Purchase Products Online Research Articles

Searching offline and buying online – An analysis of showrooming forms and segments

Showrooming is behavior where customers search for information in brick-and-mortar stores and then purchase products online. While the literature conceptualizes showrooming as a one-dimensional variable, we argue that different forms of showrooming exist. We identify four showrooming segments that differ in retailer loyalty, usage of in-store information, devices, place and time of the online purchase. We show further that loyal vs. competitive showroomers differ in psychographic variables, such as price consciousness, desire for social contact and bad conscience during showrooming. The results have important implications for retailers aiming to keep customers in their own channels.

Consumer's point of view on parcel lockers in DKI Jakarta

Online shopping businesses grow significantly in Indonesia, especially in Jakarta. Consumers find out that purchasing products online is more effective. Most of consumers in Jakarta choose direct (home) delivery as their last-mile delivery method, which proposes consumers to receive the purchased goods at home. E-commerce could minimize trip distance travelled by consumers, but distance travelled by delivery service vehicles increase. It causes new problems such as environmental issues. Parcel lockers method appeared as the solution, which proposes advantages for consumers and package delivery operators. Its scheme could minimize distance travelled by both. The packages that dropped in the lockers would be picked up, sorted, and delivered to other lockers. Consumers would pick up their goods by travelling to destination lockers. It could minimize delivery trips. This study observed the consumer's point of view on parcel lockers method, and analyse the potency of parcel lockers. This study was carried out by two online surveys with four main variables that are location, information, cost, and punctuality. The results found that punctuality is the most affecting factor (38.8%) for consumers in choosing type of delivery service. Based on the services, respondents prefer to choose parcel lockers (68.4%) rather than direct delivery.

Barriers to online shopping

Certain factors affect the consumer buying behaviour while purchasing products online. Out of these, some commonness is discussed in the present paper which affects the adoption of online shopping. A simple search with keywords 'online shopping', 'online shopping of apparels and accessories', 'factors affecting online shopping', 'drivers of online shopping' and 'barriers of online shopping' has been done with Google Scholar. Substantial studies have been conducted globally to find out the factors affecting online shopping adoption. Different models and frameworks are available to understand these factors and it is difficult to present all work altogether. Thus, this paper tries to present a comprehensive framework of the relevant literature as barriers to online shopping. All available studies from 'anytime' referred till the date has been included to build a framework of reviews.

Aspect-Oriented Sentiment Analysis: A Topic Modeling-Powered Approach

Abstract Because of exponential growth in the number of people who purchase products online, e-commerce organizations are vying for each other to offer innovative and improved services to its customers. Current platforms give its customers innovative services such as product recommendations based on their purchase histories and location, product comparison, and most importantly, a platform for expressing their experience and feedback. It is important for any e-commerce organization to analyze this feedback and to find out the sentiment of the customers for giving them better products and services. As large reviews may contain feedback in a mixed manner where a customer gives his opinion on different product features in the same review, finding out the exact sentiment is tedious. This work proposes aspect-specific sentiment analysis of product reviews using a well-sophisticated topic modeling algorithm called latent Dirichlet allocation (LDA). The topic words, thus, extracted are mapped with various aspects of an entity to perform the aspect-specific sentiment analysis on product reviews. Experiments with synthetic and real dataset show promising results compared to existing methods of sentiment analysis.

Coordination of e-commerce supply chain when e-commerce platform providing sales service and extended warranty service

ABSTRACT With the rapid development of cybereconomy and the enhancement of sales service, many e-commerce platforms provide extended warranty service to alleviate consumers from worries about product quality when consumers purchasing products online. This study examines the decisions and coordination of the e-commerce supply chain where the e-commerce platform dominates and provides sales service and extended warranty service. The findings show that the centralised decision-making model is an ideal model because of the low sales price, high service level and high extended warranty price. With the increase of the consumers’ sensitivity coefficient to the extended warranty service price, sales price increases but extended warranty service price and service level decrease, the retailer’s profit and the platform's profit decrease. The proposed contract of ‘revenue sharing joint commission’ can realise the coordination of e-commerce supply chain.

Detection of Phishing Websites Using Hybrid Model

Online technologies have revolutionized the modern computing world. Thereare number of users who purchase products online and make payment through variouswebsites. There are multiple websites who ask user to provide sensitive data such asusername, password or credit card details etc. often for malicious reasons. This type ofwebsite is known as phishing website. The phishing website can be detected based on someimportant characteristics like URL (Uniform Resource Locator) and Domain identity.Several approaches have been proposed for detection of phishing websites by extracting thephishing data sets criteria to classify their legitimacy. However, there is no such approachthat can provide better results to the users from phishing attacks. This paper is an attemptto contribute in that area by presenting a hybrid model for classification to detect phishingwebsites with high accuracy and less error rate.

Selecting Products Considering the Regret Behavior of Consumer: A Decision Support Model Based on Online Ratings

With the remarkable promotion of e-commerce platforms, consumers increasingly prefer to purchase products online. Online ratings facilitate consumers to choose among products. Thus, to help consumers effectively select products, it is necessary to provide decision support methods for consumers to trade online. Considering the decision makers are bounded rational, this paper proposes a novel decision support model for product selection based on online ratings, in which the regret aversion behavior of consumers is formulated. Massive online ratings provided by experienced consumers for alternative products associated with several evaluation attributes are obtained by software finders. Then, the evaluations of alternative products in format of stochastic variables are conducted. To select a desirable alternative product, a novel method is introduced to calculate gain and loss degrees of each alternative over others. Considering the regret behavior of consumers in the product selection process, the regret and rejoice values of alternative products for consumer are computed to obtain the perceived utility values of alternative products. According to the prior order of the evaluation attributes provided by the consumer, the prior weights of attributes are determined based on the perceived utility values of alternative products. Furthermore, the overall perceived utility values of alternative products are obtained to generate a ranking result. Finally, a practical example from Zol.com.cn for tablet computer selection is used to demonstrate the feasibility and practically of the proposed model.

ONLINE SHOPPING BEHAVIOR AMONG UNIVERSITY STUDENTS: CASE STUDY OF MUST UNIVERSITY

The goal of the research is to identify and explore most commonly purchasing products online also influencing factors on the online buying behavior of the MUST university students. Functionality, privacy, trust, firm reputation and perceived value are the major influencing factors on consumer buying online behavior. Quantitative study approached has been adopted in this study and total 100 questionnaire samples have been distributed among MUST university business faculty students. The findings indicated that about 99.0% MUST students are involved in online purchasing and most computer/electronic/ mobile are the common products purchased online. The relationship and data reliability of the influencing factors are significantly reliable and has significant relationships which justify the study hypothesis. Study concluded that among the influencing factors functionality of the web vendors ranked high importunacy followed by privacy, perceived value, firm reputation and trust. The lower ranking of trust is indicating that major respondents group feels uncomfortable or unsafe while trusting on the web vendor

How fashion brands approach cross-border e-commerce pricing

Cross-border e-commerce is the fastest, easiest and most cost-effective way for brands to expand their international sales. Research suggests that a third of shoppers around the world have purchased products online from retailers in other countries, and that fashion is the most popular product category for such purchases. Fashion brands looking to reach international markets should thus consider cross-border e-commerce as a primary channel when entering new markets or strategising for international growth. But because independent research has revealed that pricing relative to local markets is the main driver behind cross-border purchases, even fashion brands should manage pricing carefully in order to maximise the advantages cross-border e-commerce offers as a channel. This paper describes some of the major challenges fashion brands face when pricing merchandise for cross-border e-commerce and offers examples of how some brands have approached these challenges per the experience of the author.

MODELING OF AN E-BUSINESS SYSTEM

Always before we start creating or accessing a particular system, it is more than necessary to have a clearer picture of how to create, respectively, how to approach a certain system, in this case of a e-business system. It is much easier as for systems makers, as well as for ordinary users when they have before them a model of how to be accessed in such a system, because such a thing will orient users much easier to purchase products online through various systems on the one hand, but on the other hand it would help makers of systems create much easier such systems when they have already before them the right design. Modeling systems may be done in different ways, depending on the context of its research, but we in this paper we will use UML diagrams for modeling online system where we will make a comparison between UML diagrams and we will present each type of UML diagram in terms of customer access in online systems. Also using predictive techniques as CPM and PERT techniques in the paper we will present the main activities required for access to an online system by different users, and their graphic presentation and critical path finding, which shows the best way to approach such a system. There shall not fail and the description of business models and the introduction of some e-business models that are commonly used in practice in the days of today.

Automatic Discovery of Abnormal Values in Large Textual Databases

Textual databases are ubiquitous in many application domains. Examples of textual data range from names and addresses of customers to social media posts and bibliographic records. With online services, individuals are increasingly required to enter their personal details for example when purchasing products online or registering for government services, while many social network and e-commerce sites allow users to post short comments. Many online sites leave open the possibility for people to enter unintended or malicious abnormal values, such as names with errors, bogus values, profane comments, or random character sequences. In other applications, such as online bibliographic databases or comparative online shopping sites, databases are increasingly populated in (semi-) automatic ways through Web crawls. This practice can result in low quality data being added automatically into a database. In this article, we develop three techniques to automatically discover abnormal (unexpected or unusual) values in large textual databases. Following recent work in categorical outlier detection, our assumption is that “normal” values are those that occur frequently in a database, while an individual abnormal value is rare. Our techniques are unsupervised and address the challenge of discovering abnormal values as an outlier detection problem. Our first technique is a basic but efficient q-gram set based technique, the second is based on a probabilistic language model, and the third employs morphological word features to train a one-class support vector machine classifier. Our aim is to investigate and develop techniques that are fast, efficient, and automatic. The output of our techniques can help in the development of rule-based data cleaning and information extraction systems, or be used as training data for further supervised data cleaning procedures. We evaluate our techniques on four large real-world datasets from different domains: two US voter registration databases containing personal details, the 2013 KDD Cup dataset of bibliographic records, and the SNAP Memetracker dataset of phrases from social networking sites. Our results show that our techniques can efficiently and automatically discover abnormal textual values, allowing an organization to conduct efficient data exploration, and improve the quality of their textual databases without the need of requiring explicit training data.

The influence of information cascades on online purchase behaviors of search and experience products

Online users usually observe or refer to others' behaviors and discount their own information when purchasing products online. This research employed a fixed-effect regression model to elucidate ho...

A Survey on Awareness and Satisfaction Level of the Consumers of Online Gifting with Special Reference to Ahmedabad City

India is well known as the land of Gods, Worships and Offerings, but do you know there are more than 100 Million Intermet users in our developing country India. In addition to that around 50 million people are purchasing products online every year. Online selling has reduced the costs of marketing of the companies; they have come up with the cheapest rate of products by removing layers in the supply chain. This has created a win-win situation for both customers as well as sellers. No doubt India is a developing country where now a day's people have hectic work schedules which affect the relations, but the online gifting has strengthens the bond of relationships. Sitting at Kanyakumari a friend can send a cake, gift or bouquet to his best friend staying at Punjab on special occasions like Birthday or Anniversary. This study is the extended version of the survey made for testing the consumer's perception towards the online shopping in Ahmadabad. This study highlights consumer's perception towards online gifting and their preference towards online gifting. This enables e-retailer to attract and get potential customers converted to his owm customer and encourage them in a better way to make buying decision. An attempt is made here to show the views of the people on online gifting products in Ahmadabad, Gujarat.

Travel web-site design: Information task-fit, service quality and purchase intention

Several studies have explored how buyers form intentions to purchase products online. However, few studies have focused on the role that information-task fit and website design quality exert on perceived service quality and purchase intent. The data used for this study was gathered during experiments conducted on Amazon's Mechanical Turk's crowd sourcing platform. The results indicated that website design influenced perceived product quality and online purchase intentions. The implications of these results for future research and website design are presented.

Factors obstructing intentions to trust and purchase products online

Purpose – The purpose of this paper is to explore reasons for not buying products through online. The study also tries to explain the relationship between intentions to trust (IT) and online purchase intentions. Design/methodology/approach – Data were collected through well-structured instrument, distributed to 226 students of Masters of Business Administration and Masters of Computer Applications departments of a north Indian University. Confirmatory Factor Analysis and Structural Equation Modelling were used to analyse the data and to test the formulated hypotheses. Findings – The results of the study highlight that 90 per cent of the respondents are aware about online shopping sites but only 38 per cent are online buyers of various products. Major reasons for not shopping are lack of security, absence of physical examination and testing of products, lack of product’s complete information, unattractive visual displays and layouts, etc. However, it is observed that nearly 79 per cent respondents have positive intentions to buy products online in near future. Research limitations/implications – There is a need to study actual online buying behaviour. Also, models like Technology Acceptance Model and Diffusion of Innovation have not been studied. As the study was confined to students only, it can be replicated to other age group consumer segments and extended to other emerging economies as well. There is a need to take into consideration some other important dimensions in the future studies, namely, predictability, familiarity, third party certification, attitude, ease of use, perceived risk, etc., for the better analysis of behaviour. Practical implications – E-vendors must properly implement money back guarantee schemes when there is non-delivery of ordered goods, provide dispute resolution system, instil confidence in customers, highlight security, privacy policy, display contacts details, etc., to increase customers’ IT and purchase products online. Originality/value – The paper identifies the factors that obstruct customer to purchase products online. More particularly, in Indian context the present study makes valuable contribution as the Indians have been reported to be techno phobic and uncertainty avoidant.

INSTAGRAMING IN RUSSIA

Instagram’s 200 million subscribers place it among the most popular Participatory Sensing Systems (PSSs) on the Internet today (de Melo et al. 2013). With its 62 million Internet users (Comscore, 2013), Russia is quickly becoming a powerful online market. With five million active daily users, Russia follows Brazil and US and comes ahead of UK by number of users (Alexa.com 2014).Being an early adopter of many technologies, the fashion industry actively uses image-based platform, by posting shots from runway shows, outfits of the day, pre-viewing new lines. Instagram is a no language barrier tool that is proving suitable for the visualization in the fashion industry.By observing the biggest Russian retailers TrendsBrands Instagram activity over a year, this paper outlines the most efficient way of brand communicating to consumers through images only as opposed to other mixed channel social media platforms employed, e.g. Facebook or Twitter. It studies the use of the most popular hashtags, influence of the photo sharing frequency as well as specific cultural behavior, which illustrates the promising potential of PSSs for the study of Russian online fashion environment. It also analyses the visual content that creates the biggest buzz. This research is complimented by in-depth interviews with a consumer sample from Trends-Brands follower to access the consumption interaction from the individual’s perspective.Deriving from Olbrich and Holsing (2011) business model of social shopping communities, Instagram is taken as an example. Discussing the phenomena of saling through Instagram, makes this platform a perfect example of social shopping community, which is are a mix of both: online shopping platform and social networking. Users of Instagram can share, comment, tag as well as purchase products online. Social shopping is a development of an online community that plays the role of both connecting consumers by communication and shopping (Olbrich and Holsing, 2011).Building up also on the Jenkins spredability (2013) theory as well Kozinetz (2010) nethnographic approach this research paper draws upon the distinctive features of Instagram as the channel not only to engage in the consumer-brand communication but also to communicate the consumption experience. This paper sets managerial implications for marketing communication managers who wish to conduct a successful strategy in Russia on Instagram.

On-line Shopping Trends, Patterns and Preferences of University Undergraduate Students: A Survey Study on Sylhet Region

With the explosion of the e-commerce in the past decade, different buying patterns and preferences have emerged for customer groups and other demographics. These patterns have been measured and collected by numerous independent marketing, business and even academic studies to understand how consumers connect with the new adventure of e-commerce. As the internet and online shopping is growing at a very fast pace worldwide, investigating this trend within Bangladeshi context is crucial considering that it is a relatively new trend in the country, the result is a lack of literature. This paper consists of the groundwork with a brief introduction of recent trends in e-commerce on people of Bangladesh; particularly its impact on university undergraduate students in Sylhet region. This has been followed by their general perceptions and preferences of the online shopping including products and website selection. Each of these e-commerce “characteristic” is compared to information combined from survey questions and open-ended discussions with a small sample group of university students at undergraduate level in Sylhet region. It also investigates into positive as well as negative website characteristics and sum up the favorable elements into a description of an e-commerce website that would suitable to the group being studied. Findings have been presented by means of the formation identified during the data analysis, indicated that an increasing number of the students at undergraduate level are now using the internet for purchase. It also observed that between male and female students, male students are purchasing products online more than female students. Although student’s participation is increasing, there are some limitations for what the potential numbers of students are not able to purchase via online.
 JEL Classification Code: A22; Z13

E-shopping: An Extended Technology Innovation

Online shopping is a new way in the world of retailing and future of ecommerce world definitely. A report by Avendus Capital in “India goes Digital” Indian ecommerce market was estimated at 28,500 Crore in 2011. According to Forrester, ecommerce market in India will grow fastest within Asia-Pacific region at a CAGR of 57% between years 2012-2016. Both single branded and multi branded companies are selling their products and services online. This increasing growth has generated the idea to conduct this study. In this context, research paper explores three factors that influence consumer intentions to purchase products online: safety oriented, convenience oriented and price oriented. The study analyzes the perception of 150 online shoppers in Bangalore regarding convenience, safety and price and their intention and attitude towards online shopping. A structured close ended questionnaire was administered to online shoppers. The collected data were analyzed in two stages. In the first stage correlation was performed to analyze between online shopping features and consumer purchase intention. In the second stage factor analysis was carried out to find the critical factors responsible for making consumer purchase intentions towards online shopping. The findings of this research shows that ‘safety’ produces trust, ‘convenience’ originates user friendliness and ‘price’ provides economy, all three influenced directly the attitude towards purchase intentions of consumers to shop online. This paper provides useful insight for the researchers to understand the consumer’s attitude towards online shopping intention.

An Empirical Study on Behavioral Intent of Consumers in Online Shopping

An e-commerce website would taste its success only through its strong business models and loyal customers. Customer loyalty is given the prime weightage as the customer on the internet web are highly volatile and switch the brands very quickly than a brick and mortar store due to the lesser degree of physical evidence. In this scenario it becomes highly essential for management of the e-tailers to understand the behavior of the consumers at various situations as this may provide an important insight of the consumer which may be grabbed to create a highly sustainable website to provide highest customer satisfaction. This paper examines the relationship between purchasing decisions and intentions to shop online and the factors affecting the decisions regarding the same in the minds of the consumers. Consumer intention in web based shopping is analyzed through the comparison of the factors that facilitate or inhibit online purchasing of products and services using the theory of planned behavior. A theoretical model that explains purchase intentions was tested with a sample of 120 consumers.

Online shopping behaviour: moderating role of gender and product category

Various studies have investigated the effect of risk perception of consumers on their intention to purchase products online. However, it remains to be shown how the effect of risk perception on intention to purchase online differs across gender or across categories of products being purchased. More importantly, it is important to understand whether gender and product category, together, have a moderating role in influencing the relationship between perceived risk and intention to purchase. In this paper, the role of gender and product category, in moderating the impact of perceived risk on intention to purchase, is examined. Analysis from a survey of 183 respondents, based on their interaction with two specific websites, reveals that gender, by itself, does not directly impact the relationship between perceived risk and intention to purchase, indicating the levelling off of the online gender gap. However, the gender effect manifests itself when analysed in association with product category, indicating that males and females do differ in their risk perception based on the category of product being purchased. We provide the implications of this finding for theory and research on internet.