Data-Based Agricultural Business Continuity Management Policies

Athanasios Podaras ()
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Athanasios Podaras: Technical University of Liberec, Faculty of Economics, Department of Informatics

A chapter in Information and Communication Technologies for Agriculture—Theme II: Data, 2022, pp 209-233 from Springer

Abstract: Abstract Data-driven decisions are crucial for modern enterprises regardless of the sector in which they operate. In agriculture, data processing, storage, and manipulation are crucial for boosting agricultural productivity. Nevertheless, the reliance of modern agriculture on information technologies has triggered a great concern regarding the exposure of agricultural processes to various threats that can cause unexpected interruptions. Business continuity deals with these types of threats. Data collection, storage, and processing which can be effectively implemented by modern business intelligence systems can undoubtedly help modern agricultural enterprises implement standard business continuity policies. The present chapter introduces a novel multidimensional approach for facilitating effective data-based business continuity management policies in agriculture. The approach relies on realistic business continuity data from two agrarian industries that are used for the design of two business intelligence multidimensional schemas which facilitate decisions based on descriptive data and for conducting data mining predictions. Examples of descriptive data-based decision-making processes are depicted using business process modeling notation tools and the predictive decisions are conducted via machine learning classifiers. In this way, agricultural business continuity experts in collaboration with agronomists, researchers, and farmers can be motivated to apply fully data-driven agricultural business continuity policies in specific agricultural companies.

Keywords: Agriculture; BPMN; Business continuity; Business intelligence; Machine learning; Multidimensional models; Data warehouse; Decision making (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-030-84148-5_9

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DOI: 10.1007/978-3-030-84148-5_9

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