Measurement in marketing

We distinguish three senses of the concept of measurement (measurement as the selection of observable indicators of theoretical concepts, measurement as the collection of data from respondents, and measurement as the formulation of measurement models linking observable indicators to latent factors representing the theoretical concepts), and we review important issues related to measurement in each of these senses. With regard to measurement in the first sense, we distinguish the steps of construct definition and item generation, and we review scale development efforts reported in three major marketing journals since 2000 to illustrate these steps and derive practical guidelines. With regard to measurement in the second sense, we look at the survey process from the respondent's perspective and discuss the goals that may guide participants' behavior during a survey, the cognitive resources that respondents devote to answering survey questions, and the problems that may occur at the various steps of the survey process. Finally, with regard to measurement in the third sense, we cover both reflective and formative measurement models, and we explain how researchers can assess the quality of measurement in both types of measurement models and how they can ascertain the comparability of measurements across different populations of respondents or conditions of measurement. We also provide a detailed empirical example of measurement analysis for reflective measurement models

Analyzing policy capturing data using structural equation modeling for within-subject experiments (SEMWISE)

We present the SEMWISE (structural equation modeling for within-subject experiments) approach for analyzing policy capturing data. Policy capturing entails estimating the weights (or utilities) of experimentally manipulated attributes in predicting a response variable of interest (e.g., the effect of experimentally manipulated market-technology combination characteristics on perceived entrepreneurial opportunity). In the SEMWISE approach, a factor model is specified in which latent weight factors capture individually varying effects of experimentally manipulated attributes on the response variable. We describe the core SEMWISE model and propose several extensions (how to incorporate nonbinary attributes and interactions, model multiple indicators of the response variable, relate the latent weight factors to antecedents and/or consequences, and simultaneously investigate several populations of respondents). The primary advantage of the SEMWISE approach is that it facilitates the integration of individually varying policy capturing weights into a broader nomological network while accounting for measurement error. We illustrate the approach with two empirical examples, compare and contrast the SEMWISE approach with multilevel modeling (MLM), discuss how researchers can choose between SEMWISE and MLM, and provide implementation guidelines

Are There Any Class Size Effects on Early Career Earnings in West Germany?

The paper analyses the effect of class size, which stands proxy for school quality, on early career earnings. Using confidential district level information from the German Socio-Economic Panel (GSOEP), it is demonstrated that class size has no discernible effect on early career earnings. This finding is robust to changes in specification and the choice of sub-samples. The economic literature focused so far mainly on the US and the UK. This paper confirms this literature and adds new evidence to the growing empirical literature on this issue from Germany.School quality; Class size; Labour market outcomes

Reversed item bias: an integrative model

In the recent methodological literature, various models have been proposed to account for the phenomenon that reversed items (defined as items for which respondents' scores have to be recoded in order to make the direction of keying consistent across all items) tend to lead to problematic responses. In this article we propose an integrative conceptualization of three important sources of reversed item method bias (acquiescence, careless responding, and confirmation bias) and specify a multisample confirmatory factor analysis model with 2 method factors to empirically test the hypothesized mechanisms, using explicit measures of acquiescence and carelessness and experimentally manipulated versions of a questionnaire that varies 3 item arrangements and the keying direction of the first item measuring the focal construct. We explain the mechanisms, review prior attempts to model reversed item bias, present our new model, and apply it to responses to a 4-item self-esteem scale (N = 306) and the 6-item Revised Life Orientation Test (N = 595). Based on the literature review and the empirical results, we formulate recommendations on how to use reversed items in questionnaires

Does More Generous Student Aid Increase Enrolment Rates into Higher Education?: Evaluating the German Student Aid Reform of 2001

Students from low-income families are eligible to student aid under the federal students' financial assistance scheme (BAfoeG) in Germany. We evaluate the effectiveness of a recent reform of student aid that substantially increased the amount received by eligible students to raise enrolment rates into tertiary education. We view this reform as a 'natural experiment' and apply the difference-in-difference methodology using a discrete-time hazard rate model to estimate the causal effect on enrolment rates into higher education. We find that the reform had a small positive but statistically insignificant effect on enrolment rates.Educational transitions, educational finance, natural experiment and difference-indifference estimation

Enrolment into Higher Education and Changes in Repayment Obligations of Student Aid – Microeconometric Evidence for Germany.

We evaluate the effect of the federal students’ financial assistance scheme (BAfoeG) on enrolment rates into higher education by exploiting the exogenous variation introduced through a discrete shift in the repayment regulations. Supported students had to repay the full loan until 1990. Thereafter, 50 percent of the student aid has been offered as a non-repayable grant. Our results from simple difference-in- difference estimates suggest that student aid is ineffective in raising enrolment rates. Our findings may have important implications for the current debate on the reform of financing higher education in Germany and elsewhere.educational decision, educational finance, higher education, difference-in-difference, discrete-choice

Turning Unemployment into Self-Employment: Effectiveness and Efficiency of Two Start-Up Programmes

Turning unemployment into self-employment has become a major focus of German active labour market policy (ALMP) in recent years. If effective, this would not only reduce Germany's persistently high unemployment rate, but also increase its notoriously low self-employment rate. Empirical evidence on the effectiveness of such programmes is scarce. The contribution of the present paper is twofold: first, we evaluate the effectiveness of two start-up programmes for the unemployed. Our outcome variables include the probability of being employed, the probability of being unemployed, and personal income. Second, based on the results of this analysis, we conduct an efficiency analysis, i.e., we estimate whether the Federal Employment Agency has saved money by placing unemployed individuals in these programmes. Our results show that at the end of the observation period, both programmes are effective and one is also efficient. The considerable positive effects present a stark contrast to findings from evaluations of other German ALMP programmes in recent years. Hence, ALMP programmes aimed at moving the unemployed into self-employment may prove to be among the most effective, both in Germany and elsewhereStart-up subsidies, evaluation, effectiveness, efficiency, self-employment

The calibrated sigma method : an efficient remedy for between-group differences in response category use on likert scales

The authors propose a procedure, labeled the calibrated sigma method, which is designed to correct for between-group differences in endorsement likelihood of response categories that are unrelated to the content of the items. The method is especially useful in cross-cultural research where group differences may reflect variation in scale usage rather than substantive differences. However, the procedure is also relevant in other situations, for example, when different data collection modes or different experimental manipulations affect respondents’ perception of the meaning of the scale labels. The calibrated sigma method uses information derived from heterogeneous control items (calibration items) to reweight the responses to substantive items in a group-specific way. The advantages of the calibrated sigma method are that it avoids the arbitrariness in the assignment of particular numerical values to response categories; that it is compatible with the linear model, which is used by most marketing researchers; and that it does not require the use of complex nonlinear models involving the estimation of many additional measurement model parameters. The authors validate the calibrated sigma method on a simulated cross-linguistic data set pertaining to 12 different languages; an empirical data set collected from respondents of the same nationality but from two different language groups; and an experimental data set consisting of responses to two different response scale formats. The findings demonstrate that the proposed procedure controls for artefactual scale use differences across groups but does not eliminate substantive differences. It is particularly efficient for marketing research agencies, panel providers and other marketing researchers who analyze surveys involving multiple language groups, different scale formats, multiple modes of data collection, or different manipulations affecting the meaning of the response category labels