Determining optimal marketing mix configurations: An integration of opinion-oriented language and necessary condition analysis

This study investigates how Michelin-starred restaurants in Thailand can strategically configure their marketing mix to maximize customer value creation. Leveraging a novel integration of opinion-oriented language analysis and necessary condition analysis, we offer an innovative methodological framework for aligning marketing communications with customer perceptions. Our two-step text analysis of TripAdvisor reviews and restaurant-generated content reveals critical linguistic patterns across five core marketing mix elements—product, price, place, promotion, and people—guiding the development of more authentic and resonant messaging. Necessary condition analysis results pinpoint product, people, process, and physical evidence as essential conditions for achieving high customer satisfaction, supported by robust consistency (0.996) and coverage (0.672) metrics. Further analysis using SmartPLS defines precise threshold levels required for each element to yield varying degrees of satisfaction. Strikingly, only 4 out of 35 restaurants exhibit strong alignment between their marketing narratives and customer feedback, revealing a significant opportunity gap. By bridging linguistic alignment with empirical necessity, this research delivers actionable insights for luxury restaurant operators seeking to enhance strategic content development, optimize marketing investments, and foster deeper customer engagement in premium dining experiences.

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Publication Details

Journal
Journal Of Vacation Marketing
Published
2025-06-30
DOI
https://doi.org/10.1177/13567667251351025
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
0.00
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article

Determining optimal marketing mix configurations: An integration of opinion-oriented language and necessary condition analysis

Intaka Piriyakul, Shawanluck Kunathikornkit, Rapepun Piriyakul
Journal Of Vacation Marketing
Digital Marketing and Social Media
article

Determining optimal marketing mix configurations: An integration of opinion-oriented language and necessary condition analysis

Intaka Piriyakul, Shawanluck Kunathikornkit, Rapepun Piriyakul
article en

Abstract

This study investigates how Michelin-starred restaurants in Thailand can strategically configure their marketing mix to maximize customer value creation. Leveraging a novel integration of opinion-oriented language analysis and necessary condition analysis, we offer an innovative methodological framework for aligning marketing communications with customer perceptions. Our two-step text analysis of TripAdvisor reviews and restaurant-generated content reveals critical linguistic patterns across five core marketing mix elements—product, price, place, promotion, and people—guiding the development of more authentic and resonant messaging. Necessary condition analysis results pinpoint product, people, process, and physical evidence as essential conditions for achieving high customer satisfaction, supported by robust consistency (0.996) and coverage (0.672) metrics. Further analysis using SmartPLS defines precise threshold levels required for each element to yield varying degrees of satisfaction. Strikingly, only 4 out of 35 restaurants exhibit strong alignment between their marketing narratives and customer feedback, revealing a significant opportunity gap. By bridging linguistic alignment with empirical necessity, this research delivers actionable insights for luxury restaurant operators seeking to enhance strategic content development, optimize marketing investments, and foster deeper customer engagement in premium dining experiences.

Journal Of Vacation Marketing
Srinakharinwirot University (TH)
Openalex Percentile: Top 79%
Digital Marketing and Social Media
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Determining optimal marketing mix configurations: An integration of opinion-oriented language and necessary condition analysis — Intaka Piriyakul, Shawanluck Kunathikornkit, et al. · Journal Of Vacation Marketing (2025) | TGRS Research Map | TGRS