Robert F. Easley

Relating Collaborative Technology Use to Teamwork Quality and Performance: An Empirical Analysis

Although team-based work systems are pervasive in the workplace, the use of collaborative systems designed to facilitate and support ongoing teamwork is a relatively recent development. An understanding of how teams embrace and use such collaborative systems - and the relationship of that usage to teamwork quality and team performance - is critical for organizational success. We present a theoretical model in which usage of a collaborative system intervenes between teamwork quality and team performance for tasks that are supported by the system. We empirically validate the model in a setting where established teams voluntarily used a collaborative system over a four-month period to perform tasks with measurable outcomes. Our principal finding is that collaborative system use intervenes between teamwork quality and performance for tasks supported by the system but not for unsupported tasks.

Capturing group preferences in a multicriteria decision

Abstract This paper examines the extent to which methods used for analyzing judgments from a group of decision makers result in preference rankings which are consistent with the group member’s subjective beliefs about their preferences. In a laboratory group decision setting, the Analytic Hierarchy Process, a newly developed probabilistic extension to the AHP, and two pairwise voting methods are used to develop separate preference rankings based on input from the group members. The probabilistic version of the AHP, in its first independent test, is found to provide more insight into the group decision while requiring fewer a priori assumptions. A commonly used and easily implemented pairwise voting procedure is found to be significantly inferior to the other methods in its ability to capture the group’s preference rankings. This underscores the importance of using appropriate decision models for developing a full understanding of group preferences.

The MP3 open standard and the music industry's response to Internet piracy

Can open standards motivate market leaders to accept new technology?

Bidding Patterns, Experience, and Avoiding the Winner's Curse in Online Auctions

The design and implementation of online auctions has given rise to a unique set of bidding strategies that has stimulated a growing body of research. We make use of a theoretically grounded, well-understood, and empirically observable bidder behavior—the winners curse adjustment for the expected number of bidders in an auction—to examine the relationships between bidder experience, bidding patterns, and the winners curse adjustment in rare coin online auctions. We also examine the impact of uncertainty on the winners curse adjustment, both by using precise measures of uncertainty and by considering seller and bidder strategies for reducing that uncertainty. We analyze a complete record of all auctions in a three-month period for rare U. S. coins, examining 284,681 bids from 62,625 auctions hosted by eBay, the market leader in online auctions. One of the main contributions of this paper is to demonstrate that the bidding patterns associated with different bidders are strongly related to whether they calculate their bids to take into account the number of competing bidders, as predicted for common-value auctions. This is a substantial extension and empirical confirmation of prior work that has explored the implications of different observed patterns of bidding. We also explore new territory by examining the relationships between bidder experience, bidding patterns observed, and the economic outcomes for bidders. We are able to show that bidders with more domain-specific experience (rather than general auction experience) make better adjustments for the winners curse, that experience has an effect on the type of bidding strategy, and that the type of bidding strategy has a significant effect on the economic outcomes for the bidders.

Market Segmentation Within Consolidated E-Markets: A Generalized Combinatorial Auction Approach

We analyze an e-market design that allows multiple market segments to be served simultaneously with a single generalized combinatorial auction. The mechanism uses rule-based bids designed to accommodate various kinds of bidders, such as those more sensitive to price or those more restricted in their requirements. We demonstrate experimentally—using agent-based simulation of the actual market for television advertising slots—that the rule-based approach effectively handles the wide range of market segments, while maintaining buyer and seller surplus and efficiently allocating goods.

A comparative study of exchange and aggregation models in the B2B e-marketplace

This research seeks to provide an economic framework for understanding two major forms of e-marketplaces: aggregation-oriented vs. exchange-oriented e-marketplaces. By analyzing the marginal benefit per transaction in alternative models, we are able to determine the most suitable B2B e-marketplace for a wide variety of product categories, market conditions, and procurement methods. For example, when companies sell commodities in a fragmented market, the aggregation model is suitable for spot purchasing, and the exchange model works best for systematic purchasing. In addition, the effect of supplier consolidation and information technology-enabled cost reduction on model selection is discussed.

International differences in product perception: a product map analysis

Shows that traditional product mapping methods for product positioning analysis fail in international settings due to the high variability of product preferences within each country and the lack of a common product perception among countries. Shows how explicitly incorporating variation in the product positioning analysis can overcome both of these problems. Uses a comparison of how Japanese and US consumers differ in their perceptions of the gift market for young males to illustrate how the proposed method differs from traditional methods. Indicates that Japanese consumers perceive the gift market much more uniformly than Americans.

Market Model-Based Channel Selection in B2B E-Commerce: Exploring a Buyer's Adoption Decisions

Companies that seek to exploit the cost advantages of business-to-business (B2B) e-Commerce face a variety of strategic options. By analyzing the demand and cost functions for sellers, intermediaries, and buyers, this research develops an economic framework that clarifies the relative advantages of four common B2B e-Commerce channels: private exchange, web-based procurement, public aggregation, and public exchange. This research focuses on addressing two important questions: (1) How does a buyer select a suitable B2B e-Commerce channel (or an e-Marketplace structure) given a variety of market conditions, different levels of product substitution, and a range of purchasing patterns? (2) How does a buyer successfully manage a B2B e-Commerce channel for gaining the highest transaction-level buyer surplus? The analytic and numeric results of our study show that a companys product offerings, the market conditions it faces, and the purchase patterns it implements are all important determinants in the selection of B2B e-Commerce setting. For custom products, private networks (such as the private exchange or web-based procurement models) are more attractive than the public aggregation or exchange models. However, taking market conditions and purchasing behavior into consideration, the web-based procurement model is more suitable for spot purchasing, while the public exchange model is more suitable for systematic purchasing and fragmented markets. On the other hand, the aggregation model is preferable in concentrated markets while the exchange model is more suitable in fragmented markets. These results provide important implications for industrial development of B2B e-Commerce.

Optimal Digital Rights Management with Uncertain Piracy

Many firms that sell digital copies of copyrighted materials online face a common dilemma: the use of Digital Rights Management to impede pirates often also has negative implications for legitimate customers. We introduce a two-period model in which the use of DRM in the first period affects the probability of consumers encountering pirated copies in the second period, the threat of legal action affects the probability of consumers obtaining pirated copies, and firms choose whether to sell, and at what prices, either strongly or weakly DRM protected copies, or both. We are able to explain a range of observable firm behaviors with this model, including the use of price discrimination to offer both strongly and weakly protected files simultaneously, with weaker protection commanding a higher price, and the eventual abandonment of DRM protections, both of which have been observed at various times, for example, with Apples iTunes service.

Crossing properties of multiterminal cuts

Gomory and Hu proved the following classical result: For any graph with nonnegative edge weights, there exists a collection of noncrossing cuts that contains a minimum cut for every pair of nodes. In this paper, we show how this result generalizes for a natural multiterminal cut problem. We also show that our result is best possible, for k = 3, by using a computer to find feasible solutions to several large systems of linear inequalities.