Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Optimum Technology Product Life Cycle Technology Innovation Investment—Using Compound Binomial Options

Version 1 : Received: 27 July 2018 / Approved: 30 July 2018 / Online: 30 July 2018 (07:40:39 CEST)

A peer-reviewed article of this Preprint also exists.

Ko, C.-C.; Lin, T.T.; Zeng, F.-M.; Liu, C.-Y. Optimum Technology Product Life Cycle Technology Innovation Investment-Using Compound Binomial Options. Risks 2018, 6, 98. Ko, C.-C.; Lin, T.T.; Zeng, F.-M.; Liu, C.-Y. Optimum Technology Product Life Cycle Technology Innovation Investment-Using Compound Binomial Options. Risks 2018, 6, 98.

Abstract

The purpose of this paper is to evaluate the timing of innovative investment in technology product life cycles using a compound binomial option with management flexibility. Considering the business cycles changes in the macroeconomic will affect consumer purchasing power. The focus is how to evaluate the optimal investment strategy and the project value. It was applied to different product stages (three stages including production innovation, manufacture innovation, and operation innovation) and factored to different risks to build a technology innovation strategy model. An aim of this study is the options premium of the best strategy timing for each innovation stage. Its application of the compound binomial options for the manufacture innovation will only be considered after the execution of the production innovation. The same condition is applied to the operation innovation, which will only be considered after the execution of the manufacture innovation. Then, this paper constructs the dynamic investment sequential decision model, assesses the feasibility of an investment strategy, and makes a decision on the appropriate project value and options premium for each stage under the possible change of Gross Domestic Product (GDP). This paper investigates the product life cycle innovation investment topic by using the compound binomial options method and will provide a more flexible strategy decision compared with other trend forecast criteria.

Keywords

technological innovation; cloud computing; compound binomial options; investment risk; uncertainty

Subject

Social Sciences, Decision Sciences

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