Tempered stable Ornstein– Uhlenbeck processes: A practical view

We study the one-dimensional Ornstein–Uhlenbeck (OU) processes with marginal law given by tempered stable and tempered infinitely divisible distributions. We investigate the transition law between consecutive observations of these processes and evaluate the characteristic function of integrated tempered OU processes with a view toward practical applications. We then analyze how to draw a random sample from this class of processes by considering both the classical inverse transform algorithm and an acceptance–rejection method based on simulating a stable random sample. Using a maximum likelihood estimation method based on the fast Fourier transform, we empirically assess the simulation algorithm performance.     

顾客采用网络银行的影响因素研究

网络银行已经成为银行业保留老顾客和获取新顾客的一种新兴的服务渠道,而有关顾客采用网络银行影响因素的研究也越来越激发兴趣,引起关注。感知风险和信任是网络银行顾客最为担心的因素,但这似乎并没有引起学者们的足够重视。大多数研究都将顾客方面的建构作为认知建构的前置因素,而将银行方面的建构作为认知建构的前置因素的研究还几乎无人问津。本研究的重要意义在于:在具体的网络银行环境下,以科技接受模型为基础,在认知建构中增加感知风险和信任等变量,同时将顾客方面的自我效能和银行方面的便利条件两个建构分别作为认知构建的前置因素,从而对网络银行的采用意图进行理论探讨和实证检验。     

Sample Size Determination for a Two-Sided Multiple Components Tolerance Interval

In the conventional concept, the variance of a tolerance interval from the measurements is a single component, and the sample size for quality control process was estimated by the variance of a single component. However, we can find examples in recent about several components that could vary in their measurements, so an approximate method must be found to modify the conventional tolerance interval. In our paper, we develop an approach to calculate the sample size for a two-sided tolerance interval including several components in the variance from the measurements. An example is presented to illustrate our proposed method.     

Closed-Form Approximation for the AOQL of Attributes Acceptance Sample Plans

We derive upper and lower bounds at the point at which the average outgoing quality limit (AOQL) of an attributes acceptance sampling plan is achieved. Using a simple average of these bounds to approximate the ordinate of the AOQL, we develop an accurate, closed-form approximation to the AOQL. The bounds and approximation show how the parameters of a sampling plan affect the AOQL and can be used to study the behavior of the AOQL and other measures of the plan's performance.     

Simultaneous Inferences on the Cumulative Distribution Function of a Normal Distribution

This paper addresses the problem of constructing simultaneous confidence intervals for the cumulative distribution function of a normal distribution at several specified points. The procedure is based upon the observation of a random sample of independent observations from a normal distribution with an unknown mean and variance. A new methodology is proposed for obtaining confidence intervals with a specified overall simultaneous confidence level through the inversion of acceptance sets. Both one-sided and two-sided confidence intervals are considered. Some illustrations of the new method are provided, and comparisons are made with other approaches to the problem.     

A bayesian analysis of imperfect inspection models

An examination of sampling inspection models is provided for the case where inspection is not perfect and classification errors can be made. The conjugate family of distributions is obtained under t h e assumption that defective items are generated according to a Bernoulli process. To simplify analysis, the use of a single beta prior distribution is considered. Relevant predictive distributions are obtained.     

Examining the Impact of Pre‐Implementation Expectations on Post‐Implementation Use of Enterprise Systems: A Longitudinal Study

This article builds upon the technology acceptance model and theories of technology sensemaking to explore pre‐enterprise system adoption expectations and post‐enterprise system adoption outcomes in a longitudinal setting. Building on the exploitation and exploration paradigm, we propose that task productivity and task innovation expectations are the key drivers of users’ pre‐adoption enterprise system usage intention. Further, we argue that the enterprise system facilitates generation of a common knowledge base that may encourage a more integrated organizational culture and promote shared understanding among employees. Considering the distinction between mandatory and voluntary contexts, we propose that user acceptance of the enterprise system at the pre‐ and post‐adoption stages will mediate these relationships in a mandatory context. The results show that the influence of pre‐adoption expectations regarding task productivity and task innovation on intention to use an enterprise system is mediated by user acceptance of the enterprise system. Intention to use an enterprise system is positively related to actual use. At the post‐adoption stage, the influence of actual use on shared understanding is mediated by user acceptance of an enterprise system and enterprise system use has a direct negative impact on task efficiency in the initial period after implementation. Overall, the results highlight that user acceptance at both pre‐ and post‐adoption stages are critical factors when usage is mandatory. These findings suggest a number of important implications for research and for managerial action.     

Sample size choice for reliability verification in strength-stress models

This paper discusses the choice of sample size for experiments concerned with inference on R = P(Y < X), where X and Y are normal variates, in an acceptance-sampling-theory framework. A conservative approach is derived, and the properties of this solution examined by simulation.     

Major Psychological Factors Affecting Acceptance of Gene-Recombination Technology

The purpose of this study was to verify the validity of a causal model that was made to predict the acceptance of gene-recombination technology. A structural equation model was used as a causal model. First of all, based on preceding studies, the factors of perceived risk, perceived benefit, and trust were set up as important psychological factors determining acceptance of gene-recombination technology in the structural equation model. An additional factor, "sense of bioethics," which I consider to be important for acceptance of biotechnology, was added to the model. Based on previous studies, trust was set up to have an indirect influence on the acceptance of gene-recombination technology through perceived risk and perceived benefit in the model. Participants were 231 undergraduate students in Japan who answered a questionnaire with a 5-point bipolar scale. The results indicated that the proposed model fits the data well, and showed that acceptance of gene-recombination technology is explained largely by four factors, that is, perceived risk, perceived benefit, trust, and sense of bioethics, whether the technology is applied to plants, animals, or human beings. However, the relative importance of the four factors was found to vary depending on whether the gene-recombination technology was applied to plants, animals, or human beings. Specifically, the factor of sense of bioethics is the most important factor in acceptance of plant gene-recombination technology and animal gene-recombination technology, and the factors of trust and perceived risk are the most important factors in acceptance of human being gene-recombination technology.     

Using Davis's Perceived Usefulness and Ease-of-use Instruments for Decision Making: A Confirmatory and Multigroup Invariance Analysis

As key components of Davis's technology acceptance model (TAM), the perceived usefulness and perceived ease-of-use instruments are widely accepted among the MIS research community as tools for evaluating information system applications and predicting usage. Despite this wide acceptance, a series of incremental cross-validation studies have produced conflicting and equivocal results that do not provide guidance for researchers or practitioners who might use the TAM for decision making. Using a sample of 902 “initial exposure” responses, this research conducts: (1) a confirmatory factor analysis to assess the validity and reliability of the original instruments proposed by Davis, and (2) a multigroup invariance analysis to assess the equivalence of these instruments across subgroups based on type of application, experience with computing, and gender. In contrast to the mixed results of prior cross-validation efforts, the results of this confirmatory study provide strong support for the validity and reliability of Davis's sixitem perceived usefulness and six-item ease-of-use instruments. The multigroup invariance analysis suggests the usefulness and ease-of-use instruments have invariant true scores across most, but not all, subgroups. With notable exemptions for word processing applications and users with no prior computing experience, this research provides evidence that the item-factor loadings (true scores) are invariant across spread sheet, database, and graphic applications. The implications of the results for managerial decision making are discussed.