This study introduces a universal “Dome” appointment rule that can be parameterized through a planning constant for different clinics characterized by the environmental factors—no‐shows, walk‐ins, number of appointments per session, variability of service times, and cost of doctor's time to patients’ time. Simulation and nonlinear regression are used to derive an equation to predict the planning constant as a function of the environmental factors. We also introduce an adjustment procedure for appointment systems to explicitly minimize the disruptive effects of no‐shows and walk‐ins. The procedure adjusts the mean and standard deviation of service times based on the expected probabilities of no‐shows and walk‐ins for a given target number of patients to be served, and it is thus relevant for any appointment rule that uses the mean and standard deviation of service times to construct an appointment schedule. The results show that our Dome rule with the adjustment procedure performs better than the traditional rules in the literature, with a lower total system cost calculated as a weighted sum of patients’ waiting time, doctor's idle time, and doctor's overtime. An open‐source decision‐support tool is also provided so that healthcare managers can easily develop appointment schedules for their clinical environment.

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Responding to regional and international competition, many manufacturing companies have adopted MRP systems to improve their manufacturing operations. Of primary interest to managers and users of MRP is the benefits that can be derived from using the MRP technology. While the literature abounds with MRP implementation studies, there is a dearth of research that examines the determinants of specific MRP benefits. Knowledge of the determinants would enable MRP managers and users to concentrate on key areas to achieve benefits that match their company goals. This paper identifies the organisational, implementational, and technological variables that affect specific MRP benefits as reported by Singapore manufacturing companies in the most extensive MRP survey ever conducted in Singapore. Using Alternating Conditional Expectation (ACE), an advanced statistical modeling technique that increases the model fit by approximating the optimal transformations for the dependent and independent variables, the regression models developed reveal more accurate relationships compared to those in previous MRP studies. Our findings offer several novel and valuable insights into the MRP benefit‐determinant relationship. The major finding is that determinant variables such as data accuracy, people support, degree of integration, and company size affect benefits in a nonlinear fashion. Data accuracy was found to be critical in affecting operational efficiency, customer service, and interdepartmental coordination benefits. Another finding suggests that when people support and data accuracy degenerate to a critical level, users might still derive increased benefits by resorting to secondary sources to accomplish their work. Users should strive for a high degree of integration to achieve full operational efficiency and coordination benefits. Partial integration does not appear to provide significant improvements. We also found that increasing company size has a positive, followed by a negative impact on operational efficiency. Lastly, our findings suggest that the pattern of technical complaints can be an indicator of system usage and interdepartmental coordination. Our findings have important implications for managers and users of MRP.

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This paper addresses the dearth of research on the determinants of IS planning benefits. Data were collected using a questionnaire survey of top IS executives from 450 companies in Singapore. Of the 103 responses (representing a response rate of 23%), 65 companies undertook IS planning. To test the hypothesis that the determinant-benefit relationships are likely to be nonlinear, the Alternating Conditional Expectations (ACE) algorithm was used. This appears to be the first use of ACE in IS planning research. IS sophistication, communications culture, technology forecasting, top management support, and firm size were found to be nonlinearly related to IS planning benefits (e.g., improved competitiveness, operations, and resource management). For example, IS sophistication affects improved competitiveness positively, and improved resource management negatively. It seems that IS sophistication is directed more at improving competitiveness, even though this may result in less efficient resource management due to bureaucratic procedures. However, at higher levels of IS sophistication, competitiveness stagnates and may even decrease, possibly due to bureaucratic bottlenecks. Implications of our results are discussed.