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The present chapter addresses a topic that is of growing interest – namely, the exploration of alternative item response theory (IRT) models for noncognitive assessment. Previous research in the assessment of trait emotional intelligence (or “trait emotional self-efficacy”) has been limited to traditional psychometric techniques (e.g., classical test theory) under the notion of a dominance response processes describing the relationship between individuals' latent characteristics and individuals' response selection. The present study, presents the first unfolding IRT modeling effort in the general field of emotional intelligence (EI). We applied the Generalized Graded Unfolding Model (GGUM) in order to evaluate the response process and the item properties on the short form of the trait emotional intelligence questionnaire (TEIQue-SF). A sample of 866 participants completed the English version of the TEIQue-SF. Results suggests that the GGUM has an adequate fit to the data. Furthermore, inspection of the test information and standard error functions revealed that the TEIQue-SF is accurate for low and middle scores on the construct; however several items had low discrimination parameters. Implications for the benefits of unfolding models in the assessment of trait EI are discussed.

Purpose – The purpose is to present item response theory (IRT) as a promising approach to deal with theoretical and methodological challenges which may not be adequately addressed with linear factor analysis (LFA) techniques.

Approach – We address this limitations and present IRT's approach to counteracting these difficulties. We further present two IRT models in greater detail and make a theoretical comparison between these models and LFA techniques. Then, we illustrate how IRT is applied in practice by analyzing a scale of trust by an IRT and an LFA approach and comparing their results.

Practical implications – Scale properties may vary among countries because some items may function differently in different contexts. Moreover, a scale's reliability depends on the value of the latent variable being assessed, which implies that the scale may discriminate better among certain ranges of the latent trait than among others. The theory we hereby present offers a more adequate approach to dealing with these issues than extant LFA methods.

Originality/value – This chapter presents a methodology of recognized value in other fields of knowledge into the field of strategy and international business, thereby advancing the methodologies available for doing research in these domains.

This study aims to investigate the behavioural biases influencing the real estate market investing decisions of normal non-professional investors in India.

As the study involves the behavioural data with polytomous response format, psychometric test- graded response model (IRT approach) was used for the study with the help of STATA 14. Multi-stage stratified sampling was used to collect a sample of 560 respondents. The study used a 14-item scale representing behavioural biases derived from two broad behavioural theories, i.e. heuristics and prospect theories. Sample characteristics were checked using SPSS 20. Pre-required assumptions for IRT (i.e. local independence and unidimensionality) were tested by CFA using AMOS 20.

Five items, four of which belong to heuristics (anchoring – 2, representativeness – 1 and availability bias – 1) and one belong to prospect theory (regret aversion) are sufficient to measure the behavioural attitude of real estate investors in the Indian scenario. Item discrimination ai ranged from 0.95 to 1.52 (average value 1.29), showing moderate discrimination power of the items. The items have done a pretty good job of assessing the lower level of agreement. For the higher level of agreement, the scale came out to be less precise, with less information and higher standard error of measurement.

As the behavioural biases are often false, the study suggests the investors not to repeat these nasty biases to improve investment strategies. As they are shared and not easily changeable, understanding these biases may also help them in beating the market by acting as “noise traders”.

The traditional price index is incomplete in some essential respects. The inclusion of these behavioural biases into the construction of price index will greatly improve the traditional price index, policymakers should seriously think about it.

Shelter is one of the basic needs; a dwelling unit is needed for one to stay in, develop and contribute to economy and society. If investors try to minimise these biases and policymakers keep a track of these while making strategies, mispricing in this sector can be controlled to some extent, which will ultimately help in the well-being of society.

This study contributes to the limited research by investigating the behavioural biases influencing the real estate market investment decisions of normal non-professional investors. It contributes to the lacking academe on real estate market in India. The study has used a psychometric test, i.e. the item response theory, for evaluating the quality of the items.

This study aimed to develop a psychometrically reliable job satisfaction (JS) measure for university employees, guiding administrative decisions and monitoring satisfaction over time in public universities.

A JS survey developed by a Brazilian federal university’s sustainability committee containing 58 items across physical, cognitive and organizational domains was longitudinally tested with 1,214 responses collected. The data were analyzed using Item Response Theory (IRT) analysis, employing the Graded Response Model, with tools such as frequency analysis, item characteristic curve, and full-information factor analysis in RStudio. The scale’s criterion validity was also established via expert qualitative interpretation.

The instrument’s internal consistency was confirmed as the results demonstrated its high reliability with a marginal reliability coefficient of 0.95. Significant findings revealed that recognition and supervisor relationships were key discriminators of JS and that workers began to perceive satisfaction when basic environmental conditions were met.

It is important to mention that the application of this scale is specifically limited to higher education institutions and may not be directly applicable to other educational settings or industry sectors without modifications.

Although numerous measures and scales have been developed to assess JS, one elaborated by using IRT in a public university environment was lacking. Due to shifting dynamics in the workplace, traditional measurement of JS has proven inadequate, necessitating a more precise, accessible and updated tool. The developed scale allows precisely targeted interventions to improve JS and can be reapplied to evaluate their effectiveness. This research thus contributes a valuable tool for academic organizational psychology, enhancing the understanding of the measurement of JS.

The purpose of this chapter is to provide researchers a summary of some of the latest developments in item response theory (IRT), and to help these groups realize that psychometric tools can now be used for theory testing in addition to the traditional role of improving construct measurement. The author first reviews some of the fundamental tenets of classical test theory to contrast with IRT. He then describes recent advances in goodness-of-fit tests that have helped turn IRT into a model-testing tool. Finally, the author reviews several new test models that provide new flexibilities, summarizing summarize several examples of research that has used these new models in organizational research. At the end of this review, the author provides suggestions to help researchers better use these new IRT tools. Although there have been significant advances in IRT in the past decade, there has not been a systematic review of these developments. This review places those developments in context to provide readers a real appreciation of these breakthroughs.

For the past two and half decades, there has been a marked shift in the corporate governance regulations around the world. The change is more remarkable in developing countries where countries with little or no corporate governance regime have adopted “world class” standards. While there can be a debate on whether law in books actually translates into law in action, in the meantime it might be interesting to analyse the law in books to understand how the corporate governance regime has evolved in the past 20 years. This paper quantitatively tracks 21 countries, most of them being developing and emerging economies, over a period of 20 years. The period covers 1995 to 2014; thus, it traverses the pre and post crisis period in 1999 and 2008. Thus, the paper also provides a snapshot of the macrolegal changes that the countries engage in hoping to stave off the next crisis. The paper uses over 50 parameters modelled on the OECD Principles of Corporate Governance. The paper confirms the suspicion that corporate governance norms around the developing economies are converging on shareholder primacy end of the continuum. The rate of convergence was highest just before the financial crisis of 2008 and has since then slowed down.

The paper uses data collected from experts. They filled up detailed questionnaire which quizzed them on the rules relating to corporate governance norms in their country and asked them to retrospectively check their data every five years for the past 20 years. This provided an excellent overview as to how the law has evolved in the past two decades on corporate governance. The data were then tabulated using a scoring sheet and then was put together using item response theory (IRT) which is a Bayesian method similar to factor analysis. The paper then follows a comparative approach using heatmaps to analyse the evolution of corporate governance in developing countries.

Corporate governance norms around the developing economies are converging on shareholder primacy end of the continuum. The rate of convergence was highest just before the financial crisis of 2008 and has since then slowed down.

This is the first time that corporate governance panel data analysis has been carried out on top developing countries across so many parameters for such a long period. This paper also uses Bayesian IRT modelling to analyse the evolution which is novel in its approach especially in the corporate governance literature. The paper thus provides a clear view on the evolution of corporate governance norms and how they are converging on a particular ideology.

The multidimensional structure of boredom poses unique measurement challenges related to scale length and statistical modeling. We systematically address these concerns in two studies. In Study 1, we use item response theory to shorten the 29-item Multidimensional State Boredom Scale (MSBS) (Fahlman et al., 2013). In Study 2, we use structural equation modeling to compare two theoretically consistent multidimensional structures of boredom (superordinate and multivariate) with the most commonly used, yet theoretically inconsistent, structure in boredom research (unidimensional parallel model). Our findings provide support for modeling boredom as multidimensional and demonstrate the impact of model selection on effect sizes and significance.

The purpose of this study was to measure the bias on a binary option's effect estimate that appeared in the types of questions asked and in the placement changes of public service users.

The author designed Monte Carlo simulations with the analytical strategy of latent trait theory leveraging a probability of care-placement change. The author used difference-in-difference (DID) method to estimate the effects of care settings.

The author explained the extent of discrepancy between the estimates and the true values of care service effects in changes across time. The time trend of in-home care for the combined effect of in-home care, general maturity, and other environmental factors was estimated in a biased manner, while the bias for the estimate of the incremental effect for foster care could be negligible.

This study was designed based on individual child-unit only. Therefore, higher-level units, such as care setting or cluster, county, and state, should be considered for the simulation model.

This study contributed to illuminating an overlooked facet in causal inferences that embrace disproportionate selection biases that appear in categorical data scales in public management research.

To model the nuance of a disproportionate self-selection problem, the author constructed a scenario surrounding a caseworker's judgment of care placement in the child welfare system and investigated potential bias of the caseworker's discretion. The unfolding model has not been widely used in public management research, but it can be usefully leveraged for the estimation of a decision probability.

This paper aims to present recently published resources on library instruction and information literacy, providing an introductory overview and a selected annotated bibliography of publications covering various library types, study populations and research contexts.

This paper introduces and annotates English-language periodical articles, monographs, dissertations, reports and other materials on library instruction and information literacy published in 2019.

The paper provides a brief description of all 370 sources and highlights sources that contain unique or significant scholarly contributions.

The information may be used by librarians, researchers and anyone interested as a quick and comprehensive reference to literature on library instruction and information literacy.

This study aims at developing an instrument to measure the latent trait propensity to drop out in face-to-face higher education.

Based on Tinto's student integration theory, a 27-item scale was created to measure student propensity to drop out of undergraduate programs. Item response theory was used to evaluate the psychometric analysis of the items. Furthermore, different methodologies were used to evaluate and provide evidence for content validity, response process validity, internal structure validity and criterion-related validity.

With the support of specialists in the construct, the interpretation of the scores for the use of the scale was defined in four levels of propensity: high, moderate, low and very low.

The latent trait propensity to drop out in face-to-face higher education allows the inclusion of new items and aspects in the instrument. Thus, it can be adapted to distance education.

The students' propensity to drop out score can be useful for researchers and administration units in colleges and universities in the planning of permanent institutional actions and programs to take preventive measures.

Minimize dropout in order to raise the educational level of the population and make better use of the resources invested in education.

This study points out when, why and how propensity to drop out can be measured and how scores can be interpreted in the context of the problem.