How do cue utilization and value co-creation and future orientation affect the consumers’ choices of smart agricultural products?

The study addresses why and how consumers choose smart agricultural products amid environmental degradation and growing interest in food quality and safety. As smart agriculture diffuses digital technologies (IoT, big data, AI, drones, blockchain) across the agri-food value chain, understanding consumer drivers becomes critical for sustainable consumption. The research examines how cue utilization (external cues: identity label attractiveness, popularity, government endorsements; internal cue: quality), value co-creation, and attitudes shape purchase intentions, and whether future orientation moderates these relationships. It extends cue utilization theory by integrating value co-creation and tests the moderating role of future orientation in the early-stage Chinese smart agriculture market.

The theoretical framework distinguishes Agriculture 4.0, precision agriculture, and smart agriculture, emphasizing the latter’s end-to-end integration of digital technologies. In China, despite policy support and rapid market growth, consumer understanding and market penetration of smart agricultural products remain low. Cue utilization theory posits that consumers rely on internal (e.g., quality) and external cues (e.g., labels, popularity, endorsements) when direct experience is limited, shaping evaluations and decisions. Prior work suggests sustainability labels and popularity foster positive attitudes and participation, while government endorsements enhance credibility and may spur engagement. Product quality, as a core internal cue, underpins attitudes and co-creation. Value co-creation literature indicates active consumer involvement improves knowledge, trust, attitude, and willingness to buy. Attitude is a robust predictor of sustainable behavior and purchase intentions. Future orientation—focus on long-term outcomes—has been linked to pro-environmental behaviors and may strengthen the link between favorable attitudes and intentions. Hypotheses: H1a–H4a (cues→attitude), H1b–H3b & H4b (cues→value co-creation), H5 (value co-creation→attitude), H6 (value co-creation→purchase intention), H7 (attitude→purchase intention), H8a–H8b (future orientation moderates value co-creation/attitude→purchase intention).

Design: Cross-sectional online survey of Chinese residents conducted Oct–Nov 2023 across eastern (Beijing, Shanghai, Jiangsu, Shandong), central (Henan, Hubei, Jiangxi), and western (Sichuan, Guangxi, Guizhou) regions to capture geographic and economic diversity. Procedures included informed consent, a neutral primer defining smart agricultural products, and confirmation of awareness. Sampling: 1000 questionnaires distributed; 831 valid responses retained after removing incomplete, straight-lined, and unrealistically fast submissions. Demographics: 58.4% female; age concentrated in 18–40 (84.1%); education primarily junior college/undergraduate (82.4%); varied incomes. Measures: All constructs measured with multi-item 5-point Likert scales (1=strongly disagree to 5=strongly agree) adapted from prior studies and minorly modified for context. Cue utilization captured by: attractiveness of identity label (3 items), popularity (3), government endorsements (5), and quality (4). Value co-creation (4), attitude (4), future orientation (3), and purchase intention (4) were adapted from established scales. Average survey completion ≈6.5 minutes. Bias controls: Common method bias assessed via Harman’s single-factor test (first factor <50%); hypothetical bias mitigated with a cheap talk script; social desirability reduced through anonymity assurances, emphasizing no right/wrong answers, and indirect questioning for sensitive items. Analysis: Three-stage approach: (1) CFA to assess reliability/validity using standardized loadings, Cronbach’s alpha, CR, AVE (AMOS 24.0); (2) SEM to test direct effects among cues, value co-creation, attitude, and purchase intention (AMOS 24.0); (3) Moderation tested via Hayes PROCESS macro Model 88 in SPSS 23.0 using interaction terms (value co-creation×future orientation; attitude×future orientation). Model fit indices and variance explained were reported.

Measurement model demonstrated strong reliability and validity: Cronbach’s alpha and CR >0.70 across constructs; standardized loadings >0.60; AVE >0.50. Structural model fit was good: χ2=894.848, df=417, χ2/df=2.146, GFI=0.934, AGFI=0.922, TLI=0.955, CFI=0.960, RMSEA=0.037. The model explained 71.3% of the variance in purchase intention. Direct effects (SEM): - Attractiveness of identity label→Attitude: β=0.171, p<0.001 (H1a supported) - Popularity→Attitude: β=0.328, p<0.001 (H2a supported) - Government endorsements→Attitude: β=0.054, p=0.180 (H3a not supported) - Quality→Attitude: β=0.124, p<0.001 (H4a supported) - Attractiveness of identity label→Value co-creation: β=0.224, p<0.001 (H1b supported) - Popularity→Value co-creation: β=0.373, p<0.001 (H2b supported) - Government endorsements→Value co-creation: β=0.203, p<0.001 (H3b supported) - Quality→Value co-creation: β=0.176, p<0.001 (H4b supported) - Value co-creation→Attitude: β=0.208, p<0.001 (H5 supported) - Value co-creation→Purchase intention: β=0.588, p<0.001 (H6 supported) - Attitude→Purchase intention: β=0.500, p<0.001 (H7 supported) Moderation (PROCESS Model 88): - Value co-creation×Future orientation→Purchase intention: β=−0.054, p=0.227 (H8a not supported) - Attitude×Future orientation→Purchase intention: β=0.207, p<0.001 (H8b supported). The positive effect of attitude on purchase intention is stronger at higher future orientation.

Findings validate an extended cue utilization framework incorporating value co-creation for smart agricultural products. External cues (identity labels and popularity) and the internal cue (quality) foster positive attitudes; all four cues, including government endorsements, stimulate value co-creation. Government endorsements did not directly sway attitudes, potentially due to skepticism or contextual variations in perceived governmental credibility, but they do encourage participatory co-creation. Value co-creation enhances attitudes and directly drives purchase intentions, while attitudes themselves strongly predict intentions. Future orientation strengthens the attitude–intention linkage, indicating future-focused consumers translate positive attitudes into purchasing more readily. However, future orientation does not alter the effect of value co-creation on intentions, suggesting that experiential engagement from co-creation exerts a direct influence regardless of temporal outlook. These insights underscore the importance of salient cues, participatory engagement, and targeting consumers with stronger future orientation to advance sustainable consumption of smart agricultural products.

The study demonstrates that diverse cue utilization (identity label attractiveness, popularity, government endorsements, and quality) significantly shapes value co-creation and attitudes toward smart agricultural products. Value co-creation and attitudes, in turn, elevate purchase intentions. Future orientation positively moderates the attitude–intention relationship, highlighting time perspectives as a key boundary condition. The integrated framework offers a nuanced view of consumer decision-making in emerging smart agri-food markets and informs strategies for promoting sustainable consumption. Future research should test generalizability across countries, adopt longitudinal designs to capture temporal dynamics, and unpack multidimensional facets of future orientation (e.g., planning, risk preferences) to refine understanding of its moderating mechanisms.

Generalizability is limited by the single-country (China) context. The cross-sectional design precludes causal and temporal inferences about evolving attitudes, co-creation, and intentions. The moderating construct of future orientation may be multidimensional; unmeasured dimensions (e.g., long-term planning, risk tolerance) could differently affect relationships. Self-report measures may still contain residual common method or social desirability bias despite mitigation steps.