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Purpose: Since 2017, China's digital economy has accounted for more than 30% of the country's GDP. The digital economy has become the main driving force of China's economic development. Moreover, the digital economy has also changed the traditional modes of production and distribution between urban and rural areas. This paper aims to explore the influential mechanism of digital economy infrastructure (DEI) on the urban-rural income gap (URIG). Design/methodology/approach: By analyzing the theoretical model of the URIG, this paper constructs a theoretical analysis framework and clarifies the key roles of rural land circulation (RLC) and resident population urbanization (RPU) in the relationship between DEI and the URIG. Findings: The DEI can effectively reduce the URIG; the regression coefficient (RC) was −0.109. The reduction effect is mainly reflected in: 1) the wage income gap between urban and rural residents (RC = −0.128) and 2) the net property income gap of urban and rural residents (RC = −0.321). Also, for the spatial spillover effect, the path effect of "DEI – RLC – URIG" is almost equal to the path effect of "DEI – RPU – URIG"; for the local effect, the path effect of the former is far smaller than the latter. Moreover, when the RPU reaches the threshold of 86.29%, the DEI will expand the URIG (RC = 0.201). Originality/value: This paper proposes a theoretical framework for the impact of DEI on the URIG, explores the mechanism of RLC and RPU in the DEI and URIG and enriches the theory of traditional research on URIG. [ABSTRACT FROM AUTHOR]

Purpose: This study explores how to develop high-tech industries in Hunan province and enhance regional competitiveness. Through the comprehensive quantitative analysis of the development status of the high-tech industry in Hunan province, this paper provides a reference for the development of the high-tech industry in China and the world. Design/methodology/approach: This study constructs a comprehensive evaluation index system of regional competitiveness in Hunan province from the five dimensions of innovation, coordination, green, openness and sharing of the "new development concept." Through the screening and analysis of relevant economic indicators in Hunan province from 2011 to 2020, the principal component analysis method is used to measure the five development dimensions, verify the hypotheses in the study and finally draw the conclusion. Findings: Hunan's high-tech industry is positively correlated with Hunan's regional innovation development competitiveness, regional coordinated development competitiveness, regional green development competitiveness, regional open development competitiveness and regional shared development competitiveness. Among them, the promotion effect on innovation development is the best, followed by the promotion effect on green development, coordinated development and shared development dimension. In contrast, the promotion effect on the open development dimension is relatively weak. Research limitations/implications: The statistical data selected in this study have certain timeliness. At the same time, the current economic environment is affected by the new corona pneumonia epidemic, showing specific particularity. In this context, it is bound to cause changes in the impact of high-tech industries on regional competitiveness. In addition, this paper studies the regional competitiveness of Hunan's high-tech industry from a macro perspective. Although relevant studies are conducted from five dimensions, there is a lack of micro-level research. Social implications: From five aspects of the new development concept, this study provides suggestions for developing high-tech industries in Hunan province and even China and the path to enhance regional competitiveness. Originality/value: Up to now, no article measures regional competitiveness with the five development dimensions of new development: innovation, coordination, green, openness and sharing, and quantitatively analyses regional competitiveness on this basis. [ABSTRACT FROM AUTHOR]

Purpose: Accurate foreign tourist arrivals forecasting can help public and private sectors to formulate scientific tourism planning and improve the allocation efficiency of tourism resources. This paper aims to address the problem of low prediction accuracy of Chinese inbound tourism demand caused by the lack of valid historical data. Design/methodology/approach: A novel hybrid Chinese inbound tourism demand forecasting model combining fractional non-homogenous discrete grey model and firefly algorithm is constructed. In the proposed model, all adjustable parameters of the fractional non-homogenous discrete grey model are optimized simultaneously by the firefly algorithm. Findings: The data sets of annual foreign tourist arrivals to China are used to verify the validity of the proposed model. Experimental results show that the proposed method is effective and can be used as a useful predictor for the prediction of Chinese inbound tourism demand. Originality/value: The method proposed in this paper is effective and can be used as a feasible approach for forecasting the development trend of Chinese inbound tourism. [ABSTRACT FROM AUTHOR]

Purpose: Bike-sharing is popular worldwide, and it has led to a new development direction in green transportation. However, the collapse of many bike-sharing startups and residual social problems has brought about contradictions and challenges to the development of the industry. The purpose of this paper is to determine how internal factors affect the survival of bike-sharing startups. Design/methodology/approach: The authors used binary logit regression as the measurement model to conduct an empirical analysis based on 137 bike-sharing startups in China. The study focuses on using traditional theoretical evidence and considers the uniqueness of the industry to jointly explore the survival factors that influence the emerging business model of bike-sharing. Findings: The results show that entrepreneurial team size and differentiation strategy positively influence survival. Founder-CEOs have a negative impact on survival. Founders' entrepreneurial experience and venture capital have no significant influence on survival. Originality/value: The results verify the role of traditional survival factors in the new business model of sharing economy and fill the research gap on the survival strategy of startups. This study offers a unique perspective for researchers to better understand the sharing economy industry and provides practical guidance for entrepreneurs and investors to enter the market. [ABSTRACT FROM AUTHOR]

Purpose: The existing three-stage network Data Envelopment Analysis (DEA) models with shared input are self-assessment model that are prone to extreme efficiency scores in pursuit of decision-making units (DMUs) efficiency maximization. This study aims to solve the sorting failure problem of the three-stage network DEA model with shared input and applies the proposed model to evaluate innovation resource allocation efficiency of Chinese industrial enterprises. Design/methodology/approach: A three-stage network cross-DEA model considering shared input is proposed by incorporating the cross-efficiency model into the three-stage network DEA model. An application of the proposed model in the innovation resource allocation of industrial enterprise is implemented in 30 provinces of China during 2015–2019. Findings: The efficiency of DMU would be overestimated if the decision-maker preference is overlooked. Moreover, the innovation resource allocation performance of Chinese industrial enterprises had a different spatial distribution, with high in eastern and central China and low in western China. Eastern China was good at knowledge production and technology development but not good at commercial transformation. Northeast China performed well in technology development and commercial conversion but not in knowledge production. The central China did not perform well in terms of technology development. Originality/value: A three-stage network DEA model with shared input is proposed for the first time, which makes up for the problem of sorting failure of the general three-stage network model. [ABSTRACT FROM AUTHOR]

Purpose: China has emerged as the world's second-largest economy due to rapid industrial expansion and phenomenal economic growth of China in recent decades. Though, this exponential economic turnaround has been fueled by widespread energy consumption, making China among the largest pollutant emitters in the world. Chinese enterprises have come under greater scrutiny and the Government has mandated Chinese companies to undertake environmental protection investment. This study aims to explore the relationship between environmental protection investment and enterprise innovation by taking evidence from Chinese listed firms. Design/methodology/approach: The data of 2,568 Chinese A-share listed firm-year observations were collected from the Shanghai and Shenzhen stock exchanges during 2008–2016. This study employed ordinary least square and panel data fixed effects techniques to ascertain the association between proposed variables. Findings: The authors' findings conjecture the crowding-out effects of environmental investments on enterprise innovation-related expenditures. Furthermore, additional empirical testing reveals that Research and Development (R&D) undertakings of state-owned and politically connected enterprises are not affected by environmental investments. Likewise, corporate innovation activities are not negatively influenced by environmental investments in polluting industries. The study findings offer fresh insights to regulators, corporate managers and stakeholders. The authors' results are robust to alternate econometric specifications and alternate variable specifications. Originality/value: This study makes the following contributions toward the extant literature. First, the study investigates if there is a crowding-out effect of spending on environmental protection in the current period and the innovation expenditure in the upcoming period. Empirical results confirm that there exists a trade-off between both types of spending, implying that the spending on environmental protection will negatively influence the spending on innovation. Second, the study deepens the analysis in considering other influences in this relationship. For instance, the authors' separately consider the aforementioned trade-off in state-owned enterprises and non-state-owned enterprises. The study also examines the mediating influence of corporate political connections and industry attributes, whether or not these influence the relationship between the actual spending on environmental protection and the upcoming spending on innovation. [ABSTRACT FROM AUTHOR]