2019). The authors recognize that Industry 4.0 comprises other technologies beyond IoT, cloud computing, big data and analytics.

Drawing on these analyses, the authors submit a useful baseline for developing Industry 4.0 base technologies and considering their implications for business models.

In this paper, the authors focus their attention on the relationship between technologies underlying the fourth industrial revolution, identified by Frank et al. (2019), and the business model, with a particular focus on the developments that have occurred over the last decade and the authors performed a bibliometric analysis to consider all the burgeoning literature on the topic.

The purpose of this paper is to develop a quantitative risk assessment method for agricultural products cold chain logistics to assess the condition of the fresh agricultural products cold chain process objectively and accurately.

A risk assessment index system of agricultural products cold chain logistics is designed on the basis of the risk identification for the process of agricultural products cold chain logistics. This paper first uses catastrophe progression method and a new maximum deviation method to build an improved catastrophe progression assessment model for agricultural products cold chain logistics. In order to verify the reliability and validity of the model, two representative enterprises are selected as the case in the study.

The results in the empirical research indicate strong support for the assessment model and coincide with the reality. The risk assessment index system can also reflect the key risk factors from agricultural products cold chain logistics scientifically. In addition, the improved catastrophe progression assessment method proposed in this paper can be scientific and reasonable to predict risk.

This paper contributes to provide a new risk assessment model for agricultural products cold chain logistics. The new model overcomes the limitation of subjective empowerment and it increases the objectivity and scientificity in the process of cold chain logistics risk assessment. This paper also shows that practitioners involved in the field of products cold chain logistics can manage the potential risk by a set of scientific methods for assessing the risk before the accident.

The paper provides a practical guideline to practitioners, especially for cold chain logistics managers, relevant management departments, and cold chain logistics management consultants. It is proved that the new risk assessment method and the risk assessment index system of agricultural products cold chain logistics can help them assess the risk scientifically and reasonably.

Although the calculation is simple, the new model can overcome the limitation of subjective empowerment scientifically and reasonably, and thus has important practical value.

The study seeks to understand the possible opportunities that Industry 5.0 might offer for various aspects of inclusive sustainability. The study aims to discuss existing perspectives on the classification of Industry 5.0 technologies and their underlying role in materializing the sustainability values of this agenda.

The study systematically reviewed Industry 5.0 literature based on the PRISMA protocol. The study further employed a detailed content-centric review of eligible documents and conducted evidence mapping to fulfill the research objectives.

The advancement of Industry 5.0 is currently underway, with noteworthy initial contributions enriching its knowledge base. Although a unanimous definition remains lacking, diverse viewpoints emerge concerning the recognition of fundamental technologies and the potential for yielding sustainable outcomes. The expected contribution of Industry 5.0 to sustainability varies significantly depending on the context and the nature of underlying technologies.

Industry 5.0 holds the potential for advancing sustainability at both the firm and supply chain levels. It is envisioned to contribute proportionately to the three sustainability dimensions. However, the current discourse primarily dwells in theoretical and conceptual domains, lacking empirical exploration of its practical implications.

This study comprehensively explores diverse perspectives on Industry 5.0 technologies and their potential contributions to economic, environmental and social sustainability. Despite its promise, the practical evidence supporting the effectiveness of Industry 5.0 remains limited. Certain conditions are necessary to realize the benefits of Industry 5.0 fully, yet the mechanisms behind these conditions require further investigation. In this regard, the study suggests several potential areas for future research.

The purpose of this paper is to plot out pathways for organizations to implement a customer focus. These pathways are outlined with the help of illustrative examples. A well-defined customer focus is vital for organizations to ensure that they are positioned to be in line with the customers’ actual needs.

This is a conceptual paper where the argumentation is built on previous research findings, the authors’ reflections and the use of illustrative case examples of companies managing to instill a customer focus.

This paper builds a framework of potential pathways toward a customer focus by considering four strategic questions related to competition, products, insights and metrics.

This paper encourages managers to move beyond labeling themselves as customer-oriented and to actually implement a customer focus. This study puts forth a framework with strategic questions and principles designed to help with these endeavors.

Many companies pay lip service to customer focus, and it is often merely part of the corporate jargon without any real connection to strategy, the business model or everyday practices. This paper addresses the issue further by highlighting the potential pathways through which an organization can achieve a customer focus.

This study aims to develop a systematic method called servitization maturity model to support companies in developing distinctive capabilities for successful servitization.

The concept of maturity models is adopted to support companies in developing distinctive capabilities for servitization. A systematic literature review and case study approach are employed to develop the maturity model.

The findings highlight 46 capabilities classified into seven categories: strategy and leadership, performance, offerings, customers, organization, network and digital technology. Furthermore, the evolutionary path is defined by combining two types of levels, i.e. capability and maturity levels, to develop these capabilities.

The evolutionary path was partially validated through the application, while further investigation is required to validate the evolutionary path. Therefore, future research should investigate the further validation of the evolutionary path by conducting multiple case studies.

The proposed maturity model enables companies to not only capture the bigger picture of the required capabilities without oversight, but also determine a process for improving the requisite capabilities with feasible efforts.

Existing maturity models focused on the transition from less to more advanced services. However, recent studies emphasized that companies need to determine strategies that reflect their capabilities rather than simply move toward more advanced services. Based on this assumption, this study provides successive stages that enable companies to improve their capabilities through feasible efforts.

The purpose of this paper is to present a conceptual model that defines the essential components shaping the new Digital Supply Chains (DSCs) through the implementation and acceleration of Industry 4.0.

The scope of the present work exposes a conceptual approach and review of the key literature from 1989 to 2019, concerning the evolution and transformation of the actors and constructs in logistics and Supply Chain Management (SCM) by means of examining different conceptual models and a state-of-the-art review of Industry 4.0’s concepts and elements, with a focus on digitization in supply chain (SC) processes. A detailed study of the constructs and components of SCM, as defined by their authors, resulted in the development of a referential and systematic model that fuses the inherent concepts and roles of SCM, with the new technological trends directed toward digitization, automation, and the increasing use of information and communication technologies across logistics global value chains.

Having achieved an exploration of the different conceptual frameworks, there is no compelling evidence of the existence of a conceptual SCM that incorporates the basic theoretical constructs and the new roles and elements of Industry 4.0. Therefore, the main components of Industry 4.0 and their impact on DSC Management are described, driving the proposal for a new conceptual model which addresses and accelerates a vision of the future of the interconnectivity between different DSCs, grouped in clusters in order to add value, through new forms of cooperation and digital integration.

This research explores the gap in the current SCM models leading into Industry 4.0. The proposed model provides a novel and comprehensive overview of the new concepts and components driving the nascent and current DSCs. This conceptual framework will further aid researchers in the exploration of knowledge regarding the variables and components presented, as well as the verification of the newly revealed roles and constructs to understand the new forms of cooperation and implementation of Industry 4.0 in digitalized SCs.

The purpose of this paper is to identify requirements and tradeoffs on logistics services for enhanced circularity of materials and resources.

Based on multiple case study design and abductive reasoning, the study investigates 13 different product categories. The data were analyzed based on theoretical, a priori codes from the literature review. Inductive, emerging codes were added to the coding scheme during the analysis.

Requirements of logistics services to support slowing of resource flows are categorized with respect to initiator, location of the service, single or multiple actors, and transportation of parts, products and people. Moreover, the study identifies new logistics tradeoffs: material and people, knowledge and people, and information and knowledge. Transportation of product, people and parts can be reduced by increasing local knowledge and improve information sharing.

This review contributes to the understanding of the relationship between logistics services and enhancement of circularity by highlighting requirements on logistics services in the aftermarket supply chain that support slowing of resource flows. To enhance circularity, logistics services must extend the traditional material information flow with the flow of people and knowledge, respectively.

The categorization provides practitioners and researchers with an overview of requirements and tradeoffs on logistics services to enhance circularity of a particular circular cycle. The implications will provide an opportunity to address environmental impact of transportation and improve the utilization of scarce materials.

Variety of tradeoffs in logistics services can enhance slowing and hence circularity of scarce materials.

First, the authors illustrate how traditional tradeoffs in logistics such as flow of materials, resources and people need to be addressed to enhance circularity through slowing. Second, the authors identify two new tradeoffs in logistics services: knowledge flow and degree of customer involvement.