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Numerous scales have been developed and utilized in the tourism and hospitality field, yet, their psychometric properties have not been systematically reviewed and evaluated. This gap compromises researchers' ability to develop better measures and improve measurement decisions. In this current study, 56 scales were identified and evaluated in terms of their psychometric properties. It was found that most scales were imperfect in measuring tourism and hospitality domains, and most scales did not provide explicit information about the scale development procedures that were adopted. The scale development procedure and psychometric properties of the reviewed scales are summarized, evaluated, and recommendations are made for future tourism and hospitality scale development.

Organizational researchers have become increasingly interested in multi-level constructs – that is, constructs that are meaningful at multiple levels of analysis. However, despite the plethora of theoretical and empirical work on multi-level topics, explicit frameworks for validation of multi-level constructs have yet to be fully developed. Moreover, available principles for conducting construct validation assume that the construct resides at a single level of analysis. We propose a five-step framework for conceptualizing and testing multi-level constructs by integrating principles of construct validation with recent advancements in multi-level theory, research, and methodology. The utility of the framework is illustrated using theoretical and empirical examples.

Although the measurement of organizational readiness for change has been encouraged, measuring readiness for change poses a major empirical challenge. This is not because instruments designed to do this are not available. Researchers, consultants, and practitioners have published an array of instruments, suggesting that readiness can be measured from various perspectives and the concept of readiness has not been clearly defined. This paper reviews the history of the readiness concept, the perspectives used to assess readiness, and the psychometric properties of readiness instruments. Based on the review, an integrated definition of readiness is presented along with the implications of the definition for research and practice.

In this paper we discuss some key issues involved in developing, validating, and reducing multi-item scales of paper and pencil measures. Specifically, we examine the importance of content validity, dimensionality, coefficient alpha, scale length, and item redundancy with a focus on the inter-relatedness of these psychometric properties. We also examine the viability of reduced-item scales and discuss some recent trends in self-report measures of marketing and consumer behavior-related constructs.

The changing environment and competitive market forces have brought many changes in the business sector that have put organisations under immense pressure. The use of psychometric assessments and behavioural profiling help organisations to determine individuals' abilities, aptitudes, personality traits, values and factors which intrinsically motivate them and assist in bringing the right people on board who fit well within the organisational culture and can contribute towards the performance goals. Although behavioural profiling and psychometric assessments are accepted worldwide, however, developing countries particularly the public sector still relies on conventional recruitment methods and the adaptation of contemporary behavioural profiling and psychometric assessments is a challenge. Therefore, this chapter evaluates how the adaptation of behavioural profiling and psychometric assessments in the civil service exams in developing countries can improve the selection process and ultimately can help to improve the quality of public services, capacity building and achieving sustainability goals.

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.

The Keirsey Temperament Sorter (KTS) is a psychometric instrument that can be useful to researchers interested in investigating the impact of personality traits in accounting practice and education. The KTS may be used to investigate: (a) the nature of personality of accounting practitioners, faculty and students; and (b) how personality traits affect the performance of accounting practitioners, faculty and students. This paper provides KTS users with the empirical and conceptual information necessary to conduct research in these areas. The psychometric properties and underlying theory of the KTS are examined, as are its limitations. The paper also compares the KTS to the Myers-Briggs Type Indicator (MBTI), another widely used psychometric instrument. The two instruments are compared in order to determine the relative advantages of each for accounting research.

There is currently a great deal of attention in psychometric and statistical methods on ensuring measurement invariance when examining measures across time or populations. When measurement invariance is established, changes in scores over time or across groups can be attributed to changes in the construct rather than changes in reaction to or interpretation of the measurement instrument. When measurement in not invariant, it is possible that measured differences are due to the measurement instrument itself and not to the underlying phenomenon of interest. This chapter discusses the importance of establishing measurement invariance specifically in postsecondary settings, where it is anticipated that individuals' perspectives will change over time as a function of their higher education experiences. Using examples from several measures commonly used in higher education research, the concepts and processes underlying tests of measurement invariance are explained and analyses are interpreted using data from a US-based longitudinal study on bioscience PhD students. These measures include sense of belonging over time and across groups, mental well-being over time, and perceived mentorship quality over time. The chapter ends with a discussion about the implications of longitudinal and group measurement invariance as an important conceptual property for moving forward equitable, reproducible, and generalizable quantitative research in higher education. Invariance methods may further be relevant for addressing criticisms about quantitative analyses being biased toward majority populations that have been discussed by critical theorists engaging quantitative research strategies.

At least 35 years have passed since Slovic's (1987) seminal article on the ‘Perception of Risk’, wherein the conceptual foundations for understanding general risk and the psychometric properties underlying how individuals perceive risks were laid. Over the same time span, research on risk perception in the context of travel has become voluminous and recurrent. It is therefore fitting that in a modern, post-COVID age, Slovic's theory of risk perception is re-examined in the travel context, given the recent dramatic transformation of travel, the emergence of novel tourism-related risks and persistent scholarly attempts to understand travel risk theory. Using modern data mining methods and content analysis techniques, this chapter examines the stability and validity of long-standing categories and taxonomies of perceived travel risks, based on data archived in a sizeable database of scholarly studies related to travel risk (n = 17,790 studies), across an extensive 35-year period from 1990 to 2022. Findings infer two higher-order dimensions that likely underpin the taxonomic organization and relational ordering of different travel risk types and clusters. Findings also suggest a possible shift from Slovic's original theory in the way risks are perceived, at least in the travel context.