Determinants of visual analytics adoption in organizations

Abstract

Purpose Visual analytics is increasingly becoming a prominent technology for organizations seeking to gain knowledge and actionable insights from heterogeneous and big data to support decision-making. Whilst a broad range of visual analytics platforms exists, limited research has been conducted to explore the specific factors that influence their adoption in organizations. The purpose of this paper is to develop a framework for visual analytics adoption that synthesizes the factors related to the specific nature and characteristics of visual analytics technology. Design/methodology/approach This study applies a directed content analysis approach to online evaluation reviews of visual analytics platforms to identify the salient determinants of visual analytics adoption in organizations from the standpoint of practitioners. The online reviews were gathered from Gartner.com, and included a sample of 1,320 reviews for six widely adopted visual analytics platforms. Findings Based on the content analysis of online reviews, 34 factors emerged as key predictors of visual analytics adoption in organizations. These factors were synthesized into a conceptual framework of visual analytics adoption based on the diffusion of innovations theory and technology–organization–environment framework. The findings of this study demonstrated that the decision to adopt visual analytics technologies is not merely based on the technological factors. Various organizational and environmental factors have also significant influences on visual analytics adoption in organizations. Research limitations/implications This study extends the previous work on technology adoption by developing an adoption framework that is aligned with the specific nature and characteristics of visual analytics technology and the factors involved to increase the utilization and business value of visual analytics in organizations. Practical implications This study highlights several factors that organizations should consider to facilitate the broad adoption of visual analytics technologies among IT and business professionals. Originality/value This study is among the first to use the online evaluation reviews to systematically explore the main factors involved in the acceptance and adoption of visual analytics technologies in organizations. Thus, it has potential to provide theoretical foundations for further research in this important and emerging field. The development of an integrative model synthesizing the salient determinants of visual analytics adoption in enterprises should ultimately allow both information systems researchers and practitioners to better understand how and why users form perceptions to accept and engage in the adoption of visual analytics tools and applications.

Understanding business analytics continuance in agile information system development projects: an expectation-confirmation perspective

“…We argue that in agile ISD projects, users will also be satisfied with BA if they perceive it as useful and vice versa. The objectives of analytics in the big data era are evolving from decision support and performance management to data-driven businesses wherein employees are expected to acquire, transform and visualize data quickly, especially when using agile methodologies (Daradkeh, 2019;Larson and Chang, 2016;Mandal, 2019;Persaud, 2020). Thus, employees in agile ISD projects are more likely to perceive BA as useful if it can help them meet their prescriptive and predictive analytics goals through the rapid acquisition, transformation and visualization of data.…”

An Empirical Examination of the Relationship Between Data Storytelling Competency and Business Performance

“…Some of commercial self-service business analytics tools, such as Tableau 1 , QlikView 2 , and Microsoft Power BI 3 can be used for creating sharable data-driven stories via data visualizations and interactive dashboards and reports. These platforms lay the foundations for constructing narrative elements and exploratory visuals of data storytelling (Daradkeh, 2019b(Daradkeh, , 2019c. However, business analytics platforms with dedicated features for developing data stories are not yet as advanced and still used less frequently than the aforementioned alternatives (Tischler et al, 2017).…”

“…As a result, business analytics capabilities may not get used effectively, and decision-makers who usually lack analytical skills and expertise may fall back on their intuition or experience for decision-making (Herschel & Clements, 2017). As organizations create a culture of analytics, decision-makers and business partners are required to not only understand the insights generated from business analytics, but also be participants in the entire analytics workflow-from the moment of generating insights to the final decision or action (Daradkeh, 2019c).…”

Uma taxonomia de Visual Analytics em Sistemas de Apoio à Decisão

“…Diversos cenários têm se beneficiado das utilidades do SAD, como no gerenciamento de desastres por meio de dados voluntários [Horita and de Albuquerque 2013], naárea médica apresentando estimativas e previsões sobre diagnósticos ou em cidades inteligentes [Mendonça 2004], auxiliando a tomada de decisão com o auxílio de sensores e dispositivos inteligentes engenharia de tráfego entre outros desafios urbanos [Pettit et al 2018]. Em conjuntoà evolução dos SAD, a produção e disseminação de dados na rede aumentou exponencialmente [Daradkeh 2019, Al-Qirim et al 2017]. Em decorrência do aumento no volume de dados, novos desafios surgiram, como o excesso ou a falta de dados disponíveis e decisões a serem tomadas por mais de um indivíduo [Karacapilidis 2006].…”