Abstract

The paper highlights the scientific debate on the Neurolinguistic programming (NLP) issue. NLP is a collection of approaches, communication tools, techniques, and perspectives that determine how individuals think and communicate through language. NLP is used to recognize and modify patterns of human behavior. The sensory representational system, or the method for recognizing representational systems, which is made up of five main senses, influences this process. Systematization literary sources and approaches to this issue indicate that three sensory representational systems exist in the NLP approach: visual, auditory, and kinesthetic (VAK), and that the individual’s preferred representational sensory system could explain manifested behavior and characteristics in the managerial and marketing sphere. The central purpose of the research and the significance of choice made about this area of interest is to determine each individual’s preferred representational sensory system (VAK) utilizing the original PRSS-VAK methodology. The methodological research tool was the PRSS-VAK methodology which contains nine statements, which are assessed on a scale from 1 (the least describes me) to 4 (the most describes me). The PRSS-VAK methodology would help to comprehend patterns of an individual’s behavior and allied cognitive or emotional processes. EFA (Exploratory Factor Analysis) with Varimax rotation was used to verify the methodology on a sample of 214 respondents from the Slovak Republic, and CFA (Confirmatory Factor Analysis) was used to validate the structure on a sample of 268 respondents from the Slovak Republic. This research empirically and theoretically confirms that one of the preferred representational sensory systems may be dominant. However, this may change regarding the current situation (stimulus, impulse). The research results could be beneficial as a springboard not only for researchers concerning this issue. It also indicates that quantitative research does not determine exactly to which category (visual, auditory, or kinesthetic) a certain individual belongs. Using the identification of a preferred representational sensory system could help to facilitate both management and marketing communications.

Keywords: neurolinguistic programming, human senses, PRSS-VAK methodology, sensory systems.

JEL Classification: M1, M2, M3.

Cite as: Birknerova, Z., Misko, D., Ondrijova, I., Tomkova, A., Cema, V., & Cigarska, B. N (2022). Identification of Preferred Representational Sensory System in Neuro-Linguistic Programming Marketing and Management of Innovations, 3, 114-124. https://doi.org/10.21272/mmi.2022.3-10

This work is licensed under a Creative Commons Attribution 4.0 International License

References

1. Amirhosseini, M. H., & Kazemian, H. (2019). Automating the process of identifying the preferred representational system in Neuro Linguistic Programming using Natural Language Processing. Cognitive processing, 20(2), 175-193. [Google Scholar] [CrossRef]
2. Aslaksen, K., Haga, M., Sigmundsson, H., & Lorås, H. (2020). Evidence for a common multi-modal learning style in young adults? A psychometric investigation of two modality-specific learning style inventories. In Frontiers in Education (Vol. 5, p. 40). Frontiers Media SA. [Google Scholar] [CrossRef]
3. Bandler, R., & Grinder, J. (1975). The structure of magic (Vol. 1). Palo Alto, CA: Science and Behavior Books. [Google Scholar]
4. Bartkowiak, J. (2012). NLP in qualitative research. International Journal of Market Research, 54(4), 451-453. [Google Scholar] [CrossRef] 
5. Bensted, C. (2014). Representational systems. Retrieved from [Link]
6. Carter, T. (2001). Despite its detraction, NLP gains popularity. ABA Journal, 87(9), 63-63. [Google Scholar]
7. Davis, D. I., & Davis, S. L. (1991). Belief change and neurolinguistic programming. Family Dynamics of Addiction Quarterly. [Google Scholar]
8. Dimmick, S. (2017). Successful Communication Through NLP: A Trainer’s Guide. Routledge. [Google Scholar]
9. El-Ashry, M. M. (2021). The importance of neuro linguistic programming skills as a communication tool in the workplace. Journal of Global Scientific Research, 6(1), 1108-1123. [Google Scholar]
10. Fahim, A., Rehman, S., Fayyaz, F., Javed, M., Alam, M. A., Rana, S., … & Alam, M. K. (2021). Identification of preferred learning style of medical and dental students using VARK questionnaire. BioMed Research International, Volume 2021, 1-7. [Google Scholar] [CrossRef]
11. Fleming, N. D. (1995). I’m different; not dumb. Modes of presentation (VARK) in the tertiary classroom. In Research and development in higher education, Proceedings of the 1995 Annual Conference of the Higher Education and Research Development Society of Australasia (HERDSA), HERDSA (Vol. 18, pp. 308-313). [Google Scholar]
12. Grinder, J., & Bandler, R. (1976). The structure of magic: II. Science & Behavior. [Google Scholar]
13. Harrington, D. (2009). Confirmatory factor analysis. Oxford university press. [Google Scholar]
14. Hendel, R. J. (2022). A Transdisciplinary Approach to Differentiated Instruction1. Journal of Systemics, Cybernetics and Informatics, 20(1), 65-85. [Google Scholar] [CrossRef]
15. Ilyas, M. (2017). Finding relationships between acquisition of basic skills and neuro-linguistic programming techniques. Constructions, 34, 5.  [Google Scholar]
16. Joey, L., & Yazdanifard, R. (2015). Can Neuro-Linguistic Programming (NLP) be used as contemporary and effective skill for an exceptional manager in an organization?. International journal of management, accounting and economics, 2(5), 456-465. [Google Scholar]
17. John, M. T., Feuerstahler, L., Waller, N., Baba, K., Larsson, P., Celebić, A., … & Reißmann, D. R. (2014). Confirmatory factor analysis of the oral health impact profile. Journal of Oral Rehabilitation, 41(9), 644-652. [Google Scholar] [CrossRef]
18. Kong, E. (2012). The Potential of Neuro‑Linguistic Programming in Human Capital Development. Electronic Journal of Knowledge Management, 10(2), 131-141. [Google Scholar]
19. Koohestani, H. R., & Baghcheghi, N. (2020). A comparison of learning styles of undergraduate health-care professional students at the beginning, middle, and end of the educational course over a 4-year study period (2015–2018). Journal of education and health promotion, 9, 1–6. [Google Scholar] [CrossRef]
20. Kyriazos, T. A. (2018). Applied psychometrics: sample size and sample power considerations in factor analysis (EFA, CFA) and SEM in general. Psychology, 9(08), 2207. [Google Scholar] [CrossRef]
21. Lajcin, D., Frankovsky, M., & Stefko, R. (2012). Possibilities of predicting the behavior of managers when coping with demanding situations in managerial work. Ekonomicky casopis, 60(8), 835-853. [Google Scholar]
22. Lavan, I. (2002). NLP in business–or more than a trip to the zoo. Industrial and Commercial Training, 34(5), 182–187. [Google Scholar] [CrossRef]
23. Lazarus, J. (2010). Successful NLP. Hachette UK. [Google Scholar]
24. Leite, W. L., Svinicki, M., & Shi, Y. (2010). Attempted validation of the scores of the VARK: Learning styles inventory with multitrait–multimethod confirmatory factor analysis models. Educational and psychological measurement, 70(2), 323-339. [Google Scholar] [CrossRef]
25. Linder-Pelz, S., & Hall, L. M. (2007). The theoretical roots of NLP-based coaching. The Coaching Psychologist, 3(1), 12-17. [Google Scholar]
26. Mainwaring, S., & Skinner, H. (2009). Reaching donors: neuro-linguistic programming implications for effective charity marketing communications. The Marketing Review, 9(3), 231-242. [Google Scholar] [CrossRef]
27. Maisenbacher, O. M. (2014). Neuro-Linguistic Programming (NLP) as a Communication Tool for Management. University of Johannesburg (South Africa). [Google Scholar]
28. McAfee, K. (2014). «The power of words», an introduction to NLP representational systems, becoming a more effective communicator. Retrieved from [Link]
29. McNeish, D., & Wolf, M. G. (2022). Dynamic fit index cutoffs for one-factor models. Behavior Research Methods, 1-18. [Google Scholar] [CrossRef]
30. Mohl, A. (1998). El aprendiz de brujo: Manual de ejercicios prácticos de programación neurolingüística/[trad. del alemán por Ed. Sirio] (Vol. 1). Editorial Sirio, SA. [Google Scholar]
31. Newton, P. M. (2015). The learning styles myth is thriving in higher education. Frontiers in psychology, 1908. [Google Scholar] [CrossRef]
32. Nompo, R. S., Pragholapati, A., & Thome, A. L. (2021). Effect of Neuro-Linguistic Programming (NLP) on Anxiety: A Systematic Literature Review. KnE Life Sciences, 4(1), 496-507. [Google Scholar] [CrossRef]
33. Nurjanah, N., Sari, F. F., & Supriyaddin, S. (2022). Pengaruh Model VAK (Visual, Auditory, Kinestethic) terhadap Hasil Belajar IPA Siswa Kelas IV SDN 07 Manggelewa Tahun Pelajaran 2021/2022. DIKSI: Jurnal Kajian Pendidikan dan Sosial, 3(1), 81-89. [Google Scholar] [CrossRef]
34. Peker, B. G. (2010). Getting to know the art of excellence: What neuro linguistic programming can offer to teachers’ thinking and reprogramming skills. Ekev Academic Review, 14(44), 87-98. [Google Scholar]
35. Peugh, J., & Feldon, D. F. (2020). «How well does your structural equation model fit your data?»:
    Is marcoulides and Yuan’s equivalence test the answer?. CBE—Life Sciences Education, 19(3), es5. [Google Scholar] [CrossRef]
36. Pollitt, D. (2010). NLP helps Metronet Rail maintenance employees to stay on track: Techniques prove their worth in a period of organizational upheaval. Human Resource Management International Digest, 18(4), 20-21. [Google Scholar]
37. Roderique‐Davies, G. (2009). «Neuro‐linguistic programming: cargo cult psychology?». Journal of Applied Research in Higher Education, 1(2), 58-63. [Google Scholar] [CrossRef]
38. Sadowski, W., & Stanney, K. (2002). Presence in virtual environments. In Handbook of virtual environments (pp. 831-846). CRC Press. [Google Scholar]
39. Saputri, L., Mardiati, M., Sitepu, D. R., & Afni, K. (2022). Spatial Capabilities Through The Auditory Kinesthetic Visualization Self Regulated Learning Model In The Covid-19 Era. International Journal of Social Service and Research, 2(2), 114-123. [Google Scholar] [CrossRef]
40. Savalei, V. (2021). Improving fit indices in structural equation modeling with categorical data. Multivariate behavioral research, 56(3), 390-407. [Google Scholar] [CrossRef]
41. Shi, D., Lee, T., & Maydeu-Olivares, A. (2019). Understanding the model size effect on SEM fit indices. Educational and psychological measurement, 79(2), 310-334. [Google Scholar] [CrossRef]
42. Skinner, H., & Stephens, P. (2003). Speaking the same language: The relevance of neuro‐linguistic programming to effective marketing communications. Journal of Marketing Communications, 9(3), 177-192. [Google Scholar] [CrossRef]
43. Steinbach, A. M. (1984). Neurolinguistic programming: a systematic approach to change. Canadian Family Physician, 30, 147. [Google Scholar]
44. Stevenson, M. (2015). Introduction to Neuro-Linguistic Programming. NLP Representational System Preference Test. Transform Destiny NLP. Version 1.3, 5/25/15, Inc. 800-497-6614, p. 20.
45. Stone, B. M. (2021). The Ethical Use of Fit Indices in Structural Equation Modeling: Recommendations for Psychologists. Frontiers in Psychology, 12. [Google Scholar] [CrossRef]
46. Tastan, K. (2014). Nöro linguistik programlama ve aile hekimliğinde kullanımı. Konuralp Medical Journal, 6(3), 63-66. [Google Scholar]
47. Thompson, J. E., Courtney, L., & Dickson, D. (2002). The effect of neurolinguistic programming
    on organisational and individual performance: a case study. Journal of European Industrial Training, 26, 292–298. [Google Scholar] [CrossRef]
48. Tosey, P., & Mathison, J. (2003). Neuro‐linguistic programming and learning theory: A response. The Curriculum Journal, 14(3), 371-388. [Google Scholar] [CrossRef]
49. Tosey, P., & Mathison, J. (2008). Neurolinguistic programming, learning and education: An introduction. Retrieved from [Link]
50. Tosey, P., & Mathison, J. (2010). Exploring inner landscapes through psychophenomenology: The contribution of neuro‐linguistic programming to innovations in researching first person experience. Qualitative Research in Organizations and Management: An International Journal, 5(1), 63–82. [Google Scholar] [CrossRef]
51. Une, D. (2022). History Learning with the Visual Auditory Kinesthetic Model at SMA Negeri 1 Gorontalo. International Journal of Multicultural and Multireligious Understanding, 9(5), 263-269. [Google Scholar] [CrossRef]
52. Willmer, M., Westerberg Jacobson, J., & Lindberg, M. (2019). Exploratory and Confirmatory Factor Analysis of the 9-Item Utrecht Work Engagement Scale in a multi-occupational female sample: a cross-sectional study. Frontiers in psychology, 10, 2771. [Google Scholar] [CrossRef]