Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Estimation and Inference in Econometrics

Online shopping provides convenience to Web shoppers, yet its electronic format changes information-gathering methods traditionally used by customers. This change raises questions concerning customer satisfaction with the online purchasing process. Web shopping involves a number of phases, including the information phase, in which customers search for information regarding their intended purchases. The purpose of this paper is to develop theoretically justifiable constructs for measuring Web-customer satisfaction during the information phase.By synthesizing the expectation-disconfirmation paradigm with empirical theories in user satisfaction, we separate Web site quality into information quality (IQ) and system quality (SQ), and propose nine key constructs for Web-customer satisfaction. The measurements for these constructs are developed and tested in a two-phase study. In the first phase, the IQ and SQ dimensions are identified, and instruments for measuring them are developed and tested. In the second phase, using the salient dimensions of Web-IQ and Web-SQ as the basis for formulating first-order factors, we develop and empirically test instruments for measuring IQ and SQ-satisfaction. Moreover, this phase involves the design and test of second-order factors for measuring Web-customer expectations, disconfirmation, and perceived performance regarding IQ and SQ. The analysis of the measurement model indicates that the proposed metrics have a relatively high degree of validity and reliability. The results of the study provide reliable instruments for operationalizing the key constructs in the analysis of Web-customer satisfaction within the expectation-disconfirmation paradigm.

The Measurement of Web-Customer Satisfaction: An Expectation and Disconfirmation Approach

Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood, information-theoretic, and Bayesian techniques to analyze their own data using the programming language R. Drawing on extensive experience teaching these techniques to graduate students in ecology, Benjamin Bolker shows how to choose among and construct statistical models for data, estimate their parameters and confidence limits, and interpret the results. The book also covers statistical frameworks, the philosophy of statistical modeling, and critical mathematical functions and probability distributions. It requires no programming background--only basic calculus and statistics.

Ecological Models and Data in R

This study proposes a research model that examines the determinants of student learning satisfaction in a blended e-learning system (BELS) environment, based on social cognitive theory. The research model is tested using a questionnaire survey of 212 participants. Confirmatory factor analysis (CFA) was performed to test the reliability and validity of the measurements. The partial least squares (PLS) method was used to validate the measurement and hypotheses. The empirical findings indicate that computer self-efficacy, performance expectations, system functionality, content feature, interaction, and learning climate are the primary determinants of student learning satisfaction with BELS. The results also show that learning climate and performance expectations significantly affect learning satisfaction. Computer self-efficacy, system functionality, content feature and interaction significantly affect performance expectations. Interaction has a significant effect on learning climate. The findings provide insight into those factors that are likely significant antecedents for planning and implementing a blended e-learning system to enhance student learning satisfaction.

A study of student satisfaction in a blended e-learning system environment

While interactions in the real world shopping are mainly based on face‐to‐face activities between consumers and service personnels, interactions in electronic commerce take place mainly through the retailer’s Web site. This study investigated the relationship between various characteristics of online shopping and consumer purchase behavior. Results of the online survey with 602 Korean customers of online bookstores indicate that information quality, user interface quality, and security perceptions affect information satisfaction and relational benefit, that, in turn, are significantly related to each consumer’s site commitment and actual purchase behavior.

Identifying key factors affecting consumer purchase behavior in an online shopping context

A hybrid grouping genetic algorithm for the cell formation problem

In the search for substantive relationships in the use of emerging technology, information quality is often difficult to assess. This research explores user perceptions of presentation, navigation, and quality of Web home pages for approximately 200 selected Fortune 500 companies across 10 industries. An instrument is developed to measure these constructs and is assessed for convergent and discriminant validity as well as reliability. Company Web home pages are clustered using 24 Web site features. Interpretations of the type of Web home page within a cluster are based on their characteristics. An explorative analysis is performed between types of Web home pages and user perceptions of these sites. This study provides empirical evidence of relationships between companies at different positions in the supply chain and the information quality of their Web home pages.

https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1109&context=icis2000

Information quality of commericial web site home pages: an explorative analysis

H ow much will the Y2K computer-date problem cost to fix? Almost all Y2K projects require a cost estimate before actual repairs can proceed. Most cost estimates for Y2K repairs are based on rules of thumb involving some size measure, like lines of code, number of function points, and dollars of annual IS spending. These generic estimation approaches are prone to error when applied to a specific enterprise. Two of them are based on the total application inventory in an enterprise. Using function points, the average estimate for software repairs alone is $512 per function point repaired (ranging from $438 to $917, depending on industry) or an average of $42 (ranging from $23 to $53) for every function point in the enterprise [3]. Using lines of code, recommendations range from $0.75 to more than $7.00 for every line of code, averaging $1 to $2. The other rule, recommended by the Society of Information Management (SIM) Year-2000 Working Group [4, 5], derived from its 1996 survey, is approximately 30% of an annual IS operating budget. However, all of these estimating approaches tend to involve high variance and high margins for error when applied to a specific organization , because they are based on averages and there is a wide range of differences among enterprises and applications. Cost is not independent but a function of the enterprise itself, its particular Y2K problem, the solution it chooses, and the management and availability of resources during solution projects. Our purpose is to use the data from the SIM study to explore cost-estimating relationships within the context of these influences (see the sidebar \" How the Study Was Done \"). The short-term goal is not to isolate a cost-estimating formula per se but to suggest possible relationships and areas that may need special attention from managers of Y2K projects in order to use the rules of thumb. The cost of updating and/or replacing information technology (IT) for Y2K compliance is highly situa-tional and depends on an organization's specific internal and external factors. Figure 1 shows a model for cost estimation indicating four main categories of cost influence: the organization; the extent and complexity of its Y2K problem; how it will solve its problem; and the availability of resources to achieve the solution. Cost estimation should include the costs of project management, direct labor, and identification of affected software, affected data, and alternative solutions, testing, and …

Calculating the cost of year-2000 compliance

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