Competitive facility location model with concave demand

We consider a spatial interaction model for locating a set of new facilities that compete for customer demand with each other, as well as with some pre-existing facilities to capture the “market expansion” and the “market cannibalization” effects. Customer demand is assumed to be a concave non-decreasing function of the total utility derived by each customer from the service offered by the facilities. The problem is formulated as a non-linear Knapsack problem, for which we develop a novel solution approach based on constructing an efficient piecewise linear approximation scheme for the objective function. This allows us to develop exact and α-optimal solution approaches capable of dealing with relatively large-scale instances of the model. We also develop a fast Heuristic Algorithm for which a tight worst-case error bound is established.     

基于两阶段DEA方法的中国商业银行效率评价

本文考虑商业银行吸收存款和发放贷款的两阶段特点,引入“顾客满意度”这一产出指标,应用两阶段DEA模型计算了我国15家商业银行在2008年和2011年的服务质量效率和盈利效率,结果显示我国商业银行的盈利效率显著高于服务质量效率。进而综合考虑服务和盈利指标,分析了各银行的综合效率,并通过计算各银行Malmquist指数研究我国商业银行2008年到2011年间的效率变化。结果表明:各商业银行从2008年到2011年的效率整体呈上升趋势,各商业银行的技术效率以及整个银行业的效率都有一定的提高。最后,应用Tobit模型分析了影响银行效率的因素,结果显示银行的贷存比、资产利润率和不良贷款率对效率影响显著。     

Comparisons between observable and unobservable M/M/1 queues with respect to optimal customer behavior

We consider an M/M/1 queueing system in which the queue length may or may not be observable by a customer upon entering the system. The “observable” and “unobservable” models are compared with respect to system properties and performance measures under two different types of optimal customer behavior, which we refer to as “selfishly optimal” and “socially optimal”. We consider average customer throughput rates and show that, under both types of optimal customer behavior, the equality of effective queue-joining rates between the observable and unobservable systems results in differences with respect to other performance measures such as mean busy periods and waiting times. We also show that the equality of selfishly optimal queue-joining rates between the two types of system precludes the equality of socially optimal joining rates, and vice versa.     

Quantile regression for robust bank efficiency score estimation

We discuss quantile regression techniques as a robust and easy to implement alternative for estimating Farell technical efficiency scores. The quantile regression approach estimates the production process for benchmark banks located at top conditional quantiles. Monte Carlo simulations reveal that even when generating data according to the assumptions of the stochastic frontier model (SFA), efficiency estimates obtained from quantile regressions resemble SFA-efficiency estimates. We apply the SFA and the quantile regression approach to German bank data for three banking groups, commercial banks, savings banks and cooperative banks to estimate efficiency scores based on a simple value added function and a multiple-input–multiple-output cost function. The results reveal that the efficient (benchmark) banks have production and cost elasticities which differ considerably from elasticities obtained from conditional mean functions and stochastic frontier functions.     

A real-time decision rule for an inventory system with committed service time and emergency orders

In this paper, we study the inventory system of an online retailer with compound Poisson demand. The retailer normally replenishes its inventory according to a continuous review (nQ, R) policy with a constant lead time. Usually demands that cannot be satisfied immediately are backordered. We also assume that the customers will accept a reasonable waiting time after they have placed their orders because of the purchasing convenience of the online system. This means that a sufficiently short waiting time incurs no shortage costs. We call this allowed waiting time “committed service time”. After this committed service time, if the retailer is still in shortage, the customer demand must either be satisfied with an emergency supply that takes no time (which is financially equivalent to a lost sale) or continue to be backordered with a time-dependent backorder cost. The committed service time gives an online retailer a buffer period to handle excess demands. Based on real-time information concerning the outstanding orders of an online retailer and the waiting times of its customers, we provide a decision rule for emergency orders that minimizes the expected costs under the assumption that no further emergency orders will occur. This decision rule is then used repeatedly as a heuristic. Numerical examples are presented to illustrate the model, together with a discussion of the conditions under which the real-time decision rule provides considerable cost savings compared to traditional systems.     

Linking customer satisfaction, employee appraisal, and business performance: an evaluation methodology in the banking sector

The linkage among customer satisfaction, employee evaluation, and business performance data is very important in modern business organizations. Several previous research efforts have studied this linkage, focusing mainly on the financial or business performance in order to analyze the efficiency of an organization. However, recent studies have tried to consider other important performance indicators, which are able to affect business operations and future growth (e.g., external and internal customer satisfaction). In the case of the banking industry, studying the relations among the aforementioned variables is able to give insight in the performance evaluation of bank branches and the viability analysis of the banking organization. This paper presents a real-world study for measuring the relative efficiency of a set of bank branches using a Data Envelopment Analysis (DEA) approach. In particular, a multistage DEA network model is proposed, using a set of performance indicators that combine customer satisfaction, employee evaluation, and business performance indices. The main aim of the presented study is to evaluate the relative efficiency of each customer service delivery step, in the environment of a bank branch. The results are also able to estimate the contribution of the assessed performance indicators to the branch’s overall efficiency, and to determine potential improvement actions.     

Efficiency analysis to incorporate interval-scale data

We develop an approach to efficiency analysis to enable us to incorporate interval-scale data in addition to ratio-scale data. Our approach introduces a measure of inefficiency and identifies efficient units as is done in Data Envelopment Analysis. The basic idea in our approach is to find the “best” hyperplane separating the units that are better and worse than each unit. “Best” is defined in such a way that the number of not-better units is maximal. The efficiency measure is defined as a proportion of not-better units to all units. The results are invariant under a strictly increasing linear re-scaling of any input- or output-variables. Thus zeroes or negative values do not cause problems for the analysis. The approach is used to analyze the data of the research evaluation exercise recently carried out at the University of Joensuu, Finland.     

Inequalities for Queues with a Learning Server

We study a multi-class queue with a learning server who becomes stochastically faster with each subsequent customer served of the same type in a row, and returns to some baseline speed each time he switches to a different type of customer. We show under some conditions that customer waiting time is larger (in the increasing convex ordering sense) with server learning than in a queue with iid service times having the same marginal service distribution as the learning server. An easy to evaluate inequality for the mean stationary waiting time is derived from this in the case of Poisson arrivals, and results in more general settings are given. The primary tool used in the proofs is the supermodularity of the delay in queue as a function of previous service times.     

Delay Distribution of (Im)Patient Customers in a Discrete Time D-MAP/PH/1 Queue with Age-Dependent Service Times

This paper presents an algorithmic procedure to calculate the delay distribution of (im)patient customers in a discrete time D-MAP/PH/1 queue, where the service time distribution of a customer depends on his waiting time. We consider three different situations: impatient customers in the waiting room, impatient customers in the system, that is, if a customer has been in the waiting room, respectively, in the system for a time units it leaves the waiting room, respectively, the system. In the third situation, all customers are patient – that is, they only leave the system after completing service. In all three situations the service time of a customer depends upon the time he has spent in the waiting room. As opposed to the general approach in many queueing systems, we calculate the delay distribution, using matrix analytic methods, without obtaining the steady state probabilities of the queue length. The trick used in this paper, which was also applied by Van Houdt and Blondia [J. Appl. Probab., Vol. 39, No. 1 (2002) pp. 213–222], is to keep track of the age of the customer in service, while remembering the D-MAP state immediately after the customer in service arrived. Possible extentions of this method to more general queues and numerical examples that demonstrate the strength of the algorithm are also included.     

Evaluating the financial performance of bank branches

We evaluate the financial performance of most of the branch offices of a large European savings bank for a recent accounting period. We employ a complementary pair of nonparametric techniques to evaluate their financial performance, in terms of their ability to conserve on the expenses they incur in building their customer bases and providing customer services. We find variation in the ability of branch offices to perform this task, and agreement on the identity of the laggard branches. We then employ parametric techniques to determine that the list of indicators on which their financial performance is evaluated can be reduced without statistically significant loss of information to bank management. Both findings suggest ways in which the bank can increase the profitability of its branch network. A previous version of this paper was presented at CORE, Université Catholique de Louvain, Louvain-la-Neuve, Belgium, where we received many helpful comments from the audience. We are grateful to three referees for their helpful comments as well.     

Service and cost benefits through clicks-and-mortar integration: Implications for the centralization/decentralization debate

Traditional “Brick-and-Mortar” operations face the challenge of adapting to a new set of competitive rules made necessary by consumers who want the option of ordering electronically via the Internet. To satisfy these customers, firms must develop strategies that integrate their standard retail in-store channel with this relatively new on-line channel. Therefore, this research is designed to provide insights into supply chain inventory management strategies relevant to “Clicks-and-Mortar” firms trying to satisfy both on-line and in-store sales. Specifically, this work considers the total cost implications of various inventory allocation strategies while maintaining target customer service levels. Analysis focuses on the development of models capable of handling new operating strategies made possible by electronic commerce. The implications of inventory risk pooling are considered in depth, revealing the existence of characteristics that determine whether completely centralized or decentralized policies are preferable.     

Comparative efficiency analysis of Portuguese bank branches

The advent of Internet banking and phone banking is changing the role of bank branches from a predominantly transaction-based one to a sales-oriented role. This paper reports on an assessment of the branches of a Portuguese bank in terms of their performance in their new roles in three different areas: Their efficiency in fostering the use of new transaction channels, their efficiency in increasing sales and their customer base, and their efficiency in generating profits. Service quality is also a major issue in service organisations like bank branches, and therefore we analyse the way this dimension of performance has been accounted for in the literature and take it into account in our empirical application. We have used data envelopment analysis (DEA) for the different performance assessments, but we depart from traditional DEA models in some cases. Performance comparisons on each dimension allowed us to identify benchmark bank branches and also problematic bank branches. In addition, we found positive links between operational and profit efficiency and also between transactional and operational efficiency. Service quality is positively related with operational and profit efficiency.     

Meta-data envelopment analysis: Finding a direction towards marginal profit maximization

This paper discusses a new meta-DEA approach to solve the problem of choosing direction vectors when estimating the directional distance function. The proposed model emphasizes finding the “direction” for productivity improvement rather than estimating the “score” of efficiency; focusing on “planning” over “evaluation”. In fact, the direction towards marginal profit maximization implies a step-by-step improvement and “wait-and-see” decision process, which is more consistent with the practical decision-making process. An empirical study of U.S. coal-fired power plants operating in 2011 validates the proposed model. The results show that the efficiency measure using the proposed direction is consistent with all other indices with the exception of the direction towards the profit-maximized benchmark. We conclude that the marginal profit maximization is a useful guide for determining direction in the directional distance function.     

Ensuring service levels in routing problems with time windows and stochastic travel times

In the stochastic variant of the vehicle routing problem with time windows, known as the SVRPTW, travel times are assumed to be stochastic. In our chance-constrained approach to the problem, restrictions are placed on the probability that individual time window constraints are violated, while the objective remains based on traditional routing costs. In this paper, we propose a way to offer this probability, or service level, for all customers. Our approach carefully considers how to compute the start-service time and arrival time distributions for each customer. These distributions are used to create a feasibility check that can be “plugged” into any algorithm for the VRPTW and thus be used to solve large problems fairly quickly. Our computational experiments show how the solutions change for some well-known data sets across different levels of customer service, two travel time distributions, and several parameter settings.     

Evolution of bank efficiency in Brazil: A DEA approach

This paper investigates cost, technical and allocative efficiencies for Brazilian banks in the recent period (2000–2007). We use Data Envelopment Analysis (DEA) to compute efficiency scores. Brazilian banks were found to have low levels of economic (cost) efficiency compared to banks in Europe and in the US. For the period with high macroeconomic volatility (2000–2002) the economic inefficiency in Brazilian banks can be attributed mainly to technical inefficiency rather than allocative inefficiency. State-owned banks are significantly more cost efficient than foreign, private domestic and private with foreign participation. There is no evidence of differences in economic efficiency due to type of activity and bank size. These results may provide some useful guidance for financial regulators and bank managers.     

Determinants of bank efficiency: The case of Brazil

This paper analyzes the efficiency of the Brazilian banking sector over the post-privatization period of 2000–2007. We employ a Bayesian stochastic frontier approach, which provides exact efficiency estimates and confidence intervals and thus, allows an accurate comparison across institutions and bank groups. The results suggest that large banks are the most cost and profit efficient, supporting the concentration process observed in recent years. Foreign banks have achieved a good performance through either the establishment of new affiliates and the acquisition of local banks. The remaining public banks have had improvements in cost efficiency, but are relatively profit inefficient. Finally, we observe a positive impact of capitalization on efficiency.     

An Interactive Dynamic Inventory-Production Control System

The development and evaluation of an interactive model for controlling inventories and scheduling production in a high technology batch production environment are discussed. The model allows the use of expert knowledge and company policy for matters such as customer service and safety stocks, in an interactive way. Production of a large number of products has to be scheduled for a number of time periods and a modified Wagner-Whitin algorithm is used for developing good schedules. A versatile data and information management system is a part of the developed software which has been implemented using a standard microcomputer. An evaluation suggests that the system is a practical one for use by busy managers. Further, it results in substantial cost savings and increased customer service.     

An interval portfolio selection problem based on regret function

Recent mergers in the banking industry have often generated disappointing shareholder returns. Delays in implementing potential operating savings and realizing benefits of scale economies may be one reason these mergers have disappointing returns. Using data envelopment analysis (DEA), we analyze a 200-branch network formed in a merger of four banks. The operating efficiency of each branch is benchmarked against “best-practice” branches in the combined merged bank as well as “best practice” branches within each pre-merger bank. This analysis identified opportunities to reduce branch operating costs by 22 percent for the entire merged bank. In contrast, the cost savings opportunity is under seven percent when analyzed within each pre-merger bank.These findings suggest benchmarking across the entire merged bank to identify the best practices bank-wide can generate added savings. However, in this bank merger, these merger benefits were not realized until four years after the merger. Interviews with key players in the merged bank indicate that the bank deferred realizing these benefits because of political pressures, personnel integration issues, system integration issues, and financial components of the merger such as restructuring reserves and the purchase price. These causes suggest areas where shareholders can and should demand more rapid improvement in performance of bank mergers and areas for future corporate merger research.     

Telecom service provider portal: Revenue sharing and outsourcing

Early mobile phones only provided voice transmission, for a fee. They have now evolved into voice and online data portals for providing additional services through 3rd party vendors. These service providers (vendors) are given access to a customer base “owned” by the mobile phone companies, for a fee. Typically customers make two payments: to the mobile phone company for phone services and to the 3rd party vendors for specific services bought from them. Variations to the above business model may involve outsourcing the online portal and/or acquiring customers from other independent portals. For these scenarios, we study how the fees for phone service and customer access are established and how they may relate to the prices of vendor services, and which services should be located on the portal - all in a game-theoretic context. Our results prove that it is possible to reorganize revenue flows through an invoicing process that may benefit the mobile network operator more than the other parties. In addition, we establish optimality in terms of the number of vendors on the portal, and determine a rank-ordering of vendors for their inclusion into the portal.     

Applications of bulk queues to group testing models with incomplete identification

A population of items is said to be “group-testable”, (i) if the items can be classified as “good” and “bad”, and (ii) if it is possible to carry out a simultaneous test on a batch of items with two possible outcomes: “Success” (indicating that all items in the batch are good) or “failure” (indicating a contaminated batch). In this paper, we assume that the items to be tested arrive at the group-testing centre according to a Poisson process and are served (i.e., group-tested) in batches by one server. The service time distribution is general but it depends on the batch size being tested. These assumptions give rise to the bulk queueing model M/G^(m,M)/1, where m and M(>m) are the decision variables where each batch size can be between m and M. We develop the generating function for the steady-state probabilities of the embedded Markov chain. We then consider a more realistic finite state version of the problem where the testing centre has a finite capacity and present an expected profit objective function. We compute the optimal values of the decision variables (m, M) that maximize the expected profit. For a special case of the problem, we determine the optimal decision explicitly in terms of the Lambert function.