Search results

In this study, solid formaldehyde, benzoguanamine and butanol were used to synthesize butylated benzo-amino resin by one-step-two-stage method.

This research first examined the influence of solid formaldehyde content on the hydroxymethylation phase. Subsequently, the effects of butanol content, etherification time and hydrochloric acid content on the formation of benzo-amino resin during the etherification stage were studied in detail. In addition, the reaction process was further analyzed through interval sampling withdrawing during the hydroxymethylation and etherification stages. Finally, the synthesized benzo-amino resins were used in the production of high solid content polyester and acrylic coatings and the properties of that were also evaluated.

Based on the experimental findings, the authors have successfully determined the optimal process conditions for the one-step-two-stage method in this study. The hydroxymethylation stage demonstrated the most favorable outcomes at a reaction temperature of 60°C and a pH of 8.5. Similarly, for the etherification stage, the optimal conditions were achieved at a temperature of 45°C and a pH of 4.5. Furthermore, the investigation revealed that a ratio of benzoguanamine to solid formaldehyde to n-butanol, specifically at 1:5.2:15, produced the best results. The performance of the resulting etherified benzo-amino resin was thoroughly evaluated in high solid content coatings, and it exhibited promising characteristics. Notably, there was a significant enhancement in the water resistance, solvent resistance and glossiness of canned iron printing varnish coatings.

Amino resin, a versatile chemical compound widely used in various industries, presents challenges in terms of sustainability and operational efficiency when synthesized using conventional methods, primarily relying on a 37% formaldehyde solution. To address these challenges, the authors propose a novel approach in this study that combines the advantages of the solid formaldehyde with a two-stage catalytic one-step synthesis process. The primary objective of this research is to minimize the environmental impact associated with amino resin synthesis, optimize resource utilization and enhance the economic feasibility for its industrial implementation. By adopting this alternative approach, the authors aim to contribute toward a more sustainable and efficient production of amino resin.

By using Technology Acceptance Model, the purpose of this study is to investigate how the perceived usefulness and ease-of-use of shopping mobile apps affects consumer’s flow experience, attitude, impulsive buying tendency (IBT) and urge to impulsive buying on halal fashion products.

A quantitative study was done on 357 Indonesian online shoppers to find out how perceived usefulness and ease of use of mobile shopping apps affect impulsive buying tendencies and urges on halal fashion products. Flow experience and attitude were used as mediating variables, and the research hypotheses were tested using Partial Least Square Structural Equation Modeling (PLS-SEM).

This study confirmed significant positive relationships between perceived usefulness and ease of use of mobile apps, flow experience, attitude, IBT and urge to impulsive buying. The results of this study show that perceived usefulness and ease of use influence flow experience. Ease of use also influences attitude, but perceived usefulness did not impact attitude. In addition, flow experience did not impact attitude. However, both flow experience and attitude influence IBT. Furthermore, IBT significantly mediated flow experience and attitude into urge to impulsive buying.

This study only captured consumers in one country, so its results cannot be generalized to other nations. Random sampling may limit result generalization. In this study, three mobile shopping applications were investigated and the results would have been different if more mobile shopping applications were investigated.

The study gives a better understanding of how the perceived usefulness and ease of use of mobile shopping apps affect a consumer's tendency and urge to impulsive buying on halal fashion products by using flow experience as mediating variable.

Social sciences have discussed the host–guest relation from many theoretical lenses and perspectives. Violence as well as local crime has been studied as one of the major risks concerning tourism security. Anyway, less attention was given to homeless people and their interaction with foreign or local tourists. The purpose of this paper is oriented to explain how globalization has winners and losers, in which case, as noted, thousands of persons are excluded from the formal labor marketplace or the economic system year by year.

This is a conceptual paper that discusses critically not only the recent advances of sociology in urban tourism but also the connection between homeless people and tourists.

There is an urban underclass formed by those who have been excluded from the economic system. What is more important, such an underclass situates nearby luxury hotels and tourist destinations creating serious contradictions or zones of disputes. These contradictions have been approached by different sociologists since the turn of the 20th century.

The question of sustainability, as well as the idea of liveable cities, and the efficient organization of the city, have occupied a central position in the academic debate, above all after the COVID-19 pandemic. In the present paper, the authors put in dialogue the contributions of Marc Auge with Zyggy Bauman toward a new understanding of this postmodern phenomenon.

Based on the metaphor of vagabonds and tourists, we give a snapshot of the problem of homelessness in Buenos Aires city and its effects on the tourism industry. Unlike other English-speaking countries where the cities are actively organized by the state, Buenos Aires city lacks a planned program to regulate and relocate homeless people. They dwell in nonplaces nearby tourists sleeping in the streets near luxury hotels (but for sure escaping any planning or governmental control).

Empirical examinations of initial public offering (IPO) initial returns often rely heavily on linear regression models. However, these models can prove inefficient owing to their susceptibility to outliers, a common occurrence in IPO data. This study introduces a machine learning method, known as random forest, to address issues that linear regression may struggle to resolve.

The study’s sample comprises 352 fixed-priced IPOs from the year 2004 until 2021. A unique aspect of this research is its application of the random forest method. The accuracy of random forest in comparison to other methods is evaluated. The findings indicate that the random forest model significantly outperforms other methods in all of the evaluated aspects.

The variable importance measure indicates that investors’ demand, divergence of opinion among investors and offer price are the most crucial predictors of IPO initial returns. These determinants hold particular significance due to the widespread use of the fixed-price method in Malaysia, as this method amplifies the information asymmetry in the IPO market.

To the best of the authors’ knowledge, this study is among the pioneering works in Malaysian literature to apply the random forest method to address the constraints of conventional linear regression models. This is achieved by considering a more extensive array of factors and acknowledging the influence of outliers. Additionally, this study adds value to Malaysian literature by ranking and identifying the ex-ante information that best signals the issuing firm’s quality. This contribution facilitates prospective investors’ decision-making processes and provides issuing firms with effective means to communicate their value and quality to the IPO market.

This paper aims to examine the impact of board gender diversity (BOGD) following the adoption of gender quota legislation on earnings management (EM) in an emerging market, Egypt, whose cultural and economic conditions and institutional context are unlike most previously studied countries’ context.

The authors use ordinary least squares (OLS) regression to estimate the impact of gender quota legislation on EM using data from listed companies in Egypt from 2015 to 2022. Difference-in-difference (DID) approach estimation was used to validate the robustness of the main results.

This paper documents that gender diversity on boards has a significantly negative impact on EM. In addition, this paper provides robust evidence using the DID approach to show that BOGD is significantly negatively linked with EM for the period following gender quota legislation. Furthermore, the results support the critical mass and agency theories.

The findings of this study have important implications for Egyptian companies, regulatory bodies and investors in emerging markets. Specifically, these results suggest that when choosing board members, enterprises should pay particular attention to BOGD, and female involvement in all listed firms should be monitored by regulators.

This paper provides evidence supporting the positive contribution of women in society by enhancing the economic performance of Egyptian firms and promoting the country’s sustainable development strategy in light of Egypt vision 2030.

As per the authors' knowledge, this empirical study is unique in investigating the impact of BOGD quota regulation on EM in Egypt. This paper contributes to BOGD as a major factor in improving financial reporting quality in Egyptian companies.

This study aims to examine the potential of Sharia status as ex ante information to signal the quality of an issuing firm by improving the decision-making process of potential investors when assessing initial public offerings (IPOs) in an environment where information asymmetry is pronounced. Potential investors face challenges in evaluating and determining the true value of IPO issues, which inherently influences their decision-making. Consequently, this results in pronounced price fluctuations in IPO shares, leading to higher underpricing.

This study uses a sample of 350 IPOs listed on the Kuala Lumpur Stock Exchange (KLSE) between 2004 and 2021 to examine the signaling role of Sharia-compliance status. A three-model approach is used to ensure that the study's objectives are met. The first model investigates the effect of Sharia status on underpricing to determine whether the main beneficiary of such a signal is the investor or the issuer. The second model examines the effect of Sharia status on investor demand to determine if such a signal influences prospective investors' investment decision-making processes. The third model inspects the effect of Sharia status on investor divergence of beliefs to measure the signal's ability to reduce information asymmetry within the Malaysian IPO market.

The Malaysian IPO market relies heavily on the fixed-price mechanism, which exacerbates high information asymmetry, affecting potential investors' behavior, asset price formation and return generation on the first day of listing. The study results indicate that Sharia status does not have any signaling role in the Malaysian IPO market. This is because investors in the Malaysian market are driven by ex ante information that helps unveil relevant information that leads to capital gains. Furthermore, most new issues in the Malaysian IPO market fall under Sharia status, diluting the relevance of such information for prospective investors in determining profitable investments.

The findings highlight the challenges faced by issuing firms in estimating market demand due to limited premarket insights and the difficulties prospective investors face in identifying the quality of issuing firms. Efforts to provide more information on investor demand can reduce uncertainty and facilitate more informed decision-making.

This research stands as one of the pioneering efforts to provide an empirical explanation of the potential signaling influence of Sharia status in an emerging IPO market.

The world order is experiencing unremitting changes. With this, the national governance of emerging economies is also becoming robust. Therefore, the current study examines the efficacy of national governance in the context of emerging economies by investigating its effects on the profitability of the microfinancing sector. Further, the study inspects if national governance mitigates the impact of credit risks to protect profitability.

The study considers panel data from 224 microfinancing institutions from five economies of world importance: Brazil, Russia, India, China and South Africa (BRICS). The study uses dynamic panel data modeling, particularly the generalized method of moments, alongside multiple univariate and multivariate techniques.

The findings indicate that credit risks negatively impact profitability. In addition, the study documents a significant positive linkage between national governance and profitability. However, national governance fails to restrict the adverse effects of credit risks. National governance is found to be effective in reducing internal agency problems; the monitoring effects successfully limit the moral hazards due to managers' actions. Conversely, the national governance in these economies misses the mark in regulating the moral hazards due to borrowers' behavior.

The current study provides fresh perspectives on the efficacy of national governance in microfinancing in the setting of emerging economies.

Integrating the Chat Generative Pre-Trained Transformer-type (ChatGPT-type) model with government services has great development prospects. Applying this model improves service efficiency but has certain risks, thus having a dual impact on the public. For a responsible and democratic government, it is necessary to fully understand the factors influencing public acceptance and their causal relationships to truly encourage the public to accept and use government ChatGPT-type services.

This study used the Latent Dirichlet allocation (LDA) model to analyze comment texts and summarize 15 factors that affect public acceptance. Multiple-related matrices were established using the grey decision-making trial and evaluation laboratory (grey-DEMATEL) method to reveal causal relationships among factors. From the two opposite extraction rules of result priority and cause priority, the authors obtained an antagonistic topological model with comprehensive influence values using the total adversarial interpretive structure model (TAISM).

Fifteen factors were categorized in terms of cause and effect, and the antagonistic topological model with comprehensive influence values was also analyzed. The analysis showed that perceived risk, trust and meeting demand were the three most critical factors of public acceptance. Meanwhile, perceived risk and trust directly affected public acceptance and were affected by other factors. Supervision and accountability had the highest driving power and acted as the causal factor to influence other factors.

This study identified the factors affecting public acceptance of integrating the ChatGPT-type model with government services. It analyzed the relationship between the factors to provide a reference for decision-makers. This study introduced TAISM to form the LDA-grey-DEMATEL-TAISM method to provide an analytical paradigm for studying similar influencing factors.

This study aims to explore the synthesis, characteristics and utilization of polymer composites integrated with cutting-edge pigments.

The incorporation of advanced pigments introduces functionalities such as enhanced mechanical strength, thermal stability, ultraviolet resistance and color stability, thus extending the range of applications in diverse fields including automotive, aerospace, electronics and construction.

This review discusses the mechanisms underlying the property enhancements achieved through the incorporation of advanced pigments and highlights recent developments in the field.

Polymer composites incorporating advanced pigments have garnered significant attention in recent years because of their potential to enhance various material properties and broaden their applications. This paper explores the fabrication methods of polymer composites reinforced with organic/inorganic advanced pigments in brief along with their characteristics and applications.

The purpose of this study is to examine effects of classroom-level and student-level factors on student engagement in the context of a higher education system vertically differentiated into research, applied and comprehensive university types.

The study used a cross-sectional multilevel design to explain student engagement based on class and student variables. Specifically, the study collects data from 656 students and 61 randomly selected teachers at both levels and uses multilevel modeling to explain relationship patterns.

The results show that institutions vary significantly in student engagement scores. In addition, while a significant variation is found at the student and classroom level, the effects of academic achievement, instructional quality, teaching experience and teacher qualifications on student engagement vary across classrooms in institutions. However, the interaction effect of classroom and student-level variables on student engagement remains non-significant.

The main contribution of this lies in the explanation of student engagement using classroom and student level factors in a vertically differentiated higher education system using multilevel modeling. Student engagement varied in classrooms research universities applied and comprehensive universities.