Identifying the main factors involved in business intelligence implementation in SMEs

Becerra-Godínez, Juan Alexis; Serralde-Coloapa, José Leonardo; Ulloa-Márquez, Martin Salvador; Gordillo-Mejía, Abraham; Gonzaga, Elizabeth Acosta

doi:10.11591/eei.v9i1.1459

Cited by 10 publications

(7 citation statements)

References 22 publications

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“…, 2021). Further, for the business houses, the researchers mainly took into account SME’s (Becerra-Godinez et al. , 2020).…”

Section: Results Sectionmentioning

confidence: 99%

“…Talking about factors associated with ICT adoption, the major studies are the part of educational sectors considering aspects related to secondary and primary education (Christopoulos and Sprangers, 2021), different subjects (Napal et al, 2020;Alobaid, 2020;Sasota et al, 2021) and technological advancement (K€ onig et al, 2020;Hossein-Mohand et al, 2021). Further, for the business houses, the researchers mainly took into account SME's (Becerra-Godinez et al, 2020). Under the health sector, the ICT intervention has been seen in diseases including HIV (Ibeneme et al, 2020;Zhang et al, 2020) and tuberculosis (Ibeneme et al, 2020).…”

Section: Results Sectionmentioning

confidence: 99%

“…In the case of business houses, Becerra-Godinez et al. (2020) analysed the factors involved in business intelligence implementation in small and medium enterprises.…”

Section: Thematic Corementioning

confidence: 99%

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ICT – a surviving tool for economy in the phase of social distancing: a systematic literature review

Gupta¹,

Gupta²,

Kataria³

et al. 2022

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PurposeThe purpose of this study is to recognise the role of information and communication technology (ICT) tools in different sectors like Education, Health Care, Business, FMCG and Entertainment in the phase of social distancing. This study also attempts to provide a quantitative review of the scholarly literature on this topic.Design/methodology/approachA comprehensive literature evaluation was undertaken using a database encompassing 150 English-language papers with publication dates ranging from 2019 to 2021. The research profile and thematic analysis are presented through a comprehensive content analysis, resulting in four themes. The study reviews various research articles and reports related to social distancing and opens a discussion on the growing importance of ICT tools during this COVID-19 era.FindingsICT acts as a surviving tool for the economy by creating a virtual environment and helping people to stay socially connected during this pandemic. There is a lack of empirical evidence to support the facts so further research is required.Research limitations/implicationsThere are two drawbacks to the current study. Firstly, this study established a rigorous review methodology in which the researchers opted to exclude any grey literature, non-peer-reviewed articles, books, notes and book chapters from consideration. These sources could have had pertinent literature. Secondly, even after protocol’s rigour and numerous rounds of checks by a team of academicians and researchers, an anomaly may have sneaked into the evaluation.Originality/valueThe current study contributes to the growing literature on ICT tools particularly in this phase of social distancing. This paper highlights the need for future research in this area supported by different statistics.

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“…, 2021). Further, for the business houses, the researchers mainly took into account SME’s (Becerra-Godinez et al. , 2020).…”

Section: Results Sectionmentioning

confidence: 99%

Section: Results Sectionmentioning

confidence: 99%

See 1 more Smart Citation

ICT – a surviving tool for economy in the phase of social distancing: a systematic literature review

Gupta¹,

Gupta²,

Kataria³

et al. 2022

View full text Add to dashboard Cite

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“…Description of critical success factors [42], [43] Include user participation in the definition of the level of service and the requirements Define the quality plan Choose the ETL (extract, transform, and load) tool to use Preferably carry out incremental data loads Carefully choose the development platform and the appropriate database system Carry out data reconciliation processes Periodically review and modify the planning Provide user support [44], [45], [46] Sponsorship of the project Management of user expectations Use of prototypes Quick result search (quick win) Choose a measurable organizational problem Modeling and design of the "data warehouse." Selection of the appropriate business case Alignment with the organizational strategy Careful selection of tools End users' involvement [47], [48], [49] Support for the management of the organization Existence of a project leader Adequate use of resources Participation of the end-user Team with adequate skills Have adequate data sources Consider the information and its analysis as part of the organization's culture Alignment with the organization's strategy Effective BI management and control Management of organizational change [50] Initiative linked to business needs Existence of management sponsorship Cross-organizational project QA control The flexibility of the data model Data-oriented management Automatic data extraction process Knowledge Experience [51] Make incremental changes…”

Section: Authormentioning

confidence: 99%

Methodology for Business Intelligence Solutions in Internet Banking Companies

Viteri¹,

Cruzado²,

Huamán³

2022

International Journal on Advanced Science, Engineering and Information Technology

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Business intelligence in the banking industry has been studied extensively in the last decade; however, business executives still do not perceive efficiency in the decision-making process since the management and treatment of information are very timeconsuming for the deliverer, generating costs in the process. On the other hand, there is no formal methodology for developing business intelligence solutions in this sector. This work aims to optimize decision-making in a business unit that works with internet banking companies, reducing the time, the number of people, and the costs involved in decision-making. To meet the objective, basic and applied research was conducted. The basic research allowed the construction of a new methodology from a study of critical success factors and approaches from the business intelligence literature. The applied research involved the implementation of a business intelligence solution applying the new methodology in a pre-experimental study. Thirty decision-making processes were analyzed using pre-test and post-test data. Tools such as a stopwatch and observation were used to collect and record data on time spent, the number of people, and the decision-making costs. This information was processed in the specialized Minitab18 statistical software, which allowed the observation and confirmation of relevant results regarding time reduction, the number of people, and the costs generated. Therefore, it was concluded that the business intelligence solution, applying the new methodology, optimized decision making in the business unit that works with internet banking for companies.

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“…One of the recommendations that are most relevant during the implementation of BI in SMEs is to select the appropriate technology for the company depending on their needs (Becerra et al , 2020). It will help to provide access to information more efficiently, and thereby contribute to collect, store and process data in a better way.…”

Section: Business Intelligence On Cloudmentioning

confidence: 99%

A model of business intelligence on cloud for managing SMEs in COVID-19 pandemic (Case: Iranian SMEs)

Hamidinava

Ebrahimy

Samiee

et al. 2021

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PurposeThe purpose of this study was to demonstrate a cloud business intelligence model for industrial SMEs. An initial model was developed to accomplish this, followed by validation and finalization of the cloud business intelligence model. Additionally, this research employs a mixed-techniques approach, including both qualitative and quantitative methods. This paper aims to achieve the following objectives: (1) Recognize the Cloud business intelligence concepts. (2) Identify the role of cloud BI in SMEs. (3) Identify the factors that affect the design and presenting a Cloud business intelligence model based on critical factors affecting SMEs during pandemic COVID-19. (4) Discuss the importance of Cloud BI in pandemic COVID-19 for SMEs. (5) Provide managerial implications for using Cloud BI effectively in Iran’s SMEs.Design/methodology/approachIn the current study, an initial model was first proposed, and the cloud business intelligence model was then validated and finalized. Moreover, this study uses a mixed-methods design in which both qualitative and quantitative methods are used. The fuzzy Delphi Method has been applied for parameter validation purposes, and eventually, the Cloud business intelligence model has been presented through exploiting the interpretive structural modeling. The partial least squares method was also applied to validate the model. Data were also analyzed using the MAXQDA and Smart PLS software package.FindingsIn this research, from the elimination of synonym and frequently repeated factors and classification of final factors, six main factors, 24 subfactors and 24 identifiers were discovered from the texts of the relevant papers and interviews conducted with 19 experts in the area of BI and Cloud computing. The main factors of our research include drivers, enablers, competencies, critical success factors, SME characteristics and adoption. The subfactors of included competitors pressure, decision-making time, data access, data analysis and calculations, budget, clear view, clear missions, BI tools, data infrastructure, information merging, business key sector, data owner, business process, data resource, data quality, IT skill, organizational preparedness, innovation orientation, SME characteristics, SME activity, SME structure, BI maturity, standardization, agility, balances between BI systems and business strategies. Then, the quantitative part continued with the fuzzy Delphi technique in which two factors, decision-making time and agility, were deleted in the first round, and the second round was conducted for the rest of the factors. In that step, 24 factors were assessed based on the opinions of 19 experts. In the second round, none of the factors were removed, and thus the Delphi analysis was concluded. Next, data analysis was carried out by building the structural self-interaction matrix to present the model. According to the results, adoptability is a first-level or dependent variable. Regarding the results of interpretive structural modeling (ISM), the variable of critical success factors is a second-level variable. Enablers, competencies and SME characteristics are the third-level and most effective variables of the model. Accordingly, the initial model of Cloud BI for SMEs is presented as follows: The results of ISM revealed the impact of SME characteristics on BI critical success factors and adoptability. Since this category was not an underlying category of BI; thus, it played the role of a moderating variable for the impact of critical success factors on adoptability in the final model.Research limitations/implicationsSince this study is limited to about 100 SMEs in the north of Iran, results should be applied cautiously to SMEs in other countries. Generalizing the study's results to other industries and geographic regions should be done with care since management perceptions, and financial condition of a business vary significantly. Additionally, the topic of business intelligence in SMEs constrained the sample from the start since not all SMEs use business intelligence systems, and others are unaware of their advantages. BI tools enable the effective management of companies of all sizes by providing analytic data and critical performance indicators. In general, SMEs used fewer business intelligence technologies than big companies. According to studies, SMEs understand the value of simplifying their information resources to make critical business choices. Additionally, they are aware of the market's abundance of business intelligence products. However, many SMEs lack the technical knowledge necessary to choose the optimal tool combination. In light of the frequently significant investment required to implement BI approaches, a viable alternative for SMEs may be to adopt cloud computing solutions that enable organizations to strengthen their systems and information technologies on a pay-per-use basis while also providing access to cutting-edge BI technologies at a reasonable price.Practical implicationsBefore the implementation of Cloud BI in SMEs, condition of driver, competency and critical success factor of SMEs should also be considered. These will help to define the significant resources and skills that form the strategic edge and lead to the success of Cloud BI projects.Originality/valueMost of the previous studies have been focused on factors such as critical success factors in cloud business intelligence and cloud computing in small and medium-sized enterprises, cloud business intelligence adoption models, the services used in cloud business intelligence, the factors involved in acceptance of cloud business intelligence, the challenges and advantages of cloud business intelligence, and drivers and barriers to cloud business intelligence. None of the studied resources proposed any comprehensive model for designing and implementing cloud business intelligence in small and medium-sized enterprises; they only investigated some of the aspects of this issue.

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Identifying the main factors involved in business intelligence implementation in SMEs

Cited by 10 publications

References 22 publications

ICT – a surviving tool for economy in the phase of social distancing: a systematic literature review

ICT – a surviving tool for economy in the phase of social distancing: a systematic literature review

Methodology for Business Intelligence Solutions in Internet Banking Companies

A model of business intelligence on cloud for managing SMEs in COVID-19 pandemic (Case: Iranian SMEs)

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