52,555 research outputs found
From the Hands of an Early Adopter's Avatar to Virtual Junkyards: Analysis of Virtual Goods' Lifetime Survival
One of the major questions in the study of economics, logistics, and business
forecasting is the measurement and prediction of value creation, distribution,
and lifetime in the form of goods. In "real" economies, a perfect model for the
circulation of goods is impossible. However, virtual realities and economies
pose a new frontier for the broad study of economics, since every good and
transaction can be accurately tracked. Therefore, models that predict goods'
circulation can be tested and confirmed before their introduction to "real
life" and other scenarios. The present study is focused on the characteristics
of early-stage adopters for virtual goods, and how they predict the lifespan of
the goods. We employ machine learning and decision trees as the basis of our
prediction models. Results provide evidence that the prediction of the lifespan
of virtual objects is possible based just on data from early holders of those
objects. Overall, communication and social activity are the main drivers for
the effective propagation of virtual goods, and they are the most expected
characteristics of early adopters.Comment: 28 page
What attracts vehicle consumers’ buying:A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?
Purpose:
The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint.
Design/methodology/approach:
A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel NaĂŻve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint.
Findings:
The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior.
Research limitations/implications:
The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation.
Originality/value:
Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective
Intelligent Financial Fraud Detection Practices: An Investigation
Financial fraud is an issue with far reaching consequences in the finance
industry, government, corporate sectors, and for ordinary consumers. Increasing
dependence on new technologies such as cloud and mobile computing in recent
years has compounded the problem. Traditional methods of detection involve
extensive use of auditing, where a trained individual manually observes reports
or transactions in an attempt to discover fraudulent behaviour. This method is
not only time consuming, expensive and inaccurate, but in the age of big data
it is also impractical. Not surprisingly, financial institutions have turned to
automated processes using statistical and computational methods. This paper
presents a comprehensive investigation on financial fraud detection practices
using such data mining methods, with a particular focus on computational
intelligence-based techniques. Classification of the practices based on key
aspects such as detection algorithm used, fraud type investigated, and success
rate have been covered. Issues and challenges associated with the current
practices and potential future direction of research have also been identified.Comment: Proceedings of the 10th International Conference on Security and
Privacy in Communication Networks (SecureComm 2014
Personality in Computational Advertising: A Benchmark
In the last decade, new ways of shopping online have increased the
possibility of buying products and services more easily and faster
than ever. In this new context, personality is a key determinant
in the decision making of the consumer when shopping. A person’s
buying choices are influenced by psychological factors like
impulsiveness; indeed some consumers may be more susceptible
to making impulse purchases than others. Since affective metadata
are more closely related to the user’s experience than generic
parameters, accurate predictions reveal important aspects of user’s
attitudes, social life, including attitude of others and social identity.
This work proposes a highly innovative research that uses a personality
perspective to determine the unique associations among the
consumer’s buying tendency and advert recommendations. In fact,
the lack of a publicly available benchmark for computational advertising
do not allow both the exploration of this intriguing research
direction and the evaluation of recent algorithms. We present the
ADS Dataset, a publicly available benchmark consisting of 300 real
advertisements (i.e., Rich Media Ads, Image Ads, Text Ads) rated
by 120 unacquainted individuals, enriched with Big-Five users’
personality factors and 1,200 personal users’ pictures
Autonomic Cloud Computing: Open Challenges and Architectural Elements
As Clouds are complex, large-scale, and heterogeneous distributed systems,
management of their resources is a challenging task. They need automated and
integrated intelligent strategies for provisioning of resources to offer
services that are secure, reliable, and cost-efficient. Hence, effective
management of services becomes fundamental in software platforms that
constitute the fabric of computing Clouds. In this direction, this paper
identifies open issues in autonomic resource provisioning and presents
innovative management techniques for supporting SaaS applications hosted on
Clouds. We present a conceptual architecture and early results evidencing the
benefits of autonomic management of Clouds.Comment: 8 pages, 6 figures, conference keynote pape
Digital marketing actions that achieve a better attraction and loyalty of users: an analytical study
Currently, the digital economy contributes decisively to an increase in competitiveness, especially as a digital transformation involves migrating to new technological models where digital marketing is a key part of growth and user loyalty strategies. Internet and Digital Marketing have become important factors in campaigns, which attract and retain Internet users. This study aims to identify the main ways in which users can be gained and retained by using Digital Marketing. The Delphi method with in-depth interviews was the methodology used in this study. The results of the research show the most important actions for achieving user recruitment and loyalty with Digital Marketing from the opinions of consulted experts. The limitations of this study are those related to the number of experts included in the study, and the number of research papers consulted in the literature review. The literature review and the results of this research are used to propose new solid research with a consolidated critical methodology. This research deals with a new approach that will optimize web technologies for the evolution of user trends, and therefore, will be of academic and professional use for marketing managers and web solution developers. The conclusions of the investigation show the key factors, discarding others that do not affect the optimization of conversions in B2C businesses such as the duration of the session and the rebound percentage. Likewise, the results of the research identify the specific actions that must be carried out to attract and retain users in B2C companies that use the Digital Marketing ecosystem on the Internet. The requirements for companies that wish to implement a model to optimize conversions using the current digital economy are also shown.info:eu-repo/semantics/publishedVersio
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