MétaCan
Menu
Back to cohort
Record W2521529638 · doi:10.5539/ibr.v9n10p201

Does Shopping Preparation influence Consumer Buying Decisions?

2016· article· en· W2521529638 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Business Research · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessMarketingAdvertisingOrder (exchange)PopulationGrocery shoppingProduct (mathematics)

Abstract

fetched live from OpenAlex

<p class="1main-text">Changes in consumers’ environment, specifically the economic crisis and the growing penetration of digital technologies, have produced significant changes in shopping habits, designed to gradually reduced the effectiveness of in-store marketing levers in influencing shopping behaviour. On one hand, due to the global economic downturn and the associated diminished disposable income, more shoppers are now searching more information before entering a store and evaluating more alternatives before to decide where and what to shop. On the other hand, the deep penetration of technological developments, such as digital media and mobile devices, among the population, has opened up new opportunities to influence shopper attitudes and behaviour in the retail environment. A new scenario seems to be opening up where more planning and preparation for shopping is carried out before customers entering the store. In this new environment, to formulate and execute effective shopper marketing strategies, managers need to better understand the complete picture of how online, offline, mobile and in-store marketing influence shoppers in the path-to-purchase-and-beyond cycle. Starting from recent research avenues, our work intends to explore the relationship between pre-shopping behaviour and shopping behaviour in-store, with the aim to understand how pre-trip activities have influenced shopping behaviour in-store. In order to get this purpose, we conducted a survey in three stores belonging to a leading Italian grocery retailer. Shoppers were intercepted in front of the display, when the chosen product was placed in the shopping cart. Through a structured questionnaire, respondents were asked about the nature of the purchase (planned vs unplanned) and the degree of out-of-store preparation (number and type of activity carried out). Data were processed using SPSS statistical software. The degree of grocery shopping preparation is found to influence shopper behaviour inside the store in terms of planned/impulse buying: the higher is the degree of preparation, the greater is the tendency to plan purchases and the lower is the tendency to make impulse purchases. Our findings could suggest retailers and manufacturers new ways to innovate the practice of shopper marketing, considering that marketing levers cannot still affect consumers’ decisions in-store as in the past.</p>

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.106
GPT teacher head0.398
Teacher spread0.291 · 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