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The purpose of this study is to theorize and measure a consumption criterion of housing affordability and then to compare its predictions with those of a normative criterion over time. The new consumption criterion of housing affordability is quantified with predicted compensatory expenditures that a resident would pay to upgrade to their most preferred home. Its predictions are compared with those of the most popular normative criterion that predicts unaffordability if a resident spends more than a proportion such as 30% of their income on housing.

This study uses census and experimental data for owner-occupiers in two mid-sized Canadian cities between 1987 or 2001 and 2020 or 2021. These data are mapped and statistically analysed for comparing the predictions of the two criteria.

The study’s primary finding is that both criteria predict improved affordability of owned homes over time. Secondarily, however, the consumption criterion predicts worse unaffordability for the minority experiencing this. It furthermore clarifies their budgets for housing as more constraining than their social utilities that they may have already revised toward affordable home attributes. Indisputable unaffordability after the end of the study period may have nullified the originally recommended sacrifices for residents upgrading to their most preferred owned home.

The study is original because it demonstrates that a new consumption criterion of housing affordability subsumes the popular normative criterion if plausible assumptions are made about a homeowner’s choices. It then proceeds to speculate how this new criterion might refine the normative criterion with predicted compensatory expenditures for a resident’s affordable preferred homes.

This study addresses the COVID-19 infection and its relationship with the city’s constructive intensity, commuting time to work and labor market dynamics during the lockdown period.

Microdata from formal workers in Recife was used to adjust a probability model for disease contraction.

The authors' results indicate that greater distance to employment increases the probability of infection. The same applies to constructive intensity, suggesting that residences in denser areas, such as apartments in buildings, condominiums and informal settlements, elevate the chances of contracting the disease. It is also observed that formal workers with completed higher education have lower infection risks, while healthcare professionals on the frontlines of combating the disease face higher risks than others. The lockdown effectively reduced contagion by limiting people’s mobility during the specified period.

The research shows important causal relationships, making it possible to think about public policies for the health of individuals both when commuting to work and in living conditions, aiming to control contagion by COVID-19.

The lockdown effectively reduced contagion by limiting people’s mobility during the specified period.

It is also observed that formal workers with completed higher education have lower infection risks, while healthcare professionals on the frontlines of combating the disease face higher risks than others.

The authors identified positive and significant relationships between these urban characteristics and increased contagion, controlling for neighborhood, individual characteristics, comorbidities, occupations and economic activities.

The 2020 murder of George Floyd resulted in challenges to policing in the United States of America, but little is known about how police chiefs perceive them. At the same time, chiefs of police wield great influence over public perceptions of crime and disorder, the state of their profession, the laws and policies that govern the conduct of police officers and municipal public safety budgets. It is therefore critical to understand how police perceive the changes to their profession post-Floyd.

This study surveyed a randomly selected national sample of 276 municipal chiefs of police. Items probed resignations, recruitment, efforts to defund departments, community support, officer morale, suspects’ likelihood of obeying lawful orders and career risks that could inhibit proactive police work. It examined associations between perceptions and Census Bureau region, length of tenure as chief, size of police department, population served and the urban or rural designation of the jurisdiction.

Chiefs overwhelmingly reported recruiting qualified candidates had become much harder, and the present risks of proactive police work encourage inaction. Chiefs of agencies in the Northeast perceived more challenges than those in the South. Respondents with more years of experience were less likely to perceive the current situation as dire. Approximately 13.5% reported an attempt to defund their department, 56.8% of which yielded some success. Our study suggests an increase in the number and scope of challenges perceived by chiefs of police. Results vary by region and police chief years of experience.

This study provides researchers and practitioners with the perspectives of chiefs about the post-Floyd era that influence their decisions, policies and initiatives.

The aim of this research is to elucidate the correlation between open innovation, digital strategies and networking in enhancing agricultural enterprises within the new perspective of Agrifood 5.0. As such, it contributes to making businesses more competitive, especially in the Italian agricultural sector, where small and medium-sized enterprises are highly fragmented. Numerous studies have asserted that the competitiveness of actors operating within a specific territory is closely linked to local identity and image enhancement. Agricultural organizations are undergoing a profound transformation, with technological assets emerging as catalysts for new synergies. Advanced technologies such as robotics, the Internet of Things (IoT) and automation (AI) are emerging as differentiating elements capable of further advancing the agricultural sector, transitioning it from Agrifood 4.0 to Agrifood 5.0. The empirical analysis of the research shows a positive correlation between a collaborative attitude and a propensity for innovation. Indeed, the data demonstrated that digital strategies and open innovation positively influence competitiveness in agricultural SMEs.

The methodology employed in this study is mixed, incorporating both qualitative and quantitative approaches. The quantitative aspect involves analysis of the dataset from the Italian Statistical Institute (ISTAT) through logistic regression, while the qualitative component entails analysis of semi-structured interviews conducted with a sample of 174 agricultural cooperatives in southern Italian regions (Campania). This approach allows for a comprehensive understanding of the research topic, capturing both numerical trends and nuanced insights from interviews.

After analyzing the data from the 7th General Census of Agriculture conducted by ISTAT, a clear understanding of the sector has emerged, revealing several potential research avenues. It is evident that innovation in the agricultural sector is often driven by the largest and best-capitalized production entities, primarily located in Italy. Conversely, smaller agricultural entities can benefit from networking as new technological assets act as catalysts for new synergies, innovation and competitiveness.

Enhancing the relational contribution within the network and humanizing a fragmented sector are crucial elements for promoting open innovation. Network structuring facilitates the transmission of managerial knowledge, contributing to an overall increase in the intellectual and relational capital of the agricultural sector. These factors, combined with open innovation, enhance the competitiveness of individual firms and elevate the brand of the entire sector, creating a conducive environment for transitioning toward Agrifood 5.0. This transition is characterized by increased interconnection, continuous innovation and overall prosperity. Specific studies on this topic are lacking in Italy, particularly in the southern regions. Therefore, this contribution focuses on investigating the Campania region.

The novelty of this study lies in its investigation of the relationship between agricultural enterprises and innovation in the context of enterprises networking strategies (i.e. associationism and/or cooperation), promoting competitiveness. The limitations of this study are related to the dimension of the sample selected and its relationship with other productive sectors.

Mangrove forests are one of the most bio-diverse and productive wetland environments on earth. However, these unique tropical forest environments that occupy coastal areas are among the most threatened habitats globally. These threats include logging, conversion of land for agriculture and mariculture and degradation due to pollution over the past 50 years. The large population of resilient mangroves occupying the Turneffe Atoll area in Belize faces growing anthropogenic threats such as permanent clearing of land for housing, infrastructural development and pollution and natural factors (climate change). Given the few formal studies done to evaluate mangrove resilience at Turneffe Atoll, the purpose of this study was to evaluate mangrove resilience and nursery functions in the Turneffe Atoll Marine Reserve (TAMR).

Mangrove fish abundance and forest structure was assessed by means of a visual census and the point-centred quarter method (PCQM) for 11 sites that span across conservation and general use zones.

This study found that the more resilient mangroves (lower vulnerability ranks, higher standing biomass and higher fish biomass and abundance) exist in general use zones and warrant the need for improved mangrove conservation measures for these areas by Turneffe Atoll Sustainability Association (TASA).

Limitations of the methods for data collection included accessibility within mangrove forests stands when establishing PCQM, observer bias among data collectors, sites without surrounding mangroves were not captured to serve as a true control group and poor visibility underwater affected the estimation of fish species and size. The timeline for this research was only three months based on available funding, and no follow-up study was done to make a true comparison.

The findings of this research have a guiding role in the formulation of conservation measures such as better waste management, a robust framework for mangrove management, a communication strategy to guide public awareness and long-term monitoring surveys.

Using recent US regional data associated with food system operations, this study aims at building optimization and econometric models to incorporate varying influential factors on food hub location decisions and generate effective facility location solutions.

Mathematical optimization and econometric models have been commonly used to identify hub location decisions, and each is associated with specific strengths to handle uncertainty. This paper develops an optimization model and a hurdle model of the US fresh produce sector to compare the hub location solutions between these two modeling approaches.

Econometric modeling and mathematical optimization are complementary approaches. While there is a divergence between the results of the optimization model and the econometric model, the optimization solution is largely confirmed by the econometric solution. A combination of the results of the two models might lead to improved decision-making.

This study suggests a future direction in which model development can move forward, for example, to explore and expose how to make the existing modeling techniques easier to use and more accessible to decision-makers.

The models and results provide information that is currently limited and is useful to help inform sustainable decisions of various stakeholders interested in the development of regional food systems, regional infrastructure investment and operational strategies for food hubs.

This study sheds light on how the application of complementary modeling approaches improves the effectiveness of facility location solutions. This study offers new perspectives on elaborating key features to encompass facility location issues by applying interdisciplinary approaches.

Despite the growing prison population in South America and the high prevalence of infectious diseases, there is limited evidence on the factors associated with self-reported tuberculosis (TB) in this population. This study aims to identify the factors associated with self-reported TB among inmates in all prisons across Ecuador.

The 2022 Prison Census was used. The presence of TB was self-reported based on the question: Has any doctor diagnosed you with any of the following diseases: Tuberculosis? Prevalence ratios (PR) were obtained using crude and multivariable models along with their 95% confidence intervals (CI) using a generalized linear model with random effect at the prison level to assess the association among the study variables.

The prevalence of self-reported TB was 4.7%. Socio-demographic factors (prisoners aged between 18 and 29 years and indigenous), clinical factors (human immunodeficiency virus [HIV] infection, diabetes and attempted suicide) and imprisonment characteristics (re-offender, having a medical check-up on admission and being incarcerated for 6 months or more) increased the prevalence of self-reported TB compared with their counterparts.

This study provides a detailed understanding of the factors contributing to the prevalence of self-reported TB in the prison population of Ecuador. The findings highlight the need for strategies focused on TB control through diagnosis and treatment, management of HIV, diabetes and malnutrition, as well as the restructuring of prison facilities. Implementing these measures is crucial for addressing the identified factors and improving inmate health conditions.

This paper aims to compare the efficiency of spatial and nonspatial hedonic price models in capturing housing submarkets dynamics for cities in developing countries. This study expects to contribute to a better understanding of the housing price determinants from both nonspatial and spatial perspectives. In addition, this paper fills a gap in the literature on the study of housing prices from a spatial perspective in Latin American cities.

This study uses a comparative analysis between an ordinary least squares regression and a geographical weighted regression, GWR. The study also assesses the performance of two distinct data sources: the city’s cadastral records and a real estate sales web portal.

The results suggest that compared to the traditional regression model, the spatial regression models are more effective at capturing housing market variations on a fine scale. Moreover, they reveal interesting findings on the spatial varying, sometimes contradictory effects of some housing attributes on housing prices in different areas of the city, suggesting the potential impact from segregation.

The availability of data on housing prices and characteristics in Latin American cities is fragmented and complex. The level of detail, granularity and coverage is not consistent over time. For this reason, this study combines and compares data sets from official and unofficial sources in an effort to close this gap. Likewise, the socioeconomic variables that come from the census must be carefully analyzed, knowing the historical context in which they were constructed, what they represent and their interpretation.

This paper suggests that despite the improvement on the spatial models, the selection of a specific one should always be based on the diagnosis of it as it highly depends on the data used and the objectives of the study.

This study enriches the limited body of literature on spatial hedonic price models of housing in Latin American cities. It also shed light on the importance of spatial approaches to identify complex housing submarkets.

This study examines how the introduction of mobile money transfers, while making it efficient and convenient to access funds, has affected rural households’ savings behavior and the banking sector.

This study utilizes Fiji’s most recent agricultural census data to model the agricultural household’s saving decision. The study estimates an probit model to examine rural households' savings behavior. Furthermore, it utilizes time series secondary data to examine how funds transfer has been channeled to rural households in Fiji.

Firstly, the results demonstrate that with the mobile money transfer platform launch, the banking sector has lost substantial money previously used to pass through its system, thus losing service fees and interest income. Furthermore, the findings demonstrate that those using mobile wallet platforms to receive money are more likely not to have a savings account with the bank. Noting the cultural systems and social settings of the native households and the ease of payments via the mobile platform, they tend to spend more on consumption rather than saving, thus making these households more vulnerable during shocks such as natural disasters.

While mobile money transfer is hailed as a revolution, no research has yet picked up the downside to it, that of undermining the very effort by policymakers to get low-income rural households to save. Secondly, this study also highlights how mobile money transfer deprives the banking system of a significant transfer fee income and a source of funds to pool and lend to earn interest income. Furthermore, this study brings to the forefront a dichotomy about how a rural indigenous community sees the welfare and prosperity of their community much differently than what economics textbooks portray.

This study aims to explore and analyze the disparities in the distribution of housing types and characteristics among households in Saudi Arabia, taking into consideration the regional perspective.

This study uses quantitative data obtained from the General Authority for Statistics, specifically from the Saudi 2022 Statistical Census. The data were analyzed using descriptive statistics (percentages) as well as inferential statistics, including correlation analysis (Pearson correlation) and t-tests.

The study found a distinct preference among Saudis for villas, with 85.3% choosing this housing type, while only 14.7% of non-Saudis opted for villas. The statistical analysis confirmed the significance of housing type for Saudi citizens (t = 2.561, p = 0.037), while non-Saudis did not show a statistically significant preference (t = 1.703, p = 0.132). The Pearson correlation results revealed a moderate positive correlation (r = 0.641, p = 0.009) between regional landmass and the number of houses, and a very strong positive relationship (r = 0.984) between population and the number of houses across the 13 regions. As expected, with increasing population, there was a significant increase in the number of houses (p = 0.001).

This study fills a research gap by investigating regional disparities in housing characteristics in Saudi Arabia. The findings are valuable for policymakers, housing developers and the housing market in understanding these disparities. The insights from this research can inform decision-making to promote equitable access to housing types and foster social inclusivity in the housing sector.