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Annotated Bibliography Sample on Business Intelligence


Ramakrishnan, T., Jones, M. C., & Sidorova, A. (2012). Factors influencing business intelligence (BI) data collection strategies: An empirical investigation. Decision Support Systems, 52(2), 486-496.

 There is a need to investigate existing factors that affect the relationship between the strategies of data collection for an organization’s business intelligence and the aim of the implementation of the business intelligence. An online survey collects responses from 63 BI developers on the data collection strategies and purposes of BI implementation. Factor analyses of the responses investigated two data collection strategies and three BI implementation purposes. This revealed that pressures within institutions coerce organizations towards the implementation of BI-based solutions to achieve consistency and ultimately adopt succinct data collection criteria. The findings suggest that there is need to comprehend the connection between the purpose for implementing BI and the BI data collection approaches if a BI is to be successful.


Popovič, A., Hackney, R., Coelho, P. S., & Jaklič, J. (2012). Towards business intelligence systems success: Effects of maturity and culture on analytical decision-making. Decision Support Systems, 54(1), 729-739.

Understanding the value of business intelligence system (BIS) is crucial for managers and investors. Thus, this warrants for the need to establish the relationship that lies between maturity, information quality, a decision-making culture, and information use in decision making and whether these are significant aspects with regard to BIS success. A quantitative survey employs questionnaires and real-time interviews to collect data from 181 managers of medium-large organizations. Statistical analysis, descriptive statistics, and structural equation modelling of the data revealed that there exists a stronger impact of a BIS maturity with regards to information quality. Information quality affects the use of information and the findings caution that despite the fact that an analytical decision culture boosts information use, it might as well overwhelm the effect of information quality.

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Boonsiritomachai, W., McGrath, M., & Burgess, S. (2014). A research framework for the

adoption of Business Intelligence by Small and Medium-sized enterprises. In Small Enterprise Association of Australia and New Zealand 27th Annual Seaanz Conference.

The use of business intelligence applications in large companies has received a wide scholarship while that of small and medium enterprises (SMEs) remains limited. This calls for the need to explore the state of adoption of BI in the SMEs and the positive factors that facilitate this adoption process.  Three adoption models based on previous studies examine the BI adoption criteria and the success factors in the adoption of BI in SMEs using Thai SMEs. The qualitative analysis of the previous studies reveals that technological, organizational, environmental, and owner-managers characteristics affect an organization’s decision to adopt technology. The findings offer a chance for the replication of the study to further test relevance and validity of the literature practically.


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Malladi, S. (2013). Adoption of Business Intelligence & Analytics in Organizations–An

            Empirical Study of Antecedents.


There exists limited information on the factors that steer the organizational adoption of business intelligence and analytics (BIA). Thus, this warrants for the need to examine the elements that underlie the extent of the adoption of BIA in organizations. A survey is conducted to collect data from respondents from 229 firms using survey questionnaires. Cross-sectional ordered logistic regression and descriptive statistics revealed that BIA adoption depends largely on perceived benefits, organization size, and data infrastructure. The findings establish that firms that operate in knowledge-intensive sectors are more likely to adopt BIA


Fetzner, M. A. D. M., & Freitas, H. (2011). Business Intelligence (BI) implementation from the perspective of individual change. JISTEM-Journal of Information Systems and Technology Management, 8(1), 25-50.


Technological changes take place from day to day and this calls an examination of change and its nature at the individual level using experiences of business intelligence (BI) solution providers. A qualitative survey using interviews was used to collect data from eight respondents from Business Intelligence Companies, out of which only four participated. Theoretical and descriptive analysis of the responses revealed that most BI implementations proceed without difficulties and that not every information technology changes within an organization come with resistance. The findings propose that individuals develop sense towards a change, such as in IT, and position themselves with the situation.

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Olexová, C. (2014). Business intelligence adoption: a case study in the retail chain. World Scientific, Engineering Academy, and Society Transactions on Business and Economics, 11, 95-106.


Business intelligence applications have been adopted by many businesses and the most recent development is in the retail chain. This sudden change has not gone unnoticed and there is need to assess the variables that affect the BI adoption in the retail sector. A qualitative approach using semi-structured interviews comprises of nine interviewees from SAP retail chain. The analyses from the Diffusion Innovations perspective established that requirements engineering is a core factor in the adoption of BI from the Diffusion Innovations perspective. The findings highlight that managers perceive high-level and improved decision making as the most significant among all benefits associated with a BI in a retail chain.


Yeoh, W., & Koronios, A. (2010). Critical success factors for business intelligence systems. Journal of computer information systems, 50(3), 23-32.


Implementation of BI system requires certain critical success factors (CSFs), which are, however, limited due to the dominance of the IT sector and players. Thus, there is need to bring to light the CSFs that influence BI system implementation. The two-fold qualitative approach employs the Delphi Study and Case Study techniques to collect and evaluate data regarding BI systems implementation from 15 participants. The findings revealed that a successful implementation of a BI system requires clear business-oriented initiatives. Addressing the CSFs with a business perspective will lead to a better implementation.



Sujitparapitaya, S., Shirani, A., & Roldan, M. (2012). Business Intelligence Adoption in Academic Administration: An Empirical Investigation. Issues in Information Systems, 13(2), 112-122.


Researchers have conducted studies on the factors that underlie the adoption of BI in corporate organizations. However, the research gap is still wide and necessitates a study from a different perspective to examine the factors that affect the adoption of BI in private and public institutions of higher education (IHEs). The mixed-methods approach uses 243 senior administrators from different IHEs to assess the variables significant in the implementation of BI. Descriptive statistics and analyses of the findings revealed that private IHES are less likely to adopt BI as compared to the public ones. Most organizational-based factors have a direct impact on the adoption of BI in IHEs.


Puklavec, B., Oliveira, T., & Popovic, A. (2014). Unpacking Business Intelligence Systems Adoption Determinants: An Exploratory Study of Small and Medium Enterprises. Economic and Business Review for Central and South-eastern Europe, 16(2), 185.

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Most of the business intelligence systems (BIS) have focused more on large organizations, hence, the limited information on BIS adoption in small and medium enterprises (SMEs). Therefore, there is need to understand the BIS adoption in SMEs at firm level and establish the key factors that affect this adoption. A qualitative study is adopted and semi-structured interviews are administered to 10 informants, four of whom are BIS adopters while the other six are professionals from the BIS field. The findings revealed that most of the factors that influence the adoption of BIS by a firm arise from its internal features of adopting the subject technology. The organizational determinants form the larger category of those elements that influence BIS adoption in SMEs.


Huang, T. C. K., Liu, C. C., & Chang, D. C. (2012). An empirical investigation of factors influencing the adoption of data mining tools. International Journal of Information Management, 32(3), 257-270.


The adoption of different information technologies has received a broad coverage by researchers, while research on data mining tools (DMTs) continues to remain limited. It is, thus, necessary to understand users’ perception and adoption of DMTs and acquire more knowledge with regard to business intelligence. A web-based survey with questionnaires is used to collect data from 206 DMT users from enterprises in Taiwan. Findings from the statistical analyses of the data revealed that perceived usefulness and perceived ease of use are the two main aspects that influence the decision to use information technology. More specifically, the two factors have a direct influence on the behavioural intentions of a user to use DMTs.


Hwang, Y. (2012). End user adoption of enterprise systems in Eastern and Western cultures. Journal of Organizational and End User Computing (JOEUC), 24(4), 1-17.

The adoption of enterprise systems has been on the rising trend among different cultures, necessitating a close examination of enterprise management and implementation aspects through a comparison of the Eastern and Western end users of the enterprise systems. An online survey is used to collect data from 101 respondents, 47 from Japan and 54 from U.S based on their understanding of the targeted enterprise system. The findings establish that intrinsic motivation highly influenced the intention to use the ERP systems in the US while in Japan the influence is low, disregarding cultural factors. Consequently, personal innovativeness in IT largely influences the adoption of ERP in the Eastern countries than in the Western countries due to the high innovativeness of the end user in the Eastern nations.

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