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Purpose -- What motivates Sao Paulo citizens to use bicycles as a mode of transportation? To answer this question, we conceptually rely on the Goal-Framing Theory (Lindenberg, 2000), which seeks to understand how individual choices are made, and exogeneous variables such as climate and temperature which might influence in this decision. Design/methodology/approach -- Empirically, we conduct a quantitative study, relying on primary data from 252 respondents and analyzed by means of logistic regression models, through which we obtained the likelihood of using bikes and the relative weights of each of the variables defined in our theoretical section. Findings -- What motivates Sao Paulo residents are not economic reasons, but rather normative (doing what is right) or hedonic (the pursuit of personal satisfaction) aspects. In other words, we demonstrate that cyclists make this choice to comply with a norm, seeking for benefits to the environment and directly or indirectly to society, as opposed to benefitting individually from this decision. Practical implications -- The research has implication for public policies. Originality/value -- The study is one of the first to empirically test the Goal Framing Theory (Lindenberg, 2000) and, as far as we could tell, the first to assess the motivations for the use of bicycles as a means of transportation in Brazil and in Latin America. [ABSTRACT FROM AUTHOR]

The Contingent Valuation Method [CVM] emerges from environmental economics to assess the willingness to pay to improve or create a good or service for which there is no established market value. The objective of this research study is to assess through CVM a non-existent project, nonetheless necessary for water service sustainability in the municipalities belonging to the Department of Sucre in Colombia by replacing the supply of an aquifer source [Morroa Aquifer] with a surface water source. The used methodology, of an inferential nature, consisted of estimating a Logit binary choice model with cross-sectional information from an intentional survey using the referendum format applied to 117 people living in the seven municipalities involved. Results allow to establish the probabilities of the willingness to pay in various scenarios, as well as the estimated average value of the contribution of the inhabitants of the Sucre Department for this project. Conclusions point to the importance that the interviewees give to the proposed project, with high probabilities in the willingness to pay for which the territorial governments should formulate it and study its feasibility to implement it. [ABSTRACT FROM AUTHOR]

In this study, we evaluated the main risk factors for the occurrence of bovine mastitis, in the southeastern of Pará, in the Brazilian Amazon. We surveyed 91 dairy farmers to identify management practices and bovine breed characteristics. From each farm, 50 mL of milk sample was collected for microbiological analysis and somatic cell count (SCC). Depending on the management practices and breed, a logit model was used to determine the odds ratio of subclinical mastitis (SCM) occurrence. In irrigated pastures, an SCM-associated risk factor, the occurrence of SCM was 5.03 times higher than that in the non-irrigated pastures. Similarly, in Girolando breed herds, the occurrence of SCM increased by 5.8 times compared to the crossbred herds. Moreover, the occurrence of mastitis was 33 times higher in farms using common cloths for drying teats than in farms using paper towels. Therefore, adoption of better management practices can lead to SCC reduction, milk quality improvement and a guarantee to contain SCC within prescribed Brazilian limits for the Amazon region. [ABSTRACT FROM AUTHOR]

Copyright of Jurnal Manajemen dan Organisasi is the property of IPB University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Jurnal Manajemen dan Organisasi is the property of IPB University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hacettepe University Journal of Economics & Administrative Sciences / Hacettepe Üniversitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi is the property of Hacettepe University, Faculty of Economic & Administrative Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Financial management literacy is a significant knowledge to assist individuals' financial condition. There are various factors influencing monetary management, including Information technology (IT). Thus, this study aims to investigate the role of IT affecting individual awareness of financial literacy in Indonesia with household characteristics as the controlling variable; the data are generated from the Indonesian Family Life Survey conducted in 2014. Probit and logit models signify that ITs and household characteristics positively and significantly affect financial literacy. In detail, handphones, televisions and newspapers, marital status, education level, and household income levels have a positive and significant influence on households' accessing financial knowledge. Furthermore, multinomial logit estimation used to compare three different levels of financial literacy (low, medium, and high), indicates that six out of nine variables significantly affect financial literacy at low level to high levels, whereas only four out of nine influence financial literacy from medium to a high level.

Research background: Adoption of improved rice varieties remain paramount in fighting food and nutrition insecurity across sub-Sahara Africa (SSA). A lot has been done in the space of the adoption of agricultural innovations and food and nutrition insecurity. However, studies on the drivers of improved rice variety adoption and its effect on rice output, considering time and location-specific factors, are limited. Purpose of the article: This study estimated and examined the drivers and effect of improved rice variety adoption on rice output in the northern region of Ghana. Methods: A multistage sampling technique was employed to select 404 rice farm households in the northern region of Ghana. Propensity Score Matching (PSM) approach was used to analyse the data. Findings, Value added & Novelty: This study provides literature on drivers of improved rice variety adoption and its effect on rice output, by jointly considering time and location-specific factors. The empirical results revealed that adoption of improved rice varieties has significant positive effect on rice output of farm households. This could translate into reducing food and nutrition insecurity and the importation of rice into Ghana. Similarly, improved rice varieties adoption is positively and significantly affected by family labour, membership in FBO, farmers’ perception of rainfall, awareness of government rice policy, telephone ownership, and closeness to input markets. However, the adoption of improved rice varieties bears a significant negative relationship with the age of a farmer and mechanization. To enhance rice productivity and food security outcomes, the study recommends that the development of enhanced rice varieties responsive to current climatic situation. Dissemination and promotion of the varieties should be given priority among stakeholders in the rice value chain. Farmers should be encouraged to join or form farmer-based organisations (FBOs) and support their farm work with family labour to minimize rice production costs due to external payments. Access to market by farmers should be enhanced by improving rural road networks, especially in the rural areas where rice production takes place. Government policy towards rice production should be well designed and communicated to rice farmers since awareness of government rice policy stimulates improved rice varieties adoption among rice farmers.

Fuelwood consumption in the residential sector has been widely studied worldwide, being family income and other socio-demographic variables commonly identified as its major drivers. In this review, we questioned these findings by including people's preferences/perceptions and context-specific variables in the analysis, and their joint effect on households' energy choices. For this purpose, we performed a meta-analysis based on an econometrical model covering 69 studies (228 observations) on fuelwood consumption and energy transition. We conclude that people's preferences/perceptions have been undervalued in comparison to socioeconomic variables, which are more easily measured by using surveys –or they are already included in preexisting datasets-, especially when researchers are not familiar with local sociocultural and environmental contexts (traditions, status, and worldviews, among others). When people's preferences/perceptions are included in models, the commonly detected effects of gender and family income on energy transition significantly decrease, while the effect of people's schooling remains. This opens the discussion whether it is correct to tackle the dilemma about residential fuelwood consumption through policies that are based on variables like income, instead of more seriously trying to understand local contexts, and also it highlights the role that people's schooling has on energy transition beyond economic aspects. If we take into account that people's decisions about energy includes highly behavioral elements on the personal and household levels, shaped by education, we will be able to develop targeted public policies that allow for a more sustainable use of energy in the residential sector. • Study highlights the importance of preferences in residential energy transition. • Meta-analysis used data from 69 studies on fuelwood consumption and energy transition. • Preferences and perceptions are undervalued compared to socio-economic variables. • Inclusion of preferences into the studies reduces gender and income effects but schooling remains key. • Findings stress education's role and the need for targeted sustainable energy policies. [ABSTRACT FROM AUTHOR]

Bread, the most consumed floury product in the world, is one of the most wasted food products across the food supply chain. Yet, there is a paucity of research examining the magnitude of bread waste and behavioural drivers associated with it at the household level. This study analyses the incidence, behavioural drivers and disposal pathways of bread waste using a sample of 1462 households in Australia and a 7-day electronic diary method. Behavioural drivers related to bread waste were modelled using logistic regression models. The findings suggest that bread rolls, sliced bread and flat bread are the three most wasted bread products in Australian households. Higher grocery shopping frequency, 'just-in-case' buying, family households with young children and takeaway meal ordering are associated with higher bread waste. Bread disposal pathway analysis revealed that 55% of bread and bakery products are discarded through general waste bins, highlighting the immense potential of utilising bread waste in industrial processes such as biofuel production. Addressing bread and bakery waste can significantly contribute to achieving the SDG12.3 goal of halving the per capita food waste by 2030. • Household bread waste behaviours and disposal pathways analysed. • Bread and bakery waste represent 12% of total edible food wasted. • Sliced bread, bread rolls and flatbread are the most commonly discarded breads. • Just-in-case buying, and family households are associated with high bread waste. • 55% of bread and bakery waste is discarded through general waste bins. [ABSTRACT FROM AUTHOR]

Abstract Background Land clearing generates coarse woody debris (CWD), much of which ultimately becomes atmospheric CO2. Schemes for greenhouse gas accounting must consider the contribution from land clearing, but the timing of the contribution will have large uncertainty, due to a paucity of knowledge about the rate of CWD disappearance. To better understand above-ground CWD disappearance following a land clearing event—through the actions of microorganisms, invertebrates, wildfire, or deliberate burning—we combined statistical modelling with an archive of semi-quantitative observations (units of CWD %), made within Queensland, Australia. Results Using a generalised additive mixed-effects model (median absolute error = 14.7%), we found that CWD disappearance was strongly influenced by the: (i) number of years elapsed since clearing; (ii) clearing method; (iii) bioregion (effectively a climate-by-tree species interaction); and (iv) the number of times burned. Years-since-clearing had a strongly non-linear effect on the rate of CWD disappearance. The data suggested that disappearance was reverse-sigmoidal, with little change in CWD apparent for the first three years after clearing. In typical conditions for Queensland, the model predicted that it will take 38 years for 95% of CWD to disappear, following a land clearing event; however, accounting for uncertainty in the data and model, this value could be as few as 5 years, or > 100 years. In contrast, due to an assumption about the propensity of land managers to burn CWD, the official method used to assess Australia’s greenhouse gas emissions predicted that 95% of CWD will disappear in

El objetivo fue estimar el valor económico que los visitantes otorgan por disfrutar y conservar los servicios ecosistémicos de la bahía interior de Puno , Lago Titicaca. Se aplicó el enfoque cuantitativo, mediante el método de valoración contingente, se desarrolló el modelo “Diferencia en la función de utilidad indirecta” con función de probabilidad logit para estimar el valor económico de los visitantes, el formato de encuesta fue el dicotómico doble límite. La población de estudio fue el promedio anual de visitantes de la isla de los Uros, 1998-2019, la muestra es 384 observaciones divididas en cuatro submuestras, con 5% de margen de error. El valor económico del promedio anual del total de visitantes para conservar y disfrutar los servicios ecosistémicos de la bahía interior de Puno es en promedio S/ 909,479.34. Los servicios ecosistémicos que ofrece la bahía interior de Puno, Lago Titicaca son: servicios de provisión de agua dulce a la ciudad de Puno y alrededores, recursos genéticos, alimentos mediante la pesca artesanal y caza de subsistencia, puertos y transporte; culturales: valor espiritual religioso, recreación, ecoturismo y conocimiento científico; regulación climática: cinco microclimas en Puno; soporte: ciclo de nutrientes. El valor estimado de la disposición a pagar de los visitantes por disfrutar y conservar los servicios ecosistémicos de la bahía interior de Puno es S/ 15.18, las variables significativas son: precio inicial, género y si la persona tenía conocimiento acerca de la bahía interior de Puno.

O motivo de as fusões e aquisições (F&As) acontecerem em ondas é ainda um tema pouco explorado na literatura financeira, especialmente no contexto de mercados fora dos EUA e Reino Unido. Diante disso, o presente trabalho investiga se o otimismo dos agentes econômicos pode levar a uma onda de F&As, utilizando dados brasileiros entre 2007 e 2017 sobre as transações e o Índice de Confiança do Empresário, que mede o otimismo dos empresários com a situação atual e futura da economia. Foi utilizada a definição de onda de F&As como em Harford (2005). A partir de um modelo de resposta binária logit, os resultados apontam que o otimismo aumenta a probabilidade de ocorrência de uma onda de F&As. O Ibovespa foi a variável que apresentou maior efeito nas probabilidades de ocorrência de uma onda de F&As. Os resultados foram significantes para diferentes lags.

Empowerment in agriculture plays an important role in improving food and nutrition security. Understanding the determinants of farmer empowerment in agriculture is vital in improving the targeting of key indicators that matter for policy and practice. Most of the existing studies focus on female empowerment, leaving out the equally important aspect of male empowerment. We compute empowerment in agriculture index for male and female farmers and assess its determinants by applying the Tobit and Logit models on cross-sectional data of 835 farmers in Kenya. We find that only 11% of the farmers were empowered, 5% of whom were female. Econometric results show that gender had a positive and significant association with empowerment in agriculture and male and female farmers benefited to varying extents even from the same determinants. Thus, empowerment initiatives should compensate for such differences by targeting male and female farmers. Moreover, commercialization, access to government extension services and value of assets were positively and significantly associated with empowerment in agriculture indicating extra pathways through which empowerment in agriculture could be enhanced.

Cashew Productivity in Benin is very low due to the poor performance of the plant material used. To meet the ever-increasing needs of cashew producers in quality plant material, recent years interventions have focused on the development and organization of the seed system for a large scale production of quality grafted cashew trees. This research analysed the financial profitability of cashew seed production as well as the determinants. Data were collected from 111 cashew seed growers carefully selected through network sampling in the main production areas in Benin. The operating account approach was used to estimate the net margin and the Profit / Total Cost ratio. The binary logit logit model was adopted to determine the factors determining the Profit / Total Cost of Production ratio. The results showed that the net margin was on average 282.50 FCFA / plant for producers of grafted cashew trees against 110.54 FCFA / plant for producers of ungrafted plants. Also, an investment of 1 FCFA in the production of cashew trees generates 0.926 FCFA for seedlings of ungrafted plants and 1.759 FCFA for seedlings of grafted plants, indicating that the production of grafted cashew trees is financially more profitable than the production of ungrafted plants. Furthermore, the profitability of cashew seed production is positively correlated with gender, residence status, production of cashew seedlings as the main activity, formal education and the type of seeds produced. On the other hand, this profitability was negatively influenced by membership in a seed organization. These results recommend the adoption of the production of grafted cashew seedlings with an integrated production system based on the use of adequate infrastructure and management tools by all seed companies. [ABSTRACT FROM AUTHOR]

This paper investigates the propensity of youth to migrate using the survey data from two universities in Kosovo. The logit model results suggest comprehensive and statistically robust evidence that migration propensity is negatively related to age. The respondents that have political concerns, that are against or indifferent to migration as a phenomenon, compared to those that support it, have indicated statistically significant negative migration propensity. Conversely, the data suggest that economic, cultural, and security variables are significantly and positively related to migration propensity. Moreover, the data suggests no statistically significant impact of gender, marital status, residence, employment, income, relatives' network, religion, and training, variables, on the migration propensity. The robustness of estimated results is supported by diagnostic tests. Finally, the fact that 59% of respondents have indicated a propensity to migrate, clearly emphasizes the seriousness of the migration challenge, and the consequential impact it may have on the future prosperity of the country. [ABSTRACT FROM AUTHOR]

From the 1970s, emerging countries embarked on financial liberalization policies with a view to promoting growth. However, these policies can have adverse effects on the stability of banking systems. The central hypothesis of this article is that their impact on the stability of the banking system largely depends on the modalities of liberalization. The analysis focuses on a sample of seventeen emerging countries over the period 1990-2012. The interest of this period is that it allows not only to analyze the causes of these crisis but also to integrate new banking crisis such as those of South-East Asia (1997), Argentina (2001 ) and Turkey (2001) while most of the studies analyzed in the literature are limited to crisis that occurred before 1995. Then, using the logit method, we found that financial liberalization played an important role in explaining banking crisis and that economic growth reduces the probability of suffering a crisis. In addition, at the level of institutional variables, the more contracts are honored, the more the probability of suffering a banking crisis decreases. [ABSTRACT FROM AUTHOR]

We examine the drivers of research performance of 1431 economists from six European countries. Data from the Scopus database are collected. We compare the relative performance of economists from three northern European countries: Belgium, Denmark and Germany with three from the south: Greece, Italy and Portugal. Relative performance is measured as the deviation from the country average in both citations and papers. The dependent variables take the value of 1 if the productivity of the researcher is above the country average and 0 if it is below. Probit/logit analysis is employed and marginal effects are estimated to examine the significance of factors like the country of their PhD studies, gender and inbreeding at the national level. A US PhD or a German PhD affects negatively the relative productivity of German economists. Inbreeding at the national level (locally trained economists) reduces productivity among Greek, Italian and Portuguese economists. Gender is significant in the case of Denmark, Germany and Italy, but it does not affect productivity in Belgium, Greece and Portugal. [ABSTRACT FROM AUTHOR]

A summary of the eleven papers published in this special issue is presented here. This volume was the last in a series of special issues dealing with symmetric and non-symmetric continuous probability distributions. The works presented in this issue propose new probabilistic models and extend the properties of other existing models in the statistical literature. [ABSTRACT FROM AUTHOR]

We empirically investigate the role of cultural values on the occurrence of the global financial crisis. We use data based on Hofstede (Culture's consequences: comparing values, behaviors, institutions and organizations across nations, 2001) cultural values indexes and employ two econometric approaches, the self-organizing maps and logit, in a panel set of 38 developed and developing countries. We find that culture has a statistically and economically significant effect on the occurrence of the global financial crisis of 2007–2009. The relationship between cultural factors and the crisis occurrence remains strong when we consider control variables representing different sectors of the economy. [ABSTRACT FROM AUTHOR]

India is an agricultural country, and agricultural goods and trade are vital to its economy. It has been decades since India's small and marginal farmers' pricing risk was reduced through better agricultural marketing. A futures market was created to stabilize prices, decrease poverty, and promote economic growth. Investors can use future derivatives to protect their cash market positions. Agricultural commodities futures market has yet to garner considerable producer participation. A survey was conducted in Karnataka state by producers involved in a variety of crops using a blend of judgement and convenient sampling method. MS Excel and IBM SPSS 20 were used as statistical software. A logit model revealed the primary determinants impacting commodity futures adoption in the area. It tries to identify institutional, socioeconomic, and farmer involvement factors that hinder or promote farmer participation in futures markets in India and Abroad. [ABSTRACT FROM AUTHOR]

The aim of this study was to evaluate the probability of buying food away from home according to the type of household using the logit model, as well as the sociodemographic characteristics of the heads of household, and how much income expenditure represents. A cross-sectional study was carried out using the National Household Survey (ENAHO) 2019 database. After joining the database, the household type variables were created. To calculate the probability with the "logit" model of purchase, the variables—family size, income, types of household, and total expenditure—were selected as a measure of the purchasing power of the family. A statistically significant association (p < 0.05) was found between the probability of consumption and the variables: age of household members, predominance, nuclear without children–married, nuclear with children–cohabitant, nuclear with children–widowed, nuclear with children–separated, extended, compounded, poor not extreme, and not poor. The bulk of families was represented by nuclear families (61.97%). The highest expenditure in the CFAH was for families defined as composite with a yearly average of USD 1652.89 (equivalent to PEN 5520.67). Observing the expenditure on food consumed outside the home through the composition of households can allow a better approach to offer educational measures. This information can be helpful to developers of educational issues. [ABSTRACT FROM AUTHOR]

This paper examines the impact of product market competition on the dividend policy of Indian firms. We have taken product market competition as the proxy of external corporate governance. This study has used 1142 non-financial, non-utility, and non-government Indian firms listed in NSE from 2001 to 2018. For the purpose, five different product market competition and three various dividend measures were employed. Also, the interaction between product market competition (external) and board corporate governance (internal) on dividend policy was examined using a newly developed board corporate governance index (BCGI). The findings suggest that non-competitive firms are more likely to pay higher dividends than competitive firms. Non-competitive firms face more significant agency problems and therefore, pay higher dividends than competitive firms. Finally, the study found that the influence of internal corporate governance on dividends to be much higher and significant in the case of non-competitive firms compared to competitive firms. Overall, the findings of this study offer consistent evidence that external corporate governance and dividend policy are substitutes, and higher agency costs and higher internal governance strengthens this relationship. The outcomes of this study can help the managers to more precisely take dividend decisions by looking at the competition level in the market. The results suggest that managers should pay less dividends when firms operate in a high-competitive industry and vice-versa. The policymakers should design corporate governance norms after considering the competitiveness of the industry. [ABSTRACT FROM AUTHOR]

Logit and probit regression are statistical methods that have the same is to determine predictor variables affect the categorical response variable. From relevant studies, they have advantages and disadvantages on certain cases. Therefore, the logit and probit regression will be applied on factors of woman criminal considering women crime rate in Central Java is still relatively high. This study aims to compare the result of the two regression so that the best regression model is obtained to explain factors that influence woman criminal. The data type used is primary data obtained using a questionnaire and validated by non-empirical validation. The sample was taken using a quota sampling technique. The result showed that probit regression is the best model with the factors that influence woman criminal are the age of 17-25 years, 26-35 years, junior high school education level, married and ever married marital status.

El cultivo de cacao es de gran importancia para la económica agrícola del Departamento de Santander y para Colombia, ya que en los últimos años se ha promovido su implementación como una solución a los cultivos ilícitos. Es por ello, que es importante conocer que factores podrían incidir en los bajos rendimientos productivos del cultivo de cacao en esta región. Empleando un modelo logit se estimó qué variables inciden en la probabilidad de que una finca presente rendimientos superiores al promedio regional 490 kg.ha-1. Los resultados evidenciaron que, a mayor experiencia del productor, el tener acceso a créditos y que altitudes superiores a 800 m.s.n.m. favorecen cultivo de cacao, aumentan la probabilidad de que las fincas presenten rendimientos superiores a 490 kg.ha-1. Por otra parte, se determinó que pertenecer a una asociación, aumentar el tamaño de la fi nca, reduce la probabilidad de que la finca presente mejores rendimientos. Estos resultados dan herramientas importantes a las instituciones públicas y privadas que intervienen en estas comunidades, para que consideren dentro de sus paquetes tecnológicos estas variables y puedan tener mayores efectos en los rendimientos del cultivo y con ello en la calidad de vida de los productores.

The aim of the study is to estimate a nonlinear regression logit model to calculate the probability of a road accident occurring in Algeria. Referring to the literature, this probability depends on several variables related to the driver, the vehicle and the road environment. Thus, the objective is to show which explanatory variables favour the occurrence of a traffic accident and to what extent. In addition, we seek to estimate the probability that a driver with given characteristics, driving a vehicle with given characteristics, and having a driving licence for a given length of time may have an accident. The structure of the estimation is based on disaggregated data collected following the analysis of files proposed by an Algerian insurance company. The results obtained make it possible to determine the category of variables that has a significance and an important role in explaining the probability of accidents occurring.

The study aims to empirically identify the determinants of the debt crisis that occurred within the framework of 15 core EU member countries (EU-15). Contrary to previous empirical studies that tend to use event-based crisis indicators, our study develops a continuous fiscal stress index to identify the debt crises in the EU-15 and employs three different estimation techniques, namely self-organizing map, multivariate logit and panel Markov regime switching models. Our estimation results show first that the study correctly identifies the time and the length of the debt crisis in each EU-15-member country. Empirical results then indicate, via three different models, that the debt crisis in the EU-15 is the consequence of deterioration of both financial and macroeconomic variables such as nonperforming loans over total loans, GDP growth, unemployment rates, primary balance over GDP, and cyclically adjusted balance over GDP. Furthermore, variables measuring governance quality, such as voice and accountability, regulatory quality, and government effectiveness, also play a significant role in the emergence and the duration of the debt crisis in the EU-15.

In the context of an increasingly digitized global marketplace, this study seeks to shed light on its adoption in developing countries, focusing on Morocco. Applying logit, probit, and conditional mixed-process probit models to a sample of 807 Moroccan firms, we identify key factors that influence e-commerce adoption. The results show that younger, innovation-driven firms and those with a highly educated workforce tend to adopt e-commerce more readily. However, digital skills required in hiring do not significantly affect adoption, suggesting a complex relationship between digital skills and e-commerce use. The results also show that firms that are active on digital platforms and engage in innovative practices are more likely to adopt e-commerce. Therefore, this study argues for the need to improve digital skills training and for firms to establish a presence on digital platforms and promote innovation. On the policy front, the study suggests the promotion of supportive policies such as financial assistance, improved Internet infrastructure, and robust regulatory frameworks. As an important starting point for future research, these findings underscore the complexities of e-commerce adoption in Morocco and can guide further research, particularly in the context of similar emerging economies.

The removal of arsenite [As(III)] from drinking water was investigated in a column at flow rates of 2.0 and 5.0 mL/min (up-flow direction) using bark-based magnetic iron oxide particles (BMIOP) prepared by coating (Fe(NO3)3.9H2O) over Tamarindus Indica bark. The BMIOP was compared with regenerated BMIOP, commercial activated carbon, commercial activated alumina (Al2O3). At 2.0 mL/min, empty bed contact time (EBCT), breakthrough time (BT), the volume of treated water and breakthrough capacity (BC) on fresh BMIOP were found to be 6.8 min, 33.15 h, 4.380 L and 0.742 mg/g, respectively, and at 5.0 mL/min, were found to be 4.1 min, 13 h, 3.675 L and 0.453 mg/g respectively. EBCT, BT and BC were increased by 65.85%, 155% and 63.79%, respectively, as the flow rate was reduced from 5.0 to 2.0 mL/min. After regeneration of BMIOP, EBCT, BT, saturated time, BC and saturation capacity (SC) were reduced by 21.95%, 15.38%, 55.15%, 16.78% and 29.71%, respectively. The BC of fresh BMIOP was increased by factors 4.15, 3.60 and 1.20 and SC by factors 9.51, 7.88 and 1.42 compared to commercial activated carbon, commercial activated Al2O3 and regenerated BMIOP, respectively. Logit model could be used for the design of the adsorption column. Thomas model and artificial neural network (ANN) were applied to predict the characteristic column parameters useful for process design. Quality of treated water meets BIS requirements. Toxicity Characteristic Leaching Procedure (TCLP) and semi-dynamic tests show that the exhausted BMIOP is safe for disposal in a secure landfill; hence, BMIOP has been proved to separate As(III) from water. [ABSTRACT FROM AUTHOR]

This paper examined a set of over two thousand crypto-coins observed between 2015 and 2020 to estimate their credit risk by computing their probability of death. We employed different definitions of dead coins, ranging from academic literature to professional practice; alternative forecasting models, ranging from credit scoring models to machine learning and time-series-based models; and different forecasting horizons. We found that the choice of the coin-death definition affected the set of the best forecasting models to compute the probability of death. However, this choice was not critical, and the best models turned out to be the same in most cases. In general, we found that the cauchit and the zero-price-probability (ZPP) based on the random walk or the Markov Switching-GARCH(1,1) were the best models for newly established coins, whereas credit-scoring models and machine-learning methods using lagged trading volumes and online searches were better choices for older coins. These results also held after a set of robustness checks that considered different time samples and the coins' market capitalization. [ABSTRACT FROM AUTHOR]

This study applied a logistic regression model to determine the odds ratio of selecting clean versus unclean energy as the main household fuel choice. This study also undertook to establish the coefficients of the factors determining household fuel energy choice. A large microeconomic dataset from KIPPRA's comprehensive study and analysis on fuel use patterns in Kenya (2010) was employed to carry out the analysis. This study employed a multinomial logit regression model to determine the fuel choices and patterns of cooking fuels in urban Kenyan households. The results showed that in addition to income, there are several socio-demographic factors such as education, gender, and age that were important in determining household fuel choice. To encourage clean fuel use, the authorities should carry out public education campaigns, and ensure the availability of these fuels in all areas to avoid harmful effects of biomass fuels and kerosene, and more modern and efficient appliances should be made available at affordable rates to ensure more efficient use of these forms of clean energy. [ABSTRACT FROM AUTHOR]

Copyright of Journal of International Business Studies is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aims to determine which factors influence household perceptions of retirement planning decisions. Age, marital status, salary, level of education, loan payment, and savings habit will be identified as significant variables in the prediction. This study employed the logistic regression (logit) model, with the sample divided into those who have enrolled in a pension plan and those who have not begun to plan for a pension fund. The sample age range was 26 to 58 years old, with a total of 2,808 respondents. This study discovered that for the age range 26-35 years old, obtaining more education, being younger, earning higher salaries, having less loan obligation, and saving less, the household were more likely to have proper retirement planning. However, between the ages of 36 and 58, planning for retirement became more likely as they get older, gain more education, enter marriage life, and have more loan obligations. [ABSTRACT FROM AUTHOR]

Credit score models quantify the risks in credit operations, customer segmentation, and approve or reject requests to credit customers. These models provide the necessary information to calculate the probabilities of default of any customer through the application of parametric or non-parametric techniques. This work identifies which model (Logit, Probit, Neural Networks, or Linear Support-Vector Machine (L-SVM)) may be more appropriate to measure the credit risk of individuals in a Family Benefit Fund located in Colombia. The results show Linear Support Vector Machine produces better performance, but Probit - Stepwise models are equally useful and they have the advantage of being interpreting the calibrated parameters. [ABSTRACT FROM AUTHOR]

Kerala labour market witnesses a pattern of increasing female participation in the category of 'out-of-labour force', within which, majority are reported as attending domestic duties. By using the latest two rounds of NSSO employment and unemployment data and two rounds of Periodic Labour Force Surveys, this paper examines the trend, magnitude and causes of out-of-labour force (OLF) among the young females in Kerala. Particularly, the study tries to determine the factors that deter female entry into the labour force. There is a social and economic dimension for the young females falling in the category of OLF in Kerala. However, education and marital status remain major factors determining female labour force participation. This study, hence, proposes to characterise this phenomenon as 'educated out-of-labour force' among young females in Kerala. [ABSTRACT FROM AUTHOR]

This editorial summarizes the papers published in issue 17(2) (2022). The first paper evaluates logistic regression and machine-learning methods for predicting firm bankruptcy. The second paper demonstrates that machine learning outperforms existing tools to improve the estimation of regional input–output tables. The third paper investigates whether network centrality depends on the probability that a tie between two nodes is formed, as well as its intensity. The fourth paper sets out a Bayesian estimation technique to estimate a spatial autoregressive multinomial logit model. The fifth paper develops a statistic to test for several misspecification problems in spatial econometric models. The sixth paper compares the prediction accuracy of spatial and non-spatial econometric models explaining the number of tourist arrivals across countries. [ABSTRACT FROM AUTHOR]

Abstract Although the Andean region is one of the most landslide-susceptible areas in the world, limited attention has been devoted to the topic in this context in terms of research, risk reduction practice, and urban policy. Based on the collection of landslides data of the Andean city of Quito, Ecuador, this article aims to explore the predictive power of a binary logistic regression model (LOGIT) to test secondary data and an official multicriteria evaluation model for landslide susceptibility in this urban area. Cell size resampling scenarios were explored as a parameter, as the inclusion of new “urban” factors. Furthermore, two types of sensitivity analysis (SA), univariate and Monte Carlo methods, were applied to improve the calibration of the LOGIT model. A Kolmogorov–Smirnov (K-S) test was included to measure the classification power of the models. Charts of the three SA methods helped to visualize the sensitivity of factors in the models. The Area Under the Curve (AUC) was a common metric for validation in this research. Among the ten factors included in the model to help explain landslide susceptibility in the context of Quito, results showed that population and street/road density, as novel “urban factors”, have relevant predicting power for landslide susceptibility in urban areas when adopting data standardization based on weights assigned by experts. The LOGIT was validated with an AUC of 0.79. Sensitivity analyses suggested that calibrations of the best-performance reference model would improve its AUC by up to 0.53%. Further experimentation regarding other methods of data pre-processing and a finer level of disaggregation of input data are suggested. In terms of policy design, the LOGIT model coefficient values suggest the need for a deep analysis of the impacts of urban features, such as population, road density, building footprint, and floor area, at a household scale, on the generation of landslide susceptibility in Andean cities such as Quito. This would help improve the zoning for landslide risk reduction, considering the safety, social and economic impacts that this practice may produce.

Este artículo tuvo como objetivo analizar la probabilidad de riesgo crediticio comercial de 650 empresas ecuatorianas del sector alimenticio, mediante un análisis estadístico de tipo inferencial e implementación de un modelo de regresión logística. En efecto, se convergió en tres hipótesis que indican que la liquidez, el tamaño y la ubicación de la empresa influyen en la probabilidad de riesgo crediticio. Los resultados del modelo evidenciaron significativamente que las empresas ubicadas en la Sierra, grandes y con alta liquidez son las que mayor probabilidad de riesgo presentan; estas derivaciones proporcionan una aproximación predictiva del riesgo crediticio de las empresas alimenticias y una contribución a la discusión en espacios empresariales, académicos y científicos.

Although water is important for human livelihoods, access and use of improved domestic water for households in most developing countries is still a major problem. Households adopt several domestic water improvement mechanisms to improve the quality of their water before consumption. However, the drivers of the probability to engage in this behaviour have not been adequately explored in developing countries. Therefore, this study investigates the factors that determine the probability of choosing to improve domestic water quality before consumption, with data from a household survey implemented in Ghana. Using the Logit econometric model with its associated margins, this study shows evidence that environmental knowledge, age, gender and wealth are key drivers of the probability of engaging in a water improvement behaviour. Based on the identified drivers, practical lessons are discussed to inform policy decisions on the quality of water supply. HIGHLIGHTS This developing country study investigates the drivers of the probability to improve domestic water before consumption.; The study applies econometric techniques to determine the drivers.; The study finds a significant difference between those who choose to avert and otherwise.; A significant proportion of the respondents engage in averting behaviour.; The study shows that even with packaged water sources, households still avert.;

Abstract Background Mortality modelling in the critical care paradigm traditionally uses logistic regression, despite the availability of estimators commonly used in alternate disciplines. Little attention has been paid to covariate endogeneity and the status of non-randomized treatment assignment. Using a large registry database, various binary outcome modelling strategies and methods to account for covariate endogeneity were explored. Methods Patient mortality data was sourced from the Australian & New Zealand Intensive Society Adult Patient Database for 2016. Hospital mortality was modelled using logistic, probit and linear probability (LPM) models with intensive care (ICU) providers as fixed (FE) and random (RE) effects. Model comparison entailed indices of discrimination and calibration, information criteria (AIC and BIC) and binned residual analysis. Suspect covariate and ventilation treatment assignment endogeneity was identified by correlation between predictor variable and hospital mortality error terms, using the Stata™ “eprobit” estimator. Marginal effects were used to demonstrate effect estimate differences between probit and “eprobit” models. Results The cohort comprised 92,693 patients from 124 intensive care units (ICU) in calendar year 2016. Patients mean age was 61.8 (SD 17.5) years, 41.6% were female and APACHE III severity of illness score 54.5(25.6); 43.7% were ventilated. Of the models considered in predicting hospital mortality, logistic regression (with or without ICU FE) and RE logistic regression dominated, more so the latter using information criteria indices. The LPM suffered from many predictions outside the unit [0,1] interval and both poor discrimination and calibration. Error terms of hospital length of stay, an independent risk of death score and ventilation status were correlated with the mortality error term. Marked differences in the ventilation mortality marginal effect was demonstrated between the probit and the "eprobit" models which were scenario dependent. Endogeneity was not demonstrated for the APACHE III score. Conclusions Logistic regression accounting for provider effects was the preferred estimator for hospital mortality modelling. Endogeneity of covariates and treatment variables may be identified using appropriate modelling, but failure to do so yields problematic effect estimates.