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The digital economy has become a key force supporting the high-quality development of tourism. This paper discusses the coupling coordination relationship and spatiotemporal evolution path of digital economy and tourism in China's provinces.

This paper uses the entropy method to measure the development level of digital economy and tourism, and establishes coupling coordination model and spatial autocorrelation model to study the interaction between the two industries.

Results show that the development levels of the two industries are rising, which spatially show a progressively decreasing pattern of east-middle-northeast-west. The coupling coordination degrees of the two industries have increased steadily, but the overall level is still near maladjusted. Spatially, the positive correlation is increasing, but the incongruity of spatial agglomeration is still significant. The coupling coordination evolution path in the provinces shows differentiated characteristics. The migration path is mainly concentrated in Zones I and II. The eastern region has an obvious trend of extending to Zone III, where the tourism industry was the most affected by the pandemic.

The study helps clarify the industrial coupling and coordination relationship in various regions and formulate regional tourism digital transformation strategies to promote the high-quality development of China's tourism industry.

This paper enriches the research on the relationship between digital economy and tourism from the perspective of industrial integration. The development commonality of China's tourism digital transformation summarized provides theoretical reference and demonstration for the coordinated development of China's tourism.

The paper argues that the classical Marxist theory of capitalist accumulation is inadequate to understand new forms of capitalism and their accumulation processes determined by “platforms” and “big data”. Big data platforms are shaping the processes of production, labour, the price of products and market conditions. “Digital platforms” and “big data” have become an integral part of the processes of production, distribution and exchange relations. These twin pillars are central to the capitalist accumulation processes. The article argues that the classical Marxist theory of capitalist accumulation is inadequate to understand new forms of capitalism and their accumulation processes determined by “platforms” and “big data”.

As a conceptual paper, this paper follows critical methodological lineages and traditions based on non-linear historical narratives around the conceptualisation, construction and transition of the “Marxist theory of capital accumulation” in the age of platform economy. This paper follows a discourse analysis (Fairclough, 2003) to locate the way in which an artificial intelligence (AI)-led platform economy helps identify and conceptualise new forms of capitalist accumulation. It engages with Jørgensen and Phillips' (2002) contextual and empirical discursive traditions to undertake a qualitative comparative analysis by exploring a broad range of complex factors with case studies and examples from leading firms within the platform economy. Finally, it adopts two steps of “Theory Synthesis and Theory Adaptation” as outlined by Jaakkola (2020) to synthesise, adopt and expand the Marxist theory of capital accumulation under platform capitalism.

This article identifies new trends and forms of data driven capitalist accumulation processes within the platform capitalism. The findings suggest that an AI led platform economy creates new forms of capitalist accumulation. The article helps to develop theoretical understanding and conceptual frameworks to understand and explain these new forms of capital accumulation.

This study builds upon the limited theorisation on the AI and new capitalist accumulation processes. This article identifies new trends and forms of data driven capitalist accumulation processes within platform capitalism. The article helps to understand digital and platform capitalisms in the lens of digital labour and expands the theory of capitalist accumulation and its new forms in the age of datafication. While critiquing the Marxist theory of capitalist accumulation, the article offers alternative approaches for the future.

Social entrepreneurship (SE) is a complex phenomenon designed to resolve numerous societal challenges while remaining economically viable. However, how social entrepreneurs in developing countries have deployed digital technologies to address communal challenges during the Covid-19 crisis is largely undocumented. This research examines social entrepreneurs' adoption of digital technologies, the multi-level organisational conditions, and associated innovative outcomes of engaging digital technologies.

Based on the organisational resilience theoretical framework, this research employs a qualitative methodology, comprising 38 semi-structured interviews with Nigerian SE firms, to investigate social entrepreneurs' engagement with digital technologies.

The study’s findings reveal 19 pathways through which digital technologies enabled organisational resilience outcomes by Nigerian SE firms during the Covid-19 pandemic. This allows the authors to show, via a 3 × 3 matrix, how social entrepreneurs deploy digital technologies to build proximate, dynamic, and continuous resilience in a weak institutional context.

The study’s findings enables the authors to advance the SE – digital technologies – resilience scholarship in a developing economy.

Within the current institutional landscape, characterized by increased societal and governmental emphasis on environmental preservation, there is growing interest in the potential of digital transformation (DT) to advance the circular economy (CE). Nonetheless, the empirical substantiation of the connection between DT and CE remains limited. This study seeks to investigate the impact of DT on CE at the organizational level and examine how various institutional factors may shape this relationship within the Chinese context.

To scrutinize this association, we construct a research framework and formulate hypotheses drawing on institutional theory, obtaining panel data from 238 Chinese-listed high-tech manufacturing firms from 2006 to 2019. A regression analysis approach is adopted for the sample data.

Our regression analysis reveals a positive influence of DT on CE performance at the organizational level. Furthermore, our findings suggest that the strength of this relationship is bolstered in the presence of heightened regional institutional development and industry competition. Notably, we find no discernible effect of a firm’s political connections on the DT–CE performance nexus.

This study furnishes empirical evidence on the relationship between DT and CE performance. By elucidating the determinants of this relationship within the distinct context of Chinese institutions, our research offers theoretical and practical insights, thus laying the groundwork for subsequent investigations into this burgeoning area of inquiry.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

Digital transformation is essential for commercial banks to maintain long-term competitiveness in the digital economy era. This study aims to investigate the relationship between inside debt and the bank's digital transformation.

This study set up a quasi-natural experiment based on implementing the executive compensation deferral system in the Chinese banking industry. Using the annual panel data of 180 commercial banks in China from 2007 to 2021, this study employed the difference-in-differences (DID) method to conduct an empirical analysis.

This study confirms a significant statistical relationship between inside debt and the bank's digital transformation, and managerial myopia is the transmission channel of inside debt affecting the bank's digital transformation. Furthermore, the development of Internet finance and the enhancement of bankers' confidence will improve the contributions of inside debt to the bank's digital transformation.

This study contributes to the literature on inside debt and the bank's digital transformation. It has specific policy value for the scientific design of the banking compensation mechanism and accelerating banks' digital transformation.

Corporate digital transformation (CDT) has challenged traditional tax administration systems. This study examines the impact of CDT on tax avoidance behavior and tests whether tax authorities can identify this behavior.

Using data on listed companies on the Shanghai and Shenzhen Stock Exchanges from 2008 to 2020, this study applies the Heckman two-stage and cross-section models.

The results show that the higher the degree of CDT, the more aggressive the tax avoidance behavior. The CDT's impact on corporate tax avoidance is more significant under strong government tax efforts.

This study expands research on the economic consequences of CDT and the factors influencing corporate tax avoidance behavior. Moreover, it has important implications for governments to monitor tax avoidance behavior under the CDT, improve digital tax systems, and pay more attention to the tax administration of digital assets.

The purpose of this study is to investigate whether the corporate environmental, social and governance (ESG) performance of enterprise is influenced by the enterprise digital transformation. In addition, this study explains how enterprise digital transformation affects ESG performance.

The sample covers 4,646 nonfinancial companies listed on China’s A-share market from 2009 to 2021. The study adopts the fixed-effects multiple linear regression to perform the data analysis.

The study finds that enterprise digital transformation has a significant inverted U-shaped impact on ESG performance. Moderate digital transformation can improve enterprise ESG performance, whereas excessive digital transformation will bring new organizational conflicts and increase enterprise costs, which is detrimental to ESG performance. This inverted U-shaped effect is more pronounced in industrial cities, manufacturing industries and enterprises with less financing constraints and executives with financial backgrounds. Enterprise digital transformation mainly affects ESG performance by affecting the level of internal information communication and disclosure, the level of internal control and the principal-agent cost.

The government should take multiple measures to encourage enterprises to choose appropriate digital transformation based on their own production behaviors and development strategies, encourage them to innovate and upgrade their organizational management and development models in conjunction with digital transformation and guide them to use digital technology to improve ESG performance.

This study shows that irrational digital transformation cannot effectively improve the ESG performance of enterprises and promote the sustainable development of the country. Enterprises should carry out reasonable digital transformation according to their own development needs and finally improve the green and sustainable development ability of enterprises and promote the sustainable development of society.

This study examines the relationship between enterprise digital transformation and ESG performance. Different from the linear relationship between the two in previous major studies, this study proves the inverse U-shaped relationship between enterprise digital transformation and ESG performance through mathematical theoretical model derivation and empirical test. This study also explores in detail how corporate digital transformation affects ESG performance, as well as discusses heterogeneity at the city, industry and firm levels. It is proposed that enterprises should take into account their own characteristics and carry out reasonable digital transformation according to their development needs.

Urban digital transformation has become a key strategy in global countries. This study aims to provide a comprehensive and dynamic exploration of the intrinsic traits associated with urban digital transformation, in order to yield detailed insights that can contribute to the formulation of well-informed decisions and strategies in the field of urban development initiatives.

Through analysis of parallels between urban digital transformation and gyroscope motion in physics, the study developed the urban digital transformation gyroscope model (UDTGM), which comprises of seven core elements. With the balanced panel dataset from 268 cities at and above the prefecture level in China, we validate the dynamic mechanism of this model.

The findings of this study underscore that the collaboration among infrastructure development, knowledge-driven forces and economic operations markedly bolsters the urban digital transformation gyroscope’s efficacy.

This research introduces a groundbreaking framework for comprehending urban digital transformation, potentially facilitating its balanced and systemic practical implementation.

This study pioneers the UDTGM theoretically and verifies the dynamic mechanism of this model with real data.