Making the issue more complex, most service companies' problems are related to the uncertainty of the service demand. Sherman points out that the greatest resistance to change is the result of past successes: being comfortable with the status quo. Consequently, this book presents the business analytics needed to make strategic decisions in service industries. However, the authors could have been more explicit about which tab within an example is being referenced at a particular time. Lin Improving Pharmacy Operations Using Computer Simulation, Alberto Isla, Alex C. In addition, we include books in other fields that emphasize technical applications.
Is the targeted reader a professional in the management sciences who wants to learn more about supply chain optimization? Under such uncertain conditions, the development and use of robust and flexible strategies, algorithms, and methods can provide the quantitative information necessary to make better business decisions. The other chapters cover applications such as information technology services delivery, random supply disruptions, quality and service systems design, cost-effective home delivery of prescriptions, improving room turnaround time at a regional hospital, logistics outsourcing from the standpoint of hiring companies, revenue management of transportation infrastructure, inventory classification method for nuclear spare parts, and banking competition. Chapter 3 elaborates more on the market drivers and the dynamics of change. Under such uncertain conditions, the development and use of robust and flexible strategies, algorithms, and methods can provide the quantitative information necessary to make better business decisions. The uniqueness of this book lies in the linkage between service industries and quantitative decision support techniques.
David Kelton Patient Prioritization in Emergency Departments: Decision Making under Uncertainty, Omar M. Liaquat, Pragalbh Srivastava, and Lian Qi Customer Perceptions of Quality and Service System Design, George N. Most people in supply chain management do not know why to change or why to improve the performance of or transform the organization. The following books are reviewed in this issue of Interfaces, 44 3 , May—June 2014: Handbook of Global Logistics: Transportation in International Supply Chains, James H. Scala, Jayant Rajgopal, and Kim LaScola Needy Service Technology, Pricing, and Process Economics in Banking Competition, David Y. The utility plot for age is nonlinear. When applied to a real case, this study leads to offering cabotage rates at competitive freight rates, while being environmentally friendly.
Pages 272—274 discuss setting up a modeling group within a firm. Scala, Jayant Rajgopal, and Kim LaScola Needy Service Technology, Pricing, and Process Economics in Banking Competition, David Y. Data Mining and Quality in Service Industry: Review and some applications. If you are aware of a specific book that you would like to review, or that you think should be reviewed, please contact the editor. Squillante Simulation-Based Studies on Dynamic Sourcing of Customers under Random Supply Disruptions, Sanad H.
They also enumerate five differences between data mining and statistics; in my opinion, the most important of these is that statistics is a process of analyzing relationships, while data mining is a process of discovering relationships. Generally speaking, decision making is a hard task in business fields. It examines current and future trends regarding how these decision-making processes can be efficiently performed for better design of service systems by using probabilistic algorithms as well as hybrid and simulation-based approaches. Level 1 and 2 patients receive immediate evaluation and treatment, whereas patients at levels 3, 4, and 5 can be sent to a waiting area after registration. Although I enjoyed reading this book, I found that some parts of it were not directly related; some readers may not consider this to be a problem. Chapter 6 deals with the integration of international and domestic cargos i.
This book has an engaging subtitle. However, these vast amounts of data are meaningless unless they are coupled with sophisticated data mining techniques that can make sense of the data and extract meaningful knowledge out of it. It is easy to navigate to find the examples discussed within the chapters. The last few decades have been witness to great technological advances in our capacity to extract data out of living matter. The editor will be pleased to receive an email from those willing to review a book, with an indication of specific areas of interest. If you think the reason is size, cost, or investment e. It provides studies that demonstrate the suitability of quantitative methods to make the right decisions.
Part V covers transportation modes and their land interfaces. As I read this book, I wondered about its target readership. In China, more than 75 percent of freight is transported by road, 11 percent each by rail and water, and a small fraction by air. Under such uncertain conditions, the development and use of robust and flexible strategies, algorithms, and methods can provide the quantitative information necessary to make better business decisions. What I like most about his book is his enthusiasm for the topic of supply chain management and that he changes the how-to question to the why-to question. Such a professional, however, might also be advised to read Chapters 8 and 9 of , Chapter 12 of , or Chapter 5 of. Okudan Kremer Using Process Mapping and Capability Analysis to Improve Room Turnaround Time at a Regional Hospital, John F.
In Data Mining and Quality in Service Industry: Review and Some Applications Section 1, Chapter 4 by Teresa Oliveria, Amilcar Oliveria, and Alejandra Perez-Bonilla, the authors identify the seven steps in data mining: data cleansing, data integration, data selection, data transformation, prospecting, data evaluation or postprocessing, and results display. The article is quite technical and requires some background knowledge in data mining. The book provides insight and understanding into practical and methodological issues related to decision-making processes under uncertainty in service industries. Chapter 7 is an interesting chapter because it gives readers, especially supply chain technicians, some insight into how boardrooms work and how board members think. Its 16 chapters, written by authors who have a wealth of experience in their topics, are grouped into four sections: 1 Services and Decision Making, 2 Decision Making in Health Services, 3 Decision Making in Logistics Services, and 4 Decision Making in Other Service Areas. Sherman has an impressive career in supply chain management across many industries and boards, and as a presenter on the topic of supply chain transformation.
This chapter, which also includes a prescriptive model dealing with risk management, is more technical than Chapter 2. As such, the work cells could require the student to draw on additional knowledge to solve more difficult problems rather than ones whose solutions seem a bit obvious. In this review, I have chosen to highlight only three chapters. It provides studies that demonstrate the suitability of quantitative methods to make the right decisions. Why do best-in-class companies, in virtually any industry, outperform their median competitors by a total supply chain cost advantage of 50 percent or more? This book sheds light on these types of decision problems.
To excel in fully mastering change, one must excel in mastering the whole. Decision Making in Service Industries: A Practical Approach. This book explores how to use these tools for making decisions inside service industries. Three chapters address attacker-defender topics, where security forces confront elusive and strategic adversaries. Chapter 20 concentrates on proactive order consolidation as an innovative research avenue that aims to consolidate the orders before they are communicated to suppliers by incorporating inventory management techniques.