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A Fuzzy Design Decision Model for New Healthcare Service Conceptualization

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Abstract

This paper purpose a structural design decision model by using service blueprint, failure mode effect analysis (FMEA), Fuzzy method, and the theory of inventive problem solving (TRIZ). In “service process analysis” stage, the service blueprint approach is used to analyze the potential service failure points in the service process. Then, FMEA is employed to diagnose the possible causes and effects of the service failure model in “service failure diagnosis” stage. The service failure models are prioritized according to the calculated integrated Risk Priority Number (RPN) and fuzzy number. In “innovative principle generation” stage, the innovative principles are generated by utilizing the TRIZ matrix. Finally, in “innovative solution conceptualization” stage, the TRIZ inventive principles are used to inspire the new solution for new service design. An empirical survey of home-care service agencies in Beijing is conducted to demonstrate the applicability of the proposed 2S2I model to improve home-care services, medical-equipment designs, and service delivery. The advantages, implications, and contributions of 2S2I model are also concluded.

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Fig. 1
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(adapted from Tooranloo, Ayatollah [24], Bhuvanesh Kumar, Parameshwaran [43] and Mirghafoori et al. [29])

Fig. 3

(adapted from Tooranloo, Ayatollah [24], Bhuvanesh Kumar, Parameshwaran [43] and Mirghafoori et al. [29])

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References

  1. Aboderin, I.: Changing family relationships in developing nations. In: Johnson, M.L. (ed.) The Cambridge Handbook of Age and Ageing, pp. 469–475. Cambridge University Press, Cambridge (2005)

    Chapter  Google Scholar 

  2. Palmore, E.B., Whittington, F., Kunkel, S.: The International Handbook on Aging: Current Research and Developments. England, Oxford (2009)

    Google Scholar 

  3. Eiriz, V., Figueiredo, J.A.: Quality evaluation in health care services based on customer-provider relationships. Int. J. Health Care Qual. Assur. 18(6), 404–412 (2005)

    Article  Google Scholar 

  4. Francis, J., Netten, A.: Raising the quality of home care: a study of service user’s views. Social Policy Admin. 38(3), 290–305 (2004)

    Article  Google Scholar 

  5. Raynes, N., Temple, B., Glenister, C., Coulthard, L.: Quality at Home for Older People: Involving Service Users in Defining Home Care Specifications. Policy Press and Joseph Rowntree Foundation, York (2001)

    Google Scholar 

  6. Mitchell, J.M., Kemp, B.J.: Quality of life in assisted living homes: a multidimensional analysis. J. Gerontol. 55, 2 (2000)

    Article  Google Scholar 

  7. Starfish, C.: The Elusive Costs of Home Care. Starfish Consulting, London (2002)

    Google Scholar 

  8. Lee, C.H., Chen, C.H., Trappey, A.J.C.: A structural service innovation approach for designing smart product service systems: case study of smart beauty service. Adv. Eng. Inform. 40, 154–167 (2019). https://doi.org/10.1016/j.aei.2019.04.006

    Article  Google Scholar 

  9. Li, F., Chen, C.H., Lee, C.H., Khoo, L.P.: A user requirement-driven approach incorporating TRIZ and QFD for designing a smart vessel alarm system to reduce alarm fatigue. J. Navig. (2019). https://doi.org/10.1017/S0373463319000547

    Article  Google Scholar 

  10. Dziallas, M., Blind, K.: Innovation indicators throughout the innovation process: an extensive literature analysis. Technovation 80–81, 3–29 (2019). https://doi.org/10.1016/j.technovation.2018.05.005

    Article  Google Scholar 

  11. Lee, C.H., Wang, Y.H., Trappey, A.J.C.: Service design for intelligent parking based on theory of inventive problem solving and service blueprint. Adv. Eng. Inform. 29(3), 295–306 (2015). https://doi.org/10.1016/j.aei.2014.10.002

    Article  Google Scholar 

  12. Shin, H., Perdue, R.R., Kang, J.: Front desk technology innovation in hotels: a managerial perspective. Tourism Manag. 74, 310–318 (2019). https://doi.org/10.1016/j.tourman.2019.04.004

    Article  Google Scholar 

  13. Li, M.L., Hsu, C.H.C.: Customer participation in services and employee innovative behavior: the mediating role of interpersonal trust. Int. J. Contemp. Hosp. Manag. 30(4), 2112–2131 (2018). https://doi.org/10.1108/ijchm-08-2016-0465

    Article  Google Scholar 

  14. Chen, B.T.: Service innovation performance in the hospitality industry: the role of organizational training, personal-job fit and work schedule flexibility. J. Hospital. Market. Manag. 26(5), 474–488 (2017). https://doi.org/10.1080/19368623.2017.1264344

    Article  Google Scholar 

  15. Poppel, J., Finsterwalder, J., Laycock, R.A.: Developing a film-based service experience blueprinting technique. J. Business Res. 85, 459–466 (2018). https://doi.org/10.1016/j.jbusres.2017.10.024

    Article  Google Scholar 

  16. Johansson, A.E., Raddats, C., Witell, L.: The role of customer knowledge development for incremental and radical service innovation in servitized manufacturers. J. Business Res. 98, 328–338 (2019). https://doi.org/10.1016/j.jbusres.2019.02.019

    Article  Google Scholar 

  17. Yu, E., Sangiorgi, D.: Service design as an approach to implement the value cocreation perspective in new service development. J. Serv. Res. 21(1), 40–58 (2018). https://doi.org/10.1177/1094670517709356

    Article  Google Scholar 

  18. Beverungen, D., Luttenberg, H., Wolf, V.: Recombinant service systems engineering. Business Inform. Syst. Eng. 60(5), 377–391 (2018). https://doi.org/10.1007/s12599-018-0526-4

    Article  Google Scholar 

  19. Ma, S., Gu, H.M., Wang, Y.G., Hampson, D.P.: Opportunities and challenges of value co-creation. The role of customer involvement in hotel service development. Int. J. Contemp. Hospit. Manag. 29(12), 3023–3043 (2017). https://doi.org/10.1108/ijchm-08-2016-0479

    Article  Google Scholar 

  20. Hsiao, Y.C.: Exploring service innovation and value creation: the critical role of network relationships. J. Manag. Organ. 25(1), 4–25 (2019). https://doi.org/10.1017/jmo.2017.40

    Article  Google Scholar 

  21. Wang, Y.H., Lee, C.H., Trappey, A.J.C.: Modularized design-oriented systematic inventive thinking approach supporting collaborative service innovations. Adv. Eng. Inform. 33, 300–313 (2017). https://doi.org/10.1016/j.aei.2016.11.006

    Article  Google Scholar 

  22. Weng, J.P., Wang, J.H., Yang, J.H., Yang, Y.: Root cause analysis of anomalies of multitier services in public clouds. IEEE-ACM Trans. Netw. 26(4), 1646–1659 (2018). https://doi.org/10.1109/tnet.2018.2843805

    Article  Google Scholar 

  23. Chiu, M.C., Chu, C.Y., Chen, C.C.: An integrated product service system modelling methodology with a case study of clothing industry. Int. J. Prod. Res. 56(6), 2388–2409 (2018). https://doi.org/10.1080/00207543.2017.1374570

    Article  Google Scholar 

  24. Tooranloo, H.S., Ayatollah, A.S.: Pathology the internet banking service quality using failure mode and effect analysis in interval-valued intuitionistic fuzzy environment. Int. J. Fuzzy Syst. 19(1), 109–123 (2017). https://doi.org/10.1007/s40815-016-0265-y

    Article  Google Scholar 

  25. Salazar, C., Lelah, A., Brissaud, D.: Eco-designing Product Service Systems by degrading functions while maintaining user satisfaction. J. Clean. Prod. 87, 452–462 (2015). https://doi.org/10.1016/j.jclepro.2014.10.031

    Article  Google Scholar 

  26. Andriankaja, H., Boucher, X., Medini, K.: A method to design integrated product-service systems based on the extended functional analysis approach. Cirp J. Manuf. Sci. Technol. 21, 120–139 (2018). https://doi.org/10.1016/j.cirpj.2018.02.001

    Article  Google Scholar 

  27. Sun, R., Hu, J., Zhou, J., Chen, X.: A hesitant fuzzy linguistic projection-based MABAC method for patients’ prioritization. Int. J. Fuzzy Syst. 20(7), 2144–2160 (2017). https://doi.org/10.1007/s40815-017-0345-7

    Article  Google Scholar 

  28. Dincer, H., Yuksel, S.: Comparative evaluation of BSC-based new service development competencies in Turkish banking sector with the integrated fuzzy hybrid MCDM using content analysis. Int. J. Fuzzy Syst. 20(8), 2497–2516 (2018). https://doi.org/10.1007/s40815-018-0519-y

    Article  Google Scholar 

  29. Mirghafoori, S.H., Izadi, M.R., Daei, A.: Analysis of the barriers affecting the quality of electronic services of libraries by VIKOR, FMEA and entropy combined approach in an intuitionistic-fuzzy environment. J. Intell. Fuzzy Syst. 34(4), 2441–2451 (2018). https://doi.org/10.3233/jifs-171695

    Article  Google Scholar 

  30. Tooranloo, H.S., Ayatollah, A.S., Marvasti, M.T.: Diagnosing the service quality improvement of university libraries in intuitionistic fuzzy environment. Malays. J. Libr. Inform. Sci. 23(3), 69–91 (2018). https://doi.org/10.22452/mjlis.vol23no3.5

    Article  Google Scholar 

  31. Tsou, H.T., Chen, J.S., Wang, Z.Q.: Partner selection, interorganizational coordination, and new service development success in the financial service industry. Can. J. Admin. Sci. Revue Canadienne Des Sciences De L Administration 36(2), 231–247 (2019). https://doi.org/10.1002/cjas.1487

    Article  Google Scholar 

  32. Johnson, S.P., Menor, L.J., Roth, A.V., Chase, R.B.: A critical evaluation of the new services development process: integrating service innovation and service design. In: Fitzsimmons, j.A., Fitzsimmons, M.J. (eds.) New Service Development, Creating Memorable Experiences. Sage Publications, Thousand Oaks (2000)

  33. Liu, C.H., Chang, A.Y.P., Horng, J.S., Chou, S.F., Huang, Y.C.: Co-competition, learning, and business strategy for new service development. Serv. Industr. J. (2019). https://doi.org/10.1080/02642069.2019.1571045

    Article  Google Scholar 

  34. Wu, Y.-C., Lin, G.T.R., Yu, W.-H.: How to enhance customer involvement in service innovation within service industry. J. Sci. Ind. Res. 78(6), 342–344 (2019)

    Google Scholar 

  35. Anning-Dorson, T.: Customer involvement capability and service firm performance: the mediating role of innovation. J. Busin. Res. 86, 269–280 (2018). https://doi.org/10.1016/j.jbusres.2017.07.015

    Article  Google Scholar 

  36. Lee, Y.C., Chen, C.H., Lee, C.H.: Body anthropometric measurements of Singaporean adult and elderly population. Meas J Int Meas Confed (2019). https://doi.org/10.1016/j.measurement.2019.106949

    Article  Google Scholar 

  37. Behdioğlu, S., Acar, E., Burhan, H.A.: Evaluating service quality by fuzzy SERVQUAL: a case study in a physiotherapy and rehabilitation hospital. Total Qual. Manag. Bus. Excell. 30(3–4), 301–319 (2017). https://doi.org/10.1080/14783363.2017.1302796

    Article  Google Scholar 

  38. Xu, H., Fan, Z.-P., Liu, Y., Peng, W.-L., Yu, Y.-Y.: A method for evaluating service quality with hesitant fuzzy linguistic information. Int. J. Fuzzy Syst. 20(5), 1523–1538 (2018). https://doi.org/10.1007/s40815-018-0476-5

    Article  Google Scholar 

  39. Chowdhury, M.M.H., Quaddus, M.A.: A multi-phased QFD based optimization approach to sustainable service design. Int. J. Prod. Econ. 171, 165–178 (2016). https://doi.org/10.1016/j.ijpe.2015.09.023

    Article  Google Scholar 

  40. Haber, N., Fargnoli, M., Sakao, T.: Integrating QFD for product-service systems with the Kano model and fuzzy AHP. Total Qual. Manag. Bus. Excell. (2018). https://doi.org/10.1080/14783363.2018.1470897

    Article  Google Scholar 

  41. Ljubojevic, S., Pamucar, D., Jovanovic, D., Vesovic, V.: Outsourcing transport service: a fuzzy multi-criteria methodology for provider selection based on comparison of the real and ideal parameters of providers. Oper. Res. Int. Journal 19(2), 399–433 (2019). https://doi.org/10.1007/s12351-017-0293-x

    Article  Google Scholar 

  42. de Aquino, J.T., de Melo, F.J.C., Jeronimo, T.D., de Medeiros, D.D.: Evaluation of quality in public transport services: the use of quality dimensions as an input for fuzzy TOPSIS. Int. J. Fuzzy Syst. 21(1), 176–193 (2019). https://doi.org/10.1007/s40815-018-0524-1

    Article  Google Scholar 

  43. Bhuvanesh Kumar, M., Parameshwaran, R.: Fuzzy integrated QFD, FMEA framework for the selection of lean tools in a manufacturing organisation. Prod. Plan. Contr. (2018). https://doi.org/10.1080/09537287.2018.1434253

    Article  Google Scholar 

  44. Lee, C.H., Chen, C.H., Li, F., Shie, A.J.: Customized and knowledge-centric service design model integrating case-based reasoning and TRIZ. Expert Syst. Appl. (2020). https://doi.org/10.1016/j.eswa.2019.113062

    Article  Google Scholar 

  45. Lee, Y.-C., Chen, C.-H., Lee, C.-H.: Body anthropometric measurements of Singaporean adult and elderly population. Measurement 148, 106949 (2019). https://doi.org/10.1016/j.measurement.2019.106949

    Article  Google Scholar 

  46. Pan, Y., Zhang, X., Tian, J., Jin, X., Luo, L., Yang, K.: Mapping asphalt pavement aging and condition using multiple endmember spectral mixture analysis in Beijing, China. J. Appl. Remote Sens. 11, 1 (2017). https://doi.org/10.1117/1.jrs.11.016003

    Article  Google Scholar 

  47. Chhetri, J.K., Zheng, Z., Xu, X., Ma, C., Chan, P.: The prevalence and incidence of frailty in Pre-diabetic and diabetic community-dwelling older population: results from Beijing longitudinal study of aging II (BLSA-II). BMC Geriatr. 17, 1 (2017). https://doi.org/10.1186/s12877-017-0439-y

    Article  Google Scholar 

  48. Yang, X., Chen, B., Chen, C., Wang, Y.: Dynamic model of population prediction based on Aging Chains. In: 28th Chinese Control and Decision Conference, CCDC 2016 2016, pp. 216-219. Institute of Electrical and Electronics Engineers Inc

  49. Liu, X., Chen, Z., Fine, J.P., Liu, L., Wang, A., Guo, J., Tao, L., Mahara, G., Yang, K., Zhang, J., Tian, S., Li, H., Liu, K., Luo, Y., Zhang, F., Tang, Z., Guo, X.: A competing-risk-based score for predicting twenty-year risk of incident diabetes: the Beijing Longitudinal Study of Ageing study. Sci. Rep. (2016). https://doi.org/10.1038/srep37248

    Article  Google Scholar 

  50. Li, T., Horton, R.M., Bader, D.A., Zhou, M., Liang, X., Ban, J., Sun, Q., Kinney, P.L.: Aging will amplify the heat-related mortality risk under a changing climate: projection for the elderly in Beijing, China. Sci. Rep. (2016). https://doi.org/10.1038/srep28161

    Article  Google Scholar 

  51. Chen, C.K., Shie, A.J., Wang, K.M., Yu, C.H.: An ageing-in-place service innovation model by using TRIZ methodology. Hum. Fact. Ergon. Manuf. Serv. Industr. 25(2), 166–182 (2015)

    Article  Google Scholar 

  52. Cohen-Mansfield, J., Frank, J.: Relationship between perceived needs and assessed needs for services in community-dwelling older persons. Gerontologist 48(4), 505–516 (2008)

    Article  Google Scholar 

  53. Cutler, L.J.: Physical environments of assisted living: research needs and challenges. The Gerontologist 47 Spec No 3, 68-82 (2007)

  54. Stone, R.I., Reinhard, S.C.: The place of assisted living in long-term care and related service systems. The Gerontologist 47 Spec No 3, 23-32 (2007)

  55. Nakrem, S., Solbjor, M., Pettersen, I.N., Kleiven, H.H.: Care relationships at stake? Home healthcare professionals’ experiences with digital medicine dispensers—a qualitative study. Bmc Health Serv. Res. (2018). https://doi.org/10.1186/s12913-018-2835-1

    Article  Google Scholar 

  56. Dwyer, T., Craswell, A., Rossi, D., Holzberger, D.: Evaluation of an aged care nurse practitioner service: quality of care within a residential aged care facility hospital avoidance service. Bmc Health Serv. Res. (2017). https://doi.org/10.1186/s12913-017-1977-x

    Article  Google Scholar 

  57. Liu, T., Hao, X., Zhang, Z.: Identifying community healthcare supports for the elderly and the factors affecting their aging care model preference: evidence from three districts of Beijing. Bmc Health Serv. Res. 16(Suppl 7), 626 (2016). https://doi.org/10.1186/s12913-016-1863-y

    Article  Google Scholar 

  58. Rizzo, A., Requejo, P., Winstein, C.J., Lange, B., Ragusa, G., Merians, A., Patton, J., Banerjee, P., Aisen, M.: Virtual reality applications for addressing the needs of those aging with disability. MMVR 163, 510–516 (2011)

    Google Scholar 

  59. Chen, S.-H., Wen, P.-C., Yang, C.-K.: Business concepts of systemic service innovations in e-Healthcare. Technovation 34(9), 513–524 (2014). https://doi.org/10.1016/j.technovation.2014.03.002

    Article  Google Scholar 

  60. Yang, H.L., Hsiao, S.L.: Mechanisms of developing innovative IT-enabled services: a case study of Taiwanese healthcare service. Technovation 29(5), 327–337 (2009)

    Article  Google Scholar 

  61. Sun, R.X., Hu, J.H., Zhou, J.D., Chen, X.H.: A hesitant fuzzy linguistic projection-based MABAC method for patients’ prioritization. Int. J. Fuzzy Syst. 20(7), 2144–2160 (2018). https://doi.org/10.1007/s40815-017-0345-7

    Article  Google Scholar 

  62. Karami, A., Gangopadhyay, A., Zhou, B., Kharrazi, H.: Fuzzy approach topic discovery in health and medical corpora. Int. J. Fuzzy Syst. 20(4), 1334–1345 (2018). https://doi.org/10.1007/s40815-017-0327-9

    Article  Google Scholar 

  63. Dinçer, H., Yüksel, S.: An integrated stochastic fuzzy MCDM approach to the balanced scorecard-based service evaluation. Math. Comput. Simul. 166, 93–112 (2019). https://doi.org/10.1016/j.matcom.2019.04.008

    Article  MathSciNet  Google Scholar 

  64. Dincer, H., Yuksel, S., Martinez, L.: A comparative analysis of incremental and disruptive innovation policies in the European banking sector with hybrid Interval type-2 fuzzy decision-making models. Int. J. Fuzzy Syst. (2020). https://doi.org/10.1007/s40815-020-00851-8

    Article  Google Scholar 

  65. Del Chiappa, G., Martin, J.C., Roman, C.: Service quality of airports’ food and beverage retailers. A fuzzy approach. J. Air Transp. Manag. 53, 105–113 (2016). https://doi.org/10.1016/j.jairtraman.2016.02.002

    Article  Google Scholar 

  66. Hsu, W.: A fuzzy multiple-criteria decision-making system for analyzing gaps of service quality. Int. J. Fuzzy Syst. 17(2), 256–267 (2015). https://doi.org/10.1007/s40815-015-0018-3

    Article  Google Scholar 

  67. Mishra, A.R., Jain, D., Hooda, D.S.: Exponential intuitionistic fuzzy information measure with assessment of service quality. Int. J. Fuzzy Syst. 19(3), 788–798 (2017). https://doi.org/10.1007/s40815-016-0278-6

    Article  MathSciNet  Google Scholar 

  68. Vaziri, J., Beheshtinia, M.A.: A holistic fuzzy approach to create competitive advantage via quality management in services industry (case study: life-insurance services). Manag. Decis. 54(8), 2035–2062 (2016). https://doi.org/10.1108/md-11-2015-0535

    Article  Google Scholar 

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Acknowledgements

This research was supported by the Social Science Fund of Jiangsu Province [Grant Number: 19SHB003]. This research was also supported by the Xi’an Jiaotong University [Grant Number: 7121192301].

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Authors and Affiliations

  1. School of Economics and Management, Huaiyin Normal University, Huaian, China

    An-Jin Shie

  2. School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, China

    Ching-Hung Lee & Chang Wang

  3. China-ASEAN International College, Dhurakij Pundit University, Bangkok, Thailand

    Shu-Yan Yu

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  1. An-Jin Shie
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  2. Ching-Hung Lee
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Correspondence to Ching-Hung Lee.

Appendices

Appendices

1.1 Appendix A

Service blueprint structure and the set of symbols.

figure a

1.2 Appendix B

See Table 14.

Table 14 List of the 40 TRIZ invention principles
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1.3 Appendix C

See Table 15.

Table 15 TRIZ parameter correspondence table for aging-in-place service
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Shie, AJ., Lee, CH., Yu, SY. et al. A Fuzzy Design Decision Model for New Healthcare Service Conceptualization. Int. J. Fuzzy Syst. 23, 58–80 (2021). https://doi.org/10.1007/s40815-020-00942-6

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