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The purpose of this paper is to define the local integration rate and how it is calculated to assess its relevance as a national performance indicator for the Moroccan automotive industry.

The research methodology first followed a systematic review approach through the analysis of published research articles and academic works. This study then followed a qualitative approach based on semi-structured interviews with various actors in the Moroccan automotive industry. Finally, the findings of this work were reinforced by a case study to analyze the supply chain of a locally produced vehicle.

The results indicate that the local integration rate as calculated today overestimates the performance of the automotive industry and does not systematically guarantee a significant creation of value added.

Due to the confidentiality of the data in terms of turnover, payroll and purchase prices as well as the large number of suppliers in the different supply chains of the car manufacturer, the case study focused on only one of the six existing ecosystems.

On the basis of research work on the Moroccan automotive industry as well as interviews with various actors, the local integration rate is unanimously considered as a viable performance indicator. This study has not only led us to the method of calculating this rate by the Ministry of Industry but also demonstrated its limitations while proposing a new method of calculation to increase the value added.

Although situational crisis communication theory (SCCT) is centered on rationality and cognitive information processing, it ignores that people are also driven by irrationality and non-cognitive information processing. The purpose of this study aims to fill this gap by examining how gender stereotypes, based on perceived spokesperson sex influence the public’s perceptions of crisis response messages.

A 2 (industry type: automotive vs daycare industry) × 2 (spokesperson’s sex: male vs female) × 2 (crisis response appeal: rational vs emotional) between-subject online experiment was conducted to examine the effect of gender stereotype in crisis communication.

Results showed that either matching spokesperson sex with sex differed industry or matching sex differed industry with appropriate crisis response appeal can generate a more positive evaluation of the spokesperson and the organization. The results also revealed under which circumstances, the attractiveness of different sex of the spokesperson can either promote or mitigate people’s perceptions of the organization. Furthermore, when people are aware of a spokesperson’s sex, in a female-associated industry, a mismatching effect of a positive violation of a male-related stereotype overrides a matching effect of a female-related stereotype in crisis communication.

This study is among the first to identify how the gender of a spokesperson and industry type affect publics’ crisis response.

This paper explores how a firm that is established in an environment characterized by uncertainty can engage with weak regulative institutions by developing operational and institutional capabilities.

We employ a multiple case study approach with seven leading multinational firms in Brazil in industries that vary in industry concentration.

Firms choose among alternative strategies for engaging with regulative institutions as an ongoing process, based on their assessment of four characteristics of the uncertainty they face and their capabilities. Strategies that require a firm to exert greater effort to adapt to institutions or influence institutions have a greater potential to catalyze for developing operational capabilities. Although firms in industries with different concentrations behave similarly in individually adapting to regulative institutions, firms in decentralized industries are more likely to collaborate to influence institutions, which enables them to both access public agents through network partners and better negotiate their own interests.

This research guides managers in developing institutional engagement strategies to reduce the potential consequences of institutional uncertainty in their supply chain. It also suggests types of institutional capability aligned with decentralized vs concentrated industries.

We extend the construct of institutional engagement strategies from the context of entrance to a new international market to an ongoing process in firms that are established in an environment characterized by weak regulative institutions. We also examine the role of industry concentration in the application of institutional engagement strategies.

Despite the importance of green supply chain integration (GSCI) in advancing green innovation (GI) is recognized, it remains unclear how firms can translate their GSCI efforts into GI. Therefore, this study aims to understand how GSCI affects GI, with its dimensions (exploitative GI and exploratory GI), as well as to investigate the mediating role of green knowledge integration capability (GKIC) and the moderating role of blockchain technology (BCT) adoption.

On the basis of data collected from 247 managers working in Indian firms in the automotive industry, the authors tested the proposed model using the PROCESS macro tool via SPSS software.

The empirical results indicate that GSCI is positively associated with both exploitative and exploratory GI, with a higher effect on exploitative GI. In addition, GKIC mediates the link between GSCI and exploitative GI in contrast to exploratory GI. Notably, the relationship between GSCI and GKIC is stronger when BCT adoption is high.

This study opens the black box of how GSCI affects exploitative and exploratory GI by revealing the mediating role of GKIC and the moderating role of BCT adoption. It provides valuable insights for practitioners to translate GSCI efforts into GI through developing GKIC and adopting BCT.

This works provides a thorough understanding of the challenges and opportunities associated with Additive Manufacturing (AM) adoption in the medical sector. Through this analysis, we aim to better understand when to adopt AM, how to do so, and how such adoption might change in the future.

This research first conducted a systematic literature review (SLR) to identify AM challenges and opportunities in the medical sector, which were then validated through a Delphi study. The 18 Delphi study participants were also asked to suggest countermeasures for the challenges and help identify future AM adoption scenarios. Finally, these findings were analyzed according to the ecosystem pie model to design an ecosystem model for AM in the medical sector.

Among the 13 challenges and 13 opportunities identified, the lack of a skilled workforce and the responsiveness achievable via AM were by far the most relevant challenge and opportunity. Moreover, the participants identified countermeasures for 10 challenges, as well as three future AM adoption scenarios. Finally, leveraging these findings, an ecosystem model was developed.

This work contributes to the limited understanding of the AM challenges and opportunities in the medical sector. It helps medical practitioners to better understand the challenges and opportunities associated with AM and AM manufacturers to better identify where to focus their R&D efforts and how this would impact future AM adoption levels. Furthermore, this work extends current theory supporting the design of an ecosystem model for AM in the medical sector following the ecosystem pie model.

With Industry 4.0 and the extensive rise of smart technologies, we are seeing remarkable transformations in work practices and workplaces. Scholars report the phenomenal progress of smart technologies. At the same time, we can hear the rhetoric emphasising their potential threats. This study focusses on how and where intelligent machines are leveraged in the workplace, how humans co-working with intelligent machines are affected and what they believe can be done to mitigate the risks of the increased use of intelligent machines.

We conducted in-depth interviews with 15 respondents working in various leadership capacities associated with intelligent machines and technologies. Using NVivo, we coded and churned out the themes from the qualitative data collected.

This study shows how intelligent machines are leveraged across different industries, ranging from chatbots, intelligent sensors, cognitive systems and computer vision to the replica of the entire human being. They are used end-to-end in the value chain, increasing productivity, complementing human workers’ skillsets and augmenting decisions made by human workers. Human workers experience a blend of positive and negative emotions whilst co-working with intelligent machines, which influences their job satisfaction level. Organisations adopt several anticipatory strategies, like transforming into a learning organisation, identifying futuristic technologies and upskilling their human workers, regularly conducting social learning events and designing accelerated career paths to embrace intelligent technologies.

This study seeks to understand the emotional and practical implications of the use of intelligent machines by humans and how both entities can integrate and complement each other. These insights can help organisations and employees understand what future workplaces and practices will look like and how to remain relevant in this transformation.

The purpose of this study is to contribute to the debate on the impact of organizational culture and national culture on green supply chain management (GSCM) adoption by empirically testing the developed framework, and ultimately pave the way toward potential areas for future research.

Using survey data from a sample of Moroccan manufacturing firms, 130 responses were collected and analyzed using SPSS 25 and Smart PLS v 3.3.3 software. The paper used a convenience sample, as it is required by the quantitative method, which legitimate making generalization under certain conditions.

The research results indicated that the national culture does not influence the GSCM implementation. The results contradict a number of prior works. As for the second direct effect measured postulated that organizational culture has a direct and significant impact on the GSCM. The results indicate that adhocracy culture, clan culture and hierarchical culture have a positive impact on the implementation of GSCM initiatives. To assess the impact of ownership type on GSCM, we underlined the difference between local and foreign firms. In fact, as argued, the foreign firms are more implementing GSCM initiatives than local firms do. Based on the arguments advanced on prior literature, the firm size does, as expected, exert significant control over the adoption of GSCM initiatives.

The paper here is a starting point to understand how environmental sustainability and culture are interlinked; further research might contribute to this topic by empirically testing the model in similar or different contexts, using different cultural frameworks.

The practical implications for the paper are related to the necessity of adopting adequate organizational culture to build responsible behaviors for GSCM adoption by Moroccan firms. Recognizing the powerful role of organizational culture as a crucial factor responsible for GSCM’s success beyond the well-defined corporate strategies, including market presence and technological advantages, etc.

This paper contributes to the establishment of codependent links between sociology and management fields as it helps to update the social theories present in the operations management area.

To the best of the author’s knowledge, few works have pursued to review and bridge cultural theories with the GSCM implementation.

The accelerating business transformation through Industry 4.0 (I4.0) is expected to create significant value in the manufacturing industry by delivering considerably high productivity, superior quality, better efficiency and effectiveness. However, its evolutionary processes have far-reaching challenging for humanity. This has triggered a need to analyze the impact of I4.0 on various people-centric variables (PCVs).

This paper attempts to analyze the interrelationship dynamics between the PCVs in the current digital-industry ecosystem using a focus-group approach and causal loop diagrams. Application of the SWARA (stepwise weight assessment ratio analysis) methodology has provided its prioritized ranking in terms of importance.

The study has highlighted that I4.0 has a significant influence on five of the 13 PCVs – human quality of life, digital dexterity, high-skilled talent, low-skilled employment and creativity which contribute to 80% of the total impact.

The prioritized weights of the human factors from the SWARA approach have facilitated the assessment of the Human Resource Development Index (HRDI). The study is also contributing in enriching the literature on the human impact of the growing I4.0 and triggered the researchers to study further its adverse impact on critical human factors.

1. The paper pertains to debates on a very critical issue of impact of integration of the current intelligent digital technologies in manufacturing and services to transform businesses to be more flexible and agile.

2. This paper features I4.0 as a technology that allows integration of new products in the existing production lines, one-off manufacturing runs and high mix manufacturing.

3. The paper also highlights major adjustments in operational activities, processes, supply chain, and organizational redesign due to I4.0 adoption.

4. The current research study has significantly enriched the literature on the I4.0 impact on people-centric variables (PCVs) using the SWARA method. The use of the Causal Loop Diagram has very aptly brought out the type of causality (polarity) between the different PCVs in the growth of I4.0.

The paper pertains to debates on a very critical issue of impact of integration of the current intelligent digital technologies in manufacturing and services to transform businesses to be more flexible and agile.

This paper features I4.0 as a technology that allows integration of new products in the existing production lines, one-off manufacturing runs and high mix manufacturing.

The paper also highlights major adjustments in operational activities, processes, supply chain, and organizational redesign due to I4.0 adoption.

The current research study has significantly enriched the literature on the I4.0 impact on people-centric variables (PCVs) using the SWARA method. The use of the Causal Loop Diagram has very aptly brought out the type of causality (polarity) between the different PCVs in the growth of I4.0.

The industrial revolution changed the market landscape significantly in all industrial sectors. It has a noteworthy impact on enhancing the quality of goods and services. The quality aspect is of utmost concern and determines the success or failure of any product. Therefore, the presented study analyses the key barriers and solutions of Quality 4.0.

Twenty barriers and fifteen solutions were identified using a literature review and investigated using a hybrid approach. Barrier weights were evaluated with the help of the fuzzy AHP method. Furthermore, the computed weights were used to perform computations in the next step using fuzzy-TOPSIS to prioritize the ranking of identified solutions.

The research results show that “Lack of applying advanced analytics to uncover Quality 4.0 initiatives” and “Lack of integrating data from various sources across the organization” are the topmost barriers. Furthermore, “Implement a leadership development program focused on Quality 4.0” and “Cross-departmental peer learning environment” are the topmost solutions.

Managers and industrialists can benefit from Quality 4.0 through improved decision-making, process efficiency, supply chain collaboration, agile quality management, enhanced customer experience and a culture of continuous improvement. This results in better quality, operational effectiveness and a competitive edge.

The solutions need to be mapped with barriers to adopting Quality 4.0. Furthermore, the research results involve novelty by prioritizing the solutions to overcome the anticipated barriers.

Recently, autonomous vehicles (AV) acceptance has been studied intensively. This paper aims to map and analyze the bibliometric characteristics of AV acceptance literature. Furthermore, this research aims to identify research gaps and propose future research opportunities.

The bibliometric analysis was performed. Scopus database was used as the source of the literature. This study selected and analyzed 297 AV acceptance papers. The performance and science mapping analysis were performed.

The developed countries tended to dominate the topic. The publication outlet tended to be in transportation or technology journals. There were four research themes in existing literature. Technology acceptance model (TAM) and UTAUT2 tended to be used for explaining AV acceptance. AV acceptance studies tended to use two types of psychological concepts for understanding AV acceptance, namely risk related concepts and functional utilitarian benefit related concepts. In the context of research design, quantitative approach tended to be used. Self-driving feature was the most exploited feature of AV in the existing literature. Three research gaps were mapped and future research opportunities were proposed.

This paper provided a comprehensive information that allowed scientists to develop future research on AV acceptance.

There is lack of paper that discussed the bibliometric characteristics of AV acceptance literature. This paper fulfilled the gap.