John G. Lynch

Bio: John G. Lynch is an academic researcher from University of Colorado Boulder. The author has contributed to research in topics: Financial literacy & Quality (business). The author has an hindex of 47, co-authored 111 publications receiving 22822 citations. Previous affiliations of John G. Lynch include University of Florida & University of Illinois at Urbana–Champaign.

Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis

Abstract: Baron and Kenny’s procedure for determining if an independent variable affects a dependent variable through some mediator is so well known that it is used by authors and requested by reviewers almost reflexively. Many research projects have been terminated early in a research program or later in the review process because the data did not conform to Baron and Kenny’s criteria, impeding theoretical development. While the technical literature has disputed some of Baron and Kenny’s tests, this literature has not diffused to practicing researchers. We present a nontechnical summary of the flaws in the Baron and Kenny logic, some of which have not been previously noted. We provide a decision tree and a step-by-step procedure for testing mediation, classifying its type, and interpreting the implications of findings for theory building and future research.

Interactive home shopping: Consumer, retailer, and manufacturer incentives to participate in

Abstract: The authors examine the implications of electronic shopping for consumers, retailers, and manufacturers. They assume that near-term technological developments will offer consumers unparalleled opportunities to locate and compare product offerings. They examine these advantages as a function of typical consumer goals and the types of products and services being sought and offer conclusions regarding consumer incentives and disincentives to purchase through interactive home shopping vis-à-vis traditional retail formats. The authors discuss implications for industry structure as they pertain to competition among retailers, competition among manufacturers, and retailer-manufacturer relationships.

Interactive Home Shopping: Consumer, Retailer, and Manufacturer Incentives to Participate in Electronic Marketplaces:

Abstract: The authors examine the implications of electronic shopping for consumers, retailers, and manufacturers. They assume that near-term technological developments will offer consumers unparalleled oppo...

Self-generated validity and other effects of measurement on belief, attitude, intention, and behavior.

Abstract: Drawing from recent developments in social cognition, cognitive psychology, and behavioral decision theory, we analyzed when and how the act of measuring beliefs, attitudes, intentions, and behaviors affects observed correlations among them. Belief, attitude, or intention can be created by measurement if the measured constructs do not already exist in long-term memory. The responses thus created can have directive effects on answers to other questions that follow in the survey. But even when counterparts to the beliefs, attitudes, and intentions measured already exist in memory, the structure of the survey researcher's questionnaire can affect observed correlations among them. The respondent may use retrieved answers to earlier survey questions as inputs to response generation to later questions. We present a simple theory predicting that an earlier response will be used as a basis for another, subsequent response if the former is accessible and if it is perceived to be more diagnostic than other accessible inputs. We outline the factors that determine both the perceived diagnosticity of a potential input, the likelihood that it will be retrieved, and the likelihood that some alternative (and potentially more diagnostic) inputs will be retrieved. This article examines the effects of measurement operations on revealed correlations among survey measures of belief, attitude, intention, and behavior. The potential reactivity of measurement has long been of concern in psychology. Methodologists (e.g., Campbell & Stanley, 1966; Cook & Campbell, 1979; Runkel & McGrath, 1972) warn of measurement-induced distortions relating to social desirability, evaluation apprehension, and sensitization to experimental treatments. Although it is true that the problem of reactivity of measurement affects work in both the social and physical sciences, in the physical sciences, measurement effects are expressed in terms of substantive theory. For instance, Heisenberg's uncertainty principle links basic

Spotlights, Floodlights, and the Magic Number Zero: Simple Effects Tests in Moderated Regression.

Abstract: It is common for researchers discovering a significant interaction of a measured variable X with a manipulated variable Z to examine simple effects of Z at different levels of X. These “spotlight” tests are often misunderstood even in the simplest cases, and it appears that consumer researchers are unsure how to extend them to more complex designs. The authors explain the general principles of spotlight tests, show that they rely on familiar regression techniques, and provide a tutorial demonstrating how to apply these tests across an array of experimental designs. Rather than following the common practice of reporting spotlight tests at one standard deviation above and below the mean of X, it is recommended that when X has focal values, researchers should report spotlight tests at those focal values. When X does not have focal values, it is recommended that researchers report ranges of significance using a version of Johnson and Neyman's test the authors term a “floodlight.”

Conceptualizing, measuring, and managing customer-based brand equity

Abstract: The author presents a conceptual model of brand equity from the perspective of the individual consumer. Customer-based brand equity is defined as the differential effect of brand knowledge on consu...

Sources of Method Bias in Social Science Research and Recommendations on How to Control It

Abstract: Despite the concern that has been expressed about potential method biases, and the pervasiveness of research settings with the potential to produce them, there is disagreement about whether they really are a problem for researchers in the behavioral sciences. Therefore, the purpose of this review is to explore the current state of knowledge about method biases. First, we explore the meaning of the terms “method” and “method bias” and then we examine whether method biases influence all measures equally. Next, we review the evidence of the effects that method biases have on individual measures and on the covariation between different constructs. Following this, we evaluate the procedural and statistical remedies that have been used to control method biases and provide recommendations for minimizing method bias.

Understanding Information Technology Usage: A Test of Competing Models

Abstract: The Technology Acceptance Model and two variations of the Theory of Planned Behavior were compared to assess which model best helps to understand usage of information technology. The models were compared using student data collected from 786 potential users of a computer resource center. Behavior data was based on monitoring 3,780 visits to the resource center over a 12-week period. Weighted least squares estimation revealed that all three models performed well in terms of fit and were roughly equivalent in terms of their ability to explain behavior. Decomposing the belief structures in the Theory of Planned Behavior provided a moderate increase in the explanation of behavioral intention. Overall, the results indicate that the decomposed Theory of Planned Behavior provides a fuller understanding of behavioral intention by focusing on the factors that are likely to influence systems use through the application of both design and implementation strategies.

Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis

Abstract: Baron and Kenny’s procedure for determining if an independent variable affects a dependent variable through some mediator is so well known that it is used by authors and requested by reviewers almost reflexively. Many research projects have been terminated early in a research program or later in the review process because the data did not conform to Baron and Kenny’s criteria, impeding theoretical development. While the technical literature has disputed some of Baron and Kenny’s tests, this literature has not diffused to practicing researchers. We present a nontechnical summary of the flaws in the Baron and Kenny logic, some of which have not been previously noted. We provide a decision tree and a step-by-step procedure for testing mediation, classifying its type, and interpreting the implications of findings for theory building and future research.

Accounting for common method variance in cross-sectional research designs.

Abstract: Cross-sectional studies of attitude-behavior relationships are vulnerable to the inflation of correlations by common method variance (CMV). Here, a model is presented that allows partial correlation analysis to adjust the observed correlations for CMV contamination and determine if conclusions about the statistical and practical significance of a predictor have been influenced by the presence of CMV. This method also suggests procedures for designing questionnaires to increase the precision of this adjustment.