The potential for biased responses that occur when researchers interact with their study participants has long been of interest to both academicians and practitioners. Given the sensitive nature of the field, researcher interaction biases are of particular concern for business ethics researchers regardless of their preference for survey, experimental, or qualitative methodology. Whereas some ethics researchers may inadvertently bias data by misrecording or misinterpreting responses, other biases may occur when study participants' responses are systematically influenced by the mere introduction of (...) researchers into the participants' environment. Although substantial empirical research has been conducted on the general topic of researcher interaction biases, none has focused specifically on business ethics research. In order to remedy this lack of empirical substantiation in the field, we review the related literature on researcher interaction biases, present an empirical example of how such biases can influence research results in an experiment assessing reactions to insurance fraud, and discuss the implications for business ethics research. (shrink)

Sections include: experiments and generalised causal inference; statistical conclusion validity and internal validity; construct validity and external validity; quasi-experimental designs that either lack a control group or lack pretest observations on the outcome; quasi-experimental designs that use both control groups and pretests; quasi-experiments: interrupted time-series designs; regresssion discontinuity designs; randomised experiments: rationale, designs, and conditions conducive to doing them; practical problems 1: ethics, participation recruitment and random assignment; practical problems 2: treatment implementation and attrition; generalised causal inference: a grounded theory; (...) generalised causal inference: methods for single studies; generalised causal inference: methods for multiple studies; a critical assessment of our assumptions. (shrink)