Search arXivSearch

arXiv · 2212.13840

The relationship between social innovation and digital economy and society

Abstract

The information age is also an era of escalating social problems. The digital transformation of society and the economy is already underway in all countries, although the progress in this transformation can vary widely. There are more social innovation projects addressing global and local social problems in some countries than in others. This suggests that different levels of digital transformation might influence the social innovation potential. Using the International Digital Economy and Society Index and the Social Innovation Index, this study investigates how digital transformation of the economy and society affects the capacity for social innovation. A dataset of 29 countries was analysed using both simple and multiple linear regressions and Pearsons correlation. Based on the research findings, it can be concluded that the digital transformation of the economy and society has a significant positive impact on the capacity for social innovation. It was also found that the integration of digital technology plays a critical role in digital transformation. Therefore, the progress in digital transformation is beneficial to social innovation capacity. In line with the research findings, this study outlines the implications and possible directions for policy.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Szabolcs Nagy, Mariann Veresne Somosi. 2022-12-26. The relationship between social innovation and digital economy and society. https://doi.org/10.15196/rs120202

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

The time interpretation of expected utility theory

Economic models often maximise expectation values of wealth or utility. In non-ergodic settings, these can differ from time-averages, so that maximising expected outcomes need not maximise – and can systematically reduce – long-run wealth or utility. Ergodicity economics highlights this problem and models individual agents as maximising wealth in the long run, known as growth optimality. Two instances where expected utility maximisation maps to growth optimality are known: linear utility does this for additive wealth dynamics; and logarithmic utility for multiplicative wealth dynamics. Here we show that the mapping holds more generally when the utility function coincides with the ergodicity transformation in the growth optimal model. This mapping offers a theoretical basis for choosing utility functions and suggests the testable hypothesis that wealth dynamics are predictive of risk preferences.

econ.GN

Monetary Regimes and Trade before the Classical Gold Standard: Evidence from the Latin Monetary Union

This paper reexamines the trade effects of the Latin Monetary Union (LMU), a 19th century agreement to standardize gold and silver coinage among several European countries. The LMU provides a useful setting for studying whether monetary arrangements fostered trade before the classical gold standard, when gold, silver, bimetallic, and paper regimes coexisted. Because some countries already shared other monetary standards, treating all non-member pairs as a single control group mixes pairs with and without alternative forms of monetary coordination. I classify pairs by standard and estimate the LMU effect relative to pairs without a common standard, bringing the comparison closer to those used in the literature on the gold standard and contemporary currency unions. The results suggest that the LMU increased trade between its members by approximately 30\% during its early years, when bimetallism was still credible. These effects subsequently faded, converging to zero by the end of the 1870s. More broadly, these findings also highlight the importance of accounting for the existing monetary regimes when estimating the trade effects of other international policies.

econ.GN

Access to Live AI Advice and Behavior Under Risk: An Incentivized Experiment

Generative AI has become an everyday advisor, and the systems people consult are live and interactive, not pre-scripted. We ask whether access to such a system changes behavior under risk. In an incentivized experiment (N = 158), participants made lottery choices with an optional decision aid presented as a conventional pre-written tool, a live one-shot AI, or a live interactive AI they could query, with information format held equivalent across conditions. Risk preferences are elicited via DOSE. We find no evidence that access to a live AI advisor changes risk aversion.

econ.GN