Resource management in big data initiatives: Processes and dynamic capabilities

Braganza, Ashley; Brooks, Laurence; Nepelski, Daniel; Ali, Maged; Moro, Russ

doi:10.1016/j.jbusres.2016.08.006

Cited by 260 publications

(203 citation statements)

References 45 publications

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“…While at first the implementation of analytics at Southwest may look like a technical task, training personnel to adopt a data-driven approach when interacting with customers, developing the channels to collect different types of data, and encouraging a perspective of organizational learning based on insight are key components of business value. Numerous similar case studies showcase that a strong BDAC can not only help firms identify threats and opportunities, but it can also reinforce seizing of opportunities and transform operations through incremental or radical adaptations in existing modes of doing business, since insights are backed-up with empirical evidence (Braganza et al, 2017;LaValle et al, 2011). From the foregoing discussion, we hypothesize that:…”

Section: Research Modelmentioning

confidence: 99%

Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment

Mikalef

Boura

Lekakos

et al. 2019

British J of Management

498

454

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With big data analytics growing rapidly in popularity, academics and practitioners have been considering the means through which they can incorporate the shifts these technologies bring into their competitive strategies. Drawing on the resource‐based view, the dynamic capabilities view, and on recent literature on big data analytics, this study examines the indirect relationship between a big data analytics capability (BDAC) and two types of innovation capabilities: incremental and radical. The study extends existing research by proposing that BDACs enable firms to generate insight that can help strengthen their dynamic capabilities, which in turn positively impact incremental and radical innovation capabilities. To test their proposed research model, the authors used survey data from 175 chief information officers and IT managers working in Greek firms. By means of partial least squares structural equation modelling, the results confirm the authors’ assumptions regarding the indirect effect that BDACs have on innovation capabilities. Specifically, they find that dynamic capabilities fully mediate the effect on both incremental and radical innovation capabilities. In addition, under conditions of high environmental heterogeneity, the impact of BDACs on dynamic capabilities and, in sequence, incremental innovation capability is enhanced, while under conditions of high environmental dynamism the effect of dynamic capabilities on incremental innovation capabilities is amplified.

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Section: Research Modelmentioning

confidence: 99%

Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment

Mikalef

Boura

Lekakos

et al. 2019

British J of Management

498

454

View full text Add to dashboard Cite

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“…Hence, the moderating effect of organizational culture may help to resolve the inconsistency in previous studies (Greening and Gray, ; Hewett, Money and Sharma, ; Kostova, Roth and Dacin, ; Leidner and Kayworth, ; Scott, ). Therefore, in this study we have synthesized these perspectives to provide a better understanding of how manufacturing organizations with a specific resource portfolio make decisions considering certain external pressures (Braganza et al ., ; Zhang and Dhaliwal, ; Zheng et al ., ). We answer our research questions based on a sample of 195 manufacturing firms, using partial least squares (PLS)‐based structural equation modelling.…”

Section: Introductionmentioning

confidence: 99%

Big Data and Predictive Analytics and Manufacturing Performance: Integrating Institutional Theory, Resource‐Based View and Big Data Culture

Dubey

Gunasekaran

Childe

et al. 2019

British J of Management

563

395

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The importance of big data and predictive analytics has been at the forefront of research for operations and manufacturing management. The literature has reported the influence of big data and predictive analytics for improved supply chain and operational performance, but there has been a paucity of literature regarding the role of external institutional pressures on the resources of the organization to build big data capability. To address this gap, this paper draws on the resource‐based view of the firm, institutional theory and organizational culture to develop and test a model that describes the importance of resources for building capabilities, skills and big data culture and subsequently improving cost and operational performance. We test our research hypotheses using 195 surveys, gathered using a pre‐tested questionnaire. Our contribution lies in providing insights regarding the role of external pressures on the selection of resources under the moderating effect of big data culture and their utilization for capability building, and how this capability affects cost and operational performance.

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“…Yet, it fails to adhere to the value, rarity, inimitability, and non-substitutable (VRIN) assumptions of the RBV theory (Braganza et al, 2017). Cloud resource, though developed to possess unique competencies, is neither rare nor inimitable (Mitra et al, 2017).…”

Section: Resultsmentioning

confidence: 99%

“…Any independent reliance would lead to limited success and, potentially, even to an erosion of any competitive advantages that existing information systems may have once yielded (Braganza et al, 2017). Ultimately, the impact that new technologies have on a firm's information systems and performances are largely dependent on their internal competencies (e.g.…”

Section: Resource-based View Of Information Systemsmentioning

confidence: 99%

Resource-Based View of Information Systems: Sustainable and Transient Competitive Advantage Perspectives

Gupta

Tan

et al. 2018

AJIS

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The resource-based view (RBV), or resource-based theory, is one of the oldest and most influential theories in the field of information systems. This paper contends that it is timely to revisit, reflect on, and reposition RBV to ensure its continued disciplinary relevance and progress. In doing so, this paper (i) provides a succinct and sharp evaluation of the conventional RBV of information systems that firms use to establish sustainable competitive advantage, and (ii) makes an original contribution by introducing a contemporary RBV of information systems that firms can use to establish transient competitive advantage. Both these contributions should advance the current and future understanding of information systems as (a) an internal firm resource, (b) a source of competitive advantage, and (c) a driver of firm performance.

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Resource management in big data initiatives: Processes and dynamic capabilities

Cited by 260 publications

References 45 publications

Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment

Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment

Big Data and Predictive Analytics and Manufacturing Performance: Integrating Institutional Theory, Resource‐Based View and Big Data Culture

Resource-Based View of Information Systems: Sustainable and Transient Competitive Advantage Perspectives

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