20,453 research outputs found
The Effects of Twitter Sentiment on Stock Price Returns
Social media are increasingly reflecting and influencing behavior of other
complex systems. In this paper we investigate the relations between a well-know
micro-blogging platform Twitter and financial markets. In particular, we
consider, in a period of 15 months, the Twitter volume and sentiment about the
30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We
find a relatively low Pearson correlation and Granger causality between the
corresponding time series over the entire time period. However, we find a
significant dependence between the Twitter sentiment and abnormal returns
during the peaks of Twitter volume. This is valid not only for the expected
Twitter volume peaks (e.g., quarterly announcements), but also for peaks
corresponding to less obvious events. We formalize the procedure by adapting
the well-known "event study" from economics and finance to the analysis of
Twitter data. The procedure allows to automatically identify events as Twitter
volume peaks, to compute the prevailing sentiment (positive or negative)
expressed in tweets at these peaks, and finally to apply the "event study"
methodology to relate them to stock returns. We show that sentiment polarity of
Twitter peaks implies the direction of cumulative abnormal returns. The amount
of cumulative abnormal returns is relatively low (about 1-2%), but the
dependence is statistically significant for several days after the events
Money Walks: A Human-Centric Study on the Economics of Personal Mobile Data
In the context of a myriad of mobile apps which collect personally
identifiable information (PII) and a prospective market place of personal data,
we investigate a user-centric monetary valuation of mobile PII. During a 6-week
long user study in a living lab deployment with 60 participants, we collected
their daily valuations of 4 categories of mobile PII (communication, e.g.
phonecalls made/received, applications, e.g. time spent on different apps,
location and media, photos taken) at three levels of complexity (individual
data points, aggregated statistics and processed, i.e. meaningful
interpretations of the data). In order to obtain honest valuations, we employ a
reverse second price auction mechanism. Our findings show that the most
sensitive and valued category of personal information is location. We report
statistically significant associations between actual mobile usage, personal
dispositions, and bidding behavior. Finally, we outline key implications for
the design of mobile services and future markets of personal data.Comment: 15 pages, 2 figures. To appear in ACM International Joint Conference
on Pervasive and Ubiquitous Computing (Ubicomp 2014
Critical Factors of the Buyer Decision Process Model in Business-to-Customer (B2C) E-Commerce in Taiwan
The purpose of this study is to identify the critical factors involved in each stage of the Buyer Decision Process model, developed by Kotler and Armstrong (1997), as this study relates to online retail shopping in the country of Taiwan. This study explored whether and to what extent these factors influence consumers making online purchase decisions. The Buyer Decision Process model consists of five stages: (a) need recognition; (b) information search; (c) alternatives evaluation; (d) purchase decision; and (e) post-purchase decision. This research study attempted to design a framework based on this model to explore the perceived consumer value of online purchase through the entire consumption process in a B2C e-commerce setting in the country of Taiwan.
There are many problems in this research area, such as: (a) B2C e-commerce is very competitive; (b) online shoppers have different characteristics from traditional shoppers; (c) most B2C Websites are ignored by Internet users; and (d) online shoppers are unable to touch, feel, or see real products to evaluate quality. Therefore, how to attract worldwide potential customers to Websites is a challenge for global e-retailers; and how to analyze and understand consumer preferences is a challenge for global e-retailers in the fast-changing digital marketing as well.
There are five research questions in this research study, based on the five stages of the Buyer Decision Process model to measure consumer online behavior in Taiwan. In order to answer the five research questions, the researcher identified 14 critical factors for consumer online purchase decisions based on the five stages. These critical factors include: Free Trials, Internet Advertisements, Search Engines, Online Shopping Malls, Auction Websites, Convenience, Price, Brand, Security, Promotion, Refund, Satisfaction, Customized Information, and Discount. In general, the study results supported the inference of relationships between the 14 critical factors and Internet users\u27 receptivity to online shopping, with Satisfaction ranking first, Online Shopping Malls ranking second, and Convenience ranking third
Technical Change and Industrial Dynamics as Evolutionary Processes
This work prepared for B. Hall and N. Rosenberg (eds.) Handbook of Innovation, Elsevier (2010), lays out the basic premises of this research and review and integrate much of what has been learned on the processes of technological evolution, their main features and their effects on the evolution of industries. First, we map and integrate the various pieces of evidence concerning the nature and structure of technological knowledge the sources of novel opportunities, the dynamics through which they are tapped and the revealed outcomes in terms of advances in production techniques and product characteristics. Explicit recognition of the evolutionary manners through which technological change proceed has also profound implications for the way economists theorize about and analyze a number of topics central to the discipline. One is the theory of the firm in industries where technological and organizational innovation is important. Indeed a large literature has grown up on this topic, addressing the nature of the technological and organizational capabilities which business firms embody and the ways they evolve over time. Another domain concerns the nature of competition in such industries, wherein innovation and diffusion affect growth and survival probabilities of heterogeneous firms, and, relatedly, the determinants of industrial structure. The processes of knowledge accumulation and diffusion involve winners and losers, changing distributions of competitive abilities across different firms, and, with that, changing industrial structures. Both the sector-specific characteristics of technologies and their degrees of maturity over their life cycles influence the patterns of industrial organization ? including of course size distributions, degrees of concentration, relative importance of incumbents and entrants, etc. This is the second set of topics which we address. Finally, in the conclusions, we briefly flag some fundamental aspects of economic growth and development as an innovation driven evolutionary process.Innovation, Technological paradigms, Technological regimes and trajectories, Evolution, Learning, Capability-based theories of the firm, Selection, Industrial dynamics, Emergent properties, Endogenous growth
From Social Data Mining to Forecasting Socio-Economic Crisis
Socio-economic data mining has a great potential in terms of gaining a better
understanding of problems that our economy and society are facing, such as
financial instability, shortages of resources, or conflicts. Without
large-scale data mining, progress in these areas seems hard or impossible.
Therefore, a suitable, distributed data mining infrastructure and research
centers should be built in Europe. It also appears appropriate to build a
network of Crisis Observatories. They can be imagined as laboratories devoted
to the gathering and processing of enormous volumes of data on both natural
systems such as the Earth and its ecosystem, as well as on human
techno-socio-economic systems, so as to gain early warnings of impending
events. Reality mining provides the chance to adapt more quickly and more
accurately to changing situations. Further opportunities arise by individually
customized services, which however should be provided in a privacy-respecting
way. This requires the development of novel ICT (such as a self- organizing
Web), but most likely new legal regulations and suitable institutions as well.
As long as such regulations are lacking on a world-wide scale, it is in the
public interest that scientists explore what can be done with the huge data
available. Big data do have the potential to change or even threaten democratic
societies. The same applies to sudden and large-scale failures of ICT systems.
Therefore, dealing with data must be done with a large degree of responsibility
and care. Self-interests of individuals, companies or institutions have limits,
where the public interest is affected, and public interest is not a sufficient
justification to violate human rights of individuals. Privacy is a high good,
as confidentiality is, and damaging it would have serious side effects for
society.Comment: 65 pages, 1 figure, Visioneer White Paper, see
http://www.visioneer.ethz.c
Analyzing trade competitiveness : a diagnostics approach
Trade has proven to be a powerful engine of growth worldwide. But not all countries have benefited equally. Despite much effort to use trade policy to catalyze exports, many developing countries have failed to achieve successful, sustainable export and economic growth. Even with the benefit of preferential market access, many developing country exporters face a broad and diverse set of constraints that limit their potential to compete in export markets. This paper discusses the concept of"competitiveness"with respect to trade and the various dimensions on which trade competitiveness might be assessed. It argues there is a need for a framework by which trade competitiveness can be assessed in a systematic way. Inspired by the"growth diagnostics"approach, it outlines a possible framework for assessing factors that facilitate or constrain trade competitiveness.Economic Theory&Research,Environmental Economics&Policies,Markets and Market Access,E-Business,Currencies and Exchange Rates
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