http://repub.eur.nl/res/aut/154/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/40379/ 2013-05-31T00:00:00Z Surveys are widely used by scholars, companies, and public policymakers to generate invaluable insights. Despite the popularity of surveys, there are several biases that can affect the validity of self-reported data. In his inaugural address, Martijn de Jong discusses how new survey methods can help to extract valid information from surveys. Several examples are presented that showcase the relevance of better research design and careful statistical modeling of the response process. In addition, De Jong addresses some commonly held perceptions about the ability to make causal inferences with survey data. http://repub.eur.nl/res/pub/37425/ 2012-10-01T00:00:00Z In recent years academic research has focused on understanding and modeling the survey response process. This paper examines an understudied systematic response tendency in surveys: the extent to which observed responses are subject to state dependence, i.e., response carryover from one item to another independent of specific item content. We develop a statistical model that simultaneously accounts for state dependence, item content, and scale usage heterogeneity. The paper explores how state dependence varies by response category, item characteristics, item sequence, respondent characteristics, and whether it becomes stronger as the survey progresses. Two empirical applications provide evidence of substantial and significant state dependence. We find that the degree of state dependence depends on item characteristics and item sequence, and it varies across individuals and countries. The article demonstrates that ignoring state dependence may affect reliability and predictive validity, and it provides recommendations for survey researchers. http://repub.eur.nl/res/pub/37935/ 2012-09-01T00:00:00Z Answers to sensitive questions are prone to social desirability bias. If not properly addressed, the validity of the research can be suspect. This article presents multigroup item randomized response theory (MIRRT) to measure self-reported sensitive topics across cultures. The method was specifically developed to reduce social desirability bias by making an a priori change in the design of the survey. The change involves the use of a randomization device (e.g., a die) that preserves participants' privacy at the item level. In cases where multiple items measure a higher level theoretical construct, the researcher could still make inferences at the individual level. The method can correct for under- and overreporting, even if both occur in a sample of individuals or across nations. We present and illustrate MIRRT in a nontechnical manner, provide WinBugs software code so that researchers can directly implement it, and present 2 cross-national studies in which it was applied. The first study compared nonstudent samples from 2 countries (total n = 927) on permissive sexual attitudes and risky sexual behavior and related these to individual-level characteristics such as the Big Five personality traits. The second study compared nonstudent samples from 17 countries (total n = 6,195) on risky sexual behavior and related these to individual-level characteristics, such as gender and age, and to country-level characteristics, such as sex ratio. http://repub.eur.nl/res/pub/31358/ 2012-02-01T00:00:00Z We develop and test an incentive-compatible Conjoint Poker (CP) game. The preference data collected in the context of this game are comparable to incentive-compatible choice-based conjoint (CBC) analysis data. We develop a statistical efficiency measure and an algorithm to construct efficient CP designs. We compare incentive-compatible CP to incentive-compatible CBC in a series of three experiments (one online study and two eye-tracking studies). Our results suggest that CP induces respondents to consider more of the profile-related information presented to them compared with CBC. http://repub.eur.nl/res/pub/20878/ 2010-11-01T00:00:00Z n this article, the authors introduce attitude toward global products (AGP) and attitude toward local products (ALP) as generalized attitudinal constructs and address the four issues these constructs raise: (1) How are AGP and ALP related to each other? (2) What is the motivational structure underlying AGP and ALP? (3) Is the proposed theory culturally circumscribed, or does it generalize across countries? and (4) What are the managerially relevant implications of these consumer attitudes? To answer these questions, the authors propose and empirically test an integrated structure for AGP and ALP and their antecedents, organized around the powerful motivational concept of values. They test their theory using a unique data set involving 13,000 respondents from 28 countries in the Americas, Asia, and Europe, thus allowing for a global investigation of a global issue. The study findings provide managers with strategic direction on how to market their products in a globalized world. http://repub.eur.nl/res/pub/19516/ 2010-04-01T00:00:00Z Socially desirable responding (SDR) has been of long-standing interest to the field of marketing. Unfortunately, the construct has not always been well understood by marketing researchers. The authors provide a review of the SDR literature organized around three key issues—the conceptualization and measurement of SDR; the nomological constellation of personality traits, values, sociodemographics, and cultural factors associated with SDR; and the vexing issue of substance versus style in SDR measures. The authors review the current “state of the literature,” identify unresolved issues, and provide new empirical evidence to assess the generalizability of existing knowledge, which is disproportionately based on U.S. student samples, to a global context. The new evidence is derived from a large international data set involving 12,424 respondents in 26 countries on four continents. http://repub.eur.nl/res/pub/19508/ 2010-02-01T00:00:00Z The authors present a polytomous item randomized response model to measure socially sensitive consumer behavior. It complements established methods in marketing to correct for social desirability bias a posteriori and traditional randomized response models to prevent social desirability bias a priori. The model allows for individual-level inferences at the construct level while protecting the privacy of respondents at the item level. In addition, it is possible to incorporate covariates into various parts of the model. The proposed method is especially useful to study social issues in marketing. In the empirical application, the authors use a twogroup experimental survey design and find that with the new procedure, participants report their sensitive desires more truthfully, with significant differences between socioeconomic groups. In addition, the method performs better than methods based on social desirability scales. Finally, the authors discuss truthfulness in data collection and confidentiality in data utilization. http://repub.eur.nl/res/pub/16847/ 2009-07-01T00:00:00Z In the last few decades, the measurement of marketing constructs has improved tremendously. Our discipline has also started to systematically catalogue our measurement knowledge in influential handbooks of marketing scales. However, at least two important issues remain. First, existing scales are often too long for administration in nonstudent samples or in applied studies. Second, existing (U.S.-developed) scales may contain items that are not informative about the underlying construct in particular countries, whereas relevant items tapping into local cultural expressions of the construct in question may be missing. To address these issues, we propose a new model that yields country-specific yet fully cross-nationally comparable short forms of unidimensional marketing scales. The procedure is based on hierarchical item response theory and optimal test design. The procedure is flexible in the sense that the researcher can specify various constraints on item content, scale length, and measurement precision. Because our procedure allows inclusion of country-specific (or "emic") items in standardized (or "etic") scales, it presents an important step toward resolving the emic-etic dilemma that has plagued international marketing research for decades. http://repub.eur.nl/res/pub/16806/ 2009-01-01T00:00:00Z We present a class of finite mixture multilevel multidimensional ordinal IRT models for large scale cross-cultural research. Our model is proposed for confirmatory research settings. Our prior for item parameters is a mixture distribution to accommodate situations where different groups of countries have different measurement operations, while countries within these groups are still allowed to be heterogeneous. A simulation study is conducted that shows that all parameters can be recovered. We also apply the model to real data on the two components of affective subjective well-being: positive affect and negative affect. The psychometric behavior of these two scales is studied in 28 countries across four continents. http://repub.eur.nl/res/pub/13593/ 2008-02-01T00:00:00Z Extreme response style (ERS) is an important threat to the validity of survey-based marketing research. In this article, the authors present a new item response theorybased model for measuring ERS. This model contributes to the ERS literature in two ways. First, the method improves on existing procedures by allowing different items to be differentially useful for measuring ERS and by accommodating the possibility that an item's usefulness differs across groups (e.g., countries). Second, the model integrates an advanced item response theory measurement model with a structural hierarchical model for studying antecedents of ERS. The authors simultaneously estimate a person's ERS score and individual- and group-level (country) drivers of ERS. Through simulations, they show that the new method improves on traditional procedures. They further apply the model to a large data set consisting of 12,506 consumers from 26 countries on four continents. The findings show that the model extensions are necessary to model the data adequately. Finally, they report substantive results about the effects of sociodemographic and national-cultural variables on ERS. http://repub.eur.nl/res/pub/11483/ 2007-06-01T00:00:00Z Customer Lifetime Value (CLV) is one of the key metrics in marketing and is considered an important segmentation base. This paper studies the capabilities of a range of models to predict CLV in the insurance industry. The simplest models can be constructed at the customer relationship level, i.e. aggregated across all services. The more complex models focus on the individual services, paying explicit attention to cross buying, but also retention. The models build on a plethora of approaches used in the existing literature and include a status quo model, a Tobit II model, univariate and multivariate choice models, and duration models. For all models, CLV for each customer is computed for a four-year time horizon. We find that the simple models perform well. The more complex models are expected to better capture the richness of relationship development. Surprisingly, this does not lead to substantially better CLV predictions. http://repub.eur.nl/res/pub/325/ 2003-04-29T00:00:00Z Customer lifetime value (CLV) is a key-metric within CRM. Although, a large number of marketing scientists and practitioners argue in favor of this metric, there are only a few studies that consider the predictive modeling of CLV. In this study we focus on the prediction of CLV in multi-service industries. In these industries customer behavior is rather complex, because customers can purchase more than one service, and these purchases are often not independent from each other. We compare the predictive performance of different models, which vary in complexity and realism. Our results show that for our application simple models assuming constant profits over time have the best predictive performance at the individual customer level. At the customer base level more complicated models have the best performance. At the aggregate level, forecasting errors are rather small, which emphasizes the usability of CLV predictions for customer base valuation purposes. This might especially be interesting for accountants and financial analysts.