Digital transformation: towards new research themes and collaborations yet to be explored

This study aimed at providing an overview of research themes and collaborations in the digital transformation scholarship. The methods of co-word analysis, co-author analysis, and network analysis were employed to network-analyze the keywords, countries, and institutions of 2820 research articles published on the digital transformation topic and indexed by the Web of Science database. Our main results indicated that researchers have mostly focused on three aspects of the digital transformation phenomenon including Technological and Industrial View, Organizational and Managerial View, and Global and Social View. Also, it was realized that Technology, Sustainability, Big Data, Information and Communications Technology, Innovation, Industry 4.0, Artificial Intelligence, Business Model, Social Media, and Digitization are the most recurring themes in this field of research. Besides, Small and Medium-Sized Enterprises, Blockchain, Machine Learning, Knowledge Management, and Sustainable Development were respectively identified as the five hottest issues in the digital transformation scholarship. The contribution of our study highlights that European countries and specially the institutions of northern Europe have had better performance in the research collaborations in digital transformation.info:eu-repo/semantics/acceptedVersio

Using Digital Technology to Address Confirmability and Scalability in Thematic Analysis of Participant-Provided Data

This article presents a technique for analyzing large-scale qualitative data to address considerations for scalability and confirmability in thematic analysis of participant-provided data. A network approach provides a consistent means of coding that scales with the size of the dataset and is verifiable using standardized methods. This form of data analysis can be used with smaller data sources including interview transcripts as well as large data sources such as open-ended survey responses. A constructivist (inductive) approach is maintained and needed, however, to aid in interpretation of latent constructs. In this article, we provide both a conceptual overview of the co-word analysis method and a practical example

Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study

© 2018 As one of the most impactful emerging technologies, big data analytics and its related applications are powering the development of information technologies and are significantly shaping thinking and behavior in today's interconnected world. Exploring the technological evolution of big data research is an effective way to enhance technology management and create value for research and development strategies for both government and industry. This paper uses a learning-enhanced bibliometric study to discover interactions in big data research by detecting and visualizing its evolutionary pathways. Concentrating on a set of 5840 articles derived from Web of Science covering the period between 2000 and 2015, text mining and bibliometric techniques are combined to profile the hotspots in big data research and its core constituents. A learning process is used to enhance the ability to identify the interactive relationships between topics in sequential time slices, revealing technological evolution and death. The outputs include a landscape of interactions within big data research from 2000 to 2015 with a detailed map of the evolutionary pathways of specific technologies. Empirical insights for related studies in science policy, innovation management, and entrepreneurship are also provided

Novel Coronavirus Cough Database: NoCoCoDa

The current pandemic associated with the novel coronavirus (COVID-19) presents a new area of research with its own set of challenges. Creating unobtrusive remote monitoring tools for medical professionals that may aid in diagnosis, monitoring and contact tracing could lead to more efficient and accurate treatments, especially in this time of physical distancing. Audio based sensing methods can address this by measuring the frequency, severity and characteristics of the COVID-19 cough. However, the feasibility of accumulating coughs directly from patients is low in the short term. This article introduces a novel database (NoCoCoDa), which contains COVID-19 cough events obtained through public media intervi

BIG DATA: EVOLUÇÃO DAS PUBLICAÇÕES E OPORTUNIDADES DE PESQUISA

As the increasing supply and demand of data and tools to manage them creates the Big Data (BD) paradigm, the academic engagement in this discussion becomes essential. Based on bibliometric data and Baskerville and Myers (2009) lenses, this paper identifies an academic and non-academic BD interest wave raised in 2011 and continuously growing since then. To perform a deeper investigation of BD in the Information System (IS) field, some ICT publications were analyzed to capture the level of BD participation in their agenda and to present the subjects covered by them and their word cloud representations. We also propose five topics for future research, highlighting the importance of being attentive to such emergent phenomena and to build a solid IS research tradition that can effectively collaborate with the progress of theory and practice. We finally call the attention to the need of studies investigating the Brazilian academy performance concerning this topic, especially relevant in a country such as Brazil, which is a great data generator.A crescente oferta e demanda de dados e de ferramentas para manejá-los, constituindo o paradigma do Big Data (BD), torna cada vez mais relevante seu debate no meio acadêmico. A partir de dados bibliométricos e das lentes de Baskerville e Myers (2009), este artigo identifica a onda de interesse acadêmico e não-acadêmico sobre BD que se projeta em 2011 e cresce continuamente desde então. Para explorar o campo de Sistemas de Informação (SI), alguns periódicos foram analisados para captar o nível de participação do tema e apresentar brevemente os assuntos abordados e a nuvem de palavras que os representa.  Apresentamos ainda cinco temáticas para futuras pesquisas, destacando a importância de manter-nos atentos aos fenômenos emergentes para construir uma tradição de pesquisa de SI que possa contribuir com a ciência e com a prática. Por fim, salientamos a necessidade de estudos que investiguem a atuação da academia brasileira nesta temática, tão pertinente em um país gerador intensivo de dados, como o Brasil

Measuring international relations in social media conversations

This paper examines international relations as perceived by the public in their social media conversations. It examines over 1.8 billion Facebook postings in English and 51 million Chinese posts on Weibo, to reveal the relations among nations as expressed in social media conversations. It argues that social media represent a transnational electronic public sphere, in which public discussions reveal characteristics of international relations as perceived by a foreign public. The findings show that the international relations in social media postings match the core-peripheral structure proposed in the World Systems Theory. Additionally, the relations are associated with the amount of news coverage and public attention a country receives. Overall, the study demonstrates the value of webometric data in revealing how international relations are perceived by average citizens

A Big-Data based and process-oriented decision support system for traffic management

Data analysis and monitoring of road networks in terms of reliability and performance are valuable but hard to achieve, especially when the analytical information has to be available to decision makers on time. The gathering and analysis of the observable facts can be used to infer knowledge about traffic congestion over time and gain insights into the roads safety. However, the continuous monitoring of live traffic information produces a vast amount of data that makes it difficult for business intelligence (BI) tools to generate metrics and key performance indicators (KPI) in nearly real-time. In order to overcome these limitations, we propose the application of a big-data based and process-centric approach that integrates with operational traffic information systems to give insights into the road network's efficiency. This paper demonstrates how the adoption of an existent process-oriented DSS solution with big-data support can be leveraged to monitor and analyse live traffic data on an acceptable response time basis.publishedVersio