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      Impact of ambidexterity of blockchain technology and social factors on new product development: A supply chain and Industry 4.0 perspective

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      Technological Forecasting and Social Change
      Elsevier BV

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          Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives

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            Common method biases in behavioral research: A critical review of the literature and recommended remedies.

            Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.
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              Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Technological Forecasting and Social Change
                Technological Forecasting and Social Change
                Elsevier BV
                00401625
                August 2021
                August 2021
                : 169
                : 120819
                Article
                10.1016/j.techfore.2021.120819
                26d97c71-1502-458a-8582-c0149fd1ee02
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

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