Reputazione e monitoraggio della competizione in tempo reale: le sfide innovative del pricing online

Obiettivo del paper: Indagare le diverse strategie di prezzo dinamico realizzate attraverso il canale delle vendite online, in un contesto di servizi con capacitproduttiva predeterminata.

Metodologia: Analisi di regressione su un database costruito simulando la prenotazione di una camera di hotel attraverso linterrogazione di un motore di ricerca online (booking.com). Il database costituito da 57 hotel, osservati rispetto a 16 diverse ipotesi di data di soggiorno, seguendo per ciascuna landamento del prezzo a partire da una prenotazione effettuata con 90 giorni di anticipo fino ad una prenotazione last minute.

Risultati: Le strategie di prezzo dinamiche degli hotel tengono conto sia dellapprossimarsi della data di soggiorno sia dellandamento dinamico dellofferta degli altri operatori sul mercato. Inoltre, si dimostra il forte impatto sul prezzo della reputazione online derivante dalle recensioni sul web.

Limiti della ricerca: Le strategie sono analizzate esclusivamente dal lato dellofferta senza indagarne allo stesso tempo lefficacia in termini di effettivo comportamento di acquisto dei consumatori.

Implicazioni pratiche: I miglioramenti nel campo dellICT permettono ladozione di sistemi di prezzo variabile automatici, creando un rapporto innovativo con la domanda finale e suggerendo ai manager un ripensamento delle strategie di prezzo di breve e di lungo termine.

Originalitdel lavoro: Si tratta del primo lavoro che analizza contemporaneamente leffetto sul prezzo delle variabili statiche legate alle caratteristiche di un hotel e delle variabili dinamiche legate allimplementazione di tecniche di gestione dinamica dei ricavi, tenendo conto inoltre dellinterrelazione con il contesto competitivo e dei giudizi di soddisfazione dei clienti ricevuti online.

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