2018
DOI: 10.1111/1475-4932.12385
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Technology Licensing in a Network Product Market: Fixed‐Fee versus Royalty Licensing

Abstract: This study investigates pricing and technology licensing decisions in a two‐echelon supply chain with one upstream firm that provides a key input to two downstream firms. We assume that one of the downstream firms owns a licensable innovation that exhibits network effects and that the other can either accept the licence from the innovator or develop a substitutable innovation. We analyse the effects of the producer‐innovator's two alternative licensing strategies (i.e. fixed‐fee and royalty licensing) on the m… Show more

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Cited by 15 publications
(6 citation statements)
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References 30 publications
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“…In contrast, fixed-fee policies result in higher consumer surplus and welfare than royalty and FR policies when the industry size is relatively large. Zhang et al (2018) find that royalty licensing is optimal when the network effect is low. Hsu et al (2019) find that ad valorem royalty licensing is superior to per-unit royalty licensing for the supplier if cost-reducing innovation is non-drastic.…”
Section: Theoretical Backgroundmentioning
confidence: 89%
“…In contrast, fixed-fee policies result in higher consumer surplus and welfare than royalty and FR policies when the industry size is relatively large. Zhang et al (2018) find that royalty licensing is optimal when the network effect is low. Hsu et al (2019) find that ad valorem royalty licensing is superior to per-unit royalty licensing for the supplier if cost-reducing innovation is non-drastic.…”
Section: Theoretical Backgroundmentioning
confidence: 89%
“…The difference in their finding is determined by whether the patent holder is an insider or not. Some studies examine the impact of other factors such as different market structures (Katz and Shapiro, 1985), type of competition (Kabiraj, 2004), network effect (Lin and Kulatilaka, 2006;Zhang et al, 2018), imitation costs (Kogan et al, 2013), cross-licensing (Zhao, 2017;Jeon and Lefouili, 2018;Choi and Gerlach, 2019;Wang and Huang, 2019;Zhao et al, 2022); and information asymmetry (Sen and Bhattacharya, 2017;Jeon, 2019;Hong et al, 2021).…”
Section: Literature Reviewmentioning
confidence: 99%
“…In recent times, as innovation-based competition in business and economic activities become more intense, technology licensing has attracted increasing attention in many industries for its value in innovation development and commercialization (Arora et al, 2013;Agrawal et al, 2016;Hong et al, 2017Hong et al, , 2021Wu, 2018). Many factors affect the transfer and commercialization of technologies, such as competition mode (Li and Ji, 2010;Nguyen et al, 2014;Zhao et al, 2022); product differentiation (Nguyen et al, 2014(Nguyen et al, , 2017Bakaouka and Milliou, 2018), imitation costs (Kogan et al, 2013), type of innovation (Agrawal et al, 2016;Chen and Xie, 2018), bargaining power of two parties (Kishimoto, 2020), and network effect (Lin and Kulatilaka, 2006;Zhang et al, 2018). In addition, mixed competition has different influences on market equilibrium as well as on social welfare compared with those under symmetric competition strategies (Tremblay and Tremblay, 2019;Lee et al, 2020;Askar, 2021;Kopel and Putz, 2021).…”
Section: Introductionmentioning
confidence: 99%
“…A variety of market structures, competitive models, and information structure models have all been used to study technology licensing approaches by scholars (Wang & Yang, 1999;Wang, 2002;Sen, 2005;Sen & Tauman, 2007;Sen & Bhattacharya, 2017;Niu, 2018;Jeon, 2019;Hattori & Tanaka, 2018, 2021. Other factors that influence the optimal licensing contract include product differentiation (Li & Wang, 2010;Ye & Mukhopadhyay, 2013;Rau et al, 2019;Zou & Chen, 2020;Sen et al, 2021;San Martín & Saracho, 2021), the number of participants (Antelo & Sampayo, 2017), and network effects (Zhao et al, 2014;Zhang et al, 2018). However, in the studies mentioned above, licensing of green technologies has received far less consideration than licensing for manufacturing technologies.…”
Section: Technology Licensingmentioning
confidence: 99%