Blockchain technology adoption in food label systems. The impact on consumer purchase intentions.

Authors

  • Fabiana Sepe University of Naples Federico II

DOI:

https://doi.org/10.7433/s123.2024.10

Keywords:

blockchain technology, food label, behavioral intention

Abstract

Frame of the research: Food labels have a significant impact on shaping consumers’ intentions to purchase food products. The adoption of the Blockchain technology into food labels holds potential as an effective technology to enhance the data accessible to consumers, thereby shaping their purchasing patterns.

Purpose of the paper: This study adopts the Unified Theory of Acceptance and Use of Technology as a theoretical framework to understand how blockchain technology adoption in food label systems may influence consumers’ intentions toward purchasing labeled food.

Methodology: A research model with six hypotheses has been developed and tested on a sample of 781 users. The proposed model also highlights the importance of perceived trust and perceived product transparency on customers’ purchase intentions. Data have been analyzed adopting a PLS-SEM approach.

Findings: Results show that the adoption of Blockchain technology to protect information throughout the food supply chain can positively influence consumers’ purchase intentions.

Research limits: This work has some limitations, which could serve as a pathway for future investigations. First, it has been conducted within a single country (Italy). Then, even though it meets the required sample size for conducting analysis, future studies could enhance the number of observations to further reinforce this study’s findings.

Practical implications: This research contributes to a deeper understanding of the role of Blockchain technology in the food industry by providing empirical evidence of its potential as a valuable tool to sustain company purchases.

Originality of the paper: This study advances scientific knowledge of blockchain technology in the specific context of the food sector.

References

AJZEN, I. (1991), “The theory of planned behavior”, Organizational Behavior and Human Decision Processes, vol. 50, n. 11, pp. 179-211.

BEHNKE, K., JANSSEN, M.F.W.H.A. (2020). “Boundary conditions for traceability in food supply chains using blockchain technology.” International Journal of Information Management, vol. 52, pp. 101969.

BERRY, C., MUKHERJEE, A., BURTON, S., HOWLETT, E. (2015). “A COOL effect: The direct and indirect impact of country-of-origin disclosures on purchase intentions for retail food products”. Journal of Retailing, vol. 91, n. 3, pp. 533–542.

BUMBLAUSKAS, D., MANN, A., DUGAN, B., RITTMER, J. (2020). “A blockchain use case in food distribution: Do you know where your food has been?”. International Journal of Information Management, vol. 52, pp. 102008.

CENTOBELLI, P., CERCHIONE, R., VECCHIO, P. D., OROPALLO, E., SECUNDO, G. (2021). “Blockchain technology for bridging trust, traceability and transparency in circular supply chain”. Information & Management, pp. 103508.

CHANG, M., WALIMUNI, A.C., KIM, M.C., LIM, H.S. (2022). “Acceptance of tourism blockchain based on UTAUT and connectivism theory”. Technology in Society, vol. 71, pp. 102027.

DAVID, A., KUMAR, C.G., PAUL, P.V. (2022). “Blockchain technology in the food supply chain: Empirical analysis”. International Journal of Information Systems and Supply Chain Management, vol. 15, n. 3, pp. 1-12.

DAVIS, F.D. (1989), “Perceived usefulness, perceived ease of use and user acceptance of information technology”, MIS Quarterly, vol. 13, no. 3, pp. 319-339.

DEHGHANI, M., POPOVA, A., GHEITANCHI, S. (2022). “Factors impacting digital transformations of the food industry by adoption of blockchain technology”. Journal of Business & Industrial Marketing, vol. 37, no. 9, pp. 1818-1834.

DUAN, J., ZHANG, C., GONG, Y., BROWN, S., LI, Z. (2020). “A content-analysis based literature review in blockchain adoption within food supply chain”. International Journal of Environmental Research and Public Health, vol. 17, no. 5, pp. 1784.

DUBEY, R., GUNASEKARAN, A., BRYDE, D. J., DWIVEDI, Y.K., PAPADOPOULOS, T. (2020). “Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting”. International Journal of Production Research, vol. 58, n. 11, pp. 3381–3398.

FALK, R. F., MILLER, N. B. (1992). A primer for soft modeling. University of Akron Press.

FAO. 2017. The Future of Food and Agriculture: Trends and Challenges. Rome: Food and Agriculture Organization of the United Nations.

FENG, H., WANG, X., DUAN, Y., ZHANG, J., ZHANG, X. (2020). “Applying blockchain technology to improve agri-food traceability: A review of development methods, benefits and challenges”. Journal of Cleaner Production, vol. 260, pp. 121031.

FISHBEIN, M. AJZEN, I. (1975), Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research, Addison-Wesley, Reading, MA.

FORNELL, C., BOOKSTEIN, F.L. (1982). “Two structural equation models: LISREL and PLS applied to consumer exit-voice theory”. Journal of Marketing research, vol. 19, n. 4, pp. 440-452.

FRANCISCO, K., SWANSON, D. (2018). “The supply chain has no clothes: Technology adoption of blockchain for supply chain transparency”. Logistics, vol. 2, n. 1, pp. 2.

HAIR, J. F. (2009). Multivariate data analysis.

HAIR, J.F., BLACK, W.C., BABIN, B.J., ANDERSON, R.E. (2010). Multivariate data analysis (7th ed.). Englewood Cliffs: Prentice Hall.

HAIR, J., HOLLINGSWORTH, C.L., RANDOLPH, A.B., CHONG, A.Y.L. (2017). “An updated and expanded assessment of PLS-SEM in information systems research”. Industrial management & data systems, vol. 117, n. 3, pp. 442-458.

HARVARD BUSINESS REVIEW 2023. The Food and Beverage Sector Needs to Embrace Digital Transformation to Achieve Sustainability Goals, available at: https://hbr.org/sponsored/2023/05/the-food-and-beverage-sector-needs-to-embrace-digital-transformation-to-achieve-sustainability-goals (accessed 6 August, 2023).

HENSELER, J., RINGLE, C.M., SARSTEDT, M. (2015). “A new criterion for assessing discriminant validity in variance-based structural equation modeling”. Journal of the Academy of Marketing Science, vol. 43, pp. 115-135.

IBM 2022. IBM Global Consumer Study: Sustainability Actions Can Speak Louder Than Intent, available at: https://newsroom.ibm.com/2022-04-13-IBM-Global-Consumer-Study-Sustainability-Actions-Can-Speak-Louder-Than-Intent (accessed 8 August 2023).

JANSEN, L. (2003). “The challenge of sustainable development”. Journal of Cleaner Production, vol. 11, n. 3, pp. 231-245.

JENA, R.K. (2022). “Examining the factors affecting the adoption of blockchain technology in the banking sector: An extended UTAUT model”. International Journal of Financial Studies, vol. 10, n. 4, pp. 90.

KAMBLE, S.S., GUNASEKARAN, A., SHARMA, R. (2020). “Modeling the blockchain enabled traceability in agriculture supply chain”. International Journal of Information Management, vol. 52, pp. 101967.

KHAN, S.A., MUBARIK, M.S., KUSI‐SARPONG, S., GUPTA, H., ZAMAN, S.I., MUBARIK, M. (2022). “Blockchain technologies as enablers of supply chain mapping for sustainable supply chains”. Business Strategy and the Environment, vol. 31, n. 8, pp. 3742-3756.

KOCK, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, vol. 11, n.4, pp. 1-10.

KOCK, N. (2018). “Should bootstrapping be used in pls-sem? Toward stable p-value calculation methods”. Journal of Applied Structural Equation Modeling, vol. 2, n.1, pp. 1-12.

LEE, E.J., BAE, J., KIM, K.H. (2020). “The effect of environmental cues on the purchase intention of sustainable products”. Journal of Business Research, vol. 120, pp. 425–433.

LI, K., LEE, J.Y., GHAREHGOZLI, A. (2023). “Blockchain in food supply chains: A literature review and synthesis analysis of platforms, benefits and challenges”. International Journal of Production Research, vol. 61, n. 11, pp. 3527-3546.

LIN, X., CHANG, S.C., CHOU, T.H., CHEN, S.C., RUANGKANJANASES, A. (2021). “Consumers’ intention to adopt blockchain food traceability technology towards organic food products”. International Journal of Environmental Research and Public Health, vol. 18, n. 3, pp. 912.

LIU, H., WANG, Y., HE, G., MA, R., FU, S. (2023). “The impact of environmental information disclosure of origin using blockchain technology on online consumer behaviour: A combination of SEM and NCA approaches”. Journal of Cleaner Production, pp. 138449.

LOHMER, J., LASCH, R. (2020). “Blockchain in operations management and manufacturing: Potential and barriers”. Computers and Industrial Engineering, vol. 149, pp. 106789.

MAROZZO, V., VARGAS-SÁNCHEZ, A., ABBATE, T., D'AMICO, A. (2022). “Investigating the importance of product traceability in the relationship between product authenticity and consumer willingness to pay”. Sinergie Italian Journal of Management, vol. 40, n. 2, pp. 21-39.

MIN, H. (2019). “Blockchain technology for enhancing supply chain resilience”. Business Horizons, vol. 62, n. 1, pp. 35–45.

MINGIONE M., BENDIXEN M., ABRATT R. (2020) “Uncovering the sources of brand authenticity in the digital era: evidence from Italian winery”, Sinergie Italian Journal of Management, vol. 38, n.1, pp. 181-205.

MOLLENKOPF, D.A., PEINKOFER, S.T., CHU, Y. (2022). “Supply chain transparency: Consumer reactions to incongruent signals”. Journal of Operations Management, vol. 68, n. 4, pp. 306-327.

MONTECCHI, M., PLANGGER, K., ETTER, M. (2019). “It’s real, trust me! Establishing supply chain provenance using blockchain”. Business Horizons, 62(3), 283–293.

MUKHERJEE, S., BARAL, M.M., LAVANYA, B.L., NAGARIYA, R., SINGH PATEL, B., CHITTIPAKA, V. (2023). “Intentions to adopt the blockchain: investigation of the retail supply chain”. Management Decision, vol. 61, n. 5, pp. 1320-1351.

OGUNTEGBE, K.F., DI PAOLA, N., VONA, R. (2021). “Blockchain technology, social capital and sustainable supply chain management”. Sinergie Italian Journal of Management, vol. 39, n. 3, pp. 163-188.

PARMENTOLA, A., PETRILLO, A., TUTORE, I., DE FELICE, F. (2022). “Is blockchain able to enhance environmental sustainability? A systematic review and research agenda from the perspective of Sustainable Development Goals (SDGs)”. Business Strategy and the Environment, vol. 31, n. 1, pp. 194-217.

QUEIROZ, M.M., FOSSO WAMBA, S., DE BOURMONT, M., TELLES, R. (2021). “Blockchain adoption in operations and supply chain management: empirical evidence from an emerging economy”. International Journal of Production Research, vol. 59, n. 20, pp. 6087-6103.

RANA, R. L., TRICASE, C., DE CESARE, L. (2021). “Blockchain technology for a sustainable agri-food supply chain”. British Food Journal, vol. 123, n. 11, pp. 3471-3485.

ROGERSON, M., PARRY, G.C. (2020). “Blockchain: Case studies in food supply chain visibility”. Supply Chain Management, vol. 25, n. 5, pp. 601–614.

SANDER, F., SEMEIJN, J., MAHR, D. (2018). The acceptance of blockchain technology in meat traceability and transparency. British Food Journal, vol. 120, n. 9, pp. 2066-2079

SHANKAR, V., URBAN, G.L., SULTAN, F. (2002). “Online trust: a stakeholder perspective, concepts, implications, and future directions”. The Journal of Strategic Information Systems, vol. 11, n. (3-4), pp. 325-344.

SHARMA, A., SHARMA, A., SINGH, R.K., BHATIA, T. (2023). “Blockchain adoption in agri-food supply chain management: an empirical study of the main drivers using extended UTAUT”. Business Process Management Journal, vol. 29, n. 3, pp. 737-756.

SHIN, D., BIANCO, W.T. (2020). “In blockchain we trust: does blockchain itself generate trust?”. Social Science Quarterly, vol. 101, n. 7, pp. 2522-2538.

SHMUELI, G., SARSTEDT, M., HAIR, J.F., CHEAH, J.H., TING, H., VAITHILINGAM, S., & RINGLE, C. M. (2019). Predictive model assessment in PLS-SEM: guidelines for using PLSpredict. European journal of marketing, vol. 53, n. 11, pp. 2322-2347.

SINGH, V., SHARMA, S.K. (2023). “Application of blockchain technology in shaping the future of food industry based on transparency and consumer trust”. Journal of Food Science and Technology, vol. 60, n. 4, pp. 1237-1254.

STATISTA 2023. FOOD REPORT – 2023, available at: https://www.statista.com/study/55496/food-report-2021/ (accessed 7 August 2023).

STATISTA 2023. Revenue of the food market worldwide from 2018 to 2028, available at: https://www.statista.com/forecasts/1243605/revenue-food-market-worldwide (accessed 4 October 2023).

STRANIERI, S., RICCARDI, F., MEUWISSEN, M.P., SOREGAROLI, C. (2021). “Exploring the impact of blockchain on the performance of agri-food supply chains”. Food Control, vol. 119, pp. 107495.

SUNNY, J., UNDRALLA, N., PILLAI, V.M. (2020). “Supply chain transparency through blockchain-based traceability: An overview with demonstration”. Computers & Industrial Engineering, vol. 150, pp. 106895.

TARHINI, A., EL-MASRI, M., ALI, M. AND SERRANO, A. (2016), “Extending the UTAUT model to understand the customers’ Acceptance and use of internet banking in Lebanon: a structural equation modeling approach”, Information Technology & People, vol. 29, n. 4, pp. 830-849.

TREIBLMAIER, H. (2018). “The impact of the blockchain on the supply chain: A theory- based research framework and a call for action”. Supply Chain Management: An International Journal, vol. 23, n. 6, pp. 545–559.

TREIBLMAIER, H. (2019). “Toward more rigorous blockchain research: Recommendations for writing blockchain case studies”. Frontiers in Blockchain, vol. 2, n. 3, pp. 1–15.

TREIBLMAIER, H., GARAUS, M. (2023). “Using blockchain to signal quality in the food supply chain: The impact on consumer purchase intentions and the moderating effect of brand familiarity”. International Journal of Information Management, vol. 68, pp. 102514.

VENKATESH, V., MORRIS, M.G., DAVIS, G.B., DAVIS, F.D. (2003). “User acceptance of information technology: Toward a unified view”. MIS Quarterly, pp. 425-478.

VU, N., GHADGE, A., BOURLAKIS, M. (2023). “Blockchain adoption in food supply chains: A review and implementation framework”. Production Planning & Control, vol. 34, n. 6, pp. 506-523.

WONG, K.K.K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing bulletin, vol. 24, n. 1, pp. 1-32.

WONG, L.W., TAN, G.W.H., LEE, V.H., OOI, K.B. SOHAL, A. (2020), “Unearthing the determinants of Blockchain adoption in supply chain management”, International Journal of Production Research, vol. 58, n. 7, pp. 2100-2123.

WORLD HEALTH ORGANIZATION (2019). Food safety, available at https://apps.who.int/iris/handle/10665/160165. (Accessed 20 July 2023).

WU, W., ZHANG, A., VAN KLINKEN, R.D., SCHROBBACK, P., MULLER, J.M. (2021). “Consumer trust in food and the food system: a critical review”. Foods, vol. 10, n. 10, pp. 2490.

YEH, J.Y., LIAO, S.C., WANG, Y.T., CHEN, Y.J. (2019, November). Understanding consumer purchase intention in a blockchain technology for food traceability and transparency context. In 2019 IEEE Social Implications of Technology (SIT) and Information Management (SITIM) (pp. 1-6). IEEE.

YIANNAS, F. (2018). A new era of food transparency powered by blockchain. Innovations: Technology, Governance, Globalization, vol. 12, n. 1–2, pp. 46–56.

YOO, C.W., PARAMESWARAN, S., KISHORE, R. (2015). “Knowing about your food from the farm to the table: Using information systems that reduce information asymmetry and health risks in retail contexts”. Information & Management, vol. 52, n. 6, pp. 692–709.

ZHAO, G., LIU, S., LOPEZ, C., LU, H., ELGUETA, S., CHEN, H., BOSHKOSKA, B.M. (2019). “Blockchain technology in agri-food value chain management: A synthesis of applications, challenges and future research directions”. Computers in industry, vol. 109, pp. 83-99.

ZHOU, L., WANG, W., XU, J. D., LIU, T., GU, J. (2018). Perceived information transparency in B2C e-commerce: An empirical investigation. Information & Management, vol. 55, n. 7, pp. 912-927.

Downloads

Published

2024-04-30