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Determining Optimal Strategies for Investments in an Emerging IT Innovation

Title data

Häckel, Björn ; Pfosser, Stefan ; Stirnweiß, Dominic ; Voit, Christian:
Determining Optimal Strategies for Investments in an Emerging IT Innovation.
2018
Event: 26th European Conference on Information Systems (ECIS) , 23.-28.06.2018 , Portsmouth, UK.
(Conference item: Conference , Paper )

Official URL: Volltext

Abstract in another language

To generate competitive advantages through investments in emerging IT innovations, an economically well-founded investment strategy is of decisive importance, since timing and extent of investment amounts considerably determine the associated risk and return profile. Due to the uncertainty about emerging IT innovations, an early market entry time is associated with high risk, but offer high returns. A later market entry may carry lower risk but only offers lower returns. To take advantage of both investment strategies while reducing their disadvantages, a mix of both investment strategies can be advantageous. Companies often choose strict early or later investment strategies since an adequate assessment of possible combiniation opportunities and risks is not carried out in advance and company- and innovation-specific factors are neglected. Thus, we develop a quantitative optimization model enabling the determination of an optimal investment strategy and budget allocation to the two different investment strategies in the sense of maximizing the investment´s overall NPV supplementing previous studies by considering company- and IT innovation-specific factors. We show that strict investment strategies are often disadvantageous, that the amount of the investment budget influences the innovation´s expected NPV and that the company's innovativeness has a strong influence on the innovation budget allocation.

Further data

Item Type: Conference item (Paper)
Refereed: Yes
Keywords: IT Management; IT Innovations; IT Investments; Economic Value of IT
Institutions of the University: Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering
Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 29 Jun 2018 08:44
Last Modified: 19 Dec 2018 10:23
URI: https://eref.uni-bayreuth.de/id/eprint/44755