Moving from Data-Constrained to Data-Enabled Research: Experiences and Challenges in Collecting, Validating and Analyzing Large-Scale e-Commerce Data

Widespread e-commerce activity on the Internet has led to new opportunities to collect vast amounts of micro-level market and nonmarket data. In this paper we share our experiences in collecting, validating, storing and analyzing large Internet-based data sets in the area of online auctions, music file sharing and online retailer pricing. We demonstrate how such data can advance knowledge by facilitating sharper and more extensive tests of existing theories and by offering observational underpinnings for the development of new theories. Just as experimental economics pushed the frontiers of economic thought by enabling the testing of numerous theories of economic behavior in the environment of a controlled laboratory, we believe that observing, often over extended periods of time, real-world agents participating in market and nonmarket activity on the Internet can lead us to develop and test a variety of new theories. Internet data gathering is not controlled experimentation. We cannot randomly assign participants to treatments or determine event orderings. Internet data gathering does offer potentially large data sets with repeated observation of individual choices and action. In addition, the automated data collection holds promise for greatly reduced cost per observation. Our methods rely on technological advances in automated data collection agents. Significant challenges remain in developing appropriate sampling techniques integrating data from heterogeneous sources in a variety of formats, constructing generalizable processes and understanding legal constraints. Despite these challenges, the early evidence from those who have harvested and analyzed large amounts of e-commerce data points toward a significant leap in our ability to understand the functioning of electronic commerce.Comment: Published at http://dx.doi.org/10.1214/088342306000000231 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Pricing strategy and technology choices: an empirical investigation of ‘Everyday Low Price’ in the domestic US Airline sector

The Conference program's website is located at http://www.krannert.purdue.edu/faculty/kkarthik/wise12/program.aspINTRODUCTION: There is a rich literature in economics on factors that govern airline prices. With approximately 50% of airline tickets sold online, there is now a renewed interest in investigating airline pricing particularly amongst Information Systems (IS) researchers. While market transparency created by online travel agents (OTAs) is a motivation enough to reexamine airline pricing, one missing piece calls for a thorough empirical investigation: In all extant studies (economics, marketing and IS), pricing by two major airli…postprin

From supply chains to demand networks. Agents in retailing: the electrical bazaar

A paradigm shift is taking place in logistics. The focus is changing from operational effectiveness to adaptation. Supply Chains will develop into networks that will adapt to consumer demand in almost real time. Time to market, capacity of adaptation and enrichment of customer experience seem to be the key elements of this new paradigm. In this environment emerging technologies like RFID (Radio Frequency ID), Intelligent Products and the Internet, are triggering a reconsideration of methods, procedures and goals. We present a Multiagent System framework specialized in retail that addresses these changes with the use of rational agents and takes advantages of the new market opportunities. Like in an old bazaar, agents able to learn, cooperate, take advantage of gossip and distinguish between collaborators and competitors, have the ability to adapt, learn and react to a changing environment better than any other structure. Keywords: Supply Chains, Distributed Artificial Intelligence, Multiagent System.Postprint (published version

Price formats as a source of price dispersion: A Study of online and ofline pices in the dmestic U.S. arline markets

Alarge body of research in economics, information systems, and marketing has sought to understand sources of price dispersion. Previous empirical work has mainly offered consumer- and/or product-based explanations for this phenomenon. In contrast, our research explores the key role played by vendors' price-format adoption in explaining price dispersion. We empirically analyze over a half-million online and offline prices offered by major U.S. airlines in the top 500 domestic markets. Our study shows that a vendor's price format remains an important source of price dispersion in both channels even after accounting for other factors known to impact dispersion in airline ticket prices. Importantly, this finding is true for both transacted and posted tickets. We document several other interesting empirical findings. First, the lower variance in the prices of "everyday low price" (EDLP) firms serves to reduce the market-level dispersion in prices when such firms are present. Moreover, the price variance of non-EDLP firms in these markets is also lower than in those markets in which EDLP competitors are absent. Second, we also find that dispersion in offered prices increases closer to the departure date, which is consistent with theoretical assertion that price dispersion increases with reservation prices. Finally, we continue to observe dispersion of online prices even after accounting for vendor strategy and other known sources of dispersion, suggesting that the prices are unlikely to converge even in the presence of sophisticated online search mechanisms.preprin

Online Price Dispersion Revisited: How Do Transaction Prices Differ from Listing Prices?

Price dispersion of a homogeneous product reflects market efficiency and has significant implications on sellers’ pricing strategies. Two different perspectives, the supply and demand perspectives, can be adopted to examine this phenomenon. The former focuses on listing prices posted by sellers, and the latter uses transaction prices that consumers pay to obtain the product. However, no prior research has systematically compared both perspectives, and it is unclear whether different perspectives will generate different insights. Using a unique data set collected from an online market, we find that the dispersion of listing prices is three times higher than the dispersion of transaction prices. More interestingly, the drivers of price dispersion differ significantly between listing and transaction data. The dispersion of listing prices reflects sellers’ perception of market environment and their pricing strategies, and it may not fully capture consumer behavior manifested through the variation of transaction prices. Our study indicates that the difference in perspectives taken on the online prices yields different results as to their dispersion

Unveiling the features of successful ebay sellers of smartphones: a data mining sales predictive model

JEL Classification guidelines (M310); (C380).EBay is one of the largest online retailing corporations worldwide, providing numerous ways for customer feedback on registered sellers. In accordance, with the advent of Web 2.0 and online shopping, an immensity of data is collected from manifold devices. This data is often unstructured, which inevitably asks for some form of further treatment that allows classification, discovery of patterns and trends or prediction of outcomes. That treatment implies the usage of increasingly complex and combined statistical tools as the size of datasets builds up. Nowadays, datasets may extend to several exabytes, which can be transformed into knowledge using adequate methods. The aim of the present study is to evaluate and analyse which and in what way seller and product attributes such as feedback ratings and price influence sales of smartphones on eBay using data mining framework and techniques. The methods used include SVM algorithms for modelling the sales of smartphones by eBay sellers combined with 10-fold cross-validation scheme which ensured model robustness and employment of metrics MAE, RAE and NMAE for the sake of gauging prediction accuracy followed by sensitivity analysis in order to assess the influence of individual features on sales. The methods were considered effective for both modelling evaluation and knowledge extraction reaching positive results although with some discrepancies between different prediction accuracy metrics. Lastly, it was discovered that the number of items in auction, average price and the variety of products available from a given seller were the most significant attributes, i.e., the largest contributors for sales.O EBay é uma das plataformas e retalho online de maior dimensão e abarca inúmeras oportunidades de extração de dados de feedback dos consumidores sobre vários vendedores. Em concordância, o advento da Web 2.0 e das compras online está fortemente associado à geração de dados em abundância e à possibilidade da sua respetiva recolha através de variados dispositivos e plataformas. Estes dados encontram-se, frequentemente, desestruturados o que inevitavelmente revela a necessidade da sua normalização e tratamento mais aprofundado de modo a possibilitar tarefas de classificação, descoberta de padrões e tendências ou de previsão. A complexidade dos métodos estatísticos aplicados para executar essas tarefas aumenta ao mesmo tempo que a dimensão das bases de dados. Atualmente, existem bases de dados que atingem vários exabytes e que se constituem como oportunidades para extração de conhecimento dado que métodos apropriados e particularizados sejam utilizados. Pretende-se, então, com o presente estudo quantificar e analisar quais e de que modo as características de vendedores e produtos influenciam as vendas de smartphones no eBay, recorrendo ao enquadramento conceptual e técnicas de mineração de dados. Os métodos utilizados incluem máquinas de vetores de suporte (SVMs) visando a modelação das vendas de smartphones por vendedores do eBay em combinação com validação cruzada 10-fold de modo a assegurar a robustez do modelo e com recurso às métricas de avaliação de desempenho erro absoluto médio (MAE), erro absoluto relativo (RAE) e erro absoluto médio normalizado (NMAE) para garantir a precisão do modelo preditivo. Seguidamente, é implementada a análise de sensibilidade para aferir a contribuição individual de cada atributo para as vendas. Os métodos são considerados eficazes tanto na avaliação do modelo como na extração de conhecimento visto que viabilizam resultados positivos ainda que sejam verificadas discrepâncias entre as estimativas para diferentes métricas de desempenho. Finalmente, foi possível descobrir que número de itens em leilão, o preço médio e a variedade de produtos disponibilizada por cada vendedor foram os atributos mais significantes, i.e., os que mais contribuíram para as vendas

A marketing mix model for a complex and turbulant environment

Purpose: This paper is based on the proposition that the choice of marketing tactics is determined, or at least significantly influenced, by the nature of the company’s external environment. It aims to illustrate the type of marketing mix tactics that are suggested for a complex and turbulent environment when marketing and the environment are viewed through a chaos and complexity theory lens. Design/Methodology/Approach: Since chaos and complexity theories are proposed as a good means of understanding the dynamics of complex and turbulent markets, a comprehensive review and analysis of literature on the marketing mix and marketing tactics from a chaos and complexity viewpoint was conducted. From this literature review, a marketing mix model was conceptualised. Findings: A marketing mix model considered appropriate for success in complex and turbulent environments was developed. In such environments, the literature suggests destabilising marketing activities are more effective, whereas stabilising type activities are more effective in simple, stable environments. Therefore the model proposes predominantly destabilising type tactics as appropriate for a complex and turbulent environment such as is currently being experienced in South Africa. Implications: This paper is of benefit to marketers by emphasising a new way to consider the future marketing activities of their companies. How this model can assist marketers and suggestions for research to develop and apply this model are provided. It is hoped that the model suggested will form the basis of empirical research to test its applicability in the turbulent South African environment. Originality/Value: Since businesses and markets are complex adaptive systems, using complexity theory to understand how to cope in complex, turbulent environments is necessary, but has not been widely researched. In fact, most chaos and complexity theory work in marketing has concentrated on marketing strategy, with little emphasis on individual tactics and even less on the marketing mix as a whole. Therefore, this paper can be viewed as an important foundation for a new stream of research using chaos and complexity theory to better understand marketing mixes and the choice of marketing tactics for complex and turbulent business environments

Marketing Mix in E-Commerce

The purpose of this thesis is to examine McCarthy’s marketing mix, that is, the 4Ps of marketing – product, price, place and promotion – in e-commerce literature and answer the research question "How are the 4Ps presented in the context of e-commerce?". This is a current topic because e-commerce has experienced rapid growth in recent years and the evolution is still expected to continue. E-commerce has been said to reshape business processes and entire industries, bringing benefits for both the companies and the consumers. Thus, it could be assumed that the 4Ps in e-commerce are presented very differently compared to the traditional views on products, price, place and promotion. The differences are indeed visible in the presentations of the Ps in the academic literature. When it comes to products, virtual and digital goods have emerged and have even replaced physical goods in some industries. Product assortment has grown remarkably and niche products generate a great amount of the online sales. Pricing, on the other hand, is described as dynamic and price discrimination seems to be popular, especially in the travel industry but also in retail. Place-wise the purchase in not connected to a physical place anymore as shopping is possible 24/7 in online stores. Also, the role of the Internet as a distribution channel is widely noticed, as it enables e-, multi- and omnichannel solutions. In the case of promotion, the Internet provides the infrastructure for online advertising. However, the biggest opportunity and challenge offered by e-commerce is the electronic word-of-mouth that facilitates the spread of both positive and negative experiences from consumer to consumer and hence, is rather difficult for companies to control

Strategic implementation of 'everyday low price' in electronic markets: a study of airline pricing on the internet

Working papers seriesAn Everyday Low Price (EDLP) strategy is a product-portfolio level pricing strategy by which a firm attempts to convey to consumers that prices across its product portfolio are consistently low. Empirically, the EDLP strategy is operationalized along two dimensions; the “everyday” component, which relates to the consistency in product prices over time, and the “low price” component, which implies that the prices set are on average lower than other prices available in the market. There may, however, be specific categories or markets in which even EDLP firms may prefer to eschew their consistency and low price goals. The U.S. domestic airline industry has two airlines that adopt the EDLP format while most others employ a promotional (HILO) pricing strategy, thus providing a rich context to investigate how the EDLP price-image strategy is implemented. We use a web crawler to gather information on over 270,000 ticket prices offered by the major airlines in 472 markets, and use a hierarchical linear model to analyze how these two dimensions of price vary with ticket categories and market conditions – defined in economics literature by advance purchase periods, weekend restrictions, airlines’ competitiveness, market distance, and hub operations. We find that the EDLP airlines emphasize the everyday dimension of their pricing much more than the low price dimension. Thus while their prices are systematically more consistent than their HILO competitors, their price levels show that they practice the same form of price discrimination with advance-purchase periods as their HILO competitors. Interestingly, while most airlines charge higher prices for tickets without weekend restriction, which are typically targeted towards business travelers, EDLP firms charge lower prices for these tickets. Further investigation at a category level reveals that these lower business fares are distinct features of short-haul markets where EDLP firms are known to enjoy certain cost advantages due to smaller equipment sizes of their flights. From the “everyday” point of view, we see that while there are no differences in the consistency of prices of EDLP tickets based on advance purchase periods, prices of business-focused EDLP tickets are distinctly more consistent than those of leisure-oriented tickets. Curiously, even in markets where EDLP firms are monopolists, they do not appear to be exercising their monopoly power; on the other hand, HILO firms distinctly employ discriminatory pricing in their monopoly markets. Perhaps this is a reflection of EDLP firms pursuing a limit-pricing/barrier-to-entry strategy. Our research shows that the practice of EDLP in online markets involves strategic variations in how price image is communicated.preprin

Is Australia Really the Lucky Country? Price Discrimination in Digital Distribution

Digital content services have become a major source of information and entertainment for people, and the Internet has provided a means by which businesses and consumers can easily and efficiently distribute it. A large amount of this content is copyrighted or tied to a service, and sold commercially through multiple electronic and physical distribution channels. The modern day ‘gamer’ is expected to have a broadband connection and be able to access various digital distribution platforms to acquire such content. Due to price information dispersion and web resources dedicated to consumer awareness, differential pricing of PC game digital content delivery has recently become a controversial topic. This study collected and analysed price data across six geographical regions for over 1000 software titles in order to determine whether there was regional price discrimination. The results showed strong support for the price discrimination proposition. Future studies will focus on the causes and effects of such pricing and how pricing strategies can better manage the relationship between consumer and publisher