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Between 1840s and 1940s, 27 occidental concessions have been created in several cities in China which represented difficult signs and memories for Chinese. Nowadays, these territories are experiencing a joint phenomenon of heritagization and tourismification which makes them experimental theaters for modern urban life and identity. Taking the former concessions of Tianjin as place study, the purpose of this study is to analyze the role of the heritage and tourism in the former concessions in city branding and more specifically the actors, approaches and products of this phenomenon.

This research draws on the comparison and analysis of two place studies in China. The authors base their analysis on semi-structured interviews in Chinese with previously identified stakeholders. In all, 20 individuals, including developers, public authority representatives, business owners, academics and conservation association members, were interviewed. This research was completed, updated and triangulated by content analysis of Web-based materials; official documents such as urban plans, guidelines and urban and tourism strategies collected during the fieldwork, as well as non-intrusive spatial observations of the concession and its various developments.

The results of this study show that the heritage in the former concessions has become an attractive tool for the city branding through tourism development, often led by the public actors with the participation of private entrepreneurs.

This study looks at the hybrid dimensions of the former concessions in China. It provides a better understanding of the co-action of heritage and tourism in the processes of territorial rehabilitation, which contributes to both the practitioners and researchers in this domain.

In this article, the aim is to document the divergences/convergences between the market perceptions of quality and the financial estimations for office buildings relative to the notion of centrality and the distance to the central business district (CBD).

Based on a hierarchical approach that decomposes and estimates the perceived quality of buildings from the stakeholders’ perspectives, we study the geographies of perceived quality measures in the Greater Paris Metropolis and compare them to the financial geography.

The perceived location quality decreases with distance from the CBD whereas judgments on the built structure and the workplace do not, exhibiting a ring-shaped pattern. The gradient of the components of the perceived quality are heterogeneous, having positive, negative or null values. Appraisers tend only to consider the quality of location in their estimations.

This article raises the issue of fair spatial judgments by appraisers and the financial market. Monocentricity is not the rule in the market perceptions of quality. It suggests that financial estimates are strongly biased, with mental representation of centrality as a judgmental heuristic.

Prior research has revealed that a large share of managers is reluctant towards the use of artificial intelligence (AI) in decision-making. This aversion can be caused by several factors, including individual drivers. The purpose of this paper is to better understand the extent to which individual factors influence managers’ attitudes towards the use of AI and, based on these findings, to propose solutions for increasing AI adoption.

The paper builds on prior research, especially on the factors driving the adoption of AI in companies. In addition, data was collected by means of 16 expert interviews using a semi-structured interview guideline.

The study concludes on four groups of individual factors ranked according to their importance: demographics, familiarity, psychology and personality. Moreover, the findings emphasized the importance of communication and training, explainability and transparency and participation in the process to foster the adoption of AI in decision-making.

The paper identifies four ways to foster AI integration for organizational decision-making as areas for further empirical analysis by business researchers.

This paper offers four ways to foster AI adoption for organizational decision-making: explaining the benefits and training the more adverse categories, explaining how the algorithms work and being transparent about the shortcomings, striking a good balance between automated and human-made decisions, and involving users in the design process.

The study concludes on four groups of individual factors ranked according to their importance: demographics, familiarity, psychology and personality. Moreover, the findings emphasized the importance of communication and training, explainability and transparency and participation in the process to foster the adoption of AI in decision-making.

This study is one of few to conduct qualitative research into the individual factors driving usage intention among managers; hence, providing more in-depth insights about managers’ attitudes towards algorithmic decision-making. This research could serve as guidance for developers developing algorithms and for managers implementing and using algorithms in organizational decision-making.

This paper aims to assess the impact of regulatory changes on corporate environmental disclosure practices in Europe. More specifically, the authors perform a difference-in-differences analysis to study the impact of the Paris agreement (United Nations Climate Change Conference, COP21) and of the French Law 2015-992 on energy transition for green growth.

The sample consists of the listed companies belonging to the Euro Stoxx 50 index, and they are analysed over the 2010–2019 time horizon by means of an expert validated environmental disclosure dictionary and difference-in-differences analysis.

The main results show that both regulatory interventions contributed to improving corporate environmental disclosure. The authors also show that firms belonging to the most polluting sectors tend to provide more information on environmental matters, likely in an attempt to divert stakeholders’ attention.

By analysing an under-investigated topic, the paper calls for significant efforts by regulators to find the most suitable solutions to induce firms to increase their levels of transparency on the impact of environmental risks and on how these risks are managed.

This study aims to investigate how a firm's management team's capacity to efficiently use its resources affects the firm's exposure to climate change. Specifically, the authors investigate the intriguing question – does managerial ability affect a firm's climate change exposure?

The authors use an unbalanced panel dataset of 4,230 US based firms listed on Compustat from 2002–2019 and test the hypothesis by panel regression analysis. To mitigate endogeneity concerns, difference-in-differences and instrumental variable approaches are used.

The baseline analysis shows a negative, statistically significant impact of managerial ability on climate change exposure. The findings hold after controlling for endogeneity using two-stage least squares regression and difference-in-differences tests. The authors find the negative effect is stronger for managers engaged in socially responsible activities, and after climate change issues receiving greater public awareness following the 2006 release of the Stern Review and the 2016 signing of the Paris Accord.

Motivated by the resource-based theory and the natural resource-based view of the firm model, the empirical results support the view that greater managerial ability protects the firm against environmental challenges through efficient use of firm resources. Compared with traditional climate change measures that are plagued by disclosure issues, the use of the Sautner, Van Lent, Vilkov and Zhang's machine learning based dataset utilizing earning conference calls provides stronger, robust findings that will be useful to management and investors in environmental performance assessments.

Motivated by the resource-based theory and the natural resource-based view of the firm model, the empirical results support the view that greater managerial ability protects the firm against environmental challenges through efficient use of firm resources. Compared with traditional climate change measures that are plagued by disclosure issues, the use of the machine learning based dataset utilizing earning conference calls provides stronger, robust findings that will be useful to management and investors in environmental performance assessments.

This study aims to introduce and define the concept of phygital brand community (PBC). It discusses the potential conflicts that can arise from engaging in multiple PBCs and propose an enriched netnographic methodological approach to explore the role of PBC engagement overlap and its influence on the phygital experience.

Following a critical analysis of the inherent limitations of netnographic methodological approaches in the context of PBCs, this study develops an enriched netnographic research protocol that accounts for the challenges of engagement overlap among PBCs.

This study proposes two methods of analysis, namely, “participatory netnography” and “witness netnography,” which are derived from a mixed-methodology approach that integrates elements of netnography.

The findings of this study underscore the requisite methodological refinements imperative for enhancing netnographic analysis, particularly in its application for a better comprehension of individual behaviors within the realm of PBCs. In pursuit of this objective, the identified adjustments encompass ethical considerations, evaluation methods and their application in a digital milieu, where intricate mechanics and technologies frequently elude conventional methodologies.

In this study, the authors present a novel conceptualization of PBCs, highlighting their role and development, as well as the challenges they pose. To adequately capture the impact of PBC engagement overlap, the authors propose the need for an enriched mixed-methodological approach.

This study aims to examine the impact of the COVID-19 pandemic on knowledge-sharing drivers in small- and medium-sized family firms within the restaurant and fast-food industry. The pandemic has led to significant changes in business culture and consumer behaviour, accelerating digital transformation, disruptions in global supply chains and emerging new business opportunities. These changes have also influenced knowledge sharing (KS) and its underlying drivers.

To address the research objectives, a two-phase study was conducted. In the first phase, an exploratory analysis using the Delphi method was used to identify the essential drivers and factors of KS in family businesses (FBs). This phase aimed to establish a conceptual model for the study. In the second phase, confirmatory factor analysis was conducted to analyse the impact of the COVID-19 pandemic on the identified knowledge-sharing drivers. The study examined both the pre-pandemic and post-pandemic periods to capture the shifts in attitudes towards KS.

The findings indicate a significant shift in attitudes towards knowledge-sharing drivers. Before the pandemic, organisational drivers played a central role in KS. However, after the emergence of the pandemic, technological drivers became more prominent. This shift highlights the impact of the COVID-19 pandemic on KS within FB.

The research contributes to understanding knowledge-sharing in the context of FBs and sheds light on the specific effects of the COVID-19 pandemic on knowledge-sharing drivers. The insights gained from this study can inform strategies and practices aimed at enhancing KS in similar organisational settings.

This research paper aims to explore how social intrapreneurs use serious games to generate social innovation. In particular, the study depicts the coproduction process between caregivers acting as intrapreneurs, patients and other stakeholders, and unveils the contributions of serious games and their key features in producing social innovation within healthcare facilities.

Through an original case study, the article analyzes a social innovation initiated by caregivers in the French care eco-system. Primary and secondary data were used to observe and examine the successful implementation of a serious game. Specifically, caregivers in hospital designed a game that helps children overcome the stress and anxiety inherent to their hospital journey.

Results unveil the role of social innovations as catalyst of social intrapreneurship and the coproduction of services. In the healthcare setting, serious games both participate in improving the stay of child in hospitals, and in facilitating the working conditions of caregivers.

This article brings together the theoretical background of social intrapreneurship, social innovation and serious games. The successful implementation of social innovation depends on the intrinsic features of social intrapreneurs, coupled with those pertaining to serious games. The positive outcome of social innovation benefits both internal and external stakeholders. Such innovation improves the end users' experience, as the latter participate in the coproduction of their own care.

The purpose of this study is to explore the paranormal tourist experience on ghost tours, taking into account the participants’ perceptions and their prior knowledge of the paranormal, in order to determine the principal components of the future of paranormal tourist experience.

The study is divided into two phases. The first phase is based on participant observation during a ghost tour. The second phase is based on a previously published framework for paranormal tourism. It introduces a qualitative adaptation of the orchestra model to look in-depth at how experiences with paranormal tours might shape the future of tourism as a major subtype.

Paranormal tourism has external (situational-enchantment, historical, mystical, ghostly and unsolved mysteries) and internal (affective, cognitive, sensory, behavior and relationship) components that are inter-linked. Future paranormal tourist experiences (FPTEs) must be focused on enhancing these aspects in order to offer an immersive experience.

Consequently, this paper proposes the FPTE model.

The rapid global economic development in the last century, led by industrialization, brings environmental issues to the forefront as a serious concern. While some country-specific studies are undertaken to find the effectiveness of different mechanisms for funding environment-friendly projects, to the authors' knowledge, no study has been conducted to examine the impact of green bonds (GBs) on CO2 emissions for a global sample. Against this backdrop, this study examines the general impact of GBs on CO2 emissions and its differential impact for developed and developing countries and country categorizations based on sustainable development.

The study selects a sample of 44 countries from 2016–2020. The authors use trend analysis and box plots to analyze the present GBs and CO2 emissions scenarios. Further, the panel data regression model is used to examine the overall impact of GBs on CO2 emissions and uncover the variation in such relationships regarding country-level economic and sustainable development. Generalized methods of moments (GMM) and instrumental variables (IV) models are used for robustness.

The yearly trend of GBs is upward at the global level, while CO2 emissions exhibit a marginal decline during the study period. However, significant variations are observed in such trends between developed and developing countries and country-level sustainable development. The authors' regression results show that GBs significantly negatively impact CO2 emissions globally. In addition, the effect of GBs on CO2 emissions is strongly negative for developing countries, while the same influence becomes weak for developed nations. Similar variations exist between countries based on sustainable development.

This is the first study in extant literature to examine such a relationship for a global sample of 44 countries. Further, this study makes a novel contribution by analyzing the variations in the GBs-CO2 emissions nexus for developed and developing countries and country-level sustainable development.