Matching Items (8)
Filtering by
- Creators: Grebitus, Carola
- Creators: School of Mathematical and Statistical Sciences
Description
I compare the effect of anonymous social network ratings (Yelp.com) and peer group recommendations on restaurant demand. I conduct a two-stage choice experiment in which restaurant visits in the first stage are informed by online social network reviews from Yelp.com, and visits in the second stage by peer network reviews. I find that anonymous reviewers have a stronger effect on restaurant preference than peers. I also compare the power of negative reviews with that of positive reviews. I found that negative reviews are more powerful compared to the positive reviews on restaurant preference. More generally, I find that in an environment of high attribute uncertainty, information gained from anonymous experts through social media is likely to be more influential than information obtained from peers.
ContributorsTiwari, Ashutosh (Author) / Richards, Timothy J. (Thesis advisor) / Qiu, Yueming (Committee member) / Grebitus, Carola (Committee member) / Arizona State University (Publisher)
Created2013
Descriptionyour words
ContributorsWang, Dan, M.S (Author) / Grebitus, Carola (Thesis advisor) / Schroeter, Christiane (Committee member) / Manfredo, Mark (Committee member) / Hughner, Renee (Committee member) / Arizona State University (Publisher)
Created2014
Description
This thesis proposed a novel approach to establish the trust model in a social network scenario based on users' emails. Email is one of the most important social connections nowadays. By analyzing email exchange activities among users, a social network trust model can be established to judge the trust rate between each two users. The whole trust checking process is divided into two steps: local checking and remote checking. Local checking directly contacts the email server to calculate the trust rate based on user's own email communication history. Remote checking is a distributed computing process to get help from user's social network friends and built the trust rate together. The email-based trust model is built upon a cloud computing framework called MobiCloud. Inside MobiCloud, each user occupies a virtual machine which can directly communicate with others. Based on this feature, the distributed trust model is implemented as a combination of local analysis and remote analysis in the cloud. Experiment results show that the trust evaluation model can give accurate trust rate even in a small scale social network which does not have lots of social connections. With this trust model, the security in both social network services and email communication could be improved.
ContributorsZhong, Yunji (Author) / Huang, Dijiang (Thesis advisor) / Dasgupta, Partha (Committee member) / Syrotiuk, Violet (Committee member) / Arizona State University (Publisher)
Created2011
Description
Designing a hazard intelligence platform enables public agencies to organize diversity and manage complexity in collaborative partnerships. To maintain the integrity of the platform while preserving the prosocial ethos, understanding the dynamics of “non-regulatory supplements” to central governance is crucial. In conceptualization, social responsiveness is shaped by communicative actions, in which coordination is attained through negotiated agreements by way of the evaluation of validity claims. The dynamic processes involve information processing and knowledge sharing. The access and the use of collaborative intelligence can be examined by notions of traceability and intelligence cohort. Empirical evidence indicates that social traceability is statistical significant and positively associated with the improvement of collaborative performance. Moreover, social traceability positively contributes to the efficacy of technical traceability, but not vice versa. Furthermore, technical traceability significantly contributes to both moderate and high performance improvement; while social traceability is only significant for moderate performance improvement. Therefore, the social effect is limited and contingent. The results further suggest strategic considerations. Social significance: social traceability is the fundamental consideration to high cohort performance. Cocktail therapy: high cohort performance involves an integrative strategy with high social traceability and high technical traceability. Servant leadership: public agencies should exercise limited authority and perform a supporting role in the provision of appropriate technical traceability, while actively promoting social traceability in the system.
ContributorsWang, Chao-shih (Author) / Van Fleet, David (Thesis advisor) / Grebitus, Carola (Committee member) / Wilson, Jeffrey (Committee member) / Shultz, Clifford (Committee member) / Arizona State University (Publisher)
Created2015
Description
The purpose of our research was to develop recommendations and/or strategies for Company A's data center group in the context of the server CPU chip industry. We used data collected from the International Data Corporation (IDC) that was provided by our team coaches, and data that is accessible on the internet. As the server CPU industry expands and transitions to cloud computing, Company A's Data Center Group will need to expand their server CPU chip product mix to meet new demands of the cloud industry and to maintain high market share. Company A boasts leading performance with their x86 server chips and 95% market segment share. The cloud industry is dominated by seven companies Company A calls "The Super 7." These seven companies include: Amazon, Google, Microsoft, Facebook, Alibaba, Tencent, and Baidu. In the long run, the growing market share of the Super 7 could give them substantial buying power over Company A, which could lead to discounts and margin compression for Company A's main growth engine. Additionally, in the long-run, the substantial growth of the Super 7 could fuel the development of their own design teams and work towards making their own server chips internally, which would be detrimental to Company A's data center revenue. We first researched the server industry and key terminology relevant to our project. We narrowed our scope by focusing most on the cloud computing aspect of the server industry. We then researched what Company A has already been doing in the context of cloud computing and what they are currently doing to address the problem. Next, using our market analysis, we identified key areas we think Company A's data center group should focus on. Using the information available to us, we developed our strategies and recommendations that we think will help Company A's Data Center Group position themselves well in an extremely fast growing cloud computing industry.
ContributorsJurgenson, Alex (Co-author) / Nguyen, Duy (Co-author) / Kolder, Sean (Co-author) / Wang, Chenxi (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Department of Management (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Accountancy (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Twitter, the microblogging platform, has grown in prominence to the point that the topics that trend on the network are often the subject of the news and other traditional media. By predicting trends on Twitter, it could be possible to predict the next major topic of interest to the public. With this motivation, this paper develops a model for trends leveraging previous work with k-nearest-neighbors and dynamic time warping. The development of this model provides insight into the length and features of trends, and successfully generalizes to identify 74.3% of trends in the time period of interest. The model developed in this work provides understanding into why par- ticular words trend on Twitter.
ContributorsMarshall, Grant A (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
It is well understood that innovation drives productivity growth in agriculture. Innovation, however, is a process that involves activities distributed throughout the supply chain. In this dissertation I investigate three topics that are at the core of the distribution and diffusion of innovation: optimal licensing of university-based inventions, new variety adoption among farmers, and consumers’ choice of new products within a social network environment.
University researchers assume an important role in innovation, particularly as a result of the Bayh-Dole Act, which allowed universities to license inventions funded by federal research dollars, to private industry. Aligning the incentives to innovate at the university level with the incentives to adopt downstream, I show that non-exclusive licensing is preferred under both fixed fee and royalty licensing. Finding support for non-exclusive licensing is important as it provides evidence that the concept underlying the Bayh-Dole Act has economic merit, namely that the goals of university-based researchers are consistent with those of society, and taxpayers, in general.
After licensing, new products enter the diffusion process. Using a case study of small holders in Mozambique, I observe substantial geographic clustering of new-variety adoption decisions. Controlling for the other potential factors, I find that information diffusion through space is largely responsible for variation in adoption. As predicted by a social learning model, spatial effects are not based on geographic distance, but rather on neighbor-relationships that follow from information exchange. My findings are consistent with others who find information to be the primary barrier to adoption, and means that adoption can be accelerated by improving information exchange among farmers.
Ultimately, innovation is only useful when adopted by end consumers. Consumers’ choices of new products are determined by many factors such as personal preferences, the attributes of the products, and more importantly, peer recommendations. My experimental data shows that peers are indeed important, but “weak ties” or information from friends-of-friends is more important than close friends. Further, others regarded as experts in the subject matter exert the strongest influence on peer choices.
University researchers assume an important role in innovation, particularly as a result of the Bayh-Dole Act, which allowed universities to license inventions funded by federal research dollars, to private industry. Aligning the incentives to innovate at the university level with the incentives to adopt downstream, I show that non-exclusive licensing is preferred under both fixed fee and royalty licensing. Finding support for non-exclusive licensing is important as it provides evidence that the concept underlying the Bayh-Dole Act has economic merit, namely that the goals of university-based researchers are consistent with those of society, and taxpayers, in general.
After licensing, new products enter the diffusion process. Using a case study of small holders in Mozambique, I observe substantial geographic clustering of new-variety adoption decisions. Controlling for the other potential factors, I find that information diffusion through space is largely responsible for variation in adoption. As predicted by a social learning model, spatial effects are not based on geographic distance, but rather on neighbor-relationships that follow from information exchange. My findings are consistent with others who find information to be the primary barrier to adoption, and means that adoption can be accelerated by improving information exchange among farmers.
Ultimately, innovation is only useful when adopted by end consumers. Consumers’ choices of new products are determined by many factors such as personal preferences, the attributes of the products, and more importantly, peer recommendations. My experimental data shows that peers are indeed important, but “weak ties” or information from friends-of-friends is more important than close friends. Further, others regarded as experts in the subject matter exert the strongest influence on peer choices.
ContributorsFang, Di (Author) / Richards, Timothy J. (Thesis advisor) / Bolton, Ruth N (Committee member) / Grebitus, Carola (Committee member) / Manfredo, Mark (Committee member) / Arizona State University (Publisher)
Created2015
Description
Astrobiology, as it is known by official statements and agencies, is “the study of the origin, evolution, distribution, and future of life in the universe” (NASA Astrobiology Insitute , 2018). This definition should suit a dictionary, but it may not accurately describe the research and motivations of practicing astrobiologists. Furthermore, it does little to characterize the context in which astrobiologists work. The aim of this project is to explore various social network structures within a large body of astrobiological research, intending to both further define the current motivations of astrobiological research and to lend context to these motivations. In this effort, two Web of Science queries were assembled to search for two contrasting corpora related to astrobiological research. The first search, for astrobiology and its close synonym, exobiology, returned a corpus of 3,229 journal articles. The second search, which includes the first and supplements it with further search terms (see Table 1) returned a corpus of 19,017 journal articles. The metadata for these articles were then used to construct various networks. The resulting networks describe an astrobiology that is well entrenched in other related fields, showcasing the interdisciplinarity of astrobiology in its emergence. The networks also showcase the entrenchment of astrobiology in the sociological context in which it is conducted—namely, its relative dependence on the United States government, which should prompt further discussion amongst astrobiology researchers.
ContributorsBromley, Megan Rachel (Author) / Manfred, Laubichler (Thesis director) / Sara, Walker (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Earth and Space Exploration (Contributor) / Department of English (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12