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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.

Global climate change speeds up ice melting and increases flooding incidents. China launched a sponge city policy as a holistic nature-based solution combined with urban planning and development to address flooding due to climate change. Using Weibo analytics, this paper aims to study public perceptions of sponge city.

This study collected 53,586 sponge city contents from Sina Weibo via Python. Various artificial intelligence tools, such as CX Data Science of Simply Sentiment, KH Coder and Tableau, were applied in the study.

76.8% of public opinion on sponge city were positive, confirming its positive contribution to flooding management and city branding. 17 out of 31 pilot sponge cities recorded the largest number of sponge cities related posts. Other cities with more Weibo posts suffered from rainwater and flooding hazards, such as Xi'an and Zhengzhou.

To the best of the authors’ knowledge, this study is the first to explore the public perception of sponge city in Sina Weibo.

This paper aims to examine the impact of adverse personality traits (alexithymia, social inhibition, negative affectivity) and supervisor knowledge hiding on individual knowledge hiding. This study also explores the moderating role of positive affectivity.

Partial least squares path modeling and data collected from 518 Polish employees with higher education and extensive professional experience recruited via an Ariadna survey panel were used to test the research hypotheses.

Two dimensions of alexithymia were considered: difficulty identifying feelings (DIF) and difficulty describing feelings (DDF). DIF has a direct impact on individual hiding, whereas DDF has an indirect impact, via social inhibition. Negative affectivity is a predictor of social inhibition, which enhances knowledge hiding. Positive affectivity slightly weakens the positive and strong effect of supervisor knowledge hiding on subordinate knowledge hiding.

Because alexithymia, social inhibition and negative affectivity may predispose employees to knowledge hiding, managers should identify these personality traits among job applicants and hired employees to make appropriate employment decisions. Moreover, managers should be aware that hiding knowledge by a supervisor may be imitated by subordinates.

Based on conservation of resources theory, this study investigates previously unexplored relationships among alexithymia, social inhibition, affectivity and knowledge hiding.

The purpose of this paper is to establish criteria for evaluating strategic partners in a network of logistics service providers (LSPs) to show how analytical network process (ANP) can be used to identify the weights of these criteria on a case-specific basis, and to investigate whether the ANP model can be used as a starting point to evaluate strategic partners for other LSP networks.

Based on a literature review of vertical cooperation, the authors develop an overview of criteria for the evaluation of partners in a network of LSPs. The authors then apply ANP at LSP1 to validate the criteria, identify weights for these criteria and to validate model outcomes. Furthermore, the authors investigate whether the ANP model developed for LSP1 can be applied to another LSP with similar characteristics (LSP2). In-depth interviews are used to draw conclusions on the modeling approach and the model outcomes.

The research shows that evaluation criteria for partners in vertical partnerships between shippers and LSPs are applicable to LSP partners in horizontal partnership networks. The ANP model with criteria weights provides a good starting point for LSPs to customize the evaluation framework according to their specific needs or operating environments.

Limited research is available on evaluating LSP partners in horizontal partnerships. To the best of the authors’ knowledge, this paper is the first to bring forward horizontal LSP partner evaluation criteria to develop an ANP model for LSP partner evaluation and to apply this to two cases, and to provide a starting point for evaluating partners in similar horizontal LSP networks.

Genetic risk for depressive disorders is poorly understood despite consistent suggestions of a high heritable component. Most genetic studies have focused on risk associated with single variants, a strategy which has so far only yielded small (often non-replicable) risks for depressive disorders. In this paper we argue that more substantial risks are likely to emerge from genetic variants acting in synergy within and across larger neurobiological systems (polygenic risk factors). We show how knowledge of major integrated neurobiological systems provides a robust basis for defining and testing theoretically defensible polygenic risk factors. We do this by describing the architecture of the overall stress response. Maladaptation via impaired stress responsiveness is central to the aetiology of depression and anxiety and provides a framework for a systems biology approach to candidate gene selection. We propose principles for identifying genes and gene networks within the neurosystems involved in the stress response and for defining polygenic risk factors based on the neurobiology of stress-related behaviour. We conclude that knowledge of the neurobiology of the stress response system is likely to play a central role in future efforts to improve genetic prediction of depression and related disorders.

The purpose of this study was to uncover representative emergent areas and to examine the research area of marketing, tourism and big data (BD) to assess how these thematic areas have developed over a 27-year time period from 1996 to 2022. This study analyzed 1,152 studies to identify the principal thematic areas and emergent topics, principal theories used, predominant forms of analysis and the most productive authors in terms of research.

The articles for this research were all selected from the Web of Science database. A systematic and quantitative literature review was performed. This study used SciMAT software to extract indicators. Specifically, this study analyzed productivity and produced a science map.

The findings suggest that interest in this area has increased gradually. The outputs also reveal the innovative effort of industry in new technologies for developing models for tourism marketing. Ten research areas were identified: “destination marketing,” “mobility patterns,” “co-creation,” “gastronomy,” “sustainability,” “tourist behavior,” “market segmentation,” “artificial neural networks,” “pricing” and “tourist satisfaction.”

This work is unique in proposing an agenda for future research into tourism marketing research with new technologies such as BD and artificial intelligence techniques. In addition, the results presented here fill the current gap in the research since while there have been literature reviews covering tourism with BD or marketing, these areas have not been studied as a whole.

El objetivo de esta investigación fue descubrir nichos representativos de áreas emergentes y examinar el área de Marketing, Turismo y Big Data, evaluando cómo han evolucionado estas áreas temáticas durante un período de 27 años desde 1996–2022. Analizamos 1.152 investigaciones para identificar las principales áreas temáticas y temas emergentes, las principales teorías utilizadas, las formas de análisis predominantes y los autores más productivos en términos de investigación.

Todos los artículos para esta investigación fueron seleccionados de la base de datos Web of Science. Realizamos una revisión sistemática y cuantitativa de la literatura. Utilizamos el software SciMAT para extraer indicadores. Específicamente, analizamos la productividad y elaboramos un mapeo científico.

Los hallazgos sugieren que el interés en esta área ha aumentado gradualmente. Los resultados también revelan el esfuerzo innovador de la industria en nuevas tecnologías para desarrollar modelos de marketing turístico. Se identificaron diez áreas de investigación (“marketing de destinos”, “patrones de movilidad”, “co-creación”, “gastronomía”, “sostenibilidad”, “comportamiento turístico”, “segmentación de mercado”, “redes neuronales artificiales”, “precios”, y “satisfacción del turista”).

Este trabajo es único al proponer una agenda para futuras investigaciones en investigación de Marketing Turístico con nuevas tecnologías como Big Data y técnicas de Inteligencia Artificial. Además, los resultados presentados aquí llenan el vacío actual en la investigación ya que si bien se han realizado revisiones de literatura que cubren Turismo con Big Data o Marketing, estas áreas no se han estudiado como un conjunto.

这一特定研究领域的目标是发现具有代表性的新兴领域, 并考察市场营销、旅游和大数据研究领域, 以评估这些主题领域在1996年至2022年的27年间是如何发展的。我们分析了1152项研究, 以确定主要专题领域和新兴主题、使用的主要理论、主要的分析形式以及在研究方面最有成效的作者。

本研究的文章都是从Web of Science数据库中选出的。我们进行了系统化的定量文献审查, 并使用SciMAT软件来提取指标。具体来说, 我们分析了生产力并制作了一个科学研究地图。

研究结果表明, 人们对这一领域的兴趣已经逐渐增加。本文也揭示了工业界在开发旅游营销模式的新技术方面的创新努力。研究确定了十个研究领域：“目的地营销”、“流动模式”、“共同创造”、“美食”、“可持续性”、“游客行为”、“市场细分”、“人工神经网络”、“定价 “和游客满意度”。

这项研究的独特之处在于提出了未来利用大数据和人工智能技术等新技术进行旅游营销研究的议程。此外, 本文的结果填补了目前的研究空白, 因为虽然有文献综述涉及旅游与大数据或市场营销, 但这些领域还没有被作为一个整体来研究。

The purpose of this paper is to investigate the medical incident responses from two public hospitals in Hong Kong, namely, Kowloon Hospital and Caritas Medical Centre, in order to improve the strategic preparation for crisis management in hospitals.

The paper analyses two medical incidents using Situational Crisis Communication Theory by Coombs (2007). The two case studies presented herein demonstrate the importance of consistency in terms of crisis responses.

For the first case, the crisis responses from different parties after the incident, including Hospital Authority, the doctor and the nurses from Kowloon Hospital, are contradicting to each other. First, Hospital Authority confirmed that the incident is solely an accident which is a denial response. Second, the doctor passed the responsibility to the nurses which is a scapegoating response. Third, the nurses tend to reduce the responsibility for the death of patient by excusing strategy. As a whole, their responses are inconsistent to each other. For the second case, Caritas had initially denied the responsibilities, but finally had given partial apology under public pressure. That makes people think that Caritas does not really regret.

Rebuilding posture should be used instead of denial and diminishment posture. However, public organization and civil servants are reluctant to use a full apology due to possible legal consequences. The apology ordinance would ease the pressure to express regret and sympathy.

Wine packaged tours as a specific aspect of wine tourism have so far been neglected in research, for this reason, the purpose of this study is to study the key elements for the success of the wine tour in Tuscany (Italy), evaluating the points of strength and weakness.

The study combines approaches of text mining, sentiment analysis and natural language processing, drawing on data from the TripAdvisor platform, obtaining through an automatic procedure 9,616 reviews from 600 tours in the years 2010–2020.

The authors identified six elements of successful wine tours expressed by research subjects: tour guide; logistical aspects; the quality of the wine; the quality of the food; complementary tourist and recreational activities; the landscape and historic villages. The key strength associated with success was the integration of the leading wine product with food, landscape and historic villages, while the main criticisms were concerned with the organization and planning of the tour. Furthermore, the tour guide also plays a fundamental role in consumer satisfaction.

The limitations of the method were linked to the origin of the data used. The main one is that TripAdvisor does not allow you to have social and personal information about the tourist who wrote the review; therefore, the methods are substantially complementary to the traditional survey through questionnaires.

The proposed model can be used both by professionals to improve the quality of their products and by policymakers to promote the territorial development of quality wine-growing areas.

The proposed model can be useful for policymakers to promote the territorial development of quality wine-growing areas.

The methodology we tested is easily transferable to many countries and to the authors’ knowledge, for the first time attempts to combine multidimensional scaling, sentiment analysis and natural language processing approaches.

The purpose of this review is to conduct a bibliometric analysis of financial fraud exploiting the elderly by mapping its evolution, identifying major metrics and discussing directions for future research.

A bibliometric analysis was conducted, based on 434 articles retrieved from the Web of Science that represent the academic literature on the topic from 1995 to the first quarter of 2024. This paper analyses the antecedents of financial fraud exploiting the elderly, the publication trends and the most prolific countries, institutions, journals, research areas and authors. Bibliometric analyses based on co-citation and co-words explore the intellectual structure of the topic. A bibliographic coupling analysis reveals the hottest research trends in this field.

A significant increase in the number of publications in recent years shows the importance gained by this research stream. The bibliometric analysis identifies four clusters throughout the literature: differentiation of types of elder abuse; protection of the elderly from fraud; cognitive and decision-making capacity in ageing; and factors influencing fraud victimization of the eldest. The most recent research lines identified through bibliographic coupling focused on the contextual and personal antecedents of financial exploitation of the elderly, as well as the possible impact of interventions. Several key research gaps and additional suggestions for further studies, as well as action lines for the financial authorities and economic agents, are outlined.

This paper contributes to knowledge about financial fraud exploiting the elderly synthesizing the existing literature, stressing that the banking industry has to deal with such financial fraud in the context of a growing relevance of the silver economy.

This study aims to determine the prevalence of obesity and its relationship with mental health issues among healthcare workers in Kota Kinabalu District Health Office, Sabah Borneo and its associating factors.

This cross-sectional study was conducted among 387 healthcare workers working in the Kota Kinabalu District Health Office, Sabah. Sociodemographic data and anthropometric measurements were collected and DASS 21 questionnaire was used to assess mental health status.

The prevalence of obesity among healthcare workers was 29%, which is significantly associated with years of service (p = 0.016) and abnormal depression subscale scores (p = 0.012) at univariate analysis. The percentage of abnormal subscale score for depression, anxiety and stress was 16, 26 and 12%, respectively. Multivariable logistic regression revealed that more than five years of service years (OR 2.23, 95%CI 1.16–4.28) and high depressive subscale score (OR 2.09, 95%CI 1.18–3.71) were both significantly associated with obesity.

This study has affirmed the link between physical and mental health. Policies that tackle both issues should be put in place to promote wellness among healthcare workers.