Fairs for e-commerce: the benefits of aggregating buyers and sellers

In recent years, many new and interesting models of successful online business have been developed. Many of these are based on the competition between users, such as online auctions, where the product price is not fixed and tends to rise. Other models, including group-buying, are based on cooperation between users, characterized by a dynamic price of the product that tends to go down. There is not yet a business model in which both sellers and buyers are grouped in order to negotiate on a specific product or service. The present study investigates a new extension of the group-buying model, called fair, which allows aggregation of demand and supply for price optimization, in a cooperative manner. Additionally, our system also aggregates products and destinations for shipping optimization. We introduced the following new relevant input parameters in order to implement a double-side aggregation: (a) price-quantity curves provided by the seller; (b) waiting time, that is, the longer buyers wait, the greater discount they get; (c) payment time, which determines if the buyer pays before, during or after receiving the product; (d) the distance between the place where products are available and the place of shipment, provided in advance by the buyer or dynamically suggested by the system. To analyze the proposed model we implemented a system prototype and a simulator that allow to study effects of changing some input parameters. We analyzed the dynamic price model in fairs having one single seller and a combination of selected sellers. The results are very encouraging and motivate further investigation on this topic

USING FACEBOOK BRAND COMMUNITIES TO ENGAGE CUSTOMERS: A NEW PERSPECTIVE OF RELATIONSHIP MARKETING

With the advent of digital age, engaging customers on social networking sites has become a crucial marketing activity of companies. This study, through a questionnaire survey of 320 students in India, explores the role of customer engagement in enhancing customer relationships on Facebook brand communities so as to add value to the company. The direct effect of customer participation on word of mouth as well as an indirect effect through the mediation of customer engagement is investigated. The results show a positive relationship between customer participation and word of mouth, results also delineate that customer participation leads to customer engagement, which in turn plays a crucial role in generating word of mouth. This study is the first of its kind in Indian context.&nbsp

Optimal strategy for selling on group-buying website

Purpose: The purpose of this paper is to help business marketers with offline channels to make decisions on whether to sell through Group-buying (GB) websites and how to set online price with the coordination of maximum deal size on GB websites. Design/methodology/approach: Considering the deal structure of GB websites especially for the service fee and minimum deal size limit required by GB websites, advertising effect of selling on GB websites, and interaction between online and offline markets, an analytical model is built to derive optimal online price and maximum deal size for sellers selling through GB website. This paper aims to answer four research questions: (1) How to make a decision on maximum deal size with coordination of the deal price? (2) Will selling on GB websites always be better than staying with offline channel only? (3) What kind of products is more appropriate to sell on GB website? (4)How could GB website operator induce sellers to offer deep discount in GB deals? Findings and Originality/value: This paper obtains optimal strategies for sellers selling on GB website and finds that: Even if a seller has sufficient capacity, he/she may still set a maximum deal size on the GB deal to take advantage of Advertisement with Limited Availability (ALA) effect; Selling through GB website may not bring a higher profit than selling only through offline channel when a GB site only has a small consumer base and/or if there is a big overlap between the online and offline markets; Low margin products are more suitable for being sold online with ALA strategies (LP-ALA or HP-ALA) than high margin ones; A GB site operator could set a small minimum deal size to induce deep discounts from the sellers selling through GB deals. Research limitations/implications: The present study assumed that the demand function is determinate and linear. It will be interesting to study how stochastic demand and a more general demand function affect the optimal strategies. Practical implications: This paper provides a very useful model framework and optimal strategies for sellers’ selling on GB website. It takes advantage of the analytical model to explain much typical practical phenomenon for E-commerce like free sale with limited availability and so forth. It also helps GB website operator to induce deep discount from sellers. Originality/value: This paper is a first attempt to examine the seller's GB sale decision problem regarding to price and bounds on deal sizes. It analyses how the minimum deal size set by the GB website affect the optimal decision of sellers’. Moreover, it also discusses the impact of the interactions between online and offline markets on sellers’ decisionPeer Reviewe

Analysis of Life Context of On-Line Group-Buying Population by Dynamic Decision

While it is difficult to avoid uncertainties when shopping on the Internet, trust can reduce customers’ perceived uncertainties, and enhance their willingness and frequency to buy products and services. The difference in time and space information transparency between customers and on-line sellers, as well as the complex unpredictability of network structure, result in frequent uncertainty for on-line transactions. Therefore, through text mining and integrating the Genetic Algorithm (GA) with the Support Vector Machine (SVM), this project classifies the data of on-line group buying community complaints according to the posts left on Facebook and the three major group-buying websites of Taiwan. The terms are selected based on term frequency, document frequency, uniformity, and conformity, while document classification effectiveness is calculated using precision, recall rate, and F-measure. Community complaints are classified into the uncertain performance indicators that influence on-line group buying for integrated statistics, in order that specific performance indicators of community group-buying websites can be generated. Afterwards, based on the on-line group buying community performance indicator sequence, as integrated according to the dynamic Multicriteria Optimization and Compromise Solution (VIKOR) method and prosperity countermeasure signals, grey correlation sorting is applied to analyze the dynamic performance indicator sequence of different communities, in order to determine the life context of different populations for the reference of on-line group buying providers

Study of the Influence of Brand Image on Consumers\u27 Online Shopping Intention——in the Case of Cosmetics

With the rapid development of science and technology, people’s acceptance of online shopping is increasing. As an important part of online shopping, small and medium-sized cosmetics enterprises have the characteristics of small investment scale and flexible adjustment of brand strategy, but previous research lack sustained and effective methods and tools to analysis brand impact. The paper takes INOHERB as an example, to explore the connotation and feature of brand and brand image from the perspective of the cosmetics online shopping, as well as the relevant theories of online shopping intention. Through literature review, the paper applies the bell brand image measurement model, dividing brand image into corporate image and product or service image, and user image. It also adds the analysis on the consumption characteristics, so as to test result reasonableness of the brand image analysis’s influence on online shopping intention. Data were collected from college female students by print questionnaires and online surveys. The result indicated that corporate image has a strong influence on consumer online shopping intention. Besides, product and service image also have a significant influence on consumer online shopping intention, consumers are more willing to buy cosmetics online above average prices with positive word of mouth and good quality

Analysis of Life Context of On-Line Group-Buying Population by Dynamic Decision

While it is difficult to avoid uncertainties when shopping on the Internet, trust can reduce customers’ perceived uncertainties, and enhance their willingness and frequency to buy products and services. The difference in time and space information transparency between customers and on-line sellers, as well as the complex unpredictability of network structure, result in frequent uncertainty for on-line transactions. Therefore, through text mining and integrating the Genetic Algorithm (GA) with the Support Vector Machine (SVM), this project classifies the data of on-line group buying community complaints according to the posts left on Facebook and the three major group-buying websites of Taiwan. The terms are selected based on term frequency, document frequency, uniformity, and conformity, while document classification effectiveness is calculated using precision, recall rate, and F-measure. Community complaints are classified into the uncertain performance indicators that influence on-line group buying for integrated statistics, in order that specific performance indicators of community group-buying websites can be generated. Afterwards, based on the on-line group buying community performance indicator sequence, as integrated according to the dynamic Multicriteria Optimization and Compromise Solution (VIKOR) method and prosperity countermeasure signals, grey correlation sorting is applied to analyze the dynamic performance indicator sequence of different communities, in order to determine the life context of different populations for the reference of on-line group buying providers

Stated Choice Analysis of Conditional Purchase and Information Cue Effects in Online Group Purchase

Group-purchase institutions, a type of Internet shopping website, allows consumers to aggregate their demands for a product to gain discounts in purchase price. Modeling consumers’ bidding behavior in this institution using the economic perspective of constraint, expectation, and preference interactions, we study two group-purchase mechanisms (i.e., conditional purchase and information cue) on a buyer’s purchase choice across competing group-purchase alternatives. Using a conditional purchase mechanism, a buyer is not obliged to commit to the purchase if the best price is not met (i.e., the final offered price is greater than the best available lowest price). Through the information cue, a buyer could obtain information on the current number of orders collected. We analyzed a set of laboratory experimental data based on a group-purchase institution using the stated choice method. We find that a buyer is more likely to buy through group-purchase when a conditional purchase mechanism is provided. However, providing more information does not necessarily alleviate buyer uncertainty and inertia. The presence of information cue does induce them to choose a riskier but cheaper group-purchase option. In such cases, the choice elasticity of a risky group-purchase option is more sensitive to the information cue than to the conditional purchase mechanism