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Purpose The impact of demand fluctuation during crisis events is crucial to the dynamic pricing and revenue management tactics of the hospitality industry. The purpose of this paper is to improve the accuracy of hotel demand forecast during periods of crisis or volatility, taking the 2019 social unrest in Hong Kong as an example. Design/methodology/approach Crisis severity, approximated by social media data, is combined with traditional time-series models, including SARIMA, ETS and STL models. Models with and without the crisis severity intervention are evaluated to determine under which conditions a crisis severity measurement improves hotel demand forecasting accuracy. Findings Crisis severity is found to be an effective tool to improve the forecasting accuracy of hotel demand during crisis. When the market is volatile, the model with the severity measurement is more effective to reduce the forecasting error. When the time of the crisis lasts long enough for the time series model to capture the change, the performance of traditional time series model is much improved. The finding of this research is that the incorporating social media data does not universally improve the forecast accuracy. Hotels should select forecasting models accordingly during crises. Originality/value The originalities of the study are as follows. First, this is the first study to forecast hotel demand during a crisis which has valuable implications for the hospitality industry. Second, this is also the first attempt to introduce a crisis severity measurement, approximated by social media coverage, into the hotel demand forecasting practice thereby extending the application of big data in the hospitality literature.

Mitigating and avoiding social unrest caused by ecological forest restoration is a key factor in the coordinated development of forests and society. Forests, which are intricately linked with society, serve as a vital source of timber, non-timber forest products, and ecosystem services. Ecological forest restoration projects must carefully consider the relationship between forests and society to promote their coordinated development. As a key implementation area for the Natural Forest Resource Protection Project, the state-owned forest regions in Northeast China have experienced a crisis regarding harvestable resources and social unrest caused by protection policies and are currently innovating in policies and practices to mitigate social unrest. This study focuses on the history of natural forest resource conservation projects in China’s state-owned forest areas as a case study for empirical research, aiming to provide insights into ecological restoration models that foster harmony between forests and society. The empirical analyses reveal the following findings: (1) As a result of strict protection, natural forest resources on state-owned land have transitioned from providing timber to ecosystem services and non-timber products. (2) The strict logging ban policy has led to severe resource shortages; from 2000 to 2020, for every 10,000 cubic meter decrease in timber harvest, the per capita output in state-owned forest areas has dropped by more than CNY 500 (approximately USD 70). (3) Proactive ecological restoration can effectively alleviate social unrest; from 2000 to 2020, for every additional 10,000 hectares of forest tending, the average wage increased by more than CNY 900 (approximately USD 127). (4) Regional transformation can effectively generate a buffer effect to mitigate social unrest caused by strict forest protection policies and leverage the beneficial resources produced by ecological forest restoration to develop new drivers of economic growth. By systematically reviewing the comprehensive implementation of the NFPP, this paper’s findings provide insights into ecological restoration strategies that promote the harmonious development of forests and society.

This paper explores the root causes of student unrest in South African universities and evaluates the institutional responses to these protests, otherwise regarded as social unrest. The study is lensed through social movement theory and institutional theory. The study adopted transformative paradigm under qualitative approach and participatory research design to analyze the experiences of universities in South Africa that have experienced significant social unrest in recent years. Focus group discussion was conducted with university management staff, student activists, and security officers of the selected universities. The findings showed that lack of access, socio-economic inequalities, ineffective communication, and open engagement are the primary causes of social unrest. In contrast, providing equitable access, economic liberation, effective communication, and open engagement is the possible institutional response that alleviates social unrest on university campuses. Hence, promoting equitable access and economic liberation coupled with effective communication and open engagement among stakeholders was recommended. Plain Language Summary Causes and Institutional Responses of Social Unrest. This paper investigates why South African university students protest and how the institutions respond. Using social movement and institutional theories, the study talks to university managers, student activists, and security officers in universities with recent protests. The key issues identified are limited access, economic inequalities, poor communication, and exclusion from decision-making. The suggested solution is to focus on fair access, reducing economic disparities, improving communication, and involving everyone in decisions. The researcher recommends promoting equitable access and economic fairness, alongside better communication and inclusive decision-making, as a way to address and prevent social unrest on university campuses.

Social unrest events have been an issue of concern to people in various countries. In the past few years, mass unrest events appeared in many countries. Meanwhile, social media has become a distinctive method of spreading event information. It is necessary to construct an effective method to analyze the unrest events through social media platforms. Existing methods mainly target well-labeled data and take relatively little account of the event development. This paper proposes an entity-based integration event detection framework for event extraction and analysis in social media. The framework integrates two modules. The first module utilizes named entity recognition technology based on the bidirectional encoder representation from transformers (BERT) algorithm to extract the event-related entities and topics of social unrest events during social media communication. The second module suggests the K-means clustering method and dynamic topic model (DTM) for dynamic analysis of these entities and topics. As an experimental scenario, the effectiveness of the framework is demonstrated using the Lihkg discussion forum and Twitter from 1 August 2019 to 31 August 2020. In addition, the comparative experiment is performed to reveal the differences between Chinese users on Lihkg and Twitter for comparative social media studies. The experiment results somehow indicate the characteristic of social unrest events that can be found in social media.

Over the last several years research has examined anew the potential for climate change to induce political conflict and potentiate social unrest. Several explanations for the relationship between weather and social unrest have been proposed, including the idea that temperature, acting through a physiological response mechanism, gives rise to collective aggression. This proposition first appeared in the aftermath of the 1960s US riots, which occurred primarily in the heat of summer, and has re-emerged within the contemporary literature on conflict and climate, in addition to explanations rooted in political economic processes. Building on both bodies of work, this article utilizes a case-crossover time-series design to explore the relationship between meteorological factors derived from high resolution spatial data of temperature and precipitation and social disturbances occurring in 50 major cities in Africa and Asia between 1960 and 2006. Poisson regression and generalized additive modeling are utilized to model linear and non-linear effects, respectively. A significant, but qualified, association between heat and urban social disturbances is found. The general relationship is non-linear, with peak levels of unrest occurring in the upper 20s (°C). The relationship between temperature and social unrest within individual cities is linear. In addition, there are differential effects of heat on lethal versus non-lethal episodes of unrest. The non-linear response to temperature is much more pronounced among lethal events than it is among non-lethal episodes. The conclusion taken from this research is that heat is associated with urban social conflict, but generally does not trigger episodes and instead acts to supplement aggression while other factors govern the primary timing of social unrest.

Embrace the chaosHow will social unrest in the Netherlands evolve in the coming years? What consequences and opportunities will arise for the government and the security system? These questions are central to this contribution. As comedian Wim Kan once remarked during the years when the foundation for this journal was laid: ‘Nothing is as difficult as predicting, especially when it concerns the future.’ The development of the future is, after all, a prime example of chaos theory, urging caution and humility. This article, therefore, is no more than a small thought exercise, partly based on recent work on social unrest and the current state of the security system.

Hong Kong has experienced an unprecedented social unrest since June 2019, triggered by the introduction of the Fugitive Offenders Amendment Bill by the government of Hong Kong Special Administrative Region. Social unrest involves a tangle of interrelated questions, hence the article's purpose is to provide pioneer criminological perspective to explore and explain the causes and the evolution of right-wing radicalization in Hong Kong context from the year of 2008 to 2012 through the scope of Agnew's general strain theory. Previous researches mainly focused on the relationship between political factors and radicalization; therefore this study aims to revisit the birth and rise of right-wing radicalization in Hong Kong through the lens of socio-economic aspects. It has made a critical step to provide direction and consolidation for future analysis relating to the actual root causes of right-wing radicalization and social unrest in Hong Kong, as it suggests that the element of high magnitude of stress caused by economic inequality, harsher living environment, degrading quality of life and the increasing socio-cultural tensions and radical right ideological infiltration had created a perfect atmosphere for radicalization and the spread of extremism. Therefore, the theory could be a useful theoretical framework to help researchers to conduct future studies relating to radicalization and social unrest in Hong Kong and to help policy-makers to formulate public policies that focus on addressing strain issues against local citizens.

The study of security implications of climate change has developed rapidly from a nascent area of academic inquiry into an important and thriving research field that traverses epistemological and disciplinary boundaries. Here, we take stock of scientific progress by benchmarking the latest decade of empirical research against seven core research priorities collectively emphasized in 35 recent literature reviews. On the basis of this evaluation, we discuss key contributions of this special issue. Overall, we find that the research community has made important strides in specifying and evaluating plausible indirect causal pathways between climatic conditions and a wide set of conflict-related outcomes and the scope conditions that shape this relationship. Contributions to this special issue push the research frontier further along these lines. Jointly, they demonstrate significant climate impacts on social unrest in urban settings; they point to the complexity of the climate–migration–unrest link; they identify how agricultural production patterns shape conflict risk; they investigate understudied outcomes in relation to climate change, such as interstate claims and individual trust; and they discuss the relevance of this research for user groups across academia and beyond. We find that the long-term implications of gradual climate change and conflict potential of policy responses are important remaining research gaps that should guide future research.

PurposeTo examine the joint associations of civil unrest and COVID-19 with probable anxiety and depression during the first half of 2020 in Hong Kong. Associations were compared between persons with low or high assets.MethodsA population-representative sample of 4011 Hong Kong Chinese residents aged 15 years or older were recruited between February and May 2020. Respondents reported current anxiety and depressive symptoms, unrest stress, COVID-19 stress, assets (savings and home ownership), and demographics.ResultsStress due to unrest and COVID-19 was associated with higher prevalence of probable anxiety and depression; persons with both stressors had higher prevalence. This pattern was consistent among persons with low or high assets, but the probabilities of mental disorder were substantially higher among persons with fewer assets.ConclusionsThe effect of stressors on probable anxiety and depression are cumulative: persons with stress due to civil unrest and to COVID-19 reported more mental disorders than persons with stress due to only one, or none of these factors. Overall high assets appear to buffer the consequences of stressors, lowering the risk of mental disorder.