Skip to main content
SpringerLink
Log in

Impact of traditional and international logistic policies in supply chain performance

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

Mexican maquiladoras (Mexican export processing plants) are focused on exportation activities, and have several processes derived from policies related to procurement and inventory that are established by each company. This paper analyzed 17 activities related to supply chain (SC) policies and grouped them into four independent latent variables: (1) traditional logistics, (2) international logistics, (3) supply, and (4) inventories. Moreover, the impact of these policies was analyzed on ten benefits and was eventually grouped into three dependent latent variables. In order to analyze the relationship among these latent variables and to generate a measurement model, a survey was conducted in 63 exportation Mexican maquiladoras located in Ciudad Juarez, Chihuahua. Twelve hypotheses about the relationships among latent variables were then generated in order to determine the causal relationships. Finally, the hypotheses were integrated in a structural equation model (SEM) and tested using partial least squares technique that is integrated in WarpPLS® software. The obtained results indicated that traditional logistics policies have a direct impact on the inventory, international logistics, and supply variables. This impact allows for greater efficiency in the supply chain, better economic performance, and more satisfied customers.

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

Similar content being viewed by others

References

  1. Samstad JG, Pipkin S (2005) Bringing the firm back in: local decision making and human capital development in Mexico’s maquiladora sector. World Dev 33(5):805–822

    Article  Google Scholar 

  2. Hernandez P (2004) Mexico’s maquiladora expansion during the 1990s: an environmental assessment. Ecol Econ 49(2):163–185

    Article  Google Scholar 

  3. INEGI (2011) Mexican national statistical yearbook. National Institute of Statistics, Geography and Informatics (in Spanish)

  4. Maquiladoras Association AC (AMAC) (2012) http://www.slideshare.net/elperrote/juarez-amac-datos-estadisticos. 10 March 2013

  5. Cedillo-Campos M, Sanchez C (2013) Dynamic self-assessment of supply chains performance: an emerging market approach. J Appl Res Technol 11(3):338–347

    Google Scholar 

  6. Bititci US (1995) Modeling of performance measurement systems in manufacturing enterprises. Int J Prod Econ 42(2):137–147

    Article  Google Scholar 

  7. Ngai EWT, Chau DCK, Chan TLA (2011) Information technology, operational, and management competencies for supply chain agility: findings from case studies. J Strategic Inf Syst 20(3):232–249

    Article  Google Scholar 

  8. Beamon BM (1998) Supply chain design and analysis: models and methods. Int J Prod Econ 55(3):281–294

    Article  Google Scholar 

  9. Beamon BM (1999) Measuring supply chain performance. Int J Oper Prod Man 19(3):275–292

    Article  Google Scholar 

  10. Gunasekaran A, Patel C, Mcgauhhey RE (2004) A framework for supply chain performance measurement. Int J Prod Econ 87:333–347

    Article  Google Scholar 

  11. Hall DC, Saygin C (2012) Impact of information sharing on supply chain performance. Int J Adv Manuf Tech 58(1–4):397–409

    Article  Google Scholar 

  12. Aliei M, Sazvar A, Ashrafi B (2012) Assessment of information technology effects on management of supply chain based on fuzzy logic in Iran tail industries. Int J Adv Manuf Tech 63(1–4):215–223

    Article  Google Scholar 

  13. Ye F, Wang Z (2013) Effects of information technology alignment and information sharing on supply chain operational performance. Comput Ind Eng 65(3):370–377

    Article  Google Scholar 

  14. Zeng Y, Wang L, Deng X, Cao X, Khundker N (2012) Secure collaboration in global design and supply chain environment: problem analysis and literature review. Comput Ind 63(6):545–556

    Article  Google Scholar 

  15. Zhu Q, Geng Y, Sarkis J, Lai KH (2011) Evaluating green supply chain management among Chinese manufacturers from the ecological modernization perspective. Transport Res E-Log 47(6):808–821

    Article  Google Scholar 

  16. Chow WS, Madu CN, Kuei CH, Lu MH, Lin C, Tseng H (2008) Supply chain management in the US and Taiwan: an empirical study. Omega-Int J Manage S 36(5):665–679

    Article  Google Scholar 

  17. Neely A, Gregory M, Platts K (1995) Performance measurement system design. Int J Oper Prod Man 15(4):80–116

    Article  Google Scholar 

  18. Bititci US, Mendibil K, Albores P, Martinez M (2005) Measuring and managing performance in collaborative enterprises. Int J Oper Prod Man 25(4):333–353

    Article  Google Scholar 

  19. Folan P, Browne J (2005) A review of performance measurement: towards performance management. Comput Ind 56(7):663–680

    Article  Google Scholar 

  20. Lockamy IA, Mccormack K (2004) The development of a supply chain management process maturity model using the concepts of business process orientation. Supply Chain Manag 9(4):272–278

    Article  Google Scholar 

  21. Lee C, Wilhelm W (2010) On integrating theories of international economics in the strategic planning of global supply chains and facility location. Int J Prod Econ 124(1):225–240

    Article  Google Scholar 

  22. Estampe D, Lamouri S, Paris JL, Brahim DS (2013) A framework for analysing supply chain performance evaluation models. Int J Prod Econ 142(2):247–258

    Article  Google Scholar 

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

  24. Castillo-Villar KK, Smith NR, Simonton JL (2012) A model for supply chain design considering the cost of quality. Appl Math Model 36(12):5920–5935

    Article  Google Scholar 

  25. Khan M, Jaber MY, Ahmad AR (2014) An integrated supply chain model with errors in quality inspection and learning in production. Omega-Int J Manage S 42(1):16–24

    Article  Google Scholar 

  26. Sana SS (2011) A production-inventory model of imperfect quality products in a three-layer supply chain. Decis Support Syst 50(2):539–547

    Article  Google Scholar 

  27. Xia D, Chen B (2011) A comprehensive decision-making model for risk management of supply chain. Expert Syst Appl 38(5):4957–4966

    Article  Google Scholar 

  28. Yu W, Jacobs MA, Salisbury WD, Enns H (2013) The effects of supply chain integration on customer satisfaction and financial performance: an organizational learning perspective. Int J Prod Econ 146(1):346–358

    Article  Google Scholar 

  29. Low C, Chen YH (2013) A model measurement system for collaborative supply chain partners. J Manuf Syst 32(1):180–188

    Article  Google Scholar 

  30. Blanchard D (2010) Supply chain management best practices, 2nd edn. Wiley, Hoboken

    Google Scholar 

  31. Chiu YSP, Chiu SW (2006) Determining the materials procurement policy based on the economic order/production models with backlogging permitted. Int J Adv Manuf Tech 30(1–2):156–165

    Article  Google Scholar 

  32. Sazvar Z, Mirzapour Al-e-hashem SMJ, Baboli A, Akbari Jokar MR (2014) A bi-objective stochastic programming model for a centralized green supply chain with deteriorating products. Int J Prod Econ 150:140–154

    Article  Google Scholar 

  33. Hwang H, Hahn KH (2000) An optimal procurement policy for items with an inventory level-dependent demand rate and fixed lifetime. Eur J Oper Res 127(3):537–545

    Article  MATH  MathSciNet  Google Scholar 

  34. Banerjee S, Sharma A (2010) Optimal procurement and pricing policies for inventory models with price and time dependent seasonal demand. Math Comput Model 51(5–6):700–714

    Article  MATH  MathSciNet  Google Scholar 

  35. Mikalef P, Pateli A, Batenburg R, van de Wetering R (2013) Investigating the impact of procurement alignment on supply chain management performance. Procedia Technol 9:310–319

    Article  Google Scholar 

  36. Lau RSM, Xie JL, Zhao X (2008) Effects of inventory policy on supply chain performance: a simulation study of critical decision parameters. Comput Ind Eng 55(3):620–633

    Article  Google Scholar 

  37. Zhang J, Liu X, Tu YL (2011) A capacitated production planning problem for closed-loop supply chain with remanufacturing. Int J Adv Manuf Tech 54(5–8):757–766

    Article  Google Scholar 

  38. Pettersson A, Segerstedt A (2013) Measuring supply chain cost. Int J Prod Econ 143(2):357–363

    Article  Google Scholar 

  39. Roh J, Hong P, Min H (2014) Implementation of a responsive supply chain strategy in global complexity: the case of manufacturing firms. Int J Prod Econ 147(Part B):198–210

    Article  Google Scholar 

  40. Heikkilä J (2002) From supply to demand chain management: efficiency and customer satisfaction. J Oper Manag 20(6):747–767

    Article  Google Scholar 

  41. Lukas E, Welling A (2014) Timing and economic efficiency of climate-friendly investments in supply chains. Eur J Oper Res 233(2):448–457

    Article  MathSciNet  Google Scholar 

  42. Mohan S, Gopalakrishnan M, Mizzi PJ (2013) Improving the efficiency of a non-profit supply chain for the food insecure. Int J Prod Econ 143(2):248–255

    Article  Google Scholar 

  43. Liu S, Li C, Feng Y, Rong G (2012) Network structure and logistics efficiency: a new approach to analyse supply chain system. Comput Aided Chem Eng 30:392–396

    Article  Google Scholar 

  44. García JL, Maldonado AA, Alvarado A, Rivera DG (2014) Human critical success factors for kaizen and its impacts in industrial performance. Int J Adv Manuf Tech 70(9–12):2187–2198

    Article  Google Scholar 

  45. Iida T (2012) Coordination of cooperative cost-reduction efforts in a supply chain partnership. Eur J Oper Res 222(2):180–190

    Article  MATH  MathSciNet  Google Scholar 

  46. Likert R (1932) A technique for the measumerement of attitudes. Arch Psychol 22(140):1–55

    Google Scholar 

  47. Power D (2005) Supply chain management integration and implementation: a literature review. Supply Chain Manag 10(4):252–263

    Article  MathSciNet  Google Scholar 

  48. Cirtita H, Glaser-Segura DA (2012) Measuring downstream supply chain performance. J Man Tech Manag 23(2):299–314

    Article  Google Scholar 

  49. Falk H, Hogström L (2000) Key success factors for a functioning supply chain in e-commerce B2B. Master thesis. School of Business, Economics and Law. Göteborg University

  50. Tang O, Musa N (2011) Identifying risk and research advancements in supply chain risk management. Int J Prod Econ 133(1):25–34

    Article  Google Scholar 

  51. Ranganathan C, Teo TSH, Dhaliwal J (2011) Web-enabled supply chain management: key antecedents and performance impacts. Int J Inform Manage 31(6):533–545

    Article  Google Scholar 

  52. Zhou H (2003) The role of supply chain processes and information sharing in supply chain management. Thesis. The Ohio State University

  53. Gunasekaran A, Ngai EWT (2009) Modeling and analysis of built-to-order supply chains. Eur J Oper Res 195(2):319–334

    Article  MATH  MathSciNet  Google Scholar 

  54. Merschmann ULF, Thonemann UW (2011) Supply chain flexibility, uncertainty and form performance: an empirical analysis of German manufacturing firms. Int J Prod Econ 130(1):43–53

    Article  Google Scholar 

  55. Whitten GD, Green KW, Zelbst PJ (2012) Triple-A supply chain performance. Int J Oper Prod Man 32(1):28–48

    Article  Google Scholar 

  56. Young RR, Esqueda P (2005) Supply chain vulnerability: considerations of the case of Latin America. Rev Latinoam Adm 34:63–77 (In Spanish)

    Google Scholar 

  57. Haytko DL, Kent JL (2007) Mexican maquiladoras: helping or hurting the US/Mexico cross-border supply chain? Int J Log Manag 18(3):347–363

    Article  Google Scholar 

  58. Ramanathan U, Gunasekaran A (2014) Supply chain collaboration: impact of success in long-term partnerships. Int J Prod Econ 147(Part B):252–259

    Article  Google Scholar 

  59. Gunasekaran A, Ngai EWT (2004) Virtual supply chain management. Prod Plan Control 15(6):584–595

    Article  Google Scholar 

  60. Ribas I, Companys R (2007) A state of the art for collaborative planning in supply chain: a deterministic and uncertainty context and. IC 3(003): 91–121 (in Spanish)

  61. Teller C, Kotzab H, Grant DB (2011) Improving the execution of supply chain management in organizations. Int J Prod Econ 140(2):713–720

    Article  Google Scholar 

  62. Gunasekaran A, Patel C, Tirtiroglu E (2001) Performance measures and metrics in a supply chain environment. Int J Oper Prod Man 21(1, 2):71–87

    Article  Google Scholar 

  63. Schotanus F, Telgen J, De Boer L (2010) Critical success factors for managing purchasing groups. J Purch Supply Manag 16:51–60

    Article  Google Scholar 

  64. Blome C, Schoenherr T (2011) Supply chain risk management in financial crises: a multiple case-study approach. Int J Prod Econ 134(1):47–57

    Article  Google Scholar 

  65. Babak JN, Saeid I (2012) Analyzing effective elements in agile supply chain. Manage Sci Lett 2(1):369–378

    Article  Google Scholar 

  66. Lu CS, Lai KH, Chen TCE (2007) Application of structural equation modeling to evaluate the intention of shippers to use internet services in linear shipping. Eur J Oper Res 180(2):845–867

    Article  MATH  Google Scholar 

  67. Hoejmose S, Brammer S, Millington A (2012) “Green” supply chain management: the role of trust and top management in B2B and B2C markets. Ind Market Manag 41(4):609–620

    Article  Google Scholar 

  68. Dorling K, Scott J, Deakins E (2006) Determinants of successful vendor managed inventory relationships in oligopoly industries. Int J Phys Distrib 36(3):176–191

    Article  Google Scholar 

  69. Huang M, Yang M, Zhang Y, Liu B (2012) System dynamics modeling-based study of contingent sourcing under supply discruptions. Sys Eng Proc 4(2012-Part II):290–297

    Article  Google Scholar 

  70. Feng Y (2012) System dynamics modeling for supply chain information sharing. Phys Proc 25(2012):1463–1469

    Article  Google Scholar 

  71. Khaji M, Shafaei R (2011) A system dynamics approach for strategic partnering in supply networks. Int J Comp Integ M 24(2):106–125

    Article  Google Scholar 

  72. Meixell MJ, Gargeya VB (2005) Global supply chain design: a literature review and critique. Transport Res E-Log 41(6):531–550

    Article  Google Scholar 

  73. Su Y, Yang C (2010) A structural equation model for analyzing the impact of ERP on SCM. Expert Syst Appl 31(1):456–469

    Article  MathSciNet  Google Scholar 

  74. Kroes JR (2007) Outsourcing of supply chain processes: evaluating the impact of congruence between outsourcing drivers and competitive priorities on performance. Thesis. Georgia Institute of Technology

  75. Green KW, Whitten D, Inman RA (2012) Aligning marketing strategies throughout the supply chain to enhance performance. Ind Market Manag 41(6):1008–1018

    Article  Google Scholar 

  76. Mccormack K, Bronzo ML, Valadares MP (2008) Supply chain maturity and performance in Brazil. Supply Chain Manag 13(4):272–282

    Article  Google Scholar 

  77. Wiengarten F, Pagell M, Fynes B (2012) Supply chain environmental investments in dynamic industries: comparing investment and performance differences with static industries. Int J Prod Econ 135(2):541–551

    Article  Google Scholar 

  78. Quesada H, Gazo R (2007) Methodology for determining key internal business processes based on critical success factors. Lect Notes Comput Sci 13(1):5–20

    Google Scholar 

  79. Perotti S, Zorzini M, Cagno E, Micheli GJL (2012) Green supply chain practices and company performance: the case of 3PLs in Italy. Int J Phys Distrib 42(7):640–672

    Article  Google Scholar 

  80. Tsai CY (2011) On delineating supply chain cash flow under collection risk. Int J Prod Econ 129(1):186–194

    Article  Google Scholar 

  81. Cruz JM (2009) The impact of corporate social responsibility in supply chain management: multicriteria decision-making approach. Decis Support Syst 48(1):224–236

    Article  Google Scholar 

  82. Kannan VR, Tan KC (2010) Supply chain integration: cluster analysis of the impact of span of integration. Supply Chain Manag 15(3):207–215

    Article  Google Scholar 

  83. Hair JF, Black WC, Babin BJ, Anderson RE (2009) Multivariate data analysis. Prentice Hall, Upper Saddle River

    Google Scholar 

  84. Giaquinta M (2009) Mathematical analysis: an introduction to functions of several variables. Springer, New York

    Book  Google Scholar 

  85. Kaiser HM (2010) Mathematical programming for agricultural, environmental, and resource economics. Wiley, Hoboken

    Google Scholar 

  86. Rosenthal R, Rosnow RL (1991) Essentials of behavioral research: methods and data analysis. McGraw Hill, Boston

    Google Scholar 

  87. Wold S, Trygg J, Berglund A, Antti H (2001) Some recent developments in PLS modeling. Chemometr Intell Lab 58(2):131–150

    Article  Google Scholar 

  88. Cronbach LJ (1951) Coefficient alpha and the internal structure of tests. Psychometrika 16(3):297–334

    Article  Google Scholar 

  89. Nunnaly JC (1978) Psychometric theory. McGraw Hill, New York

    Google Scholar 

  90. Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50

    Article  Google Scholar 

  91. Kock N (2012) WarpPLS 3.0 user manual. ScriptWarp Systems™, Laredo

    Google Scholar 

  92. Nunnally JC, Bernstein IH (1994) Psychometric theory. McGraw-Hill, New York

    Google Scholar 

  93. Cenfetelli R, Bassellier G (2009) Interpretation of formative measurement in information systems research. Mis Quart 33(4):689–708

    Google Scholar 

  94. Petter S, Straub D, Rai A (2007) Specifying formative constructs in information systems research. Mis Quart 31(4):623–656

    Google Scholar 

  95. Hair JF, Anderson RE, Tatham RL (1987) Multivariate data analysis. Macmillan, New York

    Google Scholar 

  96. Kline RB (1998) Principles and practice of structural equation modeling. The Guilford Press, New York

    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, Ciudad Juárez, Chihuahua, Mexico, 32310

    Liliana Avelar-Sosa, Jorge Luis García-Alcaraz, Osslan Osiris Vergara-Villegas & Aidé Aracely Maldonado-Macías

  2. Division of Graduate Studies and Research, Instituto Tecnológico de Orizaba, Av. Oriente 9, No. 852, Col. Emiliano Zapata, 94320, Orizaba, Veracruz, Mexico

    Giner Alor-Hernández

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. Osslan Osiris Vergara-Villegas
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Aidé Aracely Maldonado-Macías
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Giner Alor-Hernández
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Liliana Avelar-Sosa.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Avelar-Sosa, L., García-Alcaraz, J.L., Vergara-Villegas, O.O. et al. Impact of traditional and international logistic policies in supply chain performance. Int J Adv Manuf Technol 76, 913–925 (2015). https://doi.org/10.1007/s00170-014-6308-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-014-6308-3

Keywords

Search

Navigation