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This study delves into the strategies employed by small and medium-sized enterprises (SMEs) to embed digital technology into their business models, aiming to reach carbon neutrality. We offer a comprehensive analysis of five high technology SMEs, unveiling an evolutionary process model that highlights their journey toward integrating technology. The integration process is delineated into three progressive stages. Initially, digital technology is seen as an 'enabler' that promotes the birth of an innovative business model, essentially transforming the mechanisms of value creation, delivery, and capture. As SMEs evolve to an intermediate stage, digital technology becomes a 'disruptor', reshaping and reinventing the business model in terms of how value is created, delivered, and captured. Entering the maturity stage, digital technology is elevated to the role of 'expertise', leading to a sophisticated business model that refines and optimizes these aspects of value. The influence of these business model innovations on carbon neutrality is complex and varies distinctly with each stage, reflecting the dynamic interplay between digital technology and business model evolution. • This study explores the unique strategies SMEs implement to weave DT into their business model innovation (BMI) with an aim to achieve carbon neutrality. • The paper presents an evolutionary process model that sheds light on this integration journey, using an in-depth analysis of five high-tech SMEs. • The paper elaborates the relationship between DT and BMI, delving into the integration of DTs and the roles they perform - as enablers, disruptors, and areas of expertise. • The paper provides insights for businesses seeking to leverage digital technologies to drive innovation and growth. [ABSTRACT FROM AUTHOR]

• Internal digitalization is positively associated with CSR performance. • External digitalization is positively associated with CSR performance. • Ownership structure moderates between digitalization and CSR performance. The use of technology-driven applications has become widespread in the development and distribution of products and services. In our study, we aim to investigate the role of digitalization in establishing business sustainability within the shipping industry, using a sample of Chinese listed firms. Specifically, we examine how digitalization impacts corporate social responsibility (CSR) performance. Our findings indicate that both internal and external digitalization have a positive association with CSR performance. This study is the first to explore the impact of both types of digitalization on CSR performance, and we also identify ownership structure as a positive moderator of this relationship. Our study contributes to the literature on digitalization, CSR, and stakeholders, providing practical insights for policymakers in the shipping industry. By emphasizing the positive correlation between digitalization and CSR performance, we underscore the significance of adopting digital technologies to promote sustainability and responsible business practices. Our findings also demonstrate the necessity for firms to consider ownership structure when developing and implementing digitalization strategies to enhance CSR performance. [ABSTRACT FROM AUTHOR]

Based on the frame theory and signalling theory, this article uses financial technology (fintech) to analyse online news sentiment and proposes the relevant hypothesis of the influence of news relevance on stock market risk, and conducts an empirical study on the VAR model of the stock return rate by using the news relevance and news sentiment data of the Uqer database. The results show a two‐way Granger causality between news sentiment and stock returns. News relevance is not Granger causality of yield but Granger causality of news sentiment. In addition, combined with the impulse response, variance decomposition, and relevance analysis, it is found that the news relevance degree positively affects news sentiment and then indirectly affects the stock return rate. Our findings indicate that news relevance is an essential variable in analysing online text sentiment and stock market volatility, and online news will increase the volatility of stock market risk. These results contribute to the financialization literature and guide fintech enterprises to balance market risk by combining signalling and frame theory to improve news relevance. [ABSTRACT FROM AUTHOR]

This paper investigates how big data analytics influences the innovative activities of micro, small, and medium enterprises (MSMEs) on the basis of the resource-based and dynamic capabilities views. Studying a survey sample collected from 186 entrepreneurial and MSMEs, we discovered a crucial mediating mechanism in the relationship between them: market agility. Our findings suggest that the use of big data analytics enables MSMEs to enhance their market agility, thereby strengthening their innovation adoption. In addition, an MSME’s strong dynamic capability helps boost the effects of market agility on innovation adoption. While early success traps strengthen the effects of market agility on innovation adoption, they weaken the effects on innovation generation. Our study enriches the existing literature on big data analytics and innovation and provides practical guidance for MSMEs to engage in entrepreneurial innovation through big data analytics. [ABSTRACT FROM AUTHOR]

China's shared transportation industry is leading innovation, driving employment, and promoting regional economic growth. China's aggressive efforts to promote the development of various transportation sectors motivate our investigation of this emerging industry. We examine the influence of regional environmental factors on new venture formation using a dataset encompassing newly established bike-sharing startups in 257 cities in China from 2015 to 2019. The empirical results show that entrepreneurial capital, entrepreneurial support policies, and urban auxiliary infrastructure positively impact the formation of new ventures. However, no significant relationship exists between industrial policy, competitive urban infrastructure, and new business formation. This study expands the scope of the existing research studying the characteristics of entrepreneurial space, offers inspiration for future startups entering the field of shared transportation in choosing entrepreneurial locations, and provides theoretical guidance for the government in formulating policies to attract entrepreneurial activities. [ABSTRACT FROM AUTHOR]

The aggravation of environmental pollution and resource depletion has urged the international community to seek viable solutions. As the damage caused by the manufacturing industry is particularly destructive to the environment, finding an effective governance model is imperative. This study draws upon the organizational capability view to investigate the impact of circular economy practices (ecological design and investment recovery) on financial performance through environmental and innovation performance. Using structural equation modeling analyzing the data from 308 manufacturers in China by AMOS 21.0 software, we find that ecological design and investment recovery can directly enhance companies' performance. Also, environmental and innovation performances mediate the positive effects of circular economy practices on financial performance. Meanwhile, implementing ecological design contributes to investment recovery. Our study identifies the new path of circular economy practices in promoting financial performance through environmental and innovation improvement. The findings also guide managers to effectively implement ecological design and investment recovery to maximize company benefits. [ABSTRACT FROM AUTHOR]

The rapid development of digital technology and its ease of use has changed the competitive environment for traditional manufacturing. The study focuses on the central issues of the evolution of the digital transformation (DT) process. This paper proposes a theoretical framework of digital transformation in traditional manufacturing based on environment, people, organisation, and technology synergy. We chose a large textile company in China as a case to explore the process of DT practices in the traditional manufacturing industry. The results of the study showed that data accessibility has a positive impact on a strategic responsiveness during organisation’s DT, driven by data, information, knowledge and wisdom synergy. In the process of DT, the availability of information positively impacts the industry and the social well-being of an organisation. DT has a negative impact on individual willingness to share outlier knowledge and employee role perceptions. This study is both a complement to the deconstruction of the mechanism of DT in the manufacturing industry, and a new attempt to tap the laws of digital technology in the knowledge age. [ABSTRACT FROM AUTHOR]

Several prior studies have extensively covered human-computer interaction (HCI). These studies examine several factors related to HCI such as psychological, physiological, business and social factors or those related to such factors affecting HCI ([39]; [2]; [35]). For example, (1) [9] emphasized the need to unify HCI and AI, (2) Ramos I et al. i [35] discussed the qualities of effective HCI, [23] discussed exploration strategies of HCI and recently (5) [37] discussed emotions in HCI ([2]; [35]; [3]; [31]). This application can help HCI designers gain an understanding of HCI aspects to consider while designing user interfaces for other cultures and using the cultural context based on the cultural distance between the HCI designers and the target end-users. [Extracted from the article]

Purpose: The study explores the readiness of government agencies to adopt artificial intelligence (AI) to improve the efficiency of disaster relief operations (DRO). For understanding the behavior of state-level and national-level government agencies involved in DRO, this study grounds its theoretical arguments on the civic voluntarism model (CVM) and the unified theory of acceptance and use of technology (UTAUT). Design/methodology/approach: We collected the primary data for this study from government agencies involved in DRO in India. To test the proposed theoretical model, we administered an online survey questionnaire to 184 government agency employees. To test the hypotheses, we employed partial least squares structural equation modeling (PLS-SEM). Findings: Our findings confirm that resources (time, money and skills) significantly influence the behavioral intentions related to the adoption of AI tools for DRO. Additionally, we identified that the behavioral intentions positively translate into the actual adoption of AI tools. Research limitations/implications: Our study provides a unique viewpoint suited to understand the context of the adoption of AI in a governmental context. Companies often strive to invest in state-of-the-art technologies, but it is important to understand how government bodies involved in DRO strategize to adopt AI to improve efficiency. Originality/value: Our study offers a fresh perspective in understanding how the organizational culture and perspectives of government officials influence their inclinations to adopt AI for DRO. Additionally, it offers a multidimensional perspective by integrating the theoretical frameworks of CVM and UTAUT for a greater understanding of the adoption and deployment of AI tools with organizational culture and voluntariness as critical moderators. [ABSTRACT FROM AUTHOR]

Companies actively seek digital transformation to achieve sustainable development in a volatile and uncertain environment. This study investigates the effects of digital transformation (digital strategy and capability) on eco-innovation (eco-process, eco-product, and eco-management innovation) and sustainable performance. The partial least squares structural equation modeling is employed for assessing the model using data collected from 210 manufacturing companies in China. We find that digital strategy and digital capability significantly improve eco-process, eco-product and eco-management innovation. Eco-process, eco-product and eco-management innovation also improve sustainable performance. Meanwhile, eco-innovation partially mediates the positive relationship between digital transformation and sustainable performance. The results not only enrich the theoretical framework of digital transformation and sustainability but also provide guidelines for achieving sustainable development by implementing digital transformation and eco-innovation. [ABSTRACT FROM AUTHOR]

To achieve sustainable development and cope with growing socioenvironmental pressure, manufacturing companies are becoming increasingly committed to fulfilling their social responsibilities along the entire supply chain. However, it is still unclear whether fulfilling supply chain social responsibility can improve sustainable performance. On the basis of stakeholder theory and using structural equation modeling (SEM) and fuzzy set qualitative comparative analysis (fsQCA), this study explores the complex relationship between supply chain social responsibility and sustainable performance using data collected from 209 Chinese manufacturing companies. The SEM findings show that supply chain social responsibility can improve sustainable performance, while the fsQCA results suggest that the impact of supply chain social responsibility on sustainable performance depends on fulfillment methods. In particular, three supply chain social responsibility patterns can help achieve highly sustainable performance. However, these patterns significantly impact economic, environmental, and social performance in different ways. Our empirical study provides theoretical and practical guidance for companies to fulfill their supply chain social responsibilities. [ABSTRACT FROM AUTHOR]

The Fintech mobile payment platform is expanding rapidly; this expansion, in turn, creates numerous risks. There is an urgent need to better understand these risks and to spur more secure payment behavior. This research aims to develop knowledge graphs of the mobile payment platform based on deep learning for risk analysis and policy inferences. We identify entities from collected policy documents, extract the relationships among the entities, and draw a risk knowledge graph on mobile payments. The use of unsupervised semi-automatic knowledge acquisition, we argue, can reduce the risk of mobile payment caused by a lack of knowledge. A significant benefit of this method is that risk knowledge can be acquired without supervision. Unlike other models, the absence of manual labeling allows for the relation extraction of triples to be unsupervised, while the previous triplet extraction was supervised. Compared with other unsupervised models, the precision of our model is improved, and the recall is the same as that of previous unsupervised shutdown extraction. Unsupervised relationship extraction can extract text relationships quickly and on a large scale, saving human resources for labeling. This method offers a potential solution to a fundamental problem; the content and quantity of policy documents exceed organizations' and individuals' ability to understand them. Our approach suggests the viability of developing a national policy risk knowledge graph to help mobile payment platforms understand national policies and reduce platforms' operational risks while allowing users to quickly learn the risks of mobile payments and minimize the impact of those risks. [ABSTRACT FROM AUTHOR]