Abstract: In an era when everything is increasingly digital, consumers are always looking for new options in solutions to their everyday needs. In this context, mobile apps are developing at an exponential pace. One of the fastest growing segments of mobile technologies is, obviously, e-commerce. It can be predicted that mobile commerce will record nearly three times the global growth of e-commerce across all platforms, which indicates its importance in the given segment. The current coronavirus pandemic is also changing many of the existing paradigms both socially, economically, and technologically, which has a major impact on changing consumer behavior and the emphasis on simplification and clarity of mobile solutions. This is the area that User Experience (UX) and User Interface (UI) designers deal with. Their task is to design a sufficiently attractive and interesting solution that will be available on all mobile devices and at the same time will be easy enough for the customer/visitor to get to the destination or to get the necessary information in a few clicks. The basis for changes in UX design can now be obtained not only through online analytical tools, but also through neuromarketing, especially in the case of mobile devices. The paper highlights possibilities for testing UX design applications on mobile devices using a special platform that combines a stationary eye camera (eye tracking) and facial analysis (facial coding).
Abstract: Perceived risks play a major role in consumer intentions, behaviors, attitudes, and decisions about online shopping in the KSA. This paper investigates the influence of six perceived risk dimensions on Saudi consumers: product risk, information risk, financial risk, privacy and security risk, delivery risk, and terms and conditions risk empirically. To ensure the success of this study, a random survey was distributed to reflect the consumers’ perceived risk and to enable the generalization of the results. Data were collected from 323 respondents in the Kingdom of Saudi Arabia (KSA): 50 who had never shopped online and 273 who had done so. The results indicated that all six risks influenced the respondents’ perceptions of online shopping. The non-online shoppers perceived financial and delivery risks as the most significant barriers to online shopping. This was followed closely by performance, information, and privacy and security risks. Terms and conditions were perceived as less significant. The online consumers considered delivery and performance risks to be the most significant influences on internet shopping. This was followed closely by information and terms and conditions. Financial and privacy and security risks were perceived as less significant. This paper argues that introducing adequate legal solutions to addressing related problems arising from this study is an urgent need. This may enhance consumer trust in the KSA online market, increase consumers’ intentions regarding online shopping, and improve consumer protection.
Abstract: Cryptocurrencies are getting increasingly popular, but very few of them can be conveniently used in daily mobile phone purchases. To solve this problem, we demonstrate how to build a functional prototype of a mobile cryptocurrency-based e-commerce application the communicates with Near-Field Communication (NFC) tags. Using the system, users are able to purchase physical items with an NFC tag that contains an e-commerce URL. The payment is done simply by touching the tag with a mobile device and accepting the payment. Our method is constructive: we describe the design and technologies used in the implementation and evaluate the security and performance of the solution. Our main finding is that the analysis and measurements show that our solution is feasible for e-commerce.
Abstract: With a continuously increasing speed of information exchange on the World Wide Web, retailers in the E-Commerce sector are faced with immense possibilities regarding different online purchase processes like dynamic price settings. By use of Dynamic Pricing, retailers are able to set short time price changes in order to optimize producer surplus. The empirical research illustrates the basics of Dynamic Pricing and identifies six influencing factors of Dynamic Pricing. The results of a structural equation modeling approach show five main drivers increasing the potential of dynamic price settings in the E-Commerce. Influencing factors are the knowledge of customers’ individual willingness to pay, rising sales, the possibility of customization, the data volume and the information about competitors’ pricing strategy.
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 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: 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: 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: Although current competitive challenges induced by today-s digital economy place their main emphasis on organizational knowledge, customer knowledge has been overlooked. On the other hand, the business community has finally begun to realize the important role customer knowledge can play in the organizational boundaries of the corporate arena. As a result, there is an emerging market for the tools and utilities whose objective is to provide the intelligence for knowledge sharing between the businesses and their customers. In this paper, we present a conceptual model of customer knowledge management by identifying and analyzing the existing tools in the market. The focus will be upon the emerging British dotcom industry whose customer based B2C behavior has been an influential part of the knowledge based intelligence tools in existence today.
Abstract: This study aims to examine the determinants of
purchase intention in C2C e-commerce. Specifically the role of
instant messaging in the C2C e-commerce contextis investigated. In
addition to instant messaging, we brought in two antecedents of
purchase intention - trust and customer satisfaction - to establish a
theoretical research model. Structural equation modeling using
LISREL was used to analyze the data.We discussed the research
findings and suggested some implications for researchers and
practitioners.
Abstract: In this paper we suggest a method for setting
electronic credits for the customers. In this method banks and
market-sites help each other to make doing large shopping through
internet so easy. By developing this system, the people who have less
money to buy most of the things they want, become able to buy all of
them just through a credit. This credit is given by market-sites
through a banking control on it. The method suggested can stop
being imprisoned because of banking debts.
Abstract: Recommender systems are usually regarded as an
important marketing tool in the e-commerce. They use important
information about users to facilitate accurate recommendation. The
information includes user context such as location, time and interest
for personalization of mobile users. We can easily collect information
about location and time because mobile devices communicate with the
base station of the service provider. However, information about user
interest can-t be easily collected because user interest can not be
captured automatically without user-s approval process. User interest
usually represented as a need. In this study, we classify needs into two
types according to prior research. This study investigates the
usefulness of data mining techniques for classifying user need type for
recommendation systems. We employ several data mining techniques
including artificial neural networks, decision trees, case-based
reasoning, and multivariate discriminant analysis. Experimental
results show that CHAID algorithm outperforms other models for
classifying user need type. This study performs McNemar test to
examine the statistical significance of the differences of classification
results. The results of McNemar test also show that CHAID performs
better than the other models with statistical significance.
Abstract: In our modern world, more physical transactions are being substituted by electronic transactions (i.e. banking, shopping, and payments), many businesses and companies are performing most of their operations through the internet. Instead of having a physical commerce, internet visitors are now adapting to electronic commerce (e-Commerce). The ability of web users to reach products worldwide can be greatly benefited by creating friendly and personalized online business portals. Internet visitors will return to a particular website when they can find the information they need or want easily. Dealing with this human conceptualization brings the incorporation of Artificial/Computational Intelligence techniques in the creation of customized portals. From these techniques, Fuzzy-Set technologies can make many useful contributions to the development of such a human-centered endeavor as e-Commerce. The main objective of this paper is the implementation of a Paradigm for the Intelligent Design and Operation of Human-Computer interfaces. In particular, the paradigm is quite appropriate for the intelligent design and operation of software modules that display information (such Web Pages, graphic user interfaces GUIs, Multimedia modules) on a computer screen. The human conceptualization of the user personal information is analyzed throughout a Cascaded Fuzzy Inference (decision-making) System to generate the User Ascribe Qualities, which identify the user and that can be used to customize portals with proper Web links.