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The escalating levels of greenhouse gas emissions have become a growing global concern, with household energy consumption emerging as a significant contributor. To develop effective public policies, it is crucial to understand the energy-saving behavior of households. This study delves into the determinants of energy-saving practices in a developing country.

The authors chose a multivariate probit model, as it allowed to look after possible correlations among seven energy-saving practices within households.

The findings underscore the significant influence of sociodemographic variables, such as gender, civil status, income and education, on energy-saving practices. Furthermore, the authors discovered that households where the head actively volunteers in social organizations are more likely to adopt energy-saving behaviors. Additionally, internet access positively contributes to pro-environmental behavior. This research reveals that certain energy-saving practices are interconnected, acting as complements or substitutes.

Recommendations for public policy include prioritizing education in rural areas to boost energy-saving practices, improving internet access in nonurban regions and promoting citizen involvement in social organizations to enhance environmental awareness and encourage energy-saving behavior. The authors contribute to literature evidencing that certain energy-saving practices are not independent of each other, they are rather complementary and, in some cases, substitutes.

Recommendations for public policy include prioritizing education in rural areas to boost energy-saving practices, improving Internet access in nonurban regions and promoting citizen involvement in social organizations to enhance environmental awareness and encourage energy-saving behavior.

Previous studies have overlooked these interdependencies, highlighting the necessity of a system of equations to yield more efficient estimates by considering correlations between error terms.

With the rapid development of the economy in China, the wealth of residents has continued to increase, and most families have gradually been aware of the importance of commercial insurance. The family purchase of insurance in China was still not optimistic. Many scholars focus on wealth allocation, but the attention to the commercial insurance market was still less. Based on previous research studies, this study aims to investigate the impact of education and financial literacy on the commercial insurance purchase in China.

China Household Finance Survey data was used to investigate the purchase of commercial insurance in Mainland Chinese families. Factor analysis was used to construct financial literacy, and the education data were combined to analyze the commercial insurance purchase using the Probit model and the Tobit model. Finally, the contributions of education and financial literacy to commercial insurance purchases were analyzed.

Both education and financial literacy exerted a positive impact on the purchase of commercial insurance in China. Individual characteristics such as gender, age, marital status, risk attitude, purchase of social insurance and consultation with a financial advisor possessed significant effects; household factors like household size and assets, macro factors such as the density of financial institutions and the density of financial industry staff, and regional factors as local unemployment rate excreted influences on the commercial insurance purchase.

Based on the current economic development in China, this study investigated and expressed opinions on the public and insurance companies regarding commercial insurance purchases. It accentuated financial literacy and education as factors that facilitated commercial insurance development.

This study aims to examine the nexus between digital financial literacy and customers’ perceived financial behavior within the Kuwaiti context. Moreover, it will further explore how digital financial literacy relates to financial behavior dimensions.

Data collection was facilitated by creating a questionnaire derived from multiple literature sources. This study used a cross-sectional, time-based dimension. Data was analyzed using the partial least square (PLS) structural equation modeling approach, using the Smart-PLS 4 software for computation.

Findings demonstrated a significant relationship between digital financial literacy and financial behavior, with a path coefficient of 0.542, a p-value of 0.000 and an R² value of 0.581. The explorative model revealed substantial relationships between many dimensions of digital financial literacy and various dimensions of financial behavior. More precisely, financial knowledge, awareness and decision-making were the factors that had the most significant impact on financial behavior.

Kuwaiti policymakers should consider including digital financial literacy programs in comprehensive financial education programs to improve public understanding of digital financial instruments and their consequences.

As the authors know, this is the initial endeavor to evaluate the relationship between digital financial literacy, financial behavior and their respective dimensions.

This study aims to conduct a bibliometric analysis on “intertemporal choice” behavior of individuals from journals in the Scopus database between 1957 and 2023. The research covered the data on the said topic since it first originated in the Scopus database and carried out performance analysis and content analysis of papers in the business management and finance disciplines.

Bibliometric analysis, including science mapping and performance analysis, followed by content analysis of the papers of identified clusters, was conducted. Three clusters based on cocitation analysis and six themes (three major and three minor) were identified using the bibliometrix package in R studio. The content analysis of the papers in these clusters and themes have been discussed in this study, along with the thematic evolution of intertemporal choice research over the period of time, paving a way for future research studies.

The review unpacks publication and citation trends of intertemporal choice behavior, the most significant authors, journals and papers along with the major clusters and themes of research based on cocitation and degree of centrality and relevance, respectively, i.e. discounting experiments and intertemporal choice, impulsivity, risk preference, time-inconsistent preference, etc.

Over the past years, the research on “intertemporal choice” has flourished because of the increasing interest of researchers and scholars from different fields and the dynamic and pervasive nature of this topic. The well-developed and scattered body of knowledge on intertemporal choice has led to the need of applying a bibliometric analysis in the intertemporal choice literature.

This study aims to empirically examine accounting information system (AIS) success at the organizational level during COVID-19 era.

Based on the information system success model, this paper developed its model and proposed a total of nine hypotheses. This paper gathered the required data via a questionnaire from Yemeni small and medium enterprises (SMEs) owners and managers. To test the proposed research model paths, SmartPLS software, which is known as partial least squares structural equation modeling, was used.

The results showed that the quality dimensions (information quality and system quality) positively affected the use of AIS and satisfaction; user satisfaction positively affected the use of AIS. Management support positively affected the AIS users' usage and satisfaction. Finally, the use dimensions (user satisfaction and usage) positively impacted the net benefits in terms of gaining a competitive advantage, productivity enhancement and saving time and cost. In all, this research has succeeded in providing support for DeLone and McLean's IS success model at the organizational level during the COVID-19 era.

AIS is becoming increasingly important for SMEs in low-income countries like Yemen, particularly in the present pandemic conditions (COVID-19 era). By using AIS, users can access the enterprise's data and conduct transactions without being limited by distance. Indeed, AIS proved its ability in enhancing the net benefits at the organizational level in the COVID-19 era in terms of gaining a competitive advantage, productivity enhancement and saving time and cost. However, AIS can only be considered useful to the enterprise if it is effective/successful.

This study is one of the first to have assessed the impact of AIS success at the organizational level in the era of COVID-19 pandemic, the context of Yemeni SMEs.

Research shows that having student loan debt in retirement is associated negatively with life satisfaction, suggesting that student debt is a bane of retiree well-being. The rationale for this study is to determine the factors related to owing student debt in retirement, given the adverse effects on the well-being of retired households.

The study utilizes pooled cross-sectional data from the 2015 and 2018 U.S. National Financial Capability Study. The empirical analysis uses a sample of retired Americans aged 65 years and older (N = approximately 8,000) and estimates two-block logistic regression models to examine the effects of demographic, socioeconomic and behavioral factors on student loan indebtedness in retirement. A sensitivity analysis is performed for the subsample of retirees holding student debt for their children's education. Statistical interpretations use odds ratios.

The findings indicate that financial literacy, age, homeownership and high subjective financial knowledge are associated with a low likelihood of holding student loan debt in retirement. However, being Black, having postsecondary education, having difficulty covering expenses, having financially dependent children, having high-risk preferences and spending more than income increase the likelihood of holding student debt in retirement. The ensuing discussion will assist financial planners and educators identify practical ways to shape decisions regarding student loan debt in retirement.

The amount of student loan debt is unavailable in the dataset for analysis. One cannot infer causal relations from the study. The factors examined do not reflect the time the student loan was obtained.

The study focuses on the determinants of student loan indebtedness among retired Americans rather than young adults or older adults on the verge of retirement. The paper enhances the understanding of student loan holdings in the decumulation phase of the life cycle. Many US individuals have low retirement savings from which they draw a retirement income. The more the student debt burdens on retired Americans, the greater the likelihood of outliving their resources and experiencing poverty.

Our proposed machine learning model contributes to improving the quality of Hire by providing a more nuanced and comprehensive analysis of candidate attributes. Instead of focusing solely on obvious factors, such as qualifications and experience, our model also considers various dimensions of fit, including person-job fit and person-organization fit. By integrating these dimensions of fit into the model, we can better predict a candidate’s potential contribution to the organization, hence enhancing the Quality of Hire.

Within the scope of the investigation, the competencies of the personnel working in the IT department of one in the largest state banks of the country were used. The entire data collection includes information on 1,850 individual employees as well as 13 different characteristics. For analysis, Python’s “keras” and “seaborn” modules were used. The Gower coefficient was used to determine the distance between different records.

The K-NN method resulted in the formation of five clusters, represented as a scatter plot. The axis illustrates the cohesion that exists between things (employees) that are similar to one another and the separateness that exists between things that have their own individual identities. This shows that the clustering process is effective in improving both the degree of similarity within each cluster and the degree of dissimilarity between clusters.

Employee competencies were evaluated within the scope of the investigation. Additionally, other criteria requested from the employee were not included in the application.

This study will be beneficial for academics, professionals, and researchers in their attempts to overcome the ongoing obstacles and challenges related to the securing the proper talent for an organization. In addition to creating a mechanism to use big data in the form of structured and unstructured data from multiple sources and deriving insights using ML algorithms, it contributes to the debates on the quality of hire in an entire organization. This is done in addition to developing a mechanism for using big data in the form of structured and unstructured data from multiple sources.

This paper aims to evaluate the role of depositor-specific features in a bank resolution. As the resolution framework in the EU is rather new, there are no empirical studies referring to the efficiency of this mechanism in protecting financial stability. Thus, the authors have checked the role of societal awareness of deposit guarantee schemes and the resolution, as well as the trust in public institutions, in avoiding bank runs in the case of resolution scenarios.

The study is based on telephone interviews conducted with 1,000 Poles, including bank customers whose banks have undergone resolution in recent years, and basic statistics of the resolved banks. The authors then apply two classes of models: binary probit regression and ordered probit regression.

The findings have indicated that the trust in public institutions and the experience gained with age play a key role in overall depositor behaviour. However, for resolutions, declared trust is replaced by case-specific trust based on the obtained information.

The survey is based on a sample of Polish citizens. In the future, international surveys may help diagnose cross-country differences among depositors. Moreover, studies on communication approaches may also support finding highly effective ways to reach various cohorts of depositors.

The existing literature on depositor behaviour in bank failure scenarios has relied on an experimental approach to test various research hypotheses. The research sample is not based on an experiment but on the responses of customers whose banks have actually undergone resolution.

The purpose of this study is to review the role of knowledge management (KM) in disaster management and crisis. Disaster causes many detrimental impacts on human lives through loss of life and damage to properties. KM has been shown to dampen the impact of the disaster on the utilization of knowledge among agencies involved and the local communities impacted by disasters.

Through a bibliometric methodology (co-citation, bibliographic coupling and co-word analysis), this study presents significant themes in the past, current and future predictions on the role of KM in disaster management. In this review paper, 437 publications were retrieved from the Web of Science and analyzed through VOSviewer software to visualize and explore the knowledge map on the subject domain.

Findings suggest that the significant themes derived are centralized to disaster preparedness during disaster and disaster postrecovery. This review presents a state-of-art bibliometric analysis of the crucial role of KM in building networks and interconnection among relevant players and stakeholders involved in disaster management.

The main implication of this study is how the authorities, stakeholders and local community can integrate the KM system within the three stages of disasters and the crucial role of technologies and social media in facilitating disaster management.

To the best of the authors’ knowledge, this is the first study to present a bibliometric analysis in mapping KM’s past, present and future trends in disaster management.

Active shooter incidents have risen considerably in recent years, elevating public and law enforcement focus on improving response to these incidents. The contemporary policy for reacting to an active shooter event is for the officers who first arrive on the scene to move quickly to engage and neutralize a shooter, prioritizing victim safety and minimizing loss of life. This study provides a preliminary understanding of the police view regarding their role in active shooter events and their experiences with active shooter training.

We conducted a survey of 413 sworn personnel across three US cities. Analyses examine differences in officers’ training experiences across the agencies and predictors of a sense of duty to prioritize victims’ lives over that of officers.

Officers’ training experiences differed by agency, yet most officers supported a duty to sacrifice their lives to prioritize victims’ safety during active shooter incidents. Officers with more years of experience have lower odds of supporting a duty to sacrifice their lives to save victims during an active shooter situation relative to less experienced officers. Respondents who recall officer safety among the top three most memorable topics from their recent active shooter training also have lower odds of supporting a duty to sacrifice.

The authors add knowledge about police officers’ experiences with active shooter training and officers’ opinions about their role in responding to active shooter incidents. We discuss implications of the findings relative to police culture and training and suggest directions for future research.