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Asset sales can have opposing effects on firm credit quality. On the one hand asset sales could signal increased credit risk resulting from distress or on the other hand they could improve internal liquidity and hence credit quality. Therefore the impact potential asset sales can have on credit quality is an empirical question and one that has previously not been examined in the literature. The paper aims to discuss these issues.

Using credit ratings as a measure of firm credit quality, in ordered probit regressions, this study finds evidence consistent with the internal liquidity view of the asset sales-credit risk relationship.

Results from ordered probit regressions of credit ratings show that the likelihood of higher credit ratings is increasing in industry-level turnover of real assets

Credit-rating agencies often cite the impact of asset sales on firm credit quality as a motivation for their rating assignments. Distress-driven asset sales could reduce firm credit quality whereas other asset sales could result in increased internal firm liquidity and hence improve firm credit quality. This bi-directional expectation leaves the question of how asset sales affect credit quality to be answered empirically and has not been previously tested in the literature.

This study aims to develop an ordered probit model to explain and predict small business relative performance in Chile, South America.

The design is survey research. The sample includes 403 small businesses classified as 158 failed firms, 101 mediocre firms and 144 successful firms within all economic sectors. The model variables are: internet, starting with adequate working capital, managing good financial and accounting records, planning, owner formal education, professional advice, having partners, parents owning a business, and marketing efforts.

The eight-variable model, tested with ordered probit, is a significant predictor of the level of performance at the 0.000 level. Also, six of the eight variables are significant predictors at the 0.05 level: internet, starting with adequate working capital, managing good financial and accounting records, owner, professional advice, having partners, parents owning a business, and marketing efforts. Two of the variables – i.e. planning and formal education – were not significant. ANOVA test of differences were run for each of the eight variables based on the level of performance were also run and results reported.

The model does in fact predict relative performance, so the model can be used to improve the probability of success. Thus, an entrepreneur can use the model to gain a better understanding of which resources are needed to increase the probability of success, and those who advise entrepreneurs can help them use the model. Investors and creditors can use the model to better assess a firm's potential for success. There is an extensive public policy implications discussion regarding how to use the model to assist entrepreneurial ventures so that society can benefit in direct and indirect ways via the allocation of limited resources toward higher potential businesses. Entrepreneurs and small business educators can use the model's variables to influence future business leaders, public policy makers, and their practices.

This study improves the Lussier 15 variable success versus failure prediction model by adding the use of the internet and taking out highly correlated variables. While Lussier and others ran logistic regression with only two levels of performance, this study uses the more robust ordered probit model with three levels of performance. It presents public policy with implications for Chilean institutions to promote entrepreneurship. Finally, it contributes to the literature because, to date, no empirical success versus failure studies have been found that were conducted in Chile or any small, open economies in Latin America

This paper aims to discuss the determinants of food security in Kassala state using the measurement of Household Food Insecurity Access Scale (HFIAS). We use the measurement of HFIAS and use new primary data from a food security household survey in Kassala state (2019).

This paper focuses on the determinants of food security in Kassala state using the measurement of Household Food Insecurity Access Scale (HFIAS), using new primary data from a food security household survey in Kassala state (2019) and using the multinomial logistic regression analysis and both ordered logit and ordered probit regression to examine the determinants of food security.

Our results are in support of our hypothesis that the significant determinants of household food insecurity are family-owned production (that negatively affects the probabilities of household being food insecure), household income (that negatively affects HFIAS). We observe that the effects of family-owned production on household food insecurity are particularly significant in the case of mildly and moderately food insecurity. We explain that the other factors that affect the household food insecurity include improvement in the level of agricultural services, marketing, banking services and road characteristics that reduce HFIAS. We find a gender gap related to food security in the sense that male-headed households produce more food compared to female-headed households and also families headed by males are more likely food secure. Therefore, the major policy implication from our results is the importance of increasing households income and enhancing family own production of food to eliminate food insecurity.

This paper provides a significant contribution to the Sudanese and international literature because it discusses the determinants of food security in Kassala state. Different from the two other accompanying papers that focused on the incidence of food security in Kassala state using the measurement of Household Food Insecurity Access Scale (HFIAS) and the determinants of production of food and consumption of food in Kassala state, this paper focuses on the determinants of food security in Kassala state using the measurement of HFIAS and using new primary data from a food security household survey in Kassala state (2019). We fill the gap in the Sudanese literature because we provide a more interesting analysis of the determinants of food security in Kassala state. Our analysis is useful from policy perspective since we provide useful policy recommendations to enhance food security through agricultural development in Kassala state.

This study seeks to provide a robust piece of evidence of forest depletion in Ghana and its associated driver intensities to inform national policy decisions towards achieving Sustainable Development Goal (SDG) 15 and beyond.

Using a representative sample size of 733 households, which was obtained with the aid of a structured questionnaire, a descriptive analysis is used to show the evidence of forest depletion. For robustness purposes, the geographic information system (GIS) is used to provide a piece of remote sensing evidence to substantiate the claim. In addition, an ordered probit regression model is estimated given the ranked nature of the responses to determine the drivers of forest depletion.

The results provide evidence that the urban forests in the Greater Accra Region (GAR) of Ghana have been depleted. Overall, 44% argued that the depletion of the forests is high, 30% indicated that the depletion is moderate, while 26% indicated that the depletion is low. Consistent with the literature, the ordered probit regression results show that human behaviour, climate change and institutional failure are the driver intensities of forest depletion in the Region. Besides, the authors find an increasing order effect for all three drivers. Using a descriptive analysis, majority of the respondents posited that human behaviour is the main driver intensity, followed by climate change and then institutional failure. This study recommends the need for education and advocacy, community participation, law enforcement, resource mobilization, modern adaptation strategies and internalization of externalities as a way of controlling the drivers of forest depletion.

The study uses remote sensing techniques to provide empirical evidence of protected forest depletion in the GAR, Ghana. In addition, an ordered probit regression is used to identify the driver intensities that explain the depleted protected forests in the region.

The authors investigate cocoa farmers' willingness and motivation to participate in agritourism entrepreneurship in Ghana.

Primary data were obtained from 583 cocoa farmers. Contingent valuation method, ordered probit and truncated regressions were employed.

Cocoa farmers' willingness to participate in agritourism was high. The minimum fee farmers were willing to charge per tourist per day ranged from US$0.870 to US$6.957. Agritourism products farmers were willing to offer to tourists are interaction with rural folks, indigenous cuisine, quality locally stored drinking water, indigenous primary healthcare and on-site restrooms. Cocoa farmers' motivations to participate in agritourism are income generation, alternative livelihood strategy and education. Education, being a native, farm size, motorable roads to farm, and distance to farm influence minimum fee farmers were willing to accept to participate in agritourism.

Agritourism could be considered in rural and tourism development policies of developing countries.

The authors investigate cocoa farmers' participation in agritourism, motivations and determinants of willingness to participate.

This study aims to explore patterns in e‐tail spending across different demographic groups and to predict which households are the most frequent shoppers and highest spenders. Further, it aims to investigate which households are least likely to purchase from unfamiliar online stores.

Using a random sample of Florida households, the study is the first to use probit and ordered probit models to study Internet purchasing behavior.

Younger, college educated, higher income households living in suburban, rural and small towns spend and shop the most online. Caucasians purchase online more often than African Americans and Hispanics but spend about the same amount. The study also finds that male, Hispanic, college educated and younger consumers are more willing to purchase from unfamiliar online stores.

This study provides new evidence on factors affecting household online spending and buying decisions. Previous studies have not used an ordered probit to model different levels of spending and this new specification provides information about which demographic groups are the most (or the least) frequent buyers as well as which demographic groups are the highest (or the lowest) e‐tail spenders. This study also investigates which demographic groups are most likely to shop only at stores with whom they are already familiar.

The built environment is responsible for approximately 40% of the world’s energy consumption, 30% of raw material use, 25% of solid waste, 25% of water use, 12% of land use and 33% of greenhouse gas emissions. Thus, environmental improvement and decarbonization are becoming increasingly critical objectives for the construction industry. Sustainable construction can be achieved through several practices, including: considering life-cycle assessment, circular construction, resource efficiency and waste management and providing eco-efficient materials, reducing energy demands and consumption and incorporating low-carbon technologies and renewable energy sources. To achieve sustainable construction goals, it is critical to educate the future workforce about decarbonization, circular construction and how to overcome the challenges involved in transitioning to sustainable construction. This study aims to understand the gap in student knowledge related to decarbonization and circular construction and the importance of incorporating these topics in civil engineering and construction management curricula.

This study surveyed 120 undergraduate and graduate students at one of the largest minority-serving institutions in the USA to understand the gap in student knowledge related to decarbonization and circular construction as well as the importance of incorporating these topics in civil engineering and construction management curricula. The authors conducted several statistical measures to assess the consistency, reliability and adequacy of the sample size, including the Kaiser–Meyer–Olkin measure of sampling adequacy, the normality test to evaluate the appropriateness of using an ordered probit regression analysis and a multicollinearity test to observe the correlation between independent variables. The data was analyzed using ordered probit regression analysis to investigate the need for a curriculum that serves in educating students about decarbonization and circular construction.

The results of this research highlight the gaps in students’ knowledge pertaining to sustainable practices and the importance of providing future construction workforce with such knowledge to tackle global inevitable challenges.

The findings of this study contribute to sustainable construction bodies of knowledge by advocating for a reformed curriculum to prepare the future workforce and adopt less carbonized, more circular approaches within the engineering and construction industry.

Branching is one of the crucial strategic non-price actions for banks. Previous studies on the impact of state ownership upon banks focus on bank lending behavior. This paper aims to offer a novel investigation of how state ownership affects bank branching behavior by examining state-controlled commercial banks (SCCBs) in the context of the largest developing and transitional country China.

The two-part model (TPM) is applied to analyze the branching decision process. In the first stage, the dependent variable is the choice of bank branching dynamics and in the second stage the dependent variable is the number of new branches or the number of closed branches. For robustness check, the ordered probit selection model allowing for interdependence of the two stage decisions is also employed.

Using a unique dataset of bank branches in China, this paper finds that the branching decisions of Chinese SCCBs are driven by both profit motivated factors including population size, population density, income level, financial development and banking competition and politically motivated factors as represented with the proportion of SOEs. As a comparison, branching decisions of joint-stock banks in China are fully determined by profit motivated factors.

First, this study is the first to explore the effect of state ownership on bank branching decisions, providing a new insight on the literature regarding to the impact of state ownership on bank decisions. Second, this study explores the potential effect of politically motivated factors on bank branching decisions, filling the gap in bank branching literature. Third, this study can contribute to bank branching literature by enriching the limited understanding of how SCCBs make branching decisions. Lastly, this study applies novel empirical strategies to analyze bank branching decisions, including the TPM and the ordered probit selection model.

This study aims to investigate the association between Muslim individuals’ portfolio allocation choice and Islamic religiosity (levels and dimensions), controlling for risk tolerance and sociodemographic factors.

The study uses primary data collected via survey questionnaires from a sample of 751 Muslim working individuals in Kuala Lumpur, Malaysia. Owing to the ordinal nature of the dependent variable, which reflects the levels of proportions of risky assets in portfolios, the data were analyzed using an ordered probit regression model.

The findings reveal that Islamic religiosity levels in general were insignificantly related to portfolio allocation, but that two dimensions of religiosity (virtue and obligation) significantly impact the allocations of risky assets in the portfolio. The higher the level of virtue, the lower the propensity to allocate risky assets into the portfolio. On the contrary, the higher the level of obligation, the higher the propensity to allocate risky assets in the portfolio. Meanwhile, individuals with higher risk tolerance, income and education levels show greater propensity to allocate risky assets in the portfolio.

The sample is restricted to Muslims in Kuala Lumpur; hence, the findings are not easily generalized to Muslim investors in general. Findings may differ between Muslims across the world, so future research needs to expand from a country specific to an international analysis. In addition, future studies could include other determinants of portfolio allocation, such as financial literacy.

The findings of this study may assist financial planners and policymakers to better understand the drivers of portfolio allocation among their Muslim clients.

While other studies have tended to focus on the impact of religiosity on the holdings of specific financial assets, such as Islamic bank accounts or Takaful, the present study explores the effect of Islamic religiosity dimensions on the allocations of risky assets in the portfolio. The study also develops an ordinal measure of portfolio allocation and makes a methodological contribution by using an ordered probit regression analysis.

The objective of this paper is to study the impact of political connection and governance on credit rating and whether there is a substitution or complementary relationship between them.

In order to achieve the objective, a succession of eight ordered probit regressions has been carried out. Moderating variables between the political connection and governance characteristics were introduced. The whole population is taken as a sample, i.e., 27 Tunisian companies that are evaluated by FITSH NORTH AFRICA agencies over a period of 10 years (2009–2018).

The outcomes are mixed. They show that the political connection does not always influence credit rating; the size and board independence always improves credit rating; the duality between the functions affects credit rating; whereas the majorities’ proportion does not influence credit rating; and a substitution between the political connection and the governance characteristics is validated.

Like any other research, our results are factors of our measures and variable choice and depends heavily on the how these variables were conceived. Also, although our number of observations responds to the statistical result generalization requirements, our sample remains relatively narrow with 27 companies only.

In practice, the research will allow investors to have a better vision upon the future of their investments based on whether to develop their governance system or promote political networking. It will also prompt lenders to look beyond ratings and consider factors such as political connections to make a rational judgment on their future placements.

This study leads us to find various solutions: the establishment of credit agencies that take into consideration all the data of all the operators taken as a whole (bank, leasing company, and factoring). It encourages the reorganization of the Tunisian banking sector through mergers for example.

This study is a pioneer in the credit rating field in Tunisia, where the source of debt financing is the most used by all enterprises across all sectors. This study extends the literature of political connection effectiveness, independent directors, board size, in improving corporate performance and credit rating.