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Numerous online information systems (e.g., question and answer [Q&A] forums, citizen science communities, and review websites) rely heavily on volunteer contributions. Managers have used monetary incentives to induce individuals to increase their contribution level. However, monetary incentives could also generate adverse effects, which could dampen individuals' intrinsic motivation and lead to lower contribution quality when incentives are small. To address this issue, we propose two intervention strategies, goal-setting and challenge-seeking, and conduct a series of randomized experiments. We find that small monetary incentives, when combined with the appropriate intervention strategies, can motivate users to increase contribution quantity while simultaneously sustaining high quality. Thus, integrating such intervention strategies with small incentives can be a cost-effective way to encourage voluntary contributions. Our research contributes to the literature on incentive provision and provides theoretical and practical implications for platforms relying on voluntary contributions. [ABSTRACT FROM AUTHOR]

This article studies the strategic network formation in a location-based social network. We build an empirical model of social link creation that incorporates individual characteristics and pairwise user similarities. Specifically, we define four user proximity measures from biography, geography, mobility, and short messages. To construct proximity from unstructured text information, we build topic models using Latent Dirichlet Allocation. Using Gowalla data with 385,306 users, 3 million locations, and 35 million check-in records, we empirically estimate the model to find evidence on the homophily effect on network formation. To cope with possible endogeneity issues, we use exogenous weather shocks as our instrumental variables and find the empirical results are robust: network formation decisions are significantly affected by our proximity measures. [ABSTRACT FROM PUBLISHER]

Recent years have witnessed an unprecedented explosion in information technology that enables dynamic diffusion of user-generated content in social networks. Online videos, in particular, have changed the landscape of marketing and entertainment, competing with premium content and spurring business innovations. In the present study, we examine how learning and network effects drive the diffusion of online videos. While learning happens through informational externalities, network effects are direct payoff externalities. Using a unique data set from YouTube, we empirically identify learning and network effects separately, and find that both mechanisms have statistically and economically significant effects on video views; furthermore, the mechanism that dominates depends on the video type. Specifically, although learning primarily drives the popularity of quality-oriented content, network effects also make it possible for attention-grabbing content to go viral. Theoretically, we show that, unlike the diffusion of movies, it is the combination of both learning and network effects that generate the multiplier effect for the diffusion of online videos. From a managerial perspective, providers can adopt different strategies to promote their videos accordingly, that is, signaling the quality or featuring the viewer base depending on the video type. Our results also suggest that YouTube can play a much greater role in encouraging the creation of original content by leveraging the multiplier effect. [ABSTRACT FROM PUBLISHER]

The article discusses various papers published in this issue including one by Eric Overby and Sabyasachi Mitra on electronic market, one by Chris Parker and Bruce W. Weber on options exchanges and one by Jesse C. Bockstedt and Kim Huat Goh on consumption.

This paper examines the effects of social network structures on prediction market accuracy in the presence of insider information through a randomized laboratory experiment. In the experiment, insider information is operationalized as signals on the state of nature with high precision. Motivated by the literature on insider information in the context of financial markets, we test and confirm two characterizations of insider information in the context of prediction markets: abnormal performance and less diffusion. Experimental results suggest that a more balanced social network structure is crucial to the success of prediction markets, whereas network structures akin to star networks are ill suited to prediction markets. As compared with other network structures, insider information has less positive effects on prediction market accuracy in star networks. We also find that the bias of the public information has a larger negative effect on prediction market accuracy in star networks. [ABSTRACT FROM AUTHOR]

This paper examines the effect of a social network on prediction markets using a controlled laboratory experiment that allows us to identify causal relationships between a social network and the performance of an individual participant, as well as the performance of the prediction market as a whole. Through a randomized experiment, we first confirm the theoretical predictions that participants with more social connections are less likely to invest in information acquisition from outside information sources, but perform significantly better than other participants in prediction markets. We further show that when the cost of information acquisition is low, a social network-embedded prediction market outperforms a nonnetworked prediction market. We find strong support for peer effects in prediction accuracy among participants. These results have direct managerial implications for the business practice of prediction markets and are critical to understanding how to use social networks to improve the performance of prediction markets. [ABSTRACT FROM AUTHOR]

In recent years, there has been stellar growth of location-based/enabled social networks in which people can "check in" to physical venues they are visiting and share with friends. In this paper, we hypothesize that the "check-ins" made by friends help users learn the potential payoff of visiting a venue. We argue that this learning-in-a-network process differs from the classic observational learning model in a subtle yet important way: Rather than from anonymous others, the agents learn from their network friends, about whose tastes in experience goods the agents are better informed. The empirical analyses are conducted on a unique data set in which we observe both the explicit interpersonal relationships and their ensuing check-ins. The key result is that the proportion of checked-in friends is not positively associated with the likelihood of a new visit, rejecting the prediction of the conventional observational learning model. Drawing on the literature in sociology and computer science, we show that weighting the friends' check-ins by a parsimonious proximity measure can yield a more intuitive result than the plain proportion does. Repeated check-ins by friends are found to have a pronounced effect. Our empirical result calls for the revisiting of observational learning in a social network setting. It also suggests that practitioners should incorporate network proximity when designing social recommendation products and conducting promotional campaigns in a social network. [ABSTRACT FROM AUTHOR]

The interdependency of information security risks often induces firms to invest inefficiently in information technology security management. Cyberinsurance has been proposed as a promising solution to help firms optimize security spending. However, cyberinsurance is ineffective in addressing the investment inefficiency caused by risk interdependency. In this paper, we examine two alternative risk management approaches: risk pooling arrangements (RPAs) and managed security services (MSSs). We show that firms can use an RPA as a complement to cyberinsurance to address the overinvestment issue caused by negative externalities of security investments; however, the adoption of an RPA is not incentive-compatible for firms when the security investments generate positive externalities. We then show that the MSS provider serving multiple firms can internalize the externalities of security investments and mitigate the security investment inefficiency. As a result of risk interdependency, collective outsourcing arises as an equilibrium only when the total number of firms is small. [ABSTRACT FROM AUTHOR]

This study examines the incentives for content contribution in social media. We propose that exposure and reputation are the major incentives for contributors. Besides, as more and more social media Web sites offer advertising-revenue sharing with some of their contributors, shared revenue provides an extra incentive for contributors who have joined revenue-sharing programs. We develop a dynamic structural model to identify a contributor's underlying utility function from observed contribution behavior. We recognize the dynamic nature of the content-contribution decision-that contributors are forward-looking, anticipating how their decisions affect future rewards. Using data collected from YouTube, we show that content contribution is driven by a contributor's desire for exposure, revenue sharing, and reputation and that the contributor makes decisions dynamically. [ABSTRACT FROM AUTHOR]

Designing business models that take into consideration the role of advertising support is critical to the success of online services. In this paper, we address the challenges of these business model strategies and compare different ad revenue models. We use game theory to model vertical differentiation in both monopoly and duopoly settings, in which online service providers may offer an ad-free service, an ad-supported service, or a combination of these services. Offering both ad-free and ad-supported services is the optimal strategy for a monopolist because ad revenues compensate for the cannibalistic effect of vertical differentiation. In a duopoly equilibrium, exactly one firm offers both services when the ad revenue rate is sufficiently high. Furthermore, we find that a higher ad revenue rate may lead to lower service prices. Consistently across both monopoly and duopoly settings, such price reductions are more severe in the cost-per-thousand-impressions model than in the cost-per-click model. Our findings emphasize the role of advertising revenues in vertical differentiation and offer strategic guidance for monetizing online services. [ABSTRACT FROM AUTHOR]

We examine a platform's optimal two-sided pricing strategy while considering seller-side innovation decisions and price competition. We model the innovation race among sellers in both finite and infinite horizons. In the finite case, we analytically show that the platform's optimal seller-side access fee fully extracts the sellers' surplus, and that the optimal buyer-side access fee mitigates price competition among sellers. The platform's optimal strategy may be to charge or subsidize buyers depending on the degree of variation in the buyers' willingness to pay for quality; this optimal strategy induces full participation on both sides. Furthermore, a wider quality gap among sellers' products lowers the optimal buyer-side fee but leads to a higher optimal seller-side fee. In the infinite innovation race, we perform computations to find the stationary Markov equilibrium of sellers' innovation rate. Our results show that when all sellers innovate, there exists a parameterization under which a higher seller-side access fee stimulates innovation. [ABSTRACT FROM AUTHOR]

Online communities provide a social sphere for people to share information and knowledge. While information sharing is becoming a ubiquitous online phenomenon, how to ensure information quality or induce quality content remains a challenge because of the anonymity of commentators. This paper introduces moderation into reputation systems. We show that moderation directly affects strategic commentators' incentive to generate useful information, and moderation is generally desirable to improve information quality. We find that when being moderated with different probabilities based on their reputations, commentators might display a pattern of reputation oscillation, in which they generate useful content to build up high reputation and then exploit their reputation. As a result, the expected performance from high-reputation commentators can be inferior to that from low-reputation commentators (reverse reputation). We then investigate the optimal moderation resource allocation and conclude that the seemingly abnormal reverse reputation could arise as an optimal result. Our study underscores the importance of moderation and highlights that the frequency of moderation should be properly chosen for better performance of online communities. [ABSTRACT FROM AUTHOR]

We examine contract choices in the provision of "software-as-a-service" (SaaS), which is a business innovation that transforms information technology (IT) resources into a continuously provided service. We draw upon agency theory and modularity theory to propose that one of the central challenges in service disaggregation is that of knowledge interdependencies across client and provider organizations. The resulting lack of verifiability of certain tasks results in a multitask agency problem. Our key research questions involve (1) the suitability of high- versus low-powered incentives in SaaS contracts when the outsourced tasks involve business analytics that are difficult to verify, and (2) how such contract choices are affected by the modularity of interfaces between the client and the provider. Analysis of data collected from 154 providers of SaaS offering a range of IT services supports our contention that when contracting for business analytics characterized by knowledge interdependencies across clients and providers, incentives should be "low powered." Modularity in the interfaces of the service provider increases the desirability of high-powered incentives in such situations. Our results are robust after accounting for endogeneity issues arising from unobserved matching between service providers and the nature of IT services outsourced by clients. With the increasing importance of information systems in services, this paper suggests that arm's-length relationships and high-powered incentives may be ineffective in incentivizing providers to perform on complex business analytic tasks, unless accompanied by the modularization of interfaces. [ABSTRACT FROM AUTHOR]

Application service providers (ASP), which host and maintain information technology (IT) applications across the Internet, offer an alternative to traditional models of IT service for user firms. We build on prior literature in transaction cost economics (TCE) to argue that the contract design should address ex post transaction costs that result due to contractual incompleteness and opportunism. We argue that contract design is multidimensional, and that it is necessary to design governance structures that can protect user firms from shirking and monitoring costs, as well as provide for efficient adaptation when requirements are incompletely specified at the start of the initiative. Our empirical analysis suggests that factors such as uncertainty in specifying service requirements, interdependence between the ASP application and IT systems in the client organization, and the need for specific investments favor time and materials contracts, whereas fixed prices are desirable when strong incentives are needed for cost reduction. We also find that contracts that are aligned with transaction attributes in a transaction cost--economizing manner are significantly less likely to experience budget overruns and realize better ex post performance than those that are not. These results hold normative implications for both user and provider firms to assess the performance implications of choosing contracts in line with prescriptions of TCE. [ABSTRACT FROM AUTHOR]

Because uncertainties around innovative technologies resolve over time, investments in such technologies are often made in stages so that organizations can use the knowledge gained from earlier stages to decide the next step. Previous studies usually assume that once some uncertainty is resolved, it becomes common knowledge within the investing organization. We develop a game-theoretical model to study how different parties within an organization gain and transfer knowledge about new technologies while investing in these technologies, and how the learning process may affect the investment decisions. We show that managers with incentives misaligned with the organization may transfer their knowledge untruthfully and distort the learning process of decision makers. Such behavior may lead to inefficient investment decisions. We also study the effect of uncertainty on the misreporting problem and the investment decisions. Mechanisms to mitigate or prevent untruthful knowledge transfer are also proposed. In particular, powerful incentive schemes may alleviate, but not prevent, the misreporting problem; punishing managers who are caught misreporting may deter the misreporting behavior, but in practice such mechanisms are difficult to implement. [ABSTRACT FROM AUTHOR]

The Internet provides an additional channel for manufacturers to provide information about and sell their products. The electronic channel has the advantage of reduced search cost and its reach is increasing, but it has limited capability to provide product information. This paper examines how Internet technology affects a monopoly manufacturer's distribution problem in an environment where product information is important for consumers to identify their ideal product. The model suggests that a manufacturer uses the electronic channel in addition to the physical channel when the product information is very valuable and product information is largely about digital attributes, or when the product information is not valuable. The model also suggests that when the manufacturer chooses to sell through both channels, there is an increase in price competition between the two channels such that the manufacturer need not sell through the electronic retailer with the highest reach. Also, when a large proportion of consumers have access to both channels, the manufacturer may sell through only one channel. The paper also examines the case where the manufacturer operates in the electronic channel and the case where the retailers are integrated. [ABSTRACT FROM AUTHOR]

Media and network companies are increasingly providing digital media online. We develop a model to examine optimal strategies for media providers to utilize the online channel to distribute digital media. We examine a number of options for media providers. Our results suggest that media companies should sell programs online when content quality is relative high and online access cost is low. When online access cost is relative high, media providers could use the advertising strategy. Overall, companies are better off providing both pricing and advertising options to consumers. We derive the optimal price and advertising level, and analyze the factors that affect the price and advertising decisions. We find that as advertisement revenue rate increases, advertising level should be kept low. In addition, media companies should set online price and advertising level with consideration of the traditional channel in order to avoid channel cannibalization. We also analyze the advertising level in the traditional channel. Our results suggest that as digital video recorder technologies provide more convenience to consumers, media companies should increase, rather than decrease, revenues from advertising. [ABSTRACT FROM AUTHOR]

The capabilities of network technologies have facilitated the growth of electronic commerce. Major issues--notably, security and product quality uncertainty--still pose serious challenges to the further adoption of electronic commerce. Traditional market transactions have a long history and well-understood protections for buyers and sellers. In the electronic markets, formal and informal mechanisms such as trusted third parties (TTP) have emerged trying to ensure safe transactions . In this paper, we investigate under what conditions people will stick to the traditional market and face-to-face transactions, and under what conditions electronic transactions will be the convention of the future. Of particular interest is the role of TTPs in facilitating online transactions. Using evolutionary game theory, we present an analytical model of buyer and seller choices and examine which patterns of transactions can be sustained. We further study how the traders' adaptive behavior may influence the outcome of the market evolution. Through this analysis, we demonstrate that the market will show divergence: for commodity products, electronic transactions through TTPs will get established as the convention for market transactions when traders use historical information about other traders' past strategies. For "look and feel" products, the market evolution depends on the initial distribution of the transaction strategies in the population. [ABSTRACT FROM AUTHOR]

Creating electronic communities is a critical venture in the digital economy. However, fraud and misrepresentation have led to widespread skepticism and distrust of electronic communities. We develop an evolutionary model to explore the issue of trust within an electronic community from a dynamic process perspective. This model emphasizes large populations, continuous change in community memberships, and imperfect information and memory. As the term trust is often used in the context of individual interaction, at a group level we propose using the term health to measure the sustained competitive advantages of honest members over cheaters throughout the evolution of a community. We find conditions under which an electronic community is healthy and attracts outside population. We find that many factors, such as information dissemination speed, honest players' payoffs and possible losses, new community members' initial trust status, and the replacement rate of community members, all affect the health of an electronic community, and that some of them also affect a community's size. We then discuss the implications of our research for e-community practices. [ABSTRACT FROM AUTHOR]

Internet traffic pricing is necessary for the vitality of electronic commerce because uncontrolled congestion creates a detrimental effect on quality of the Internet services. Pricing approaches based on negative externality have potential to address the issue of congestion. However, most externality-based pricing approaches require the knowledge of consumers' private demand characteristics, and this requirement is often pointed out as the single most important shortcoming of these mechanisms. The fact that the Internet is a "public good" presents challenging information extraction problems for network managers in implementing any pricing mechanism. Ideally, we seek an incentive-compatible mechanism--a means of extracting the required information that provides no incentives for users to alter their behavior in an attempt to manipulate the information extraction and price setting processes. The authors present a solution based on a new nonparametric statistical technique that was developed for this purpose. While the results in this paper are presented in the context of our prior research on pricing, the approach presented here applies to information extraction and implementation in other resource pricing approaches. [ABSTRACT FROM AUTHOR]

This paper presents a control methodology for flow shops that is decentralized and adaptive in nature, and has low data handling and computational requirements. The methodology is based on stochastic automata methods for modelling learning behaviour. It is proposed that such a methodology can be used with Kanban type control technique to make flow shop systems more flexible and adaptive in nature. Relationship of the control model to computational models such as neural computing is discussed. [ABSTRACT FROM AUTHOR]

The Internet has become increasingly important to organizations for certain aspects of electronic commerce. Many organizations have set up Web pages to capture the attention of potential buyers and to develop new business relationships. Others have set up indexing services to provide easy search capabilities to prospective buyers. While the unit search and communication costs have been lowered dramatically by the Internet, the cost of evaluating potential suppliers may still be prohibitive, especially for certain types of products and services. Thus, although the Internet makes it possible to locate a large number of new suppliers, an organizational buyer needs to deploy appropriate supplier-selection strategies (such as sequential evaluation with stopping rules versus bidding systems) that consider all cost elements involved in choosing a vendor. We develop an analytical model that allows a buyer to maximize payoff (net of supplier search, communication, and evaluation costs) from the selection process. We analyze how the nature of the product and the buyer's expectations about supplier characteristics determine whether a sequential evaluation or bidding should be used in the selection process. The Internet, when used in conjunction with the proposed strategies, results in a lower total expected cost to the buyer, even though more suppliers are being evaluated, because a better supplier is selected. We describe how intelligent database searching can further increase the efficiency of the proposed selection strategies. We also develop a minimum requirements announcement mechanism, which makes supplier selection through a bidding strategy economically feasible in situations where legal restrictions may bar the use of sequential evaluation. [ABSTRACT FROM AUTHOR]

The development of effective techniques for allocating computer resources is a major concern in computer center management. Most proposals, while based on concepts originally developed by economists, are based on the assumption that participants provide truthful information. Over the past twenty years, researchers in economics have explored truth-revealing mechanisms. We apply these ideas to charging for computing resources within an organization. The resulting mechanism provides an incentive for users to tell the system administrator their true valuation of a given configuration. Applications of this mechanism to both long-term and short-term situations are outlined. The long-term situation demonstrates how an appropriate computer configuration can be derived from information obtained from its future users. The short-term situation involves setting priorities among jobs. [ABSTRACT FROM AUTHOR]

The main contention of this article is that online auction markets are amenable to efficiency considerations akin to traditional financial markets. While the underlying assets traded are dissimilar between the financial and online auction markets, the fundamental principles that drive these markets are consanguineous in that similar efficiency notions are applicable. Based on the principles of arbitrage, we develop a set of efficiency criteria to evaluate the auction activity of new and identically described items. Two arbitrage principles, seller arbitrage and buyer arbitrage, are developed. These principles can be employed to evaluate the price behavior of temporally proximate auctions and to generate a useful benchmark to make efficiency evaluations. We find evidence of inefficiency for each of the items we empirically tested based on the data from eBay, currently the largest online auction house. [ABSTRACT FROM AUTHOR]

This paper considers the interaction between investment to increase Web site stickiness (consumer switching costs) and competition. A duopoly model is used to examine investment by a superior firm to increase consumer switching costs and competition for customer acquisition and customer retention between the investing firm and a non-investing firm. Gaining a competitive advantage in customer retention is the purpose of strategic technology investment, but the model shows that where consumers are myopic about the benefits they will derive from the technology investment, aggressive price competition by a non-investing firm can prevent the investing firm from acquiring a larger market share and consequently reduce its incentive to invest. However, an investing firm that can persuade consumers of the benefits of the technology investment will have an advantage in customer acquisition and thus may have an incentive to invest. [ABSTRACT FROM AUTHOR]

This paper proposes an on-line mediation services (OMS) mechanism to alleviate the consequences of asymmetric information for traders in C2C markets. In an adverse-selection setting, the mechanism facilitates on-line transactions by (1) inducing traders to negotiate efficiently in the presence of ex post discrepancy, and (2) enabling sellers with higher probability of selling a high-quality product to signal their superiority and enjoy a price premium. The mechanism con also be implemented as a profitable business model. [ABSTRACT FROM AUTHOR]

The synergies between technological developments and market-exchange mechanisms hold considerable promise to unlock market inefficiencies and unleash a new era of digital commerce. Two powerful and fundamental techno-economic forces are already in motion in Internet commerce. One, micro-commoditization, is the ability of a producer to disaggregate a product or service into granular components and deliver it to consumers in a sequence. The other, micro-consumption, is the ability of users to consume such components over time to satisfy a specific need. These emerging phenomena are likely to revolutionize trade practices in the digital world. A model of the interactions among the underlying components of this emerging market structure is developed that envisions the consequents of their behavior on digital markets and consumer behavior, and derives a visionary framework for micro-product market structures of the future. [ABSTRACT FROM AUTHOR]

ABSTRACT: The use of computing technology is a necessary but not sufficient approach to enhancing e-commerce security. It should be supplemented by the application of economic mechanisms to design e-processes that discourage the exploitation of security weaknesses. Mechanisms that function well in traditional commerce should be updated to accommodate new problems raised in e-commerce, such as the lack of authentication. As an illustration, thiezezs research focuses on on-line auction mechanisms and develops a Leveled Partition Set (LPS) protocol for multi-unit sealed-bid auctions. LPS prevents on-line false-name bidding whereby bidders increase their utility by splitting their bids for a large bundle to several smaller bundles under false identities. KEY WORDS AND PHRASES: Economic mechanisms, electronic commerce, information system, multi-unit auction, on-line auction, security. [ABSTRACT FROM AUTHOR]

Rapid technological innovation and changing market expectations in electronic commerce are pushing companies to develop strategies for radically new products, Fast and unbiased new marketing research methods are needed to reduce the associated risks. A full-revelation mechanism is a crucial element of these new methods. It can be implemented with a two-round, second-price, sealed-bid auction. The process of marketing research is accelerated by conducting the auction on-line. [ABSTRACT FROM AUTHOR]

Presents information on the complementarity of mass customization and electronic commerce in profit maximization. Concept of mass customization; Review of literature on different types of mass customization and advancements in electronic commerce; Business value model for mass customization.

Organizations will increasingly be regarded as joint human‐computer knowledge processing systems. This perspective has significant implications for the design, management, and success of an organization. A knowledge‐based organization is seen as a society of knowledge workers who are interconnected by a computerized infrastructure. Their work with various distinct types of knowledge is supported in a coordinated, cooperative fashion by the computerized infrastructure. This article identifies the various knowledge types and the building blocks for an infrastructure. It suggests ways in which the blocks can be combined to enhance worker productivity and ways in which the traditional functional areas of management can contribute to the realization of viable knowledge‐based organizations. [ABSTRACT FROM PUBLISHER]

Scheduling in a flexible manufacturing system (FMS) must take into account the shorter lead-time, the multiprocessing environment, the flexibility of machine tools, and the dynamically changing states. The scheduling approach described in this paper employs a knowledge-based system to carry out the nonlinear planning method developed in artificial intelligence. The state-space process for plan-generation, by either forward- or backward- chaining, can handle scheduling requirements unique to the FMS environment. A prototype of this scheduling system has been implemented on a LISP machine and is applied to solve the scheduling problem in flexible manufacturing cells. This scheduling method is characterized by its knowledge-based organization, symbolic representation, state-space inferencing, and its ability for dynamic scheduling and plan revision. It provides a foundation for integrating intelligent planning, scheduling, and machine learning in FMSs. [ABSTRACT FROM AUTHOR]

In this paper, we present a comprehensive view of problem solving in manufacturing. The central tenet of this. paper is that in addressing complex manufacturing problems, the major focus should be on key decisions and tasks, with the specific aim of improving the effectiveness of the manager's problem solving process. That entails modeling the decision-making process and integrating that with the rest of the problem solving process. A decision support system (DSS) framework that attempts to address these concerns in a unified manner is proposed. [ABSTRACT FROM AUTHOR]

The operation of a networked computing system (NCS), such as the Internet, can be viewed as a resource allocation problem and can be analyzed using the techniques of mathematical economics. We define a general NCS and translate that set-up into a m odel of an economy. The preferences of users are taken as primitives, and servers (providing database services including entertainment and news or computational services) in the network are viewed as productive firms with priority input queues. Each serv er charges a rental price for its services by priority class. We characterize optimal system a!locations and derive formulas for supporting rental prices and priority premiums, such that the aggregated individual user demands ,do not exceed optimal level s, and waiting-time expectations are correct. We propose and implement a decentralized price adjustment process. Some results from a simulation study are presented and discussed. Profit measures for each server can be used to guide investment decisions. [ABSTRACT FROM AUTHOR]

Focuses on the challenges and opportunities of electronic commerce. Description of electronic commerce; Impact of electronic commerce on business communication; Organizational concepts that will be affected by electronic commerce.

The Internet, started as a military communications system and later opened to the public, has created cyberspace, a seemingly limitless array of resources and services. Users can communicate interactively and order products and services from electr onic shopping malls, and organizations can transact business with their partners. Earlier, organizations had limited opportunities to search and select trading partners because of time and cost constraints posed by manual methods of locating and processi ng information on potential partners. Electronic networks like the Internet have opened up a wide array of choices of products and services. Unit cost of communication has reduced dramatically, and a vast amount of supplier/vendor information will be mad e available online. Unfortunately, the information explosion can quickly become an infoglut, if unmatched by better methods of searching and processing information. Without smart strategies, total communication cost may actually increase for network-base d transactions because the cost of information processing (e.g., evaluating supplier bids) has not changed significantly for nonstandard products, and it increases linearly with the number of potential trading partners. Although the Internet reduces time and unit communication cost, it may not reduce total transaction cost. Thus it is critical for commercial Internet service providers to develop guidelines and applications whereby users can appropriate the full benefits of the technology. We suggest tha t such value-added services will reduce price competition among the providers. Taking the case of an organizational buyer using the Internet to select a supplier, we demonstrate that the optimal mechanism depends on the nature of product or service being sought, and the buyer's in-house development... [ABSTRACT FROM AUTHOR]

Internet applications such as the World Wide Web (WWW) have created the possibility of developing global collaborative platforms for supporting interactions between professionals and academics in various disciplines. While Web browsers such as Mosaic and Netscape have revolutionized the way we use the Internet, we envision the need for a theory-based approach to the development of Collaboratories on the Internet. Based on complementarity theory, we provide a conceptual foundation for designing Collaboratories which maximize users' value through the judicious choice of complementary design factors. We emphasize the need for developments in the area of "open'' collaborative systems, and suggest that analyzing the design problem from a complementarity theory standpoint can lead to useful insights regarding the value users derive from the system. We also describe the design and an early implementation of an MIS Collaboratory, which uses this theoretical foundation to organize information and to provide a forum for document-centric, multimedia interactions between users. While the prototype focuses on the MIS discipline, we believe that the general principles of out design are applicable to other areas as well. [ABSTRACT FROM AUTHOR]

We discuss how methods for computer-based collaboration and computer-aided decision analysis may be combined to yield a new generation of decision support systems. We examine the role of these technologies using a three-phase model (problem definition; problem structuring; modeling/analysis) of decision making activities. We argue that decision making is a recursive mesh of these three phases, i.e., each phase involves argumentation/discussion, structuring, and analysis. Representations and methods suited to one kind of activity (e.g., discussion) are not directly suited to the others. Decision support systems, therefore, should facilitate the use of all of these methods in a way that information represented under each of them may be combined effectively, supporting the decision makers in switching from one activity to another. [ABSTRACT FROM AUTHOR]

A going-concern judgment is an important classification of a client that auditors are called upon to render. We study the collective group process of interpretation that auditors are engaged in by examining their individual interpretation processes and their interactions among themselves and with clients. The interpretation process leading to the going-concern judgment involves four phases: (1) recognizing any potential going-concern problems, (2) understanding the cause of those problems, (3) evaluating client plans to mitigate those problems, and (4) rendering a going concern judgment. We capture the process underlying a going-concern judgment by representing the content and process of the interactions using an argumentation language. [ABSTRACT FROM AUTHOR]

In recent years, network organizations have gained much attention as more and more of them have emerged in various industries. The problem of coordination within network organizations is an important one that differs in major ways from coordination within hierarchies or markets. We contend that computer technology has a potential for usefully supporting coordination efforts in networks. As a basis for studying such potential in a systematic way, a formal model of network organizations would be helpful, particularly to the extent that it represents coordination possibilities. From a long-term perspective, the success of a network organization depends on more than efficient transaction processing. It also depends on factors such as participant reliability, motivation, mutual trust, cooperation, creativity, and prudent evolution. All of these are related to the issue of a participant's value (past, current, ongoing, changing) to the network. We introduce a model that formalizes some key aspects of network organizations. At the heart of our formulation is a construct called "reputation," which encapsulates the many attributes that can characterize participants' past behaviors in a network. This model characterizes essential informational aspects of a network organization in a quantifiable form that lays a foundation for analyzing, designing, and implementing computer-based systems to facilitate network operation and growth. We use the model to discuss possibilities for computer-based support of network organizations at managerial and strategic levels, as complements to transaction-level Electronic Data Interchange-like systems. [ABSTRACT FROM AUTHOR]

Organization design is a pervasive phenomenon that significantly impacts performance, and yet organization design activity has received little direct support from computer technology. If organization learning is viewed as the process whereby knowledge is developed, then organization design both influences the organizational learning that occurs and is at least a partial reflection of the organizational learning that has occurred. This article examines the significance, bases, and means for developing multi-user, computer-based environments for supporting organization design and learning. The article introduces a working perspective of organization design and learning highlighted by three key ideas. Organization design and learning (1) is defined in terms of organization work, structure, and process; (2) is an ongoing evolutionary phenomenon; and (3) can and should be an inclusive, distributed, multi-participant effort. The article identifies the requirements for computer-based technology that supports this working perspective and then presents an overview of a prototype technology that addresses these requirements. The prototype technology consists of two interacting components: Deva, an interactive, multi-user, graphical editor for managing process descriptions; and GPOD, an associated group process for using Deva for organization design. We conclude that such technologies will enable organizations to become self-organizing systems, thereby allowing them to compete more effectively and survive in today's rapidly changing environment. [ABSTRACT FROM AUTHOR]

This article describes the initial stage of an exploratory research project on improving scientific collaboration. For the purpose of laying conceptual foundations of scientific collaboration, we discuss general requirements of a collaborative system for Scientific researchers. With these requirements in mind, we outline the technical design of a prototype system to support scientific collaboration. This design involves a method of structured discourse and is integrated with electronic mail. The prototype system, currently being developed, will be tested by the authors who are collaborating on various research projects in the United States and Finland. Preliminary results will be available in the near term. Further development will include the incorporation of project management, negotiation support, and document production tools into the system. [ABSTRACT FROM AUTHOR]

Editorial. Focuses on the definition of the organizational computing (OC) field. Scope of OC; Identification of research using OC; Characteristics of OC systems.

The article presents a list of the members of the editorial board of the "Journal of Organizational Computing & Electronic Commerce," including Starr Roxanne Hiltz from New Jersey Institute of Technology, Ray Panko from the University of Hawaii, and Judith Olson from the University of Michigan.

Focuses on the topics presented in the special issue of the Journal of Organizational Computing. Goal of exploring the challenging and exciting developments in the field of organizational computing; Dynamics of interacting behavior; Presentation of requirement for effective collaboration system.