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This study examined how audience characteristics and attitudes relate to their perceptions of sincerity and forgiveness of apologies by public figures posted on YouTube.

Four hundred twenty-seven adult participants recruited through Amazon's Mechanical Turk completed an online survey via Qualtrics. Participants were randomly assigned to view two of four public figure apologies posted on YouTube.

Results indicated that audience fandom and perceived reputation and attractiveness of the public figure were related to perceptions of sincerity and forgiveness; and perceptions of sincerity and forgiveness were related to intentions of future support.

“Sameness” between the public figure and audience did not garner a more favorable response to the apology, and this is not consistent with earlier studies. For race similarity, the results could have been a reflection of the low number of non-White participants. However, results could indicate that “sameness” is not as simplistic as demographic sameness, such as race, sex or age.

The authors’ findings elevate the importance of gathering and benchmarking pre-crisis attitudinal research to better equip and inform communication professionals for crisis response. In addition, the study suggests that a public figure's strong reputation and fanbase provide a type of inoculation, lessening reputational damage.

The finding that perceived attractiveness relates positively to perceptions of sincerity and forgiveness is consistent with psychological research indicating attractiveness has many positive social implications – even in mediated communication.

Evidence suggests social media apologies matter. Communication professionals need to approach apology opportunities with a keen awareness that relational outcomes and intentions of future support can shift based on social media audiences' attitudes related to the public figure.

This study aims to provide a cutting-edge evaluation of the sharing economy's impact within the realm of tourism and hospitality. The primary objectives guiding this research are as follows: to uncover the prevalent discussions and debates within the tourism and hospitality sector concerning the implications and effects of the sharing economy on urban destinations; and to analyse how scholarly inquiries and empirical investigations have contributed to a comprehensive comprehension of the intricate theoretical foundations and practical intricacies inherent in the sharing economy. This exploration takes place within the extensive expanse of existing literature.

The study used the non-conventional method for data mining. An artificial intelligence (AI) tool called www.dimensions.ai was used to mine data between the year 2002 and 2021. After which the data was analysed, using Citespace software that assisted in building themes for answering the research questions.

The sharing economy has multifaceted implications for rural and urban destinations. For instance, the findings demonstrated that emotional solidarity fosters community bonds between tourists and residents, enhancing authenticity. While, management firms optimise short-term rentals, boosting revenue and occupancy rates despite capped at 20%. It further demonstrated that the sharing economy disrupts traditional accommodations, especially hotels, impacting rural and urban destinations differently based on location and regulatory flexibility. Technological advancements would shape the digital future, transforming the resource in sharing and connectivity in urban settings.

Management firms or agents significantly enhance property facilities, revenue and occupancy rates. Properties managed by professionals perform better in terms of revenue and occupancy; furthermore, traditional accommodations need innovative strategies to compete with sharing economy platforms. Policymakers must consider location-specific regulations to balance sharing economy impacts. Embracing technological advancements ensures urban destinations stay relevant and competitive.

Emotional solidarity fosters bonds between residents and tourists, contributing to a sense of community. Management firms contribute to local economies and stability. However, Airbnb's impact on traditional accommodations raises concerns about the effect on residents and communities.

The study incorporates classical sociology theory to understand emotional solidarity and extends the concept of moral economy to guide economic behaviour in the sharing economy. The analysis also underscores the influence of technological trends such as mobile technology, Internet of Things, AI and blockchain on sharing practices in reshaping existing theoretical frameworks in the sharing atmosphere. Furthermore, the co-creation of value theory highlights collaborative interactions between hosts and guests, shaping the sharing economy experience. Consumer segmentation and choice theories shed light on sharing economy dynamics. Institutional and location-based theories provide insights into regulatory and location-specific impacts.

This research contributes by comprehensively exploring the multifaceted implications of the sharing economy on a tourist destination. It delves into emotional solidarity, management firm roles and location-specific impacts, enriching the understanding of the sharing economy's effects. The application of co-creation of value theory and examination of platform technologies offer fresh perspectives on value creation and user engagement. The study's focus on practical dimensions guides stakeholders in optimising the benefits and addressing challenges posed by the sharing economy in urban contexts. The exploration of moral economy and its relevance to the sharing economy provides a novel perspective, while the examination of technological influences on sharing practices contributes to understanding the digital future of the sharing economy.

This paper develops a theoretical model that analyzes the decision problem the landowner has to face between the construction of second homes and hotels. The starting point implies verifying that for a given tourist destination, the land available for the construction of accommodation is limited. For this reason, when choosing between building second homes or building hotels, many factors influence the decision model. The theoretical mechanism generalizes the model introduced in Brida and Boffa (2010) and is based on a four-stage sequential game with four players. From the results of the model, the authors conclude that it is optimal from the social point of view both to build a hotel and to build a second home because both generate added value during the year. For this reason, the construction of second homes should be taken into account in the planning policy of the tourist destination. This arises from considering that second homes, as they remain occupied all year like hotels, in certain tourist destinations, do not generate seasonality.