Re-examining online customer experience to include purchase frequency and perceived risk

This research examines the important emerging area of online customer experience (OCE) using data collected from an online survey of frequent and infrequent online shoppers. The study examines a model of antecedents for cognitive and affective experiential states and their influence on outcomes, such as online shopping satisfaction and repurchase intentions. The model also examines the relationships between perceived risk, trust, satisfaction and repurchase intentions. Theoretically, the study provides a broader understanding of OCE, through insights into two shopper segments identified as being important in e-retailing. For managers, the study highlights areas of OCE and their implications for ongoing management of the online channel.     

高炮随动系统自动测试中正弦机发送频率的确定

在某型高炮随动系统测试中,正弦机的发送频率直接影响着输出信号的平滑度,从而会影响测试的精度。为了避免在正弦机运行过程中,计算耗用过多机时,在正弦机发送之前,先计算出每个位置信号、前馈信号的数值,存放于内存中。本文根据该正弦机信号的特点,分析了几种正弦机角位置信号发送频率方式的优缺点,确定了正弦机发送频率的方式。     

定西地区农业生态系统结构优化的对策

本文通过定西地区农业生态系统结构与功能分析，认为：生态系统结构不完善，生产力和经济功能低下。据此从农业可持续发展的角度出发，提出了优化农业生态系统结构和提高其功能的对策。     

Escalating penalties for repeat offenders: a note on the role of information

The severity of the sanction for a given offense is often determined by the offense history of the offender. We establish that this policy can be welfare-maximizing if individuals are imperfectly informed about the magnitude of the sanction. Imperfect information distorts individuals’ perception of the expected sanction of the first offense. Once detected, individuals learn about the sanction applicable to their act, making this argument less relevant for consecutive offenses.      

Probabilistic Models for Bacterial Taxonomy

We give a survey of different partitioning methods that have been applied to bacterial taxonomy. We introduce a theoretical framework, which makes it possible to treat the various models in a unified way. The key concepts of our approach are prediction and storing of microbiological information in a Bayesian forecasting setting. We show that there is a close connection between classification and probabilistic identification and that, in fact, our approach ties these two concepts together in a coherent way.     

Causality effects in return volatility measures with random times

We provide a structural approach to identify instantaneous causality effects between durations and stock price volatility. So far, in the literature, instantaneous causality effects have either been excluded or cannot be identified separately from Granger type causality effects. By giving explicit moment conditions for observed returns over (random) duration intervals, we are able to identify an instantaneous causality effect. The documented causality effect has significant impact on inference for tick-by-tick data. We find that instantaneous volatility forecasts for, e.g., IBM stock returns must be decreased by as much as 40% when not having seen the next quote change before its (conditionally) median time. Also, instantaneous volatilities are found to be much higher than indicated by standard volatility assessment procedures using tick-by-tick data. For IBM, a naive assessment of spot volatility based on observed returns between quote changes would only account for 60% of the actual volatility. For less liquidly traded stocks at NYSE this effect is even stronger.     

Tax reform and collective family decision-making

Traditional analysis of tax reform treats market behaviour as arising out of individual utility maximisation. In this paper, behaviour is modelled as the Pareto-efficient outcome of a family decision process. Conditions for the existence of a feasible, Pareto-improving tax change are presented and contrasted with those that obtain in the individualistic case. The consequences of treating households as a single individual are also discussed.     

The role of externalities and information aggregation in market collapse

We examine the role that belief, network externality, and information aggregation play in inefficient market collapses. After receiving consecutive negative shocks, some ex-ante identical Bayesian agents will be discouraged about the unknown state of the market they invest; therefore, they will stop investing. This decision will have two effects: first, it will cause agents to aggregate information through social/observational learning; second, it will decrease the network externality effect. We show that there might be an inefficient market collapse if the externality effect diminishes too much, and the cost of re-entry to the market is too high. We also analyze the effects of strategic delay and experimentation on the exit decision of the agents. I especially thank Thomas D. Jeitschko, Matthew Mitchell, B. Ravikumar Ted Temzelides. I also thank anonymous referees, an associate editor, John Conlon, Larry Samuelson, Troy Tassier, Stephen Williamson, and seminar participants of the University of Saskatchewan, Georgia Tech, Concordia University, University of Manitoba, Iowa Alumni Workshop, Midwest Economic Theory Conferences held at Indiana Bloomington, and Notre Dame, and 1st International Conference on Business, Management and Economics organized by Yasar University.     

Local asymptotic normality for randomly censored models with applications to rank tests

For randomly right censored models we study the asymptotic behaviour of linear (rank) statistics under local alternatives. The results can be used to evaluate the asymptotic power of the corresponding tests. For instance we treat the question how to choose the best scores in order to derive asymptotically optimal (rank) tests under certain alternatives.     

A note on Deaton's theorem on the undesirability of nonuniform excise taxation

The paper provides an extension and a new proof of Deaton's theorem on the undesirability of nonuniform excise taxation when income taxes are affine and preferences over consumption goods are separable from labour–leisure choices, homothetic, and identical across agents.