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Combining Balanced Scorecard and Data Envelopment Analysis to Design Performance Measurement for Supply Chain Actor and Regulator: A Case Study in Innovative Product in Indonesia

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Industrial Engineering, Management Science and Applications 2015

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 349))

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Abstract

This research is a sequel of the authors’ earlier conducted researches in the fields of identifying the key performance indicator for actors and regulators. In the previous study, authors proposed a model based on Balanced Scorecard perspective, by integrating process based on SCOR into the internal business processes and incorporated the role of regulators in each perspective. This model referred as B-S-Rc model (Balanced Scorecard-SCOR-Regulator contribution). The weakness of this model is it has no standard methodology and the inability to provide a benchmark. The objective of the present study is developing a model to overcome the shortcomings of the B-S–Rc, by combining the B-S - Rc with Data Envelopment Analysis (DEA). This integrated model is validated on supply chain’s SME and regulators of innovative products in Yogyakarta, Indonesia. It is found that the combination of BS-Rc-DEA provides information that enables benchmarking to overcome the weaknesses of B-S-Rc model.

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References

  1. Barber, E.: How to measure the “Value” in value chains. International Journal of Physical Distribution & Logistics Management 38(9), 685–698 (2008)

    Article  Google Scholar 

  2. Bhagwatt, R., Sharma, M.K.: Performance measurement of supply chain management using the analytical hierarchy process. Production Planning & Control 18(8), 666–680 (2007a)

    Article  Google Scholar 

  3. Brewer, P.C., Speh, T.W.: Using balanced scorecard to measure supply chain performance. Journal of Business Logistics 21(1) (2000)

    Google Scholar 

  4. Chia, A., Goh, M., Hum, S.: Performance measurement in supply chain entities: balanced scorecard perspective. Benchmarking: An International Journal 16(5), 605–620 (2009)

    Article  Google Scholar 

  5. Chang, H.H.: An empirical study of evaluating supply chain management integration using balanced score card in Taiwan. The Service Industries Journal 29(2), 185–201 (2009)

    Article  Google Scholar 

  6. Gunasekaran, A., Patel, C., Tirtiroglu, E.: Performance measures and metrics in a supply chain environment. International Journal of Operation & Production Management 21, 71–87 (2001)

    Article  Google Scholar 

  7. Gunasekaran, A., Patel, C., McGaughey, R.E.: A framework for supply chain performance measurement. International Journal Production Economy 87, 333–347 (2004)

    Article  Google Scholar 

  8. Park, J.H., Lee, J.S., Yoo, J.S.: A framework for designing the balanced supply chain scorecard. European Journal of Information Systems 14, 335–346 (2005)

    Article  Google Scholar 

  9. Georgise, F.B., Thoben, K.D., Seifert, M.: Adapting the SCOR model to suit the different scenarios: a literature review & research agenda. International Journal of Business and Management 7(6), 1–17 (2012)

    Article  Google Scholar 

  10. Chae, K.: Developing key performance indikators for supply chain: an industry perspective. Supply Chain Management: An International Journal 14(6), 422–428 (2009)

    Article  MathSciNet  Google Scholar 

  11. Huan, S.H., Sheoran, S.K., Wang, G.: A review and analysis of supply chain operations reference (SCOR) model. Supply Chain Management, ABI/INFORM 9(1), 23–29 (2004)

    Article  Google Scholar 

  12. Lockamy, A., McCormack, K.: Linking SCOR planning practices to supply chain performance: an exploratory study. International Journal of Operations & Production Management 24(11/12), 1192–1217 (2004)

    Article  Google Scholar 

  13. Supply Chain Council: Supply Chain Operation Reference Model (2001), http://www.supply-chain.org

  14. Theeranuphattana, A., Tang, J.C.S.: A conceptual model of performance measurement for supply chains alternative considerations. Thailand Journal of Manufacturing Technology Management 19(1), 125–148 (2008)

    Article  Google Scholar 

  15. Beamon, B.M.: Measuring supply chain performance. International Journal of Operation & Production Management 19, 275–292 (1999)

    Article  Google Scholar 

  16. Espinoza, O., Bond, B.H., Kline, E.: Supply chain measures of performance for wood products manufacturing. Forest Production Journal 60(7/8), 700–708 (2010)

    Article  Google Scholar 

  17. Farris, M.T., Hutchison, P.D.: Cash-to-cash: the new supply chain management metric. International Journal of Physical Distribution & Logistics Management 32(4), 288–298 (2002)

    Article  Google Scholar 

  18. Hum, S.-H., Parlar, M.: Measurement and optimization of supply chain responsiveness. IIE Transactions, Taylor & Francis Group, Philadephia 46(1) (2014)

    Google Scholar 

  19. Marthin, P.R., Patterson, J.W.: On measuring company within a supply chain. International Journal of Production Research 47(9), 2449–2460 (2009)

    Article  Google Scholar 

  20. Pohlen, T.L., Coleman, B.J.: Evaluating internal operations and supply chain performance using EVA and ABC. S.A.M. Advanced Management Journal 70(2), ABI/INFORM Global, 45–58 (2005)

    Google Scholar 

  21. Wong, W.P., Wong, K.Y.: Supply chain performance measurement system using DEA modeling. Industrial Management & Data Systems 107(3), 361–381 (2007)

    Article  Google Scholar 

  22. Yang, F., Wu, D., Liang, L., Bi, G., Wu, D.D.: Supply chain DEA: production possibility set and performance evaluation model. Annals of Operations Research 185(1), 195–211 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  23. Liang, L., Yang, F., Cook, W.D., Zhu, J.: DEA models for supply chain efficiency evaluation. Ann. Oper. Res. 145, 35–49 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  24. Tambunan, T.: Promoting small and medium enterprises with a clustering approach: a policy experience from Indonesia. Journal of Small Business Management 43(2), 138–154 (2005)

    Article  Google Scholar 

  25. Mawardi, M.K., Choi, T., Perera, N.: The factors of SME cluster developments in a developing country: the case of Indonesian clusters. In: ICSB World Conference Proceedings, pp. 1–28. International Council for Small Business (ICSB), Washington (2011)

    Google Scholar 

  26. Parrilli, M.D.: Collective efficiency, policy inducement and social embeddedness: drivers for the development of industrial district. Entrepreneurship & Regional Development 21(1), 1–24 (2009)

    Article  Google Scholar 

  27. Nakagawa, R.: The policy approach in promoting small and medium sized enterprises in Japan. International Business & Economics Research Journal 11(10) (2012)

    Google Scholar 

  28. Kusrini, E.S., Masruroh, N.A.: A New Approach to Design Supply Chain Key Performance Indicator for Actors and Regulator: A Case Study in Innovative Produc. In: Indonesia. International Journal of Business Performance Management (2014) (accepted)

    Google Scholar 

  29. Striteska, M., Spickova, M.: Review and Comparison of Performance Measurement Systems. Journal of Organizational Management Studies 2012 (2012)

    Google Scholar 

  30. Banker, R.D., Potter, G., Srinivasan, D.: An empirical investigation of an incentive plan that includes nonfinancial performance measures. Accounting Review 75(1), 65–92 (2000)

    Article  Google Scholar 

  31. Lee, J.Y.: Combining balanced scorecard and data envelopment analysis in kitchen employees performance measurement - An exploratory study - A dissertation Hospitality Management, Iowa (2012)

    Google Scholar 

  32. Rickards, R.C.: Setting benchmarks and evaluating balanced scorecards with data envelopment analysis. International Benchmarking Journal 10(5), 62–86 (2003)

    Google Scholar 

  33. Coelli, T.: A Guide to DEAP version 2.1. A Data Envelopment Analysis (Computer) Program. Department of Economic University of New England (1996)

    Google Scholar 

  34. Banker, R.D., Charness, A., Cooper, W.W.: Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science 30(6), 1078–1092 (1984)

    Article  MATH  Google Scholar 

  35. Aryanezhad, M.B., Najafib, E., Bakhshi, F.S.: A BSC-DEA approach to measure the relative efficiency of service industry: a case study of banking sector. International Journal of Industrial Engineering Computations 2(2), 273–282 (2011)

    Article  Google Scholar 

  36. Kaplan, R.S., Norton, D.P.: Using the balanced scorecard as a strategic management system. Harvard Business Review 74(1), 75–85 (1996)

    Google Scholar 

  37. Charnes, A., Cooper, W., Rhodes, E.: Measuring the efficiency of decision making units. European Journal of Operational Research 2(6), 429–444 (1978)

    Article  MATH  MathSciNet  Google Scholar 

  38. Chen, Y.S., Chen, B.Y.: Using data envelopment analysis (DEA) to evaluate the operational performance of the wafer fabrication industry in Taiwan. Journal of Manufacturing Technology Management 20(4), 475–488 (2009)

    Article  Google Scholar 

  39. Huang, S.P.: Performance analyses of traditional industries in taiwan with data envelopment analysis. The International Journal of Organizational Innovation 4(3) (Winter 2012)

    Google Scholar 

  40. Nooreha, H., Mokhtar, A., Suresh, K.: Evaluating publicsector efficiency with Data envelopment Analysis (DEA): A case study in road Transport deartement, Seangor Malaysia. Total Quality Management, pp. 4–6 (July 2000)

    Google Scholar 

  41. Meza, D.: Measuring the efficiency of a lean six sigma program in a u.s. government agency using data envelopment analysis, thesis the Faculty of University of Houston Clear Lake (2012)

    Google Scholar 

  42. Sarkis, J., Talluri, S.: Ecoefficiency measurement using dataenvelopment analysis: research and practitioner issues. Journal of Environmental Assessment Policy and Management 6(1), 91–123 (2004)

    Article  Google Scholar 

  43. Min, H., Min, H., Joo, S.J.: A data envelopment analysis-based balanced scorecard for measuring the comparative efficiency of Korean luxury hotels. International Journal of Quality & Reliability Management 25(4), 349–365 (2008)

    Article  Google Scholar 

  44. Wu, W., Liao, Y.: A balanced scorecard envelopment approach to assess airlines’ performance. Industrial Management & Data Systems 114(1), 123–143 (2014)

    Article  MathSciNet  Google Scholar 

  45. Chen, T., Chen, C., Peng, S.: Firm operation performance analysis using dataenvelopment analysis and balanced scorecard: a case study of a credit cooperative bank. International Journal of Productivity and Performance Management 57(7), 523–539 (2008)

    Article  Google Scholar 

  46. Poister, T.H., Streib, G.: Performance Measurement in Municipal Government: Assessing the State of the Practice. Public Administration Review 59(4), 325–335 (1999)

    Article  Google Scholar 

  47. Neely, A., Gregory, M., Platts, K.: Performance measurement system design: a literature review and research agenda. International Journal of Operation and Production Management 25, 1228–1263 (2005)

    Article  Google Scholar 

  48. Nyhan, R.C., Martin, L.L.: Assessing the Performance of Municipal PoliceServices Using Data Envelopment Analysis: An Exploratory Study. State and Local Government Review 31(1), 18–30 (1999)

    Article  Google Scholar 

  49. Ammons, D.N.: Overcoming the Inadequacies of Performance Measurement in Local Government: the Case of Libraries and Leisure Services. Public Administration Review 55(1), 37–47 (1995)

    Article  Google Scholar 

  50. Kusrini, E., Subagyo, Masruroh, N.A.: Good Criteria for Supply Chain Performance Measurement. International Journal of Engineering Business Management 6, 9 (2014), doi:10.5772/58435

    Google Scholar 

  51. Kellogg Foundation: Using Logic models to bring together planning, evaluation, and action Logic model development guide, One East Michigan Avenue East Battle Creek, Michigan 49017-4058 (2004), http://www.wkkf.org (accessed September 2, 2012)

  52. Northcott, D., Taulapapa, T.M.: Using the balanced scorecard to manage performance in public sector organizations Issues and challenges. International Journal of Public Sector Management 25(3), 166–191 (2012)

    Article  Google Scholar 

  53. Anthoula, K., Alexandros, H.: Designing a balanced scorecard for the evaluation of a local authority organization European Research Studies XIV(2) (2011)

    Google Scholar 

  54. Farneti, F., Guthrie, J.: Italian and Australian local governments: balanced scorecard practices: A research note. Journal of Human Resource Costing & Accounting 12(1), 4–13 (2008)

    Article  Google Scholar 

  55. Neely, A., Adam, C., Kennerly, M.: The performance prism – the scorecard for measuring and managing business success. London Pearson Education Limited (2002)

    Google Scholar 

  56. Baldrige National Quality Program. Criteria for performance excellence. Administration Building, Gaithersburg (2007), http://www.baldrige.nist.gov (accessed November 18, 2011)

  57. Deng, Z., Wu, C., Zhang, J., Wang, J.: Study on the supply chain efficiency of rural public service in china based on three stage dea model. Asian Agricultural Research 69(1), 6–13 (2014)

    Google Scholar 

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kusrini, E., Subagyo, Masruroh, N.A. (2015). Combining Balanced Scorecard and Data Envelopment Analysis to Design Performance Measurement for Supply Chain Actor and Regulator: A Case Study in Innovative Product in Indonesia. In: Gen, M., Kim, K., Huang, X., Hiroshi, Y. (eds) Industrial Engineering, Management Science and Applications 2015. Lecture Notes in Electrical Engineering, vol 349. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47200-2_59

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  • DOI: https://doi.org/10.1007/978-3-662-47200-2_59

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