Modeling On-Line Art Auction Dynamics Using Functional Data Analysis

In this paper, we examine the price dynamics of on-line art auctions of modern Indian art using functional data analysis. The purpose here is not just to understand what determines the final prices of art objects, but also the price movement during the entire auction. We identify several factors, such as artist characteristics (established or emerging artist; prior sales history), art characteristics (size; painting medium--canvas or paper), competition characteristics (current number of bidders; current number of bids) and auction design characteristics (opening bid; position of the lot in the auction), that explain the dynamics of price movement in an on-line art auction. We find that the effects on price vary over the duration of the auction, with some of these effects being stronger at the beginning of the auction (such as the opening bid and historical prices realized). In some cases, the rate of change in prices (velocity) increases at the end of the auction (for canvas paintings and paintings by established artists). Our analysis suggests that the opening bid is positively related to on-line auction price levels of art at the beginning of the auction, but its effect declines toward the end of the auction. The order in which the lots appear in an art auction is negatively related to the current price level, with this relationship decreasing toward the end of the auction. This implies that lots that appear earlier have higher current prices during the early part of the auction, but that effect diminishes by the end of the auction. Established artists show a positive relationship with the price level at the beginning of the auction. Reputation or popularity of the artists and their investment potential as assessed by previous history of sales are positively related to the price levels at the beginning of the auction. The medium (canvas or paper) of the painting does not show any relationship with art auction price levels, but the size of the painting is negatively related to the current price during the early part of the auction. Important implications for auction design are drawn from the analysis.Comment: Published at http://dx.doi.org/10.1214/088342306000000196 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

The Impact Of Economic And Social Orientation On Trust Within Teams

In this paper, we develop a model to examine the impact of an individual’s economic and social orientation and the congruence of such orientations across the trustor-trusted dyad on the level of dyadic trust within a team.  The model explicitly accounts for higher order dependencies in trust among team members and the potential reciprocity in trust between members of a dyad.  The results from our model estimation provide evidence that congruence in economic and social orientation is an important antecedent of dyadic trust.  We also find that dyadic trust is characterized by higher order dependencies among team members; however, we do not find that trust is characterized by reciprocity.  We also find a wide variation in the polarization in teams based on the levels of trust among their members.  Taken together, these findings highlight the need to account for higher order dependencies in the study of trust in teams

The Role of Media Richness of Channels on Consumer Decision- Making and Channel Choice

With the increasing popularity of multichannel strategies, many retailers actively encourage their customers to undertake purchasing activities across various retail channels. Extant literature on multichannel strategies advances our understanding of why and how consumers select channels, but our knowledge is limited on how different channel characteristics affect consumer behavior, decision-making across channels and channel choice. In this paper, we focus on one such channel characteristic, called media richness of the retail channels, and investigate the effects of media richness of channels on consumer decision-making and channel choice. Media richness, as originally described by Media Richness Theory, is a set of objective characteristics such as feedback and communication capability, language variety, and personal focus, which determine a channel’s ability to communicate richness of information. We present related predictions based on media richness theory and cognitive cost (behavioral decision theory) on what level of channel richness is favorable for various purchase tasks. Findings of an experiment provide evidence that consumers prefer channels with medium to high levels of media richness for carrying out decision-making tasks. Consumers indicate that they are unlikely to return to channels that incorporate low levels of media richness, as these channels are not suitable for complete decision-making tasks. The study further finds that product type moderates the effect of media richness on perceived channel-task fit, post-purchase evaluation and channel choice. These insights should prove helpful to retailers in managing content across different channels

Research Framework, Strategies, And Applications Of Intelligent Agent Technologies (IATs) In Marketing

In this digital era, marketing theory and practice are being transformed by increasing complexity due to information availability, higher reach and interactions, and faster speeds of transactions. These have led to the adoption of intelligent agent technologies (IATs) by many companies. As IATs are relatively new and technologically complex, several definitions are evolving, and the theory in this area is not yet fully developed. There is a need to provide structure and guidance to marketers to further this emerging stream of research. As a first step, this paper proposes a marketing-centric definition and a systematic taxonomy and framework. The authors, using a grounded theory approach, conduct an extensive literature review and a qualitative study in which interviews with managers from 50 companies in 22 industries reveal the importance of understanding IAT applications and adopting them. Further, the authors propose an integrated conceptual framework with several propositions regarding IAT adoption. This research identifies the gaps in the literature and the need for adoption of IATs in the future of marketing given changing consumer behavior and product and industry characteristics

Research Framework, Strategies, And Applications Of Intelligent Agent Technologies (IATs) In Marketing

In this digital era, marketing theory and practice are being transformed by increasing complexity due to information availability, higher reach and interactions, and faster speeds of transactions. These have led to the adoption of intelligent agent technologies (IATs) by many companies. As IATs are relatively new and technologically complex, several definitions are evolving, and the theory in this area is not yet fully developed. There is a need to provide structure and guidance to marketers to further this emerging stream of research. As a first step, this paper proposes a marketing-centric definition and a systematic taxonomy and framework. The authors, using a grounded theory approach, conduct an extensive literature review and a qualitative study in which interviews with managers from 50 companies in 22 industries reveal the importance of understanding IAT applications and adopting them. Further, the authors propose an integrated conceptual framework with several propositions regarding IAT adoption. This research identifies the gaps in the literature and the need for adoption of IATs in the future of marketing given changing consumer behavior and product and industry characteristics

Transforming Marketing Education of the Future: The Role of Intelligent Agent Technologies (IATs) in Enhancing Student Learning

This conceptual paper introduces IATs and discusses how such intelligent and interactive applications can translate into better education environment for marketing curriculum, particularly marketing research. We present a conceptual model based on extant literature. We present some initial test of our conceptual model of IAT usage in marketing education in a marketing research class

An Investigation of Value Updating Bidders in Simultaneous Online Art Auctions

Simultaneous online auctions, in which the auction of all items being sold starts at the same time and ends at the same time, are becoming popular especially in selling items such as collectables and art pieces. In this paper, we analyze the characteristics of bidders (Reactors) in simultaneous auctions who update their preauction value of an item in the presence of influencing bidders (Influencers). We represent an auction as a network of bidders where the nodes represent the bidders participating in the auction and the ties between them represent an Influencer-Reactor relationship. We further develop a random effects bilinear model that is capable of handling covariates of both bidder types at the same time and account for higher-order dependence among the bidders during the auction. Using the model and data from a Modern Indian Art auction, we find that Reactors tend to update their values on items that have high preauction estimates, bid on items created by high investment risk artists, bid selectively only on certain items, and are more active in the second half of the auction. Implications for the auction house managers are discussed