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This study aims to theoretically hypothesize and empirically examine the impact of economic policy uncertainty (EPU) on firms' innovation performance as well as the contingency conditions of this relationship.

This study collects and combines secondary longitudinal data from multiple sources to test for a direct impact of EPU on firms' innovation performance. It further examines the moderating effects of firms' operational and marketing capabilities. A series of robustness checks are performed to ensure the consistency of the findings.

In contrast to the common belief that EPU reduces the innovativeness of firms, the authors find an inverted-U relationship between EPU and innovation performance, indicating that a moderate level of EPU actually promotes innovation. Further analysis suggests that firms' operational and marketing capabilities make the inverted-U relationship steeper, further enhancing firms' innovation performance at a moderate level of EPU.

This study adds to the emerging literature that investigates the operational implications of EPU, which enhances our understanding of the potential bright side of EPU and broadens the scope of operational risk management.

The purpose of this study is to empirically investigate the relationship between executive shareholding, institutional investor shareholding and corporate innovation, and to further explore in depth the impact of executive shareholding on corporate innovation under different industries.

This paper uses the panel data of A-share listed companies in Shanghai and Shenzhen from 2012 to 2020 as the research sample to empirically study the relationship between executive shareholding, institutional investor shareholding and corporate innovation based on multiple linear regression models and panel fixed effects.

The research shows that: on the whole, the impact of executive shareholding on enterprise innovation presents an inverted “U” shape; institutional investors will negatively regulate the impact of executive shareholding on enterprise innovation; the impact of executive shareholding on enterprise innovation will show obvious industry differences in different industries.

The empirical results not only enrich the research on the effects of institutional investors' involvement in corporate governance practice, but also provide targeted experience for promoting enterprise innovation. Due to the limitations of innovation indicators and industry sample selection, it is necessary to be cautious when extending the results to other fields.

Enterprises should fully consider the impact of executive shareholding on innovation and formulate a scientific executive incentive system according to the differences of their industries. The government should be aware of the important role of institutional investors in enterprises, improve the channels and ways for institutional investors to participate in corporate governance, and improve the basic system of capital markets.

On the one hand, this paper empirically tests the regulatory role of institutional investors' shareholding and the relationship between executive shareholding and enterprise innovation, which enriches the research on the effect of institutional investors' involvement in corporate governance practice. On the other hand, the research by industry is more targeted to provide experience for promoting enterprise innovation.

The absence of government intervention and market supervision cannot effectively promote green process innovation in manufacturing industries. As a new government regulation approach, environmental taxes provide a platform to internalize the externality of environmental pollution. This paper empirically investigates the impact of environmental taxes on green process innovation and the moderating effects of industry pollution heterogeneity and green credit.

This research collects manufacturing industry data ranging from 2008 to 2020, resulting in a total of 351 observations. Time-individual, two-way fixed effect models are constructed to examine the hypotheses.

The results indicate environmental taxes have an inverted-U effect on green process innovation in manufacturing industries. Implementation intensity of the current environmental taxes on China's manufacturing industries does not reach an inflection point. Further analysis suggests that environmental taxes exert influence on the inverted-U relationship with low-pollution industries displaying a steeper curvilinear pattern than high-pollution industries. Moreover, the analysis shows that green credit plays a moderating role in the inverted-U relationship, as low green credit provides more limited stimulus than high green credit in terms of the effect of environmental taxes on green process innovation.

This study offers empirical evidence to accommodate negative externalities of corporate production and provides new perspectives in nudging corporate green-process innovation.

This paper verifies the effect of environmental taxes on green process innovation amid industry pollution heterogeneity by introducing an industrial-level analysis unit. This study improves the means by which environmental taxes are measured. Existing literature has narrowly used pollution discharge fees as a proxy for environmental taxes. The authors have summed up the taxes on vehicle and vessels, urban land use, urban maintenance and construction, vehicle purchases, waste gas, wastewater and solid waste to measure the effect of environmental taxes in this study.

The purpose of this paper is to have a deeper understanding of the nonlinear relationship between the impact of climate change on tourism development. Current studies on the effects of climate change on tourism development primarily rely on linear correlation assumptions.

Based on the New Institutional Economics theory, the institutional setting inherently motivates and ensures the growth of the tourism industry. For a precise evaluation of the nonlinear consequences of climate change on tourism, this paper concentrates on Chinese cities between 2011 and 2021, methodically analyzing the influence of climate change on tourism.

The study findings suggest that there is an “inverse U”-shaped nonlinear relationship between climate change and tourism development, initially strengthening and subsequently weakening. Based on these findings, the research further delves into how institutional contexts shape the nonlinear association between climate change and tourism growth. It was found that in a higher institutional backdrop, the “inverse U” curve tends to flatten and surpass the curve adjusted for a lesser institutional context. Upon deeper mechanism analysis, it was observed that cities with more advanced marketization, improved industrial restructuring and enhanced educational growth exhibit a more evident “inverse U”-shaped nonlinear connection between climate change and tourism evolution.

First, previous studies on climate change and tourism development largely rely on questionnaire data (Hu et al., 2022). In contrast to these studies, this paper uses dynamic panel data, which to some extent overcomes the subjectivity and difficulty of causality identification in questionnaire data, making our research conclusions more accurate and reliable. Second, this study breaks through the linear relationship hypothesis of previous literature regarding climate change and tourism development. By evaluating the nonlinear relationship of climate change to tourism development from the institutional pressure perspective, it more intricately delineates their interplay mechanism, expanding and supplementing the research literature on the relationship mechanism between climate change and tourism development. Thirdly, the conclusions of this study are beneficial for policymakers to better understand and assess the scope of climate change impacts. It also aids relevant departments in clarifying the direction of institutional environment optimization to elevate the level of tourism development when faced with adverse impacts brought about by climate change.

The purpose of our study is to investigate how a manufacturing plant’s internal operations along with its network of connections (upstream and downstream) can have an impact on its recovery time from a disruption. The authors also examine the inverse-U impact of complexity. Finally, the authors test the moderating role that business continuity management plans (BCP) at the plant level have on recovery time.

To test our hypotheses, the authors partnered with Resilinc Corporation, a Silicon Valley-based provider of supply chain risk management solutions to identify focal firms’ suppliers, customers and plant-level data including information on parts, manufacturing activities, bill of materials, alternate sites and formal business continuity plans. The authors employed censored data regression technique (Tobit).

Several important findings reveal that the plant’s internal operations and network connections impact recovery time. Specifically, the number of parts manufactured at the plant as well as the number of internal plant processes significantly increase disruption recovery time. In addition, the number of supply chains (upstream and downstream) involving the plant as well as the echelon distance of the plant from its original equipment manufacturer significantly increase recovery time. The authors also find that there exists an inverted-U relationship between complexity and recovery time. Finally, the authors find partial support that BCP will have a negative moderating effect between complexity and recovery time.

This research highlights gaps in the literature related to supply chain disruption and recovery. There is a need for more accurate methods to measure recovery time, more research on recovery at the supply chain site level and further analysis of the impact of supply chain complexity on recovery time.

Several empirical studies indicate that the existence of a large informal sector is a major obstacle to firms’ choices of innovation strategies. This paper aims to address this issue and investigates the effect of the informal sector on the innovation of formal firms in Greece.

Using the World Bank’s Enterprise Survey data, the impact of informal competition on formal firms’ innovation in Greece is investigated by testing whether formal firms use innovation as a tool to protect and sustain their competitive advantage vis-à-vis informal firms and whether overall and informal competition has an inverted-U relationship with the innovation of formal firms. The effects of bribing and other variables drawn from the empirical literature are also controlled for.

The findings fill a gap in the literature regarding the effects of the informal sector on formal economic activity in Greece, by indicating that the informal sector puts pressure on formal firms to innovate, in order to differentiate their product or service and enhance their productivity and by offering learnings to help policymakers to promote innovation in Greece.

The originality of this study is that it investigates the impact of informal competition on formal firms’ innovation in Greece, a developed economy with a large informal sector. It does so by focusing on the effects that formal firms’ informal practices have on their competitors’ innovation activities, and the role of informal competition in creating and sustaining a competitive advantage in Greece.

With the development of regional economy, innovation network plays an increasingly prominent role in reducing regional innovation cost and enabling information, knowledge and capital flow and diffusion. Building an efficient innovation network has become a feasible way to improve regional innovation capabilities and performance. Thus, under the background of Chinese special triple helix structure, the specific mechanism of innovation network characteristics on regional innovation performance is still an issue that needs to be studied urgently.

This study conducts a multi-level regression analysis regional innovation panel data of China from the past four years to explore how the three dimensions of innovation network characteristics (i.e. network density, openness and strength) affect regional innovation performance.

The results show that there is an inverted-U relationship exists between network density and regional innovation performance. The network openness and regional innovation performance show a significantly positive relationship and a U-shaped relationship exists between network strength and regional innovation performance.

First, this study examines the relationship between network density, openness, strength and innovation ability in the network variable structure. However, this study does not analyze how absorptive capacity impacts the network structure and innovation performance of regional innovators. Second, innovation network intensity largely varies according to different types of enterprises or industries. Therefore, future studies can attempt to analyze the relationship between innovation network and innovation performance on the basis of the industry or the enterprise itself. Fourth, this study does not consider the change in the influence of innovation network structure on innovation ability.

The results of this study provide insights for the formulation of the regional innovation policy. First, enterprises must maintain good contact with research institutes, universities and technology intermediaries and promote resource, information and money flow between networks through formal and informal interactions. Enterprises can currently only interact with a limited number of innovative subjects due to their limited resources. Therefore, we should continue implementing the open policy of foreign capital utilization and absorb the technology, knowledge, management, ideas, talent and other resource advantages in the world. The investment environment in the central and western regions should be improved as soon as possible to guide foreign direct investments to the middle and the west part of China, thereby promoting the coordinated development of regional innovation ability and economy.

In 2015, the Chinese Government proposed “public entrepreneurship and innovation,” including technological, institutional, management and mode innovations. This study suggests that innovation subjects in the region should establish an interactive and dynamic innovation network among innovators.

The innovation of this study lies in the analysis of the characteristics of innovation network that significantly affect regional innovation performance, the exploration of different stages of innovation network construction path and provide theoretical guidance for the construction of innovation network.

Product presentation plays a critical role in influencing consumers’ purchasing decisions in online shopping. The purpose of this study is to examine the effects of text-image information on online product presentation pages on sales. This study also specifically explores the moderating role of celebrity endorsements in the relationship between text-image presentation information and sales.

This study is based on regression analysis using data sets from the largest online book retailer in China, Dangdang.com.

The results of this study show that there is an inverse U-shaped relationship between word count and book sales. Conversely, image quantity has a positive linear effect on book sales. Furthermore, celebrity endorsements moderate the relationship between word count and sales in two distinct ways. First, the positive effect of increasing word count from low to medium is enlarged by increasing the number of celebrity endorsers. Second, the turning point of the inverse-U relationship between word count and sales rank moves to the right as the number of endorsers increases.

To the best of the authors’ knowledge, this study is among the first to examine the effects of text-image quantity on sales across the full continuum. This study adds understanding on how information load might have distinct consequences on the processing performance of text and images. Furthermore, this study investigates how sales are impacted by the quantity of celebrity endorsers in relation to textual and pictorial information in online shopping contexts, extending our knowledge of the effectiveness of celebrity endorsements.

Although previous research has recognized the pivotal role of mobile social media in knowledge sharing among project members, little is known about what factors affect knowledge sharing in mobile social media groups (MSMGs). Against this background, using normative social influence theory, this study attempts to explore factors influencing knowledge sharing in MSMGs.

Data from 205 Chinese construction project members are collected and used for analysis. Ordinary least squares regression by Stata 16 is used to test the proposed hypotheses.

Concerning role norms, gender difference in knowledge sharing behavior (KSB) is found, while it is not the case for knowledge quality (KQ). Work experience is found to positively affect KQ, but shows no influence on KSB. As for group norms, the inverted-U relationship between number of members and KSB is partially supported. In addition, organizational norms generally exhibit the greatest influence on both KSB and KQ among the three forms of norms.

This study deepens the understanding of knowledge sharing factors in mobile social media environments and affords practical implications for how to make full use of social media for knowledge management within construction project teams.

The existence of the regional Kuznets curve, i.e. an inverted U-shaped relationship between regional disparity and economic development is widely debated and discussed. The bell-shaped curve of the spatial growth process where during the initial phase inequality increases and then reduces is theoretically supported by Myrdal (1957), Hirschman (1958), and Williamson (1965). It becomes important to understand regional Kuznets curve globally. Understanding the relationship between regional disparity and economic development becomes essential for public policy for balanced regional growth.

Regional Kuznets Curve which is an inverted U-shaped relationship between regional disparity and economic development is not a new phenomenon. Theoretical framework by Myrdal (1957), Hirschman (1958), and Williamson (1965) support the an inverted U-shaped relationship. To understand the relationship between regional disparity and economic development, the authors investigate the regional Kuznets curve by using data for 184 countries and 1765 subnational regions. Using parametric, semi-parametric, and non-parametric, it is found that there exists an inverted U-shaped relationship between regional disparity and economic development. The presence of the regional Kuznets curve is observed. As the theoretical framework suggests, regional inequality increases with income initially and decreases after attaining a certain level of income. This study identifies two stages of divergence-convergence where in the first stage, divergence across regions in a country happens with increasing income and in the later stage, convergence across regions in a country occurs with increasing income.

Using the parametric approach (panel data analysis), semi-parametric and non-parametric approaches, it is found that there exists a regional Kuznets curve. It is found that there exists an inverted-U relationship between regional inequality and per capita GNI. This suggests that the divergence-convergence passes through two stages. In the first stage, divergence across regions in a country happens with increasing income while in the later stage convergence occurs.

This research work has done three important things which fill the research gap that exists in the literature: (1) constructing the Gini coefficient to measure the regional inequality for 184 countries using 1765 subnational regional data; (2) using a parametric approach (panel data analysis) to understand the regional Kuznets phenomenon and (3) using a semi-parametric approach and non-parametric approach to understand the regional Kuznets phenomenon.