Reasons for researchers regressing to unethical behaviour³¹

For reasons of time, convenience and cost, online channels have become the dominant in many areas of marketing research. It has been recognised for some time that the research community needs a coherent ethical code of practice to guide research activities conducted online. Many online researchers are distressed at the manner in which some researchers abuse the internet as a means of collecting data. In particular, marketing research has been charged with engaging in deception, conflict of interest, violation of anonymity, invasion of privacy, data falsifications, dissemination of faulty research findings and the use of research as a guise to sell merchandise. It has been posited that when a researcher chooses to participate in unethical activities, that decision may be influenced by organisational factors. Therefore, a study using multiple regression analysis was designed to examine organisational factors as determinants of the incidence of unethical research practices. Six organisational variables were used as the independent variables, namely: extent of ethical problems within the organisation; top management actions on ethics; code of ethics; organisational rank; industry category; and organisational role. The participant’s evaluation of the incidence of unethical marketing research practices served as the dependent variable. Regression analysis of the data suggested that four of the six organisational variables influenced the extent of unethical research practice: extent of ethical problems within the organisation; top management actions on ethics; industry category; and organisational role. Thus, to reduce the incidence of unethical research practice, top management should take stern actions, clarify roles and responsibilities for ethical violations and address the extent of general ethical problems within the organisation.

In a survey pre-test, data were obtained from 20 participants on preference for boots () on a seven-point scale (1 = not preferred, 7 = greatly preferred). The participants also provided their evaluations of the boots on comfort (), style () and durability (), also on seven-point scales (1 = poor, 7 = excellent). The resulting data are given in the following table:

a Calculate the simple correlations between V₁ and V₄ and interpret the results.

b Run a bivariate regression with preference for boots (V₁) as the dependent variable and evaluation on comfort (V₂) as the independent variable. Interpret the results.

c Run a bivariate regression with preference for boots (V₁) as the dependent variable and evaluation on style (V₃) as the independent variable. Interpret the results.

d Run a bivariate regression with preference for boots (V₁) as the dependent variable and evaluation on durability (V₄) as the independent variable. Interpret the results.

e Run a multiple regression with preference for boots (V₁) as the dependent variable and V₂ to V₄ as the independent variables. Interpret the results. Compare the coefficients for V₂, V₃ and V₄ obtained in the bivariate and the multiple regressions.