A multilevel analysis of social capital and self-reported health: evidence from Seoul, South Korea

<p>Abstract</p> <p>Background</p> <p>This study aims to resolve two limitations of previous studies. First, as only a few studies examining social capital have been conducted in non-western countries, it is inconclusive that the concept, which has been developed in Western societies, applies similarly to an Asian context. Second, this study considers social capital at the individual-level, area-level and cross-levels of interaction and examines its associations with health while simultaneously controlling for various confounders at both the individual-level and area-level, whereas previous studies only considered one of the two levels. The purpose of this study is therefore to examine the associations between social capital and health by using multilevel analysis after controlling for various confounders both at the individual and area-levels (i.e., concentrated disadvantage) in non-western countries.</p> <p>Methods</p> <p>We conducted a cross-sectional survey from December 2010 to April 2011 in Seoul, South Korea. The target population included respondents aged 25 years and older who have resided in the same administrative area since 2008. The final sample for this study consisted of 4,730 respondents within all 25 of Seoul's administrative areas.</p> <p>Results</p> <p>In our final model, individual-level social capital, including network sources (OR = 1.23; 95% CI = 1.11-1.37) and organizational participation (OR = 2.55; 95% CI = 2.11-3.08) was positively associated with good/very good health. Interestingly, the individual × area organizational participation cross-level interaction was negatively associated with good/very good health (OR = 0.40; 95% CI = 0.32-0.50), indicating that in areas with higher organizational participation, individuals with high organizational participation were less likely to report good/very good health when compared to low organizational participation individuals.</p> <p>Conclusion</p> <p>Our study provides evidence that individual-level social capital is associated with self-reported health, even after controlling for both individual and area-level confounders. Although this study did not find significant relationships between area-level organizational participation and self-reported health, this study found the cross-level interaction for social capital. Hence, in areas with lower organizational participation, the probability of reporting good/very good health is higher for individuals with high organizational participation than individuals with low organizational participation. This study, albeit tentatively, suggests that policy makers should focus upon social capital when making policies which aim to enhance one's health.</p

Familiarity with Big Data, Privacy Concerns, and Self-disclosure Accuracy in Social Networking Websites: An APCO Model

Social networking websites have not only become the most prevalent communication tools in today’s digital age but also one of the top big data sources. Big data advocates promote the promising benefits of big data applications to both users and practitioners. However, public polls show evidence of heightened privacy concerns among Internet and social media users. We review the privacy literature based on protection motivation theory and the theory of planned behavior to develop an APCO model that incorporates novel factors that reflect users’ familiarity with big data. Our results, which we obtained from using a cross-sectional survey design and structural equation modeling (SEM) techniques, support most of our proposed hypotheses. Specifically, we found that that awareness of big data had a negative impact on and awareness of big data implications had a positive impact on privacy concerns. In turn, privacy concerns impacted self-disclosure concerns positively and self-disclosure accuracy negatively. We also considered other antecedents of privacy concerns and tested other alternative models to examine the mediating role of privacy concerns, to control for demographic variables, and to investigate different roles of the trust construct. Finally, we discuss the results of our findings and the theoretical and practical implications

Social capital and interlocal service collaboration in US counties

<p>Social capital and interlocal service collaboration in US counties. <i>Regional Studies</i>. Local governments are increasingly faced with public policy problems that span across their individual jurisdictional boundaries. Interlocal service collaboration has been suggested as a preferable alternative to address these issues. This study examines the association between collective social capital, especially focusing on Putnam-type organizations and interlocal service collaboration, by investigating the interlocal revenues at the county level for the fiscal year 2002 in the United States. An instrumental variables estimator to address a potential endogeneity problem of social capital was adopted. The results show that social capital is positively associated with interlocal service collaboration. Further analysis revealed that 15.8% of counties’ variation in interlocal service collaboration was attributed to the state level.</p

Construction Waste Reduction through Application of Different Structural Systems for the Slab in a Commercial Building: A South Korean Case

Construction waste generation along with the extensive consumption of natural resources has propelled researchers to investigate effective measures for minimising the waste. While several studies have shown that the structural design would be an influencing factor on the carbon dioxide emissions of a building, there is a lack of studies to corroborate the effect of different structural systems to generate waste during the construction stage. This article seeks to bridge some of the knowledge gaps regarding the waste generation from different structural systems during the construction phase in a building project in South Korea and demonstrate its potential for waste reduction. In this study, the amount of waste generation during the construction phase was calculated based on the quantities and the material loss rate of each building material to estimate the quantity of construction waste by the changes in the application of different structural systems for the slab of the studied model. The total waste generation during the construction phase of the different slab systems shows that the solid slab system produces the largest amount of construction waste, which is 101,361.385 kg. On the other hand, the void slab system generates 87,603.958 kg of the construction waste, which is the lowest amount among the four variables of this study. The additional purchasing costs due to the loss of construction materials indicate that the solid slab system would require 80,709.76 USD, which is the highest value of the four variables in this study. The void slab system would cost USD 50,054.12 for additional materials purchasing costs, which is approximately 38% lower than the solid slab system

Firm Size and Artificial Intelligence (AI)-Based Technology Adoption: The Role of Corporate Size in South Korean Construction Companies

This research addresses the factors that impact the acceptance of AI-based technologies or products depending upon firm size in the construction industry, in which various corporates exist. In order to achieve the research goals, a technology acceptance model was applied to investigate the influencing factors in respect to adopting AI-based technologies or products. From the research results, technological and organizational factors were found to positively influence perceived usefulness and perceived ease of use. Corporate users perceived that technology is useful to their work and is easy to use when enough capital and education were invested prior to the company adopting AI-based technologies or products. It was found that perceived ease of use and perceived usefulness indicate satisfaction with new technology, and the higher the intention to use, the higher the satisfaction. In addition, as various information sharing and distribution channels increase, the frequency of use of new technologies or products also increases, not through traditional marketing, but through viral marketing via social media or promotion by influential persons or organizations. Furthermore, there are differences in the adoption of AI-based technologies or products depending on the size of the company

Acceptance Model of Artificial Intelligence (AI)-Based Technologies in Construction Firms: Applying the Technology Acceptance Model (TAM) in Combination with the Technology&ndash;Organisation&ndash;Environment (TOE) Framework

In the era of the Fourth Industrial Revolution, artificial intelligence (AI) is a core technology, and AI-based applications are expanding in various fields. This research explored the influencing factors on end-user&rsquo;s intentions and acceptance of AI-based technology in construction companies using the technology acceptance model (TAM) and technology&ndash;organisation&ndash;environment (TOE) framework. The analysis of end-users&rsquo; intentions for accepting AI-based technology was verified by applying the structure equation model. According to the research results, the technological factors along with external variables and an individual&rsquo;s personality had a positive influence (+) on the perceived usefulness and the perceived ease of use of end-users of AI-based technology. Conversely, environmental factors such as suggestions from others appeared to be disruptive to users&rsquo; technology acceptance. In order to effectively utilise AI-based technology, organisational factors such as the support, culture, and participation of the company as a whole were indicated as important factors for AI-based technology implementation