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This paper aims to examine tourists' behavioral changes in response to health crises, this study examines the individual's uncertainty and adaptability to the challenges using behavioral coping strategies.

The study combines the theory of planned behavior (TPB) and protection motivation theory. Using the PLS-SEM technique, this study examines the relationship between the destination's competitive profits and travel intention of Iranian tourists in the post-Covid-19 pandemic.

The social-support coping (Instrumental) does not incorporate tourists' adaptive behaviors. Vulnerable vaccination significantly affects the extremeness of an individual's problem-focused coping, which affects tourist's adaptive behaviors in crisis time, indicating the effectiveness of the Covid-19 vaccination on travel intention.

The findings may assist tourism authorities and planners develop unique tourism products and services based on tourist behavior following the health crises.

This study contributes to development of the TPB method, indicating that visa exemption and competitive profits of a destination would motivate travel intention existing inefficacy of local government and its negative background, reshaping and thus influencing changing behavior.

Port competition attracted much scholarly attention in Northwest Europe during the 1980s. Following the rise of powerful economies in East Asia, particularly during the 1980s and 1990s, port competition has become an important phenomenon with the top five container ports in the world being located in the region. This paper aims to overview major port competition issues and outlines and analyzes the main alternative methodologies that researchers have employed to address them, referring to 70 items, mostly papers but including a few books and reports

This paper empirically investigates the performance of Islamic funds, which have been praised for weathering the 2008 financial storm relatively well and compares it to a European product designed to protect the most vulnerable of investors, UCITS funds.

This paper builds on 128 time-series regressions using various factor models to analyse the risk-return relationship of 242 Islamic and UCITS funds relative to a market benchmark, over a 10-year period starting January 2006, to capture severe bear and bull market conditions.

Islamic funds do not face a competitive disadvantage arising from their strict compliance with Sharīʿah principles, and their performance and investment style is relatively similar to UCITS schemes.

Islamic funds represent a low risk investment due to their very mild betas. Therefore, when forming part of a diversified portfolio, they can act as a hedging tool against adverse market movements.

Muslim investors are not punished relative to conventional retail investors when following their own beliefs. Other investors can consider Islamic funds in their portfolio allocation, especially those who seek socially and ethically responsible investments.

This paper fills a lacuna in the existing literature, because the sample is made up of Islamic funds established worldwide and includes not only equity, but also fixed income and mixed allocation funds.

The amount of features in handwritten digit data is often very large due to the different aspects in personal handwriting, leading to high-dimensional data. Therefore, the employment of a feature selection algorithm becomes crucial for successful classification modeling, because the inclusion of irrelevant or redundant features can mislead the modeling algorithms, resulting in overfitting and decrease in efficiency.

The minimum redundancy and maximum relevance (mRMR) and the recursive feature elimination (RFE) are two frequently used feature selection algorithms. While mRMR is capable of identifying a subset of features that are highly relevant to the targeted classification variable, mRMR still carries the weakness of capturing redundant features along with the algorithm. On the other hand, RFE is flawed by the fact that those features selected by RFE are not ranked by importance, albeit RFE can effectively eliminate the less important features and exclude redundant features.

The hybrid method was exemplified in a binary classification between digits “4” and “9” and between digits “6” and “8” from a multiple features dataset. The result showed that the hybrid mRMR +  support vector machine recursive feature elimination (SVMRFE) is better than both the sole support vector machine (SVM) and mRMR.

In view of the respective strength and deficiency mRMR and RFE, this study combined both these methods and used an SVM as the underlying classifier anticipating the mRMR to make an excellent complement to the SVMRFE.

This study aims to assess the knowledge and attitudes toward recovering citizenship (RC)/5 Rs and mental illness of people aged ≥18 years in Hong Kong using a telephone survey approach.

A questionnaire comprised the Mental Health Knowledge Schedule (MAKS), Short Form-Community Attitudes Toward Mental Illness (SF-CAMI) and questions on attitudes toward RC/5 Rs, was administered on the phone.

A total of 1,009 respondents completed the telephone survey. A high mean score of MAKS (4.37 ± 1.08) was found with 68%–94% answering the knowledge items correctly. The mean score of SF-CAMI was 46.50 ± 8.74 with the most positive attitude toward fear and exclusion. Approximately half had heard about a similar concept of RC and 79%–94.3% agreed with people in recovery to possess the 5 Rs. Those with greater knowledge or more positive toward mental illness, or knowing someone in recovery were more supportive toward 5 Rs. Those aged 18–44 years, attained a post-secondary education, were employed, and received a monthly income of US$3,861–6,434 were significantly more positive toward 5 Rs.

To the best of the authors’ knowledge, this is the first study assessing the views of RC of people in the community. The sample had a good knowledge of mental illness but recognition of recovery from mental illness and a sympathetic view toward people in recovery can be further improved. Besides promotion programs, dissemination of the concept of RC and having people in recovery take up valued roles in the community could potentially facilitate the acceptance of social inclusion and acceptance in the community.

This study aims to examine the relationship between auditor industry specialization (IS) and audit fees.

The authors utilize 2,100 firm-year data of Jordanian companies from 2005 to 2018. Two conflicting theoretical approaches of IS were employed: the product differentiation approach, as assessed by market share (MS); and the shared efficiency approach, as evaluated by portfolio share (PS).

Results of the ordinary least squares (OLS) regression support product differentiation (shared efficiency) and show that employing experts' auditors exerts a very substantial and favorable direct impact on audit fees (negative).

This research contributes new empirical data to the auditing literature by examining if IS does influence Jordanian businesses' audit fees. The findings offer useful data for Jordanian officials to examine the auditing industry's difficulties while refining regulations and revising auditor pricing. Additionally, the results offer advice to Jordan's regulatory bodies who oversee the auditing industry. Arguably, results from Jordan may be extrapolated to other Middle Eastern nations.

This paper examines the network dynamics of the cross-border trades utilizing Social Network Analysis (SNA) based on data obtained from the WTO-OECD Trade in Value Added database from 2000-2011. The main results of this paper are as follows: regarding the top 10 in-degree centrality industries, industries in China, Germany, and the U.S. have emerged as the largest importers of foreign value added, implying that the global production network is dominated by two different types of industries. The first type includes processing and assembling functions in China and Germany. The other type of industry involves foreign value added largely for domestic final demand in the U.S. Secondly, there are also two types of brokerage roles. U.S. industries are operating in a liaison role, while Chinese and German industries are mostly operating as coordinator or gatekeeper. Thirdly, manufacturing industries in China and Germany which have emerged as higher in-degree centrality incur a large portion of their value added from the logistics industry. This suggests that those leading industries with the highest characteristics of hubness in the global production network cannot sustain their network status without efficient utilization of the logistics industry.

The purpose of this paper is to use tenets of the complexity theory in order to study the effect of various determinants of firm’s performance, such as CEO’s compensation and age, for the case of 72 insurance companies.

The authors identify the asymmetries in the data set by creating quantiles and using contrarian analysis. Instead of ignoring this information and use a main effects approach, all the available information in the data set is taken into account. For this purpose, the authors use qualitative comparative analysis to find alternative equifinal routes toward high firm performance.

Five configurations are found which lead to high performance. Every one of the five configurations is found to be sufficient but not necessary for high firm performance.

The research findings contribute to a better understanding of the determinants of firm’s performance taking into account the asymmetries in the data set. The authors identify alternative paths toward high firm performance, which could be vital information for the decision maker inside a firm.

This study aims to explore the similarities and differences between the three concepts that are commonly used to describe the knowledge of traditional and indigenous communities, namely, indigenous knowledge, traditional knowledge and local knowledge, with a view to contributing to the discourse on conceptualizing indigenous knowledge.

Data was extracted from the Scopus database using the main terms that are used for indigenous knowledge, namely, “indigenous knowledge” (IK), “traditional knowledge” (TK) and “local knowledge” (LK). Data were analyzed according to the themes drawn from the objectives of the study, using the VOSviewer software and the analytical tool embedded in the Scopus database.

The findings indicate that whereas IK and LK are older concepts than TK, TK has become more visible in the literature than the former; there is minimal overlap in the use of the labels in the literature; the three labels’ literature is largely domiciled in the social sciences; and that there were variations in representation of the labels according to countries and geographic regions.

The author avers that the scatter of literature on the knowledge of traditional and indigenous peoples under the three main labels has huge implications on the accessibility and use the literature by stakeholders including researchers, students, information and knowledge managers and information service providers.

This study demonstrates the application of informetrics beyond is traditional use to assess trends, nature and types of research patterns and mathematical modeling of information patterns to encompass the definition of the scope of concepts as covered in the literature.

The purpose of this paper is to examine peer-to-peer sharing platform business models, their sources of competitive advantage, and the roles, motivations and behaviors of key actors in their ecosystems.

This paper uses a conceptual approach that is rooted in the service, tourism and hospitality, and strategy literature.

First, this paper defines key types of platform business models in the sharing economy anddescribes their characteristics. In particular, the authors propose the differentiation between sharing platforms of capacity-constrained vs capacity-unconstrained assets and advance five core properties of the former. Second, the authors contrast platform business models with their pipeline business model counterparts to understand the fundamental differences between them. One important conclusion is that platforms cater to vastly more heterogeneous assets and consumer needs and, therefore, require liquidity and analytics for high-quality matching. Third, the authors examine the competitive position of platforms and conclude that their widely taken “winner takes it all” assumption is not valid. Primary network effects are less important once a critical level of liquidity has been reached and may even turn negative if increased listings raise friction in the form of search costs. Once a critical level of liquidity has been reached, a platform’s competitive position depends on stakeholder trust and service provider and user loyalty. Fourth, the authors integrate and synthesize the literature on key platform stakeholders of platform businesses (i.e. users, service providers, and regulators) and their roles and motivations. Finally, directions for further research are advanced.

This paper helps platform owners, service providers and users understand better the implications of sharing platform business models and how to position themselves in such ecosystems.

This paper integrates the extant literature on sharing platforms, takes a novel approach in delineating their key properties and dimensions, and provides insights into the evolving and dynamic forms of sharing platforms including converging business models.