The empirical assessment of construct validity

O'Leary-Kelly, Scott W; Vokurka, Robert J.

doi:10.1016/s0272-6963(98)00020-5

Cited by 1,011 publications

(542 citation statements)

References 38 publications

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“…Table 3 shows that all our construct obtained Cronbach"s alpha and Composite Reliability scores above the threshold of 0.70. We assessed construct validity by evaluating convergent validity [42] and discriminant validity [49]. In general, convergent validity is considered acceptable when the Average Variance Extracted (AVE) values successfully exceed the threshold of 0.50 for all constructs [12,19], which indicates that more than 50% of the variance of the measurement items can be accounted for by the constructs [30].…”

Section: Measurement Modelmentioning

confidence: 99%

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The Implications of Trust in the Sharing Economy: An Empirical Analysis of Uber

Mittendorf¹

2017

Proceedings of the Annual Hawaii International Conference on System Sciences

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Section: Measurement Modelmentioning

confidence: 99%

“…Therefore, we could claim convergent validity for our measurement model. Discriminant validity means the degree to which measures of different latent variables are unique [42].…”

Section: Measurement Modelmentioning

confidence: 99%

The Implications of Trust in the Sharing Economy: An Empirical Analysis of Uber

Mittendorf¹

2017

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…Construct Validity is the assessment of the degree to which an operationalization correctly measures its targeted variables. 46 Bentler-Bonett coeffi cient 47 is used to measure Convergent Validity of the model, which is the measure of the degree to which multiple methods of measuring a variable provide the same results. 46 Results from the Table 8 show that all six dimensions have Bentler-Bonett Goodness of Coeffi cient more than 0.90, which is above the required level.…”

Section: Measurement Model Fi Tmentioning

confidence: 99%

Analyzing customer satisfaction with service quality in life insurance services

Siddiqui

Sharma²

2010

J Target Meas Anal Mark

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Life insurance players have started realizing that their business depends on customer service and customer satisfaction. This research, using confi rmatory factor analyses, proposes a six dimensional service-quality instrument consisting of ' assurance ' , ' personalized fi nancial planning ' , ' competence ' , ' corporate image ' , ' tangibles ' and ' technology ' in life insurance. A causal model, using structural equation modeling, is suggested to investigate the effects of the proposed service quality instrument on customer satisfaction ( ' satisfaction with agents ' , ' satisfaction with functional services ' , ' satisfaction with company ' and fi nally with ' overall satisfaction ' ). The proposed framework attempts to provide a blueprint for appropriate course of action (by life insurance service providers) to create a base of satisfi ed customers through quality services.

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“…14 convergent validity and reliability to be assessed. Establishing these properties helps assure researchers and research consumers that the scales actually measure the phenomena that they purport to measure (Churchill, 1979;O'Leary-Kelly and Vokurka, 1998). Several refinements to the scales were made during this process (i.e.…”

Section: Sample Characteristicsmentioning

confidence: 99%

Enterprise resource planning (ERP) systems and the manufacturing–marketing interface: an information-processing theory view

Gattiker

2007

International Journal of Production Research

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This is an electronic version of an article published in Gattiker, TF. (2007). ERP Systems and the manufacturing-marketing interface: An information processing theory view. International Journal of Production Research, 45(13): 2895-2917.. International Journal of Production Research is available online at: http://www.informaworld.com/smpp. DOI: 10.1080/00207540600690511This is an electronic version of an article published in Gattiker, TF. (2007). ERP Systems and the manufacturing-marketing interface: An information processing theory view. AbstractThe manufacturing-marketing (MM) interface has received substantial consideration in the operations management literature; however, relatively little attention has been paid to the role of information systems in facilitating MM integration. As integrated cross-functional systems, enterprise resource planning systems (ERP) are well-suited to provide MM integration. Based on information processing theory, the central proposition of this paper is the greater the interdependence between manufacturing and marketing, the greater the benefit of ERP. Specifically, H1 states that the greater ERP-enabled coordination between manufacturing and marketing, the greater the benefit of ERP to the plant. H2 states that the degree to which ERP-enabled manufacturing-marketing coordination improvements are realized, depends on the amount of interdependence between manufacturing and marketing. Using multiple regression, the model is tested on survey data from 107 manufacturing plants running ERP. The data support H1 and H2. These findings support the general proposition that interdependence between functions is one factor that influences the degree to which organizations reap benefits from their ERP investments. Based on the ERP literature, the model controls for the amount of time that ERP has been running in the plant; This factor was found to be insignificant in the model. However, exploratory analysis finds that time is associated with other ERP benefits.Keywords: Enterprise systems (ERP); Manufacturing-Marketing interface; Interdependence; Information Processing Theory This is an electronic version of an article published in Gattiker, TF. (2007). ERP Systems and the manufacturing-marketing interface: An information processing theory view.

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The empirical assessment of construct validity

Cited by 1,011 publications

References 38 publications

The Implications of Trust in the Sharing Economy: An Empirical Analysis of Uber

The Implications of Trust in the Sharing Economy: An Empirical Analysis of Uber

Analyzing customer satisfaction with service quality in life insurance services

Enterprise resource planning (ERP) systems and the manufacturing–marketing interface: an information-processing theory view

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