Justifying business intelligence systems adoption in SMEs

Abstract

Purpose The purpose of this paper is to provide a better understanding of how post-adoption use of business intelligence system (BIS) affects firm performance. It develops and empirically tests a conceptual model for assessing the impact of BIS routine and innovative usage on firm performance the context of small and medium enterprises (SMEs). Design/methodology/approach Drawing on the data collected from 181 SMEs we analyzed how BIS usage influences firm performance using the PLS-SEM method. Findings The paper provides empirical insights about how BIS routine and innovative usage affect firm performance. Practical implications The results provide instrumental insights for managers and solution providers to help them understand the influence of various determinants to more effectively conclude the post-adoption process in SMEs. Originality/value This study represents important progress in the authors’ theoretical understanding of the role of BIS routine and innovative usage across different BIS partial impacts on firm performance dimensions.

The impact of knowledge management process and business intelligence on organizational performance

“…The result of this study is consistent with the results of Popovič et al (2019). Business Intelligence is a data-based decision support system at all levels of the organization that collects data and stores data and presents it ready for decision-making analysis.…”

Industry 4.0 technologies in the purchasing process

“…2.5 provides the research model. Big Data refers to high-volume, high-velocity and high-variety data (Wang et al, 2016), that are difficult to analyze with traditional data processing methods (Popovic et al, 2019;Kang et al, 2016). Through BD, new technologies extract information from various data types and create actionable knowledge (Zhou et al, 2015).…”

“…One content analysis by Oesterreich and Teuteberg (2016) within Industry 4.0 publications, and another broad overview provided by Pfohl et al (2015), signalled the need to limit and focus certain technologies. Therefore this study focuses on two central technologies; Big Data/Business Intelligence -BD/BI (Popovic et al, 2019;Wang et al, 2016;Kagermann, 2015) and Internet of Things -IoT (Lin et al, 2018;Osmonbekov and Johnston, 2018;Smit et al, 2016). The importance of purchasing continues to increase (Bals et al, 2019: Osmonbekov andJohnston, 2018;GEP, 2018).…”

BPM and BI in SMEs: The role of BPM/BI alignment in organizational performance

“…A discussion within this category refers to identification and understanding of BI and BPM implementation and adoption CSFs in SMEs. Following the recommendations of Nguyen, Meredith and Burstein as well as Rockart, the CSFs are categorized into three groups 43,44 : (1) common, (2) 35 Ø Ø P P Ø Reher 36 Ø P Ø Ø P Rolinek et al 37 Ø P P P Ø Singer 38 Ø Ø P P P Braunnagel et al 8 Ø P P P Broccardo et al 39 P Ø Ø P Ø Bandara and Opsahl 4 P Ø Ø Ø P Lö ckmann and Feldmann 40 Ø P Ø Ø P Giacosa et al 41 P Ø Ø Ø P Mamoghli et al 42 P Ø P Ø P Business intelligence Dubravac and Bevanda 25 P Ø Ø P Ø Boonsiritomachai et al 6 P Ø P P Ø Raj et al 26 Ø P Ø Ø P Gauzelin and Bentz 27 Ø P Ø Ø P Adeyelure et al 28 Ø P Ø P Ø Gudfinnsson and Strand 29 P Ø P Ø P Llave et al 30 P Ø Ø Ø P Puklavec et al 31 P Ø Ø P Ø Popovič et al 32 P Ø Ø P Ø Raj et al 33 Ø P Ø Ø P…”

“…These findings are in line with the results of various studies, showing that BI and BPM effect customer satisfaction, improve customer support, increase sales and competitive advantage. 9,12,25,27,32 Some authors indicate that the implementation of social BPM technologies, process mining, online analytical processing (OLAP)-based intelligent systems and data mining could help enterprises to gain efficient collaboration throughout the whole supply chain and to manage customer experience. [69][70][71][72]…”