Extant research within competitive dynamics recognizes a positive relationship between high levels of competitive activity and firm performance, but the cognitive and psychological antecedents to competitive activity are far less clearly understood. I explore the role of a specific psychological antecedent - status, in impacting firms’ motivations to launch competitive moves against rivals. The key question, which extant literature does not seem fully equipped to answer, is when and under exactly what circumstances lower-status firms become motivated to launch action against higher-status ones and vice-versa. I use the stimulus-response model in social cognition to build theory which helps to answer the question by considering structural properties of market engagement. The specific structural property of market engagement that I focus on is market commonality, or the extent to which a rival is a significant player in markets important to a focal firm. I predict that a rival’s market commonality with a focal firm and its status relative to the focal firm have independent and positive effects on the extent to which the focal firm pays attention to the rival, that a rival’s market commonality with a focal firm and its status relative to the focal firm interact negatively to predict the focal firm’s motivation to launch action against that rival, and that a rival’s relative status and market commonality with a focal firm interact positively to predict the extent to which the focal firm pays attention to the rival. I test theory through a field study on gourmet food trucks in Lexington and an experiment through Amazon’s Mechanical Turk tool. Results provide broad support for the hypotheses. Three consequences follow from my study – that high-status firms are likely to come under attack from lower-status firms with whom they do not compete in markets, that they are unlikely to be paying attention to those lower-status firms when first attacked, and that they are likely to become aware of and motivated to act against those lower-status firms only after the lower-status firms have occupied key markets. My study contributes to the literatures in competitive dynamics, status, multi-market contact, and entrepreneurial action.

The purpose of this study was to develop a questionnaire to measure academic self-efficacy for undergraduates. The theoretical framework of the questionnaire was based on Bandura¡¦s self-efficacy theory. A total of 409 participants were selected by judgment sampling from the first- and second-grade undergraduate of six colleges in national Sun Yat-sen university (Liberal Arts, Science, Engineering, Management, Marine Sciences, and Social Sciences). The newly developed Academic Efficacy and Motivation Questionnaire (AEMQ) was modified and derived from eight related scales. Expert content validity was conducted by three experts in the field, and the data were analyzed by rating scale model (RSM) in ConQuest. The findings were as follows: 1. All the 69 items in AEMQ have good fit values (MNSQ between 0.6 and 1.4). 2. The items of the AEMQ tended to be too easy for participants. 3. The reliability of each dimension of AEMQ was poor. The highest reliability value was 0.575, and the lowest was 0.382. 4. The first dimension ¡§actual performance¡¨ and the second dimension ¡§vicarious experience¡¨ have negative correlation with the forth dimension ¡§psychological index¡¨. The result was consistent with past studies.

The current study contributes to the already substantial scholarly literature on telecommuting by estimating a joint model of three dimensions- option, choice and frequency of telecommuting. In doing so, we focus on workers who are not self-employed workers and who have a primary work place that is outside their homes. The unique methodological features of this study include the use of a general and flexible generalized hurdle count model to analyze the precise count of telecommuting days per month, and the formulation and estimation of a model system that embeds the count model within a larger multivariate choice framework. The unique substantive aspects of this study include the consideration of the "option to telecommute" dimension and the consideration of a host of residential neighborhood built environment variables. The 2009 NHTS data is used for the analysis, and allows us to develop a current perspective of the process driving telecommuting decisions. This data set is supplemented with a built environment data base to capture the effects of demographic, work-related, and built environment measures on the telecommuting-related dimensions. In addition to providing important insights for policy analysis, the results in this study indicate that ignoring the "option" dimension of telecommuting can, and generally will, lead to incorrect conclusions regarding the behavioral processes governing telecommuting decisions. The empirical results have implications for transportation planning analysis as well as for the worker recruitment/retention and productivity literature. / text

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FundaÃÃo de Amparo à Pesquisa do Estado do Cearà / Com o objetivo de avaliar o grau de maturidade, quanto à utilizaÃÃo de ferramentas e tÃcnicas da GestÃo pela Qualidade Total (GQT), e sua evoluÃÃo nos Ãltimos 10 anos, nas empresas de transformaÃÃo e construÃÃo civil de portes mÃdio e grande no Estado do CearÃ, o presente trabalho utilizou o Modelo de Resposta Gradual da Teoria da Resposta ao Item (TRI). Este modelo foi projetado para analisar respostas graduadas e passÃveis de ordenaÃÃo. Como base de comparaÃÃo para verificar uma possÃvel evoluÃÃo na maturidade, foi utilizado o trabalho realizado por Alexandre (1999). A metodologia empregada para a coleta de dados foi a pesquisa quantitativa, atravÃs de um questionÃrio estruturado na escala de Likert com 5 categorias de resposta. O estudo utilizou o modelo de Resposta Gradual da TRI para avaliaÃÃo da maturidade criando-se uma escala de medida padronizada, atravÃs do qual se tornou possÃvel a comparaÃÃo e a verificaÃÃo de que houve uma evoluÃÃo pouco significativa da maturidade das empresas, principalmente levando-se em conta a importÃncia da qualidade como diferencial competitivo para a manutenÃÃo das empresas no mercado globalizado. A escala construÃda pode auxiliar na identificaÃÃo de prÃticas nÃo implantadas que poderiam melhorar a qualidade dos produtos. / Aiming to evaluate the degree of maturity in the use of tools and techniques of Total Quality Management (TQM), and its evolution over the past 10 years, in the companies of transformation and construction of medium and large scale in the State of Ceara, this study used the Graded Response Model of Item Response Theory (IRT). This model was designed to examine responses graded and capable of ordinate. As a basis of comparison for possible evaluates in the maturity, it was used the work done by Alexander in 1999. The methodology used for collecting data was the quantitative survey, using a structured questionnaire in Likert scale with five response categories. The study used a model for assessment of maturity by creating a standardized measurement scale with the support of the IRT, whereby it became possible to compare and to check that there was a low evolution of maturity of organizations, especially taking into account the importance of quality as a competitive differential for maintenance companies in the global market. The scale constructed may serve as a basis to enable companies to identify potential practice has not implanted, allows, still monitoring their development level of maturity.

The present study examined the structural construct validity of the LoTi Digital-Age Survey, a measure of teacher instructional practices with technology in the classroom. Teacher responses (N = 2840) from across the United States were used to assess factor structure of the instrument using both exploratory and confirmatory analyses. Parallel analysis suggests retaining a five-factor solution compared to the MAP test that suggests retaining a three-factor solution. Both analyses (EFA and CFA) indicate that changes need to be made to the current factor structure of the survey. The last two factors were composed of items that did not cover or accurately measure the content of the latent trait. Problematic items, such as items with crossloadings, were discussed. Suggestions were provided to improve the factor structure, items, and scale of the survey.

The primary goal of this study was to develop a new procedure for estimating decision consistency and accuracy indices using the bifactor and testlet response theory (TRT) models. This study is the first to investigate decision consistency and accuracy from a multidimensional perspective, and the results have shown that the bifactor model at least behaved in way that met the author's expectations and represents a potential useful procedure. The TRT model, on the other hand, did not meet the author's expectations and generally showed poor model performance. The multidimensional decision consistency and accuracy indices proposed in this study appear to provide good performance, at least for the bifactor model, in the case of a substantial testlet effect. For practitioners examining a test containing testlets for decision consistency and accuracy, a recommended first step is to check for dimensionality. If the testlets show a significant degree of multidimensionality, then the usage of the multidimensional indices proposed can be recommended as the simulation study showed an improved level of performance over unidimensional IRT models. However, if there is a not a significant degree of multidimensionality then the unidimensional IRT models and indices would perform as well, or even better, than the multidimensional models. Another goal of this study was to compare methods for numerical integration used in the calculation of decision consistency and accuracy indices. This study investigated a new method (M method) that sampled ability estimates through a Monte-Carlo approach. In summary, the M method seems to be just as accurate as the other commonly used methods for numerical integration. However, it has some practical advantages over the D and P methods. As previously mentioned, it is not as nearly as computationally intensive as the D method. Also, the P method requires large sample sizes. In addition, the P method has conceptual disadvantage in that the conditioning variable, in theory, should be the true theta, not an estimated theta. The M method avoids both of these issues and seems to provide equally accurate estimates of decision consistency and accuracy indices, which makes it a strong option particularly in multidimensional cases.

Bifactor Item Response Theory (IRT) models are presented as a plausible structure for psychological measures with a primary scale and two or more subscales. A bifactor graded response model, appropriate for polytomous categorical data, was fit to two university counseling center datasets (N=4,679 and N=4,500) of Outcome-Questionnaire-45.2 (OQ) psychotherapy intake data. The bifactor model showed superior fit compared to a unidimensional IRT model. IRT item parameters derived from the bifactor model show that items discriminate well on the primary scale. Items on the OQ's subscales maintain some discrimination ability over and above the primary scale. However, reliability estimates for the subscales, controlling for the primary scale, suggest that clinical use should likely proceed with caution. Item difficulty or severity parameters reflected item content well, in that increased probability of endorsement was found at high levels of distress for items tapping severe symptomatology. Increased probability of endorsement was found at lower levels of distress for items tapping milder symptomatology. Analysis of measurement invariance showed that item parameters hold equally across gender for most OQ items. A subset of items was found to have item parameters non-invariant across gender. Implications for research and practice are discussed, and directions for future work given.

On paper and pencil multiple choice tests, the potential for examinees to mark their answers in incorrect locations presents a serious threat to the validity of test score interpretations. When an examinee skips one or more items (i.e., answers out of sequence) but fails to accurately reflect the size of that skip on their answer sheet, that can trigger a string of misaligned responses called shift errors. Shift errors can result in correct answers being marked as incorrect, leading to possible underestimation of an examinee's true ability. Despite movement toward computerized testing in recent years, paper and pencil multiple choice tests are still pervasive in many high stakes assessment settings, including K 12 testing (e.g., MCAS) and college entrance exams (e.g., SAT), leaving a continuing need to address issues that arise within this format. Techniques for detecting aberrant response patterns are well established but do little to recognize reasons for the aberrance, limiting options for addressing the misfitting patterns. While some work has been done to detect and address specific forms of aberrant response behavior, little has been done in the area of shift error detection, leaving great room for improvement in addressing this source of aberrance. The opportunity to accurately detect construct irrelevant errors and either adjust scores to more accurately reflect examinee ability or flag examinees with inaccurate scores for removal from the dataset and retesting would improve the validity of important decisions based on test scores, and could positively impact model fit by allowing for more accurate item parameter and ability estimation. The purpose of this study is to investigate new algorithms for shift error detection that employ IRT models for probabilistic determination as to whether misfitting patterns are likely to be shift errors. The study examines a matrix of detection algorithms, probabilistic models, and person parameter methods, testing combinations of these factors for their selectivity (i.e., true positives vs. false positives), sensitivity (i.e., true shift errors detected vs. undetected), and robustness to parameter bias, all under a carefully manipulated, multifaceted simulation environment. This investigation attempts to provide answers to the following questions, applicable across detection methods, bias reduction procedures, shift conditions, and ability levels, but stated generally as: 1) How sensitively and selectively can an IRT based probabilistic model detect shift error across the full range of probabilities under specific conditions?, 2) How robust is each detection method to the parameter bias introduced by shift error?, 3) How well does the detection method detect shift errors compared to other, more general, indices of person fit?, 4) What is the impact on bias of making proposed corrections to detected shift errors?, and 4) To what extent does shift error, as detected by the method, occur within an empirical data set? Results show that the proposed methods can indeed detect shift errors at reasonably high detection rates with only a minimal number of false positives, that detection improves when detecting longer shift errors, and that examinee ability is a huge determinant factor in the effectiveness of the shift error detection techniques. Though some detection ability is lost to person parameter bias, when detecting all but the shortest shift errors, this loss is minimal. Application to empirical data also proved effective, though some discrepancies in projected total counts suggest that refinements in the technique are required. Use of a person fit statistic to detect examinees with shift errors was shown to be completely ineffective, underscoring the value of shift error specific detection methods.

This study examined the psychometric properties of the Trauma Inventory for Partners of Sex Addicts (TIPSA). Using the Nominal Response Model (NRM), I examined several aspects of item and option functioning including discrimination, empirical category ordering, and information. Category Boundary Discrimination (CBD) parameters were calculated to determine the extent to which respondents distinguished between adjacent categories. Indistinguishable categories were collapsed through recoding. Empirically disordered response categories were also collapsed through recoding. Findings revealed that recoding solved some technical functioning issues in some items, and also revealed items (and perhaps option anchors) that were probably poorly conceived initially. In addition, nuisance or error variance was reduced only marginally by recoding, and the relative standing of respondents on the trait continuum remained largely unchanged. Items in need of modification or removal were identified, and issues of content validity were discussed.