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The rapid increase in importance of the remanufacturing operation in the present scenario is just because of its ability to retrieve the functional value of the End-of-Use or End-of-Life products which is as good as the original product. However, customers are still concerned about the reliability of the remanufactured product which is considered as one of the major problems in the area of remanufacturing. The purpose of this paper is to study and analyse the behavioural pattern of the mixture failure rate of a remanufactured product.

In order to analyse the behavioural pattern of the mixture failure rate, different proportions of new and remanufactured products are mixed. In this paper, a two-parameter Weibull distribution is used to observe the mixture failure rate characteristics. Also, the mixture failure rate of the remanufactured product is evaluated under two conditions, that is when the shape parameter of new and remanufactured components is the same and when the shape parameter values are different.

From the analysis, it is observed that the mixture failure rate is always decreasing in nature when the shape parameter values are same. In that case, the value of the mixture failure rate depends only on the proportion of the new components. When the shape parameter values are different, the mixture failure rate characteristics depend upon the shape parameter value of the remanufactured product.

The results of the research can be applied to any remanufactured automotive product. This study also shows the behavioural characteristics of the mixture failure rate of a remanufactured product at different mixture proportions.

The COVID-19 pandemic has caused major disruptions and revealed the fragilities in supply chains. This crisis has re-opened the debate on supply chain resilience and sustainability. This paper aims to investigate distinct impacts of COVID-19 on supply chains. It identifies both short- and medium-to-long-term measures taken to mitigate the different effects of the pandemic and highlights potential transformations and their impacts on supply chain sustainability and resilience.

To address the purpose of the study, a qualitative research approach based on case studies and semi-structured interviews with 15 practitioners from various supply chain types and sectors was conducted. Studied organizations included necessary and non-necessary supply chain sectors, which are differently impacted by the COVID-19 pandemic.

This study reveals five main challenges facing supply chains during COVID-19, including uncertain demand and supply, suppliers' concentration in specific regions, globalized supply chains, reduced visibility in the supply network, and limited supplier capacity. To help mitigate these challenges and develop both sustainability and resilience, this paper identifies some mitigating actions focusing on the promotion of the health and wellbeing of employees and supply chain stabilization. Further, in the post-COVID era, sustainable and resilient supply chains should consider regionalization of the supply chain, diversification of the supply network, agility, collaboration, visibility, and transparency; and should accelerate the use of smart technologies and circular economy practices as dynamic capabilities to improve supply chain resilience and sustainability.

This study contributes to exploring the sustainability- and resilience-related challenges posed by the COVID-19 pandemic. Its findings can be used by researchers and supply chains decision-makers to limit disruptions and improve responsiveness, resilience, sustainability, and restoration of supply chains. The results support benchmarking through sharing of the best practices and organizations can also integrate the different capabilities discussed in this study into the processes of selection and auditing of their suppliers.

This paper aims to investigate the phases of new product development within the design-driven innovation (DDI) process, the role of designers and collaborators in the process and how this process relates to some quality principles.

This study adopted a qualitative approach using Gioia methodology. In particular, four Italian manufacturing companies in the home appliances and furniture industry were selected, and data mainly collected through direct interviews were analysed through content analysis.

The new product development related to DDI includes the following phases: the company brief, the designer research, the concept of the designer, the design, legal protection, prototyping, production and the market launch. Designers play a strategic role in the above phases of DDI, but other actors also cooperate and some quality principles affect positively on the process. This study proposes a model for a DDI process in the home appliances and furniture sector.

Although this exploratory study was conducted on only four companies, it advances the DDI research in relation to new product development.

This study makes recommendations to entrepreneurs and managers on how to innovate successfully and to effectively manage designers and collaborators to ensure competition.

This analysis highlights that design-based innovation contributes to improving the quality of life of consumers.

To the best of the authors' knowledge, this is the first qualitative study to examine the phases of new product development in DDI process, the actors involved and relationship to quality principles for the Italian home appliances and furniture sector.

The main purpose of this exploratory study is to investigate the attitude of pharmacists, as small- and medium-sized enterprise (SME) owners, toward new technologies, and more precisely, toward the adoption of mobile apps for mobile health (mHealth). Such apps are generally used to improve customer satisfaction and loyalty. This study measures pharmacists’ subjective experiences of mobile apps for mHealth and aims to understand how these pharmacists make sense of these apps.

The study adopted the narrative inquiry technique combined with critical event analysis. Participants' experiences were categorized based on how they viewed new technology tools. Interpretative inductive analysis identified precise aspects of the sense making illustrative of non-adoption or confused adoption of new technologies by pharmacists.

This study investigates to what extent new technology tools such as mobile apps affect retailers and more precisely the reasons why mobile apps are and are not adopted by retailers, as potential users, in the pharmaceutical industry. We identified four aspects of sense making that illustrated non-adoption or confused adoption of new technologies by pharmacists. These aspects are deeply discussed in the paper and are referred to the dimensions of confusion to confidence; suspicion to trust; frustration to education; mistrust to cooperation.

The main limitation of the present study is the limited number of territories investigated. This limitation arose because of the exploratory nature of the available research, which is generally based on case studies, and the lack of clear operationalization of the research available at the time of data collection. Another limitation is that the sample included only SMEs operating in the Italian pharmacy industry.

Many studies have highlighted the opportunities related to new mobile apps in the business-to-business market. Several have investigated customer interest in such new technology. If some contributions have indirectly investigated the acceptance of information technology tools, to the best of our knowledge, no study has been conducted to investigate directly and precisely the level of pharmacists' acceptance, use, and willingness to adopt information technology (e.g., mobile apps) for customer service in mHealth and mainly the reasons of non-adoption.

This paper explores how digitalization affects the academic research publication process by taking into account the perspective of management scholars. It provides an overview of the digital professional services dedicated to academic research, and investigates academics' awareness of, the impact on the publication process of, and scholars' expectations regarding digital services and software.

This explorative study adopted a qualitative approach by performing direct observations of websites regarding digital professional research services and in-depth interviews with national and international management scholars.

The multiple digital professional services dedicated to academic research enable authors to develop a scientific paper independently or with the support of professionals. The scholars' awareness regarding the digital services and software was limited, because of both the plethora of options on the market and the frequent use of the same digital tools over time. In impact terms, these tools enable scholars to improve research quality and to increase productivity. However, the negative effects led scholars to express different expectations about how they can be improved and what difficulties should be overcome to favor the publication process.

The results of this study provide suggestions both for scholars who engage in academic research and digital services and software providers.

To the best of the authors' knowledge, this is the first study to examine the ongoing development of digitalization in support of the research publication process from the perspective of academics.

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.

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.

This paper aims to provide and empirically test a conceptual model in which artificial intelligence (AI), knowledge management processes (KMPs) and supply chain resilience (SCR) are simultaneously considered in terms of their reciprocal relationships and impact on manufacturing firm performance (MFP).

In the study, six hypotheses have been developed and tested through an empirical survey administered to 120 senior executives of Italian manufacturing firms. The data analysis has been carried out via the partial least squares structural equation modelling approach, using the Advanced Analysis for Composites 2.0 variance-based software program.

Using a conceptual model validated using an empirical survey, the study sheds light on the relationships between AI, KMPs and SCR, as well as their impacts on MFP. In particular, the authors show the positive effects of the adoption of AI on KMPs, as well as the influence of KMPs on SCR and MFP. Finally, the authors demonstrate that KMPs act as a mediator through which AI affects SCR and MFP.

This study highlights the critical role of KMPs for manufacturing firms that can deploy AI to stimulate KMPs and through attaining a high level of the latter might succeed in enhancing both their SCR and MFP.

This study demonstrates that manufacturing firms interested in properly applying AI to ameliorate their performance and resilience must carefully consider KMPs as a mediator mechanism.