Revisiting activity sampling: A fresh look at binomial proportion confidence intervals

The Wald interval is typically used to assign confidence to the accuracy of activity sampling studies. It is known the performance of the Wald interval is poor, especially when the observed probability is near zero or one. The suitability of the Wald interval for activity sampling is not often discussed in the operations management literature; if it is, this is usually followed by inappropriate and incorrect advice. Herein, a range of alternative binominal confidence intervals for activity sampling is reviewed. A number of selection criteria are considered including achievement of the target nominal coverage probability, size of the interval, and ease of use and presentation. It is recommended that the Clopper-Pearson interval is used for activity sampling. A table of confidence intervals and sample sizes that is specifically designed to be used within a new activity sampling procedure based on the Clopper-Pearson interval is developed. Finally, pedagogical issues are considered

Supply Chain Collaboration in Tourism: A Transaction Cost Economics Analysis

This paper explores inter-firm collaboration in a tourism supply chain via transaction cost economics using a single case-study method. We focus on supply chain collaboration between a hotel, and its food and beverage suppliers. The transaction costs found consist of the search cost and cost of quality checking. Search cost exists due to bounded rationality of the firm. This is influenced by asymmetric information. The cost of quality checking incurs because the firm perceives that its suppliers may behave opportunistically. It is revealed that trust could reduce transaction cost of the tourist operators

The order-up-to policy "sweet spot": using proportional controllers to eliminate the bullwhip problem

We develop a discrete control theory model of a stochastic demand pattern with both Auto Regressive and Moving Average (ARMA) components. We show that the bullwhip effect arises when the myopic Order-Up-To (OUT) policy is used. This policy is optimal when the ordering cost is linear. We then derive a set of z-transform transfer functions of a modified policy that allows us to avoid the bullwhip problem by incorporating a proportional controller into the inventory position feedback loop. With this technique, the order variation can be reduced to the same level as the demand variation. However, bullwhip-effect avoidance in our policy always comes at the costs of holding extra inventory. When the ordering cost is piece -wise linear and increasing, we compare the total cost per period under the two types of ordering policies: with and without bullwhip - effect reduction. Numerical examples reveal that the cost saving can be substantial if order variance is reduced using the proportional controller