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The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

The Arab world has witnessed a remarkable surge in the growth of its tourism and hospitality (T&H) industry, positioning it as a vital cornerstone for sustainable development. However, an exclusive bibliometric analysis of T&H research contributed by the Arab world has not yet been conducted in the past 30 years, that is, 1993–2022. Therefore, the purpose of this study is to provide a first-of-its-kind bibliometric assessment and visualization of T&H research produced by the Arab world spanning from 1993 to 2022.

A comprehensive collection of 1,327 scientific publications related to T&H research contributed by the Arab world was acquired from the Web of Science Core Collection database. To perform a large-scale bibliometric analysis, encompassing performance analysis, science mapping and network analysis, this study used state-of-the-art analytical tools, namely, Bibliometrix package of R Studio and VOSviewer.

The findings of this study show that the Arab world’s research on T&H has significantly surged since COVID-19, contributing nearly half (50.56%) of the total literature in the T&H domain between 2020 and 2022. Elshaer IA (Suez Canal University, Egypt) emerged as the most productive author, while Nusair K (Sultan Qaboos University, Oman) was identified as the most impactful author in the T&H domain in the Arab world. The most productive journal was found to be Sustainability (MDPI), while Tourism Management (Elsevier) was identified as the most impactful journal in the field of T&H. Furthermore, the thematic analysis highlights that research themes in T&H are not static but rather constantly evolving in response to dynamic changes in the industry, such as emerging trends, shifts in tourist preferences and the impact of global events like the COVID-19 pandemic.

To the best of the authors’ knowledge, this is the first bibliometric analysis of T&H research contributed by the Arab world, specifically covering the period from 1993 to 2022. This study's findings can inform the development of strategies and policies for the sustainable and competitive growth of the T&H industry in the Arab world. This study highlights the importance of continued research and collaboration among industry professionals, academics and policymakers to promote innovation and drive positive change in the T&H sector in the Arab world.

阿拉伯世界已经目睹了其旅游和酒店（T&H）行业增长的显著激增, 将其定位为可持续发展的重要基石。然而, 在过去30年中, 即1993年至2022年, 尚未进行关于阿拉伯世界贡献的T&H研究的专属文献计量分析。因此, 这项研究代表了提供阿拉伯世界自1993年至2022年间T&H研究的首创性文献计量评估和可视化的先驱努力。

从Web of Science核心合集数据库收集了1327篇与阿拉伯世界贡献的T&H研究相关的科研论文。为进行大规模的计量分析, 包括性能分析、科学映射和网络分析, 我们采用了先进的分析工具, 即R Studio的Bibliometrix软件包和VOSviewer。

研究结果显示, 自COVID-19以来, 阿拉伯世界对T&H的研究显著增加, 占2020年至2022年期间发表文献总数的近一半（50.56%）。关键词分析揭示了阿拉伯世界T&H领域的当前研究热点, 包括“旅游”、 “影响”、“满意度”、“管理”、“酒店业”、“绩效”、“决定因素”、“感知”、“忠诚度”、“质量”和“顾客满意度”。然而, 阿拉伯世界的T&H学者和从业者需要进一步研究一些研究空白, 包括“器官移植旅游”、“伦理领导”、“消费者感知”、“生态足迹”、“员工参与”、“爱彼迎”、“目的地营销”、“顾客不文明行为”、“可持续旅游发展”和“环境可持续性”等主题。主题分析突显了T&H领域的研究主题不断随行业动态变化而不断演化, 如新兴趋势、游客偏好变化以及全球事件如COVID-19大流行的影响。

据我们所知, 这是首次对阿拉伯世界贡献的T&H研究进行的计量分析, 特别涵盖了1993年至2022年的时期。研究结果可为阿拉伯世界T&H行业可持续和竞争性增长的战略和政策提供信息。这项研究强调了继续研究和行业专业人员、学者和政策制定者之间的合作的重要性, 以促进创新并推动阿拉伯世界T&H行业的积极变革。

El mundo árabe ha presenciado un notable aumento en el crecimiento de su industria de turismo y hostelería (T&H), posicionándola como una piedra angular vital para el desarrollo sostenible. Sin embargo, aún no se ha realizado un análisis bibliométrico exclusivo de la investigación en T&H realizada por el mundo árabe en los últimos 30 años, es decir, de 1993 a 2022. Por lo tanto, este estudio se erige como el esfuerzo pionero en proporcionar una evaluación bibliométrica y visualización sin precedentes de la investigación en T&H producida por el mundo árabe desde 1993 hasta 2022.

Se recogieron 1327 publicaciones científicas relativas a la investigación en T&H elaboradas por el mundo árabe, a partir de la base de datos Web of Science Core Collection. Para llevar a cabo un análisis bibliométrico a gran escala que abarcara el análisis de rendimiento, el mapeo científico y el análisis de redes, se emplearon herramientas analíticas de última generación, como el paquete Bibliometrix de R Studio y VOSviewer.

Los resultados muestran que la investigación del mundo árabe en T&H ha aumentado significativamente desde la COVID-19, representando casi la mitad (50.56%) de la literatura total publicada entre 2020 y 2022. El análisis de palabras clave reveló que “turismo,” “impacto,” “satisfacción,” “gestion,” “hospitalidad,” “rendimiento,” “determinantes,” “percepción,” “lealtad,” “calidad” y “satisfacción del cliente” son los temas de investigación actuales más destacados en T&H en el mundo árabe. Sin embargo, existen varias lagunas de investigación que requieren una investigación adicional por parte de académicos y profesionales de T&H en el mundo árabe, incluyendo temas como “turismo de trasplante,” “liderazgo ético,” “percepción del consumidor,” “huella ecológica,” “compromiso de los empleados,” “Airbnb,” “marketing de destinos,” “incivilidad del cliente,” “desarrollo de turismo sostenible,” y “sostenibilidad ambiental.” El análisis temático destaca que los temas de investigación en T&H evolucionan constantemente en respuesta a cambios dinámicos en la industria, como tendencias emergentes, cambios en las preferencias de los turistas y el impacto de eventos globales como la pandemia de COVID-19.

Hasta dónde llega nuestro conocimiento, este es el primer estudio bibliométrico de la investigación en T&H realizada por el mundo árabe, cubriendo específicamente el período de 1993 a 2022. Los hallazgos del estudio pueden desplegar el desarrollo de estrategias y políticas para el crecimiento sostenible y competitivo de la industria de T&H en el mundo árabe. Este estudio resalta la importancia de la investigación continua y la colaboración entre profesionales de la industria, académicos y responsables políticos para promover la innovación y generar un cambio positivo en el sector de T&H en el mundo árabe.

The purpose of this study is to explore the relationship between nonmarket strategy and innovation performance, as well as the boundary factors that influence this relationship in the context of the pharmaceutical industry in emerging markets.

This study analyzed matched data of 227 Chinese pharmaceutical firms and two secondary databases with SPSS to examine the hypotheses.

Nonmarket strategy promotes the innovation performance. High level of firm internal knowledge utilization ability and strategic flexibility strengthens the effect of nonmarket strategy in promoting innovation performance, while information technology (IT) environment weakens the effect of nonmarket strategy in promoting innovation performance.

The research studies the positive impact of nonmarket strategy on innovation performance in the specific context of Chinese pharmaceutical industry, and it introduces the internal capabilities and external IT environment of the firm as moderators of the relationship between nonmarket strategy and innovation performance. More importantly, this research echoes the call for research on moderator of nonmarket strategy and identifies important boundary conditions. To the best of the authors’ knowledge, it also explores the impact of the IT environment on the implementation of nonmarket strategy for the first time, which deepens the research on nonmarket strategy’s effect on innovation.

After the identification of a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at Wuhan, China, a pandemic was widely spread worldwide. In Italy, about 240,000 people were infected because of this virus including 34,721 deaths until the end of June 2020. To control this new pandemic, epidemiologists recommend the enforcement of serious mitigation measures like country lockdown, contact tracing or testing, social distancing and self-isolation.

This paper presents the most popular epidemic model of susceptible (S), exposed (E), infected (I) and recovered (R) collectively called SEIR to understand the virus spreading among the Italian population.

Developed SEIR model explains the infection growth across Italy and presents epidemic rates after and before country lockdown. The results demonstrated that follow-up of strict measures such that country lockdown along with high testing is making Italy practically a pandemic-free country.

These models largely help to estimate and understand how an infectious agent spreads in a particular country and how individual factors can affect the dynamics. Further studies like classical SEIR modeling can improve the quality of data and implementation of this modeling could represent a novelty of epidemic models.

The purpose of this study is to address the relevance of archaeological heritage in the context of supply chains for the tourism industry. It does so by providing converging ideas on the usefulness of individual sites, not in their strict scientific or latent value but as an enhancer for optimizing cultural production in a wider scenario of aggregate demand.

While examples from the United Arab Emirates (UAE) illustrate this reasoning, the underlying principles have a widespread application and point to a need for defragmenting and realigning tangible heritage as a key production factor. Methods used consist of an inductive approach, based on secondary sources and semi-structured interviews.

Results indicate that, while archaeological resources remain central to the promotion of cultural tourism in the UAE, suppliers face challenges when incorporating particular sites into consumer-friendly packages.

The study contributes to the identification of common risks and opportunities for archaeological resource management in the development of UAE tourism products.

This represents an original angle, given the focus on the specific regional, cooperative added value of archaeological resources and the need for optimizing them in a functional supply chain.

This paper aims to examine the effect of dividend policy on firm value for financial sector in an emerging country. Furthermore, it examines the moderating effect of IFRS adoption and the abolishment of mandatory dividend payment policy with considering the Lintner model of dividend smoothing.

Data were collected from 111 firms listed on Borsa Istanbul in the financial sector in Turkey over 1995–2017. Using an explanatory research design, this study performs various multivariate regression techniques to investigate the proposed relationships.

The outcomes demonstrate a positive and significant association between dividend policy and firm value. In addition, the relationship has strengthened after IFRS adoption, indicating that accounting information such as dividend-based ratios prepared under IFRS is more value relevant. The empirical outcomes supported the Lintner model, which is persistent with the signalling hypothesis. Moreover, the findings state that the abolishment of mandatory dividend payment in 2009 strengthened the association between dividend policy and firm value for financial institutions in Turkey.

These results provide an insight to the investors and managers that the effect of IFRS adoption and other policy changes could be greater on the association between dividend policy and firm value. The study empirically tests Lintner model of dividend smoothing for financial firms in an emerging economy.

This study contributes to the literature through providing vital insights on the relationship between dividend policy and firm value and empirically revisiting the Lintner model for financial sector in a developing economy, specifically Turkey. Furthermore, it addresses the influence of IFRS implementation on the association between dividend policy and firm value. These findings are robust to alternative sampling methods and to controlling for other factors which influence firm value.

The choices that international students make regarding abroad study destination selection or leave the host country after graduation are influenced by a variety of factors that are both related to positive and negative aspects of the host country.

This study builds on the push-pull factor theory and examines the factors that influence international students' decision to choose abroad study destination (Finland) or leave the country after their graduations. The data were collected through an online survey of 195 international students currently studying in Finland and were analysed using partial least squares structural equation modelling (PLS-SEM) technique. This method offers a flexible and robust approach to test relationships, particularly in situations where sample size and the conceptual model are small and complex.

The results show that international students' choice of study destination (Finland) is influenced by the host country's quality of life, academic excellence and economic factors such as salary and benefits. Unfamiliarity with the culture and language barriers have a negative impact on their decisions to stay in the host country after graduation.

By utilising a comprehensive analysis of both push and pull factors in relation to the host country, this study unveils a novel perspective in the field of international student mobility. The results provide insights to the institutional leaders and policymakers into how to attract and retain international students by focusing on the factors that matter most to international students. To attract more international students, higher education institutions (HEIs) should include career development activities, e.g. job fairs, language training, scholarships and internships in their curriculum. Moreover, it provides recommendations on how to create a welcoming and supportive environment that promotes academic excellence and career development.

The purpose of this paper is to investigate risk propagation and resilience in the agribusiness supply chain (ASC).

The paper undertakes a systematic literature review (SLR). Overall, 94 articles from six databases published between 2000 and 2022 underwent descriptive and thematic analysis.

There is a lack of research on risk propagation and resilience in the ASC for more than two decades. Accordingly, this research fills the gap in the extant literature by advancing the construct of risk propagation and resilience in the ASC and developing a framework proposing directions in risk propagation and resilience in ASC research.

Firstly, only the Web of Science and Scopus databases were mostly used as primary sources while other databases were used as secondary sources to validate search results. Secondly, SLR is based on the peer-reviewed articles, books and conference papers; other non-academic sources relevant to the topic were not included in this paper.

The paper offers a set of constructs for understanding risk propagation and resilience in the ASC, develops a framework proposing directions in risk propagation and resilience in the ASC research and recommends three key themes for future research directions, namely, keep updated with recent constructs of risk propagation and resilience in the ASC, conduct case studies based on empirical studies to determine the current risk dependency and propagation in the ASC and conduct case studies based on empirical studies to determine resilience and sustainability in the ASC.

The present study aims to evaluate the effect of climate change on the flood hazard potential in the Kelantan River Basin using current and future scenarios.

The intensity-duration-frequency (IDF) was used to estimate the current 50- and 100-year return period 24-h design rainfall, and the climate change factor (CCF) was used to compute the future design rainfall. The CCF was calculated from the rainfall projections of two global climate models, CGCM1 and CCSM3, with different pre-processing steps applied to each. The IDF data were used in the rainfall-runoff-inundation model to simulate current and future flood inundation scenarios.

The estimated CCF values demonstrate a contrast, whereby each station had a CCF value greater than one for CGCM1, while some stations had a CCF value of less than one for CCSM3. Therefore, CGCM1 projected an aggravation and CCSM3 a reduction of flood hazard for future scenarios. The study reveals that topography plays an essential role in calculating the CCF.

To the best of the author’s knowledge, this is the first study to examine flood projections in the Kelantan River Basin. It is, therefore, hoped that these results could benefit local managers and authorities by enabling them to make informed decisions regarding flood risk mitigation in a climate change scenario.