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Lai, N.Y.G.;  Foo, W.C.;  Tan, C.S.;  Kang, M.S.;  Kang, H.S.;  Wong, K.H.;  Yu, L.J.;  Sun, X.;  Tan, N.M.L. Theory of Planned Behavior in Lean Manufacturing Training. Encyclopedia. Available online: (accessed on 24 June 2024).
Lai NYG,  Foo WC,  Tan CS,  Kang MS,  Kang HS,  Wong KH, et al. Theory of Planned Behavior in Lean Manufacturing Training. Encyclopedia. Available at: Accessed June 24, 2024.
Lai, Nai Yeen Gavin, Wai Choong Foo, Chon Siong Tan, Myoung Sook Kang, Hooi Siang Kang, Kok Hoong Wong, Lih Jiun Yu, Xu Sun, Nadia Mei Lin Tan. "Theory of Planned Behavior in Lean Manufacturing Training" Encyclopedia, (accessed June 24, 2024).
Lai, N.Y.G.,  Foo, W.C.,  Tan, C.S.,  Kang, M.S.,  Kang, H.S.,  Wong, K.H.,  Yu, L.J.,  Sun, X., & Tan, N.M.L. (2022, July 08). Theory of Planned Behavior in Lean Manufacturing Training. In Encyclopedia.
Lai, Nai Yeen Gavin, et al. "Theory of Planned Behavior in Lean Manufacturing Training." Encyclopedia. Web. 08 July, 2022.
Theory of Planned Behavior in Lean Manufacturing Training

The Theory of Planned Behavior (TPB) is a useful framework that helps explain people’s behavior across a wide range of settings. Lean manufacturing is one of the most successful continuous improvement methods to increase a manufacturing organization’s productivity and efficiency. It has been considered a practical methodology to help manufacturing organizations improve production quality and cost. 

learning intention training lean manufacturing

1. Introduction

The roots of lean manufacturing can be traced back to the Toyota Production System (TPS), which Taichi Ohno developed to improve the manufacturing competitiveness of Toyota factories in Japan at the end of the Second World War [1][2]. There has not been a standardized definition for lean manufacturing used in the field. However, some of the lean concept’s key characteristics can be traced back to the book The Machine that Changed the World [3]. Lean production is “an integrated socio-technical system whose main objective is to eliminate waste by concurrently reducing or minimizing supplier, customer, and internal variability” [4]. Lean manufacturing is also seen as a customer-value-focused approach to production which can bring remarkable productivity increases [5]. Therefore, implementing lean manufacturing, including addressing the human aspects of lean manufacturing, has become a priority for many manufacturing organizations [6][7].

2. Workers’ Impact on Lean Manufacturing Innovations

Workers have a significant impact on lean manufacturing implementation, especially in labor-dependent manufacturing industries. Direct workers fundamentally are an essential part of the manufacturing process in such industries, and the performance of operations relies heavily on their involvement and abilities. Womack, widely acknowledged as a key authority on the lean concept, had even considered that workers’ work teams are at the very heart of the lean factory [3]. This is also in line with other researchers’ views that lean manufacturing implementation success depends on workers’ cooperation and full participation [6][8][9][10]. Without workers’ contribution, not only will the continuous improvement effort fail, but operations and production may even come to a halt. Past studies have also highlighted the importance of workers’ commitment to successful lean manufacturing implementation in organizations [11][12][13]. Others have highlighted the risk of worker resistance as a threat to be considered for any lean manufacturing implementation effort [14]. Addressing workers’ fear of new methods or procedures taking over their jobs will be an issue when planning for improvement and innovation in a manufacturing environment [15][16]. There have been indications that workers may fear that lean manufacturing implementation may lead to job losses, and therefore they may resist any changes required [17]. Consequently, it is hard to assume that workers will openly accept any continuous improvement effort, even if it is for the good of the organization.
Conversely, a continuous improvement effort pursued through the lean manufacturing methodology will allow workers the opportunity to harness their creativity and experience [18][19]. These improvement initiatives and opportunities will lead to a better sense of pride and a sense of job security among workers [20][21]. It has been suggested that workers should be empowered to provide ideas and suggestions to improve the processes that they are working on [5]. Employees who are skilled and experienced in their tasks could effectively contribute to their organization’s innovation development [22]. More organizations are also integrating the drive for efficiency through lean approaches with the need to be more innovative by adopting open innovation [23][24]. Lean practices could potentially effectively contribute to open innovation in organizations [25]. It is evident that workers could play an essential and positive role, but organizations must prepare them well for the requirements and challenges through training initiatives.

3. Lean Manufacturing Training Complexities

The training of staff is an integral part of a lean manufacturing implementation effort. Without proper training, lean and other innovative change implementations could never be successfully implemented [26]. The training and education of workers have been noted as a critical success factor for lean manufacturing and other related improvement initiatives implementation in various industrial settings [27][28][29][30][31]. Proper resources must be allocated for workers’ training, and management should encourage workers to attend the training by providing the appropriate rewards and outcomes for those engaging in training activities [10][32]. Experiences during training may also alter a learner’s intention to complete the training [33]. Failure to provide proper and adequate training could even lead to low morale in the workplace [34][35]. For better quality and effectiveness, the training of skilled workers should be accomplished through a formalized process [36]. The right approach to the on-the-job training will have a positive impact on the level of innovation of the organization [37]. However, determining the types of training and how much training is necessary is a complex and complicated process [38]. The participants’ learning intentions are an even more critical consideration for organizations seeking to train their workers.
Past research has identified that participation in training is a rational decision on the part of the participant. These studies enabled an understanding of the relationships between different factors and the impact on participants in training sessions [39][40][41][42][43]. Studies have also highlighted that participants could be encouraged to learn better from training activities through motivational initiatives [44][45][46]. Accordingly, the TPB has considered that a person’s intention is affected by the different motivational factors that influence their behavior [47]. Therefore, the TPB is a suitable framework to be considered for better understanding participants’ learning intention regarding training activities.
A limited number of past studies have applied the TPB to cover training participants’ motivation, engagement, and learning. Wiethoff 2004 [48] adapted the TPB for a study on diversity training, while Renkema and van der Kamp 2006 [49] conducted a quasi-experimental study examining the individual learning accounts of learning intention and perceived learning cultures of different sectors. More recently, Ho et al. 2011 [43] conducted an empirical study testing the TPB to predict public sector employees’ training participation and examine the factors that influence the participants’ intentions and behaviors regarding participating in training. Alok et al., 2018 [50] tested the efficacy of the TPB in the prediction of lean adoption practices among workers of cement companies. Liu et al., 2020 [51], on the other hand, used the TPB to investigate workers’ safety behavior and discussed the important role of safety training in an off-plant manufacturing environment. Other studies have also built upon the TPB framework to better understand the factors affecting participants’ learning from training initiatives. Sanders et al., 2011 [41] considered the different factors that could stimulate low-education workers’ learning intention in workplace learning activities. Kyndt et al., 2011 [42] completed a detailed study on the effects of past participation on the learning intentions of low-qualified workers. Similarly, Sanders et al., 2015 [52] investigated the impact of low-educated workers’ training participation and learning experience on their self-efficacy. These past studies indicate the TPB framework’s potential suitability for considering workers’ learning intentions in lean manufacturing training.


  1. Arnheiter, E.D.; Maleyeff, J. The integration of lean management and Six Sigma. TQM Mag. 2005, 17, 5–18.
  2. Lai, N.Y.G.; Wong, K.H.; Halim, D.; Lu, J.; Kang, H.S. Industry 4.0 Enhanced Lean Manufacturing. In Proceedings of the 2019 8th International Conference on Industrial Technology and Management (ICITM), Cambridge, UK, 2–4 March 2019; pp. 206–211.
  3. Womack, J.; Jones, D.T.; Roos, D. The Machine That Changed the World; Rawson Associates: New York, NY, USA, 1990.
  4. Shah, R.; Ward, P.T. Defining and developing measures of lean production. J. Oper. Manag. 2007, 25, 785–805.
  5. Sanders, A.; Elangeswaran, C.; Wulfsberg, J. Industry 4.0 implies lean manufacturing: Research activities in industry 4.0 function as enablers for lean manufacturing. J. Ind. Eng. Manag. 2016, 9, 811–833.
  6. Gaspar, F.; Leal, F. A methodology for applying the shop floor management method for sustaining lean manufacturing tools and philosophies: A study of an automotive company in Brazil. Int. J. Lean Six Sigma 2020, 11, 1233–1252.
  7. Saini, S.; Singh, D. Impact of implementing lean practices on firm performance: A study of Northern India SMEs. Int. J. Lean Six Sigma 2020, 11, 1005–1034.
  8. Shah, R.; Ward, P.T. Lean manufacturing: Context, practice bundles, and performance. J. Oper. Manag. 2003, 21, 129–149.
  9. Schonberger, R.J. Japanese production management: An evolution—With mixed success. J. Oper. Manag. 2007, 25, 403–419.
  10. Needy, K.L.; Norman, B.A.; Bidanda, B.; Ariyawongrat, P.; Tharmmaphornphilas, W.; Warner, R.C. Assessing human capital: A lean manufacturing example. Eng. Manag. J. 2002, 14, 35–39.
  11. Parker, S.K. Longitudinal effects of lean production on employee outcomes and the mediating role of work characteristics. J. Appl. Psychol. 2003, 88, 620.
  12. Vidal, M. Lean production, worker empowerment, and job satisfaction: A qualitative analysis and critique. Crit. Sociol. 2007, 33, 247–278.
  13. Hernandez-Matias, J.C.; Ocampo, J.R.; Hidalgo, A.; Vizan, A. Lean manufacturing and operational performance: Interrelationships between human-related lean practices. J. Manuf. Technol. Manag. 2019, 31, 217–235.
  14. Durand, J.; Hatzfeld, N. Living Labour: Life on the Line at Peugeot France; Springer: Berlin/Heidelberg, Germany, 2003.
  15. Lai, N.Y.G.; Jayasekara, D.; Wong, K.H.; Yu, L.J.; Kang, H.S.; Pawar, K.; Zhu, Y. Advanced automation and robotics for high volume labour-intensive manufacturing. In Proceedings of the 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), Ankara, Turkey, 26–28 June 2020; pp. 1–9.
  16. Castillo, C. The workers’ perspective: Emotional consequences during a lean manufacturing change based on VSM analysis. J. Manuf. Technol. Manag. 2022, 33, 19–39.
  17. Zhang, L.; Narkhede, B.E.; Chaple, A.P. Evaluating lean manufacturing barriers: An interpretive process. J. Manuf. Technol. Manag. 2017, 28, 1086–1114.
  18. Conti, R.; Angelis, J.; Cooper, C.; Faragher, B.; Gill, C. The effects of lean production on worker job stress. Int. J. Oper. Prod. Manag. 2006, 26, 1013–1038.
  19. Möldner, A.K.; Garza-Reyes, J.A.; Kumar, V. Exploring lean manufacturing practices’ influence on process innovation performance. J. Bus. Res. 2020, 106, 233–249.
  20. Koenigsaecker, G. Multiple sites multiply change and management challenges. Lean Manuf. Advis. 2000, 3–7.
  21. Leyer, M.; Reus, M.; Moormann, J. How satisfied are employees with lean environments? Prod. Plan. Control. 2021, 32, 52–62.
  22. Imran, M.Y.; Elahi, N.S.; Abid, G.; Ashfaq, F.; Ilyas, S. Impact of perceived organizational support on work engagement: Mediating mechanism of thriving and flourishing. J. Open Innov. Technol. Mark. Complex. 2020, 6, 82.
  23. Lewin, A.Y.; Välikangas, L.; Chen, J. Enabling open innovation: Lessons from Haier. Int. J. Innov. Stud. 2017, 1, 5–19.
  24. Di Guardo, M.C.; Marku, E.; Bonivento, W.M.; Castriotta, M.; Ferroni, F.; Galbiati, C.; Gorini, G.; Loi, M. When nothing is certain, anything is possible: Open innovation and lean approach at MVM. RD Manag. 2022, 52, 165–177.
  25. Chesbrough, H.; Tucci, C.L. The interplay between open innovation and lean startup, or, why large companies are not large versions of startups. Strat. Manag. Rev. 2020, 1, 277–303.
  26. Lai, N.Y.G.; Kuah, A.T.H.; Kim, C.H.; Wong, K.H. Toward sustainable express deliveries for online shopping: Reusing packaging materials through reverse logistics. Thunderbird Int. Bus. Rev. 2022, 64, 351–362.
  27. Näslund, D. Lean and six sigma-critical success factors revisited. Int. J. Qual. Serv. Sci. 2013, 5, 86–100.
  28. Demissie, A.; Zhu, W.; Kitaw, D.; Matebu, A. Quality assessment and improvement for Ethiopian garment enterprises. J. Ind. Prod. Eng. 2017, 34, 450–460.
  29. Belhadi, A.; Sha’ri, Y.B.M.; Touriki, F.E.; El Fezazi, S. Lean production in SMEs: Literature review and reflection on future challenges. J. Ind. Prod. Eng. 2018, 35, 368–382.
  30. Swarnakar, V.; Tiwari, A.K.; Singh, A. Evaluating critical failure factors for implementing sustainable lean six sigma framework in manufacturing organization. Int. J. Lean Six Sigma 2020, 11, 1069–1104.
  31. Hoque, I. Buyer-assisted lean intervention in supplier firms: A supplier development approach. J. Manuf. Technol. Manag. 2021, 33, 146–168.
  32. Zirar, A.; Trusson, C.; Choudhary, A. Towards a high-performance HR bundle process for lean service operations. Int. J. Qual. Reliab. Manag. 2021, 38, 25–45.
  33. Hutton, E.A.; Skues, J.L.; Wise, L.Z. Using control-value theory to predict completion intentions in vocational education students. Int. J. Train. Res. 2019, 17, 157–175.
  34. Sanders, A.; Wulfsberg, J. Industrie 4.0: Shopfloor Management im Wandel: Konzeptionelle Handlungsempfehlungen. ZWF Z. Wirtsch. Fabr. 2015, 110, 653–656.
  35. Ninan, N.; Roy, J.C.; Thomas, M.R. Training the workforce for industry 4.0. Int. J. Res. Soc. Sci. 2019, 9, 782–790.
  36. Noronha, C.; Endow, T. Informal training for skilled workers: Issues arising from a qualitative study in four sites in Rajasthan and Madhya Pradesh. Int. J. Train. Res. 2011, 9, 110–122.
  37. Na, K. The effect of on-the-job training and education level of employees on innovation in emerging markets. J. Open Innov. Technol. Mark. Complex. 2021, 7, 47.
  38. Soti, A.; Shankar, R.; Kaushal, O. Modeling the enablers of Six Sigma using interpreting structural modeling. J. Model. Manag. 2010, 5, 124–141.
  39. Maurer, T.J.; Weiss, E.M.; Barbeite, F.G. A model of involvement in work-related learning and development activity: The effects of individual, situational, motivational, and age variables. J. Appl. Psychol. 2003, 88, 707.
  40. Klein, H.J.; Noe, R.A.; Wang, C. Motivation to learn and course outcomes: The impact of delivery mode, learning goal orientation, and perceived barriers and enablers. Pers. Psychol. 2006, 59, 665–702.
  41. Sanders, J.; Oomens, S.; Blonk, R.W.; Hazelzet, A. Explaining lower educated workers’ training intentions. J. Workplace Learn. 2011, 23, 402–416.
  42. Kyndt, E.; Govaerts, N.; Dochy, F.; Baert, H. The learning intention of low-qualified employees: A key for participation in lifelong learning and continuous training. Vocat. Learn. 2011, 4, 211–229.
  43. Ho, Y.-Y.; Tsai, H.-T.; Day, J.-d. Using the theory of planned behaviour to predict public sector training participation. Serv. Ind. J. 2011, 31, 771–790.
  44. Bates, R.A. Public sector training participation: An empirical investigation. Int. J. Train. Dev. 2001, 5, 136–152.
  45. Tharenou, P. The relationship of training motivation to participation in training and development. J. Occup. Organ. Psychol. 2001, 74, 599–621.
  46. Al Karim, R.; Islam, M.W.; Rashid, H. How Organizational Training Affects Employee Performance: A Case on Bangladesh Private Banking Sector. Int. J. Entrep. Res. 2019, 2, 1–6.
  47. Ajzen, I. The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211.
  48. Wiethoff, C. Motivation to learn and diversity training: Application of the theory of planned behavior. Hum. Resour. Dev. Q. 2004, 15, 263–278.
  49. Renkema, A.; van der Kamp, M. The impact of a learning incentive measure on older workers. In Promoting Lifelong Learning for Older Workers. An International Overview; Tikkanen, T., Nyham, B., Eds.; Cedefop Reference Series, 65; Office for Official Publications of the European Communities: Luxembourg, 2006.
  50. Alok, S.; Kabra, A.; Mudam, A. Predicting the behavioural intention to adopt lean practices: An empirical study in the manufacturing industry. Int. J. Serv. Oper. Manag. 2018, 29, 557.
  51. Liu, Q.; Ye, G.; Feng, Y. Workers’ safety behaviors in the off-site manufacturing plant. Eng. Constr. Archit. Manag. 2020, 27, 765–784.
  52. Sanders, J.M.; Damen, M.A.; Van Dam, K. Are positive learning experiences levers for lifelong learning among low educated workers? In Evidence-Based HRM: A Global Forum for Empirical Scholarship; Emerald Group Publishing: Bingley, UK, 2015.
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