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Mixed-mode designs are increasingly important in surveys, and large longitudinal studies are progressively moving to or considering such a design. In this context, our knowledge regarding the impact of mixing modes on data quality indicators in longitudinal studies is sparse. This study tries to ameliorate this situation by taking advantage of a quasi-experimental design in a longitudinal survey. Using models that estimate reliability for repeated measures, quasi-simplex models, 33 variables are analyzed by comparing a single-mode CAPI design to a sequential CATI-CAPI design. Results show no differences in reliabilities and stabilities across mixed modes either in the wave when the switch was made or in the subsequent waves. Implications and limitations are discussed. [ABSTRACT FROM AUTHOR]

Cross-level interaction effects lay at the heart of multilevel contingency and interactionism theories. Also, practitioners are particularly interested in such effects because they provide information on the contextual conditions and processes under which interventions focused on individuals (e.g., selection, leadership training, performance appraisal, and management) result in more or less positive outcomes. We derive a new intraclass correlation, ρβ, to assess the degree of lower-level outcome variance that is attributed to higher-level differences in slope coefficients. We provide analytical and empirical evidence that ρβ is an index of variance that differs from the traditional intraclass correlation ρα and use data from recently published articles to illustrate that ρα assesses differences across collectives and higher-level processes (e.g., teams, leadership styles, reward systems) but ignores the variance attributed to differences in lower-level relationships (e.g., individual level job satisfaction and individual level performance). Because ρα and ρβ provide information on two different sources of variability in the data structure (i.e., differences in means and differences in relationships, respectively), our results suggest that researchers contemplating the use of multilevel modeling, as well those who suspect nonindependence in their data structure, should expand the decision criteria for using multilevel approaches to include both types of intraclass correlations. To facilitate this process, we offer an illustrative data set and the icc beta R package for computing ρβ in single- and multiple-predictor situations and make them available through the Comprehensive R Archive Network (i.e., CRAN). [ABSTRACT FROM AUTHOR]

The importance of intermediate items has been overlooked since the emergence of dominance-based Likert-type scales. The current study aims to advance our understanding of the psychometric properties of intermediate items by showing that they can be successfully calibrated by an ideal point model. A student sample and an MTurk sample were selected to answer personality scales with intermediate items included. Results showed that personality scales with intermediate items demonstrated satisfactory model fits to the ideal point model, but not to the dominance model. When analyzed with the ideal point model, intermediate items provided more information than extreme items for respondents with high latent trait levels. Among four proposed domains of intermediate items (Frequency, Average, Condition, and Transition, “FACT”), the Average domain was consistently found to exhibit the best properties. The proportion of intermediate items in the scale also affected the model fit and the validity of the scale. [ABSTRACT FROM AUTHOR]

Corporate environmental performance (CEP) has been of fundamental interest in scholarly research during the last few decades. However, there is a great deal of disagreement pertaining to the definition, conceptualization, and adequate measurement of CEP. Our study addresses these issues and provides a methodologically rigorous and comprehensive examination of content validity and construct validity. By integrating the available literature on CEP, we derive a parsimonious definition and theoretically sound framework of the focal construct. Drawing on non-aggregated and publicly available data for a sample of 706 firm-years, we test the construct validity of this framework by means of factor analysis. Our results provide evidence for the multidimensional nature of the focal construct. By contrasting our findings with existing measurement approaches in empirical research, we emphasize several deficiencies with regard to the inferences and conclusions yielded in prior research. Future empirical and practically oriented studies can build on our findings and thus provide more stringent results. [ABSTRACT FROM AUTHOR]

Companies have traditionally considered innovation an internal process, and accordingly, they have relied on their internal intellectual capital. However, this closed innovation strategy has, in recent years, been superseded by an open innovation strategy. The existing measurement model of intellectual capital, which is concerned mainly with an internal dimension, is no longer appropriate for open innovation practice. To address this challenge, this paper reconstructs the measurement model of intellectual capital, expanding the concept to include both internal and external dimensions, both of which have the same three elements: human, structural, and relationship capital. To test the reliability and validity of this new model, we explore the impact of each element on innovation performance through an empirical study of 149 companies in China, and we find that all elements of internal and external intellectual capital have a significantly positive impact on innovation performance. This implies that our new measurement is appropriate for firms with an increasing degree of openness for innovation. [ABSTRACT FROM AUTHOR]

This article provides an overview and guide to implementing item response theory (IRT) measurement equivalence (ME) or differential item functioning (DIF) analysis. We (a) present the need for establishing IRT ME/DIF analysis, (b) discuss the similarities and differences between factor-analytic ME/DIF analysis, (c) review commonly used IRT ME/DIF indices and procedures, (d) provide three illustrations to two recommended IRT procedures, and (e) furnish recommendations for conducting IRT ME/DIF. We conclude by discussing future directions for IRT ME/DIF research. [ABSTRACT FROM PUBLISHER]

Copyright of Estudios Gerenciales is the property of Universidad ICESI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose -- This paper aims to investigate empirically how broadband has been implemented at the business level and what are the potential adoption benchmarks. Several recent studies have called for the development of frameworks of broadband adoption, particularly at the business level, to help policy makers, communities and businesses with their strategic decision-making process. Design/methodology/approach -- This paper opens the discussion by presenting concerns and challenges of Internet adoption. Internet adoption is viewed as the current challenge facing businesses, communities and governments. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) techniques are used to create, analyze and develop Internet adoption models. Findings -- Based on the Internet usage data from a number of states across the USA, measurement models are developed using EFA and CFA. The findings indicate that for our sample, a three-factor model is the most appropriate for the representation of Internet adoption in the tourism sector, while a five-factor model can best describe Internet adoption in the sample of manufacturing organizations. Research limitations/implications -- The availability of data on Internet usage at the business/organizational level is one of the main constraints. Industry/community-specific data can also provide valuable insights about the Internet adoption and support the development of industry/community-specific adoption models. Practical implications -- The findings and the employed research method can be used by businesses, communities and government managers and policy makers as benchmarks to examine broadband adoption based on gap-opportunity criteria. Originality/value -- This is the first study that provides Internet adoption models based on an empirical study at the business level. The benefits of broadband Internet have been investigated by many researchers in the past decade. There seems to be a consensus among practitioners and scholars about the role of broadband Internet in gaining competitive advantage. However, there have not been any previous studies that investigate how broadband has been implemented and what the potential adoption benchmarks at the business level are. [ABSTRACT FROM AUTHOR]

Interest in 21st century skills has brought concomitant interest in ways to teach and measure them. Games hold promise in these areas, but much of their potential has yet to be proven, and there are few examples of how to use the rich data from games to make inferences about players' knowledge, skills, and attributes. This article builds an evidence model for the assessment of persistence from Poptropica, a popular commercial game for children. Task persistence is an important skill related to successful school and work outcomes, particularly given new, complex tasks requiring sustained application of effort. Evidence extracted from log files of the game was used to identify players with a particular goal and then create a measure of persistence toward that goal. The results support the ability to create an assessment argument for a game-based measure of persistence. [ABSTRACT FROM AUTHOR]

Copyright of Revista Pretexto is the property of Revista Pretexto and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The conceptual and methodological framework for measurement equivalence procedures has been well established and widely used. Although multilevel theories and methods have been widely used in organizational research, there is no comparable framework for measurement equivalence of multilevel constructs, or psychometric isomorphism. In this article, we present a conceptual and methodological framework for understanding and testing various forms of isomorphism. Within this framework, we explicate (a) the different types of psychometric isomorphism, (b) the conditions where psychometric isomorphism is appropriate and necessary, (c) how psychometric isomorphism corresponds with different composition models and estimation methods, and (d) the analytic procedures that can be used. Using simulated data, we also illustrate how the proposed procedures may be applied via two analytic methods—item response theory and factor analysis. We conclude with a discussion of theoretical and methodological implications provided by the proposed framework of psychometric isomorphism. [ABSTRACT FROM AUTHOR]

Cet article vise à dresser un bilan des études ayant porté sur les modèles de mesure ou sur un aspect particulier de ces derniers au cours des trente der nières années. Pour ce faire, nous avons réalisé une recension des écrits à partir de quatorze revues internationales traitant, notamment, des modèles de mesure en éducation. Après avoir effectué une synthèse des résultats qui ressortent de notre analyse des articles sélectionnés, nous présentons des développements et des défis majeurs qui s’imposent encore aujourd’hui à ceux et celles qui travaillent à l’élaboration, au raffinement et à l’utilisation des modèles de réponse aux items. Enfin, dans un dernier temps, nous proposons un certain nombre d’avenues de recherche pour les années à venir.

Research concerning the relationship between female status and demographic behaviour has largely concluded that community level influences are most important, while status and autonomy at the individual level are far less so. This consensus, however, rests on an untested a priori typology of women’s status and tenuous assumptions about the measurement of defined status dimensions on the individual level. To better understand the potential influences of both community and individual elements it is necessary to take a step back and assess the validity of the constructs of autonomy used. This work uses a latent variable measurement modelling framework to test both the dimensionality of women’s status and the appropriateness of using simple additive index scaling in constructing measures of women’s status on the individual level using questions from the Demographic and Health Surveys status-of-women module in India for 1998/1999. [ABSTRACT FROM AUTHOR]

The current article notes that the standard application of relative importance analyses is not appropriate when examining the relative importance of interactive or other higher order effects (e.g., quadratic, cubic). Although there is a growing demand for strategies that could be used to decompose the predicted variance in regression models containing such effects, there has been no formal, systematic discussion of whether it is appropriate to use relative importance statistics in such decompositions, and if it is appropriate, how to go about doing so. The purpose of this article is to address this gap in the literature by describing three different yet related strategies for decomposing variance in higher-order multiple regression models—hierarchical F tests (a between-sets test), constrained relative importance analysis (a within-sets test), and residualized relative importance analysis (a between- and within-sets test). Using a previously published data set, we illustrate the different types of inferences these three strategies permit researchers to draw. We conclude with recommendations for researchers seeking to decompose the predicted variance in regression models testing higher order effects. [ABSTRACT FROM AUTHOR]

The Edinburgh Handedness Inventory was administered to 1224 high school students (605 males and 619 females). Confirmatory factor analysis was used to re-examine its psychometric properties. The results showed that this instrument has poor measurement properties. Removal of a few problematic items improved internal consistency of the questionnaire and improved its validity. The results also suggest that the impact of modification did not affect classification of individuals into left- and right-handedness categories but did influence classification of mixed-handers with the original version classifying significantly more individuals into mixed-handedness category than the modified version. [ABSTRACT FROM AUTHOR]

This paper proposes a measurement modelfor evaluating e-government service quality, and generates quality indicators to assist practitioners in identifying the strong and weak points of service delivery. The statistical sample is based on questionnaires of citizens' preferences for the evaluation of an ideal e-government site. To accurately evaluate the influence of criteria and sub-criteria on service quality the model applies the Analytic Hierarchy Process (AHP) a multi-criteria decision-making method. Finally, the authors apply their model to the evaluation of the six most popular Greek e-government sites. To test the possible existence of interrelationships among criteria, they also apply the Analytic Network Process (ANP) method and compare the results of the two methods. The results show that 'Reliability `is the most important quality criterion, with 'Citizen Support', 'Trust', and 'Efficiency 'following in importance. Furthermore, the case study revealed no interrelations between evaluation criteria of the model. [ABSTRACT FROM AUTHOR]

We adopt a construct validity lens to provide a critical reexamination of established corporate governance research. In particular, we focus on the body of work relying on the theoretical bases of agency theory and involving boards of directors’ independence, CEO duality, equity holdings, and their relationships to corporate financial performance. We offer a five-step protocol involving the following components: (1) establishing the base rate for the phenomenon in question, (2) evaluating the extent to which the dependent variables are germane, (3) evaluating the extent to which the independent variables are germane, (4) determining whether explanatory power is improved as a consequence of improved measurement, and (5) concluding whether previously established estimates should be revised. We implemented the proposed protocol and used alternative measures that reduce threats to construct validity. Results yielded substantially higher estimates of relationships in corporate governance research. Future research can adopt the proposed protocol to understand whether a similar improvement in explanatory power could be achieved in other research domains. [ABSTRACT FROM AUTHOR]

Organizational performance is a fundamental construct in strategic management. Recently, researchers proposed a framework for organizational performance that includes three dimensions: accounting returns, growth, and stock market performance. We test the construct validity of indicators of these dimensions by examining reliability, convergent validity, discriminant validity, and nomological validity. We conduct a confirmatory factor analysis with 19 analytically derived indicators on a sample of 37,262 firm-years for 4,868 listed U.S. organizations from 1990 to 2010. Our results provide evidence of four, rather than three, organizational performance dimensions. Stock market performance and growth are confirmed as separate dimensions, whereas accounting returns must be decomposed into profitability and liquidity dimensions. Robustness analyses indicate stability of our inferences for three dissimilar industries and for a period of 21 years but reveal that organizational performance dimensions underlie dynamics during years in which environmental instability is high. Our study provides an initial contribution to the clarification of the important organizational performance construct by defining four dimensions and validating indicators for each dimension. Thus, we provide essential groundwork for the measurement of organizational performance in future empirical studies. [ABSTRACT FROM AUTHOR]

The carrier and code phases tracking is the central work of Global Position System (GPS) receivers. A number of algorithms have been developed to improve the performance of the receivers in tracking the carrier and code phase in challenging environments, such as the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). This paper uses GPS software receiver to implement the algorithms, provides details about the implementation, deeply compares the two different methods and takes into consideration different numbers of measurements. To evaluate the performance effectively, some criterions to compare these two algorithms are proposed. The results show although both algorithms have satisfying performance in tracking weak signals, the UKF exceeds in some aspects. The results also indicate that algorithms with more measurements in the measurement model could track the signals more accurately, but the outperformance becomes less obvious when the number of measurements surpasses certain threshold. [ABSTRACT FROM AUTHOR]

This article presents a replication and extension study of the relationship between scenario planning and perceptions of conversation quality and engagement. The key contribution of this article is that it addresses a major limitation of the previous study - a small sample size. This article begins with descriptions of scenario planning, conversation quality, and dialogue which establish a foundation for scenario planning and theoretical framework for measuring the effects of scenario planning on perceptions of conversation quality and engagement. Data from participant perceptions of strategic conversations skills were collected pre-and post-scenario planning project, and were subsequently compared using paired samples t-test for data analysis. For testing the construct validities of the proposed measurement models, confirmatory factor analysis (CFA) was also conducted. This study suggests strong evidence of construct validity for the scale measuring conversation quality and engagement and further demonstrates that scenario planning is associated with significant increases in self-reported personal and interpersonal conversation and engagement skills, with moderate and strong effect sizes respectively. [ABSTRACT FROM AUTHOR]

Copyright of Ekonomski Vjesnik is the property of Ekonomski Vjesnik and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Quantitative researchers distinguish between causal and effect indicators. What are the analytic problems when both types of measures are present in a quantitative reasoned action analysis? To answer this question, the authors use data from a longitudinal study to estimate the association between two constructs central to reasoned action theory: behavioral beliefs and attitudes toward the behavior. The belief items are causal indicators that define a latent variable index while the attitude items are effect indicators that reflect the operation of a latent variable scale. The authors identify the issues when effect and causal indicators are present in a single analysis and conclude that both types of indicators can be incorporated into analyses of data based on the reasoned action approach. [ABSTRACT FROM PUBLISHER]

This paper highlights theoretical and mathematical differences between formative and reflective measurement models, in the context of academic SEM oriented research in Operations and Manufacturing Management, an area of significant current interest. It discusses problems associated with measurement model misspecification. It further illustrates, using survey data, the effects of possible misspecification on model fit parameters and path coefficients in a nomological model, using the Partial Least Squares (PLS) approach. It then proposes guidelines for the use of the PLS methodology for analyzing formative measurement models. [ABSTRACT FROM AUTHOR]

A complete ultrasonic measurement model is obtained for contact testing, where all the electrical, electromechanical, and acoustic/elastic elements are explicitly described. Reciprocity principles are used to model those acoustic/elastic elements that cannot be measured directly in terms of an integral of the incident and scattered wave fields over the surface of the flaw. This general measurement model for contact testing is then reduced to new, highly modular forms that are applicable to contact tests involving bulk, surface, and plate waves. These modular forms are similar in structure to the measurement model previously developed by Thompson and Gray [7] for immersion bulk wave inspections. [ABSTRACT FROM AUTHOR]

Abstract: Despite the popularity of the NEO-PI-R as a measure of the five-factor model (FFM), several questions regarding its psychometric foundation have yet to be investigated. Using NEO-PI-R data obtained in a US community sample, confirmatory factor analyses demonstrated that most of the single-factor models of individual facets and domains evidenced acceptable fit. However, one-factor models of the domains Extraversion and Agreeableness were not supported, which calls into question their adequacy as measurement models. Analyses of variants of the FFM revealed that only the unrestricted exploratory factor model showed acceptable fit as well as replicability across gender and educational level. [Copyright &y& Elsevier]

Interest in on-demand noncognitive assessment has flourished due to advances in computer technology and studies demonstrating noteworthy predictive validities for organizational outcomes. Computerized adaptive testing (CAT) based on the Zinnes-Griggs (ZG) ideal point item response theory (IRT) model may hold promise for organizational settings, because a large pool of items can be created from a modest number of stimuli, and the items have been shown to be resistant to some types of rater bias. However, sample sizes needed for marginal maximum likelihood (MML) estimation of statement parameters are quite large and could thus limit usefulness in practice. This article addresses that concern and its ramifications for CAT. Specifically, we conducted empirical and simulation studies to examine whether subject matter expert (SME) ratings of statement extremity (location) can be substituted for MML estimates to streamline test development and launch. Results showed that error in SME-based location estimates had little detrimental effect on score accuracy or validity, regardless of whether measures were constructed adaptively or nonadaptively. Implications for research involving small samples and CAT in field settings are discussed. [ABSTRACT FROM AUTHOR]

In management research, there is a growing trend toward formative measurement, in which measures are treated as causes of constructs. Formative measurement can be contrasted with reflective measurement, in which constructs are specified as causes of measures. Although recent work seems to suggest that formative measurement is a viable alternative to reflective measurement, the emerging enthusiasm for formative measurement is based on conceptions of constructs, measures, and causality that are difficult to defend. This article critically compares reflective and formative measurement on the basis of dimensionality, internal consistency, identification, measurement error, construct validity, and causality. This comparison leads to the conclusion that the presumed viability of formative measurement is a fallacy, and the objectives of formative measurement can be achieved using alternative models with reflective measures. [ABSTRACT FROM AUTHOR]

The article discusses research which described a penalized latent class regression aimed at allowing additional scientific information to affect the estimation of the measurement model while keeping the standard assumption of non-differential measurement. In the simulation studies, ridge and LASSO penalty functions were found to improve the precision of estimates. It is concluded that this approach may be useful in large numbers of collinear covariates or in cases where latent class model assumptions are violated.

The current study examined the Type I error rates and power of several item response theory (IRT) item fit indices used in conjunction with the graded response model (GRM). Specifically, S — χ2, χ2*, and adjusted χ 2 degrees of freedom ratios (χ2/dfs) were examined. Model misfit was introduced by manipulating item parameters and by using a different IRT model to generate item data. Results indicated lower than expected Type I error rates for S — χ2 and χ 2*. Adjusted χ2/dfs resulted in large Type I error rates when used with cross validation and very low Type I error rates when used without cross validation. χ2* and adjusted χ 2/dfs without cross validation were the most powerful overall. [ABSTRACT FROM AUTHOR]

When writing items for survey measures, common advice dictates that one should avoid using extreme words like ''always.'' However, the systematic study of extreme wording effects is rare. The current study applies confirmatory factor analysis (CFA) and item response theory (IRT) methods to assess the effects of extreme item wording (i.e., the word ''always'') on item-level, response option-level, and scale- (or test) level invariance. The authors hypothesized that including the word ''always'' in an item stem would affect responses such that individuals would be less likely to strongly agree with these items. To test this hypothesis, six items with extreme wording from the Wong and Law Emotional Intelligence Scale (WLEIS) were compared with more moderately worded versions of the same items. Although an effect was found for item wording, the magnitude of nonequivalence was small and is unlikely to have a strong influence on scale-level measurement outcomes. Implications for evaluating survey psychometric properties are discussed. [ABSTRACT FROM AUTHOR]

Organizational creativity research has a curious misalignment between construct definitions and measurement model specifications—definitions embrace multiple facets, but empirical measures do not. The purpose of this study was to examine potential measurement model misspecification in organizational creativity research. We compare whether creativity is best assessed as a unidimensional common latent construct model with reflective indicators or as a multi-dimensional composite latent construct model with formative indicators. To assess potential measurement model misspecification, two studies were conducted in organizational and professional settings. For Study One, MBA students ( n = 152) evaluated stimuli from entrepreneurship and advertising. For study, two professional artists ( n = 167) evaluated art domain stimuli. CFA results suggest composite latent construct models with two factors (novelty and usefulness) represent creativity assessments in entrepreneurship, advertising, and art better than one- and three-factor models. Results suggest that failure to acknowledge inconsistencies between construct definitions and measurement models may put researchers at risk of reporting findings with limited statistical conclusion validity. Further, improved theories and empirical models should include facets of creativity. Broader implications of measurement model misspecification for organizational science research are also discussed. This is one of the first studies to examine the potential measurement model misspecification in organizational creativity research. We examined this potential using data from three domains and across two domain-specific samples. The results were robust across all samples and settings and suggest concern with respect to current methods used for measuring organizational creativity. [ABSTRACT FROM AUTHOR]

Common method variance is routinely viewed as a pervasive problem in organizational research, one that undermines good science and biases empirical conclusions. The authors review research that has used multitrait-multimethod (MTMM) designs to estimate the magnitude of common method variance in organizational research. The results of this study show that method variance accounts for less variance (18%) than has been suggested by previous reviews. The authors also consider simultaneously the attenuating effect of measurement error with the inflationary effect of common method variance on observed relationships. Results indicate that although common method variance does have an inflationary effect on observed relationships, this effect is almost completely offset by the attenuating effect of measurement error. [ABSTRACT FROM AUTHOR]

The use of formative measurement in the field of Information Systems has increased, arguably due to statistical tools (e.g., PLS) that can test such models. However, in the literature, there exist two contradictory views on the potential deficiency of formative measurement. While opponents who are critical of formative measurement argue that there are native weaknesses of the formative approach in model estimation, proponents who are in favor of using formative measurement counter that opponents' research methods in measurement model specification are flawed. The goal of this work is to empirically test these opposing views on whether the alleged estimation instability of formative measurement is due to measurement model misspecification or simply the shortcoming of formative measurement. To assess the integrity of arguments of both parties, we adopt a research design in which four different cases are tested in terms of interpretational confounding and external consistency. We find that regardless of whether there is a specification issue, formative measures can lead to misleading outcomes. Based on the results, we offer guidelines that researchers may adopt in planning and executing data analysis with structural equation modeling. Given that the use of formative measurement is at a critical juncture in the IS field, we believe that the guidelines in this research note are important to promote appropriate use of the approach rather than relegate it to a bandwagon effect. [ABSTRACT FROM AUTHOR]

The aim of this study was to analyze conventional wisdom regarding the construction and analysis of oral health-related quality of life (OHRQoL) questionnaires and to outline statistical complications. Most methods used for developing and analyzing questionnaires, such as factor analysis and Cronbach’s alpha, presume psychological constructs to be latent, inferring a reflective measurement model with the underlying assumption of local independence. Local independence implies that the latent variable explains why the variables observed are related. Many OHRQoL questionnaires are analyzed as if they were based on a reflective measurement model; local independence is thus assumed. This assumption requires these questionnaires to consist solely of items that reflect, instead of determine, OHRQoL. The tenability of this assumption is the main topic of the present study. It is argued that OHRQoL questionnaires are a mix of both a formative measurement model and a reflective measurement model, thus violating the assumption of local independence. The implications are discussed. [ABSTRACT FROM AUTHOR]