Organizational Adoption of Sentiment Analytics in Social Media Networks

Enterprise adoption and application of sentiment analytics (SA) has recently attracted significant interest from both academia and industry, as it offers exciting opportunities to generate competitive intelligence on consumer attitudes and opinions. Yet, there is limited understanding of the factors underlying successful and widespread adoption of SA in enterprises. This study presents a systematic literature review (SLR) to analyze and summarize previous research on corporate adoption of SA in social media. The SLR examines the results of 83 studies and focuses on tasks, techniques, application domains, and factors that influence enterprise adoption of SA. The findings provide insights into (i) key factors influencing SA adoption, (ii) research trends and paradigms across disciplines, and (iii) potential areas for future research on enterprise adoption of SA. These findings recommend actionable future research agendas for scholars and inform practitioners' understanding of the decision-making processes involved in enterprise adoption of SA in social media.

Analysis of Factors Affecting Adoption of Volunteered Geographic Information in the Context of National Spatial Data Infrastructure

Spatial data infrastructures (SDIs) have been implemented for the last four decades in most countries. One of the key objectives of SDIs is to ensure the quick availability and accessibility of spatial data. The success of SDI depends on the underlying spatial datasets. Many developing countries such as Pakistan are facing problems in implementing SDI because of the unavailability of spatial data. Volunteered Geographic Information (VGI) is an alternate source for obtaining spatial data. Therefore, the question is what factors hamper the adoption of VGI for making it part of SDI in Pakistan. The intention behind this paper is to explore such factors as the key research question. To do so, we make use of the Technology–Organization–Environment (TOE) framework along with the partial least square structural equation model (PLS-SEM) to empirically analyze the factors impeding VGI from becoming part of SDI in the country. The study concludes that many technical, organizational, and environmental factors affect the adoption of VGI to be part of SDI in Pakistan.

Characterizing the Capabilities of Internet of Things Analytics through Taxonomy and Reference Architecture

The increasing prevalence of business cases utilizing Internet of Things (IoT) analytics, coupled with the diversity of IoT analytics platforms and their capabilities, poses an immense challenge for organizations seeking to make the best choice of IoT analytics platform for their specific use cases. Aiming to characterize the capabilities of IoT analytics, this article presents a reference architecture for IoT analytics platforms created through a qualitative content analysis of online reviews and published implementation architectures of IoT analytics platforms. A further contribution is a taxonomy of the functional and cross-functional capabilities of IoT analytics platforms derived from the analysis of published use cases and related business surveys. Both the reference architecture and the associated taxonomy provide a theoretical basis for further research into IoT analytics capabilities and should therefore facilitate the evaluation, selection and adoption of IoT analytics solutions through a unified description of their capabilities and functional requirements.