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1 – 10 of over 3000Yong Qi, Qian Chen, Mengyuan Yang and Yilei Sun
Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the…
Abstract
Purpose
Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.
Design/methodology/approach
This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.
Findings
The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.
Originality/value
First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.
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Krisztina Demeter, Levente Szász, Béla-Gergely Rácz and Lehel-Zoltán Györfy
The purpose of this paper is to investigate how different manufacturing technologies are bundled together and how these bundles influence operations performance and, indirectly…
Abstract
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.
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Abstract
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.
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Daryl John Powell, Désirée A. Laubengaier, Guilherme Luz Tortorella, Henrik Saabye, Jiju Antony and Raffaella Cagliano
The purpose of this paper is to examine the digitalization of operational processes and activities in lean manufacturing firms and explore the associated learning implications…
Abstract
Purpose
The purpose of this paper is to examine the digitalization of operational processes and activities in lean manufacturing firms and explore the associated learning implications through the lens of cumulative capability theory.
Design/methodology/approach
Adopting a multiple-case design, we examine four cases of digitalization initiatives within lean manufacturing firms. We collected data through semi-structured interviews and direct observations during site visits.
Findings
The study uncovers the development of learning capabilities as a result of integrating lean and digitalization. We find that digitalization in lean manufacturing firms contributes to the development of both routinized and evolutionary learning capabilities in a cumulative fashion.
Originality/value
The study adds nuance to the limited theoretical understanding of the integration of lean and digitalization by showing how it cumulatively develops the learning capabilities of lean manufacturing firms. As such, the study supports the robustness of cumulative capability theory. We further contribute to research by offering empirical support for the cumulative nature of learning.
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Rouhollah Khakpour, Ahmad Ebrahimi and Seyed-Mohammad Seyed-Hosseini
This paper recommends a method entitled “SMED 4.0” as a development of conventional single minute exchange of die (SMED) to avoid defect occurrence during production and improve…
Abstract
Purpose
This paper recommends a method entitled “SMED 4.0” as a development of conventional single minute exchange of die (SMED) to avoid defect occurrence during production and improve sustainability, besides reducing setup time.
Design/methodology/approach
The method builds upon an extensive literature review and in-depth explorative research in SMED and zero defect manufacturing (ZDM). SMED 4.0 incorporates an evolutionary stage that employs predict-prevent strategies using Industry 4.0 technologies including the Internet of Things (IoT) and machine learning (ML) algorithms.
Findings
It presents the applicability of the proposed approach in (1) identifying the triple bottom line (TBL) criteria, which are affected by defects; (2) predicting the time of defect occurrence if any; (3) preventing defective products by performing online setting on machines during production as needed; (4) maintaining the desired quality of the product during the production and (5) improving TBL sustainability in manufacturing processes.
Originality/value
The extended view of SMED 4.0 in this research, as well as its analytical approach, helps practitioners develop their SMED approaches in a more holistic way. The practical application of SMED 4.0 is illustrated by implementing it in a real-life manufacturing case.
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Haihan Li, Per Hilletofth, David Eriksson and Wendy Tate
This study aims to investigate the manufacturing reshoring decision-making content from an Eclectic Paradigm perspective.
Abstract
Purpose
This study aims to investigate the manufacturing reshoring decision-making content from an Eclectic Paradigm perspective.
Design/methodology/approach
Data were collected through a six-step systematic literature review on factors influencing manufacturing reshoring decision-making. The review is based on 100 peer-reviewed journal papers discussing reshoring decision-making contents published from 2009 to 2022.
Findings
In total, 80 decision factors were extracted and then categorized into resource-seeking (8%), market-seeking (11%), efficiency-seeking (41%) and strategic asset-seeking (16%) advantages. Additionally, 24% of these were identified as hybrid, which means that they were classified into multiple categories. Some decision factors were further identified as reshoring influencing factors (i.e. drivers, enablers and barriers).
Research limitations/implications
Scholars need to consider what other theories can be used or developed to identify and evaluate the decision factors (determinants) of manufacturing reshoring as well as how currently adopted theory can be further advanced to create clearer and comprehensive theoretical frameworks.
Practical implications
This research underscores the importance of developing clearer and more comprehensive theoretical frameworks. For practitioners, understanding the multifaceted nature of decision factors could enhance strategic decision-making regarding reshoring initiatives.
Originality/value
To the best of the authors’ knowledge, this is the first study to investigate the value and practicality of the Eclectic Paradigm in categorizing factors in manufacturing reshoring decision-making content and presents in-depth theoretical classifications. In addition, it bridges the gap between decision factors and influencing factors in the decision-making content research realm.
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Sheak Salman, Shah Murtoza Morshed, Md. Rezaul Karim, Rafat Rahman, Sadia Hasanat and Afia Ahsan
The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular…
Abstract
Purpose
The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular economy across diverse industries in recent years. However, a notable gap exists in the research landscape, particularly concerning the implementation of lean practices within the pharmaceutical industry to enhance circular economy performance. Addressing this void, this study endeavors to identify and prioritize the pivotal drivers influencing lean manufacturing within the pharmaceutical sector.
Findings
The outcome of this rigorous examination highlights that “Continuous Monitoring Process for Sustainable Lean Implementation,” “Management Involvement for Sustainable Implementation” and “Training and Education” emerge as the most consequential drivers. These factors are deemed crucial for augmenting circular economy performance, underscoring the significance of management engagement, training initiatives and a continuous monitoring process in fostering a closed-loop practice within the pharmaceutical industry.
Research limitations/implications
The findings contribute valuable insights for decision-makers aiming to adopt lean practices within a circular economy framework. Specifically, by streamlining the process of developing a robust action plan tailored to the unique needs of the pharmaceutical sector, our study provides actionable guidance for enhancing overall sustainability in the manufacturing processes.
Originality/value
This study represents one of the initial efforts to systematically identify and assess the drivers to LM implementation within the pharmaceutical industry, contributing to the emerging body of knowledge in this area.
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Abstract
Purpose
This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.
Design/methodology/approach
The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.
Findings
The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.
Originality/value
This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.
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Bilal Mukhtar, Muhammad Kashif Shad and Fong Woon Lai
The purpose of this study is to examine the influence of green technology innovation on sustainability performance with the moderating effect of innovation capabilities in the…
Abstract
Purpose
The purpose of this study is to examine the influence of green technology innovation on sustainability performance with the moderating effect of innovation capabilities in the Malaysian manufacturing listed companies.
Design/methodology/approach
This was a quantitative study and carried out by applying a research survey. The questionnaire was used to collect the data from 204 Malaysian manufacturing companies of the “consumer products and services” sector listed at Bursa Malaysia, incorporating a five-point Likert scale. All the hypothesized relationships were tested by using the partial least square structural equation modeling (PLS-SEM).
Findings
The empirical results showed that the comprehensive adoption of green technology innovation significantly promotes sustainability performance including economic, environmental and social performance. In addition, innovation capabilities significantly and positively moderate the relationship between green technology innovation and sustainability performance.
Research limitations/implications
The scope of this study is specifically confined to the Malaysian manufacturing listed companies, operating within the consumer products and services sector listed at Bursa Malaysia. Consequently, the findings of this study may not be generalized to manufacturing companies of the different geographical contexts.
Practical implications
The findings of this study may help the top management and policymakers of the Malaysian manufacturing listed companies to scrutinize green technology innovation and innovation capabilities to achieve higher sustainability performance.
Originality/value
This study magnifies and provides new insights into the extant literature by developing a comprehensive research model that concurrently tests the direct and moderation effects between green technology innovation, innovation capabilities and sustainability performance. Additionally, this is the first study to examine the influence of green technology innovation on sustainability performance with the moderating effect of innovation capabilities in the Malaysian manufacturing listed companies. This distinct approach significantly bolsters the originality of this study.
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Chieh-Yu Lin, Cathay Kuo-Tai Kang and Yi-Hui Ho
This study aims to analyze the determinants influencing Chinese manufacturing companies in implementing lean manufacturing (LM).
Abstract
Purpose
This study aims to analyze the determinants influencing Chinese manufacturing companies in implementing lean manufacturing (LM).
Design/methodology/approach
The determinants to be explored in this study consist of technological, organizational and environmental (TOE) dimensions. A questionnaire survey was conducted on Chinese manufacturing companies, and 208 samples were analyzed.
Findings
The findings show that the relative advantage of LM and organizational support have significantly positive effects on Chinese manufacturing firms’ adoption of LM. The complexity of LM, quality of human resources, organizational readiness, customer pressure, international situation, governmental support and environmental uncertainty do not have significant effects.
Originality/value
This paper contributes to the literature by using the TOE model to explore the factors influencing LM adoption in the Chinese manufacturing industry.
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