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The set of compositional approaches to product space development is expanded to include confirmatory methods. Specifically, describes and compares product space development (perceptual mapping) via confirmatory factor analysis and partial least squares with the aid of an empirical example. Both of these procedures are widely used in causal or structural equation modelling. Since they tend to be confirmatory extensions to factor analysis and principal components analysis, the approaches are also well suited to the development of product spaces. Confirmatory approaches have several advantages over exploratory approaches including the incorporation of prior knowledge, the elimination of rotational indeterminacy, and the use of a wide variety of measurement tools to assess the reliability and validity of model results.

Constructing and evaluating behavioral science models is a complex process. Decisions must be made about which variables to include, which variables are related to each other, the functional forms of the relationships, and so on. The last 10 years have seen a substantial extension of the range of statistical tools available for use in the construction process. The progress in tool development has been accompanied by the publication of handbooks that introduce the methods in general terms (Arminger et al., 1995; Tinsley & Brown, 2000a). Each chapter in these handbooks cites a wide range of books and articles on specific analysis topics.

This study aims to offer insight into the applications of multilevel confirmatory factor analysis (MCFA) within organizational behavior (OB) studies, specifically when using macro-level variables. The authors used the case of a scale measuring collective organizational engagement (COE) to demonstrate the advantage of using MCFA over single-level confirmatory factor analysis (CFA).

The authors used nine referent-shift items to measure the dimensions of physical, cognitive and emotional COE. MCFA and aggregated single-level CFA were conducted on the same data using Mplus V. 8.7, and the authors compared standardized parameters from the two techniques.

The results indicate a three-factor model of collective engagement with CFA and MCFA. Stronger item loadings, factor correlations and composite reliability were found in the MCFA within-level model compared to aggregated CFA model. MCFA also supported an alternate one-factor-between-three-factors-within model of COE.

This study demonstrates the application of MCFA with a compositional construct and compares MCFA to mean-aggregated single-level CFA. It presents a case for OB researchers to apply MCFA to compositional constructs as a best methodological practice.

In this study, the authors propose a confirmatory factor analysis (CFA) to create a tenable measurement model and identify the factors that have the potential to enhance awareness of pro-environmental measures. The successful implementation of demand response (DR) programs and their required infrastructure is significant for moving towards green energy communities and a better environment for living. Not only can renewable energy capacities contribute to this desideratum, but also electricity consumers who, until the last decade, have played a passive role.

To answer these questions, a complex data set of 243 post-trial questions created by the Irish CER are analyzed using first-order and hierarchical CFA models with several SAS procedures (PROC CALIS, MIANALYZE). The questionnaire was launched to over 3,000 electricity consumers from Ireland that were participants to a trial program after the installation of smart metering systems and implementation of DR programs.

The effect of five latent factors – positive attitude, negative attitude, perceived impact of own actions, price- and incentive-DR programs – is measured. With a bi-factor CFA measurement model, the authors assess that they significantly influence the electricity consumers' awareness.

However, these findings have to be backed up by relevant information and simulations showing consumers benefits in exchange to their efforts. They have research implications on the design of the business models and DR programs pointing out the importance of benefits and fairness of value sharing mechanisms within energy communities.

Thus, the electricity consumers may change their consumption behavior as they positively perceive the implementation of DR programs.

This paper fulfills an identified need to study post-trial questionnaire and reveal latent factors that make electricity consumer change their behavior.

Considering the relevance of operational excellence as a business strategy, organizations are striving to improve themselves by adopting best practices and universally accepted principles through the process of continuous improvement, and these principles should be embedded in the culture of an organization. Organizations pursue to align themselves by continuously improving their processes by adopting scientifically proven techniques and cultural transformation throughout the organization. However, there is a lack of scientific instruments for the assessment of operational excellence. The objective of this study is to develop a scale for the assessment of practices of operational excellence principles in the organizations. Further reliability and validity of the developed scale are measured by testing the relationship between Human Resource Practices (HRP) and Operational Excellence (OE).

This study comprises quantitative design through exploratory and confirmatory studies and also includes qualitative analysis to develop a scale for the assessment of Operational Excellence (OE). Interviews from industry experts have been conducted to identify the major components for which organizations are striving for OE. Previous literature and excellence models, especially principles of the Shingo Operational Excellence Model (SOEM), have been reviewed and considered to finalize the scale items. Data were collected in two stages from both Telecommunication subsectors (Cellular Mobile Operators and Fixed Local Loop Operators) of Pakistan through the cross-sectional survey. In the first stage, exploratory factor analysis (EFA) was performed on the sample of 611 respondents from both Cellular Mobile and Fixed Local Loop operators of Pakistan. In the second stage, confirmatory factor analysis (CFA) was performed on the sample of 423 respondents from the Fixed local loop operators. EFA was conducted by using SPSS version 23 to finalize the OE scale, and for confirmatory factor analysis, PLS-SEM using Smart PLS was used to confirm the reliability and validity of the OE Scale.

The results of EFA reveal that OE is a multidimensional construct with three dimensions and 23 items. The dimensions of the developed OE Scale explored in this study are cultural enablers (CE), continuous process improvement (CPI) and enterprise alignment (EA). The confirmatory factor analysis of OE confirmed the scale dimensionality, reliability and validity along with the hypothesis testing to measure the impact of antecedent variable HRP on OE.

Organizations pursue to improve and align their operational processes but usually unable to confirm the implementation of their desired objectives. Based on the developed OE scale, managers may assess the implementation of OE principles in their organizations. This research has been conducted in the telecommunication sector of Pakistan only, and the developed instrument needs to be further tested in other organizations.

The instrument developed in this study will help both researchers and practitioners to assess the principles of operational excellence in their organizations and enable them to design the strategies for improving organizational performance.

The results of this study will create awareness about the principles of operational excellence. The developed OE instrument will assist in identifying the gaps in organizational norms and values from the perspective of paying respect to every individual inside and outside the organization. OE instrument will be further helpful in the identification and assurance of health, safety, protection of the environment and community issues.

This study provides a reliable and validated scale for the scientific area of operation management and helps managers with the assessment of operational excellence in their organizations. This newly developed scale is also valid to test and use in different studies and industries by researchers and practitioners.

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 paper is to propose a model (structural equation modeling (SEM)) from the 16 identified just in time (JIT) elements useful for implementation of JIT in maintenance.

Data were collected using questionnaires posted to 421 manufacturing industries and automotive service industries in India from which 133 usable responses were obtained. First, exploratory factor analysis (EFA) is carried out to identify the factor structure after that confirmatory factor analysis (CFA) is carried out to verify the factor structure of a set of identified JIT elements. CFA is conceded by an SEM statistical technique. In this paper, EFA is applied to extract the factors in JIT implementation by the statistical package for social sciences (SPSS 24) software and confirming these factors by CFA through analysis of moment structures (AMOS 18) software.

Out of 18 identified JIT elements through literature and expert opinion only 16 JIT elements are selected for the study, two JIT elements removed due to the low value of correlation item-total correlation (CITC). Three factors extracted through EFA, which affects the benefits of JIT implementation in maintenance in quality improvement, production improvement and process control. SEM using AMOS 18.0 was used to perform the first-order three-factor structure (quality improvement, production improvement and process control) of the JIT implementation in maintenance.

The results will be useful for maintenance managers and maintenance professionals to understand the process of implementation of JIT in maintenance and to gain benefits after the implementation of JIT in maintenance in their respective organization.

This chapter presents and discusses various steps to ensure empirical reliability and theoretical validity in the construction of competence scales in graduate surveys. The development of a scale to assess demands of the teacher profession and related abilities in graduates for a German tracer study project serves as an example. Confirmatory factor analysis (CFA), principal component analysis (PCA) and Cronbach’s coefficient alpha are employed to test the reliability of the scale. Differing results illustrate how the method applied influences decisions in the process of developing a scale. Our findings show that multidimensionality can only be tested appropriately by CFA; PCA renders no feasible or similar results to CFA depending on the predetermination of the number of factors; Cronbach’s alpha produces misleading results as the prerequisite assumption of unidimensionality is violated by the data.

This chapter focusses on the identification of sustainability factors. Out of the 77 variables used in the questionnaire for collection of the information, on sustainability of financial innovation in e-payment system (EPS), the important factors are identified and derived using exploratory factor analysis (EFA). This chapter further presents validation of the identified factors through confirmatory factor analysis (CFA). Based on the identified factors, a model for EPS is proposed. The chapter also presents a scale developed based on identified factors.

The purpose of this paper is to draw on the resource-based view of the firm from strategic management and apply it to a study of competitive advantage in the project management context. Confirmatory factor analysis (CFA) is used to examine the factors that constitute strategic characteristics of project management resources and outcomes of the project management process.

This study gathered data from 437 North American project management professionals using an existing survey tool from prior research involving a smaller sample.

The final model derived from CFA demonstrated construct validity, meaning acceptable convergent and discriminant validity. It showed only minor differences from a prior exploratory factor analysis (EFA). The final model consisted of two factors representing valuable project management characteristics, one factor representing rare project management characteristics, one factor representing inimitable project management characteristics, three factors representing organizational support for project management assets, one factor representing project-level performance and one factor representing firm-level performance.

Limitations of the study include self-report bias and the use of a panel for data collection.

This study draws managerial attention to project management characteristics that constitute a source of competitive advantage.

The study validates a survey tool from previous research, reflects few deviations from factor structure of the prior EFA, and sets the stage for future research to elaborate on the conceptual model. It extends understanding of the characteristics of project management assets that lead to a firm’s competitive advantage.