Electronic Marketplace Research Articles

TRIVIA: visualizing reputation profiles to detect malicious sellers in electronic marketplaces

Reputation systems are an essential part of electronic marketplaces that provide a valuable method to identify honest sellers and punish malicious actors. Due to the continuous improvement of the computation models applied, advanced reputation systems have become non-transparent and incomprehensible to the end-user. As a consequence, users become skeptical and lose their trust toward the reputation system. In this work, we are taking a step to increase the transparency of reputation systems by means of providing interactive visual representations of seller reputation profiles. We thereto propose TRIVIA - a visual analytics tool to evaluate seller reputation. Besides enhancing transparency, our results show that through incorporating the visual-cognitive capabilities of a human analyst and the computing power of a machine in TRIVIA, malicious sellers can be reliably identified. In this way we provide a new perspective on how the problem of robustness could be addressed.

Advertising Role of Recommender Systems in Electronic Marketplaces: A Boon or a Bane for Competing Sellers?

Recommender systems have become the cornerstone of electronic marketplaces that sell products from competing sellers. Similar to traditional advertising, recommender systems can introduce consumers to new products and increase the market size which benefits sellers. The informative role of recommender systems in electronic marketplaces seems attractive to sellers because sellers do not pay the marketplaces for receiving recommendations. We show that in a marketplace that deploys a recommender system helping consumers discover the product that provides them the highest expected net utility, the sellers do not necessarily benefit from the “free” exposure provided by the recommender system. The impacts of the recommender system are the result of a subtle interaction between advertising effect and competition effect. The advertising effect causes sellers to advertise less on their own and the competition effect causes them to decrease prices in the presence of a recommender system. Essentially, sellers “pay” in the form of more intense price competition because of the recommender system. Furthermore, the competition effect is exacerbated by the advertising effect because the recommender system alters a seller's own strategies related to advertising intensity and price from being strategic substitutes in the absence of the recommender system to being strategic complements in the presence of the recommender system. As a result of these two effects, we find that sellers are more likely to benefit from the recommender system only when it has a high precision. The results do not change qualitatively whether sellers use targeted advertising or uniform advertising. However, we find that a recommender system that benefits sellers when sellers do not employ targeted advertising may actually hurt sellers when sellers adopt targeted advertising with a high precision. On the other hand, in the electronic marketplace with the recommender system, an increase in sellers' targeting precision beyond a threshold softens price competition, increases seller profits, and reduces consumer surplus.

Automated concurrent negotiations: An artificial bee colony approach

In Electronic Marketplaces (EMs), a number of unknown entities can interact to conclude purchase actions. Interactions are, usually, between buyers and sellers. Both groups of entities (e.g., buyers, sellers) aim to acquire items in the most profitable price. The discussed interactions are realized in the form of negotiations over a number of items characteristics. In this paper, we focus on the buyer side and deal with automated multi-issue concurrent negotiations. Such negotiations are between buyers and multiple sellers having in their property specific items. Each buyer negotiates with a number of sellers trying to achieve the most profitable value for a number of items’ characteristics. We propose an optimization model for achieving the maximum possible utility. Our method adopts the principles of the Artificial Bee Colony (ABC) algorithm that offers a number of advantages compared to other Swarm Intelligence (SI) methods (e.g., Particle Swarm Optimization – PSO). The buyer, based on a number of threads, tries to find the optimal agreement when negotiating with a group of sellers. Every agreement, realized with a specific seller, results a utility for the buyer concluded over a weighted scheme on the items characteristics. Each thread adopts a weights adaptation model for optimizing the utility. A set of experiments reveal the strengths and weaknesses of the proposed model. We also report on a comparison assessment between the proposed method and other efforts found in the respective literature.

An Argumentation-Based Negotiation Approach in Electronic Marketplace based on Semantic Web

The argumentation-based negotiation is studied in several research works, the majority of them propose general models. The modeling of argumentation-based negotiation mechanism for a domain, such as e-commerce takes into account its specificity with regard to the nature of exchanged information. This study aimed to propose a new approach of argumentation-based negotiation in e-commerce which synthesize and improve the general approaches of argumentation. The model of argument is studied, for the use of its elements and structure. The force field analysis technique is improved to represent the various forces which conduct decisions taken during a dialog of negotiation. Semantic Web technologies are employed for the representation of the arguments, forces conducting agents' decisions, as well as the protocol of negotiation. Semantic web technologies are also employed in the representation of all knowledge which relates to marketplace and its elements (products, buyer and sellers). This study is supported by an agent based modeling of an electronic marketplace, in which a set of agents is developed and a set of ontology is created. Laptops are taken as a case of study of sold products. In addition, an argument interchange mechanism is implemented to transfer the arguments represented by OWL-DL sub-language into the content of FIPA-ACL messages. This modeling forms part to a work of development for the validation of the proposed approach.

Mining customer requirements from online reviews: A product improvement perspective

Big data commerce has become an e-commerce trend. Learning how to extract valuable and real time insights from big data to drive smarter and more profitable business decisions is a main task of big data commerce. Using online reviews as an example, manufacturers have come to value how to select helpful online reviews and what can be learned from online reviews for new product development. In this research, we first proposed an automatic filtering model to predict the helpfulness of online reviews from the perspective of the product designer. The KANO method, which is based on the classical conjoint analysis model, is then innovatively applied to analyze online reviews to develop appropriate product improvement strategies. Moreover, an empirical case study using the new method is conducted with the data we acquired from JD.com, one of the largest electronic marketplaces in China. The case study indicates the effectiveness and robustness of the proposed approach. Our research suggests that the combination of big data and classical management models can bring success for big data commerce.

AN INTERVAL-VALUED FUZZY NUMBER APPROACH FOR SUPPLIER SELECTION

Supplier assessment in supply chain management and electronic marketplaces plays an important role in the business transaction. Many methods have been proposed to deal with the supplier selection problems. Some of them are based on fuzzy set theory. However, traditional fuzzy numbers cannot precisely express the vagueness in the decision process. In this paper, we are going to propose a new fuzzy multiple criteria decision making model based on interval-valued fuzzy numbers to tackle the supplier selection problem in the circumstances where uncertainty is introduced. Usually, fuzzy numbers are employed to express uncertainty. For a fuzzy number, the degree of the membership is a crisp number whereas the degree of the membership for an interval-valued fuzzy number is an interval. To grasp the vagueness more precisely, we employ interval-valued fuzzy numbers to represent the ratings and weights of the evaluation instead of traditional fuzzy numbers. One of the merits of our method compared to the traditional fuzzy methods is that our method can express the uncertainty more precisely in the evaluation process. Beside, we propose a new ranking method for intervalvalued fuzzy numbers.

Optimized flexibility management enacting Data Centres participation in Smart Demand Response programs

In this paper we address the problem of Data Centres (DCs) integration into the Smart Grid scenario by proposing a technique for scheduling and optimizing their operation allowing them to participate in Smart Demand Response programs. The technique is leveraging on DCs available flexible energy resources, on mechanisms for eliciting this latent flexibility and on an innovative electronic marketplace designed for trading energy flexibility and ancillary services. This will enact DCs to shape their energy demand to buy additional energy when prices are low and sell energy surplus when prices are high. At the same time DCs will be able to provide increased energy demand due to a large un-forecasted renewable energy production in their local grid, shed or shift energy demand over time to avoid a coincidental peak load, provide fast ramping power by turning on their backup fossil fuelled generators and injecting the energy surplus in the grid and finally provide reactive power regulation by changing their power factor. Numerical simulations results considering traces of an operational DC indicate the great potential of the proposed technique for supporting DCs participation in Smart Demand Response programs.

A classification framework for data marketplaces

Trading data as a commodity has become increasingly popular in recent years, and data marketplaces have emerged as a new business model where data from a variety of sources can be collected, aggregated, processed, enriched, bought, and sold. They are effectively changing the way data are distributed and managed on the Internet. To get a better understanding of the emergence of data marketplaces, we have conducted several surveys in recent years to systematically gather and evaluate their characteristics. This paper takes a broader perspective and relates data marketplaces as currently discussed in computer science to the neoclassical notions of market and marketplace from economics. Specifically, we provide a typology of electronic marketplaces and discuss their approaches to the distribution of data. Finally, we provide a distinct definition of data marketplaces, leading to a classification framework that can provide structure for the emerging field of data marketplace research.

Supercapacitors Improve the Performance of Linear Power-Management Circuits: Unique new design options when capacitance jump from micro-farads to farads with a low equivalent series resistance

For over a century, the electronics design community has used electrolytic or polypropylene capacitors with values from 10 pF to 100,000 nF, and they come with voltage ratings from less than 10 V to several thousand volts. They are traditionally used for filters, dc blocking, and very short-term energy storage in electronic circuits. Within the last two decades, a new form of capacitors, electric doublelayer capacitors (EDLCs), entered the electronic marketplace, filling the gap between rechargeable batteries and electrolytic capacitors. Today, these devices are generally known as supercapacitors (SCs), ultracapacitors (UCs), electrochemical capacitors (ECs), and EDLCs.

Discretion Is the Better Part of Valor: Rebutting Negative Online Client Reviews

better part of valor is discretion!.] William Shakespeare Henry IV, Part 1, Act 5, Scene 4, Lines 119-120 PUBLIC criticism of lawyers is nothing new. President Theodore Roosevelt, for example, described lawyers as hired cunning during commencement address at Harvard University in 1905. (1) What is new, however, are the many digital platforms now available for disgrunded former clients to publicly broadcast their criticism of individual lawyers. (2) The criticism involved often does not rise to the level of threatened claim--with he is lousy more common than she committed malpractice. Given the importance of web-based marketing for many lawyers today, this kind of criticism can nonetheless pose very real problem for lawyer's reputation in the electronic marketplace. When confronted with such public affronts, lawyers may contemplate responses that include revealing otherwise confidential information to set the record straight. This course, however, risks compounding the problem because the lawyer may inadvertently expose him or herself to regulatory discipline. Historically, the so-called exception to the confidentiality rule (3) has been applied to threatened or actual malpractice claims or bar complaints rather than simple public criticism. This leaves lawyer with dilemma over effectively--but safely (4)--rebutting negative online client reviews. This article will first survey the constraints imposed by the self-defense exception and will then turn to avenues for effectively rebutting such criticism from former clients without violating the confidentiality rule. (6) II. Self-Defense Is Generally No Defense The self-defense exception is found in ABA Model Rule of Professional Conduct 1.6(b)(5): (b) A lawyer may reveal information relating to the representation of client to the extent the lawyer reasonably believes necessary: (5) to establish claim or defense on behalf of the lawyer in controversy between the lawyer and the client, to establish defense to criminal charge or civil claim against the lawyer based upon conduct in which the client was involved, or to respond to allegations in any proceeding concerning the lawyer's representation of the (7) Today's exception traces its lineage to Canon 37, which was adopted in 1928 as an addition to the ABA Canons of Professional that were originally promulgated in 1908. (8) When the Canons were replaced by the ABA Model Code of Professional Responsibility in 1969, (9) the self-defense exception was carried over into Model DR 4-101 (C)(4). (10) When, in turn, the Model Code was replaced by the ABA Model Rules in 1983, (11) the exception continued as Model Rule 1.6(b)(2) and was then renumbered to its current position in 2003 as part of the Ethics 2000 amendments. (12) Comment 10 to ABA Model Rule 1.6 rounds out the text of the exception and focuses on civil claims, disciplinary charges and similar proceedings (13) involving a wrong allegedly committed by the lawyer: Where legal claim or disciplinary charge alleges complicity of the lawyer in client's conduct or other misconduct of the lawyer involving representation of the client, the lawyer may respond to the extent the lawyer reasonably believes necessary to establish defense. The same is true with respect to claim involving the conduct or representation of former client. Such charge can arise in civil, criminal, disciplinary or other proceeding and can be based on wrong allegedly committed by the lawyer against the client or on wrong alleged by third person, for example, person claiming to have been defrauded by the lawyer and client acting together. The lawyer's right to respond arises when an assertion of such complicity has been made. Paragraph (b)(5) does not require the lawyer to await the commencement of an action or proceeding that charges such complicity, so that the defense may be established by responding directly to third party who has made such an assertion. …

E-marketing services and e-marketing performance: the roles of innovation, knowledge complexity and environmental turbulence in influencing the relationship

ABSTRACTThe business-to-business electronic marketplace (e-marketplace) is becoming critical for small- and medium-sized enterprises (SMEs). However, which e-marketing services determine a firm’s e-marketing performance and how innovation, knowledge complexity and environmental turbulence influence the relationship between e-marketing services and e-marketing performance are under-researched topics in the field. We first empirically tested 176 SMEs from China to evaluate which e-marketing services are significantly related to e-marketing performance and how these services collectively influence the performance. Then, we used an NK model to examine how innovation, knowledge complexity and environmental turbulence mediate/moderate the relationship. The results show that five e-marketing services (e-CRM, e-SCM, e-competitiveness, IS/IT integration and information transparency) can greatly influence e-marketing performance; innovation positively mediates the relationship between e-marketing services and performance; and knowledge complexity and environmental turbulence positively moderate the relationship.

Small and medium sized manufacturer performance on third party B2B electronic marketplaces: The role of enabling and IT capabilities

This research investigates the determinants of the performance of small and medium sized manufacturers on business-to-business electronic marketplaces (B2B EMs). Based on the resource-based view, the framework proposed suggests that a manufacturing firm's performance on a B2B EM is determined by EM enabling capabilities, namely the online marketing capability, flexible manufacturing capability and content management capability. Further, the framework posits that these EM enabling capabilities are in turn determined by the firm's IT capability. Data from 358 online manufacturers participating in a B2B EM is collected and analyzed. The results confirm our hypotheses that the online marketing capability, flexible manufacturing capability and content management capability fully mediate the impact of the IT capability on the firm's online performance. Furthermore, the online marketing capability is found to be a stronger factor in influencing the manufacturer's online performance than the others.

E-visibility maturity model: A tool for assessment and comparison of individual firms and sets of firms in e-business

The Internet has transformed traditional patterns of firm-to-customer communication and opened new channels through which enterprises can engage with consumers around the world. Yet ways to measure firms’ visibility in this electronic marketplace have failed to keep pace with these developments. We present a new model – the e-visibility maturity (e-VM) model – that can be used to assess the degree to which a firm or set of firms has the potential to engage customers in the global e-business market. The suggested model is developed based on a literature review, an international survey of online customers, and a comprehensive review of 1868 firm websites representing 27 industries in five countries. After presenting the model, we show how it can be scaled to different levels (e.g., the industry or country level) using three illustrative cases: a set of four countries across industries; a set of four industries across countries; and a set of four individual firms. We found substantial differences in levels of e-visibility and its specific dimensions of interactivity, firm globalization, sociability, and security between the countries and specific firms sampled. The industries sampled all emphasize firm globalization and interactivity. The model offers a simple and reliable way to evaluate a company’s adaptation to the challenges of the social web, and can be used by strategists and policy makers at the industry or government level as well as to help firms establish strategies for improving their position in the online marketplace.

Service value exchange in B2B electronic marketplaces

Purpose – This paper aims to explore what aspects of organisational value can be realised through taking a service exchange perspective of e-marketplaces as opposed to a product transaction perspective Marketing is increasingly concerned with the notion of service value in business-to-business markets. Electronic marketplaces (e-marketplaces) have been used in B2B exchanges for many years and continually evolve as the understanding of e-marketplace participation and the technologies develop. Design/methodology/approach – A case study approach is taken using three large e-marketplace organisations and interviews with senior managers from each company. Findings – The paper argues that e-marketplaces should not be thought of solely as a product transaction mechanism but rather as a digital marketing and communication network where service, rather than products, forms the basis of a value creating exchange. Practical implications – Organisations can co-create value within an e-marketplace network but must market services value across organisational boundaries. Originality/value – The paper extends the literature in the area of e-marketplace trading and recognises the importance of the digital communication network in enabling service exchange between the e-marketplace, buyers and suppliers.

Selecting advisor agents using reliability, reputation and risks

This paper presents an enhanced trust model for evaluating and selecting trustworthy advisor agents in multi-agent systems. In particular, the study proposes a computational trust model based on three main components, reliability, reputation and risk of interactions (3-R) in order to select trustworthy advisor agents. These advisors are buyer agents which suggest a trustworthy seller agent for transaction. The 3-R model represents a method for calculating reliability, with each advisor that has similar preferences with the buyer. Experimental results are presented in defense of the proposed approach and to demonstrate the accuracy of the presented model in evaluating the trustworthiness of advisors, even when a social network of advisors contains few numbers of advisors. The proposed 3-R model will be useful for researchers to improve the safety of electronic marketplaces in the case where the buyer agent has no previous experience with sellers, and it has to trust the other buyers as an advisor to make a decision about sellers.

A simulation framework for measuring robustness of incentive mechanisms and its implementation in reputation systems

In game theoretical analysis of incentive mechanisms, all players are assumed to be rational. Since it is likely that mechanism participants in the real world may not be fully rational, such mechanisms may not work as effectively as in the idealized settings for which they were designed. Therefore, it is important to evaluate the robustness of incentive mechanisms against various types of agents with bounded rational behaviors. Such evaluations would provide us with the information needed to choose mechanisms with desired properties in real environments. In this article, we first propose a general robustness measure, inspired by research in evolutionary game theory, as the maximal percentage of invaders taking non-equilibrium strategies such that the agents sustain the desired equilibrium strategy. We then propose a simulation framework based on evolutionary dynamics to empirically evaluate the equilibrium robustness. The proposed simulation framework is validated by comparing the simulated results with the analytical predictions based on a modified simplex analysis approach. Finally, we implement the proposed simulation framework for evaluating the robustness of incentive mechanisms in reputation systems for electronic marketplaces. The results from the implementation show that the evaluated mechanisms have high robustness against a certain non-equilibrium strategy, but is vulnerable to another strategy, indicating the need for designing more robust incentive mechanisms for reputation management in e-marketplaces.

INMO: A Web Architecture For Real Estate Search Systems

This paper describes the development of a real estate electronic marketplace based on platform J2EE. A novel real estate search method based on Google Maps APIs is included. We explain the approach we propose on a prototypical implementation exhibiting the described functionality.

THE ELECTRONIC MARKETPLACE AS THE ELEMENT OF THE AGRICULTURAL MARKET INFRASTRUCTURE

The article discusses the issues of conducting transactions for agricultural products via the Internet between businesses. In particular, it is dedicated to the socalled electronic agricultural commodity marketplaces that are virtual meeting places of buyers and sellers of agricultural commodities. The purpose of this article is an indication of the changes taking place in the agricultural market under the influence of electronic marketplaces for agricultural commodities. The research method that was used to write this article was a case study. Three foreign electronic agricultural commodity marketplaces were analysed. Information on electronic marketplaces described came from their websites and scientific studies. The presented three examples of foreign electronic agricultural marketplaces show how complex issue is the development of electronic markets for agricultural commodities and how they induce profound changes in the functioning of traditional agricultural commodity markets.

A multi-attribute rating based trust model: improving the personalized trust modeling framework

Recently, trust models have contributed much to the success of online multimedia recommendation service. However, most of them only consider the case of binary ratings and ignore the attributes of ratings, which will limit their universal applicability. To address this problem, we propose a multi-attribute rating based trust model to improve the Zhang's Personalized trust modeling framework, an existing framework for trust modeling by using binary ratings in multi-agent electronic marketplaces. In our approach, it does not restrict users to using a single attribute rating; it allows a rating to be a certain value between 0 and 1 rather than only 0 or 1; it can improve assessment accuracy by calculating the similarity of common ratings between recommenders and users; and it considers the certainty of ratings to deal with the sudden change of partner's behaviours. Finally, experimental results show that, our approach can effectively model the trustworthiness of recommenders and providers, and it can also resist several malicious attacks.

Reputation and social (dis)approval in feedback mechanisms: An experimental study

Several previous studies have highlighted the role of feedback mechanisms in the success of electronic marketplaces. This paper contends that the effectiveness of online feedback mechanisms passes through two channels, namely a ‘reputational’ effect that has been largely documented in the literature, but also a ‘(dis)approval’ effect that has received less attention. We attempt to isolate these two effects using an experimental approach. For this purpose, we compare two experimental feedback systems that differ in the set of information available to participants. In the first feedback system, each player can observe the feedback profile of the other party, whereas in the second feedback system, this information is private. Our findings indicate that both systems improve cooperation. However, we observe that Private Feedback is less efficient in enhancing trust and trustworthiness than systems in which rating profiles are observed by partners. This finding is due to both a reduction of the number of assigned ratings and a lower impact of private ratings on subsequent decisions. All these results suggest that even if social (dis)approval matters, rating observability – and thus reputation – remains critical to induce honest behavior and improve efficiency in markets characterized by imperfect information.