Understanding the Determinants of Service Channel Preference in the Early Stages of Adoption: A Social Cognitive Perspective on Online Brokerage Services*

In today's increasingly technology‐mediated world, individuals are often confronted with a decision of whether to obtain services through online, self‐service technologies or traditional, nontechnological alternatives. Understanding the mechanisms by which consumers choose among these competing service channels represents an important concern for organizations, consumers, and Web site designers. This study develops a research model based on Social Cognitive Theory to explain and predict service channel preferences that arise in the early stages of adoption, before a consumer conducts business using a particular channel. The model is subsequently tested in the brokerage services context, using observations obtained via survey. Given the growing popularity of online investing combined with the challenging prospect of making optimal decisions in an inherently risky environment, the context offers insights of practical and theoretical importance. The results suggest that task‐specific self‐efficacy beliefs serve as the activating mechanism kicking off a chain of psychological events that entice consumers to favor a particular service channel. Higher levels of self‐efficacy induce individuals to prefer the online approach. In addition to its direct effect on preference for the online service channel, higher levels of self‐efficacy influence one's propensity to take risks and expectations of performance‐oriented rewards, which, in turn, sway consumers to favor the online service channel. Furthermore, self‐efficacy and perceptions concerning the credibility of online information interact to affect service channel preference. Consumers are more likely to prefer the online service channel when they view themselves as capable and perceive online sources to be credible. Implications for theory and practice are discussed in light of the findings.     

Construction and selection of quick switching double sampling system-acceptance number tightening

This paper presents a new sampling inspection system consisting of simple switching rule. The performance of the system is compared with those of other equivalent plans. Necessary tables are constructed and procedures presented for the selection of the sampling system.     

Tests Concerning Equicorrelation Matrices with Grouped Normal Data

ABSTRACT

This article considers three practical hypotheses involving the equicorrelation matrix for grouped normal data. We obtain statistics and computing formulae for common test procedures such as the score test and the likelihood ratio test. In addition, statistics and computing formulae are obtained for various small sample procedures as proposed in Skovgaard (2001 Skovgaard , I. M. . ( 2001 ). Likelihood asymptotics . Scand. J. Statist. . 28 : 3 – 32 . [CROSSREF] [Crossref], [Web of Science ®] , [Google Scholar]). The properties of the tests for each of the three hypotheses are compared using Monte Carlo simulations.     

Testing for Heteroscedasticity and/or Autocorrelation in Longitudinal Mixed Effect Nonlinear Models with AR(1) Errors

The effect of influental observation son the parameter estimates of ordinary least squares regression models has received considerable a t t e n t i o n fn the last decade. However, very little attention has been given to the problem of influential observation sinthea naysis of variace . The purpose of this paper is to show by way of examples that in fluential observations can alter the conclusions of tests of hypotheses in the analysis of variance . Regression diagno stics for identifying both extreme points and out liers can be used toreveal potential data and design problems.     

On Some New α-Modified Binomial and Poisson Distributions and Their Applications

A new class of α-modified binomial distribution has been proposed, and its distributional properties like probability generating function (pgf), moments, and their interrelations have been studied. Two new α-modified Poisson distributions and Poisson distribution have been obtained as limiting distributions. Modified binomial and Poisson distributions introduced by Berg and Jaworski (1988 Berg , S. , Jaworski , J. ( 1988 ). Modified binomial and Poisson distributions with application in random mapping theory . J. Statist. Plann. Infer. 18 : 313 – 322 . [Google Scholar]) have been seen as particular cases. Mixture distributions of α-modified binomial distributions have been derived. A new distributions called α-modified binomial distributions of type j, their moment properties, limiting distributions as α-modified Poisson distribution of type j, their different convolution properties, pgf, parameter estimators have been studied. Two more new distributions namely Doubly α-modified binomial distributions of type (i, j) and α-modified weighted generalized Poisson distributions of type (j ? 1) have also been studied. Various α-modified binomial and Poisson distributions of Berg and Mutafchiev (1990 Berg , S. , Mutafchiev , L. ( 1990 ). Random mapping with an attracting center: Lagrangian distributions and a regression function . J. Appl. Probab. 27 : 622 – 636 . [Google Scholar]) and Berg and Nowicki (1991 Berg , S. , Nowicki , K. ( 1991 ). Statistical inference for a class of modified power series distributions with applications to random mapping theory . J. Statist. Plann. Infer. 28 : 247 – 261 . [Google Scholar]) have been seen as special cases. Application of some of these proposed distributions have been identified.     

Reweighted Smooth Tests of Goodness of Fit

Starting from a smooth test for goodness of fit we develop a method to alter this test to a reweighted smooth test, which has greater power to a certain directional alternative. Whereas the original smooth test gives equal weight to the different directions in the space of alternatives, the reweighted smooth test makes a distinction in importance of the directions. The advantage of this test, as opposed to directional tests, is that the smooth character is largely maintained. We discuss both nested and non nested directional alternatives.     

Matching pseudocounts for interval estimation of binomial and Poisson parameters

ABSTRACT

For interval estimation of a binomial proportion and a Poisson mean, matching pseudocounts are derived, which give the one-sided Wald confidence intervals with second-order accuracy. The confidence intervals remove the bias of coverage probabilities given by the score confidence intervals. Partial poor behavior of the confidence intervals by the matching pseudocounts is corrected by hybrid methods using the score confidence interval depending on sample values.     

Confidence Interval of the Difference of Two Independent Binomial Proportions Using Weighted Profile Likelihood

Interval estimation of the difference of two independent binomial proportions is an important problem in many applied settings. Newcombe (1998 Newcombe , R. G. ( 1998 ). Interval estimation for the difference between independent proportions: comparison of seven methods . Statistics in Medicine 17 : 873 – 890 .[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) compared the performance of several existing asymptotic methods, and based on the results obtained, recommended a method known as Wilson's method, a modified version of a method originally proposed for single binomial proportion. In this article, we propose a method based on profile likelihood, where the likelihood is weighted by noninformative Jeffrey' prior. By doing extensive simulations, we find that the proposed method performs well compared to Wilson's method. A SAS/IML program implementing this method is also given with this article.     

Imputation in Data Fusion of Heterogeneous Data Sets A Model-Based Numerical Experiment

Given the very large amount of data obtained everyday through population surveys, much of the new research again could use this information instead of collecting new samples. Unfortunately, relevant data are often disseminated into different files obtained through different sampling designs. Data fusion is a set of methods used to combine information from different sources into a single dataset. In this article, we are interested in a specific problem: the fusion of two data files, one of which being quite small. We propose a model-based procedure combining a logistic regression with an Expectation-Maximization algorithm. Results show that despite the lack of data, this procedure can perform better than standard matching procedures.     

Analysis of survival data by a Weibull–Bessel distribution

In survival analysis and reliability studies, problems with random sample size arise quite frequently. More specifically, in cancer studies, the number of clonogens is unknown and the time to relapse of the cancer is defined by the minimum of the incubation times of the various clonogenic cells. In this article, we have proposed a new model where the distribution of the incubation time is taken as Weibull and the distribution of the random sample size as Bessel, giving rise to a Weibull–Bessel distribution. The maximum likelihood estimation of the model parameters is studied and a score test is developed to compare it with its special submodel, namely, exponential–Bessel distribution. To illustrate the model, two real datasets are examined, and it is shown that the proposed model, presented here, fits better than several other existing models in the literature. Extensive simulation studies are also carried out to examine the performance of the estimates.