Digital Transformation In Manufacturing Research Articles

Digital Transformation in Manufacturing: The Synergy of Chatbots and Tailored Gamification Strategies

Chatbots have revolutionized human-computer interactions in various fields, driven by advancements in Artificial Intelligence. Similarly, gamification techniques have emerged as innovative methods to engage users and enhance experiences. This paper presents an analysis of the trends, applications, methods, and challenges associated with chatbots, with a particular emphasis on their capability to generate customized gamification solutions for industrial 5.0 environments. These environments are characterized by the increased use of technologies - such as Virtual and Augmented Reality - driven by the digital transformation of Industry 4.0 (I4.0). As Industry 5.0 (I5.0) builds upon I4.0, emphasizing human-technology collaborations and coexistence of humans and advanced technologies, the role of chatbots and gamification in this context becomes even more compelling. Within this research, various gamification applications and chatbot architectures, ranging from rule-based to generative models, are identified to assess their suitability for the specific needs of industrial 5.0 environments. The primary objective of this study is to explore the potential of leveraging chatbot assistance to enhance gamification experiences by considering employee specific characteristics, workplace technologies, and other relevant factors. By examining the advancements and obstacles in this field, this study aims to explore the potential of chatbots for increasing the effectiveness of gamification strategies. This integration is anticipated to lead to more immersive and personalized experiences, increased employee satisfaction, positive work environment, and enhanced skill development and performance. However, several challenges such as security, user acceptance and the need for continuous adaptation must be addressed to ensure the successful implementation of chatbot-driven gamification in I5.0 environments. The navigation through these challenges holds the key to unlocking the full potential of these transformative technologies and methods, paving the way for a more engaging and enriching work environment.

Exploring the linkages among green digital transformation capability, ambidextrous green learning and sustainability performance: a case study of manufacturing firms in Taiwan

PurposeThis study proposes an innovative concept of green digital transformation capability (GDTC) and explores the interrelationships among GDTC, ambidextrous green learning (AGL) and sustainability performance (SP) from multiple perspectives.Design/methodology/approachSurvey questionnaires were distributed to Taiwanese firms engaged in various sectors, including electrical and information, metal and precision machinery, rubber material, chemical, daily necessity and food and beverage manufacturing, resulting in 306 valid responses. Structural equation modeling in SPSS v26 was used to test the hypotheses. Furthermore, we analyzed the mediating effects using SPSS PROCESS.FindingsThe results demonstrated that GDTC affected SP both directly and indirectly through exploratory and exploitative green learning. Furthermore, this study revealed the pathways through which GDTC influenced the SP of Taiwanese manufacturing firms.Research limitations/implicationsThis study is limited to Taiwanese manufacturing firms. Future studies should expand their sample size to explore digital transformation (DT) practices in various regions and industries.Social implicationsThe DTs in manufacturing have profound social implications, emphasizing that companies should consider economic, social and environmental sustainability during digitalization.Originality/valueThis study introduces a novel concept of GDTC and provides important theoretical insights and practical implications for the intersection of DT and sustainability perspective. These findings will offer valuable guidance to companies seeking sustainable development in the digital era.

Research on the influence of digitalization on competitive advantage of manufacturing enterprises

AbstractIn the current era of rapid digital development, the digital transformation of manufacturing has gradually become an inevitable trend in industry development, and the in‐depth study of the relationship between digitalization and competitive advantage has become an important topic in the field of management science. Based on data from Chinese‐listed manufacturing companies from 2012 to 2021, this paper uses empirical analysis to show that digitalization can effectively enhance the low‐cost competitive advantage and differentiation competitive advantage of manufacturing companies, with organizational slack and environmental uncertainty playing a moderating role in this process. The study also delves into the heterogeneity among firms of different scales, ownership characteristics, and life cycles. This research helps to examine the actual effectiveness of manufacturing companies in the process of digital transformation, while also providing a theoretical basis for how manufacturing companies can better acquire and maintain competitive advantages in the process of digitalization.

Research on collaborative innovation cooperation strategies of manufacturing digital ecosystem from the perspective of multiple stakeholders

The digital ecosystem has hastened the fusion of manufacturing and digital technology in realizing product and service value. However, due to the coordination dilemmas within the digital ecosystem such as risk sharing, competition and cooperation among stakeholders, this study aims to explore the collaborative innovation cooperation strategies of multiple stakeholders, and to investigate the interaction effects of differential incentives on each other's strategies. By constructing a dynamic differential game model, this study solves the optimal innovation efforts, digital servitization levels and innovation benefits under different cooperation intensities, and analyzes the influence of various factors on the total innovation benefits of the digital ecosystem. It is found that under different decision-making modes, the influence of incentive subsidy coefficient and cost-sharing coefficient on the innovation efforts and innovation benefits of multiple stakeholders is different. Under the decentralized decision-making mode, the incentive mechanism positively promotes the innovation efforts of both parties of cooperative enterprises, while the local government is not affected, while under the centralized decision-making mode, the incentive mechanism positively affects the innovation efforts and innovation benefits of all three parties. Specifically, under the Stackelberg game, both the innovation efforts and innovation benefits achieve Pareto improvement, while under the cooperative game, the total system innovation benefits reach Pareto optimality and the optimal strategy is realized. In addition, an optimal range exists for the benefit distribution coefficient and the policy guidance coefficient. Furthermore, factors like the cooperative benefit impact coefficient, innovation capability coefficient, and policy guidance coefficient have a positive effect on the total system innovation benefits. Conversely, factors like the discount rate, technology decay coefficient, and innovation input coefficient inhibit the growth of the total system innovation benefits. The value provides theoretical support for collaborative innovation cooperation in the digital ecosystem, thus facilitating the progress of digital transformation in manufacturing.

The Role and Potential of Intelligent Robots in The Garment Manufacturing Industry in The Industry 5.0 Era

The era of Industry 5.0 marks a new stage in the digital transformation of manufacturing, in which intelligent robotics play a key role. In the garment manufacturing industry, intelligent robots can improve production efficiency, reduce labor costs, optimize product quality, and meet the needs of personalized customization. This article explores the potential and role of intelligent robots in the garment manufacturing industry in the era of Industry 5.0, and analyzes the challenges they face and future development trends.

Key Drivers and Performances of Smart Manufacturing Adoption: A Meta-Analysis

This study focused on the smart factory, one of the critical paradigms in the digital transformation in manufacturing, and attempted a meta-analysis to systematically integrate statistical results from existing empirical analysis studies. An integration model, key factors—smart manufacturing adoption—performances, was established from collecting 42 Korean examples of literature. To compare effect sizes between domestic and foreign empirical study results, 11 foreign articles were added, and the moderating effect verification was conducted. As a result of the analysis, (1) the key factors of the adoption and continuous use of smart manufacturing were the network effect, social influences, finances, performance expectancy, facilitating condition, technological capabilities, and entrepreneurship. (2) The adoption and continuous use of smart manufacturing had a significant impact on business performances, especially the financial performance. (3) The impacts of entrepreneurship and the network effect as factors influencing the decision making of smart manufacturing adoption in Korea can be seen to be significantly higher than those of foreign countries. (4) The impact of smart manufacturing adoption on performances in Korea was higher than other countries. The findings of this study will provide practical implications for practitioners optimizing digital transformation manufacturing policies and supporting the adoption of smart manufacturing systems.

How does digital transformation drive green total factor productivity? Evidence from Chinese listed enterprises

Digital transformation is a critical paradigm for advancing the in-depth integration of the digital economy and the real economy that can drive enterprises' green and low-carbon transformation. Previous research has primarily analyzed the relationship between digital transformation and green total factor productivity (GTFP) at the macro level; however, the impact of digital transformation on enterprises' GTFP as a force of economic growth and pollution management has been neglected. To fill this research gap, we explored the effects of digital transformation and associated micromechanisms on GTFP using a sample of Chinese A-share listed enterprises from 2004 to 2020. Furthermore, we launched a conducted heterogeneity analyses of the research themes from enterprise, industry, and province perspectives. We elicit three notable findings. (1) Digital transformation enhances enterprise GTFP, a finding that holds after endogeneity and robustness tests, including difference-in-differences and instrumental variable methods. (2) At the enterprise level, the benefits of digital transformation are higher for lower-growth and state-owned enterprises. At the industry level, digital transformation in manufacturing, non-high-tech, and non-heavy polluting industries has a stronger GTFP improvement effect. At the provincial level, provinces with higher intensities of environmental regulation and intellectual property protection are more effective in improving GTFP through enterprises' digital transformation. (3) Structural optimization and green technology innovation effects are two critical paths through which digital transformation affects GTFP. This study confirms that enterprises’ implementation of digital transformation strategies can achieve the benefits of performance growth, energy saving, and emissions reduction at the micro level, providing relevant insights driving digital transformation more effectively and stimulating the “digital dividend.”

The role of contractual and relational governance for the success of digital traceability: Evidence from Chinese food producers

Digital traceability (DT), as an important application of technology in the supply chain visibility field under digital transformation in manufacturing, is critical for food producers to guarantee food safety. The success of DT requires closer collaboration among all supply chain members. A big challenge for food producers is that most supply chain members show a disinclination to participate in DT initiatives. The involvement of participants through effective governance approaches oriented around the supply chain—either via formal contracts or informal relational governance—is therefore needed. Unfortunately, the way in which food producers can facilitate the success of DT through such governances is still unclear and lacks sufficient studies. Drawing upon the transaction cost theory and relational exchange theory, this study develops a conceptual model assuming that the contractual governance food producers adopt over their supply chain members can promote the success of DT, and the relationship between contractual governance and DT success is contingent on relational governance. The hierarchical regression method is employed to test hypotheses based on survey responses from 280 Chinese food producers in four provinces with national demonstration projects for the digital technology-enabled traceability system. The statistical results demonstrate that contractual governance has an inverse-U curvilinear effect (from positive to negative) on DT success. Moreover, relational governance moderates the impact of contractual governance on DT success. Specifically, a high level of relational governance mitigates the negative impact of contractual governance, and the joint use of relational governance and contractual governance could facilitate successful DT—but only in cases with higher relational governance. This study contributes to the literature by applying two theories to reveal how food producers can drive DT success through the adoption of governance approaches. It also provides useful managerial implications for food producers to effectively employ both types of governances over their supply chain members to achieve large-scale successful DT. • Involvement of supply chain (SC) members is needed for digital technology (DT). • We study how food producers promote DT success through governance over SC members. • Hierarchical regression analysis is employed to test hypotheses using 280 samples. • Contractual governance has an inverse-U curvilinear effect upon DT success. • Relational governance moderates the impact of contractual governance on DT success.

How Multidimensional Digital Empowerment Affects Technology Innovation Performance: The Moderating Effect of Adaptability to Technology Embedding

Technology innovation in high-end equipment manufacturing (HEM) enterprises technology innovation plays an important role in supporting national economies and social development, accelerating the speed of digital transformation. Digital empowerment aggravates the dynamics, complexity, and uncertainty of technology innovation in HEM enterprises. In order to improve the innovation performance mechanism of China’s HEM enterprises, the adaptability of technology embedding and digital empowerment are introduced to further explain the direct and the moderating effect. Specifically, through a literature review and practical research, the connotation and dimensional division of digital empowerment are defined. According to empowerment tools, digital empowerment is divided into resource empowerment and structural empowerment, and according to the empowerment actor relationships, digital empowerment is divided into platform empowerment and ecological empowerment. Additionally, 436 HEM enterprises are used as research objects to build a conceptual model of the different digital empowerment dimensions, adaptability to technology embedding and technology innovation performance. The research results show that resource empowerment and structural empowerment have U–shaped effects on technology innovation performance, and platform empowerment and ecological empowerment positively affect technology innovation performance. Then, adaptability to technology embedding positively moderates the U-shaped relationship between structural empowerment and technology innovation performance. Adaptability to technology embedding positively moderates the relationship between resource empowerment, platform empowerment, ecological empowerment and technology innovation performance. The research findings deepen the connotation and dimension of digital empowerment, demonstrating the nonlinear relationship between digital empowerment and technology innovation performance of HEM enterprises. Additionally, the research expands on the new applications of adaptability to technology embedding in the digital transformation of manufacturing.

Business models in the context of Industry 4.0 as support in generating value and strategic alignment

The production models created by the industry throughout the twentieth century are now put in check in the face of technological developments and the new digital transformation of manufacturing, known as Industry 4.0 (I4.0). Although many advantages and possibilities are still perceived from this transition, there is little discussion about the business models that will best adapt to this context, making it opportune to review the business models that emerge or are adapted to this new paradigm. This study aims to study the business models related to I4.0, in order to understand how these models support the value creation and how the alignment takes place with the strategy, in addition to identifying gaps for future studies. The methodology used was a systematic literature review, using bibliometrics and network and content analysis. This research had a descriptive purpose, making use of secondary sources through bibliographic survey, with consultation of SCOPUS and Web of Science databases. The sample of 149 publications was analyzed, allowing the discussion of business models in the context of Industry 4.0. Likewise, the analysis of the selected articles made evident the wide scope for future research. It is concluded from the research, that business models in the context of Industry 4.0 point to sustainable industrial value creation and tend to be directed to consumers, with a flexible and customized demand offer, passing by the lot size one, mass customization, when companies will shift their focus from marketing their products to providing solutions to specific customer desires.

A Paradigm Shift in Beauty Education in Response to the Digital Transformation Era -Based on Analysis of Trends in the Cosmetics and Beauty Industry-

In the present age, the social and economic structures are rapidly shifting to a digital base. In the cosmetics and beauty field, “contactless industry” which is grafted into the digital technology has been on the issues. In the field of education, educational standard is increasing through digital transformation using “Edu-Tech”. This study is to explore a new paradigm of beauty education to respond to the digital transformation era. Moreover, it aims to find academic basis to train digital savvy manpower in the field of cosmetics and beauty. The research methods are as follows: trends in domestic and foreign cosmetics and beauty industries were analyzed by referring to academic and degree papers, academic presentation documents, trends and research reports, and websites with the keywords of the 4<sup>th</sup> Industrial Revolution, Digital Transformation, Edu-Tech, beauty education, and cosmetics and beauty industry trends. This study results can be summarized in five points as follows. Firstly, government announced a plan to build a related infrastructure to increase productivity dramatically with the “Digital New Deal”. Secondly, “Edu-Tech” industry can lead the digital transformation to provide customized education. Thirdly, the government selects and promotes four key projects: the development of sustainable K-beauty innovative technology, enhancement of corporate activities through regulatory improvement, support for strategic overseas expansion, and creation of the K-beauty industry ecosystem. Fourthly, major issues in the global cosmetics market include differentiation of clean beauty, realization of substantiality, marketing with the new technologies such as AI, AR, VR, and Metabus, and expansion of the customized cosmetics market. Finally, domestic and foreign companies leading those industries also take the head of digital transformation in manufacturing, distribution, and marketing. Based on the research results above, three conclusions are presented. First of all, it is the development of a curriculum for the digital indigenous generation that has to actively respond to changes in the future society. Nextly, innovation is also required in the development of digital education programs and textbooks. Lastly, it is an effort for instructors to change the perception of digital transformation and to strengthen digital capabilities. Digital transformation should be accompanied by a self-directed educational system centered on learners rather than the existing system centered on instructors. The reason is that it is necessary to respond to the continuous reduction in the number of students, the crisis of higher education due to COVID-19, and the rapidly changing both internal and external environments.

Can Coordinated Development of Manufacturing and Information Communication Service Industries Boost Economic Resilience? An Empirical Study Based on China’s Provinces

Information and communication technology has supported industrial digitalization and brought profound changes to many industries. Under the influence of new technologies and applications, the production mode, enterprise form, business mode and employment mode of manufacturing have accelerated reform, which has effectively promoted the production efficiency and green development of manufacturing. In the face of the complicated and severe economic situation and the wave of industrial digitalization in the world today, it is necessary to study the influence of the coordinated development of manufacturing and information communication service industries (M&ICS industries) on economic resilience. Based on the data of China’s 30 provinces during 2010–2020, this paper estimates the economic resilience and the degree of coordinated development of M&ICS industries. Next, based on the setting of two spatial weight matrices, it uses a spatial econometric model to systematically analyze the influence of the coordinated development of M&ICS industries on economic resilience across China’s provinces. The research results show that the economic resilience across China’s provinces had significant positive spatial correlation. Moreover, the coordination between M&ICS industries had a significant positive effect on economic resilience; however, such an effect was concentrated mostly locally, and the spillover effect on surrounding regions was negative and nonsignificant. This study is of vital strategic significance and practical value to promoting both the resilience of the regional economy and the digital transformation of manufacturing.

Does Digital Transformation in Manufacturing Affect Trade Imbalances? Evidence from US–China Trade

In the new era of the Fourth Industrial Revolution, digitalization has progressively transformed manufacturing and further affected the balance in international trade patterns. This study assesses whether and how the digital transformation in manufacturing contributes to trade imbalances. Using detailed industry-level data from the US, this study constructs an integrated evaluation to measure the level of digital transformation in manufacturing and investigates the ways in which digital transformation in manufacturing affects the US–China trade imbalance. Empirical results show that the US digital transformation in manufacturing is positively associated with the US–China total trade imbalance, which in turn is negatively associated with their related-party trade imbalance. The further analysis presents a moderated mediation model that includes the US-imported intermediate input from China (mediator for the US–China total trade imbalance), foreign direct investment in China by the US multinationals (mediator for the US–China related-party trade imbalance), and Chinese important manufacturing policy (moderator) simultaneously. The results reveal that the Chinese important manufacturing policy moderates the mediation process and the moderated mediation effect is stronger for the industries which are not involved with this policy. Our findings are informative for developing digital transformation strategies for both manufacturing firms and government authorities.

Scope and trends of the digital transformation in the world industry

The impact that the digital transformation in manufacturing has on businesses, suppliers and other third parties has increased significantly now. Digital transformation in manufacturing means improving traditional manufacturing processes with the help of digital technologies. The goal of digital transformation is to increase production efficiency and reduce costs, improve the quality of goods and services produced, and quickly adapt to changes in the global market. The state of industrial production is constantly changing due to the instability of global, economic and political decisions, so the adoption and expansion of digital solutions based on Industry 4.0, the Internet of things, machine learning and other technologies of the future is accelerating. With the help of these technologies, industrial companies are trying to change approaches and find new ways to solve problems. As practice shows, mining and metallurgical companies lag behind other industries in the field of digital transformation, although they have great potential. This lag behind mainly due to the risks associated with the transformation and development of new digital production technologies, while it is possible to adhere to traditional and proven methods of work.

Developing a digital transformation process in the manufacturing sector: Egyptian case study

Digital transformation is of crucial importance in the manufacturing industry, especially after the COVID-19 pandemic because of the increasing need for remote working and socially distanced workplaces. However, there is a lack of a clear and well-defined process to implement digital transformation in manufacturing. This paper aims to identify the most critical stages to implementing digital transformation in the manufacturing sector. Twenty-one structured interviews with experienced specialists in digitalisation in the manufacturing sector in the Egyptian economy were held and used the Best–Worst Method to analyse the data as an analysis tool for a multiple criteria decision making (MCDM) approach. The digital transformation process comprises eight stages covering technology, management, communications, and customer elements. The main contribution of this work stage is the balance between the different elements of digital transformation—digital technologies, leadership and strategy, people and business processes—to create an integrated 8-step process of digital transformation in the manufacturing sector of developing economies such as the Egyptian economy.

Combined Technology Selection Model for Digital Transformation in Manufacturing: A Case Study From the Automotive Supplier Industry

Among generic technology management activities, rapid technology identification and selection stand as the significant determinants of technology adoption success in the digital transformation era. Especially for manufacturing SMEs in developing countries, rapid digital technologies are critical since they struggle to protect their competitiveness in global value chains threatened by digitalization. Previous studies introduce various multi-criteria decision-making model-based approaches to identify and select appropriate manufacturing technologies. However, these approaches were relatively rigid and required an advanced understanding of the technology for criteria and alternative settings and evaluation. Decision-makers need more flexible and scalable contextual frameworks for technology selection in digitalization. Since digital technologies offer both benefits and challenges, the decision-making models should reflect this dialectic nature of Industry 4.0 adoption and contextually optimize their decisions by combining multiple quantitative methods for technology identification and selection. Besides, case studies on digital technology selection are rare in manufacturing SMEs from developing country context in the literature. In this context, this study proposes a technology selection framework that utilizes the three dimensions (industry 4.0 technologies, benefits, and challenges) and combines AHP with a QFD-inspired intervention matrix and an optimization model by Mixed Integer Programming (MIP). The proposed model is validated with a case study from the automotive supplier industry in Turkey with the data provided from interviews and a Delphi survey with 11 experts from the digitalization value chain of the selected industry. Case study results revealed that the highest benefits of industry 4.0 lie in process/quality efficiency improvement and reduced inventory. At the same time, data analytics and sensor technologies occurred as the most critical tools. Significant challenges of digital technology adoption are insufficient expert know-how and budget constraints.

Cloud Technology and the Digital Transformation of Manufacturing

Principles for the introduction of cloud technology in the digital infrastructure of manufacturing enterprises are outlined. Aspects of the technology are discussed.

Aircraft Maintenance 4.0 in an era of disruptions

Digital transformation in manufacturing is having a distinct impact on a variety of business models, including aircraft maintenance. Airline operators are revamping their Maintenance, Repair and Overhaul (MRO) activities with the use of integrated digital platforms and data mining to achieve greater operational efficiencies in parts usage, downtime, and service costs. The term Aircraft Maintenance 4.0 captures the leveraging of information to achieve greater operational agility and to reduce costs. Consolidating data obtained via wireless connectivity from diverse sources enables effective performance monitoring that can inform MRO operations. The severe restriction of flights worldwide due to the pandemic has disrupted the progress of Aircraft Maintenance 4.0 by altering flight routes and rendering most of the historical data obsolete. In this paper, certain aspects of the disruption that deal with airline network changes and their evolution during the pandemic are studied by using publicly available data of a commercial airline.

Towards Industry 4.0: digital transformation of traditional safety shoes manufacturer in Thailand with a development of production tracking system

Abstract There are many digital transformation challenges going forward towards Industry 4.0 in Thailand, especially for the traditional manufacturing firms that have been operating without digital technologies. The paper presents a case study of a safety shoe manufacturer, CPL Group Public Company Limited, adopting digital technologies to transform its production system of 40 years. It presents a conceptual design for production tracking based on IoT technologies for productivity improvement. This research uses inductive case study research design by interviewing executives and participating in the digital tracking development project using IoT sensors and image processing. The findings show the key success factors of digital transformation in manufacturing, strategies required for development, and the conceptual design of the production tracking system.

Smart Additive Manufacturing: The Path to the Digital Value Chain

The aim of this article is to characterize the impacts of Smart Additive Manufacturing (SAM) on industrial production, digital supply chains (DSCs) and corresponding digital value chains (DVCs), logistics and inventory management. The method used consists of a critical review of the literature, enriched by the authors’ field experience. The results show that digital transformation of manufacturing is affecting business models, from resource acquisition to the end user. Smart manufacturing is considered a successful improvement introduced by Industry 4.0. Additive Manufacturing (AM) plays a crucial role in this digital transformation, changing the way manufacturers think about the entire lifecycle of a product. SAM combines AM in a smart factory environment. SAM reduces the complexity of DSCs and contributes to a more flexible approach to logistics and inventory management. It has also spurred the growth and popularization of customized mass production as well as decentralized manufacturing, rapid prototyping, unprecedented flexibility in product design, production and delivery, and resource efficiency and sustainability. SAM technology impacts all five Fletcher’s stages in DVCs. However, the need for clear definitions and regulations on 3D printing of digital files and their reproduction, as well as product health, safety, and integrity issues, cannot be ignored. Furthermore, investment in this technology is still expensive and can be prohibitive for many companies, namely SMEs.