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The present study examines the effect of supervisor incivility on service employee creativity and the mediating mechanism of negative affect state on the said relationship with the aid of Affective Events Theory (AET) and Social Power Theory. Additionally, the study explores the mitigating role of core self-evaluation in the dual stage of the moderated mediation model.

Survey data were collected from 420 frontline employees working in four-star and five-star hotels across India and PROCESS macro in SPSS 23.0 was employed to test the hypotheses proposed in the study.

The study findings observe that frontline employees experiencing supervisor incivility face a negative affect state and it further diminishes service employee creativity. Also, the indirect effect gets attenuated at dual stages when frontline employees are equipped with a high level of core self-evaluation.

The study findings provide various insights to the managers to understand the deleterious effect of supervisor incivility at work and to develop interventions to manage supervisor incivility and the negative affect state among frontline hotel employees.

The present study is the first and unique attempt to investigate the role of supervisor incivility experienced by frontline hotel employees in India with reference to their creativity towards customers and mediating mechanism of negative affect state. The study adds value to the literature by establishing the role of core self-evaluation in the moderated mediation model. Further, the study also provides a unique contribution to the management of frontline hospitality employees.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

Job satisfaction is essential in understanding turnover intentions. Previous studies reveal that highly educated hospitality employees generally have lower levels of job satisfaction, indicating that the antecedents of job satisfaction may be different from hospitality managers and frontline employees. This study compared the different antecedents of job satisfaction for housekeeping managers and employees.

This study used a mixed-methods approach for a two-part study. The researchers recruited housekeeping managers for the exploratory survey. The results of open-end questions helped us build a custom dictionary for the text mining of comments from Glassdoor.com. Finally, a multilinear regression of themes from housekeeping employees’ ratings on Glassdoor.com was conducted to understand the antecedents of job satisfaction for housekeeping managers and employees.

The results of the exploratory survey indicated that the housekeeping department has an urgent need for organizational support and training. The text-mining revealed organizational support impacts both managers and frontline employees, while training impacts managers more than employees. Finally, the regression analysis showed compensation, business outlook, senior management, and career opportunity impacted both groups. However, work-life balance only influenced managers.

With a large number of employees at low salaries, housekeeping departments have a higher-than-average turnover rate for lodging. This study is among the first to compare the antecedents of managers’ and frontline employees’ job satisfaction in the housekeeping department, extending Social Exchange Theory. It provides suggestions for the housekeeping department to decrease turnover intentions.

The purpose of this paper is to present an optimisation of four-point star-shaped structures produced through additive manufacturing (AM) polylactic acid (PLA). The study also aims to investigate the compression failure mechanism of the structure.

A Taguchi L₉ orthogonal array design of the experiment is adopted in which the input parameters are resolution (0.06, 0.15 and 0.30 mm), print speed (60, 70 and 80 mm/s) and bed temperature (55°C, 60°C, 65°C). The response parameters considered were printing time, material usage, compression yield strength, compression modulus and dimensional stability. Empirical observations during compression tests were used to evaluate the load–response mechanism of the structures.

The printing resolution is the most significant input parameter. Material length is not influenced by the printing speed and bed temperature. The compression stress–strain curve exhibits elastic, plateau and densification regions. All the samples exhibit negative Poisson’s ratio values within the elastic and plateau regions. At the beginning of densification, the Poisson’s ratios change to positive values. The metamaterial printed at a resolution of 0.3 mm, 80 mm/s and 60°C exhibits the best mechanical properties (yield strength and modulus of 2.02 and 58.87 MPa, respectively). The failure of the structure occurs through bending and torsion of the unit cells.

The optimisation study is significant for decision-making during the 3D printing and the empirical failure model shall complement the existing techniques for the mechanical analysis of the metamaterials.

To the best of the authors’ knowledge, for the first time, a new empirical model, based on the uniaxial load response and “static truss concept”, for failure mechanisms of the unit cell is presented.

The current study aimed to examine the moderating role of perceived supervisor support in the nexus between employee empowerment and organizational commitment in the Ghanaian hospitality industry.

A quantitative research design was adopted, and data were collected from 274 frontline workers from 4-star and 5-star hotels at two different waves within a 7-month interval. The data received were analyzed using descriptive and inferential statistics with the aid of Statistical Package for Social Sciences (SPSS V. 23.0) and SmartPLS (V.4.0), respectively.

As hypothesized in the study, employee empowerment was significantly related to organizational commitment. Furthermore, the results revealed that perceived supervisor support moderated the nexus between employee empowerment and affective and continuance commitment but did not moderate the nexus between employee empowerment and normative commitment.

Arguably, support from supervisors has been theoretically identified as a key construct in enhancing subordinates' commitment to an organization. However, less is known in the literature about the moderating role of perceived supervisory support in the nexus between employee empowerment and organizational commitment, especially in the Ghanaian hospitality industry.

This study aims to identify factors that can improve customer service performance by verifying the relationships between these factors, such as customer orientation, firm-specific resource integration, transactive memory system and service innovation capability. In other words, this study identifies the determinants of customer service performance from the perspective of the resource advantage theory of competition.

This research was conducted through an online survey of hotel managers and supervisors in Indonesia, which produced 327 questionnaires that could be processed with a response rate of 70.6%. Structural equation modelling was used to analyse the data and test the hypotheses with the help of AMOS 23.

This study confirms that firm-specific resource integration can improve customer service performance, with the antecedents of the former being customer orientation and a transactive memory system.

This research was conducted with a sample of three-, four- and five-star hotels, which have different conditions. In future research, it would be interesting to compare how such hotels over a larger geographical area behave in improving customer service performance using the investigated variables.

This research provides additional insight into the resource advantage theory of competition, namely, that integrated enterprise-specific resources are good antecedents for innovation and customer service performance.

Corporate social responsibility (CSR) promotes society, reduces risk, and encourages ethical business practices. Due to its relevance, we study how CSR influences firms' sustainable development. We analyze data from 427 New York Stock Exchange (NYSE)-listed firms from 2008 to 2022. The Refinitiv environmental and social score is used to measure CSR, whereas for firms' sustainable development we rely on corporate sustainable growth rate (SGR) and market-based metrics. The analysis employs various econometric techniques, including ordinary least square, fixed effect regression, two-stage least square, generalized method of moment, and simultaneous quantile regression. The results indicate that CSR has a positive and significant effect on firms' sustainable development across all models. This relationship supports the notion that socially responsible business can contribute to long-term financial sustainability in line with “stakeholder theory”, indicating that companies should accommodate the concerns of various stakeholders, including society and the environment, to achieve sustainable development. We evaluate how the conditional distributions of SGR and firms’ value are affected by CSR, categorizing them into high, moderate, and low regimes. The quantile regression estimates indicate that the effect of CSR is more pronounced at upper quantiles, followed by moderate and low regimes. These findings underscore the importance of considering CSR in assessing the SGR and enterprises market value. We also confirm that our results are robust under range of different econometrics' methods. Finally, we enlighten current literature, and our research has useful policy implications for management and investors.

Most previous studies predicting review helpfulness ignored the significance of deep features embedded in review text and instead relied on hand-crafted features. Hand-crafted and deep features have the advantages of high interpretability and predictive accuracy. This study aims to propose a novel review helpfulness prediction model that uses deep learning (DL) techniques to consider the complementarity between hand-crafted and deep features.

First, an advanced convolutional neural network was applied to extract deep features from unstructured review text. Second, this study used previous studies to extract hand-crafted features that impact the helpfulness of reviews and enhance their interpretability. Third, this study incorporated deep and hand-crafted features into a review helpfulness prediction model and evaluated its performance using the Yelp.com data set. To measure the performance of the proposed model, this study used 2,417,796 restaurant reviews.

Extensive experiments confirmed that the proposed methodology performs better than traditional machine learning methods. Moreover, this study confirms through an empirical analysis that combining hand-crafted and deep features demonstrates better prediction performance.

To the best of the authors’ knowledge, this is one of the first studies to apply DL techniques and use structured and unstructured data to predict review helpfulness in the restaurant context. In addition, an advanced feature-fusion method was adopted to better use the extracted feature information and identify the complementarity between features.

大多数先前预测评论有用性的研究忽视了嵌入在评论文本中的深层特征的重要性, 而主要依赖手工制作的特征。手工制作和深层特征具有高解释性和预测准确性的优势。本研究提出了一种新颖的评论有用性预测模型, 利用深度学习技术来考虑手工制作特征和深层特征之间的互补性。

首先, 采用先进的卷积神经网络从非结构化的评论文本中提取深层特征。其次, 本研究利用先前研究中提取的手工制作特征, 这些特征影响了评论的有用性并增强了其解释性。第三, 本研究将深层特征和手工制作特征结合到一个评论有用性预测模型中, 并使用Yelp.com数据集对其性能进行评估。为了衡量所提出模型的性能, 本研究使用了2,417,796条餐厅评论。

广泛的实验验证了所提出的方法优于传统的机器学习方法。此外, 通过实证分析, 本研究证实了结合手工制作和深层特征可以展现出更好的预测性能。

据我们所知, 这是首个在餐厅评论预测中应用深度学习技术, 并结合了结构化和非结构化数据来预测评论有用性的研究之一。此外, 本研究采用了先进的特征融合方法, 更好地利用了提取的特征信息, 并识别了特征之间的互补性。

This paper presents a comprehensive decision-making framework designed for family-owned hotels, specifically focusing on evaluating and selecting suppliers and strategic partners, with a particular emphasis on Iranian holding companies and five-star hotels.

The research emphasizes the unique position of family-owned hotels as not only commercial enterprises but also embodiments of tradition, personal touch and community engagement, which sets them apart in a competitive market. Through a detailed literature review, methodology and analysis, including fuzzy analysis and the TOPSIS method, the study systematically evaluates various criteria crucial for selecting suppliers and strategic partners.

The framework evaluates criteria such as price competitiveness, quality of products/services, reliability and timeliness, flexibility and scalability, communication and responsiveness, after-sales service and support, ethical and sustainable practices, technology and innovation, and compatibility with business culture. By integrating these parameters, the framework addresses both operational needs and strategic objectives, ensuring chosen suppliers and partners align with the hotels' core values and operational requirements.

The study offers valuable insights for family-owned hospitality businesses to navigate supplier and strategic partner selection, and opens avenues for future research, particularly in adapting to technological advancements, sustainability practices and the evolving dynamics of the hospitality industry.

The research underscores the significance of family-owned hotels in fostering tradition, personal connection and community engagement, contributing to the social fabric of the hospitality industry.

This paper provides a unique perspective on supplier and strategic partner selection, tailored for family-owned hotels and offers a comprehensive framework that integrates both operational needs and strategic objectives, ensuring alignment with core values and requirements.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Higher education institutions can utilize sustainability reporting tools as a means of increasing organizational learning and strengthening sustainability. Finding ways to deepen and broaden the nature of learning will help better equip these institutions to address complex challenges like climate change.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.