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Means, medians and SD for available socio‐economic status (SES) black‐white differences are here substituted for those of IQ in a between‐groups model published by the author over a decade ago. The goodness of fit of the SES variables used is compared with that for the earlier IQ data. Even when SES variables are relatively successful this can be viewed as additional evidence of the importance of IQ differences to black‐white differences in delinquency.

The purpose of this paper is to investigate the properties of the classical goodness of fit test statistics X², G², GM², and NM² in testing quality of process represented as the trinomial distribution with dip null hypothesis and to devise a control chart for the trinomial distribution with dip null hypothesis based on demerit control chart.

The research involves the linear form of the test statistics, the linear function of counts since the marginal distribution of the counts in any category is binomial or approximated Poisson, in which the uniformly minimum variance unbiased estimator is the linear function of counts. A control chart is used for monitoring student characteristics in Thailand. The control chart statistics based on an average of the demerit value computed for each student as a weighted average lead to a uniformly most powerful unbiased test marginally. The two‐sided control limits were obtained using percentile estimates of the empirical distribution of the averages of the demerit.

The demerit control chart of the weight set (1, 25, 50) shows a generally good performance, robust to direction of out‐of‐control, mostly outperforms the GM² and is recommended. The X², NM² are not recommended in view of inconsistency and bias. The performance of the demerit control chart of the weight set (1, 25, 50) does not dramatically change between both directions.

None of the multivariate control charts for counts presented in the literature deals with trinomial distribution representing the practical index of the quality of the production/process in which the classification of production outputs into three categories of “good”, “defective”, and “reworked” is common. The demerit‐based control chart presented here can be applied directly to this situation.

The research considers how to deal with the trinomial distribution with dip null hypothesis which no research study so far has presented. The study shows that the classical Pearson's X², Loglikelihood, modified Loglikelihood, and Neyman modified X² could fail to detect an “out‐of‐control”. This research provides an alternative control chart methodology based on demerit value with recommended weight set (1, 25, 50) for use in general.

The purpose of this paper is to propose a new method based on goodness of fit tests for shift detection problems.

In this method, although the distribution of gathered data from the process is the subject of control, but any out-of-control signal could also be generalized to the overall state of the process including the parameters of the distribution.

Results of simulation study denote that among goodness of fit tests, the χ2 test has a better performance than the Kolmogorov-Smirnov test in detecting shifts of process. Also comparison of proposed method with traditional methods denotes that, proposed method generally has smaller probabilities of first and second type errors.

To the best of author’s knowledge, no attention has previously been paid to application of goodness of fit tests in process control.

This study aims to apply a systematic statistical approach, including several plot indexes, to diagnose the goodness of fit of a logistic regression model, and then to detect the outliers and influential observations of the data from experimental data.

The proposed statistical approach is applied to analyze some experimental data on internal solitary wave propagation.

A suitable logistic regression model in which the relationship between the response variable and the explanatory variables is found. The problem of multicollinearity is tested. It was found that certain observations would not have the problem of multicollinearity. The P‐values for both the Pearson and deviance χ² tests are greater than 0.05. However, the Pearson χ² value is larger than the degrees of freedom. This finding indicates that although this model fits the data, it has a slight overdispersion. After three outliers and influential observations (cases 11, 27, and 49) are removed from the data, and the remaining observations are refitted the goodness‐of‐fit of the revised model to the data is improved.

A comparison of the four predictive powers: R², max‐rescaled R², the Somers' D, and the concordance index c, shows that the revised model has better predictive abilities than the original model.

The goodness‐of‐fit and prediction ability of the revised logistic regression model are more appropriate than those of the original model.

The purpose of this study is to empirically examine the utility of information systems (IS) success models in mandatory e-government services, as opposed to the volitional ones that have been the focus of previous studies. The models include the technology acceptance model (TAM) (1989) and Seddon’s model (1997), which involve three (ease of use, usefulness and citizens satisfaction) and four variables (system quality, information quality, usefulness and citizen satisfaction).

The models were compared based on a survey conducted on 780 foundation year students of government universities in Saudi Arabia. The Saudi Government has launched a mandatory e-government service geared to assist high school graduates in the university academic admission process. The goodness-of-fit and parsimony of fit indices and the explanatory power were used to compare the two models.

The structural equation modeling techniques revealed that overall, the two models both exhibited reasonable fit with the collected data, whereas TAM showed the best fit to the sample data and yielded superior goodness-of-fit indices over Seddon’s model. In terms of explanatory power, Seddon’s model predicted 28% (R² = 0.28) of the variance explained for citizen satisfaction, whereas TAM predicted 21% (R² = 0.21). All the parsimony of fit indices favored TAM over Seddon’s model.

This study examined the validity of TAM and Seddon’s model, using citizen satisfaction as the dependent variable to compare them. TAM and Seddon’s model were modified to better fit the current research context of mandatory e-government services; thus, the findings may not hold for their original or other voluntary settings. In addition, the focus on a single survey for a certain time in a certain territory of mandatory e-government service may have limited the generalizability of the results to other mandatory contexts. Future research should make use of large, cross-sectional samples in different mandatory contexts to enhance result generalization.

This study’s findings can provide e-government practitioners with deeper perceptions of how to address citizen satisfaction with mandatory e-government services. The results exposed usefulness as the common and major construct, having the strongest influence on citizen satisfaction in both TAM and Seddon’s model; thus, maximizing the benefits of e-government services for citizens is crucial to their success. The causal relationship between information quality and citizen satisfaction was not supported. This supports the perspective that e-government services are currently evolving quickly, becoming more integrated and easier-to-use, generally requiring only a few clicks and less information.

This study has extended the assessment of the validity of IS success models to a mandatory IS usage setting. The comparison study of different IS success models is crucial as it acts as a guide for researchers to determine the trade-off between the models used to conduct research on a particular context. The study concludes that TAM is the most parsimonious and universal model for the study of user satisfaction in mandatory contexts. The findings will provide e-government practitioners with insights into IS success measures suited to enhance the effectiveness of newly and future mandated e-government services.

Companies in all industries are searching for new sources of competitive advantage since the competition in their marketplace is becoming increasingly intensive. The resource-based view of the firm explains the sources of sustainable competitive advantages. From a resource-based view perspective, relational based assets (i.e., the assets resulting from firm contacts in the marketplace) enable competitive advantage. The relational based assets examined in this work are brand image and corporate reputation, as components of brand equity, and customer value. This paper explores how they create value. Despite the relatively large amount of literature describing the benefits of firms in having strong brand equity and delivering customer value, no research validated the linkage of brand equity components, brand image, and corporate reputation, simultaneously in the customer value–customer loyalty chain. This work presents a model of testing these relationships in consumer goods, in a business-to-business context. The results demonstrate the differential roles of brand image and corporate reputation on perceived quality, customer value, and customer loyalty. Brand image influences the perception of quality of the products and the additional services, whereas corporate reputation actions beyond brand image, estimating the customer value and customer loyalty. The effects of corporate reputation are also validated on different samples. The results demonstrate the importance of managing brand equity facets, brand image, and corporate reputation since their differential impacts on perceived quality, customer value, and customer loyalty. The results also demonstrate that companies should not limit to invest only in brand image. Maintaining and enhancing corporate reputation can have a stronger impact on customer value and customer loyalty, and can create differential competitive advantage.

Describes research which continues the quest to model performance using structural equation models. The objective is to provide meaningful and substantively interpretable predictions of process performance using structural equation modelling. Develops structural equation models which clearly define the performance relationships for a backroom bank card remittance process using criteria such as process quality errors, employee turnover rates, labour productivity, on‐time delivery, and unit cost. Also defines the idea of a process quality equilibrium point (error rate) using structural equation modelling, and investigates how to use these structural equation models to help set internal and external standards of performance.

Goodness‐of‐fit test based on K_ϕ‐divergence between observed and theoretical frequencies are considered. The asymptotic chi‐square null distribution and three alternative approximations to the exact distribution function of this family are compared in small samples. Numerical results are presented for the symmetric null hypothesis for different multinomial sample sizes with various cell numbers. Exact power under specific alternatives to the symmetric null hypothesis are calculated and a comparison with the family of power divergence statistics is made.

Purpose – In this chapter, copula theory is used to model dependence structure between hedge fund returns series.

Methodology/approach – Goodness-of-fit tests, based on the Kendall's functions, are applied as selection criteria of the “best” copula. After estimating the parametric copula that best fits the used data, we apply previous results to construct the cumulative distribution functions of the equally weighted portfolios.

Findings – The empirical validation shows that copula clearly allows better estimation of portfolio returns including hedge funds. The three studied portfolios reject the assumption of multivariate normality of returns. The chosen structure is often of Student type when only indices are considered. In the case of portfolios composed by only hedge funds, the dependence structure is of Franck type.

Originality/value of the chapter – Introducing goodness-of-fit bootstrap method to validate the choice of the best structure of dependence is relevant for hedge fund portfolios. Copulas would be introduced to provide better estimations of performance measures.