Structural equation modeling to identify the human resource value in the JIT implementation: case maquiladora sector

  • Jorge Luis García-Alcaraz
  • Diana Jazmín Prieto-Luevano
  • Aidé Aracely Maldonado-Macías
  • Julio Blanco-Fernández
  • Emilio Jiménez-Macías
  • José María Moreno-Jiménez


The research analyzes the particularities of the Mexican maquiladora industry in the Just in Time (JIT) implementation process as a global example of maquiladoras, analyzing 31 competitive advantages or benefits obtained after a JIT implementation process, which were integrated into four dimensions: Human Resources, Production Process, Inventory Management, and Economic Performance of companies. The study proposes a structural equation model which assumes that human factor is the most important benefit obtained after JIT implementation and is proposed as the initial or independent latent variable, being the final latent variable or last benefits the company’s Economic Performance. The final results in the model show how the capabilities and skills in Human Resources affect 86 % of the variance of the Production Process, which together explains the 82 % of Inventory Management. Finally, Human Resources, Production Process, and Inventory Management explain 79 % of Economic Performance obtained from JIT.


JIT implementation JIT benefits JIT performance SEM for JIT 


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  1. 1.
    Gupta A (2011) A conceptual JIT model of service quality. Int J Eng Sci Tech 3(3):2414–2427Google Scholar
  2. 2.
    Helm R, Gritsch S (2014) Examining the influence of uncertainty on marketing mix strategy elements in emerging business to business export-markets. Int Bus Rev 23(2):418–428. doi: 10.1016/j.ibusrev.2013.06.007 CrossRefGoogle Scholar
  3. 3.
    Marín F, Delgado J (2000) Las técnicas justo a tiempo y su repercusión en los sistemas de producción. Econ Ind 331:35–41Google Scholar
  4. 4.
    Eng T-Y, Ozdemir S (2014) International R&D partnerships and intrafirm R&D–marketing–production integration of manufacturing firms in emerging economies. Indust Mark Manag 43(1):32–44. doi: 10.1016/j.indmarman.2013.07.013 CrossRefGoogle Scholar
  5. 5.
    Balasubramanian R, Padhi A (2005) The next wave in US offshoring. McKinsey Q 1:6–9Google Scholar
  6. 6.
    Jun M, Cai S, Shin H (2006) TQM practice in maquiladora: antecedents of employee satisfaction and loyalty. J Oper Manag 24(6):791–812. doi: 10.1016/j.jom.2005.09.006 CrossRefGoogle Scholar
  7. 7.
    Hadjimarcou J, Brouthers LE, McNicol JP, Michie DE (2013) Maquiladoras in the 21st century: six strategies for success. Bus Horiz 56(2):207–217. doi: 10.1016/j.bushor.2012.11.005 CrossRefGoogle Scholar
  8. 8.
    Inegi (2013) Monthly statistics for manufacturing industry, maquiladora and export services (immex). Mexican national institute of statistics and geography, Mexico, DFGoogle Scholar
  9. 9.
    Machuca JAD (2002) JIT facing the new millennium. Int J Prod Econ 80((2):131–134. doi: 10.1016/S0925-5273(02)00312-2 CrossRefGoogle Scholar
  10. 10.
    Singh S, Garg D (2011) JIT system: concepts, benefits and motivations in Indian Industries. Int J Manag Bus Stud 1(1):26–30Google Scholar
  11. 11.
    Contreras OF, Carrillo J, Alonso J (2012) Local entrepreneurship within global value chains: a case study in the Mexican automotive industry. World Dev 40(5):1013–1023. doi: 10.1016/j.worlddev.2011.11.012 CrossRefGoogle Scholar
  12. 12.
    Sargent J, Matthews L (2009) China versus Mexico in the Global EPZ Industry: Maquiladoras, FDI quality, and plant mortality. World Dev 37(6):1069–1082. doi: 10.1016/j.worlddev.2008.10.002 CrossRefGoogle Scholar
  13. 13.
    Lawrence JJ, Hottenstein MP (1995) The relationship between JIT manufacturing and performance in Mexican plants affiliated with U.S. companies. J Oper Manag 13(1):3–18. doi: 10.1016/0272-6963(95)00018-N CrossRefGoogle Scholar
  14. 14.
    Garg D, Deshmukh S (1999) JIT purchasing: literature review and implications for Indian industry. Prod Plan Control 10(3):276–285. doi: 10.1080/095372899233235 CrossRefGoogle Scholar
  15. 15.
    Garg D, Deshmukh S, Kaul O (1996) Critical analysis in JIT purchasing in Indian context. Product J 37:271–279Google Scholar
  16. 16.
    Kumar V (2010) JIT based quality management: concepts and implications in indian context. Int J Eng Sci Technol 2(1):40–50Google Scholar
  17. 17.
    Bonavia T, Marin-Garcia JA (2011) Integrating human resource management into lean production and their impact on organizational performance. Int J Manpow 32(8):923–938. doi: 10.1108/01437721111181679 CrossRefGoogle Scholar
  18. 18.
    Power D, Sohal AS (2000) Human resource management strategies and practices in just-in-time environments: Australian case study evidence. Technovation 20(7):373–387. doi: 10.1016/S0166-4972(99)00151-0 CrossRefGoogle Scholar
  19. 19.
    Inman RA, Sale RS, Green KW Jr, Whitten D (2011) Agile manufacturing: relation to JIT, operational performance and firm performance. J Oper Manag 29(4):343–355. doi: 10.1016/j.jom.2010.06.001 CrossRefGoogle Scholar
  20. 20.
    Dong Y, Carter CR, Dresner ME (2001) JIT purchasing and performance: an exploratory analysis of buyer and supplier perspectives. J Op Manag 19(4):471–483. doi: 10.1016/S0272-6963(00)00066-8 CrossRefGoogle Scholar
  21. 21.
    Bonito J (1990) Motivating employees for continuous improvement efforts. Prod Invent Manag Rev APICS News 8:225–236Google Scholar
  22. 22.
    Chong V, Rundus M (2000) The effect of new manufacturing practices and intensity of market competition on organizational performance: an empirical investigation. Paper presented at the International Conference on Management Research Accounting Research and Case Symposium, Mesa, AZ, USA, January 6–8, 2000Google Scholar
  23. 23.
    Ebrahtmpour M, Schonberger RJ (1984) The Japanese just-in-time/total quality control production system: potential for developing countries. Int J Prod Res 22(3):421–430. doi: 10.1080/00207548408942463 CrossRefGoogle Scholar
  24. 24.
    Bartezzaghi E, Turco F, Spina G (1992) The impact of the just-in-time approach on production system performance: a survey of Italian industry. Int J Oper Prod Manag 12(1):5. doi: 10.1108/EUM0000000001292 CrossRefGoogle Scholar
  25. 25.
    Kumar V, Garg D (2000) JIT elements in Indian context: an analysis. Product J 41(2):217–222Google Scholar
  26. 26.
    Macbeth DK, Baxter L, Farguson N, Neil G (1988) Buyer-vendor relationship with just-in-time: lessons from us multinationals. Ind Eng 20(9):38–41Google Scholar
  27. 27.
    Martel M (1993) The role of just-in-time purchasing in Dynapert’s transition to world class manufacturing. Prod Invent Manag J 34:71–76Google Scholar
  28. 28.
    Parnaby J (1988) A systems approach to the implementation of JIT methodologies in Lucas Industries. Int J Prod Res 26(3):483–492. doi: 10.1080/00207548808947878 CrossRefGoogle Scholar
  29. 29.
    Sakurai K (1986) Japanese worker attitudes: a key factor in productivity. Int J Oper Prod Manag 6(1):42–53. doi: 10.1108/eb054754 CrossRefGoogle Scholar
  30. 30.
    Balakrishnan R, Linsmeier T, Venkatakchalam M (1996) Financial benefits from JIT adoption: effects of customer concentration and cost structure. Account Rev 71(2):183–205Google Scholar
  31. 31.
    Hall R (1983) Zero inventories. Dow Jones-Irwin, HomewoodGoogle Scholar
  32. 32.
    Hong J-D, Hayya JC, Kim S-L (1992) JIT purchasing and setup reduction in an integrated inventory model. Int J Prod Res 30(2):255–266. doi: 10.1080/00207549208942893 CrossRefzbMATHGoogle Scholar
  33. 33.
    Singhvi S (1992) Employee involvement in JIT success: Eicher experience. Product J 33:366–369Google Scholar
  34. 34.
    Ha D, Kim S-L (1997) Implementation of JIT purchasing: an integrated approach. Prod Plan Control 8(2):152–157. doi: 10.1080/095372897235415 CrossRefGoogle Scholar
  35. 35.
    Fiedler K, Galletly JE, Bicheno J (1993) Expert advice for JIT implementation. Int J Oper Prod Manag 13(6):23–30. doi: 10.1108/01443579310038994 CrossRefGoogle Scholar
  36. 36.
    Dutton B (1990) Switching to quality excellence. Manuf Syst 8:245–256Google Scholar
  37. 37.
    Padukone H, Subba R (1993) Global status of JIT-implication for developing countries. Product J 34(3):419–429Google Scholar
  38. 38.
    Singh P, Bhandarkar A (1996) Paradigm shift in Indian industries: the need for tolerance of ambiguity. MDI Manag J 9:106–112Google Scholar
  39. 39.
    Bozbura FT, Beskese A, Kahraman C (2007) Prioritization of human capital measurement indicators using fuzzy AHP. Expert Syst Appl 32(4):1100–1112. doi: 10.1016/j.eswa.2006.02.006 CrossRefGoogle Scholar
  40. 40.
    Flynn B, Salakibara S, Schroeder R (1995) Relationship between JIT and TQM practices and performance. Acad Manag J 38(5):1325–1360CrossRefGoogle Scholar
  41. 41.
    Garg D (1997) Relevance of JIT purchasing in Indian industries. Kurukshetra University, IndiaGoogle Scholar
  42. 42.
    Roy R, KK G (1996) IT: world scenario and possibility of its applicability in Indian industries. Paper presented at the National conference on operation research in modern technology, REC Kurukshetra, India, March 8–9Google Scholar
  43. 43.
    Green KW Jr, Inman RA, Birou LM, Whitten D (2014) Total JIT (T-JIT) and its impact on supply chain competency and organizational performance. Int J Prod Econ 147(Part A):125–135. doi: 10.1016/j.ijpe.2013.08.026 CrossRefGoogle Scholar
  44. 44.
    Prodipto R (1999) Data warehousing for textiles, Texinfotech-99. Paper presented at the Techno park (I) Ltd, New DelhizbMATHGoogle Scholar
  45. 45.
    Vrat P, Mittal S, Tyagi K (1993) Implementation of JIT in Indian environment: a Delhi study. Product J 34:251–256Google Scholar
  46. 46.
    Bortolotti T, Danese P, Romano P (2012) Assessing the impact of just-in-time on operational performance at varying degrees of repetitiveness. Int J Prod Res 51(4):1117–1130. doi: 10.1080/00207543.2012.678403 CrossRefGoogle Scholar
  47. 47.
    Giunipero LC, Law WK (1990) Organizational support for just-in-time implementation. Int J Logist Manag 1(2):35–40. doi: 10.1108/09574099010804572 CrossRefGoogle Scholar
  48. 48.
    Priestman S (1985) SQC and JIT: partnership in quality, does culture make a difference. Qual Prog 18(5):31–35Google Scholar
  49. 49.
    Singh A (1989) Just-in-time system: an integrated system. Product J 30(3):309–314Google Scholar
  50. 50.
    RC B, RE C, IC C (1994) Switching rules for JIT purchasing. Prod Invent Manag J 35(3):13–17Google Scholar
  51. 51.
    Vuppalapati K, Ahire SL, Gupta T (1995) JIT and TQM: a case for joint implementation. Int J OperProd Manag 15(5):84–94. doi: 10.1108/01443579510083686 CrossRefGoogle Scholar
  52. 52.
    Boer J, Blaga P (2012) A more efficient production using quality tools and human resources management. Procedia Econ Finance 3(0):681–689. doi: 10.1016/S2212-5671(12)00214-6 CrossRefGoogle Scholar
  53. 53.
    Blaga P, Jozsef B (2014) Increasing human resource efficiency in the production process. Procedia Technol 12(0):469–475. doi: 10.1016/j.protcy.2013.12.516 CrossRefGoogle Scholar
  54. 54.
    Jabbour CJC, Jabbour ABLS, Govindan K, Teixeira AA, Freitas WRS (2013) Environmental management and operational performance in automotive companies in Brazil: the role of human resource management and lean manufacturing. J Clean Prod 47(0):129–140. doi: 10.1016/j.jclepro.2012.07.010 CrossRefGoogle Scholar
  55. 55.
    Martínez-Jurado PJ, Moyano-Fuentes J, Jerez-Gómez P (2014) Human resource management in lean production adoption and implementation processes: success factors in the aeronautics industry. BRQ Bus Res Q 17(1):47–68. doi: 10.1016/j.cede.2013.06.004 CrossRefGoogle Scholar
  56. 56.
    Jayaram J, Das A, Nicolae M (2010) Looking beyond the obvious: unraveling the Toyota production system. Int J Prod Econ 128(1):280–291. doi: 10.1016/j.ijpe.2010.07.024 CrossRefGoogle Scholar
  57. 57.
    Narayana SA, Kumar Pati R, Vrat P (2014) Managerial research on the pharmaceutical supply chain—a critical review and some insights for future directions. J Purch Supply Manag 20(1):18–40. doi: 10.1016/j.pursup.2013.09.001 CrossRefGoogle Scholar
  58. 58.
    Lengnick-Hall ML, Lengnick-Hall CA, Rigsbee CM (2013) Strategic human resource management and supply chain orientation. Hum Resour Manag Rev 23(4):366–377. doi: 10.1016/j.hrmr.2012.07.002 CrossRefGoogle Scholar
  59. 59.
    Greer CR, Ireland TC, Wingender JR (2001) Contrarian human resource investments and financial performance after economic downturns. J Bus Res 52(3):249–261. doi: 10.1016/S0148-2963(99)00108-3 CrossRefGoogle Scholar
  60. 60.
    Kesti M (2012) Organization human resources development connection to business performance. Procedia Econ Financ 2(0):257–264. doi: 10.1016/S2212-5671(12)00086-X CrossRefGoogle Scholar
  61. 61.
    Lampel J, Giachetti C (2013) International diversification of manufacturing operations: performance implications and moderating forces. J Oper Manag 31(4):213–227. doi: 10.1016/j.jom.2013.04.001 CrossRefGoogle Scholar
  62. 62.
    Katou AA, Budhwar PS (2010) Causal relationship between HRM policies and organisational performance: evidence from the Greek manufacturing sector. Eur Manag J 28(1):25–39. doi: 10.1016/j.emj.2009.06.001 CrossRefGoogle Scholar
  63. 63.
    Fullerton RR, McWatters CS (2001) The production performance benefits from JIT implementation. J Oper Manag 19(1):81–96. doi: 10.1016/S0272-6963(00)00051-6 CrossRefGoogle Scholar
  64. 64.
    Hofer C, Eroglu C, Rossiter Hofer A (2012) The effect of lean production on financial performance: the mediating role of inventory leanness. Int J Prod Econ 138(2):242–253. doi: 10.1016/j.ijpe.2012.03.025 CrossRefGoogle Scholar
  65. 65.
    Brox JA, Fader C (1997) Assessing the impact of JIT using economic theory. J Oper Manag 15(4):371–388. doi: 10.1016/S0272-6963(97)00005-3 CrossRefGoogle Scholar
  66. 66.
    González-Benito J, Suárez-González I, Spring M (2000) Complementarities between JIT purchasing practices: an economic analysis based on transaction costs. Int J Prod Econ 67(3):279–293. doi: 10.1016/S0925-5273(00)00032-3 CrossRefGoogle Scholar
  67. 67.
    Cao Q, Schniederjans M (2004) A revised EMQ/JIT production-run model: an examination of inventory and production costs. Int J Prod Econ 87(1):83–95CrossRefGoogle Scholar
  68. 68.
    Maiga AS, Jacobs FA (2009) JIT performance effects: a research note. Adv Account 25(2):183–189. doi: 10.1016/j.adiac.2009.06.003 CrossRefGoogle Scholar
  69. 69.
    Singh R, SH S, Metri B, Kaur R (2011) Organizational performance and retail challenges: a structural equation approach. Sci Res 3:159–168Google Scholar
  70. 70.
    Cronbach L (1951) Coefficient alpha and the internal structure of tests. Psychometrika 16(3):297–334. doi: 10.1007/BF02310555 CrossRefGoogle Scholar
  71. 71.
    Liu H, Ke W, Wei KK, Hua Z (2013) The impact of IT capabilities on firm performance: the mediating roles of absorptive capacity and supply chain agility. Decis Support Syst 54(3):1452–1462. doi: 10.1016/j.dss.2012.12.016 CrossRefGoogle Scholar
  72. 72.
    Nunnaly J (1978) Psychometric theory. Mc Graw Hill, New YorkGoogle Scholar
  73. 73.
    Fornell C, Larcker D (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50CrossRefGoogle Scholar
  74. 74.
    Nunnaly J, Bernstein I (1994) Psychometric theory. Mc Graw Hill, New YorkGoogle Scholar
  75. 75.
    Rexhausen D, Pibernik R, Kaiser G (2012) Customer-facing supply chain practices—the impact of demand and distribution management on supply chain success. J Oper Manag 30(4):269–281. doi: 10.1016/j.jom.2012.02.001 CrossRefGoogle Scholar
  76. 76.
    Lin C, Chow W, Madu C, Kuei C, Pei Y (2005) A structural equation model of supply chain quality management and organizational performance. Int J Prod Econ 96(3):355–365CrossRefGoogle Scholar
  77. 77.
    Zailani S, Jeyaraman K, Vengadasan G, Premkumar R (2012) Sustainable supply chain management (SSCM) in Malaysia: a survey. Int J Prod Econ 140(1):330–340. doi: 10.1016/j.ijpe.2012.02.008 CrossRefGoogle Scholar
  78. 78.
    Ramanathan U, Gunasekaran A (2014) Supply chain collaboration: impact of success in long-term partnerships. Int J Prod Econ 147(0):252–259. doi: 10.1016/j.ijpe.2012.06.002 CrossRefGoogle Scholar
  79. 79.
    Blome C, Schoenherr T, Eckstein D (2014) The impact of knowledge transfer and complexity on supply chain flexibility: a knowledge-based view. Int J Prod Econ 147(0):307–316. doi: 10.1016/j.ijpe.2013.02.028 CrossRefGoogle Scholar
  80. 80.
    Hair J, Anderson R, Tatham R (1987) Multivariate data analysis. Macmillan, New YorkGoogle Scholar
  81. 81.
    Hair J, Black W, Babin B, Anderson R (2009) Multivariate data analysis. Prentice Hall, Upper Saddle RiverGoogle Scholar
  82. 82.
    Giaquinta M (2009) Mathematical analysis: an introduction to functions of several variables. Springer, New YorkCrossRefGoogle Scholar
  83. 83.
    Kaiser H (2010) Mathematical programming for agricultural, environmental, and resource economics. Wiley, HobokenGoogle Scholar
  84. 84.
    Rosenthal R, Rosnow R (1991) Essentials of behavioral research: methods and data analysis. Mc Graw Hill, BostonGoogle Scholar
  85. 85.
    Wold S, Trygg J, Berglund A, Antti H (2001) Some recent developments in PLS modeling. Chemometr Intell Lab Syst 58(2):131–150. doi: 10.1016/S0169-7439(01)00156-3 CrossRefGoogle Scholar
  86. 86.
    García-Alcaraz J, Maldonado-Macias A, Iniesta AA, Robles GC, Hernández GA (2014) A systematic review/survey for JIT implementation: Mexican maquiladoras as case study. Comput Ind 65(4):761–773. doi: 10.1016/j.compind.2014.02.013 CrossRefGoogle Scholar
  87. 87.
    García-Alcaraz J, Maldonado A, Alvarado A, Rivera D (2014) Human critical success factors for kaizen and its impacts in industrial performance. Int J Adv Manuf Technol 70(9–12):2187–2198. doi: 10.1007/s00170-013-5445-4 CrossRefGoogle Scholar
  88. 88.
    Avelar-Sosa L, García-Alcaraz J, Vergara-Villegas O, Maldonado-Macías A, Alor-Hernández G (2014) Impact of traditional and international logistic policies in supply chain performance. Int J Adv Manuf Technol 1–13. doi: 10.1007/s00170-014-6308-3
  89. 89.
    Kock N (2013) Using WarpPLS in e-collaboration studies: what if I have only one group and one condition. Int J e-Collab 9(3):12CrossRefMathSciNetGoogle Scholar
  90. 90.
    Cenfetelli R, Bassellier G (2009) Interpretation of formative measurement in information systems research. MIS Q 33(4):19Google Scholar
  91. 91.
    Petter S, Straub D, Rai A (2007) Specifying formative constructs in information systems research. MIS Q 31(4):623–656Google Scholar
  92. 92.
    Kline R (1998) Principles and practice of structural equation modeling. Guilford, New YorkGoogle Scholar
  93. 93.
    Tastle WJ, Wierman MJ (2007) Consensus and dissention: a measure of ordinal dispersion. Int J Approx Reason 45(3):531–545. doi: 10.1016/j.ijar.2006.06.024 CrossRefMathSciNetGoogle Scholar
  94. 94.
    García-Alcaraz J, Rivera L, Blanco J, Jiménez E, Martínez E (2014) Structural equations modelling for relational analysis of JIT performance in maquiladora sector. Int J Prod Res 52(17):4931–4949. doi: 10.1080/00207543.2014.885143 CrossRefGoogle Scholar
  95. 95.
    Merschmann U, Thonemann UW (2011) Supply chain flexibility, uncertainty and firm performance: an empirical analysis of German manufacturing firms. Int J Prod Econ 130(1):43–53. doi: 10.1016/j.ijpe.2010.10.013 CrossRefGoogle Scholar
  96. 96.
    Yang S, Albert R, Carlo TA (2013) Transience and constancy of interactions in a plant-frugivore network. Ecosphere 4(12):147. doi: 10.1890/ES13-00222.1 CrossRefGoogle Scholar
  97. 97.
    Ketkar M, Vaidya OS (2012) Study of emerging issues in supply risk management in India. Procedia Soc Behav Sci 37(0):57–66. doi: 10.1016/j.sbspro.2012.03.275 CrossRefGoogle Scholar
  98. 98.
    Fullerton RR, McWatters CS (2002) The role of performance measures and incentive systems in relation to the degree of JIT implementation. Account Organ Soc 27(8):711–735. doi: 10.1016/S0361-3682(02)00012-0 CrossRefGoogle Scholar
  99. 99.
    Świerczek A (2013) The impact of supply chain integration on the “snowball effect” in the transmission of disruptions: an empirical evaluation of the model. Int J Prod Econ. doi: 10.1016/j.ijpe.2013.08.010
  100. 100.
    White RE, Prybutok V (2001) The relationship between JIT practices and type of production system. OMEGA 29(2):113–124. doi: 10.1016/S0305-0483(00)00033-5 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  • Jorge Luis García-Alcaraz
    • 1
  • Diana Jazmín Prieto-Luevano
    • 1
  • Aidé Aracely Maldonado-Macías
    • 1
  • Julio Blanco-Fernández
    • 2
  • Emilio Jiménez-Macías
    • 2
  • José María Moreno-Jiménez
    • 3
  1. 1.Department of Industrial Engineering and Manufacturing, Institute of Engineering and TechnologyAutonomous University of Ciudad JuárezCiudad JuárezMexico
  2. 2.Department of Mechanical EngineeringUniversity of La RiojaLogroñoSpain
  3. 3.Department of Quantitative Methods, Faculty of Economics SciencesUniversidad de ZaragozaZaragozaSpain

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