50,157 research outputs found
e-Consumer Behaviour
Purpose – The primary purpose of this article is to bring together apparently disparate and yet
interconnected strands of research and present an integrated model of e-consumer behaviour. It
has a secondary objective of stimulating more research in areas identified as still being underexplored.
Design/methodology/approach – The paper is discursive, based on analysis and synthesis of econsumer
literature.
Findings – Despite a broad spectrum of disciplines that investigate e-consumer behaviour and
despite this special issue in the area of marketing, there are still areas open for research into econsumer
behaviour in marketing, for example the role of image, trust and e-interactivity. The
paper develops a model to explain e-consumer behaviour.
Research limitations/implications – As a conceptual paper, this study is limited to literature and
prior empirical research. It offers the benefit of new research directions for e-retailers in
understanding and satisfying e-consumers. The paper provides researchers with a proposed
integrated model of e-consumer behaviour.
Originality/value – The value of the paper lies in linking a significant body of literature within a
unifying theoretical framework and the identification of under-researched areas of e-consumer
behaviour in a marketing context
The Impact of Trust on Acceptance of Online Banking
Major benefits of Online Banking include for banks cost savings, and for customers convenience. Nevertheless, many people perceive Internet banking as risky. This paper introduces a tentative conceptual framework. Trust will be integrated into the Technology Acceptance Model – TAM - (Davis, 1989). Recent research showed that Trust has a striking influence on user willingness to engage in online exchanges of money and personal sensitive information. Detailed literature about Online Banking and Trust is provided. TAM is discussed in depth; external variables that are suitable for the Online Banking context is suggested. In addition the theoretical justification for the conceptual framework integration is discussed. Finally managerial implications and recommendations for Online Banking acceptance are suggested
Leveraging Personal Navigation Assistant Systems Using Automated Social Media Traffic Reporting
Modern urbanization is demanding smarter technologies to improve a variety of
applications in intelligent transportation systems to relieve the increasing
amount of vehicular traffic congestion and incidents. Existing incident
detection techniques are limited to the use of sensors in the transportation
network and hang on human-inputs. Despite of its data abundance, social media
is not well-exploited in such context. In this paper, we develop an automated
traffic alert system based on Natural Language Processing (NLP) that filters
this flood of information and extract important traffic-related bullets. To
this end, we employ the fine-tuning Bidirectional Encoder Representations from
Transformers (BERT) language embedding model to filter the related traffic
information from social media. Then, we apply a question-answering model to
extract necessary information characterizing the report event such as its exact
location, occurrence time, and nature of the events. We demonstrate the adopted
NLP approaches outperform other existing approach and, after effectively
training them, we focus on real-world situation and show how the developed
approach can, in real-time, extract traffic-related information and
automatically convert them into alerts for navigation assistance applications
such as navigation apps.Comment: This paper is accepted for publication in IEEE Technology Engineering
Management Society International Conference (TEMSCON'20), Metro Detroit,
Michigan (USA
Why We Read Wikipedia
Wikipedia is one of the most popular sites on the Web, with millions of users
relying on it to satisfy a broad range of information needs every day. Although
it is crucial to understand what exactly these needs are in order to be able to
meet them, little is currently known about why users visit Wikipedia. The goal
of this paper is to fill this gap by combining a survey of Wikipedia readers
with a log-based analysis of user activity. Based on an initial series of user
surveys, we build a taxonomy of Wikipedia use cases along several dimensions,
capturing users' motivations to visit Wikipedia, the depth of knowledge they
are seeking, and their knowledge of the topic of interest prior to visiting
Wikipedia. Then, we quantify the prevalence of these use cases via a
large-scale user survey conducted on live Wikipedia with almost 30,000
responses. Our analyses highlight the variety of factors driving users to
Wikipedia, such as current events, media coverage of a topic, personal
curiosity, work or school assignments, or boredom. Finally, we match survey
responses to the respondents' digital traces in Wikipedia's server logs,
enabling the discovery of behavioral patterns associated with specific use
cases. For instance, we observe long and fast-paced page sequences across
topics for users who are bored or exploring randomly, whereas those using
Wikipedia for work or school spend more time on individual articles focused on
topics such as science. Our findings advance our understanding of reader
motivations and behavior on Wikipedia and can have implications for developers
aiming to improve Wikipedia's user experience, editors striving to cater to
their readers' needs, third-party services (such as search engines) providing
access to Wikipedia content, and researchers aiming to build tools such as
recommendation engines.Comment: Published in WWW'17; v2 fixes caption of Table
Psychological elements explaining the consumer's adoption and use of a website recommendation system: A theoretical framework proposal
The purpose of this paper is to understand, with an emphasis on the psychological perspective of the research problem, the consumer's adoption and use of a certain web site recommendation system as well as the main psychological outcomes involved. The approach takes the form of theoretical modelling. Findings: A conceptual model is proposed and discussed. A total of 20 research propositions are theoretically analyzed and justified. Research limitations/implications: The theoretical discussion developed here is not empirically validated. This represents an opportunity for future research. Practical implications: The ideas extracted from the discussion of the conceptual model should be a help for recommendation systems designers and web site managers, so that they may be more aware, when working with such systems, of the psychological process consumers undergo when interacting with them. In this regard, numerous practical reflections and suggestions are presented
Tourism and the smartphone app: capabilities, emerging practice and scope in the travel domain.
Based on its advanced computing capabilities and ubiquity, the smartphone has rapidly been adopted as a tourism travel tool.With a growing number of users and a wide varietyof applications emerging, the smartphone is fundamentally altering our current use and understanding of the transport network and tourism travel. Based on a review of smartphone apps, this article evaluates the current functionalities used in the domestic tourism travel domain and highlights where the next major developments lie. Then, at a more conceptual level, the article analyses how the smartphone mediates tourism travel and the role it might play in more collaborative and dynamic travel decisions to facilitate sustainable travel. Some emerging research challenges are discussed
Vulnerable Users’ Perceptions of Transport Technologies
As the global population continues to grow, age and urbanize, it is vital to provide accessible transport so that neither ageing nor disability constitute barriers to social inclusion. While technology can enhance urban access, there is a need to study the ways by which transport technologies - real-time information, pedestrian navigation, surveillance, and road pricing - could be more effectively adopted by users. The reason for this is that some people, and particularly vulnerable populations, are still likely to reluctantly use (or even avoid using) technologies perceived as 'unknown' and 'complicated'. Based on evidence from British and Swedish case studies on older people's perceptions of the aforementioned transport technologies, as well as on a Swedish case study of visually impaired people's perceptions, this article makes the case that technology is only one tool in a complex socio-technical system, and one which brings challenges. The authors also suggest that although vulnerable populations are not homogeneous when expressing attitudes towards transport technologies, their assessment criteria tend to be 'pro-social' as they usually consider that the societal benefits outweigh the personal benefits. Emphasising aspects linked to the technologies' pro-social potential or relevance to the individual user could increase acceptance
Improving Natural Language Interaction with Robots Using Advice
Over the last few years, there has been growing interest in learning models
for physically grounded language understanding tasks, such as the popular
blocks world domain. These works typically view this problem as a single-step
process, in which a human operator gives an instruction and an automated agent
is evaluated on its ability to execute it. In this paper we take the first step
towards increasing the bandwidth of this interaction, and suggest a protocol
for including advice, high-level observations about the task, which can help
constrain the agent's prediction. We evaluate our approach on the blocks world
task, and show that even simple advice can help lead to significant performance
improvements. To help reduce the effort involved in supplying the advice, we
also explore model self-generated advice which can still improve results.Comment: Accepted as a short paper at NAACL 2019 (8 pages
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