The Use and Value of Social Information in Selective Selling of Exclusive Products

2020 ◽  
Vol 66 (6) ◽  
pp. 2610-2627 ◽  
Author(s):  
Ruslan Momot ◽  
Elena Belavina ◽  
Karan Girotra
Keyword(s):  
Social Network ◽  
Operations Management ◽  
Social Information ◽  
Social Comparisons ◽  
Network Information ◽  
Customer Base ◽  
Goods And Services ◽  
Customer Preferences ◽  
Low Degree ◽  
Do So

We consider the use and value of social-network information in selectively selling goods and services whose value derives from exclusive ownership among network connections or friends. Our model accommodates customers who are heterogeneous in their number of friends (degree) and their proclivity for social comparisons (conspicuity). Firms with information on either (or both) of these characteristics can use it to make the product selectively available and to personalize prices. We find that firms’ preferred customers are low degree and high conspicuity, with the conspicuity threshold nondecreasing in degree. Interestingly, although both degree and conspicuity levels are relevant to curating the desired customer base, we find that firms do not need conspicuity information to do so; its absence can be substituted by incentivizing customers to self-select. There is no such recourse for the absence of degree information. As a result, degree information is typically more valuable than conspicuity information. Our analysis suggests that there are two canonical categories of social information—less valuable “consonant” information on characteristics where firm and customer preferences are aligned and more valuable “competing” information where preferences are misaligned. Customers can be incentivized to act in a way that their actions are a perfect substitute for consonant information, making it less valuable. This paper was accepted by Gad Allon, operations management.

scholarly journals Effects of Social Network Information on Online Language Learning Performance

2021 ◽  
Vol 17 (2) ◽  
pp. 1-16
Author(s):  
Abrar Al-Hasan
Keyword(s):  
Social Network ◽  
Social Interaction ◽  
Language Learning ◽  
Social Information ◽  
Learning Performance ◽  
Networked Learning ◽  
Network Information ◽  
Online Language Learning ◽  
Collaborative Language ◽  
Better Than

This study examines the value and impact of social network information on a user's language learning performance by conducting an online experiment in a peer-to-peer collaborative language learning marketplace. Social information or information about others in one's network can present a socially networked learning environment that enables learners to engage more in the learning process. Experimental research design in an online language learning marketplace was conducted. The study finds evidence that the mere visibility of social network information positively impacts a learner's learning performance. Learners that engage with social interaction perform better than those that do not. In addition, active social interaction has a stronger impact on learning performance as compared to passive social interaction. The study concludes with implications for platform developers to enable the visibility of social information and engineer the user experience to enhance interactive learning.

scholarly journals Social learning and networks in Nestor parrots

2021 ◽  
Author(s):  
◽  
Daniel Donoghue
Keyword(s):  
Social Network ◽  
Social Learning ◽  
Tool Use ◽  
Social Information ◽  
Habitat Modification ◽  
Future Research ◽  
Video Playback ◽  
Food Aversion ◽  
Network Analyses ◽  
The Social

<p>Social learning and network analyses are theorised to be of great utility in the context of behavioural conservation. For example, harnessing a species’ capacity for social learning may allow researchers to seed useful information into populations, while network analyses could provide a useful tool to monitor community stability, and predict pathways of pathogen transfer. Thus, an understanding of how individuals learn and the nature of the social networks within a population could enable the development of new behavioural based conservation interventions for species facing rapid environmental change, such as human-induced habitat modification. Parrots, the most threatened avian order worldwide, are notably underrepresented in the social learning and social network literature. This thesis addresses this knowledge gap by exploring social learning and networks using two endangered species of parrot; kākā (Nestor meridionalis) and kea (Nestor notabilis). The first study explores social learning of tool use in captive kea, using a trained kea demonstrator. The results from this experiment indicate that both social learning and play behaviour facilitated the uptake of tool use, and suggests that kea are highly sensitive to social information even when presented with complex tasks. The second study assesses whether wild kākā can socially learn novel string-pulling and food aversion behaviours from video playbacks of conspecific demonstrators. Although there was no evidence to indicate that kākā learn socially, these individuals also show no notable reaction to video playback of a familiar predator. Therefore, these results are likely due to difficulties in interpreting information on the screens, and not necessarily a reflection of their ability to perceive social information. In the final study, social network analysis (SNA) was performed to map social connectivity within wellington’s urban kākā population. SNA indicates that kākā form non-random social bonds, selectively associating with some individuals more than others, and also show high levels of dissimilarity in community composition at different feeding sites. Taken together, these results provide rare empirical evidence of social learning in a parrot species and suggest that even complicated seeded behaviours can quickly spread to other individuals. These findings may also be indicative of the difficulties in conducting video playback experiments in wild conditions, which is an area in need of future research. Overall, these findings contribute to the very limited body of research on social learning and networks in parrots, and provide information of potential value in the management of these species.</p>

scholarly journals Social learning and networks in Nestor parrots

2021 ◽  
Author(s):  
Daniel Donoghue
Keyword(s):  
Social Network ◽  
Social Learning ◽  
Tool Use ◽  
Social Information ◽  
Habitat Modification ◽  
Future Research ◽  
Video Playback ◽  
Food Aversion ◽  
Network Analyses ◽  
The Social

<p>Social learning and network analyses are theorised to be of great utility in the context of behavioural conservation. For example, harnessing a species’ capacity for social learning may allow researchers to seed useful information into populations, while network analyses could provide a useful tool to monitor community stability, and predict pathways of pathogen transfer. Thus, an understanding of how individuals learn and the nature of the social networks within a population could enable the development of new behavioural based conservation interventions for species facing rapid environmental change, such as human-induced habitat modification. Parrots, the most threatened avian order worldwide, are notably underrepresented in the social learning and social network literature. This thesis addresses this knowledge gap by exploring social learning and networks using two endangered species of parrot; kākā (Nestor meridionalis) and kea (Nestor notabilis). The first study explores social learning of tool use in captive kea, using a trained kea demonstrator. The results from this experiment indicate that both social learning and play behaviour facilitated the uptake of tool use, and suggests that kea are highly sensitive to social information even when presented with complex tasks. The second study assesses whether wild kākā can socially learn novel string-pulling and food aversion behaviours from video playbacks of conspecific demonstrators. Although there was no evidence to indicate that kākā learn socially, these individuals also show no notable reaction to video playback of a familiar predator. Therefore, these results are likely due to difficulties in interpreting information on the screens, and not necessarily a reflection of their ability to perceive social information. In the final study, social network analysis (SNA) was performed to map social connectivity within wellington’s urban kākā population. SNA indicates that kākā form non-random social bonds, selectively associating with some individuals more than others, and also show high levels of dissimilarity in community composition at different feeding sites. Taken together, these results provide rare empirical evidence of social learning in a parrot species and suggest that even complicated seeded behaviours can quickly spread to other individuals. These findings may also be indicative of the difficulties in conducting video playback experiments in wild conditions, which is an area in need of future research. Overall, these findings contribute to the very limited body of research on social learning and networks in parrots, and provide information of potential value in the management of these species.</p>

The Kind Master is Petting Puppies - Transmutation of the Simplified Populist Rhetoric into Instagram Photography

2020 ◽  
pp. 28-31
Author(s):  
Teja Miholič
Keyword(s):  
Social Network ◽  
Social Power ◽  
Everyday Lives ◽  
The People ◽  
The Social ◽  
The Future ◽  
Do So

The communication power of the social network Instagram is important to address due to its relaxed nature of presenting details from the ordinary lives of individuals. A comparison of the manners in which influencers and politicians represent themselves brings to front a changed dynamic of social power, as it is available online to anyone who can persuade followers to identify with them or to wish to do so in the future. Two ways of identification with an influencer are assumed, namely increasing and decreasing of distance between them and their followers. The text focuses on the latter, where politicians approach the people by showing the banality of their everyday lives. After reviewing the profiles of two Slovenian politicians, a noticeable pattern is that they most often do so with photographs of puppies and kittens. Keywords: populists’ rhetoric, master, Instagram, politics, pets, selfie

Predictive Analytics of Social Networks

2018 ◽  
pp. 823-862
Author(s):  
Ming Yang ◽  
William H. Hsu ◽  
Surya Teja Kallumadi
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Predictive Analytics ◽  
Concept Drift ◽  
Customer Relationship ◽  
Community Formation ◽  
Heterogeneous Information ◽  
Network Information ◽  
Partial Data ◽  
Business To Consumer

In this chapter, the authors survey the general problem of analyzing a social network in order to make predictions about its behavior, content, or the systems and phenomena that generated it. They begin by defining five basic tasks that can be performed using social networks: (1) link prediction; (2) pathway and community formation; (3) recommendation and decision support; (4) risk analysis; and (5) planning, especially causal interventional planning. Next, they discuss frameworks for using predictive analytics, availability of annotation, text associated with (or produced within) a social network, information propagation history (e.g., upvotes and shares), trust, and reputation data. They also review challenges such as imbalanced and partial data, concept drift especially as it manifests within social media, and the need for active learning, online learning, and transfer learning. They then discuss general methodologies for predictive analytics involving network topology and dynamics, heterogeneous information network analysis, stochastic simulation, and topic modeling using the abovementioned text corpora. They continue by describing applications such as predicting “who will follow whom?” in a social network, making entity-to-entity recommendations (person-to-person, business-to-business [B2B], consumer-to-business [C2B], or business-to-consumer [B2C]), and analyzing big data (especially transactional data) for Customer Relationship Management (CRM) applications. Finally, the authors examine a few specific recommender systems and systems for interaction discovery, as part of brief case studies.

Competence Management over Social Networks Through Dynamic Taxonomies

2013 ◽  
pp. 103-120
Author(s):  
Giuseppe Berio ◽  
Antonio Di Leva ◽  
Mounira Harzallah ◽  
Giovanni M. Sacco
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Real World ◽  
Reference Model ◽  
Effective Solution ◽  
Network Information ◽  
The Social ◽  
Competence Management

The exploitation and integration of social network information in a competence reference model (CRAI, Competence, Resource, Aspect, Individual) are discussed. The Social-CRAI model, which extends CRAI to social networks, provides an effective solution to this problem and is discussed in detail. Finally, dynamic taxonomies, a model supporting explorative conceptual search, are introduced and their use in the context of the Social-CRAI model for exploring retrieved information available in social networks is discussed. A real-world example is provided.

Social Network Mining from the Web

2011 ◽  
pp. 149-175 ◽  
Author(s):  
Yutaka Matsuo ◽  
Junichiro Mori ◽  
Mitsuru Ishizuka
Keyword(s):  
Social Network ◽  
Search Engine ◽  
Relevant Information ◽  
Web Content ◽  
Message Boards ◽  
Network Information ◽  
Network Mining ◽  
Social Network Mining ◽  
The Social ◽  
The Web

This chapter describes social network mining from the Web. Since the end of the 1990s, several attempts have been made to mine social network information from e-mail messages, message boards, Web linkage structure, and Web content. In this chapter, we specifically examine the social network extraction from the Web using a search engine. The Web is a huge source of information about relations among persons. Therefore, we can build a social network by merging the information distributed on the Web. The growth of information on the Web, in addition to the development of a search engine, opens new possibilities to process the vast amounts of relevant information and mine important structures and knowledge.

Utilizing the Lead User Method for Promoting Innovation in E-Recruiting

2009 ◽  
pp. 252-274 ◽  
Author(s):  
Elfi Furtmueller ◽  
Celeste Wilderom ◽  
Rolf van Dick
Keyword(s):  
Social Network ◽  
Social Identity ◽  
Service Innovation ◽  
New Product ◽  
Customer Base ◽  
Lead User ◽  
Innovation Project ◽  
Lead Users ◽  
User Groups ◽  
New Product Innovation

In order to maintain their customer base, many e-recruiting firms are in need of developing innovations. The Lead User (LU) Method has been heralded in the new product innovation literature but not yet applied often in e-service settings. Based on an e-recruiting portal, the authors compare new service ideas emerging from interviews with 60 registered applicants to the ideas derived from 15 so-called lead users. Whereas most users offered us social-network features they already know from other platforms, lead users came up with more novel service solutions for different user segments. From both type of users we learned that applicants are more inclined to re-use the same e-recruiting portal if it includes community and social network features for specified user segments, sharing a similar social identity supplementing offline ties. Thus, carefully specifying and treating differentially various user groups at the outset of an e-service innovation project is likely to pay off. This and other practical findings have prompted us to sketch implications for innovating e-recruiting services.

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