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By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the sustainable practices implemented in these developed regions, and derive valuable insights that can foster the promotion of green transformation.

First, the urban green development system (GDS) was decomposed into the economic benefit subsystem (EBS), social benefit subsystem (SBS), and pollution control subsystem (PCS). Then, a mixed network SBM model was proposed to evaluate the GDE during 20152020, with Moran’s I and Bootstrap truncated regression model subsequently applied to measure the spatial characteristics and driving factors of efficiency.

Subsystem efficiency presents a distribution trend of PCS > EBS > SBS. There is a particular spatial aggregation effect in EBS efficiency, whereas SBS and PCS efficiencies have no significant spatial autocorrelation. Furthermore, urbanization level contributes significantly to the efficiency of all subsystems; industrial structure, energy consumption, and technological innovation play a crucial role in EBS and SBS; external openness is a pivotal factor in SBS; and environmental regulation has a significant effect on PCS.

This study further decomposes the black box of GDS into subsystems including the economy, society, and environment. Additionally, by employing a mixed network SBM model and Bootstrap truncated regression model to investigate efficiency and its driving factors from the subsystem perspective, it endeavors to derive more detailed research conclusions and policy implications.

This paper attempts to study the relationship between the level of urban innovation and subjective well-being (SWB). The following questions are discussed: (1) Does improving the level of innovation in cities affect the SWB of residents? (2) If urban innovation levels affect residents' SWB, can improving urban innovation level improve residents' SWB? (2) If urban innovation level improves residents' SWB, what is the possible mechanism? (3) Is there any difference in the effect of urban innovation level on the SWB of different groups?

This paper chooses the ordinary least squares (OLS) regression method for baseline regression with robust standard errors, and the regression results of Oprobit will be presented in detail in the robustness test section. The model is constructed by matching the micro data and the macro data. Meanwhile, the instrumental variable (IV) method is also used to deal with the possible endogeneity problem.

This paper finds that urban innovation has significantly improved the SWB of residents. This finding still holds after considering the endogeneity issue and conducting a series of robustness tests. Moreover, the level of innovation positively influences residents' SWB mainly through the paths of increasing income levels, improving environmental quality and promoting convenience in life. What's more, urban innovation has a more significant effect on the SWB of low-income groups and those with low education levels. Finally, based on the findings, this paper also proposes some policy recommendations to further improve the SWB of residents.

Given the limitations of the data, the above study deals with China. In the future, international data can be further used to further explore the impact of the innovation level of international cities on the SWB of residents and then the research conclusions can be applied to the international community to provide theoretical basis and empirical support for policy makers of various countries, which will help improve the SWB of residents of various countries and enrich the theoretical and empirical research on the impact of innovation on the SWB of residents.

Well-being is a goal constantly pursued by human beings. This paper shows that urban innovation has significantly improved the SWB of residents. The findings provide guides to improve the SWB of residents and provide a certain theoretical basis and empirical reference for policy makers.

The possible innovations or contributions of this paper include: (1) based on the China Household Income Survey (CHIP) and the “Report on Innovation of Chinese Cities and Industries”, this paper studies the impact of urban innovation levels on residents' SWB, supplementing the gaps in existing literature; (2) through group analysis, the heterogeneity of the impact of urban innovation level on groups with different incomes and education levels was discussed and (3) the mechanism of urban innovation level on residents' SWB was identified. These studies and discussions provide a basis for more effective improvement of residents' SWB and provide a valuable reference for promoting people's pursuit of a better life.

The main purpose of this paper is to explore the impact of digital transformation on enterprises' performance considering financing constraints in the capital market to explore whether digital transformation improves enterprises' performance through the financing constraints channel.

This study, using a panel data set of 14,669 observations of 2,858 non-financial enterprises that issued A shares on the Shanghai and Shenzhen stock exchanges from 2013 to 2019, theoretically and empirically tests the impact and mechanism of digital transformation on enterprise performance.

Digital transformation has a significant positive effect on enterprise performance; this conclusion remains the same after the robustness test and endogeneity problems are dealt with. Financing constraints play a mediation role between digital transformation and enterprise innovation. The effect of digital transformation on enterprise performance varies significantly by size, ownership and industry.

The theoretical contributions of this study not only enrich the literature on the economic benefits and mechanism of digital transformation but also expand the literature on the factors that influence enterprise performance. The practical contribution of this study is the reference that it provides for implementing decisions about enterprise digital transformation and formulating differentiated policies for government digital transformation.

In recent years, Yoga practice has seen a rapid rise in popularity with many positive consequences, both physical and mental attributed to its practice. Ashtanga Yoga has been less well researched in this area and is the specific focus on this work. The aim of this study is to investigate the possible positive impact of long-term Ashtanga Yoga on psychological well-being.

In total, 213 long-term Ashtanga Yoga practitioners were asked to complete the positive emotion, engagement, relationships, meaning, accomplishment (PERMA) 23 scale (Butler and Kern, 2016) which measures psychological well-being. The values given by these individuals were then compared against a larger sample of 31,966 representative of the general population.

Scores were then compared with a PERMA data set representative of the general population (see Butler and Kern, 2016), primarily using a test of difference to compare samples. Secondly, the causal relationship between time spent in practice upon well-being scores.

Findings indicated that those individuals engaged in long-term Ashtanga Yoga practice significantly outperformed the control group on all dimensions of psychological well-being.

This work has demonstrated specific benefits to the practice of Ashtanga Yoga on psychological well-being. Yoga is a form of exercise that is now widely available across the globe, and as such, represents an accessible form of physical practice, which has important psychological benefits.

To the authors’ knowledge, this is the first work investigating differences in psychological well-being profiles using PERMA, as a function of Yoga practice.

The purpose of this paper is to determine the most efficient hotels in the Indian hotel industry, the competitive positioning of these hotels, and the factors that affect their efficiency change.

This study conducts a two-stage analysis and uses data envelopment analysis (DEA) and Global Malmquist productivity index (MPI) approach in the first stage to calculate the managerial performance of a panel of 63 Indian hotels in 2019–2020 and their efficiency change from 2009–2010 to 2019–2020. Bootstrapped generalized least square (GLS) approach is applied in the second stage to evaluate the impact of contextual variables on efficiency change.

Using the results of the first stage analysis, the authors categorized the 63 Indian hotels into 7 distinct clusters. These clusters represent different levels of competitiveness and pace of growth. The GLS regression reveals a U-shaped relationship between hotel size and efficiency change and a negative relationship between pro social investments and efficiency.

This is the first study in the hotel industry that has used global MPI as a measure of efficiency change in the first stage and GLS in the second stage. In the Indian context, to the best of authors’ knowledge, no such study exists.

Previous studies on social influence and virtual product adoption have mainly taken users’ purchase behavior as a dichotomous variable (i.e. purchasing or not). Given the prevalence of competing versions (basic vs upgraded) of a virtual product in online communities, this paper investigated the differences in the effect of social influence on users’ adoption of basic and upgraded choices of a virtual product. It also examined how the effect varies with users’ social status and user-level network density.

A natural experiment was conducted in an online game community. Two competing versions (basic vs upgraded) of a virtual product were provided for in-game purchase while a random set of users selected from 897,765 players received the notification of their friends’ adoption information. A competing-risk model was used to test the hypotheses.

Social influence exerts a stronger positive effect on users’ adoption of the upgraded virtual product than of the basic virtual product. Middle-status users have the greatest (least) susceptibility to social influence in adopting the upgraded (basic) virtual product than low- and high-status users. User’s network density enhances the effect of social influence on adoption of both virtual products, even more for the upgraded one.

This research contributes to the social influence and product adoption literature by disentangling the different effects of social influence on basic and upgraded versions of a virtual product. It also identifies the boundary conditions that social influence works for each version of the virtual product.

This paper aims to assess whether incubation affects the technical efficiency of innovative firms after entering the market. The study of efficiency allows firms to understand how well resources have been used in production processes. The research intends to contribute to the literature on the performance of incubated firms.

This study estimates the relative efficiency of innovative firms adopting a DEA-based two-stage semi-parametric method. Incubation, firm age and initial capital are used for explaining the relative performance of previously incubated firms compared to non-incubated ones over a six-year period of activity. This research focuses on Italian innovative firms using a large sample of companies.

Results show that incubators have a positive and significant effect on efficiency for firms that have been in the market for more than two years. Efficiency also improves with age and with the level of initial capital of the firm.

This analysis is limited to the quantitative dimension of inputs as reported in the balance sheets, without qualitative considerations.

Findings enhance firms' understanding of the role of incubators as neutral places to develop a business culture of efficiency. From an empirical standpoint, this study provides useful insights to start-uppers who intend to attend incubation programs. Overall, incubators matter to the extent that they enable new firms, net of those that fail to survive in the first two years of activity, to improve their efficiency in the use of inputs. This research also suggests incubators consider the start-ups’ potential of being efficient.

Findings provide tips to policymakers when they are called upon to propose funding programs to support prominent firms entering the business scalability.

This study contributes to the literature on the relative performance of post-incubated firms, highlighting the efficiency frontier analysis. This methodological approach is relatively new in this field. It allows researchers to study the innovative firms' performance in relative terms, that is with respect to the input level. It integrates the performance-based with efficiency frontier analysis. Also, this study reinforces the idea that incubators prepare start-ups to develop capacities and managerial skills, which will be useful in post-incubation life to improve their cost competitiveness.

This study investigates the correlation between economic development and scientific knowledge production indicators in the BRICS countries from 2000 to 2020, highlighting the importance of human resources, natural resources, and innovation. Addressing a gap in the existing literature, this study aims to contribute significantly to understanding this relationship.

Employing a descriptive statistical approach, this study utilizes GDP and per capita income as economic indicators and scientific data from WoS and SCOPUS databases, focusing on scientific document production and citations per document.

The analysis reveals a strong correlation between economic development and scientific performance within the BRICS nations during the specified period. It emphasizes the interdependence of economic progress and scientific prowess, underscoring that they cannot be considered independently.

However, limitations exist, notably the reliance on specific databases that might not cover the entire scientific output and the inability to capture all factors influencing economic and scientific development.

Understanding this interdependence has crucial originality. Policymakers and stakeholders in BRICS countries can leverage these insights to prioritize investments in human capital development and scientific research. This approach can foster sustainable economic growth by reducing reliance on natural resources.

This study aims to examine how environmental, social and governance (ESG) initiatives and ISO 14001, which is an internationally agreed standard to set out the requirements for an environmental management system, affect firm performance in the context of the Industry 4.0 supply chain.

The authors develop a new chance-constrained network data envelopment analysis (DEA) in the presence of non-positive data to estimate innovation, operational and profitability performances for three main relation groups (suppliers, partners and customers) in Microsoft's supply chain.

Results of this study show the following: (1) the application of ISO 14001 will reduce profitability but increase overall performance (OP); (2) ESG implementation has a convex U-shaped influence on profitability and OP, which means that firms will benefit when ESG investment goes beyond a particular level; (3) the nonlinear U-shape is presented in the E and G components, but not in the S of the individual ESG initiatives, and (4) only specific subcomponents of S and G in the subcomponent of individual ESG initiatives are nonlinearly connected to OP. Research's results reveal that the customer group has a higher performance value than the other two groups, which suggests that this group will create competitive advantages for Microsoft.

Overall, the authors provide an insightful viewpoint into supply chain management by examining the ESG initiatives, ISO 14001 and performances of Microsoft's supply chain.

Access to financing is a key success factor for start-ups. High failure rates, long payback periodse and asymmetries lead to conservative pricing and valuation discounts. The authors examine financial marketing and contingent factors, as enablers of a “patent premium” by private equity (PE) investors targeting start-ups in their growth and expansion stages.

Drawing from the contingency, innovation and signaling theories, the authors collect patent records for Italian start-ups in which a higher than 30% stake was acquired by PE investors during the period 2014–2020. The authors apply a generalized linear model with a logit link and robust clustered error to test the key relationships and control for endogeneity with a Heckman two-stage selection model.

Findings indicate start-ups’ access to financing is significantly impacted by marketing constructs adopted in the operation. Innovation alone does not suffice to determine a valuation premium, unless contingent on the promotion of its product, the placement -investors targeted-of the equity, brand equity levers of previous ownership and marketing competence backing the deal.

The authors provide new insights in the marketing-finance interface, highlighting levers that reassure investors and enable monetizing innovation in start-ups that are still privately held. The authors bridge a gap in literature that has mainly focused on venture capital and innovation financing in the open market, as well as a significant gap regarding the marketing design of private equity placements.