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In this paper, we analyse the market determinants of price differentials between new and remanufactured products in Electronics using data on purchases made on eBay UK. The empirical analysis is carried out by means of linear regression methods, which are capable of controlling for the presence of collinearity among the explanatory variables. Our empirical results suggest that the seller reputation, length of warranties, proxies of demand and supply of remanufactured products, duration, end day of product listings as well as the availability of return policies are important determinants of price differentials. Most importantly, we find that the seller identity plays an important role, as our empirical results are predominantly driven by transactions carried out by non-manufacturer-approved vendors. [ABSTRACT FROM PUBLISHER]

This paper focuses on the pricing of reused personal computers that are discarded and sold on the secondary market. We first extract the main components affecting the performance of a reused computer. We then use quality function deployment to compare the weights of the main components against what reusable computer customers require. Third, we use TOPSIS to rank the selected reused computers. Finally, we price every reused computer according to relative monopoly power and perform an accumulated depreciation analysis on each one at various sale periods. The results show that each reused computer can be easily evaluated and priced on the secondary market. [ABSTRACT FROM PUBLISHER]

The authors examine the relative magnitude of price reductions for product systems and their constituent components (e.g., cameras, computers, monitors, lenses) and hypothesize that these price reductions systematically vary across different types of systems. The authors offer rational inattention as an explanation and document patterns of downward rigidity in online prices of computers and cameras that are consistent with this view. Their basic argument is that under certain circumstances, it is rational for consumers to ignore small price changes. This results in some price rigidity because firms would see no demand effect for small reductions. The authors suggest that this inattention systematically varies across different types of multicomponent systems, leading to specific hypotheses about sellers' pricing behavior. They first check the validity of their theoretical arguments using data from two surveys of consumers and managers. They then examine 669,557 daily price listings for 1052 high-end cameras and computers from 102 online vendors and find evidence consistent with their predictions. Using publicly available web traffic data, the authors also find that their predicted pricing behavior is aligned with better traffic response for the firm. [ABSTRACT FROM AUTHOR]

E-commerce has today become an integral part of our day-to-day life. From reading newspapers to ordering food, shopping for daily groceries or important purchases like electronics, formal wear, conducting bank transactions, etc., e-commerce has, in fact, invaded our lives. This is more so when we have moved from being click away to being touch away from internet via our smart phones. Mobiles are just a touch away from the consumer's shopping needs, information search, entertainment desires, cab hiring, location tracking, social media connects, news updates and many more applications. This has provided an opportunity for the marketer to stay connected to their customers throughout the day. The paper investigates pertinent secondary data sources such as industry and government reports, to highlight the behaviour of e-consumers in India. The study also compares the global trends of e-consumers world over vis-à-vis the Indian online shoppers. Such investigation can help the e-commerce firms to further harness the unprecedented growth in the e-consumer market by taking care of unique nuances of the Indian online shoppers. Besides, the study is helpful to the Indian policy makers in accelerating the e-commerce boom by taking care of the grey areas like security issues, increasing the e-consumer trust on online payment mode, internet penetration in tier 2 and 3 cities, easy entry and financing route for e-business etc. [ABSTRACT FROM AUTHOR]

This article traces the development and expansion of early computer systems for managing and disseminating ‘real-time’ market data at the most influential stock market in the United States, the New York Stock Exchange (NYSE). It follows electronic media at the NYSE over a roughly ten-year period, from the time of the deployment of a computer called the Market Data System (MDS) through debates surrounding the National Market System and the passage of the 1975 Securities Acts Amendments. Building on research at the archives of the NYSE and the Securities and Exchange Commission (SEC), this history emphasizes the regulatory and managerial contexts in which market data became computerized. The SEC viewed market automation as both necessary for the viability of the securities industry and a mechanism for expanding regulatory oversight over the venues of stock trading. Moving from the MDS to later technical projects in the late 1960s and early 1970s, this article charts the changing meaning of electronic governance in a market increasingly conceptualized as a technical object. Adding to recent work in the social studies of finance and financial technologies, this history sites early NYSE computerization programs within managerial efforts to consolidate control over the clerical labor of financial markets, and in contests between regulatory and market institutions. It concludes by exploring the differing forms of electronic governance activated in these efforts to bring computers into the market. [ABSTRACT FROM AUTHOR]

Purpose Multi-unit discounts (MUDs, e.g. “3 for $4”) typically increase sales relative to other discounting frames. This study demonstrates the value of MUDs by showing that positive multi-unit price/quantity signals are potent enough to match and even exceed the sales produced by larger discounts on single items. However, there is reason to believe that MUDs can produce neutral effects in some cases (e.g. among consumers interested in only single-unit purchases) and even negative effects in others. In addition, the study considers whether MUDs can, in some cases, reduce purchase quantities by signaling smaller-than-otherwise-planned purchase amounts and/or lower-quality products.Design/methodology/approach The effectiveness of MUDs is tested in both the field and lab. Study 1 models purchase quantities stemming from 2,374 purchases of discounted items at a mass retailer. Purchased products ranged in type from pantry items to apparel and electronics, and ranged in price from 44¢ to $99.99. There were 1,530 single-unit discounts, 596 two-unit discounts and 248 discounts, involving three or more units. Study 2 consists of a laboratory experiment that overcomes the shortcomings of Study 1 by accounting for non-purchasers, controlling for product classes and testing whether smaller MUDs can lead to lower purchase quantities for larger-purchase-quantity products.Findings The results of both the field study and the laboratory experiment indicate that MUDs’ monetary cue (savings) and purchase-quantity cue (volume) increase purchase quantities. Generally, purchase quantities increased monotonically with the number of units offered in the discount. In fact, the quantity cue is so effective that it can increase sales enough as to substitute for larger discounts. However, in some instances, MUDs can decrease intended purchase quantities. The negative effect of MUDs is the most pronounced for larger unit deals, offering deeper discounts on perishable goods.Originality/value This research is the first to demonstrate that the power of the signals provided by MUDs may be so positive as to lead them to be more effective than discounts of substantially larger value but also so negative as to render them less effective than single-units discounts. This negative outcome poses a threat beyond those typically associated with discounts, in that rather than consumers simply discounting a discount, in which case the discount remains positive even if their impact at the margin wanes, the MUD frame may actually reduce sales. [ABSTRACT FROM AUTHOR]

Copyright of ESIC Market. Economic & Business Journal is the property of ESIC Business & Marketing School and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article presents the application of neuro-fuzzy techniques in forecasting a new technology in shopping. Neural networks have been used successfully to forecast time series due to their significant properties of treating nonlinear data with self-learning capability. However, neural networks suffer the difficulty of dealing with qualitative information and the “black box” syndrome that more or less limits their applications in practice. To overcome the drawbacks of neural networks, in this study, we proposed a fuzzy neural network that is a class of adaptive networks functionally equivalent to a fuzzy inference system. The results derived from the experiment based on electronic sales indicated that the suggested fuzzy neural network could be an efficient system to forecast a new technology in shopping. Experimental results also show that the neuro-fuzzy approach outperforms the other two conventional models (AR and ARMA). [ABSTRACT FROM PUBLISHER]

The article discusses the court case Vincent Deroo-Blanquart v. Sony Europe Ltd. related to a combined offer consisting of the sale of a computer equipped with pre-installed software. Topics discussed include interpretation of Articles of Directive of the European Parliament and of the Council concerning unfair business-to-consumer commercial practices in the internal market, sale of such computer termed as an unfair commercial practice, and providing correct information to consumers.

Copyright of Law & Justice Review is the property of Justice Academy of Turkey and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Our Tablet Computer data set, collected from various websites, contains market dynamics related to 2,163 products, characteristics of 794 products, more than 40,000 consumer-generated product reviews, and information about 39,278 reviewers. The market dynamic information was collected weekly for 24 weeks starting February 1, 2012. Our Tablet Computer data set comprises four tables: the Market Dynamics of Products, Product Characteristic Information, Consumer-Generated Product Reviews, and Reviewer Information tables. In turn, it offers three unique properties. First, it contains both structured product information and unstructured product reviews. Second, it comprises product characteristic information and market dynamic information. Third, this data set integrates user-generated content with manufacturer-provided content. This integrated data set (available at http://pubsonline.informs.org/page/mksc/online-databases) is valuable for both academics and practitioners who conduct research related to marketing, information systems, computer science, and other fields using digital data readily available through the Internet. [ABSTRACT FROM AUTHOR]

Abstract: Fuzzy systems have been explored in diverse application fields which require reaching fuzzy inferences at high computer rates. To accomplish this task, fuzzy hardware is the best choice. At inference engine, conjunction and disjunction operations play a very important role for decision making. Common operations in existing fuzzy hardware are minimum, maximum, algebraic product and probabilistic sum. In order to extend the applicability of existing fuzzy hardware, it is necessary to consider a wider range of operations. It is even desirable to have configurable circuits which take advantage of hardware resources. This work presents the hardware implementation of configurable circuits for the realization of diverse fuzzy t-norm and t-conorm operations. Resultant circuits are low hardware resource consumers which makes them efficient to be used as add-in modules for existing fuzzy hardware in FPGA or ASIC. Comparative results are presented showing the advantages of these circuits. [Copyright &y& Elsevier]

The article focuses on the using of the balanced scorecard to assess and enhance Magna PC's Performance, the largest private-label personal computer (PC) manufacturers. It mentions that Magna's private-label PCs as large electronic retailers, such as Best Buy, who place their brands on the PCs; also focuses on DataMax PC, one of Magna's largest and strongest competitors.