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1 – 10 of 92Yousery Nabil M.K. Elsayed, Sawsan Haider Khreis, Abuelhassan Elshazly Abuelhassan and Mohamed Abdelgawwad Aly Abdelgawwad
This study aims to provide a new vision for investigating the different human resources management (HRM) practices in hotels after the COVID-19 pandemic.
Abstract
Purpose
This study aims to provide a new vision for investigating the different human resources management (HRM) practices in hotels after the COVID-19 pandemic.
Design/methodology/approach
A quantitative research approach was adopted using confirmatory factor analysis and structural equation modeling to reveal updated priorities and relations as stated by 504 hospitality employees.
Findings
The research approach contributed to highlighting exciting findings, as training and development (T&D) had an insignificant effect on turnover intention (IT) or affective organizational commitment (AOC) following the COVID-19 pandemic; job security (JS) had the highest impact on AOC and compensation had the highest effect on TI.
Practical implications
Individual HRM practices have different strong impacts on employee outcomes. This paper provides human resource directors with realistic and practical implications to boost individuals' AOC and reduces their intention to quit their job in conditions of uncertainty and ambiguity.
Originality/value
This pioneering study reveals the influence of HRM practices in the hospitality HRM systems regarding employee attitudes and behaviors, especially after the COVID-19 pandemic. It provides novel theoretical and practical contributions.
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Thowayeb Hassan and Mahmoud Ibraheam Saleh
The study aims to investigate how attribution theory in the context of pricing strategies can help tourism destinations recover from the negative impacts of the COVID-19 pandemic.
Abstract
Purpose
The study aims to investigate how attribution theory in the context of pricing strategies can help tourism destinations recover from the negative impacts of the COVID-19 pandemic.
Design/methodology/approach
The study adopted a qualitative research design using semi-structured interviews to address the lack of research in this area. Interview participants included tourists and tourism customers. The interview responses were then analyzed using “Nvivo” qualitative data analysis software to identify critical themes regarding applying attribution theory to pricing strategies.
Findings
The findings revealed that tourists prefer bundled and hedonic pricing strategies that integrate the service providers' pricing strategies' locus of control, stability and controllability. Tourists do not favor dual pricing strategies unless the reasons for price controllability or stability are justified. Tourists also prefer the controllable pay-what-you-want pricing strategy. Although tourists accept dynamic pricing, certain conditions related to price locus, stability and controllability must be met.
Practical implications
The research shows tourists prefer pricing strategies that give them control and flexibility, like bundled packages and pay-what-you-want models. Service providers should integrate pricing strategies that transparent costs and justify price fluctuations. While dynamic pricing is accepted if necessitated by external factors, tourists are wary of unnecessary price changes. Providers can build trust and satisfaction by explaining pricing rationale and offering controllable options like bundles.
Originality/value
The study contributes to the theory by applying attribution theory to the context of pricing strategies in tourism. It also provides innovative recommendations for tourism managers on how to use pricing strategies after the COVID-19 pandemic. The findings offer new insights that extend beyond previous research.
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This study aims to apply the appreciative inquiry approach (AI) to develop a tourism strategy for poverty alleviation in marginalised communities. The focus is to provide…
Abstract
Purpose
This study aims to apply the appreciative inquiry approach (AI) to develop a tourism strategy for poverty alleviation in marginalised communities. The focus is to provide practical insights for leveraging tourism to drive positive socio-economic change for the impoverished, using Rosetta, a port city in Egypt with cultural and historical significance, as a case study.
Design/methodology/approach
This qualitative applied study uses the four-D phases of AI and thematic analysis to strategise tourism development in Rosetta. Through interviews, focus groups and field visits, the study identifies tourism potential, stakeholder aspirations and actionable strategies for sustainable development. The approach prioritises a bottom-up, community-centric and stakeholder-involved process, aiming for inclusive and equitable growth.
Findings
The study revealed Rosetta’s underutilised tourism potential, emphasising heritage tourism. Although tourism offers some economic benefits, its impact on alleviating poverty in Rosetta remains limited. A holistic strategy for tourism development in Rosetta is proposed for economic growth and poverty reduction, focusing on sustainable management, local empowerment, enhanced marketing, improved infrastructure and diversified tourism offerings.
Originality/value
While AI is not new in qualitative studies, the novelty of this study lies in its application to tourism planning for poverty alleviation in a marginalised community like Rosetta, introducing a comprehensive tourism strategy with an original framework applicable to comparable destinations. The study’s significance is emphasised by providing actionable strategies for policymakers, valuable insights for practitioners and enriching the discourse and methodology on pro-poor tourism for academics, representing a step towards filling the gap between theoretical concepts and practical strategies.
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Wen-Qian Lou, Bin Wu and Bo-Wen Zhu
This study aims to clarify influencing factors of overcapacity of new energy enterprises in China and accurately predict whether these enterprises have overcapacity.
Abstract
Purpose
This study aims to clarify influencing factors of overcapacity of new energy enterprises in China and accurately predict whether these enterprises have overcapacity.
Design/methodology/approach
Based on relevant data including the experience and evidence from the capital market in China, the research establishes a generic univariate selection-comparative machine learning model to study relevant factors that affect overcapacity of new energy enterprises from five dimensions. These include the governmental intervention, market demand, corporate finance, corporate governance and corporate decision. Moreover, the bridging approach is used to strengthen findings from quantitative studies via the results from qualitative studies.
Findings
The authors' results show that the overcapacity of new energy enterprises in China is brought out by the combined effect of governmental intervention corporate governance and corporate decision. Governmental interventions increase the overcapacity risk of new energy enterprises mainly by distorting investment behaviors of enterprises. Corporate decision and corporate governance factors affect the overcapacity mainly by regulating the degree of overconfidence of the management team and the agency cost. Among the eight comparable integrated models, generic univariate selection-bagging exhibits the optimal comprehensive generalization performance and its area under the receiver operating characteristic curve Area under curve (AUC) accuracy precision and recall are 0.719, 0.960, 0.975 and 0.983, respectively.
Originality/value
The proposed integrated model analyzes causes and predicts presence of overcapacity of new energy enterprises to help governments to formulate appropriate strategies to deal with overcapacity and new energy enterprises to optimize resource allocation. Ten main features which affect the overcapacity of new energy enterprises in China are identified through generic univariate selection model. Through the bridging approach, the impact of the main features on the overcapacity of new energy enterprises and the mechanism of the influence are analyzed.
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Xiaoxu Dang, Mengying Wang, Xiaopeng Deng, Hongtao Mao and Pengju He
Corporate social responsibility (CSR) practices frequently result in increased costs for Chinese international contractors (CICs), where profitability is the primary objective;…
Abstract
Purpose
Corporate social responsibility (CSR) practices frequently result in increased costs for Chinese international contractors (CICs), where profitability is the primary objective; therefore, internal corporate drivers and external pressures play a crucial role in encouraging them to engage in sustainable CSR practices. This study systematically examines the dynamic impact of internal and external stakeholders on the CSR practices of CICs.
Design/methodology/approach
This study adopted a structural equation model (SEM) to identify and validate a correlation between stakeholders and CSR practices. Standardized causal coefficients estimated in SEM were used to construct a fuzzy cognitive map (FCM) model to illustrate the effect of stakeholders on CSR practices with linkage direction and weights. Predictive, diagnostic, and hybrid analyses were performed to dynamically model the variation in stakeholders on the evolution of CSR practices.
Findings
The empirical results demonstrate that (1) employee participation in CSR has the greatest impact on CSR practices, followed by CSR strategies, partner and customer expectations, and finally government regulations. (2) In the early stage of CSR fulfillment, CSR strategies have the greatest influence on CSR practices; in the later stage of CSR fulfillment, employee participation in CSR has the greatest influence on CSR practices. (3) In the long run, the most effective and economical integrated interventions are those that address employee participation in CSR, partner expectations and customer expectations, and intervention in CSR strategies is needed if the level of CSR practice needs to be improved in the short term.
Originality/value
This study contributes to the research on the influence mechanisms of CSR practices of CICs and systematically analyzes their dynamic influence on CSR practices of CICs from the perspective of stakeholders.
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Fan Zhang and Haolin Wen
Based on dual information asymmetry, the two-stage segmented compensation mechanism for technological innovation of civilian enterprises’ participation in military (CEPIM) has…
Abstract
Purpose
Based on dual information asymmetry, the two-stage segmented compensation mechanism for technological innovation of civilian enterprises’ participation in military (CEPIM) has been discussed.
Design/methodology/approach
On the basis of the traditional principal-agent problems, the incentive compatibility condition is introduced as well as the hybrid incentive compensation model is established, to solve optimal solution of the compensation parameters under the dynamic contract condition and the validity is verified by numerical simulation.
Findings
The results show that: (1) The two-stage segmented compensation mechanism has the functions of “self-selection” and “stimulus to the strong”, (2) It promotes the civilian enterprises to obtain more innovation benefit compensation through the second stage, (3) There is an inverted U-shaped relationship between government compensation effectiveness and the innovation ability of compensation objects and (4) The “compensable threshold” and “optimal compensation threshold” should be set, respectively, to assess the applicability and priority of compensation.
Originality/value
In this paper, through numerical simulation, the optimal solution for two-stage segmented compensation, segmented compensation coefficient, expected returns for all parties and excess expected returns have been verified under various information asymmetry. The results show that the mechanism of two-stage segmented compensation can improve the expected returns for both civilian enterprises and the government. However, under dual information asymmetry, for innovation ability of the intended compensation candidates, a “compensation threshold” should be set to determine whether the compensation should be carried out, furthermore an “optimal compensation threshold” should be set to determine the compensation priority.
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Zhen Xu, Ruohong Hao, Xuanxuan Lyu and Jiang Jiang
Knowledge sharing in online health communities (OHCs) disrupts consumers' health information-seeking behavior patterns such as seeking health information and consulting. Based on…
Abstract
Purpose
Knowledge sharing in online health communities (OHCs) disrupts consumers' health information-seeking behavior patterns such as seeking health information and consulting. Based on social exchange theory, this study explores how the two dimensions of experts' free knowledge sharing (general and specific) affect customer transactional and nontransactional engagement behavior and how the quality of experts' free knowledge sharing moderates the above relationships.
Design/methodology/approach
We adopted negative binomial regression models using homepage data of 2,982 experts crawled from Haodf.com using Python.
Findings
The results show that experts' free general knowledge sharing and free specific knowledge sharing positively facilitate both transactional and nontransactional engagement of consumers. The results also demonstrate that experts' efforts in knowledge-sharing quality weaken the positive effect of their knowledge-sharing quantity on customer engagement.
Originality/value
This study provides new insights into the importance of experts' free knowledge sharing in OHCs. This study also revealed a “trade-off” between experts' knowledge-sharing quality and quantity. These findings could help OHCs managers optimize knowledge-sharing recommendation mechanisms to encourage experts to share more health knowledge voluntarily and improve the efficiency of healthcare information dissemination to promote customer engagement.
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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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
The study contributes to the very limited literature that offers qualitative analyses of SEA in developing countries.
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Mahmoud Alghemary, Basil Al-Najjar and Nereida Polovina
The authors empirically investigate the association between acquisition, ownership structure and accrual earnings management (AEM) on real earnings management (REM) using Gulf…
Abstract
Purpose
The authors empirically investigate the association between acquisition, ownership structure and accrual earnings management (AEM) on real earnings management (REM) using Gulf Cooperation Council (GCC)-listed firms' context.
Design/methodology/approach
The authors' sample consists of 1,892 firm-year observations for the period from 2007–2017, and the authors adopt a panel data approach in investigating the interrelationships in this study. The authors employ different econometrics approach to test the authors' hypotheses.
Findings
The findings reveal that acquiring companies engage more in AEM if compared to REM. In terms of ownership structure, institutional ownership and state ownership mitigate the engagement in REM, whereas foreign ownership is found to be an ineffective mechanism in reducing engagement in REM. The authors report similar findings on ownership structure for AEM. The authors also find that the GCC firms engage more in REM when the firms engage in AEM, suggesting a complementary relation between these two earnings management techniques. These findings are robust after controlling for different aspects including any endogeneity issue in the authors' models.
Originality/value
The authors' research highlights the importance of understanding REM and AEM dynamics in GCC context. Also, the authors' findings on ownership structure suggest that GCC-listed firms can gain from institutional and state ownership which restricts earnings management, improving firm transparency and subsequently impacting firm performance.
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Jiaqi Liu, Haitao Wen, Rong Wen, Wenjue Zhang, Yun Cui and Heng Wang
To contribute to achieving the Sustainable Development Goals, this study aims to explore how to encourage innovative green behaviors among college students and the mechanisms…
Abstract
Purpose
To contribute to achieving the Sustainable Development Goals, this study aims to explore how to encourage innovative green behaviors among college students and the mechanisms behind the formation of green innovation behavior. Specifically, this study examines the influences of schools, mentors and college students themselves.
Design/methodology/approach
A multilevel, multisource study involving 261 students from 51 groups generally supported this study’s predictions.
Findings
Proenvironmental and responsible mentors significantly predicted innovative green behavior among college students. In addition, creative motivation mediated the logical chain among green intellectual capital, emotional intelligence and green innovation behavior.
Practical implications
The study findings offer new insights into the conditions required for college students to engage in green innovation. In addition, they provide practical implications for cultivating green innovation among college students.
Originality/value
The authors proposed and tested a multilevel theory based on the ability–motivation–opportunity framework. In this model, proenvironmental and responsible mentors, green intellectual capital and emotional intelligence triggered innovative green behavior among college students through creative motivation.
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