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This paper aims to develop a comprehensive model on intra- and interpersonal emotion regulation (ER) in hospitality and tourism (H&T) service encounters.

A critical review and reflection of ER research from multiple disciplines was conducted. Methodologies appropriate for investigating ER were also reviewed.

A comprehensive framework was proposed to outline key influential factors, processes and consequences of intra- and interpersonal ER in service encounters in the H&T industry. Methodologies integrating advanced tools were suggested to measure complex and dynamic emotion generation and regulation processes in social interactions from a multimodal perspective.

The researchers developed a comprehensive conceptual model on both intra- and interpersonal ER based on a critical review of the most recent psychological research on ER. Various theoretical and methodological considerations are discussed, offering H&T scholars a solid starting point to explore dynamic emotion generation and regulation processes in complex social settings. Moreover, the model provides future directions for the expansion of ER theories, which have been mostly developed and tested based on laboratory research.

The proposed model addresses two critical issues identified in emotion research in the H&T field: the lack of a dynamic perspective and the neglect of the social nature of emotions. Moreover, the model provides a roadmap for future research.

The purpose of this study is to investigate the relationship between support (i.e. supervisor support (SS) and co-worker support (CS)), job characteristics (job autonomy, job complexity and skill variety) and work engagement (WE). Furthermore, the study examined whether there is a mediating effect of employee resilience (ER) on the aforementioned variables.

Data were collected from employees working in SMEs in Uganda. A sample of 324 responses was used for data analysis. Structural equation modelling and bootstrapping procedures were used to test the hypothesized relationships.

The study findings confirmed that SS, CS and job characteristics were positively related to WE. The study revealed that SS, job autonomy, job complexity and skill variety were found to foster WE through ER. Yet, CS was found not to have an indirect impact on WE through ER.

Because this study was conducted using a cross-sectional research methodology, it makes it hard to draw causal inferences.

This study’s findings contribute to the existing body of literature on WE and job characteristics and also adds to the growing body of research on ER.

Because employees’ positive attitudes and behaviors are important to ensure organizational performance, organizations attempt to carry out human resource practices to shape these attitudes and behaviors. This paper aims to examine this issue by focusing on the effects of training and development (TD) on employee engagement (EE), satisfaction (ES) and retention (ER).

For empirical analysis, the authors use structural equation modeling and data collected from employees in a developing economy.

TD is positively and directly associated with EE, ES and ER. In addition, EE is found to mediate the indirect effects of TD on ES and ER.

The findings suggest some practical implications for TD activities to enhance employees’ positive attitudes and behaviors.

To the best of the authors’ knowledge, this research is among the early attempts to examine the direct and indirect effects of TD on EE, ES and ER in a developing economy. The findings add to the growing literature suggesting that TD can contribute to the improvement of employees’ positive attitudes and behaviors.

This study aims to examine the influence of perceived organizational support (POS) on boundary-spanning behaviors (BSBs) among frontline employees in the hospitality industry. It also considered perceived supervisory support (PSS) as a moderating factor within a conceptual model.

Data were gathered from 651 full-time hospitality employees across 12 hotels in China. The analysis of the data used confirmatory factor analysis and structural equation modeling.

The findings revealed that POS influences hospitality boundary spanners’ BSBs, specifically external representation (ER), internal influence (II) and service delivery (SD). In addition, PSS moderates the relationship between POS and these frontline employees’ behaviors.

This study offers practical strategies for hospitality professionals to enhance frontline employees’ BSBs and foster supportive workplaces that drive employee excellence. These strategies encompass cultivating a supportive organizational culture, implementing supportive measures, fostering a sense of belonging among employees and ensuring supervisors’ well-being and competence in supporting their teams during daily interactions. These actions effectively motivate customer-contact employees to excel in their performance.

Fostering a helpful attitude in frontline employees is crucial for service firms’ success. Hospitality organizations must provide support to achieve this. Few studies have explored how organizational support contributes positively to the BSBs of customer-contact employees. This study goes beyond oversimplification and delves into the nuanced interplay between perceived support (POS and PSS) and hospitality frontline employees’ BSBs, focusing on ER, II and SD. The moderated mediating model enhances the understanding of support dynamics in the organizational context.

Green transition is a long-term direction of corporate development that can achieve sustainable corporate development. This study aims to investigate whether state ownership promotes corporate green transition by mitigating managerial myopia and the impact of environmental regulations, internal controls and ownership on this pathway.

Using data from 2,608 Chinese listed companies for 2010–2019, the authors investigate the relationship between state ownership, managerial myopia and corporate green transition by using fixed-effects and moderated mediation models.

State ownership can boost green transitions and alleviate managerial myopia. Managerial myopia mediates the relationship between state ownership and corporate green transition. Furthermore, environmental regulations, internal controls and ownership moderate the mediating effects of managerial myopia.

The authors construct a multidimensional green transition index to examine the influence of state ownership on corporate green transition behavior and reveal the underlying mechanism by which state ownership promotes green transition by “mitigating managerial myopia.” This study enriches the literature on state ownership, management myopia and green transition and provides important evidence for the promotion of mixed ownership reforms.

This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

Exploring the intrinsic connection between the ecological environment and the digital economy and empirically testing how the level of digital economic development affects the ecological environment. Using the entropy weighting method to analyze the weights of the indicators in the digital economic development level and ecological environment system to explore the factors that have the greatest impact on the ecological environment in the indicator system of the digital economic development level so as to deepen the theoretical understanding of the relationship between the level of development of the digital economy and the ecological environment. Explore the regional heterogeneity of the level of development of the digital economy to promote the healthy development of China’s ecological environment proving the difference in the level of development of the digital economy in the east west and central regions of China and the difference in the effect on the ecological environment.

Based on the panel data of 30 provinces in China from 2013 to 2021 this paper fits the index system of digital economy development level with three factors. A digital infrastructure digital industry and digital application combines environmental pollution and energy consumption to construct ecological environment indicators and explored the impact of digital economy development level on the ecological environment by using the entropy weight method and the random effect model.

The findings indicate that the degree of digital economic development has a positive and significant impact on promoting the healthy development of the ecological environment, in which the digital industry has the greatest impact on the ecological environment. Meanwhile, the improvement of industrial structure also has a positive effect on the improvement of the ecological environment, whereas the level of human capital inhibits the healthy development of the ecological environment, and the governmental support fails to effectively and significantly promote the improvement of the ecological environment. Furthermore, the empirical research indicates that the level of digital economy development has obvious regional heterogeneity on the healthy development of the ecological environment: the eastern and central regions have a significant effect, while the western region has a less significant effect.

Although domestic and foreign scholars and experts have conducted sufficient studies on the ecological environment and the development level of digital economy respectively, there are few studies on the empirical analysis of the positive significance and regional heterogeneity of the impact of the development level of digital economy on the ecological environment, which can be supplemented and referred to in this study. At the same time, it also provides intellectual support for our country to achieve high-quality development of digital economy and efficient governance of ecological environment.

Public–Private Partnerships (PPPs) are crucial to the procurement of global infrastructure projects. Moreover, a price mode based on a cluster of core concessionary items is key to the delivery of value-for-money and successful project outcomes. However, existing research has yet to fully identify PPP concessionary items, nor yet described the range of practical price modes. This study provides taxonomy of core concessionary items impacting PPP projects, systematically classifies price modes, and assesses the applicability and risk impacts of those price modes on PPP projects.

This study adopts a comparative case study method in analyzing core concessionary items and alternative price modes. China is taken as the context, as it is one of the world’s largest PPP markets. In ensuring research validity and reliability, diverse data sources are utilized, with a graphic content analysis tool developed to capture the structure of price modes.

Eight PPP price modes are identified. These are: (1) UP (Unit Price) mode, (2) ALS (Annual Lump Sum) mode, (3) IRR (Internal Rate of Return) mode, (4) RP (Return for Investing Capital (RIC) - Profit Rate of O&M (PROM)) mode, (5) RFP (RIC - Financing Interest Rate (FR) - PROM) mode, (6) RFPL (RIC - FR - PROM - Lower Limit of User Charge (LLoUC)) mode, (7) RFL (RIC - FR - Lump Sum/Fixed Unit Price O&M Contract (LSOM/FUP)) mode, and (8) RFLL (RIC - FR - LSOM/FUP - LLoUC) mode. Other main findings are as follows: (1) Five risk allocation configurations can be achieved via these price modes. Yet while different price modes enable the allocation of specific risks, these do not always align with contracting parties’ original intentions. (2) IRR and RP modes may be less applicable in general because of their vulnerability in allocating critical risks and capacity for spurring opportunistic behavior.

By depicting the paths by which concessionary items in price modes affect cash flow, a systematic analysis of price modes was conducted exposing structural characteristics, along with risk allocation choice implications. The study is unique in: (1) Providing a systematic classification of PPP price modes used in PPP projects, (2) Presenting a comprehensive identification and streamlining of concessionary items in PPP practice, and (3) Analyzing the risk effects of different price modes. Together, these outcomes offer a hitherto unavailable perspective on PPP project risk management. The value of the study lies in the following: (1) Existing studies employ diverse concessionary items, but their applicability varies. This study offers an overarching framework facilitating decision-making in selecting appropriate PPP price modes and in determining concessionary items. (2) This study adds to the understanding of PPP price modes in significant ways that will aid local governments and potential sponsors in crafting and administrating more workable contract designs.

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.

The purpose of this paper is to examine the alternative accounts produced by Green Earth Volunteers (GEV), a Chinese environmental non-governmental organisation, over a 10-year period in the context of their campaign to create visibilities about hydroelectric dam projects along the Chang Jiang.

Drawing on conceptions of the human–nature relationship, including those evident in ancient Chinese philosophy and mythology, and the Chinese way of viewing and resolving conflict, this paper offers an interpretive analysis of the alternative accounts of GEV in terms of their form and content.

In terms of their content, the alternative accounts reflect elements of interrelated thinking, being underpinned by a recognition of the relationship between humans and nature, which is evident in Confucianism, Taoism and ancient Chinese mythology. The strategies adopted by GEV are a non-confrontational but feasible way to promote their ecological beliefs in the Chinese context.

The study suggests that social and environmental accounting (SEA) in developing countries is steeped in local cultural and philosophical traditions that need to be considered and incorporated into the design of alternative accounts.

The study contributes to the very limited literature that offers qualitative analyses of SEA in developing countries.