Journal of Manufacturing Technology Management最新文献

Purpose

This study examines the mediating roles of the three dimensions of business intelligence (sensing capability, transforming capability and driving capability) in the relationship between the three dimensions of big data analytics capability (big data analytics management, technology and talent capabilities), and radical innovation among Chinese manufacturing enterprises.

Design/methodology/approach

A theoretical framework was developed using the resource-based view. The hypothesis was tested using empirical survey data from 326 Chinese manufacturing enterprises.

Findings

Empirical results show that, in the Chinese manufacturing context, business intelligence sensing capability, business intelligence transforming capability and business intelligence driving capability positively mediate the impact of big data analytics capability on radical innovation.

Practical implications

The results offer managerial guidance for leaders to properly use big data analytics capability, business intelligence and radical innovation as well as offering theoretical insight for future research in the manufacturing industry’s radical innovation.

Originality/value

This is among the first studies to examine three dimensions of big data analytics capability on the manufacturing industry’s radical innovation by considering the mediating role of three dimensions of business intelligence.

Purpose

Industry 4.0 has put forward a smart perspective on managing supply chain networks and their operations. The current manufacturing system is primarily data-driven. Industries are deploying new emerging technologies in their operations to build a competitive edge in the business environment; however, the true potential of smart manufacturing has not yet been fully unveiled. This research aims to extensively analyse emerging technologies and their interconnection with smart manufacturing in developing smarter supply chains.

Design/methodology/approach

This research endeavours to establish a conceptual framework for a smart supply chain. A real case study on a smart factory is conducted to demonstrate the validity of this framework for building smarter supply chains. A comparative analysis is carried out between conventional and smart supply chains to ascertain the advantages of smart supply chains. In addition, a thorough investigation of the several factors needed to transition from smart to smarter supply chains is undertaken.

Findings

The integration of smart technology exemplifies the ability to improve the efficiency of supply chain operations. Research findings indicate that transitioning to a smart factory radically enhances productivity, quality assurance, data privacy and labour efficiency. The outcomes of this research will help academic and industrial sectors critically comprehend technological breakthroughs and their applications in smart supply chains.

Originality/value

This study highlights the implications of incorporating smart technologies into supply chain operations, specifically in smart purchasing, smart factory operations, smart warehousing and smart customer performance. A paradigm transition from conventional, smart to smarter supply chains offers a comprehensive perspective on the evolving dynamics in automation, optimisation and manufacturing technology domains, ultimately leading to the emergence of Industry 5.0.

Purpose

Business Model Innovation is increasingly created by an ecosystem of related companies. This paper aims to investigate the transition of a manufacturing ecosystem toward electric vehicles from a business model perspective.

Design/methodology/approach

The authors investigate an automotive manufacturing ecosystem that is in transition toward electric and electrified vehicles, conducting semi-structured interviews with 46 informants from 27 ecosystem members.

Findings

The results reveal that the actions of several ecosystem members are driven by regulations relating to emissions. Novel requirements regarding components and complementary offers necessitate the entry of actors from other industries and the formation of new ecosystem members. While the newly emerged ecosystem has roots in an established ecosystem, it relies on new value offers. Further, the findings highlight the importance of ecosystem governance, while the necessary degree of change in the members' business models depends on their roles and positions in the ecosystem. Therefore, upstream suppliers of components must perform business model adaptation, whereas downstream providers must perform more complex business model innovation.

Originality/value

The paper is among the first to investigate an entire manufacturing ecosystem and analyze its transition toward electric vehicles and the implications for business model innovation.

Purpose

Different studies have been conducted on the relationship between technological capability and firm performance. These studies obtain different values for the relationship, known as heterogeneous results. The purpose of this paper is to analyze the relationship between technological capability and firm performance and its statistical between-study heterogeneity.

Design/methodology/approach

In order to analyze all the results from this relationship that were found in the literature, we adopted the literature review with a meta-analytic method. We consulted the Scopus and Web of Science databases, which returned, after the application of inclusion criteria, 23 primary studies with data from 5,882 manufacturing firms.

Findings

We observed that technological capability and performance are positively related; however, the results regarding this relationship are heterogeneous. We discovered four possible sources of statistical between-study heterogeneity: (i) the statistical between-study heterogeneity of the variables to measure technological capability and performance; (ii) orientation of the thematic approach – some illustrate the relationship between technological capability and performance using mathematical and theoretical models, while others examine the relationship between technological capability and performance and propose implications pertaining to that relationship; (iii) the source of data for primary studies and (iv) the context in which this relationship is observed.

Research limitations/implications

It is necessary to standardize a set of variables through which technological capability and performance are evaluated so that results and implications can be usefully compared between countries and industrial sectors.

Originality/value

The contribution to knowledge is identifying the statistical between-study heterogeneity on the relationship between technological capabilities and firm performance, as well as its potential sources.

Purpose

While previous operations management literature acknowledges the positive influence of Lean and Industry (I4.0) on performance, recent studies examining the synergy between these two factors have produced inconsistent and contradictory results. Therefore, this study aims to provide a comprehensive understanding of the effect of Lean and I4.0 synergy on firm performance.

Design/methodology/approach

This study utilised a meta-analysis approach, examining 23 empirical studies exploring multiple effects of the Lean and I4.0 synergy on firm performance. Multiple subgroup analyses were conducted to assess the contradictory outcomes and identify in what conditions such synergy may achieve performance.

Findings

The results affirm the prevailing positivist perspective among most scholars regarding the positive influence of the Lean and I4.0 synergy on firm performance. However, the overall effect size derived from the studies indicates a weak relationship, suggesting that this synergy alone is not the sole determinant factor of firm performance. In addition, the subgroup analyses reveal the presence of contingent conditions that may affect the performance outcomes when integrating Lean and I4.0, as most effects exhibit a weak relationship.

Originality/value

This study represents the first meta-analysis investigating the relationship between the Lean and I4.0 synergy on firm performance. By shedding light on the contradictory effects often depicted in the operations management literature, this study provides a critical reflection for researchers who tend to adopt an overly optimistic view of such synergy.

Purpose

While Digitalisation is gaining momentum among practitioners and the scientific world, there is still a struggle to embark on the digitalisation journey successfully. The struggles are more significant for SMEs compared to large companies. Such transformation could face internal resistance, which evokes the need to put it into a socio-technical perspective such as lean. This paper investigates how SMEs could implement digital tools and technologies in their operations.

Design/methodology/approach

We relied on a multiple case study design in three SME manufacturing companies in Italy. Based on the experience of those companies, the struggles in the implementation and the lessons learned, we formulate an implementation model of digital tools driven by lean thinking.

Findings

Companies tend to implement first digital tools that help with real-time data collection and stress that introducing digital tools becomes challenging without reducing waste in production. The model stresses top management commitment, middle-line involvement and operator training to resist change. All these factors coincide with socio-technical lean bundles developed by seminal works. In addition, the study highlights that financial incentives are not necessarily the common barrier to digital tools implementation in SMEs but rather the cultural aspect.

Originality/value

Our paper enriches the extant body of knowledge by deriving knowledge around digitalisation implementation through lessons learned and corrective actions. It allows managers to benchmark and compare the current state of the implementation process with that of other companies and the one proposed to make corrective actions when necessary.

Purpose

The purpose of this paper is to investigate how different manufacturing technologies are bundled together and how these bundles influence operations performance and, indirectly, business performance. With the emergence of Industry 4.0 (I4.0) technologies, manufacturing companies can use a wide variety of advanced manufacturing technologies (AMT) to build an efficient and effective production system. Nevertheless, the literature offers little guidance on how these technologies, including novel I4.0 technologies, should be combined in practice and how these combinations might have a different impact on performance.

Design/methodology/approach

Using a survey study of 165 manufacturing plants from 11 different countries, we use factor analysis to empirically derive three distinct manufacturing technology bundles and structural equation modeling to quantify their relationship with operations and business performance.

Findings

Our findings support an evolutionary rather than a revolutionary perspective. I4.0 technologies build on traditional manufacturing technologies and do not constitute a separate direction that would point towards a fundamental digital transformation of companies within our sample. Performance effects are rather weak: out of the three technology bundles identified, only “automation and robotization” have a positive influence on cost efficiency, while “base technologies” and “data-enabled technologies” do not offer a competitive advantage, neither in terms of cost nor in terms of differentiation. Furthermore, while the business performance impact is positive, it is quite weak, suggesting that financial returns on technology investments might require longer time periods.

Originality/value

Relying on a complementarity approach, our research offers a novel perspective on technology implementation in the I4.0 era by investigating novel and traditional manufacturing technologies together.

Purpose

This paper explores the orchestration of digital innovation in Industry 4.0 organisations.

Design/methodology/approach

The study applies the activity theory to explorative multiple case studies. Observations of innovation activities in five business cases take place at two large international organisations.

Findings

The results underline five logics of action that drive digital innovation: (1) digital transformation, (2) technology translation, (3) catalyst agents, (4) digital thread and (5) empowerment. Further, the case study organisations highlight the importance of developing a sustainable culture capable of continuously adopting new technologies, processes and infrastructure that will allow the management of digital innovations.

Originality/value

The study empirically shows the motivations and challenges in orchestrating digital innovation in Industry 4.0 organisations.

Purpose

Smart manufacturing (SM) lies at the core of Industry 4.0. Uniform adoption of SM across business partners is crucial to exploit its value creation potential. However, firms' willingness to invest in SM is limited by insufficient or inconclusive evidence on its performance-related benefits. To close this gap, this paper develops and tests a model linking SM adoption to firms' financial performance. Improvements along the four dimensions of operational performance (i.e. cost quality, delivery and flexibility) mediate this relation.

Design/methodology/approach

This study follows an empirical research approach. In particular, survey data from 234 automotive component suppliers are analyzed via covariance-based structural equation modeling to explore the link between SM adoption and operational performance. Survey data are then matched with secondary data from balance sheets of 81 firms to investigate the impact of SM on financial performance via partial least square structural equation modeling.

Findings

Findings highlight that adoption of SM results in improvements in cost, quality, delivery performance, thus suggesting that SM is a mean to overcome performance trade-offs. Improvements in operational performance enabled by SM do not give rise to superior financial performance, thus implying that SM might support firms in maintaining the competitive position in the market, but could be insufficient to generate higher margin.

Originality/value

Results have implications for SM research and for manufacturing executives engaged in the adoption of SM, as they provide a detailed analysis of the impact of SM on operational performance and clarify the effect that SM adoption has on financial performance.

Purpose

Corona Virus Disease (Covid-19) is a global pandemic that emerged at the end of 2019 and caused disruptions in global supply chains, particularly in the food supply chains that exposed the vulnerability of today’s food supply chain in a major disruption which provided a unique research opportunity. This review explores the current research direction for food supply chain resilience and identifies gaps for future research in preparing for future major global pandemics.

Design/methodology/approach

This article presents a review of food supply chain resilience followed a systematic literature review of the business and management-based studies related to the food supply chain in Covid-19 published between December 2019 and December 2021 to identify the immediate issues and responses that need to be addressed in the event of future disruptions in food supply chains due to new global health threats.

Findings

The study revealed the need for more literature on food supply chain resilience, particularly resilience to a major global pandemic. The study also uncovered the sequence of events in a major pandemic and identified some strategies for building resilience to potential future risks of such an event.

Research limitations/implications

The limitations of this study are apparent. Firstly, the selection of databases is not comprehensive. Due to time limitations, authoritative publishers such as Springer, Emerald, Wiley and Taylor & Francis were not selected. Secondly, a single author completed the literature quality testing and text analysis, possibly reducing the credibility of the results due to subjective bias. Thirdly, the selected literature are the studies published during the immediate event of Covid-19, and before January 2022, other research studies may have been completed but were still in the state of auditing at this time.

Originality/value

This paper is the first study that provides a detailed classification of the immediate challenges to the food supply chain faced in both upstream and downstream nodes during a major global disruption. For researchers, this clearly shows the immediate difficulties faced at each node of the food supply chain, which provides research topics for future studies.