Valuation of an innovation strategy in the diversification of products in the agricultural auto parts sector
Purpose The purpose of this paper is to value an innovation project derived from a product diversification strategy in the agricultural auto parts sector, considering uncertainties and flexibility as sources of value for the project. Design/methodology/approach A case study project is presented and...
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Veröffentlicht in: | Agricultural finance review 2019-09, Vol.79 (4), p.519-536 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | Purpose
The purpose of this paper is to value an innovation project derived from a product diversification strategy in the agricultural auto parts sector, considering uncertainties and flexibility as sources of value for the project.
Design/methodology/approach
A case study project is presented and valued using real options, with the possibility of including new information modelled by Bayes’ theorem, which enables the fitting of the probabilities of the project for the purpose of valuation through the decision tree method.
Findings
The results indicate the effect of new information and provide implications for value creation, demonstrating the need for a more profound and systematic approach to the use of investment strategies considering factors endogenous and exogenous to a firm that can and should be considered in the decision-making process.
Practical implications
This study contributes to an understanding of the relationship of strategy and innovation through product diversification with value creation and serves as a guide for controlling the possibility of investments in diversified companies and agribusiness using the methodology discussed in this paper.
Originality/value
Valuing the inclusion of new information through Bayesian inference in the analysis of investments is a methodological feature that has received minimal attention in the literature. Therefore, the use of Bayesian theory for the real options model applied to agribusiness is the main innovation of this study to demonstrate new ways of modelling uncertainty in addition to stochastic processes. |
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ISSN: | 0002-1466 2041-6326 |
DOI: | 10.1108/AFR-10-2018-0088 |