Analyzing manufacturing strategies and Industry 4.0 supplier performance relationships from a resource-based perspective

Adoption of modern technologies for implementing industry 4.0: an integrated MCDM approach

Purpose

Modern technologies are seen as an essential component of the fourth industrial revolution (industry 4.0) and their adoption is vital to transform the existing manufacturing system into industry 4.0-based manufacturing system. Therefore, the primary objective of this research explores the barriers of modern technology adoption and their mitigating solutions in order to align with Industry 4.0 objectives.

Design/methodology/approach

Barriers to adopting modern technologies and respective mitigating solutions are identified from the available literature. Further, these barriers are ranked with the help of expert opinions by using the BWM method appropriately. The identified solutions are ranked using the combined compromise solution (CoCoSo) method.

Findings

Several modern technologies and their capabilities are recognised to support the industry 4.0-based manufacturing systems. This study identifies 22 barriers to the effective adoption of modern technologies in manufacturing and 14 solutions to overcome these barriers. Change management, the high initial cost of technology and appropriate support infrastructure are the most significant barriers. The most prominent solutions to overcome the most considerable barriers are ‘supportive research, development and commercialisation environment’, ‘updated policy and effective implementation’ and ‘capacity building through training’ that are the top three solutions that need to be addressed.

Research limitations/implications

The barriers and solutions of modern technology adoption are obtained through a comprehensive literature review, so there is a chance to ignore some significant barriers and their solutions. Furthermore, ranking barriers and solutions is done with expert opinion, which is not free from biases.

Practical implications

This identification and prioritisation of barriers will help managers to understand the barriers so they can better prepare themselves. Furthermore, the suggested solutions to overcome these barriers are helpful for the managers and could be strategically adopted through optimal resource utilisation.

Originality/value

This study proposes a framework to identify and analyse the significant barriers and solutions to adopting modern technologies in the manufacturing system. It might be helpful for manufacturing organisations that are willing to transform their manufacturing system into industry 4.0.

Emerging competencies for logistics professionals in the digital era: A literature review

The speed of technology integration among businesses has accelerated during the COVID-19 pandemic due to the work-from-home arrangements and safe distancing regulations, prompting businesses to automate operations and digitalize work environments. These impacts have disrupted work environments and operational processes, and a fresh set of competencies is required to stay competent in this new normal. Consequently, there is a need to develop a state-of-the-art competency framework for logistics professionals during these trying times. This study has adopted the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to review, identify, and update the emerging competencies required by logistics professionals. The relevant academic documents were narrowed down to 81 and were used to identify the emerging competencies relevant to Industry 4.0 and COVID-19. The competencies were subsequently categorized into four key domains i.e., business, logistics, digital, and personal competencies, with a total of 17 sub-domains. This state-of-the-art framework contributes to academic research by updating the existing competency frameworks. Future research can also build upon this holistic list of emerging competencies by utilizing it to reduce the competency gaps faced by those who are less technology savvy i.e., older logistics professionals. Additionally, future research can correlate the competency framework to organizational learning theories to improve the overall performance of logistics companies.

Artificially Intelligent Super Computer Machines and Robotics: Apprehensions and Challenges – A Call for Responsible Innovation Framework

“Industrial revolution 4.0” is a term that is becoming increasingly popular among academics. A number of articles have been carved to emphasize the beneficial aspects of the stated issue under many titles such as cyber-physical systems, internet of things, artificial intelligence, smart manufacturing, digitalization of industrial production, and so on. However, few academics have delved into the negative or dark side of such a profound technological paradigm change, especially the artificially intelligent robotics, creating a large knowledge vacuum. Because of this, little is known about the negative repercussions of artificial intelligence (AI), a key component of the Fourth Industrial Revolution (or IR 4.0). It is an open secret now that AI machines may have serious impacts on human autonomy, fairness, justice, and agency. These unanticipated consequences have resulted in the development of an emerging concept, that is, responsible innovation. The responsible innovation framework binds the firm ethically, morally, and socially to be responsible, environmentally friendly, humanitarian, and business-oriented while developing innovative products. The current study proposes an integrated responsible innovation framework that acts as a science governance mechanism and considers organizations and stakeholders collectively responsible for upcoming technological innovations. This study has suggested several implications for policymakers.

Benchmarking strategic core competencies of performance across Chinese and South Korean manufacturing companies

Purpose

This study empirically investigates the significance of the core competencies on various economic performance indices by utilizing accounting and market-based performance in Chinese and South Korean leading manufacturing companies.

Design/methodology/approach

This research employs a series of hierarchical regression models to test the hypotheses concerning the significance of R&D and export strategy on firms' performance.

Findings

This study finds that R&D intensity and foreign trade activities through export are most likely to be significantly associated with firm performance, particularly market-based performance, across the Chinese and South Korea manufacturing companies. The significance of other core strategic factors such as capital intensity, leverage, inventory turnover, labor productivity, administrative cost efficiency, and collection policy on performance was also contemplated.

Originality/value

The relationship between R&D and firm performance has been an interesting issue concerning the performance measures employed across different country settings. Research issues addressed in this paper relate to how R&D, and foreign trade by export influence firm performance across two diverse economic environments inherent of Chinese and South Korean leading manufacturing firms. Particularly, this study explores the directions and magnitudes of the operational and strategic relationships between key strategic factors, such as R&D intensity, export by foreign trade, and the firm's economic and market-based performance.

Exploring Key Decisive Factors in Manufacturing Strategies in the Adoption of Industry 4.0 by Using the Fuzzy DEMATEL Method

Globalization has created a highly competitive and diverse market, an uncertain and risky business environment, and changing customer expectations. An effective manufacturing strategy reduces complexity and provides organizations with a well-organized manufacturing structure. However, existing research on manufacturing strategies appears scattered, lacking systematic understanding and finding no causal relationship between manufacturing strategies’ outputs (MSOs) and their importance. Therefore, this study is a pioneer in identifying the influential factors of MSOs in the adoption of Industry 4.0 (I4.0) technologies utilizing the decision-making trial and evaluation laboratory (DEMATEL) approach. This method is considered an effective method for identifying the cause-effect relationship of complex problems. It evaluates interdependent relationships among MSO factors from the perspective of academic and industry experts. Identifying cause and effect factors leads to increasing the market’s competitiveness and prioritizing them. To deal with the vagueness of human beings’ perceptions, this study utilizes fuzzy set theory and the DEMATEL method to form a structural model. Results show that customer satisfaction, cost per unit produced, and the number of advanced features are the main factors influencing MSOs.

Digitalization of the supply chain: transformation factors

Purpose

There is an increasing interest in the supply chain’s digitalization, yet the topic is still in the preliminary stages of academic research. The academic literature has no consensus and is still limited to research assessing the supply chain’s digitalization of organizations. This study aims to explore the supply chain digitalization drivers to understand the emerging phenomena. More specifically, the authors devised from the literature the most common factors in assessing the readiness in scaling supply chain digitalization.

Design/methodology/approach

This study followed a five-phased systematic literature review (SLR) methodology in this research: designing, analyzing, conducting, writing and assessing the quality of the review. The SLR is beneficial for justifying future research regardless of the complex process that requires dealing with high-level databases, information filtering and relevancies of the content. Through analysis of 347 titles and abstracts and 40 full papers, the authors showed and discussed the supply chain digitalization: transformation factors.

Findings

The results generated three main themes: technology, people and processes. The study also generated ten subthemes/primary drivers for assessing the readiness for supply chain digitalization in organizations: IT infrastructure, cybersecurity systems, digitalization reskilling and upskilling, digitalization culture, top management support, digitalization and innovation strategy, integrated supply chain, digital innovation management, big data management and data analytics and government regulations. The importance of each factor was discussed, and future research agenda was presented.

Research limitations/implications

While the key drivers of the supply chain digitalization were identified, there is still a need to study the statistical correlation to confirm the interrelationships among factors. This study is also limited by the articles available in the databases and content extraction.

Practical implications

This study supports decision-makers in understanding the critical drivers in digitalizing the supply chain. Once these factors are studied and comprehended, managers and decision-makers could better anticipate and allocate the proper resources to embark on the digitalization journey and make informed decisions.

Originality/value

The digitalization of the supply chain is more critical nowadays due to the global disruptions caused by the Coronavirus (COVID-19) pandemic and the surge of organizations moving toward the digital economy. There is a gap between the digital transformation pilot studies and implementation. The themes and factors unearthed in this study will serve as a foundation and guidelines for further theoretical research and practical implications.

International mobile marketing: a satisfactory concept for companies and users in times of pandemic

Purpose

This study’s purpose is to analyze the international mobile marketing (IMK) in order to stage the importance of this tool in the internationalization of companies. Our understanding of mobile marketing is constantly evolving, due to its high business penetration in a world globalized by technologies.

Design/methodology/approach

A review of the relevant literature on IMK, companies and customers is undertaken to understand the link between them. The paper begins by explaining the coronavirus disease 2019 is accelerating the change of the rules of the game in traditional and online commerce around the world. Furthermore, this study uses secondary data from organisation for economic co-operation and development (OECD), Sensor Tower, mobile marketing association (MMA), App Annie, among others, to support research results.

Findings

The results have shown that IMK has opened a melting pot of opportunities for companies and consumers in this period of pandemic; the potential of this tool is being redefined, in order to identify, anticipate and satisfy customers requirement profitably and efficiently. This study aims to provide an assessment of new concept of IMK and how this tool has to be integrated into the firm’s digital marketing strategies.

Originality/value

The study contributes to make better future decisions in the international digital expansion of companies by company executives and marketing experts. This paper provides a comprehensive framework intended to guide research efforts focusing on digital marketing as well as to aid practitioners in their quest to achieve IMK success.

Implementing Vertical Integration in the Industry 4.0 Journey: Which Factors Influence the Process of Information Systems Adoption?

One of the key principles of Industry 4.0 is the implementation of vertical integration, which considers the integration of information systems from different hierarchical levels in a company to support decision-making with real-time data flows. Companies face challenges when they want to implement vertical integration, which is not trivial due to the risks inherent to the decision stages of adoption. We investigate the main factors influencing the different stages of adoption of vertical integration to provide a clearer view of what managers should consider at each stage. We adopt a multi-case study approach based on the investigation of ten companies that followed this adoption process. We develop a framework with 22 factors deployed in the three stages of decision (knowledge, persuasion, and final decision) and three main dimensions of analysis: technology, organization, and environment. We analyze the potential tensions between these factors and show how managers should balance such factors during the decision stages.

Quality 4.0 and its impact on organizational performance: an integrative viewpoint

Purpose

Quality 4.0 is managing quality during the fourth industrial revolution. It is used by modern-day organizations as a strategy to compete and thrive in the marketplace. The purpose of this study is to analyze the potential impact of Quality 4.0 on organizational performance.

Design/methodology/approach

This study through an integrative literature review critically analyzed 41 previous literature articles to study the impact of Quality 4.0 on various metrics of organizational performance.

Findings

The results of the review suggest that Quality 4.0 may have an impact on financial performance, customer value proposition, internal business processes, learning and growth, environmental performance and social performance.

Research limitations/implications

This study is limited by the databases reviewed. The second limitation is that this study considered articles published in the English language. Therefore, articles published in other languages were not considered in this study.

Practical implications

Organizations can use the findings of this study to strongly leverage the implementation of Quality 4.0 to reach their strategic objectives and improve competitive advantage.

Originality/value

This is the first study to explore the impact of Quality 4.0 on organizational performance through an integrative literature review.

How does performance vary between early and late adopters of Industry 4.0? A qualitative viewpoint

Purpose

Industry 4.0 is a new trend among organizations. Some organizations have been early adopters or later adopters of Industry 4.0. The purpose of this paper is to investigate how performance effects vary between early and late adopters of Industry 4.0.

Design/methodology/approach

This study applies a qualitative research methodology using grounded theory. 14 senior management professionals who have implemented Industry 4.0 participated in this study through a theoretical and snowball sampling approach. These professionals were from manufacturing and service sectors, from North America, Europe and Asia. The study used semi structured open-ended interviews to capture the organizational performance on operational, financial, environmental and social dimensions.

Findings

The findings were analyzed in terms of four broad themes which emerged from the interviews. In operational performance the operational and implementation cost will be higher for early adopters. The late adopters may enjoy the advantage in terms of improved business models. In terms of financial performance, the early adopters may see a marginal increase in profit and increased stock price compared to late adopters. The performance on the environmental dimension will see early adopters enjoying material efficiency, energy savings and an improved image of the company compared to late adopters. In social performance, the early adopters will provide a better quality of work life, safer manufacturing environment. However, the resistance from labor unions will be higher for early adopters compared to late adopters.

Practical implications

Organizations must decide the timing of implementation of Industry 4.0. This study will act as a guide wherein they can decide to be an early adopter or late adopter based on knowledge of the resulting performance consequences.

Originality/value

This is the first paper that studies the performance effects of early versus late adopters of Industry 4.0.

The impact of Logistics 4.0 on corporate sustainability: a performance assessment of automated warehouse operations

Purpose

The purpose of this study is to gain a better understanding of the impacts of Logistics 4.0 initiatives (focusing on automated warehousing systems) on the economic, environmental and social dimensions of firms' sustainability performance. To achieve this objective, a new framework for the assessment of sustainable warehousing in the 4.0 era is developed.

Design/methodology/approach

The framework, developed via the item-objective congruence index, Q-sort method and interviews with experts, is employed to assess performance changes through management interviews in two warehousing companies after the implementation of automation technologies.

Findings

Most aspects of both companies' sustainability performance are considerably improved (e.g. productivity, accuracy, air emission, worker safety and supply chain visibility); however, the outcome for some criteria might be worsened or improved depending on each company's solutions and strategies (e.g. increasing electricity bills, maintenance costs and job losses).

Practical implications

The findings provide insight into the effective implementation of warehousing technologies. The proposed framework is also a valid and reliable instrument for sustainability assessment for warehousing operators, which companies can utilise for self-assessment.

Originality/value

This paper contributes to establishing a body of literature that explores the previously unclarified effects of Logistics 4.0 on firms' sustainability performance. The proposed framework, which captures critical concerns of corporate sustainability and technological adaptation, is also the first of its kind for warehouse performance assessment.

Applying Industry 4.0 technologies in the COVID–19 sustainable chains

Purpose

The purpose of this paper is 1) to investigate the effects on the crucial Industry 4.0 technological innovations that interact between the real and virtual worlds and that are applied in the sustainable supply chain process; 2) to contribute to the identification of the opportunities, the challenges and the gaps that will support the new research study developments and 3) to analyze the impact of the Industry 4.0 technologies as facilitators of the sustainable supply chain performance in the midst of the Coronavirus (COVID-19).

Design/methodology/approach

This research is performed through a bibliographic review in the electronic databases of the Emerald Insight, the Scopus and the Web of Science, considering the main scientific publications on the subject.

Findings

The bibliographic search results in 526 articles, followed by two sequential filters for deleting the duplicate articles (resulting in 487 articles) and for selecting the most relevant articles (resulting in 150 articles).

Practical implications

This article identifies the opportunities and the challenges focused on the emerging Industry 4.0 theme. The opportunities can contribute to the sustainable performance of the supply chains and their territories. The Industry 4.0 can also generate challenges like the social inequalities related to the position of the man in the labor market by replacing the human workforce with the machines. Therefore, the man-machine relationship in the Industry 4.0 era is analyzed as a gap in the literature. Therefore, as a way to fill this gap, the authors of this article suggest the exploration of the research focused on the Society 5.0. Also known as “super-smart society,” this recent theme appeared in Japan in April 2016. According to Fukuda (2020), in addition to the focus on the technological development, the Society 5.0 also aims at the quality of life and the social challenge resolutions.

Originality/value

This article contributes to the analysis of the Industry 4.0 technologies as facilitators in the sustainable supply chain performance. It addresses the impacts of the Industry 4.0 technologies applied to the supply chains in the midst of the COVID-19 pandemic, and it analyzes the research gaps and limitations found in the literature. The result of this study can add value and stimulate new research studies related to the application of the Industry 4.0 technologies as facilitators in the supply chain sustainable performance. It can encourage the studies related to the COVID-19 impacts on the sustainable supply chains, and it can promote the research development on the relationship among the man, the machine and the labor in the Fourth Industrial Revolution.

An integrated ANP–QFD approach for prioritization of customer and design requirements for digitalization in an electronic supply chain

Purpose

Supply chain efficiency can be enhanced by integrating the activities in supply chain through digitalization. Advancements in digital technologies has facilitated in designing robust and dynamic supply chain by bringing in efficiency, transparency and reduction in lead times. This research tries to identify and prioritize the customer requirements and design requirements for effective integration of supply chain through digitalization.

Design/methodology/approach

The key nine customer requirements and 16 design requirements applicable for an electronics company were shortlisted in consultation with the experts from the company and academia. An integrated analytic network process (ANP) and quality function deployment (QFD) methodology has been applied for prioritizing the customer and design requirements. The relative importance and interdependence of these requirements were identified and a House of Quality (HOQ) is constructed.

Findings

The HOQ constructed has prioritized and identified interrelationships among customer requirements and design requirements for effective supply chain digitalization. These findings could be effectively used by managers for planning the objectives on long-term, medium-term and short-term basis.

Originality/value

This study tries to bridge the gap of identifying and prioritizing the design and customer requirements for effective supply chain integration through digitalization. The results could aid practicing managers and academicians in decision-making on supply chain digitalization process.

Supply chain integration and Industry 4.0: a systematic literature review

Purpose

The current industrial revolution is powered by data, which is also referred as Industry 4.0. The Industry 4.0 has attracted significant attention from academia and the industry professionals. The supply chain integration (SCI) has played a significant role in enhancing supply chain performance and organizational performance. This study explores the relationship between Industry 4.0 and SCI via an extensive literature review to understand the various levels of integration with the supply chain processes and to identify missing links, through a framework, and suggest further research directions.

Design/methodology/approach

In this paper, we have used systematic literature review approach to identify the building blocks of the conceptual framework, which is the main contribution of the present study. We have used Scopus database to search literature using keywords.

Findings

The study offers some interesting insights that may help scholars to advance theoretical debates. Moreover, the study also provides interesting direction to the practitioners engaged in supply chain management in data-driven environment. In this study, we have proposed a conceptual framework for the adoption of Industry 4.0 and SCI.

Research limitations/implications

In this study we have proposed a conceptual framework. However, the framework is yet to be empirically tested. Hence, we caution readers to evaluate the findings of the present study in context to its limitations. This is an attempt to develop a conceptual framework which may be tested using longitudinal data.

Originality/value

The present work helps in integrating two independent subjects', i.e. Industry 4.0 and SCI. The theoretical framework presented here integrates Industry 4.0 and SCI which can be useful to the practitioners and policymakers engaged in implementing Industry 4.0.

Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations

Purpose

Human resource managers are adopting AI technology for conducting various tasks of human resource management, starting from manpower planning till employee exit. AI technology is prominently used for talent acquisition in organizations. This research investigates the adoption of AI technology for talent acquisition.

Design/methodology/approach

This study employs Technology-Organization-Environment (TOE) and Task-Technology-Fit (TTF) framework and proposes a model to explore the adoption of AI technology for talent acquisition. The survey was conducted among the 562 human resource managers and talent acquisition managers with a structured questionnaire. The analysis of data was completed using PLS-SEM.

Findings

This research reveals that cost-effectiveness, relative advantage, top management support, HR readiness, competitive pressure and support from AI vendors positively affect AI technology adoption for talent acquisition. Security and privacy issues negatively influence the adoption of AI technology. It is found that task and technology characteristics influence the task technology fit of AI technology for talent acquisition. Adoption and task technology fit of AI technology influence the actual usage of AI technology for talent acquisition. It is revealed that stickiness to traditional talent acquisition methods negatively moderates the association between adoption and actual usage of AI technology for talent acquisition. The proposed model was empirically validated and revealed the predictors of adoption and actual usage of AI technology for talent acquisition.

Practical implications

This paper provides the predictors of the adoption of AI technology for talent acquisition, which is emerging extensively in the human resource domain. It provides vital insights to the human resource managers to benchmark AI technology required for talent acquisition. Marketers can develop their marketing plan considering the factors of adoption. It would help designers to understand the factors of adoption and design the AI technology algorithms and applications for talent acquisition. It contributes to advance the literature of technology adoption by interweaving it with the human resource domain literature on talent acquisition.

Originality/value

This research uniquely validates the model for the adoption of AI technology for talent acquisition using the TOE and TTF framework. It reveals the factors influencing the adoption and actual usage of AI technology for talent acquisition.

Twenty-five years’ contribution of “Benchmarking: an International Journal” to manufacturing strategy: a scientometric review

Purpose

This study aims at reviewing the articles on the themes of manufacturing strategy (MS) published in “Benchmarking: An International Journal (BIJ)” and investigating the trends of publication for future research.

Design/methodology/approach

Five-stage methodology to conduct a literature review is adopted comprising: (1) article collection, (2) inclusion/exclusion criteria, (3) reviewing the articles, (4) analyzing the articles and (5) future research directions. A total of 57 articles specific to MS domain published in BIJ are reviewed. Further, a bibliometric analysis comprising keywords co-occurrence, citation and co-citation using a VOSviewer© software followed by content analysis to analyze the type of research, type of industry and type of tool/method used is carried out.

Findings

The study helps to find the scope of the journal and research gaps in the MS domain to provide future research directions. Most of the work found is survey-based or case-based in nature. However, there is a need for empirical research to be done in the field of MS.

Research limitations/implications

The study facilitates researchers willing to publish in BIJ to understand different themes of accepted papers concerning MS domain. The identified research gaps and future research direction can motivate researchers and practitioners to coin new approaches in the MS domain.

Originality/value

A comprehensive review and analysis of the MS literature published in BIJ has been provided. To the best of authors' knowledge, the current study is the only review study in MS domain focusing on one specific journal.