网购平台在线声誉机制作用的实证研究方法评析

在线声誉机制是网购平台重要的信号机制,是平台可持续成长的基础.从理论基础、研究假设、数据来源、变量选择、模型应用等方面,全面梳理了在线声誉机制作用的实证研究方法,包括Hedonic回归、Logit、Probit、Poisson、Tobit、截取正态回归、样本选择回归、固定效应、广义最小二乘法等模型的应用.最后展望未来相关研究及方法,并构建在线声誉机制作用的实证研究综合框架.     

Supporting Learning in Evolving Dynamic Environments

In dynamic decision environments such as direct sales, customer support, and electronically mediated bargaining, decision makers execute sequences of interdependent decisions under time pressure. Past decision support systems have focused on substituting for decision makers' cognitive deficits by relieving them of the need to explicitly account for sequential dependencies. However, these systems themselves are fragile to change and, further, do not enhance decision makers' own adaptive capacities. This study presents an alternative strategy that defines information systems requirements in terms of enhancing decision makers' adaptation. In so doing, the study introduces a simulation model of how decision makers learn patterns of sequential dependency. When a system was used to manage workflows in a way predicted by the model to enhance learning, decision makers in a bargaining experiment learned underlying patterns of sequential dependencythat helped them adapt to new situations. This result is rare if not unique in the study of dynamic decision environments. It indicates that a shift, away from substituting for short-term deficits and toward enhancing pattern learning, can substantially improve the effectiveness of decision support in dynamic environments. Based on the specific findings in this study, this shift has important implications for designing information system workflows and potential future applications in interface design.     

电子商务环境下定价与退货策略整合优化研究

在电子商务供应链环境下,顾客直接从电子市场采购商品,失去了现场检查商品性能与质量的机会,结果造成顾客对所购商品不满意甚至退货的可能性增加.一个清晰、优惠的退货条例会受到顾客的欢迎,增加市场需求,提升企业的竞争力,然而,对制造厂家来说既可能增加收入,也可能增加退货成本.本文以商品价格和退货退款为决策变量,建立企业利润最大化模型,以此为依据企业可获得最优的定价和退货退款比例,使得从事电子商务的经理们有了使企业获得最大利润的理论依据.最后,指出了未来可能的几个研究方向.