SCIENCE ARTICLE
Identifying and prioritising barriers to neuromarketing adoption: an empirical study of the automotive sector in India using TOE and DEMATEL
 
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1
Research Scholar, Symbiosis International (Deemed University),, India
 
2
Symbiosis Institute of Business Management, Symbiosis International (Deemed University), India
 
 
Submission date: 2026-03-22
 
 
Final revision date: 2026-07-05
 
 
Acceptance date: 2026-07-31
 
 
Online publication date: 2026-09-28
 
 
Publication date: 2026-09-24
 
 
Corresponding author
Pratik B Puprediwar   

Research Scholar, Symbiosis International (Deemed University),, India
 
 
Management 2026;(2):216-247
 
KEYWORDS
JEL CLASSIFICATION CODES
D21
M3
D9
 
TOPICS
ABSTRACT
Research background and purpose:
Various companies conduct traditional market research studies to test digital interfaces, product de-signs, advertisements. etc. This helps them capture customer response and make their offering more relevant. Neuroscience tools like eye tracking, facial coding, EEG (Electroencephalogram) used in market research is Neuromarketing. Though Neuromarketing has multiple advantages over tradi-tional research like removing interviewer / customer bias, decoding real time emotions, etc. Still its adoption among companies has been very limited.

Design/methodology/approach:
A qualitative‑dominant, multi‑method strategy is employed, combining literature review, semi‑structured interviews with automotive organizations professional in sales, marketing and product design functions

Findings:
TOE (Technology, Organization, Environment) Framework and Dematel (Decision Making Trial and Evaluation Laboratory) model are implemented to prioritize the barriers to adoption of Neuromar-keting and understand the causal relationship between them. Top technological barriers of Neuro-marketing are complex technology and expensive. Top environmental barriers are lesser adoption among peers & competition. And top organization barrier is preference towards traditional methods of market research. The study also gives recommendations on how to overcome barriers of Neuro-marketing. It has various implications for market research companies, automotive companies and market research associations.

Value added and limitations:
This study utilises the research work done by done academia and considers the views of automotive industry to enhance industry – academia partnership. If the top barriers identified in this study are overcome, it can increase the spend on Neuromarketing and hence increase the revenue of market research companies. It can also benefit automotive companies to test the advertisements and prod-uct designs in advance to avoid major cost of failure of going wrong. Though the literature review is global, the study outcomes are based on interaction with automotive company representatives in India. As the concept of Neuromarketing is still emerging in India, there could be subjectivity in response from the automotive company representatives met in this study. In future, similar studies can be conducted in various countries and sectors. Larger sample can be also covered including various functions in automotive sector, market research companies and associations like MRSI. This can help in better generalization of the findings.
AUTHORS' CONTRIBUTIONS
P.P.: article conception, theoretical content of the article, research methods applied, conducting the research, data collection, analysis and interpretation of results, draft manuscript preparation. P.T.: article conception, theoretical content of the article, research methods applied, analysis and interpretation of results, draft manuscript preparation.
ADDITIONAL INFORMATION
During the preparation of this work the authors did not use Generative AI and AIassisted technologies in the writing process
REFERENCES (33)
1.
Alsharif, A. H., Salleh, N. Z. M., Baharun, R., Abuhassna, H., & Hashem, A. R. (2022). A global research trends of neuromarketing: 2015-2020. Revista de Comunicación, 21(1), 15-32.
 
2.
Aldayel, M., Ykhlef, M., & Al-Nafjan, A. (2020). Deep learning for EEG-based preference classification in neuromarketing. Applied Sciences, 10(4), 1525.
 
3.
Baños-González, M., Baraybar-Fernández, A., & Rajas-Fernández, M. (2020). The Application of Consumer Neuroscience Techniques in the Spanish Advertising Industry: Weaknesses and Opportunities for Development. Frontiers in Psychology, 11.
 
4.
Brenninkmeijer, J., Schneider, T., & Woolgar, S. (2020). Witness and silence in neuromarketing: Managing the gap between science and its application. Science, Technology, & Human Values, 45(1), 62–86. https://doi.org/10.1177/016224....
 
5.
Chatterjee, S., Rana, N. P., Dwivedi, Y. K., & Baabdullah, A. M. (2021). Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model. Technological Forecasting and Social Change, 170, 120880.
 
6.
Cherubino, P., Martinez-Levy, A. C., Caratù, M., Cartocci, G., Di Flumeri, G., Modica, E., ... & Trettel, A. (2019). Consumer behaviour through the eyes of neurophysiological measures: State‐ofthe‐art and future trends. Computational Intelligence and Neuroscience, 2019(1), 1976847.
 
7.
Dutta, M., Trayambak, S., & Sharma, M. (2024, February). A study on neuromarketing variables in automobile sector with special reference to Indian consumers. In 2024 4th International Conference on Innovative Practices in Technology and Management (ICIPTM) (pp. 1219–1224). IEEE. https://doi.org/10.1109/ ICIPTM59564.2024.10563298.
 
8.
De Oliveira, J. H. C. (2014). Neuromarketing and sustainability: challenges and opportunities for Latin America. Latin American Journal of Management for Sustainable Development, 1(1), 35-42.
 
9.
Dikmen, F. C., & Taş, Y. (2018). Applying DEMATEL approach to determine factors affecting hospital service quality in a university hospital: A case study. Journal of Administrative Sciences, 16(32), 11-28.
 
10.
ESOMAR. (n.d.). Global market research. https://esomar.org/global-mark... Exchange4media. (2024, February 15). Paid search leads in auto sector’s digital AdEx. https://www.exchange4media.com....
 
11.
Kazemi, A., Mehrani, S., & Homayoun, S. (2025). Risk in Sustainability Reporting: Designing a DEMATEL-Based Model for Enhanced Transparency and Accountability. Sustainability, 17(2), 549.
 
12.
Kumar, H., & Singh, P. (2015). Consumer Neuroscience: An Emerging Tool of Market Research. International Journal of Engineering and Management Research, 5, 530–535.
 
13.
Kumar, A., Luthra, S., Mangla, S. K., Garza-Reyes, J. A., & Kazancoglu, Y. (2023). Analysing the adoption barriers of low-carbon operations: A step forward for achieving net-zero emissions. Resources Policy, 80, 103256.
 
14.
Kurtoglu, A. L., & Ferman, A. M. (2020). An exploratory research among fashion business leaders and neuromarketing company executives on the perception of applied neuromarketing. Journal of Management Marketing and Logistics, 7(2), 72-80.
 
15.
Hengsberg, K. (2015). Neuromarketing: Fundamentals and insights for advantageous advertising in a luxury watch context [Master’s thesis, Dublin Business School]. Dublin Business School eSource. http://hdl.handle.net/10788/23....
 
16.
King, N. (2012). Doing template analysis. In G. Symon & C. Cassell (Eds.), Qualitative organizational research: Core methods and current challenges (pp. 426–450). Sage.
 
17.
Lim, W. M. (2018). Demystifying neuromarketing. Journal of Business Research, 91, 205-220.
 
18.
Meyerding, S. G., & Mehlhose, C. M. (2020). Can neuromarketing add value to the traditional marketing research? An exemplary experiment with functional near-infrared spectroscopy (fNIRS). Journal of Business Research, 107, 172-185.
 
19.
Mohsen, H., & Mostafa, E. M. (2020). The Relationship between the Applicability of Neuromarketing and Competitiveness: An Applied Study on Real-Estate Marketing Companies in Egypt. Open Journal of Business and Management, 8(05), 2006-2028.
 
20.
Market Research Society of India. (2024, December 24). Indian research and insights industry report 2024. https://www.mrsi.co.in/newsdet...
 
21.
Mardones, R. E., & Ulloa, J. (2017). Construcción subjetiva del territorio: Experiencias del habitar la provincia del Bio Bio, Chile [ Subjective construction of the territory: Experiences of dwell the province of Bio Bio, Chile]. Estudos de Psicologia, 22(4), 422-431.
 
22.
NITI Aayog. (2025, April). Automotive industry: Powering India’s participation in global value chains. https://www.niti.gov.in/sites/...
 
23.
Pillai, R., & Sivathanu, B. (2020). Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations. Benchmarking: an International Journal, 27(9), 2599-2629.
 
24.
Plakhin, A., Semenets, I., Ogorodnikova, E., & Khudanina, M. (2018). New directions in the development of neuromarketing and behavioral economics. MATEC Web of Conferences, 184, Article 04023. https://doi.org/10.1051/matecc....
 
25.
Puprediwar, P. B., & Tapas, P. (2024). Beyond traditional consumer research-current adoption and next steps for neuromarketing. Management, 28(2), 70-105. https://doi.org/10.58691/man/1....
 
26.
Sharma, M., & Nair, R. (2025). Analysis of barriers to introducing circular economy practices in the automotive industry within Rajasthan, India. Circular Economy and Sustainability, 5(4), 3053-3071.
 
27.
Saunders, M. N. K., Lewis, P., & Thornhill, A. (2007). *Research methods for business students* (4th ed.). Pearson Education.
 
28.
Prabhu, S. (2024, May 27). Neuromarketing: Transforming consumer engagement in India. LinkedIn. https://www.linkedin.com/pulse....
 
29.
Uday, R. M., Salman, S., Karim, M. R., Ar Salan, M. S., Islam, M., & Shahriar, M. (2025). Assessing the barriers to lean manufacturing adoption in the furniture industry of Bangladesh: a fuzzy-DEMATEL study. International Journal of Industrial Engineering and Operations Management, 7(1), 44-67.
 
30.
Widuri, R., O’Connell, B., & Yapa, P. W. (2016). Adopting generalized audit software: an Indonesian perspective. Managerial Auditing Journal, 31(8/9), 821-847.
 
31.
Xu, X., Tatge, L., Xu, X., & Liu, Y. (2024). Blockchain applications in the supply chain management in German automotive industry. Production Planning & Control, 35(9), 917-931.
 
32.
Yoon, C. (2023). Factors affecting the adoption of digital marketing in non-profit organizations: An empirical study. Administrative Sciences, 14(1), 10.
 
33.
Zahraee, S. M. (2016). A survey on lean manufacturing implementation in a selected manufacturing industry in Iran. International Journal of Lean Six Sigma, 7(2), 136-148.
 
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