Business Intelligence and Analytics Use, Innovation Ambidexterity, and Firm Performance--Model

Božič, Katerina; Dimovski, Vlado

doi:10.1037/t79998-000

Cited by 2 publications

(2 citation statements)

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“…Furthermore [ 29 ], made the discovery that the application of business intelligence (BI) is driving the transformation of information engineering to optimize business decisions and operations, resulting in high performance. Lastly [ 30 ], proposed that business intelligence and analytics (BI&A) can support innovation, provide organizational value, and enhance performance.…”

Section: Introductionmentioning

confidence: 99%

“…An empirical gap is found where not all organizational learning directly affects firm performance [ 25 , 35 ]. Therefore, this gap attracts mediation in the form of innovations produced by companies, and innovation has also proven to play a major role in achieving SMEs performance [ 25 , 26 , 28 , 30 ]. Meanwhile, not only organizational learning predisposes to innovation, but network learning also positively induces innovation [ 31 , 36 ].…”

Section: Introductionmentioning

confidence: 99%

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Spurring SMEs’ performance through business intelligence, organizational and network learning, customer value anticipation, and innovation - Empirical evidence of the creative economy sector in East Java, Indonesia

Anjaningrum,

Azizah,

Suryadi

2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spurring SMEs’ performance through business intelligence, organizational and network learning, customer value anticipation, and innovation - Empirical evidence of the creative economy sector in East Java, Indonesia

Anjaningrum,

Azizah,

Suryadi

2024

Heliyon

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Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda

2021

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In the past decade, current literature and businesses have drawn attention to Artificial Intelligence (AI) tools and in particular to the advances in machine learning techniques. Nevertheless, while the AI technology offers great potential to solve difficulties, challenges remain implicated in practical implementation and lack of expertise in the strategic usage of AI to create business value. This paper aims to implement a systematic literature review analyzing convergence of the AI and corporate strategy and develop a theoretical model incorporating issues based on the existing research in this field. Eighty-one peer-reviewed articles were discussed on the basis of research methodology from Webster and Watson (2002). In addition to gaps in future research, a theoretical model is developed, discussing the four sources of value creation: AI and Machine Learning in organizations; alignment of AI tools and Information Technology (IT) with organizational strategy; AI, knowledge management and decision-making process; and AI, service innovation and value. These outcomes lead to both theoretical and managerial viewpoints, with extensive possibilities to generate new methods and types of management practices.

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Business Intelligence and Analytics Use, Innovation Ambidexterity, and Firm Performance--Model

Cited by 2 publications

References 0 publications

Spurring SMEs’ performance through business intelligence, organizational and network learning, customer value anticipation, and innovation - Empirical evidence of the creative economy sector in East Java, Indonesia

Spurring SMEs’ performance through business intelligence, organizational and network learning, customer value anticipation, and innovation - Empirical evidence of the creative economy sector in East Java, Indonesia

Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda

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