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Digitalization accelerates the need of tourism and hospitality ecosystems to reframe business models in line with a data-driven orientation that can foster value creation and innovation. Since the question of data-driven business models (DDBMs) in hospitality remains underexplored, this paper aims at (1) revealing the key dimensions of the data-driven redefinition of business models in smart hospitality ecosystems and (2) conceptualizing the key drivers underlying the emergence of innovation in these ecosystems.

The empirical research is based on semi-structured interviews collected from a sample of hospitality managers, employed in three different accommodation services, i.e. hotels, bed and breakfast (B&Bs) and guesthouses, to explore data-driven strategies and practices employed on site.

The findings allow to devise a conceptual framework that classifies the enabling dimensions of DDBMs in smart hospitality ecosystems. Here, the centrality of strategy conducive to the development of data-driven innovation is stressed.

The study thus developed a conceptual framework that will serve as a tool to examine the impact of digitalization in other service industries. This study will also be useful for small and medium-sized enterprises (SMEs) managers, who seek to understand the possibilities data-driven management strategies offer in view of stimulating innovation in the managers' companies.

The paper reinterprets value creation practices in business models through the lens of data-driven approaches. In this way, this paper offers a new (conceptual and empirical) perspective to investigate how the hospitality sector at large can use the massive amounts of data available to foster innovation in the sector.

Climatic extreme events are predicted to occur more frequently and intensely and will significantly threat the living of residents in arid and semi-arid regions. Therefore, this study aims to assess climatic extremes’ response to the emerging climate change mitigation strategy using a marine cloud brightening (MCB) scheme.

Based on Hadley Centre Global Environmental Model version 2-Earth System model simulations of a MCB scheme, this study used six climatic extreme indices [i.e. the hottest days (TXx), the coolest nights (TNn), the warm spell duration (WSDI), the cold spell duration (CSDI), the consecutive dry days (CDD) and wettest consecutive five days (RX5day)] to analyze spatiotemporal evolution of climate extreme events in the arid Sahara-Sahel-Arabian Peninsula Zone with and without MCB implementation.

Compared with a Representative Concentration Pathways 4.5 scenario, from 2030 to 2059, implementation of MCB is predicted to decrease the mean annual TXx and TNn indices by 0.4–1.7 and 0.3–2.1°C, respectively, for most of the Sahara-Sahel-Arabian Peninsula zone. It would also shorten the mean annual WSDI index by 118–183 days and the mean annual CSDI index by only 1–3 days, especially in the southern Sahara-Sahel-Arabian Peninsula zone. In terms of extreme precipitation, MCB could also decrease the mean annual CDD index by 5–25 days in the whole Sahara and Sahel belt and increase the mean annual RX5day index by approximately 10 mm in the east part of the Sahel belt during 2030–2059.

The results provide the first insights into the impacts of MCB on extreme climate in the arid Sahara-Sahel-Arabian Peninsula zone.

This paper aims to address the following questions: What is the impact of the pandemic on the hospitality industry in South Africa? Which innovations and strategies are in place to rebuild hospitality in South Africa?

This article emanates from the resent pandemic situation, and it is structured to include conceptual information drawn from the literature, empirical study and industry observation. These were conducted in 2020 and 2021 using, concepts from the literature, online questionnaires and observation to gather data about the impact of COVID-19 on hospitality operations across South Africa.

Historically literature shows that the hospitality industry positively impacts the economy and employment However, the pandemic greatly affected these contributions. The findings reported in the empirical study revealed that the pandemic affected business operations and employment and caused financial hardship for the industry.

There are relatively few studies that report on the issues relating to the pandemic and the hospitality industry in South Africa. This paper contributes to the literature regarding a pre-COVID-19 overview, the impact of the pandemic and the innovations and strategies in place to rebuild the hospitality industry.

A leading characteristic of international tourists at every tourist destination is their role as foreign–income disseminator, and a large number of papers have been dedicated to exploring their behavior. In contrast, this paper aims to shed light on the supply-side of tourism through the study of a hotels’ ability to internationalize their businesses.

Based on each hotel’s input data, its efficiency was estimated by a data envelopment analysis approach. Then, the hotel’s intensity of demand from foreign guests was regressed against hotel efficiency along with firm’ control variables.

Results from Heckman correction model indicate that ordinary least squares regression would be subject to selection bias, and the results from the correction model strongly indicate a positive linkage between the hotel’s efficiency level and its foreign to total guest ratio, especially in the sub-sample of hotels located in non-tourist destinations. In addition, the results also reveal that the availability of certain services and facilities at hotels are positively related to the number of foreign guests, namely, a spa service and swimming pools.

Therefore, the main implications from this study are twofold. First, if a hotel’s target market is international travelers, a swimming pool and the availability of a spa service are essential features for hotels in Thailand. Second, policies to improve productivity in hotels should be simultaneously implemented along with tourist-destination-promotion campaigns to optimize the economic impact of international tourist arrivals.

Radical changes in consumer habits induced by the coronavirus disease (COVID-19) pandemic suggest that the usual demand forecasting techniques based on historical series are questionable. This is particularly true for hospitality demand, which has been dramatically affected by the pandemic. Accordingly, we investigate the suitability of tourists’ activity on Twitter as a predictor of hospitality demand in the Way of Saint James – an important pilgrimage tourism destination.

This study compares the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) time-series model with that of the SARIMA with an exogenous variables (SARIMAX) model to forecast hotel tourism demand. For this, 110,456 tweets posted on Twitter between January 2018 and September 2022 are used as exogenous variables.

The results confirm that the predictions of traditional time-series models for tourist demand can be significantly improved by including tourist activity on Twitter. Twitter data could be an effective tool for improving the forecasting accuracy of tourism demand in real-time, which has relevant implications for tourism management. This study also provides a better understanding of tourists’ digital footprints in pilgrimage tourism.

This study contributes to the scarce literature on the digitalisation of pilgrimage tourism and forecasting hotel demand using a new methodological framework based on Twitter user-generated content. This can enable hospitality industry practitioners to convert social media data into relevant information for hospitality management.

2019冠狀病毒病引致消費者習慣有根本的改變; 這些改變顯示，根據歷史序列而運作的慣常需求預測技巧未必是正確的。這不確性尤以受到大流行極大影響的酒店服務需求為甚。因此，我們擬探討、若把在推特網站上的旅遊活動視為聖雅各之路 (一個重要的朝聖旅遊聖地) 酒店服務需求的預測器，這會否是合適的呢?

本研究比較 SARIMA 時間序列模型與附有外生變數 (SARIMAX)模型兩者在預測旅遊及酒店服務需求方面的表現。為此，研究人員收集在推特網站上發佈的資訊，作為外生變數進行研究。這個樣本涵蓋於2018年1月至2022年9月期間110,456個發佈資訊。

研究結果確認了傳統的時間序列模型，若涵蓋推特網站上的旅遊活動，則其對旅遊需求方面的預測會得到顯著的改善。推特網站的數據，就改善預測實時旅遊需求的準確度，或許可成為有效的工具; 而這發現對旅遊管理會有一定的意義。本研究亦讓我們進一步瞭解朝聖旅遊方面旅客的數碼足跡。

現存文獻甚少探討朝聖旅遊的數字化，而本研究不但在這方面充實了有關的文獻，還使用了一個根據推特網站上使用者原創內容嶄新的方法框架，進行分析和探討。這會幫助酒店從業人員把社交媒體數據轉變為可供酒店管理之用的合宜資訊。

There is a gap in understanding with regards to the discrimination and prejudice experienced by gay entrepreneurs. To address this, an intersectional perspective is adopted to facilitate a better understanding of how lesbian and gay entrepreneurs may experience heterosexism.

This qualitative study uses semi-structured interviews to explore the experiences of 14 lesbian and gay entrepreneurs as they navigate homophobia and heterosexism.

The study contributes novel insights to the field of entrepreneurship, extending the study of lesbian and gay entrepreneurs to include gender and a fine-grained analysis of the experience of heterosexism. Its inclusion of an intersectional perspective of the lesbian-female entrepreneur expands the emerging body of literature examining intersectional identities of minority entrepreneurs.

The authors provide a more nuanced understanding of the impact of heterosexism on LGBT+ entrepreneurial activities. This is facilitated by the authors' adoption of an intersectional perspective which shows how the different axes of identity influenced gender identity performance in relation to the model of perceived neutrality in LGBT+ entrepreneurship. The authors also make an original contribution to minority stress literature through the authors' exploration of one facet of minority entrepreneurship, namely the impact of heterosexism on LGBT+ entrepreneurial activities.