Investigating the opportunities and challenges influencing consumer purchase behaviors and media influence in online food ordering: a thematic analysis
Bibliographic record
Abstract
Purpose This study has two main objectives. First, it aims to identify the opportunities and challenges influencing consumer purchase behaviors when ordering food through food aggregator platforms. Second, it seeks to determine consumer preferences for paid, owned and earned media (POEM) channels in the context of food aggregators. Design/methodology/approach Data were collected through semi-structured interviews with consumers who ordered food via aggregator platforms. Qualitative data analysis was conducted using NVivo 14. Findings The study identifies eight key themes representing the opportunities and challenges faced by food aggregators: (1) Streamlining and transparency in charges, (2) Enhancing speed, quality and reliability of delivery services, (3) Strategizing discounts and promotions to maximize customer engagement, (4) Ensuring food quality, packaging and accuracy in delivery, (5) Diversifying payment portfolios to cater to different customers, (6) Streamlining the ordering process and timely addressing of issues, (7) Normalizing pricing issues and (8) Ensuring the safety of delivery agents. The results indicate consumer preferences for POEM channels, showing a preference for earned media first, followed by owned media, with paid forms of communication ranking last. Research limitations/implications The study enhances the understanding of consumer perceptions and the dynamics of media influence on purchasing decisions, contributing valuable insights to the existing body of knowledge. Practical implications The qualitative analysis highlights critical themes and areas that brands must address to maintain customer satisfaction. Identifying opportunities and challenges allows food aggregators to prioritize strategic initiatives effectively. Additionally, understanding customer preferences for POEM channels enables marketers to tailor their communication strategies to better align with consumer expectations. Social implications The study highlights that while food aggregators provide convenience and flexibility for consumers, major concerns such as the quality and packaging of delivered food as well as the safety of delivery partners, also influence customer decisions when ordering through aggregators. Originality/value This research is novel in its approach, providing an in-depth qualitative analysis that captures the nuanced perspectives of consumers using food aggregators. By analyzing customer interactions and feedback, the study aims to offer actionable insights for enhancing service quality and meeting consumer expectations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".