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This study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.

This study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.

The findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.

This study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.

Knowledge adoption is the key to effective knowledge exchange in virtual question-and-answer (Q&A) communities. Although previous studies have examined the effects of knowledge content, knowledge source credibility and the personal characteristics of knowledge seekers on knowledge adoption in virtual Q&A communities from a static perspective, the impact of answer deviation on knowledge adoption has rarely been explored from a context-based perspective. The purpose of this study is to explore the impact of two-way deviation on knowledge adoption in virtual Q&A communities, with the aim of expanding the understanding of knowledge exchange and community management.

The same question and the same answerer often yield multiple answers. Knowledge seekers usually read multiple answers to make adoption decisions. The impact of deviations among answers on knowledge seekers' knowledge adoption is critical. From a context-based perspective, a research model of the impact of the deviation of horizontal and vertical answers on knowledge adoption is established based on the heuristic-systematic model (HSM) and empirically examined with 88,287 Q&A data points and answerer data collected from Zhihu. Additionally, the moderation effects of static factors such as answerer reputation and answer length are examined.

The negative binomial regression results show that the content and emotion deviation of horizontal answers negatively affect knowledge seekers' knowledge adoption. The content deviation of vertical answers is negatively associated with knowledge adoption, while the emotion deviation of vertical answers is positively related to knowledge adoption. Moreover, answerer reputation positively moderates the negative effect of the emotion deviation of horizontal answers on knowledge adoption. Answer length weakens the negative correlation between the content deviation of horizontal and vertical answers and knowledge adoption.

This study extends previous research on knowledge adoption from a static perspective to a context-based perspective. Moreover, information deviation is expanded from a one-way variable to a two-way variable. The combined effects of static and contextual factors on knowledge adoption are further uncovered. This study can not only help knowledge seekers identify the best answers but also help virtual Q&A community managers optimize community design and operation to reduce the cost of knowledge search and improve the efficiency of knowledge exchange.

Innovative modern technologies are utilised in the hospitality and tourist industry to attract prospective consumers. Travel vlogs have emerged as a type of visual travel blog which includes information regarding tourist destinations, accommodation, cuisine, touristic activities, mode of accessibility, etc. The current study aims to investigate the influence of vlogger credibility on triggering the tourist intention to visit an eco-tourism destination.

The present study is a quantitative study, and it was conducted by surveying 218 respondents. A structured, close-ended and self-administrated questionnaire was used to collect data from the respondents.

The findings indicated that vlogger trustworthiness, expertise and attractiveness significantly impact Bangladeshi tourists' intention towards visiting an eco-tourist destination.

The present study has several theoretical and practical contributions. Theoretically, the research framework illustrated how the vloggers' trustworthiness, expertise and attractiveness on Bangladeshi tourists' visit intention to eco-tourist destinations. Practically, tourism industry practitioners, particularly destination marketers, will get benefit from the present study.

Purpose of This Chapter: This study examines the relationship of ambidextrous leadership with employee voice behaviour, underscoring the intervening role of employee thriving.

Design / Methodology / Approach: This study proposes a conceptual framework based on an extensive literature review using the conservation of resource theory, social exchange theory, and the broaden-and-build theory of positive emotions.

Findings: This study demonstrates that employee thriving act as an underlying mechanism explaining the relationship between ambidextrous leadership and employee voice behaviour.

Research Limitations: Being a conceptual study, the proposed framework lacks empirical validation.

Practical Implications: Organizations should focus on leaders with flexible behaviours who understand situational necessities to adopt diverse leadership styles and contribute to employee thriving.

Originality: This is one of the first studies to propose the role of ambidextrous leadership in impacting and enhancing change in employee voice through employee thriving at work. By introducing a framework that delves into the unexplored territory of ambidextrous leadership, acting as a catalyst for enhancing employee voice via the lens of employee thriving. This study provides a fresh perspective and adds value to the evolving conversations around employee voice behaviour.

Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.

From a technological determinist perspective, machine learning (ML) may significantly contribute towards sustainable development. The purpose of this study is to synthesize prior literature on the role of ML in promoting sustainability and to encourage future inquiries.

This study conducts a systematic review of 110 papers that demonstrate the utilization of ML in the context of sustainable development.

ML techniques may play a vital role in enabling sustainable development by leveraging data to uncover patterns and facilitate the prediction of various variables, thereby aiding in decision-making processes. Through the synthesis of findings from prior research, it is evident that ML may help in achieving many of the United Nations’ sustainable development goals.

This study represents one of the initial investigations that conducted a comprehensive examination of the literature concerning ML’s contribution to sustainability. The analysis revealed that the research domain is still in its early stages, indicating a need for further exploration.

Straightness measurement of rail weld joint is of essential importance to railway maintenance. Due to the lack of efficient measurement equipment, there has been limited in-depth research on rail weld joint with a 5-m wavelength range, leaving a significant knowledge gap in this field.

In this study, the authors used the well-established inertial reference method (IR-method), and the state-of-the-art multi-point chord reference method (MCR-method). Two methods have been applied in different types of rail straightness measurement trollies, respectively. These instruments were tested in a high-speed rail section within a certain region of China. The test results were ultimately validated through using traditional straightedge and feeler gauge methods as reference data to evaluate the rail weld joint straightness within the 5-m wavelength range.

The research reveals that IR-method and MCR-method produce reasonably similar measurement results for wavelengths below 1 m. However, MCR-method outperforms IR-method in terms of accuracy for wavelengths exceeding 3 m. Furthermore, it was observed that IR-method, while operating at a slower speed, carries the risk of derailing and is incapable of detecting rail weld joints and low joints within the track.

The research compare two methods’ measurement effects in a longer wavelength range and demonstrate the superiority of MCR-method.

This study aims to determine consumer satisfaction dimensions that lead to a willingness to share positive emotions through the study of TripAdvisor users’ reviews on St. Petersburg museums. The explorative study reveals the most significant factors that could predict museum visitors’ behavioral intentions.

The study is based on the theory of planned behavior and the “cognitive-affective-conative” model to analyze TripAdvisor reviews (n = 23020) and understand the relationship between the affective and the conative components of consumer behavior. Quantitative text-mining analysis allowed us to view every lemma of every review as a single factor for a deeper understanding of the phenomenon.

The research has enlarged the literature on museum consumer behavior. Behavioral intentions of museum visitors are affected by satisfaction dimensions, especially emotions felt; the esthetic dimension and museums’ surroundings affect consumers’ overall willingness to share positive emotions, while bad service quality and pricing policy make a visit to the museums less satisfying.

Managers can enhance their offerings and attract new consumers by identifying the satisfaction dimensions that influence their intentions to share positive emotions. The research findings can aid museums, tour agencies and government officials in developing targeted products and strategies to meet consumers’ expectations and promote urban tourism.

The research identified the dimensions that influence visitors’ willingness to share positive emotions through user-generated content in the context of museums. The study applies quantitative text analysis based on logit regression, which is a novel approach in the field of urban tourism research.

This study analyses the advantages and weaknesses of using Facebook to aid the learning of Japanese as a foreign language.

A questionnaire survey was conducted to collect data from 100 Hong Kong Japanese language learners (who are generally fluent in Chinese and English), ranging from total amateur to advanced learners (Japanese Language Proficiency Test (JLPT) qualified at different levels).

The authors' results suggest that the advantages of using Facebook to help learn Japanese include: (1) serving as a free-of-charge, casual, and convenient learning platform; (2) enriching learners' knowledge beyond the language learning and (3) encouraging interactive and collaborative learning with other users for practicing the language. However, the low credibility and unstructured educational materials posted on Facebook and being easily distracted by other Facebook feeds are the major weaknesses of learning a language through Facebook. Furthermore, the authors' result shows that Facebook is especially effective for Japanese learning when learners fall into either one of the following groups: young, female, or intermediate (N2/3) learners.

Scant studies focus on the aid of learning Japanese via Facebook, especially Hong Kong learners' perceptions, or generally in the East. Therefore, this study aims to fill this research gap. The authors' findings will facilitate the students, teachers, and language institutions from Hong Kong and other countries to improve the students' effectiveness in learning and teaching Japanese.