Discriminant validity assessment in marketing research

2018 ◽  
Vol 61 (2) ◽  
pp. 210-222 ◽  
Author(s):  
Joseph M Matthes ◽  
A Dwayne Ball
Keyword(s):  
Measurement Error ◽  
Sample Size ◽  
Discriminant Validity ◽  
Marketing Research ◽  
Size Measurement ◽  
Artificial Data ◽  
Validity Assessment ◽  
Recommendations For Practice ◽  
Artificial Datasets ◽  
Measurement Validity

Establishing discriminant validity has been a keystone of measurement validity in empirical marketing research for many decades. Without statistically showing that constructs have discriminant validity, contributions to marketing literature are likely to foster the proliferation of constructs that are operationally the same as other constructs already present in the literature, thus leading to confusion in the development of theory. This article addresses this concern by evaluating well-established methods for testing discriminant validity through the simulation of artificial datasets (containing varying levels of correlation between constructs, sample size, measurement error, and distribution skewness). The artificial data are applied to six commonly used approaches for testing the existence of discriminant validity. Results strongly suggest that several methods are much more likely than others to yield accurate assessments of whether discriminant validity exists, especially under specific conditions. Recommendations for practice in the assessment of discriminant validity are suggested.

scholarly journals An Updated Guideline for Assessing Discriminant Validity

2020 ◽  
pp. 109442812096861
Author(s):  
Mikko Rönkkö ◽  
Eunseong Cho
Keyword(s):  
Monte Carlo ◽  
Measurement Error ◽  
Monte Carlo Simulations ◽  
Empirical Research ◽  
Discriminant Validity ◽  
Ad Hoc ◽  
Validity Assessment ◽  
Two Measures ◽  
Definition Of

Discriminant validity was originally presented as a set of empirical criteria that can be assessed from multitrait-multimethod (MTMM) matrices. Because datasets used by applied researchers rarely lend themselves to MTMM analysis, the need to assess discriminant validity in empirical research has led to the introduction of numerous techniques, some of which have been introduced in an ad hoc manner and without rigorous methodological support. We review various definitions of and techniques for assessing discriminant validity and provide a generalized definition of discriminant validity based on the correlation between two measures after measurement error has been considered. We then review techniques that have been proposed for discriminant validity assessment, demonstrating some problems and equivalencies of these techniques that have gone unnoticed by prior research. After conducting Monte Carlo simulations that compare the techniques, we present techniques called CICFA(sys) and [Formula: see text](sys) that applied researchers can use to assess discriminant validity.

Common Method Bias in PLS-SEM

2015 ◽  
Vol 11 (4) ◽  
pp. 1-10 ◽  
Author(s):  
Ned Kock
Keyword(s):  
Structural Equation ◽  
Discriminant Validity ◽  
Least Squares Method ◽  
Common Method ◽  
Equation Modeling ◽  
Common Method Bias ◽  
Validity Assessment ◽  
Convergent And Discriminant Validity ◽  
Partial Least Squares Method ◽  
Method Bias

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.

scholarly journals Erratum

2016 ◽  
Vol 53 (5) ◽  
pp. NP1-NP1
Keyword(s):  
Cognitive Load ◽  
Sample Size ◽  
Degrees Of Freedom ◽  
Health And Safety ◽  
Marketing Research ◽  
Initial Sample ◽  
Safety Concerns ◽  
Main Effect

White, Katherine, Lily Lin, Darren W. Dahl, and Robin J. B. Ritchie (2016), “When Do Consumers Avoid Imperfections? Superficial Packaging Damage as a Contamination Cue,” Journal of Marketing Research, 53 (February), 110–23. (Original DOI: 10.1509/jmr.12.0388 ) The following reporting errors have been noted in this article. These errors were clerical only, and the changes do not affect the data patterns or significance of the results in any way. Study 1, page 113 The numerator degrees of freedom for the interaction should be 2. At the end of the last full paragraph, the text should read: “The interaction qualified a significant main effect for type of package damage (F(2, 139) = 4.90, p < .05) and a marginal main effect for cognitive load (F(1, 139) = 3.36, p < .07).” Study 2, page 115 The degrees of freedom should be 130. The text should read: “Results revealed a main effect for packaging damage (t(130) = 5.49, p < .001; b = −.561) and the anticipated three-way interaction (t(130) = 2.24, p < .03; b = −.286; see Figure 2).” Study 4, page 116 The numerator degrees of freedom was omitted in one sentence. The text should read: “As we predicted, packaging appearance predicted both contamination perceptions (F(2, 150) = 4.17, p < .05) and health and safety concerns (F(2, 150) = 3.41, p < .05; see Table 1).” Study 5, page 118 The initial sample size is 200 participants. The text should say: “Those who failed to properly complete the cognitive load task were removed from the analyses (9.5% of the sample, leaving 181 participants).”

scholarly journals Product Acceptance Determination with Measurement Error Using the Neutrosophic Statistics

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Muhammad Aslam
Keyword(s):  
Measurement Error ◽  
Sample Size ◽  
Optimization Problem ◽  
Sampling Plan ◽  
Measurement Process ◽  
Comparison Study ◽  
Classical Statistics ◽  
Neutrosophic Statistics ◽  
Variable Data ◽  
Uncertainty Environment

The variable data is obtained from the measurement process which is not fully complete or clear in nature due to measurement error. The neutrosophic statistics which is the extension of classical statistics can be applied in the industry for the lot senescing when observations or parameters are uncertain or indeterminate or unclear. In this manuscript, a new sampling plan for the measurement error using the neutrosophic statistics is designed. The proposed sampling plan has two neutrosophic parameters, namely, sample size and acceptance number. The neutrosophic operating function is also given. The neutrosophic plan parameters will be determined through the neutrosophic optimization problem. Some tables are given for some specified parameters. From the comparison study, it is concluded that the proposed sampling plan is more flexible, adequate, and effective in the uncertainty environment as compared to the existing sampling plan under the classical statistics. A real example is given for the illustration purpose.

Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

1981 ◽  
Vol 18 (1) ◽  
pp. 39-50 ◽  
Author(s):  
Claes Fornell ◽  
David F. Larcker
Keyword(s):  
Measurement Error ◽  
Sample Size ◽  
Structural Equation ◽  
Structural Model ◽  
Structural Equation Models ◽  
Statistical Tests ◽  
Explanatory Power ◽  
Measurement Model ◽  
Measurement Properties ◽  
Chi Square

The statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined. A drawback of the commonly applied chi square test, in addition to the known problems related to sample size and power, is that it may indicate an increasing correspondence between the hypothesized model and the observed data as both the measurement properties and the relationship between constructs decline. Further, and contrary to common assertion, the risk of making a Type II error can be substantial even when the sample size is large. Moreover, the present testing methods are unable to assess a model's explanatory power. To overcome these problems, the authors develop and apply a testing system based on measures of shared variance within the structural model, measurement model, and overall model.

scholarly journals Validation of Dimensions of Learning Organization Questionnaire (DLOQ) in health care setting in Greece

2020 ◽  
Vol 9 (4) ◽  
Author(s):  
Aspasia Goula ◽  
Maria-Aggeliki Stamouli ◽  
Dimitra Latsou ◽  
Vasiliki Gkioka ◽  
Markos Sarris
Keyword(s):  
Health Care ◽  
Learning Organization ◽  
Discriminant Validity ◽  
Continuous Process ◽  
Correlation Coefficients ◽  
Public Hospitals ◽  
Face Validity ◽  
Validity And Reliability ◽  
Validity Assessment ◽  
Dimensions Of Learning

Background: In health care systems the organizational learning is a continuous process to improve actions through better knowledge and detect or correct errors. This study examines the validity and reliability of the Dimensions of Learning Organization Questionnaire in addition to the applicability of the instrument in a Greek health care cultural context.Design and methods: Α cross-sectional study was carried out in 6 general hospitals of Attica and the sampling scheme was the stratified sampling. Questionnaires were distributed to 487 healthcare professionals and 380 valid questionnaires were returned. The research tool used in this survey is the extensive form of DLOQ, which has been adapted and translated into Greek language. Data analysis was carried out with SPSS 25.Results: Three leading experts of the health sector examined the face validity assessment of the translated DLOQ and stated that it is characterized by high face validity. As regard construct validity of the DOLQ throughout Multitrait-Multimethod Matrix, was proved that all the variables of the same factors are statistically significantly correlated (p<0.001), and their correlation coefficients have moderate to high power ranging between 0.563 and 0.798. Moreover, the discriminant validity was demonstrated as certain correlation coefficients between variables of different factors were found to be higher than of certain correlation coefficients between variables of the same factors. The internal consistency among the items of the DOLQ range between 0.842 and 0.977 and they are considered to be good to excellent.Conclusions: Our results confirmed that DLOQ is a valuable tool in measuring Learning Organizational in Greek public hospitals.

Strategies for Sustainable Quality Service Delivery in Hotels in Owerri

2018 ◽  
pp. 1-12
Author(s):  
I.B. Anyanwu
Keyword(s):  
Data Collection ◽  
Service Quality ◽  
Service Delivery ◽  
Sample Size ◽  
Customer Service ◽  
Marketing Research ◽  
Sampling Technique ◽  
Hospitality Management ◽  
Quality Service ◽  
Infinite Population

This study sought to determine strategies for sustainable quality service delivery in hotels in Owerri. Two research questions guided the study. The study population comprised all customers of registered hotels. It is an infinite population. The researcher used Cochran (1977) formula for determining sample size for an infinite population, and it gave a sample size of 384. A structured questionnaire was used as an instrument for data collection which was validated by academics in Hospitality Management and Tourism, and Marketing. Crombach Alpha Coefficient of 0.73 was obtained confirming the usability of the instrument. Convenient sampling technique was adopted for data collection, which was analyzed using frequency, mean, and standard deviation. Findings revealed that the level of quality service delivery in the hotels studied was very poor as shown by the clustered mean. Similarly, the respondents agreed on specific strategies such as marketing research and anticipation of guest needs, employee empowerment, and training, among others for improving quality service delivery in hotels in the study area. Given the findings of the study, recommendations were made to the effect that hotel operations are encouraged to carry out periodic service quality assessment to determine customer service quality perceptions and also develop sustainable feedback mechanisms such as comment cards and other online interactive platforms that can facilitate constant updates on customer needs and wants.

The role of the museumscape on positive word of mouth: examining Italian museums

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Emanuela Conti ◽  
Massimiliano Vesci ◽  
Paola Castellani ◽  
Chiara Rossato
Keyword(s):  
Structural Equation ◽  
Discriminant Validity ◽  
Word Of Mouth ◽  
Marketing Research ◽  
Measurement Model ◽  
Quantitative Methodology ◽  
Positive Word ◽  
Ambient Conditions ◽  
Content Type ◽  
Positive Word Of Mouth

PurposeThis study aims to develop an all-encompassing model to analyse various aspects of atmospherics, including components of the museum space and its physical surroundings. Moreover, it evaluates whether the identified attributes of the “museumscape” affect the positive word of mouth of museum visitors.Design/methodology/approachThis exploratory study adopts a quantitative methodology. Data were collected through direct interviews with visitors at three Italian art museums and through a structured questionnaire. All dimensions were measured with multiple items on a five-point Likert scale. To assess the influence of the museumscape attributes on positive word of mouth, a structural equation model is performed adopting the two-stage testing procedure estimating the measurement model in the first stage and running a confirmatory factor analysis to assess reliability and demonstrate convergent and discriminant validity for all multi-item measures.FindingsSix attributes of the museumscape are delineated (ambient conditions; facilities and convenience; signs and signage; staff behaviour; art gallery quality; exhibition space aesthetics). The latter three positively influence visitors' positive word of mouth.Research limitations/implicationsThe study expands frameworks from previous service museum marketing research in general and service museum research on atmospherics in particular. The framework developed here identifies the direct predictive power of museumscape cues on positive museum visitor's word of mouth, thus increasing knowledge of the customer service experience and service quality and atmospherics management.Practical implicationsThe constructs discovered here may help museum managers to carefully design and manage the museumscape to enhance visitors' satisfaction and loyalty.Originality/valueThis study is the first application of servicescape theory in the museum context; previous applications focus on for-profit sectors.

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