Big Data Concept in the Food Supply Chain: Small Markets Case

Navickas Valentinas () and Gružauskas Valentas ()
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Navickas Valentinas: School of Economics and Business, Kaunas University of Technology, Lithuania
Gružauskas Valentas: Mechanical Engineering and Design Faculty, Kaunas University of Technology, Lithuania

Scientific Annals of Economics and Business, 2016, vol. 63, issue 1, 15-28

Abstract: The strategies of competitive advantage are changing dramatically because of high technology development. The data size in the world is multiplying rapidly - the amount of information in the world doubles every 12 months. Therefore, the authors analyzed Big data in the food supply chain. The methodology used in the paper consists of a review of global competitiveness reports and secondary data analysis together with document-based literature synthesis; a competitiveness maximization methodology was modelled referring to a case of small markets. The supply of food industry is complicated, because of various regulations and a demand for high quality products just on time. Various companies are transporting partial freight; therefore, the visibility, lead-time and cost minimization is essential for them. However, they are unable to use all the gathered information and are not utilizing the potential that is possible. The problem of data analysis is a bigger concern to the smaller markets. Many of the small markets are less developed countries that still are not using Big data in their enterprises. In addition, new technologies are developing in the Big data industry. Therefore, the gap of technology will increase even more between large and small markets. The analysed innovation level and technology usage indicated a need for the food industry to change competitiveness strategies. Therefore, the authors developed a competitiveness strategy that is orientated to the food industry of small markets.

Keywords: Big data; supply chain; logistics; competitiveness; food industry; small market (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:aicuec:v:63:y:2016:i:1:p:15-28:n:2

DOI: 10.1515/saeb-2016-0102

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