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Addresses the standardization of the measurements and the labels for concepts commonly used in the study of work organizations. As a reference handbook and research tool, seeks to improve measurement in the study of work organizations and to facilitate the teaching of introductory courses in this subject. Focuses solely on work organizations, that is, social systems in which members work for money. Defines measurement and distinguishes four levels: nominal, ordinal, interval and ratio. Selects specific measures on the basis of quality, diversity, simplicity and availability and evaluates each measure for its validity and reliability. Employs a set of 38 concepts ‐ ranging from “absenteeism” to “turnover” as the handbook’s frame of reference. Concludes by reviewing organizational measurement over the past 30 years and recommending future measurement reseach.

The purpose of this study is to evaluate the psychometric properties of each item in the Sport Spectator Identification Scale (SSIS) (Wann and Branscombe, 1993) using the item response theory (IRT) and to provide evidence for modifications in the scale.

A total of 635 spectators of US professional sports responded to the seven-item SSIS on an eight-point semantic differential scale. The general partial credit model was fitted to the data.

The results revealed that four items (Items 1, 2, 3 and 5) provide a relatively high amount of information, whereas three items (Items 4, 6 and 7) provide a low amount of information, indicating different levels of measurement precision among the items. Furthermore, the results showed that some low-level response options were rarely selected by participants, indicating that it may not be necessary to include response options as many as eight within each item.

Unlike previous studies examining the psychometric properties of the SSIS as a whole, the present study provides information about the usefulness of each item of the SSIS in measuring individuals' team identification. Based on the findings, the authors identified some issues with the three problematic items, including the wording of the items and the link between the question and the target construct. The authors make several suggestions for researchers and practitioners in improving individual item quality and in making informed decisions when using the SSIS in the future.

The purpose of this paper is to examine aspects of how workplace bullying is identified by the Negative Acts Questionnaire-Revised (NAQ-R), with a focus on the appropriateness of its response scale using item response theory (IRT).

IRT, in which the probability of a particular item response reflects an underlying latent variable, was used to examine NAQ-R responses from a sample of 1,173 Australian public servants (Study 1), and a representative UK data set (n=3,494; Study 2).

Results indicated that problems with the response scale appear to be due to the inclusion of the abstract “now and then” option amongst concrete time options (“never”, “now and then”, “monthly”, “weekly” and “daily”). These results were replicated in Study 2, providing evidence of the robustness of the findings, and suggesting the observations are not sample specific.

This work has implications for methods employed to identify and measure workplace bullying in research and organisational practice. Inconsistent endorsement of response scale options is a concern when total scores are calculated, or when a number of behaviours being experienced with a particular frequency on the response scale are taken as an indication of bullying having occurred.

Examining and refining the manner in which workplace bullying is indexed is important for identifying and managing workplace risks to health, safety and well-being.

This study aims to evaluate Netemeyer and colleagues' much cited financial well-being scale in Brazil and India and compare responses from different demographics. It also compares the results using two analysis techniques, item response theory (IRT) and confirmatory factor analysis (CFA).

A total of 994 survey responses from Brazil and 1,081 from India were collected. IRT and CFA models were used to analyse the data.

The results demonstrate the two-dimensional structure of the financial well-being scale and show that different items are differentially useful in measuring the construct across different groups. These findings may support the scale's future refinement and use in applied studies that will target specific groups (e.g. males, females, younger respondents and older respondents).

This study serves as an example to others who can explore the advantages of IRT over classical test theory methods to assess the psychometric properties of scales aimed at measuring latent constructs of interest in the field of marketing.

The correct diagnosis of financial well-being is important to guide interventions by governments and non-governmental entities, as well as by financial institutions interested in better understanding individuals.

The authors show how the identification of the characteristics of scale items provided by the IRT technique allows for a better understanding of its properties and how it can be improved.

Surveys that include skill measures may suffer from additional sources of error compared to those containing questionnaires alone. Examples are distractions such as noise or interruptions of testing sessions, as well as fatigue or lack of motivation to succeed. This paper aims to provide a review of statistical tools based on latent variable modeling approaches extended by explanatory variables that allow detection of survey errors in skill surveys.

This paper reviews psychometric methods for detecting sources of error in cognitive assessments and questionnaires. Aside from traditional item responses, new sources of data in computer-based assessment are available – timing data from the Programme for the International Assessment of Adult Competencies (PIAAC) and data from questionnaires – to help detect survey errors.

Some unexpected results are reported. Respondents who tend to use response sets have lower expected values on PIAAC literacy scales, even after controlling for scores on the skill-use scale that was used to derive the response tendency.

The use of new sources of data, such as timing and log-file or process data information, provides new avenues to detect response errors. It demonstrates that large data collections need to better utilize available information and that integration of assessment, modeling and substantive theory needs to be taken more seriously.

Psychometric analyses of self-administered questionnaire data tend to focus on items and instruments as a whole. The purpose of this paper is to investigate the functioning of the response scale and its impact on measurement precision. In terms of the response scale direction, existing evidence is mixed and inconclusive.

Three experiments are conducted to examine the functioning of response scales of different direction, ranging from agree to disagree versus from disagree to agree. The response scale direction effect is exemplified by two different latent constructs by applying the Rasch model for measurement.

The agree-to-disagree format generally performs better than the disagree-to-agree variant with spatial proximity between the statement and the agree-pole of the scale appearing to drive the effect. The difference is essentially related to the unit of measurement.

A careful investigation of the functioning of the response scale should be part of every psychometric assessment. The framework of Rasch measurement theory offers unique opportunities in this regard.

Besides content, validity and reliability, academics and practitioners utilising published measurement instruments are advised to consider any evidence on the response scale functioning that is available.

The study exemplifies the application of the Rasch model to assess measurement precision as a function of the design of the response scale. The methodology raises the awareness for the unit of measurement, which typically remains hidden.

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.

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 paper aims to validate the Korean version of the decent work scale and examine the relationship between decent work and work engagement.

After completing translation and back translation, the authors surveyed 266 Korean employees from various organizations via network sampling. They assessed Rasch’s model based on item response theory. In addition, they used classical test theory to evaluate the decent work scale’s validity and reliability.

The authors found that the current version of the decent work scale has good validity, reliability and item difficulty, and decent work has a positive relationship with work engagement. However, based on item response theory, the assessment showed that three of the items are extremely similar to another item within the same dimension, implying that the items are unable to discriminate among individual traits.

This study validated the decent work scale in a Korean work environment using Rasch’s (1960) model from the perspective of item response theory.

The paper investigates the suitability of the Rasch model for establishing data equivalence. The results based on a real data set are contrasted with findings from standard procedures based on CFA methods.

Sinkovics et al.'s data on technophobia was used and re‐evaluated using both classical test theory (CTT) (multiple‐group structural equations modelling) and Rasch measurement theory.

Data equivalence in particular and measurement in general cannot be addressed without reference to theory. While both procedures can be considered best practice approaches within their respective theoretical foundation of measurement, the Rasch model provides some theoretical virtues. Measurement derived from data that fit the Rasch model seems to be approximated by classical procedures reasonably well. However, the reverse is not necessarily true.

The more widespread application of Rasch models would lead to a stronger justification of measurement, in particular, in cross‐cultural studies but also whenever measures of individual respondents are of interest.

Measurement models outside the framework of CTT are still scarce exceptions in marketing research.