Purpose The purpose of this paper is to explore how the use of social media by citizens has impacted the traditional conceptualization and operationalization of political participation in the society. Design/methodology/approach This study is based on Teorell et al.’s (2007) classification of political participation which is modified to suit the current context of social media. The authors classified 15,460 tweets along three parameters suggested in the framework with help of supervised text classification algorithms. Findings The analysis reveals that Activism is the most prominent form of political participation undertaken by people on Twitter. Other activities that were undertaken include Formal Political participation and Consumer participation. The analysis also reveals that identity of participant does not play a classifying role as expected from the theoretical framework. It was found that the social media as a platform facilitates new forms of participation which are not feasible offline. Research limitations/implications The current work considers only the microblogging platform of Twitter as the data source. For a more comprehensive insight, analysis of other social media platforms is also required. Originality/value To the best of the authors’ knowledge, this is one of the few analyses where such a large database covering multiple social media events has been created and analysed using supervised text classification algorithms. A large proportion of previous studies on social media have been based on case study and have limited analysis to only a particular event on social media. Although there exist a few works that have studied a vast and varied collection of social media data (Gaby and Caren, 2012; Shirazi, 2013; Rane and Salem, 2012), such efforts are few in number. This study aims to add to that stream of work where a wider and more generalized set of social media data is studied.
A number of studies have examined the failures of e-government efforts from various theoretical perspectives in the domains of government-to-citizen (G2C) and government-to-business (G2B). However, only a few studies have been done in government-to-government (G2G) e-government projects. This paper examines the impasse reached during the implementation of a statewide Digital Secretariat Project in India through the lens of stakeholder theory. A qualitative case study approach employing semi-structured interviews with the stakeholders was employed to explore the issue. The results reveal the importance of power dynamics, which can stall the entire project. In a G2G project, that is interactional in nature and has to be used by multiple departments, it is crucial for the implementing agency to identify dominant stakeholder departments and take them into confidence right from the beginning of the project. In such cases intervention by higher level government offices is important to impart saliency to the implementing agency and prevent any other dominant stakeholder from stalling the project. Undertaking such widespread projects without strong government support can lead to failure of implementation and waste of important public resources. Implications for theory and practice are discussed.
Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.
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