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This paper investigates the extent to which the COVID-19 pandemic has accelerated service innovation in the restaurant sector. It explores the use of digital technologies (DT) as a safety-empowerment and resilient strategy in the food-service industry during the pandemic. It also investigates the impact of DT on customers' risk perception (CRP) and customers' intention to go to restaurants (CIR) in Italy.

Based on the theory of planned behaviour and perceived risk theory, this study investigates a sample of customers residing in Italy. Multiple regression and mediation analyses are conducted to test the research hypotheses, adapting the logic model developed. Using the bootstrapping technique, this study also explores whether the pandemic has moderated the relationship among several variables adapted from the literature. Robustness tests are also performed to corroborate the analysis.

The pandemic has accelerated the food-service industry's digital transformation, forcing restauranteurs to implement DT to survive. Findings show that DT support restauranteurs in implementing innovative services that reduce interactions and empower cleanliness among workers and customers, reducing CRP and preserving CIR. Thus, managing risk perception is helping the restaurant sector to recover.

Practical implications are presented for policymakers to catalyse the digital transformation in small- and medium-sized restaurants. The results may also be beneficial for entrepreneurs who can implement innovative service practices in order to reduce interaction and empower cleanliness levels. Moreover, academics can use these results to conduct similar research in other geographical contexts.

The present research represents the first study investigating the relationship between the use of digital technologies and the intentions of customers to go out for dinner during the ongoing pandemic in Italy.

This study aims to predict overnight stays in Italy at tourist accommodation facilities through a nonlinear, single factor, stochastic model called CIR#. The contribution of this study is twofold: in terms of forecast accuracy and in terms of parsimony (both from the perspective of the data and the complexity of the modeling), especially when a regular pattern in the time series is disrupted. This study shows that the CIR# not only performs better than the considered baseline models but also has a much lower error than other additional models or approaches reported in the literature.

Typically, tourism demand tends to follow regular trends, such as low and high seasons on a quarterly/monthly level and weekends and holidays on a daily level. The data set consists of nights spent in Italy at tourist accommodation establishments as collected on a monthly basis by Eurostat before and during the COVID-19 pandemic breaking regular patterns.

Traditional tourism demand forecasting models may face challenges when massive amounts of search intensity indices are adopted as tourism demand indicators. In addition, given the importance of accurate forecasts, many studies have proposed novel hybrid models or used various combinations of methods. Thus, although there are clear benefits in adopting more complex approaches, the risk is that of dealing with unwieldy models. To demonstrate how this approach can be fruitfully extended to tourism, the accuracy of the CIR# is tested by using standard metrics such as root mean squared errors, mean absolute errors, mean absolute percentage error or average relative mean squared error.

The CIR# model is notably simpler than other models found in literature and does not rely on black box techniques such as those used in neural network (NN) or data science-based models. The carried analysis suggests that the CIR# model outperforms other reference predictions in terms of statistical significance of the error.

The proposed model stands out for being a viable option to the Holt–Winters (HW) model, particularly when dealing with irregular data.

The proposed model has demonstrated superiority even when compared to other models in the literature, and it can be especially useful for tourism stakeholders when making decisions in the presence of disruptions in data patterns.

The novelty lies in the fact that the proposed model is a valid alternative to the HW, especially when the data are not regular. In addition, compared to many existing models in the literature, the CIR# model is notably simpler and more transparent, avoiding the “black box” nature of NN and data science-based models.

一般来说, 旅游需求往往遵循规律的趋势, 例如季度/月的淡季和旺季, 以及日常的周末和假期。该数据集包括欧盟统计局在打破常规模式的2019冠状病毒病大流行之前和期间每月收集的在意大利旅游住宿设施度过的夜晚。

本研究旨在通过一个名为cir#的非线性单因素随机模型来预测意大利游客住宿设施的过夜住宿情况。这项研究的贡献是双重的:在预测准确性方面和在简洁方面(从数据和建模复杂性的角度来看), 特别是当时间序列中的规则模式被打乱时。我们表明, cir#不仅比考虑的基线模型表现更好, 而且比文献中报告的其他模型或方法具有更低的误差。

当大量搜索强度指标被作为旅游需求指标时, 传统的旅游需求预测模型将面临挑战。此外, 鉴于准确预测的重要性, 许多研究提出了新的混合模型或使用各种方法的组合。因此, 尽管采用更复杂的方法有明显的好处, 但风险在于处理难使用的模型。为了证明这种方法能有效地扩展到旅游业, 使用RMSE、MAE、MAPE或AvgReIMSE等标准指标来测试cir#的准确性。

cir#模型明显比文献中发现的其他模型简单, 并且不依赖于黑盒技术, 例如在神经网络或基于数据科学的模型中使用的技术。所进行的分析表明, cir#模型在误差的统计显著性方面优于其他参考预测。

这个模型作为Holt-Winters模型的一个拟议模型, 特别是在处理不规则数据时。

即使与文献中的其他模型相比, 所提出的模型也显示出优越性, 并且在数据模式中断时对旅游利益相关者做出决策特别有用。

创新之处在于所提出的模型是Holt-Winters模型的有效替代方案, 特别是当数据不规律时。此外, 与文献中的许多现有模型相比, cir#模型明显更简单、更透明, 避免了神经网络和基于数据科学的模型的“黑箱”性质。

Normalmente, la demanda turística tiende a seguir tendencias regulares, como temporadas altas y bajas a nivel trimestral/mensual y fines de semana y festivos a nivel diario. El conjunto de datos consiste en las pernoctaciones en Italia en establecimientos de alojamiento turístico recogidas mensualmente por Eurostat antes y durante la pandemia de COVID-19, rompiendo los patrones regulares.

El presente estudio pretende predecir las pernoctaciones en Italia en establecimientos de alojamiento turístico mediante un modelo estocástico no lineal de un solo factor denominado CIR#. La contribución de este estudio es doble: en términos de precisión de la predicción y en términos de parsimonia (tanto desde la perspectiva de los datos como de la complejidad de la modelización), especialmente cuando un patrón regular en la serie temporal se ve interrumpido. Demostramos que el CIR# no sólo aplica mejor que los modelos de referencia considerados, sino que también tiene un error mucho menor que otros modelos o enfoques adicionales de los que se informa en la literatura.

Los modelos tradicionales de previsión de la demanda turística pueden enfrentarse a desafíos cuando se adoptan cantidades masivas de índices de intensidad de búsqueda como indicadores de la demanda turística. Además, dada la importancia de unas previsiones precisas, muchos estudios han propuesto modelos híbridos novedosos o han utilizado diversas combinaciones de métodos. Así pues, aunque la adopción de enfoques más complejos presenta ventajas evidentes, el riesgo es el de enfrentarse a modelos poco manejables. Para demostrar cómo este enfoque puede extenderse de forma fructífera al turismo, se comprueba la precisión del CIR# utilizando métricas estándar como RMSE, MAE, MAPE o AvgReIMSE.

El modelo CIR# es notablemente más sencillo que otros modelos encontrados en la literatura y no se basa en técnicas de caja negra como las utilizadas en los modelos basados en redes neuronales o en la ciencia de datos. El análisis realizado sugiere que el modelo CIR# supera a otras predicciones de referencia en términos de significación estadística del error.

El modelo propuesto destaca por ser una opción viable al modelo Holt-Winters, sobre todo cuando se trata de datos irregulares.

El modelo propuesto ha demostrado su superioridad incluso cuando se compara con otros modelos de la bibliografía, y puede ser especialmente útil para los agentes del sector turístico a la hora de tomar decisiones cuando se producen alteraciones en los patrones de datos.

La novedad radica en que el modelo propuesto es una alternativa válida al Holt-Winters especialmente cuando los datos no son regulares. Además, en comparación con muchos modelos existentes en la literatura, el modelo CIR# es notablemente más sencillo y transparente, evitando la naturaleza de “caja negra” de los modelos basados en redes neuronales y en ciencia de datos.

This paper aims to test three parametric models in pricing and hedging higher-order moment swaps. Using vanilla option prices from the volatility surface of the Euro Stoxx 50 Index, the paper shows that the pricing accuracy of these models is very satisfactory under four different pricing error functions. The result is that taking a position in a third moment swap considerably improves the performance of the standard hedge of a variance swap based on a static position in the log-contract and a dynamic trading strategy. The position in the third moment swap is taken by running a Monte Carlo simulation.

This paper undertook empirical tests of three parametric models. The aim of the paper is twofold: assess the pricing accuracy of these models and show how the classical hedge of the variance swap in terms of a position in a log-contract and a dynamic trading strategy can be significantly enhanced by using third-order moment swaps. The pricing accuracy was measured under four different pricing error functions. A Monte Carlo simulation was run to take a position in the third moment swap.

The results of the paper are twofold: the pricing accuracy of the Heston (1993) model and that of two Levy models with stochastic time and stochastic volatility are satisfactory; taking a position in third-order moment swaps can significantly improve the performance of the standard hedge of a variance swap.

The limitation is that these empirical tests are conducted on existing three parametric models. Maybe more critical insights could have been revealed had these tests been conducted in a brand new derivatives pricing model.

This work is 100 per cent original, and it undertook empirical tests of the pricing and hedging accuracy of existing three parametric models.

The purpose of this study is to evaluate the effect of some internal features that influence the efficiency of non-bank financial institutions (NBFIs) in Bangladesh.

The study selected the top 15 Dhaka Stock Exchange (DSE)-listed NBFIs according to purposive sampling. The study period was from 2016 to 2020. Secondary data were collected from annual reports. The cost-to-income ratio was a dependent variable that was used as a proxy of operational efficiency. The ordinary least square regression technique was applied to measure the impact of firm-specific factors on efficiency.

Results showed that number of employees, branch number, firm size and deposit ratio have a significant effect on efficiency at 5% level. The number of branches and employees showed a negative impact, whereas firm size and deposit ratio showed a positive effect on the firms' efficiency. The deposit ratio is negatively related because deposit interest expenses were more than offset by interest income generation through the conversion of deposits into loans.

The study has practical and policy implications on NBFIs' managers, employees, shareholders, depositors, clients, regulatory authorities and government as efficiency enhancement would bring financial soundness.

This study shed light on some firm-specific factors that can be changed to increase operational efficiency or reduce the cost-to-income ratio. The novelty of the study is that it identified some significant associations between firm-specific factors and the operational efficiency of NBFIs.

The study aims to identify whether international financial reporting standards (IFRS) or local generally accepted accounting principles (GAAP) reporting provides investors and senior management of acquirer banks with superior information on target banks under post-merger bank performance.

The authors examine the claim that IFRS improves corporate transparency and increases financial reporting quality in European Bank merger and acquisitions (M&As). The authors compare the financial performance of merged banks where the target and acquirer banks employed the same reporting system (up to 305 merged banks) to the performance of a control group of banks not engaged in M&A activity (up to 1,690 European banks).

Local GAAP reporting allows a more transparent assessment of financial performance using traditional indicators, making it a superior tool for assessing potential acquisition targets.

Overall, the empirical findings are consistent with prior studies and indicate a significant relationship between local GAAP and post-merger performance, while IFRS does not contribute to post-merger bank performance.

The study is one of the very few studies to investigate the relationship between bank performance, M&A activity and accounting standards in EU-28 countries. The primary contribution the finding of poor performance of IFRS reporting merged banks compared to local GAAP banks in EU-28 countries in line with prior results of Huian (2012). In addition, several deal- and bank-specific characteristics that affect accounting standards influence M&A transactions in European banks.

The purpose of this study is to explore educational policy directions in the Maldives to continue learning in public schools during the coronavirus disease 2019 (COVID-19) pandemic and identify policy changes that could improve the preparedness of the schools for future pandemics.

This qualitative study is descriptive in nature with an analytical methodology of document and interview data analysis. The purposively selected participants for the interviews included senior officials of the Ministry of Education, school leaders and teachers of public schools in the Maldives.

This study identified significant policy changes for public schools in the Maldives during the COVID-19 pandemic. These were early response and timely policy directions to continue education during the COVID-19 pandemic. Another finding was the effective change communication of the educational policies for its implementation. Following the policy changes, the teachers were trained for online teaching, hence increasing their competency in information and communications technology. As a result, this led to resilient teachers who were determined to provide education through the challenging times of the pandemic. Hence, it is evident that the school system of the Maldives will emerge stronger beyond COVID-19.

The education policy changes for public schools in the Maldives during the global COVID-19 pandemic have merits for education practices beyond the pandemic.

Kiobel v. Royal Dutch Petroleum Co. involves an action under the Alien Tort Statute (ATS). The case was brought in the United States, Southern District of New York, by the widow of Dr. Barinem Kiobel, a Nigerian activist and member of the Ogoni tribe, and others for human rights violations committed in the Niger River Delta. Defendants include Royal Dutch Petroleum, Shell Transport and Trading Co., and Shell Petroleum Development Company of Nigeria. Although the human rights violations including murder and torture were allegedly committed by the Nigerian military government, it is claimed that the Royal Dutch Petroleum defendants aided and abetted the Nigerian military in the human rights violations. The plaintiffs had engaged in protests about the environmental damage caused by the Royal Dutch Petroleum defendants in the area of the Niger Delta and the plight of the Ogoni people in Ogoniland. At the trial level, the court decided that certain claims involving violations of the Law of Nations could be heard by the court. However, the case was appealed to the U.S. Supreme Court, which decided that there is a presumption against extraterritoriality in the application of the ATS, and that “mere presence” of a defendant corporation in the United States is insufficient for a court to assume jurisdiction. However, the question remains: What corporate presence would serve as a sufficient basis for a court to assume jurisdiction under the ATS? Given the possibility that corporations could, and perhaps in the future will, be found liable for human rights violations occurring in foreign locales even after Kiobel, prudent risk management behooves corporations and their counsel to monitor whether human rights violations are occurring in connection with their operations, even when those human rights violations are committed by foreign governments or their agents.

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.

Local Safeguarding Adults Board (SAB) policies, procedures, guidance and related documents on self-neglect were gathered and analysed, to map what approaches are being taken across England. This paper aims to identify areas of divergence to highlight innovations or challenges faced by SABs.

Self-neglect documents were identified by searching SAB websites. Data were extracted into a framework enabling synthesis and comparison between documents.

This paper reports on how English SAB documentation defines self-neglect, treats executive capacity, lays out pathways for self-neglect cases, advises on refusal of service input and multi-agency coordination and draws on theories or tools. Greater coherence in understanding self-neglect has developed since it was brought within safeguarding in 2014; however, variation remains regarding scope, referral pathways and threshold criteria.

This review was limited to published SAB documentation at one point in time and could not consider either the wider context of safeguarding guidance and training or implementation in practice.

This review provides an overview of how SABs are interpreting national guidance and guiding practitioners. The trends and areas of uncertainty identified offer a resource for informed research and policy-making.

To the best of the author’s knowledge, this is the first systematic survey of SAB self-neglect policies, procedures and guidance since self-neglect was included under safeguarding.