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The purpose of this paper is to review and critique the existing literature on entrepreneurial teams (ET) by taking a multi-disciplinary viewpoint and provide a future research agenda based on the identified themes and trends.

A systematic literature review (SLR) was undertaken using “business source complete”. Further scrutiny and application of exclusion criteria led to a final sample consisting of 139 papers from 27 different journals belonging to not just entrepreneurship and strategic management but also other disciplines like OB, finance, sociology, psychology, etc. Using qualitative thematic analysis, the authors identified 11 major themes.

The paper reviews both the eleven themes and the linkages between the themes. Thereby identifying areas that have been understudied and those that have received comparatively more attention. The review revealed that the research stream possesses certain conceptual and methodological concerns apart from its cross-sectional and primarily bivariate nature. Five such main concerns have been identified and discussed in detail. Other elements of the resulting research agenda include calls for more clinical process-oriented research, further attention to context, shifting the level of analysis, and a need to integrate across disciplines.

This paper incorporates a broad insight of ET across academic disciplines to show how future contributions could benefit by incorporating research from other fields. In doing so, provides a starting point for more nuanced discussions around the interrelationships between the different conversations that are taking place in the ET literature.

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.

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.

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.

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.

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.

The purpose of this paper is to make a unified approach in identifying the issues affecting usage intention of mobile-based payment services. The work aims to analyze the reduced factors from data obtained from a survey to highlight the influencers of usage intention mobile-based payment in an integrated manner by incorporating the technical characteristics, technology-specific characteristics, user-specific characteristics and task-specific characteristics.

A nationwide primary survey was conducted using validated questionnaire requesting response for 11 factors obtained from published literature. In all, 196 respondents participated in the survey in India. Valid responses were analyzed using Growing Hierarchical Self-Organizing Map (GHSOM) model. The interactive GHSOM application was applied to automatically determine the filtering rules for clustering.

The hierarchical structure of clusters as obtained by applying GHSOM is mainly influenced by factors like innovativeness, discomfort, system quality, perceived usefulness, perceived ease of use, task-fit, connectivity, absorptive capacity and structural assurance.

Increasing trend of online and mobile-based payment has been observed and reported by several studies in India. The frequency of online transactions by women have shown a steady increase over a short period of time. But the survey obtained higher percentage of data from males. Thus future researchers could focus on this aspect to study the influence of this rising trend on adoption of services like mobile-based payment. Trust and existence of physical institutions seem to affect the perception and usage intention. Future researchers may explore the influence of these two issues in situations where there has been some reported cases of breach of trust.

There has been very few studies conducted which reported mobile-based transfer payment adoption issues where-in the transfer mechanism is independent of formal banking. Also no other study adopted the GHSOM approach to analyze the data. The findings would be beneficial for service providers of mobile-based payment services to understand their subscribers and roll out value-added services.