Exploring business intelligence and its depth of maturity in Thai SMEs

Boonsiritomachai, Waranpong; McGrath, G. Michael; Burgess, Stephen

doi:10.1080/23311975.2016.1220663

Cited by 44 publications

(54 citation statements)

References 48 publications

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“…8,31 Resource availability is one of the key factors that significantly affect BPM initiatives' success. 6 Many SMEs do not provide sufficient staff and do not clearly establish relevant BI and BPM roles, for example, project champion and process owner. 8,31 Other authors reveal that the lack of IT support and lack of understanding can cause a failure of BI deployment in SMEs.…”

Section: Literature Review Discussionmentioning

confidence: 99%

“…Boonsiritomachai et al proposed BI maturity model identifying five levels of maturity in the following order: operate, consolidate, integrate, optimize and innovate. 6 These maturity levels comprise five maturity dimensions as follows: infrastructure, knowledge process, human capital, culture and applications. The results of the BI maturity model show that 'Thai SMEs are at an early stage of BI adoption'.…”

Section: Literature Review Discussionmentioning

confidence: 99%

“…The results of the BI maturity model show that 'Thai SMEs are at an early stage of BI adoption'. 6 Although the users of mobile BI recognize numerous benefits of BI systems adoption (e.g. increased efficiency, improved financial results, better cooperation between employees), less than 30% of SMEs use some form of mobile BI solutions.…”

Section: Literature Review Discussionmentioning

confidence: 99%

“…These findings are in line with the results of other studies identifying a low level of BI and BPM maturity in SMEs and emphasizing a positive correlation between the maturity level and the number of employees. [4][5][6]8,34,37 The results of empirical research studies show that BPM initiatives are of interest to large organizations, with a large number of processes. 62 On the other hand, many authors point out that the modern manufacturing and service companies should consider both BI (e.g.…”

Section: Discussionmentioning

confidence: 99%

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

Bach

Vukšić

Glavan

2019

International Journal of Engineering Business Management

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Business intelligence (BI) and business process management (BPM) are widely implemented in various organizations. However, their impact on organizational performance strongly depends on their alignment. Previous research has focused mainly on large companies. Small and medium-sized enterprises (SMEs) also started to use BI and BPM in order to improve their performance. However, the research regarding this issue is scarce. The goal of the article is to examine the interrelationship of BI and BPM and their impact on organizational performance of SMEs. In order to attain this goal, a systematic literature review and a survey research on the sample of SMEs in Croatia and Slovenia have been conducted.

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Section: Literature Review Discussionmentioning

confidence: 99%

Section: Literature Review Discussionmentioning

confidence: 99%

Section: Literature Review Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

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

Bach

Vukšić

Glavan

2019

International Journal of Engineering Business Management

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“…The information is presented visually to give the intended users a clear guidance for a smooth decision making process and most importantly, an accurate and fairly fast decision. Numerous organizations in the world have adopted BI due to its capability to make effective and well-timed business decisions to increase profit [5]. BI usage in manufacturing has shown an uplifting trend.…”

Section: Business Intelligence In Manufacturingmentioning

confidence: 99%

A model of acceptance factors for business intelligence in manufacturing using theoretical models

Yusof¹,

Othman

Yusuf

et al. 2019

IJEECS

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<span>Manufacturing organizations implemented Business Intelligence (BI) due to many advantages offered by it. The lack of research on the acceptance of BI in manufacturing motivates the initiative in this study to have an understanding of the factors that influence the acceptance of BI in manufacturing sector. Therefore, the research proposes a model which indicates the acceptance factors of BI in manufacturing. An integrated model consisting of underlying models of Technology Acceptance Model (TAM), Expectation Confirmation Theory (ECT) and Task-Technology Fit (TTF) will be developed. The new model will formulate 19 hypotheses and 11 factors contributing to the continuance and acceptance of BI. The model will be tested using quantitative and qualitative survey conducted to Malaysian manufacturing companies and validated using Structural Equation Modelling (SEM) to investigate the causal and mediating relationships between the factors. The expected result is hoping to suggest that selected factors in the model are positively related towards the acceptance of BI in manufacturing. The results are also hoping to guide future initiatives by industrial practitioners to develop and distribute BI to the manufacturing market.</span>

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