An Auction-Based Recommender System for Over-The-Top Platform

In this era of digital domination,it is fit to say that individuals are more inclined towards viewership on online platforms due to the wide variety and the scope of individual preferences it provides.In the past few years,there has been a massive growth in the popularity of Over-The-Top platforms,with an increasing number of consumers adapting to them.The Covid-19 pandemic has also caused the proliferation of these services as people are restricted to their homes.Consumers are often in a dilemma about which subscription plan to choose,and this iswhere a recommendation systemmakes their task easy.The Subscription recommendation system allows potential users to pick the most suitable and convenient plan for their daily consumption from diverse OTT platforms.The economic equilibrium behind allocating these resources follows a unique voting and bidding system propped by us in this paper.The systemis dependent on two types of individuals,type 1 seeking the recommendation plan,and type 2 suggesting it.In our study,the system collaborates with the latterwho participate in voting and invest/bid in the available options,keeping in mind the user preferences.This architecture runs on an interface where the candidates can login to participate at their convenience.As a result,selective participants are awarded monetary gains considering the rules of the suggested mechanism,and the most voted subscription plan gets recommended to the user.

What Drives Up Land Price in China?Evidence from Bidding Processes of Land Auctions in Beijing

The land price in big cities draws much attention and discussion for its skyrocketing appreciation.Most researches are from the macro perspective due to data restriction.This paper aims to investigate the critical factors in the price formation process of a land auction,using the listing auction micro bidding-level data in Beijing from 2013 to 2018.We construct a model for the relationship between quitting price and land,bidder's characteristics,housing market conditions and competitive intensity(including private and public signals),then we use OLS for identification.We find that competitive intensity increases the quitting price by causing competition and interaction between bidders.More importantly,we find evidence of cheating behavior in the land market.Results show that bidders have higher quitting prices when they are in a joint venture,and when a central SOE developer or a top 10 developer exist in the joint venture.We also find different behavior of developers in the short run and long run.Our research contributes to the literature of land auctions by analyzing the price formation process and developers'behavior.We also provide supporting evidence for the government to make adjustments of the auction system and identify the cheating developers.

Pareto Optimal Solution for Supply Contracts with Multiple Suppliers

This paper analyzes an electronic procurement （e-procurement） process between a manufacturer and N-supplier in the e-market. We proof that using the general contract based on auction theory, i. e. the wholesale price contract, would not achieve the coordination of channel composed of the manufacturer and the winning supplier. The paper designs a contract mechanism, i.e. the side payment price-restricted contract based on auction theory, which not only ensures Pareto optimal solutions for both, but also coordinates the supply chain. A numerical experiment is provided to compare the performance of different auction mechanisms and to reinforce key managerial insights generated through analysis.