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The purpose of this paper is to analyze the Bayes acceptance plan of the parallel system for pre‐specified consumer's and producer's specifications regarding the system availability.

This study considers Bayesian technique to examine the acceptance plan for steady state availability of a parallel system for half‐normal failure as well as repair time.

If there is variation(s) in mean availability of the test plan, then according to their admissible risks producer and consumer may choose a suitable plan.

The methodology proposed in the paper represents Bayes acceptance plan for testing the lots of the parallel system model when failure and repair time follows half‐normal distribution.

The main objective of this paper is to consider the problem of strength of a manufactured item against an array of stresses, when each component follows exponential failure law.

The study considers a system consisting of n components in a series with lifetimes that follow exponential failure law and applies a competing failure model to examine the strength reliability of the system.

In process of developing a new product, the engineer is given the goal for the system and must then develop a design that will achieve the desired reliability of the system, while performing all of the system's intended functions at a minimum cost. The paper involves a balancing act of determining how to distribute reliability to the components in the system, so that the system will meet all the other associated performance specifications.

The application of the proposed technique will not only help the reliability engineers/managers/system engineers to understand the design methodology of the system, but also lead to the problem of addressing the risks involved in perceived quality and reliability levels by eliminating or at least reducing the risk‐impact at the design phase.

The main objective of this paper is to consider the problem of a system amenable to maintenance and to provide to posterior analysis, Bayesian point estimators and Bayesian availability analysis of a k− out of −m system with geometric failure as well as repair time distribution.

The study considers a Bayesian approach, treats these population models as random quantities and makes good use of old information to construct a prior distribution model for these parameters, and then make use of current data to revise this starting assessment in the form of a posterior distribution model for the population model parameters, while the primary motivation to use a Bayesian reliability method is typically a desire to save on test time and materials cost.

The study clearly demonstrates that, when inspections are performed at specific intervals, time is not continuous and is measured on a discrete scale. It considers the number of successful cycles or operations before failure, then the repair process helps to improve the system reliability.

The proposed methodology represents an efficient way to evaluate the maintenance performance when time is not continuous and measured on a discrete scale.

This study aims to contribute to literature on mobile learning (m-learning) by proposing four research clusters whereby scholars can expand m-learning research to facilitate effective learning experiences for students.

This study reviews student-centric literature on m-learning since 2010 and presents insights on m-learning while applying well-established bibliometric techniques. Consequently, 722 articles published in the past decade were evaluated by identifying key research areas, most influential authors, countries, journals and organisations. Most influential studies based on number of citations were also examined.

Through article co-citation analysis, four clusters representing m-learning literature were identified: concept of m-learning, application of m-learning in education, designing framework for model learning/acceptance and emerging technologies.

As mobile learning (m-learning) has undergone an evolution from being an emerging field to a significant teaching and research tool, it is pertinent to explore and identify the trends of m-learning research.

While prior research has examined customer acceptance of humanized chatbots, the mechanisms through which they influence customer value creation remain unclear. This study aims to investigate the emerging concept of Perceived Humanization (PH), examining how hedonic motivation, social influence and anthropomorphism influence value creation through the serial mediation of PH and trust. The moderating roles of rapport and social presence are also explored.

Based on data from an online survey involving 257 respondents, this study employs Partial Least Squares Structural Equation Modeling utilizing SmartPLS3 software.

Hedonic motivation leads to value creation via two routes: PH and affective trust; and PH and cognitive trust. Social influence and anthropomorphism also positively impact value creation through similar pathways. Rapport moderates the impact of social influence on PH, while social presence moderates the relationship between PH and both affective and cognitive trust. A cross-cultural analysis of China, India and New Zealand highlights varying cultural dimensions influencing PH and its effects on value creation.

For practitioners in the tourism industry, the findings highlight the strategic importance of enhancing PH in chatbot interactions. By understanding and optimizing these elements, businesses can significantly improve their customer value-creation process.

This study contributes to the service marketing literature by generating a comprehensive framework for the comprehension and application of PH. Its cross-cultural perspective provides rich insights, offering valuable information for service marketers aiming to thrive in the dynamic and competitive tourism industry.

The purpose of this study is to investigate the factors that influence eco-friendly apparel purchase behaviors concerning Bangladeshi young consumers in light of the theory of planned behavior.

Data were collected by a survey among 198 respondents in Bangladesh in terms of consumer attitude, subjective norm (SN), perceived behavioral control (PBC), environmental concern (EC), environmental knowledge (EK) and purchase intention (PI). Structural equation modeling approach was used to find out the influencing factors.

The study reveals that purchase intention is significantly influenced by attitudes, SN, EC and EK of consumers. Consumers perceived behaviors variable is always not an accurate predictor to control actual purchase behavior. SN and EK were found to be highly influential to eco-friendly apparel purchase patterns among young consumers in Bangladesh.

This study provides key marketing insights for retailers and practitioners on how strategically they can decide for fashion consumers, specifically the young group in Bangladesh. Eco-friendly apparel purchase behaviors will gradually influence the retail business contexts for retailers. The study reveals the need for eco-labeling and marketing strategies of eco-friendly apparel products among young consumers to communicate benefits and green values among wider consumers. Findings were restricted to specific young consumers group in Bangladesh and did not examine purchase behaviors of other consumer segment.

The study reveals that Bangladeshi young consumers are becoming concerned about purchasing apparel products. It provides valuable insights for entrepreneurs, practitioners and marketers to trace and perceive purchase behavior of the Bangladeshi young consumers while adopting a strategic marketing approach.

The study uses VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR)-structural equation modeling (SEM) to construct benchmarks for service providers and evaluate a multimethodology practice in the Internet industry.

The data were collected using a survey based on an email/interview with 444 Internet users participating. SEM obtained coefficient values by way of customer expectations for Internet service providers. The authors normalized coefficients and integrated them into the VIKOR method for ranking competitors in the Internet industry.

VIKOR-SEM revealed that network and information quality and security/privacy significantly positively impact customer trust while network and information quality and customer trust significantly positively affect Internet users' value perceptions. Customer services do not affect customer trust, while security/privacy and customer services have no significant influence on customer value perceptions. Though customer services and Internet users' trust and value perceptions directly, significantly and positively affect their commitments, the quality of network and information and security/privacy indirectly, significantly and positively influence customer commitments.

The study was in the Internet industry of Iraq. The results cannot be accurate for the other countries and the service sectors. The researchers/managers can adopt the model in other service sectors to test the multimethodology.

VIKOR-SEM evaluated the changes in customer expectations and service providers in the Internet industry.

In this study, we have collected the response from 200 private university lecturers in Kurdistan Region of Iraq. In order to test the hypotheses, we have proposed structural equations modeling (SEM).

The purpose of this paper is to elaborate the direct and indirect effects of e-service quality on perceived value, satisfaction and willingness to pay for online meeting platforms in the education sector. This study also explores the effect of e-service quality on users' perception and satisfaction.

The results reveal that e-service quality directly affects the perceived value and satisfaction but has no direct effect on the willingness to pay. Secondly, perceived value and satisfaction mediated the relationships between service quality and willingness to pay. However, it is observed that perceived value has a more significant impact on the willingness to pay compared to satisfaction. It is further reported that perceived value is one of the antecedents of satisfaction. The study also explores the direct relationship between perceived value and willingness to pay, and introduces satisfaction as a mediating variable between perceived value and willingness to pay.

The sample is geographically limited as only online faculty and staff working at private universities participated in the study. This study has implications for administrators of higher educational institutions and companies providing IT solutions for online meetings. From a managerial standpoint, this study provides and IT companies a broad theoretical basis that designing a successful online meeting platform should specifically emphasize e-service quality, perceived value and customer satisfaction.

There is no study that evaluated the links among e-service quality, value, satisfaction, and willingness to pay for the online meeting platform services. Therefore, this study is useful for the private university administration and online meeting platform developers and investors.

The purpose of this paper is to expand and analyze deeply customer emotions, concretize the levels of positive or negative emotions with the aim of using machine learning methods, and build a model to identify customer emotions.

The study proposed a customer emotion detection model and data mining method based on the collected dataset, including 80,593 online reviews on agoda.com and booking.com from 2009 to 2022.

By discerning specific emotions expressed in customers' comments, emotion detection, which refers to the process of identifying users' emotional states, assumes a crucial role in evaluating the brand value of a product. The research capitalizes on the vast and diverse data sources available on hotel booking websites, which, despite their richness, remain largely unexplored and unanalyzed. The outcomes of the model, pertaining to the detection and classification of customer emotions based on ratings and reviews into four distinct emotional states, offer a means to address the challenge of determining customer satisfaction regarding their actual service experiences. These findings hold substantial value for businesses operating in this domain, as the findings facilitate the evaluation and formulation of improvement strategies within their business models. The experimental study reveals that the proposed model attains an exact match ratio, precision, and recall rates of up to 81%, 90% and 90%, respectively.

The study has yet to mine real-time data. Prediction results may be influenced because the amount of data collected from the web is insufficient and preprocessing is not completely suppressed. Furthermore, the model in the study was not tested using all algorithms and multi-label classifiers. Future research should build databases to mine data in real-time and collect more data and enhance the current model.

The study's results suggest that the emotion detection models can be applied to the real world to quickly analyze customer feedback. The proposed models enable the identification of customers' emotions, the discovery of customer demand, the enhancement of service, and the general customer experience. The established models can be used by many service sectors to learn more about customer satisfaction with the offered goods and services from customer reviews.

The research paper helps businesses in the hospitality area analyze customer emotions in each specific aspect to ensure customer satisfaction. In addition, managers can come up with appropriate strategies to bring better products and services to society and people. Subsequently, fostering the growth of the hotel tourism sector within the nation, thereby facilitating sustainable economic development on a national scale.

This study developed a customer emotions detection model for detecting and classifying customer ratings and reviews as 4 specific emotions: happy, angry, depressed and hopeful based on online booking hotel websites agoda.com and booking.com that contains 80,593 reviews in Vietnamese. The research results help businesses check and evaluate the quality of their services, thereby offering appropriate improvement strategies to increase customers' satisfaction and demand more effectively.

The aim of this paper is to explore the relationship between perception of service quality, student satisfaction, switching barriers on behavioural intentions among private higher education institutions (HEIs) with self-accreditation status in Malaysia.

A total of 388 valid questionnaires were collected via a self-administered questionnaire from the undergraduate students of private HEIs with self-accreditation status in Malaysia. PLS-SEM has been employed for hypotheses testing.

The results show that student perceived service quality is positively influence student satisfaction and student behavioural intentions, particularly the positive word-of-mouth (WOM). The relationship of student perceived service quality and student behavioural intentions is fully mediated by student satisfaction. However, there is no mediating effect found for the switching barriers on the relationship between student satisfaction and behavioural intentions.

This study's findings are only generalizable to the private HEI with self-accreditation status in Malaysia. The paper contributes to the body of knowledge in the areas of service quality, satisfaction, switching barriers and behavioural intentions. These findings provide valuable insight to the private universities management and policymakers to improve existing policies and practices in order to formulate effective strategies to attract potential new students and retain the existing students through the delivery of high-quality services.

This study's findings have reconfirmed that the causal relationship of perceived service quality-satisfaction-behavioural intentions model. Switching barriers has treated as the mediator which received less attention in the context of private higher education sector. Thus, this study broadens the exiting body of knowledge and advances the understanding of how switching barriers play a crucial role by influencing students' behavioural intention, particular WOM.