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Aim of the paper is to analyse the occurrence of occupational stress across European Union countries, considering gender and job sustainability as determinants, with a specific attention to the effects of home-based work. Although COVID-19 pandemic has brought such issues into a novel spotlight, to detect the response pattern towards occupational stress we chose to employ the latest official data collected by the Sixth European Working Condition Survey developed and carried out in a pre-COVID-19 scenario. This information may provide a reliable picture of working conditions, which are likely to become the "new normal" across Europe, at least for a subset of workers. Descriptive analyses do not seem to help disclosing any different response behaviour with specific respect to reported stress by gender, even when combined with the condition of working from home. Whereas a noteworthy finding of our study is that results from the implemented ordered probit model display that some differences in the response pattern do exist and are even substantial. A question still arises about whether and to what extent hybrid forms of work are here to stay and even to grow in the post-pandemic period. Some of the critical features of teleworking-from-home emerged during the epidemic indicate that the implementation of policies at a national and, ideally, even supra-national level is clearly necessary. However, since both occupations and company organizations are strongly differentiated, it seems also that the enterprises are allowed some flexibility in defining corporate policies for teleworking practices, especially aiming at providing workers with improved and more sustainable working conditions, such as a less distressing environment and more supportive managerial styles. [ABSTRACT FROM AUTHOR]

Bayesian additive regression trees (BART) is a nonparametric model that is known for its flexibility and strong statistical foundation. To address a robust and flexible approach to analyse ordinal data, we extend BART into an ordered probit regression framework (OPBART). Further, we propose a semiparametric setting for OPBART (semi‐OPBART) to model covariates of interest parametrically and confounding variables nonparametrically. We also provide Gibbs sampling procedures to implement the proposed models. In both simulations and real data studies, the proposed models demonstrate superior performance over other competing ordinal models. We also highlight enhanced interpretability of semi‐OPBART in terms of inference through marginal effects. [ABSTRACT FROM AUTHOR]

This paper investigates the influence of physical activity on well-being. We use data from the Aspects of Daily Life survey provided by the Italian National Institute of Statistics, for the period 2013–2019. To capture the effect of sport participation on life satisfaction we face the problem of endogeneity. We solve this issue from a methodological point of view by using an instrumental variable (IV) ordered probit model, where the instrument has been identified in living nearby to an equipped green area. Our investigation suggests that physical activity is positively and strongly associated with life satisfaction, showing that the probability of being very happy is very high (70%) among individuals practicing sport regularly. For this reason, policies targeted at promoting and supporting sport practice play a key role in determining the subjective well-being of citizens. Our results also indicate a significant association between life satisfaction and gender, and between life satisfaction and inability to work, revealing the need to foster inclusive policies to reduce differences in well-being among groups of population. [ABSTRACT FROM AUTHOR]

Forensic firearms and tool mark examiners compare bullets and cartridge cases to assess whether they originate from the same source or different sources. To communicate their observations, they rely on predefined conclusion scales ranging from Identification to Elimination. However, these terms have not been calibrated against the actual strength of the evidence except indirectly through error rate studies. The present research reanalyzes the findings of firearms and cartridge case comparisons from error rate studies to generate a quantitative measure of the strength of the evidence for each comparison. We use an ordered probit model to summarize the distribution of responses of examiners and aggregate the data for all comparisons to produce a set of likelihood ratios. The likelihood ratios can be as low as less than 10, which does not seem to justify the current articulation scale that may imply a strength of evidence of 10,000 or greater. This suggests that examiners are using language that overstates the strength of the evidence by several orders of magnitude. [ABSTRACT FROM AUTHOR]

Abstract Using a mixed research design, the overall objective of this study is to investigate the profiles of child labour in Ethiopia’s districts of Raya-Kobo and Angot. The study’s specific objectives are to examine types of activities and prevalence of child labour, to identify the children’s working contexts, and to evaluate the extent of harm children face in workplaces. The study hypothesizes the existence of significant variations in the profiles of child labour (activity types, prevalence rates, settings, and level of harm to children) as a result of several circumstances. While survey methodology was used to collect primary data from 431 randomly selected respondents, desk review and document analysis were also used to gather secondary data. The sampling procedures used include multi-stage purposive and systematic random sampling. Descriptive and inferential (Ordered Probit Regression model) methods of data analysis are utilized to analyze the data. The results of the descriptive analysis demonstrate a high incidence and magnitude of child labour, as well as children’s early entry to work. The regression analysis reveals children’s exposure to high levels of harm at work, which is directly exacerbated by household age, income diversification, land fragmentation, livestock number, shocks, and the predicted value of remittances. Contrarily, access to rural transportation, household heads’ education level, cart ownership, and family size reduce children’s harm extent while working. The study highlights the need to design strategies for age-appropriate work to protect children from hazardous and high-intensity activities, undertake community awareness campaigns about the impact of child labour on children, and strengthen local stakeholders’ capacity. Additionally, connecting rural areas and farmers’ croplands to towns or major routes via repaired or new roads would be beneficial.

This study examines the association between listening to music at home and subjective well-being, using data from 14,162 respondents in the China General Social Surveys conducted in 2015, 2017, and 2021. Among the respondents, the average happiness score was 3.958. Regression analyzes indicate that frequent music listening is significantly associated with higher happiness levels, with coefficients of 0.384 in the baseline model and 0.570 in the model with control variables. Robustness checks performed across different models support these findings. Instrumental variable analysis, using Mandarin proficiency, yielded a coefficient of 0.212, indicating a robust association despite a slight reduction in magnitude. Heterogeneity analyzes showed consistent associations across genders, religious beliefs, and regions, with slightly stronger associations observed for females and non-religious individuals. Mediation analysis identified mental health and class identity as significant mediators, contributing to a total association of 0.146. These results highlight the positive correlation between music listening and well-being, suggesting the potential value of integrating music resources into well-being strategies. [ABSTRACT FROM AUTHOR]

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• Collected people's opinions regarding CAV safety with field experiments. • Revealed people's opinions will change when a successful CAV ride is provided. • Studied factors related to people's initial opinions and opinion changes with a set of statistical models. • Provide managerial and regulatory insights for implementing and popularizing CAV technologies. Connected and autonomous vehicles (CAVs) are considered one of the most promising mobility technologies to be implemented in the near future. A recent study (Shi et al. 2021) investigated how riding experience influences perceptions of autonomous vehicle safety through field experiments. This study used the same dataset as Shi et al. (2021) but focused on investigating the factors influencing people's initial opinions toward CAV safety and how these opinions will change following a successful CAV ride. A random parameter ordered probit model was adopted to analyze people's initial opinions before the CAV ride, which resolves the fixed parameter estimations limitation of the traditional ordered probit model. Furthermore, a hierarchical ordered probit model was used to study people's opinion changes after experiencing the CAV ride, overcoming the fixed thresholds limitation of the traditional ordered probit model. Based on the estimation results, we identified the characteristics of prospective CAV users, such as individuals who drive alone, have Auto Pilot ride experience, have high income, have a long commute time, and have high education levels. Therefore, the needs of these demographics should be well considered in future CAV technology development. We also found that high-education individuals tend to have more negative initial opinions regarding CAV safety compared with others. However, their opinions are more likely to shift toward the positive side after experiencing a successful test ride. In addition, we found that although CAV technologies can enhance traffic efficiency through communication with traffic signals, this improvement may raise people's concerns about the safety of CAVs. The results obtained from this research provide valuable managerial and regulatory insights for the future development and popularization of CAV technologies. [ABSTRACT FROM AUTHOR]

Climate change and its negative impacts pose a threat to crop production in Kenya. However, climate change adaptation strategies have the potential to address the challenges faced by crop farmers. Despite this, there is limited literature to inform policy on the best interventions to help farmers deal with climate issues. This study assessed the determinants of climate change adaptation strategies and the intensity of their use among 723 crop farmers in Busia County, Kenya, selected through a multistage sampling technique. Data were collected using a structured questionnaire and analyzed using principal component analysis (PCA), multinomial logit regression, and the ordered probit model. The climate change adaptation strategies were categorized into crop diversity, cover crops, use of drought-resistant crops, and irrigation. According to the results, the factors contributing to the uptake of the different adaptation strategies were age, household size, access to credit, training access, off-farm income, group membership, frequency of receiving climate change information, and extension services. The major factors influencing the uptake of multiple climate change adaptation strategies were access to credit and off-farm income. The study shows that certain adaptation strategies, such as using cover crops, do not require credit and offer an important option in an environment with limited resources. On the other hand, adaptation measures such as irrigation demand financial resources for farmers to implement them, highlighting the importance of information and awareness in adopting adaptation strategies and the supportive role of financial resources, particularly for adopting multiple strategies. Therefore, this study suggests implementing policies and interventions that encompass knowledge-based strategies such as extension services, training, climate change education, group participation, and financial mechanisms like income generation activities and access to credit. These integrated strategies will enable farmers to adopt various climate change adaptation methods for sustainable crop production. [ABSTRACT FROM AUTHOR]

Using a mixed research design, the overall objective of this study is to investigate the profiles of child labour in Ethiopia's districts of Raya-Kobo and Angot. The study's specific objectives are to examine types of activities and prevalence of child labour, to identify the children's working contexts, and to evaluate the extent of harm children face in workplaces. The study hypothesizes the existence of significant variations in the profiles of child labour (activity types, prevalence rates, settings, and level of harm to children) as a result of several circumstances. While survey methodology was used to collect primary data from 431 randomly selected respondents, desk review and document analysis were also used to gather secondary data. The sampling procedures used include multi-stage purposive and systematic random sampling. Descriptive and inferential (Ordered Probit Regression model) methods of data analysis are utilized to analyze the data. The results of the descriptive analysis demonstrate a high incidence and magnitude of child labour, as well as children's early entry to work. The regression analysis reveals children's exposure to high levels of harm at work, which is directly exacerbated by household age, income diversification, land fragmentation, livestock number, shocks, and the predicted value of remittances. Contrarily, access to rural transportation, household heads' education level, cart ownership, and family size reduce children's harm extent while working. The study highlights the need to design strategies for age-appropriate work to protect children from hazardous and high-intensity activities, undertake community awareness campaigns about the impact of child labour on children, and strengthen local stakeholders' capacity. Additionally, connecting rural areas and farmers' croplands to towns or major routes via repaired or new roads would be beneficial. [ABSTRACT FROM AUTHOR]

Agriculture is a key sector in many African economies, making access to accurate agricultural information vital for boosting productivity. This study investigated the factors influencing smallholder farmers’ access to agricultural information in the East Gojjam zone of Amhara, Ethiopia. A cross-sectional survey of 403 households was conducted, and data were analyzed using Stata software with the Ordered Probit model. The study found that farmers’ access to agricultural information is significantly influenced by factors such as experience, exposure to electronic and printed media, farm size, access to extension services, input availability, market distance, proximity to development centers, and participation in Farmer Training Centers (FTC). Major constraints to information access included inadequate government policies, insufficient extension services, limited information sources, poor infrastructure, network issues, and a lack of effective knowledge exchange. The study recommends that smallholder farmers increase exposure to various media channels and participate in FTC programs. Additionally, the Ethiopian government should prioritize infrastructure improvements (mobile networks, roads, and electricity), expand extension services, and diversify information sources to improve farmers’ access to relevant agricultural knowledge. Addressing these barriers will help enhance agricultural productivity in the study area.

Per- and polyfluoroalkyl substances (PFAS) are forever chemicals that have been used for their heat, grease, and water-resistant properties on disposable dinnerware. However, PFAS pose risks to human health and the environment and alternative treatments are currently being implemented in the disposable dinnerware industry, including bio- or plant-based treatments. To date, consumer perceptions of the practical usage and environment-related attributes of PFAS versus plant-based alternative treatments have not been addressed. An online survey elicited 1304 U S. consumers' perceptions of the attributes from each treatment and factors impacting those perceptions. On average, participants purchased disposable plates 13 times per year with 50 % ± 50 purchasing them for everyday use. Approximately 20 % ± 40 of the sample had heard of PFAS prior to the study while 62 % ± 49 had heard of bio-based products. In general, PFAS treatments were perceived as performing slightly better in the practical usage attributes (i.e., grease resistant, water resistant, durable); however, the plant-based alternative treatments were perceived as more environmentally friendly (i.e., better for the environment, better for personal health, recyclable, compostable). Older participants viewing plant-based treatments as better at grease resistance, water resistance, durability, and microwavable relative to younger participants. Conversely, people with higher education levels viewed plant-based treatments as less resistant to grease but more durable. Interestingly, participants’ perceptions and existing knowledge of PFAS and bio-based products influenced their perceptions of plant-based treatments being more environmentally friendly. Results provide insights for industry stakeholders as they move forward in implementing PFAS alternative treatments.

While Saudi coffee (SC) holds deep cultural and historical significance within the Kingdom, rising global exposure and modern coffee shops are driving domestic consumers toward other coffee (OC) varieties. In this context, this study has two objectives: First, to segment the coffee market and analyze how consumer characteristics vary among its components, and second, to estimate the coffee expenditure function. The study data were collected through our custom online survey. We employed a multinomial probit model to estimate choices within the identified market segments of individuals consuming: (1) SC, (2) OC varieties, such as American or Turkish coffee and (3) Both Saudi and OC types. Additionally, we applied an ordered probit model to estimate coffee-related expenditure. The results offer valuable insights for marketing and policy considerations relevant to the concurrent government’s efforts as consumers are increasing their consumption of OC types.

AbstractDue to the high emissions produced by the transport sector, one of the most implemented initiatives in developed countries in the last decade is the electrification of the public transport fleet and the private vehicle fleet. The purchase of electric and hybrid vehicles in developing countries is negligible compared to developed countries and little has been indicated about the characteristics of potential buyers of this type of technology. In this paper, we aim to cover this aspect. Chile is a good case to study, as it is an emerging country with the highest level of penetration of electric and hybrid vehicles in the market and with better import scenarios according to the free trade agreements signed with the USA, Europe, and Asia. The results show that the socio-demographic characteristics with the greatest impact on the likelihood of purchasing low-emission vehicles, in the absence of any incentives, are household size, educational level, and gender. Particularly the marginal effects indicate that of the individuals surveyed who belong to a two-person household, they are 9% more likely to choose to buy a low-pollution vehicle compared to single people, and 8.96% less likely to choose a high-pollution vehicle compared to a single person.

Despite the beneficial effects of cocoa agroforestry on cocoa production and yield levels, adoption is below expectation while the factors driving adoption are not well known. This study therefore explored the typology of cocoa agroforestry (AF) in Ghana and the drivers of adoption using cross-sectional data from cocoa producers in Ghana’s Sefwi Wiawso Municipal. A 5-point Likert scale was used to analyze farmers’ perceptions of cocoa AF while an ordered probit model was applied to assess the factors influencing adoption of cocoa AF. The study revealed that the cocoa landscape in the study area consisted of 7.51% full sun, 31.62% low shade, 30.83% medium shade and 30.04% high shade. Moreover, adoption of cocoa AF was influenced by farmer characteristics (such as sex, farming experience, and household size), farm-specific factors (such as total farm size, number of cocoa farms), and institutional factors (such as involvement in off-farm work, participation in AF training, farmer association membership, and participation in cocoa hand pollination exercise. The most important constraint affecting cocoa AF adoption is poor communication of the benefits of shade trees on cocoa farming. We conclude that farmers are indifferent to the adoption of the AF systems, while the adoption determinants vary across the typology of AF systems. The authors recommend provision of effective training of farmers on cocoa AF to increase adoption. Also, the benefits of cocoa AF should be effectively communicated to farmers via appropriate communications channels such as cooperative groups and farmers’ fora to enhance adoption of the technology.

AbstractPrevious studies on green bonds (GBs) in China have not extensively analyzed how investor characteristics such as demographic background and environmental concerns affect Chinese investors’ decisions to invest in GBs. Therefore, these aspects should be examined to understand the GB market and its potential expansion. To address this gap, this study analyzed how Chinese institutional investors’ social attributes, environmental concerns, and residential locations affect their decisions to purchase GBs. The ordered-probit model estimation revealed that experience in investing in GBs and high environmental awareness lowers the yield required for institutional investors to invest in GBs, suggesting that these factors increase investors’ willingness to pay (WTP) for GBs. The study also finds that investors in Shanghai have a higher WTP for GBs than those in Beijing and Shenzhen. The results provide important insights for the government and financial authorities to implement measures aimed at increasing institutional investors’ interest in the environment. Additionally, these results can drive GB issuers to promote sales to institutional investors with an environmental focus.

IntroductionConsidering the current process of destruction of natural resources in the country and the problems faced by the present and future generations, the measures taken in the field of conservation and restoration and development of natural resources do not seem to be enough. Although, to solve these problems, the role of the government as a planner and supporter of natural resources projects is clear and important (Arayesh & Farajilah Hosseini, 2010). However, the projects designed to conserve natural resources are implemented based on people's participation. In general, people's participation in projects in the field of natural resources protection can take place in various fields. The most important of these issues have been considered in the behavioral examples of the Helpers of Nature project which can be including planting seedlings, people's participation in times of crisis such as fire, protection of forests, contributing to environmental protection associations, joining environmental associations, waste management in terms of separation and volume, joining the natural resources projects through the organization's systems, introducing people to the natural resources organization in the form of nature's helper, paying the green tax and etc (Natural resources & watershed management organization-I.R of IRAN, 2023). However it is the question as how to attract people's participation in the mentioned issues requires tools that can influence human behavior. Behavioral economics, as a new scientific field of economic sciences, can measure and analyze the impact of intentions, beliefs, and motivations on human behavior and decisions, and based on this, it can also provide policy tools (Asgari et al., 2021). For this reason, it can influence people's behavior to participate in the conservation of natural resources using behavioral economics approach. Therefore, to realize the goal of attracting people's participation, the current study considers to examine nudges and the effectiveness of nudges on people's behavior using behavioral economics approach Materials and MethodsThe sampling method of the research is convenience sampling. The number of samples is 213 people using the online questionnaire in two separate groups. This study is a quasi-experimental design and its type is a comparison between two groups. The number of the control group includes 108 people and the number of the treatment group includes 105 people. The control and treatment groups were independent. Each of the groups had completely common questions and response criteria. In this study, the control and treatment groups did not receive any training, but only the treatment group was given additional information about cognitive errors along with related questions. First, the Mann-Whitney-Wilcoxon test is used to check and compare the ratings regarding supplementary information as well as the answers of people in the two groups. The ordered probit regression is used to analyze the relationship between ordinal or ranked dependent variables related to natural resource protection behavior and independent treatment (nudge) variables and other variables. For the relative dependent variables (the time of registration of cooperation request and the number of people introduced as a nature helper), the ordinary least square regression is used to analyze the effect of the treatment binary variable on the people's behavior in the field of natural resources conservation Results and DiscussionThis study results showed that out of 19 nudges, 14 nudges includes; Normative default, time limit, anchor and exemplify, carrot and stick, personalization, decoy effect, authority confirmation bias, bandwagon effect, present bias, automatic recommendation, halo effect and ownership effect (1) and (2) and (3) had a significant impact on these people's behavior, respectively, the number of seedlings, the time of registering a request for cooperation, participation in firefighting, waste production, the number of members introduced as a nature’s helper, choosing tasks, membership in associations, membership in a special association, recycling, people's action preferences for forest protection, the percentage of perceived success for projects, willingness to spend taxes to beautify one's neighborhood, willingness to spend taxes to protect forests in one's area, and applying zoning to protect forests. The direction of influence in all nudges (except for the normative default and time limit) on people's behavior has been positive and significant. The marginal effects also showed that all nudges had the positive effect (with ordinal or ranked dependent variable) on the selection of the target option(s) in the treatment group compared to the control group. The carrot and stick policy had no significant effect on the ordinal variable of waste production, but the effect of this nudge on dummy variable of waste production was significant, This means that this nudge has had a positive and significant effect on maintaining the existing situation (garbage collection every day of the week) and reducing the amount of garbage (choosing 20 kg of garbage and less per week). The normative default and the time limit had a negative and significant effect (respectively) on the number of seedlings and the registration time of cooperation requests for planting seedlings. These negative effects have also confirmed the positive effect of nudging on people's behavior. Although the normative default resulted in fewer seedlings being planted by individuals, this occurred because the default was set at a minimal level and individuals were significantly more inclined to follow the default. The nudge of the time limit also led to a reduction in the time to register cooperation requests by individuals, so that people tended to register their request faster. ConclusionAccording to the results of this research, to attract the people's participation in the conservation of natural resources, these following should be considered: defaults, low-cost anchors, clear examples, incentives and punishments, highlight individual performance through personalization, using existing privileges for more cooperation, confirming people's sovereignty, presenting reports during performance, immediate rewards, making SMS and telephone systems available to compensate for people's lack of action, considering time limits for registering people in programs and projects, providing success reports to join people in an action, applying people's ownership of the green tax to further encourage them to pay taxes, allocating each zone to an environmental association for forests protection.

Introduction Considering the current process of destruction of natural resources in the country and the problems faced by the present and future generations, the measures taken in the field of conservation and restoration and development of natural resources do not seem to be enough. Although, to solve these problems, the role of the government as a planner and supporter of natural resources projects is clear and important (Arayesh & Farajilah Hosseini, 2010). However, the projects designed to conserve natural resources are implemented based on people's participation. In general, people's participation in projects in the field of natural resources protection can take place in various fields. The most important of these issues have been considered in the behavioral examples of the Helpers of Nature project which can be including planting seedlings, people's participation in times of crisis such as fire, protection of forests, contributing to environmental protection associations, joining environmental associations, waste management in terms of separation and volume, joining the natural resources projects through the organization's systems, introducing people to the natural resources organization in the form of nature's helper, paying the green tax and etc (Natural resources & watershed management organization-I.R of IRAN, 2023). However it is the question as how to attract people's participation in the mentioned issues requires tools that can influence human behavior. Behavioral economics, as a new scientific field of economic sciences, can measure and analyze the impact of intentions, beliefs, and motivations on human behavior and decisions, and based on this, it can also provide policy tools (Asgari et al., 2021). For this reason, it can influence people's behavior to participate in the conservation of natural resources using behavioral economics approach. Therefore, to realize the goal of attracting people's participation, the current study considers to examine nudges and the effectiveness of nudges on people's behavior using behavioral economics approach Materials and Methods The sampling method of the research is convenience sampling. The number of samples is 213 people using the online questionnaire in two separate groups. This study is a quasi-experimental design and its type is a comparison between two groups. The number of the control group includes 108 people and the number of the treatment group includes 105 people. The control and treatment groups were independent. Each of the groups had completely common questions and response criteria. In this study, the control and treatment groups did not receive any training, but only the treatment group was given additional information about cognitive errors along with related questions. First, the Mann-Whitney-Wilcoxon test is used to check and compare the ratings regarding supplementary information as well as the answers of people in the two groups. The ordered probit regression is used to analyze the relationship between ordinal or ranked dependent variables related to natural resource protection behavior and independent treatment (nudge) variables and other variables. For the relative dependent variables (the time of registration of cooperation request and the number of people introduced as a nature helper), the ordinary least square regression is used to analyze the effect of the treatment binary variable on the people's behavior in the field of natural resources conservation Results and Discussion This study results showed that out of 19 nudges, 14 nudges includes; Normative default, time limit, anchor and exemplify, carrot and stick, personalization, decoy effect, authority confirmation bias, bandwagon effect, present bias, automatic recommendation, halo effect and ownership effect (1) and (2) and (3) had a significant impact on these people's behavior, respectively, the number of seedlings, the time of registering a request for cooperation, participation in firefighting, waste production, the number of members introduced as a nature's helper, choosing tasks, membership in associations, membership in a special association, recycling, people's action preferences for forest protection, the percentage of perceived success for projects, willingness to spend taxes to beautify one's neighborhood, willingness to spend taxes to protect forests in one's area, and applying zoning to protect forests. The direction of influence in all nudges (except for the normative default and time limit) on people's behavior has been positive and significant. The marginal effects also showed that all nudges had the positive effect (with ordinal or ranked dependent variable) on the selection of the target option(s) in the treatment group compared to the control group. The carrot and stick policy had no significant effect on the ordinal variable of waste production, but the effect of this nudge on dummy variable of waste production was significant, This means that this nudge has had a positive and significant effect on maintaining the existing situation (garbage collection every day of the week) and reducing the amount of garbage (choosing 20 kg of garbage and less per week). The normative default and the time limit had a negative and significant effect (respectively) on the number of seedlings and the registration time of cooperation requests for planting seedlings. These negative effects have also confirmed the positive effect of nudging on people's behavior. Although the normative default resulted in fewer seedlings being planted by individuals, this occurred because the default was set at a minimal level and individuals were significantly more inclined to follow the default. The nudge of the time limit also led to a reduction in the time to register cooperation requests by individuals, so that people tended to register their request faster. Conclusion According to the results of this research, to attract the people's participation in the conservation of natural resources, these following should be considered: defaults, low-cost anchors, clear examples, incentives and punishments, highlight individual performance through personalization, using existing privileges for more cooperation, confirming people's sovereignty, presenting reports during performance, immediate rewards, making SMS and telephone systems available to compensate for people's lack of action, considering time limits for registering people in programs and projects, providing success reports to join people in an action, applying people's ownership of the green tax to further encourage them to pay taxes, allocating each zone to an environmental association for forests protection. [ABSTRACT FROM AUTHOR]

Household food insecurity persists in the KwaZulu-Natal Province, South Africa, despite the significant contribution of agriculture to the country's economy. The role that the combination of crop production systems and value chains can play in improving household food security has yet to be addressed. This paper examines the combined effects of crop production systems and value chains on household food insecurity. A Principal Component Analysis (PCA) transformed the correlated variables into three distinct domains, namely, modern agro-production practices, sustainable market integration, and traditional knowledge. An Ordered Probit Analysis was used to determine the factors that influence household food insecurity. Household food insecurity was measured using the Household Food Insecurity Access Scale (HFIAS) using 300 randomly selected smallholder farmers. The results showed that sustainable market integration, traditional knowledge focus, education, and livestock ownership significantly and negatively impact a household's food insecurity. A household's size, food expenditure, and cash credit, as well as floods, significantly and positively affect its food insecurity. Policymakers and stakeholders should prioritise the integration of a sustainable market and the preservation of traditional knowledge, while reducing the food costs, in order to combat household food insecurity. [ABSTRACT FROM AUTHOR]

South Korea has legislated "2050 carbon neutrality" in 2021 and is currently implementing it, and debate is brewing over which to focus on as the main means of achieving it in the power generation sector: renewable energy (RE) or nuclear power (NP). This article aims to collect and analyze data on the public preference for RE versus NP. In a national survey of 1000 people, respondents were first asked which was preferred, RE or NP, and then asked to indicate the preference intensity along a 5-point scale. Of all the respondents, 60.3% preferred RE and 27.7% preferred NP. The preference for the former was about 2.2 times more than that for the latter. However, the intensity of the preference for NP was 1.3 times more than that for RE. Both the two-limit Tobit model and ordered probit model have been applied to analyzing the factors influencing the preference. The effects of some variables on the preference for RE over NP are explained, and implications from this are discussed. The findings can be used as a reference to determine the main means of implementation of carbon neutrality or to increase the public acceptance of the specified means. [ABSTRACT FROM AUTHOR]

Climate change and its negative impacts pose a threat to crop production in Kenya. However, climate change adaptation strategies have the potential to address the challenges faced by crop farmers. Despite this, there is limited literature to inform policy on the best interventions to help farmers deal with climate issues. This study assessed the determinants of climate change adaptation strategies and the intensity of their use among 723 crop farmers in Busia County, Kenya, selected through a multistage sampling technique. Data were collected using a structured questionnaire and analyzed using principal component analysis (PCA), multinomial logit regression, and the ordered probit model. The climate change adaptation strategies were categorized into crop diversity, cover crops, use of drought-resistant crops, and irrigation. According to the results, the factors contributing to the uptake of the different adaptation strategies were age, household size, access to credit, training access, off-farm income, group membership, frequency of receiving climate change information, and extension services. The major factors influencing the uptake of multiple climate change adaptation strategies were access to credit and off-farm income. The study shows that certain adaptation strategies, such as using cover crops, do not require credit and offer an important option in an environment with limited resources. On the other hand, adaptation measures such as irrigation demand financial resources for farmers to implement them, highlighting the importance of information and awareness in adopting adaptation strategies and the supportive role of financial resources, particularly for adopting multiple strategies. Therefore, this study suggests implementing policies and interventions that encompass knowledge-based strategies such as extension services, training, climate change education, group participation, and financial mechanisms like income generation activities and access to credit. These integrated strategies will enable farmers to adopt various climate change adaptation methods for sustainable crop production.

A growing body of literature discusses food insecurity in rural and urban contexts in Sub-Saharan Africa (SSA). Peri-urban food insecurity and coping strategies remain an understudied topic. To fill this gap, household cross-sectional survey data was collected from randomly selected 300 farm households in the peri-urban area of Jimma City and complemented with key informant interviews (KIIs) and focus group discussions (FGDs) to assess their food insecurity status and coping strategies in the face of rapid urbanization. A structured questionnaire was used to collect quantitative data from farm households while an unstructured questionnaire was used to gather qualitative data from key informants. Twelve indicators involving the four food insecurity dimensions were identified to develop a food insecurity index and categorize households into four food insecurity levels. The Principal Component Analysis (PCA) is employed to determine the most important indicators of household food insecurity. The ordered probit regression model was employed to ascertain significant factors affecting farming household food insecurity. The results revealed that 46% of peri-urban farm households were food-insecure at various levels. The household food insecurity status varied with their level of human capital, physical endowments, risk aversion behaviour, and institutional barriers. The expansion of built-up areas and marketable crops, particularly eucalyptus trees have greatly affected the food security status of peri-urban farm households. Income diversification, farming diversification, social ties, and farming specialization were the main food insecurity coping strategies of peri-urban farm households. The findings of this study highlighted insights into the urban expansion of medium-sized cities and agricultural land loss, marginalization of staple food crops, and market food prices increase, which resulted in increased vulnerability to food insecurity and poverty among farm households in peri-urban areas. The recommendations drawn from these findings are formulating strategies that preserve agricultural land-use and promoting food insecurity mitigation programs that capitalize on the coping strategies of households in peri-urban areas in the face of rapid urbanization.

This study aims to investigate the influence of pre-entrepreneurial career mobility frequency and job changes among returning migrant workers (RMWs) on the innovation level of enterprises, with a particular focus on the mediating role of urban social capital accumulated by RMWs. Using data from the “current entrepreneurial status of RMWs”, we applied an ordered probit model to validate our hypotheses. To address endogeneity, a recursive bivariate probit model was used, and stepwise regression combined with bootstrap methods was employed to ascertain the mediating influence of urban social capital. Our results demonstrate a significant positive correlation (P

This study examines the association between listening to music at home and subjective well-being, using data from 14,162 respondents in the China General Social Surveys conducted in 2015, 2017, and 2021. Among the respondents, the average happiness score was 3.958. Regression analyzes indicate that frequent music listening is significantly associated with higher happiness levels, with coefficients of 0.384 in the baseline model and 0.570 in the model with control variables. Robustness checks performed across different models support these findings. Instrumental variable analysis, using Mandarin proficiency, yielded a coefficient of 0.212, indicating a robust association despite a slight reduction in magnitude. Heterogeneity analyzes showed consistent associations across genders, religious beliefs, and regions, with slightly stronger associations observed for females and non-religious individuals. Mediation analysis identified mental health and class identity as significant mediators, contributing to a total association of 0.146. These results highlight the positive correlation between music listening and well-being, suggesting the potential value of integrating music resources into well-being strategies.

There is a lack of studies investigating household water consumption while considering the possible heterogeneity in the observed data and its temporal instability, often resulting in inconsistent and biased parameter estimations and, as a result, inaccurate forecasting of household water consumption. To address these constraints, the current study investigates temporal shifts in the household water consumption pattern and the effects of different socioeconomic factors on forecasting household water consumption. Using the results of a household survey performed seasonally in three major cities in Northern Jordan over a 4-year period, separate seasonal models of water consumption are estimated using three alternate modeling approaches to account for possible unobserved heterogeneity. Likelihood ratio tests were performed to investigate the temporal stability of the models' estimations over different seasons across the 4-year period. The findings of these tests indicated that the data are temporally stable over two datasets (the summer and winter seasons). Also, the findings revealed that household water consumption is influenced by a variety of factors, with the impact of many of these factors varying across observations. Finally, the findings highlight the need for additional research into how unobserved heterogeneity can be best modeled in temporal contexts for accurate water consumption forecasting. HIGHLIGHTS This study provides a framework for investigating the impact of socioeconomic factors on household water consumption while accounting for possible unobserved heterogeneity in temporal contexts.; Separate seasonal models of water consumption are estimated using three alternate statistical modeling approaches to account for possible unobserved heterogeneity and data temporal instability.;

Mango is one of the most traded, exported, and consumed tropical fruits worldwide. However, little is known about Italian consumers’ preferences for mango. This study empirically explores the factors that influence the consumption of mango in Italy. Food values, subjective and objective knowledge, and socio-demographic aspects were considered. An online survey was administered, resulting in an overall sample of 487 Italian participants. The data were statistically analysed through an ordered probit model. The results show that mango is more likely to be consumed by individuals who are more concerned with the naturalness of the product. Moreover, both subjective and objective knowledge positively affect the probability of consuming mango. The findings also show that socio-demographic traits, particularly gender and undertaking sports activities, significantly influence the probability of consuming mango. Practical implications are proposed based on the study findings.

In the research, socio-economic and demographic factors affecting the fish consumption amount of consumers in Iğdır province were tried to be determined. The main material of the research is the survey data obtained from 325 consumers residing in the province of Iğdır and determined by using the commensurate sampling method. In the research, the factors affecting the fish consumption amount of the consumers were analyzed with the sequential probit model. In the sequential probit model created, the fish consumption levels of the consumers were used as the addict variable, and the inaddict variables were determined as gender, income level, frequency of fish consumption, type of fish consumed, annual red meat consumption and type of fish consumption. The model results; The variables of gender, income level, frequency of fish consumption, type of fish consumed, annual red meat consumption and fish consumption pattern were all found to be statistically significant. According to the ordinal probit model results, it was determined that the gender of the consumer decreased the fish consumption level. As expected in the research, it was defined that there was a negative relationship between income level and fish consumption level, and a positive relationship between fish consumption frequency and consumption amount. With respect to the model conculsions, it was defined that there is a positive relationship between the amount of red meat consumption of consumers and the amount of fish consumption. [ABSTRACT FROM AUTHOR]

The scourge of poverty has spread over Nigeria. Efforts to address the problem have yielded no tangible results. This study investigated a gendered approach to determinants of adoption of cassava-legume intensification technology and its impact on households' poverty status in innovation platforms. A multistage sampling technique was used in selecting 160 respondents. The adoption index, the Tobit regression model, FGT analysis, and the ordered probit regression model were used to analyze the data. The adoption intensity of cassava-legume intensification technology was relatively low (28.06%), with that of female gender households 3.20% higher than that of their male counterparts. The Tobit regression model revealed that the intensity of adoption of cassava-legume technology was positively and significantly influenced by the years of education, household size, credit accessibility and household gender participation, among other factors. In addition, the ordered probit regression model revealed that revenue generated from cassava-legume, adoption intensity of the technology, extension visits, and gender of the household head were significant factors positively affecting household poverty while household size negatively affected household poverty. This indicates that cassava-legume intensification technology can assist individuals in escaping poverty. Gender sensitivity should, however, be considered when adopting new technologies, and an enabling atmosphere should be developed to enable women to participate. [ABSTRACT FROM AUTHOR]

Enhancing corporate social mobility is of great practical importance for improving economic dynamism. There are new institutional arrangements in place to optimize construction land structure, i.e., construction land reduction. The impact of institutional arrangements on corporate social mobility has not yet been explored in academia. There is also a lack of academic discussion on how to enhance corporate social mobility. This paper investigates the impact of institutional arrangements on corporate social mobility using construction land reduction as an example. The following findings are discussed: (1) Construction land reduction is an important institutional arrangement for solving problems of inefficiencies such as inefficient corporates, the transfer of inefficient construction land, spatial quotas' allocation, and macro use conversion. (2) Construction land reduction significantly promotes corporate social mobility. (3) Compared to non-cadre residents, cadres perceive greater corporate social mobility. (4) Compared to planned incremental-type areas, planned decremental-type areas are the key areas for construction land reduction, which can free up more space for construction land and is more conducive to improving corporate social mobility. Accordingly, policy implications are proposed to improve construction land reduction policies and promote corporate social mobility. [ABSTRACT FROM AUTHOR]

This study analyzes the impact on the sustainability performance of firms during the outbreak of the COVID‐19 pandemic, based on microdata made available by the World Bank through the Enterprise Surveys platform. By employing econometric estimation techniques like multinomial limited dependent variable model alongside data visualization tools, this analysis provides insights into the effects of the pandemic outbreak, as well as the moderating influence of enterprise innovation levels and CSR. The findings highlight that the duration of firm operations and company size play significant roles in mitigating turnover during the initial response to the pandemic. The analysis evaluates the actions taken by companies and governments to navigate the crisis, one and a half years after its appearance: containing the impact has a strong social impact, related to corporate social responsibility. The companies that successfully contained the shock and recovered more quickly are those that relied on innovation through their private investments or government measures. The analysis reveals how evenly distributed government subsidies have failed to produce significant effects. [ABSTRACT FROM AUTHOR]

AbstractBuffer stock intervention is a hedging policy against income losses due to price fluctuations, primarily from farming activities, notably the production of cereals. This paper investigates the impact of buffer stock intervention on smallholder farmers’ food security in Ghana. To this end, the motivation was to estimate the nutrient-content household dietary diversity index (NHDDI) based on a cross-sectional data set. We apply Coarsened Exact Matching, Weighted Least Squares, and Weighted Ordered Probit analysis as econometric methods. We find that marital status, gender, education, and income positively impact food security, while the household size and the number of children under five years old have a negative impact. We also find that income and education, which have a positive direct impact on food security, have a mitigating effect on the negative impact of children under five years. The most important finding is that participation in the buffer stock operations improves the household food security of participating smallholder farmers. NAFCO in its present form has positive effects on food security for participants, positive but smaller price effects for non-participating smallholder farmers, and negative effects for consumers at large. The latter effect could be reduced by implementing a buffer stock policy consisting of buying during the glut and selling when supply is tight.

Based on the survey report by the United Nations Sustainable Development Solutions Network (SDSN) and Ipsos Group, the world ranking of Chinese people’s happiness shows a significant gap. This study attempts to analyze the subjective well-being of Chinese residents through public database from the China Household Finance Survey Center in 2017. An ordered Probit model is constructed to investigate the impact of non-monetary factors, specifically basic public services, on the subjective well-being of Chinese people. The results indicate that: (1) The subjective well-being of Chinese residents is found to be lower than what the survey report indicated. (2) Basic public services have a significant positive impact on residents’ happiness. (3) Social trust played a moderating role, positively influencing the relationship between basic public services and residents’ happiness. (4) The impact of basic public services on happiness varied significantly depending on factors such as age, registered residence, and places of residence. To enhance the happiness of Chinese residents, it is recommended to focus on improving the equalization of basic public services and establishing a robust basic public service system. These measures can effectively contribute to the overall well-being and happiness of the population.

Road users’ safety at railroad grade crossings (RRGCs) is one of the most demanding concerns, because the majority of RRGC accidents are fatal in nature. These accidents are mainly caused by collisions between road users and trains, principally due to road users’ violation. In general, road users commit violations either individually or in groups. Moreover, they have a pattern of committing violations regularly or only on occasion, and a fraction of them may be nonviolators. The current study attempts to figure out the factors that are linked to such behavior, as well as the probable causes of violation. In this context, a comprehensive survey was undertaken at 21 RRGCs throughout nine Indian states, yielding a total of 7,208 responses. Descriptive statistical analysis was carried out using this database, and separate ordered probit models for individual and group violations were developed. The findings demonstrated that a number of socioeconomic factors, triprelated factors, and behavioral factors significantly impact the violations (individual and group) at RRGCs. On the other hand, gender, education level, and trip type were found to be insignificant factors for group violations. Engagement in secondary activities followed by crossing speed tendency projects a strong correlation with violations among all the factors. The reason for such risk-taking behavior is revealed to be excessive waiting time, followed by habit, social impact, inadequate knowledge, and attitude. These findings are useful for planners and policymakers in determining viable interventions to enhance safety at RRGCs, particularly in developing nations like India. [ABSTRACT FROM AUTHOR]

This study aimed to examine postharvest losses encountered by banana cultivators in the northeastern Indian states of Assam and Meghalaya across three discrete temporal phases: prior to the onset of COVID-19, during the COVID-19 pandemic, and in the aftermath of COVID-19. A total of 100 households, distributed among the selected villages with 10 households per village, were chosen through a random selection process. Furthermore, the current study evaluates the impact of diverse socio-economic variables on these losses through the application of an ordered probit model. The findings of the study suggested that, during both pre- and post-COVID 19 periods, the postharvest losses of banana farmer ranges between 1 to 32%, whereas, it was between 34 to 70% during COVID 19 period. Moreover, the study argued that the postharvest losses of banana farmers were influenced by the locational indicator, education, farming experience, land pattern as well as some other production and cost related factors of farmers. Despite this, the factors that influenced postharvest losses exhibited a significant change in direction across the various time periods. The study suggests that in less developed regions such as North East India, decreasing postharvest losses could play a vital role in alleviating poverty and fostering rural advancement by creating more opportunities for agribusiness livelihoods. [ABSTRACT FROM AUTHOR]

The aim of this study is to contribute to the poverty literature in Turkey by associating the serious economic difficulties experienced by the tenants with the burden of housing costs. Housing costs, which are an important expenditure item for households, reduce non-housing expenditures such as health, education, food, and clothing, and thus cause serious economic difficulties for households. The empirical analysis relies on data derived from the TURKSTAT Income and Living Conditions Survey (ILCS) micro data set for 2021. We limited our research to tenants aged 15 and over who are in the respondent of the household. We first worked with the probit model to understand the impact of actual and perceived housing cost burdens on household economic difficulties. In the following part, We worked with ordered probit models to determine the probability of households being unable to pay their electricity and water bills, rent, interest-bearing debts, or housing loans as planned in the last 12 months, and finally being unable to meet their total expenditures with their total income. We acted with the hypothesis that those responsible for households who have heating problems due to insulation are unemployed (or not working), have health problems, are married, have a low education level, and have a low income are traditionally included in the disadvantaged categories. Our findings indicate that as housing expenses increase, the probability of households experiencing severe economic difficulties also increases. As housing costs rise, individuals are more likely to be unable to pay their rent, energy, and water bills once or twice a year. The study revealed that the cost of living imposed a greater economic burden on vulnerable groups such as young people, individuals with health problems, parents of children under 6 years old, unemployed, women, low-educated, those living in substandard housing, and married individuals. [ABSTRACT FROM AUTHOR]

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As an important component of human capital, the contribution of health to accelerating economic development and technological progress is obvious.The Internet has had a profound impact on the lifestyle of rural residents. Using the nationally representative data from the 2017 Chinese General Social Survey (CGSS), this study estimates the impacts of internet use on residents' health in rural China. We employ the propensity score matching (PSM) model to address the selection bias. Our findings reveal that Internet use can reduce the physical and mental health of rural residents significantly. Disaggregated analysis indicates that Internet use has a greater positive effect on physical health of male, elderly, high-educated, and eastern regional rural residents. Internet use only had significant positive effects on mental health of female, middle-aged, high-educated and western regional rural residents. In addition, we explore the mechanisms by which Internet use affects rural residents' health from social network.

Despite the importance of heavy vehicles in Australia's transportation system, little is known on the factors influencing injury severity from accidents involving a single heavy vehicle. Heavy vehicular crashes have been one of the main causes of fatal injuries in Australia, and this raises safety concerns for transport authorities, insurance companies, and emergency services. Although there have been several potential attempts to identify the factors contributing to heavy vehicle crashes and injury severity, it is still necessary to reduce the number of traffic crashes and lower the fatality rate involving heavy vehicles. The aims of this study were investigating the effects of heavy trucks' presence in accidents on the injury severity level sustained by the vehicle driver and detecting the contributing factors that lead to specific injury severity levels. Fixed- and random-parameter ordered probit and logit models were applied for predicting the likelihood of three injury severity categories severe, moderate, and no injury based on data from crashes caused by heavy trucks in Victoria, Australia in 2012–2017. The results showed that the random-parameter ordered probit model performed better than the other models did. Twenty variables (i.e., factors) were found to be significant, and 12 of them were found to have random parameters that were normally distributed. Since some of the investigated factors had different effects on the type of injury severity in Australia, this paper does not recommend generalizing the findings from other case studies. Based on the findings, Victoria state authorities can have insight and enhanced understanding of the specific factors that lead to various types of injury severity involving heavy trucks. Consequently, the safety of all road users, including heavy vehicle drivers, can be enhanced.

Since the LEADER (Liaisons Entre Activités de Developpement de l'Economie Rural) method was launched in 1991, through its Rural Development Programmes, it has tried to support rural areas by promoting the creation of opportunities, strengthening rural territorial resilience and holding back depopulation processes. It has also introduced social considerations such as gender and age and has fostered the knowledge economy. One aspect of particular interest is employment: rural areas that offer employment opportunities can trigger a set of processes and dynamics that are positive for rural resilience in that they strengthen competitive, socially dynamic and economically viable spaces. The purpose of this article is to define the profile of a LEADER project that can generate and/or consolidate employment in the Spanish region of Castilla-La Mancha during the current 2014-2022 programming period. This is done by means of a study using ordered probit of the 4 465 projects by the Local Action Groups (LAGs). The study points to the preponderance of agro-industrial activity and the large size of the municipalities where employment is generated. It also finds that a very large proportion of the jobs created are for young people and that many women have found jobs in projects funded by the LAGs.

Local governments worldwide have been making efforts to regulate Airbnb and its negative externalities (NEs), as peer-to-peer (P2P) accommodations have grown exponentially. This study seeks to explore the perceptions of potential guests regarding the NEs of Airbnb accommodation by using a contextual approach and multiple methodologies to understand the effects of their choice. Through an experiment involving the collection of data on the responses of 296 participants from Taiwan's post-Millennials and ordered probit model estimations, this study provides a quantitative analysis to distinguish the factors and NEs affecting the likelihood of choosing Airbnb. Under the circumstance where concern for NEs was not included, the results indicated that the accommodation environments and interactive experiences were among the significant Airbnb service features that attracted consumers. However, when NE factors were added a potential effect was identified, with the community environment and security assurances being factors that decreased the likelihood of choosing Airbnb. Previous experiences of staying in hotels were also found to reduce the acceptance of Airbnb as an accommodation mode. These research findings provide insights into Airbnb preferences which could assist in improving the administrative and managerial efforts of P2P accommodation platforms. [ABSTRACT FROM AUTHOR]