Non-Response Error within Internet Surveys: A Cautionary Note

The use of the internet as a method to conduct survey research has expanded rapidly over the past decade. High speeds of response and lower expenses have driven this rapid growth. Relatively low response rates, however, suggest online surveys may be compromised by high levels of non-sampling error. This paper examines a major component of non-sampling error and the consequences that may be associated with internet survey non-response. Known population parameters are compared to point estimates from a census as well as a random sample of non-respondents in order to provide insight on the magnitude and direction of nonresponse error. Issue salience and response latency are found to exhibit a significant relationship to self-selection and response valance biases. Specifically, lower rates of nonresponse were obtained from respondents who perceived the topic of the survey as more important and patterns of response were more favorable among initial study participants

Comparison of rating scales for measuring attitudes

Se han comparado cinco versiones simplificadas del Diferencial Semántico Clásico para la evaluación subjetiva de objetos. Todas las versiones han resultado ser altamente fiables y comprensibles para el sujeto experimental. El tiempo invertido en la realización de las tareas también ha resultado ser semejante en todas las versiones. Todas las versiones investigadas constituyen, por tanto, una alternativa importante al Diferencial Semántico Clásico, sobre todo, en su vertiente aplicada, siendo muchos los investigadores que pueden beneficiarse de su utilidadFive simplified versions of Classic Semantic Differential for the subjective evaluation of objects were compared. All the versions were shown to be highly reliable and comprehensible to the experimental subject. The time to complete the tasks was also shown to be similar for all the versions. Therefore, all the versions under study are an important alternative to the Classic Semantic Differential, mainly in their applied aspect, and many researchers may benefit from their usefulnessEsta investigación se ha realizado con el apoyo económico de la Consellería de Educación y Ordenación Universitaria, de la Xunta de Galicia (PROY94-143, XUGA 21102A94)S

Antecedents of the attraction effect: An information-processing approach

This is the published version. Copyright 1993 American Marketing Association.Many researchers have demonstrated the existence of an attraction effect that increases the choice probability of an existing target brand by the introduction of a relatively inferior decoy brand. A causal model that links antecedent variables with the attraction effect is developed. It is found that the attraction effect is explained to a considerable extent by changes in the following 7 variables: 1. information relevance or stimulus meaningfulness, 2. product class knowledge, 3. task involvement, 4. perceived similarity between decoy and target, 5. relative brand preference, 6. share captured by decoy brand, and 7. perceived decoy popularity. The overall results were consistent across product classes studied, which included beer, cars, and television sets. The popularity explanation for attraction effect, alluded to by Huber, Payne, and Puto (1982), was tested and found to hold true

Comparación de escalas de respuesta para la medición de las actitudes

Se han comparado cinco versiones simplificadas del Diferencial Semántico Clásico para la evaluación subjetiva de objetos. Todas las versiones han resultado ser altamente fiables y comprensibles para el sujeto experimental. El tiempo invertido en la realización de las tareas también ha resultado ser semejante en todas las versiones. Todas las versiones investigadas constituyen, por tanto, una alternativa importante al Diferencial Semántico Clásico, sobre todo, en su vertiente aplicada, siendo muchos los investigadores que pueden beneficiarse de su utilida