Skip to main content
SpringerLink
Log in

Fuzzy-based sustainability evaluation method for manufacturing SMEs using balanced scorecard framework

  • Published:
Journal of Intelligent Manufacturing Aims and scope Submit manuscript

Abstract

Sustainability has become a necessity, partly due to the threats created by traditional manufacturing practices, and due to regulations imposed by stakeholders. Performance evaluation is an important component of sustainability initiatives in manufacturing organizations. This study proposes a sustainability evaluation method for manufacturing SMEs using integrated fuzzy analytical hierarchal process (FAHP) and fuzzy inference system (FIS) approach. The performance indicators are identified from literature considering the characteristics of SMEs. Balanced scorecard framework is used to categorize the indicators among its four aspects. The linguistic variables are used to collect the opinions of decision makers about the performance ratings and importance of the aspects and corresponding indicators. The FAHP method is applied to determine the relative weights of measures and indicators. The performance ratings of the organization with respect to indicators and relative weights of indicators are combined to obtain the weighted performance ratings. The weighted performance ratings are considered as inputs to FIS. The hierarchal FIS is applied to derive the overall sustainability performance. Using a case study of manufacturing SME, the sustainability score of the organization was elicited in accordance with this procedure. Consequently, a sensitivity analysis of the proposed method reveals the most important basic indicators affecting overall sustainability, identifying areas which decision makers should place special attention. This method can also assist managers of larger enterprises to assess the effectiveness of their sustainability strategies, especially when dealing with suppliers from the SMEs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Abran, A., & Buglione, L. (2003). A multidimensional performance model for consolidating balanced scorecards. Advances in Engineering Software, 34(6), 339–349.

    Article  Google Scholar 

  • Addy, C., Pearce, J., & Bennet, J. (1994). Performance measures in small manufacturing enterprises; Are firms measuring what matters? In 10th National conference on manufacturing research (proceedings), 1994. Taylor & Francis, pp. 110–114.

  • Afghan, N. H., Darwish, M., & Carvalho, M. (1999). Sustainability assessment of desalination plants for water production. Desalination, 124, 19–31.

    Article  Google Scholar 

  • Agan, Y., Acar, M. F., & Borodin, A. (2013). Drivers of environmental processes and their impact on performance: A study of Turkish SMEs. Journal of Cleaner Production, 51, 23–33.

    Article  Google Scholar 

  • Alshawi, S., Missi, F., & Irani, Z. (2011). Organisational, technical and data quality factors in CRM adoption—SMEs perspective. Industrial Marketing Management, 40(3), 376–383. doi:10.1016/j.indmarman.2010.08.006.

    Article  Google Scholar 

  • Amindoust, A., Ahmed, S., Saghafinia, A., & Bahreininejad, A. (2012). Sustainable supplier selection: A ranking model based on fuzzy inference system. Applied Soft Computing, 12(6), 1668–1677. doi:10.1016/j.asoc.2012.01.023.

    Article  Google Scholar 

  • Asosheh, A., Nalchigar, S., & Jamporazmey, M. (2010). Information technology project evaluation: An integrated data envelopment analysis and balanced scorecard approach. Expert Systems with Applications, 37(8), 5931–5938.

    Article  Google Scholar 

  • Ayağ, Z., & Özdemir, R. (2006). A fuzzy AHP approach to evaluating machine tool alternatives. Journal of Intelligent Manufacturing, 17(2), 179–190.

    Article  Google Scholar 

  • Ayağ, Z., Samanlioglu, F., & Büyüközkan, G. (2013). A fuzzy QFD approach to determine supply chain management strategies in the dairy industry. Journal of Intelligent Manufacturing, 24(6), 1111–1122. doi:10.1007/s10845-012-0639-4.

    Article  Google Scholar 

  • Azadegan, A., Porobic, L., Ghazinoory, S., Samouei, P., & Saman Kheirkhah, A. (2011). Fuzzy logic in manufacturing: A review of literature and a specialized application. International Journal of Production Economics, 132(2), 258–270.

    Article  Google Scholar 

  • Baja, S., Chapman, D. M., & Dragovich, D. (2002). A conceptual model for defining and assessing land management units using a fuzzy modeling approach in GIS environment. Environmental Management, 29(5), 647–661. doi:10.1007/s00267-001-0053-8.

    Article  Google Scholar 

  • Bhagwat, R., & Sharma, M. K. (2007). Performance measurement of supply chain management: A balanced scorecard approach. Computers & Industrial Engineering, 53(1), 43–62.

    Article  Google Scholar 

  • Biondi, Vittorio, Frey, Marco, & Iraldo, Fabio. (2000). Environmental management systems and SMEs. Greener Management International, 2000(29), 55–69.

    Article  Google Scholar 

  • Boër, C. R., Sorlini, M., Bettoni, A., & Pedrazzoli, P. (2013). Mass customization and sustainability. New York: Springer.

    Book  Google Scholar 

  • Brundtland, G. (1987). Our common future: Report of the 1987 World Commission on Environment and Development. Oxford: Oxford University Press.

    Google Scholar 

  • Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 233–247.

    Article  Google Scholar 

  • Bullinger, H.-J., Kühner, M., & Van Hoof, A. (2002). Analysing supply chain performance using a balanced measurement method. International Journal of Production Research, 40(15), 3533–3543.

    Article  Google Scholar 

  • Butler, J. B., Henderson, S. C., & Raiborn, C. (2011). Sustainability and the balanced scorecard: Integrating green measures into business reporting. Management Accounting Quarterly, 12(2), 1–10.

    Google Scholar 

  • Carrera, D. A., & Mayorga, R. V. (2008). Supply chain management: A modular fuzzy inference system approach in supplier selection for new product development. Journal of Intelligent Manufacturing, 19(1), 1–12.

    Article  Google Scholar 

  • Carter, C. R., & Rogers, D. S. (2008). A framework of sustainable supply chain management: Moving toward new theory. International Journal of Physical Distribution & Logistics Management, 38(5), 360–387. doi:10.1108/09600030810882816.

    Article  Google Scholar 

  • Cebeci, U. (2009). Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard. Expert Systems with Applications, 36(5), 8900–8909.

    Article  Google Scholar 

  • Chan, F. T. S., & Qi, H. J. (2002). A fuzzy basis channel-spanning performance measurement method for supply chain management. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 216(8), 1155–1167. doi:10.1243/095440502760272421.

    Article  Google Scholar 

  • Cheng, C.-H. (1997). Evaluating naval tactical missile systems by fuzzy AHP based on the grade value of membership function. European Journal of Operational Research, 96(2), 343–350.

    Article  Google Scholar 

  • Chouikhi, H., Khatab, A., & Rezg, N. (2014). A condition-based maintenance policy for a production system under excessive environmental degradation. Journal of Intelligent Manufacturing, 25(4), 727–737. doi:10.1007/s10845-012-0715-9.

    Article  Google Scholar 

  • Ciliberti, F., Pontrandolfo, P., & Scozzi, B. (2008). Investigating corporate social responsibility in supply chains: A SME perspective. Journal of Cleaner Production, 16(15), 1579–1588. doi:10.1016/j.jclepro.2008.04.016.

    Article  Google Scholar 

  • Conner, J., Phillis, Y., & Manousiouthakis, V. (2009). A fuzzy logic global optimization approach to sustainability assessment. Paper presented at the AIChE Annual Meeting, Nashville, 8–13 November.

  • Csutora, R., & Buckley, J. J. (2001). Fuzzy hierarchical analysis: The Lambda–Max method. Fuzzy Sets and Systems, 120(2), 181–195.

  • Detyniecki, M., Bouchon-meunier, D. B., Yager, D. R., & Prade, R. H. (2000). Mathematical aggregation operators and their application to video querying. Doctoral Thesis-Research Report, Laboratoire d’Informatique de Paris.

  • Egilmez, G., Kucukvar, M., & Tatari, O. (2013). Sustainability assessment of U.S. manufacturing sectors: An economic input output-based frontier approach. Journal of Cleaner Production, 53, 91–102.

    Article  Google Scholar 

  • Epstein, M. J., & Wisner, P. S. (2001). Using a balanced scorecard to implement sustainability. Environmental Quality Management, 11(2), 1–10.

    Article  Google Scholar 

  • Erginel, N. (2010). Modeling and analysis of packing properties through a fuzzy inference system. Journal of Intelligent Manufacturing, 21(6), 869–874.

    Article  Google Scholar 

  • Fatimah, Y. A., Biswas, W., Mazhar, I., & Islam, M. N. (2013). Sustainable manufacturing for Indonesian small-and medium-sized enterprises (SMEs): The case of remanufactured alternators. Journal of Remanufacturing, 3(1), 1–11.

    Article  Google Scholar 

  • Fernandes, K. J., Raja, V., & Whalley, A. (2006). Lessons from implementing the balanced scorecard in a small and medium size manufacturing organization. Technovation, 26(5), 623–634.

    Article  Google Scholar 

  • Gokulachandran, J., & Mohandas, K. (2015). Comparative study of two soft computing techniques for the prediction of remaining useful life of cutting tools. Journal of Intelligent Manufacturing, 26(2), 255–268. doi:10.1007/s10845-013-0778-2.

    Article  Google Scholar 

  • Haapala, K. R., Zhao, F., Camelio, J., Sutherland, J. W., Skerlos, S. J., Dornfeld, D. A., et al. (2013). A review of engineering research in sustainable manufacturing. Journal of Manufacturing Science and Engineering, 135(4), 041013.

    Article  Google Scholar 

  • Hervani, A. A., Helms, M. M., & Sarkis, J. (2005). Performance measurement for green supply chain management. Benchmarking: An International Journal, 12(4), 330–353. doi:10.1108/14635770510609015.

    Article  Google Scholar 

  • Hillary, R. (2004). Environmental management systems and the smaller enterprise. Journal of Cleaner Production, 12(6), 561–569.

    Article  Google Scholar 

  • Hsieh, T.-Y., Lu, S.-T., & Tzeng, G.-H. (2004). Fuzzy MCDM approach for planning and design tenders selection in public office buildings. International Journal of Project Management, 22(7), 573–584.

    Article  Google Scholar 

  • Huang, C.-Y. (2015). Innovative parametric design for environmentally conscious adhesive dispensing process. Journal of Intelligent Manufacturing, 26(1), 1–12. doi:10.1007/s10845-013-0755-9.

    Article  Google Scholar 

  • Hudson, M., Lean, J., & Smart, P. (2001). Improving control through effective performance measurement in SMEs. Production Planning & Control, 12(8), 804–813.

    Article  Google Scholar 

  • Iqbal, A., Zhang, H.-C., Kong, L. L., & Hussain, G. (2013). A rule-based system for trade-off among energy consumption, tool life, and productivity in machining process. Journal of Intelligent Manufacturing, 1–16. doi:10.1007/s10845-013-0851-x.

  • ITA, D. o. C., United State. (2007). How does commerce define sustainable manufacturing? In D. o. Commerce (Ed.).

  • Jaffar, H., Venkatachalam, A., Joshi, K., Ungureanu, A., De Silva, N., Dillon, O, Jr, et al. (2007). Product design for sustainability: A new assessment methodology and case studies. In M. Kutz (Ed.), Handbook of environmentally conscious mechanical design (pp. 25–65). New York: Wiley.

    Chapter  Google Scholar 

  • Jakovljevic, Z., Petrovic, P. B., Mikovic, V. D., & Pajic, M. (2014). Fuzzy inference mechanism for recognition of contact states in intelligent robotic assembly. Journal of Intelligent Manufacturing, 25(3), 571–587.

    Article  Google Scholar 

  • Jassbi, J., Serra, P., Ribeiro, R., & Donati, A. (2006). A comparison of mandani and sugeno inference systems for a space fault detection application. In Automation congress, 2006. WAC’06. World, 2006. IEEE, pp. 1–8.

  • Joung, C. B., Carrell, J., Sarkar, P., & Feng, S. C. (2013). Categorization of indicators for sustainable manufacturing. Ecological Indicators, 24, 148–157. doi:10.1016/j.ecolind.2012.05.030.

    Article  Google Scholar 

  • Kaplan, R. S., & Norton, D. P. (1992). The balanced scorecard-measures that drive performance. Harvard Business Review, 70(1), 71–79.

    Google Scholar 

  • Kaplan, R. S., & Norton, D. P. (2001). Transforming the balanced scorecard from performance measurement to strategic management: Part I. Accounting Horizons, 15(1), 87–104.

    Article  Google Scholar 

  • Kemp, R. (1994). Technology and the transition to environmental sustainability—The problem of technological regime shifts. Futures, 26(10), 1023–1046. doi:10.1016/0016-3287(94)90071-X.

    Article  Google Scholar 

  • Kim, J., Suh, E., & Hwang, H. (2003). A model for evaluating the effectiveness of CRM using the balanced scorecard. Journal of Interactive Marketing, 17(2), 5–19.

    Article  Google Scholar 

  • Kommadath, B., Sarkar, R., & Rath, B. (2012). A fuzzy logic based approach to assess sustainable development of the mining and minerals sector. Sustainable Development, 20(6), 386–399. doi:10.1002/Sd.503.

    Article  Google Scholar 

  • Kouikoglou, V. S., & Phillis, Y. A. (2009). On the monotonicity of hierarchical sum-product fuzzy systems. Fuzzy Sets and Systems, 160(24), 3530–3538. doi:10.1016/j.fss.2009.02.001.

    Article  Google Scholar 

  • Kouloumpis, V., Kouikoglou, V., & Phillis, Y. (2008). Sustainability assessment of nations and related decision making using fuzzy logic. IEEE Systems Journal, 2(2), 224–236.

    Article  Google Scholar 

  • Kovac, P., Rodic, D., Pucovsky, V., Savkovic, B., & Gostimirovic, M. (2013). Application of fuzzy logic and regression analysis for modeling surface roughness in face milliing. Journal of Intelligent Manufacturing, 24(4), 755–762. doi:10.1007/s10845-012-0623-z.

    Article  Google Scholar 

  • KPMG international survey of corporate responsibility reporting (2013). http://www.kpmg.com/Global/en/IssuesAndInsights/ArticlesPublications/corporate-responsibility/Pages/default.aspx. Accessed November 05, 2014.

  • Labuschagne, C., Brent, A. C., & van Erck, R. P. G. (2005). Assessing the sustainability performances of industries. Journal of Cleaner Production, 13(4), 373–385. doi:10.1016/j.jclepro.2003.10.007.

    Article  Google Scholar 

  • Lee, A. H., Chen, W.-C., & Chang, C.-J. (2008). A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan. Expert Systems with Applications, 34(1), 96–107.

    Article  Google Scholar 

  • Lee, K.-H. (2009). Why and how to adopt green management into business organizations? The case study of Korean SMEs in manufacturing industry. Management Decision, 47(7), 1101–1121.

    Article  Google Scholar 

  • Lepoutre, J., & Heene, A. (2006). Investigating the impact of firm size on small business social responsibility: A critical review. Journal of Business Ethics, 67(3), 257–273.

    Article  Google Scholar 

  • Leung, L., Lam, K., & Cao, D. (2005). Implementing the balanced scorecard using the analytic hierarchy process & the analytic network process. Journal of the Operational Research Society, 57(6), 682–691.

    Article  Google Scholar 

  • Liberatore, M. J. (1987). An extension of the analytic hierarchy process for industrial R&D project selection and resource allocation. IEEE Transactions on Engineering Management, 1, 12–18.

    Article  Google Scholar 

  • Mamdani, E. H., & Assilian, S. (1975). An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, 7(1), 1–13.

    Article  Google Scholar 

  • Manville, G. (2007). Implementing a balanced scorecard framework in a not for profit SME. International Journal of Productivity and Performance Management, 56(2), 162–169.

    Article  Google Scholar 

  • Mon, D.-L., Cheng, C.-H., & Lin, J.-C. (1994). Evaluating weapon system using fuzzy analytic hierarchy process based on entropy weight. Fuzzy Sets and Systems, 62(2), 127–134.

    Article  Google Scholar 

  • Moore, S. B., & Manring, S. L. (2009). Strategy development in small and medium sized enterprises for sustainability and increased value creation. Journal of Cleaner Production, 17(2), 276–282. doi:10.1016/j.jclepro.2008.06.004.

    Article  Google Scholar 

  • OECD. (2011). OECD Sustainable Manufacturing Toolkit. http://www.oecd.org/innovation/green/toolkit/

  • Olugu, E. U., Wong, K. Y., & Shaharoun, A. M. (2011). Development of key performance measures for the automobile green supply chain. Resources Conservation and Recycling, 55(6), 567–579. doi:10.1016/j.resconrec.2010.06.003.

    Article  Google Scholar 

  • Ordoobadi, S. M. (2009). Development of a supplier selection model using fuzzy logic. Supply Chain Management: An International Journal, 14(4), 314–327.

    Article  Google Scholar 

  • Phillis, Y. A., & Davis, B. J. (2009). Assessment of corporate sustainability via fuzzy logic. Journal of Intelligent & Robotic Systems, 55(1), 3–20. doi:10.1007/s10846-008-9289-3.

    Article  Google Scholar 

  • Rachuri, S., Sriram, R. D., & Sarkar, P. (2009). Metrics, standards and industry best practices for sustainable manufacturing systems. IEEE International Conference on Automation Science and Engineering, 2009, 472–477. doi:10.1109/Coase.2009.5234090.

    Google Scholar 

  • Ravi, V., Shankar, R., & Tiwari, M. (2005). Analyzing alternatives in reverse logistics for end-of-life computers: ANP and balanced scorecard approach. Computers & Industrial Engineering, 48(2), 327–356.

    Article  Google Scholar 

  • Reich-Weiser, C., Vijayaraghavan, A., & Dornfeld, D. A. (2009). Metrics for sustainable manufacturing. In Msec 2008: Proceedings of the ASME international manufacturing science and engineering conference 2008, Vol. 1, pp. 327–335.

  • Saaty, T., & Vargas, L. L. G. (2001). Models, methods, concepts, and applications of the analytic hierarchy process (Vol. 34). New York: Springer.

    Book  Google Scholar 

  • Saaty, T. L. (1980). The analytical hierarchical process. New York: Wiley.

    Google Scholar 

  • Schau, E. M., & Fet, A. M. (2011). Assessing the ecological soundness of organic and conventional agriculture by means of life cycle assessment (LCA) - a case study of leek production (vol 111, pg 1028, 2009). British Food Journal, 113(6–7), 809–809.

  • Seuring, S., & Muller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16(15), 1699–1710. doi:10.1016/j.jclepro.2008.04.020.

    Article  Google Scholar 

  • Singh, S., Olugu, E. U., & Fallahpour, A. (2014). Fuzzy-based sustainable manufacturing assessment model for SMEs. Clean Technologies and Environmental Policy, 16(5), 847–860.

  • Singh, S., Olugu, E. U., Musa, S. N., & Mahat, A. B. (2014). Proposition of key performance measures for sustainable manufacturing in SMEs. Paper presented at the MSME conclave cum conference on sustainable supply chain capabilities of micro, small and medium enterprises: Influences, practices, training needs and employment opportunities, Doon University, Dehradun, 10th May 2014.

  • Solvang, W. D., Romàn, E., Deng, Z., & Solvang, B. (2006). A framework for holistic greening of value chains. In Knowledge enterprise: Intelligent strategies in product design, manufacturing, and management. Springer, pp. 350–355

  • Tanzil, D., & Beloff, B. R. (2006). Assessing impacts: Overview on sustainability indicators and metrics. Environmental Quality Management, 15(4), 41–56. doi:10.1002/tqem.20101.

  • Ticehurst, J. L., Newham, L. T. H., Rissik, D., Letcher, R. A., & Jakeman, A. J. (2007). A Bayesian network approach for assessing the sustainability of coastal lakes in New South Wales. Australia. Environmental Modelling & Software, 22(8), 1129–1139. doi:10.1016/j.envsoft.2006.03.003.

    Article  Google Scholar 

  • Tseng, M.-L. (2010). Implementation and performance evaluation using the fuzzy network balanced scorecard. Computers & Education, 55(1), 188–201.

    Article  Google Scholar 

  • Varma, S., Wadhwa, S., & Deshmukh, S. (2008). Evaluating petroleum supply chain performance: Application of analytical hierarchy process to balanced scorecard. Asia Pacific Journal of Marketing and Logistics, 20(3), 343–356.

    Article  Google Scholar 

  • Vinodh, S., & Balaji, S. (2011). Fuzzy logic based leanness assessment and its decision support system. International Journal of Production Research, 49(13), 4027–4041.

    Article  Google Scholar 

  • Vinodh, S., Jayakrishna, K., & Joy, D. (2012). Environmental impact assessment of an automotive component using eco-indicator and CML methodologies. Clean Technologies and Environmental Policy, 14(2), 333–344. doi:10.1007/s10098-011-0405-x.

    Article  Google Scholar 

  • Vinodh, S., Varadharajan, A. R., & Subramanian, A. (2013). Application of fuzzy VIKOR for concept selection in an agile environment. International Journal of Advanced Manufacturing Technology, 65(5–8), 825–832.

    Article  Google Scholar 

  • Williamson, D., Lynch-Wood, G., & Ramsay, J. (2006). Drivers of environmental behaviour in manufacturing SMEs and the implications for CSR. Journal of Business Ethics, 67(3), 317–330.

    Article  Google Scholar 

  • Won, J. M., Park, S. Y., & Lee, J. S. (2002). Parameter conditions for monotonic Takagi–Sugeno–Kang fuzzy system. Fuzzy Sets and Systems, 132(2), 135–146. doi:10.1016/S0165-0114(02)00121-5.

    Article  Google Scholar 

  • Wu, H.-Y., Tzeng, G.-H., & Chen, Y.-H. (2009). A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard. Expert Systems with Applications, 36(6), 10135–10147.

    Article  Google Scholar 

  • Zhang, L. F. (2007). On the assessment of petroleum corporation’s sustainability based on linguistic fuzzy method. In Computational science—ICCS 2007, Pt 1, proceedings, Vol. 4487, pp. 562–566.

Download references

Acknowledgments

This study is supported by University of Malaya Research Grant (RG138-12AET). We thank reviewers for their comments which have helped to improve the quality of our manuscript.

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia

    Sujit Singh, Ezutah Udoncy Olugu, Siti Nurmaya Musa & Abu Bakar Mahat

Authors
  1. Sujit Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ezutah Udoncy Olugu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Siti Nurmaya Musa
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Abu Bakar Mahat
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ezutah Udoncy Olugu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Singh, S., Olugu, E.U., Musa, S.N. et al. Fuzzy-based sustainability evaluation method for manufacturing SMEs using balanced scorecard framework. J Intell Manuf 29, 1–18 (2018). https://doi.org/10.1007/s10845-015-1081-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10845-015-1081-1

Keywords

Search

Navigation