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Citizen trust in police is important in terms of citizen consent to government policies and of police achieving their organizational goals. In the previous study, improvements in police policy, organizational operation and policing activities were developed to clarify which factors influence trust in police and how trust can be improved. This research raises the question, would changes in trust in police have an impact on trust in government? In this paper, this research question is discussed theoretically and the causal relationship analyzed empirically by applying OLS, ordered logistic, 2SLS and logistic regressions.

The basic analysis methods are to apply the OLS and the ordered logistic regression. OLS regression analysis is an analytical method that minimizes an error range of a regression line. The assumptions for OLS are: linearity, independence, equilibrium, extrapolation and multicollinearity issues. These problems were statistically verified and analyzed, in order to confirm the robustness of the analysis results by comparing the results of the ordered logistic regression because of the sequence characteristic of the dependent variable. The data to be used in this study is the Asia Barometer Survey in 2013.

Trust in police and citizen perception of safety are analyzed as important factors to increase trust in the government. The effects of trust in police are more significant than the effects of control variables, and the direction and strength of the results are stable. The effect of trust in police on trust in government is strengthened by the perception of safety (IV). In addition, OLS, ordered logistic regression analysis, which analyzed trust in central government and local government, and logistic regression analysis categorized by trust and distrust show the stability.

This paper has implications in terms of theoretical and empirical analysis of the relationship between trust in police and trust in government. In addition, the impact of perception of safety on trust in police can be provided to police officers, policymakers and governors who are seeking to increase trust in government. This paper is also meaningful in that it is the microscopic research based on the citizens' survey. One of the limitations of macroscopic research is that it does not consider the individual perceptions of citizens.

The results of this paper can confirm the relationship of the virtuous cycle, which is perception of safety – trust in police – trust in government. The police will need to provide security services to improve citizens' perception of safety and make great efforts to create safer communities and society. Trust in police formed through this process can be an important component of trust in government. By making citizens feel safer and achieving trust in police, ultimately, trust in government will be improved.

The police perform one of the essential roles of government and are one of the major components of trust in government, but the police sector has been neglected compared to the roles of the economic and political sectors. These influences of macro factors are too abstract to allow specific policy directions to be suggested. If we consider trust in police, and factors that can improve trust in government, we can suggest practical policy alternatives.

This study aims to identify the determinants of transport mode choice and the constraints on shifting freight in New Zealand (NZ) from road to rail and/or coastal shipping, and to quantify the trade-off between factors affecting shippers’ perceptions, to assist in increasing the share of freight moved by non-road transport modes.

A revealed preference survey of 183 freight shippers, including small and medium enterprises and freight agents in NZ, is used to investigate whether freight shippers’ characteristics affect their ranked preference for attributes related to mode choice and modal shift. Additionally, a rank-ordered logistic (ROL) model is estimated using the ranking data.

The results reveal several distinct types of transport mode choice behaviour within the sample and show how the preferences for timeliness, cost, accessibility, damage and loss, customer service, and suitability vary between industry groups and business types. Also, the ROL method allows us to identify heterogeneity in preferences for mode choice and mode shift factors for freight within NZ.

The results imply that NZ shippers ranked transport time as the most significant constraint upon distributing goods by rail, while accessibility and load size were the most significant constraints upon using coastal shipping. The study also identifies how NZ shippers’ modal shift constraints vary according to the firm’s individual or logistical characteristics.

This study informs freight transport policy makers about the needs of NZ shippers by providing quantitative measures of the intensity of preference for the various mode choice factors.

Those involved in freight transport have a better basis for formulating transport policy.

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 attempts to identify fundamental determinants of bond ratings for non-financial and financial firms. Further the study aims to develop a parsimonious bond rating model and compare its efficacy across statistical and range of machine learning methods in the Indian context. The study is motivated by the insufficiency of prior work in the Indian context.

The authors identify the critical determinants of non-financial and financial firms using multinomial logistic regression. Various machine learning and statistical methods are employed to identify the optimal bond rating prediction model. The data cover 8,346 bond issues from 2009 to 2019.

The authors find that industry concentration, sales, operating leverage, operating efficiency, profitability, solvency, strategic ownership, age, firm size and firm value play an important role in rating non-financial firms. Operating efficiency, profitability, strategic ownership and size are also relevant for financial firms besides additional determinants related to the capital adequacy, asset quality, management efficiency, earnings quality and liquidity (CAMEL) approach. The authors find that random forest outperforms logit and other machine learning methods with an accuracy rate of 92 and 91% for non-financial and financial firms.

The study identifies important determinants of bond ratings for both non-financial and financial firms. The study interalia finds that the random forest technique is the most appropriate method for bond ratings predictions in India.

Better bond ratings may mitigate corporate defaults.

Unlike prior literature, the study identifies determinants of bond ratings for both non-financial and financial firms. The study also experiments with modern machine learning techniques besides the traditional statistical approach for model building in case of relatively under researched market.

The purpose of this paper is to examine whether credit ratings issued by Fitch predict auditor’s opinion for the Tunisian financial companies. It studies the association between Fitch’s credit rating and the audit opinion.

The whole population was analyzed. It is composed of 35 banks, leasing companies and factoring companies in Tunisia. The hand-collected data over 11 years (2005–2015) were used and a multiple-ordered logistic regression was performed.

The findings show that firms with a high short-term grade, a high long-term grade or a positive outlook are more likely to receive an unqualified audit opinion. In addition, companies with a stable outlook are more likely to receive an explanatory paragraph, a qualification or a going-concern opinion.

Studies examining the relationship between credit ratings and audit opinion are rare. This piece of research adds to knowledge about the relationship between different components of agency ratings and the auditor’s opinion in a developing country. Previous studies have investigated the case of developed countries and have been interested in the only impact of the long-term credit rating. This study analyzes three components of credit rating, namely long-term credit rating, short-term credit rating and rating outlook. In addition, it sheds light on the effect of various rating grades issued by rating agencies on the audit opinion. It gives a broader view of the relationship between credit ratings and audit opinion.

This study aims to examine the perceptions and opinions of relevant stakeholders regarding entrepreneurship opportunities and growth in the Gilgit-Baltistan (GB) province of Pakistan. Specifically, it focuses on the role of special economic zones (SEZs), such as Maqpondass SEZ and the China–Pakistan Economic Corridor (CPEC), in fostering nascent entrepreneurship (NE) and promoting regional development.

The study employs ordered logistic regression to estimate the relationship between various independent variables and nascent entrepreneurship (NE). The independent variables include awareness of CPEC (AAC), awareness of Maqpondass SEZ (AAMEZ), SEZ incentives (SEZInc), regional market competitiveness (RMC), loan availability (LA) and education and experience (EE).

The findings indicate a robust positive relationship between SEZ-based industries and the growth of local small businesses and enterprises in Gilgit-Baltistan. Furthermore, the study suggests that government incentives, access to finance, skill development, relevant knowledge, and connections with local businesses facilitate the establishment of new ventures.

The study underscores the importance of focusing on human capital development, providing financial assistance, and creating incentives for adopting advanced technology to foster the growth of local businesses in Gilgit-Baltistan through SEZs. It emphasizes the need for policymakers and stakeholders to prioritize initiatives that support entrepreneurship and innovation in the region.

This study contributes to the existing literature by providing novel insights into the perceptions of entrepreneurship development in Gilgit-Baltistan, particularly concerning the influence of natural resources and SEZs. It fills a gap in the research by offering valuable implications for policymakers, researchers, and practitioners seeking to promote sustainable economic development in the region.

The purpose of this study is to determine the impact of environment, social and governance (ESG) disclosure on credit ratings of companies in India.

Firms under study are listed on the Bombay Stock Exchange (BSE) 500 and represent almost 93 per cent of the total market capitalization on BSE. This study considers a sample of 122 firms from a population of 500 to examine the relationship between ESG scores and Credit Rating. The scope of this study is confined to those firms listed on the S&P BSE 500 which have made ESG disclosures and were rated by various credit rating agencies like Crisil, ICRA and CARE. Data were sourced from Bloomberg. Ratings were given in ascending order. In the first model, credit rating was used as predicted variable; ESG score as predictor variable and market capitalization, net debt to equity, and total debt to asset as control considering the ordered nature of dependent variable in the study, ordered logistic regression was applied. It was repeated taking individual scores on environment rating, social rating and governance rating as predictors. The authors further segregated the 122 selected firms into large, medium and low capital firms and assessed separate logistic regression models taking credit rating as the predicted variable and overall ESG score as the predictor.

It was found that overall ESG performance and performance of individual components (environment, social and financial variables such as market capitalization, and debt to equity ratio) had significant positive indicators of creditworthiness as measured through credit rating. Governance score had a positive and insignificant relation with credit rating. Market capitalization was observed to have significant direct relationship with credit worthiness. On the other hand, number of independent directors in companies showed significant inverse relationship with creditworthiness. ESG significantly impacted credit rating in the desired direction only for small- and middle-level firms; for large firms which already had higher credit rating, ESG showed no effect. It was also found that credit rating itself determined significantly the extent of overall ESG reporting and disclosure of its components.

This is unique study that covers the aspects of ESG reports and its impact on credit rating.

This article investigates the effectiveness of pepper spray as a means of aiding arrest. The authors aim to provide a more rigorous study than has previously been achieved. Data from the Baltimore County Police Department have been used in this analysis. The evaluation undertaken has taken into account the “effective‐ineffective” dichotomy of the incapacitating effects of pepper spray as well as whether those being arrested were drunk, under the influence of drugs or mentally disturbed. Five variables of age, weight, height, race and sex were also recorded, the latter three having little or no effect. The overall conclusion which is drawn is that using pepper spray eases arrest in the majority of instances. The conclusions drawn leave the way open for further detailed analysis of the use of the spray to ease arrest.

The objective of this study is to investigate the relationship between trade credit supply and financial distress outcomes, considering the role that trade credit plays as a substantial source of liquidity for distressed companies. Specifically, it examines whether there is an association between trade credit supply and the outcomes experienced by companies that undergo the voluntary administration (VA) insolvency procedure under Australian corporate law.

The study examines a sample of companies that were listed on the Australian Securities Exchange and entered VA between 2002 and 2019. Ordered logistic regression is used to determine the relation between trade credit and VA outcomes. The VA outcomes considered are as follows: (1) company liquidation, (2) orderly dissolution through an agreement with creditors, or (3) an agreement with creditors for reorganization of all or part of the company's business.

The findings show that trade creditors' willingness to supply credit is influenced by their rational expectations about the future prospects of financially distressed customers. Higher levels of trade credit and an increase in trade credit supply prior to VA are associated with a greater probability of achieving a reorganization versus a liquidation or dissolution outcome.

There is no apparent prior study investigating the connection between trade credit supply and outcomes for distressed companies entering insolvency administration. Therefore, this study provides novel evidence on the role of trade credit in the context of financial distress. Understanding the relationship between trade credit supply and outcomes is particularly significant considering that many jurisdictions offer distressed companies the opportunity to pursue reorganization under their insolvency laws. Examining financial distress and trade credit in the Australian creditor-friendly context expands on existing research. Prior research has predominantly relied on data from the United States, which has debtor-friendly bankruptcy law. Consequently, these studies may lack generalizability to jurisdictions with creditor-friendly law such as Australia.

This study examines, in a European context, whether a management-induced International Financial Reporting Standards (IFRS) accounting strategy is affected by national culture. It analyses the association between management's accounting strategy and Hofstede's cultural dimensions of individualism and uncertainty avoidance, as well as institutional and firm-specific factors.

Using hand-collected accounting decisions from 301 annual reports of firms from 14 European countries in 2017, a model is developed to identify two ordinally scaled accounting strategy variables, each representing the aggregated effect of the decisions on earnings and equity ratio. Afterwards, the effect of the cultural dimensions on these accounting-strategy variables is analysed by an ordered logistic regression.

The results do not support an association between management's accounting strategy and national culture, complementing the previous critical literature on values-based theories of culture. However, there is evidence that national legal enforcement, disclosure requirements and firm size explain differences in management's accounting strategy across countries.

Using the cultural value dimensions of the Global Leadership and Organizational Behavior Effectiveness (GLOBE) project, the findings are robust and stable. However, the study is limited to a European data set and the sample year.

This study contributes to the discussion on the transparency and comparability of IFRS accounting. The results imply that these issues are not affected by cultural differences but rather by differences in institutional and firm-specific factors. In order to bring about improvements, regulators should establish a uniform institutional setting, while the standard setter should reduce the number of implicit and explicit accounting choices embodied in the IFRS.

The paper advances the understanding of cultural influences on management's IFRS accounting behaviour by providing an alternative to the existing accruals approach.