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• The entry of high-tech FDI does promote the robot adoption by domestic manufacturers in China. • A Bartik instrumental variable is constructed to address the endogeneity issue. • Two main influencing channels are detected: demonstration and competition. • The effect is more salient among enterprises with stronger absorptive capacity. • Different levels of dependence on labor and energy inputs lead to heterogeneity. With the intensification of transnational economic activities, industrial robots have been making inroads into developing countries. However, few studies have analyzed how foreign direct investment (FDI) affects the diffusion of industrial robots among domestic enterprises in developing countries. To bridge the gap, we combine several datasets to empirically examine the causal relationship between high-tech FDI and the robot adoption by domestic manufacturers in China. We discover a significantly positive impact of high-tech FDI on the adoption of industrial robots by domestic manufacturers, evidenced by the expansion in both stock and flow, as well as an increase in the variety of robots. Mechanism tests indicate that this effect can be achieved through both proactive learning and absorption of external technology, as well as through passive participation in more intense market competition. Moreover, the impact of high-tech FDI on robot adoption is more salient among enterprises with stronger absorptive capacity as well as those characterized by lower labor intensity and higher energy intensity. [ABSTRACT FROM AUTHOR]

• Focuses on the role of digital finance in the TFP of manufacturing enterprises. • Tests the mediating role of financing constraints, human capital, and risk-taking. • Analyzes digital finance's dynamic impact on firm productivity through entry/exit. The development of digital finance offers numerous development opportunities, particularly in the accessing of funds for enterprises that traditionally face financial constraints. The economic downturn globally and especially in China requires new policies for stimulating economic growth. The manufacturing industry in particular is apt for this kind of intervention. Although studies have examined these topics, several gaps exist in the literature, specifically in the area of the effect mechanism. Therefore, this study examines the direct relationship between digital finance and the total factor productivity (TFP) of manufacturing enterprises and discusses the mechanism of action between the two from the intermediary and entry/exit perspectives. The findings show that digital finance affects manufacturing TFP positively and significantly. The promotion effect of digital finance is more evident from the enterprise heterogeneity analysis, particularly for small- and medium-sized private and manufacturing enterprises with better growth. The effect mechanism analysis shows that digital finance affects manufacturing TFP positively by reducing financing constraints, improving the level of human capital, and enhancing enterprise risk-taking ability. From the perspective of enterprise entry and exit, the entry of high-productivity enterprises enhances market competition and is an important way that digital finance promotes the improvement of industry TFP. [ABSTRACT FROM AUTHOR]

The literature shows that the financial system dominated by large national banks restricts enterprises' financing channels, leading to efficiency losses. In response, governments introduce different types of banks to address this issue. However, the literature overlooks the relationships among regional banks, financing constraints and manufacturing enterprises' productivity. We fill this gap by exploiting the China's unique policy of staggered rollout of city commercial banks across cities and using data from Chinese listed manufacturing enterprises over the period 1992 to 2022 to explore how regional banks affect productivity. We find that regional banks represented by city commercial banks in China significantly increase the manufacturing enterprises' total factor productivity by alleviating financing constraints, especially pronounced for state-owned enterprises, large enterprises, and well-established enterprises. Our research results emphasize the effectiveness of regional banks in promoting the development of the manufacturing industry and offer insights for sustainable economic development policies. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of digital transformation on positive social emotions within manufacturing enterprises and examines the moderating effects of management tone and marketing capabilities on this relationship. This research uses a panel fixed-effect regression model to empirically examine the impact of positive social emotions on the digital transformation of manufacturing enterprises from 2016 to 2020 based on panel data of Chinese A-share listed companies in Shanghai and Shenzhen. The results indicate that social positive emotions significantly contribute to the digital transformation of manufacturing enterprises. The effect of social positive emotions on the digital transformation of manufacturing enterprises is strongly heterogeneous in terms of differences in enterprise attributes and geographical differences. Further analysis reveals that marketing capability and corporate executive tone, directly or indirectly, both have a considerable positive moderating effect on the aforementioned mechanism. In contrast, innovation capability has little moderating influence. In order to better regulate external positive social emotions to promote digital transformation, manufacturing enterprises need to emphasise management tone and enhance their marketing capabilities. These might facilitate companies in utilising additional social resources, strengthen internal strategic digital transformation decisions, and advance the development of digital transformation in China's manufacturing sector. [ABSTRACT FROM AUTHOR]

This study examined the relationship between accounting conservatism (AC) and financial performance for 231 manufacturing companies listed in Vietnam on the Hanoi Stock Exchange and Ho Chi Minh Stock Exchange stock exchanges between 2019 and 2022 using book value which includes ROA, ROE, and ROS. Accounting conservatism harms ROA, ROE, and ROS throughout six years from 2017 to 2022, according to a multivariable regression study using Ordinary Least Square (OLS), FEM, REM, and FGLS models on Stata. In addition, the COVID-19 pandemic has affected the global economy in general and manufacturing enterprises listed in Vietnam in particular, so the authors also analyze the influence of AC on financial performance in two periods, before and after COVID-19. The results obtained in the pre-COVID-19 period (from 2017 to 2019) are the same as those of the 6 years. However, from 2020 to 2022, AC has an adverse effect on ROA and ROE. Nonetheless, ROS is unaffected by AC. The article has given some discussion and recommendations to stakeholders including the government, auditors, and accountants at enterprises regarding the level of AC in enterprises to help users of financial information make the most optimal economic decisions. [ABSTRACT FROM AUTHOR]

The article is devoted to the study of the conceptual foundations of organizational culture of manufacturing enterprises in wartime. The author generalizes approaches to the concept of “organizational culture” and presents the author’s own definition, which is understood as an integrated system of values, norms and behavioral models, which in wartime acts as an adaptive and protective mechanism, providing the enterprise with the ability to quickly restructure and strengthening corporate solidarity by enhancing the socio-psychological stability of the team; as a strategic tool, it ensures cohesion and motivation of employees, activating their ability to dedication and support each other, which is a once-in-a-lifetime opportunity. The article highlights the peculiarities of organizational culture in wartime, in particular: strategic direction; values that form a unique socio-psychological environment at an enterprise, thereby shaping its competitive advantages; specific components - implicit (socio-psychological) and explicit (regulatory and image elements). The characteristics of modern models of organizational culture are identified: spiritual, socio-psychological, and material. It is proved that the organizational culture of an enterprise is formed under the influence of external and internal factors, and the factors from each group are specified. The functions of the organizational culture of enterprises are studied and the functions of internal integration and functions of external adaptation are allocated. The functions of internal integration include organizational, integrating, regulatory, substitution, adaptive, educational and cognitive, motivating, communicative, quality management, and recreational. External adaptation is ensured by the following functions: innovation, formation of a positive image, customer orientation, management of partnership relations, and adaptation of the enterprise to the needs of society. The key aspects of the conceptual foundations of building the organizational culture of production enterprises are defined: process orientation; hierarchical organizational structure; physical work; safety and risks; innovation and adaptation; relationship with suppliers and consumers. New requirements for the formation of the organizational culture of enterprises during the war period were considered. The experience of foreign countries regarding the formation of organizational culture in conditions of war and constant armed conflicts, in particular Germany, South Korea, and Israel, is studied. It is proposed to introduce as elements of organizational culture specific for production enterprises under conditions of war, including: adaptability to risks and crises, support for safety and protection of personnel, patriotic aspect and values of sustainability, as well as humanitarian and social responsibility.

The construction of the industrial Internet platform is the key to the digital, networked and intelligent transformation and innovation of the manufacturing industry. At present, there are some limitations in the research on the mechanism of the construction of industrial Internet platform with the participation of developers. It fails to consider the reasonable benefit sharing coefficient and the influence of the decision-making process of the form and strength of government support. Therefore, a four party dynamic interactive evolutionary game model based on the logical framework of “government platform manufacturing enterprise developer” was constructed, and the strategic choices of the four parties in the process of building an industrial Internet platform in collaboration were analyzed in depth, and the influencing factors of the strategic choices of each party were simulated. The results indicate that government subsidies and penalties affect the strategic choices of manufacturing enterprises, platforms, and developers. A reasonable revenue sharing contract coefficient can ensure long-term cooperation and stable development between the platform and developers. In addition, the effective range of influencing factors that promote the evolution of the system to different stable states is defined, which provides a theoretical basis for manufacturing enterprises, industrial Internet platforms, governments and developers to choose strategies.

In the era of the digital economy, the application of digital technology plays an important role in improving the efficiency of resource allocation in manufacturing enterprises and promoting innovative development in manufacturing.Based on the theory of resource allocation, using data from Chinese cities and manufacturing enterprises spanning from 2010 to 2021, this study empirically tests the impact mechanism of urban digital economy development on resource allocation of manufacturing enterprises using the mediation effect model. Research has found that: (ⅰ) the development of the digital economy has significantly improved the allocation efficiency of manufacturing capital, labor, and intermediate inputs. This conclusion still holds after robustness testing. (ⅱ) The development of the digital economy has a positive effect on the allocation of manufacturing resources by weakening industry monopolies. Weakening industry monopolies is an inherent driving force for improving the allocation of manufacturing resources in the digital economy era. (ⅲ) Government intervention not only exacerbates the distortion of manufacturing resource allocation, but also strengthens the distortion of resource allocation by weakening the enhancement effect of the digital economy. (ⅳ) Heterogeneity analysis shows that the digital economy has a significant improvement effect on resource allocation in the central and western regions, competitive industries, and non-state-owned enterprises. This study enriches theoretical research on the digital economy and resource allocation at the enterprise level, and holds significant practical value for accurately grasping the positioning of new driving forces in the emerging digital economy development paradigm. [ABSTRACT FROM AUTHOR]

The article focuses on the problem of designing, constructing, measuring and interpreting indices for assessing the digital transformation of manufacturing companies. We analyse the compositional features, advantages and limitations of the three indices, which are a fairly focused on comparing industrial sectors (or at least extended groups of industries) according to their level of digital transformation or digital maturity: Industrial Digitalisation Index MGI McKinsey, Smart Industry Readiness Index (SIRI) of the World Economic Forum, Digitalisation Index for Economy and Social Sectors by the Higher School of Economics. The main thesis of the article is the need to develop a unified, continuous and relevant index of digital transformation for manufacturing companies, taking into account all the positive experiences in the conceptual and methodological development of digitalisation assessment indices that research and analysis teams have managed to develop so far. At the same time, the author points out the need to avoid retrospective construction of indices based on lagging statistical data. It seems very important to take into account the need to introduce a strategic vector when measuring the level of digital transformation of manufacturing companies. It is not enough to simply aggregate indicators of digital adoption and identify certain indices or sub-indices as the main markers of digital transformation. From a statistical point of view, such an approach can be perfectly correct, reliable, and verifiable.Questions arise about the productive potential of clustered technologies in the context of evolving business models, particularly in manufacturing. As a part of constructing any indices and methods for assessing the dynamics of digital maturity, digitalisation, digital transformation, it is better to face the inevitable uncertainty about the potential of some frontier technologies in an attempt to foresee the intersections of technological factors and future niches for business models, than to try to generalise the trajectory already traversed with a more retrospective logic based only on the verified and more tested parts and layers of the technologies. With this approach, digital transformation indices for manufacturing companies take on projective and instrumental functions, as they serve, in a sense, as a roadmap. They make it possible to improve the strategic vision of companies in different sectors, as well as their stakeholders, associations and public authorities (especially those in charge of digitalisation and industrial policy), with a view to achieving later stages of digital maturity.

The essence of social and environmental responsibility of industrial enterprises is disclosed. The role of growth of environmental and social responsibility in improving the image and reputation of enterprises is defined. The relationship between social and environmental responsibility and corporate culture of enterprise is shown. The main opportunities for growth of internal and external social responsibility for production enterprises have been identified. A model of internal and external communications for a manufacturing enterprise has been proposed. The main opportunities for increasing environmental responsibility for manufacturing enterprises have been identified, including the stages of production, use of products by consumers and post-operation stage. Analytical indicators have been identified, which allow assessing the level of growth of environmental responsibility of production enterprises at the listed stages. [ABSTRACT FROM AUTHOR]

An important aspect of developing new quality productivity is utilizing the latest scientific and technological advancements for industrial upgrading, which includes developing emerging industries (high-tech industries) and transforming traditional industries. The weakness in advanced equipment manufacturing is a key challenge in China's current industrial upgrading. This study, based on the global distribution of manufacturing enterprises, proposes a classification of four types of enterprises. It explains the reasons behind China's lack of the fourth type of enterprise (those capable of integrating the latest technological achievements into their produced equipment) and the difficulties in cultivating and developing such enterprises. The study also categorizes technical teams related to advanced equipment into three types (equipment users, equipment manufacturers, and fundamental technology researchers), emphasizing that successful research and production of advanced equipment require the long-term, stable, and close cooperation of these three teams. Finally, it introduces several practical outcomes from the Ji Hua Laboratory (Guangdong Provincial Laboratory of Advanced Manufacturing Science and Technology) in Foshan, Guangdong Province, which was established in 2018. [ABSTRACT FROM AUTHOR]

Applying blockchain technology to the cloud manufacturing platform (CMfg) endowed it with features such as decentralized resource management, distributed data storage, and platform robustness. However, during the implementation of service optimization composition, challenges are encountered, including the need for centralized resource scheduling, data entry dependence on the moment of block generation, and a lack of dynamic adaptability in the execution scheme. To address this, this paper proposed a solution in the form of cloud dual-chain oriented to service optimization composition. The cloud dualchain comprised a manufacturing service chain (MSC) and a process data chain (PDC). It segregated the management of service resources and composition scheme into distinct chains, allowing the CMfg to reconcile blockchain characteristics with real-world service collaboration needs. The manufacturing service within the cloud dual-chain was self-managed by the enterprise, and the MSC chain was formed by smart contracts based on task orders, balancing distributed and centralized management. The PDC, generated based on service composition, recorded process data in parallel. In case of service failure, a new service was invoked in the corresponding MSC node, updating the information in the PDC node to ensure dynamic adaptability of the execution plan. Experimental results demonstrate that cloud dual-chain facilitates flexible service management, distributed parallel entry of process data, and provides dynamic adaptability to execution scheme. Cloud dual-chain can effectively support the development of CMfg. [ABSTRACT FROM AUTHOR]

Copyright of Transformations in Business & Economics is the property of Vilnius University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Artificial intelligence (AI) is emerging as a new driving force for green transformation of manufacturing enterprises. Drawing from panel data of manufacturing enterprises listed on China’s A-share market spanning from 2013 to 2019, this study finds that AI can promote green transformation of manufacturing enterprises. This finding maintains its robustness after re-measuring the core independent variable and the dependent variable, addressing endogeneity issues, excluding specific research sample, adding urban-level control variables, adding more fixed effects. The promotion effect emanates from the intermediary roles of enhanced managerial efficiency, reduced financial pressures, and the reinforcement of capabilities for green innovation. Furthermore, this study conducts heterogeneity analysis across three dimensions: corporate ownership, industry affiliation, and geographical location. The analysis discerns a heightened promotion effect when the manufacturing enterprises operate as non-state-owned enterprises, operate within labor-intensive and technology-intensive industries, or are geographically located in the eastern region. The findings offer insights to expedite the application of AI within manufacturing and propel the synergistic convergence of intelligence and sustainability in the sector. [ABSTRACT FROM AUTHOR]

Ergonomics, which is the process of adapting the physical environment to the human, aims to prevent the wear and tear of employees due to excessive stresses and to maximize employee performance. For this purpose, it can be stated that ergonomics applications will provide positive benefits for both employee and employer and considering today's economic and social conditions, the importance of ergonomics in enterprises is increasing. In this study, a research has been carried out on the evaluation of the studies on ergonomics in manufacturing enterprises. In this context, studies on risk assessment methods in the field of ergonomics in manufacturing enterprises in the national literature were analyzed bibliometrically. During the determination of the studies, inquiries were made using the relevant keywords. As a result of the investigations, the research universe was evaluated according to the status of the research. In the analysis phase, answers were asked to what are the ergonomic factors in the studies, what methods are used in the evaluation of ergonomic risks, the frequency of use of methods, what are the applied sectors, and the distribution of the studies according to the years. As a result of the analyzes, suggestions were made for the researchers who focused on ergonomics. [ABSTRACT FROM AUTHOR]

This study presents a holistic model based on Fuzzy Bayesian Network-Human Factor Analysis and Classification System (FBN-HFACS) to analyze contributing factors in the pandemic, Covid 19, risk management under uncertainty. The model contains three main phases include employing a) HFACS to systematically identify influencing factors based on validation using content validity indicators, b) Fuzzy Set Theory to obtain the prior probability distribution of contributing factors in pandemic risk and address the epistemic uncertainty and subjectivity, and finally, c) Bayesian network to develop causality model of the risk, probabilistic inferences and handle parameter and model uncertainties. The Ratio of Variation (RoV), as BN-driven importance measures, is utilized to conduct sensitivity analysis and explore the most critical factors that yield effective safety countermeasures. The model is tested to investigate four large manufacturing industries in South Khorasan (Iran). It provided a deep understanding of influencing human and organizational factors and captured dependencies among those factors, while quantitative finding paves a way to efficiently make risk-based decisions to deal with the pandemic risks under uncertainty. [ABSTRACT FROM AUTHOR]

Copyright of Modern Economic Science is the property of Modern Economic Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Competitiveness is one of the key success indicators of manufacturing enterprises. The purpose of this study was to design a model of strategic indicators effective in improving the competitiveness of companies, productivity . The present research was of a contextual survey type in terms of its practical purpose and of a mixed type in terms of the type of grounded theory search. The statistical population included professors, owners of companies producing sports products, experts in the field of export and import of sports products, experts in the field of marketing and managers of sports products companies, who distributed 20 interviews in the qualitative section and 120 questionnaires in the quantitative section collected. In the present study, to achieve a comprehensive conceptual model, first the from Glaser's method of grounded theory, then to confirm the conceptual model based on the grounded theory, a questionnaire was developed according to the research results After Confirming its Content Validity and reliability, it was Presentes to Second Sample of the Study. The research findings showed that internal indicators included management and structure, product improvement, service improvement, supply and design and marketing, and external indicators including legal and supportive factors, customer and consumer, market control and trade and international issues. Also, structural equation modeling findings showed the goodness of fit of a research model. According to the research results, companies producing can be successful in the market by improving their strategic indicators and improve their competitiveness [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

With uncertainty intensifying the international technological innovation environment, the innovation situation of Chinese manufacturing enterprises has been impacted. Based on 12,781 micro panel data in 2011–2020 of 2347 Chinese A-share manufacturing listed enterprises, this paper empirically analyzes the impact of innovation plight faced by enterprises on operational efficiency. The innovation plight in this article refers to the degree to which the actual innovation performance of enterprises has not reached the expected innovation performance or is introduced by an innovation gap, measured by the difference when actual innovation performance is lower than the expected innovation performance. The empirical results show that the innovation plight of manufacturing enterprises significantly inhibits operational efficiency by reducing their risk tolerance, development ability expectation, and profitability. After using a series of tests, such as the instrumental variable method, replacing the dependent variable, and changing the parameters for measuring the independent variable, the conclusion is still robust. In addition, the results illustrate that the inhibitory effect of innovation plight on operational efficiency is more obvious for non-state-owned enterprises, small and medium-sized enterprises, high-tech enterprises, and enterprises in the eastern region. Finally, we formulate some relevant management suggestions. [ABSTRACT FROM AUTHOR]

Companies face complex decisions when considering investing in green technology innovation versus traditional products. Key factors include financial constraints, risk of failure, and retailer demand uncertainty and risk aversion for new green products. This study constructs three financing models to analyse green tech manufacturer financing strategies and how the likelihood of success and risk tolerance impacts stakeholder behaviours and profits. Results demonstrate interdependencies between financing model chosen, investment willingness, order volumes, and participant earnings based on the success probability and risk appetite towards unproven green innovations. The models provide nuanced insights into investor and retailer uncertainties surrounding green technology, highlighting how perceived chances of success alongside risk preferences influence funding availability, production scales, and profit outcomes. By quantifying these relationships, the study aims to guide manufacturer decisions and promote suitable financing structures to support wider adoption of sustainability-focused technological innovations. [ABSTRACT FROM AUTHOR]

Haining, as the top ten industrial counties in Zhejiang, a strong manufacturing city, to keep pace with the pace of the digital era, to deepen the digital application of all aspects of the manufacturing production process, to provide a strong momentum for the transformation and upgrading of the manufacturing industry in Haining. Based on the background of digital economy, this paper analyzes the necessity of improving the innovation ability of China's manufacturing enterprises, as well as the problems faced by Haining's manufacturing enterprises in improving their innovation ability, such as the construction of innovation platforms that need to be perfected, the degree of enterprise innovation investment is not high, and the cultivation of digital innovation talents is facing serious challenges, etc., and from the coordination and optimization of the construction of innovation platforms, accelerating the promotion of the construction of digital infrastructure, deepening the reform of the system and mechanism for the development of talents, building The new pattern of digital transformation of higher education and multiple inputs, focusing on stimulating the vitality of innovation and other five aspects of the digital economy era in the context of Haining's manufacturing enterprises to enhance the innovation capacity of countermeasures, aimed at accelerating the creation of Haining City with Haining's recognizable "142" advanced manufacturing clusters, the construction of "manufacturing strong city digital strong city". The purpose is to provide useful reference for Haining City to accelerate the creation of "142" advanced manufacturing clusters with Haining City's recognizability and to build a "strong manufacturing city and digital city." [ABSTRACT FROM AUTHOR]

In order to make full use of the decision support knowledge contained in the structured chart data that matches the needs of the enterprise, we propose a deep learning approach for automatic statistical chart analysis. This method uses LSTM as the basic model for chart analysis, and mainly makes the following improvements: (1) A discriminator layer is added after the embedding layer of the model, so that the model can perform more targeted semantic understanding and text prediction according to the knowledge of chart; (2) In the character sampling process of the model, a random cluster sampling strategy is proposed to improve the quality of chart description; (3) The model is optimized by using the knowledge distillation method, so that it can generate more valuable description text for manufacturing scenarios. Experiments show that this method improves the text quality by 12.4% compared with traditional LSTM. To further evaluate the analysis description quality of ASCAT, we use the same dataset to train RNN, LSTM, AISG, EICT, and AGNLD models. Experiment results show that our ASCAT model obtained better description quality evaluation scores in description quality under the METEOR criteria considering the precision and recall rate, or under the CIDEr criteria with the TF-IDF weight introduced. [ABSTRACT FROM AUTHOR]

Innovation activities in manufacturing enterprises in emerging countries face a dilemma in simultaneously implementing exploitation and exploration innovation due to a lack of synergy capacity. Building upon the theories of dual innovation synergy and strategic flexibility, this study proposes a mechanism for achieving dual innovation synergy through digitalization, which can enhance innovation performance. We argue that digitalization improves innovation performance via dual innovation synergy. Additionally, we suggest that strategic flexibility moderates the relationship between digitalization and innovation performance by coordinating innovation strategy and other strategies. The results indicate a positive impact of digitalization on innovation performance, mediated by dual innovation synergy. Furthermore, an increase in strategic flexibility enhances the positive effect of dual innovation synergy on innovation performance, thereby amplifying the positive influence of digitalization on innovation performance through dual innovation synergy. This research contributes to the existing literature on the impact of digitalization on innovation performance by emphasizing the crucial role of dual innovation synergy and strategic flexibility in innovation management. [ABSTRACT FROM AUTHOR]

Supply chain management practices are always helpful for multinational enterprises in increasing their growth. However, there has always remained an open debate about which practices are helpful for small and medium enterprises (SMEs). Therefore, this study has examined the influence of supply chain management practices on the performance of SMEs. Moreover, it has examined how the moderation of supply chain ecocentricity and innovation capabilities strengthens or weakens the relationship between supply chain management practices and SMEs’ performance. The quantitative study involved 352 SME managers as they can provide the relevant information and possess complete knowledge of management practices. The data were gathered via a questionnaire, and the responses were analyzed using IBM SPSS 28 and IBM AMOS. The results show that SMEs’ performance is linked to supply chain management practices (β = 0.544; P < .001), and this linkage is further strengthened by supply chain ecocentricity (R2 change = 0. 082***, F-Statistics = 47.18) and innovation capabilities (R2 change = 0.061***, F-Statistics = 39.74). SMEs can enhance their performance by efficiently incorporating supply chain management practices and developing innovation capabilities and supply chain ecocentricity. AcknowledgmentsThis study is funded by Al Hussein Bin Talal University, Ma’an, Jordan, No. 125/2023.

Copyright of Nankai Business Review is the property of Nankai Business Review Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The digital economy has a significant influence on the financial behavior of enterprises. According to the panel data of A-share listed enterprises in the manufacturing industry from 2010 to 2020, we discuss how manufacturing enterprises allocate their financial assets in the process of digitalization from the perspective of operating profit and risk taking. The results reveal that ICT investment significantly reduces financial asset allocation, while digital transformation improves the financial asset allocation of manufacturing enterprises. Because ICT investment increases operating profit from the main business, manufacturing enterprises reduce the allocation of short-term and long-term financial assets. We thus propose two phenomena: precautionary saving and substitutional investment. As digital transformation increases risk taking, financial assets are elevated by manufacturing enterprises for the precautionary saving motivation, boosting the short-term financial assets in their portfolios. These findings are further supported by the heterogeneity of innovation characteristics and ownership. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Technology Economics is the property of Chinese Society of Technology Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Changzhou University (Social Science Edition) is the property of Editorial Department of Journal of Changzhou University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This research aims to assess a conceptual framework that includes radio frequency identification (RFID) technology usage and integrated with supply chain (SC) global positioning information system (GPIS) as antecedents to supply chain performance (SCP). A Web‐based survey questionnaire was used for the data collection process. The research framework and the derived hypotheses were tested by structural equation modeling. Data were gathered from a sample of 314 participants who are working in manufacturing‐sector enterprises. The targeted respondents were categorized as either managers (IT, engineers, production, operations, logistics, sales, purchasing, etc.), supervisors (IT/technical/operational workers, etc.) in medium and large‐sized enterprises (MLEs) in developing countries (Jordan, Lebanon, King Saudi Arabia, Bahrain, Qatar, Emirates, Egypt, Oman, Kuwait, and Turkey). The findings of this research indicate that RFID technology usage directly affects the integration with supply chain global positioning information system (SCGPIS) and SCP. Furthermore, SCGPIS achieves enhancing information sharing among supply chain partners, which in turn leads to enhancing SCP. This research paper offers empirical evidence for using RFID technology within the planning‐resources of manufacturing enterprises' context for enhancing their SCP. [ABSTRACT FROM AUTHOR]

The increasing intensity and frequency of extreme climate events have made improving the adaptability to extreme climate events a strategic imperative for manufacturing companies. This paper investigates whether manufacturing enterprises increase green technology innovation affected by different extreme climate events. Based on panel data of Chinese listed manufacturing enterprises, we show that extreme precipitation events can positively promote green technology innovation, yet extreme temperature events do not. Heterogeneity analyses suggest that the effect of extreme precipitation events on green technology innovation is more significant for non-state-owned enterprises, poor performance enterprises, and high R&D intensity enterprises than other enterprises. Furthermore, the facilitating effect of extreme precipitation events on green technology innovation is merely temporary. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Technology Economics is the property of Chinese Society of Technology Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The fourth Industrial Revolution is in full swing, the whole world is pondering the same question: Where is the core breakthrough? With the continuous breakthrough and extensive application of cloud computing, big data, artificial intelligence and other next-generation information technologies, One sign has emerged: digital economy is becoming a new driving force for global economic growth. The impact of digital transformation on enterprises is to improve the quality and efficiency、Improve information quality, Or spread out limited resources and reduce productivity, There is no consensus among academics. To fill that gap, this paper aims to sort out the internal mechanism of how digital transformation improves the output quality of the technological innovation of enterprises from a theoretical perspective, and to establish a digital transformation index at the micro level. On this basis, this study empirically examines how digital transformation affects the output quality of technological innovation.we adopts panel data. It uses data collected from 159 manufacturing enterprises in China. By adopting the methods of PLS structural equation and fuzzy set qualitative comparative analysis (fsQCA), it empirically tests the research model and conducts a mediation analysis through regression analysis. The findings indicated that, Digital transformation can help manufacturing enterprises to improve the output quality of their technological innovation; digital infrastructure plays a significant mediating role between digital transformation and the output quality of technological innovation; the investment of manufacturing enterprises in software and hardware digital infrastructure have a positive impact on the output quality of technological innovation. There is a complementary relationship between the two. The paper was conducted in the context of Chinese culture and can be generalized to other Asian countries. We believe that the research conclusions of this study have important practical significance for how manufacturing enterprises can effectively carry out digital transformation and improve the output quality of technological innovation. [ABSTRACT FROM AUTHOR]

With the rapid development of industrial manufacturing, the operation and maintenance problems of the power system are becoming increasingly prominent, and traditional manual maintenance methods are no longer able to meet the needs. This article aims to provide better power support for manufacturing enterprises. This article establishes a digital twin model of the power system, which corresponds the physical information and operational data of the actual power system to the digital model. Based on this model for simulation and prediction, machine learning and artificial intelligence algorithms are used to analyze historical data, extract features and patterns, and establish a monitoring and prediction model for the operation status of the power system. Finally, through real-time monitoring and prediction, timely detection and handling of faults and anomalies in the power system, the results can effectively improve the operational efficiency and reliability of the power system in manufacturing enterprises. Through real-time monitoring and prediction, faults and anomalies in the power system can be detected in a timely manner, reducing downtime and maintenance costs. Digital twin technology can also provide analysis and optimization suggestions for operating data for manufacturing enterprises, helping them improve production efficiency and competitiveness. [ABSTRACT FROM AUTHOR]