Organizational Design and Control across Multiple Markets: The Case of Franchising in the Convenience Store Industry

Many companies operate units which are dispersed across different types of markets, and thus serve significantly diverging customer bases. Such market-type dispersion is likely to compromise the headquarters' ability to control its local managers' behavior and satisfy the divergent needs of different types of customers. In this paper we find evidence that market-type dispersion is an important determinant of delegation and the provision of incentives. Using a sample of convenience store chains, we show that market-type dispersion is related to the degree of franchising at the chain level as well as the probability of franchising a given store within a chain. Our results are robust to alternative definitions of market-type dispersion and to other determinants of franchising such as the stores' geographic distance from headquarters and geographic dispersion. Additional analyses also suggest that chains that do not franchise at all, may cope with market-type dispersion by decentralizing operations from headquarters to their stores, and, to a weaker extent, by providing higher variable pay to their store managers.Control, Market Dispersion, Decentralization, Incentives, Franchising, Retailing

Investigating the Application of Queue Theory in the Nigerian Banking System

This study examined the application of queue theory in the banking system in Nigeria, with particular reference to GTBank and Ecobank Idumota branch, Lagos, Lagos state. The queuing characteristics of the banks were analyzed using a Multi-Server Queuing Model. The performance measures analysis including the waiting and operation costs for the banks were computed with a view to determining the optimal service level. Findings revealed that the traffic intensity was higher in GTbank with p =0.98 than in Ecobank with p= 0.78. Also, the potential utilization showed that Ecobank was far below efficiency compared to GTBank. Looking at the waiting time of customers in line and the time spent in the system, that is (Wq + Ws), we discovered that customers in Ecobank spent more time before being served both on queue and in the system than that of GTBank bank. The study concluded by emphasizing the relevance of queuing theory to the effective service delivery of the banking sector in Nigeria and strongly recommends that for efficiency and quality of service delivery to customers, the management of GTBank and Ecobank should adopt a 13-server model and 10-server model respectively to reduce total expected costs and increase customer satisfaction

Investigating the Application of Queue Theory in the Nigerian Banking System

This study examined the application of queue theory in the banking system in Nigeria, with particular reference to GTBank and Ecobank Idumota branch, Lagos, Lagos state. The queuing characteristics of the banks were analyzed using a Multi-Server Queuing Model. The performance measures analysis including the waiting and operation costs for the banks were computed with a view to determining the optimal service level. Findings revealed that the traffic intensity was higher in GTbank with p =0.98 than in Ecobank with p= 0.78. Also, the potential utilization showed that Ecobank was far below efficiency compared to GTBank. Looking at the waiting time of customers in line and the time spent in the system, that is (Wq + Ws), we discovered that customers in Ecobank spent more time before being served both on queue and in the system than that of GTBank bank. The study concluded by emphasizing the relevance of queuing theory to the effective service delivery of the banking sector in Nigeria and strongly recommends that for efficiency and quality of service delivery to customers, the management of GTBank and Ecobank should adopt a 13-server model and 10-server model respectively to reduce total expected costs and increase customer satisfaction

Service Delivery and Customer Satisfaction in Nigerian Banks

The study examined the impact of the quality of service delivery on customer satisfaction in the Nigerian banks using Ordinary Least Square (OLS) methodology. The study established a relationship between better banks performance in service delivery and customer satisfaction through effective customer relationship management (CRM). Findings revealed that increase in the number of working days and number of bank branches led to better levels of customer satisfaction. Empirical evidence also revealed that increase in PROFIT margin is a function of improved level of customer satisfaction while number of bank branches (NNB) has a positive but insignificant relationship with customer satisfaction because the spread of branch networks or channels has better effects on customer satisfaction than number of banks. It also emphasized the role of the number of working days in achieving better bank services and profitable customer relationship management. The study thus recommends that the Nigeria banking industry should improve the quality of service delivery as it is a prerequisite for achieving a high level of customer satisfaction

Service Delivery and Customer Satisfaction in Nigerian Banks

The study examined the impact of the quality of service delivery on customer satisfaction in the Nigerian banks using Ordinary Least Square (OLS) methodology. The study established a relationship between better banks performance in service delivery and customer satisfaction through effective customer relationship management (CRM). Findings revealed that increase in the number of working days and number of bank branches led to better levels of customer satisfaction. Empirical evidence also revealed that increase in PROFIT margin is a function of improved level of customer satisfaction while number of bank branches (NNB) has a positive but insignificant relationship with customer satisfaction because the spread of branch networks or channels has better effects on customer satisfaction than number of banks. It also emphasized the role of the number of working days in achieving better bank services and profitable customer relationship management. The study thus recommends that the Nigeria banking industry should improve the quality of service delivery as it is a prerequisite for achieving a high level of customer satisfaction

Algorithmic Decision-Making Safeguarded by Human Knowledge

Commercial AI solutions provide analysts and managers with data-driven business intelligence for a wide range of decisions, such as demand forecasting and pricing. However, human analysts may have their own insights and experiences about the decision-making that is at odds with the algorithmic recommendation. In view of such a conflict, we provide a general analytical framework to study the augmentation of algorithmic decisions with human knowledge: the analyst uses the knowledge to set a guardrail by which the algorithmic decision is clipped if the algorithmic output is out of bound, and seems unreasonable. We study the conditions under which the augmentation is beneficial relative to the raw algorithmic decision. We show that when the algorithmic decision is asymptotically optimal with large data, the non-data-driven human guardrail usually provides no benefit. However, we point out three common pitfalls of the algorithmic decision: (1) lack of domain knowledge, such as the market competition, (2) model misspecification, and (3) data contamination. In these cases, even with sufficient data, the augmentation from human knowledge can still improve the performance of the algorithmic decision

Task Selection and Workload: A Focus on Completing Easy Tasks Hurts Long-Term Performance

How individuals manage, organize, and complete their tasks is central to operations management. Recent research in operations focuses on how under conditions of increasing workload individuals can increase their service time, up to a point, in order to complete work more quickly. As the number of tasks increases, however, workers may also manage their workload by a different process – task selection. Drawing on research on workload, individual discretion, and behavioral decision making we theorize and then test that under conditions of increased workload individuals may choose to complete easier tasks in order to manage their load. We label this behavior Task Completion Bias (TCB). Using two years of data from a hospital emergency department we find support for TCB and also show that it improves short-term productivity. However, although it improves performance in the short-term we find that an overreliance on this task selection strategy hurts performance – as measured both by speed and revenue – in the long run. We then turn to the lab to replicate conceptually the task selection effect and show that it occurs due to the positive feelings individuals get from task completion. These findings provide an alternative mechanism for the workload-speedup effect from the literature. We also discuss implications for both research and the practice of operations in building systems to help people succeed in both the short and long run

Services in Manufacturing Industries: Contributions to Quality and Competition

Motivated by the increasingly important role of services in manufacturing industries, this dissertation examines implications of this trend for quality management and competition by firms engaged in the production of joint product-service offerings. Broadly defined, we study the following research questions: How do the service contracts offered by manufacturers affect product quality? How does consumer demand respond to product quality and service attributes when manufacturers compete on services? How are consumer intentions influenced by product quality and service quality perceptions, and how does consumer heterogeneity influence this relationship? We empirically study these questions in the aerospace, automobile and consumer electronics industries, respectively. In the first study, we examine the impact of Performance-Based Contracting on product reliability in an application in the aerospace industry (aircraft engines), and show that the incentive alignment induced by performance-based contracts positively influences product reliability by different mechanisms. In the second essay, we formulate and estimate a structural model to analyze the impact of service competition and product quality in the U.S. automobile industry. We show that the impact of service attributes (warranty length, service quality) on consumer demand critically depends on the firm\u27s product quality. Finally, in the third essay (consumer electronics industry), we examine the joint influence of product quality and service quality perceptions on consumer intentions toward a brand, and show that consumer heterogeneity plays a significant role in defining this relationship. Collectively, our results suggest that the joint consideration of product and service is essential for the development of an effective competitive strategy and for the management of quality by manufacturing firms

Data-driven System Design in Service Operations

The service industry has become an increasingly important component in the world's economy. Simultaneously, the data collected from service systems has grown rapidly in both size and complexity due to the rapid spread of information technology, providing new opportunities and challenges for operations management researchers. This dissertation aims to explore methodologies to extract information from data and provide powerful insights to guide the design of service delivery systems. To do this, we analyze three applications in the retail, healthcare, and IT service industries. In the first application, we conduct an empirical study to analyze how waiting in queue in the context of a retail store affects customers' purchasing behavior. The methodology combines a novel dataset collected via video recognition technology with traditional point-of-sales data. We find that waiting in queue has a nonlinear impact on purchase incidence and that customers appear to focus mostly on the length of the queue, without adjusting enough for the speed at which the line moves. We also find that customers' sensitivity to waiting is heterogeneous and negatively correlated with price sensitivity. These findings have important implications for queueing system design and pricing management under congestion. The second application focuses on disaster planning in healthcare. According to a U.S. government mandate, in a catastrophic event, the New York City metropolitan areas need to be capable of caring for 400 burn-injured patients during a catastrophe, which far exceeds the current burn bed capacity. We develop a new system for prioritizing patients for transfer to burn beds as they become available and demonstrate its superiority over several other triage methods. Based on data from previous burn catastrophes, we study the feasibility of being able to admit the required number of patients to burn beds within the critical three-to-five-day time frame. We find that this is unlikely and that the ability to do so is highly dependent on the type of event and the demographics of the patient population. This work has implications for how disaster plans in other metropolitan areas should be developed. In the third application, we study workers' productivity in a global IT service delivery system, where service requests from possibly globally distributed customers are managed centrally and served by agents. Based on a novel dataset which tracks the detailed time intervals an agent spends on all business related activities, we develop a methodology to study the variation of productivity over time motivated by econometric tools from survival analysis. This approach can be used to identify different mechanisms by which workload affects productivity. The findings provide important insights for the design of the workload allocation policies which account for agents' workload management behavior