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Enregistrement W2411706149 · doi:10.15200/winn.146521.13799

How Businesses are Influencing the Relationship between the Weather and Consumer Demand

2016· dataset· en· W2411706149 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

aboutLe titre ou le résumé porte un signal canadien du lexique géographique.
no affAucune affiliation canadienne : ce travail est invisible pour une base fondée sur la seule affiliation.
Aucune affiliation canadienne. Une base fondée sur la seule affiliation (le devis habituel) n'aurait jamais vu ce travail. C'est l'un des travaux qui justifient l'inversion de la base.

Notice bibliographique

RevueThe Winnower · 2016
Typedataset
Langueen
DomaineBusiness, Management and Accounting
ThématiqueBig Data and Business Intelligence
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésProduct (mathematics)BusinessSnowPurchasingExtreme weatherClothingMarketingHot weatherAdvertisingMeteorologyGeographyEcologyClimate change

Résumé

récupéré en direct d'OpenAlex

When it comes to weather affecting consumer behaviour and purchase decisions, it has long been known that weather has an impact on consumer demand. The food we eat, clothes we wear, and how, where and how much we buy has all been scientifically proven to be influenced by the weather, it being second only to the economy in being the biggest single influencer on consumer behaviour. Indeed, every day people make purchasing decisions based on the weather, from buying ice cream, sandals and swimsuits in the summer, hot soups and snow tyres in the winter, and less of beer and bottled water as autumn approaches. In turn, the seasonal cycle of weather purchases are accounted for by supply chain managers in stocking store rooms and giving discounts to clear out product before the seasonal event- or the season itself- leaves stockpiles of unsellable wares in their hands. But what if everything we have known to be true about how the weather affects consumer behaviour and our ability to control this relationship was wrong? What if the seemingly uni-directional, unmanipulatable relationship between the weather and consumer behaviour was now being found to be being turned on its head? Specifically, what if a business could influence the relationship between the weather and consumers to its advantage? On the face of it, this sounds like something out of a sci-fi tale, like the fictional X-Men character Storm’s psionic ability to control everything from ocean currents to electromagnetic fields. Or perhaps a reference to the days of the mythological weather deities of Jupiter, Thor, or Zeus. Moreover, it has some rather frightening ramifications for the c-suite, as gone would be the days of businesses blaming profit losses on the weather. Of course, we’ve seen rudimentary versions of such weather risk management techniques: consumers have been prodded out of their living rooms and into storerooms under even the most unfavourable weather condition by discounts and sales promotions since the dawn of the modern economy. And, more recently, these promotions have become more cutting-edge, with businesses taking advantage of advances in weather data technology, weather sensitivity modeling, and new index weather hedging tools to create weather-related sales promotions. In this way, if a certain weather event occurs in a given period, consumer will receive a full or partial reimbursement on purchases made during the sales period, with retailers themselves protected by reinsurance treaties underwritten by weather risk management specialists such as Meteo Protect. Thus, an automobile parts retailer will stock those aforementioned snow tyres, even if the meteorologists are calling for a mild winter[1]See weatherandeconomics.com/2016/05/30/its-not-gambling-if-you-never-lose. But taking this one step further, and drawing now from advances in digital signage, remote weather sensing, and available real-time feedback between advertising mediums and weather stations, today we have the brave new world of an inter-directional relationship between the weather and consumers. Say goodbye to everything from advertising promotions and restaurant menus being set in advance, static, or fixed. Welcome to the age of digital signage and interactive advertising platforms which draw from dozens of smart components, including the weather, but also what’s trending on the news and social media. Take McDonald’s, for instance, which this past year started installing digital menu boards in restaurants around the world following a successful testing period in Canada. These menus make food recommendations based on the weather. If it’s cold outside, the menu might promote hot soups and heartier meals, whereas on a hot and sunny day, refreshing beverages and ice creams might be highlighted. Moving images further engage customers and draw their attention to these promoted items. McDonald’s has already reported success with these digital menus, stating that customers are spending more on every transaction in restaurants where the new menu boards were tested.[2]uk.businessinsider.com/mcdonalds-menus-will-recommend-food-based-on-the-weather-2015-1\n1 Similarly, Mark’s, a Canadian apparel and footwear retailer, recently won accolades for their innovation in brand activation, coming up with a novel way to meet the business objective of clearing out holiday inventory in anticipation of spring, in the face of a price-point war across industry, and amidst clearance clutter. Mark’s used digital signage on transit shelters in areas in proximity to their flagship stores to drive consumer demand by linking their advertisements to live weather feeds. As the temperature dropped, so did Mark’s discounts on winter apparel. They effectively customized their prices and advertising to fluctuations in temperatures, and influenced consumer behaviour by responding to the weather and consumer demand in real-time. The campaign was an immense success: Mark’s reported up to a 21% increase in sales year-over-year for the 3-week campaign period of this digital weather-driven marketing platform.[3]promoawards.strategyonline.ca/Winners/Winner/2015/?w=marks-readytowinter It’s not surprising that out of Canada we should see such innovation in mitigating the effects of the weather, but what businesses may find surprising is how quickly they can be left in the cold if they don’t decide to make their relationship with the weather a priority in 2016. That’s precisely why Meteo Protect, experts in weather risk financial management, have partnered with industry leaders such as MeteoGroup, a world leading weather data provider, in order to create products that leverage the data of Meteo Group with the bespoke hedging solutions and marketing and consulting services of Meteo Protect. Thanks to the scale and capability of Meteo Protect’s SAP cloud data services platform, it is able to provide clients significant competitive advantage as they link their business and sensor data with weather and other pertinent information in real-time. This may or may not be as alluring as teaming up with Professor Xavier’s team, but a manager who employs cutting-edge weather risk management techniques to increase profits and control losses in the face of any weather variable is bound to be considered a superhero at the office. References [ + ] 1. ↑ See weatherandeconomics.com/2016/05/30/its-not-gambling-if-you-never-lose 2. ↑ uk.businessinsider.com/mcdonalds-menus-will-recommend-food-based-on-the-weather-2015-1\n1 3. ↑ promoawards.strategyonline.ca/Winners/Winner/2015/?w=marks-readytowinter

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)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCommunication savante
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,449
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,001
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
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 Opus0,084
Tête enseignante GPT0,283
Écart entre enseignants0,199 · 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