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This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

This study aims to investigate the performance analysis, science mapping and future direction of artificial intelligence (AI) technology, applications, tools and software used to preserve, curate and predict the historical value of cultural heritage.

This study uses the bibliometric research method and utilizes the Scopus database to gather data. The keywords used are “artificial intelligence” and “cultural heritage,” resulting in 718 data sets spanning from 2001 to 2023. The data is restricted to the years 2001−2023, is in English language and encompasses all types of documents, including conference papers, articles, book chapters, lecture notes, reviews and editorials.

The performance analysis of research on the use of AI to aid in the preservation of cultural heritage has been ongoing since 2001, and research in this area continues to grow. The countries contributing to this research include Italy, China, Greece, Spain and the UK, with Italy being the most prolific in terms of authored works. The research primarily falls under the disciplines of computer science, mathematics, engineering, social sciences and arts and humanities, respectively. Document types mainly consist of articles and proceedings. In the science mapping process, five clusters have been identified. These clusters are labeled according to the contributions of AI tools, software, apps and technology to cultural heritage preservation. The clusters include “conservation assessment,” “exhibition and visualization,” “software solutions,” “virtual exhibition” and “metadata and database.” The future direction of research lies in extended reality, which integrates virtual reality (VR), augmented reality (AR) and mixed reality (MR); virtual restoration and preservation; 3D printing; as well as the utilization of robotics, drones and the Internet of Things (IoT) for mapping, conserving and monitoring historical sites and cultural heritage sites.

The cultural heritage institution can use this result as a source to develop AI-based strategic planning for curating, preservation, preventing and presenting cultural heritages. Researchers and academicians will get insight and deeper understanding on the research trend and use the interdisciplinary of AI and cultural heritage for expanding collaboration.

This study will help to reveal the trend and evolution of AI and cultural heritage. The finding also will fill the knowledge gap on the research on AI and cultural heritage.

Some similar bibliometric studies have been conducted; however, there are still limited studies on contribution of AI to preserve cultural heritage in wider view. The value of this study is the cluster in which AI is used to preserve, curate, present and assess cultural heritages.

This chapter focuses on the COVID-19 pandemic’s impact on the recognition through discourses of essentiality, of low-status workers and more specifically of care aides as an occupational group that performs society’s ‘dirty work’. The pandemic appears as a privileged moment to challenge the normative hegemony of how work is valued within society. However, public recognition through political discourse is a necessary but insufficient element in producing social change. Based on the theory of performativity, this chapter empirically probes conditions and mechanisms that enable a transition from discourse of essentiality to substantive recognition of the work performed by care aides in healthcare organizations. The authors rely on three main sources of data: scientific-scholarly works, documents from government, various associations and unions, and popular media reports published between February 2020 and 1 July 2022. While discourse of essentiality at the highest level of politics is associated with rapid policy response to value the work of care aides, it is embedded in a system structure and culture that restrains the establishment of substantive policy that recognizes the nature, complexity, and societal importance of care aide work. The chapter contributes to the literature on performativity by demonstrating the importance of the institutionalization of competing logics in contemporary health and social care systems and how it limits the effectiveness of discourse in promulgating new values and norms and engineering social change.

This study aims to investigate the role of negative media coverage of environmental, social and governance (ESG) issues in deterring tax avoidance. Inspired by media agenda-setting theory and legitimacy theory, this study hypothesises that an increase in ESG negative media coverage should cause a reputational drawback, leading companies to reduce tax avoidance to regain their legitimacy. Hence, this study examines a novel channel that links ESG and taxation.

This study uses panel regression analysis to examine the relationship between negative media coverage of ESG issues and tax avoidance among the largest European entities. This study considers different measures of tax avoidance and negative media coverage.

The results show that negative media coverage of ESG issues is negatively associated with tax avoidance, suggesting that media can act as an external monitor for corporate taxation.

The findings have implications for policymakers and regulators, which should consider tax transparency when dealing with ESG disclosure requirements. Tax disclosure should be integrated into ESG reporting.

The study has social implications related to the media, which act as watchdogs for firms’ irresponsible practices. According to this study’s findings, increased media pressure has the power to induce a better alignment between declared ESG policies and tax strategies.

This study contributes to the literature on the mechanisms that discourage tax avoidance and the literature on the relationship between ESG and taxation by shedding light on the role of media coverage.

This paper aims to provide a critical reflection on the management of experiences in hospitality and tourism (H&T). The paper investigates the evolution of experience research, while discussing the emerging challenges and opportunities for management.

The study adopts a critical and reflective approach for providing future directions of experience research. Three major fields are identified to discuss advances, challenges and opportunities in experience research: conceptualization and dimensions of experiences; relational network for experience management; and theoretical and methodological approaches.

The paper proposes a mindset shift to guide experience research, but also to redirect and research thinking and managerial practices about the role of experiences in the economy and society. This proposed humanized perspective to experience research and management is deemed important given the contemporary socio-economic, environmental and technological challenges of the environment.

This paper identifies a set of theoretical and managerial implications to help scholars and professionals alike to implement the humanized perspective to experience research. Implications relate to conceptualization, relational network and theoretical and methodological approaches in experience research.

This study critically assesses research challenges and opportunities around customer experience management (CEM) in H&T contexts. This reflective and critical look at customer experiences not only informs future research for advancing knowledge and practice but also proposes a mindset shift about the role and nature of CEM in the society and economy.

Middle-aged and elderly users become an important group on short-video platforms, however, the research on determinants of their video-creating intention is limited. Based on lifespan development theories, this study examines the impact of aging experiences on their video-creating intention, considering internal generative motivations as mediators and age as a moderator.

To test this study’s hypotheses, survey data from 321 Chinese middle-aged and elderly short-video users were collected and partial least square-structural equation modelling (PLS-SEM) approach was used to analyze these data.

Middle-aged and elderly users' aging experiences of social loss and personal growth are positively related to their video-creating intention. Aging experiences (i.e. physical loss, social loss, and personal growth) are positively related to internal generative motivations (i.e. need to be needed and symbolic immortality), and need to be needed is positively related to video-creating intention. Via the mediation of need to be needed, physical loss and personal growth are indirectly positively related to video-creating intention. Personal growth strengthens the relationship between physical loss and symbolic immortality, but weakens the associations of social loss with need to be needed and symbolic immortality. Age weakens the relationship between symbolic immortality and video-creating intention.

This study is the first wave to introduce and integrate lifespan theories such as selective optimization with compensation model, socioemotional selectivity theory, and generativity theory to explore the impacts of aging experiences on middle-aged and elderly users' video-creating intention by considering generativity motivations as mediators and age as a moderator.

Although trade volumes in e-retailing have increased significantly in recent years, logistics service failures are inevitable, especially at the delivery stage. Therefore, it is essential to provide customers with effective recovery strategies to increase their satisfaction and repurchase intentions. There is a lack of empirical evidence on whether the response time or the discount offered in compensation is more crucial for customers. Therefore, this study aims to determine whether the response time or the discount offered for high and low criticality failures has a greater impact on customer satisfaction levels and repurchase intentions for female and male customers.

A scenario-based experimental design method has been adopted to collect data, and 697 participants aged 18 and 58 years have been reached. The research utilized a between-subjects design, incorporating three factors: gender (female vs male), criticality (high vs low) and compensation (7 days: 10% discount, 10 days: 20% discount and 14 days: 30% discount). Six scenarios depicting the failure of an online retailer were created, and factorial univariate ANOVA was conducted to test the hypotheses.

The study's results show that in terms of customer satisfaction, female customers attach more importance to the response time in the case of high criticality and the amount of discount offered in the case of low criticality. On the other hand, male customers give more importance to the response time in terms of customer satisfaction when they experience a high or low criticality failure. In the case of low criticality, response time is more important for male customers to increase their repurchase intentions, while the amount of the discount is more important for female customers.

The study demonstrates the relative importance of the response time and discount amount according to the criticality level of failures and to guide business managers in terms of the recovery strategies they will implement. It focuses on gender differences and determine whether the response time or discount amount is more important for male and female customers in high or low-criticality situations.

Unacceptable behaviour in retailing – negative customer deviance (NCD) is rising, damaging retailers financially. Current research investigates forms of NCD by addressing its impact on employees but overlooks its effects on bystander-customers and their retail channel preferences. As channel switching within retailing is increasing unprecedentedly, this research investigates its correspondence with NCD encounters.

This research uses structural equation modelling, based on data collection administered through a web-based survey of 1,008 customers of at least 16 years of age, to analyse the research model.

The findings reveal unexplored forms of NCD perceived by bystander-customers in retailing and their consequences, linking it to bystander-customers' ill-being, dissatisfaction with the shopping experience, a decrease in store commitment and an increase in their retail channel-switching intentions. Additionally, the research uncovers moderating variables.

This research tests NCD dimensions and effects on bystander-customers, which indicate the need for retailers to address shopping values, attitudes and commitment through corrective, proactive and long-term strategic actions.

As one of the first studies to investigate the impact of NCD on bystander-customers' intentions to switch from store-based to online shopping, strategies for retailers are developed to help diminish and control NCD-induced threats to bystander-customers.

As the Philippines enters into the era of the “next normal,” that is, from the pandemic era called the “new normal,” we look into how the Philippines' state of tourism and built environment sectors. We also revisit its situation having the “longest lockdown in the world” and look into iterations of socioeconomic models, business platforms, and other elements that lead to the dream of a postpandemic sustainable tourism industry. In this inquiry, we highlight the importance of elements of the built environment, both at the macroeconomic level and at the micro units of business, civil society, and the tourism sector at large. While there has been a substantive discussion on the nexus of the tourism and built environment sectors, little has been devoted to the challenges these intertwined sectors faced during the COVID-19 pandemic. We suggest complementation of practices from the macroscale to the microlevel tourism and built environment sectors, and vice-versa, which will ensure the full complementation of the sectors. These proposals are in full contextualization of the objective toward the postpandemic continued recovery, growth, and sustainability, from the local, national, and the regional economy of Southeast Asia, and also to various parts of the world.