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on Social Norms and Social Capital |
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Issue of 2025–04–21
seven papers chosen by Fabio Sabatini, Università degli Studi di Roma “La Sapienza” |
| By: | Harris, Tom (Harvard University); Iyer, Shankar; Rutter, Tom; Chi, Guanghua; Johnston, Drew; Lam, Patrick; Makinson, Lucy; Silva, Antonio S.; Wessel, Martin; Liou, Mei-Chen |
| Abstract: | Social capital is widely believed to impact a wide range of outcomes including subjective well-being, social mobility, and community health. We aggregate data on over 20 million Facebook users in the United Kingdom to construct several measures of social capital including cross-type connectedness, social network clustering, and civic engagement and volunteering. We find that social networks in the UK bridge class divides, with people below the median of the socioeconomic status distribution (low-SES people) having about half (47%) of their friendships with people above the median (high-SES people). Despite the presence of these cross-cutting friendships, we find evidence of homophily by class: high-SES people have a 28% higher share of high-SES friends. In part, this gap is due to the fact that high-SES individuals live in neighbourhoods, attend schools, and participate in groups that are wealthier on average. However, up to two thirds of the gap is due to the fact that high-SES people are more likely to befriend other high-SES peers, even within a given setting. Cross-class connections vary by region but are positively associated with upward income mobility: low-SES children who grew up in the top 10% most economically connected local authorities in England earn 38% more per year on average (£5, 100) as adults relative to low-SES children in the bottom 10% local authorities. The relationship between upward mobility and connectedness is robust to controlling for other measures of social connection and neighbourhood measures of income, education, and health. We also connect measures of subjective well-being and related concepts with individual social capital measures. We find that individuals with more connections to high-SES people and more tightly-knit social networks report higher levels of happiness, trust, and lower feelings of isolation and social disconnection. We make our aggregated social capital metrics publicly available on the Humanitarian Data Exchange to support future research. |
| Date: | 2025–03–23 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:kb7dy_v1 |
| By: | Nicolás Ajzenman; Cevat Giray Aksoy; Sergei Guriev |
| Abstract: | Does exposure to mass migration affect the attitudes and economic behavior of natives in transit countries? In order to answer this question, we use a unique locality-level panel from the 2010 and 2016 rounds of the Life in Transition Survey and data on the main land routes taken by migrants in 18 European countries during the refugee crisis in 2015. To capture the exogenous variation in natives’ exposure to transit migration, we construct an instrument that is based on each locality’s distance to the optimal routes that minimize traveling time between refugees’ main origins and destinations. We find that the entrepreneurial activity of native population falls considerably in localities that are more exposed to mass transit migration, compared to those located farther away. We explore potential mechanisms and find that exposure to mass transit migration results in lower confidence in government, higher perceived political instability, and less willingness to take risks. We also document an increase n anti-migrant sentiment while attitudes towards other minorities remain unchanged |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:udt:wpgobi:20250319 |
| By: | Fernandez-Urbano, Roger |
| Abstract: | This article explores the relationship between individuals’ satisfaction with their social life and global life satisfaction during periods of economic prosperity and crisis, using data from the Panel of Social Inequalities in Catalonia, Spain (PaD 2001-2012). The study also investigates how this relationship varies across different social origins. Catalonia is a pertinent context due to its significant increase in inequality and unemployment during the 2008 Economic Crisis, positioning it among the most affected regions in Europe. The findings reveal that satisfaction with one’s social life matters for global life satisfaction, even after accounting for individual and macro characteristics. However, contrary to the initial expectations, the study demonstrates that satisfaction with one’s social life becomes less influential for global life satisfaction during the macroeconomic crisis, particularly among individuals from middle and low social origins. Furthermore, while a strong positive relationship exists between satisfaction with one’s social life and global life satisfaction during times of economic prosperity for all social groups, a robust negative relationship emerges in periods of macroeconomic crisis for individuals from high social origins. The article offers several potential explanations for these findings. |
| Date: | 2024–03–26 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:6sj2t_v1 |
| By: | Fernandez-Urbano, Roger |
| Abstract: | This chapter examines the relationship between satisfaction with social life and overall subjective well-being in Spain. Despite increasing recognition of social life as a key determinant of well-being, direct empirical research on its influence remains scarce, particularly in Southern Europe, where much of the existing evidence is anecdotal. Unlike concepts such as social capital, social support, and relational support, satisfaction with social life captures the intrinsic value of social interactions rather than their instrumental utility. It reflects an individual's subjective appraisal of their overall social relationships, encompassing not only close ties but also broader interactions with acquaintances, neighbours, and peripheral contacts. Drawing on data from the first wave of the Global Flourishing Study (2020–2022), this chapter investigates how social life satisfaction contributes to both cognitive and affective well-being. Spanish findings are contextualized within a comparative framework, including high-income, upper-middle-income, and lower-middle-income countries. The results highlight that subjective evaluations of social life play a crucial role in shaping overall well-being, surpassing the influence of individual characteristics. Furthermore, the significance of social life satisfaction for both cognitive and affective well-being increases with socioeconomic development, positioning Spain alongside upper-middle-income countries with collectivistic and Latin cultural orientations. An analysis of heterogeneity within Spain reveals no substantial variations across gender, social background, or regions. However, significant age-related differences emerge, with the importance of social life satisfaction on overall well-being—particularly affective well-being—increasing with age. The chapter concludes by discussing theoretical and practical implications and outlining directions for future research, including methodological considerations. |
| Date: | 2025–03–26 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:tdm4c_v1 |
| By: | Laura Onofri; Conrad Landis; Phoebe Koundouri |
| Abstract: | The study performs a qualitative meta-analysis of literature on economic valuation of spiritual values, to possibly assess and attach them a common meaning and content. We apply the qualitative meta-analysis procedure, developed by Atkins et al. (2008), and validated by econometric analysis, to (1) literature on spiritual ecosystem services (SES) valuations studies and to (2) literature on measurement of spiritual capital impacts on economies and markets, with a focus on religious markets. Markets and economies, in fact, are complex social structures, where the spiritual values originated in environmental and ecosystem contexts might change connotation and significance. Results show that when spiritual values are expressed as nature direct consumption or instinctual feedback from nature, they seem to have a use value at personal level and a negative impact at social level (economies and institutions). When spiritual values are expressed as responsibility and connection through nature they have a non-use value at personal level and a positive impact at social level (economies and institutions). In this perspective, qualitative meta-analysis results may offer a preliminary support for a better understanding, design and implementation of quantitative and monetary valuation methods for SES and other spiritual values. |
| Keywords: | spiritual values, ecosystems, spiritual ecosystem services, spiritual capital, spiritual capital impacts on economies and markets, qualitative meta-analysis |
| JEL: | Z12 Q01 Q57 O10 |
| Date: | 2025–04–15 |
| URL: | https://d.repec.org/n?u=RePEc:aue:wpaper:2530 |
| By: | Fecho, Mariska |
| Abstract: | The advent of artificial intelligence (AI) has significantly transformed the digital landscape, offering substantial potential for innovation and advancement across multiple fields. With the ability to automate complex tasks, analyze large datasets in real-time, and make autonomous decisions, AI and machine learning (ML) in particular offer new opportunities for organizations and individuals to solve problems. For instance, AI systems assist organizations in enhancing the efficacy and efficiency of their processes. Hence, AI has become a key driver in the evolution of industries such as healthcare, finance, manufacturing, and education, pushing the boundaries of what is possible in the digital age. Moreover, AI’s integration into everyday applications – such as the generation of personalized recommendations, the provision of healthcare services, or the automation of driving – provides valuable support for individuals in their daily lives. Beyond the potential for saving time by optimizing product selection when shopping online, AI-based systems can also serve the personal well-being of individuals. However, while some organizations have begun to apply AI to their core processes, the full potential of AI has yet to be realized. This is particularly the case in areas that do not directly impact an organization's effectiveness but are crucial to long-term success and compliance. Thus, the transformative power of AI in these critical yet undervalued domains remains largely untapped. Previous studies have demonstrated that the adoption of AI in organizations is a complex and challenging process, often associated with a range of difficulties and obstacles. On the one hand, this is due to the distinctive attributes of AI in comparison to traditional information systems. On the other hand, technical and user-related challenges frequently impede the successful adoption of AI in organizations. Despite the existence of numerous research papers on AI, the factors influencing the adoption of AI in specific organizational contexts, such as corporate environmental sustainability, remain underexplored. This dissertation offers valuable insights into AI adoption in organizations, particularly in the context of corporate environmental sustainability. In addition to the examination of technical and organizational factors, the influence of the external organizational environment is also investigated. Moreover, trust is crucial for the decision to adopt and use AI. The unique characteristics of AI including autonomy, learning capabilities, and the complexity of its decision-making processes can give rise to skepticism and impede its usage. In particular, a lack of knowledge about AI’s decision-making processes and outcomes can lead to concerns, making trust a critical element in achieving the widespread adoption and usage of AI. While trust often has been previously investigated as a single construct within the context of AI, this dissertation additionally considers the impact of diverse trust concepts on human behavior. This dissertation aims to provide a comprehensive understanding of AI adoption in the context of corporate environmental sustainability and offer actionable knowledge for enhancing trust in AI technologies. Two quantitative studies, a qualitative study, and an experimental study were conducted in this cumulative dissertation to investigate AI’s adoption with a focus on trust. The results of these studies were published in peer-reviewed conference proceedings. The four published studies contribute to theory development by revealing the factors influencing the organizational adoption of AI. Furthermore, they highlight the role of trust in AI and its impact on human behavior. Additionally, the research papers presented in this dissertation offer valuable guidance for practitioners. The first part of this dissertation comprises two research papers that examine the organizational adoption of AI. Paper A addresses the adoption of green AI in the context of corporate environmental sustainability, whereas Paper B analyzes the influence of external pressures on green AI adoption. For Paper A, interviews with 21 experts from various industries were conducted to provide an integrative framework including factors that determine the adoption of green AI. As a result, eight propositions were developed to explain the effects of the identified factors. For Paper B, an anonymous online survey was conducted with 453 participants to investigate the influence of specific factors, including external pressures, on the adoption of green AI. The key findings of Paper B indicate that coercive, mimetic, and normative pressures significantly influence green AI adoption, while top management support mediates these pressures’ effects. This highlights the pivotal role of high-level decision-makers within organizational contexts and the role of external influences. Furthermore, the second part of this dissertation examines the role of trust in AI. Previous research has indicated that trust is critical when using new information systems. This dissertation confirmed that trust in AI can facilitate the use of such systems. While papers A and B report results at the organizational level, papers C and D focus on the individual user. In particular, Paper C examines trust as a multidimensional concept, emphasizing cognitive and emotional trust in AI depending on two types of AI vendors (i.e., automobile manufacturers and technology companies). By conducting a large-scale anonymous online survey with 687 participants, a multi-group analysis revealed different degrees of trust depending on the vendor types. In particular, emotional trust is more important for technology companies, whereas cognitive trust has a greater impact on automobile manufacturers. Understanding how trust influences the intention to use AI systems is crucial, but knowing how to design trustworthy AI systems is also important. This ensures that AI systems are more likely to be adopted and used to their full potential, as users will be more willing to rely on and integrate these technologies into their daily lives. Thus, a design science research methodology is used in Paper D to develop design principles for a user-centered, trustworthy AI, namely a ML system. After conducting an effectiveness test, the results revealed that the design of the ML system based on the design principles is perceived as more trustworthy than existing designs. In summary, this dissertation contributes to the successful organizational adoption of AI, particularly in the context of corporate environmental sustainability, by providing a comprehensive overview of adoption factors. This work guides practitioners and decision-makers in the adoption process and helps organizations prepare to gather the necessary resources for adopting AI. In addition, the findings highlight the importance of trust for AI usage and provide insights into different trust concepts. By specifying design principles for a trustworthy and user-centered ML system, this dissertation guides developers in developing trustworthy ML systems. Such ML-based systems have the potential to facilitate the use of AI in everyday contexts. Moreover, the dissertation contributes to the advancement of theory by offering novel insights grounded in established theoretical models and provides researchers with a deeper comprehension of the factors influencing the adoption of AI, particularly the critical role of trust. |
| Date: | 2025–03–18 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:153649 |
| By: | Wang, Weijia (Dept. of Economics, Norwegian School of Economics and Business Administration); Valasek, Justin (Dept. of Economics, Norwegian School of Economics and Business Administration) |
| Abstract: | The experimental literature on preferences for redistribution has established that individual perceptions of what earning distributions are fair depend greatly on context. In this paper, we study an important and novel dimension of context: whether the choice to redistribute occurs before workers work and accrue earnings, or after. Contrary to the predictions of our theoretical framework, we fi nd no evidence that spectators are less likely to equalize earnings ex ante than to equalize earnings ex post. Interestingly, our study also suggests that, relative to American subjects, Scandinavian subjects are more likely to equalize ex post earnings, but we find no evidence that Scandinavian and American subjects make different choices ex ante. A follow-up analysis suggests that the latter result is largely due to Scandinavian and American subjects having similar preferences over ex ante redistribution when equalizing earnings comes at a cost to efficiency. Overall, our results suggest that context-dependent preferences for redistribution are sensitive to the relative timing of the redistribution choice. |
| Keywords: | Inequality; Fairness; Institutions; Experiment |
| JEL: | C91 D63 J16 |
| Date: | 2025–04–01 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:nhheco:2025_008 |