Fingerprint‐Based Recognition

Biometric recognition, or biometrics, refers to the authentication of an individual on the basis of her or his biometric traits. Among the various biometric traits (e.g., face, iris, fingerprint, and voice), fingerprint‐based authentication has the longest history and has been successfully adopted in both forensic and civilian applications. Advances in fingerprint capture technology have resulted in new large‐scale civilian applications (e.g., US Visitor and Immigrant Status Indicator Technology program). However, these systems still encounter difficulties due to various noise factors present in operating environments. There is also a general lack of scientific development in forensic methods, including fingerprint‐based methods, in terms of identifying, incorporating, and quantifying sources of variability in the decision‐making process. The purpose of this article is to give an overview of current practice in fingerprint‐based recognition, its challenges, and areas of future research.     

Maximizing bidder surplus in simultaneous online art auctions via dynamic forecasting

This paper presents a novel intelligent bidding system, called SOABER (Simultaneous Online Auction BiddER), which monitors simultaneous online auctions of high-value fine art items. It supports decision-making by maximizing bidders’ surpluses and their chances of winning an auction. One key element of the system is a dynamic forecasting model, which incorporates information about the speed of an auction’s price movement, as well as the level of competition both within and across auctions. Other elements include a wallet estimator, which gauges the bidders’ willingness to pay, and a bid strategizer, which embeds the forecasting model into a fully automated decision system. We illustrate the performance of our intelligent bidding system on an authentic dataset of online art auctions for Indian contemporary art. We compare our system with several simpler ad-hoc approaches, and find it to be more effective in terms of both the extracted surplus and the resulting winning percentage.     

A holistic network model for supply chain analysis

Supply chain researchers are experiencing a conceptual and analytical paradox. They are asked to move beyond dyadic analyses and investigate larger network effects with only a limited analytical toolkit. This research proposes the use of bilinear mixed-modeling to holistically analyze supply chain phenomena. Through this approach, researchers are able to account for multiple supply chain relationships, higher-order dependencies among member firms, and simultaneously evaluate covariates from buyer and seller perspectives. The model is validated through the lens of a pervasive supply chain problem commonly referred to as the bullwhip effect. A sample of firms from the US apparel industry in 2004 is analyzed and then the findings are confirmed using data from 2005. In addition to validating the model through the presence of the bullwhip effect, the bilinear model illuminates variables such as advertising, price deals, inventory turnover, and inventory backlogs that exacerbate or diminish inventory differences between firms in a supply chain. The results extend research on supply networks and supply efficiency to a more holistic level and show that higher-order dependencies are important drivers of supply chain phenomena.     

Brand vulnerability to product assortments and prices

Abstract

The assortment of brands that a specific brand competes against varies from one point of sale to another. The competitive landscape changes further because of within-assortment price variations at each location. The joint variation in assortment composition and pricing creates a complex set of scenarios under which a brand needs to compete. In this paper, we develop an approach to assess changes in a brand's vulnerability under alternative assortment and price configurations. We specifically propose that, in market environments with high variability in the competitive set and prices, it is more appropriate to assess a brand's strength relative to alternative assortment configurations rather than against individual competing brands. We build a model that depicts a brand's vulnerability in latent assortment space rather than the traditional brand space. The results from an illustrative model application are used to draw inferences about changes in brand vulnerabilities under shallow and deep promotions.     

Areas of Corruption in the Distribution of Foreign-Made Goods Where a Firm's Size and Origin Play a Role: The Russian Experience

Drawing on interview evidence, this article explores areas whereby business corruption in Russia affects distributors of foreign goods with both local and foreign ownership and whether its effects on distributors of small and large sizes vary. The findings reveal the areas of corruption wherein distributors of foreign goods in Russia are most likely to be affected and suggest that, though widespread in Russia, corruption may have far greater effect on smaller distributors as compared to large firms. Large distributing firms can avoid involvement in corruption in some of the areas explored. This in turn may limit small-sized foreign manufacturers' capability to compete in this market, as they are most likely to be able to contract only to small-sized distributors. The study presents findings that are based on interviews with the distributors of foreign-made goods operating in Russia. The findings of the study can help to explain activities of corruption as related to the size of business firms involved in distribution of foreign products in Russia. Hence, its value to firms contemplating export to Russia. The research can also be considered a valuable platform for further research in this field.     

Exploring satisfaction in business-to-business services: a path-analytic approach

In this article, we propose a path-analytic approach to model the relationships among overall satisfaction, satisfaction with higher order performance domains and the lower order performance attributes for business-to-business services. The model is estimated using data from the business customers of a large provider of electronics products and services. Our results show that overall satisfaction in such contexts may be driven by satisfaction on multiple higher order performance domains and the relevant lower order performance attributes may not drive satisfaction. An adoption of our modeling approach can help service providers make resource allocation decisions across performance domains and identify the micro-level performance levers that they can pull to manage satisfaction levels of their business clients.     

Bringing product and consumer ecosystems to the strategic forefront

The widespread adoption of technology and electronic media has dramatically altered the set of products consumers compare before making a purchase decision. Online platforms have succeeded at drawing linkages among products by highlighting those that are preferred, evaluated, or purchased together. However, despite the increase in both product and customer inter-connectedness across markets, managers continue to make decisions based largely on the dynamics of competition within narrow product categories. In this article, we raise the call for a migration from a category-focused mindset to an ecosystem-focused strategic mindset that acknowledges and accounts for the network of related or unrelated entities that a specific product resides within. We illustrate the importance of this shift using examples of preference, choice, and customer networks from popular online platforms. We then discuss the impact of the shift in strategic mindset toward ecosystems on competitive structure analysis, market research, brand footprint analysis, intra-band ecosystems, promotion planning, new product development, customer valuation, strategic alliances, and market segmentation.     

The Antecedents and Moderators of Offline Information Search: A Meta-Analysis

An examination of consumer information search literature reveals that the effects of several antecedents (cost, price dispersion, knowledge, prior experience) on offline information search vary greatly in terms of the directions and magnitudes of the determinants’ effect sizes, particularly indicating the possibility of inverted-U shaped relationships. Also, despite a wide range of studies undertaken, there remains a need for identifying an overarching framework for consumer information search. This article synthesizes previous empirical studies on offline information search literature, and attempts to provide and test a framework that advances our understanding of the current state of this literature. The review identifies significant antecedents to offline information search, and also tests the moderating effects of demographic variables and study conditions on the direct effects. In the context of the main effects, findings suggest that the nature of relationships of several antecedents with the central construct is indeed inverted-U shaped. Further, moderator analyses identify the boundary conditions under which specific theories hold. The closing section provides future research directions.     

Within-syndicate conflicts,loan covenants,and syndicate formation

We study how conflicts within a lending syndicate affect loan contract and syndicate formation. We argue that loan provisions serve an important dual function: In addition to moderating borrower–lender conflicts, they reduce within-syndicate conflicts. We show that greater potential for within-syndicate conflicts is associated with more and stricter covenants. Loans are less restrictive when the interests of participants and the lead arrangers are better aligned, for example, when participant–banks have stronger relationships with the lead arranger or hold borrower's equity (indirectly). Overall, our results show that covenant choice, syndicate formation, and lead arranger's loan allocation all play an important role in reducing within-syndicate conflicts.