Empowering SMEs through Business Intelligence

Table 1 provides the descriptive information of the collected data that are related to the research trends of business intelligence model and its contribution in the enhancement of competitive advantage and decision-making process of SMEs. The first examination returned 509 documents, whereas the authors' restriction to the selection of solely articles yielded 317 documents. All these publications use 848 author keywords and 817 keywords plus. The referent period of the analysis is the time between 2007 and 2022. Moreover, the selected papers have written by 809 authors and only 45 have been written by one-single author. In addition, there is a high collaboration in publications in the studied field of business intelligence in SMEs, which can be approved by the collaboration index. Specifically, document per author ratio is 0.392, which means, on average, almost three authors have written one document.

Table 1 Descriptive characteristics of literature regards business intelligence in SMEs.

Figure 2 presents the annual scientific production, while Fig. 3 illustrates the citation per year for publications related to business intelligence in SMEs and the way that this model affects their competitive advantage and decision-making process. At the beginning of the research year there is a limited production of scientific papers (Fig. 2), which indicates the restricted knowledge of SMEs regards the model of business intelligence. It is noteworthy that between 2009 and 2010 there was a little development on the scientific production in the studied field, but 1 year later (2011) there is a sharp decrease in the production of papers, which is based on the financial crisis that affects the global community. However, after 2013, there was a fluctuation trend in the publications and citations of studies in business intelligence and SMEs, while 2021 can be characterized as the peak year of both publications and citations. This increase is due to the outbreak of Covid-19, which enhanced more the role of emerging technologies in the business arena. The transition to the new digital age helps small and medium-sized enterprises to create a new digital network, a factor that is crucial for such enterprises to respond to the increased competition, to promote their products in larger markets and to implement new innovative proposals with greater success rates. Thus, SMEs can increase their competitive advantage. Additionally, regarding Fig. 3, the development of the typical article's citation shows a distinct tendency. This is predicated on the assumption that when a new body of research arises, it takes time for it to develop, and as more papers in that body of literature are published, the number of citations increases as well.

Fig. 2 Annual scientific production.

Fig. 3 Average articles citation per year.

Bibliometric citation analysis

Table 2 ranks the most influential journals in the studied field of business intelligence in SMEs. Journals have been ranked based on the number of the published papers that are related to the research field. "Sustainability" was the journal with the highest number of published articles on business intelligence and SMEs (15) during the period 2007–2022. "International Journal of Business Information Systems", "Journal of Information and Knowledge Management" and Journal of Knowledge Management" are ranked in the second position with 5 articles each. Moreover, most of the cited journals on the field of business intelligence are indexed by Scimago and ABS list, while plenty of them are subject to the research area of Information System and Management.

Table 2 Top 20 journals in the field of business intelligence in SMEs.

Table 3 presents the most related publications regards the role of business intelligence in SMEs and the contribution of this business model in the enhancement of the competitiveness and improvement of the decision-making process of SMEs. The list of Table 3 includes the twenty most relevant articles to the subject studied in this article. At the top of the list is the publication of Maier, who published the first study in 2007 on the role of information analytics that has transformed businesses, organizations and society. Also, the aim of Nguyen's research was to gain a clearer understanding of Information Technology (IT) adoption in SMEs by analyzing and contrasting the current literature. Whilst describing how and why SMEs acquire IT, this paper was aiming to present the factors that influence the adoption process both positively or negatively. In addition, Chatterjee et al.in their paper are referred to the contribution of the Industry 4.0 era, which has brought a breakthrough in emerging technologies in the fields such as artificial intelligence, machine learning, deep learning, robotics, the Internet of Things, fully autonomous vehicles, 3D printing and much more. Also, authors in their study have attempted to identify social, environmental, and technological factors that affect the integration of artificial intelligence embedded technology by digital manufacturing and production organizations. Thus, the framework of technology-organization-environment (TOE) is used to explore the applicability of Industry 4.0. Furthermore, TOE model is indicated as one of the most important in helping SMEs to integrate emerging technologies in their business model.

Table 3 Most globally cited articles.

Table 4 Most relevant affiliations.

Fig. 4 Word growth overtime.

Fig. 5 Research trends on the field of business intelligence in SMEs

Network analysis

To detect the main research themes in the studied field, thematic map has been developed with the use of Biblioshiny. Thematic map apart from the axis of centrality, which presents the importance of each of the entitled theme, and the axis of density, which represents the development of the theme that has been chosen. The map is divided into four quadrants, which each of them illustrates a different theme category. The quadrant that is positioned in the lower left quadrant represents the emerging or declining themes, which are new themes that can emerge or drop from the research area. The quadrant that is positioned in the lower right side of the thematic map indicates the basic or transversal themes and are characterized by low density and high centrality. Issues that are included in this part of the map illustrates that much research has been done on these. Moreover, the quadrant that is in the upper left part of the map are characterized by high density and low centrality and are called as niche themes. Finally, the quadrant in the upper right part of the thematic map is represented by both high density and high centrality. These themes are characterized as motor themes, which are developed and crucial. Thus, Fig. 6 illustrates the thematic map for the integration of business intelligence in SMEs.

Fig. 6 Thematic map.

Cluster analysis

Although SMEs have started integrating business intelligence model to enhance their competitive advantage and improve the decision-making process, Multiple Correspondence Analysis (MCA) (Fig. 7) reveals that business intelligence should be combined with traditional business models that help especially SMEs to integrate emerging technologies in their operational system. TOE framework is among those business models that can facilitate SMEs with the adoption of business analytics. The technology-organization-environment framework, also known as the TOE framework, is a theoretical framework that explains the adoption of technology in organizations and describes how the process of adopting and implementing technological innovations is influenced by the technological, organizational, and environmental context. Although the spread of the coronavirus has acted as an opportunity for many companies to accelerate their digital transformation, SMEs, which represent a large percentage of the global economy, are slow to adopt new technologies, which has a negative effect on their competitiveness. Therefore, the development of a new business model, which will be based on the TOE and business intelligence is crucial for SMEs to adopt emerging technologies and enhance their competitive advantage.

Fig. 7 Cluster analysis based on the MCA method.