Skip to main content
SpringerLink
Log in

The Impact of the Technologies and Tools Factor on Manufacturing System Performance: A Causal Model

  • Chapter
  • First Online:
Macroergonomics for Manufacturing Systems

Part of the book series: Management and Industrial Engineering ((MINEN))

  • 427 Accesses

Abstract

In this chapter, we present a hypothetical causal model to understand the impact of tools and technologies as a macroergonomic factor on manufacturing system performance. More specifically, the model assesses the effects of three macroergonomic elements of technologies and tools on Production Processes, Customers, and Organizational Performance. Data were obtained after administering the Macroergonomic Compatibility Questionnaire (MCQ) to middle and senior managers on Mexican manufacturing companies located in the state of Chihuahua. Results reveal that information technology has significant effects on manufacturing system performance, which is why they must be considered as a source of competitiveness. Also, we found that Customers and Production Processes have a positive impact on Organizational Performance.

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 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
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

Notes

  1. 1.

    Total factor productivity (TFP) is the portion of output not explained by the amount of inputs in production. As such, its level is determined by how efficiently and intensely the inputs are used in production (Comin 2008).

References

  • Abdulmalek FA, Rajgopal J (2007) Analyzing the benefits of lean manufacturing and value stream mapping via simulation: a process sector case study. Int J Prod Econ 107(1):223–236. doi:10.1016/j.ijpe.2006.09.009

  • Aliu A, Halili A (2013) The impact of information and communication technologies as a tool to facilitate growth in the manufacturing sector in republic of Kosovo. Procedia Technol 8:465–470. doi:10.1016/j.protcy.2013.11.060

    Article  Google Scholar 

  • Armstrong M, Baron A (2002) Strategic HRM: the key to improved business performance. London

    Google Scholar 

  • Avci U, Madanoglu M, Okumus F (2011) Strategic orientation and performance of tourism firms: evidence from a developing country. Tour Manag 32:147–157. doi:10.1016/j.tourman.2010.01.017

    Article  Google Scholar 

  • Axtell R (2001) Zipf distribution of US firm sizes. Science 293(80):1818–1820. doi:10.1126/science.1062081

  • Bauer AM, Thielke SM, Katon W, Unützer J, Areán P (2014) Aligning health information technologies with effective service delivery models to improve chronic disease care. Prev Med (Baltim) 66:167–172. doi:10.1016/j.ypmed.2014.06.017

    Article  Google Scholar 

  • Chandler GN, DeTienne DR, McKelvie A, Mumford TV (2011) Causation and effectuation processes: a validation study. J Bus Ventur 26:375–390. doi:10.1016/j.jbusvent.2009.10.006

    Article  Google Scholar 

  • Chou Y-C, Hao-Chun Chuang H, Shao BBM (2014) The impacts of information technology on total factor productivity: a look at externalities and innovations. Int J Prod Econ 158:290–299. doi:10.1016/j.ijpe.2014.08.003

    Article  Google Scholar 

  • Comin D (2008) Total factor productivity. In: University NY, Research NB of E (eds) An eponymous dictionary of economics. Elgar Publishers Ltd., New York

    Google Scholar 

  • Dale WJ (2001) Information technology and the U.S. Econ Am Econ Rev 91:1–32

    Google Scholar 

  • Damanpour F, Walker RM, Avellaneda CN (2009) Combinative effects of innovation types and organizational performance: a longitudinal study of service organizations. J Manag Stud 46:650–675. doi:10.1111/j.1467-6486.2008.00814.x

  • Do TT, Hua KA, Tantaoui MA (2004) P2VoD: providing fault tolerant video-on-demand streaming in peer-to-peer environment. In: 2004 IEEE international conference on communications, vol 3 (IEEE Cat. No.04CH37577). IEEE, pp 1467–1472

    Google Scholar 

  • dos Reis RA, do Freitas MCD (2014) Critical factors on information technology acceptance and use: an analysis on small and medium Brazilian clothing industries. Procedia Comput Sci 31:105–114. doi:10.1016/j.procs.2014.05.250

  • Etgar M (2008) A descriptive model of the consumer co-production process. J Acad Mark Sci 36:97–108. doi:10.1007/s11747-007-0061-1

    Article  Google Scholar 

  • García-Alcaraz JL, Maldonado-Macías AA, Alvarado A, Rivera DG (2014) Human critical success factors for kaizen and its impacts in industrial performance. Int J Adv Manuf Technol 70:2187–2198. doi:10.1007/s00170-013-5445-4

    Article  Google Scholar 

  • Gunasekaran A, Ngai EWT, McGaughey RE (2006) Information technology and systems justification: a review for research and applications. Eur J Oper Res 173:957–983. doi:10.1016/j.ejor.2005.06.002

    Article  MATH  Google Scholar 

  • Gunday G, Ulusoy G, Kilic K, Alpkan L (2011) Effects of innovation types on firm performance. Int J Prod Econ 133:662–676. doi:10.1016/j.ijpe.2011.05.014

  • Ismail RB (2007) Implementations problems in lean manufacturing: a study in manufacturing industries. Malaysia Technical University of Melaka

    Google Scholar 

  • Kaderlan N (19991) Designing your practice: a principal guide to creating and managing design practice. McGraw-Hill, New York

    Google Scholar 

  • Kock N (2015) WarpPLS© 5.0 user manual. ScriptWarp SystemsTM, Laredo, TX, USA

    Google Scholar 

  • Levina NL, Ross WJ (2003) From the vendor’s perspective: exploring the value proposition in information technology outsourcing. MIS Q 27:331–364

    Article  Google Scholar 

  • Lin K-Y, Tsai M-H, Gatti UC, Je-Chian Lin J, Lee C-H, Kang S-C (2014) A user-centered information and communication technology (ICT) tool to improve safety inspections. Autom Constr 48:53–63. doi:10.1016/j.autcon.2014.08.012

    Article  Google Scholar 

  • Luneburg WV, Susman TM (2005) The lobbying manual: a complete guide to federal law governing lawyers and lobbyists, 3rd edn. Am Bar Assoc, Chicago

    Google Scholar 

  • Maister DH (2012) Managing the professional service firm. Simon and Schuster UK, New York

    Google Scholar 

  • Makkonen Vuori M (2014) The role of information technology in strategic buyer–supplier relationships. Ind Mark Manag 43:1053–1062. doi:10.1016/j.indmarman.2014.05.018

    Article  Google Scholar 

  • Melián-González S, Bulchand-Gidumal J (2016) A model that connects information technology and hotel performance. Tour Manag 53:30–37. doi:10.1016/j.tourman.2015.09.005

    Article  Google Scholar 

  • Morita H, Nakahara H (2004) Impacts of the information-technology revolution on Japanese manufacturer–supplier relationships. J Jpn Int Econ 18:390–415

    Article  Google Scholar 

  • Ni M, Yang L, Chen J, Chen H, Li X (2014) How to improve divergent thinking capability by information technology and extenics. Procedia Comput Sci 31:158–164. doi:10.1016/j.procs.2014.05.256

    Article  Google Scholar 

  • Ockert D (2014) Japanese JHS students’ ideal L2 selves: confidence, anxiety, and willingness to communicate. In: Bailey B (ed) The language teacher. JALT Publications, Tokio, p 61

    Google Scholar 

  • Oyedele LO, Tham KW (2007) Clients’ assessment of architects’ performance in building delivery process: evidence from Nigeria. Build Environ 42:2090–2099. doi:10.1016/j.buildenv.2005.06.030

    Article  Google Scholar 

  • Pearl J (2001) Direct and indirect effects. In: Proceedings of the seventeenth conference on uncertainty in artificial intelligence, Morgan Kaufmann Publishers Inc., San Francisco, CA., pp 411–420

    Google Scholar 

  • Piegorsch KM, Watkins KW, Piegorsch WW, Reininger B, Corwin SJ, Valois RF (2006) Ergonomic decision-making: a conceptual framework for experienced practitioners from backgrounds in industrial engineering and physical therapy. Appl Ergon 37:587–598. doi:10.1016/j.apergo.2005.11.002

    Article  Google Scholar 

  • Real JC, Leal A, Roldán JL (2006) Information technology as a determinant of organizational learning and technological distinctive competencies. Ind Mark Manag 34:505–521. doi:10.1016/j.indmarman.2005.05.004

    Article  Google Scholar 

  • Realyvásquez A, Maldonado-Macías AA, García-Alcaraz J, Blanco-Fernández J (2015) Effects of organizational macroergonomic compatibility elements over manufacturing systems’ performance. Procedia Manuf 3:5715–5722. doi:10.1016/j.promfg.2015.07.807

  • Realyvásquez A, Maldonado-Macías A, García-Alcaraz J, Cortés-Robles G, Blanco-Fernández J (2016) Structural model for the effects of environmental elements on the psychological characteristics and performance of the employees of manufacturing systems. Int J Environ Res Public Health 13:1–21. doi:10.3390/ijerph13010104

    Article  Google Scholar 

  • Robey Daniel, Boudreau Marie-Claude, Rose GM (2000) Information technology and organizational learning: a review and assessment of research. Accounting Manag Inf Technol 10:125–155. doi:10.1016/S0959-8022(99)00017-X

    Article  Google Scholar 

  • Romaní JCC (2009) El concepto de tecnologías de la información. Benchmarking sobre las definiciones de las TIC en la sociedad del conocimiento. Zer-Revista Estud Comun 14:295–318

    Google Scholar 

  • Ruiz-Mercader J, Meroño-Cerdan AL, Sabater-Sánchez R (2006) Information technology and learning: their relationship and impact on organisational performance in small businesses. Int J Inf Manage 26:16–29. doi:10.1016/j.ijinfomgt.2005.10.003

    Article  Google Scholar 

  • Scheer A-W, Nüttgens M (2000) ARIS Architecture and reference models for business process management. In: van der Aalst W, Desel J, Oberweis A (eds) Business process management. Springer, pp 376–389

    Google Scholar 

  • Shao BM, Lin WT (2001) Measuring the value of information technology in technical efficiency with stochastic production frontiers. Inf Softw Technol 43:447–456. doi:10.1016/S0950-5849(01)00150-1

    Article  Google Scholar 

  • Stiroh KJ (2002) Are ICT spillovers driving the new economy? Rev Income Wealth 48:33–57. doi:10.1111/1475-4991.00039

    Article  Google Scholar 

  • Surej J (2015) The integration of information technology in higher education: a study of faculty’s attitude towards IT adoption in the teaching process. Contaduría y Adm 60:23. doi:10.1016/j.cya.2015.08.004

    Google Scholar 

  • Webber SS (2011) Dual organizational identification impacting client satisfaction and word of mouth loyalty. J Bus Res 64:119–125. doi:10.1016/j.jbusres.2010.02.005

    Article  Google Scholar 

  • Wilson JR, Carayon P (2014) Systems ergonomics: looking into the future—editorial for special issue on systems ergonomics/human factors. Appl Ergon 45:3–4. doi:10.1016/j.apergo.2013.08.007

    Article  Google Scholar 

  • Yao LJ, Liu C, Chan SH (2010) The influence of firm specific context on realizing information technology business value in manufacturing industry. Int J Account Inf Syst 11:353–362. doi:10.1016/j.accinf.2010.09.007

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Instituto Tecnológico de Tijuana, Calzada Tecnológico, Tijuana, 22414, Baja California, Mexico

    Arturo Realyvásquez-Vargas

  2. Department of Industrial Engineering and Manufacturing, Universidad Autónoma de Ciudad Juárez, Av. del Charro 450 Norte, Ciudad Juárez, 32310, Chihuahua, Mexico

    Aide Aracely Maldonado-Macías & Jorge Luis García-Alcaraz

Authors
  1. Arturo Realyvásquez-Vargas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aide Aracely Maldonado-Macías
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jorge Luis García-Alcaraz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Arturo Realyvásquez-Vargas .

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this chapter

Cite this chapter

Realyvásquez-Vargas, A., Maldonado-Macías, A.A., García-Alcaraz, J.L. (2018). The Impact of the Technologies and Tools Factor on Manufacturing System Performance: A Causal Model. In: Macroergonomics for Manufacturing Systems. Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-68684-4_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-68684-4_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68683-7

  • Online ISBN: 978-3-319-68684-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation