Consumer Perceptions of Precision Livestock Farming—A Qualitative Study in Three European Countries
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Participants
2.2. Focus Group Procedure
2.3. Topics and Questions Addressed
2.4. Data Analysis
3. Results
3.1. Consumer Perceptions of PLF: Benefits and Fears
- ‘[PLF data makes the] lives of pigs transparent’.
- ‘[PLF technologies provide] faster and detailed information about total effects in the big picture [of livestock farming]’.
3.2. Consumer Perceptions of PLF: Transformational Impact on Livestock Farming
3.3. Consumer Perceptions of PLF: Is It Purely a Matter of Communication?
4. Discussion and Implications
4.1. The Fear of Industrialisation, Robotisation and Digitalisation
4.2. The Concerns Related to Cyber-Crime and Data Misuse
4.3. The Concerns Relating to Inadequate Communication Systems
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Acknowledgments
Conflicts of Interest
References
- Berckmans, D. Precision livestock farming technologies for welfare management in intensive livestock systems. Rev. Sci. Technol. 2014, 33, 189–196. [Google Scholar] [CrossRef] [PubMed]
- Buller, H.; Blokhuis, H.; Lokhorst, K.; Silberberg, M.; Veissier, I. Animal welfare management in a digital world. Animals 2020, 10, 1779. [Google Scholar] [CrossRef] [PubMed]
- Rowe, E.; Dawkins, M.S.; Gebhardt-Henrich, S.G. A systematic review of precision livestock farming in the poultry sector: Is technology focused on improving bird welfare? Animals 2019, 9, 614. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Benjamin, M.; Yik, S. Precision livestock farming in swine welfare: A review for swine practitioners. Animals 2020, 9, 133. [Google Scholar] [CrossRef] [Green Version]
- Caria, M.; Sara, G.; Todde, G.; Polese, M.; Pazzona, A. Exploring smart glasses for augmented reality: A valuable and integrative tool in precision livestock farming. Animals 2020, 9, 903. [Google Scholar] [CrossRef] [Green Version]
- Patelli, N.; Mandrioli, M. Blockchain technology and traceability in the agrifood industry. J. Food Sci. 2020, 85, 3670–3678. [Google Scholar] [CrossRef] [PubMed]
- Zhang, Y.; Lee, S.; van de Ligt, J.L.G. Blockchain Technology: What Is It? 2019. Available online: https://vetmed.umn.edu/sites/vetmed.umn.edu/files/shmp_2018l19.47_blockchain_technology_part_2-sciencepage.pdf (accessed on 19 February 2021).
- Ingram, J.; Damian, M. What are the implications of digitalisation for agricultural knowledge? Front. Sustain. Food Syst. 2020, 4, 66. [Google Scholar] [CrossRef]
- Rotz, S.; Duncan, E.; Small, M.; Botschner, J.; Dara, R.; Mosby, I.; Fraser, E.D. The politics of digital agricultural technologies: A preliminary review. Sociol. Rural. 2019, 59, 203–229. [Google Scholar] [CrossRef]
- Abeni, F.; Petrera, F.; Galli, A. A survey of Italian dairy farmers’ propensity for precision livestock farming tools. Animals 2019, 9, 202. [Google Scholar] [CrossRef] [Green Version]
- Aune, J.B.; Coulibaly, A.; Giller, K.E. Precision farming for increased land and labour productivity in semi-arid West Africa. A review. Agron. Sustain. Dev. 2017, 37, 16. [Google Scholar] [CrossRef]
- Klerkx, L.; Jakku, E.; Labarthe, P. A review of social science on digital agriculture, smart farming and agriculture 4.0: New contributions and a future research agenda. NJAS-Wagening. J. Life Sci. 2019, 90, 100315. [Google Scholar] [CrossRef]
- Broom, D.M. Indicators of poor welfare. Br. Vet. J. 1986, 142, 524–526. [Google Scholar] [CrossRef]
- Siegrist, M.; Hartmann, C. Consumer acceptance of novel food technologies. Nat. Food 2020, 1, 343–350. [Google Scholar] [CrossRef]
- Cardello, A.V.; Schutz, H.G.; Lesher, L.L. Consumer perceptions of foods processed by innovative and emerging technologies: A conjoint analytic study. Innov. Food Sci. Emerg. Technol. 2007, 8, 73–83. [Google Scholar] [CrossRef]
- Bruhn, C.M. Enhancing consumer acceptance of new processing technologies. Innov. Food Sci. Emerg. Technol. 2007, 8, 555–558. [Google Scholar] [CrossRef]
- Rollin, F.; Kennedy, J.; Wills, J. Consumers and new food technologies. Trends Food Sci. Technol. 2011, 22, 99–111. [Google Scholar] [CrossRef]
- Frewer, L.J.; Bergmann, K.; Brennan, M.; Lion, R.; Meertens, R.; Rowe, G.; Siegrsist, M.; Vereijken, C.M.J.L. Consumer response to novel agri-food technologies: Implications for predicting consumer acceptance of emerging food technologies. Trends Food Sci. Technol. 2011, 22, 442–456. [Google Scholar] [CrossRef]
- Short, S.E. Focus groups: Focus group interviews. In A Handbook for Social Science Field Research: Essays & Bibliographic Sources on Research Design and Methods; SAGE Publications, Inc.: New York, NY, USA, 2006; pp. 104–117. [Google Scholar]
- Lunt, P.; Livingstone, S. Rethinking the focus group in media and communications research. J. Commun. 1996, 46, 79–98. [Google Scholar] [CrossRef] [Green Version]
- Lune, H.; Berg, B.L. Qualitative Research Methods for the Social Sciences; Pearson: London, UK, 2017. [Google Scholar]
- Nyumba, T.; Wilson, K.; Derrick, C.J.; Mukherjee, N. The use of focus group discussion methodology: Insights from two decades of application in conservation. Methods Ecol. Evol. 2018, 9, 20–32. [Google Scholar] [CrossRef] [Green Version]
- Cornwall, A.; Jewkes, R. What is participatory research? Soc. Sci. Med. 1995, 41, 1667–1676. [Google Scholar] [CrossRef]
- Hayward, C.; Simpson, L.; Wood, L. Still left out in the cold: Problematising participatory research and development. Sociol. Rural. 2004, 44, 95–108. [Google Scholar] [CrossRef]
- Israel, B.A.; Schulz, A.J.; Parker, E.A.; Becker, A.B. Review of community-based research: Assessing partnership approaches to improve public health. Annu. Rev. Public Health 1998, 19, 173–202. [Google Scholar] [CrossRef] [Green Version]
- Miltgen, C.L.; Peyrat-Guillard, D. Cultural and generational influences on privacy concerns: A qualitative study in seven European countries. Eur. J. Inf. Syst. 2014, 23, 103–125. [Google Scholar] [CrossRef]
- Kitzinger, J. The methodology of focus groups: The importance of interaction between research participants. Sociol. Health Illn. 1994, 16, 103–121. [Google Scholar] [CrossRef]
- Eurobarometer, S. Attitudes of EU Citizens towards Animal Welfare; European Commission: Brussels, Belgium, 2007; Available online: https://ec.europa.eu/commfrontoffice/publicopinion/archives/ebs/ebs_270_en.pdf (accessed on 19 February 2021).
- Probst, L.; Pedersen, B.; Lonkeu, O.K.; Martinez-Diaz, C.; Araujo, L.N.; Klitou, D.; Rasmussen, M. Digital Transformation Scoreboard 2017: Evidence of Positive Outcomes and Current Opportunities for EU Businesses; The European Commission: Brussels, Belgium, 2017; Available online: http://ec.europa.eu/DocsRoom/documents/21124 (accessed on 10 March 2021).
- European Commission. Eurobarometer, Special, Future of Europe: Reflections and Scenarios for the EU27 by 2025. 2017. Available online: https://ec.europa.eu/info/sites/info/files/white_paper_on_the_future_of_europe_en.pdf (accessed on 24 February 2021).
- Stremersch, S.; Tellis, G.J. Understanding and managing international growth of new products. Int. J. Res. Mark. 2004, 21, 421–438. [Google Scholar] [CrossRef]
- Alonso, M.E.; González-Montaña, J.R.; Lomillos, J.M. Consumers’ concerns and perceptions of farm animal welfare. Animals 2020, 10, 385. [Google Scholar] [CrossRef] [Green Version]
- Bruner, G.C.; Kumar, A.; Heppner, C. Predicting innovativeness: Development of the technology adoption scale. In Progress in Wireless Communications Research; Nova Science Publishers, Inc.: Hauppauge, NY, USA, 2007; pp. 1–20. Available online: https://www.researchgate.net/publication/277020646 (accessed on 24 February 2021).
- Herzog, H.; Grayson, S.; McCord, D. Brief measures of the animal attitude scale. Anthrozoös 2015, 28, 145–152. [Google Scholar] [CrossRef] [Green Version]
- Cacioppo, J.T.; Petty, R.E. The need for cognition. J. Personal. Soc. Psychol. 1982, 42, 116. [Google Scholar] [CrossRef]
- Donthu, N.; Garcia, A. The internet shopper. J. Advert. Res. 1999, 39, 52. [Google Scholar] [CrossRef] [Green Version]
- Morgan, D.L. Focus Groups as Qualitative Research; Sage Publications: New York, NY, USA, 1996; Volume 16. [Google Scholar]
- Van Riemsdijk, L.; Ingenbleek, P.T.M.; Van Der Veen, G.; Van Trijp, H.C.M. Positioning Strategies for Animal-Friendly Products: A Social Dilemma Approach. J. Consum. Aff. 2020, 54, 100–129. [Google Scholar] [CrossRef] [Green Version]
- Cox, D.N.; Evans, G. Construction and validation of a psychometric scale to measure consumers’ fears of novel food technologies: The food technology neophobia scale. Food Qual. Prefer. 2008, 19, 704–710. [Google Scholar] [CrossRef]
- Levitt, T. Communications and industrial selling. J. Mark. 1967, 31, 15–21. [Google Scholar] [CrossRef]
- Wicker, A.W. Attitudes versus actions: The relationship of verbal and overt behavioral responses to attitude objects. J. Soc. Issues 1969, 25, 41–78. [Google Scholar] [CrossRef] [Green Version]
- Moser, A.K. Thinking green, buying green? Drivers of pro-environmental purchasing behavior. J. Consum. Mark. 2015, 32, 167–175. [Google Scholar] [CrossRef]
- Yoo, C.W.; Parameswaran, S.; Kishore, R. Knowing about your food from the farm to the table: Using information systems that reduce information asymmetry and health risks in retail contexts. Inf. Manag. 2015, 52, 692–709. [Google Scholar] [CrossRef]
- Suchman, M.C. Managing legitimacy: Strategic and institutional approaches. Acad. Manag. Rev. 1995, 20, 571–610. [Google Scholar] [CrossRef] [Green Version]
- Pinillos, R.G.; Appleby, M.C.; Manteca, X.; Scott-Park, F.; Smith, C.; Velarde, A. One Welfare: A platform for improving human and animal welfare. Vet. Rec. 2016, 179, 412–413. [Google Scholar] [CrossRef] [Green Version]
- Clark, B.; Panzone, L.A.; Stewart, G.B.; Kyriazakis, I.; Niemi, J.K.; Latvala, T.; Tranter, R.; Jones, P.; Frewer, L.J. Consumer attitudes towards production diseases in intensive production systems. PLoS ONE 2019, 14. [Google Scholar] [CrossRef]
- Lubell, M.; Hillis, V.; Hoffman, M. Innovation, cooperation, and the perceived benefits and costs of sustainable agriculture practices. Ecol. Soc. 2011, 16, 23. [Google Scholar] [CrossRef] [Green Version]
- Fraune, M.R.; Sherrin, S.; Šabanović, S.; Smith, E.R. Is human-robot interaction more competitive between groups than between individuals? In Proceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction, Daegu, Korea, 11–14 March 2019; IEEE: Piscataway, NJ, USA, 2019; pp. 104–113. [Google Scholar]
- Złotowski, J.; Yogeeswaran, K.; Bartneck, C. Can we control it? Autonomous robots threaten human identity, uniqueness, safety, and resources. Int. J. Hum. Comput. Stud. 2017, 100, 48–54. [Google Scholar] [CrossRef]
- Astill, J.; Dara, R.A.; Campbell, M.; Farber, J.M.; Fraser, E.D.; Sharif, S.; Yada, R.Y. Transparency in food supply chains: A review of enabling technology solutions. Trends Food Sci. Technol. 2019, 91, 240–247. [Google Scholar] [CrossRef]
- Kamrath, C.; Wesana, J.; Bröring, S.; De Steur, H. What do we know about chain actors’ evaluation of new food technologies? A systematic review of consumer and farmer studies. Compr. Rev. Food Sci. Food Saf. 2019, 18, 798–816. [Google Scholar] [CrossRef] [PubMed]
- Frewer, L.J. Consumer acceptance and rejection of emerging agrifood technologies and their applications. Eur. Rev. Agric. Econ. 2017, 44, 683–704. [Google Scholar] [CrossRef]
- Wiseman, L.; Sanderson, J.; Zhang, A.; Jakku, E. Farmers and their data: An examination of farmers’ reluctance to share their data through the lens of the laws impacting smart farming. NJAS Wagening. J. Life Sci. 2019, 90, 100301. [Google Scholar] [CrossRef]
- Jakku, E.; Taylor, B.; Fleming, A.; Mason, C.; Fielke, S.; Sounness, C.; Thorburn, P. “If they don’t tell us what they do with it, why would we trust them?” Trust, transparency and benefit-sharing in Smart Farming. NJAS Wagening. J. Life Sci. 2019, 90, 100285. [Google Scholar] [CrossRef]
- Lusk, J.L.; Roosen, J.; Bieberstein, A. Consumer acceptance of new food technologies: Causes and roots of controversies. Annu. Rev. Resour. Econ. 2014, 6, 381–405. [Google Scholar] [CrossRef]
- Anagnostou, A.; Ingenbleek, P.T.; van Trijp, H.C. Sustainability labelling as a challenge to legitimacy: Spillover effects of organic Fairtrade coffee on consumer perceptions of mainstream products and retailers. J. Consum. Mark. 2015, 32, 422–431. [Google Scholar] [CrossRef]
- van der Burg, S.; Wiseman, L.; Krkeljas, J. Trust in farm data sharing: Reflections on the EU code of conduct for agricultural data sharing. Ethics Inf. Technol. 2020, 1–14. [Google Scholar] [CrossRef]
- Grewal, D.; Gauri, D.K.; Roggeveen, A.L.; Sethuraman, R. Strategizing Retailing in the New Technology Era. J. Retail. 2021, 97, 6–12. [Google Scholar] [CrossRef]
- Laurent, G.; Kapferer, J.N. Measuring consumer involvement profiles. J. Mark. Res. 1985, 22, 41–53. [Google Scholar] [CrossRef]
- De Jonge, J.; van Trijp, H.C. Meeting heterogeneity in consumer demand for animal welfare: A reflection on existing knowledge and implications for the meat sector. J. Agric. Environ. Ethics 2013, 26, 629–661. [Google Scholar] [CrossRef]
Country/Criteria | Spain | Netherlands | Finland | Total |
---|---|---|---|---|
Number participants | N = 20 (Dairy n = 10; pork n = 10) | N = 16 (Dairy n = 8; pork n = 8) | N = 20 (Dairy n = 10; pork n = 10) | N = 56 (Dairy n = 28; pork n = 28) |
Mean Age of Participants | Dairy focus group Mage = 30.40; SD = 7.93 Pork focus group Mage = 32.70; SD = 8.73 | Dairy focus group Mage = 28.25; SD = 7.94 Pork focus group Mage = 34.13; SD = 6.64 | Dairy focus group Mage = 39.60; SD = 9.35 Pork focus group Mage = 39.60; SD = 7.31 | Dairy focus group Mage = 33.07, SD = 8.41 Pork focus group Mage = 35.57, SD = 7.56 |
Innovative Attitude Scale | Dairy focus group Minnovativeness = 17.90; SD = 2.28 Pork focus group Minnovativeness = 18.40; SD = 3.27 | Dairy focus group Minnovativeness = 21.88; SD = 2.58 Pork focus group Minnovativeness = 21.88; SD = 2.58 | Dairy focus group Minnovativeness = 17.1; SD = 2.85 Pork group Minnovativeness = 17.5; SD = 3.03 | Dairy focus group Minnovativeness = 18.7; SD= 2.57 Pork focus group Minnovativeness = 19.07; SD = 2.96 |
Benefits | Risks |
---|---|
Increased transparency in the value chain and its processes | Increased digitalisation and robotisation in animal farming |
Improved health and welfare of farm animals | Decreased ‘human attention’ to farm animals→decreased animal welfare |
Environmental improvements: less emissions | Vulnerability of PLF technologies and data leaks |
Improved productivity and control of production processes | Highly dependent on the digital and energy infrastructure and supply |
Improved food safety | Lack of trust in the management of PLF data |
Pain-free slaughtering | More administrative work for stakeholders in the short term |
More freedom for farmers | More technological waste |
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Krampe, C.; Serratosa, J.; Niemi, J.K.; Ingenbleek, P.T.M. Consumer Perceptions of Precision Livestock Farming—A Qualitative Study in Three European Countries. Animals 2021, 11, 1221. https://doi.org/10.3390/ani11051221
Krampe C, Serratosa J, Niemi JK, Ingenbleek PTM. Consumer Perceptions of Precision Livestock Farming—A Qualitative Study in Three European Countries. Animals. 2021; 11(5):1221. https://doi.org/10.3390/ani11051221
Chicago/Turabian StyleKrampe, Caspar, Jordi Serratosa, Jarkko K. Niemi, and Paul T. M. Ingenbleek. 2021. "Consumer Perceptions of Precision Livestock Farming—A Qualitative Study in Three European Countries" Animals 11, no. 5: 1221. https://doi.org/10.3390/ani11051221
APA StyleKrampe, C., Serratosa, J., Niemi, J. K., & Ingenbleek, P. T. M. (2021). Consumer Perceptions of Precision Livestock Farming—A Qualitative Study in Three European Countries. Animals, 11(5), 1221. https://doi.org/10.3390/ani11051221