Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation

Ciampi, Francesco; Demi, Stefano; Magrini, Alessandro; Marzi, Giacomo; Papa, Armando

doi:10.1016/j.jbusres.2020.09.023

Cited by 292 publications

(250 citation statements)

References 106 publications

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“…Few researchers study the literature about AI from a managerial viewpoint, addressing the management of information [6,11,[20][21][22]; decision-making [3,23,24]; knowledge management [25]; and skills [5,[26][27][28][29]. This paper, therefore, to the best of our understanding, varies from those previously conducted by synthesizing to a systematic review of literature by examining the state of the correlation between AI and organizational strategy, a topic not included in the aforementioned articles.…”

Section: Introductionmentioning

confidence: 99%

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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Section: Introductionmentioning

confidence: 99%

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

2021

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“…Apart from that, solid business knowledge, a sense for analytics, and a good understanding of upcoming data-related trends, including changes in customer behavior (Olszak 2014), are useful in developing ideas on how to use analytical methods effectively (Elbashir et al 2013). Industry expertise about practices and competitors are further prerequisites for executives, so that they may allocate suitable resources to analytical undertakings (Ciampi et al 2021). Lastly, executives need a general analytical understanding of BDA.…”

Section: Management Capabilitymentioning

confidence: 99%

Human-related capabilities in big data analytics: a taxonomy of human factors with impact on firm performance

Korherr

Kanbach

2021

Rev Manag Sci

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This study intends to provide scholars and practitioners with an understanding of human resource challenges in the context of Big Data Analytics (BDA). This paper provides a holistic framework of human-related capabilities that organizations must consider when implementing BDA to facilitate decision-making. For this purpose, the authors conducted a systematic literature review adapted from Tranfield et al. (BJM 14:207–222, 2003) to identify relevant studies. The 75 publications reviewed provided the sample for an inductive, and systematic data evaluation following the well-known and accepted approach introduced by Gioia et al. (ORM 16:15–31, 2012). The comprehensive review uncovered 33 first-order concepts linked to human-related capabilities, which were distilled into 15 s-order themes and then merged into five aggregated dimensions: Personnel Capability, Management Capability, Organizational Capability, Culture and Governance Capability, and Strategy and Planning Capability. The study is, to the best of the authors’ knowledge, the first to categorize all relevant human-related capabilities for successful BDA application. As such, it not only provides the scientific basis for further research, but also serves as a useful overview of the critical factors for BDA use in decision-making processes.

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“…Higher levels of productivity and performance, as well as economic growth and enhanced company value, have all been identified as factors influenced by organizational capacity to innovate [73]. Technical and organizational innovations are two essential components for improving performance and boosting the firm's value [73,74]. Organizational innovations create a conducive atmosphere for other forms of innovation and have a substantial and direct influence on inventive performance [75].…”

Section: Big Data Analytics Innovation Capabilitymentioning

confidence: 99%

The Value of Big Data Analytics Pillars in Telecommunication Industry

et al. 2021

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In the Big Data age, businesses in every industry must deal with vast volumes of data. Several experts and practitioners have lately emphasized the need of understanding how, why, and when Big Data Analytics (BDA) applications may be a valuable resource for businesses seeking a competitive edge. However, BDA pays off for some firms while failing to pay off for others due to the fact that investment in Big Data continues to present significant challenges due to the missing link between analytics capabilities and firm performance. According to a recent survey, many businesses spend the bulk of their time analyzing data, with only a tiny fraction employing Big Data Analytics to forecast outcomes and even fewer utilizing analytics apps to enhance processes and strategies. As a result, BDA is not widely used, and only a few companies have seen any benefit from it. To address this issue in the telecommunications domain and in light of the paucity of research on the subject, this study focused on the BDA Pillars (BDAP) in order to achieve benefits through increased revenues and cost savings. For the purpose of this research we have adopted qualitative approach with case study method, and technique of data collection includes semi-structure interview and document analysis. The Delphi technique and in-depth interviews conducted confirmed the existence of five critical elements that contribute to the sustainability of BDAPs and their impact on firm performance.

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Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation

Cited by 292 publications

References 106 publications

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

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

Human-related capabilities in big data analytics: a taxonomy of human factors with impact on firm performance

The Value of Big Data Analytics Pillars in Telecommunication Industry

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