How to improve firm performance using big data analytics capability and business strategy alignment

By Shahriar Akter, Samuel Fosso Wamba, Angappa Gunasekaran, Rameshwar Dubey, Stephen J. Childe. 2016

1,294 citations recorded by the source corpus.

Subfields: Management Information Systems, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/abf4c7acd0d2729e3e78c2d515f588502c9858e8

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In Management Information Systems

In Strategy and Management

Citations in the corpus

Impact of Industry 4.0 on supply chain performance (2020, background): “These technologies can form new enterprise-wide communication platforms and new forms of collaboration and coordination (Helo and Hao 2017; Akter et al. 2016), enabling high level of integration and real-time information sharing (Shamsuzzoha et al. 2016; Rashid and Tjahjono 2016; Chen and Deng…”
An integrated big data analytics-enabled transformation model: Application to health care (2018, background): “Research on big data analytics has primarily focused the role of big data analytics capability and examined its direct e ﬀ ect on ﬁ rm performance (e.g., [6,7]).”
Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations (2020, background): “, big data analytics/big data predictive analytics) on operational performance (OP) (Akter et al., 2016; Gupta and George, 2016; Fosso Wamba et al., 2017; Mikalef and Pateli, 2017; Golzer and Fritzsche, 2017; Srinivasan and Swink, 2018; Dubey et al., 2019; Aydiner et al., 2019; Mikalef et al., 2019b”
A critical investigation of Industry 4.0 in manufacturing: theoretical operationalisation framework (2018, background): “These tools can enable real-time data stream analysis, which, in turn, can result in real time problem solving (Li et al. 2016) and dramatic improvements in performance (Akter et al. 2016; Wamba et al. 2017).”
Big data analytics capability in supply chain agility (2019, positive): “Moreover, our results strengthen the notion that managers who can exploit the innovative technology in attempts to build capability at supply chain level can expect their organizations to gain competitive edge over their competitors (Davenport, 2006; Akter et al. 2016; Srinivasan and Swink, 2017).”
Big data analytics capabilities: a systematic literature review and research agenda (2017, methodology): “Analyzing high-quality and reliable data is imperative in enabling management to make cognizant decisions and derive business value (Akter et al. 2016b).”
Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience (2019, background): “It is observed that researchers or practitioners often use data analytics, big data analytics, supply chain analytics and big data & predictive analytics interchangeably (see, Davenport, 2006; Waller and Fawcett, 2013; Agarwal and Dhar, 2014; Akter et al. 2016; Raffoni et al. 2017;Srinivasan and Swi”
Assessing the impact of big data on firm innovation performance: Big data is not always better data (2020, methodology): “Indeed, 87 percent of firms believe big data will change the competitive landscape, and 89 percent believe they will lose considerable market share if they do not adopt big data within the next few years (Akter, Wamba, Gunasekaran, Dubey, & Childe, 2016).”
Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation (2021, positive): “In particular, the presence of a modular technological infrastructure (an essential component of BDAC; Akter et al., 2016) usually increases business decision-making flexibility, which in turn promotes research, discovery, experimentation and risk-taking behaviours possibly directed to the quick…”
Big Data and Predictive Analytics and Manufacturing Performance: Integrating Institutional Theory, Resource‐Based View and Big Data Culture (2019, positive): “Previous studies (Akter et al., 2016; Gupta and George, 2016; Fosso Wamba et al., 2017; Fosso Wamba et al., 2017) have used RBV or dynamic capability view to explain the adoption of BDPA.”
Resources and digital export: An RBV perspective on the role of digital technologies and capabilities in cross-border e-commerce (2021, background): “…analytics to create value (Davenport, 2017) and argued that firms possessing them can achieve a competitive performance advantage by contributing to more satisfying customer journeys and e-commerce experiences (Akter et al., 2016; Wamba et al., 2017; Vakulenko, Shams, Hellstrom and Hjort, 2019).”
Achieving superior organizational performance via big data predictive analytics: A dynamic capability view (2019, background): “Despite increasing interest in BDPA, only a small amount of literature is available (Akter et al., 2016; Dubey et al., 2019a; Gupta & George, 2016; Hitt et al., 2016; Teece et al., 1997; Wamba et al., 2017).”