Jeroen Van den Ochtend, René Algesheimer, Jacob Goldenberg, The Effect Of Non-reciprocal Behavior On Community Participation: The Threat Of Inactive Members For Online Brand Communities, In: INFORMS Marketing Science Conference 2020. 2020. (Conference Presentation)
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Manuel Mariani, Linyuan Lü, Network-based ranking in social systems: three challenges, Journal of Physics: Complexity, Vol. 1 (1), 2020. (Journal Article)
Ranking algorithms are pervasive in our increasingly digitized societies, with important real-world applications including recommender systems, search engines, and influencer marketing practices. From a network science perspective, network-based ranking algorithms solve fundamental problems related to the identification of vital nodes for the stability and dynamics of a complex system. Despite the ubiquitous and successful applications of these algorithms, we argue that our understanding of their performance and their applications to real-world problems face three fundamental challenges: (1) rankings might be biased by various factors; (2) their effectiveness might be limited to specific problems; and (3) agents’ decisions driven by rankings might result inpotentially vicious feedback mechanisms and unhealthy systemic consequences. Methods rooted innetwork science and agent-based modeling can help us to understand and overcome these challenges. |
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Sheng-Nan Li, Zhao Yang, Claudio Tessone, Mining blocks in a row: a statistical study of fairness in Bitcoin mining, In: 2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), IEEE, 2020-05-02. (Conference or Workshop Paper published in Proceedings)
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Shuqi Xu, Qianming Zhang, Linyuan Lü, Manuel Mariani, Recommending investors for new startups by integrating network diffusion and investors’ domain preference, Information Sciences, Vol. 515, 2020. (Journal Article)
Over the past decade, many startups have sprung up, which create a huge demand for financial support from venture investors. However, due to the information asymmetry between investors and companies, the financing process is usually challenging and time-consuming, especially for the startups that have not yet obtained any investment. Because of this, effective data-driven techniques to automatically match startups with potentially relevant investors would be highly desirable. Here, we analyze 34,469 valid investment events collected from www.itjuzi.com and consider the cold-start problem of recommending investors for new startups. We address this problem by constructing different tripartite network representations of the data where nodes represent investors, companies, and companies’ domains. First, we find that investors have strong domain preferences when investing, which motivates us to introduce virtual links between investors and investment domains in the tripartite network construction. Our analysis of the recommendation performance of diffusion-based algorithms applied to various network representations indicates that prospective investors for new startups are effectively revealed by integrating network diffusion processes with investors’ domain preference. |
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Xia Cao, Chuanyun Li, Evolutionary game simulation of knowledge transfer in industry-university-research cooperative innovation network under different network scales, Scientific Reports, Vol. 10 (4027), 2020. (Journal Article)
This paper takes the industry-university-research cooperation innovation network constructed by the weighted evolutionary BBV model as the research object, which is based on bipartite graph and evolutionary game theory, and constructing the game model of knowledge transfer in the industry-university-research cooperation innovation network, by using the simulation analysis method and analyzing the evolution law of knowledge transfer in the industry-university-research cooperation innovation network under different network scales, three scenarios, the knowledge transfer coefficient and the knowledge reorganization coefficient. The results show that the increase of network scale reduces the speed of knowledge transfer in the network, and the greater the average cooperation intensity of the nodes, the higher the evolution depth of knowledge transfer. Compared with university-research institutes, the evolution depth of knowledge transfer in enterprises is higher, and with the increase of network scale, the gap between the evolution depth of knowledge transfer between them is gradually increasing. Only when reward, punishment and synergistic innovation benefits are higher than the cost of knowledge transfer that can promote the benign evolution of industry-university-research cooperation innovation networks. Only when the knowledge transfer coefficient and the knowledge reorganization coefficient exceed a certain threshold will knowledge transfer behavior emerge in the network. With the increase of the knowledge transfer coefficient and the knowledge reorganization coefficient, the knowledge transfer evolutionary depth of the average cooperation intensity of all kinds of nodes is gradually deepening. |
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Elmar Schlueter, Anu Masso, Eldad Davidov, What factors explain anti-Muslim prejudice? An assessment of the effects of Muslim population size, institutional characteristics and immigration-related media claims, Journal of Ethnic and Migration Studies, Vol. 46 (3), 2020. (Journal Article)
What factors explain majority members’ anti-Muslim prejudice? This is an increasingly important question to ask, but to date only relatively few studies have sought to provide answers from a cross-national comparative perspective. This study aims to help fill this gap. Using data from the seventh round of the European Social Survey (ESS) linked with country-level characteristics, our results indicate that (a) a larger Muslim population size, (b) more liberal immigrant integration policies and (c) greater state support of religion are all associated with lower levels of majority members’ negative attitudes towards Muslim immigration – our indicator of anti-Muslim prejudice. Such attitudes, however, prove to be unrelated to (d) cross-national differences in the frequency of negative immigration-related news reports as measured by the ESS media claims data. Collectively, these findings bring us one important step closer towards a better understanding of interethnic relations between majority members and Muslim immigrants in European host societies. |
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Bart Meuleman, Koen Abts, Peter Schmidt, Thomas F Pettigrew, Eldad Davidov, Economic conditions, group relative deprivation and ethnic threat perceptions: a cross-national perspective, Journal of Ethnic and Migration Studies, Vol. 46 (3), 2020. (Journal Article)
Explaining negative attitudes towards immigration in general and threat due to immigration, in particular, has been a major topic of study in recent decades. While intergroup contact has received considerable attention in explaining ethnic threat, group relative deprivation (GRD), that is, feelings that one’s group is unfairly deprived of desirable goods in comparison to relevant out-groups, has been largely ignored in cross-national research. Nevertheless, various smaller-scale studies have demonstrated that GRD can have a decisive impact on prejudice. In the current study, we examine the association between GRD and ethnic threat systematically across 20 European countries, thereby controlling for intergroup contact and value priorities. The 7th round of the European Social Survey (ESS) includes questions assessing respondents’ feelings of group deprivation compared to immigrants and offers for the first time an opportunity to contextualise the threat-inducing effect of GRD across Europe. A multilevel structural equation model (MLSEM) demonstrates a considerable association between GRD and ethnic threat both on the individual and country levels. The results indicate that GRD is not only an important mediating factor between social structural positions and perceived threat, but also fully mediates the relation between contextual economic indicators and ethnic threat. |
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Anthony Heath, Eldad Davidov, Robert Ford, Eva G T Green, Alice Ramos, Peter Schmidt, Contested terrain: explaining divergent patterns of public opinion towards immigration within Europe, Journal of Ethnic and Migration Studies, Vol. 46 (3), 2020. (Journal Article)
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Eldad Davidov, Daniel Seddig, Anastasia Gorodzeisky, Rebeca Raijman, Peter Schmidt, Moshe Semyonov, Direct and indirect predictors of opposition to immigration in Europe: individual values, cultural values, and symbolic threat, Journal of Ethnic and Migration Studies, Vol. 46 (3), 2020. (Journal Article)
The current study examines the following questions: (1) the extent to which individual basic human values are linked with attitudes towards immigration; (2) whether symbolic threat by immigration mediates this relation; and (3) whether cultural values moderate the relations between individual values, threat, and attitudes towards immigration. The empirical analysis relies on the 2014/2015 data from the immigration module of the European Social Survey (ESS) for West and East European countries. We find that universalistic individuals expressed lower threat due to immigration and higher support of immigration while conservative individuals displayed the opposite pattern. Symbolic threat mediated the association between values and immigration attitudes, but in most countries the mediation was partial. The associations between values, symbolic threat, and attitudes towards immigration were stronger in countries characterised by higher levels of intellectual and affective autonomy and weaker in countries characterised by higher levels of cultural embeddedness. The findings provide support for the centrality of human values in the formation of threat and attitudes towards immigration. |
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Shuqi Xu, Manuel Mariani, Linyuan Lü, Matúš Medo, Unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data, Journal of Informetrics, Vol. 14 (1), 2020. (Journal Article)
Despite the increasing use of citation-based metrics for research evaluation purposes, we do not know yet which metrics best deliver on their promise to gauge the significance of a scientific paper or a patent. We assess 17 network-based metrics by their ability to identify milestone papers and patents in three large citation datasets. We find that traditional information-retrieval evaluation metrics are strongly affected by the interplay between the age distribution of the milestone items and age biases of the evaluated metrics. Outcomes of these metrics are therefore not representative of the metrics’ ranking ability. We argue in favor of a modified evaluation procedure that explicitly penalizes biased metrics and allows us to reveal metrics’ performance patterns that are consistent across the datasets. PageRank and LeaderRank turn out to be the best-performing ranking metrics when their age bias is suppressed by a simple transformation of the scores that they produce, whereas other popular metrics, including citation count, HITS and Collective Influence, produce significantly worse ranking results. |
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Hui Liu, Naiding Yang, Zhao Yang, Jianhong Lin, Yanlu Zhang, The impact of firm heterogeneity and awareness in modeling risk propagation on multiplex networks, Physica A: Statistical Mechanics and its Applications, Vol. 539, 2020. (Journal Article)
Growing interest has emerged to understand the coupled awareness-epidemic dynamics in multiplex network. However, most previous studies usually assume that all the infected nodes have the same influence on the susceptible neighbors, without considering node’s heterogeneity. In this paper, with the similarity between epidemic spreading and risk propagation, we apply the UAU-SIS model to investigate the interplay between awareness and risk propagation in R&D networks considering firms’ heterogeneity. Here, the risk triggering probabilities are heterogenous and depend on two factors: cooperation intensity and local risk prevalence. The results reveal that the cooperation intensity can increase the risk propagation prevalence and decrease the risk propagation threshold, while the local risk prevalence can only increase the risk propagation prevalence. Moreover, we find that the risk propagation threshold undergoes an abrupt transition with a certain point of the local awareness ratio (the global awareness ratio) ignoring the global awareness (the local awareness ratio), which includes two-stage effects on risk propagation threshold. Furthermore, threshold lies in three different areas when considering both the global and local awareness. These results could provide a basis for managerial professionals to improve the robustness of interdependent R&D networks under risk propagation by taking effective measures. |
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Chuanyun Li, Xia Cao, Ming Chi, Research on an evolutionary game model and simulation of a cluster innovation network based on fairness preference, PLoS ONE, Vol. 15 (1), 2020. (Journal Article)
The cluster innovation network is an important part of regional economic development. In addition, the fairness preference of internal innovators in the processes of investment and benefit distribution are particularly important for curbing "free riding" and other speculative behaviors and for creating a good cooperation environment. Therefore, taking a cluster innovation network constructed by the weighted evolutionary BBV model as the research subject, this paper constructs an evolutionary game model of a cluster innovation network based on a spatial public goods game and the theory of fairness preferences, which involves the processes of investment and payoff allocation. Using simulation analysis, this paper studies the evolution of innovators’ cooperative behaviors and benefits in cluster innovation network under the conditions of a fairness preference and a return intensity. The results show that an increase in the weight coefficient, gain coefficient and degree of differentiation between the previous income and current investment can effectively promote improvements in the level of enterprise cooperation. Indeed, the greater the weight coefficient, the gain coefficient and the degree of differentiation are, the more substantial the improvement in the level of enterprise cooperation will be. Moreover, an improvement in the differentiation of the breadth and depth of enterprise cooperation has an inhibitory effect on enterprise cooperation. Furthermore, whereas increases in regulation and gain coefficients can effectively promote enterprise cooperation. However, the increase in the weight coefficient has a different effect on enterprise benefit in terms of the breadth and depth of cooperation. Finally, we hope to improve the overall cooperation level and cooperation income of the network by deeply understanding the fair preferences of innovators in the processes of investment and benefit distribution, which is helpful for promoting the evolution and development of cluster innovation networks. |
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Ewa Skimina, Jan Cieciuch, Explaining everyday behaviours and situational context by personality metatraits and higher‐order values, European Journal of Personality, Vol. 34 (1), 2020. (Journal Article)
In the current study, we looked for the relations between broad personality dimensions (metatraits of personality and higher‐order values) and everyday behaviours. We asked participants (N = 374; aged 17 to 53, Mage = 23.72) about their current behaviour, followed by questions on situational context (company and perceived autonomy) seven times per day for seven consecutive days, using an experience sampling mobile app. This method allowed us to capture a wide range of descriptions of behavioural acts (n = 13 873), which were then empirically categorized. Personality metatraits distinguished within the Circumplex of Personality Metatraits (i.e. Stability vs. Disinhibition, Plasticity vs. Passiveness, Integration vs. Disharmony, and Self‐Restraint vs. Sensation‐Seeking) and values from the refined model of Schwartz et al. (Openness to Change vs. Conservation and Self‐Transcendence vs. Self‐Enhancement) were measured by self‐descriptive questionnaires. Multilevel logistic regressions with multiple predictors, including traits and values simultaneously, revealed significant effects or tendencies for 20 of the 35 categories of activities, five kinds of company, and perceived autonomy. The best predictors of activities and situational context were the higher‐order values Openness to Change vs. Conservation. |
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Patrick Bachmann, Customer lifetime value: Relevance, improvement and implementation of existing models in non-contractual settings, University of Zurich, Faculty of Business, Economics and Informatics, 2020. (Dissertation)
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Anne Scherer, Claudia Wenzel, Geteilte Verantwortung, In: Wert von Daten, Stiftung Mercator Schweiz, Zürich, p. 55 - 57, 2020. (Book Chapter)
Kundinnen und Kunden wünschen sich personalisierte Informationen und Angebote. Gleichzeitig sorgen sie sich um ihre Daten. Die Frage ist nicht, ob Unternehmen persönliche Daten nutzen sollten. Die Frage ist, wie sie dies verantwortungsvoll tun können. |
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Clemens Mader, Johann Cas, Anne Scherer, Wie mit künstlicher Intelligenz umgehen? Die Gesellschaft begegnet der Digitalisierung teilweise mit tiefem Misstrauen. Um die Chancen der künstlichen Intelligenz für die Gesellschaft nutzbar zu machen, muss man diese Skepsis ernst nehmen., Die Volkswirtschaft, Vol. 2020 (8-9), 2020. (Journal Article)
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Ewa Skimina, Włodzimierz Strus, Jan Cieciuch, Piotr Szarota, Pawel K Izdebski, Psychometric properties of the Polish versions of the HEXACO-60 and the HEXACO-100 personality inventories, Current Issues in Personality Psychology, Vol. 8 (3), 2020. (Journal Article)
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Alex Mari, Andreina Mandelli, René Algesheimer, The Evolution of Marketing in the Context of Voice Commerce: A Managerial Perspective, In: HCI in Business, Government and Organizations, Springer International Publishing, Cham, p. 405 - 425, 2020. (Book Chapter)
The world is confronted with the rise of voice assistants, increasingly used for shopping activities. This paper examines managers' perceptions of the evolution of voice assistants and their potential effects on the marketing practice. Shopping-related voice assistants are likely to radically change the way consumers search and purchase products with severe impact on brands. However, the behavior of these AI-enabled machines represents a "black box" for brand owners. The study of the managers' interpretation of a voice-enabled marketplace is critical as it may influence future marketing choices. The authors use an inductive theory construction process to study the phenomenon of voice commerce through the eyes of AI experts and voice-aware managers. A mixed-method approach paced three distinct data collection phases. First, systematic machine behavior observations (Amazon Alexa) unfolded the unique characteristics of voice shopping. Second, in-depth interviews with 30 executives drew the current brand owner's challenges and opportunities in the context of voice commerce. Third, an expert survey with international managers (N=62) revealed the expected impact of voice assistants on the shopping process. Findings show that managers consider voice assistants a disruptive technology assuming a central relational role in the consumer market. However, they often divergence in opinions across industry, function, and seniority level. Besides, managers' familiarity with voice commerce is correlated to a higher optimism towards voice technologies (opportunity for brands) but also a greater sense of urgency (short-term focus) with implications for marketing strategy. This article offers support to brand owners explaining how voice assistants work and examining their effects on consumption. The authors discuss empirical results while providing managerial guidelines to create resilient and sustainable brands in the era of voice commerce. |
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Albertine Weber, Flavio Iannelli, Sebastián Gonçalves, Trend analysis of the COVID-19 pandemic in China and the rest of the world, 2020. (Other Publication)
The recent epidemic of Coronavirus (COVID-19) that started in China has already been "ex-
ported" to more than 140 countries in all the continents, evolving in most of them by local spreading. In this contribution we analyze the trends of the cases reported in all the Chinese provinces, as well as in some countries that, until March 15th, 2020, have more than 500 cases reported. Notably and differently from other epidemics, the provinces did not show an exponential phase. The data available at the Johns Hopkins University site [1] seem to fit well an algebraic sub-exponential growing behavior as was pointed out recently [2]. All the provinces show a clear and consistent pattern of slowing down with growing exponent going nearly zero, so it can be said that the epidemic was contained in China. On the other side, the more recent spread in countries like, Italy, Iran, and Spain show a clear exponential growth, as well as other European countries. Even more recently, US - which was one of the first countries to have an individual infected outside China (Jan 21st, 2020)- seems to follow the same path. We calculate the exponential growth of the most affected countries, showing the evolution along time after the first local case. We identify clearly different patterns in the analyzed data and we give interpretations and possible explanations for them. The
analysis and conclusions of our study can help countries that, after importing some cases, are not yet in the local spreading phase, or have just started. |
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Selin Akca, Anita Rao, Value of Aggregators, Marketing Science, Vol. 39 (5), 2020. (Journal Article)
Aggregators are facing increased scrutiny by regulatory authorities, suggesting these sites have considerable market power. On the other extreme, firms are bypassing aggregators, choosing instead to sell directly to consumers. This raises the question as to which party has more market power: the aggregator or the individual firm. Focusing on the airline industry, we investigate who benefits most in the airline-aggregator relationship. Specifically, we ask what would happen to airline and aggregator site visits and purchases in the absence of a comprehensive aggregator. We first explore consumers’ search patterns on Southwest, an airline that has never been part of any aggregator. In a descriptive exercise, we find that consumers who book on Southwest are the least likely to visit aggregator sites. Second, we use the 2011 American dispute with Orbitz as an exogenous event, which led to American fares no longer being displayed on Orbitz for five months. We use this dispute to identify who was hurt the most—the aggregator or the airline—in the months following the dispute. Our findings indicate the aggregator loses the most when it is not comprehensive. |
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