Development of an Electrical Energy Consumption Model for Malaysian Households, Based on Techno-Socioeconomic Determinant Factors

Energy-saving strategies are required to address the increasing global CO2 and electrical energy consumption problems. Therefore, the determinant factors of electrical energy consumption consist of socio-demographic changes, occupant behavior, house and appliance characteristics, or so-called techno-socioeconomic factors, which all need to be assessed. Statistics models, such as the artificial neural network (ANN), can investigate the relationship among those factors. However, the previous ANN model only used limited factors and was conducted in the developed countries of subtropical regions with different determinant factors than those in the developing countries of tropical regions. Furthermore, the previous studies did not investigate the various impacts of techno-socioeconomic factors concerning the performance of the ANN model in estimating monthly electrical energy consumption. The current study develops a model with a more-in depth architecture by examining the effect of additional factors such as socio-demographics, house characteristics, occupant behavior, and appliance characteristics that have not been investigated concerning the model performance. Thus, a questionnaire survey was conducted from November 2017 to January 2018 with 214 university students. The best combination factors in explaining the monthly electrical energy consumption were developed from occupant behavior, with 81% of the variance and a mean absolute percentage error (MAPE) of 20.6%, which can be classified as a reasonably accurate model. The current study’s findings could be used as additional information for occupants or for companies who want to install photovoltaic or wind energy systems.

Socioeconomic determinants of micro and small enterprise growth in North Wollo and Waghimira Zone selected towns

This study aims to investigate the socioeconomic determinant factors that affect the growth of micro and small enterprises (MSEs) in North Wollo and Waghimira Zone selected towns. In this study, a cross-sectional research design with both descriptive and explanatory research design has been employed, and 303 owners of enterprises have participated. The towns were selected purposely, and the respondents were also selected by using a simple random sampling technique. The data were analyzed by using STATA v-14 and applied descriptive and binary logistic regression analysis (odds ratio). The finding of the study revealed that age of the owner, access to finance, family business background, and interest rate most likely affect the growth of the enterprises with the statistically significant level. On the contrary, entrepreneurship training, the experience of the owner, the inflation rate, and competition less likely affect the growth of the enterprises with a statistical significant level. The remaining factors such as gender of the owners, education background, business age, business type, business location, social responsibility, tax rate, and social attitude were not statistically significant to determine the growth of MSEs.

On the determinants, gains and challenges of electronic banking adoption in Nigeria

PurposeThe purpose of this study is to examine the gains, challenges and determinants of electronic banking adoption in Nigeria.Design/methodology/approachThis paper applied the generalized structural equation modelling (GSEM) to a large sample of respondents surveyed from five of the six geopolitical zones of Nigeria to model the determinants of electronic banking. In addition to many other advantages, GSEM can be used as a likelihood function. As a result, this paper proposes GSEM as the most appropriate tool for modelling the socioeconomic determinant of electronic banking adoption.FindingsAbout three-quarter of respondents adopted at least a form of electronic banking. However, only a tenth of users used e-banking for purchase of goods or services, implying low electronic payment adoption. The low adoption of electronic payment was due to poor digital security infrastructure which made users vulnerable to widespread electronic frauds. The findings also show that the adoption of e-banking platforms or services was characterized by users' socioeconomic status. For example, the odds of adopting internet/mobile banking decreases with older users but increase with higher educational attainment and income, whereas the odds of adopting e-banking platforms such as short message service (SMS) and point of sale (POS) banking increases with older users and informally employed users respectively.Practical implicationsFor a sustainable cashless economy and financial inclusion in Nigeria, policy consolidation that provides safe e-banking services is necessary. Also, e-banking service providers should deliver specific contents and services that match the physical and economic characteristics of users.Originality/valueGeneralized structural equation modelling (GSEM) is a robust likelihood function method that combines the power of structural equation modelling with the generalized linear model. The application of GSEM to predict the likelihood of adopting a banking technology or Service has not been explored in electronic banking literature. Also, as a fast-growing economy with a heterogeneous population, Nigeria presents an interesting context to study the determinants of electronic banking.

A State-Level Socioeconomic Data Collection of the United States for COVID-19 Research

The outbreak of COVID-19 from late 2019 not only threatens the health and lives of humankind but impacts public policies, economic activities, and human behavior patterns significantly. To understand the impact and better prepare for future outbreaks, socioeconomic factors play significant roles in (1) determinant analysis with health care, environmental exposure and health behavior; (2) human mobility analyses driven by policies; (3) economic pressure and recovery analyses for decision making; and (4) short to long term social impact analysis for equity, justice and diversity. To support these analyses for rapid impact responses, state level socioeconomic factors for the United States of America (USA) are collected and integrated into topic-based indicators, including (1) the daily quantitative policy stringency index; (2) dynamic economic indices with multiple time frequency of GDP, international trade, personal income, employment, the housing market, and others; (3) the socioeconomic determinant baseline of the demographic, housing financial situation and medical resources. This paper introduces the measurements and metadata of relevant socioeconomic data collection, along with the sharing platform, data warehouse framework and quality control strategies. Different from existing COVID-19 related data products, this collection recognized the geospatial and dynamic factor as essential dimensions of epidemiologic research and scaled down the spatial resolution of socioeconomic data collection from country level to state level of the USA with a standard data format and high quality.

Debt-Related Financial Hardship and Health

Recent research shows personal financial debt is an important socioeconomic determinant of health, but the mechanisms through which it operates are not well understood. This article uses data from a mixed-methods study to explore how changes in spending and behavior that result from debt have salient health consequences in a cross-sectional sample of Boston area adults ( n = 286). Findings show that a large majority of respondents had skipped medical care, housing payments, or consumer purchases at least once because of their debt. Controlling for multiple sociodemographic characteristics, each of these measures of debt-related behavior change was associated with worse self-rated health, and higher depressive symptoms, anxiety, and perceived stress. In models including all three measures, skipped medical care was associated with worse health across all outcomes, while skipped consumer purchases were associated with higher perceived stress and depression. These findings suggest that altered spending and care-seeking behaviors are potential pathways through which financial debt can negatively affect health and suggest areas in need of additional research.

Socioeconomic determinants of property crime offending in Ethiopia

Purpose The purpose of this study is to investigate the socioeconomic determinants of property crimes on convicted offenders in the Chilga district correctional institution (CDCI). Design/methodology/approach This study conducted a socioeconomic determinant of property crimes on convicted offenders using quantitative research. Respondents consisted of a random sample of 170 convicted offenders in CDCI. This study used descriptive statistics, logistic regression and Pearson correlations for analyzing the quantitative data in CDCI. Findings The results of the study showed that the age at first engagement, educational status, offender’s immediate economic situation and previous experience of the offender were the perceived reasons in one’s major property crime offending. However, average monthly income, peer effect and family structure (grown up with) were found to be non-perceived reasons. Youths who are unmarried, illiterate and unemployed offenders had over three times more probabilities of committing theft than robbery and burglary in the winter season, especially in February, because of the determinants of illiteracy and unemployment such as negligence for the future life. Furthermore, the convicted offenders who were illiterate, unemployed and raised by single parents have engaged in theft for the first time, but burglary and robbery by employed and literate offenders in more probable. Originality/value This paper takes a fresh perspective on knowledge about property crime and economic as well as criminological theories using various bodies of academic research. This paper’s insight will be helpful to fill the literature gaps; there are lot research studies with little investigations addressing to the issue of the determinants of property crime. It will also be useful for policymakers to mitigate the determinant of property crime.

Embodied Neoliberalism: Epidemiology and the Lived Experience of Consumer Debt

A growing set of epidemiological data links personal financial debt to negative mental and physical health outcomes. These findings point to debt as a potentially significant socioeconomic determinant of population health, especially given rising rates of household and consumer debt in industrialized nations. However, the political and economic contexts in which rising consumer debt is embedded and the ways in which it is experienced in everyday life are underexplored in this epidemiological literature. This gap leaves open questions about how best to situate and understand debt as a health determinant with both psychosocial and neo-material attributes. In this article, we discuss findings from a qualitative study of personal debt experience in Boston, Massachusetts. Participants’ debt narratives highlight the powerful feelings of shame, guilt, and personal responsibility that debt engenders. The findings point to the influence of neoliberal ideology in shaping emotional responses to debt and suggest that these responses may be important pathways through which debt affects health. We discuss our findings within the broader landscape of American neoliberal economic policy and its role in shaping trends of consumer debt burden.

Socioeconomic Determinants of Psychotropic Drug Utilization at a Tertiary Hospital in Dhaka City

Background: Mental illness is the most neglected disease in Bangladesh with a large number of people suffering from different types of mental illness.Objectives: The purpose of the present study was to find out socioeconomic determinant of psychotropic drug in tertiary level hospital.Methodology: This cross sectional descriptive study was carried out at the Sir Salimullah Medical College and Mitford Hospital (SSMC & MH), Dhaka from the period of July 2009 to June 2010. All the patients attended at psychiatry outpatient department were included as study population. The collected data include socio-demographic details by depth interview; Informed consent was obtained verbally from the patient or legal guardian. The psychiatry out-patient departments are selected because both rural and urban population of different classes and different socio-economic status daily come to these out-patient departments for their treatment purposes. They predominantly represent poor rural and urban population.Result: A total 300 patients were included in this study. Out of 300 patients158 patient (52.66%) were female, most of the patients were age group 18-27 years, 108(36%) patient were house wife. Schizophrenia and other psychotic disorder are most common complaint among the patient attending the psychiatry OPD, 293(97.67%) patient came from rural areas, 175(58.33%) patient were married. Most of the patients are illiterate. It was observed that less educated, illiterate, housewife, unemployed and lower income group of patients generally attend psychiatry out-patient department.Conclusion: In conclusion less educated, illiterate, house wife, unemployed and lower income group of patients generally attend psychiatry out-patient department.J Shaheed Suhrawardy Med Coll, 2015; 7(1):10-13