Industrial Revolution Technologies Research Articles

Optimizing the readiness for industry 4.0 in fulfilling the Sustainable Development Goal 1: focus on poverty elimination in Africa

This study explores the transformative potential of fourth industrial revolution (called Industry 4.0) technologies in the context of poverty elimination, with a particular focus on Africa. Given the multidimensional nature of poverty, which spans economic, social, and environmental aspects, there is a critical need for innovative and sustainable solutions. This paper presents a comprehensive literature review to identify how recent advancements, such as artificial intelligence (AI), the Internet of Things (IoT), robotics, blockchain, big data, and 5G can be harnessed to address various facets of poverty. Drawing on insights from existing research and expert opinions, we propose a conceptual framework that integrates these technologies with strategic policy interventions, infrastructure development, and capacity building. The paper proposes a framework that illustrates the prerequisite requirements before adopting Industry 4.0 technologies in poverty elimination efforts. This framework aims to ensure that the benefits of technological innovations are accessible to the most vulnerable populations, thereby contributing to the broader goals of socioeconomic development and poverty reduction. The work shows that while Industry 4.0 presents a critical opportunity for sustainable development and poverty elimination in Africa, it needs to have essential capacities to optimize the use of observations, visualizations, and mindset management before or when adopting the first stage of Industry 4.0 solutions for poverty elimination.

Fourth industrial revolution technologies and sectoral employment in South Africa

Fourth industrial revolution technologies and sectoral employment in South Africa

Does industry 4.0 and environmental quality asymmetrically affect South Africa’s manufacturing sector? A fresh insight from nonlinear autoregressive distributed lag (NARDL) model

Owing to recent developments and implications inspired by fourth industrial revolution (4IR) technologies in the global manufacturing sector through the Industry 4.0 (I4.0) concept, this study was conducted to discover the impacts of I4.0 and environmental quality on the South African manufacturing sector, considering governance quality. To the best of our knowledge, no study has analysed the long-run and short impacts of I4.0, environmental quality and governance quality on the South African manufacturing sector integrating the bound test cointegration, Fully-Modified Ordinary Least Squares (FMOLS) & Dynamic Ordinary Least Squares (DOLS) and nonlinear autoregressive distributed lag (NARDL) estimations techniques. Therefore, this study attempts to bridge this gap using different econometric approaches. The data used spans from 2000Q1 to 2020Q4. The principal component analysis was used to create Industry 4.0 (I4.0) and governance quality components. In this study, utilising the dynamic NARDL, it is seen that the LCO2, representing environmental quality, possesses positive and significant relationship with the LMVA, but when in interaction with the governance quality variables (GOV, INS, POL & ECO), there exists a positive and insignificant relationship with the LMVA showing there exists a dearth of green innovative technologies in the South Africa manufacturing sector respective of its significance. Utilising the FMOLS and DOLS, the GOV, INS, POL & ECO which represents governance quality, mostly possesses negative but significant relationships with the LMVA, even when in interaction with the I4.0 variable proving the I4.0 technologies have not yet started to be impactful to the South African manufacturing industry at large.

Political Economy of STI in China: Analyzing Official Discourse on Science, Technology and Innovation-Driven Development in the Contemporary China

Science, technology, and Innovation (STI) have been the cornerstone of China’s Reform and Opening-up processes. Employing a hybrid methodology, including textual analysis, this paper asserts that four decades of reform and opening-up have witnessed STI’s pivotal role across sectors despite numerous challengesб such as economic slowdown, growing disparities, environmental issues, and a huge burden on the state-owned enterprises. China’s substantial investments in the Fourth Industrial Revolution technologies, including Artificial Intelligence and New Energy Vehicles, exemplify its commitment to innovation, reflected in over 2.5% of GDP allocated for research and development in 2022. This robust investment has bolstered China’s innovative capabilities and brought about its high ranking on the Global Innovation Index. In Chinese STI politics and policy-making, the programs like MLP-2006, SEI-2010 and Made in China 2025 have created a watershed moment. Three central research questions guide our exploration: the trajectory of policy framing on STI-Driven development, the theoretical underpinnings of Innovation-Driven Development and Green Development in Chinese STI politics, and the significance of these paradigms in China’s context. This paper also hypothesizes the emergence of two distinct trajectories within China’s STI politics through the adoption of Innovation-Driven Development and Green Development, positioning STI at the core of China’s development paradigm. The study thoroughly dissects China’s official discourse, framing these paradigms within the Sustainable Development context and highlighting their crucial roles in China’s journey toward technological advancement and sustainability. The analysis of the evolution of China’s STI policy as portrayed in official discourse offers insights into the strategic role played by science, technology, and Innovation in moulding China’s socio-economic trajectory alongside global implications stemming from its transformative development agenda.

Improving Risk and Customer Management Information System - A Case of Vietnam Commercial Bank

Purpose: The purpose of this paper is to delineate strategies for enhancing the risk and customer management information system (MIS) within Asia Commercial Bank (ACB), a prominent Vietnam-based commercial bank. Through a blend of qualitative methods involving synthesis, analysis, and inductive reasoning alongside quantitative approaches such as econometric modeling employing Ordinary Least Squares (OLS) regression, this study aims to offer actionable insights. It underscores the necessity for ACB to adopt a flexible approach in implementing the proposed methodologies. Methods: The study employs a combination of qualitative and quantitative methodologies. Qualitative techniques involve synthesis, analysis, and inductive reasoning to discern patterns and extract insights. Quantitative methods entail the development of an econometric model employing OLS regression to analyze systematic factors influencing stock returns within the observed period. The synthesis of these methodologies enables a comprehensive understanding of the factors affecting the efficacy of the MIS within ACB. Results and Discussion: The intelligent implementation of the data collection, management, exploitation, and utilization processes within the 4th Industrial Revolution technology platform promises enhanced convenience in data analysis and processing for banks, including ACB. Furthermore, the recognition of systematic factors influencing stock returns over the observation period underscores the significance of refining the organization of the MIS system within ACB. The results obtained from both qualitative and quantitative analyses serve as a foundation for informed discussions regarding the optimization of risk and customer management within ACB's operational framework. Implications of the Research: The findings of this research carry significant implications for the strategic direction of ACB's risk and customer management practices. By embracing flexible implementation strategies and leveraging advanced technologies inherent to the 4th Industrial Revolution, ACB stands poised to streamline its data processing capabilities and enhance decision-making processes. Moreover, the recognition of systematic factors influencing stock returns underscores the importance of fine-tuning the organization of ACB's MIS system to accommodate dynamic market conditions. Originality/Value: This study contributes to the existing body of knowledge by offering novel insights into the optimization of risk and customer management information systems within the banking sector, with a specific focus on ACB. By synthesizing qualitative and quantitative methodologies, the research provides a nuanced understanding of the challenges and opportunities inherent to MIS enhancement. The practical implications derived from this study serve as a valuable resource for banking institutions seeking to augment their operational efficiency and strategic effectiveness in an increasingly complex financial landscape.

Awareness and Readiness of Malaysian Generation Z Students towards the Fourth Industrial Revolution (IR4.0)

The Fourth Industrial Revolution (IR4.0) is marked by the integration of digital literacies and technologies, artificial intelligence (AI), and the Internet of Things (IoT), resulting in substantial transformative changes across global industries, economies, and societies. Hence, it is crucial to assess current awareness levels of the Malaysian Generation Z students, who are set to enter the workforce as employees, leaders and entrepreneurs in a time period subjugated by the IR4.0and to evaluate the readiness of these students in navigating possible challenges and opportunities offered by the IR4.0. The instrument for this quantitative study was adapted from the conceptual framework proposed by Sarfaraz J (2017) & Mer, A., & Virdi, A. S. (2021), which was obtained through the research report of Lee Weng Zhan (2022) whereby an investigation was conducted to determine whether the independent variables, namely Performance Expectancy, Effort Expectancy, Social Influence, Perceived Risks, Trust, are related to the dependent variable, which is Behavioural Intention to use IR4.0 Technologies, among Generation Z students. The sample size consisted of 920 Generation Z students born between 1997 and 2012, currently aged between 16 and 26 years old actively studying in public schools in Putrajaya, Public Higher Education Institutions and Private Higher Education Institutions across Malaysia. The decisive findings from the study reveals that the level of awareness and readiness of Generation Z students in Fourth Industrial Revolution (IR4.0) technologies such as automation, artificial intelligence, data analytics, and the Internet of Things in Malaysia is still low and hence is a definite cause for concern. The findings also underscore the pressing need for immediate action to be taken by educational institutions and industries together, to promote awareness about IR4.0 among Generation Z students, increase the acceptance and use of this technology in their everyday lives and integrate adequate educational infrastructure and resources to support IR4.0 teaching and learning in schools and in higher learning educational institutions

When Taekwondo Meets Artificial Intelligence: The Development of Taekwondo

This study explores the comprehensive understanding of taekwondo, the application of fourth industrial revolution technologies in various kinds of sports, the development of taekwondo through artificial intelligence (AI), and essential technology in the fourth industrial revolution while suggesting advanced science directions through a literature review. Literature was sourced from six internet search electronic databases, consisting of three English databases and three Korean databases, from January 2016 to August 2023. The literature indicated cases of sports convergence with the application of fourth industrial revolution technologies, such as the game of go, golf, table tennis, soccer, American football, skiing, archery, and fencing. These sports not only use big data but also virtual reality and augmented reality. Taekwondo is a traditional martial art that originated in Republic of Korea and gradually became a globally recognized sport. Since taekwondo’s competition analysis is an analysis in which researchers manually write events, it takes a very long time to analyze, and the scale of the analysis varies depending on the researcher’s tendencies. This study presented the development of an AI Taekwondo performance improvement analysis and evaluation system and a metaverse-based virtual Taekwondo pumsae/fighting coaching platform through an AI-based motion tracking analysis method.

Exploring intention of undergraduate students to embrace chatbots: from the vantage point of Lesotho

The increasing prevalence of Fourth Industrial Revolution (4IR) technologies has led to a surge in the popularity of AI application tools, particularly chatbots, in various fields, including education. This research explores the factors influencing undergraduate students' inclination to embrace AI application tools, specifically chatbots, for educational purposes. Using an expanded diffusion theory of innovation framework, the study investigates the relationship between relative advantages, compatibility, trialability, perceived trust, perceived usefulness, perceived ease of use, and behavioral intention. Using a 7-point scale, a questionnaire was given to 842 undergraduate students to collect data. The analysis, conducted using SmartPLS 4.0.9.2 software with a covariance-based structural equation model, produced significant findings. The study confirms hypotheses related to the relative advantages, compatibility, trialability, perceived usefulness, and perceived trust associated with chatbots. Notably, students who perceive the benefits of chatbots show a strong intention to use them for academic purposes. The perception of compatibility between students and chatbots positively influences adoption intention, highlighting the importance of compatibility. Additionally, students who have the opportunity to trial chatbots are more likely to use them, emphasizing the significance of trialability. Interestingly, the study did not establish direct relationships between perceived usefulness, perceived ease of use, and behavioral intention. This suggests the presence of other influential factors or dynamics in the adoption of chatbots for educational purposes. These findings offer practical insights for students and contribute to the theoretical understanding of the diffusion theory of innovation. Future research can further explore these insights to unravel the complexities of chatbot adoption and facilitate the broader adoption of AI tools in educational settings.

Industry 4.0 in Finance, Digital Financial Services and Digital Financial Inclusion in Developing Countries: Opportunities, Challenges, and Possible Policy Responses

Fintech and the adoption of Fourth Industrial Revolution (industry 4.0) technologies have expanded the provision and uptake of digital financial services (DFSs) globally. Digital transformation in the financial industry intended to modify financial service provisioning by reducing the costs of accessing and challenges such as inaccessibility due to remoteness, not having a bank account, not having a credit history, or having erratic incomes. Digital financial inclusion (DFI) aims to ensure that financial services, such as deposits, payments, transfers, withdrawals, investments, accessing insurance and credit, checking account balances, receiving money, and making international remittances, are conducted conveniently, easily, safely, reliably, and affordably. DFI focuses on ensuring access to financial services through digital channels and platforms for individuals, businesses, and households, to promote financial inclusion for all stakeholders, especially previously financially excluded groups. Through a critical review of the literature, this study explores the opportunities and challenges of DFI or the adoption and use of DFS. The review unpacks the possible benefits of using DFSs, which include the broadening financial inclusion, increasing diversity and innovation in the financial services sector, attainment of the SDGs, reduction of poverty, increased economic growth, and minimization of the gender financial inclusion gap, as well as reduction in inequalities. The constraints include the inadequacy of digital infrastructure, taxes on DFS, literacy challenges, digital exclusion, poverty and the gender divide, risks, and lack of trust in the financial services sector. The study recommends appropriate regulation and oversight, literacy enhancement initiatives, investment in digital infrastructure, and increased consumer protection as measures to improve DFI in developing countries.

Penerapan Information Adoption Model Untuk Mengukur Pengaruh Electronic Word Of Mouth Terhadap Niat Beli Scarlett Whitening di Media Sosial Tiktok

Technological developments have increased from year to year, starting from the first industrial revolution technology 1.0 until now the ongoing revolution is named industry 4.0 by the World Economic Forum in 2016 which is called the digital era. The industrial revolution 4.0 involves all activities centered on the internet or often called the Internet of Things. TikTok has experienced a rapid increase where in 2022 it will be 61.3% of the total population and in 2021 it will be 38.7%. Based on these data, TikTok is the social media that has experienced the most rapid increase as the most active social media application in Indonesia. Scarlett Whitening is one of the most viewed brands on the Tiktok app. This study aims to better understand the effect of eWOM based on the TikTok application on Scarlett Whitening's purchase intention. To understand the impact of eWOM, I apply the information adoption model as a model that has been widely used in previous eWOM studies. Research using quantitative methods with the aim of this research is causal. Data collection used the non-probability sampling method with the convenience sampling type of 385 respondents using Scarlett. This study used a questionnaire data collection technique with a Likert scale and data analysis techniques using Partial Least Square Structural Equation Modeling (PLS-SEM) with the help of SmartPLS software.

UTILIZATION OF 4IR TECHNOLOGIES TO ENHANCE STRATEGIC INTELLIGENCE AND DYNAMIC CAPABILITIES FOR A SUSTAINABLE COMPETITIVE ADVANTAGE

This paper delves into the transformative role of the Fourth Industrial Revolution (4IR) technologies—Artificial Intelligence (AI), the Internet of Things (IoT), Robotics, and Blockchain—in reshaping strategic intelligence and dynamic capabilities in businesses. It presents an in-depth analysis of how these technologies enhance strategic decision-making, predictive analytics, and operational agility, thereby contributing to a sustainable competitive advantage in rapidly evolving markets. The paper also explores the synergistic effects of integrating these technologies and the resulting challenges and opportunities, including cybersecurity risks, workforce displacement, and ethical considerations. Furthermore, it proposes a comprehensive framework that integrates technology adoption with organizational strategy, emphasizing continuous learning, sustainability, and ethical practices. This study concludes by discussing the implications for practitioners and policymakers and suggesting directions for future research, particularly in understanding long-term impacts, cross-industry applications, and societal implications of 4IR technologies. This paper aims to provide valuable insights for businesses and policymakers navigating the complexities of the 4IR era.

The Ethical Challenges of Educational Artificial Intelligence and Coping Measures: A Discussion in the Context of the 2024 World Digital Education Conference

Artificial intelligence (AI), as the core technology of the fourth industrial revolution, has been widely deployed in many areas, bringing tremendous changes to human society. At the same time, AI has also instigated a variety of ethical issues regarding basic human rights, social order, private safety, and more. In order to maintain a balance between technological development and the ethics of AI, governments of various countries and international organizations are working to develop AI regulations and ethical norms. A forum themed “Artificial Intelligence and Digital Ethics” was held as a side event during the 2024 World Digital Education Conference (WDEC), showcasing the Chinese government’s adherence to the ethical notion of “human-centered AI” and the principle of “digital for good” in using AI in digital education. The forum emphasized the importance of establishing the ethics of educational AI for circumventing relevant ethical risks and creating healthy environments for the digital transformation of education. Based on the forum’s theme, this article seeks to set forth the necessity of formulating a code of ethical norms for educational AI and to explore pathways to building an ethical framework in this regard in order to provide insights into the rational application of AI in education and promote the sustainable development of digital education.

재난 위험 및 자원 운영·관리 시스템

In this study, we present a disaster situation and response resource management system. This system aims to proactively prepare for and respond to both single and complex disaster scenarios within a city. Additionally, we propose strategies for the effective operation of such resource management systems during emergencies. Notably, we leverage blockchain technology to enhance the transparency of disaster management resource operations and the overall system. While our research successfully designed and developed a disaster resource management system using 4th industrial revolution technologies, practical considerations remain. This process is critical not only for the secure operation of disaster management resources but also for the overall usability of the prototype system, especially when integrating it with government departments and management agencies. The feasibility of blockchain implementation in this context needs further review and evaluation. Future studies will focus on refining the prototype system to enhance its performance and ultimately create a practical solution for real-world disaster response.

Effects of Clay Minerals on Enzyme Activity as a Potential Biosensor of Soil Pollution in Alice Township

Inadequate waste management and illegal trash dumping continue to be the leading causes of severe environmental pollution. Human exposure to harmful heavy metals has emerged as a serious health concern on the continent. Some people in Alice, a small town, grow their food in home gardens. They use animal manure and compost derived from soil obtained from landfills to enhance the fertility of the garden soil. Heavy metal heaps in garbage disposals are constantly present, releasing dangerous amounts of metal into the environment. The harmful effects of heavy metals on plants lead to unsanitary conditions and environmental problems. Animals and people who consume these vegetables may also be at risk for health problems. Assessing the soil’s enzyme activity can potentially lessen the negative effects of the accumulated pollutants and improve the soil’s overall health and quality. Soil enzymes are biologically active components that have a catalytic impact and are released from root exudates, crop residues, and animal remains. The activity of enzymes serves as an excellent bioindicator of soil cleanliness and quality because they are sensitive to heavy metals. X-ray diffraction (XRD) was used to quantify the mineral elements in soil using 40 kV parallel beam optics, 30 mA, and CuKα radiation. Meanwhile, the activity of the enzyme was essayed in different coupled substrates. Thirteen (13) clay minerals were found, including Talc 2M, Kaolinite 2M, and Chlorite Lawsonite Muscovite 2M1. The detected trace elements have high concentration levels that exceed the World Health Organization’s (WHO) allowed levels. The identified elements affected the enzyme activity at different levels. The Mn, Al, Si, V, Ti, and Ca negatively affect soil enzyme activity, specifically invertase (INV). However, the amount of Mg, K, Fe, and Zn showed a slightly positive effect on the same enzyme (INV). According to this view, these elements come from several sources, each with a particular impact on soil contamination and enzyme activity. High levels of heavy metals in this study may be due to improper waste disposal, limited recycling opportunities, lack of public awareness, and inadequate enforcement of waste management regulations. It is essential to employ Fourth Industrial Revolution (4IR) technologies, correct disposal techniques, suitable agricultural methods, preventive regulations, and efficient waste management to mitigate the negative effects of heavy metals on the environment.

Development of Architectural Object Automatic Classification Technology for Point Cloud-Based Remodeling of Aging Buildings

In this study, we address the challenge of efficiently handling the maintenance and remodeling of buildings constructed post-1960s, lacking architectural drawings. The conventional approach involves manual measurements and data recording, followed by digital drawing creation. However, we leverage Fourth Industrial Revolution technologies to develop a deep learning-based automatic object classification system using point cloud data. We employ the FCAF3D network with multiscale cells, optimizing its configuration for classifying building components such as walls, floors, roofs, and other objects. While classifying walls, floors, and roofs using bounding boxes led to some boundary-related errors, the model performed well for objects with distinct shapes. Our approach emphasizes efficiency in the remodeling process rather than precise numerical calculations, reducing labor and improving architectural planning quality. While our dataset labeling strategy involved bounding boxes with limitations in numerical precision, future research could explore polygon-based labeling, minimizing loss of space and potentially yielding more meaningful results in classification. In summary, our technology aligns with the initial research objectives, and further investigations could enhance the methodology for even more accurate building object classification.

Comparative analysis of national innovation systems: Implications for SMEs' adoption of fourth industrial revolution technologies in developing and developed countries

PURPOSE: This study aims to identify the differences and similarities in the innovation systems of developing vs. developed countries that influence SMEs’ adoption of Fourth Industrial Revolution (4IR) technologies. There is a notable absence of comparative research between National Innovation Systems (NIS) of developing and developed countries. Additionally, the current scholarly conversation lacks a holistic view of NIS. Our study aims to fill these gaps by employing Lundvall’s framework to explore both developed and developing countries’ systems comprehensively. METHODOLOGY: The data was collected through a Systematic Literature Review, identifying a total of 695 publications from SCOPUS, Web of Science (WoS), and ProQuest. The PRISMA process was adhered to, resulting in 32 papers undergoing quality evaluation using Gough’s ‘weight of evidence’ guidelines. Twenty-nine primary papers were selected, comprising twelve from developed countries, another twelve from developing countries, and the remainder from both categories. Using Qualitative Meta-synthesis (QMS) with ATLAS.ti, a systematic alignment of codes with research inquiries pertaining to NIS ensued, revealing a multifaceted spectrum of findings across these scholarly investigations. FINDINGS: We found that there are similarities and differences between the innovation systems of developed and developing nations. The similarities include the intra-firm interactions taking place between managers and workers, inter-firm relations between the SMEs and Academia and other SMEs, as well as the role of the government in providing funding and regulation (albeit at significantly varying degrees). The most significant differences observed were in the funding mechanisms, the role of the government, and the R&D systems. It was found that governments in developed countries provided SMEs with substantial incentives, tax credits, and subsidies to adopt 4IR technologies, which appears to positively impact the adoption rate. We conclude by developing a conceptual framework for the NIS necessary for the adoption of SMEs’ 4IR technologies in developing countries. IMPLICATIONS: This study contributes to the literature on innovation systems by examining the NIS of both developed and developing countries. This analysis allows us to gain deeper insights into how specific aspects of each country (developed or developing) affect (positively or negatively) SMEs’ adoption of 4IR technologies. Practically, it informs governments in developing countries on which aspects to focus on in their NIS to increase the rate of the adoption of 4IR technologies by SMEs. ORIGINALITY AND VALUE: A distinctive aspect of this study lies in the creation of a comprehensive conceptual model delineating the essential components of the innovation system pivotal for the successful integration of 4IR technologies within SMEs. This model is designed to serve as a practical tool for governments in developing countries, providing a structured framework to facilitate and enhance the strategic development of their innovation landscapes.

Revolutionising the Sustainability of Steel Manufacturing Using Computer Vision

The pressure of the global sustainability problem is growing faster than ever after the social and economic havoc wreaked by the pandemic, as well as the present time nearing to the 2050 net zero carbon goal. In 2021 the steel industry had a turnover of around €125 billion and was directly responsible for providing at least 300000 jobs. In 2022, it was responsible for roughly 5% of CO2 emissions in the EU and 7% globally, and was responsible for at least 20278 injuries and 90 deaths. Environmental solutions for mitigating negative consequences of the steel industry exist such as hydrogen-based steelmaking, carbon capture, utilisation and storage and electrolysis, whilst safety regulations and personal protective equipment have been used to improve safety. However, little has been done to combat the problem using the most powerful emerging technology of the fourth industrial revolution, artificial intelligence. In particular, computer vision has already shown great competence in a range of applications related to steelmaking, but without seriously considering sustainability, resulting in limited awareness of the potential benefits computer vision can bring to industry. A lack of this awareness leads to missed opportunities for sustainable development. This paper aims to address the gap in research that discusses computer vision capabilities for enhancing the sustainability of steel production by providing a literature review covering recent advances in computer vision, as well as an industry 4.0 approach for integrating computer vision systems with steelworks. Research presented here successfully exposes the untapped potential of computer vision in the steel industry and paves the way for future developments by exhibiting a blueprint for simultaneously elevating sustainability and technological advancement.

ЕВРАЗИЙСКИЙ ИНТЕГРАЦИОННЫЙ ПРОЕКТ В УСЛОВИЯХ ЦИФРОВОЙ ТРАНСФОРМАЦИИ ЭКОНОМИКИ РОССИИ

Digitalization and innovative development occupy an important place on the agenda of the countries of the Eurasian Economic Union (EAEU). Comprehensive sanctions against Russia and changes in trade flows caused by the unstable geopolitical situation have created an obvious need for innovation and digital technologies in finance, transport, customs control, including digital integration. The purpose of the study is to determine the innovative potential of the EAEU in the context of digital infrastructure development and the fourth industrial revolution technologies. The study compares the innovation potential of the EAEU with other regional integration association. It is concluded that if there is a well developed digital infrastructure, the further growth of the innovative potential of the EAEU will be complicated by sanctions preventing access to foreign technologies, and will largely depend on the effectiveness of the import policy in Russia.

4IR 시대의 식품 콜드체인 3PL 서비스품질과 공급체인 성과에 관한 실증연구

Recently, the cold chain market in the food industry has been rapidly advancing with the application of Fourth Industrial Revolution technologies such as Big Data, IoT, RFID, enhancing both information technology and logistics systems. Consequently, in the support of food cold chain systems, physical quality and logistics information quality have improved during the distribution and logistics processes. Therefore, there is a need for distribution and logistics companies to derive and examine service quality factors that impact relationship maintenance and performance in the supply chain management process with small and medium-sized enterprises (SMEs) in the food industry during the Fourth Industrial Revolution era. This study aims to identify the cold chain service quality factors of third-party logistics (3PL) companies based on expert in-depth interviews and a three-dimensional service quality model. Additionally, it seeks to understand the influence of relationship orientation in Korean food SMEs on supply chain performance. To achieve this, a systematic survey was conducted through preliminary investigations, distributing structured questionnaires, and collecting a total of 240 responses, excluding 9 unreliable responses, for empirical analysis. The collected survey data were analyzed using SPSS version 28.0 for frequency analysis to understand the general characteristics of respondents. Furthermore, Smart PLS version 4.0 was employed to test the internal consistency reliability, concentration, and discriminant validity of the measurement model. After evaluating the structural model, hypotheses were verified. The results of the analysis indicate that all three-dimensional service quality factors of cold chain services provided by 3PL companies (data processing expertise, digital-based customer responsiveness, and smart logistics information accuracy) positively influence relationship orientation. Additionally, the relationship orientation of food SMEs toward 3PL companies was confirmed to have a positive impact on supply chain performance. Therefore, the significance of this study lies in providing service quality factors for distribution and logistics companies to maintain relationships with food SMEs in South Korea and confirming the causal relationships affecting supply chain performance.

RESEARCH TRENDS IN DIGITAL TRANSFORMATION IN SUPPLY CHAIN BASED ON BIBLIOMETRIC AND NETWORK ANALYSIS

With the development of the 4th Industrial Revolution technology, the digitalization of supply chain is also receiving a lot of attention. With various technological developments, the importance of digital transformation in a firm’s supply chain is increasing. Therefore, for a more comprehensive understanding of digital transformation in supply chain, we have implemented a rigorous systematic literature review by supplementing the shortcomings of existing literature and combining bibliometric analysis and network analysis with keyword network analysis. Using the SCOPUS database, we collected 182 papers addressing digital transformation in the supply chain published in renowned business administration journals, identified research trends. Then, we analyzed the connection of citations as well as the author’s keywords and their changes over time. Based on these results, this study presents the number of publications and changes in papers by period, influential authors and papers, key keywords and topics, etc. on digital transformation in supply chain.