Investigating the Factors Affecting Business Intelligence Systems Adoption

Owusu, Acheampong; Baghestan, Abbas Ghanbari; Kalantari, Abdolhossein

doi:10.4018/ijtd.2017040101

Cited by 26 publications

(12 citation statements)

References 56 publications

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“…Lautenbach et al (2017) investigated the impact of six TOE determinants on the BIS usage, half of which proved to be significant, i.e., determinants as data-related infrastructure capabilities, top management support, and external market impact. Owusu et al (2017) investigated the TOE determinants' impact on the overall BIS adoption process among 120 private universities in Malaysia. Owusu et al (2017) focused on TOE determinants by observing five BIS adoption stages: (1) basic information system (IS) usage, (2) data warehouse (DW) usage, (3) DW and analytics usage, (4) DW, analytics and strategic tools usage, and (5) real-time use of all previously mentioned BIS tools and methods.…”

Section: Bis Adoptionmentioning

confidence: 99%

Exploring Risks in the Adoption of Business Intelligence in SMEs Using the TOE Framework

Glavan

Bach

Vukšić

2021

JRFM

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The business success of small- and medium-sized enterprises (SMEs) increasingly relies on the adoption of various technological innovations. For today’s unpredictable business operations, business intelligence systems (BISs) represent one of the most prominent tools with a significant impact on business performance. However, different internal and external risks may influence BIS adoption. The goal of this paper is to investigate the risks that impact BIS adoption in SMEs, using the Technology, Organization, and Environment (TOE) framework. For that purpose, we develop the logistic regression model, using data collected by a questionnaire survey using a sample of 100 Croatian SMEs. The results indicate the applicability of the TOE theoretical framework for examining BIS adoption in SMEs. Given the results obtained, the sampled SMEs should take into account the internal risks related to the organizational dimension and external risks related to the environmental dimension. Our research did not reveal the significant impact of technological risks that encompass characteristics of considered technological innovation related to the technology dimension.

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Section: Bis Adoptionmentioning

confidence: 99%

Exploring Risks in the Adoption of Business Intelligence in SMEs Using the TOE Framework

Glavan

Bach

Vukšić

2021

JRFM

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“…Compatibility refers to the existing infrastructure that influences the adoption decisions for innovation in organizations, it means if new technology is perceived as compatible with available technologies, values, systems, and procedures of the strong adopters in the context of infrastructure the more likely it will be adopted [56]. Satisfaction with existing systems (T3)…”

Section: Compatibility (T2)mentioning

confidence: 99%

Statistical Assessment of Business Intelligence System Adoption Model for Sustainable Textile and Apparel Industry

et al. 2021

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The textile and apparel industry is one of the biggest competitive industries in the world. Nowadays, industry 4.0 concepts put pressures on textile and apparel companies to integrate advanced technologies. Consequently, Business Intelligence (BI) systems are diffusing rapidly to process large data sets to harness the true value of smart technologies. Regardless of its potentials, most textile and apparel companies are lagging and hesitating to adopt this credible innovation in the presence of a high failure rate (70%-80%) especially in developing countries. To achieve the successful adoption of BI systems, statistical assessment is required to better understand this complex phenomenon. Therefore, a BI system model based on Technology-Organization-Environment (TOE) is developed to evaluate the role of potential determinants pertaining to the users, technology, organization, and environment. Data were collected using a survey with self-administered questionnaires from decision-makers with authoritative designations in the textile and apparel industry, academia, and software companies. Influential relationships among critical determinants were assessed and validated by using Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach. The results of this study would contribute to the success of costly BI system projects and will motivate the industry experts to potentially assign investments for the BI projects in the developing countries to sustain in the competitive markets.

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“…Competition has been considered as a potential determinant that can encourage the necessary adoption of innovations to maintain market position [51] and can promote speedy diffusion of innovation. The high degree of competition may guide high operational use of new systems [37].…”

Section: Competitive Pressurementioning

confidence: 99%

“…The existing infrastructure matters in the context of an organization's adoption decision. [51]. This is depicted by eight interviewees' statement: "Initially, we face major technological barriers in terms of integration of BI tools with legacy systems such as ERP, SCM, CRM and other 3rd party databases because of gadgets from different vendor companies with distinctive intelligent standards and communication protocols."…”

Section: Compatibilitymentioning

confidence: 99%

Exploration of Influential Determinants for the Adoption of Business Intelligence System in the Textile and Apparel Industry

et al. 2020

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The textile and apparel industry is prone to digitization with business intelligence systems (BIS) and big data concepts to contribute the global sustainability. BIS, an impactful and leading technology, is being implemented in many industrial sectors but almost 80% of BIS fail to give expected results due to unknown reasons. Although many scholars put effort into finding the influential determinants for the BIS implementation, they neglect the BIS adoption context, especially in the textile and apparel industry. A purposive and proportionate choice of potential determinants in the context of adoption would contribute significantly to the success of BIS. Multi-stage research is employed to identify and prioritize the significant determinants. In the first stage, twenty-two semi-structured in-depth interviews are conducted with seventeen textile and apparel companies. Ten significant determinants emerged after thematic analysis of interview data. The determinants are sustainability, competitive pressure, market trends, compatibility, technology maturity, leadership commitment and support, satisfaction with existing systems, sustainable data quality and integrity, users’ traits, and interpersonal communications that influence the adoption of BIS. In the second stage, the Best Worst Method (BWM) is used to calculate the weights for prioritizing the determinants based on experts’ opinion. These weights are then used to evaluate and rank the determinants. The findings of this research show that the leadership commitment and support, sustainability, users’ traits, and technology maturity, are the top-ranked determinants that influence the practitioners’ choice to adopt the BIS in the textile and apparel industry. The results of this study enable the BIS stakeholders to holistically comprehend the significant determinants that would drive or impede the success of BIS projects in the sustainable textile and apparel industry.

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Investigating the Factors Affecting Business Intelligence Systems Adoption

Cited by 26 publications

References 56 publications

Exploring Risks in the Adoption of Business Intelligence in SMEs Using the TOE Framework

Exploring Risks in the Adoption of Business Intelligence in SMEs Using the TOE Framework

Statistical Assessment of Business Intelligence System Adoption Model for Sustainable Textile and Apparel Industry

Exploration of Influential Determinants for the Adoption of Business Intelligence System in the Textile and Apparel Industry

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