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Product release strategies in the digital economy
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Koca-E-2018-PhD-Thesis.pdf | Thesis | 7.17 MB | Adobe PDF | View/Open |
Title: | Product release strategies in the digital economy |
Authors: | Koca, Esma |
Item Type: | Thesis or dissertation |
Abstract: | Digital technologies have been transforming the economy and are challenging many traditional frameworks. In this thesis, we contribute to the research stream that revisits conventional models in the light of the digital economy. Our focus is on the releases of new products, a widespread business practice disrupted by digitally-driven consumer preferences and by an enhanced toolbox for firms. First, we model analytically the releases of different versions of a durable product in a monopoly. A firm selects the price, time to release a new version, and whether to continue selling the old product at a discount or not. Consumers, on the other hand, have distinct foresight and perception of product obsolescence. We show that the firm's release strategy crucially depends on obsolescence perception of consumers and that the firm can influence obsolescence by a prudent timing of the new version. Secondly, we provide an analytical framework for the release of a new product category when two asymmetric firms engage in price and quality competition. One of the firms, the ecosystem firm, can leverage its previous market coverage. The other firm, the category firm, is new to the market. The ecosystem firm can add on to the stand-alone quality of the new product by linking the two classes of products via a software while the category firm relies only on the intrinsic connection between the products. We characterize the conditions when the ecosystem leverage keeps the competitor at bay and deters innovation. Finally, we discuss release strategies of online content providers, such as streaming services and e-learning platforms. We provide an optimization model that covers three aspects of the release strategy: release of an individual series, order of multiple series within each subscription period, and personalization of the content. Further, we test our model using data from online education. |
Content Version: | Open Access |
Issue Date: | Sep-2018 |
Date Awarded: | Dec-2018 |
URI: | http://hdl.handle.net/10044/1/84703 |
DOI: | https://doi.org/10.25560/84703 |
Copyright Statement: | Creative Commons Attribution NonCommercial Licence |
Supervisor: | Valletti, Tommaso Wiesemann, Wolfram |
Department: | Imperial College Business School |
Publisher: | Imperial College London |
Qualification Level: | Doctoral |
Qualification Name: | Doctor of Philosophy (PhD) |
Appears in Collections: | Imperial College Business School PhD theses |
This item is licensed under a Creative Commons License