자연주의적 탐구조사(Naturalistic Inquiry)

Basics of qualitative research: Grounded theory procedures and techniques

According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

The purpose of this paper is to provide a comprehensive, yet concise, overview of the considerations and metrics required for partial least squares structural equation modeling (PLS-SEM) analysis and result reporting. Preliminary considerations are summarized first, including reasons for choosing PLS-SEM, recommended sample size in selected contexts, distributional assumptions, use of secondary data, statistical power and the need for goodness-of-fit testing. Next, the metrics as well as the rules of thumb that should be applied to assess the PLS-SEM results are covered. Besides presenting established PLS-SEM evaluation criteria, the overview includes the following new guidelines: PLSpredict (i.e., a novel approach for assessing a model’s out-of-sample prediction), metrics for model comparisons, and several complementary methods for checking the results’ robustness.,This paper provides an overview of previously and recently proposed metrics as well as rules of thumb for evaluating the research results based on the application of PLS-SEM.,Most of the previously applied metrics for evaluating PLS-SEM results are still relevant. Nevertheless, scholars need to be knowledgeable about recently proposed metrics (e.g. model comparison criteria) and methods (e.g. endogeneity assessment, latent class analysis and PLSpredict), and when and how to apply them to extend their analyses.,Methodological developments associated with PLS-SEM are rapidly emerging. The metrics reported in this paper are useful for current applications, but must always be up to date with the latest developments in the PLS-SEM method.,In light of more recent research and methodological developments in the PLS-SEM domain, guidelines for the method’s use need to be continuously extended and updated. This paper is the most current and comprehensive summary of the PLS-SEM method and the metrics applied to assess its solutions.

https://www.emerald.com/insight/content/doi/10.1108/EBR-11-2018-0203/full/pdf

When to use and how to report the results of PLS-SEM

Part I. Experimental Studies: 2. Experiment in psychology 3. Experiments on perceiving III Experiments on imaging 4-8. Experiments on remembering: (a) The method of description (b) The method of repeated reproduction (c) The method of picture writing (d) The method of serial reproduction (e) The method of serial reproduction picture material 9. Perceiving, recognizing, remembering 10. A theory of remembering 11. Images and their functions 12. Meaning Part II. Remembering as a Study in Social Psychology: 13. Social psychology 14. Social psychology and the matter of recall 15. Social psychology and the manner of recall 16. Conventionalism 17. The notion of a collective unconscious 18. The basis of social recall 19. A summary and some conclusions.

Remembering. A Study in Experimental and Social Psychology, Cambridge (University Press) 1964.

The author discusses common method bias in the context of structural equation modeling employing the partial least squares method PLS-SEM Two datasets were created through a Monte Carlo simulation to illustrate the discussion: one contaminated by common method bias, and the other not contaminated A practical approach is presented for the identification of common method bias based on variance inflation factors generated via a full collinearity test The author's discussion builds on an illustrative model in the field of e-collaboration, with outputs generated by the software WarpPLS They demonstrate that the full collinearity test is successful in the identification of common method bias with a model that nevertheless passes standard convergent and discriminant validity assessment criteria based on a confirmation factor analysis

/pdf/common-method-bias-in-pls-sem-a-full-collinearity-assessment-1x6hxvwkg2.pdf

Common Method Bias in PLS-SEM: A Full Collinearity Assessment Approach

Variance-based structural equation modeling is extensively used in information systems research, and many related findings may have been distorted by hidden collinearity. This is a problem that may extent to multivariate analyses in general, in the field of information systems as well as in many other fields. In multivariate analyses, collinearity is usually assessed as a predictor-predictor relationship phenomenon, where two or more predictors are checked for redundancy. This type of assessment addresses vertical, or “classic,” collinearity. However, another type of collinearity may also exist, called here “lateral” collinearity. It refers to predictor-criterion collinearity. Lateral collinearity problems are exemplified based on an illustrative variance-based structural equation modeling analysis. The analysis employs WarpPLS 2.0, with the results double-checked with other statistical analysis software tools. It is shown that standard validity and reliability tests do not properly capture lateral collinearity. A new approach for the assessment of both vertical and lateral collinearity in variance-based structural equation modeling is proposed and demonstrated in the context of the illustrative analysis.

Lateral Collinearity and Misleading Results in Variance-Based SEM: An Illustration and Recommendations

Despite the growing prominence of canonical action research (CAR) in the information systems discipline, a paucity of methodological guidance contin- ues to hamper those conducting and evaluating such studies. This article elicits a set of five principles and associated criteria to help assure both the rigor and the relevance of CAR in information systems. The first principle relates to the devel- opment of an agreement that facilitates collaboration between the action researcher and the client. The second principle is based upon a cyclical process model for action research that consists of five stages: diagnosis, planning, inter- vention, evaluation and reflection. Additional principles highlight the critical roles of theory, change through action, and the specification of learning in terms of impli- cations for both research and practice. The five principles are illustrated through the analysis of one recently published CAR study.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2575.2004.00162.x

Principles of canonical action research

Partial least squares-based structural equation modelling (PLS-SEM) is extensively used in the field of information systems, as well as in many other fields where multivariate statistical methods are used. One of the most fundamental issues in PLS-SEM is that of minimum sample size estimation. The ‘10-times rule’ has been a favourite because of its simplicity of application, even though it tends to yield imprecise estimates. We propose two related methods, based on mathematical equations, as alternatives for minimum sample size estimation in PLS-SEM: the inverse square root method, and the gamma-exponential method. Based on three Monte Carlo experiments, we demonstrate that both methods are fairly accurate. The inverse square root method is particularly attractive in terms of its simplicity of application. © 2016 John Wiley & Sons Ltd

Ned Kock

Papers

Common Method Bias in PLS-SEM: A Full Collinearity Assessment Approach

Lateral Collinearity and Misleading Results in Variance-Based SEM: An Illustration and Recommendations

Lateral Collinearity and Misleading Results in Variance-Based SEM: An Illustration and Recommendations

Principles of canonical action research

Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods