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Diffusion of shared goods in consumer coalitions. An agent-based model
This paper focuses on the process of coalition formation conditioning the common decision to adopt a shared good, which cannot be afforded by an average single consumer and whose use cannot be exhausted by any single consumer. An agent based model is developed to study the interplay between these two processes: coalition formation and diffusion of shared goods. Coalition formation is modelled in an evolutionary game theoretic setting, while adoption uses elements from both the Bass and the threshold models. Coalitions formation sets the conditions for adoption, while diffusion influences the consequent formation of coalitions. Results show that both coalitions and diffusion are subject to network effects and have an impact on the information flow though the population of consumers. Large coalitions are preferred over small ones since individual cost is lower, although it increases if higher quantities are purchased collectively. The paper concludes by connecting the model conceptualisation to the on-going discussion of diffusion of sustainable goods, discussing related policy implications
Using MapReduce Streaming for Distributed Life Simulation on the Cloud
Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp
Location-based Marketing: the academic framework
Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Over the last several years one could observe revolution in location-based
technologies and geospatial information. Location awareness of mobile devices
resulted in development of Location-Based Services (LBS) that are realization of that
revolution in the most personal and contextual way. The ability to reach consumers
in the highly targeted manner based on spatio-temporal criteria, attracted marketers
from the early beginning of LBS creating field called Location-Based Marketing.
Today decreasing prices of smartphones and wireless internet, as well as integration
of location-aware mobile solutions and social media is leading to new possibilities
and opportunities. The academic and professional interests of the author made him noticed that
although the industry has challenged a significant development, there is lack of
publications that would put an academic framework on that progress. The research
has fulfilled this gap by extensive investigation of the current state of the art of
Location-Based Marketing and its foundations - Location Based Services.
The dissertation provides academic framework by comprehensive analysis of the
Location-Based Marketing from LBS and marketing perspective. Further the thesis is
addressing the issue of significant discrepancy between theoretical concepts of
measurable Location-Based Social Media data and the actual data than can be legally
accessed and used for marketing analysis purposes by investigation a case study of
Location-Based Social Network - Foursqaure and Location-Based Analytics platform
VenueLabs
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