Various issues confront instant delivery,such as elevated labor expenses,low efficiency,and courier accidents.Consequently,e-commerce and logistics providers have turned their attention towards autonomous delivery veh...Various issues confront instant delivery,such as elevated labor expenses,low efficiency,and courier accidents.Consequently,e-commerce and logistics providers have turned their attention towards autonomous delivery vehicles(ADVs).There are no studies on customers who use instant delivery that focus on their preferences for ADVs in relation to cargo dam-age in conjunction with other delivery attributes such as instant delivery service use fre-quency and price of orders.The objective of this study is to examine customers’preferences for ADVs in comparison to traditional courier delivery.To account for the heterogeneity of customers,this study employs the random parameter logit(RPL)model with interactions to quantify the relevance of attributes and their interaction effects.This study is the first to consider cargo damage as an alternative-specific attribute(ASA)in the context of preference studies for instant delivery modes.We also examine the inter-action effects between delivery price and personal and delivery attributes,considering the significance and notable preference variations regarding delivery price across different populations.For data collection,a survey employing stated-preference(SP)approach was conducted in China,resulting in 309 effective surveys.The findings indicate that cus-tomer preference heterogeneity regarding delivery price and cargo damage both follow normal distributions.And gender,privacy,instant delivery service use frequency,and price of orders all show significant effects on customers’preferences for ADVs.Analysis of the survey answers also revealed statistically significant positive interaction effects on delivery price associated with income and instant delivery service use frequency.This study con-tributes to understanding customer preferences for ADVs,thereby assisting logistics provi-ders in identifying target customers for ADVs.展开更多
Big data on product sales are an emerging resource for supporting modular product design to meet diversified customers’requirements of product specification combinations.To better facilitate decision-making of modula...Big data on product sales are an emerging resource for supporting modular product design to meet diversified customers’requirements of product specification combinations.To better facilitate decision-making of modular product design,correlations among specifications and components originated from customers’conscious and subconscious preferences can be investigated by using big data on product sales.This study proposes a framework and the associated methods for supporting modular product design decisions based on correlation analysis of product specifications and components using big sales data.The correlations of the product specifications are determined by analyzing the collected product sales data.By building the relations between the product components and specifications,a matrix for measuring the correlation among product components is formed for component clustering.Six rules for supporting the decision making of modular product design are proposed based on the frequency analysis of the specification values per component cluster.A case study of electric vehicles illustrates the application of the proposed method.展开更多
In a multichannel supply chain comprising of dual-channel retailers with both physical and online channels as well as single-channel e-tailers with online channels,a multichannel demand model for e-commerce is constru...In a multichannel supply chain comprising of dual-channel retailers with both physical and online channels as well as single-channel e-tailers with online channels,a multichannel demand model for e-commerce is constructed based on customer channel preferences,and a Stackerberg game model with price competition dominated by dual-channel retailers and single-channel e-tailers as well as a Bertrand game model with equal rights are established to analyze the impact of different channel rights structures on the price,demand,and profit of the two retailers.The results show that the single-channel e-tailer under the dual-channel retailer-dominated game has the highest profit,and the dual-channel retailer xmder the single-channel e-tailer-dominated game has the highest profit;thus,both retailers should accept the other's dominant channel rights for profit maximization.展开更多
基金supported in part by the National Natural Science Foundation of China(No.72101188)the Shanghai Municipality Science and Technology Commission Soft Science Research Project(No.24692106100).
文摘Various issues confront instant delivery,such as elevated labor expenses,low efficiency,and courier accidents.Consequently,e-commerce and logistics providers have turned their attention towards autonomous delivery vehicles(ADVs).There are no studies on customers who use instant delivery that focus on their preferences for ADVs in relation to cargo dam-age in conjunction with other delivery attributes such as instant delivery service use fre-quency and price of orders.The objective of this study is to examine customers’preferences for ADVs in comparison to traditional courier delivery.To account for the heterogeneity of customers,this study employs the random parameter logit(RPL)model with interactions to quantify the relevance of attributes and their interaction effects.This study is the first to consider cargo damage as an alternative-specific attribute(ASA)in the context of preference studies for instant delivery modes.We also examine the inter-action effects between delivery price and personal and delivery attributes,considering the significance and notable preference variations regarding delivery price across different populations.For data collection,a survey employing stated-preference(SP)approach was conducted in China,resulting in 309 effective surveys.The findings indicate that cus-tomer preference heterogeneity regarding delivery price and cargo damage both follow normal distributions.And gender,privacy,instant delivery service use frequency,and price of orders all show significant effects on customers’preferences for ADVs.Analysis of the survey answers also revealed statistically significant positive interaction effects on delivery price associated with income and instant delivery service use frequency.This study con-tributes to understanding customer preferences for ADVs,thereby assisting logistics provi-ders in identifying target customers for ADVs.
基金National Key R&D Program of China(Grant No.2018YFB1701701)Sailing Talent Program+1 种基金Guangdong Provincial Science and Technologies Program of China(Grant No.2017B090922008)Special Grand Grant from Tianjin City Government of China。
文摘Big data on product sales are an emerging resource for supporting modular product design to meet diversified customers’requirements of product specification combinations.To better facilitate decision-making of modular product design,correlations among specifications and components originated from customers’conscious and subconscious preferences can be investigated by using big data on product sales.This study proposes a framework and the associated methods for supporting modular product design decisions based on correlation analysis of product specifications and components using big sales data.The correlations of the product specifications are determined by analyzing the collected product sales data.By building the relations between the product components and specifications,a matrix for measuring the correlation among product components is formed for component clustering.Six rules for supporting the decision making of modular product design are proposed based on the frequency analysis of the specification values per component cluster.A case study of electric vehicles illustrates the application of the proposed method.
文摘In a multichannel supply chain comprising of dual-channel retailers with both physical and online channels as well as single-channel e-tailers with online channels,a multichannel demand model for e-commerce is constructed based on customer channel preferences,and a Stackerberg game model with price competition dominated by dual-channel retailers and single-channel e-tailers as well as a Bertrand game model with equal rights are established to analyze the impact of different channel rights structures on the price,demand,and profit of the two retailers.The results show that the single-channel e-tailer under the dual-channel retailer-dominated game has the highest profit,and the dual-channel retailer xmder the single-channel e-tailer-dominated game has the highest profit;thus,both retailers should accept the other's dominant channel rights for profit maximization.
