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Big Data in Data-Driven Innovation: Applications, prospects and limitations in Marketing

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In the era of Industry 4.0 (4th industrial revolution), data has major impact on businesses, since the revolution of networks, platforms, people and digital technology changed the determinants of firms' innovation and competitiveness (OECD,
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  4 th  International Conference on Contemporary Marketing Issues (ICCMI) 2016 701 Big Data in Data-Driven Innovation: Applications, prospects and limitations in Marketing   Ioannis Kopanakis   Department of Business Administration Technological Educational Institute of Crete Agios Nikolaos, Crete, Greece Corresponding author:kopanakis@staff.teicrete.gr    Konstantinos Vassakis  Research Associate Technological Educational Institute of Crete Agios Nikolaos, Crete, Greece George Mastorakis Department of Business Administration Technological Educational Institute of Crete Agios Nikolaos, Crete, Greece Abstract  In the era of Industry 4.0 (4th industrial revolution), data has major impact on businesses, since the revolution of networksĽ platformsĽ people and digital technology changed the determinants of firms‘ innovation and competitiveness (ECDĽ β01η). In the ― knowledge-  based economy‖Ľ enterprises have to be innovative in order to build and sustain a competitive advantage against rivals. However, innovation is complex due to fast changing technology, globalization (extremely competitive market conditions) and ch anging customers‘ needs. ThereforeĽ innovation is dependent on the combination of technologies and exploitation of knowledge.  ζowadaysĽ λ0Σ of the data in the world was generated in just the last β years (IBεĽ β01θ)Ľ as ―Internet of Things - IoT‖ provide s an enormous increase in volume (exabytes) and variety of data generation through sensors and connected devices. Digital data is everywhere (social media, sensors etc.), in every sector (agriculture, health, energy and infrastructure, economics and insurance, sports, food and transportation) and in every economy worldwide. The insights by leveraging big data provide a competitive advantage in enterprise through new ways of productivity, growth, innovation and consumer surplus (MGI, 2011). The real power of enterprises is related to their innovativeness, translated to their capacity accessing data and creating valuable knowledge. ―Data - Driven Innovation‖ (DDI)Ľ techniques and technologies for processing and analysing ―big data‖Ľ is defined as the method to  innovate using data-based decision process. Big data characterized by 3Vs: volume, variety and velocity seems to be a major resource for enterprises in the competitive race against rivals, since data provides significant knowledge about processes, customers, human capital and technology to enterprises. Data-driven innovation has the capacity to introduce new improved products and services, new improved production processes, better organizational management, more efficient R&D, better supply chain management and more efficient marketing.  4 th  International Conference on Contemporary Marketing Issues (ICCMI) 2016 702 Big data and its applications in business intelligence can contribute to business added value. In marketing intelligence, leveraging data for marketing decision making has the ability to improve sales and marketing performance by reducing inefficient marketing expenditures and increasing consumer surplus with customised marketing. Recent evidence shows that 5Ps (People, Product, Promotion, Price and Place) marketing mix can be used in Big Data management for marketing intelligence (Fan, 2015). Therefore, leveraging big data can create the prerequisites for marketing innovation, which is the implementation of a new marketing method involving significant changes in product design or packaging, product placement, product promotion or pricing (OECD, 2005). There is evidence that data- driven decision making have a positive impact in enterprises‘ performance (BrynjolfssonĽ 2011; Davenport & Harris, 2007; Lavalle, 2010; Bakhshi et al., 2014), but limited research exists in the impact big data in marketing innovation. The scope of this study is to present evidence about the impact of big data in marketing innovation of enterprises, sources of data-driven innovation in marketing and limitations of that approach.  Keywords :big data, data-driven, innovation, marketing, marketing intelligence   References Bakhshi, H., Bravo-Biosca, A., and Mateos-Garcia, J. (2014), "Inside the Datavores: Estimating the Effect of Data and Online Analytics on Firm Performance", Nesta, available at: www.nesta.org.uk/sites/default/files/inside_the_datavores_technical_report.pdf (accessed 15 April 2016). Brynjolfsson, E., Hitt, L.M., and Kim, H.H. (2011),"Strength in Numbers: How does data-driven decision-making affect firm performance?"  ICIS 2011 Proceedings . Davenport, T.H., and Harris, J.G. (2007),"Competing on Analytics: The New Science of Winning",  Harvard Business Press . Fan, S., Lau, R.Y.K., and Zhao, J.L. (2015),"Demystifying Big Data Analytics for Business Intelligence Through the Lens of Marketing Mix".  Big Data Research , Vol. 2, No. 1, pp. 28  –  32. IBεĽ (β01θ)ĽΟExtracting business value from 4 V‘s of big dataΟĽavailable atμ http://www.ibmbigdatahub.com/infographic/extracting-business-value-4-vs-big-data(accessed 20 April 2016). Lavalle, S., Hopkins, M.S., Lesser, E., Shockley, R., and Kruschwitz, N. (2010), "Analytics: The New Path to Value,"  MIT Sloan Management Review  (Fall). McKinsey Global Institute, (2011),"Big data: The next frontier for innovation, competition, and productivity", available at:www.mckinsey.com/business-functions/business-technology/our-insights/big-data-the-next-frontier-for-innovation (accessed 01 April 2016). OECD, (2005), "Oslo Manual, Guidelines for Collecting and Interpreting Innovation Data", 3rd Edition, available at: www.oecd.org/sti/oslomanual, (accessed 01 April 2016). OECD, (2015),"Data-Driven Innovation: Big Data for Growth and Well-Being", available at: http://www.oecd-ilibrary.org/content/book/9789264229358-en(accessed 01 April 2016).
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