E-COMMERCE: A NEW BUSINESS MODEL FOR THE FOOD SUPPLY/DEMAND CHAIN

The use of electronic commerce for quality control and cost cutting efficiencies by the food and agricultural industries in the United States is the focus of this paper. The food industry engages in e-commerce through 1.) Internet shopping for consumers called business-to-consumer (B2C) e-commerce 2.) Business-to-business (B2B) Internet market discovery exchanges used by food suppliers at any point in the supply chain, and 3.) Business-to-business (B2B) relationships that reduce costs and increase efficiencies in the procurement, storage and delivery of food to retail stores or distribution centers. This third use of e-commerce is the most highly developed and widely adopted. It allows retailers to share information about consumers' purchases and preferences with food manufacturers and farmers and for tracking food products' characteristics, source, and movement from production to consumer. This circle of information allows high quality and consistent products to be consumed at lower prices. This paper is about the development of e-commerce in the food industry, the economic concepts and goals that it meets, and the changes it brings to the industry. E-commerce both fosters and demands vertical coordination. It favors consolidation of firms. It changes the business culture from one of adversarial relationships to one of cooperation and trust. It changes the historical supply chain into a supply/demand loop while it lowers the cost of food. Policy issues arise around monopoly power, privacy, a diminution of variety, and the demise of small, undercapitalized firms.Industrial Organization, Marketing,

E-COMMERCE IN AGRICULTURE: DEVELOPMENT, STRATEGY, AND MARKET IMPLICATIONS

Marketing,

Endogene und exogene Preisdeterminanten bei online Auktionen am empirischen Fallbeispiel eBay

Der behandelte Forschungsgegenstand der Arbeit sind die endogenen und exogenen Ein-flussgrößen auf den Endpreis bei online Auktionen, bei starker Homogenität der Aukti-onsobjekte. Als Forschungsobjekt dient der iPod touch 8gb, da es von diesem Produkt zu dem beobachteten Zeitpunkt ein ausreichendes Angebot auf dem Portal eBay.de gab. Die Daten aller entsprechenden Auktionen wurden dann über einen Zeitraum von 15 Tagen beobachtet und aufgezeichnet. Danach wurden die Daten analysiert und die Ergebnisse waren teilweise doch überraschend. Signifikante Werte gab es für die Wochentage, daraus kann man schließen, dass an Wo-chenenden niedrigere Auktionsendpreise erzielt werden als während der Woche. Auch die Tageszeit zeigt einen ausschlaggebenden Einfluss auf den Endpreis der Auktionen; so wird bei Auktionen in den frühen Abendstunden ein niedrigerer Auktionsendpreis erzielt, als zu anderen Zeitpunkten. Der Zustand eines Artikels hat auch einen signifikanten Wert erzielt, demnach erzielen neue Geräte einen höheren Endpreis als bereits gebrauchte aber neuwertige Geräte. Einen entscheidenden Einfluss hatte auch die Variable konkurrierende Auktionen innerhalb von drei Stunden, demnach erzielten Auktionen mit einer hohen An-zahl dieser Variable deutlich niedrigere Preise. Andere Variablen hingegen vielen nicht signifikant aus. So war es zum Beispiel überra-schend, dass die Variablen Garantie und Rechnung vollkommen uninteressant erscheinen. Demnach legen die Käufer keinen Wert darauf zu wissen, wo das Produkt herkommt und nehmen scheinbar gerne in Kauf, dass es sich eventuell um gestohlene Produkte handeln könnte. Auch die Anbieterreputation hatte keinerlei Einfluss auf den Endpreis, allerdings kann dies daher kommen, dass die Mehrheit der Bewertungen sehr positiv war.The research concentrates on exogenous and endogenous determinants that may occur in the end price of online auctions, where the objects of these auctions have to be highly homogenous. The object of research is the iPod touch 8 GB. This product was chosen because there were enough offers on the German portal eBay.de within the observed period of time. For 15 days all data of the concerned auctions have been collected and then analyzed. Some of the results gained were quite surprising. Significant values could be found for the variable day of the week. In more detail it means that lower prices are achieved on weekends compared to days during the week. The time of the day shows an influence as well; so it can be said that in the early evening a higher end price can be obtained than on other time periods on a day. Significant results could also be seen for the condition. This means that the newer a product is, the higher the end price will be. Moreover the variable competing auctions within three hours showed significant values: the more competing auctions, the less the end price of an auction. So it was surprising that variables like guarantee or check had no affect at the price at all. It can be speculated that the buyer does not want to know where the product comes from and accepts that it might be a stolen one. The reputation of the seller had no effect as well, but there is to say that the majority of the ratings were extremely positive

Factors Influencing Consumer Bidding Behavior in Online Auction (Consumer-to-Consumer)

According to the critical analysis of theoretical and empirical literature, there is a need to better understand and to examine the relationship between consumer bidding behavior in online auctions and the related influencing factors. Online auction is a relatively new field of study. It is important to further research the area of online auctions. The theoretical structure, research questions, research hypotheses, and the hypothesized research model are introduced. Theory of Reasoned Auction, Theory of Planned Behavior, and Technology Acceptance Model are used as theoretical foundations of this study. This study focuses on the relationship between consumer bidding behaviors in online auctions, and factors influencing those behaviors. The research is focused on the following influencing factors: customer satisfaction, ease of use of the web site, and demographic profile. A non-experimental, quantitative, correlational research design was conducted to study the relationship between influencing factors and consumer bidding behavior. The target population was people with online shopping experience with eBay who have current access to the Internet. After IRB approval, the researcher collected the date by a paper and pen questionnaire at a public beach in Boca Raton. The questionnaire was handed out to the eligible participants. The questionnaires were dropped in a closed box. The data for this study collected from at least 146 eligible participants using pen and paper questionnaire as an instrument. Findings helped to serve the online consumers and the vendors, as well as being a scholarly contribution to the study of online bidding. This study used SPSS software to analyze the collected data. Descriptive statistics, Cronbach alpha, Pearson r correlation, simple regression, and multiple regressions, were applied in this study. The study findings indicated that an individual\u27s bidding behavior is influenced positively by factors like consumer satisfaction and ease of use and bidding behavior is not influenced by demographic characteristics

A web-based agent service platform for e-commerce applications.

by Chi-Wai Lee.Thesis (M.Phil.)--Chinese University of Hong Kong, 2002.Includes bibliographical references (leaves 112-117).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.iiiChapter 1 --- Introduction --- p.1Chapter 1.1 --- Background and Motivations --- p.1Chapter 1.2 --- Problem Definition --- p.5Chapter 1.3 --- Contributions --- p.5Chapter 1.4 --- Thesis Organization --- p.7Chapter 2 --- Literature Review --- p.8Chapter 2.1 --- Electronic Commerce --- p.8Chapter 2.2 --- Agents for Electronic Commerce --- p.9Chapter 2.3 --- Online Auctions --- p.11Chapter 2.3.1 --- Business Models --- p.12Chapter 2.3.2 --- Auction Formats --- p.13Chapter 2.3.3 --- Time Duration of Auctions --- p.14Chapter 2.3.4 --- Minimum Bids and Reserve Prices --- p.15Chapter 2.3.5 --- Auction Properties and Bidder Behaviours --- p.15Chapter 2.3.6 --- "Comparison of English, Dutch and Double auction" --- p.16Chapter 2.4 --- Agents Developing Tools and Tool-kits --- p.17Chapter 2.5 --- Limitations of Agent Tool-kits --- p.18Chapter 2.6 --- Markov Processes for Stochastic Modeling --- p.20Chapter 2.6.1 --- Continuous Time Markov Chain --- p.21Chapter 2.6.2 --- Poisson Arrival Model --- p.22Chapter 2.6.3 --- Example: discrete time Markov chain with stationary probabilities --- p.22Chapter 3 --- Markov Chain Model --- p.25Chapter 3.1 --- Markov Chain for English Auction --- p.25Chapter 3.1.1 --- Variables --- p.27Chapter 3.1.2 --- Auction Assumptions --- p.27Chapter 3.1.3 --- Bidder Assumptions --- p.29Chapter 3.1.4 --- Propositions of the Markov Model --- p.31Chapter 3.1.5 --- Tractability --- p.35Chapter 3.2 --- Markov Chain for Dutch Auction --- p.38Chapter 3.2.1 --- Variables --- p.39Chapter 3.2.2 --- Model Assumptions --- p.39Chapter 3.2.3 --- Propositions of the Markov Model --- p.42Chapter 3.2.4 --- Tractability --- p.43Chapter 3.3 --- Progression of the Price Vector for English and Dutch Auction --- p.43Chapter 3.4 --- Markov Chain for Double auction --- p.45Chapter 3.4.1 --- Variables --- p.47Chapter 3.4.2 --- Model Assumptions --- p.47Chapter 3.4.3 --- Propositions of the Markov Model --- p.49Chapter 3.4.4 --- Tractability --- p.53Chapter 3.5 --- Progression of the Price Vector for Double Auction --- p.53Chapter 3.6 --- Summary --- p.54Chapter 4 --- System Design --- p.57Chapter 4.1 --- System Features --- p.58Chapter 4.2 --- System Architecture --- p.59Chapter 4.2.1 --- System Workflow --- p.60Chapter 4.2.2 --- Communication Layer --- p.61Chapter 4.2.3 --- Agent Logic Layer --- p.62Chapter 4.2.4 --- Database Abstraction Layer --- p.62Chapter 4.3 --- Roles of the Agents --- p.62Chapter 4.4 --- Implementation Details --- p.65Chapter 4.4.1 --- Choosing a Scripting Language --- p.65Chapter 4.4.2 --- Choosing a Database --- p.68Chapter 4.4.3 --- Server-Side Java with Jakarta-tomcat --- p.69Chapter 4.4.4 --- Agent API --- p.70Chapter 4.4.5 --- Class java.agent.Agent --- p.72Chapter 4.5 --- Summary --- p.73Chapter 5 --- Experimental Results --- p.75Chapter 5.1 --- Simulation Environment --- p.75Chapter 5.2 --- Experiment One: A small English auction --- p.76Chapter 5.3 --- Experiment Two: A large English auction --- p.80Chapter 5.4 --- Experiment Three: A small Dutch auction --- p.82Chapter 5.5 --- Experiment Four: A large Dutch auction --- p.83Chapter 5.6 --- Experiment Five: Partial knowledge on other BAs --- p.84Chapter 5.7 --- Experiment Six: Partial knowledge on closing time --- p.86Chapter 5.8 --- Experiment Seven: A small Double auction --- p.87Chapter 5.9 --- Comparisons and Discussions --- p.89Chapter 5.10 --- Summary --- p.90Chapter 6 --- Conclusion --- p.91Chapter A --- Markov Chain for English Auction --- p.93Chapter A.1 --- Graphs of F and F* Functions --- p.93Chapter A.2 --- Solution of a Small Example --- p.96Chapter A.2.1 --- Computation of Transition Probabilities --- p.97Chapter A.2.2 --- Progression of the Price Vector --- p.97Chapter B --- Markov Chain for Double Auction --- p.101Chapter B.1 --- Graphs of Fb(vbi) and Fs(vsi) Functions --- p.101Chapter B.2 --- Solution of a Small Example --- p.102Chapter B.2.1 --- Computation of Transition Probabilities --- p.102Chapter C --- Implementation Details --- p.105Chapter C.1 --- Tables Design in MySQL --- p.105Chapter C.2 --- Sample Apache Configuration File --- p.109Bibliography --- p.11

Optimal design of Dutch auctions with discrete bid levels.

The theory of auction has become an active research area spanning multiple disciplines such as economics, finance, marketing and management science. But a close examination of it reveals that most of the existing studies deal with ascending (i.e., English) auctions in which it is assumed that the bid increments are continuous. There is a clear lack of research on optimal descending (i.e., Dutch) auction design with discrete bid levels. This dissertation aims to fill this void by considering single-unit, open-bid, first price Dutch auctions in which the bid levels are restricted to a finite set of values, the number of bidders may be certain or uncertain, and a secret reserve price may be present or absent. These types of auctions are most attractive for selling products that are perishable (e.g., flowers) or whose value decreases with time (e.g., air flight seats and concert tickets) (Carare and Rothkopf, 2005). I began by conducting a comprehensive survey of the current literature to identify the key dimensions of an auction model. I then zeroed in on the particular combination of parameters that characterize the Dutch auctions of interest. As a significant departure from the traditional methods employed by applied economists and game theorists, a novel approach is taken by formulating the auctioning problem as a constrained mathematical program and applying standard nonlinear optimization techniques to solve it. In each of the basic Dutch auction model and its two extensions, interesting properties possessed by the optimal bid levels and the auctioneer's maximum expected revenue are uncovered. Numerical examples are provided to illustrate the major propositions where appropriate. The superiority of the optimal strategy recommended in this study over two commonly-used heuristic procedures for setting bid levels is also demonstrated both theoretically and empirically. Finally, economic as well as managerial implications of the findings reported in this dissertation research are discussed

Buyout prices in online auctions

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2006.Includes bibliographical references (p. 149-154).Buyout options allow bidders to instantly purchase at a specified price an item listed for sale through an online auction. A temporary buyout option disappears once a regular bid above the reserve price is made, while a permanent option remains available until it is exercised or the auction ends. Buyout options are widely used in online auctions and have significant economic importance: nearly half of the auctions today are listed with a buyout price and the option is exercised in nearly one fourth of them. We formulate a game-theoretic model featuring time-sensitive bidders with independent private valuations and Poisson arrivals but endogenous bidding times in order to answer the following questions: How should buyout prices be set in order to maximize the seller's discounted revenue? What are the relative benefits of using each type of buyout option? While all existing buyout options we are aware of currently rely on a static buyout price (i.e. with a constant value), what is the potential benefit associated with using instead a dynamic buyout price that varies as the auction progresses?(cont.) For all buyout option types we exhibit a Nash equilibrium in bidder strategies, argue that this equilibrium constitutes a plausible outcome prediction, and study the problem of maximizing the corresponding seller revenue. In particular, the equilibrium strategy in all cases is such that a bidder exercises the buyout option provided it is still available and his valuation is above a time-dependent threshold. Our numerical experiments suggest that a seller may significantly increase his utility by introducing a buyout option when any of the participants are time-sensitive. Furthermore, while permanent buyout options yield higher predicted revenue than temporary options, they also provide additional incentives for late bidding and may therefore not be always more desirable. The numerical results also imply that the increase in seller's utility (over a fixed buyout price auction) enabled by a dynamic buyout price is small and does not seem to justify the corresponding increase in complexity.by Shobhit Gupta.Ph.D

Agentenbasierter Handel auf Spotmärkten am Beispiel eines Energiemarktszenarios

Der drohende Klimawandel mit der Forderung den CO2 Ausstoß zu minimieren und der geplante Atomausstieg werfen zahlreiche neue Fragestellungen auf. Daher liegt der Focus der vorliegenden Arbeit auf dem Verkauf und Kauf von dezentral erzeugtem Strom aus alternativen Energiequellen. Durch die vorliegende Arbeit sollen privaten Käufern und Verkäufern in einem Spotmarkt für dezentral erzeugten Strom, verschiedene Unterstützungsmöglichkeiten zur Verfügung gestellt werden