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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.

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.

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.

Agriculture in Ethiopia relies heavily on traditional farm power sources and is designated by the lowest farm machinery access, in contrast to other Sub-Sahara African (SSA) countries. The purpose of this research is to analyze the heterogeneity of mechanization service transactions and factors determining farmers' cooperation in mechanization clusters and willingness to accept land consolidation.

The authors conducted a cross-sectional survey of producer households in major crop production areas in the Oromia, SNNPR, Amhara and Tigray regions. The sampling design involved three stages: districts were selected using a stratified sampling approach accompanied by simple random samples of kebele units and producer households in the second and final stages, respectively.

This study’s results show that mechanization service costs, service relationships, clustering and land consolidation exhibit significant heterogeneity across the study areas. Cluster farming was found to be advantageous against diseconomies, rationalized by upgrading the mechanization scale. The probit model parameterization of the probability distributions reveals that household, land, crop, mechanization service, remoteness and location-related factors determine participation in mechanization clusters and willingness to accept land consolidation.

Fostering cooperation by focusing on constraints and demand of users is suggested to reduce transaction costs and expand hired mechanization services to unaddressed areas. The findings are relevant to most SSA countries where mechanization development is hampered by land fragmentation.

Limited information is available on agricultural mechanization development for smallholder farmers, particularly in Ethiopia, and this study adds empirical evidence about the synergy between cluster farming and mechanization, horizontal coordination and alternative supply models.

Through the development of an empirical model and using community sport organizations (CSOs) as the basis for intervening variables, this study aims to ascertain the impact of Muslim household consumption, sport development officers (SDOs) and CSOs on Islamic sport development (ISD) during the COVID-19 pandemic.

All of the sports branch managers in Banten Province make up the study’s sample. Non-probability sampling with a purposive sampling strategy was the sampling method used. Making use of a questionnaire to gather data, 275 different sets of data are available for analysis.

Partial least squares is a tool for technical data analysis. With a t-statistic value of 71.358, the Moslem household consumption construct had a favorable and significant impact on the SDO construct. With a t-statistic value of 1.111, the Moslem household consumption construct had a positive but not statistically significant impact on ISD.

With a t-statistic value of 3.926, the Moslem household consumption construct had a positive and statistically significant impact on CSOs. With a t-statistic value of 1.111, the SDO construct had a positive and statistically significant impact on ISD. This study makes a new contribution by providing practical recommendations for the relationship between ISD authorities, community sports organizations and the positive and substantial impact on the development of the community and ISD.

The purpose of this paper is to develop optimal estimation procedures for the stress-strength reliability (SSR) parameter R = P(X > Y) of an inverse Pareto distribution (IPD).

We estimate the SSR parameter R = P(X > Y) of the IPD under the minimum risk and bounded risk point estimation problems, where X and Y are strength and stress variables, respectively. The total loss function considered is a combination of estimation error (squared error) and cost, utilizing which we minimize the associated risk in order to estimate the reliability parameter. As no fixed-sample technique can be used to solve the proposed point estimation problems, we propose some “cost and time efficient” adaptive sampling techniques (two-stage and purely sequential sampling methods) to tackle them.

We state important results based on the proposed sampling methodologies. These include estimations of the expected sample size, standard deviation (SD) and mean square error (MSE) of the terminal estimator of reliability parameters. The theoretical values of reliability parameters and the associated sample size and risk functions are well supported by exhaustive simulation analyses. The applicability of our suggested methodology is further corroborated by a real dataset based on insurance claims.

This study will be useful for scenarios where various logistical concerns are involved in the reliability analysis. The methodologies proposed in this study can reduce the number of sampling operations substantially and save time and cost to a great extent.

The demand for power has surged in recent times and continues to increase yearly. In comparison to developed countries, the power industry’s risks, especially in piblic–private partnership (PPP) projects, are more complex and essential in developing countries. Appreciating the inter relationship among these risk factors is crucial. However, there exist no studies developing quantitative models to explain how various PPP power risk factors influence each other, especially in developing countries like Ghana. This study aims to investigate and model the relationship, the probability of occurrence and severity of impact of PPP power risk factors in Ghana.

Data were collected through ranking type questionnaire in a two-round Delphi survey with 48 respondents using purposive and snowball sampling techniques. partial least squares structural equation modelling (PLS-SEM) was used for analysis of data.

A model was developed to investigate the influence the risk factors inherent in PPP power projects have on each other. Validity of the model was tested based on the data collected. PLS-SEM results indicated the various relationships and interdependencies the risk factors had on each other considering their probability and severity. Both significant and insignificant levels of relationships were found among the various risk factors.

The SEM that was developed to assess the relationships among the risk factors has great value for policy makers in the energy sector, industry practitioners, researchers and industry practitioners. Strategies can be mapped out to mitigate and effectively allocate the risks with the high interdependencies.

Regarding the quantitative impact of the interrelationship among risk factors in PPP power projects, the findings of this research are arguably the first to be presented for the construction sector and contribute to knowledge on PPP practice and further has implications toward achieving power sector risk mitigation.

The main objective of this research is to exploratorily analyse different factors that influence the decision of the senior population (+50 years) to engage in entrepreneurship activities in a group of Latin American countries. This study considers the motivations for entrepreneurship (opportunity and necessity) and the level of development of the countries.

The authors used data from the Global Entrepreneurship Monitor (GEM) with a sample of 22,139 observations of senior individuals in seven Latin American countries surveyed between 2013 and 2017. The authors also used the Human Development Index to capture the relevance of the level of development. The authors employed a multilevel logistic regression model to test the study hypotheses.

The study results show that individual factors such as personal income, education and occupation have a significant influence on the probability of entrepreneurship of senior individuals. Related to contextual factors, the level of human development of a country has a negative influence mainly on opportunity-based entrepreneurs.

Because of the rapidly ageing population in Latin America, understanding senior entrepreneurs and their motivations is very relevant not only in terms of theoretical development but also for policy and practical implications, primarily those related to labour markets and social protection.

Given the scarcity of research exploring the influence of emotional dimensions on knowledge hiding (KH), this paper aims to examine how various facets of emotional intelligence (EI) affect teachers’ tendencies to hide knowledge. Additionally, the study delves into the mediating influence of organizational cynicism (OC) and explores the moderating role of servant leadership (SL) in this context.

The non-probability sampling method was used to gather data from 542 university teachers teaching in India. Structural equation modelling using Smart-PLS has been used to test the hypothesis.

The study revealed that EI negatively influences KH. Additionally, OC mediates the relationship between EI and KH. Furthermore, SL moderates the relationship between OC and KH.

As per the authors’ knowledge, the present study makes an additional contribution by investigating the mediating role of OC in the relationship between EI and KH. Moreover, it also investigates the moderating role of SL in the relationship between OC and KH.