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Policing activities aim to provide a safe environment for tourists. With the recent major protests that have erupted around the world, and the novel use of excessive police force against protestors, people may wonder if the policing deployment is for destination safety or to deter tourists from visiting. This paper aims to investigate anti-police and pro-police attitudes and tourists' behavioural responses towards a popular destination experiencing an ongoing social movement.

Data were collected between December 2019 and January 2020 (during the social movement). An online survey with a snowball sampling method was adopted to reach international tourists who were aware of the social movement in Hong Kong.

The results revealed that an individual with an anti-police attitude was found to be related to cognitive and affective destination images and perceived risks while those holding a pro-police attitude were more concerned with destination images only. No significant correlation was found between attitudes towards policing and travel intention.

This research presents a first attempt to investigate the relationship between tourists' policing attitudes and their behavioural responses during an ongoing social movement in a popular destination city.

The Lebanese began their present emigration in the middle of the nineteenth century, heading towards North America, Central and South America, Europe, Africa, and Australia. Today's Lebanese diaspora is made of highly educated and prominent entrepreneurs who have created huge marks in their adopted homelands and the world. In the current study the authors aim to explore this and make suggestions for future research.

The authors use historical literature review and synthesis in order to explore the topic and make suggestions for future research.

The authors find that entrepreneurs from Lebanon have had a significant impact on the economies of many parts of the world.

This paper is original in that it brings together the research on entrepreneurship and Lebanon so that future researchers can have good ideas as to ways to pursue future cross‐cultural research.

System dynamics is a whole-system modelling and learning approach, useful for tackling non-linear problems, such as sustainable urban development. The purpose of this paper is to review system dynamics applications in the simulation of sustainable urban development over a period from 2005 to 2017.

The analysis reveals that the number of applications of system dynamics modelling in the area of urban sustainable development increased in the analysed period. Research has changed its focus from the modelling of environmental problems to more complex models, portraying the multidimensional socio-economic processes that have an impact on the sustainability of urban development. Analysed case studies most often use the behaviour reproduction test for model validation, but without a unified approach. In most cases, modelling has been done in China, Germany and the USA, while urban development in the Eastern European countries, Africa and Latin America has not often been investigated. This paper indicates the knowledge gaps and suggests future research directions.

Papers that report the use of system dynamics modelling reveal a wide range of applications in urban sustainability. The analysis shows significant emphasis on environmental problems, while the interest for modelling social problems has been increasing during the last several years. Most of the modelled problems examine the sustainability of resources (land, water) and waste management, which are used for insights into the reasons for the system behaviour, forecasting future behaviour and policy testing.

The presented models were developed in most cases for the purpose of understanding the phenomena examined, as well as the future use of the models in policy planning. This brings us back to the need for greater stakeholder involvement, not only in the initial phase, but also during the whole modelling process, which could increase understanding, use and ownership of the models in the future, and thus increase their practical application.