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In the present study, we examined how effectively online travel agencies (OTAs) handle negative e-word-of-mouth on social media platforms like Facebook, Twitter, and Instagram. We collected data from 497 participants using survey method. To test the hypotheses formulated from the existing literature, structural equation modeling was adopted in this study. The results from structural equation modeling indicate effective handling of the negative e-word of mouth (e-WOM) on social media websites significantly affects customer satisfaction and repurchase intention. The current research work provides insight into social media recovery efforts and service fairness when handling negative e-WOM. The study recommends that customers can distinguish the differences between general efforts and adaptive complaint-handling efforts, and dissimilarities may influence satisfaction, repurchase intentions, etc. Although empathy, apology, responsiveness, and paraphrasing are considered pioneer strategies in complaint handling, customers' negative e-WOM, and firms' recovery management, but the current study is among a few to categorize OTAs' handling of negative e-WOM and complaint handling efforts in the social media environment.

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.

Purpose: This paper aims to study the impact of adoption eXtensible Business Reporting Language (XBRL) on earnings management.

Design/methodology/approach: This study uses a sample of all firms listed on the Indonesian stock exchange, except for finance and real-estate sectors from 2012 to 2019, with a total of 2,560 firms–years with panel data analysis.

Findings: Four findings in this study are listed as follow. First, the surprising result is that accrual earnings management increase after the adoption of XBRL. Second, after the adoption of XBRL, there was an increase in real earnings management. Third, the results of the study prove that the use of Big 4 auditors will weaken the increase in real earnings management after the adoption of XBRL. Finally, this study shows that after the adoption of XBRL, it turns out that both accrual and real earnings management experienced an increase.

Originality/value: This study contributes to providing an evaluation note to IDX regulators that the goals they want to achieve have not been achieved. This study provides empirical evidence for the debate over whether the adoption of XBRL is beneficial.

Purpose: This study examines the effect of uncertainties on the hospitality industry from different perspectives across the globe. The hospitality industry faces several contemporary issues and challenges that have the potential to impact its growth and development. This study aims to analyse the current problems and uncertainties in the hospitality sector.

Need for the Study: The hospitality industry plays a significant role in the global economy with various services, including accommodation, food and beverage, events, and tourism. However, the sector faces several contemporary issues and challenges that have the potential to impact its growth and development. This study provides an overview of the most significant problems and challenges facing the hospitality industry today.

Methodology: A systematic literature review was conducted to identify and synthesise relevant studies on the effect of uncertainties issues on the hospitality industry. A systematic search of the Web of Science and Scopus databases was conducted to determine relevant studies published between 2010 and 2021. Studies were screened and selected based on pre-defined inclusion and exclusion criteria. A thematic analysis was performed to categorise the uncertainties and issues in the hospitality industry.

Findings: The study identified several uncertainties and issues facing the hospitality industry, including the pandemic uncertainties, financial crisis, whether positive and negative impacts, terrorism attacks on hotels and tourist places, uncertainties in government policies, situational risks like uncertainties, ambiguity, cultural differences, changes in tourist preferences and changing habits of the tourist.

Purpose: The aim of this chapter is to provide a quantitative literature review on machine learning (ML) and artificial intelligence (AI) in the Insurance Sector.

Need for the Study: The current study maps the literature regarding AI and ML in the insurance sector through bibliometric tools to identify the significant gaps in the available literature, considerable insights that emerged, and a scientific evaluation of AI and ML in the Insurance sector.

Methodology: The VOS viewer method was used to conduct the depth and quantitative analysis of the AI and ML in Insurance. The study of 450 articles has been retrieved through the Scopus database from 2012 to 2021. The implication of performance analysis methods has helped to explore influential journals, authors, countries, Keywords, and affiliations, elevating the literature in AI and the Insurance Sector.

Finding: This study conducts an exploratory analysis and identifies the prominent authors, sources, countries, affiliations, and articles using modern bibliometric analysis (BA) tools. The geographic scattering of the study indicates that the USA and the UK have highly influential publications and contribute to AI and Insurance. East and Southern Asia countries are far behind.

Practical Implication: Furthermore, this chapter can be used as a reference paper to explore the new field of study in the insurance sector using AI. The search criteria were set in the study to limit the sample published papers/articles included in Scopus data based on the AI and ML in Insurance.

Cities and the tourism industry are closely related. Cities are destinations that serve for the welfare of the people and the tourists visiting the city. The tourism sector, on the other hand, uses the environmental and sociocultural resources of the cities, ensures that these resources are transferred to the future by protecting them, and contributes to the economic development of the cities by creating employment. Several urban models have been created within this framework to make urban tourism viable. Eco-city tourism is one of these urban design concepts. Eco-city tourism aims to protect cities from sociocultural, economic, and environmental factors while promoting their growth. Eco-city tourism, which includes a number of practices such as prevention of pollution, protection of biological diversity, consumption of renewable energy, production of local products, employment, and protection of cultural values, is easily implement in cities in an integrated manner with smart technological systems. Smart building and smart energy systems for energy saving, mobile applications, Wi-Fi, big data, Internet of Things (IoT), and cloud computing are among the smart technological systems used in the tourism sector.