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Record W2589205294 · doi:10.1108/intr-03-2016-0082

The impact of reference effects on online purchase intention of agricultural products

2017· article· en· W2589205294 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternet Research · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsBrock University
Fundersnot available
KeywordsEnvironmental consciousnessContext (archaeology)BusinessAgricultureMarketingAdvertisingConsciousnessPsychology

Abstract

fetched live from OpenAlex

Abstract Purpose The purpose of this paper is to analyze the impact of reference effects on online purchase intention (OPI) of agricultural products in B2C context and to examine how consumers' food safety consciousness (FSC) moderates that impact. Design/methodology/approach An empirical survey was used to test the hypotheses. Data were collected from a total of 297 online consumers in China. A structural equation modeling is utilized to assess the relationships proposed in the research model. Findings The findings of this study show that reference effects have a significant impact on OPI of agricultural products. Both perceived value (PV) and perceived risk (PR) play a mediating role in the relations between reference effects and OPI, but the mediating effect of the PV is found to be significantly greater than that of the PR. Consumers' FSC significantly and positively moderates the impact of reference effects on OPI, meaning that the more attention consumers pay to food safety, the greater the impact of reference effects on OPI will become. Research limitations/implications First, this study mainly analyzes the positive impact of reference effects on OPI. Future research could discuss the negative impact of reference effects and compare the differences between them. Second, this study only takes the PV and PR as mediators into the research model. Future research could consider adding trust, attitude, and other variables and further explore and clarify the influencing mechanism between reference effects and OPI. Third, this study examines the moderating role of consumers' FSC but does not fully discuss the moderating role of product categories. Further research could compare the influence of reference effects among multiple product categories. Practical implications This study provides valuable insights for agricultural enterprises and online vendors that reference effects are one of the most important factors to influence OPI. It suggests to agricultural enterprises and online vendors that reference effects can be used as a new instrument to influence consumers' online purchase decisions. Originality/value This study for the first time defines reference effects in an online setting and introduces the perspective of reference effects to establish a theoretical model to explain consumers' OPI of agricultural products. The study reveals the influencing mechanism of reference effects on OPI and thus enriches the theory of online purchase behavior.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.132
GPT teacher head0.481
Teacher spread0.349 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it