Macro-level Determinants Research Articles

Artificial intelligence in corporate communications: determinants of acceptance and transformative processes

PurposeThis study investigates the determinants of artificial intelligence (AI) acceptance in and AI-driven transformations of corporate communications. From a technology adoption perspective, the study explores the dual influence of individual and organizational factors on AI acceptance.Design/methodology/approachEmploying a qualitative research design, this study conducted semi-structured interviews with 19 AI experts in large-scale companies in Germany.FindingsThe study reveals micro-level determinants of AI acceptance related to AI’s perceived usefulness and ease of use. It also identifies macro-level determinants, including organizational awareness and frameworks. Corporate communications is expected to gain relevance due to the organizational integration of AI.Research limitations/implicationsThe proposed model integrates crucial factors influencing AI adoption and offers a starting point for quantitative validation. The study serves as a benchmark for future research, particularly given its timing right before the extensive adoption of ChatGPT.Practical implicationsOrganizations are encouraged to develop strategies that enhance both individual and organizational AI readiness. By reflecting both micro- and macro-level determinants of AI acceptance, a more holistic understanding of effective change management initiatives related to AI integration can be fostered.Originality/valueBy proposing an extension to the technology acceptance model, which incorporates both micro- and meso-level determinants, this study provides a novel framework for holistically understanding AI acceptance in corporate communications.

Age Discrimination of Senior Citizens in European Countries

This paper addresses perceived age discrimination of older persons in European countries. This disturbing issue has become all the more prominent, having doubled over a relatively short period between 2018 and 2021. Strongly associated with bad health outcomes, low levels of wellbeing, and considerable social tensions, age-related discrimination against senior citizens is a sign of the lack of their social integration. Our study used secondary data analysis based on survey methodology. Statistical analysis was performed on data from the European Social Survey wave 10 (2021) subsample of people aged 65 and above to assess the senior population’s age-based discrimination experiences and its individual and macro-level determinants. The results indicate that in all European countries, low socioeconomic status, older age, and living alone are strongly associated with the experience of age discrimination. Having bad health and being functionally limited in everyday activities results in a state of dependency that is connected to a higher risk of perceived exposure to age discrimination. Smaller populations, such as those in villages, are protective against discrimination at older age. Finally, compared to other welfare regimes, in social democratic welfare states with egalitarian redistribution systems and high levels of social benefits, there is a significantly larger share of old people who reported to have been victims of age discrimination. Our results have implications for policy in the context of ageing societies.

Global Perspectives on Determinants of Older Adults’ Subjective Well-being: A Comprehensive Longitudinal Study

Current research has established a relationship between older adults' subjective well-being and factors extending beyond their economic status to encompass various non-monetary elements. While most studies in this domain focus on factors within a single country, our analysis utilizes international longitudinal surveys to explore older adults' well-being at both the national and global scale. This comprehensive analysis considers micro- and macro-level determinants of retirement well-being, revealing consistent variations in happiness levels across countries. Our study specifically suggests a compelling positively relationship between ago and subjective well-being within the United States. This finding presents a contrast with the negative association observed in European countries. Our global analysis further indicates a positive relationship between age and subjective well-being. This study not only contributes to greater understanding of the complexities related to aging and well-being but also provide significant implications for financial services professionals and public policymakers that aim to improve the well-being of elderly populations.

Realization of Short-Term Fertility Intentions in a Comparative Perspective: Which Macro-Level Conditions Matter?

This is the first large-scale comparative study to search for macro-level determinants of the realization of short-term fertility intentions across European countries. Using the unique follow-up feature of the Generations and Gender Survey and adopting rigorous definitions of intentions and outcomes, it reports on the level of fulfilment and finds clear heterogeneity across European countries. Using a multilevel, multivariate approach, it examines the nature of macro-level factors that may explain differences in the realization of fertility intentions. Based on our analysis, we conclude that labour market stability (as measured by fluctuations in the unemployment rate), price stability, heavy welfare state involvement, and the dominance of certain attitudinal conditions all support the greater realization of short-term fertility intentions.

Bank intermediation efficiency and liquidity risk in Egypt: a two-stage non-parametric analyses

This is a pioneering study that undertakes a comparative analysis assessing the annual intermediation efficiency of public versus private banks in Egypt. Moreover, liquidity risk is a major threat facing banks in their efforts to sustain financial stability. Thus, this study is the first to model the determinants of liquidity risk in public and private banks in Egypt while examining the impact of banks’ intermediation efficiencies on their liquidity risk levels. The study employs advanced nonparametric econometric approaches on a sample of Egyptian public and private banks from 2014 to 2022. The data envelopment analysis is used in estimating banks’ intermediation efficiency scores, while the quantile regression analysis is applied to examine the impact of bank intermediation efficiency on liquidity risk under different liquidity risk quantiles. The findings indicate that public banks show consistent superiority in terms of their financial intermediation efficiency levels compared to private banks. Moreover, the paper findings demonstrate the negative significant relationship between bank intermediation efficiency and liquidity risk while highlighting the higher significant positive impact of intermediation efficiency on reducing the liquidity risk of banks that are characterized by undertaking high liquidity risk levels. Furthermore, contrary to general assumptions, this study’s findings demonstrate that the significance of micro- and macro-level determinants of a bank’s liquidity risk is dependent on its prevailing liquidity risk level. Hence, the positive impact of equity capital, asset concentration, size, and growth in gross domestic product and the negative effect of asset quality on bank liquidity risk vary under banks’ different liquidity risk quantiles.

“Expected to happen”: perspectives on post-release overdose from recently incarcerated people with opioid use disorder

BackgroundOpioid-related overdose is the leading cause of death for people recently released from incarceration, however treatment with medications for opioid use disorder (MOUD) during incarceration can reduce the mortality risk. This study seeks to qualitatively analyze perceptions of post-release overdose risk from the perspectives of people who received MOUD while incarcerated in one of eight Massachusetts jails during 2021–2022 using the Risk Environment Framework to guide analyses.MethodsN = 38 participants with lived experience of MOUD treatment during incarceration who are now living in the community were interviewed on factors that may contribute to or protect against post-release overdose risk. Themes were identified inductively and deductively using the Risk Environment Framework and its domains, which organizes themes along physical, social, economic, and policy environments on both the micro- and macro- scales.ResultsThe physical risk environment included loss of opioid tolerance during incarceration, polysubstance use, and the toxicity of the regional drug supply as key producers of increased risk for post-release overdose. Social drivers of risk included peer group risk norms—including peer-driven harm reduction practices and interpersonal relationships between drug sellers and buyers—as well as macro-level social determinants of health such as housing insecurity and availability of mental health services. Economic drivers of post-release overdose risk included lack of income generation during incarceration and employment challenges. Participants discussed several aspects of policy that contribute to post-release overdose risk, including availability of harm reduction supplies, public health services, and broader policy around MOUD.ConclusionsThe perspectives of people with lived experience are vital to understanding the disproportionate risks of overdose for those recently released from incarceration. Our results highlight the intersectional factors that produce and reproduce the post-release overdose risk environment, providing support for interventions across each domain of the Risk Environment Framework. By capturing perspectives from people with lived experience of OUD and incarceration during this critical period of risk, we can better identify interventions that target and mitigate overdose-related harm in this population.

Discovering the determinants of energy intensity of Indian manufacturing firms: a panel data approach

Our study pores on evaluating the impact of firm specific and macro level determinants of energy intensity of Indian firms belonging to manufacturing and power sector. We collect a panel dataset of 3316 firms for 10 years ranging from 2010 to 2020. We employ the advanced biased corrected method of moments estimator and the quantile regression estimator for panel data models for our empirical analysis. We find that poor labor efficiency is largely responsible for increasing energy intensity of the sample firms. Energy intensity can be optimized by investing in better plant and machinery. Moreover, machineries that require frequent repairs and maintenance need to be replaced with latest tools. While larger firms are found to be energy intensive, profitable firms are found to be in a better position to enhance their energy efficiency. Under macroeconomic scenario, GDP growth and trade openness lead to boosting up the energy consumption at the firm level whereas, the global energy prices act as a constraint and necessitate careful use of energy. Based on our findings we provide certain policy recommendations and suggestions in order to limit energy intensity and enhance energy efficiency of the Indian manufacturing firms.

Macro-level determinants of entrepreneurial behavior and motivation

Macro-level determinants of entrepreneurial behavior and motivation

Assessment of working capital management efficiency – a two-stage slack-based measure of data envelopment analysis

PurposeThis study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and macro-level determinants on working capital management (WCM) efficiency.Design/methodology/approachThe current study accommodates a slack-based measure (SBM) in data envelopment analysis (DEA) for computing WCM efficiency. Further, we implement a panel data fixed-effects model that controls for heterogeneity across firms in determining the relationships of selected variables with WCM efficiency.FindingsThe results highlight that manufacturing firms operate at around 50 percent efficiency, which is constant throughout the study period. Furthermore, among the selected variables, yield, earnings, age, size, ability to create internal resources, interest rate and gross domestic product (GDP) significantly affect WCM efficiency.Originality/valueInstead of the traditional models used for assessing efficiency, the SBM-DEA model is unit-invariant and monotone for slacks, implying that it can handle zero and negative data, which overcomes the incapability of prior DEA models. Hence, this provides accurate efficiency scores for robust analysis. Additionally, this paper provides a holistic working capital model recognizing firm-specific and macro-level determinants for a more explicit estimation of the relationship between WCM efficiency and the selected determinants.

A Semantic Approach to Describe Social and Economic Characteristics That Impact Health Outcomes (Social Determinants of Health): Ontology Development Study.

Social determinants of health (SDoH) have been described by the World Health Organization as the conditions in which individuals are born, live, work, and age. These conditions can be grouped into 3 interrelated levels known as macrolevel (societal), mesolevel (community), and microlevel (individual) determinants. The scope of SDoH expands beyond the biomedical level, and there remains a need to connect other areas such as economics, public policy, and social factors. Providing a computable artifact that can link health data to concepts involving the different levels of determinants may improve our understanding of the impact SDoH have on human populations. Modeling SDoH may help to reduce existing gaps in the literature through explicit links between the determinants and biological factors. This in turn can allow researchers and clinicians to make better sense of data and discover new knowledge through the use of semantic links. An experimental ontology was developed to represent knowledge of the social and economic characteristics of SDoH. Information from 27 literature sources was analyzed to gather concepts and encoded using Web Ontology Language, version 2 (OWL2) and Protégé. Four evaluators independently reviewed the ontology axioms using natural language translation. The analyses from the evaluations and selected terminologies from the Basic Formal Ontology were used to create a revised ontology with a broad spectrum of knowledge concepts ranging from the macrolevel to the microlevel determinants. The literature search identified several topics of discussion for each determinant level. Publications for the macrolevel determinants centered around health policy, income inequality, welfare, and the environment. Articles relating to the mesolevel determinants discussed work, work conditions, psychosocial factors, socioeconomic position, outcomes, food, poverty, housing, and crime. Finally, sources found for the microlevel determinants examined gender, ethnicity, race, and behavior. Concepts were gathered from the literature and used to produce an ontology consisting of 383 classes, 109 object properties, and 748 logical axioms. A reasoning test revealed no inconsistent axioms. This ontology models heterogeneous social and economic concepts to represent aspects of SDoH. The scope of SDoH is expansive, and although the ontology is broad, it is still in its early stages. To our current understanding, this ontology represents the first attempt to concentrate on knowledge concepts that are currently not covered by existing ontologies. Future direction will include further expanding the ontology to link with other biomedical ontologies, including alignment for granular semantics.

Closer is more important: The impact of Chinese and global macro-level determinants on Shanghai crude oil futures volatility

<p>Using the GARCH-MIDAS model, we investigated the impact of Chinese and global macro-level determinants on the return volatility of Shanghai crude oil futures, covering Chinese and global economic policy uncertainty, Chinese and global crude oil demand as well as production, Chinese crude oil import, and global crude oil speculation. The in-sample empirical results showed that Chinese crude oil demand, Chinese crude oil production, Chinese economic policy uncertainty, and global crude oil speculation have significant impact on the long-term volatility component of Shanghai crude oil futures. The out-of-sample prediction results show that Chinese current crude oil production and previous crude oil import have the relatively best predictive power for the return volatility of Shanghai crude oil futures. As a whole, Chinese domestic macro-factors have a stronger impact and higher predictive power on the return volatility of Shanghai crude oil futures compared with corresponding global macro-factors. Besides, the global crude oil speculation is the global macro-level determinant, which deserves most attention.</p>

ACCESS AND USAGE OF CARE AMONG OLDER MIGRANTS: CHALLENGES AND OPPORTUNITIES

Abstract Equitable access to care is critical to support healthy aging in underserved groups. Recent global demographic trends such as the rapid aging of the population in developing and developed countries, the growing proportion of migrants from the Global South to the Global North over the past 50 years, and increasing health inequalities between and within countries reflect a continued need to address the underlying pathways and causal mechanisms that determine access to and usage of care among migrants. This paper reviews the current state of knowledge on the micro-, meso-, and macro-level determinants that intersect and shape access to and usage of care services and programs among older migrants. It makes the case that foreign-born older adults are more likely to experience challenges accessing services and programs due to cultural and language barriers and factors related to their socio-economic status, race/ethnicity, gender, and time since immigration. Next, the paper provides a deeper exploration of the interface of structure and agency and an interrogation of how access and usage of care among older migrants may be conditioned, not simply by individual socio-economic circumstances and life course events, but also by macro-level factors like the distribution of power relationships and neoliberal public policies. The paper concludes with a call for sustained efforts to acquire a more profound understanding of individual-level, socio-economic and socio-political forces that influence access and usage of care. Finally, it provides directions for future research with the ultimate goal of supporting healthy aging among older migrants.

Socio and macroeconomic determinants of mobile money adoption: a cross-cultural study of selected MENA and Sub-Saharan countries

PurposeThis study aims to investigate the factors contributing to the low adoption rate of mobile money services (MMS) in the Middle East and North Africa (MENA) region compared to other regions. The study focussed on socio-demographic factors and macro-level determinants in several selected MENA and Sub-Saharan African (SSA) regions where MMS have been successful.Design/methodology/approachThis study analysed 23 countries across MENA and SSA to establish the correlation between socio and macroeconomic factors and MMS adoption using a quantitative approach. The analysis used the generalized least square (GLS) method.FindingsThe study revealed that gender and income are factors that positively influence the adoption of MMS in MENA and SSA regions. Additionally, the study found that the affordability index, which measures macroeconomic indicators, correlates with MMS adoption in both regions but in an inversed way. On the other hand, political stability appears to have a positive correlation with MMS adoption in the MENA region. The correlation between the regulatory index and MMS adoption positively impacts the entire study group, although it is insignificant in the SSA region.Research limitations/implicationsFuture studies should assess market competition among MMS providers and the psychological aspect of user adoption behaviour. Additionally, conducting a focus group discussion with stakeholders in the MMS industry can assist in uncovering potential factors contributing to low MMS adoption in the MENA region.Originality/valueThis study contributes to understanding the role of the socio-demographic and macroeconomic determinants in promoting digital transformation through adopting MMS.

The Market Reaction to Repurchase Announcements

This paper investigates the drivers of the market’s reaction to share repurchase announcements in the UK and the related abnormality in stock performance. It uniquely captures the impact of globalisation in tandem with a variety of firm-level and macro-level determinants. We undertake multivariate OLS regression to test the determinants of the market’s reaction and find a negative influence when repurchases are tax-friendlier than dividends if there is high debt exposure and economic globalisation is rising, with a positive influence when the company has a history of distributing above average dividends. To quantify the short-term price abnormality, we employ event study analysis, and the findings compute positive (insignificant) stock price abnormality for nonfinancial (financial) firms. For long-term stock price abnormality, we compare against the FTSE 100 by computing annual geometric stock performances. The findings indicate a negative (insignificant) stock price abnormality for nonfinancial (financial) firms. The results can aid corporate management in improving repurchase timing, aid in the decision making of financial practitioners when trading or investing in repurchasing firms, and assist policymakers in mapping more efficient fiscal and cross-market trade frameworks.

Public attitudes towards dialects: Evidence from 31 Chinese provinces.

Dialect Attitude is conceptualized as an individual's cognitive and affective evaluation of a dialect and its speakers. In the contemporary China, dialect is suffering from significant stigmatization, resulting in social inequalities, which hinder sustainable development. This study aims to reveal the Chinese public attitudes towards dialects, and clarify the potential determinants related to heterogeneous attitudes at a macro level. We combine the crawler technology and sentiment analysis to conduct a provincial cross-sectional study. We collect 1,650,480 microblogs about public attitudes towards dialects from Microblog across 31 specific Chinese provinces. Spatial regression models are utilized to clarify the influence of macro-level determinants on differences in public attitudes. The present study reveals that: (1) The Chinese public generally holds positive attitudes towards dialects, with significant variation between provinces. (2) Political Resource (β = 0.076, SD = 0.036, P<0.05), Economic Development (β = 0.047, SD = 0.022, P<0.05), and Cultural Resource (β = 0.054, SD = 0.021, P<0.05) promote public positive attitudes towards dialects. (3) Political Resource and Culture Resource influence more significant in the relatively advantaged regions, and Economic Development poses a higher influence in the relatively disadvantaged regions. Basing on the combination of crawler technology and sentiment analysis, the present study develops the most comprehensive database which takes 1,650,480 dialects-related microblogs from 31 Chinese provinces, and describes the following scenario: (1) Overall, the Chinese public shares a relatively positive attitude towards dialects with significant variations among different provinces, (2) Political Resource, Economic Development and Culture Resource pose positive effects on Chinese public attitudes towards dialects and (3) Political Resource and Culture Resource influence more significant in the relatively disadvantaged regions, and Economic Development poses a higher influence in the relatively advantaged regions.

Labour informality in forestry: A longitudinal (2009–2020) cross-country analysis of determinants in 70 developing countries

Informality accounts for a significant proportion of the forestry labour market and provides a critical livelihood option for millions of people in developing regions. Recent estimates reveal that at least three million people were informally employed in forestry. Nonetheless, informality is highly characterized by decent work deficits, profoundly impacting employment quality and sectoral development. It is thus crucial to contextualize which factors determine the prevalence of informality in the forestry sector to advance decent work and livelihood opportunities. The present study examines macro-level determinants of forestry-related informality using a cross-country panel dataset over the 2009–2020 period. Our analysis covers 70 developing countries in Africa, the Americas and Asia. Results from econometric models confirm that the widespread informality in forestry is a co-presence of exclusion and exit perspectives. Informality is significantly associated with economic recession and deforestation after controlling for possible endogeneity. Study findings further suggest that fostering education and forest certification compliance, along with control of corruption and ratifying international labour standards on freedom of association and labour inspection, can lessen the incidence of forestry-related informality. A balanced mix of policies and strategies that emphasize improving the identified determinants is thus decisive. This further necessitates tailoring them to the nature of forestry labour markets to address the existing issues of informality in the sector. Expanding temporal and spatial coverage of statistics on the informal economy will enhance future studies to examine patterns of informality in forestry across regions' development levels and evaluate the long-term effects of determinant factors.

The structural and social determinants of Alzheimer's disease related dementias.

The projected growth of Alzheimer's disease (AD) and AD-related dementia (ADRD) cases by midcentury has expanded the research field and impelled new lines of inquiry into structural and social determinants of health (S/SDOH) as fundamental drivers of disparities in AD/ADRD. In this review, we employ Bronfenbrenner's ecological systems theory as a framework to posit how S/SDOH impact AD/ADRD risk and outcomes. Bronfenbrenner defined the "macrosystem" as the realm of power (structural) systems that drive S/SDOH and that are the root cause of health disparities. These root causes have been discussed little to date in relation to AD/ADRD, and thus, macrosystem influences, such as racism, classism, sexism, and homophobia, are the emphasis in this paper. Under Bronfenbrenner's macrosystem framework, we highlight key quantitative and qualitative studies linking S/SDOH with AD/ADRD, identify scientific gaps in the literature, and propose guidance for future research. Ecological systems theory links structural/social determinants to AD/ADRD. Structural/social determinants accrue and interact over the life course to impact AD/ADRD. Macrosystem is made up of societal norms, beliefs, values, and practices (e.g., laws). Most macro-level determinants have been understudied in the AD/ADRD literature.

Multiscale spatial analysis of macro-level determinants of bicycle crash frequencies in the Phoenix metro region

The realization of the many benefits of bicycling will not be achieved in American regions until safer bike infrastructure and bicycling conditions are presented to a more general population. The Phoenix region—one of the nation’s most populous—has sought policies and programs to increase bicycling rates. Yet, the region continues to have a small mode share, underscoring a need to motivate population-level bicycling adoption. This study examines 2015–2019 bicycle-vehicle crash data to identify those macro-level factors associated with bicycle-vehicle crashes and a subset of crashes where a serious injury or fatality occurred. Specifically, the effects of a robust set of socioeconomic and built environment factors, measured at three hexagon spatial extents, in negative binomial and spatial Durbin models were estimated for the two crash outcomes. Results show denser zones with a traditional network design experienced more bicyclist-involved crashes, as did zones with a higher percentage of low-income households and working-age adults. Findings, which also found spatial clustering of total and severe bicyclist-involved crashes, suggest that the targeted provision of safer bike infrastructure and a more complete network in zones exhibiting certain macro-level attributes holds promise in creating bike-friendly conditions that generate more utilitarian and recreational bicycling throughout the region.

Socioeconomic Macro-Level Determinants of Hypertension: Ecological Analysis of 138 Low- and Middle-Income Countries.

To assess the relative importance of major socioeconomic determinants of population health on the burden of hypertension in Low-and-Middle-Income Countries (LMICs). Country-level data from 138 countries based on World Development Indicators 2020 were used for correlation and linear regression analyses of eight socioeconomic predictors of hypertension: current health expenditure, domestic general government health expenditure per capita, GDP per capita, adult literacy rate, unemployment rate, urban population, multidimensional poverty index, and total population. The median prevalence of age-standardised hypertension was 25.8% across the 138 countries, ranging from 13.7% in Peru to 33.4% in Niger. For every 10% increase in the unemployment rate, the prevalence of hypertension increased by 2.70%. For every 10% increase in the percentage of people living in urban areas, hypertension was reduced by 0.63%. The findings revealed that countries with high GDP, more investment in health and an improved multidimensional poverty index have a lower prevalence of hypertension.

Macro-Level Determinants of Financial Inclusion of the Underprivileged

Macro-Level Determinants of Financial Inclusion of the Underprivileged