Contributions published at Marketing and Market Research (René Algesheimer)

While multiple-country repeated cross-sectional datasets are increasingly available, few cross-national studies fully exploit the richness of such data. This paper contributes to the practical knowledge on statistical analysis of cross-national time series data. For that purpose, we present a novel application of a societal growth curve model (Fairbrother, 2014) analyzing the pressing question whether the economic crisis of the past years has stirred up immigration-related threat perceptions among European citizens. Concretely, we analyze six rounds of European Social Survey data (2002-2012) to investigate whether indicators of economic downturn are systematically related to increased levels of economic and cultural threat. The societal growth curve modeling approach makes it possible to set longitudinal effects apart from cross-sectional differences and thus overcomes the weaknesses of analyses relying on single-shot cross-sectional data. Our results provide evidence that growing unemployment as well as decreasing rates of economic growth instigate feelings of economic threat. Rather than affecting citizens’ opinion uniformly, the economic crisis is found to have the strongest impact on economic threat among low educated people. While this study provides evidence that economic shocks affect concerns that immigration is bad for the economy, feelings of cultural threat are not affected by economic crises.

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Multiple group confirmatory factor analysis has become the most common technique for assessing measurement invariance. However, higher-order factor modeling is less frequently discussed in this context. In particular, the literature provides only very general guidelines for testing measurement invariance of second-order factor models, which is a prerequisite for conducting meaningful comparative research using higher-order factors. The current paper attempts to fill this gap. First, we explicate the constraints required for identification of the invariance levels in a multiple group second-order factor model. Second, in addition to the conventional interpretation of the results of this assessment, we suggest an alternative view on the invariance properties of a second-order factor as evidence of structural rather than measurement invariance. Third, we present an empirical application of the test which builds on Seeman’s alienation scale and utilizes data from eight countries collected in 2008-2009. We found empirical support for metric invariance of both the firstand second-order factors, but no support for scalar invariance of the first- and second-order factors. However, we find pairs of countries where scalar invariance for both the first- and second-order factors is supported by the data. We finalize with a discussion of the results and their interpretation.

The 7th round of the European Social Survey (ESS) from 2014-15 includes a partial repetition of the immigration module from the first ESS wave (2002-03) with information on individual attitudes toward immigration and immigrants in both old and new immigration societies. The goal of the present study is to test whether and to what extent questions in the module are equivalent across ESS countries. We performed two types of measurement equivalence tests: exact and approximate. Whereas the exact approach requires that measurement parameters are exactly equal across groups, the approximate and newer approach suggests that it is sufficient that measurement parameters are approximately equal to allow a meaningful comparison across groups. Our findings suggest that two measurement scales, allowing immigrants into the country and realistic threat, are approximately invariant across most ESS countries.

Objective The Mental Health Continuum-Short Form (MHC-SF) is a brief scale measuring positive human functioning. The study aimed to examine the factor structure and to explore the cross-cultural utility of the MHC-SF using bifactor models and exploratory structural equation modelling. Method Using multigroup confirmatory analysis (MGCFA) we examined the measurement invariance of the MHC-SF in 38 countries (university students, N = 8,066; 61.73% women, mean age 21.55 years). Results MGCFA supported the cross-cultural replicability of a bifactor structure and a metric level of invariance between student samples. The average proportion of variance explained by the general factor was high (ECV = .66), suggesting that the three aspects of mental health (emotional, social, and psychological well-being) can be treated as a single dimension of well-being. Conclusion The metric level of invariance offers the possibility of comparing correlates and predictors of positive mental functioning across countries; however, the comparison of the levels of mental health across countries is not possible due to lack of scalar invariance. Our study has preliminary character and could serve as an initial assessment of the structure of the MHC-SF across different cultural settings. Further studies on general populations are required for extending our findings.

This research is the first to assess directly Schwartz’s claim that the circular structure of values derives from value compatibilities or conflicts experienced in real-time behaviors. We differentiate two types of values: value traits guide perception and behavior over time and situations and value states guide real-time behavioral acts. We measured the value states of 374 participants for 13,873 behavioral acts with experience sampling, distinguishing volitional from non-volitional acts. As hypothesized, value states for volitional acts, but not for non-volitional acts reproduced the circular value structure. The importance hierarchies of value states differed substantially from the importance hierarchy of value traits, suggesting that the importance of value states depends more on situations than on the hierarchy of value traits.

It is necessary to test for equivalence of measurements across groups to guarantee that comparisons of regression coefficients or mean scores of a latent factor are meaningful. Unfortunately, when tested, many scales display nonequivalence. Several researchers have suggested that nonequivalence may be used as a useful source of information as to why equivalence is biased and proposed employing a multilevel structural equation modeling (MLSEM) approach to explain why equivalence is not given. This method can consider a latent between-level factor and/or single contextual variables and use them to explain items’ nonequivalence. In the current study, we show that this method may also be useful for social science studies in general and for survey research and sociological comparative studies in particular when one fails to establish cross-group equivalence. We utilize data from the International Social Survey Program national identity module (2003) to test for the cross-country equivalence of a scale measuring attitudes toward granting citizenship rights to immigrants. As expected, the scale fails to achieve scalar equivalence. However, we explain a significant part of the most nonequivalent intercept by a latent between-level factor and one contextual variable, namely, the percentage of foreigners in the country relying on group threat theory. We show that the method does not necessarily rectify nonequivalence, but it can help to explain why it is absent.

We offer a new conceptualization and measurement models for constructs at the group-level of analysis in small group research. The conceptualization starts with classical notions of group behavior proposed by Tönnies, Simmel, and Weber and then draws upon plural subject theory by philosophers Gilbert and Tuomela to frame a new perspective applicable to many forms of small group behavior. In the proposed measurement model, a collective property is operationalized as shared interpersonal action that explicitly allows us to control for systematic (method) error and random error. Group members act as key-informants of group properties and processes and are treated as methods in a multi-trait multi-method setting to validate our models. The models are applied to empirical data of 277 three-person groups to develop and illustrate new procedures for ascertaining variation in measures due to hypothesized construct(s), method error, and random error. Implications and guidelines for small group research are discussed.

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It has been acknowledged that social influence affects the adoption and repurchase decision of products. The author suggests social influence on repeat service usage. Obviously, own experience of customers impacts the repeat purchase decisions. However, customers also get inspiration for their decisions from their social contacts. Thus, a customer’s social network is likely to play a role in repeat purchase decisions. In this thesis the repeat purchase behavior of a Video-On-Demand service is analyzed. A customer’s individual social networks were created based on communication data from a European telecommunication provider. The results show, that social influence from network neighbors affects customers’ repurchase probability, after controlling for a set of traditional repeat purchase drivers. Furthermore, the nature of social influence is subject to different social mechanisms, namely to normative pressure and social learning. These findings highlight social influence as a repeat purchase driver in service context and pave the way for further investigation. Keywords: repeat purchase, social influence, social networks, normative pressure, social learning, service

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