Consumer purchase intention towards a quick response (QR) code for antibiotic information: an exploratory study

Consumer concern about food quality and safety has risen due to crises (e.g., BSE, avian influenza, melamine milk, horse meat scandal), prompting the development of traceability systems. Antimicrobial use (AMU) in livestock, particularly pigs, remains under scrutiny despite declines in usage in UK pork production. Calls for antibiotic-free production risk compromising animal welfare and may mislead consumers into believing conventional products are unsafe. There is currently no operational system to provide farm-level antibiotic information to consumers at point of purchase. Quick Response (QR) codes, widely used in food traceability, could deliver antibiotic-related information. This study investigates UK consumers’ perceptions and purchase intentions toward QR code–labelled pork, identifying determinants of intention using the Theory of Planned Behaviour (TPB). Objectives: (1) determine purchase intention and exploratory factors influencing purchase; (2) test whether TPB constructs (attitude, perceived behavioural control, trust) influence intention; (3) understand consumers’ perceptions of QR code–labelled pork.

- Food traceability systems enhance perceived safety, quality, and trust; many consumers desire transparent on-pack information, and brands have adopted QR codes. - TPB is commonly applied to predict food choices; intention is driven by attitude, subjective norms, and perceived behavioural control. - Consumers exhibit willingness-to-pay (WTP) for higher animal welfare; however, antibiotic-free labels may mislead, associating them with improved welfare and creating information gaps and confusion. - Research indicates varying consumer perceptions of AMU/AMR; misconceptions persist about AMR causes and risks. QR codes could provide nuanced antibiotic and welfare information without implying conventional products are unsafe.

Design: Cross-sectional online survey of a nationally representative UK adult sample (n = 1000; age 18–92) conducted in May 2020 via Dynata. Quotas ensured representation by age, region, sex, and SES. Exclusions: under 18, employed in media/food safety/processing/farming, no shopping responsibility, and pork purchase/consumption less than every few months. Stimuli: Respondents were randomly assigned to one of two hypothetical QR code pork labels (visual aid shown): (1) antibiotic usage label (included quantified AMU at farm level in mg/kg); (2) farm assurance label (stated product is Red Tractor assured). Both included origin, farmer, rearing conditions, breed, and assurances about legal compliance, withdrawal periods, and RSPCA welfare standards. Measures (primarily 7-point Likert scales unless stated): - Attitude toward buying QR code pork versus traditional pork. - Perceived behavioural control (PBC): ability to find/understand QR code antibiotic information; preference for rating/colour coding vs numeric figures. - Trust in QR code antibiotic information. - Behavioural beliefs comparing QR code vs traditional pork (quality, animal welfare, expense). - Perceptions of QR code (usefulness, reassurance about responsible antibiotic use, perceived reduction in antibiotic intake/AMR risk). - Purchase intention (intent, search, importance, buying to learn about welfare). - Generalised trust (trust in people). - Perceptions of AMU practices: Personal concern (AMR risk), Animal welfare standards importance, Animal AMU acceptance. - Pork purchasing attribute importance (extrinsic, animal welfare, marketing qualities). - WTP premium question using a £2/500 g base price. - Knowledge of EU regulations (5 true/false items; 0–5 scale). - Awareness of AMR (2 yes/no items: heard of AMR; know what AMR is). Analysis: Maximum likelihood factor analysis with Direct Oblimin rotation; constructs formed by averaging items (Cronbach’s alpha generally >0.70; Personal concern alpha 0.65 deemed acceptable; Animal concern factor removed). Descriptive statistics reported. Hierarchical multiple regression predicted intention from exploratory variables (Step 1) and socio-demographics (Step 2). Separate regressions tested behavioural beliefs predicting attitude. Assumptions met; no multicollinearity concerns.

Sample and behaviour: - N = 1000 (51% female), mean age 46.8 (SD 16.8); all had some shopping responsibility. - Pork purchase frequency: several times/month 64%; consumption several times/month 54%. - Attribute importance (means): extrinsic qualities M = 5.56 (SD 0.97) most important; animal welfare qualities M = 5.00 (SD 1.13); marketing qualities least important M = 4.77 (SD 1.25). - QR code experience: among smartphone users, 51% had scanned a QR code previously. Perceptions and TPB constructs: - Attitude slightly favourable: QR1 4.79; QR2 4.77. - Trust high: QR1 4.90; QR2 4.91. - Beliefs: QR code pork perceived more expensive (>5 in both groups); not easy to find (QR1 3.87; QR2 3.84). - PBC moderately high: QR1 4.76; QR2 4.82. Strong preference for rating/colour coding vs numeric figures (QR1 5.26; QR2 5.18). - Perceptions of QR code moderately positive: QR1 4.42; QR2 4.55. - AMU/AMR perceptions: personal risk and animal welfare importance high (>5); acceptance of AMU neutral (QR1 4.20; QR2 4.30); low agreement pets as AMR source (QR1 3.35; QR2 3.55; p = 0.043). - Knowledge/awareness: knowledge of EU regulations M = 3.29/5 (SD 1.01); 52% had heard of AMR, 38% knew what AMR is. Intention and WTP: - Purchase intention neutral: QR1 4.20; QR2 4.29. - WTP premium: antibiotic usage label—34.8% unwilling to pay more; among 65.2% willing, average ~10% more. Farm assurance label—35.2% unwilling; among 64.8% willing, average ~15% more. Determinants of intention (regressions): - Strongest predictor: perception of QR code (β ≈ 0.64) in both sub-groups. - Attitude (β ≈ 0.25 antibiotic usage; β ≈ 0.22 farm assurance) and PBC (β ≈ 0.07–0.11) positively predicted intention in both groups. - Additional predictors: personal concern about AMU positively predicted intention for farm assurance; animal welfare standards positively predicted intention for antibiotic usage; acceptance of animal AMU negatively predicted intention for antibiotic usage. - Knowledge of EU regulations (farm assurance) and awareness of AMR (antibiotic usage) showed negative associations with intention. - Variance explained: R²adj ≈ 0.73 (antibiotic usage) and 0.77 (farm assurance). Adding socio-demographics (age, gender, education, SES) did not increase explained variance meaningfully; demographics were not significant predictors. Beliefs shaping attitude: - Quality beliefs significantly predicted attitude in both groups (β ≈ 0.52 antibiotic usage; β ≈ 0.40 farm assurance); animal welfare beliefs additionally predicted attitude in farm assurance (β ≈ 0.28). Expense beliefs were not predictive. Models explained 37% and 40% of attitude variance for antibiotic usage and farm assurance, respectively.

Findings indicate that UK consumers hold somewhat favourable attitudes and perceptions toward QR code–labelled pork, and that these psychological factors—especially perceptions of the QR code—are primary drivers of intention to purchase. Consistent with TPB, attitude and PBC positively predicted intention; enhancing usability (e.g., clear rating/colour-coded formats) could bolster PBC and intention. Despite relatively high reported trust, trust did not significantly predict intention, suggesting that for QR code antibiotic information, perceived usefulness and attitudes matter more than trust alone. Consumers preferred simplified, interpretable indicators of antibiotic use (traffic-light style) over raw numeric data, underlining the need for user-friendly information design. The negative association between AMR awareness/knowledge of regulations and intention suggests possible unfamiliarity effects or misconceptions; individuals with lower awareness may ascribe higher perceived benefits to the QR-labelled product. Tailored communication is warranted to improve AMR literacy while maintaining interest in informed choices. Socio-demographics added little explanatory power, implying broad relevance across consumer segments. Overall, QR codes can communicate antibiotic practices without implying that conventional pork is unsafe, potentially mitigating confusion around antibiotic-free labels while supporting animal welfare transparency.

The study demonstrates that consumers’ perceptions of QR codes, attitudes toward the product, and perceived behavioural control are key determinants of intention to buy QR code–labelled pork. QR codes represent a promising alternative to antibiotic-free/RWA labelling by providing transparent antibiotic and welfare information without stigmatising conventional products. For effective adoption, stakeholders should: (1) emphasise quality and welfare benefits in marketing (drivers of attitude), (2) design intuitive displays (e.g., colour-coded ratings) to enhance usability, and (3) develop communication strategies to address knowledge gaps and misconceptions about AMU/AMR. Future research should validate these results with real purchasing contexts (e.g., experimental auctions, in-store trials), directly compare QR-coded vs antibiotic-free labels, and explore trust-building via credible information sources and system design.

- Behavioural intention measured rather than actual purchasing behaviour; intention–behaviour gap may exist. - Hypothetical product exposure; consumers may not notice or scan QR codes in real settings. - Potential information overload and competing labels/logos not addressed. - Online survey context; results preliminary and require replication in field studies (e.g., in-store experiments, experimental auctions). - Measurement limitations: some constructs with marginal reliability; negative associations for AMR awareness/knowledge require further investigation.