Understanding Moderators of Peer Influence for Engineering Viral Marketing Seeding Simulations and Strategies

Seeding as an emerging viral marketing strategy requires a better understanding on how various contextual factors that embedded in social networks affect peer influence and product diffusion. Realistic simulations for seeding need to incorporate empirical insights about the complexities (various moderators) and dynamics (temporal changes) of peer influence by analyzing real-world data. We analyze the impacts of peer influence moderators in a large-scale phone call network of 0.48 million customers with 364 million calls and 3.9 million video-on-demand purchases, to design empirical models and engineer data-driven simulations of product diffusion, as well as developing and evaluating seeding strategies. We intend to contribute to existing research by 1) enriching the theoretical and empirical understanding of peer influence moderators for stakeholders, 2) combining econometric models and analyses with data-driven simulations towards a complex system approach for devising and evaluating effective seeding strategies in different scenarios

Value Incoherence Precedes Value Change:Evidence from Value Development in Childhood and Adolescence Across Cultures

We test the theory that personality incoherence may instigate personality change in the context of personal values. Values’ near-universal organization makes value incoherence assessment straightforward. The study included 13 longitudinal samples from seven cultures (Australia, Israel Palestinian citizens, Israel Jewish majority, Italy, Poland, Portugal, and Switzerland), total N = 7,126, and T1 Mage ranging between 6-18. Each participant reported values between two- and six-times. Using unfolding analysis, we calculated the fit of the internal value structure of each participant at the first time point to the value structure in their sample (normative structure) and to the theoretical structure of Schwartz (1992). We estimated value change using Growth Curve Modeling (when at least three measurement times were available) and the difference between T1 and T2 in each sample. We correlated value incoherence with value change and estimated the effect across samples using a meta-analysis. Incoherence with the structure of values predicted greater value change. The associations were stronger when participant’s value structures were compared to the normative value structure at T1 than when they were compared to the theoretical structure. A meta-regression analysis indicated that effects were not moderated by age. We discuss possible underlying processes and implications for personality development

Fear of Missing Out (FOMO) on Emerging Technology: Biased and Unbiased Adoption Decision Making

Corporate decision-makers (DMs) are increasingly being challenged to adopt emerging technologies with undefined market potential while being susceptible to biases. Failure to achieve the expected benefits may affect collective and individual-level performance. Fear of missing out (FOMO) influences the ability to make rational decisions. Although FOMO can lead DMs to prioritize popular but immature technologies, there remains a limited understanding of the notion in organizational settings. Drawing on semi-structured interviews and archival data corroborated by insights from key stakeholders, our research investigates the role of FOMO when adopting emerging technology. Findings reveal that FOMO (i) is experienced by DMs experience in one of three performance levels (firm, team, employee), each differentiated by specific targets and responses, and (ii) influences the decision process both directly and via inflated expected outcomes. The mere presence of FOMO does not constitute a bias in the decision. Further, we suggest how to regulate FOMO in organizations

Assessment of cross-cultural comparability

Recent years have witnessed both a growing number of cross-cultural datasets but also a growing awareness of problems connected with cross-cultural comparisons. In particular, researchers have realized that measurement invariance is a necessary precondition for a meaningful comparison of data across cultures or countries. The literature on measurement invariance is very rich and provides researchers with a variety of approaches which suggest when and how measurement invariance may be tested. This chapter provides an explanation of what measurement invariance is and offers a guide designed to help researchers interested in testing for measurement invariance. We distinguish six main issues that have to be addressed by researchers while testing for measurement invariance. The first issue concerns the level of measurement invariance to be tested (configural, metric or scalar), the second – the type of data used (continuous or ordinal-categorical), the third – choice of rules to evaluate whether measurement invariance is established, the fourth – decision about whether cross-loadings of the items are to be permitted, the fifth – the scope of measurement invariance (full or partial), and the sixth – the accuracy of invariance that needs to be established (i.e. exact or approximate). We describe possibilities to address these issues and formulate recommendations for applied researchers

Testing for Approximate Measurement Invariance of Human Values in the European Social Survey

Measurement invariance is a necessary precondition for meaningful cross-country comparisons, and three levels have been differentiated: configural, metric, and scalar. Unfortunately, establishing the most stringent form, that is, scalar measurement invariance, across groups is difficult. Recently, Muthen and Asparouhov proposed testing for approximate rather than exact measurement invariance, as this may be sufficient for meaningful comparisons. Following their strategy, the results of cross-country approximate measurement invariance tests of the 21-item Portrait Value Questionnaire (PVQ-21) scale to measure values in the European Social Survey are presented (N = 274,447 respondents from 15 countries participating in all six rounds). Applying the new approximate method for the test of measurement invariance allows both using more moderate constraints of approximate equality of parameters across groups and exploring the extent of noninvariance. Approximate measurement invariance was established in almost all rounds for two higher-order values: openness to change and self-enhancement. In the case of the two other higher-order values, self-transcendence and conservation, approximate measurement invariance was established across a subset of countries