Importance of Data Strategy for the Intellectualization of Agriculture. Business Recommendations Exemplified by the Chinese Agriculture Market
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Sprache:Deutsch
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Ja
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Erscheinungsdatum
09.04.2021
Verlag
GRINSeitenzahl
24 (Printausgabe)
Dateigröße
2450 KB
Auflage
1. Auflage
Sprache
Deutsch
EAN
9783346383563
Studienarbeit aus dem Jahr 2021 im Fachbereich Agrarwissenschaften, , Sprache: Deutsch, Abstract: The objective of this paper is, firstly, to emphasize the relevance of data and the impact of applying an appropriate corporate data strategy. Secondly, to raise awareness for the intellectualization of productive industries (e.g. agriculture) in order to become more effective. Both objectives are partly covered in the introduction chapter and will be further illuminated in the course of the paper by elaborating on the theoretical background. The aspects Data Strategy and Intelligent Agriculture have received much attention in the past decade. Consequently, they became a central issue in numerous research papers.
Previous work has only focused on one of the subjects at a time and therefore failed to analyze their interplay. Few researchers have addressed both topics simultaneously. This paper seeks to address how both subjects influence and depend on each other. Thirdly, the derivation of concrete guidelines for companies how data strategy and the development of intelligence must be synchronized. Using best practices based on the analysis of the agriculture industry, recommendations will be formulated. The ability to manage data wisely is becoming increasingly important for businesses both today and in the future, and it is therefore a decisive key competence for their success. One central question is to be discussed by this paper: When implementing a data strategy, should an agricultural company develop and continuously adapt the strategy to changing requirements to remain competitive in fast-moving markets?
To answer this question, we look at a company that has successfully made the transition from a traditional agricultural business to a cloud service provider: Top Cloud-Agri Technology Co., Ltd. (TPYN). This methodology ensures proximity to practical application, which in turn facilitates the development of practice-oriented use cases. Later, business recommendations (Chapter 3) will be derived from the company's strategic decisions based on the theoretically knowledge about data strategy gained in Chapter 2. Based on the subject, the paper can be assigned to the discipline of strategic IT management (SITM). Furthermore, a reference to the cross-disciplinary field of digital transformation can be made. Eventually, emerging technologies are required to enable and support the growing intelligence.
Previous work has only focused on one of the subjects at a time and therefore failed to analyze their interplay. Few researchers have addressed both topics simultaneously. This paper seeks to address how both subjects influence and depend on each other. Thirdly, the derivation of concrete guidelines for companies how data strategy and the development of intelligence must be synchronized. Using best practices based on the analysis of the agriculture industry, recommendations will be formulated. The ability to manage data wisely is becoming increasingly important for businesses both today and in the future, and it is therefore a decisive key competence for their success. One central question is to be discussed by this paper: When implementing a data strategy, should an agricultural company develop and continuously adapt the strategy to changing requirements to remain competitive in fast-moving markets?
To answer this question, we look at a company that has successfully made the transition from a traditional agricultural business to a cloud service provider: Top Cloud-Agri Technology Co., Ltd. (TPYN). This methodology ensures proximity to practical application, which in turn facilitates the development of practice-oriented use cases. Later, business recommendations (Chapter 3) will be derived from the company's strategic decisions based on the theoretically knowledge about data strategy gained in Chapter 2. Based on the subject, the paper can be assigned to the discipline of strategic IT management (SITM). Furthermore, a reference to the cross-disciplinary field of digital transformation can be made. Eventually, emerging technologies are required to enable and support the growing intelligence.
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