Integrating the Expanded Task-technology Fit Theory and the Technology Acceptance Model: A Multi-wave Empirical Analysis

Task-technology fit theory proposes that the match between tasks and technologies, known as task-technology fit, has a positive relation with technology use and performance. Researchers have recently extended task-technology fit theory by conceptualizing task-technology misfit, which describes instances in which technology provides too few (too little) or too many (too much) features to perform a task. We link this newly expanded theory, which we label expanded task- technology fit (E-TTF) theory, with the technology acceptance model (TAM). We conducted a study and found that task- technology fit and too little significantly related to the variables in the TAM and that each ultimately had an indirect effect on use. In contrast, too much did not significantly relate to any variable in the TAM. These results support that E-TTF theory explains meaningful variance in the TAM, which suggests that integrating these theories is important for understanding technology use. Likewise, these results emphasize the importance of the multidimensional conceptualization that the E-TTF theory proposes. Too little (too few features) predicted outcomes beyond task- technology fit and meaningfully improved our model’s predictive abilities. In contrast, too much’s (too many features) relationships lacked significance, which emphasizes the need to distinguish types of task-technology misfit. Therefore, our study provides benefits for research on E-TTF theory, the TAM, and their integration

Multilevel modeling for longitudinal data: concepts and applications

Purpose – This paper aims to discuss multilevel modeling for longitudinal data, clarifying the circumstances in which they can be used. Design/methodology/approach – The authors estimate three-level models with repeated measures, offering conditions for their correct interpretation. Findings – From the concepts and techniques presented, the authors can propose models, in which it is possible to identify the fixed and random effects on the dependent variable, understand the variance decomposition of multilevel random effects, test alternative covariance structures to account for heteroskedasticity and calculate and interpret the intraclass correlations of each analysis level. Originality/value – Understanding how nested data structures and data with repeated measures work enables researchers and managers to define several types of constructs from which multilevel models can be used

Development and validation of attitudes measurement scales: fundamental and practical aspects

Purpose – This paper aims to present the fundamental aspects for the development and validation (D&V) of attitudes’ measurement scale, as well as its practical aspects that are not deeply explored in books and manuals. These aspects are the results of a long experience of the authors and arduous learning with errors and mistakes. Design/methodology/approach – The nature of this paper is methodological and can be very useful for an initial reading on the theme that it rests. This paper presents four D&V stages: literature review or interviews with experts; theoretical or face validation; semantic validation or validation with possible respondents; and statistical validation. Findings – This is a methodological paper, and its main finding is the usefulness for researchers. Research limitations/implications – The main implication of this paper is to support researchers on the process of D&V of measurement scales. Practical implications – Became a step-by-step guide to researchers on the D&V of measurement scales. Social implications – Support researchers on their data collection and analysis. Originality/value – This is a practical guide, with tips from seasoned scholars to help researchers on the D&V of measurement scale

Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R

Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method’s flexibility in terms of data requirements and measurement specification. This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software’s SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the “how-tos” of using SEMinR to obtain solutions and document their results. Rules of thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM

Common Beliefs and Reality About PLS: Comments on Ronnkko and Evermann (2013)

Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen Jr., D. J., Hair, J. F., Hult, G. T. M., & Calantone, R. J. (2014). Common Beliefs and Reality About PLS: Comments on Ronnkko and Evermann (2013). Organizational Research Methods, 17(2), 182-209. https://doi.org/10.1177/1094428114526928This article addresses Rönkkö and Evermann’s criticisms of the partial least squares (PLS) approach to structural equation modeling. We contend that the alleged shortcomings of PLS are not due to problems with the technique, but instead to three problems with Rönkkö and Evermann’s study: (a) the adherence to the common factor model, (b) a very limited simulation designs, and (c) overstretched generalizations of their findings. Whereas Rönkkö and Evermann claim to be dispelling myths about PLS, they have in reality created new myths that we, in turn, debunk. By examining their claims, our article contributes to reestablishing a constructive discussion of the PLS method and its properties. We show that PLS does offer advantages for exploratory research and that it is a viable estimator for composite factor models. This can pose an interesting alternative if the common factor model does not hold. Therefore, we can conclude that PLS should continue to be used as an important statistical tool for management and organizational research, as well as other social science disciplines.publishersversionpublishe

Cluster Analysis of Symptoms Among Patients with Upper Extremity Musculoskeletal Disorders

Introduction Some musculoskeletal disorders of the upper extremity are not readily classified. The study objective was to determine if there were symptom patterns in self-identified repetitive strain injury (RSI) patients. Methods Members (n = 700) of the Dutch RSI Patients Association filled out a detailed symptom questionnaire. Factor analysis followed by cluster analysis grouped correlated symptoms. Results Eight clusters, based largely on symptom severity and quality were formulated. All but one cluster showed diffuse symptoms; the exception was characterized by bilateral symptoms of stiffness and aching pain in the shoulder/neck. Conclusions Case definitions which localize upper extremity musculoskeletal disorders to a specific anatomical area may be incomplete. Future clustering studies should rely on both signs and symptoms. Data could be collected from health care providers prospectively to determine the possible prognostic value of the identified clusters with respect to natural history, chronicity, and return to work

Inovatividade, envolvimento, atitude e experiência na adoção da compra on-line

This work seeks to analyze the inter-relationships that exist between innovation, involvement and attitude in the decomposed model of the Theory of Planned Behavior (TPB), as applied in social psychology, and experience of using the Internet in the process of buyingon-line. An integrative model was prepared that made it possible to explain the relationship that exists between these factors and purchasing from the Internet. A field survey was undertaken with a non-probabilistic sample of students. A multivariate structural equation modeling method was used and applied by the Partial Least Squares (PLS) technique for checking, explaining and comparing the relationship between the constructs. The results show that intention to buy via the Internet is directly influenced by attitude and innovativeness, and attitude is influenced by involvement. No relationship was found between experience in using the Internet and buying from i

Construção de instrumento para avaliação de cursos de pós-graduação

Este artigo tem como objetivo propor um método para avaliar cursos de pós-graduação em Instituições de Ensino Superior (IES). O método busca identificar, através de um questionário, critérios inibidores da qualidade e promotores da qualidade em cursos de pós-graduação. Critérios significativos nos dois blocos são identificados através de uma Análise Fatorial. Em um segundo passo, esses critérios são contemplados através de ações que atendem as demandas identificadas. O método proposto é ilustrado através de um estudo de caso. Ao final do estudo pode-se constatar a eficiência da Análise Fatorial como técnica auxiliar à tomada de decisão por parte da IES.This paper presents a method to evaluate graduate programs in Higher Education Institutions (HEIs). The method aims at identifying criteria that inhibit and promote the quality of graduate programs. Significant criteria in both cases are indentified through a Factor Analysis. In a second step such criteria are converted into actions addressing the demands identified. The method is illustrated through a case study. We eventually conclude for the efficiency of Factor Analysis as technique to support the decision making processes in HEIs