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      Unraveling the diverse nature of service quality in a sharing economy : A social exchange theory perspective of Airbnb accommodation

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          Most cited references108

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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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            A power primer.

            One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.
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              Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

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                Author and article information

                Journal
                International Journal of Contemporary Hospitality Management
                Int J Contemp Hospitality Mngt
                Emerald
                0959-6119
                September 11 2017
                September 11 2017
                : 29
                : 9
                : 2279-2301
                Affiliations
                [1 ]Department of Marketing, Branding and Tourism, Middlesex University Business School, London, UK
                [2 ]Department for Marketing, Innovation, Leisure and Enterprise, University of Wolverhampton Business School, Wolverhampton, UK and Department of Management, School of Economics, Finance and Management, University of Bristol, Bristol, UK
                [3 ]Department of Marketing, Innovation, Leisure and Enterprise, University of Wolverhampton, Wolverhampton, UK
                [4 ]Department of International Management and Innovation, Middlesex University, London, UK
                Article
                10.1108/IJCHM-08-2016-0420
                7a1b99d3-7f82-4fc5-8589-6eeaf8c5fb77
                © 2017

                http://www.emeraldinsight.com/page/tdm

                History

                Quantitative & Systems biology,Biophysics
                Quantitative & Systems biology, Biophysics

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