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This study aims to uncover marketing strategies to restore a positive image in times of pandemic crisis to bring tourists back to a popularly affected tourism city in China, Wuhan in Hubei Province. The paper argues that the process of restoring city image requires understanding the perceptions of Generation Z, a segment of the population who have a high propensity to travel after COVID-19.

This study employed a constructivist grounded theory approach to explore the perspectives of China’s Generation Z consumers of Wuhan’s future image to restart tourism. The data is collected through semi-structured interview of 29 respondents and analyzed with the initial, focused and theoretical coding process.

Start by narrowing the gap between projected and perceived image, the findings suggest that Generation Z could be pulled to visit Wuhan city through four core products such as dark tourism activities, special-interest leisure, heroism and storytelling.

The destination image restoration framework after health-related crisis is creatively proposed. It combines the analysis of crisis and urban characteristics from the perspective of the target audience (Generation Z) and provides specific strategies to restore the tourism city image from cognitive, affective and conative dimensions. Significantly, two novel characteristics of Generation Z (i.e. lighthearted and patriotic) emerge in addition to the typical features of this generational cohort. This study also found a high preference for a technologically oriented type of attraction that reverses the morbid COVID-19 memories into an entertainment tool.

Promoting “Quality Education” as part of Sustainable Development Goal 4 requires educational stakeholders to understand the nature of online learning from the learners’ perspective. This study aims to explore the asymmetric effects of online learning attributes on overall learning satisfaction in tourism and hospitality education.

The authors adopt the three-factor satisfaction theory and the three analytical steps penalty–reward contrast analysis, impact range performance analysis (IRPA) and impact asymmetry analysis. The authors then juxtapose the results of such analytical approaches to the traditional importance–performance analysis (IPA) for further insights.

Traditional IPA suggests nine high importance and performance online attributes. However, the IRPA reveals that only four attributes fall within high performance and high range of impact on satisfaction. The attribute “secure” had a low performance despite a significant impact on satisfaction.

By exploring asymmetric effects, scholars, service providers and participants of online education can have a deeper insight into the nature and dynamic effect of attributes on overall satisfaction.

By exploring the asymmetric impacts of online learning attributes on overall learning satisfaction, the findings provide a novel insight into the multidimensionality of online learning attributes.

推动“优质教育”作为可持续发展目标四的一部分, 要求教育利益相关者从学习者的角度从本质上了解在线学习。本研究探讨了在线学习属性对旅游和酒店教育整体学习满意度的非对称影响。

我们采用三因素满意度理论结合三个分析步骤：惩罚奖励对比分析（PRCA）; 影响范围性能分析（IRPA）; 影响非对称分析（IAA）, 并将这种分析方法的结果与传统的重要性-表现分析（IPA）对比以获得深入理解。

传统的重要性-表现分析的结果展现了在线学习满意度具有较高重要性和表现的九个属性。然而, IRPA 显示只有四个属性属于高性能和满意度的高影响范围。“安全”这一属性虽然对满意度有显着影响, 但它的表现评估却很低。

对非对称影响的探索帮助在线教育的学者、服务提供者和参与者们更深入地了解对于整体满意度而言不同属性的本质和动态影响。

通过探讨在线学习属性对整体学习满意度的非对称影响, 我们的研究结果为理解在线学习属性对于整体满意度的影响提供了多维度的新颖视角。

La promoción de la “Educación de Calidad” como parte del Objetivo de Desarrollo Sostenible 4 requiere que los actores educativos entiendan la naturaleza del aprendizaje en línea desde la perspectiva de los estudiantes. Este estudio explora los efectos asimétricos de los atributos del aprendizaje en línea sobre la satisfacción general del aprendizaje en la educación en turismo y hotelería.

Aplicamos la teoría de la satisfacción de tres factores y los tres pasos analíticos: análisis de contraste de penalización-recompensa (PRCA), análisis de rendimiento del rango de impacto (IRPA) y análisis de impacto asimétrico (IAA). A continuación, aplicamos los resultados de estos enfoques analíticos al tradicional análisis de importancia-rendimiento (IPA) para obtener más información.

El análisis tradicional de importancia-rendimiento sugiere nueve atributos en línea de gran importancia y rendimiento. Sin embargo, el IRPA revela que sólo cuatro atributos se encuentran dentro de la franja de alto rendimiento y alto impacto en la satisfacción. El atributo “seguridad” tuvo un desempeño bajo a pesar de tener un impacto significativo en la satisfacción.

Al explorar los efectos asimétricos, los académicos, los proveedores de servicios y los participantes de la educación en línea pueden tener una visión más profunda de la naturaleza y el efecto dinámico de los atributos en la satisfacción general.

Al explorar los impactos asimétricos de los atributos del aprendizaje en línea en la satisfacción general del aprendizaje, nuestros hallazgos brindan una visión novedosa de la multidimensionalidad de los atributos del aprendizaje en línea.

The purpose of this paper is to report the findings of a study that examines the influence of leader–member exchange (LMX) on employees' turnover intention and presenteeism with the mediating role of perceived organizational support in the context of the semiconductor industry.

An empirical study based on a sample of 124 department managers and 241 team members in five high-tech companies in Taiwan. Structural equation modelling analysis was used for hypothesis testing.

The results reveal that perceived organization support significantly relates to employees' turnover intention and mediates the relationship between LMX and turnover intention. Additionally, employees' presenteeism is influenced by perceived LMX.

The results of the study are of high importance for high-tech companies, which continuously strive for innovation efficiency and sustainability. Managers and practitioners could benefit from better understanding regarding the importance of perceived organization support and LMX in affecting employee behaviours and company performance.

The present study finds a significant positive relationship between LMX and presenteeism, which is contrary to the previous research.

This study aims to complement existing studies by investigating the impact of different corporate social responsibility (CSR) information disclosed by peer listed stars (i.e. governance information [GI] and output information [OI]) on focal firms’ responsive CSR (RCSR) and strategic CSR (SCSR) practices. The authors also investigate the influence of different boundary conditions (i.e. founders’ social status [SS] and industry pollution intensity).

Based on the listed stars of 16 industries and their 4,096 private peers in China, the authors use the least squares method and logistic regression models to analyze the data set.

The results indicate that the GI of peer listed stars can only positively affect firms’ RCSR behavior. The OI of peer listed stars has a positive effect on firms’ SCSR behavior while negatively affecting firms’ RCSR behavior. The SS of focal firms’ founders and their interaction with the industry’s pollution level strengthen the abovementioned positive relationships while weakening the negative ones.

This study provides insights into the role of listed stars in influencing peer firms’ CSR activities, offering important practical implications for both policymakers and managers.

This study extends the recent discussion on peer effects of CSR by elucidating the peer star effect on CSR and confirms that firms may adopt heterogeneous CSR practices to achieve sustainable growth by investigating peer firms’ different responses to their listed stars’ different CSR information. Moreover, by introducing the SS of founders and the pollution intensity of the industry as boundary conditions, this study enriches the research context on CSR activities.

Customer Support Knowledge of Customer Support Organization is one of the important assets of enterprises and “Customer Support Knowledge Management” is also the critical aspect of Business Knowledge Management; however, the attributes of Customer Support Knowledge are complicated, diverse, renewed rapidly and difficult to be managed. Thus, in order to design a successful Customer Support Knowledge Management System, apart from the consideration of “human” and “information technology” aspects, the concerns of attributes and Customer Support Knowledge and industry characteristics should be involved for meeting the requirements of Customer Support Organization and allowing the organization to acquire the competitive advantage of “Differentiation Service”. This research used the “Customer Support Knowledge Management System” in a high‐tech industry as an example and treated the end users of medical instruments in different types of hospitals in Taiwan which have received the support service of our company in recent six months as the population. The end users were mostly the nursing executives or ultrasonic wave technical personnel in intensive care unit and they had similar educational background and incomes and adopted the medical instruments such as physical supervision system, ultrasonic wave system, heart start or ECG machine produced by our company; the research method was to randomly treat the investigation results of the telephone customers’ satisfaction from respective 30 end users in the population three months before and after this system execution as the samples and use hypotheses to validate if the end users’ customer satisfaction significantly improved in terms of “Remote Support,” “On‐site Support,” “Service Turn Around time,” “Technical Competence” and “Service Manner” in order to understand the influence and managerial significance of execution of “Customer Support Knowledge Management System” on Customer Support Organization.

Since the emergence of the Internet in the twentieth century and the rapid growth of different types of information technologies (IT), our lives, either personal or professional, have become digitised. Adoption and diffusion of IT enhance individuals and organisational performance, yet scholars discovered a dual nature of IT in which IT usage may have negative aspects too. First, the inability to cope with IT in a healthy manner creates stress in users, termed technostress. Second, digitisation and adoption of new technologies (e.g. IoT and multi-cloud environments) have increased vulnerabilities to information security (InfoSec) threats. Although organisations utilise counteraction strategies (e.g., security systems, security policies), end-users remain the top source of security incidents. Existing behavioural research has approached technostress and InfoSec independently. However, it is not clear how technology-stressors influence employees’ security-related behaviours. This chapter reviews the interaction effect of these concepts in detail by proposing a conceptual model that explains that technostress is the main reason for employees’ non-compliance with security policies in which users with high-level perceptions of technostress are more likely to violate InfoSec policies. Counteraction strategies to mitigate technostress and security threats are also discussed.

The purpose of this paper is to explore the relationship between formal environmental regulation (FER) and informal environmental regulation (IER), technological innovation and employment.

This paper uses data from the 30 provinces of China during 2003–2015. The impacts of formal and IER and technological innovation on employment are estimated by generalized least squares, and the eastern region of China is analyzed separately.

First, both formal and IERs have different degrees of significant impact on employment, and the relationship is not a simple linear. FER has an inverted U-shaped relationship with employment, but IER has a U-shaped relationship. However, in the test including technological innovation, the results of the national sample and the eastern sample are different. In the eastern sample, the relationship between informal regulation and employment has an inverted U-shaped curve. Second, the results of model 3 and model 6 show that technological innovation has a significant negative effect on employment both in the national and the eastern region sample.

This paper puts forward corresponding policy implications: first, in designing environmental regulations, it is necessary to consider not only the stringency but also the type of regulation. Second, environmental regulations need to be differentiated by region. Finally, when designing environmental regulations, it is necessary to consider more flexible employment policies that are contingent on the stringency of regulations, in order to prevent employment decline due to technological innovations.

The conclusions about the influence of environmental regulation on employment reached are not consistent in China. Most existing research studies seldom consider environmental regulations into categories and focus only on the whole environmental regulation. This paper pays attention to the influences of different types of environmental regulations on employment. It analyzes the eastern region separately to explore whether there is a difference in the effects of environmental regulations. Furthermore, this considers the effect of technological innovation as a mediator.

In a classroom, a support vector machines model with a linear kernel, a neural network and the k-nearest neighbors algorithm failed to detect simulated money laundering accounts generated from the Panama papers data set of the offshore leak database. This study aims to resolve this failure.

Build a graph attention network having three modules as a new money laundering detection tool. A feature extraction module encodes these input data to create a weighted graph structure. In it, directed edges and their end vertices denote financial transactions. Each directed edge has weights for storing the frequency of money transactions and other significant features. Social network metrics are features of nodes for characterizing an account’s roles in a money laundering typology. A graph attention module implements a self-attention mechanism for highlighting target nodes. A classification module further filters out such targets using the biased rectified linear unit function.

Resulted from the highlighting of nodes using a self-attention mechanism, the proposed graph attention network outperforms a Naïve Bayes classifier, the random forest method and a support vector machines model with a radial kernel in detecting money laundering accounts. The Naïve Bayes classifier produces second accurate classifications.

This paper develops a new money laundering detection tool, which outperforms existing methods. This new tool produces more accurate detections of money laundering, perfects warns of money laundering accounts or links and provides sharp efficiency in processing financial transaction records without being afraid of their amount.

This paper builds homogenous series of the rate of surplus value (RSV) for the Chinese economy over the extended period 1956–2014 with a Marxian approach. It finds that the high profitability that stimulated capital accumulation in the decade before the 2008 crisis had relied on the continuous growth in the RSV. Given that the global crisis and changes in the domestic economy undermine all the conditions maintaining the accumulation model (an expanding external market, a relatively large reserve army of labor, and a low debt-income ratio), the RSV has failed to increase and profitability declined since 2008. Thus, this paper interprets the so-called new normal of the Chinese economy as a stage of declining profitability that results mainly from the stagnant RSV and the rising value composition of capital.