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This paper aims to empirically investigate the asymmetrical relationship between changes in oil price and the banking stability of the conventional and Islamic banks in the Middle East and North African (MENA) countries.

This paper measures banking stability with Z-score and probability of default using the Generalized Method of Moment. This paper selects a sample of conventional and Islamic banks operating within the MENA oil-producing states between 2008 and 2016.

The result of this paper reveals that the banking stability of the two types of banks responds to positive and negative shocks in oil prices. Thus, the stability of conventional banks is slightly better than that of Islamic banks in the region. Consequently, this paper also reveals that bank capitalization improves with the banking stability of the two banking systems in the region.

The findings of this paper will help the banks in the MENA oil-producing countries with strategies for improving banking stability during the oil price fluctuations and provide the policymakers with possible time for bank capital reform.

This paper explores the impact of the international oil price shocks on Islamic and conventional banks in one of the essential global oil-producing regions. As such, this paper extends the banking stability literature by accounting for the role of oil shock prices on banking distance and the probability of default. To the best of the authors’ knowledge, this is the first investigation of different transmission channels of oil price fluctuations in the region while considering the dual banking system in the hub of Islamic banks.

This study investigates the repetitive mixed sampling (MRS) plan based on the Cpk index that was proposed by Aslam et al. (2013a). They were the first to study the MRS plan, but they did not pay attention to the fact that submitting to the variable inspection a sample that was first submitted to the attribute inspection, truncates the X observations. In addition, they did not work with an accurate expression to calculate the probabilities of the Cpk statistic.

The authors presented the results based on their original sampling plan through Monte Carlo simulation and defined the theoretical results of their plan when the sample submitted to the variable inspection is no longer the same one submitted to the attribute inspection.

The β risks of the optimum sampling plans presented by Aslam et al. (2013a) are pretty high, exceeding 46%, on average – this same problem was also observed in Saminathan and Mahalingam (2018), Balamurali (2020) and Balamurali et al. (2020), where the β risks of their proposed sampling plans are yet higher.

In terms of originality, the authors can declare the following. It is not a big deal to propose new sampling plans, if one does not know how to obtain their properties. The miscalculations of the sampling plans risks are dangerous; imagine the situation where the acceptance of bad lots exceeds 50% just because the sampling plan was incorrectly designed. Yes, it is a big deal to warn that this type of problem is arising in a growing number of papers. The authors of this study are the pioneers to discover that many studies focusing on the sampling plans need to be urgently revised.

Ensuring the safety of structures is important. However, when a structure possesses both an implicit performance function and an extremely small failure probability, traditional methods struggle to conduct a reliability analysis. Therefore, this paper proposes a reliability analysis method aimed at enhancing the efficiency of rare event analysis, using the widely recognized Relevant Vector Machine (RVM).

Drawing from the principles of importance sampling (IS), this paper employs Harris Hawks Optimization (HHO) to ascertain the optimal design point. This approach not only guarantees precision but also facilitates the RVM in approximating the limit state surface. When the U learning function, designed for Kriging, is applied to RVM, it results in sample clustering in the design of experiment (DoE). Therefore, this paper proposes a FU learning function, which is more suitable for RVM.

Three numerical examples and two engineering problem demonstrate the effectiveness of the proposed method.

By employing the HHO algorithm, this paper innovatively applies RVM in IS reliability analysis, proposing a novel method termed RVM-HIS. The RVM-HIS demonstrates exceptional computational efficiency, making it eminently suitable for rare events reliability analysis with implicit performance function. Moreover, the computational efficiency of RVM-HIS has been significantly enhanced through the improvement of the U learning function.

The restaurants in Peru enjoy today a high level of international recognition, and the gastronomy of the country is recognised as one of the best in the world. For this reason, aspiring to excellence should be one of the priorities in the industry, which should mean, among other things, enhancing those aspects related to food with the greatest impact on the maximum level of customer satisfaction. However, to the authors knowledge, this research line has not been addressed before in the context of Peruvian restaurant, so that this research focuses on assessing the influence of food – through the concept of food values –, on the probability of reaching the maximum level of satisfaction both with the food consumption experience and with the foods consumed in restaurants in Peru. This research also takes into account differences according to the geographical origin of the customers.

An in-person survey of customers was conducted at the exit of different flagship restaurants with a high level of recognition and tourist orientation in the department of Ayacucho (Peru) between September and November 2022. Five restaurants acknowledged as tourist restaurants were selected for this study, of which, one has been officially granted the status of Tourist Restaurant and One Fork, in accordance with the Peruvian legal regulations. A total of 468 valid questionnaires were collected. The database was analysed using descriptive statistics, principal component factor analysis for food values, and binary logistic regressions.

The following food values factors emerged from the factorial analysis: “Image and Accessibility (IAA)”, “Ethics and Sustainability (EAS)” and “Natural Food-Safe (NFS)”. For the overall sample, IAA is more influential in the probability of obtaining the maximum level of both satisfactions (i.e. satisfaction with the food consumption experience and with the foods consumed in restaurants in Peru). In second place, EAS, as well as NFS (the latter one with a significance level of 90%), also affect, in this order, the probability of obtaining the highest level of satisfaction, but only with the foods consumed. When the geographical origin of the customer is considered (regional, national, international), interesting findings appear. For national customers, IAA is the factor with the greatest impact on the probability of achieving the maximum level of the endogenous satisfaction variables considered, followed by EAS, whilst for regional customers, only EAS is found to be influential in the probability of obtaining the maximum level of both types of satisfaction. For international customers, no factor is found to exert a significant influence.

This is the first study to assess the influence of food values on the maximum level of satisfaction among restaurant customers in Peru with both the food consumption experience and the foods consumed. Thus, this research represents a notable contribution to this research line, especially considering the great international reputation of Peruvian cuisine.

This study aims to examine the resilience of Peruvian startups during the COVID-19 pandemic using a framework proposed by Lengnick-Hall et al. (2011), in which resilience impacts organizational strengthening. The goal is to identify those characteristics that allowed certain startups to discover growth opportunities amid this crisis.

This study analyzed human, social and entrepreneurial capital variables in Peruvian startups using data from a survey conducted in July 2020. Binary logistic regression was used to determine which organizational resources increased the probability of identifying growth opportunities during the pandemic.

The findings suggest that human capabilities become secondary in extreme crises such as pandemics. Critical factors for startup resilience include commercial partnerships with established firms, founders’ capital investment, business maturity and adoption of advanced digital technologies.

This research provides unique insights into startup resilience and growth in Peru during the COVID-19 crisis. The authors observed that business growth during this period was largely unpredictable, with less emphasis on human capabilities. The study highlights the importance of external factors in resilience, the role of collaboration between established firms, the integration of advanced digital technologies and the influence of founders’ investments and business maturity in navigating difficult times.

Este estudio examina la resiliencia de las startups peruanas durante la pandemia de COVID-19 utilizando un marco propuesto por Lengnick-Hall et al. (2011), en el que la resiliencia tiene un efecto en el fortalecimiento de las organizaciones. Su objetivo es identificar las características que permitieron a ciertas startups descubrir oportunidades de crecimiento en medio de esta crisis.

Analizamos variables de capital humano, social y empresarial en startups peruanas utilizando datos de una encuesta realizada en julio de 2020. Se utilizó regresión logística binaria para determinar qué recursos organizativos incrementaban la probabilidad de identificar oportunidades de crecimiento durante la pandemia.

Nuestros hallazgos sugieren que las capacidades humanas pasan a un segundo plano en crisis extremas como las pandemias. Los factores críticos para la resiliencia de las startups incluyen las asociaciones comerciales con empresas establecidas, la inversión de capital de los fundadores, la madurez empresarial y la adopción de tecnologías digitales avanzadas.

Esta investigación proporciona una visión única sobre la resiliencia y el crecimiento de las startups en Perú durante la crisis COVID-19. Observamos que el crecimiento empresarial durante este período fue en gran medida impredecible, con menos énfasis en las capacidades humanas. El estudio subraya la importancia de los factores externos en la resiliencia, el papel de la colaboración con las empresas establecidas, la integración de tecnologías digitales avanzadas, la influencia de las inversiones de los fundadores y la madurez empresarial para navegar en tiempos difíciles.

Este estudo examina a resiliência das startups peruanas durante a pandemia da COVID-19 usando uma abordagem proposta por Lengnick-Hall et al. (2011), na qual a resiliência tem um efeito fortalecedor nas organizações. Seu objetivo é identificar as características que permitiram que determinadas startups descobrissem oportunidades de crescimento em meio a essa crise.

Analisamos variáveis de capital humano, social e empresarial em start-ups peruanas usando dados de uma pesquisa realizada em julho de 2020. A regressão logística binária foi usada para determinar quais recursos organizacionais aumentaram a probabilidade de identificar oportunidades de crescimento durante a pandemia.

Nossas análises sugerem que as capacidades humanas se tornam secundárias em crises extremas, como as pandemias. Os fatores essenciais para a resiliência das startups incluem parcerias comerciais com empresas estabelecidas, investimento de capital dos fundadores, maturidade dos negócios e adoção de tecnologias digitais avançadas.

Esta pesquisa fornece informações exclusivas sobre a resiliência e o crescimento de startups no Peru durante a crise da COVID-19. Observamos que o crescimento das empresas durante esse período foi amplamente imprevisível, com menos ênfase nas capacidades humanas. O estudo destaca a importância de fatores externos na resiliência, o papel da colaboração com empresas estabelecidas, a integração de tecnologias digitais avançadas e a influência dos investimentos dos fundadores e da maturidade dos negócios na superação de tempos difíceis.

Digital technology has been widely applied in zakat collection. Millennials, who are now dominating the productive phase and at their peak carrier path, are the potential target for zakat collection as their number reached 31.3% of the Indonesian population. On the other hand, public and private zakat institutions have attempted to optimize the country’s zakat potential, reaching 233.6tn rupiahs, through development of a digital platform for zakat collection. However, the gap between the actual collection of zakat with its potential is still large. This study aims to analyse the factors affecting millennials in paying zakat through direct payment or through digital platform of private or public zakat institutions.

Multinomial logistic regression method, which signifies the contribution of this study, is used to analyse factors influencing millennials in their zakat payment. In addition, cross-tabulation is used to classify the characteristics of respondents. Respondents are selected conveniently through a digital questionnaire distributed in February–March 2021. Respondents are also selected purposively based on their experience in paying zakat through direct, private or public zakat institutions, which are consisted of 50 respondents per each category; thus, the total becomes 150 respondents.

Based on the results, three variables, namely, education, accessibility and age, are found to have a significant influence on zakat payment through online platforms provided by private zakat institutions. Meanwhile, variables that influence zakat payment through online platforms provided by public zakat institutions are education, accessibility and income. This study also finds that millennials have the highest probability to select online platforms provided by private zakat institutions as a channel of their zakat payment. However, the overall result shows that millennials tend to pay directly to the mustahik (zakat recipients) rather than via online platforms, presumably because of their limited zakat literacy.

The purposive sampling technique used to determine the research samples limits the generalization of the study.

This paper establishes a new approach in analysing millennials preference in their zakat payment with digital inclusiveness. The use of a multinomial logistic approach, which has not been widely applied in such research, strengthens the analysis that is relevant to the need of both private and public zakat institutions to analyse determinants of millennials in paying their zakat through online platform. This study can be used as a reference to formulate a more effective marketing strategy for zakat collection. This paper also serves as an estimate of the preference with some selected typical characteristics of millennials by using a multinomial logistic approach.

Formal payment through the zakat institution theoretically is more preferable than direct payment to mustahik (zakat recipients) in the zakat campaign. However, based on this research, despite digital marketing and platforms having been well-used by both private and public zakat institutions, the millennials still prefer direct zakat payment than through online platforms. The findings of this research suggest the importance of strengthening zakat literacy through a more effective digital marketing strategy of zakat institutions which target the millennials.

This study fills the gap in the literature on how millennials choose their zakat payment method, whether through digital platforms developed by private and public zakat institutions or directly to the targeted zakat recipients. The use of multinomial logistic regression approach adds the novelty of this research.

This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.

Some researchers regard discretionary accrual (DA) as one of the factors that drive corporate managers to conduct tax planning (Scott, 2009; Basri and Buchari, 2017). Based on agency theory and positive accounting theory, corporate managers can transform accounting information and manipulate firm earnings to reduce tax liability. There is a lot of research concerning earnings management and tax planning in the developed economy. These studies include Wang and Chen (2012) and Pettersson and Wu (2015). In the emerging economies, it includes Jamei and Khedri (2016), Kurniasih and Sulardi Suranta (2017), Prastiwi (2017), Almashaqbeh et al. (2018), Bayunanda et al. (2018), Rani et al. (2018) and Kałdoński and Jewartowski (2019). It is important to note that none of the research mentioned above has evaluated the impact of real earnings management (REM) on tax planning in Nigeria. While in the developed economy only Kałdoński and Jewartowski (2019) used REM as an explanatory variable, while the majority of studies used DA. Consequently, no study has used REM to moderate the relationship between financial attributes and tax planning. Despite the widespread notion, as well as positive accounting theory, tax planning theory that financial attributes (profitability, leverage, liquidity and firm growth), REM and DA motivate tax planning, previous investigations have produced mixed results (Dwenger and Steiner, 2009; Wang and Chen, 2012; Chen and Zolotoy, 2014; Aghouei and Moradi, 2015; Pettersson and Wu, 2015; Ribeiro, 2015; Chen et al., 2016; Jamei and Khedri, 2016; Ogbeide, 2017; Yuniawati et al., 2017; Chen and Lin, 2017; Firmansyah and Febriyanto, 2018; Prastiwi, 2018; Rani et al., 2018; Kibiya and Aminu, 2019; Kałdoński and Jewartowski, 2019 and Siyanbonla, 2021). This study aims to use REM as a moderator to examine the relationship between financial attributes and tax planning whether it will strengthen or weaken the relationship.

The study examines the impact of financial attributes on the corporate tax planning of listed manufacturing firms in Nigeria. It also tests for the moderating effect of REM on the relationship between financial attributes and tax planning. Data for the study was sourced from the annual reports of sampled manufacturing firms. The study used the panel data methodology for analysis. The study used fixed effect estimation to interpret the parsimonious model and random effect was used to interpret the moderated model. The study documented that financial leverage has a positive significant influence on the tax planning of the sampled manufacturing firms. While firm growth has a negative significant impact on the tax planning of listed manufacturing firms in Nigeria. REM has a positive significant impact on tax planning. Also, REM moderate significantly the relationship between financial attributes on one hand and tax planning on the other. The study recommends that firms should go for more debt to take advantage of the tax shield of interest on the debt. Also, firm management should use non-current debt to finance non-current assets and use current debt to finance current assets to avoid the risk of taking over or liquidation. The study also recommends that firm management should engage in intercompany and intracompany transactions by selling their goods to affiliates in countries with low prices and low tax rates. A firm should also overproduce goods to have high production costs and high closing inventory since real earning management significantly reduces tax liabilities by deferring income into a later year.

The study documented that financial leverage has a positive and significant influence on the tax planning of the sampled manufacturing firms. While firm growth has a negative but significant impact on the tax planning of listed manufacturing firms in Nigeria. REM has a positive and significant impact on tax planning. Also, REM moderate significantly the relationship between financial attributes on one hand and tax planning on the other.

There is a lot of research concerning earnings management and tax planning in the developed economy. These studies include Wang and Chen (2012) and Pettersson and Wu (2015). In the emerging economies, it includes Jamei and Khedri (2016), Kurniasih and Sulardi Suranta (2017), Prastiwi (2017), Almashaqbeh et al. (2018), Bayunanda et al. (2018), Rani et al. (2018) and Kałdoński and Jewartowski (2019). It is important to note that none of the research mentioned above has evaluated the impact of REM on tax planning in Nigeria. While in the developed economy only Kałdoński and Jewartowski (2019) used REM as an explanatory variable, while the majority of studies used DA. Consequently, no study has used REM to moderate the relationship between financial attributes and tax planning.

This study aims to focus on exploring the construction productivity of building projects under the influence of potential factors. The three primary purposes are (1) determining critical factors affecting construction productivity; (2) identifying causal relationship and occurrence probability of these factors to develop a Bayesian network (BN) model; and (3) validating the accuracy of predictions from the proposed BN model via a case study.

A conceptual framework that includes three performance stages was used. Twenty-two possible factors were screened from a comprehensive literature review and evaluated through expert opinions. Data were collected using a structured questionnaire-based survey and case-study-based survey. The sampling methods were based on non-probability sampling.

Worker characteristic-related factors significantly affect labour productivity for a construction task. Construction productivity is dominated by the working frequency of workers (overtime), complexity of the task, level of technology application and accidents. Labour productivity is defined as nearly 50% of the baseline productivity using the BN model created by the caut 2sal relationship and probability of factors. The prediction error of the BN model was 6.6%, 10.0% and 9.3% for formwork (m²/h), reinforcing steel (ton/h) and concrete (m³/h), respectively.

The evaluation or prediction of productivity performance has become a necessary topic for research and practice.

Managers and practitioners in the construction sector can utilise the outcome of this study to create good productivity management policies for their prospective projects.

Worker-related characteristics are dominant among critical factors affecting labour productivity for a construction task; the proposed BN-based predictive model is built based on these critical factors. The BN approach is highly accurate for construction productivity prediction. The findings of this study can fill gaps in the construction management body of knowledge when modelling construction productivity under the effects of multiple factors and using a simple probabilistic graphic tool.

The purpose of this paper is to examine the adoption of Islamic finance products (murabaha, musharakah, mudarabah, salam, ijara, istisna and Qard Hassan) by small and medium-sized enterprises (SMEs) in Cameroon, a non-Islamic Sub-Saharan African country.

It used primary data collected from a cross-section of 1,358 SMEs in eight regions of Cameroon using self-administered structured questionnaires. To facilitate the analyses and interpretation, these products are grouped into four groups based on certain characteristics. A multivariate probit model is estimated to take into account the interaction between these different Islamic finance products.

This study revealed that the desire to comply with Sharia law, awareness, attitude and intention were critical determinants of the decision to adopt Islamic finance products by Cameroonian SMEs. The least influential factors were perceived behavioral control, subjective norms, enterprise characteristics (size, age and location) and socio-demographic characteristics of the entrepreneur (gender, age and marital status). The extension of the multivariate approach permitted us to compute for predicted probabilities which revealed that there exists a synergy effect between the different Islamic finance products. That is, Cameroonian SMEs combine different Islamic finance products at the same time based on their needs. This is especially the case between the partnership-based products (musharakah and mudarabah) and manufacture/rent products (istisna and ijara).

Policymakers are encouraged to develop stakeholder-oriented strategies to promote effective consumer education in Islamic finance products which will boost awareness. Also, Islamic finance institutions should endeavor to develop innovative financial products that are Sharia-compliant and economically beneficial to the individual and business needs of SMEs. Moreover, policymakers and management of Islamic finance institutions should ensure the putting in place of effective governance structures to guide Islamic finance operations. Finally, policymakers should endeavor to take into account the possible synergy between the different Islamic finance products in their quest to develop this activity.

To the best of the authors’ knowledge, this is the first study that analyses the adoption of different Islamic finance products while taking into account the possible synergy that exists between these products.