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There is a need to predict whether the consumers liked the stay in the hotel rooms or not, and to remove the aspects the customers did not like. Many customers leave a review after staying in the hotel. These reviews are mostly given on the website used to book the hotel. These reviews can be considered as a valuable data, which can be analyzed to provide better services in the hotels. The purpose of this study is to use machine learning techniques for analyzing the given data to determine different sentiment polarities of the consumers.

Reviews given by hotel customers on the Tripadvisor website, which were made available publicly by Kaggle. Out of 10,000 reviews in the data, a sample of 3,000 negative polarity reviews (customers with bad experiences) in the hotel and 3,000 positive polarity reviews (customers with good experiences) in the hotel is taken to prepare data set. The two-stage feature selection was applied, which first involved greedy selection method and then wrapper method to generate 37 most relevant features. An improved stacked decision tree (ISD) classifier) is built, which is further compared with state-of-the-art machine learning algorithms. All the tests are done using R-Studio.

The results showed that the new model was satisfactory overall with 80.77% accuracy after doing in-depth study with 50–50 split, 80.74% accuracy for 66–34 split and 80.25% accuracy for 80–20 split, when predicting the nature of the customers’ experience in the hotel, i.e. whether they are positive or negative.

The implication of this research is to provide a showcase of how we can predict the polarity of potentially popular reviews. This helps the authors’ perspective to help the hotel industries to take corrective measures for the betterment of business and to promote useful positive reviews. This study also has some limitations like only English reviews are considered. This study was restricted to the data from trip-adviser website; however, a new data may be generated to test the credibility of the model. Only aspect-based sentiment classification is considered in this study.

Stacking machine learning techniques have been proposed. At first, state-of-the-art classifiers are tested on the given data, and then, three best performing classifiers (decision tree C5.0, random forest and support vector machine) are taken to build stack and to create ISD classifier.

This issue is a selected bibliography covering the subject of leadership.

The purpose of this paper is to determine the role of service quality (SQ), trust and commitment to customer loyalty (CL) for telecom service users. Further, the moderating role of gender, marital status and connection type within the model was tested.

A measurement model was created based on valid 615 responses from Indian TSUs for SQ, trust, commitment and loyalty with the help of partial least squares structural equation modeling (PLS-SEM). Multi-group analysis (MGA) was conducted to understand the moderating effect of marital status, gender and connection type within the model.

The results suggest that, out of five dimensions of SQ, only responsiveness, assurance and empathy have a significant positive relationship with both commitment and trust. Tangibility has a significant positive relationship with trust only. Both commitment and trust have a significant impact on loyalty. It was noticed that both commitment and trust act as mediators between three SQ dimensions (assurance, empathy and responsiveness) and CL. MGA revealed that empathy and responsiveness positively induce trust in telecom users who are single. Whereas, assurance increases commitment toward telecom service providers in married users. Assurance and empathy significantly contribute toward commitment and trust, respectively, in male users as compared to females. Empathy was found important for postpaid users for trust-building, whereas trust was found to be more important for prepaid users to stay loyal to the service provider.

This article contributes toward understanding the role of SQ, trust and commitment to CL moderated by marital status, gender and connection type in an integrated model concerning telecom service.

This study aims to explore the links among supplier relationship (SR), customer relationship (CR) and supply performance (SP): cost, flexibility, partnership and responsiveness for manufacturing sector in Thailand.

Having extensively reviewed literature, the survey instruments were proposed and validated by experts and statistical techniques. Path analysis of structural equation modeling was used to assess the hypotheses.

It revealed that CR has significant positive direct effects on every SP construct. SR has a significant positive direct effect on CR but has no significant positive effects on SP. However, SR has significant positive total effects and indirect effects on every SP through CR.

This study presents insights into the arguments about the links among SR, CR and SP. SR should not be introduced alone. It should be applied together with CR to improve SP.

Emotional labour (EL) is a complex phenomenon that has received increasing attention in recent years due to its impact on employee’s well-being and job satisfaction. For a comprehensive understanding of the evolving field of EL, it is important to extract different research trends, new developments and research directions in this domain. The study aims to reveal 13 prominent research topics based on the topic modelling analysis.

Using latent Dirichlet allocation (LDA) method, topic modelling is done on 1,462 journal research papers published between 1999 and 2023, extracted from the Scopus database using the keyword “EL”.

The analysis identifies several emerging trends in EL research, including emotional regulation training and job redesign. Similarly, the topics like EL strategies, cultural differences and EL, EL in hospitality, organizational support and EL, EL and gender and psychological well-being of nursing workers are popular research topics in this domain.

The findings provide valuable insights into the current state of EL research and can provide a direction for future research as well as assist organizations to design practices aimed at improving working conditions for employees in various industries.

Topic modelling on emotional labor is done. The paper identifies specific topics or clusters related to emotional labor, quantifies these topics using topic modeling, adds empirical rigor, and allows for comparisons across different contexts.

Although employee race has been an actively investigated area of scientific inquiry for decades, a thorough and informed understanding of the role of race in the organizational sciences has eluded us for a number of reasons. The relationship of race and stress in organizations is a prime example of this neglect and deficiency in our knowledge base, as little work has been done in this area. We attempt to address this limitation in the literature by proposing an inductively derived, review-centric framework that attempts to articulate the multiple intermediate linkages that explain the process dynamics taking place in the relationship between employee race and health and well-being in organizations. We argue that socialization processes, social networks, information and resource access, and mentoring contribute to distance and differences between racial minorities and nonminorities concerning control, reputation, performance, and political understanding and skill, which in turn, creates barriers to success, and increased stress and strain for racial minorities. The implications of this framework along with directions for future theory and research are discussed in this chapter.

Constructive deviance has received increasing attention across the last 20 years. However, because the distinction between constructive and traditional forms of deviance (i.e., destructive) is based on the intent behind the behaviors, it can be difficult to determine which acts are constructive. As an umbrella construct consisting of several forms of deviant acts (e.g., whistle-blowing, employee voice, necessary evils), research into constructive deviance has largely remained focused on the individual behaviors to date. While advancements have been made, this focus has limited the consideration of an overarching understanding of constructive deviance in the workplace. Further, constructs like constructive deviance that straddle the bounds between beneficial and detrimental necessitate the exploration into their antecedents as determined by the employees (i.e., apples), their environments (e.g., barrels), or some combination of the two. The author seeks to advance the research in constructive deviance by proposing a testable model. In which, the author develops an interactionist perspective of the antecedents to reposition constructive deviance as the acts of good employees in restrictive or negative environments. In doing so, the author considers how various aspects of individuals, their organizational environments, and the influence of their leaders interact. The author then develops a multi-stakeholder approach to the outcomes of constructive deviance to consider how the various parties (i.e., organization, coworkers, customers) are expected to respond and how these responses impact the more distal outcomes as well as the likelihood of engaging in future constructive deviance.

One area in which strategy and organizational ecology converge is organizational change. This essay weaves together salient themes in my (and my co-authors’) various writings on organizational change, and is anchored in the research literature of the last twenty years. Among other ideas developed here, I point out that there is now a convergence of agendas in strategy and ecology, with an important role being played by intraorganizational ecology. I develop the distinction between strong and weak selection approaches to organizational ecology. While the strong selection view does not find empirical support, there is stronger support for the weak selection view. I lay out some key features of an emerging evolutionary synthesis for the study of strategy and organization, and develop an evolutionary approach to organizational change.