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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.

This study aims to investigate the impact of the ethical management of data privacy on the overall reputation of businesses.

A conceptual model was proposed and tested. Data were collected from 208 small and medium-sized enterprises (SMEs) in the textile industry in Valencia, Spain using a survey instrument. Partial least squares (PLS) allowed for the analysis of the data collected.

The theoretical model explains 46.1% of the variation in the organisational reputation variable. The findings indicate that ethical data privacy has a beneficial effect on an organisation's reputation and eco-innovation. The findings also demonstrate how eco-innovation drives the development of new knowledge and green skills that, in turn, communicate to stakeholders a company's ethical commitment. These results should encourage SMEs to invest in data privacy in order to meet the needs of the SMEs' increasingly technology- and environment-sensitive stakeholders and to improve their reputation.

This study provides the first empirical evidence that ethical data privacy management has a positive impact on the reputation of firms. Furthermore, the originality of the research derives from the analysis of the results from an environmental perspective. Indeed, this study shows that effective data privacy management can indirectly support organisational reputation through eco-innovation and green skills.

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 examines the impact of profitability, firm size and leverage on corporate tax avoidance in Bangladesh, an emerging South Asian economy.

A balanced panel data of 62 firms from Dhaka and Chittagong stock exchanges in Bangladesh from 2009 to 2020 were used to run the regression. This study employed the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) to examine the hypotheses.

The findings show that large firms positively impact corporate tax avoidance. Similarly, profitability and leverage are positively associated with tax avoidance, and the results are significant. Furthermore, the study conducts robustness tests that confirm the findings.

The use of cash effective tax rate (ETR) to investigate firms’ tax avoidance practices poses some limitations, and the results should be interpreted cautiously.

The current study may help policymakers better enhance tax collection from business firms. The findings could serve as a valuable input for effectively monitoring tax collection from large profit-earning firms.

To the authors' best knowledge, this is the first historical attempt in Bangladesh to use panel data to examine the relationship between the firm’s level characteristics and corporate tax avoidance. Panel data often provides greater flexibility with large data, simplifying calculation and statistical analysis.

Through this study, four different types of woven fabric structures were created by using cotton/banana blends with a 70:30 ratio by varying the weaving specifications. This study aims to investigate the comfort and mechanical properties of these woven materials.

Taguchi L16 experimental design (5 factors and 4 levels) with response surface methodology tool was used to optimize mechanical and comfort characteristics. The yarn samples used in this study are cotton/banana with a blend ratio of 70:30. Fabric type (A), grams per square metre (GSM; B), yarn count (C), fabric thickness (D) and cloth cover factor (E) are the chosen process characteristics.

The highest tensile strength and tearing strength of the cotton/banana blended fabric samples were obtained as 326.3 N and 90.3 k.gf/cm, respectively. Similarly, the highest thermal conductivity and overall moisture management capacity values were found to be 0.6628 and 3.06 W/mK X10⁻⁴, respectively. The optimized process parameters for obtaining maximum mechanical properties were using canvas fabric structure, 182 GSM, 36^s Ne yarn count, 0.48 mm fabric thickness and 23.5 cloth cover factor. Similarly, the optimized process parameters for obtaining maximum comfort properties were achieved using a twill fabric structure, 182 GSM, 32^s Ne yarn count, 0.4 mm fabric thickness and 23 cloth cover factor.

In contrast to synthetic fabrics, banana fibre and its blended materials are significant ecological solutions for apparel and functional clothing. Products made from banana fibre are a sustainable and green alternative to conventional fabrics. Banana fibre obtained from the pseudostem of the plant has an appearance similar to ramie and bamboo fibres. Numerous studies showed that banana fibre could absorb significant moisture and be spun into yarn through ring and rotor spinning technology. On the other hand, this fibre can be easily combined with cotton, jute, wool and synthetic fibre. The present utilization of pseudostem of banana plant fibre is very minimal. This type of research improves the usability of bananas their blended fabrics as apparel and functional wear.

Motivated by the disastrous impact of COVID-19 on the world’s economies, the purpose of this study is to examine its effect on the association between auditor industry specialization and external audit fees, referring to two time periods: before and during COVID-19.

A quantitative analysis based on the ordinary least squares regression is performed, using 3,200 company-year observations from 2005 to 2020 in Jordan to test the hypotheses. The qualitative component is a textual analysis of firms’ annual reports that support the quantitative analysis findings.

The analysis confirms there is a direct positive relationship between COVID-19 and external audit fees, confirming the tough consequences of the crisis on audit complexity and risks. While the results show evidence that the relationship between auditor specialist and audit fees is weakened because of COVID-19, the content analysis explained that COVID-19 led to fewer requests for high-quality audit, given the urgent need to report on firms’ financial circumstances. Jordan’s capital market is controlled by family businesses, and the insolvency of several large firms during COVID-19 led auditors to offer their services at low cost.

The findings of this study have serious implications for policymakers, legislators, regulators and the audit profession, as they examine the arising difficulties during a period of economic uncertainty. The findings can help to improve laws that control the auditing industry in Jordan following the damage caused by COVID-19. As well, the outcomes can be extrapolated to other Middle East nations.

To the best of the authors’ knowledge, the authors believe that this research presents the first evidence on the influence of COVID-19 on the auditing industry.

The purpose of this paper is to examine the impact of social movements engendered by the Arab Spring crisis on the relationship between corporate social responsibility disclosure (CSRD) and corporate governance attributes, particularly board composition, considering the importance of governance after the Arab Spring event.

Content analysis was used to examine the extent and nature of CSRD in annual reports of Jordanian companies listed on the Amman Stock Exchange covering the period 2009–2016. A dynamic regression model using panel data is then undertaken for a sample of 114 listed companies over the period to analyse the potential impact of board composition on the level of CSRD.

The results reveal that there was a significant increase in the level of CSRD post-the Arab Spring crisis; and that governance appears to be a key driver. Specifically, board age, directors educated in business and/or accounting-related fields and foreign members are found to have a significant positive relationship with CSRD.

Looking at the Arab region pre- and after the Arab Spring helps to complete the global picture of how company governance can lead to improved CSR performance. Specifically, this region has been behind in developing rules and codes that include CSR. The results show that having a diverse board, with directors with expertise specific to the context, increases the effectiveness of stakeholder management through CSRD. The results, therefore, offer valuable insights for companies, policymakers and for the development of regulations.

This paper aims to provide the security and privacy for Byzantine clients from different types of attacks.

In this paper, the authors use Federated Learning Algorithm Based On Matrix Mapping For Data Privacy over Edge Computing.

By using Softmax layer probability distribution for model byzantine tolerance can be increased from 40% to 45% in the blocking-convergence attack, and the edge backdoor attack can be stopped.

By using Softmax layer probability distribution for model the results of the tests, the aggregation method can protect at least 30% of Byzantine clients.

This study aims to practically determine the optimum proportion of aggregates to attain the desired strength of geopolymer concrete (GPC) and then compare the results using established analytical particle packing methods. The investigation further aims to assess the influence of various amounts of recycled aggregate (RA) on properties of low-calcium fly ash-based GPC of grade M25.

Fine and coarse aggregates were blended in various proportions and the proportion yielding maximum packing density was selected as the optimum proportion and they were compared with analytical models, such as Modified Toufar Model (MTM) and J. D. Dewar Model. RAs for this study were produced in laboratory and they were used in various amounts, namely, 0%, 50% and 100%. 12M NaOH solution was mixed with Na₂SiO₃ in the ratio of 1:2. The curing of concrete was done at the temperatures of 60° and 90 °C for 24, 48 and 72h.

The experimentally obtained optimum proportion of coarse to fine aggregate was 60:40 for all amounts of RA. Meanwhile, MTM and Dewar Model resulted in coarse aggregate to fine aggregates as 40:60, 45:55, 55:45 and 55:45, 35:65, 60:40, respectively, for 0% 100% and 50% RAs. The compressive strength of GPC elevated with the increase in curing regime. In addition, the ultrasonic pulse velocity also displayed a similar trend as that of strength.

The GPC with 50% RAs may be considered for use, as it exhibited superior properties compared to GPC with 100% RAs and was comparable to GPC with natural aggregates. Furthermore, compressive strength is correlated with split tensile strength and ultrasonic pulse velocity.

This paper systematically reviewed research work on drivers of teamwork, which will reinforce construction work teams to enhance workers’ safety performance. This study adds to the existing but limited understanding of teamwork drivers on construction workers’ safety performance. This paper presents scholars and industry-based professionals with critical initiatives that have to be implemented in organisations to get positive results in safety while working in teams with an emphasis on systems drivers of teamwork on safety performance at the organisational level, which will help in providing information on the functioning of the teams and contribute towards improved safety performance of team workers.

This study aims to systematically examine the existing body of knowledge on drivers of teamwork by analysing 53 publications from the years 1997–2021. The Scopus search engine was used to conduct a systematic review and germane publications were collated.

According to the findings of the review, since 1997, there has been a burgeoning concern in the research of drivers of teamwork and its impact on workers’ safety performance. After performing a systematic review, 37 drivers of teamwork were identified. The top five drivers are effective communications, team workers’ relations, leadership, shared knowledge and information, and team training. Moreover, it was noted that the United States and Australia have been the international regions of focus for most of the research in the area of drivers of teamwork from the years 1997–2021. The 37 drivers of teamwork are distributed into six major socio-technical components: people drivers; culture drivers; metrics drivers; organisational and management practices and procedures drivers; infrastructure drivers and technology drivers.

The results reported present research scholars and professional practitioners with an overview of the drivers of teamwork that could be implemented in the construction industry to streamline potential implementations and improve safety performance of construction workers.

A list of teamwork drivers has been developed to ratify potential empirical research in the area of construction safety. The results would contribute to the existing but restricted understanding of drivers of teamwork in the construction industry.