Date of Award


Embargo Period


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Tepper School of Business


Alan Scheller-Wolf


In this dissertation, I discuss three problems within service operations management: identifying situational attributes that lead to positive customer outcomes under a Twitter-based customer service framework; the conditions for finite delay of first-in-first-out multiserver systems when confronted with integral loads; and the relative performance of different bargaining mechanisms for a seller of finite perishable inventory, with a further investigation of the consequences of modeling private information. First, we consider a large telecommunications company that provides customer support over Twitter. Using 10 months of service data, we apply model selection techniques to develop an ordinal logistic regression model assessing the probability that a given customer service interaction will result in a positive, neutral or negative resolution as determined by the customer’s sentiment expression. Our model incorporates customer, service and network explanatory attributes. We find that customers are less likely to experience a positive final sentiment as time passes, that is, those cases later in the 10 month period studied are less likely to experience positive resolution. This suggests that there is a drop-off in the likelihood of more positive resolution, but that this effect levels off. This finding may indicate a shift by the customer service team to harder to resolve cases as the program matures. Next, we consider conditions for finite expected delay in FIFO multiserver queues with integral loads. Scheller-Wolf and Vesilo (2006) find necessary and sufficient conditions for a finite rth moment of expected delay in a FIFO multiserver queue, assuming a non-integral load and a service time distribution belonging to class L1B . Removing the non-integral load assumption results in a gap between the identified necessary and sufficient conditions, as discussed by Foss (2009). We decrease the size of this gap through the application of domain of attraction results. Specifically, we find a stricter necessary condition for a GI/GI/K-server system with integral p that is more restrictive than those in the literature. Finally, we consider the problem of a seller with a finite supply of perishable inventory. We consider four price setting mechanisms: seller posted price, buyer posted price, split-the-difference, and the neutral bargaining solution. We rank the value of these different mechanisms analytically and numerically in the context of the symmetric uniform trading problem from the perspective of the seller. While the ordering of the mechanisms remains the same as compared to the infinite horizon case studied in the literature, we use a model analogous to the infinite horizon case to find numerically that the relative value of the split-the-difference mechanism increases when the seller ultimately faces a dead- line to complete the sales. The split-the-difference mechanism becomes more valuable as the ratio of available inventory to time remaining increases because it is more likely to result in a sale than the seller posted price mechanism. In general, modeling private information is more challenging for the split-the-difference and neutral bargaining solution mechanisms than for the two posted price mechanisms. To assess the importance of this added complication, we quantify the effect of modeling private information when computing the seller’s opportunity cost and find that while private information makes only a small difference in the neutral bargaining solution case, this modeling choice makes a large difference in the split-the-difference case when the seller is weak.