Understanding Patterns of Publishing Activity in Academic Research Occupations*

While it is widely understood that faculty in various disciplines tend to publish at different rates and in different forms, knowledge of these differences is too limited to facilitate systematically differentiated performance appraisal and reward systems. In this study, theory concerning knowledge production system characteristics as influences on individual performance is applied to academic research occupations using a classification scheme developed by Biglan [4]. Regression analysis is applied to a general (industry-wide) sample of United States faculty, with publishing patterns as performance measures. Each dimension of the classification scheme is found to have predictive validity. Output patterns are consistent with a conceptualization of research occupations in terms of (1) transformational/technological processes, (2) research mission, and (3) input/subject matter characteristics. The results offer a basis for generating disciplinary publishing norms and differentiated reward systems.     

ONE APPROACH TO REALLOCATING INSTRUCTIONAL RESOURCES: THE HOUSTON MODEL

In this paper a model for deciding which instructional departments should receive and surrender new or reallocatable resources is developed. It combines a two-dimensional assessment of resource needs based on instructional characteristics and the academic priority of the department to arrive at resource allocation priorities. Unusual features of the model are its reliance on judgments of departmental centrality to institutional mission as the discriminating variable in ascribing academic priorities and the careful avoidance of “halo effects” through independent assessment of resource needs and academic priorities. The model is sensitive enough to discriminate between competing claims for scarce resources while retaining a simplicity of logic that makes its mechanics understandable to those with little grounding in the decision sciences.     

DEMAND MANAGEMENT: THE EVALUATION OF PRICE AND DUE DATE NEGOTIATION STRATEGIES USING SIMULATION

The research considers the problem of demand management in a firm where the firm's historical delivery service level reputation influences the number of quotation requests from its potential customers. Customers have a maximum and the firm has a minimum net price to due date tradeoff curve for each job. The demand management function bargains with the customer over price and promised due date. Bargaining finishes either with an agreed price and delivery date or with the customer refusing the firm's bid and placing the order elsewhere. The firm's objective is to maximize its long-term net revenue. The firm's demand management negotiation strategy guides this bidding process. The research demonstrates the use of simulation to test different demand management bidding and negotiation strategies for different market and firm scenarios. The demonstration uses 16 scenarios to test the different demand management negotiation strategies with a model of a classical job shop in a classical market. The investigation examines finite scheduling-based due date estimation methods, as well as the more traditional parameter-based methods. This demonstration shows that it is possible to test different bidding policies, using a simulation model of a firm and its customers, and to obtain usable results.