Knowledge that Transforms

During the early phase of systems development, systems analysts often conceptualize the domain under study and represent it in one or more conceptual models. One of the most important, yet elusive ...

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The theory of incomplete contracts has been used to study the relationship between buyers and suppliers following the deployment of modern information technology to facilitate coordination between them. Previous research has sought to explain anecdotal evidence from some industries on the recent reduction in the number of suppliers selected to do business with buyers by appealing to relationship-specific costs that suppliers may incur. In contrast, this paper emphasizes that information technology enables greater completeness of buyer-supplier contracts through more economical monitoring of additional dimensions of supplier performance. The number of terms included in the contract is an imperfect substitute for the number of suppliers. Based on this idea, alternative conditions are identified under which increased use of information technology leads to a reduction in the number of suppliers without invoking relationship-specific costs. We find that a substantial increase in contract completeness due to reduced cost of information technology could increase the cost per supplier even though the cost of coordination and the cost per term monitored decrease. Such an increase in the cost per supplier leads to a reduction in the number of suppliers with whom the buyer chooses to do business. Similarly, we find that if coordination cost is reduced when more information technology is deployed so that the number of suppliers in the buyer’s pool increases substantially, the buyer might choose to make the supplier contracts less complete, instead relying on a more market-oriented approach to finding a supplier with good fit.

This paper reports an analysis of the proportion of faculty publishing articles in premier business journals (i.e., the ratio of authors of premier business journal articles to total faculty of a discipline) across the disciplines of accounting, finance, management, marketing, and information systems (IS) for the years 1994–2003. This analysis revealed that over this period the management discipline had on average the highest proportion of faculty publishing in premier journals (12.7 authors per 100 management faculty), followed by finance (9.4 authors per 100 faculty), marketing (9.2 authors per 100 faculty), IS (5.5 authors per 100 faculty), and accounting (4.8 authors per 100 faculty). A further analysis examined these ratios for the different disciplines over time, finding that the ratios of authors to faculty have actually decreased for the disciplines of marketing and IS over this time period but have remained stable for the disciplines of accounting, management, and finance. Given steady growth in faculty size of all disciplines, the proportion of faculty publishing articles in premier journals in 2003 for all disciplines is lower than their 10-year averages, with IS having the lowest proportion in 2003. A sensitivity analysis reveals that without substantial changes that would allow more IS faculty to publish in the premier journals (e.g., by increasing publication cycles, number of premier outlets, and so on), IS will continue to lag far below the average of other disciplines. The implications of these findings for IS researchers, for institutions and administrators of IS programs, and for the IS academic discipline are examined. Based on these implications, recommendations for the IS discipline are presented.

A tariff is the total charge payable by a customer for services provided. We study the design of tariffs for a telecommunications service provider. We develop an economic model that captures the negative externalities of the network and the diversity of customers. The tariff is designed so that it reflects the expected response of different customers and the system congestion it would induce. We study a simple tariff structure in wide use by mobile phone carriers—a menu of “fixed-up-to (FUT)” plans like “fixed access fee $35 up to 300 minutes, and $0.40 per minute beyond the limit.” We derive the optimal menu of FUT plans and show that such a simple FUT menu structure delivers as good performance to the monopolistic carrier as any nonlinear pricing schedule.

To respond to growing concerns about privacy of personal information, organizations that use their customers' records in data-mining activities are forced to take actions to protect the privacy of the individuals involved. A common practice for many organizations today is to remove identity-related attributes from the customer records before releasing them to data miners or analysts. We investigate the effect of this practice and demonstrate that many records in a data set could be uniquely identified even after identity-related attributes are removed. We propose a perturbation method for categorical data that can be used by organizations to prevent or limit disclosure of confidential data for identifiable records when the data are provided to analysts for classification, a common data-mining task. The proposed method attempts to preserve the statistical properties of the data based on privacy protection parameters specified by the organization. We show that the problem can be solved in two phases, with a linear programming formulation in Phase I (to preserve the first-order marginal distribution), followed by a simple Bayes-based swapping procedure in Phase II (to preserve the joint distribution). Experiments conducted on several real-world data sets demonstrate the effectiveness of the proposed method.