This paper examines the optimal forecast-sharing strategy in a hybrid-format online platform supply chain where a supplier sells a product through agency format and reselling format provided by a platform retailer who...This paper examines the optimal forecast-sharing strategy in a hybrid-format online platform supply chain where a supplier sells a product through agency format and reselling format provided by a platform retailer who possesses demand forecasts from two channels.Forecast asymmetry and co-opetitive relationship arise between the platform retailer and the supplier,which affect their operational decisions and the supply chain’s performance.To improve supply chain efficiency,we compare different forecast-sharing strategies(i.e.,no forecast sharing,sharing a single forecast,and sharing two forecasts),and analyze the effects of co-opetitive parameters on the optimal forecast-sharing strategy.Our analysis shows that forecast sharing is always beneficial to the supplier,and sharing two forecasts is more beneficial than sharing a single forecast.Whereas for the platform retailer and the whole supply chain,forecast sharing is beneficial only under certain conditions,depending on the co-opetitive parameters.The optimal forecast-sharing strategy is the result of a combination of the negative effect of double marginalization in reselling channel and the positive effect of responding pricing to demand uncertainty in agency channel.We illustrate the parameter regions of the platform retailer’s voluntary sharing,contract sharing,and no sharing,and also find that higher channel competition intensity,higher market share of agency channel,and higher commission rate can promote the platform retailer’s voluntary sharing.Our study extends the research scope of demand forecast-sharing and sheds light on the decision-making processes for managing a hybrid-format online platform supply chain.展开更多
The spread of online topics,which is a complex socio-psychological and information dissemination process,can significantly influence the online public opinion. The behavior of online topics spreading is explored and i...The spread of online topics,which is a complex socio-psychological and information dissemination process,can significantly influence the online public opinion. The behavior of online topics spreading is explored and its regularity is attempted to analyze. A general model for the spread of online topics is introduced,and the differential equation that describes the velocity of an online topic＇s spreading is derived. The velocity of an online topic＇s spread indicates the level of the topic＇s development and reflects its popularity over time. The proposed model has been theoretically analyzed and empirically studied,respectively. By analyzing the data set from a famous Internet forum,it is shown that the development of spread velocity of online topics has some certain features and our model matches the laws of reality. This method,which is suitable for forecasting the development trend of online topics’ spread velocity in short term,is also critical to the success of online topics’ regularity analysis.展开更多
基金supported in part by National Natural Science Foundation of China under Grant Nos.72171169 and 71971076.
文摘This paper examines the optimal forecast-sharing strategy in a hybrid-format online platform supply chain where a supplier sells a product through agency format and reselling format provided by a platform retailer who possesses demand forecasts from two channels.Forecast asymmetry and co-opetitive relationship arise between the platform retailer and the supplier,which affect their operational decisions and the supply chain’s performance.To improve supply chain efficiency,we compare different forecast-sharing strategies(i.e.,no forecast sharing,sharing a single forecast,and sharing two forecasts),and analyze the effects of co-opetitive parameters on the optimal forecast-sharing strategy.Our analysis shows that forecast sharing is always beneficial to the supplier,and sharing two forecasts is more beneficial than sharing a single forecast.Whereas for the platform retailer and the whole supply chain,forecast sharing is beneficial only under certain conditions,depending on the co-opetitive parameters.The optimal forecast-sharing strategy is the result of a combination of the negative effect of double marginalization in reselling channel and the positive effect of responding pricing to demand uncertainty in agency channel.We illustrate the parameter regions of the platform retailer’s voluntary sharing,contract sharing,and no sharing,and also find that higher channel competition intensity,higher market share of agency channel,and higher commission rate can promote the platform retailer’s voluntary sharing.Our study extends the research scope of demand forecast-sharing and sheds light on the decision-making processes for managing a hybrid-format online platform supply chain.
基金supported by the National Natural Science Foundation of China under Grant No. 60972012the Beijing Natural Science Foundation under Grant No. 4102047+2 种基金the Major Program for Research on Philosophy & Humanity Social Sciences of the Ministry of Education of China under Grant No. 08WL1101the Academic Discipline and Postgraduate Education Project of Beijing Municipal Commission of Educationthe Service Business of Scientists and Engineers Project under Grant No. 2009GJA00048
文摘The spread of online topics,which is a complex socio-psychological and information dissemination process,can significantly influence the online public opinion. The behavior of online topics spreading is explored and its regularity is attempted to analyze. A general model for the spread of online topics is introduced,and the differential equation that describes the velocity of an online topic＇s spreading is derived. The velocity of an online topic＇s spread indicates the level of the topic＇s development and reflects its popularity over time. The proposed model has been theoretically analyzed and empirically studied,respectively. By analyzing the data set from a famous Internet forum,it is shown that the development of spread velocity of online topics has some certain features and our model matches the laws of reality. This method,which is suitable for forecasting the development trend of online topics’ spread velocity in short term,is also critical to the success of online topics’ regularity analysis.
