A Note on the Growth of Research in Service Operations Management

PRODUCTION AND OPERATIONS MANAGEMENT Vol. 16, No. 6, November-December 2007, pp. 780 –790 issn 1059-1478 07 1606 780$1. 25 POMS doi 10. 3401/poms.  © 2007 Production and Operations Management Society A Note on the Growth of Research in Service Operations Management Jeffery S. Smith †¢ Kirk R. Karwan †¢ Robert E. MarklandDepartment of Marketing, Florida State University, Rovetta Business Building, Tallahassee, Florida 32306, USA Department of Business and Accounting, Furman University, 3300 Poinsett Highway, Greenville, South Carolina 29613, USA Management Science Department, Moore School of Business, University of South Carolina, 1705 College Street, Columbia, South Carolina 29208, USA [email  protected] fsu. edu †¢kirk. [email  protected] edu †¢[email  protected] sc. edu e present an empirical assessment of the productivity of individuals and institutions in terms of service operations management (SOM) research.We reviewed ? ve mainstream operation s management journals over a 17-year time period to generate a sample of 463 articles related to service operations. The results indicate that SOM research has been growing and key contributions are being made by an array of researchers and institutions. Key words: research productivity; research review; service operations Submissions and Acceptance: Original submission: Received November 2005; revisions received July 2006 and October 2007; accepted October 2007 by Aleda Roth. W 1. IntroductionThe transformation of industrialized economies from a manufacturing base to a service orientation is a continuing phenomenon. The trend is readily apparent in the United States where, by virtually all accounts, over 80% of private sector employment is engaged in some sort of service work (Karmarkar, 2004). Despite this, observers of research in operations management (OM) have long been critical of the ? eld for not transitioning in a similar manner. One study by Pannirselvam et al. (1999) revi ewed 1,754 articles between 1992 and 1997 in seven key OM journals and reported only 53 (2. 7%) addressed service-related problems.Roth and Menor (2003) also voiced concern about a paucity of research in presenting a Service Operations Management (SOM) research agenda for the future. Regardless of the exact ? gures, there is clearly enormous potential and need for research in the service operations arena. Recent developments within the discipline are encouraging. For example, Production and Operations Management (POM) and the Production and Operations Management Society (POMS) have taken several steps to facilitate research in service operations. First, the journal recently published three focused issues on 780 service operations.Second, POMS created a society subdivision, the College of Service Operations, that has hosted several national and international meetings. Finally, the journal now has an autonomous editorial department dedicated to service operations. Other initiatives to promote the service operations management ? eld include the establishment of IBM’s Service Science, Management, and Engineering initiative (Spohrer et al. , 2007) and the Institute for Operations Research and Management Science Section on Service Science. To a large extent, the service operations ? eld has long been considered to occupy a niche within operations management.If service operations management researchers are to establish themselves ? rmly within the OM community, it is our contention that their theoretical contributions to leading academic journals must be more widely recognized and their relevance to practice acknowledged. As a part of the effort to encourage this progress, the purpose of this note is twofold: (1) to demonstrate that published work in the key operations journals is indeed showing an upward trend and (2) to facilitate research of individual scholars by identifying the individuals and institutions that have contributed most to the ? ld of service operations. Smith, Karwan, and Markland: Growth of Research in Service Operations Management Production and Operations Management 16(6), pp. 780 –790,  © 2007 Production and Operations Management Society 781 2. Methodology and Results Although much more complex mechanisms exist to measure â€Å"contribution,† we relied on a straightforward approach to assess contributions by individuals and institutions. We considered four issues: (1) the time frame for the review, (2) the journals to be included, (3) the metric for productivity, and (4) the means to identify the articles to be included.First, we selected a 17-year time frame beginning with 1990 and running through 2006 because we believed that this interval would provide a comprehensive picture of the service operations ? eld as it has developed, as well as an opportunity to detect any overall trends. Next, we limited our assessment to the outlets identi? ed by the University of Texas at Dallas as the premier journ als in operations management (see http://citm. utdallas. edu/ utdrankings/).These include 3 journals dedicated to OM, the Journal of Operations Management (JOM), Manufacturing and Service Operations Management (MSOM), and POM, and two multidisciplinary journals, Management Science (MS) and Operations Research (OR). Third, we assessed scholarly productivity by counting the number of research articles attributable to both individuals and their academic institutions, assigning a weight of 1/n to an author and his or her institution if an article had multiple (â€Å"n†) authors. The ? al issue to determine was what constituted a SOM article. We ? rst eliminated any article or research note that centered on agriculture, mining, or manufacturing. Then, two authors served as independent judges to determine whether an article employed an operations focus while addressing a service-speci? c problem or situation. In cases where there was disTable 1 Year 1990 1991 1992 1993 1994 1995 19 96 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Totals Service % agreement between the two raters, the third author made the ? al decision. Consequently, an article was excluded if it developed a generic operations model or involved an operations topic that was discussed in a general way and was applicable in either a manufacturing or a service environment. When an article made speci? c reference to service contexts and elaborated on them, it was included. To clarify this point, consider the case of an article investigating an inventory-positioning policy between a manufacturer and a series of retailers.The article would be included as pertaining to service operations if it took the perspective of the retail operation but would be excluded if it took the manufacturing viewpoint. Using this methodology, we identi? ed 463 distinct service operations articles (see the Appendix for a complete list) and recorded information on the author(s) and author af? liation(s) at the time of p ublication. The numerical summary of articles is shown in Table 1, with each journal’s share of service operations articles.Over the 17-year period JOM, MSOM, and POM all exceeded 15% of service articles with respect to the total number of articles published, with OR and MS publishing somewhat smaller percentages. Additionally, there is an upward trend in the total number of service articles appearing in all ? ve journals, with a marked increase in the past 3 years (see Figure 1). With regard to JOM and POM, part of this move is attributable to the publication of special issues, which is a positive development because it demonstrates a heightened emphasis originating at the editorial level.The total number of individuals appearing in the sample pool was 799. In Table 2, we list 27 individuals Distribution of Service Operations Publications by Selected Journal and Year JOM 4 1 n/a 2 1 4 3 1 3 3 6 5 8 3 7 11 13 75 15. 4 MS 3 9 5 4 5 12 4 8 11 15 5 7 3 4 11 16 13 135 6. 5 MSOM n /a n/a n/a n/a n/a n/a n/a n/a n/a 0 3 5 3 1 5 5 6 28 16. 8 OR 10 5 10 12 6 8 6 7 10 5 9 5 8 6 11 16 16 150 10. 1 POM n/a n/a 3 1 2 3 3 2 3 11 2 4 4 14 11 3 9 75 17. 9 Total 17 15 18 19 14 27 16 18 27 34 25 26 26 28 45 51 57 463 Service % 7. 0 6. 7 6. 6 7. 8 5. 9 8. 9 6. 3 7. 0 9. 2 12. 5 9. 0 9. 2 8. 8 10. 7 15. 17. 2 17. 2 10. 0 Note. n/a (not applicable) indicates that no issue was published in the speci? c journal in the target year; totals indicate the sum of all service operations articles in the noted year/journal; service % indicates the representation of service articles in comparison to the total number of articles published. 782 Figure 1 Smith, Karwan, and Markland: Growth of Research in Service Operations Management Production and Operations Management 16(6), pp. 780 –790,  © 2007 Production and Operations Management Society Distribution of Service Articles over the Investigation Period 70Number of Service Articles 60 50 40 30 20 10 2001 2004 1990 1993 1995 1998 2000 2002 2003 1994 1999 1991 1992 1996 1997 Year who contributed the most articles on SOM in the ? ve journals. We conducted the same analysis by institution, and it resulted in 343 organizations appearing in the sample. Columbia University contributed the most articles, with a score of 16. 17. Massachusetts Institute of Technology, the University of Minnesota, and the University of Pennsylvania followed with productivity scores greater than 12. Table 3 lists the remainder of the 26 most productive institutions.Although clearly dependent upon the journals within the sample, an important conclusion that might Table 2 Name Ward Whitt Gary Thompson Stefanos Zenios Scott Sampson Richard Chase Arnold Barnett Kenneth Boyer Arthur Hill Aleda Roth Robert Shumsky Dimitris Bertsimas Susan Meyer Goldstein Julie Hays Ananth Iyer Andreas Soteriou Cynthia Barnhart Vishal Gaur Deborah Kellogg Larry Jacobs Marshall Fisher Francois Soumis William L Cooper Jean Harvey Serguei Netessine Gerard Cacho n Kingshuk Sinha Avishai Mandelbaum Individual Author Contributions Productivity score 8. 0 5. 50 3. 33 3. 33 3. 17 2. 90 2. 67 2. 67 2. 67 2. 53 2. 50 2. 50 2. 50 2. 50 2. 50 2. 42 2. 33 2. 25 2. 20 2. 17 2. 03 2. 00 2. 00 2. 00 1. 83 1. 83 1. 83 be drawn from Tables 2 and 3 is that the key contributions in SOM research are diverse and originate from a broad array of authors and institutions. Many of these authors and institutions are known to approach the ? eld from normative or prescriptive perspectives and others from more empirical or descriptive perspectives.In fact, Gupta, Verma, and Victorino (2006) recently noted that much of the growth in service research has come from studies that completely or partially employed empirical research methodologies. This increased emphasis on empirical studies bodes well for the â€Å"new† and growing ? eld. Table 3 Institution Institutional Contributions Productivity score 16. 17 16. 05 13. 41 12. 17 8. 75 8. 15 6. 75 6. 67 6. 67 6. 17 5. 77 5. 67 5. 67 5. 58 5. 50 5. 42 4. 95 4. 87 4. 75 4. 70 4. 50 4. 50 4. 42 4. 33 4. 33 4. 08Columbia University Massachusetts Institute of Technology University of Minnesota University of Pennsylvania University of Southern California Michigan State University University of Texas at Austin Stanford University Purdue University Cornell University Carnegie Mellon University University of North Carolina at Chapel Hill Georgia Institute of Technology University of Utah New York University Harvard University Northern Illinois University University of Rochester Southern Methodist University Naval Postgraduate School AT&T University of Cyprus University of California at Los Angeles University of Maryland Vanderbilt University University of Michigan 2006 2005Smith, Karwan, and Markland: Growth of Research in Service Operations Management Production and Operations Management 16(6), pp. 780 –790,  © 2007 Production and Operations Management Society 783 3. Concluding Comments â € ¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ A variety of forces appear to be stimulating a longexpected increase in research emphasis on service operations management. Because service organizations and issues increasingly dominate the global economy, a greater emphasis on SOM research seems important and inevitable. With operations management journals and related professional societies simultaneously providing visibility for researchers and their efforts, it is likely that we will move forward toward a clearer and more robust SOM research paradigm.Acknowledgments We thank the anonymous reviewers and the editorial team for their insightful comments on earlier drafts of this paper. †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ Appendix Journal of Operations Management †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ Davis, 1990, An analysis of customer satisfaction with waiting times in a two-stage service process. 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Jack, 1992, Design and implementation of an interactive optimization system f or telephone network planning. Klimberg, 1992, Improving the effectiveness of FDA drug inspection. Ng, 1992, A multicriteria optimization approach to aircraft loading. Oren, 1992, Design and management of curtailable electricity service to reduce annual peaks. Stroup, 1992, A fuel management model for the airline industry. Weatherford, 1992, A taxonomy and research overview of perishable-asset revenue management. Wollmer, 1992, An airline seat anagement model for a single leg routine when lower fare classes book ? rst. Ball, 1993, A reliability model applied to emergency service vehicle location. Berge, 1993, Demand driven dispatch. Bradley, 1993, Measuring performance in a multiproduct ? rm. Brumelle, 1993, Airline seat allocation with multiple nested fare classes. Caulkins, 1993, Local drug markets’ response to focused police enforcement. Caulkins, 1993, The on-time machines. Fleurent, 1993, Allocating games for the NHL using integer programming. Franz, 1993, Scheduling med ical residents to rotations. Martin, 1993, Design and implementation of an expert system for controlling health care costs.Rautman, 1993, Scheduling the disposal of nuclear waster material in a geologic repository using the transportation model. Soumis, 1993, A stochastic, multiclass airline network equilibrium model. Terrab, 1993, Strategic ? ow management for air traf? c control. Blanco, 1994, A sea story. Reisman, 1994, Operations research in libraries. Ringel, 1994, A stochastic analysis of state transitions in an air-space management system. Russell, 1994, Devising a cost effective schedule for a baseball league. Vranas, 1994, The multi-airport ground-holding problem in air traf? c control. Weintraub, 1994, A heuristic system to solve mixed integer forest planning models.Barnhart, 1995, Deadhead selection for the long-haul crew pairing problem. †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ Bitran, 1995, An application of yield management to the hotel industry considering multiple day stays. Brusco, 1995, Improving personnel scheduling at airline stations. Kaplan, 1995, Probability models of needle exchange. Keeney, 1995, Evaluating improvements in electric utility reliability at British Columbia hydro. Peterson, 1995, Decomposition algorithms for analyzing transient phenomena in multiclass queuing networks in air transportation. Richetta, 1995, Optimal algorithms and a remarkably ef? cient heuristic for the ground-holding problem in air traf? c control.Robinson, 1995, Optimal and approximate control policies for airline booking with sequential nonmonotonic fare classes. Barnhart, 1996, Air network design for express shipment service. Bitran, 1996, Managing hotel reservations with uncertain arrivals. Eisenstein, 1996, Separating logistics ? ows in th e Chicago public school system. Maclellan, 1996, Basing airtankers for forest ? re control in Ontario. Rosenthal, 1996, Optimizing ? ight operations for an aircraft carrier in transit. Thompson, 1996, DEA/assurance region SBDC ef? ciency and unique projections. Ahmadi, 1997, Managing capacity and ? ow at theme parks. Bevers, 1997, Spatial optimization of prairie dog colonies for black-footed ferret recovery.Bukiet, 1997, A Markov chain approach to baseball. Day, 1997, Flight attendant rostering for short-haul airline operations. Eppen, 1997, Improved fashion buying with Bayesian updates. Griggs, 1997, An air mission planning algorithm using decision analysis and mixed integer programming. Vance, 1997, Airline crew scheduling. Andreatta, 1998, Multiairport ground holding problem. Bertsimas, 1998, The air traf? c ? ow management problem with enroute capacities. Bixby, 1998, Solving a truck dispatching scheduling problem using branch-and-cut. Caprara, 1998, Modeling and solving the cre w rostering problem. Chatwin, 1998, Multiperiod airline overbooking with a single fare class.Gopalan, 1998, The aircraft maintenance routing problem. Lederer, 1998, Airline network design. Mason, 1998, Integrated simulation, heuristic and optimisation approaches to staff scheduling. Nemhauser, 1998, Scheduling a major college basketball conference. Savelsbergh, 1998, Drive: Dynamic routing of independent vehicles. Gamachea, 1999, A column generation approach for largescale aircrew rostering problems. Hobbs, 1999, Stochastic programming-based bounding of 788 Smith, Karwan, and Markland: Growth of Research in Service Operations Management Production and Operations Management 16(6), pp. 780 –790,  © 2007 Production and Operations Management Society †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ expected production costs for multiarea electric power systems. Keeney, 1999, Identifying and structuring values to guide integrated resource planning at BC Gas. Mingozzi, 1999, A set partitioning approach to the crew scheduling problem. Murty, 1999, The U. S. Army National Guard’s mobile training simulators location and routing problem. Barnett, 2000, Free-? ight and en route air safety. Barnhart, 2000, Railroad blocking. Bashyam, 2000, Service design and price competition in business information services. Feng, 2000, Optimal policies of yield management with multiple predetermined prices.Haight, 2000, An integer optimization approach to a probabilistic reserve site selection problem. Hoffman, 2000, A comparison of formulations for the single-airport ground-holding problem with banking constraints. Smith, 2000, Management of multi-item retail inventory systems with demand substitu tion. Van Slyke, 2000, Finite horizon stochastic knapsacks with applications to yield management. Zenios, 2000, Dynamic allocation of kidneys to candidates on the transplant waiting list. Barnett, 2001, Safe at home? Cai, 2001, Solving large nonconvex water resources management models using generalized benders decomposition. Cordeau, 2001, Simultaneous assignment of locomotives and cars to passenger trains.Feng, 2001, A dynamic airline seat inventory control model and its optimal policy. Henz, 2001, Scheduling a major college basketball conference—Revisited. Baker, 2002, Optimizing military aircraft. Camm, 2002, Nature reserve site selection to maximize expected species covered. Caprara, 2002, Modeling and solving the train timetabling problem. Cooper, 2002, Asymptotic behavior of an allocation policy for revenue management. Cooper, 2002, An illustrative application of IDEA (imprecise data envelopment analysis) to a Korean telecommunication company. Gans, 2002, Managing learn ing and turnover in employee staf? ng. Netessine, 2002, Flexible service capacity. Powell, 2002, Implementing real-time optimization models.Bertsimas, 2003, Restaurant revenue management. Brumelle, 2003, Dynamic airline revenue management with multiple semi-Markov demand. Cohn, 2003, Improving crew scheduling by incorporating key maintenance routing decisions. Deshpande, 2003, An empirical study of service differentiation from weapon system service parts. Erhun, 2003, Enterprise-wide optimization of total landed cost at a grocery retailer. Rajaram, 2003, Flow management to optimize retail pro? ts at theme parks. †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ Armony, 2004, Contact centers with a call-back option and real-time delay information. Armony, 2004, On customer contact centers with a callback option.Bollapragada, 2004, Scheduling commercials on broadcast t elevision. Bollapragada, 2004, Scheduling commercial videotapes in broadcast television. Borst, 2004, Dimensioning large call centers. Cappanera, 2004, A multicommodity ? ow approach to the crew rostering problem. Gaur, 2004, A periodic inventory routing problem at a supermarket chain. Hamacher, 2004, Design of zone tariff systems in public transportation. Karaesmen, 2004, Overbooking with substitutable inventory classes. Qi, 2004, Class scheduling for pilot training. Zhu, 2004, Imprecise DEA via standard linear DEA models with a revisit to Korean mobile telecommunication company. Armstrong, 2005, A stochastic salvo model for naval surface combat.Ata, 2005, Dynamic power control in a wireless static channel subject to a quality-of-service constraint. Bertsimas, 2005, Simulation based booking limits for airline revenue management. Brown, 2005, A two-sided optimization for theater ballistic missile defense. Chardaire, 2005, Solving a time-space network formulation for the convoy movem ent problem. Dasci, 2005, A continuous model for multistore competitive location. De Vericourt, 2005, Managing response time in a callrouting problem with service failure. Holder, 2005, Navy personnel planning and the optimal partition. Jahn, 2005, System-optimal routing of traf? c ? ows with user constraints in networks with congestion. Maglaras, 2005, Pricing and design of differentiated services.Savin, 2005, Capacity management in rental businesses with two customer bases. Shu, 2005, Stochastic transportation-inventory network design problem. Su, 2005, Patient choice in kidney allocation. Wu, 2005, Optimization of in? uenza vaccine selection. Yang, 2005, A multiperiod dynamic model of taxi services with endogenous service intensity. Zhang, 2005, Revenue management for parallel ? ights with customer-choice behavior. Agur, 2006, Optimizing chemotherapy scheduling using local search heuristics. Bassamboo, 2006, Design and control of a large call center. Cook, 2006, Incorporating mul tiprocess performance standards into the DEA framework. Cordeau, 2006, A branch-and-cut algorithm for the diala-ride problem.Dawande, 2006, Effective heuristics for multiproduct partial shipment models. Smith, Karwan, and Markland: Growth of Research in Service Operations Management Production and Operations Management 16(6), pp. 780 –790,  © 2007 Production and Operations Management Society †¢ 789 †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ Deshpande, 2006, Ef? cient supply chain management at the U. S. Coast Guard using part-age dependent supply replenishment policies. Fry, 2006, Fire? ghter staf? ng including temporary absences and wastage. Ghiani, 2006, The black and white traveling salesman problem. Green, 2006, Managing patient service in a diagnostic medical facility. Mannino, 2006, The network packing problem in terrestrial broadcasting.Marcus, 2006, Online low price guarantees. Marklund, 2006, Controlling inventories in dive rgent supply chains with advance-order information. Netessine, 2006, Revenue management through dynamic cross selling in e-commerce retailing. Perakis, 2006, An analytical model for traf? c delays and the dynamic user equilibrium problem. Romeijn, 2006, A new linear programming approach to radiation therapy treatment planning problems. Washburn, 2006, Piled-slab searches. †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ Production and Operations Management †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ Easton, 1992, Analysis of alternative scheduling policies for hospital nurses.Ernst, 1992, Coordination alternatives in a manufacturing/dealer inventory system under stochastic demand. Schneeweiss, 1992, Planning and scheduling the repair shops of the Deutsche Lufthansa AG. Rajago palan, 1993, Allocating and scheduling mobile diagnostic imaging equipment among hospitals. Malhotra, 1994, Scheduling ? exibility in the service sector. Sainfort, 1994, A pavement management decision support system. Cox, 1995, A new learning approach to process improvement in a telecommunications company. Roth, 1995, Hospital resource planning. Schneider, 1995, Power approximations for a two-echelon inventory system using service levels. Chase, 1996, The mall is my factory.Crandall, 1996, Demand management. Joglekar, 1996, A pro? t maximization model for a retailer’s stocking decisions on products subject to sudden obsolescence. Cachon, 1996, Campbell soup’s continuous replenishment program. Clark, 1997, Reengineering channel reordering processes to improve total supply-chain performance. Harvey, 1998, Building the service operations course around a ? eld project. Kolesar, 1998, Insights on service system design from a normal approximation to Erlang’s delay for mula. Lee, 1998, Effects of integrating order/backorder quantity and pricing decisions. Boronico, 1999, Reliability-constrained pricing, capacity, and quality.Cheng, 1999, Optimality of state dependent (s,S) policies in inventory models with Markov demand and lost sales. Cook, 1999, Service typologies. Dasu, 1999, A dynamic process model of dissatisfaction for unfavorable non-routine service encounters. †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ Dube, 1999, Adapting the QFD approach to extended service transactions. Hays, 1999, The market share impact of service failures. Kapalka, 1999, Retail inventory control with lost sales, service constraints, and factional lead times. Metters, 1999, Measurement of multiple sites in service ? rms with data envelopment analysis. Nie, 1999, How professors of operations management view service operations.Soteriou, 1999, Resource allocation to impro ve service quality perceptions in multistage service systems. Stewart, 1999, The impact of human error on delivering service quality. Anderson, 2000, A simulation game for teaching servicesoriented supply chain management. Petersen, 2000, An evaluation of order picking policies for mail order companies. Chaouch, 2001, Stock levels and delivery rates in vendormanaged inventory programs. Devaraj, 2001, Product and service quality. Hays, 2001, A longitudinal study of the effect of a service guarantee on service quality. Van Woensel, 2001, Managing the environmental externalities of traf? c logistics. Agrawal, 2002, Multi-vendor sourcing in a retail supply chain.Boyer, 2002, Drivers of Internet purchasing success. Heim, 2002, Service process con? gurations in electronic retailing. Tagaras, 2002, Effectiveness of stock transshipment under various demand distributions and nonnegligible transshipment times. Akkermans, 2003, Ampli? cation in service supply chains. Alfaro, 2003, The value of sku rationalization in practice. Athanassopoulos, 2003, Modeling customer satisfaction in telecommunications. Baker, 2003, The bene? ts of optimizing prices to manage demand in hotel revenue management systems. Cayirli, 2003, Outpatient scheduling in health care. Giloni, 2003, Service system design for the property and casualty insurance industry.Goodale, 2003, A market utility-based model for capacity scheduling in mass services. Green, 2003, An improved heuristic for staf? ng telephone call centers with limited operating hours. Kassinis, 2003, Greening the service pro? t chain. Keizers, 2003, Diagnosing order planning performance at a Navy maintenance and repair organization using logistic regression. Meyer-Goldstein, 2003, Employee development. Mondschein, 2003, Appointment policies in service operations. Roth, 2003, Insights into service operations management. Stewart, 2003, Piecing together service quality. Boyaci, 2004, Supply chain coordination in a market with customer serv ice competition.Craighead, 2004, The effects of severity of failure and customer loyalty on service recovery strategies. Field, 2004, Managing quality in the e-service system. Gavish, 2004, Dynamic policies for optimal LEO satellite launches. 790 †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ Smith, Karwan, and Markland: Growth of Research in Service Operations Management Production and Operations Management 16(6), pp. 780 –790,  © 2007 Production and Operations Management Society †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ Hur, 2004, Real-time work schedule adjustment decisions. Jack, 2004, Volume ? exible strategies in health services. Lapre, 2004, Performance improvement paths in the U. S. airline industry. Napoleon, 2004, The creation of output and quality in services.Sampson, 2004, Practical implications of preference-based conference scheduling. Tsay, 2004, Channel con? ict and coordination in the ecommerce age. Tsikriktsis, 2004, Adoption of e-processes by service ? rms. Chakravarthy, 2005, Optimal workforce mix in service systems with two types of customers. Gaur, 2005, In-store experiments to determine the impact of price on sales. Miller, 2005, A learning real options framework with application to process design and capacity planning. Anderson, 2006, Stochastic optimal control for staf? ng and backlog policies in a two-stage customized service supply chain. Berling, 2006, Heuristic coordination of decentralized inventory systems using induced backorder costs.Boyer, 2006, Analysis of effects of operational execution on repeat purchasing heterogeneous customer segments. Chambers, 2006, Modeling and managing the percentage of satis? ed customers in hidden and revealed waiting line systems. Ferguson, 2006, Information sharing to improve retail product freshness of perishables. Hays, 2006, An extended longitudinal study of the effects of a service guarantee. Rajamani, 2006, A framework to analyze cash supply chains. Sampson, 2006, Foundations and implications of a proposed uni? ed services theory. Whitt, 2006, Staf? ng a call center with uncertain arrival rate and absenteeism. References Gupta, S. , R. Verma, L. Victorino. 2006.Empirical research published in Production and Operations Management (1992–2005): Trends and Future Research Directions. Production and Operations Management 15(3) 432– 448. Karmarkar, U. 2004. 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