The Experts below are selected from a list of 19461 Experts worldwide ranked by ideXlab platform
Jianqing Chen - One of the best experts on this subject based on the ideXlab platform.
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Spillover Effect of Consumer Awareness on Third Parties’ Selling Strategies and Retailers’ Platform Openness
Information Systems Research, 2020Co-Authors: Wen Song, Jianqing ChenAbstract:Global e-commerce sales have experienced unprecedented growth for the past years and have reached over $2 trillion annually. One interesting phenomenon along with this remarkable growth is that giant online retailers, such as Amazon.com in the United States and JD.com in China, open their platforms and allow third-party sellers to offer products there, thus inviting competition. We explore why an online retailer would open its platform and why a third-party seller would join the platform. We highlight the role of a Spillover Effect that, when the third-party seller joins the retailer’s platform, more consumers become aware of the third-party seller’s existence and its products which are not even listed on the retailer’s platform. We characterize how the third-party seller’s optimal selling strategies should vary with and how the retailer’s openness decision should be determined by the extent of the Spillover Effect and the retailer’s initial awareness advantage. Compared with the case without a Spillover Effect, the Spillover Effect makes the retailer less likely to open its platform, but it makes the third-party seller more likely to sell identical products on an open retailer platform; the Spillover Effect always (weakly) benefits the third-party seller, but it does not necessarily hurt the retailer.
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Spillover Effect of Consumer Awareness on Third Parties' Selling Strategies and Retailers' Platform Openness
SSRN Electronic Journal, 2017Co-Authors: Wen Song, Jianqing ChenAbstract:In this study, we explore why an online retailer would open its platform and why a third-party seller would join the platform when the third party carries products identical to those the retailer sells as well as products the retailer does not carry. When the third party joins the retailer's platform, more consumers become aware of the third party's existence, and thus might become aware of the products it does not list on the retailer's platform (e.g., by searching the seller brand online), which is called the Spillover Effect. We develop a game-theoretic model to first examine the Spillover Effect on the third-party seller's product offering on the retailer's platform under an exogenous commission rate and then examine the Effect on the retailer's platform-openness decision. We find that the third party's optimal selling strategies vary with its initial awareness level, the extent of the Spillover Effect, and the commission rate. Furthermore, we characterize how the initial awareness level and the extent of the Spillover Effect together determine the retailer's openness decision and equilibrium selling partnership. When the Spillover Effect is mild, the retailer opens its platform and the third-party seller sells its exclusive product on the platform. When the Spillover Effect is salient, if the retailer has a large awareness advantage over the third party, the retailer has no incentive to open; otherwise, the retailer opens its platform and the third party sells the identical product on the platform. Finally, we find that, compared to the case without a Spillover Effect, the Spillover Effect makes the retailer less likely to open its platform, but it makes the third party more likely to sell identical products on an open retailer platform; the Spillover Effect always (weakly) benefits the third party, but it does not necessarily hurt the retailer.
Wen Song - One of the best experts on this subject based on the ideXlab platform.
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Spillover Effect of Consumer Awareness on Third Parties’ Selling Strategies and Retailers’ Platform Openness
Information Systems Research, 2020Co-Authors: Wen Song, Jianqing ChenAbstract:Global e-commerce sales have experienced unprecedented growth for the past years and have reached over $2 trillion annually. One interesting phenomenon along with this remarkable growth is that giant online retailers, such as Amazon.com in the United States and JD.com in China, open their platforms and allow third-party sellers to offer products there, thus inviting competition. We explore why an online retailer would open its platform and why a third-party seller would join the platform. We highlight the role of a Spillover Effect that, when the third-party seller joins the retailer’s platform, more consumers become aware of the third-party seller’s existence and its products which are not even listed on the retailer’s platform. We characterize how the third-party seller’s optimal selling strategies should vary with and how the retailer’s openness decision should be determined by the extent of the Spillover Effect and the retailer’s initial awareness advantage. Compared with the case without a Spillover Effect, the Spillover Effect makes the retailer less likely to open its platform, but it makes the third-party seller more likely to sell identical products on an open retailer platform; the Spillover Effect always (weakly) benefits the third-party seller, but it does not necessarily hurt the retailer.
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Spillover Effect of Consumer Awareness on Third Parties' Selling Strategies and Retailers' Platform Openness
SSRN Electronic Journal, 2017Co-Authors: Wen Song, Jianqing ChenAbstract:In this study, we explore why an online retailer would open its platform and why a third-party seller would join the platform when the third party carries products identical to those the retailer sells as well as products the retailer does not carry. When the third party joins the retailer's platform, more consumers become aware of the third party's existence, and thus might become aware of the products it does not list on the retailer's platform (e.g., by searching the seller brand online), which is called the Spillover Effect. We develop a game-theoretic model to first examine the Spillover Effect on the third-party seller's product offering on the retailer's platform under an exogenous commission rate and then examine the Effect on the retailer's platform-openness decision. We find that the third party's optimal selling strategies vary with its initial awareness level, the extent of the Spillover Effect, and the commission rate. Furthermore, we characterize how the initial awareness level and the extent of the Spillover Effect together determine the retailer's openness decision and equilibrium selling partnership. When the Spillover Effect is mild, the retailer opens its platform and the third-party seller sells its exclusive product on the platform. When the Spillover Effect is salient, if the retailer has a large awareness advantage over the third party, the retailer has no incentive to open; otherwise, the retailer opens its platform and the third party sells the identical product on the platform. Finally, we find that, compared to the case without a Spillover Effect, the Spillover Effect makes the retailer less likely to open its platform, but it makes the third party more likely to sell identical products on an open retailer platform; the Spillover Effect always (weakly) benefits the third party, but it does not necessarily hurt the retailer.
Chen Zeng - One of the best experts on this subject based on the ideXlab platform.
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spatial Spillover Effect on land conveyance fee a multi scheme investigation in wuhan agglomeration
Land Use Policy, 2019Co-Authors: Chen ZengAbstract:Abstract Land revenue in the context of socioeconomic and political transformation has aroused a new round of attention among local governments. In this study, we attempt to address the questions on how the spatial Spillover Effect functions in the regional land conveyance fee (LCF), whether close administrative relations produce great spatial Spillover Effect on LCF, and whether a narrow gap in land premium rate can generate a strong spatial influence. We apply spatial modeling techniques in three different and progressive schemes, with Wuhan agglomeration as the case study area (2011–2017). The first scheme is based on the simple contiguity-based spatial weight matrix. The second is administrative-closeness-based (ACB) scheme that incorporates various spatial interaction magnitudes at different administrative ranks at the county level, which are acquired and calculated through a field survey. The third scheme embraces the gap in land premium rate into the spatial weight matrix to formulate the disparity-based (DPR) scheme. Results show that the spatial Spillover Effect is prominent when counties have a low level of administrative closeness and is apparent when the disparity of the land premium rate is large. Moreover, sector structure and rural income have significantly influenced LCF in recent years, with the former one being positive and the latter being negative. In the ACB scheme, the spatial Spillover Effect of LCF in the negative assumption is significant and increased from 2011 to 2017. In the DPR scheme, the spatial influences are larger in the positive assumption than in the negative one in spatial autoregressive terms in 2011 and 2017, but they are insignificant in 2013 and 2015. In the future, reforms on land revenue should be implemented to utilize the positive and negative spatial interactions at the county level for achieving a balanced regional development on land resources.
Lu Chen - One of the best experts on this subject based on the ideXlab platform.
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Optimization and Decision of Supply Chain Considering Negative Spillover Effect and Service Competition
Sustainability, 2021Co-Authors: Jiguang Wang, Lu ChenAbstract:Excellent service plays a vital role in the sustainability of enterprise and supply chains development in today’s increasingly fierce market competition. However, due to the inevitable Spillover Effect in the competitive network, enterprises’ initiative to improve the service level is reduced. From the perspective of negative Spillover Effect, optimization and decision-making in the competitive network of retailer-dominated supply chain are examined in this study. Considering four competitive situations in practical operation management, the corresponding double-layer compound nested Stackelberg game models are constructed, and the optimal equilibrium solutions are derived. Employing comprehensive comparison and analysis of the results, it is found that when the negative Spillover Effect of service increases, the optimal profit and service level of the leading supply chain or its retailers decrease, and the optimal retail price and overall optimal profit also gradually decline. For the leading supply chain, the centralized decision-making can achieve higher profits, and also more willing to improve the level of service. However, for the following supply chain, when the negative Spillover Effect of service is weak, the optimal service level under decentralized decision is higher, while when the Spillover Effect of service is strong, the optimal service level under integrated decision is higher. In addition, the supply chain-to-chain competition can bring negative incentives to the retailer that provides services, while for the rival that does not provide services, it can generate a certain free-riding Effect that benefits them, and the Effect is enhanced with the increase of competition.
Qingbin Guo - One of the best experts on this subject based on the ideXlab platform.
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Technology Spillover Effect in China: The Spatiotemporal Evolution and Its Drivers
Sustainability, 2019Co-Authors: Chengliang Liu, Qingbin GuoAbstract:Under the background of global economic integration, the technology Spillover Effect is playing a more and more important role in the technological progress of developing countries. In this circumstance, this paper conducted an in-depth analysis on the 12-year spatial-temporal evolution of the international technology Spillover Effect and its driving determinants in China during the period of 2003 to 2014. Analytical results highlighted that: (1) As a whole, the international technology Spillover Effect in general has shown an upward trend in China, except in 2008 and 2012, which are observed as deep-V plunge variations. The plunge in 2008 was more dramatic. After 2011, the growth rate of international technology Spillover Effect from international import trade and foreign direct investment (FDI) respects slowed obviously down. (2) The spatial distribution of the international technology Spillover Effect from FDI in China transferred from the ribbon-like pattern to the flake-like pattern, while the Effect from import trade held steady with little difference in regional spatial distribution. (3) From the drivers, human capital, economic development, trade openness, and institutional factors promoted the technological Spillover Effect of import trade channels positively, and financial development, human capital, economic development, and institutional factors promoted the technological Spillover Effect of FDI channels positively.
