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This study aims to explore the factors affecting the adoption of mGov apps using the theoretical foundations of service-dominant (SD) logic. The authors specifically explore the impact of resource distribution (infrastructure and knowledge) and environmental variables (health infrastructure) among the Indian states on the adoption of Aarogya Setu (the COVID-19 tracking app) by their citizens.

For the meso-level study, the states of India are the unit of analysis. The authors have used secondary data published by the government and other reliable organizations. The study is based on 29 states of India and Delhi, a union territory and the capital of India. The authors conducted a regression and moderation analysis using SPSS and PROCESS macros on the collected secondary data.

The findings reveal that operand resources (state domestic productivity per capita and internet penetration rate) positively impact the adoption of the mGov app. The operant resource (literacy) and the environmental variable (health index) are, however, negatively affecting the adoption of the mGov app. On the other hand, another operant resource, digital literacy, was found to have no significant effect on the adoption of the mGov app. Further, the moderating variable, health index, is found to be moderating all the relationships except internet penetration and adoption of the mGov app.

The study is novel in two aspects. First, in using the theoretical foundation of SD logic to examine the factors impacting the adoption of mGov app. Second, it is a meso-level study, which is not a widely explored avenue in mGov research.

This paper aims to investigate the mechanisms through which social media news consumption across different platforms leads to opinion polarization in society. To this end, the authors draw from cultivation theory to examine whether social media news consumption imparts a mainstreaming or resonance effect. Media consumption imparts a mainstreaming effect if frequent users, regardless of their social identity, develop homogenous attitudes about issues, whereas resonance is at play if there is a differing cultivation effect on various social groups depending on their relatability of life experiences.

The authors conduct the study in the developing context of India, using a population survey dataset from 2019. Regression-based mediation and moderation analyses were carried out to test the hypotheses.

The findings reveal that resonance is the most prominent mechanism through which social media news consumption cultivates opinion polarization, contrary to the mainstreaming effect imparted by television. Further, WhatsApp use was found to strengthen the polarizing effect of overall social media news consumption, while YouTube use weakened the cultivation of polarization.

The paper unearths how social media news consumption influences the opinion polarization of various social groups differently. The authors also find the differential effect of specific platform use. These findings have the potential to inform policymakers and developers about how to mitigate the detrimental effects of platform-based political persuasion.

This study offers significant contributions. First, the authors explain social media-induced polarization using the novel theoretical lens of cultivation. Second, the authors find that social media and television news consumption differ in their polarizing effects. Third, the authors find that while WhatsApp use amplifies the polarizing effect of social media news consumption, YouTube use weakens it.