Technology Licensing With Strategic Corporate Social Responsibility in a Vertically Differentiated Duopoly
Dongdong Li
School of Public Policy and Administration, Northwestern Polytechnical University, Xi'an, Shaanxi, China
Search for more papers by this authorWenyao Lin
School of Public Policy and Administration, Northwestern Polytechnical University, Xi'an, Shaanxi, China
Search for more papers by this authorCorresponding Author
Chenxuan Shang
Institute of Energy, Environment and Economy, Tsinghua University, Beijing, China
Correspondence:
Chenxuan Shang ([email protected])
Search for more papers by this authorDongdong Li
School of Public Policy and Administration, Northwestern Polytechnical University, Xi'an, Shaanxi, China
Search for more papers by this authorWenyao Lin
School of Public Policy and Administration, Northwestern Polytechnical University, Xi'an, Shaanxi, China
Search for more papers by this authorCorresponding Author
Chenxuan Shang
Institute of Energy, Environment and Economy, Tsinghua University, Beijing, China
Correspondence:
Chenxuan Shang ([email protected])
Search for more papers by this authorABSTRACT
In this paper, we study the impact of strategic corporate social responsibility (CSR) activities on the optimal licensing strategy for cost-reducing technology in a vertically differentiated duopoly. We compare three types of licensing strategies—fixed fee, royalty, and two-part tariff—under three CSR strategy structures: ST model (only firm 1 adopts a CSR strategy), TS model (only firm 2 adopts a CSR strategy), and SS model (both firms adopt CSR strategies). The results show that the licensor prefers fixed-fee licensing when it adopts a CSR strategy (i.e., ST and SS) but opts for two-part tariff licensing when it does not (i.e., TS). We also find that the optimal licensing contract leads to higher social welfare under the CSR compliance strategy than under the mixed CSR strategy. Finally, we show that firms endogenously choose the CSR compliance strategy.
Open Research
Data Availability Statement
Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.
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