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Considering the speedy growth of Islamic finance and limited research work on Muslim behavior regarding Islamic Banking, this study aims to investigate to comprehend the stimulus of religiosity on customer’s behavior.

A conceptual model is developed on existing literature. The key dimensions of religiosity in the model include practice, knowledge, experience and consequences to capture the whole religiosity of customers. Model of the study investigates the impact of customer’s religiosity on their behavior in decision-making about selection of Islamic bank. Analysis of the study is based on the sample of 370 customers of Islamic banks from District Nowshera Khyber Pakhtunkhwa, Pakistan. The data for the study collected through random sampling by a comprehensive survey questionnaire. Binary logistic model is used to test the data for statistical analysis.

The key findings of the study suggest that religiosity influence customer behavior positively in decision-making regarding Islamic finance. Service standards of Islamic banking has also significant impact on customer perception, while the financial education of the customers has insignificant impact on customer behavior.

This study mainly focused on the curiosity of the customer religious commitment, so religiosity is a vast phenomenon; there are deep sections in each dimension of religiosity, so further study is suggested for the comprehensive capture of each dimension of religiosity.

The results of the study have a great importance for the managers of Islamic finance industry to identify and detect the potential customers and divide the target market of banking industry on the base of religiosity. Furthermore, the study may bring significant managerial suggestions for marketing planners and can help them in market segmentation strategies.

The study examined the association between Muslim religiosity and Islamic banking customer’s selection behavior. This study spread the understanding of religiosity and its impact on Islamic banking customer’s behavior. Furthermore, the study is valuable to discover the level to which religiosity determines the inclinations of customers. This study helps marketing practitioners and researchers to grow their knowledge about customer’s motives in terms of religious commitment.

This chapter investigates whether, and if so, how particular firms in a transition economy are involved in bribery. Built on pressure theories, we explain how the direct effects of firm characteristics and contextual characteristics determine firm bribery behavior. Entrepreneurs make choices based on perceptions of a specific pressure due to organizational characteristics (internal pressures) or due to context (external pressures). The relationship between firm characteristics, context, and bribery was estimated using unique data from a survey of 606 Vietnamese entrepreneurs. We controlled for various entrepreneurial, organizational, and industrial characteristics. The exploratory findings support firm attributes hypotheses, which is a negative relationship between firm size and bribery and a nonmonotonic U-shaped relationship between firm age and bribery. Besides, the effects of context on bribery are also found. Specifically, the result supports a positive relationship between competition and bribery and a negative relationship between the quality of the government and bribery.

As online learning is the embryonic form of education in the metaverse, it is extremely important to explore the behavioral preferences of users. The aim is to explore the impact of interactive features on continuous use in online learning and to further explore what kind of interaction mode should be constructed for different types of students to obtain the best educational experience.

The study developed an empirical model and used a real-world dataset to test hypotheses. Specifically, the interaction in online learning is analyzed from different dimensions, including the interaction intensity of multiple subjects, the immersion of interactive technology, the timeliness of interactive feedback, and the fun in interaction.

The authors found that the intensity of interaction, immersion, timeliness of feedback and fun in the interaction all had significant positive effects on continuous use. Among them, the most important is the interaction between teachers and students. With the growth of user grades, the role of parents in the interaction is getting smaller and smaller, and the fun in the interaction is gradually becoming unnecessary. For high school students, gamified interactions can even have a negative impact. In addition, from the perspective of gender, males prefer immersive interaction, while females pay more attention to themselves and have negative feedback on fees.

The authors deepened the interaction and summarized the impact of different interactive features on continuous use in online learning platforms. The authors focused on the impact of the immersive experience brought by the application of interactive technology, which can confirm the user behavior preferences of online learning in the context of the metaverse. The research also provides a reference for online learning institutions to set up course interaction modes and targeted marketing programs.

While the existing studies largely suggest that valuation uncertainty benefits acquirers, who apply discounts to targets' value attributable to information asymmetry, the authors argue that the opposite may be the case.

Through multivariate econometric analysis of transaction data, the authors establish the link between the degree of valuation uncertainty measured by targets' track of public listing and acquisition premia. The authors use text-mining tools to measure acquirer–target similarity and control for its role in intermediating the posited empirical relationships.

Having analyzed 618 acquisitions involving listed targets from China, the authors find that acquirers pay higher valuation premia for the more recently listed and relatively younger companies than for those with a longer history since floatation. Similar patterns apply to valuation multiples. Higher valuations are partially attributable to premia for control, as acquirers are likelier to buy a majority stake in the recently listed firms, especially if the latter are similar to them. Such transactions take less time to complete and involve a transfer of larger share blocks despite the higher degree of information asymmetry and a frequent lack of targets' operational profitability. The authors also observe a significant premium for target–acquirer similarity: acquirers appear to rush deal completion due to possible overestimation of targets' potential and familiarity bias.

The authors show that acquisition premia may be driven by acquirers' proclivity to place risky investment bets on the growth potential of opaque targets. This pattern may partially explain frequent failures of mergers and acquisitions (M&A).

The e-commerce boom presents new challenges for last-mile delivery (LMD), which may be mitigated by new delivery technologies. This paper evaluates the impact of mobile parcel lockers (MPL) on costs and CO₂ equivalent (CO₂e) emissions in existing LMD networks, which include home delivery and shipments to stationary parcel lockers.

To describe customers’ preferences, we design a multinomial logit model based on recipients’ travel distance to pick-up locations and availability at home. Based on route cost estimation, we define the operating costs for MPLs. We devise a mathematical model with binary decision variables to optimize the location of MPLs.

Our study demonstrates that integrating MPLs leads to additional cost savings of 8.7% and extra CO₂e emissions savings of up to 5.4%. Our analysis of several regional clusters suggests that MPLs yield benefits in highly populous cities but may result in additional emissions in more rural areas where recipients drive longer distances to pick-ups.

This paper designs a suitable operating model for MPLs and demonstrates environmental and economic savings. Moreover, it adds recipients’ availability at home to receive parcels improving the accuracy of stochastic demand. In addition, MPLs are evaluated in the context of several regional clusters ranging from large cities to rural areas. Thus, we provide managerial guidance to logistics service providers how and where to deploy MPLs.

Users' voluntary forwarding behavior opens a new avenue for companies to promote their brands and products on social networking sites (SNS). However, research on voluntary information disseminators is limited. This paper aims to bring an in-depth understanding of voluntary disseminators by answering the following questions: (1) What is the underlying mechanism by which some users are more enthusiastic to voluntarily forward content of interest? (2) How to identify them? We propose a theoretical model based on the Elaboration-Likelihood Model (ELM) and examine three types of factors that moderate the effect of preference matching on individual forwarding behavior, including personal characteristics, tweet characteristics and sender–receiver relationships.

Via Twitter API, we randomly crawled 1967 Twitter users' data to validate the conceptual framework. Each user’s original tweets and retweeted tweets, profile data such as the number of followers and followees and verification status were obtained. The final corpus contains 163,554 data points composed of 1,634 valid twitterers' retweeting behavior. Tweets produced by these core users' followees were also crawled. These data points constitute an unbalanced panel data and we employ different models — fixed-effects, random-effects and pooled logit models — to test the moderation effects. The robustness test shows consistency among these different models.

Preference matching significantly affects users' forwarding behavior, implying that SNS users are more likely to share contents that align with their preferences. In addition, we find that popular users with lots of followers, heavy SNS users who author tweets or forward other-sourced tweets more frequently and users who tend to produce longer original contents are more enthusiastic to disseminate contents of interest. Furthermore, interaction strength has a positive moderating effect on the relationship between preference matching and individuals' forwarding decisions, suggesting that users are more likely to disseminate content of interest when it comes from strong ties. However, the moderating effect of perceived affinity is significantly negative, indicating that an online community of individuals with many common friends is not an ideal place to engage individuals in sharing information.

This work brings about a deep understanding of users' voluntary forwarding behavior of content of interest. To the best of our knowledge, the current study is the first to examine (1) the underlying mechanism by which some users are more likely to voluntarily forward content of interest; and (2) how to identify these potential voluntary disseminators. By extending the ELM, we examine the moderating effect of tweet characteristics, sender–receiver relationships as well as personal characteristics. Our research findings provide practical guidelines for enterprises and government institutions to choose voluntary endorsers when trying to engage individuals in information dissemination on SNS.

This paper aims to examine the effect of critical mass of women managers on corporate boards on the voluntary disclosure of climate change in a developing country in which the regulations on climate change disclosure is an area of growing research interest.

This study uses logistic panel regression models with a sample of 1,001 firm-years for companies in the Borsa Istanbul 100 Index that were asked to disclose voluntary climate change indicators over the seven-year period from 2014 to 2020 through the Carbon Disclosure Project.

This paper provides evidence from an emerging country that the critical mass of women on the board has no impact on voluntary climate change disclosure. In addition, the presence of independent managers on the board was found to have a significant impact on climate change disclosure. In addition, the results show that larger companies are more likely to report their climate change activities. Large companies are more visible due to their size, are perceived by stakeholders as more polluting and are, therefore, more likely to report on the environment.

The results show that the critical mass of women on the board has no effect on voluntary disclosure of climate change. Empirical tests are still needed to strengthen the overall validity of the critical mass of at least three women on boards in Türkiye.

Despite many valuable insights provided by critical mass theory, very few studies directly address critical mass and voluntary disclosure of climate change. To the best of the authors’ knowledge, this study is the first empirical and comprehensive paper in the Turkish context evaluating critical masses and voluntary corporate climate change giving a comparison between firms listed on financial industry and nonfinancial industry.

The purpose of this study is to investigate the role of sales, as a proxy for size, in moderating the impact of institutional incongruence between formal and informal institutions on the formalization of microenterprises in middle-income countries in Latin America.

The paper uses a probit regression model to examine business formalization as a binary outcome of formal and informal institutions. Data was collected through interviews and surveys across 52 municipalities in the Metropolitan Region of Santiago, Chile. The study used a stratified sampling approach and was conducted between November 2022 and January 2023.

The results offer three key insights into the formalization of microenterprises in middle-income countries. First, we show that formal institutions do not significantly influence formalization decisions among microentrepreneurs in middle-income countries, challenging the traditional belief that formal institutions alone significantly influence formalization in these contexts. Second, we show that informal institutions are significant predictors of informality, especially among smaller microenterprises. Third, we highlight that the smaller the business, the stronger the negative effect of informal institutions on formalization, and thus, the institutional incongruence between formal and informal institutions decreases for larger businesses.

This paper contributes to management literature by shedding light on the drivers of formalization in middle-income countries, a departure from most formalization studies wherein the focus is primarily on low-income economies. The findings suggest that policymakers in middle-income countries should focus on enabling microenterprise growth through sales, rather than targeting specific demographic groups or relying solely on formal institutional enforcement to promote formalization.

El objetivo de este estudio es investigar el papel de las ventas, utilizadas como un indicador de tamaño, en la mediación del impacto de la incongruencia institucional entre instituciones formales e informales en la formalización de microempresas en países de ingresos medios en América Latina.

Utilizamos un modelo de regresión Probit para examinar la formalización empresarial como un resultado binario de instituciones formales e informales. Los datos se recopilaron a través de 110 entrevistas y encuestas en 52 municipios de la Región Metropolitana de Santiago, Chile. El estudio empleó un enfoque de muestreo estratificado y se llevó a cabo entre noviembre de 2022 y enero de 2023.

Nuestros resultados ofrecen tres ideas clave sobre la formalización de microempresas en países de ingresos medios. Primero, demostramos que las instituciones formales no influyen significativamente en las decisiones de formalización entre las microempresas en países de ingresos medios; esto desafía la creencia tradicional de que las instituciones formales por sí solas influyen significativamente en la formalización en estos contextos. Segundo, nuestro estudio muestra que las instituciones informales son predictores significativos de la informalidad, especialmente entre las microempresas más pequeñas. Tercero, nuestro estudio destaca que el efecto negativo de las instituciones informales sobre la formalización es más fuerte para negocios de menor tamaño; por lo tanto, la incongruencia institucional entre instituciones formales e informales disminuye para negocios de mayor tamaño.

Este artículo contribuye a la literatura iluminando sobre los impulsores de la formalización en países de ingresos medios, a diferencia de la mayoría de los estudios de formalización en la región latinoamericana que se centran principalmente en países de bajos ingresos. Nuestros hallazgos sugieren que los responsables de políticas en países de ingresos medios deberían centrarse en impulsar el crecimiento de las microempresas a través de las ventas, en lugar de enfocarse en grupos demográficos específicos o depender únicamente del cumplimiento institucional formal para promover la formalización.

O objetivo deste estudo é investigar o papel das vendas, usadas como um indicador de tamanho, na mediação do impacto da incongruência institucional entre instituições formais e informais na formalização de microempresas em países de renda média na América Latina.

Utilizamos um modelo de regressão Probit para examinar a formalização empresarial como um resultado binário de instituições formais e informais. Os dados foram coletados por meio de 110 entrevistas e pesquisas em 52 municípios da Região Metropolitana de Santiago, Chile. O estudo empregou uma abordagem de amostragem estratificada e foi realizado entre novembro de 2022 e janeiro de 2023.

Nossos resultados oferecem três ideias-chave sobre a formalização de microempresas em países de renda média. Primeiro, demonstramos que as instituições formais não influenciam significativamente as decisões de formalização entre as microempresas em países de renda média; isso desafia a crença tradicional de que as instituições formais, por si só, influenciam significativamente a formalização nesses contextos. Segundo, nosso estudo mostra que as instituições informais são preditores significativos da informalidade, especialmente entre as microempresas menores. Terceiro, nosso estudo destaca que o efeito negativo das instituições informais sobre a formalização é mais forte para negócios de menor porte; portanto, a incongruência institucional entre instituições formais e informais diminui para negócios de maior porte.

Este artigo contribui para a literatura iluminando os impulsionadores da formalização em países de renda média, ao contrário da maioria dos estudos de formalização na região latino-americana, que se concentram principalmente em países de baixa renda. Nossos achados sugerem que os responsáveis pelas políticas em países de renda média deveriam focar em impulsionar o crescimento das microempresas por meio das vendas, em vez de se concentrar em grupos demográficos específicos ou depender exclusivamente do cumprimento institucional formal para promover a formalização.

This article aims to evaluate the entry and exit of companies from local productive structures, with a specific focus on the sectoral complexity of these activities and the complexity of these portfolios. The study focuses on empirically demonstrating the thesis that related economic diversification exacerbates the development gap between more and less complex regions.

The article uses indicators formulated by the economic complexity approach. They allow a relevant descriptive analysis of the economic diversification process in Brazilian micro-regions and provide the foundation for the econometric tests conducted. Through three distinct estimation strategies (OLS, logit, probit), the influence of complexity and relatedness on the entry and exit events of firms from local portfolios is tested.

In all estimated models, the stronger relationship between an activity and a portfolio significantly increases its probability of entering the productive structure and, at the same time, acts as a significant factor in preventing its exit. Furthermore, the results reveal that the complexity of a sector reduces the probability of its specialization in less complex regions while increasing it in more complex regions. On the other hand, sectoral complexity significantly increases the probability of a sector leaving less complex local structures but has no significant effect in highly complex regions.

Due to the data used, the indicators are calculated considering only formal job numbers. Additionally, the tests do not detect the influence of spatial issues. These limitations should be addressed by future research.

The article characterizes a prevailing process of uneven development among Brazilian regions and brings relevant implications, primarily for policymakers. Specifically, for less complex regions, policies should focus on creating opportunities to improve their diversification capabilities in complex sectors that are not too distant from their portfolios.

The article makes an original contribution by proposing an evaluation of regional diversification in Brazil with a focus on complexity, introducing a more detailed differentiation of regions based on their complexity levels and examining the impact of sectoral complexity on diversification patterns within each group.

A stroke is a serious, life-threatening condition that occurs when the blood supply to a part of the brain is cut off. The earlier a stroke is treated, the less damage is likely to occur. One of the methods that can lead to faster treatment is timely and accurate prediction and diagnosis. This paper aims to compare the binary integer programming-data envelopment analysis (BIP-DEA) model and the logistic regression (LR) model for diagnosing and predicting the occurrence of stroke in Iran.

In this study, two algorithms of the BIP-DEA and LR methods were introduced and key risk factors leading to stroke were extracted.

The study population consisted of 2,100 samples (patients) divided into six subsamples of different sizes. The classification table of each algorithm showed that the BIP-DEA model had more reliable results than the LR for the small data size. After running each algorithm, the BIP-DEA and LR algorithms identified eight and five factors as more effective risk factors and causes of stroke, respectively. Finally, predictive models using the important risk factors were proposed.

The main objective of this study is to provide the integrated BIP-DEA algorithm as a fast, easy and suitable tool for evaluation and prediction. In fact, the BIP-DEA algorithm can be used as an alternative tool to the LR model when the sample size is small. These algorithms can be used in various fields, including the health-care industry, to predict and prevent various diseases before the patient’s condition becomes more dangerous.