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Enregistrement W2883560324 · doi:10.15444/gmc2018.02.01.06

HOW NUTRITION-FACT INFORMATION INFLUENCES ONLINE FOOD SALES

2018· article· en· W2883560324 sur OpenAlex

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Notice bibliographique

RevueGlobal Fashion Management Conference · 2018
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueConsumer Packaging Perceptions and Trends
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésNutrition informationBusinessFood labelingMarketingAdvertisingInternet privacyComputer scienceFood scienceBiology

Résumé

récupéré en direct d'OpenAlex

Introduction Online shopping has become an important part of people’s daily lives. The very nature of online shopping makes it unlikely for consumers to examine products with their senses (e.g., touch, smell) as they can do in offline stores. The consumer obtains information from a variety of online sources (sellers, other buyers, and third parties) to assess a product and make a purchase decision. This variety of online information (e.g., product description, reviews and ratings) informs and persuades consumers. While sellers’ decisions comprise most information displayed on their product’s website, other information is shown because consumers have a moral, ethical, and legal “right” to know (e.g., ingredients, weight, size) (Jacoby, Speller, & Berning, 1974). Regarding the latter information, some countries (e.g., the U.S., China, Canada, the EU and India) have regulations that require pre-packaged food manufacturers to provide a nutrition-fact label and claims displaying standardized information on product packaging (Health Canada, 2010). We ask the following question to public policy makers and marketers: Should online pre-packaged food shops also need to present nutrition facts? There are two perspectives one might adopt regarding the array of information confronting online shoppers. The first perspective deals with human information processing. This position maintains that humans’ ability to assimilate and process information has finite limits during any given unit of time, and that once these limits are surpassed, behavior tends to become confused and dysfunctional (Miller, 1956; Driver & Streufert, 1969). Conceivably, such information overload might also occur in online shopping. Online shoppers often make their selections from a range of products, each with an array of information. Moreover, they make such purchase decisions within a relatively short time period. An alternative perspective is that nutrition-fact information provides key cues for consumers to assess product quality in the online marketplace. Cues can be categorized as extrinsic or intrinsic to the product (Maheswaran & Chaiken, 1991; Anderson, 1981). Extrinsic cues are product-related attributes that can be altered whereas intrinsic cues are inherent to the product itself (e.g., ingredients) and cannot be easily altered (Rao & Monroe, 1988; Purohit & Srivastava, 2001). An online shopper's evaluation of a product is based upon both intrinsic and extrinsic cues. In the online shopping environment, few intrinsic cues are available to consumers and the disclosure of nutrition facts (an intrinsic product feature) can help to fill this gap. Theoretical Development The understanding of how nutrition information presentation influences online food sales is a substantial topic for both industry and academia. With the convenience of online shopping, the potential for food producers and retail stores to take their products online is enormous. eMarketer (2014) reports that online food and beverage purchases increased 15.2% in U.S. retail ecommerce sales, and that this trend will remain consistent. Online food shopping is extremely popular in China, with 92% of consumers purchasing food or beverages at least once a month (Weber Shandwick, 2014). Moreover, eMarketer (2016) reports that by 2020, one-fourth of China's online purchases will be made directly from foreign websites or from third-party platforms. Thus, it is important for other countries to learn about the Chinese market. Among these potential issues, whether nutrition-fact information affects consumer purchase decisions in the online shopping context remains unexplored. Nutrition-fact labels have proven to be useful cues for consumer purchasing decision in offline conditions (Shah, Bettman, Ubel, Keller, & Edell, 2014). However, researchers have been unable to determine the effects of nutrition information in online conditions with network virtualization (Mavlanova, Benbunan-Fich, & Koufaris, 2012) and information multiplicity. In addition, the nutrition information disclosed by online sellers may cue consumers to acquire healthy food. Previous research has found that when information pertaining to a food’s nutritional content is provided, less-healthy food tastes better (Raghunathan, Naylor, & Hoyer, 2006). This literature raises the issue of whether nutrition information is more effective for healthy or unhealthy products. In summary, we investigate the effect of nutrition-fact information on online food shopping. The research questions address: (1) whether and how nutrition-fact information influences food sales in online conditions; (2) how nutrition-fact information interacts with other online extrinsic cues (i.e., word of mouth and historical sales); and (3) whether nutrition-fact information is more effective for healthy or unhealthy products. Research Design We then address these issues using panel data collected from Taobao.com (the largest online shopping platform in China). We selected 45 days as our study period, and the sample comprised 273 sellers. In addition, we conduct an experiment using an eye-tracking system to test the necessity and helpfulness of nutrition-fact information. Results and Conclusion The results show that the nutrition-fact information has a significant impact on sales. More specifically, consumers are more likely to choose sellers with the nutrition-fact information, and the healthy (unhealthy) food with nutrition-fact information tends to attract more (fewer) purchase. In addition, our results reveal some interesting interactions between nutrition-fact information and other cues. Specifically, WOM and historical sales strengthen the sales impact of nutrition-fact information. Our eye-tracking experiment leads to several interesting results. First, consumers pay attention to nutrition-fact information and spend considerable time reading it. Second, a long fixation length on nutrition-fact information would reasonably increase sales. This study makes several academic contributions. First, we extend the topic of nutrition information to an e-commerce context. Second, this is one of the first studies to examine the role of nutrition-fact information from an experimental perspective. Third, we supplement the findings of previous studies on the role of food type. This study also provides several practical implications. First, governments could require online sellers to reveal nutrition information in a truthful and detailed manner at the point of sale. In addition, labeling policies not only increase nutrition awareness and protect consumers, but they can also offer a profitable path for marketers. Second, sellers should design nutrition information and other cues strategies jointly. Third, compared with unhealthy food, nutrition-fact information is more effective for the purchase of healthy food. Sellers might be encouraged by this trend and consider more strategies to display nutrition-fact information on healthy food.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCommunication savante, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,539
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0020,003
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,030
Tête enseignante GPT0,250
Écart entre enseignants0,220 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle