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Engaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings.

We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.

The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.

These findings help managers optimize their webcare strategy for better business results and develop automated webcare.

We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.

COVID-19 disrupted the usual way of working for many people across the globe, making full-time work from home and hybrid models two popular work arrangements. Despite the proliferation and high acceptance of the hybrid model, very little research has focused on the same. This study aims to compare the impact of transitions caused by remote work on work disengagement under two settings: remote work and hybrid model.

The data is collected from three corporate hubs in India: Hyderabad, Gurgaon and Bangalore. This study’s respondents represent two working models: full-time work from home and a hybrid model. Responses were collected using Google forms-based questionnaire, which resulted in the following usable responses: 356 (hybrid) and 398 (work from home).

The findings reveal that the structural model for the hybrid sector explained 11% of the variance in work disengagement, while the same for work from home model accounted for 20% of the variance in work disengagement. The authors also tested for the moderation of individual resilience between work-home and home-to-work conflicts and home-to-work transitions and work-to-home conflict under full-time work-from and hybrid models. Based on 356 respondents from hybrid category and 398 from work from home, the study found that employees experience less work-to-home and home-to-work conflicts in the hybrid model and employees experience more work-to-home and home-to-work conflicts in the full-time work from home model.

The study is also the first to examine the moderating role of individual resilience as a tool to bounce back and handle conflicts. As the full-time work from home model leads to more work-to-home and home-to-work conflicts, individuals have more scope to exhibit resilience, and thus, the moderating relationship is stronger in the full-time work from home model. The paper offers theoretical and managerial implications.

The purpose of this paper is to analyse and classify the literature that contributed to three questions, namely, what are the benefits of big data analytics (BDA) in the field of supply chain management (SCM) and logistics, what are the challenges in BDA applications in the field of SCM and logistics and what are the determinants of successful applications of BDA in the field of SCM and logistics.

This paper conducts a systematic literature review (SLR) to analyse the findings of 44 selected papers published in the period from 2016 to 2020, in the area of BDA and its impact on SCM. The designed protocol is composed of 14 steps in total, following Tranfeld (2003). The selected research papers are categorized into four themes.

This paper identifies sets of benefits to be gained from the use of BDA in SCM, including benefits in data analytics capabilities, operational efficiency of logistical operations and supply chain/logistics sustainability and agility. It also documents challenges to be addressed in this application, and determinants of successful implementation.

The scope of the paper is limited to the related literature published until the beginning of Corona Virus (COVID) pandemic. Therefore, it does not cover the literature published since the COVID pandemic.

This paper contributes to the academic research by providing a roadmap for future empirical work into this field of study by summarising the findings of the recent work conducted to investigate the uses of BDA in SCM and logistics. Specifically, this paper culminates in a summary of the most relevant benefits, challenges and determinants discussed in recent research. As the field of BDA remains a newly established field with little practical application in SCM and logistics, this paper contributes by highlighting the most important developments in contemporary literature practical applications.

Drawing upon the stimulus-organism-response model, this study aims to explore the impact of soft aspects of service quality on revisit intention through the mechanism of perceived empathy.

For the examination of the hypothesized relationships, the study adopts structural equation modelling to analyse the data of 562 respondents (i.e. 281 family members and 281 inpatients).

The empirical results suggest that service quality increased family member empathy perception, which, in turn, improved inpatients’ revisit intentions.

Past studies have focused on the roles of overall service quality. The authors have extended the literature by examining the specific but important aspect of service quality and its effects on emotional response. Importantly, the study explains that the affective reactions of a patient’s family, fastened with perceived empathy, have a central role in influencing the patients’ subsequent reactions. Moreover, the prior studies collected the data either from hospital employees or patients. However, in the present study, the authors used a unique sample (family members as well as patients) to have a deeper understanding. Thus, the study enhances the literature on the stimuli-response (i.e. service quality – revisit intentions) relationship in the context of service marketing in general and health care in specific. Important academic and managerial contributions and recommendations for future research are discussed.

This study aims to investigate and test the impact of competitive priorities, in terms of quality, speed, dependability, flexibility, cost and patient engagement, on patient satisfaction with healthcare services. It considers patients’ rather than managers’ points of view to collect responses about competitive priorities.

This research employed a cross-sectional survey design to analyze a sample of customers through an empirical study of 488 patients in Qatar’s healthcare service context.

The confirmatory factor analysis results show that competitive priorities and engagement positively and significantly impact patient satisfaction.

Researchers can use this methodology to explore the role of competitive priorities in different service contexts and sectors. The researchers conducted the study in Qatar; therefore, the results are not generalizable to all healthcare sectors. However, regardless of geographic location, the research approach can be used in healthcare.

Managers can employ the developed scales to diagnose competitive priorities and improve customer service experiences.

The paper is original as it suggests using competitive priorities as a measurement tool for predicting patient satisfaction compared to prior research that mostly measured competitive priorities based on internal perspectives (managers’ perspectives). Further, this paper is original because it depends on the external perspective (customers’ perspective) for the competitive priorities for measuring patient satisfaction.

The purpose of this study is to identify and prioritize capabilities and practices to ensure a resilient supply chain during an unexpected disruption. In addition, this study ranks maturity factors that influence the main capabilities identified.

This paper is conducted in three stages. First, capabilities and practices are extracted through a literature review. Second, capabilities and practices are ranked using the analytical hierarchical process method. Third, a gray technique for order preference by similarity to ideal solution method is used to rank maturity factors influencing capabilities.

The findings indicate that responsiveness, readiness, flexibility and adaptability are the most important capabilities for supply chain resilience. Also, commitment and communication are the highest maturity factors influencing resilience capabilities.

The findings provide a hierarchical vision of capabilities and practices for industries to increase resilience. Limitations of the paper are related to capabilities, practices and number of experts consulted.

This paper highlights the importance of high-maturity practices in resilience capability adoption. The findings of this study will encourage decisions-makers to increase maturity practices to build resilience against disruption.

The paper reveals that developing powerful capabilities, good practices and a high level of maturity improve supply chain resilience.

Supply chain vulnerability (SCV) analysis is vital for manufacturers globally because it creates a pathway for building resilient supply chains in uncertain environments. This study aims to identify drivers of SCV in the Indian manufacturing sector.

Sixteen drivers were identified from the literature review and followed by expert interviews. Interpretive structural modeling was used to determine the hierarchical structural relationship among identified SCV factors.

It was found that risk is not a board room agenda. Misaligned performance measures with incentives and lack of risk dashboard are the causal factors of SCV. Supply chain security, centralized production and distribution and lack of trust in the supply chain were driven factors.

This provides new insights to assess and prioritize initiatives for supply chain sustainability in terms of continuing business operations. The structural model provides a systemic view of SCV and helps reduce vulnerability.

This study aims to enhance the knowledge by offering perspectives from an emerging market by reviewing the existing literature on food tourism. This study applies a multimethod analysis, providing insights into the advancement of food tourism in India, the contributions, critical findings and emerging research themes.

The study adopted a multimethod analysis using descriptive, narrative and bibliometric analysis using VOSviewer to analyze research papers published on food tourism in India shortlisted from Scopus and Google Scholar.

Future research should focus on gauging the potential of food tourism in different regions of the country, applying theoretical frameworks that have not been used. “Culinary Diversity and Heritage,” “Sustainable and Responsible Food Tourism,” “Consumer Behavior and Food Tourism Experiences,” “Rural Development and Economic Impact,” “Technology and Digitalization,” “Stakeholder Collaboration,” “Food Safety and Hygiene” and “Policy and Regulation” were the identified future research themes. These findings are significant for emerging economies across the globe.

This study summarized the progress of food tourism research in India, the contributions and emerging themes, supplementing the need to study food tourism in India. This study contributed methodologically to the literature by adopting a multimethod review combining descriptive, narrative and bibliometric analysis. Finally, by proposing ideas and constructs for future research, this study provides directions for future food tourism research from an emerging market’s perspective.

Findings will assist managers and stakeholders in comprehending the factors influencing tourists, destination marketing and branding, aiding in effective planning and executing food tourism strategies to promote destinations. The identified themes and keywords can help academicians and researchers dwell upon the emerging research themes in food tourism.

To the best of the author’s knowledge, this is the first study analyzing food tourism research in India adopting a multimethod analysis. The study provides an in-depth analysis applying descriptive, narrative and bibliometric analysis, highlighting the critical trends and research themes. A framework for future studies was also proposed.

该研究旨在通过回顾有关美食旅游的现有文献, 提供来自新兴市场的观点, 从而强化现有的知识。本研究采用多方法分析, 深入了解印度美食旅游的发展、贡献、重要发现和新兴研究主题。

该研究采用了多种方法分析, 使用 VOSviewer 进行描述性、叙述性和文献计量分析, 以分析从 Scopus 和谷歌学术搜索中入围的关于印度美食旅游的研究论文。

未来的研究应侧重于衡量该国不同地区美食旅游的潜力, 应用尚未使用的理论框架。 “烹饪多样性和传统”、“可持续和负责任的美食旅游”、“消费者行为和美食旅游体验”、“农村发展和经济影响”、“技术和数字化”、“利益相关者协作”、“食品安全和卫生”, “政策与法规”是确定的未来研究主题。这些发现对全球新兴经济体具有重要意义。

本研究总结了印度美食旅游研究的进展、贡献和新兴主题, 补充了研究印度美食旅游的必要性。本研究采用结合描述性、叙述性和文献计量分析的多方法回顾, 在方法论上为文献做出了贡献。最后, 通过提出未来研究的思路和结构, 本研究从新兴市场的角度为未来的美食旅游研究提供了方向。

调查结果将帮助管理者和利益相关者理解影响游客、目的地营销和品牌的因素, 帮助有效规划和执行食品旅游战略以促进目的地。 确定的主题和关键词可以帮助院士和研究人员深入研究食品旅游中新兴的研究主题。

El estudio tiene como objetivo mejorar el conocimiento al ofrecer perspectivas de un mercado emergente mediante la revisión de la literatura existente sobre turismo gastronómico. Este estudio aplica un análisis de múltiples métodos, que proporciona información sobre el avance del turismo gastronómico en la India, las contribuciones, los hallazgos críticos y los temas de investigación emergentes.

El estudio adoptó un análisis multimétodo mediante un análisis descriptivo, narrativo y bibliométrico utilizando VOSviewer para analizar los artículos de investigación publicados sobre el turismo gastronómico en la India preseleccionados de Scopus y Google Scholar.

La investigación futura debería centrarse en calibrar el potencial del turismo gastronómico en las distintas regiones del país, aplicando marcos teóricos que no se han utilizado. “Diversidad culinaria y patrimonio”, “Turismo gastronómico sostenible y responsable”, “Comportamiento del consumidor y experiencias de turismo gastronómico”, “Desarrollo rural e impacto económico”, “Tecnología y digitalización”, “Colaboración de las partes interesadas”, “Seguridad e higiene alimentaria”, “Política y regulación” fueron los temas de investigación futura identificados. Estos hallazgos son significativos para las economías emergentes de todo el mundo.

Este estudio resumió el progreso de la investigación sobre turismo alimentario en la India, las contribuciones y los temas emergentes, complementando la necesidad de estudiar el turismo alimentario en la India. Este estudio contribuyó metodológicamente a la bibliografía al adoptar una revisión multimétodo que combina el análisis descriptivo, narrativo y bibliométrico. Por último, al proponer ideas y constructos para futuras investigaciones, este estudio proporciona orientaciones para futuras investigaciones sobre el turismo gastronómico desde la perspectiva de un mercado emergente.

Los resultados ayudarán a los gestores y a las partes interesadas a comprender los factores que influyen en los turistas, el marketing de los destinos y la creación de marcas, contribuyendo a una planificación y ejecución eficaces de las estrategias de turismo gastronómico para promocionar los destinos. Los temas y palabras clave identificados pueden ayudar a los académicos e investigadores a profundizar en los temas de investigación emergentes en el turismo gastronómico.

Se trata del primer estudio que analiza la investigación sobre turismo gastronómico en la India adoptando un análisis multimétodo. El estudio proporciona un análisis en profundidad aplicando un análisis descriptivo, narrativo y bibliométrico, destacando las tendencias críticas y los temas de investigación. También se propone un marco para futuros estudios.

The primary purpose of this study is to examine the factors leading to shopping cart abandonment and construct a model depicting interrelationship among them using interpretive structural modeling (ISM) and Matriced Impact Croises Multiplication Appliquee an un Classement (MICMAC).

Initially, 20 factors leading to shopping cart abandonment were extracted through a systematic literature review and expert opinions. Fifteen factors were finalized using the importance index and CIMTC method, for which consistency has been checked in SPSS software through a statistical reliability test. Finally, ISM and MICMAC approach is used to develop a model depicting the contextual relationship among finalized factors of shopping cart abandonment.

The ISM model depicts a technical glitch (SC8), cash on delivery not available (SC4), bad checkout interface (SC9), just browsing (SC11), and lack of physical examination (SC12) are drivers or independent factors. Additionally, four quadrants have been formulated in MICMAC analysis based on their dependency and driving power. This facilitates technical managers of e-commerce companies to focus more on factors leading to shopping cart abandonment according to their dependency and driving power.

Taking an expert’s opinion as a base may affect the results of the study due to biases based on subjectivity.

This study’s outcomes would accommodate practitioners, researchers, and multinational or national companies to indulge in e-commerce to anticipate factors restricting the general public from online shopping.

For the successful running of an e-commerce business and to retain the confidence of e-shoppers, every e-commerce company must make a strategy for controlling factors leading to shopping cart abandonment at the initial stage. So, this paper attempts to highlight the main factors leading to shopping cart abandonment and interrelate them using ISM and MICMAC approaches. It provides a clear path to technical heads, researchers, and consultants for handling these shopping cart abandonment factors.

Drawing on the dynamic capability view, this study aims to examine the relationships between big data analytics capability (BDAC) and sustainable supply chain performance (SSCP) by exploring the mediating effects of knowledge development (KD) in terms of knowledge acquisition, information distribution, shared meaning and achieved memory.

Data were collected by questionnaire survey from 300 manufacturing organizations. Structural equation modeling was used to test the research hypotheses.

It was found that all the dimensions of KD were positively related to BDAC and SSCP. Although no direct association was established between BDAC and SSCP, the empirical findings indicated that all the dimensions of KD fully mediated the relationship between BDAC and SSCP. This highlights that organizations need to harness KD because developing BDAC alone may not be sufficient.

No previous research has explored how KD dimensions such as knowledge acquisition, information distribution, shared meaning and achieved memory mediate the relationship between BDAC and SSCP. This paper addresses this gap in the literature and contributes to the existing debate to better understand the conditions in which BDAC affects SSCP. Pointers for future research are also identified.