A method to evaluate service delivery process quality

Purpose – The purpose of this paper is to develop a method to evaluate the quality of service delivery process designs, based on how closely they meet process requirements of key stakeholders while taking variability into account.Design/methodology/approach – A Monte Carlo computer simulation of the flowchart of the service delivery process is used to capture the effects of multiple types of variabilities and parametric uncertainties on process variables of interest, and the Taguchi quality loss framework is applied to estimate overall process quality. As an example, a proposed modification to a patient‐treatment process in a hospital emergency department is evaluated.Findings – This paper demonstrated a method that service managers can use to evaluate the quality of service delivery process designs.Practical implications – This method can evaluate modifications to various aspects of a service delivery process, and can assist managers to fail‐safe the entire process. Furthermore, it characterises process ...

[1]  Joseph T. Mahoney,et al.  The resource-based view within the conversation of strategic management , 1992 .

[2]  M. Aral,et al.  Probabilistic-fuzzy health risk modeling , 2004 .

[3]  J. Stuart Hunter,et al.  Statistical Design Applied to Product Design , 1985 .

[4]  Madeleine E. Pullman,et al.  Optimizing Service Attributes: The Seller's Utility Problem , 2001, Decis. Sci..

[5]  Mary Frances Luce,et al.  Attribute Conflict and Preference Uncertainty: The RandMAU Model , 2000 .

[6]  John H. Sheesley,et al.  Quality Engineering in Production Systems , 1988 .

[7]  William E. Youngdahl,et al.  “Lean” service: in defense of a production‐line approach , 1998 .

[8]  C. Wise,et al.  The logic of transaction cost economics in health care organization theory. , 2001, Health care management review.

[9]  E. Anderson,et al.  The Antecedents and Consequences of Customer Satisfaction for Firms , 1993 .

[10]  Gary M. Thompson,et al.  Strategies for Integrating Capacity With Demand in Service Networks , 2003 .

[11]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[12]  B. Edvardsson,et al.  Key Concepts for New Service Development , 1996 .

[13]  J. Baron,et al.  Investigating the effect of stimulus range on attribute weight. , 1991, Journal of experimental psychology. Human perception and performance.

[14]  Abbie Griffin,et al.  The Voice of the Customer , 1993 .

[15]  Takao Enkawa,et al.  Variability and quality loss in services: concepts and countermeasures , 1992 .

[16]  J. Hornik.  Subjective vs. Objective Time Measures: A Note on the Perception of Time in Consumer Behavior , 1984 .

[17]  Xiande Zhao,et al.  Optimizing the service configuration with the least total cost approach , 2002 .

[18]  Jianmin Jia,et al.  What You Don'T Know About Customer-Perceived Quality: the Role of Customer Expectation Distributions , 1999 .

[19]  R. Freeman.  Strategic Management: A Stakeholder Approach , 2010 .

[20]  R. Rust,et al.  Return on Quality (ROQ): Making Service Quality Financially Accountable , 1995 .

[21]  Stephen S. Tax,et al.  Designing and implementing new services: The challenges of integrating service systems , 1997 .

[22]  Bo Edvardsson,et al.  Service Break-Downs a Study of Critical Incidents in an Airline , 1992 .

[23]  C. C. Waid,et al.  An Experimental Comparison of Different Approaches to Determining Weights in Additive Utility Models , 1982 .

[24]  J. Ovretveit,et al.  A comparison of hospital quality programmes: lessons for other services , 1997 .

[25]  Thomas L. Saaty,et al.  Marketing Applications of the Analytic Hierarchy Process , 1980 .

[26]  C. Grönroos.  A Service Quality Model and its Marketing Implications , 1984 .

[27]  Jan Barnsley,et al.  Competing values of emergency department performance: balancing multiple stakeholder perspectives. , 2004, Health services research.

[28]  K. K. Lai,et al.  Improving the quality of the credit authorization process: A quantitative approach , 2001 .

[29]  N. A. Nichols.  Scientific management at Merck: An interview with CFO Judy Lewent , 1994 .

[30]  B. Kahn,et al.  Consumer Multiattribute Judgments under Attribute-Weight Uncertainty , 1991 .

[31]  David Vose,et al.  Quantitative Risk Analysis: A Guide to Monte Carlo Simulation Modelling , 1996 .

[32]  A. Parasuraman,et al.  A Conceptual Model of Service Quality and Its Implications for Future Research , 1985 .

[33]  Eugene M. Johnson,et al.  A Proposed Model for New Service Development , 1989 .

[34]  Bart Van Looy,et al.  Dealing with productivity and quality indicators in a service environment: some field experiences , 1997 .

[35]  R. Di Mascio,et al.  An economic measure for comparing dynamic robustness , 2002 .

[36]  Padmini Srinivasan,et al.  Fuzzy versus probabilistic models for user relevance judgments , 1990 .

[37]  T. L. Saaty.  A Scaling Method for Priorities in Hierarchical Structures , 1977 .

[38]  Joseph Moses Juran,et al.  Quality Planning and Analysis: From Product Development Through Usage , 1982 .

[39]  Frank McGuire.  Using simulation to reduce length of stay in emergency departments , 1994, Proceedings of Winter Simulation Conference.

[40]  Edward S. Rubin,et al.  Parameter design methodology for chemical processes using a simulator , 1994 .

[41]  R. H. Myers,et al.  Response Surface Alternatives to the Taguchi Robust Parameter Design Approach , 1992 .

[42]  Peter Otto,et al.  Gloucester Fishery: insights from a group modeling intervention , 2004 .

[43]  V. Zeithaml,et al.  A Dynamic Process Model of Service Quality: From Expectations to Behavioral Intentions , 1993 .

[44]  J. C. Goodale,et al.  Tour scheduling with dynamic service rates , 1998 .

[45]  Peretz Shoval,et al.  Models for computer system evaluation and selection , 1987, Inf. Manag..

[46]  Connie M. Borror,et al.  Response Surface Methodology: A Retrospective and Literature Survey , 2004 .

[47]  J. H. Myers,et al.  Semantic Confusion in Attitude Research: Salience Vs. Importance Vs. Determinance , 1977 .

[48]  R. Maxwell,et al.  Stochastic environmental risk analysis: an integrated methodology for predicting cancer risk from contaminated groundwater , 1999 .

[49]  Manuel D. Rossetti,et al.  Emergency department simulation and determination of optimal attending physician staffing schedules , 1999, WSC '99.

[50]  Duško Pavletić,et al.  The Fundamental Concepts of Excellence , 2007 .

[51]  Curtis P. McLaughlin,et al.  Why variation reduction is not everything: a new paradigm for service operations , 1996 .

[52]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[53]  J. Barney.  Firm Resources and Sustained Competitive Advantage , 1991 .

[54]  Mary Jo Bitner,et al.  The Development and Emergence of Services Marketing Thought , 1994 .

[55]  M. Aral,et al.  2D Monte Carlo versus 2D Fuzzy Monte Carlo health risk assessment , 2005 .

[56]  Rita Di Mascio,et al.  Service process control: conceptualising a service as a feedback control system , 2002 .

[57]  S. Ward,et al.  Constructively simple estimating: a project management example , 2003, J. Oper. Res. Soc..

[58]  Mahmoud M. Yasin,et al.  Application of root cause analysis in a service delivery operational environment , 1997 .

[59]  N. Pennington,et al.  Explanation-based decision making: effects of memory structure on judgment , 1988 .

[60]  K. Stave.  Using system dynamics to improve public participation in environmental decisions , 2002 .

[61]  Robert T. Eckenrode,et al.  Weighting Multiple Criteria , 1965 .

[62]  Paul E. Green,et al.  Attribute Importance Weights Modification in Assessing a Brand's Competitive Potential , 1995 .

[63]  Ralph L. Keeney,et al.  New Industrial Product Design and Evaluation Using Multiattribute Value Analysis , 1987 .

[64]  Richard A. Spreng,et al.  Modeling the determinants of customer satisfaction for business-to-business professional services , 1997 .

[65]  A. Parasuraman,et al.  Alternative scales for measuring service quality: A comparative assessment based on psychometric and diagnostic criteria , 1994 .

[66]  Jochen Wirtz,et al.  Introducing uncertain performance expectations in satisfaction models for services , 1999 .

[67]  S. Erdem,et al.  An exploratory study of services marketing in global markets: major areas of inquiry for the health care services industry. , 1996, Health marketing quarterly.

[68]  John D. C. Little,et al.  Models and Managers: The Concept of a Decision Calculus , 2016, Manag. Sci..

[69]  R. N. Kackar.  Off-Line Quality Control, Parameter Design, and the Taguchi Method , 1985 .

[70]  Richard Metters,et al.  Linking Marketing and Operations , 2002 .

[71]  G. W. Fischer.  Range Sensitivity of Attribute Weights in Multiattribute Value Models , 1995 .

[72]  W. Woodall,et al.  A probabilistic alternative to fuzzy logic controllers , 1997 .

[73]  Thomas R. Stewart,et al.  A comparison of seven methods for obtaining subjective descriptions of judgmental policy , 1975 .

[74]  G. L. Shostack.  Designing Services That Deliver , 1996 .

[75]  Liang-Hsuan Chen.  Designing robust products with multiple quality characteristics , 1997, Comput. Oper. Res..

[76]  G. Geoffrey Vining,et al.  Combining Taguchi and Response Surface Philosophies: A Dual Response Approach , 1990 .