Skip to main content
SpringerLink
Log in

Techniques and Attributes Used in the Supply Chain Performance Measurement: Tendencies

  • Chapter
  • First Online:
Book cover Lean Manufacturing in the Developing World

Abstract

The evaluation and performance measurement in supply chain (SC) is a key element in modern business competitiveness and it is an activity extremely important for improve its process, practices and common goals. The purpose of this chapter is to present a statistical analysis based in a literature review related to supply chain tendencies that includes 95 chapters published from January 2000 to June 2012. This research identifies the techniques and methodologies used in the supply chain performance evaluation process, and attributes most commonly evaluated as well as the industrial sector and regions where the solutions were applied, and finally the journals where they were published. The results show that multivariate analysis is the most important and frequent methodology for study supply chain performance, looking to find variables relations and association among them. Also, the finds indicate that most evaluated attributes in supply chain performance are the delivery, information flow and processes activities. The most important research groups that are investigating this area are located in Unites States of America, Taiwan and United Kingdom.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Abu-Suleiman, A., Boardman, B. & Priest, J. (2004). A framework for an integrated Supply Chain Performance Management System. Industrial Engineering research Conference. University of Texas Arlington, Arlington, TX.

    Google Scholar 

  • Agarwal, A., Shankar, R., Tiwari, M. K. (2006). Modeling the metrics of lean, agile and leagile supply chain: An ANP-based approach. European Journal of Operational Research, 173, 211–225.

    Google Scholar 

  • Akkermans, H. A., Bogerd, P., Yücesan, E., & van Wassenhove, L. N. (2003). The impact of ERP on supply chain management: Exploratory findings from a European Delphi study. European Journal of Operational Research, 146, 284–301.

    Google Scholar 

  • Arlbjørn, J. S., & Lüthje, T. (2012). Global operations and their interaction with supply chain performance. Industrial Management & Data Systems, 112(7), 1044–1064.

    Google Scholar 

  • Arun Kanda, A., & Deshmukh, S. G. (2008). Supply chain coordination: Perspectives, empirical studies and research directions. International Journal of Productions Economics, 115, 316–335.

    Article  Google Scholar 

  • Askarany, D., Yazdifar, H., & Askary, S. (2010). Supply chain management, activity-based costing and organizational factors. International Journal of Production Economics, 127, 238–248.

    Article  Google Scholar 

  • Autry, C. W., Grawe, S. J., Daugherty, P. J., & Richey, R. G. (2010). The effects of technological turbulence and breath on supply chain technology acceptance and adoption. Journal of Operations Management, 28, 522–536.

    Article  Google Scholar 

  • Babak, J. N., & Saeid, I. (2012). Analyzing effective elements in agile supply chain. Management Science Letters, 24, 369–378.

    Google Scholar 

  • Bhatnagar, R., & Sohal, A. S. (2005). Supply chain competitiveness: Measuring the impact of location factors, uncertainty and manufacturing practices. Technovation, 25(5), 443–456.

    Google Scholar 

  • Blome, C., & Schoenherr, T. (2011). Supply chain risk management in financial crises: A multiple case-study approach. International Journal of Productions Economics, 134(1), 43–57.

    Article  Google Scholar 

  • Boddy, D., Cahill, C., Charles, M., Fraser-Kraus, H., & Macbeth, D. (1998). Success and failure in implementing supply chain partnering an empirical study. European Journal of Purchasing and Supply Management, 4(1), 143–151.

    Google Scholar 

  • Büyüközkan, G., & Vardaloglu, Z. (2012). Analyzing CPFR success factors using fuzzy cognitive maps in retail industry. Expert Systems with Applications, 39(12), 10438–10455.

    Google Scholar 

  • Cambra-Fierro, J. J., & Polo-Redondo, Y. (2011). Post-satisfaction factors effecting the long-term orientation of supply relationships. Journal of Business and Industrial Marketing, 26(6), 395–406.

    Article  Google Scholar 

  • Cannella, S., Ciancimino, E., Framian, J. M., & Disney, S. M. (2010). The four arquetypes in supply chain. Universia Business Review, Second quarter, (26), 134–149, Universia Portal, Spain (In Spanish).

    Google Scholar 

  • Caniato, F., Golini, R., & Kalchschmidt, M. (2013). The effect of global supply chain configuration on the relationship between supply chain improvement programs and performance. International Journal of Production Economics, 143(2), 285–293.

    Article  Google Scholar 

  • Cedillo, M. G., Sánchez, J., & Sánchez, C. (2006). The new relational schemas of inter-firms cooperation: The case of the Coahuila automobile cluster in Mexico. International Journal Automotive Technology and Management, 6(4), 406–418.

    Article  Google Scholar 

  • Cedillo, M. G., & Sánchez, C. (2008). Dynamic analysis of industrial systems. Mexico: In Spanish. Trillas Publishers.

    Google Scholar 

  • Cedillo, M. G., & Pérez, A. (2010). Hybrid supply chains in emerging markets the case of the Mexican auto industry. South African Journal of Industrial Engineering, 21(1), 193–206.

    Google Scholar 

  • Chan, F. T. S. (2003). Performance measurement in a Supply Chain. International Journal Advanced Manufacturing of Technology, 21, 534–548.

    Google Scholar 

  • Chen, D. C., Rajkumar, T. M., & Tomochko, N. A. (2011). The antecedent factors on trust and commitment in supply chain relationships. Computer Standards & Interfaces, 33, 262–270.

    Google Scholar 

  • Chen, T., & Gong, X. (2013). Performance evaluation of a supply chain network. Procedia Computer Science, 17, 1003–1009.

    Article  Google Scholar 

  • Chen, J. V., Yen, D. C., & Tomochko, N. A. (2011). The antecedent factors on trust and commitment in supply chain relationships. Computers Standards and Interfaces, 33, 262–270.

    Article  Google Scholar 

  • Chen, C., & Yan, H. (2011). Network DEA model for supply chain performance evaluation. European Journal of Operational Research, 213(1), 147–155.

    Article  MATH  MathSciNet  Google Scholar 

  • Cho, D. W., Lee, Y. H., Ahn, S. H., & Hwang, M. K. (2012). A framework for measuring the performance of service supply chain management. Computers and Industrial Engineering, 62(3), 801–818.

    Google Scholar 

  • Choi, S. (2010). Key success factor of supply chain relationships: multiple case studies in China from buyer’s and supplier’s perspective. Master Thesis, University of Gävle, Sweden.

    Google Scholar 

  • Chong, A. Y., Ooi, K., & Sohal, A. (2009). The relationship between supply chain factors and adoption of e-collaboration tools: An empirical examination. International Journal of Production Economics, 122(1), 150–160.

    Google Scholar 

  • Cirtita, H., & Glaser-Segura, D. A. (2012). Measuring downstream supply chain performance. Journal of Manufacturing Technology Management, 23(3), 299–314.

    Article  Google Scholar 

  • Cruz, J. M. (2009). The impact of corporate social responsibility in supply chain management: Multicriteria decisión-making approach. Decision Support Systems, 48(1), 224–236.

    Article  Google Scholar 

  • Cruz, J. M. (2013). Modeling the relationship of globalized supply chains and corporate social responsibility. Journal of Cleaner Production, 56(October), 73–85.

    Article  Google Scholar 

  • Cunha, V., & Zwicker, R. (2009). The forerunners of relationship and performance in supply chain companies: Structuring and applying structural equations. RAE: Revista de Administração de Empresas, 49(2), 147–161, (in Portuguese).

    Google Scholar 

  • DaeSoo, K. (2006). Process chain: A new paradigm of collaborative commerce and synchronized supply chain. Kelly School of Business, 49(5), 359–367.

    Google Scholar 

  • De Giovanni, P., & Esposito Vinzi, V. (2012). Covariance versus component-based estimations of performance in green supply chain management. International Journal of Production Economics, 135(2), 907–916.

    Article  Google Scholar 

  • Díaz M. A., & Pérez, C. C. (2002). Logistics practices in Venezuela an exploratory study. Working paper, Enterprise Institute, Madrid.

    Google Scholar 

  • Dorling, K., Scott, J., & Deakins, E. (2006). Determinants of successful vendor managed inventory relationships in oligopoly industries. International Journal of Physical Distribution and Logistics Management, 36(3), 176–191.

    Article  Google Scholar 

  • Droge, C., Vickery, S. K., & Jacobs, M. (2012). Does supply chain integration mediate the relationships between product/process strategy and service performance? An empirical study. International Journal of Production Economics, 137(2), 250–262.

    Article  Google Scholar 

  • Elgazzar, S. H., Tipi, N. S., Hubbard, N. J., & Leach, D. Z. (2012). Linking supply chain processes’ performance to a company’s financial strategic objectives. European Journal of Operational Research, 223(1), 276–289.

    Article  Google Scholar 

  • Falk, H., & Hogström, L. (2000). Key success factors for a functioning supply chain in e-commerce B2B. Master Thesis, Göteborg University, Sweden.

    Google Scholar 

  • Fawcett, S. E., Magnan, G. M., & McCarter, M. W. (2006). Benefits, barriers, and bridges to effective supply chain management. Supply Chain Management: an International Journal, 13(1), 35–48.

    Article  Google Scholar 

  • Feng, Y. (2012). System dynamics modeling for supply chain information sharing. Physics Procedia, 25, 1463–1469.

    Article  Google Scholar 

  • Forrester, J. W. (1961). Industrial Dynamics. Portland (Or): Productivity Press.

    Google Scholar 

  • Forslund, H., & Jonsson, P. (2007). The impact of forecast information quality on supply chain performance. International Journal of Operations and Production Management, 27(1), 90–107.

    Article  Google Scholar 

  • Gallear, D., Ghobadian, A., & Chen, W. (2012). Corporate responsibility, supply chain partnership and performance: An empirical examination. International Journal of Production Economics, 140(1), 83–91.

    Article  Google Scholar 

  • Green, JR., K. W., & Inman, R. A. (2005). Using a just in time selling strategy to strengthen supply chain linkages. International Journal of production Research, 43(16), 3437–3453.

    Google Scholar 

  • Green JR., K. W., Whitten, D., & Inman, R. A. (2012). Aligning marketing strategies throughout the supply chain to enhance performance. Industrial Marketing Management, 41(6), 1008–1018.

    Article  Google Scholar 

  • Guiffrida, A. L., & Nagi, R. (2006). Cost characterizations of supply chain delivery performance. International Journal of Production Economics, 102(1), 22–36.

    Article  Google Scholar 

  • Gunasekaran, A., Patel, C., & Tirtiroglu, E. (2001). Performance measures and metrics in a supply chain environment. International Journal of Operations and Production Management, 21(1,2), 71–87.

    Article  Google Scholar 

  • Gunasekaran, A., Patel, C., & McGauhhey, R. E. (2004). A framework for supply chain performance measurement. International Journal of Productions Economics, 87(3), 333–347.

    Article  Google Scholar 

  • Gunasekaran, A., & Ngai, E. W. T. (2004). Virtual supply chain management. Production Planning and Control, 15(6), 584–595.

    Article  Google Scholar 

  • Gunasekaran, A., & Ngai, E. W. T. (2009). Modeling and analysis of built-to-order supply chains. European Journal of Operational Research, 195(2), 319–334.

    Article  MATH  MathSciNet  Google Scholar 

  • Haytko, D. L., & Kent, J. L. (2007). Mexican maquiladoras: helping or hurting the US/Mexico cross-border supply chain? The International Journal of Logistics Management, 18(3), 347–363.

    Article  Google Scholar 

  • Huang, M., Yang, M., Zhang, Y., & Liu, B. (2012). System dynamics modeling-based study of contingent sourcing under supply discruptions. Systems Engineering Procedia, 4, 290–297.

    Article  Google Scholar 

  • Hishamuddin, H., Sarker, R. A., & Essam, D. (2013). Recovery model for a two-echelon serial supply chain with consideration of transportation disruption. Computers and Industrial Engineering, 64(2), 552–561.

    Article  Google Scholar 

  • Hui, L., & Nuo, L. (2011). System dynamics modeling and simulation of multi-stage supply chain: The value of information sharing. Energy Procedia, 13, 4861–4867.

    Article  Google Scholar 

  • Ip, W. H., Chan, S. L., & Lam, C. Y. (2011). Modeling supply chain performance and stability. Industrial Management and Data Systems, 111(8), 1332–1354.

    Article  Google Scholar 

  • Janvier-James, A. M. (2012). A new introduction to supply chains and supply chain management: Definitions and theories perspective. International Business Research, 5(1), 194–207.

    Google Scholar 

  • Jeong, J. S., & Hong, P. (2007). Customer orientation and performance outcomes in supply chain management. Journal of Enterprise Information Management, 20(5), 578–594.

    Article  Google Scholar 

  • Jiménez, J. E. (2004). Critical success factors in supply chain (Technique Publication No. 237). Mexican Institute of Transport, Sanfandila, Querétaro, Mexico.

    Google Scholar 

  • Jiménez J. E., & Hernández, S. (2002). Conceptual framework of the supply chain: A new logistics focus (Technique Publication No. 215). Mexican Institute of Transport, Sanfandila, Querétaro, Mexico.

    Google Scholar 

  • Kannan, V. R., & Tan, K. C. (2010). Supply chain integration: cluster analysis of the impact of span of integration. Supply Chain Management: an International Journal, 15(3), 207–215.

    Article  Google Scholar 

  • Khaji, M., & Shafaei, R. (2011). A system dynamics approach for strategic partnering in supply networks. International Journal of Computer Integrated Manufacturing, 24(2), 106–125.

    Article  Google Scholar 

  • Kim, D., Cavusgil, S. T., & Cavusgil, E. (2013). Does IT alignment between supply chain partners enhance customer value creation? An empirical investigation. Industrial Marketing Management, 42(6), 880–889.

    Article  Google Scholar 

  • Kisperska-Morón, D. (2011). Virtual logistics as a support for the decomposition process of supply chain (conceptual reflections). Scientific Journal of Logistics, 7(5), 49–60.

    Google Scholar 

  • Kroes, J. R. (2007). Outsourcing of supply chain processes: Evaluating the impact of congruence between outsourcing drivers and competitive priorities on performance. PhD. Thesis, Georgia Institute of Technology, United States of America.

    Google Scholar 

  • Kumar, S., McCreary, M. L., & Nottestad, D. A. (2011). Quantifying supply chain trade-offs using six sigma, simulation, and designed experiments to develop a flexible distribution network. Quality Engineering, 23(2), 180–203.

    Article  Google Scholar 

  • Laosirihongthog, T., Punnakitikashem, P., & Adebanjo, D. (2011). Improving supply chain operations by adopting RFID technology: Evaluation and comparison of enabling factors. Production Planning and Control, 1, 1–20.

    Google Scholar 

  • Lassar, W., Haar, J., Montalvo, R., & Hulser, L. (2010). Determinants of strategic risk management in emerging markets supply chain: Case of Mexico. Journal of Economics, Finance and Administrative Science, 15(28), 25–140.

    Google Scholar 

  • Le Dain, M., Calvi, R., & Cheriti, S. (2010). Measuring supplier performance in collaborative design: Proposition of a framework. R&D Management, 41(1), 61–79.

    Article  Google Scholar 

  • Lee, M. S., & Lee, S. (2012). Success factors of open-source enterprise information systems development. Industrial Management & Data Systems, 112(7), 1065–1084.

    Google Scholar 

  • Lin, C., Wing, S., Madu, C. N., Kuei, C., & Yu, P. (2005). A structural equation model of supply chain quality management and organizational performance. International Journal of Productions Economics, 96(3), 355–365.

    Article  Google Scholar 

  • Lin, R., Chen, R., & Nguyen, T. (2011). Green supply chain management performance in automobile manufacturing industry under uncertainty. Procedia-Social and Behavioral Sciences, 25, 233–245.

    Google Scholar 

  • Lin, Y., Wang, Y., & Yu, C. (2010). Investigating the drivers of the innovation in cannel integration and supply chain performance: A strategy orientated perspective. International Journal of Productions Economics, 127(2), 320–332.

    Article  Google Scholar 

  • Lockamy, A, I. I. I., & McCormack, K. (2004). Linking SCOR planning practices to supply chain performance: An exploratory study. International Journal of Operations and Production Management, 24(12), 1192–1218.

    Article  Google Scholar 

  • Lu, X., Huang, L., & Heng, M. S. H. (2006). Critical success factors of inter-organizational information systems: A case study of Cisco and Xiao Tong in China. Information and Management, 43(3), 395–408.

    Article  Google Scholar 

  • Lu, C., Lai, K., & Chen, T. C. E. (2007). Application of structural equation modeling to evaluate the intention of shippers to use internet services in linear shipping. European Journal of Operational Research, 180(2), 845–867.

    Article  MATH  Google Scholar 

  • McCormack, K., Bronzo, M. L., & Valadares, M. P. (2008). Supply chain maturity and performance in Brazil. Supply Chain Management: An International Journal, 13(4), 272–282.

    Article  Google Scholar 

  • Meixell, M. J., & Gargeya, V. B. (2005). Global supply chain design: A literature review and critique. Transportation Research Part E, 41(6), 531–550.

    Article  Google Scholar 

  • Mendoza, E. (2007). Uncertainty, integration and supply flexibility. PhD. Thesis, Universitat Pompeu Fabra, Department of Economics and Business, Barcelona, Catalonia, Spain.

    Google Scholar 

  • Merschmann, U., & Thonemann, U. W. (2011). Supply chain flexibility, uncertainty and form performance: An empirical analysis of German manufacturing firms. International Journal of Productions Economics, 130(1), 43–53.

    Article  Google Scholar 

  • Nath, T., & Standing, C. (2010). Drivers of information technology use in the supply chain. Journal of Systems and Information Technology, 12(1), 70–84.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • Otto, A., & Kotzab, H. (2003). Does supply chain management really pay? Six perspectives to measure the performance of managing a supply chain. European Journal of Operational Research, 144(2), 306–320.

    Article  MATH  Google Scholar 

  • Özdemir, A. I., & Aslan, E. (2011). Supply chain integration, competition capability and business performance: A study on Turkish SMEs. Asian Journal of Business Management, 3(4), 325–332.

    Google Scholar 

  • Papageorgiou, L. G. (2009). Supply chain optimization for the process industries: Advances and opportunities. Computers and Chemical Engineering, 33(12), 1931–1938.

    Article  Google Scholar 

  • Perotti, S., Zorzini, M., Cagno, E., & Micheli, G. J. L. (2012). Green supply chain practices and company performance: the case of 3PLs in Italy. International Journal of Physical Distribution and Logistics Management, 42(7), 640–672.

    Article  Google Scholar 

  • Persson, F. (2011). SCOR template: A simulation based dynamic supply chain analysis tool. International Journal of Production Economics, 131(1), 288–294.

    Article  Google Scholar 

  • Power, D. (2005). Supply chain management integration and implementation: A literature review. Supply Chain Management: an International Journal, 10(4), 252–263.

    Article  MathSciNet  Google Scholar 

  • Quesada, H., & Gazo, R. (2007). Methodology for determining key internal business processes based on critical success factors. Business Process Management Journal, 13(1), 5–20.

    Article  Google Scholar 

  • Ramanathan, U. (2014). Performance of supply chain collaboration—a simulation study. Expert Systems with Applications, 41(1), 210–220.

    Article  Google Scholar 

  • Ramanathan, U., & Gunasekaran, A. (2014). Supply chain collaboration: Impact of success in long-term partnerships. International Journal of Production Economics,147 (Part B), 252–259.

    Google Scholar 

  • Ranganathan, C., Teo, T. S. H., & Dhaliwal, J. (2011). Web-enabled supply chain management: Key antecedents and performance impacts. International Journal of Information Management, 31(6), 533–545.

    Article  Google Scholar 

  • Revilla, E., & Sáenz, M. J. (2013). Supply chain disruption management: Global convergence versus national specificity. Journal of Business Research, (in press), Corrected Proof.

    Google Scholar 

  • Ribas, I., & Companys, R. (2007). Estado del arte de la planificación colaborativa en la cadena de suministro: contexto determinista e incierto. Intangible capital, 3(003), ISSN: 1697-9818, Universitat Politecnica de Catalunya.

    Google Scholar 

  • Ryu, I., So, S., & Koo, C. (2009). The role of partnership in supply chain performance. Industrial Management and Data Systems, 109(4), 496–514.

    Article  Google Scholar 

  • Sánchez, C., Cedillo, M. G., & Piña, M. R. (2007). Model for dynamic analysis of industrial clusters: the case of supply chain in the automotive clusters in the southeast region of Coahuila. International Conference on Industrial Engineering. Proceedings of the 13th Annual.

    Google Scholar 

  • Sánchez, C., Cedillo, M. G., & Pérez, V. P. (2008). Sensitivity analysis of the impact of inventory and cycle time on performance of the automotive supply chain. International Conference on Industrial Engineering. Proceedings of the 13th Annual.

    Google Scholar 

  • Santos, J. C. (2010). http://ciclog.blogspot.mx/2010/11/decisiones-el-flujo-escondido-en-la.html. Accessed 15 May 2012.

  • Sarimveis, H., Patrinos, P., Tarantilis, C. D., & Kiranoudis, C. T. (2008). Dynamic modeling and control of supply chain systems: a review. Computers and Operations Research, 35(11), 3530–3561.

    Article  MATH  Google Scholar 

  • SCC, (2010). SCOR model. http://www.SupplyChain.org. Accessed 20 June 2012.

  • Schliephake, K., Stevens, G., & Clay, S. (2009). Making resources work more efficiently—the importance of supply chain partnerships. Journal of Cleaner Production, 17(14), 1257–1263.

    Article  Google Scholar 

  • Schmitt, A., & Singh, M. (2012). A quantitative analysis of disruption risk in a multi-echelon supply chain. International Journal of Production Economics, 139(1), 22–32.

    Article  Google Scholar 

  • Schotanus, F., Telgen, J., & de Boer, L. (2010). Critical success factors for managing purchasing groups. Journal of Purchasing and Supply Management, 16(1), 51–60.

    Article  Google Scholar 

  • Singh, R., Singh, S. H., Metri, B. A., & Kaur, R. (2011). Organizational performance and retail challenges: A structural equation approach. Scientific Research, 3, 159–168.

    Google Scholar 

  • Soin, S. S. (2004). Critical success factors in supply chain management at high technology companies. PhD. Thesis, University of Southern Queensland, Australia.

    Google Scholar 

  • Su, Y., & Yang, C. (2010a). A structural equation model for analyzing the impact of ERP on SCM. Expert Systems with Applications, 37(1), 456–469.

    Article  Google Scholar 

  • Su, Y., & Yang, C. (2010b). Why are enterprise resource planning systems indispensable to supply chain management? European Journal of Operational Research, 203(1), 81–94.

    Article  MathSciNet  Google Scholar 

  • Surana, A., Kumara, S., Greaves, M., & Raghavan, N. (2005). Supply chain networks: A complex adaptive system perspective. International Journal of Production Research, 43(20), 4235–4265.

    Google Scholar 

  • Swafford, P. M., Ghosh, S., & Murthy, N. (2006). The antecedents of supply chain agility of a firm: scale development and model testing. Journal of Operations Management, 24(2), 170–188.

    Article  Google Scholar 

  • Świerczek, A. (2013). The impact of supply chain integration on the “snowball effect” in the transmission of disruptions: An empirical evaluation of the model. International Journal of Production Economics, (in press), Corrected Proof.

    Google Scholar 

  • Tang, O., & Musa, N. (2011). Identifying risk and research advancements in supply chain risk management. International Journal of Production Economics, 133(1), 25–34.

    Article  Google Scholar 

  • Teller, C., Kotzab, H., & Grant, D. B. (2012). Improving the execution of supply chain management in organizations. International Journal of Production Economics, 140(2), 713–720.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Thomassey, S. (2010). Sales forecasts in clothing industry: The key success factor of the supply chain management. International Journal of Productions Economics, 128(2), 470–483.

    Article  Google Scholar 

  • Vilko, J. P. P., & Hallikas, J. M. (2012). Risk assessment in multimodal supply chains. International Journal of Production Economics, 140(2), 586–595.

    Article  Google Scholar 

  • Vlachos, I. P. (2014). A hierarchical model of the impact of RFID practices on retail supply chain performance. Expert Systems with Applications, 41(1), 5–15.

    Article  Google Scholar 

  • Whitten, G. D., Green, K. W, Jr, & Zelbst, P. J. (2012). Triple-A supply chain performance. International Journal of Operations and Production Management, 32(1), 28–48.

    Article  Google Scholar 

  • Wiengarten, F., Pagell, M., & Fynes, B. (2012). Supply chain environmental investments in dynamic industries: Comparing investment and performance differences with static industries. International Journal of Production Economics, 135(2), 541–551.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Wu, T., Blackhurst, J., & Chidambaram, V. (2006). A model for inbound supply risk analysis. Computers in Industry, 57(4), 350–365.

    Article  Google Scholar 

  • Youn, S., Yang, M. G., & Hong, P. (2012). Integrative leadership for effective supply chain implementation: An empirical study of Korean Firms. International Journal of Production Economics, 139(1), 237–246.

    Google Scholar 

  • Young, R. R., & Esqueda, P. (2005). Supply chain vulnerability: Considerations of the case of latin America. Revista Latinoamerican of Administration Journal, 34, 63–77.

    Google Scholar 

  • Yu, W., Jacobs, M., Salisbury, W., & Enns, H. (2013). The effects of supply chain integration on customer satisfaction and financial performance: An organizational learning perspective. International Journal of Production Economics, 146(1), 346–358.

    Article  Google Scholar 

  • Zhang, C., & Dhaliwal, J. (2009). An investigation of resource-based and institutional theoretic factors in technology adoption for operations and supply chain management. International Journal of Productions Economics, 120(1), 252–269.

    Article  Google Scholar 

  • Zhou, H., B.S., M.S., M.A. (2003). The role of supply chain processes and information sharing in supply chain management. PhD. Thesis. The Ohio State University, United States of America.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Engineering and Technology, Autonomous University of Ciudad Juarez, Av. del Charro 450 Norte. Col. Partido Romero, 32315, Ciudad Juárez, Chihuahua, Mexico

    Liliana Avelar-Sosa & Jorge Luis García-Alcaraz

  2. Department of Logistics and Supply Chain Management, Autonomous University of Nuevo Leon, Av. Universidad s/n. Ciudad Universitaria, 6645, San Nicolás de los Garza, Nuevo León, Mexico

    Miguel Gastón Cedillo-Campos

Authors
  1. Liliana Avelar-Sosa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jorge Luis García-Alcaraz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Miguel Gastón Cedillo-Campos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Liliana Avelar-Sosa .

Editor information

Editors and Affiliations

  1. Departamento de Ingeniería Industrial y Manufactura, Instituto de Ingeniería y Tecnología Universidad Autónoma de Ciudad Juárez, Chihuahua, Mexico

    Jorge Luis García-Alcaraz

  2. Avenue Del Charro, Autonomous University of Ciudad Juarez, Chihuahua, Mexico

    Aidé Aracely Maldonado-Macías

  3. Institute of Technology of Orizaba Av. Instituto Tecnologico, Orizaba, Mexico

    Guillermo Cortes-Robles

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Avelar-Sosa, L., García-Alcaraz, J.L., Cedillo-Campos, M.G. (2014). Techniques and Attributes Used in the Supply Chain Performance Measurement: Tendencies. In: García-Alcaraz, J., Maldonado-Macías, A., Cortes-Robles, G. (eds) Lean Manufacturing in the Developing World. Springer, Cham. https://doi.org/10.1007/978-3-319-04951-9_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-04951-9_25

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04950-2

  • Online ISBN: 978-3-319-04951-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation