Users’ processing of online marketplace listings for high and low involvement goods

Purpose – To understand how users of online marketplaces process market signals in their decision making and whether this depends on if the good is of high or low involvement.Design/methodology/approach – The paper employs a mixed methods approach. Study 1 draws on an analysis of interviews with online marketplace users using hypothetical eBay purchases as stimuli, understanding how users conceptualize specific market signals and whether their importance varies depending on the type of purchase (high versus low involvement good). Study 2 tests hypotheses derived from signaling theory, using an eye tracking experiment.Findings – Price and photographs act as “fast and frugal” signals for inclusion in consideration sets for low involvement purchases, but consumers deem them insufficient for high involvement purchases where high-cost signals that help establish seller credibility are far more salient. Users pay relatively greater attention to costly market signals, which are beyond sellers’ direct control, for high involvement goods.Practical implications – The paper offers insights for sellers regarding the presentation of quality cues and strategies online marketplaces can employ to reduce information asymmetry.Originality/value – Drawing on and extending signaling theory, the paper introduces and confirms hypotheses for understanding users’ attention to market signals when making purchase decisions on online marketplaces. It identifies how the degree of involvement of a product affects the processing of market signals.<br/

Selected Topics on Systems Modeling and Natural Language Processing: Editorial Introduction to the Issue 7 of CSIMQ

The seventh issue of Complex Systems Informatics and Modeling Quarterly presents five papers devoted to two distinct research topics: systems modeling and natural language processing (NLP). Both of these subjects are very important in computer science. Through modeling we can simplify the studied problem by concentrating on only one aspect at a time. Moreover, a properly constructed model allows the modeler to work on higher levels of abstraction and not having to concentrate on details. Since the size and complexity of information systems grows rapidly, creating good models of such systems is crucial. The analysis of natural language is slowly becoming a widely used tool in commerce and day to day life. Opinion mining allows recommender systems to provide accurate recommendations based on user-generated reviews. Speech recognition and NLP are the basis for such widely used personal assistants as Apple’s Siri, Microsoft’s Cortana, and Google Now. While a lot of work has already been done on natural language processing, the research usually concerns widely used languages, such as English. Consequently, natural language processing in languages other than English is very relevant subject and is addressed in this issue

How to Improve Efficiency of Analysis of Sequential Data? 1

Abstract: In order to extract useful knowledge from large databases of sales data, data mining algorithms (the so-called market basket analysis) are used. Unfortunately, these algorithms, depending on data and parameters, may generate a large number of patterns. Analysis of these results is performed by the user and involves executing a lot of queries on complex data types that are not well supported by commercially available database management systems. To increase efficiency of analysis of data mining results, new index structures need to be developed. In this paper we propose the indexing scheme for non-timestamped sequences of sets, which supports set subsequence queries. Experimental evaluation of the index proves the feasibility and benefit of the index in query processing

New Trends in Databases and Information Systems: Contributions from ADBIS 2013

Research on database and information system technologies has been rapidly evolving over the last few years. Advances concern either new data types, new management issues, and new kind of architectures and systems. The 17th East-European Conference on Advances in Databases and Information Systems (ADBIS 2013), held on September 1–4, 2013 in Genova, Italy, and associated satellite events aimed at covering some emerging issues concerning such new trends in database and information system research. The aim of this paper is to present such events, their motivations and topics of interest, as well as briefly outline the papers selected for presentations. The selected papers will then be included in the remainder of this volume