Infrastructure-related Variables Research Articles

A Quest for Livelihood Sustainability? Patterns, Motives and Determinants of Non-Farm Income Diversification among Agricultural Households in Punjab, Pakistan

Many farmers worldwide resort to choosing various income-earning options for diversifying their income sources as a means of risk-avoidance, social protection, and, above all, to finance agricultural operations. Non-farm income generation among farm families has become an imperative part of livelihood earning strategies in recent years amid fast-evolving climatic and sociodemographic changes. In this regard, this study seeks to identify the patterns and socioeconomic factors responsible for the uptake of various non-farm income diversification sources among agricultural households in southern Punjab, Pakistan. For this purpose, a total of 290 farm households were sampled using a random sampling technique to collect relevant data through structured questionnaires. Results show that approximately 79% of the surveyed farmers were involved in non-farm income generation activities, whereas, the income from these sources accounts for about 15% of total household income. The majority of the respondents offered labour for off-farm work followed by self-employment ventures. The major reason to pursue non-farm work includes low income from agriculture, mitigating risks associated with farming, and acquiring funds to finance farming operations, along with the desire to increase family income. A range of socioeconomic and infrastructure-related variables are associated with the decision to participate in specific off-farm activity, such as age, education, family size, farm income, dependency burden, farming experience, and distance to the main city. Results imply the provision of technical support to increase livelihood from farming operations to ensure food security and curb rural-urban migration. However, vocational training can enhance the rural inhabitants’ skillset to diversify on the farm through agribusiness development within rural areas, enabling them to employ local people instead of populating urban centres.

A Comprehensive Approach Combining Regulatory Procedures and Accident Data Analysis for Road Safety Management Based on the European Directive 2019/1936/EC

The European Union policy for road safety management is based on the European Directive 2019/1936/EC. Among the safety management procedures and strategies, road safety inspections (RSI) are an effective tool for preventing accident risk and reducing crash frequency and severity for existing road networks. The European Transport Safety Council encourages the extension of these measures to the main urban and rural roads by the 5th Road Safety Action Programme. In light of the above, in this study, a safety performance evaluation through the RSI approach is carried out for a high-risk rural road in Southern Italy in order to identify all the road infrastructure-related features with poor safety conditions. Afterwards, the relationship between infrastructure deficiencies and the frequency and severity of accidents is investigated; a significant relationship between accident density/total number of injured people and road markings gap is found. Furthermore, the results confirm that a high density of driveways strongly impacts crash frequency. The analysis of the contribution of multiple infrastructure-related variables on the crash occurrences is proposed by the identification of several mathematical models. A second-order AIC (Akaike’s information criterion) approach is carried out to compare the five fitted models investigated. Finally, a prediction calibrated model is proposed.

Some influencing factors for passenger train punctuality in Sweden

Punctuality is regarded as an important measure of the performance of a railway system, and is the one most commonly used and discussed measure both in the industry and among travelers. In many countries, the punctuality of trains, and thus the performance of the railway system, is deemed as lacking. The aim of this article is to study and quantify how several weather-, timetable, operational and infrastructure-related variables influence punctuality in passenger train traffic. This can contribute to better understanding of the performance of railway systems, and help identify possible improvements. The study is based on a dataset containing detailed timetables and records of all 32.4 million train movements for all trains in Sweden during the year of 2015, over 1.1 million departures. Supporting this is a comprehensive register of over 80 000 infrastructure elements, and almost 87 million weather observations. We consider the size and allocation of margins, the existence of negative margins, two measures for traffic volume, the journey time and distance, how often different vehicle individuals are used, the number of line and station interactions between trains, the amount of precipitation, the temperature, wind speed, snow depth, and eight types of infrastructure elements. We show how these variables affect punctuality, and estimate how much of the variation in punctuality can be explained by them. The findings can be used to design timetables, change operational parameters and modify infrastructure design so that punctuality improves. They can also help identify areas which should be prioritized in planning, maintenance and research.

Impact of Bus Routes on Crash Frequency in Metropolitan Areas

Although research in transportation safety is abundant, very few studies have examined the relationship between public transportation systems and safety performance. Most studies on the subject have focused on the impact of infrastructure countermeasures related to bus rapid transit systems. However, the impact of city-street buses on safety performance remains unknown. This research explores the pseudo-causal impact of the presence of bus routes and bus traffic on observed crash frequencies by developing safety performance functions (SPFs) that include the presence of a bus route and estimated weekly bus traffic as input variables. The SPFs were developed using the propensity score–potential outcomes (PS-PO) framework to reduce unobserved biases that might exist between segments that have and do not have bus routes. The results suggest that PS-PO reduced standardized biases significantly, allowing stronger causal inferences to be obtained. The results revealed that the presence of a bus route was associated with a 27% increase in expected crash frequency after controlling for other infrastructure-related variables. Weekly bus traffic was also found to be a significant predictor of overall crash frequency, with a 1% increase in ] weekly bus traffic associated with an expected increase in crash frequency of 0.016%. A non-parametric approach is also presented for comparison with the results from the SPFs; this confirmed the findings from the parametric method used.

Effect of rural transport infrastructure on the intensification of purchased input use for major food crop production: the case of smallholder farmers in Horro Guduru Wollega Zone, Western Ethiopia

This paper examines the effect of rural transport on smallholder farmers’ purchased input use. A random sample of 500 respondents was selected and relevant data was collected. Descriptive, correlation, and regression statistics were used to analyze the data. The multiple linear regression analysis revealed that farmers’ purchased input use was found to be significantly and negatively related to distance to major market, distance to all weather road, distance to farm plot, transport cost, and size of land holding. In contrast, farmers’ purchased input use was found to be significantly and positively related to family size, off farm income, membership in a cooperative, being in Horro district, having animal cart, and access to good road. Further, the results of hierarchical multiple regression showed that approximately 82% of the total variation in purchased input use can be explained by the linear combination of all independent variables. Furthermore, the result showed that rural transport infrastructure-related variables, as a set, contributed 13.3% to the prediction of farmers’ purchased input use over and above the remaining predictors. The results suggest that improving the rural road infrastructure and access to rural transportation services is vital in encouraging farmers’ purchasedinput use.

Attentional Demand as a Function of Contextual Factors in Different Traffic Scenarios.

To assess the attentional demand of different contextual factors in driving. The attentional demand on the driver varies with the situation. One approach for estimating the attentional demand, via spare capacity, is to use visual occlusion. Using a 3 × 5 within-subjects design, 33 participants drove in a fixed-base simulator in three scenarios (i.e., urban, rural, and motorway), combined with five fixed occlusion durations (1.0, 1.4, 1.8, 2.2, and 2.6 s). By pressing a microswitch on a finger, the driver initiated each occlusion, which lasted for the same predetermined duration within each trial. Drivers were instructed to occlude their vision as often as possible while still driving safely. Stepwise logistic regression per scenario indicated that the occlusion predictors varied with scenario. In the urban environment, infrastructure-related variables had the biggest influence, whereas the distance to oncoming traffic played a major role on the rural road. On the motorway, occlusion duration and time since the last occlusion were the main determinants. Spare capacity is dependent on the scenario, selected speed, and individual factors. This is important for developing workload managers, infrastructural design, and aspects related to transfer of control in automated driving. Better knowledge of the determinants of spare capacity in the road environment can help improve workload managers, thereby contributing to more efficient and safer interaction with additional tasks.

The effect of ambient temperature on cardiovascular mortality in 27 Brazilian cities.

There is limited evidence on the relationship between temperature and cardiovascular mortality in middle and low-income countries, particularly in Latin America. In this study, we investigated the total effect of temperature on cardiovascular mortality in 27 Brazilian cities, and the effect modification by geographic, socioeconomic, demographic and infrastructure characteristics within cities. In the city-specific analysis, we used time-series analyses to estimate the relationship between mean temperature and daily cardiovascular mortality using quasi-Poisson generalized linear models combined with distributed lag non-linear models. In the second stage, a meta-analysis was used to pool the effects of temperature on cardiovascular mortality for Brazil and its five regions (Central-West, North, Northeast, South, and Southeast). We used a meta-regression to examine the effect modification of city-specific geographic, socioeconomic, demographic and infrastructure-related variables. The risks associated with temperature varied across the locations. Higher cardiovascular mortality was associated with low and high temperatures in most of the cities, Brazil and the Central-West, North, South, and Southeast regions. The overall relative risk (RR) for Brazil was 1.26 (95% confidence interval [CI]: 1.17-1.35) for the 1st percentile of temperature and 1.07 (95% CI: 1.01-1.13) for the 99th percentile of temperature versus the 79th percentile (27.7 °C), where RR was lowest. The temperature range was the variable that best explained the variation in effects among the cities, with greater effects in locations having a broader range. The results indicate effects of low and high temperatures on the risk of cardiovascular mortality in most of Brazil's capital cities, besides a pooled effect for Brazil and the Central-West, North, South, and Southeast regions. These findings can help inform public policies addressing the health impact of temperature extremes, especially in the context of climate change.

A mixed effects negative binomial analysis of road mortality determinants in Sub-Saharan African countries

This paper uses aggregate data for a panel of 23 Sub-Saharan African countries to explore the potential predictors of road traffic fatalities between 2001 and 2010. In addition to the Gross Domestic Product per capita, the set of covariates includes some demographic, safe driving behavior, health and infrastructure-related variables. Estimations from a mixed effects negative binomial regression suggest that the fraction of populations aged between 15 and 64 years, the size of the road network and seat belt laws significantly increase fatalities. However, populations of age 65 and above, hospital beds and physicians’ densities, and road audits significantly decrease these fatalities. Moreover, traffic fatalities are found to increase with the Gross Domestic Product per capita. The economic implications of this finding is not to lower the economic growth but to design policies and technologies that could prevent African countries from experiencing the same road tragedy observed in industrialized countries during their development process.

Territorial variation in mortality from causes amenable to medical care in Poland.

This study examines the geographical variation of amenable mortality in Poland, focusing primarily on the role of health care resources at the level of administrative districts and regions, and selected area socioeconomic characteristics as explanatory factors. The concept was used of amenable mortality, based on the assumption that deaths from certain causes should not occur in the presence of timely and effective health care. Standardized death rates (SDR) from causes considered amenable to health care and, separately, for ischaemic heart disease (IHD), were calculated for each of 379 districts (NUTS 4 level) in Poland in 1991-1995 and 2006-2010, using unit mortality data from the National Causes of Death Register. The analytical procedure involved spatial analysis of the distribution of amenable mortality rates, selection of explanatory variables and fitting multilevel regression models using area-level and regional-level characteristics. The results indicate that mortality from conditions which have become amenable to medical intervention has generally decreased in all districts of Poland in the past two decades. Considerable territorial variation in mortality can be observed. Since the 1990s, these differences have been reduced for IHD-related mortality and have increased for amenable mortality. The presented analysis only partly confirms the correlation between variables reflecting the infrastructure of health care resources and the territorial variation in mortality from these two categories of causes of death. Significant correlations with variation in mortality are revealed for the number of primary care physicians (at district level) and the number of specialist practitioners (at regional level). However, after controlling for socioeconomic variables, such as education and low income, the effect of the health care infrastructure-related variables was considerably reduced. The multi-level models also revealed a substantial variation at the regional level, which implies that there are other unobserved contextual influences on amenable mortality at this level.

Editorial: Enterprise Websites Usage in the European Union - Outlook to the Western Balkans Countries

IntroductionThe Internet usage by individuals and enterprises has become unavoidable in the contemporary society [16], [20], [21], [25], [27], especially taking into account the European Commission's Digita l Agenda [6], [28]. Therefore, it is very important for enterprises to recognize usefulness and potential benefits of being present on the Internet [22], [27]. Although many enterprises use social media and Web 2.0 tools [2], [3], [23] there are still numerous enterprises that have not decided to open their own website yet [26].There are many factors which influence the decision whether to have or not to have a website [25]. However, in this paper only variables related to the information technology (ICT) usage for e-commerce purposes (online ordering and buying), and availability of ICT infrastructure (e.g. broadband availability) were taken into account as possible determinants of the decision on the establishment of a company's website. A similar approach was used by [1], [4], [15].In the analysis, the ICT development levels (in terms of enterprise websites, e-commerce and ICT infrastructure) in selected European countries were observed, with a special focus on the following selected Western Balkans (WB) countries: Bulgaria, Croatia, Greece, Romania, Serbia, Slovenia, and the Former Yugoslav Republic of Macedonia (FYROM). Since Bulgaria, Croatia, Greece, Romania, and Slovenia are the EU member states, whereas Serbia and the Former Yugoslav Republic of Macedonia (FYROM) are not, it is expected that these five EU member states have a higher ICT development level than the two named non-EU member states, which is in line with the previous research [5], [19].The paper is organized as follows. After a brief Introduction, Chapter 2 describes data and methods used in the research. In Chapter 3, results are discussed whereas in Chapter 4 conclusions are brought.in full.Data and MethodsThe data used in the analysis are extracted from the Eurostat database. The list of all selected ICT variables is given in Table 1. The percentage of enterprises having a website or homepage is determined as the dependent variable of the research, while there are also two groups of potential independent variables: e-commerce-related variables and ICT infrastructure-related variables. E-commerce-related variables measure the percentage of enterprises having purchased via computer-mediated networks and having received orders via computer-mediated networks. ICT infrastructure-related variables measure variables such as the percentage of enterprises with a broadband access (fixed or mobile). All the information is presented as the percentage of enterprises, having at least 10 employees, in a particular country in 2015. Financial sector enterprises were not included in the analysis.Data are collected for enterprises from 33 European countries, namely, for all the European Union member states (EU28), Iceland, Norway, Serbia, FYROM and Turkey. Even though the most recent data, from 2015, are collected for most of the countries, data from 2014 were used as an approximation for 2015 for Iceland, Serbia and FYROM. Similarly, because of the same reason data from 2014 were also used for the variable XPurch for Denmark and for the variable XMobBAcc for the United Kingdom. Unfortunately, the most recent data for the variable XPurch for Turkey are those for the year 2010, and this information was used as a proxy for the 2015 level, corrected by the increase in t he variable XOrder, which is available for the year 2015.First, an outlier detection and analysis is performed due to the fact that outliers could have a significant impact on the results of the analysis. The outliers were omitted from the analysis. Second, after omitting detected outliers, descriptive statistical results are provided for each variable separately. The position of the observed WB countries according to the values of the observed ICT variables is additionally examined using profile diagrams. …

Rivers as municipal infrastructure: Demand for environmental services in informal settlements along an Indonesian river

In many developing world cities, where municipal infrastructure lags urban growth, lower-income communities may compensate by relying on local waterways to meet basic needs for water, sanitation, and recreational space. Access to these environmental services is possible because residents settle in floodplains, but thus entails elevated exposure to several water-related hazards, especially flooding. We examine this complex relationship in the neighborhoods of Bukit Duri and Kampung Melayu on the Ciliwung River in Jakarta, Indonesia. Based on a spatially referenced household survey, we analyze and map the patterns of use of six environmental services provided by the river: direct sanitary use, recreation, harvesting plants, groundwater use, solid waste disposal, and sewage disposal. Using spatial interpolation and regression methods, we identify the most probable areas where services are being used and analyze possible influences on this behavior. We find that proximity to the river significantly influences households’ behavior toward the river, as do infrastructure-related variables and neighborhing households’ behavior, while household demographic factors appear less significant. These results indicate that many households rely on multiple environmental services, and that residents most reliant on these services are also at greater risk of water-related hazards, service disruption (e.g., a decline in water quality), and potentially, eviction. This pattern of floodplain development is prevalent in many low-income countries, and a better understanding of how informal settlements rely on environmental services can be used to assess their vulnerabilities and inform more sustainable courses of development.

Urban sprawl and social interaction potential: an empirical analysis of large metropolitan regions in the United States

This paper investigates the impact of urban spatial structure on the opportunities for people to participate in face-to-face activities. We make use of the Social Interaction Potential (SIP) metric, a tool to measure the average level of opportunity for people to engage in face-to-face activities given some basic constraints on their daily mobility patterns. Generally, this opportunity is a reflection of whether the urban spatial structure – a term that broadly applies to the spatial arrangement of land-uses and the interactions between them – constrains or permits the ability for potential activity partners to be at the same place and time. In this paper, the SIP metric is applied to 42 metropolitan regions in the United States with populations over 1,000,000 people. These measurements are regressed against a set of indicators of urban sprawl to expose the relationship between spatial structure and SIP. The indicators are generated by a factor analysis of a large set of variables describing the scale, centrality and dispersion of land-uses in addition to several other structural and infrastructure-related variables. Cluster analysis is also used to organize the regions into similar groupings with respect to their structural characteristics and the level of SIP they provide. The findings indicate that social interaction potential is hampered by decentralization, fragmentation, and longer commutes in the largest metropolitan regions in the country. Interestingly, the negative effect of decentralization on SIP Efficiency is found to be nearly ten times stronger than that of fragmentation and nearly 20 times stronger than the effect of mean commuting duration.

Global and local analysis of fragmentation in a mountain region of Colorado

Although relationships between fragmentation of urban development and other forms of administrative and land cover fragmentation are important, they are poorly understood. This research aimed to better understand these relationships in order to inform land use planning in the Roaring Fork/Colorado River Corridor of Colorado. Change in fragmentation of urban development between 1985 and 1999 was modeled as a function of other forms of administrative and land cover fragmentation using two different regression specifications. While a standard “global” regression provided a good averaged model of change for the entire study area, a geographically weighted regression (GWR) demonstrated how the process changed locally over space. Results of the global regression showed that the intercept was close to zero and therefore the fragmentation of urban development was expected to be close to zero in the absence of other forms of fragmentation. Results of the GWR showed that the relationships between change in fragmentation of urban development and other fragmentation variables (initial edge density of urban development, edge density of public/private interface, farmland density and road density) varied significantly within the study area. By modeling this variation, GWR helped to identify ways to reduce fragmentation of urban development in two different regions of the study area. The analysis suggested that fragmentation of urban development in one area, Aspen–Basalt, was more strongly driven by amenity-related variables, while in the New Castle area fragmentation was more strongly driven by infrastructure-related variables. Ultimately, local analysis may help fine-tune “one-size-fits-all” land use polices for specific regions.