Manufacturing Enterprises Research Articles

Digital technology adoption and the latecomer firms’ catch-up: an empirical study on Chinese manufacturing enterprises

ABSTRACT Digital technology has a significant influence on future economic growth. Achieving catch-up in the context of digital development is crucial for firms. However, the mechanisms between firms’ digital technology adoption (DTA) and catch-up are underexplored. Based on panel data of A-share listed manufacturing firms in China from 2012 to 2021, this study investigates the impact of DTA on firms’ technological catch-up (TC) and market catch-up (MC) from theoretical and empirical perspectives. The following findings are drawn. (1) DTA positively and significantly affects firms’ TC and MC, and the results remain valid after using the instrumental variables method, propensity score matching, and other robustness tests. After removing the order-of-magnitude discrepancies and dimensions, DTA had a more significant effect on MC than TC. (2) Dynamic capacity mediates the relationship between DTA and firms’ catch-up. (3) The heterogeneity analysis finds that DTA influences TC and MC in state-owned enterprises and high-tech firms more significantly. This study provides a new perspective on firms’ catch-up and guides for firms to develop effective DTA and catch-up strategies.

Strategic Risk Agility on the Performance of Edible Oil Manufacturing Company at Pwani Oil Products Limited, Kenya

An organization’s capacity to foresee and address strategic risks pro-actively and flexibly is strategic risk agility. It entails seeing possible dangers and opportunities, evaluating how they could affect the organization, and swiftly adjusting and reacting to shifting conditions. Disruptive technologies, economic downturns, supply chain disruptions, and regulatory changes are a few examples of strategic risks that demand agility and flexibility to manage. This study primarily focused on the impact of strategic risk agility on the performance of edible oil manufacturing enterprises in Kenya. The study sought to establish the effect of strategic risk adaptability on the performance of edible oil manufacturing companies in Kenya, at Pwani Oil Products Limited. The research was guided by the Theory of Dynamic Capability. A descriptive research design was adopted for this study. The primary instrument for data collection in this study was a Questionnaire. The target population was 380 employees from the edible oil manufacturing company, Pwani Oil Products Limited for the period between August to November 2023. The sample consisted of 30% of the target population (70 men, 45 women and work experience of 0-11 years). The reliability of the questionnaire was assessed by measuring its internal consistency using Cronbach's Alpha. Conclusion are that the ability to swiftly adjust production processes, adapt to changing market demands, and respond to unexpected disruptions can translate into improved financial performance. The study's outcomes underscore the importance of strategic risk innovation and collaboration in enhancing financial performance. It is evident that these factors are pivotal for success. The recommendations are that Pwani Oil Products Limited should invest in improving its strategic risk adaptability. This can be achieved through regular risk assessments, scenario planning, and flexible business strategies. The company should develop a culture that encourages employees to quickly adapt to changing market conditions and mitigate risks effectively.

Unlocking new opportunities in the industry 4.0 era, exploring the critical impact of digital technology on sustainable performance and the mediating role of GSCM practices

In the context of industry 4.0, digital technology has become one of the core drivers of production and operations for enterprises, promoting the transformation of businesses towards more sustainable development models. Concurrently, green supply chain management (GSCM) practices contribute to the development of sound business strategies for driving sustainable development. This study examines the impact of digital technology on sustainable performance in the context of industry 4.0, from the perspective of practice-based view (PBV) theory and information processing theory (IPT). It also focuses on the mediating role of GSCM practices in the influence of digital technology on sustainable performance. Data was collected from 486 manufacturing enterprises in China for empirical analysis using the PLS-SEM method. The results indicate that: (1) Under the industry 4.0 context, digital technology (IDT) has a significant positive impact on environmental performance (EP), economic performance (ECP), and social performance (SP). (2) IDT has a significant positive effect on green manufacturing (GM), green purchasing (GP), green design (GD), green information systems (GIS), reverse logistics (RL) and investment recovery (IR). (3) GM, GP, GD, GIS, RL, IR have significant positive effects on EP, ECP and SP. (4) Among the six different dimensions of GSCM practices, IDT has a partially mediating effect through CM on EP, a partially mediating effect through GM on ECP and SP, a partially mediating effect through GP on EP and SP, a partially mediating effect through GD on EP, ECP, and SP, a partially mediating effect through GIS on ECP and SP, a partially mediating effect through RL on EP, ECP, and SP. Finally, IDT has a partially mediating effect through IR on EP and SP. It is noteworthy that GP does not have a mediating effect between IDT and ECP, GIS does not have a mediating effect on EP, and IR does not have a mediating effect between IDT and ECP. By conducting in-depth research on the impact of digital technology on the economic, environmental, and social performance of enterprises in the industry 4.0 environment, this study aims to promote the enhancement of sustainable performance for businesses. It also aims to provide specific strategies and practical guidance for enterprises to promote sustainable development in the industry 4.0 era.

How to Leverage Digital Sustainability Orientation to Promote Environmentally Sustainable Practices of Manufacturing Enterprises in China

The promotion of high-quality, environmentally sustainable practices in enterprises in the digital age has become an important topic in business and academic circles. In this study, by employing a perspective combining digital orientation (DO) and sustainability commitment orientation (SCO), the concept of digital sustainability orientation (DSO) is presented, and digital green capability (DGC) is introduced as the mediating variable. Moreover, the driving mechanism model of corporate environmental sustainability practice (ESP) is constructed, and the moderating role of environmental scanning (ES) is taken into consideration. Using two sets of research data from 353 manufacturing enterprises in China, the empirical test results show that DSO has a significant role in improving ESP, and DGC is important in mediating between DSO and ESP. ES acts as a moderating variable between DSO and DGC and further moderates the mediating role of DGC between DSO and EPS; that is, the stronger the ES, the more significant the mediating effect of DGC. The conclusion of this study broadens the application scope of strategic orientation theory in the study of digital sustainability and has theoretical and practical implications for exploring the development of DGC and the dynamic mechanism of ESP.

Evaluating supply chain management practice among micro and small manufacturing enterprise in southwest, Ethiopia

The aim of this study was to assess the supply chain management practices of micro and small scale manufacturing enterprise operated in Bench-Sheko zone, southwest, Ethiopia. This examination utilized the realistic investigation plan to overview the appraisal of store network the board rehearses on the miniature and limited scope fabricating endeavors worked in Bench-Sheko zone. The assessment has accepted qualitative investigation approach. The study uncovered that just 38%, 26%, 32%, 49%, 15%, 43%, 36%, 38%, 32%, 27% and 34% of assembling endeavors in the zone consolidate natural prerequisites in choosing suppliers, reuse side-effect, squander reusing strategy, utilized crude materials that needs less energy, give impetuses to the possible providers, share data oftentimes to the providers, advance vital provider relationship, advance store network joining, quality coordination’s, electronic coordination’s the executives and coordination’s timetable alone. The after effect of this study has some significant ramifications to the miniature and limited scope producing undertakings. In such manner to remain serious and make due over the long haul the assembling ventures should zero in additional on accepting green supply chain network, supplier relationship and logistics management.

Digital Transformation and Non-Financial Performance in Manufacturing

In the context of the digital economy era, can digital transformation promote the improvement of non-financial performance of manufacturing enterprises? Taking Shanghai and Shenzhen A-share listed manufacturing firms from 2012 to 2021 as instances, this paper decomposes non-financial performance from five dimensions: innovation performance, ESG performance, working capital management performance, organizational resilience, and corporate market competitiveness, and examines the effects and mechanisms of the digital revolution on manufacturing companies’ non-financial performance via empirical analysis. The findings are as follows: (1) digital transformation of manufacturing enterprises plays a significant positive role in innovation performance, ESG performance, working capital management performance, organizational resilience, and corporate market competitiveness, and (2) digital transformation can promote the improvement of non-financial performance of manufacturing enterprises by improving the quality of internal control. In addition, the heterogeneity analysis results show that digital transformation contributes more to the non-financial performance of non-state-owned manufacturing enterprises. The study conclusion can provide experience for promoting the sustainable development of manufacturing enterprises and driving high-quality economic development.

Research on the Production Capacity Evaluation of Prefabricated Component Manufacturing Enterprises

Due to the industrialization of the construction sector, enterprises that manufacture prefabricated components are developing rapidly. Because the production capacity of each enterprise varies immensely, the upstream enterprises are unable to match the component manufacturing enterprises that are suitable for the supply target. With respect to the product capacity, scientific and accurate evaluations are crucial. The authors preliminarily determined factors that impact the production capacity of components and considered a literature review and the inspection results of component manufacturing enterprises. By performing a thorough investigation and analysis, they constructed the index system for evaluating the production capacity of enterprises that manufacture prefabricated components, and each index was interpreted. To determine the weight of the evaluation index, an analytic hierarchy process was utilized; furthermore, the characteristics of each grade were described, and a fuzzy comprehensive evaluation model was built. Moreover, to empirically analyze the built model, the authors selected a construction company and analyzed 127 questionnaires filled in by employees at all the organizational levels related to PCT production and to 34 evaluation results of experts from standard quota research institutions in various provinces. The results of the two methods revealed the following: This enterprise level is the “Reinforcement level” (level 3). The evaluation results are consistent with the empirical results of the model established herein, which verifies its feasibility.

Change is safer: a dynamic safety stock model for inventory management of large manufacturing enterprise based on intermittent time series forecasting

Change is safer: a dynamic safety stock model for inventory management of large manufacturing enterprise based on intermittent time series forecasting

Digital Transformation, Absorptive Capacity and Enterprise ESG Performance: A Case Study of Strategic Emerging Industries

Digital transformation provides new drivers for economic performance growth in enterprises, but can it further improve ESG performance and support sustainable development? Based on the perspective of resources and capabilities, this article uses the relevant data of 1588 listed companies in strategic emerging industries from 2011 to 2021 to study the impact of digital transformation on enterprise ESG performance examines the intermediary role of absorptive capacity and the moderating role of regional digitalization level, and further analyzes the heterogeneity of property rights and industrial nature. The research results indicate that: firstly, digital transformation of enterprises can positively promote the improvement of ESG performance; secondly, absorptive capacity serves as a conduit through which digital transformation influences a company’s ESG performance; thirdly, the regional digitalization level positively moderates the promotion effect of digital transformation on enterprise ESG performance; fourthly, the impact of digital transformation on ESG performance of enterprises is significantly differentiated in the nature of enterprise property rights and industrial nature, and the ESG performance of state-owned enterprises and high-end equipment manufacturing enterprises is more sensitive to digital transformation. The research conclusion is based on a digital perspective, providing relevant insights for improving the ESG performance of strategic emerging industry enterprises and expanding their ESG development paths.

Automated machine learning methodology for optimizing production processes in small and medium-sized enterprises

Machine learning can be effectively used to generate models capable of representing the dynamic of production processes of small and medium-sized enterprises. These models enable the estimation of key performance indicators, and are often used for optimizing production processes. However, in most industrial applications, modeling and optimization of production processes are currently carried out as separate tasks, manually in a very costly and inefficient way. Automated machine learning tools and frameworks facilitate the path for deriving models, reducing modeling time and cost. However, optimization by exploiting production models is still in infancy. This work presents a methodology for integrating a fully automated procedure that embraces automated machine learning pipelines and a multi-objective optimization algorithm for improving the production processes, with special focus on small and medium-sized enterprises. This procedure is supported on embedding the generated models as objective functions of a reference point based non-dominated sorting genetic algorithm, resulting in preference-based Pareto-optimal parametrizations of the corresponding production processes. The methodology was implemented and validated using data from a manufacturing production process of a small manufacturing enterprise, generating highly accurate machine learning-based models for the analyzed indicators. Additionally, by applying the optimization step of the proposed methodology it was possible to increase the productivity of the manufacturing process by 3.19 % and reduce its defect rate by 2.15 %, outperforming the results obtained with traditional trial and error method focused on productivity alone.

Time Series Trends Forecasting for Manufacturing Enterprises in the Digital Age

In the digital age, manufacturing enterprises face challenges like information overload and data fragmentation. To address these issues, this paper proposes a novel method that integrates the Improved Whale Optimization Algorithm (IWOA), Bidirectional Long Short-Term Memory (BILSTM), and Temporal Pattern Attention (TPA) for analyzing time series data. IWOA optimizes hyperparameters, BILSTM captures temporal dependencies, and TPA enhances interpretability. Experimental results show the method's effectiveness in market trend prediction, production planning, and supply chain management. It enables accurate forecasts in a competitive environment, enhancing flexibility and foresight. This research overcomes existing limitations, offering a valuable analytical tool for understanding the digital economy's impact on manufacturing enterprises. It provides guidance for the industry's development in the digital era.

Stakeholder-Driven Sustainable Technology Application in Fashion Manufacturing Enterprises and Performance Impact

Stakeholder-Driven Sustainable Technology Application in Fashion Manufacturing Enterprises and Performance Impact

Employees’ perceptions of corporate social responsibility in a selected manufacturing enterprise in South Africa

Despite small and medium enterprises (SMEs) being the backbone of any economy, their performance is not satisfactory. Corporate Social Responsibility (CSR) is frequently utilised to improve business sustainability and meet stakeholder responsibilities. However, literature focuses on CSR practices in larger corporations, neglecting the practice in SMEs. On the other hand, CSR research usually overlooks internal stakeholders such as employees. In order to bridge this gap, the researcher investigated internal stakeholders’ perceptions of CSR in a South African medium-sized organization located in the eThekwini municipal area, as this perspective is critical in developing a comprehensive CSR strategy. Data for this research was gathered through interviews and focus group discussions with managers and employees of the selected organization. Thematic content analysis was the primary method utilised for analysing the collected data, which was aided by NVivo 12 software for complete data processing and organization. The findings revealed that employees view CSR as a viable practice that encourages dedication and motivation to improve work performance. CSR implementation within the organization is seen as an effective motivational tool, resulting in greater output, increased staff dedication, decreased absenteeism, and increased employee turnover. The researcher argues that CSR can increase employee performance and emphasizes the necessity for SME managers to incorporate social, environmental and employee-related CSR projects into their business strategy to improve overall performance.

Catalysing responsible production: Evaluating the impact of EPR system on manufacturing enterprises

Catalysing responsible production: Evaluating the impact of EPR system on manufacturing enterprises

PARADONT DISEASES AND MORPHOLOGICAL CHANGES IN TEETH IN HUMANS WORKING WITH CHEMICAL DYES

The article covers the use of various organic and inorganic dye solutions in paint -finishing workshops in the manufacturing industry as well as in all sectors of the textile industry. These chemical dyes and solutions are a factor that calls autoallergenic reactions by denaturing proteins on the mucous membrane of the skin, respiratory tract. Clinical-experimental tests conducted among workers of a manufacturing enterprise, in which organic and inorganic compounds were applied by several scientists, comprehensively substantiated the negative effects of chemical substances, reagents, catalysts and others on the tissues of the oral cavity and in the whole organism.

Smart platforming in automotive manufacturing for NetZero: Intelligentization, green technology, and innovation dynamics

Green technology innovation is integral to fostering sustainable economic development and environmental conservation. The application of smart product platform has emerged as a transformative force in shaping the trajectory of green technology innovation. Drawing on the foundation of knowledge theory and utilizing a sample of 1240 valid cases from listed Chinese automotive manufacturing enterprises between 2013 and 2022, this paper employs a mixed regression method to explore the relationship between smart product platform usage and green technology innovation. Additionally, it analyzes the mediating role of corporate innovation input in this relationship and the moderating effect of intelligentization level on the association between smart product platform usage and green technology innovation. The research reveals the following key findings: (1) Corporate smart product platform usage and innovation input significantly and positively drive green technology innovation. (2) Innovation input acts as a complete mediator in the relationship between smart product platform usage and green technology innovation. (3) Corporate intelligentization level positively moderates the relationship between smart product platform usage and innovation input. (4) Considering regional and ownership attribute disparities, the impact of smart product platform usage on green technology innovation is asymmetric. This study, as one of the few empirical examinations of the effects of smart product platform, enriches research in the areas of smart product platform and green technology innovation. The study, contributing to the empirical understanding of smart product platforms, offers valuable insights for automotive manufacturing enterprises to strategically leverage these platforms for advanced and flexible operations, aligning with the imperative of achieving global environmental goals such as NetZero. As indicated in COP28, the findings underscore the urgency of integrating smart technologies into the automotive industry to advance these crucial environmental objectives.

Research on the mechanism and effect of digitalization on technology innovation: evidence from Chinese manufacturing listed enterprises

ABSTRACT Digitalization provides a new impetus for technological innovation in manufacturing enterprises. However, research on the influence of digitalization on technological innovation is still in an exploratory phase, lacking a systematic theoretical framework and unified conclusions. It is crucial to clarify the mechanisms by which enterprise digitalization impacts technological innovation and to confirm the role of digitalization in promoting technological innovation in the digital era. The listed A-share manufacturing enterprises in China from 2010 to 2019 serve as the research samples in this study. Moreover, the influence mechanism and effect of enterprise digitalization on technology innovation are studied at the micro level. The improvement of enterprise’s digital level can facilitate technology innovation, and this effect continues to be significant after a series of endogenous and robustness tests are performed, as indicated by the results of this study. In the above research, a more comprehensive and in-depth discussion at the micro level has been conducted to gain more insights into the correlation between enterprise digitalization and technology innovation, such that the black box of digitalization affecting technology innovation can be revealed more effectively.

Influence of Supply Chain Technological Integration on the Performance of Formal Manufacturing Firms in Mombasa County, Kenya

Technological integration within the supply chain has emerged as a pivotal determinant for the growth and competitiveness of manufacturing companies amidst the rapidly evolving business landscape. However, in Kenya, numerous firms encounter challenges in embracing and assimilating the latest technological advancements into their supply chain operations. This study aimed to assess the impact of supply chain technological integration on the performance of formal manufacturing firms in Mombasa County. Grounded on the Innovation Diffusion Theory, the research targeted 50 general procurement managers, 100 warehouse managers, and 100 general operation managers across 50 manufacturing enterprises. Utilizing the Yamane formula, a sample size of 152 respondents was determined, and data was collected through questionnaires. Statistical analysis was conducted using SPSS. The findings show that by enhancing operational efficacy and efficiency, the integration of supply chain technology significantly enhances overall business performance. Consequently, the study concludes that supply chain technological integration plays a positive role in influencing firm performance among formal manufacturing enterprises in Mombasa County. To optimize performance, it is recommended that firms invest in robust and reliable technologies. Furthermore, there is a need for additional research to explore the impact of supply chain technological integration on firm performance across diverse industries and regions within Kenya.

Green technology innovation and carbon emission efficiency: The moderating role of environmental uncertainty

Given the significant global warming caused by large-scale carbon emissions, it has become a crucial issue affecting human survival and world development. As a supportive means for relevant policies, the implementation of green technology innovation is essential for effectively achieving dual carbon goals. In order to explore the intrinsic relationship and impact mechanism between green technology innovation and carbon emission efficiency, this study takes data from high-energy-consuming manufacturing companies listed on the A-share market in China from 2010 to 2019 as samples. It uses the Super-SBM model to measure the carbon emission efficiency of sample companies and employs a two-way fixed effects model to verify the impact of green technology innovation on the carbon emission efficiency of high-energy-consuming manufacturing enterprises. Furthermore, this study also explores the external mechanism of green technology innovation related to carbon emission efficiency, focusing on the moderating variable of environmental uncertainty. The study found that both the quantity and quality of green technology innovation can significantly promote the carbon emission efficiency of high-energy-consuming manufacturing enterprises, and the accuracy of the results remains unchanged after conducting robustness tests. Environmental uncertainty plays an important role in moderating the process of green technology innovation, affecting the carbon emission efficiency of high-energy-consuming manufacturing enterprises. Heterogeneity tests show that the impact of green technology innovation on carbon emission efficiency is particularly significant in the central region and in enterprises experiencing decline. The policy implications derived from empirical analysis aim to provide empirical evidence for promoting the high-quality development of China's high-energy-consuming manufacturing enterprises.

Innovation strategy, digital transformation and competitive advantage of manufacturing enterprises: evidence from China

PurposeThis study aims to integrate the concepts of digital transformation, innovation strategy, and competitive advantage, into a novel research model in an effort to identify a more competitive path for digital transformation within manufacturing enterprises.Design/methodology/approachThe research model was tested through multivariate hierarchical regression analyses, and Hayes’ PROCESS for SPSS, utilizing survey data collected from 183 manufacturing enterprises in China.FindingsThe results indicate that, in comparison to research and development (R&D) and production, digital transformation in service and organizational activities exert a more significant impact on competitive advantage. Conversely, digital transformation in sales does not exhibit a significant impact on competitive advantage. Furthermore, in contrast to exploratory innovation and ambidexterity, exploitative innovation has a more pronounced influence on digital transformation. Additionally, digital transformation has been confirmed as a mediator in the relationship between innovation strategy and competitive advantage.Originality/valueThese findings expand our comprehension of digital transformation as an evolving process and shed light on the relationship between digital transformation and competitive advantage across various value-creating activities. This research serves as a valuable resource for decision-makers in selecting the most suitable path for digital transformation and configuring innovative resources.