Predicting the causal agent in verbally described social interactions

Implicit causality in interpersonal verbs (i.e., causal assumptions about the initiator of a social interaction) has been extensively investigated, especially in English and German language (cf. Rudolph & Försterling, 1997). The present study is the first to investigate verb causality in Danish language using a student sample (N = 96) while simultaneously examining consensus (i.e., to what extent others besides the grammatical subject treat the object like this) and distinctiveness (i.e., to what extent solely the object person is treated by the subject like this) as predictors of causal attribution to subject or object. A strong verb causality effect in Danish language emerged. Consensus proved to be a better predictor than distinctiveness for causal attribution

The 100 most eminent psychologists of the 20th century on the internet – Do internet page counts provide latent indicators of scientific eminence?

Recently, Haggbloom et al. (2002) established a rank-ordered list of the 100 most eminent psychologists of the 20th century (though only the first 99 are actually reported by the authors) meticulously measured by several quantitative and qualitative indicators. We aimed at replicating this listing by simply using page counts obtained from three major internet search engines using different search queries with a five times repeated measurement. The resulting highly reliable indicators of internet frequency were consistently positively associated with the existing ranking and this correlation reached significance when the field of research was included in the query as an operator. We conclude that frequency data obtained by this method can be considered a simple and valid indicator of scientific impact and discuss additional applications of this method

Walk this Way! Incentive Structures of Different Token Designs for Blockchain-Based Applications

Cryptoeconomics is an emerging research area in the field of blockchain technology aiming at understanding token design mechanisms intended to incentivize certain behaviors. Whereas several blockchain ecosystems have been emerging in recent years, little is known about incentive design in blockchain protocols other than Bitcoin. To address this gap, we use agent-based modeling (ABM) to simulate the effects of different token designs on usage in the context of prediction markets. We find that network tokens (i.e., tokens providing services within a system) provide the largest incentive for individuals to join and become long-term active users. Moreover, we find that investment tokens (i.e., tokens used to passively invest in the issuing entity) provide the smallest incentive compared to network tokens and cryptocurrencies (i.e., means of payment in a blockchain ecosystem). We advance the literature by testing the boundary conditions of different token designs for blockchain-based ecosystems using a novel ABM approach

Dimensions of perceived product quality – understanding the consumer’s view

Objectives. We identify core product quality components from the consumers’ perspective and construct a psychometrically sound instrument for their assessment within different purchasing contexts. Methods. Study 1 (N = 34) used a qualitative approach to reveal core components of perceived product quality in the context of apparel evaluations. Study 2 (N = 305) was designed to construct and quantitatively validate the quality scale in a retail store setting. In Study 3 (N = 180) using a second purchasing context the scale’s dimensionality was cross-validated in a mail-order context. Results. Six components of product quality emerged (material, workmanship, design, care, color, fit) and explained approximately 75% of the variance in consumers’ product evaluations. Their dimensional structure was validated using confirmatory factor analysis. Differences concerning the quality dimensions’ relative importance were found for the two purchasing situations. Conclusion. The quality scale proved to be reliable and valid in two important purchasing contexts

Gender roles and implicit causality

Numerous studies investigated the phenomenon of implicit verb causality (cf. Rudolph & Försterling, 1997). This research revealed the robust finding that different types of interpersonal verbs lead to systematic causal attributions to one of the interacting persons. However, few studies addressed the interaction between verb causality and context variables. The present cross-cultural study investigates implicit gender roles in action and state verbs comparing two samples from Germany and China. Results show that the German sample perceived actions to be caused by men whereas states were causally attributed to women. However, our Chinese sample perceived men and women rather equally accountable

Is content king? Job seekers’ engagement with social media employer branding content

Resumen de la ponencia[EN] Increasing digitization and the emergence of social media have radically changed the recruitment landscape adding interactive digital platforms to traditional means of employer communication. Removing barriers of distance and timing, social media enable firms to continue their efforts of promoting their employment brand online. However, social media employer communication and employer brand building remains woefully understudied. Our study addresses this gap by investigating how firms use social media to promote their employer brand. We analyze employer branding communication in a sample of N = 216,828 human resources (HR) related Tweets from N = 166 Fortune 500 companies. Using supervised machine learning we classify the Tweet content according to its informational and inspirational nature, identifying five categories of employer branding social media communication on Twitter.Moser, K.; Tumasjan, A.; Welpe, I. (2016). Is content king? Job seekers’ engagement with social media employer branding content. En CARMA 2016: 1st International Conference on Advanced Research Methods in Analytics. Editorial Universitat Politècnica de València. 124-124. https://doi.org/10.4995/CARMA2016.2016.3103OCS12412

Disrupting Industries with Blockchain: The Industry, Venture Capital Funding, and Regional Distribution of Blockchain Ventures

The blockchain (i.e., a decentralized and encrypted digital ledger) has the potential to disrupt many traditional business models. This study investigates the emerging blockchain business-application landscape by analyzing its industry, venture capital funding, and regional distribution. By matching four venture databases on blockchain-based startups we create a unique database to analyze the technology from a diffusion of innovation theoretical perspective. First, our results show that blockchain startups are present across all industry segments and are most prominently represented in the Finance & Insurance and Information & Communication industries. A fine-grained analysis of financial services yields increasing novel applications in existing service offerings. Second, we find that mainly Finance & Insurance and Information & Communication industries are funded by venture capital, but that blockchain startups are present across all industries. Third, our regional distribution analysis of the emerging ventures identifies two leading geographical blockchain clusters (i.e., the US and UK)

The Interaction of Trait Competitiveness and Leaderboard Design - An Experimental Analysis of Effects on Perceptions and Usage Intention

Gamification is a valuable approach to foster user engagement, raise motivation, and induce behavioral change. As a maturing field of research, the complex interactions of the various elements of gameful systems remain opaque. However, understanding these interactions, especially between user and gamified system, builds the foundation for the vast application of gamified systems. To advance our knowledge in this field, we employ an experimental research design with 192 participants. Thereby we show that users’ personal development competitiveness positively affects the perception and usage intention of a competitive gamified system in a work scenario. Further, this relationship is moderated by the system’s design. Focusing on a team-based rather than a player-based leaderboard supports the usage intentions and perceptions of individuals high in personal development competitiveness. Our study supports the need for individualized gameful systems rather than relying on one-system-fits-all approaches often found in business practice

Implizite Verbkausalität in chinesischer Sprache - Replikation und differentielle Befunde

Verben, die zwischenmenschliche Ereignisse beschreiben, existieren in jeder Sprache der Welt. Beispiele sind “überraschen”, “bestechen”, “tadeln” oder “bewundern”. Diese so genannten interpersonalen Verben führen, auch wenn keinerlei weitere Informationen gegeben werden, zu systematischen Ursachenzuschreibungen auf einen der beiden Interaktionspartner – ein Phänomen, das als „implizite Kausalität in Sprache" bezeichnet wird. Die vorliegende Studie untersucht anhand einer Stichprobe in der Volksrepublik China (N=193) die vorhergesagten Ursachenzuschreibungen von 24 interpersonalen Verben, die nach der Revised Action-State Distinction (Rudolph & Försterling, 1997) ausgewählt wurden. Es zeigt sich in Übereinstimmung mit der bisherigen Forschung, dass auch bei einer kollektivistisch geprägten Kultur die Ursache in systematischer und vorhersagbarer Weise auf einen Interaktionspartner attribuiert wird. Allerdings ergeben sich hierbei für einige Verben systematische Abweichungen, die auf eine kulturspezifische Semantik eines Verbtyps hindeuten: So zeigt sich bei einzelnen Zustandsverben, die üblicherweise Attributionen auf das Objekt nahelegen (z.B. “mögen”), dass in Abweichung hiervon in systematischer Weise eher auf das Satzsubjekt attribuiert wird. Dies deutet darauf hin, dass - zumindest wenn keine weiteren Kausalinformationen vorliegen - in der chinesischen Kultur möglicherweise das grammatikalische Subjekt stärker als Verursacher wahrgenommen wird als in westlichen Kulturen

Assessing candidate preference through web browsing history

Predicting election outcomes is of considerable interest to candidates, political scientists, and the public at large. We propose the use of Web browsing history as a new indicator of candidate preference among the electorate, one that has potential to overcome a number of the drawbacks of election polls. However, there are a number of challenges that must be overcome to effectively use Web browsing for assessing candidate preference—including the lack of suitable ground truth data and the heterogeneity of user populations in time and space. We address these challenges, and show that the resulting methods can shed considerable light on the dynamics of voters’ candidate preferences in ways that are difficult to achieve using polls.Accepted manuscrip