Abstract: Online dispute resolution has been identified in many countries as a viable alternative for resolving conflicts which have arisen in the so-called digital age. This system of dispute resolution is developing alongside the Internet, and as new types of transactions are made possible by our increased connectivity, new ways of resolving disputes must be explored. Developed nations, such as the United States of America and the European Union, have been involved in creating these online dispute resolution mechanisms from the outset, and currently have sophisticated systems in place to deal with conflicts arising in a number of different fields, such as e-commerce, domain name disputes, labour disputes and conflicts arising from family law. Specifically, in the field of e-commerce, the Internet’s borderless nature has served as a way to promote cross-border trade, and has created a global marketplace. Participation in this marketplace boosts a country’s economy, as new markets are now available, and consumers can transact from anywhere in the world. It would be especially advantageous for developing nations to be a part of this global marketplace, as it could stimulate much-needed investment in these nations, and encourage international co-operation and trade. However, for these types of transactions to proliferate, an effective system for resolving the inevitable disputes arising from such an increase in e-commerce is needed. Online dispute resolution scholarship and practice is flourishing in developed nations, and it is clear that the gap is widening between developed and developing nations in this regard. The potential for implementing online dispute resolution in developing countries has been discussed, but there are a number of obstacles that have thus far prevented its continued development. This paper aims to evaluate the various political, infrastructural and socio-economic challenges faced in developing nations, and to question how these have impacted the acceptance and development of online dispute resolution, scholarship and training of online dispute resolution practitioners and, ultimately, developing nations’ readiness to participate in cross-border e-commerce.
Abstract: The aim of this paper is to identify and discuss the obstacles to the ability of the accounting information systems of Kuwaiti companies to deal with electronic commerce, and then to propose appropriate solutions to overcome the barriers. The study revealed a remarkable decrease in external auditors who have professional certification. The results also showed an agreement regarding the accounting systems and the ability to deal with e-commerce, with a different degree of importance, despite the presence of obstacles to the ability of accounting systems in dealing with different companies.
Abstract: Nowadays, e-commerce shopping websites have experienced noticeable growth. These websites have gained consumers’ trust. After purchasing a product, many consumers share comments where opinions are usually embedded about the given product. Research on the automatic management of opinions that gives suggestions to potential consumers and portrays an image of the product to manufactures has been growing recently. After launching the product in the market, the reviews generated around it do not usually contain helpful information or generic opinions about this product (e.g. telephone: great phone...); in the sense that the product is still in the launching phase in the market. Within time, the product becomes old. Therefore, consumers perceive the advantages/ disadvantages about each specific product feature. Therefore, they will generate comments that contain their sentiments about these features. In this paper, we present an unsupervised method to extract different product features hidden in the opinions which influence its purchase, and that combines Time Weighting (TW) which depends on the time opinions were expressed with Term Frequency-Inverse Document Frequency (TF-IDF). We conduct several experiments using two different datasets about cell phones and hotels. The results show the effectiveness of our automatic feature extraction, as well as its domain independent characteristic.
Abstract: The introduction of a multitude of new and interactive
e-commerce information technology (IT) artifacts has impacted
adoption research. Rather than solely functioning as productivity
tools, new IT artifacts assume the roles of interaction mediators and
social actors. This paper describes the varying roles assumed by IT
artifacts, and proposes and distinguishes between four distinct foci of
how the artifacts are evaluated. It further proposes a theoretical
model that maps the different views of IT artifacts to four distinct
types of evaluations.
Abstract: Sentiment analysis means to classify a given review
document into positive or negative polar document. Sentiment
analysis research has been increased tremendously in recent times
due to its large number of applications in the industry and academia.
Sentiment analysis models can be used to determine the opinion of
the user towards any entity or product. E-commerce companies can
use sentiment analysis model to improve their products on the basis
of users’ opinion. In this paper, we propose a new One-class Support
Vector Machine (One-class SVM) based sentiment analysis model
for movie review documents. In the proposed approach, we initially
extract features from one class of documents, and further test the
given documents with the one-class SVM model if a given new test
document lies in the model or it is an outlier. Experimental results
show the effectiveness of the proposed sentiment analysis model.
Abstract: Given the increase in the number of e-commerce sites,
the number of competitors has become very important. This means
that companies have to take appropriate decisions in order to meet the
expectations of their customers and satisfy their needs. In this paper,
we present a case study of applying LRFM (length, recency,
frequency and monetary) model and clustering techniques in the
sector of electronic commerce with a view to evaluating customers’
values of the Moroccan e-commerce websites and then developing
effective marketing strategies. To achieve these objectives, we adopt
LRFM model by applying a two-stage clustering method. In the first
stage, the self-organizing maps method is used to determine the best
number of clusters and the initial centroid. In the second stage, kmeans
method is applied to segment 730 customers into nine clusters
according to their L, R, F and M values. The results show that the
cluster 6 is the most important cluster because the average values of
L, R, F and M are higher than the overall average value. In addition,
this study has considered another variable that describes the mode of
payment used by customers to improve and strengthen clusters’
analysis. The clusters’ analysis demonstrates that the payment method is
one of the key indicators of a new index which allows to assess the
level of customers’ confidence in the company's Website.
Abstract: Construction industry plays a vital role in the
economy of the world. However, due to high uncertainty and
variability in the industry, its performance is not as efficient in terms
of quality, lead times, productivity and costs as of other industries.
Moreover, there are continuous conflicts among the different actors
in the construction supply chains in terms of profit sharing. Previous
studies suggested partnership as an important approach to promote
cooperation among the different actors in the construction supply
chains and thereby it improves the overall performance. Construction
practitioners tried to focus on partnership which can enhance the
performance of construction supply chains but they are not fully
aware of different approaches and techniques for improving
partnership. In this research, a systematic review on partnership in
relation to construction supply chains is carried out to understand
different elements influencing the partnership. The research
development of this domain is analyzed by reviewing selected
articles published from 1996 to 2015. Based on the papers, three
major elements influencing partnership in construction supply chains
are identified: ‘Lean approach’, ‘Relationship building’ and ‘E-commerce
applications’. This study analyses the contributions in the
areas within each element and provides suggestions for future
developments of partnership in construction supply chains.
Abstract: The paper discusses mineral water consumer market
and development policy in Georgia, the tools and measures, which
will contribute to production of mineral waters and increase its
export.
The paper studies and analyses current situation in mineral water
production sector as well as the factors affecting increase and
reduction of its export. It’s noted that in order to gain and maintain
competitive advantage, it’s necessary to provide continuous supply of
high quality goods with modern design, open new distribution
channels to enter new markets, carry out broad promotional activities,
organize e-commerce. Economic policy plays an important role in
protecting markets from counterfeit goods. The state also plays an
important role in attracting foreign direct investments. Stable
business environment and export oriented strategy is the basis for the
country’s economic growth.
Based on the research, the paper suggests the strategy for
improving competitiveness of Georgian mineral waters; relevant
conclusions and recommendations are provided.
Abstract: Recommendation systems are widely used in
e-commerce applications. The engine of a current recommendation
system recommends items to a particular user based on user
preferences and previous high ratings. Various recommendation
schemes such as collaborative filtering and content-based approaches
are used to build a recommendation system. Most of current
recommendation systems were developed to fit a certain domain such
as books, articles, and movies. We propose1 a hybrid framework
recommendation system to be applied on two dimensional spaces
(User × Item) with a large number of Users and a small number
of Items. Moreover, our proposed framework makes use of both
favorite and non-favorite items of a particular user. The proposed
framework is built upon the integration of association rules mining
and the content-based approach. The results of experiments show
that our proposed framework can provide accurate recommendations
to users.
Abstract: E-business technologies, whereby business
transactions are conducted remotely using the Internet, present
unique opportunities and challenges for business. E-business
technologies are applicable to a wide range of organizations and
small and medium-sized enterprises (SMEs) are no exception. There
is an established body of literature about e-business, looking at
definitions, concepts, benefits and challenges. In general, however,
the research focus has been on larger organizations, not SMEs. In an
attempt to redress the balance of research, this paper looks at ebusiness
technologies specifically from a small business perspective.
It seeks to identify the possible barriers that SMEs might face when
considering adoption of the e-business concept and practice as part of
their business process change initiatives and implementation. To
facilitate analysis of these barriers a conceptual framework has been
developed which outlines the key conceptual and practical challenges
of e-business implementation in SMEs. This is developed following a
literature survey comprised of three categories: characteristics of
SMEs, issues of IS/IT use in SMEs and general e-business adoption
and implementation issues. The framework is then empirically
assessed against 7 SMEs who have yet to implement e-business or
whose e-business efforts have been unsatisfactory. Conclusions from
the case studies can be used to verify the framework, and set
parameters for further larger scale empirical investigation.
Abstract: Since the emergence of e-Commerce, the world of
business has witnessed a radical shift in the way business activities
are conducted. However, the emergence of m-Commerce has further
pushed the boundaries of virtual commerce revolution. As a result,
there seems to be a growing blur in the distinction between e-
Commerce and m-Commerce. In addition, existing definitions for
both forms of commerce highlight characteristics (e.g. type of device
and activity conducted) that may be applicable to both concepts. The
aim of this paper is to identify the characteristics that help define and
delineate between e- and m- Commerce. The paper concludes that
characteristics of mobility, ubiquity and immediacy provide a clearer
and simpler template to distinguish between e-Commerce and m-
Commerce.
Abstract: The purpose of this research was to identify factors
that influenced the success of e-commerce implementation within
SMEs businesses. In order to achieve the objectives of this research,
the researcher collected data from random firms in Thailand, both the
users and those who are not using the e-commerce. The data was
comprised of the results of 310 questionnaires, as well as 10
interviews with owner/managers of businesses who are currently
using e-commerce successfully. The data were analyzed by using
descriptive statistics, which included frequency, percentages, mean,
and the standard deviation of pertinent factors. Independent t-test and
one-way ANOVA test were also used. The findings of this research
revealed that 50% of all the firms surveyed had e-commerce website,
whereas, over 20% of all firms surveyed had developing an ecommerce
strategy. The result findings also indicate that
organizational factors, technological factors and environment factors
as significant factors effecting success of e-commerce
implementation in SMEs. From the hypotheses testing, the findings
revealed that the different level of support use ecommerce by
owner/manager had different success in e-commerce implementation.
Moreover, the difference in e-commerce management approach
affected the success in terms of higher total sales for the business or
higher number of retained or returning customers.
Abstract: Consumer-to-Consumer (C2C) E-commerce has been
growing at a very high speed in recent years. Since identical or
nearly-same kinds of products compete one another by relying on
keyword search in C2C E-commerce, some sellers describe their
products with spam keywords that are popular but are not related to
their products. Though such products get more chances to be retrieved
and selected by consumers than those without spam keywords,
the spam keywords mislead the consumers and waste their time.
This problem has been reported in many commercial services like
ebay and taobao, but there have been little research to solve this
problem. As a solution to this problem, this paper proposes a method
to classify whether keywords of a product are spam or not. The
proposed method assumes that a keyword for a given product is
more reliable if the keyword is observed commonly in specifications
of products which are the same or the same kind as the given
product. This is because that a hierarchical category of a product
in general determined precisely by a seller of the product and so is
the specification of the product. Since higher layers of the hierarchical
category represent more general kinds of products, a reliable degree
is differently determined according to the layers. Hence, reliable
degrees from different layers of a hierarchical category become
features for keywords and they are used together with features only
from specifications for classification of the keywords. Support Vector
Machines are adopted as a basic classifier using the features, since
it is powerful, and widely used in many classification tasks. In
the experiments, the proposed method is evaluated with a golden
standard dataset from Yi-han-wang, a Chinese C2C E-commerce,
and is compared with a baseline method that does not consider
the hierarchical category. The experimental results show that the
proposed method outperforms the baseline in F1-measure, which
proves that spam keywords are effectively identified by a hierarchical
category in C2C E-commerce.
Abstract: The objectives of this research were to study the
influencing factors that contributed to the success of e-collaborative
in e-commerce of B2C (Business to Customer) business in Bangkok,
Thailand. The influencing factors included organization, people,
information technology and the process of e-collaborative. A
questionnaire was used to collect data from 200 small e-commerce
businesses and the path analysis was utilized as the tool for data
analysis.
By using the path analysis, it was revealed that the factors
concerning with organization, people and information technology
played an influence on e-collaborative process and the success of ecollaborative,
whereas the process of e-collaborative factor
manipulated its success. The findings suggested that B2C ecommerce
business in Thailand should opt in improvement approach
in terms of managerial structure, leaderships, staff’s skills and
knowledge, and investment of information technology in order to
capacitate higher efficiency of e-collaborative process that would
result in profit and competitive advantage.
Abstract: The objectives of this research paper was to study the influencing factors that contributed the willingness of consumers to purchase products online included quality of website, perceived ease of use, perceived usefulness, trust on online purchases, attitude towards online shopping and intentions to online purchases. The research was conducted in both quantitative and qualitative methods, by utilizing both questionnaire and in-depth interview. A questionnaire was used to collect data from 350 consumers who had online shopping experiences in Bangkok, Thailand. Statistics utilized in this research included descriptive statistics and path analysis.
The findings revealed that the factors concerning with quality of website, perceived ease of use and perceived usefulness played an influence on trust in online shopping. Trust also played an influence on attitude towards online purchase, whereas trust and attitude towards online purchase manipulated the intention of online purchase.
Abstract: The continued rise of e-commerce is the main driver of the rapid growth of global online purchase. Consumers can nearly buy everything they want at one occasion through online shopping. The purchase behavior models which focus on single product category are insufficient to describe online shopping behavior. Therefore, analysis of multi-category purchase gets more and more popular. For example, market basket analysis explores customers’ buying tendency of the association between product categories. The information derived from market basket analysis facilitates to make cross-selling strategies and product recommendation system.
To detect the association between different product categories, we use the market basket analysis with the multidimensional scaling technique to build an associated map which describes how likely multiple product categories are bought at the same time. Besides, we also build an inter-purchase time model for associated products to describe how likely a product will be bought after its associated product is bought. We classify inter-purchase time behaviors of multi-category products into nine types, and use a mixture regression model to integrate those behaviors under our assumptions of purchase sequences. Our sample data is from comScore which provides a panelist-label database that captures detailed browsing and buying behavior of internet users across the United States. Finding the inter-purchase time from books to movie is shorter than the inter-purchase time from movies to books. According to the model analysis and empirical results, this research finally proposes the applications and recommendations in the management.
Abstract: The objectives of this research paper were to study the expectation and satisfaction of tourists in five tourism service quality dimensions, namely, website quality, service ability, trust ability, customer empathy, and responsiveness to customer and also to study the influences of satisfaction affecting loyalty toward quality service of the online tourism enterprises located in Bangkok Thailand. This research utilized both quantitative and qualitative research methods. In terms of quantitative method, a questionnaire was used as a tool to collect data from 400 tourists who were using in online travel services. Statistics analysis included descriptive statistics, t-test and Multiple Regression Analysis. In terms of qualitative analysis, an in-depth interview and content analysis were used along with 10 individual management levels of e-commerce enterprises.
The results revealed that the respondents had higher expectations than their level of satisfaction in all five categories. However, the respondents were more satisfied with online travel services than without online service. The demographic factors such as gender and age had no influence on the level of satisfaction whereas the demographic factors of education, occupation, and income had influenced the level of satisfaction. The test results also indicated that the level of satisfaction from responsiveness to customer had the highest influence on the loyalty of tourists who used online travel. The level of satisfaction from customer empathy had the highest influence on the tourists to recommend others to use online travel services. Also, the level of satisfaction from service ability had the highest influence on tourists to take an actual trip.
Abstract: Nowadays, more engineering systems are using some
kind of Artificial Intelligence (AI) for the development of their
processes. Some well-known AI techniques include artificial neural
nets, fuzzy inference systems, and neuro-fuzzy inference systems
among others. Furthermore, many decision-making applications base
their intelligent processes on Fuzzy Logic; due to the Fuzzy
Inference Systems (FIS) capability to deal with problems that are
based on user knowledge and experience. Also, knowing that users
have a wide variety of distinctiveness, and generally, provide
uncertain data, this information can be used and properly processed
by a FIS. To properly consider uncertainty and inexact system input
values, FIS normally use Membership Functions (MF) that represent
a degree of user satisfaction on certain conditions and/or constraints.
In order to define the parameters of the MFs, the knowledge from
experts in the field is very important. This knowledge defines the MF
shape to process the user inputs and through fuzzy reasoning and
inference mechanisms, the FIS can provide an “appropriate" output.
However an important issue immediately arises: How can it be
assured that the obtained output is the optimum solution? How can it
be guaranteed that each MF has an optimum shape? A viable solution
to these questions is through the MFs parameter optimization. In this
Paper a novel parameter optimization process is presented. The
process for FIS parameter optimization consists of the five simple
steps that can be easily realized off-line. Here the proposed process
of FIS parameter optimization it is demonstrated by its
implementation on an Intelligent Interface section dealing with the
on-line customization / personalization of internet portals applied to
E-commerce.
Abstract: This paper addresses the fundamental requirements for
starting an online business. It covers the process of ideation,
conceptualization, formulation, and implementation of new venture
ideas on the Web. Using Facebook as an illustrative example, we learn
how to turn an idea into a successful electronic business and to execute
a business plan with IT skills, management expertise, a good
entrepreneurial attitude, and an understanding of Internet culture. The
personality traits and characteristics of a successful e-commerce
entrepreneur are discussed with reference to Facebook-s founder,
Mark Zuckerberg. Facebook is a social and e-commerce success. It
provides a trusted environment of which participants can conduct
business with social experience. People are able to discuss products
before, during the after the sale within the Facebook environment. The
paper also highlights the challenges and opportunities for e-commerce
entrepreneurial startups to go public and of entering the China market.
Abstract: The study aimed to identify the logical structure of
data and particularities of developing and testing a website designed
for selling farm products through online auctions.
The research is based on a short literature review in the field and
exploratory trials of some successful models from other industries, in
order to identify the advantages of using such tool, as well as the
optimal structure and functionality of an auction portal. In the last
part, the study focuses on the results of testing the website by the
potential beneficiaries.
Conclusions of the study underlines that the particularities of some
agricultural products could raise difficulties in the process of selling
them through online auctions, but the use of such system it is
perceived to bring significant improvements in the supply chain.
The results of scientific investigations require a more detailed
study regarding the importance of using quality standards for
agricultural products sold via online auction, the impact that
implementation of an online payment system could have on trade
with agricultural products and problems which could arise in using
the website in different countries.