Contributions published at Marketing and Market Research (René Algesheimer)

Digitalization allows retailers to target customers with personalized promotions when they enter the store. Although traditional promotional retailer objectives, such as store visit, become obsolete once the shopper is already in the store, retailers still tend to target customers based on indicators that drive store visit, such as recency, frequency, and monetary value (RFM). In order to improve promotional efficiency, the authors propose targeting shoppers based on information derived from regularity patterns in individual interpurchase times at the point of sale. When compared to RFM-based targeting, the proposed live targeting approach translates into higher redemption rates (+ 10.5 percentage points), revenues (+ 42.3 percentage points), and purchase frequencies (+ 44.2 percentage points). The findings emphasize the importance of promotional timing and of considering customers’ outside potential for dynamic in-store targeting.

Welzel et al. (2021) claim that non-invariance of instruments is inconclusive and inconsequential in the field for cross-cultural value measurement. In this response, we contend that several key arguments on which Welzel et al. (2021) base their critique of invariance testing are conceptually and statistically incorrect. First, Welzel et al. (2021) claim that value measurement follows a formative rather than reflective logic. Yet they do not provide sufficient theoretical arguments for this conceptualization, nor do they discuss the disadvantages of this approach for validation of instruments. Second, their claim that strong inter-item correlations cannot be retrieved when means are close to the endpoint of scales ignores the existence of factor-analytic approaches for ordered-categorical indicators. Third, Welzel et al. (2021) propose that rather than of relying on invariance tests, comparability can be assessed by studying the connection with theoretically related constructs. However, their proposal ignores that external validation through nomological linkages hinges on the assumption of comparability. By means of two examples, we illustrate that violating the assumptions of measurement invariance can distort conclusions substantially. Following the advice of Welzel et al. (2021) implies discarding a tool that has proven to be very useful for comparativists.

We propose a model of basic self-regulatory mechanisms that integrates descriptive-structural and dynamic-explanatory approaches to personality. Using a structural way of thinking and based on a structural model of personality (the Circumplex of Personality Metatraits), we deduced two orthogonal (distinct) but interactive mechanisms: (a) Impulse Control responsible for controlling automatically activated impulses, urges, and affective reactions and (b) Self-Motivation responsible for regulating intentions in goal-oriented behaviors. Their operation depends on both situational and dispositional factors and optimal functioning of both mechanisms is needed for effective regulation of behavior. People can also be characterized by relatively stable levels of Impulse Control and Self-Motivation as dispositions, which depend on temperamental predispositions but can develop incoherently with them due to the impact of environmental factors. Combinations of Impulse Control and Self-Motivation as dispositions result in personality types, which differ in their adaptiveness. Importantly, Impulse Control and Self-Motivation mechanisms reveal substantial similarities to other self-regulatory constructs described in the literature, particularly those included in Block and Block's as well as Kuhl's theories. The contribution of our paper may serve as an example of how to apply the descriptive-structural approach to develop a dynamic-explanatory model of personality.

A key element to understand complex systems is the relationship between the spatial scale of investigation and the structure of the interrelation among its elements. When it comes to economic systems, it is now well-known that the country-product bipartite network exhibits a nested structure, which is the foundation of different algorithms that have been used to scientifically investigate countries' development and forecast national economic growth. Changing the subject from countries to companies, a significantly different scenario emerges. Through the analysis of a unique dataset of Italian firms' exports and a worldwide dataset comprising countries' exports, here we find that, while a globally nested structure is observed at the country level, a local, in-block nested structure emerges at the level of firms. This in-block nestedness is statistically significant with respect to suitable null models and the algorithmic partitions of products into blocks correspond well with the UN-COMTRADE product classification. These findings lay a solid foundation for developing a scientific approach based on the physics of complex systems to the analysis of companies, which has been lacking until now.

Objective We examined changes in value interrelations during middle childhood. In line with the Personal Values Theory, we expected a value system, with individuals similarly valuing related motivations, and setting priorities between conflicting motivations. We hypothesized this system to develop dynamically during middle childhood as children deepen their understanding of their own values. Method Using unfolding analysis, we estimated intraindividual value structure coherence, that is, the extent to which the interrelations among a child's values are similar to the hypothesized interrelations. Cross-Cultural Study 1 (N = 4615, 6–12-year-old children) included children from 12 countries. Cross-Sequential Study 2 (N = 629, 6–10-year-old children at Time 1) included three annual measurements. Results In Study 1, we found a curvilinear association between age and intraindividual value structure coherence: Children's values were more coherent at ages 9–10 than before or after. Study 2 confirmed this pattern of within-individual development. Conclusions We propose that development in coherence with the theoretical value structure offers insight into children's understanding of values as well as changes in value priorities.

Affect is involved in many psychological phenomena, but a descriptive structure, long sought, has been elusive. Valence and arousal are fundamental, and a key question–the focus of the present study–is the relationship between them. Valence is sometimes thought to be independent of arousal, but, in some studies (representing too few societies in the world) arousal was found to vary with valence. One common finding is that arousal is lowest at neutral valence and increases with both positive and negative valence: a symmetric V-shaped relationship. In the study reported here of self-reported affect during a remembered moment (N = 8,590), we tested the valence-arousal relationship in 33 societies with 25 different languages. The two most common hypotheses in the literature–independence and a symmetric V-shaped relationship–were not supported. With data of all samples pooled, arousal increased with positive but not negative valence. Valence accounted for between 5% (Finland) and 43% (China Beijing) of the variance in arousal. Although there is evidence for a structural relationship between the two, there is also a large amount of variability in this relation.

This review summarizes the current state of the art of statistical and (survey) methodological research on measurement (non)invariance, which is considered a core challenge for the comparative social sciences. After outlining the historical roots, conceptual details, and standard procedures for measurement invariance testing, the paper focuses in particular on the statistical developments that have been achieved in the last 10 years. These include Bayesian approximate measurement invariance, the alignment method, measurement invariance testing within the multilevel modeling framework, mixture multigroup factor analysis, the measurement invariance explorer, and the response shift-true change decomposition approach. Furthermore, the contribution of survey methodological research to the construction of invariant measurement instruments is explicitly addressed and highlighted, including the issues of design decisions, pretesting, scale adoption, and translation. The paper ends with an outlook on future research perspectives.

Borderline personality disorder is characterized by considerable heterogeneity. The present studies attempt to describe this heterogeneity by locating the borderline construct and its facets in the overall personality structure within the Circumplex of Personality Metatraits and by using the pathological personality traits of the ICD-11. Two studies were conducted with adults – a non-clinical group and a clinical group. It turned out that two facets of the borderline can be differentiated: the Borderline Internalizing Facet and Borderline Externalizing Facet, which have distinct personality underpinnings. General borderline was explained by Negative affectivity, Dissociality, Disinhibition and Detachment. At the facet level, the Borderline Internalizing Facet was mainly explained by Negative affectivity and Detachment, while the Borderline Externalizing Facet was explained by Disinhibition and Dissociality. Moreover, in both groups the general borderline was located close to Alpha-Minus (between Alpha-Minus and Gamma-Minus in the non-clinical group and between Alpha-Minus and Delta-Minus in the clinical group) and the Borderline Internalizing Facet and the Borderline Externalizing Facet were located on both sides of the general borderline. The results of our research revealed broader personality underpinnings of borderline personality disorder and distinct personality underpinnings of its facets.

Artificial intelligence (AI) enables corporate communicators to effectively reach stakeholders through the systematic collection of information, identification of patterns, and prediction of future behaviours. Voice assistants (VAs) such as Amazon Alexa and Google Home represent the fastest-growing AI-based technology across diverse geographical regions and languages. Such emerging voice-enabled agents offer novel communication and relational opportunities within, between, and beyond organisations. Following this rapid diffusion, many companies are launching voice-based initiatives driven by digital corporate communication (DCC) objectives. However, the unique characteristics of voice are likely to challenge traditional DCC principles. Drawing on in-depth interviews and rich archival data, this research introduces the digital voice communication (DVC) framework showing (i) how voice-based corporate communication initiatives generate value for organisations and (ii) how corporate communication, marketing, and commerce goals converge in the voice environment. Furthermore, this chapter critically examines the changes introduced by VAs while discussing threats and opportunities for organisations.

Research on key determinants of negative attitudes toward immigration has often suggested that values held by individuals systematically explain such sentiments. Universalists appear to have more positive and conservatives more negative attitudes. So far, however, these insights are based on studies using adult samples. In our study, we analyze these relations among children and adolescents. For the analysis, we utilized a Swiss-Polish panel dataset (2015–2017, N = 5,332) with three time points collected among school children aged 8–19 years. We employed autoregressive cross-lagged models. The results indicated that while universalism decreased negative attitudes toward immigrants, the expected effect for conformity-tradition was not found.

Studying networked systems in a variety of domains, including biology, social science and internet of things, has recently received a surge of attention. For a networked system, there are usually multiple types of interactions between its components, and such interaction type information is crucial since it always associated with important features. However, some interaction types which actually exist in the network may not be observed in the metadata collected in practice. This paper proposes an approach aiming to detect previously undiscovered interaction types (PUITs) in networked systems. The first step in our proposed PUIT detection approach is to answer the following fundamental question: is it possible to effectively detect PUITs without utilizing metadata other than the existing incomplete interaction type information and the connection information of the system? Here, we first propose a temporal network model which can be used to mimic any real network and then discover that some special networks which fit the model shall a common topological property. Supported by this discovery, we finally develop a PUIT detection method for networks which fit the proposed model. Both analytical and numerical results show this detection method is more effective than the baseline method, demonstrating that effectively detecting PUITs in networks is achievable. More studies on PUIT detection are of significance and in great need since this approach should be as essential as the previously undiscovered node type detection which has gained great success in the field of biology.

Addressing the demands of our aging society, technologies such as smart home systems enhance older adults' independence and enable them to live longer at home. Yet, older adults tend to avoid, delegate, or defer decisions, and smart home systems are rarely used by individuals over the age of 65. Drawing on research on choice overload and age labels, we investigate across four studies how the presentation of smart home systems can influence the decision-making process of older adults ages 65+ by mitigating choice complexity and, consequently, choice avoidance. We argue that age-framing of complex systems makes the choice options easier to process for older adults than does price-framing, the current market standard. We find that age-framing positively affects the rate of choice, and we identify reduced choice complexity as the underlying process. Our research further demonstrates that family members, as important co-deciders, evaluate decisions made on age-framed alternatives more positively, thus making it easier for older adults to justify their decisions. We thus contribute to research on the decision-making of older adults in general and on age labels in particular, and we identify important practical implications for providers of high investment products for older adults.

Recent literature on narcissism argues that there are three factors covering the construct: agentic, antagonistic, and neurotic. Within the current study, we aim to (a) empirically test whether this hypothesized structure reproduces using, for the first time, network psychometrics with eight distinct narcissism measures as well as reanalysing data from eleven narcissism measures from Crowe et al. (2019) and (b) scrutinize the personality underpinnings of the differentiated facets through the lens of the circumplex of personality metatraits (CPM) model. Within the study, N = 465 Polish adults were administered eight distinct narcissism measures, comprising 13 scales capturing different aspects of narcissistic personality and a measure of personality metatraits. Results revealed that the three-factor structure reproduces well in the network approach across both data sets. The circumplex analyses provided further evidence for the personality underpinnings of the three factors. We discuss the role of pathological narcissism within the three-factor conceptualization of narcissism. Findings of the current article facilitate the understanding of narcissistic personality

Delegation is an important part of organizational success and can be used to overcome personal shortcomings and draw upon the expertise and abilities of others. However, delegation comes with risks and uncertainties, as it entails a transfer of power and loss of control. Indeed, research has documented that people tend to under-delegate to other humans, often leading to poor decisions and ultimately negative economic consequences. Today, however, people are faced with a new delegation choice: Artificial Intelligence (AI). Fueled by Big Data, AI is rapidly becoming more intelligent and frequently outperforming human forecasters and decision-makers. Given this evolution of computational autonomy, researchers need to revisit the hows and whys of decision delegation and clarify not only whether people are willing to cede control to AI agents but also whether AI can reduce the under-delegation that is especially pronounced when people are faced with decisions that spur a high desire for control. By linking research on decision delegation, social risk, and control premium to the emerging field of trust in AI, we propose and find that people prefer to delegate decisions to AI as compared to human agents, especially when decisions entail losses (Studies 1–3). Results further illuminate the underlying psychological process involved (Study 1 and 2) and show that process transparency increases delegation to humans but not to AI (Study 3). These findings have important implications for research on trust in AI and the applicability of autonomous AI systems for managers and decision makers.

Objectives: This paper presents results of a study on the Polish adaptation of the Personality Inventory for ICD-11 (PiCD), which was developed to measure pathological traits under a new, dimensional model of personality disorders proposed in ICD-11. Methods: The study involved a non-clinical sample of N = 597 adults (51.4% female; M = 30.24 years, SD = 12.07 years). For convergent and divergent validity, Personality Inventory for DSM-5 (PID-5; Krueger et al., 2012) and Big Five Inventory-2 (BFI-2; Soto & John, 2017) were used. Results: The results showed the Polish adaptation of the PiCD to be reliable and valid. Cronbach's alpha coefficient for PiCD scale scores ranged from 0.77 to 0.87 (M⍺ = 0.82). The four-factor structure of PiCD items with the three unipolar factors, Negative Affectivity, Detachment, and Dissociality, and one bipolar Anankastia vs. Disinhibition factor was conformed. All PiCD traits are related to PID-5 pathological traits and BFI-2 normal traits in an expected way both in correlational and factor analyses. Conclusions: Obtained data demonstrate satisfactory internal consistency, factorial validity, and convergent-discriminant validity of the Polish adaptation of PiCD in a non-clinical sample.

Approximately one-third of all food produced for human consumption is either lost or wasted. Given the central position of retailers in the supply chain, they have the potential to effectively reduce consumer food waste by implementing targeted interventions. To do so, however, they should target distinct consumer groups. In this research, we use a unique data set comprising the grocery shopping data of customers who use loyalty cards, complemented with food waste reports, to derive three distinct target groups: traditionals, time-constrained, and convenience lovers. Based on the general behavioral change literature, we discuss diverse target group-specific interventions that retailers can implement to reduce consumer food waste. Overall, we pave a research path to examine how retailers and marketing can effectively shift consumer behavior toward more sustainable food and shopping practices and assume responsibility within the food supply chain.

During the recent pandemic, fear of COVID-19 has been widespread and is considered to deteriorate mental health. We assessed whether vaccination can effectively reduce the fear of COVID-19 and, thus, contribute to improving people's mental health status. We used two-wave panel data from a German online study collected in April 2021 (t1) and August/September 2021 (t2) and estimated differences-in-differences to determine whether those who were vaccinated against COVID-19 experienced a reduction of fear of COVID-19, and whether the reduction was more evident as compared to people who were not vaccinated for various reasons. Fear of COVID-19 generally decreased between t1 and t2 for all respondents. Moreover, reduction of fear for people who were unvaccinated at t1 but received the vaccine between t1 and t2 was strongest as compared to people who did not get vaccinated during that period, even after we controlled for factors associated with fear (e.g., age, gender). Vaccination reduced fear of COVID-19 beyond some seasonal fluctuation and, therefore, we argue that vaccination partially reduces the psychological distress caused by the pandemic. We recommend that scientists, practitioners, and politicians highlight this additional positive effect of vaccination in health communication.

Researchers around the world are applying the recently revised Portrait Value Questionnaire (PVQ-RR) to measure the 19 values in Schwartz’s refined values theory. We assessed the internal reliability, circular structure, measurement model, and measurement invariance of values measured by this questionnaire across 49 cultural groups (N = 53,472) and 32 language versions. The PVQ-RR reliably measured 15 of the 19 values in the vast majority of groups and two others in most groups. The fit of the theory-based measurement models supported the differentiation of almost all values in every cultural group. Almost all values were measured invariantly across groups at the configural and metric level. A multidimensional scaling analysis revealed that the PVQ-RR perfectly reproduced the theorized order of the 19 values around the circle across groups. The current study established the PVQ-RR as a sound instrument to measure and to compare the hierarchies and correlates of values across cultures.

Successful campaigns to combat the COVID-19 pandemic depend, in part, on people's willingness to be vaccinated. It is therefore critical to understand the factors that determine people's vaccination intentions. We applied a reasoned action approach - the theory of planned behavior - to explore these factors. We used data from an online survey of adults (18–74 years; n = 5044) conducted in Germany between April 9 and April 28, 2021 and found that attitudes toward getting vaccinated predicted vaccination intentions, while normative and control beliefs did not. In turn, positive attitudes toward getting vaccinated were supported by trust in science and fear of COVID-19 whereas negative attitudes were associated with acceptance of conspiracy theories and skepticism regarding vaccines in general. We advise policymakers, physicians, and health care providers to address vaccination hesitancy by emphasizing factors that support positive attitudes toward getting vaccinated, such as prevention of serious illness, death, and long-term health detriments, as opposed to exerting social pressure or pointing to the ease of getting vaccinated.