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Business Intelligence (BI) systems have been dominating the technological priority list of many Chief Information Officers (CIO’s) since 2009 (Luftman & Ben-Zvi, 2010). Likewise, the worldwide expenditure of BI tools by IT companies was expected to grow from nearly $122 billion in 2015 to more than $187 billion in 2019, an increase of more than 50% over the five-year forecast period (IDC, 2016). The integration of BI systems with the business process is seen as important to monitor business value at both operational and strategic level in dynamic business environments (Chen, Chiang, & Storey, 2012).
Even though, as for most information technology tools, the majority of BI systems are mainly adopted by large enterprises, their advantages are mostly the same for both large and small and medium-sized enterprises (SMEs) (Popovič, Puklavec, & Oliveira, 2019). Indeed, in order to survive, SMEs are seeking to adopt and implement information systems (IS) particularly BI systems now considered as an important component of competitiveness in the current data-driven economy (Howson et al., 2019; Poba-Nzaou, Uwizeyemungu, & Saada, 2019).
As a matter of fact, SMEs found themselves faced with the increasing demand for business information with voluminous data and limited time for decision-making (Muryjas, 2014). Furthermore, the socio-economic environment, characterized by strong competition and data availability, encourages companies to adopt systems such as BI, that facilitate efficient processing and analysis of data from different sources (Poba-Nzaou et al., 2019). However, the implementation of BI tools, like any other enterprise system, is often characterized by a high level of complexity and entails greater risk of implementation failure (Dresner, 2019).
Notwithstanding the importance of BI systems, SMEs are still lagging behind in terms of implementing and leveraging the advantages stemming from the use of the BI systems. In this regard, it is essential that research focus on ways to improve implementation of BI tools project (Deng & Chi, 2012; Popovič, 2017). This is most important in resource-limited context that characterizes SMEs.
In addition, research on BI systems in the context of SMEs is particularly limited. A quick search on Scopus database (in February 2020) using “Business Intelligence” AND “Small Business” as key words returned only 7 journal articles. In a recent systematic literature review conducted in eight databases including Google Scholar, Llave (2017) found only 26 journal articles investigating on BI in the context of SMEs. Moreover, in the existing literature on BI systems, to the best of our knowledge, no study has yet explicitly addressed the possibility of reducing the risk of implementing a BI system at the adoption stage in the SME context. Here it is important to emphasize that results obtained from IS studies realized in the context of large firms cannot necessarily be generalized and transferred to the context of SMEs (Sarkar, Wingreen, & Cragg, 2017). Hence, following Poba-Nzaou and Raymond (2011), this study addresses the above-mentioned gaps in the literature by attempting to answer the following research question: How does the process of adopting a BI system affect the level of risk of its implementation in the context of SMEs?