Characterizing Key Stakeholders in an Online Black-Hat Marketplace

Over the past few years, many black-hat marketplaces have emerged that facilitate access to reputation manipulation services such as fake Facebook likes, fraudulent search engine optimization (SEO), or bogus Amazon reviews. In order to deploy effective technical and legal countermeasures, it is important to understand how these black-hat marketplaces operate, shedding light on the services they offer, who is selling, who is buying, what are they buying, who is more successful, why are they successful, etc. Toward this goal, in this paper, we present a detailed micro-economic analysis of a popular online black-hat marketplace, namely, SEOClerks.com. As the site provides non-anonymized transaction information, we set to analyze selling and buying behavior of individual users, propose a strategy to identify key users, and study their tactics as compared to other (non-key) users. We find that key users: (1) are mostly located in Asian countries, (2) are focused more on selling black-hat SEO services, (3) tend to list more lower priced services, and (4) sometimes buy services from other sellers and then sell at higher prices. Finally, we discuss the implications of our analysis with respect to devising effective economic and legal intervention strategies against marketplace operators and key users.Comment: 12th IEEE/APWG Symposium on Electronic Crime Research (eCrime 2017

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

CONTENT ON SPORTS PRODUCT INDUSTRY WEBSITES: DIGITAL MARKETING ANALYSIS

The sports industry is an industry that has significant revenue potential. This can then be further optimized with proper marketing. Digital marketing through a website is a marketing step that has relatively good potential. This research will determine how digital marketing is carried out for sports products through websites. This research will be conducted using a qualitative approach. The data used in this study is secondary data derived from the results of previous research and studies. This study found that the website can function as a medium for spreading information related to sports products, especially products that have just come out. Then the help of SEO can increase the website’s optimization so that it will be on the first page of searches using Google so that, in the end, it will increase the amount of traffic on the website

Suljettujen online-mainosalustojen strategiat — tapaukset Google ja Facebook

This thesis studies closed ad platforms in the modern online advertising industry. The research in the field is still nascent and the concept of a closed ad platform doesn’t exist. The objective of the research was to discover the main factors determining the revenue of online advertising platforms and to understand why some publishers choose to establish their own closed ad platforms instead of selling their inventory for third-party ad platforms. The concept of a closed ad platform is defined leveraging the existing online advertising literature and the platform governance structure theory. Using the case study method, Google and Facebook were chosen as the cases as they have driven most of the innovation in the field and quickly gained significant market share. In total, 47 people were interviewed for this study, most of them working for advanced online advertisers. Based on the interviews, a microeconomic mathematic formula is created for modeling an ad platform’s net advertising revenue. The formula is used to identify the five main drivers of an ad platform’s revenue an each of them are studied in depth. The results suggest that the most important revenue drivers the ad platforms can affect are access to an active user base, the efficiency of ad serving and the comprehensiveness of measurement. Setting up a closed ad platform requires significant investments from a publisher and should be only done if it can improve the advertisers’ results. After it’s been established, a closed platform can leverage its position to collect user data and structured business data to optimize its performance further. The results provide a structured understanding of the main dynamics in the industry that can be used in decision-making and a basis for future research on closed ad platforms.Tämä diplomityö tutkii suljettuja mainosalustoja nykyaikaisella online-mainonta-alalla. Alan tutkimus on vielä aluillaan ja suljetun mainosalustan konseptia ei ole olemassa. Tämän tutkimuksen tavoitteena oli löytää online-mainosalustojen liikevaihdon määrittävät tekijät ja ymmärtää miksi jotkut julkaisijat valitsevat omien suljettujen mainosalustojen perustamisen mainospaikkojen kolmansien osapuolien mainosalustoille myymisen sijaan. Suljetun mainosalustan konsepti määritellään olemassaolevaa online- mainontakirjallisuutta ja alustojen hallintarakenneteoriaa hyödyntäen. Tapaustutkimusmenetelmää käyttäen, Google ja Facebook valittiin tapauksiksi, sillä ne ovat ajaneet eniten innovaatioita alalla ja nopeasti saavuttaneet merkittävän markkinaosuuden. Yhteensä 47 henkilöä haastateltiin tätä tutkimusta varten, useimmat heistä edistyneiden online-mainostajien työntekijöitä. Haastattelujen perusteella luodaan mikrotaloudellinen matemaattinen kaava mainosalustan nettoliikevaihdon mallintamiseksi. Kaavaa käytetään tunnistamaan mainosalustan liikevaihdon viisi pääkomponenttia, ja kuhunkin niistä perehdytään syvällisemmin. Tulokset viittaavat, että tärkeimmät liikevaihdon ajurit, joihin mainosalustat voivat vaikuttaa ovat pääsy aktiiviseen käyttäjäkantaan, mainosten näyttämisen tehokkuus ja mittaamisen kattavuus. Suljetun mainosalustan perustaminen vaatii merkittäviä investointeja julkaisijalta ja tulisi tehdä ainoastaan, jos sillä voidaan parantaa mainostajien tuloksia. Suljetun alustan perustamisen jälkeen sen positiota voidaan hyödyntää käyttäjädatan ja strukturoidun liiketoimintadatan keräämiseksi suorituskyvyn edelleen optimoimiseksi. Tulokset tarjoavat toimialan päädynamiikkojen ymmärryksen, jota voidaan käyttää päätöksenteossa sekä pohjana suljettujen mainosalustojen edelleen tutkimiseksi tulevaisuudessa

A dynamic pricing model for unifying programmatic guarantee and real-time bidding in display advertising

There are two major ways of selling impressions in display advertising. They are either sold in spot through auction mechanisms or in advance via guaranteed contracts. The former has achieved a significant automation via real-time bidding (RTB); however, the latter is still mainly done over the counter through direct sales. This paper proposes a mathematical model that allocates and prices the future impressions between real-time auctions and guaranteed contracts. Under conventional economic assumptions, our model shows that the two ways can be seamless combined programmatically and the publisher's revenue can be maximized via price discrimination and optimal allocation. We consider advertisers are risk-averse, and they would be willing to purchase guaranteed impressions if the total costs are less than their private values. We also consider that an advertiser's purchase behavior can be affected by both the guaranteed price and the time interval between the purchase time and the impression delivery date. Our solution suggests an optimal percentage of future impressions to sell in advance and provides an explicit formula to calculate at what prices to sell. We find that the optimal guaranteed prices are dynamic and are non-decreasing over time. We evaluate our method with RTB datasets and find that the model adopts different strategies in allocation and pricing according to the level of competition. From the experiments we find that, in a less competitive market, lower prices of the guaranteed contracts will encourage the purchase in advance and the revenue gain is mainly contributed by the increased competition in future RTB. In a highly competitive market, advertisers are more willing to purchase the guaranteed contracts and thus higher prices are expected. The revenue gain is largely contributed by the guaranteed selling.Comment: Chen, Bowei and Yuan, Shuai and Wang, Jun (2014) A dynamic pricing model for unifying programmatic guarantee and real-time bidding in display advertising. In: The Eighth International Workshop on Data Mining for Online Advertising, 24 - 27 August 2014, New York Cit

THE ADVANTAGES AND LIMITATIONS OF E-COMMERCE TO BOTH CUSTOMERS & BUSINESSES

One of the major new trends affecting the business world, the consumers and the economy is the emergence of e-commerce. In this paper, we will analyze both its advantages and limitations, clarifying the future impacts of this rapidly growing phenomenon. We will clarify the advantages that e-commerce helps businesses achieve, such as increasing their customers, penetrating new markets, reducing financial costs as well as enhancing customer satisfaction levels and retention rates. We will also showcase the various advantages that e-commerce provides customers such as the grater accessibility to a wider variety of products from numerous vendors, enhanced connivance in the shopping experience, as well as grater delight due the personalization features that the digital provides. Finally, we will examine the limitations that e-commerce businesses have that could limit their rapid growth. Such limitations include security and privacy issues as well as the lack of experience and proper infrastructure. This study will examine previous literature to provide a consolidated list of the advantages and limitations that e-commerce has resulted in, for both consumers and businesses

THE FOOD SERVICE INDUSTRY: TRENDS AND CHANGING STRUCTURE IN THE NEW MILLENNIUM

By 2010, foodservice establishments are projected to capture 53 percent of consumers' food expenditures, whereas in 1980, foodservice captured less than 40 percent. The foodservice industry accounts for approximately 4 percent of the Gross Domestic Product and about 11 million jobs. It has been rapidly changing due to economic factors, technological advances, and labor matters.1 This overview covers many of the issues and trends affecting the different segments of the foodservice supply chain including the foodservice operators, distributors and food manufacturers. Changing customer demographics are a driving force in the evolution of the foodservice industry. As the baby boomers reach middle age, they do not seem to have time to cook and their children and grandchildren do not seem to have the interest, or talent. The U.S. population in 2000 had over double ($6,500) the per capita discretionary income that it had in 1975 ($3,109) 2 and, with a high value for recreation and pleasure they are pulled out of the kitchen and into the restaurants. An ever-shrinking world also brings variety to menus as cultures and cuisines converge, introducing new flavors and textures. A tight labor market has affected the foodservice industry from top to bottom leading to a derived demand for convenience products from manufacturers. At all links in the chain, companies are experiencing mergers and acquisitions. Operators, manufacturers, and distributors are all fighting for a share of the profits as competition continues to intensify. This review of the foodservice industry incorporates interviews with industry professionals, current information from leading foodservice associations, and predictions from the top industry research firms and consultants.Agribusiness, Industrial Organization,

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

Economics of Daily-deal Websites: Advertising and Sampling Effects

With the advent of Groupon.com in 2008, daily deal platforms have seen phenomenal growth. Surprisingly there is very sparse analytical research that has studied the economics of the daily deal platforms that they connect merchants to consumers. We develop a stylized two-period Stackelberg leader-follower game-theoretic model to analyze the strategic interaction between heterogeneous merchants and a daily-deal website. The monopolist daily deal website is revenue maximize. Merchants take into consideration the sampling, advertising and cannibalization effects when they decide participation and discount strategy on the daily-deal website. Our result shows the merchants offer higher discount rates on the daily deal website and less known merchants benefit more from offering deals on the daily deal website. Some of the merchants never offer a deal on the platform even if offering a deal on the platform is free