Digital Industry Research Articles

Corporate social and digital responsibility in esports

PurposeThe esports industry has experienced a dynamic growth. In this context, a significant evolution in the logic of corporate social responsibility (CSR) can be observed, particularly in the digital sphere. By extending Carroll’s three-dimensional model to include corporate digital responsibility (CDR), this paper addresses a key research question: How does CSR evolve and develop in the dynamic digital industry of esports?Design/methodology/approachThis study employed a qualitative multiple case study research design. It drew on secondary data from 50 professional esports organisations and key players in CSR development in the global esports industry, such as game publishers, pro-teams, pro-athletes, event organisers, and governing bodies. A content analysis of 50 official websites and 72 public annual, CSR, and environmental reports for the financial years ending in 2021 and 2022 was conducted.FindingsOur empirical findings not only map the territory of esports CSR and CDR but also provide practical insights. These insights are later synthesized to develop an esports CSR/CDR framework that extends Carroll’s three-dimensional model. CSR and CDR domains of esports are theoretically grounded (business performance, responsiveness, social issues, and digital responsibilities), while practical implications for managers and academics are forwarded.Originality/valueThis paper stands out as a pioneering empirical study, filling a significant research gap in the fields of CSR and CDR in esports. To the best of our knowledge, it is the first to illuminate these concepts within the unique ecosystem of esports, thereby contributing to the evolving understanding of CSR in the digital context.

The impact of digital industrialization and industrial digitalization on regional green innovation efficiency in China -From the perspective of the innovation value chain

To systematically detect the influence of digital economy on regional green innovation, this study regards regional green innovation as a two-stage sequential process, and constructs a network SBM model to evaluate the overall and stage green innovation efficiency of 30 provinces in China from 2011 to 2020. Digital economy development is decomposed into digital industrialization and industrial digitalization, and an empirical study based on fixed effects regression model of panel data is conducted to determine their influence on the overall and stage green innovation efficiency. The results suggest the following: (1) The overall efficiency in China remained at a low level, with the efficiency of research and development being slightly higher than that of achievement transformation. (2) From the national perspective, there is no discernible effect of digital industrialization on overall efficiency, but there is a negative impact on research and development and a significant positive impact on achievement transformation. Industrial digitalization significantly improves achievement transformation and overall efficiency but has no discernible effect on the research and development stage. (3) In the eastern region, industrial digitalization promotes the improvement of both stages and overall efficiency, while digital industrialization does not have a significant impact. In the central region, digital industrialization and industrial digitalization have significant positive impacts on both overall efficiency and the efficiency of achievement transformation but have no impact on research and development. In the western region, digital industrialization inhibits the overall and achievement transformation efficiency, and industrial digitalization does not have significant impact on the overall efficiency or the efficiency of each stage. Finally, some relevant policy recommendations are proposed.

Subscriber retention management: SRM framework and future research agenda

Purpose This article aims to systematically review the fragmented but increasingly relevant research field of customer retention management in subscription scenarios, proposing the subscriber retention management framework for retention management in subscription settings and directing future research. Design/methodology/approach The authors systematically reviewed 1,295 articles to offer a comprehensive, unbiased overview on customer retention management in subscription-based services. From 122 selected articles, the authors conducted a descriptive analysis, conceptualized key insights into a novel framework and recognized research gaps. Findings Among 122 articles, 111 focus on private customers across various service sectors, while lacking reflection on new digital industries, reactive retention and the corporate context. The conceptualization of results merges existing insights into seven dimensions, encompassing strategic and tactical aspects and the interplay of controllable and uncontrollable factors. The authors also outline 12 emerging research directions. Research limitations/implications Given the extensive body of literature, the authors were unable to delve into detailed explanations. The findings are limited to management science research sourced from Scopus, adhering to a rigorous filtering process. Sub-domains, such as reactive or business-to-business retention management, remain somewhat provisional due to little results. Practical implications A sustainable subscriber retention strategy hinges on: (1) integrating retention into business strategy, (2) adjusting acquisition and retention tactics to specific markets and (3) using a consistent retention marketing mix considering affective, calculative and habitual commitment factors. Originality/value The authors contribute with a first systematic review of subscription-specific retention management in a rapidly growing area. This results in a novel framework that broadens the understanding of subscriber retention and identifies research gaps.

Tourism digital marketing in Indonesia: Current issues, challenges and opportunities

Purpose of the study: Marketing strategies must evolve with shifts in customer trends, behavior, and technological advancements. Academically, marketing has long been a key area of interest for scholars. This study systematically analyzes research references on tourism marketing in Indonesia. Methodology: This analysis draws on national publication data featuring tourism marketing keywords from 2014 to 2024, obtained via web scraping from the Google Scholar database. Additionally, it seeks to identify key concerns, challenges, and opportunities for digital marketing within Indonesia's tourism sector. Main Findings: This review highlights that academic journals cover diverse aspects of tourism marketing, including tourism, social sciences, communication management, and technology. Despite its limited scale, digital marketing is widely explored by scholars across fields. Bali, Bantul, Sleman, and Yogyakarta are frequently studied locations. Indonesian tourism marketing research tends to adopt qualitative approaches, yet a broad spectrum of contexts such as economics, business, communication, entrepreneurship, sociology, anthropology, and creative industries is also examined. Applications of the study: This study's scope is limited by the narrow range of Google Scholar articles. Future research can expand the literature, with key findings serving as hypotheses for further studies. Policymakers and the digital industry can use these insights for tourism product development. It also represents one of the latest ten-year reviews of digital marketing literature in Indonesia. Novelty/Originality of the study: Tourism must use effective marketing and adapt to changing market behaviors. Collaboration among stakeholders, including academics, is key to seizing opportunities and tackling future challenges.

Strategi Pengembangan dan Pemasaran Digital Industry Agency

This research aims to report on the development of Digital Industry Agency (DIA), covering the company’s identity, organization, target market, and financials. DIA, known for specializing in the development of digital products, focuses on big data and ERP (Enterprise Resource Planning) systems. The goal of establishing DIA is to address various issues within companies related to Industry 4.0 through digitalization. ERP, as the main product, is designed to enhance company efficiency and effectiveness by integrating systems and business processes into a unified platform that can be used by all departments and branches of the company. DIA has successfully overcome challenges in developing and marketing digital solutions, particularly ERP, in the era of Industry 4.0. By focusing on innovation and digitalization, DIA has been able to improve operational efficiency and expand its market reach. The strategy of combining digital technology with service personalization has proven effective in attracting and retaining customers. To maintain its position as a leader in Indonesia's digital industry, DIA is advised to continue investing in advanced technology, human resource training, and product innovation to stay competitive and relevant in the market. Sustained investment in technology and product development will ensure DIA remains a key player in an ever-evolving market.

Intelligent Financial Management Systems Innovations and Applications in the Digital Era

With the advancement of digital transformation, intelligent financial management systems have played a significant role in improving the efficiency, accuracy, and decision-making capabilities of corporate financial management. This study explores the performance and impact of three intelligent financial management systems — Digital Processing Methods and Financial Reimbursement Document System (System A), Industrial Digitalization Industry Enterprise Growth Evaluation System (System B), and Cloud-based Intelligent Financial Management Tools (System C) — in practical applications through case study methods. The results show that these systems have significantly improved the efficiency and accuracy of financial management, enhanced decision-making capabilities, and reduced operational costs through automated processes, data mining, and machine learning techniques. The study also points out challenges in the implementation process, such as data quality, user acceptance, and system integration issues, and predicts future development trends. Finally, the paper discusses the limitations of the research and proposes directions for future research.

FBLearn: Decentralized Platform for Federated Learning on Blockchain

In recent years, rapid technological advancements have propelled blockchain and artificial intelligence (AI) into prominent roles within the digital industry, each having unique applications. Blockchain, recognized for its secure and transparent data storage, and AI, a powerful tool for data analysis and decision making, exhibit common features that render them complementary. At the same time, machine learning has become a robust and influential technology, adopted by many companies to address non-trivial technical problems. This adoption is fueled by the vast amounts of data generated and utilized in daily operations. An intriguing intersection of blockchain and AI occurs in the realm of federated learning, a distributed approach allowing multiple parties to collaboratively train a shared model without centralizing data. This paper presents a decentralized platform FBLearn for the implementation of federated learning in blockchain, which enables us to harness the benefits of federated learning without the necessity of exchanging sensitive customer or product data, thereby fostering trustless collaboration. As the decentralized blockchain network is introduced in the distributed model training to replace the centralized server, global model aggregation approaches have to be utilized. This paper investigates several techniques for model aggregation based on the local model average and ensemble using either local or globally distributed validation data for model evaluation. The suggested aggregation approaches are experimentally evaluated based on two use cases of the FBLearn platform: credit risk scoring using a random forest classifier and credit card fraud detection using a logistic regression. The experimental results confirm that the suggested adaptive weight calculation and ensemble techniques based on the quality of local training data enhance the robustness of the global model. The performance evaluation metrics and ROC curves prove that the aggregation strategies successfully isolate the influence of the low-quality models on the final model. The proposed system’s ability to outperform models created with separate datasets underscores its potential to enhance collaborative efforts and to improve the accuracy of the final global model compared to each of the local models. Integrating blockchain and federated learning presents a forward-looking approach to data collaboration while addressing privacy concerns.

Digital Industry transformation strategy analysis and decision-based on intelligent decision technology

Expanding and being competitive in the current economic environment requires companies to embrace digital transformation. In the framework of Industry 4.0, the network of interconnected machines, sensors, and software known as the IIoT plays a crucial role in transforming conventional manufacturing facilities into smart factories, notably in monitoring and optimising the manufacturing process. The issues about enormous record storage and how they react challenge conventional automated methods in the IIoT. Cognitive systems optimally modify production settings based on managing uncertainty and sensory inputs. This work uses the Internet of Things-based decision support system with cognitive automation (IoT-DSS-CA) for industrial informatics across the board, including data collection, transmission, processing, and storage. Incorporating the elements frequently neglected during digital transformation, the suggested method uses the business process management (BPM) paradigm to give a systematic approach that industrial organizations may employ to aid their path towards Industry 4.0. The proposed mechanism is thoroughly investigated and evaluated compared to an original solution using several sensing and decision-making features in industrial parameter settings determined by Simple Additive Weighting (SAW) and Analytic Hierarchy Process (AHP).

The Creative Economy in Local Territories: Alibaba and Amazon in Territorial Competition, but Ideological Synergy to Bypass Democratic Governance

Alibaba and Amazon now dominate global e-commerce. Although their strategies partly differ, they are both territorializing their activities around sorting hubs and warehouses. This often creates tensions in local territories. In our research exploring the effects of these strategies, conducted in France and Belgium from 2019 to 2022, we hypothesized that the impacts of the digital industrialization of local and global trade go beyond sales and logistics; the concentration of these markets in the hands of two ultra-dominant actors reflects unequal power relations that are reconfiguring governance, public decision-making, and democracy, notably by obscuring the major challenges that territories face.

The effect of using method timer media on reducing eye fatigue industry workers

The outcomes of an initial research on eye fatigue in the Digital Industry in Yogyakarta, Indonesia revealed that 76% of the employees encountered complaints of eye fatigue as a result of prolonged computer usage. Eye fatigue is considered one of the parameters of office ergonomics in accordance with Indonesian Minister of Health Regulation No. 48 of 2016. One method recommended by this regulation to mitigate eye fatigue is to incorporate short breaks using the 20-20-20 technique. However, a considerable number of workers tend to disregard these recommendations, necessitating the use of media reminders, such as timers, to enforce discipline among workers. The objective of this research was to assess the impact of employing a timer-based media using the 20-20-20 method on the reduction of eye fatigue. The research employed a quasi-experimental design with a nonequivalent control group. In this research, a total of forty workers were selected as the sample population and subsequently divided into two groups: the intervention group and the control group. Sampling was conducted to select a total of 20 workers for each group through purposive sampling. Bivariate analysis was performed using the Sign test and Mann-Whitney test, with a significance threshold of 95% (α=0.05). The results of the statistical tests conducted in both the intervention and control groups revealed a significant difference in reducing eye fatigue, with a p-value of 0.041. This research concludes that the utilization of the 20-20-20 method timer media has a significant effect on reducing eye fatigue among workers.

The impact of China’s digital economy industry development and its structural indicators on carbon emission intensity

IntroductionThe development of the digital economy has a profound impact on industrial economics. The article starts from the perspective of industrial organization theory. The thesis aims to analyze the industrial development of the digital economy and its three structural variables: digital manufacturing industry, digital service industry, and the development of industrial digitization on carbon emission intensity.MethodBased on the data of Input-output Tables with extended tables of 30 provinces, this paper analyzes the industrial development of digital economy and its three structural variables: digital manufacturing industry, digital service industry, and the development of industrial digitization on carbon emission intensity.Results and discussionThe empirical results show that: 1) at the national level, the development of China’s digital economy industries has a suppressive effect on carbon emission intensity; 2) in terms of spatial effects, the development of digital economy has significant carbon spillover effects, but digital industrialization and industrial digitization present different spatial effect results; 3) from the analysis of regional heterogeneity, in the northeast, central and western regions, the direction of influence of digital industrialization and industrial digitalization on carbon emission intensity is consistent; in the eastern region, the development of digital industrial service sector and industrial digitalization has a suppressive effect on carbon emission intensity, while digital industrial manufacturing sector presents a pro-increasing effect; 4) Non-linear relationship analysis shows that the development of the digital industrial manufacturing sector has a “promoting and then inhibiting” effect on carbon emission intensity. Overall, the impact of digital industry development on carbon intensity exhibits a “promoting increase, then suppressing, then promoting increase” trend. In conclusion, the findings suggest that China’s digital economy industry has entered the low-carbon development stage.

Research on the influence of the digital economy on the development of China’s small household appliance industry and enhancement countermeasures

Purpose The implementation of the digital economy has had a considerable influence on the manufacturing industry, and this paper aims to address the important issues of how to capture the opportunities presented by digital innovation and promote the transformation and upgrading of the manufacturing industry, as well as the improvement of quality and efficiency. Design/methodology/approach Using panel data from 30 Chinese provinces and cities between 2010 and 2021, this study establishes the panel vector autoregression (PVAR) model and uses impulse response function analysis to evaluate the influence of the digital economy on the high-quality transformation and upgrading of China's small home appliance industry across five dimensions under the digital economy. Findings The development of digital infrastructure has not demonstrated a noteworthy capacity for advancing the transformation and upgrading of the small home appliance industry. Furthermore, digital industrialization has exerted a minimal restraining influence on this process. Nevertheless, digital governance has consistently exhibited a substantial impact on facilitating the transformation and upgrading of the small home appliance industry. While both industrial digitization and digital innovation hold significant potential for promoting the transformation and upgrading of the small home appliance industry, their sustainability remains limited. Practical implications The organization should logically join independent innovation and open innovation, construct an industrial ecosystem for the profound convergence of the digital economy and compact household appliances, use digital-wise science and technology to empower the establishment of brand effects, strengthen the portrayal of the digital standard framework for the intelligent compact household appliance industry, advance the development of a public stage for computerized administrations in the compact household appliance industry and develop a strategy ecosystem for computerized assets in the compact household appliance industry. Originality/value This study offers systematic evidence of the relationship between the digital economy and the development of the small home appliance industry. The results of this research contribute to the literature on the impact of the digital economy on the manufacturing sector and provide a logical explanation for the transformation and upgrading of the small home appliance industry within the context of the digital economy.

Toward low carbon development through digital economy: A new perspective of factor market distortion

The development and application of digital technology has brought profound influences on our economic development. It is therefore urgent to measure such impact on low carbon development. This study aims to measure the impact of digital economy development among Chinese provinces by using an intermediary effects model and conducting heterogeneity analysis. The results show that digital economy can facilitate low carbon development in China by alleviating capital and labor market distortions. Industrial digitization has the greatest impact, while digital industrialization has the smallest impact. Moreover, from a region perspective, digital economy is more effective to promote low carbon development in those eastern regions, while it is critical to improve the digital economy development environment in those central and western regions. Finally, several policy recommendations are raised by considering the Chinese realities.

The Impact of Digital Economy Development on Improving the Ecological Environment—An Empirical Analysis Based on Data from 30 Provinces in China from 2012 to 2021

The rapid progress in science and technology has ushered in a new era of organized and efficient development within the digital economy. China has repeatedly emphasized the need for high-quality development that prioritizes ecological conservation. The central challenge is to balance economic growth with environmental protection, ensuring sustainable development. Understanding the environmental impact of the digital economy is critical for achieving green growth in China. This paper investigates the relationship between the digital economy and ecological protection, using data from 30 provinces and cities in China between 2012 and 2021. Through empirical analysis, including a two-way fixed effect model, mechanism analysis, regional difference analysis, and robustness tests, the study found a significant negative correlation between the digital economy and environmental pollution. This indicates that the development of the digital economy can effectively improve the ecological environment. In the information age, seizing the opportunities presented by the digital economy is crucial. By deepening the digital industry and leveraging digital technologies, China can enhance enterprise production, promote innovation, and create a positive feedback loop between economic development and environmental optimization. However, it is essential to recognize regional disparities in digital economy development and work to narrow these gaps, ensuring balanced and sustainable growth across the country.

Reducing transport carbon intensity in the belt and road countries using the global value chain and the moderating role of digital industrialization

Reducing transport carbon intensity in the belt and road countries using the global value chain and the moderating role of digital industrialization

ASSESSMENT OF DIGITAL REINDUSTRIALIZATION OF DEPRESSED REGIONS OF RUSSIA

Digital re-industrialization of depressed regions of the Russian Federation is a strategically significant process aimed at implementing a set of measures to introduce digital technologies in industrial production, the purpose of which is to stimulate economic growth and improve the competitiveness of these territories. This process is particularly relevant in the context of the need to overcome structural imbalances and socio-­economic problems in depressed regions, as well as in the context of increasing globalization and technological transformation of the world economy. The purpose of the study is to assess digital re-industrialization in depressed regions of the Russian Federation with a focus not only on the modernization and transformation of existing traditional industrial sectors with the help of digital technologies, but also on the creation of new digital industries. The basis for the analysis was Rosstat data for 2022–2023, as well as the materials of the Strategies of Digital Transformation of the constituent entities of the Russian Federation. As a result of the study, a methodology for assessing digital reindustrialization, adapted to the special conditions of depressed regions of the Russian Federation, was developed and tested, demonstrating how the processes of digital reindustrialization affect the economic development of depressed regions. The novelty of the author’s concept of digital re-industrialization lies in its consideration on the basis of the convergence of digital industrialization and industrial digitalization. In some regions, digital transformation promotes accelerated modernization and growth, while in others it faces a number of obstacles related to limited resources and infrastructural problems. The practical value of the study is expressed in the recommendations for stimulating economic resilience of depressed regions of the Russian Federation. The authors’ further research will be aimed at expanding the empirical database. It also seems important to integrate the presented methodology with other digital strategy tools. It is necessary to conduct long-term monitoring of the results of the implementation of strategies of digital transformation of depressed regions, taking into account the specifics of each region. A promising direction is the study of interregional interaction and the creation of conditions for the dissemination of best practices of digital reindustrialization.

Application of Machine Learning in 3D Bioprinting: Focus on Development of Big Data and Digital Twin.

The application of machine learning (ML) in bioprinting has attracted considerable attention recently. Many have focused on the benefits and potential of ML, but a clear overview of how ML shapes the future of three-dimensional (3D) bioprinting is still lacking. Here, it is proposed that two missing links, Big Data and Digital Twin, are the key to articulate the vision of future 3D bioprinting. Creating training databases from Big Data curation and building digital twins of human organs with cellular resolution and properties are the most important and urgent challenges. With these missing links, it is envisioned that future 3D bioprinting will become more digital and in silico, and eventually strike a balance between virtual and physical experiments toward the most efficient utilization of bioprinting resources. Furthermore, the virtual component of bioprinting and biofabrication, namely, digital bioprinting, will become a new growth point for digital industry and information technology in future.

DIGITAL MARKETING STRATEGY IN THE CREATIVE DIGITAL INDUSTRY? WHY NOT!

This research refers to the implementation of digital marketing strategies carried out by Seven Creative Media, along with the types of content they use. Seven Creative Media is one of the creative digital industries actively marketing through several social media platforms. This research aims to identify the elements used in digital marketing techniques to increase brand awareness, the role of social media in brand awareness, and the content used to enhance brand awareness in the Creative Digital Industry. The research employs a descriptive qualitative approach, with purposive sampling of 16 informants based on specific criteria. The results show that the elements used in digital marketing techniques to increase brand awareness at Seven Creative Media have met market needs and market responses. The role of social media in promoting brand awareness by Seven Creative Media has successfully created content with an audience that already has engagement, leading to an increase in the reach of consistent content. The content created by Seven Creative Media is quite eye-catching, supported by clear voice-over articulation, ensuring that the information is conveyed very well. The image quality in the videos is also clear, allowing viewers to easily understand the content's message. Unique selling is also applied by Seven Creative Media, where this creative digital industry employs storytelling that includes product or service education. Keywords : Digital Marketing, Social Media, Brand Awareness, Content Marketing, Creative Digital Industry

Spatial differentiation and driving factors of scientific and technological innovation efficiency under the background of the digital economy

Scientific and technological innovation (STI) activities are facilitated under the influence of the digital economy and depend on digital elements to support innovation activities. This study measures digital element inputs and outputs using data related to the digital economy and estimates STI efficiency in 29 provincial regions in mainland China from 2010 to 2021 employing the global super-efficiency slacks-based measure (SBM) model. Then, spatial characteristics and driving forces of STI efficiency are quantified using spatial autocorrelation and geographic detectors. The results reveal that STI efficiency exhibits a fluctuating, W-shaped pattern, and the spatial correlation effect shows a gradually declining trend from 2010 to 2021. The findings reveal that the core drivers of STI efficiency are digital financial development, e-commerce development, digital access level, and related factors. Therefore, strengthening inter-regional innovation links, promoting the construction of 5 G mobile internet and accelerating the integration of digital industries into traditional industries are recommended.

Digital economy development and regional innovation resilience: mechanism and empirical analysis

ABSTRACT Improving the resilience of innovation systems is a prerequisite for achieving high-level self-reliance and self-improvement in science and technology. This study defines a conceptual framework of innovation resilience. It delves into its theoretical and empirical aspects to thoroughly examine the impact and transmission mechanisms of digital economic development on the resilience of regional innovation systems. The research findings reveal that the digital economy positively impacts regional innovation resilience (RIR), a result that persists even after a series of robustness tests. Second, the digital economy can effectively enhance RIR by expanding the scale of the digital industry, strengthening intellectual property protection, and increasing innovation. Third, there is a threshold effect on the influence of the digital economy on RIR, which becomes more pronounced with the developing digital economy and increasing levels of innovation personnel, funding, and output. The conclusions of this study provide new policy tools to strengthen innovation resilience and promote the optimization of regional innovation policies.