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<p>This study investigates how restaurants in Taiwan can enhance sustainability marketing through the strategic adoption of big data technologies. It examines the roles of entrepreneurial orientation, internal driving forces, and performance outcomes in this transformation process. A hybrid multicriteria decision-making (MCDM) approach combining the analytic network process (ANP) and the Vlse Kriterijumska Optimizacija I Kzompromisno Resenje (VIKOR) method was employed. In-depth interviews with 30 experts from industry, government, and academia in Taiwan provided qualitative insights, followed by quantitative evaluation to determine the relative importance of factors influencing big data adoption in restaurant sustainability marketing. The results reveal that performance and sustainability marketing are the most influential dimensions in facilitating big data adoption. While restaurants prioritize performance improvements and brand image, government and academic stakeholders emphasize internal driving forces such as corporate social responsibility and perceived behavioral control. Big data adoption has been shown to support timely decision-making, enhance customer loyalty, and promote sustainable competitive advantages in Taiwan’s restaurant sector. This study contributes a novel hybrid evaluation framework grounded in the quintuple helix model of innovation to assess sustainability strategies in the restaurant industry. This study provides empirical insights into how Taiwanese restaurants can effectively integrate big data and sustainability marketing, bridging a gap in practical applications within the current literature.</p>

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Advancing Big Data Adoption for Sustainability Marketing in Restaurants: A Hybrid Multi-Criteria Decision-Making Approach

  • 期刊论文

  • 发表日期：

    2026年3月9日

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  • Sheng-Fang Chou,
  • Jeou-Shyan Horng,
  • Chih-Hsing Liu,
  • Tai-Yi Yu,
  • I.-Yen Lu,
  • Kuo-Wei Chen,
  • Jun-You Lin

摘要

This study investigates how restaurants in Taiwan can enhance sustainability marketing through the strategic adoption of big data technologies. It examines the roles of entrepreneurial orientation, internal driving forces, and performance outcomes in this transformation process. A hybrid multicriteria decision-making (MCDM) approach combining the analytic network process (ANP) and the Vlse Kriterijumska Optimizacija I Kzompromisno Resenje (VIKOR) method was employed. In-depth interviews with 30 experts from industry, government, and academia in Taiwan provided qualitative insights, followed by quantitative evaluation to determine the relative importance of factors influencing big data adoption in restaurant sustainability marketing. The results reveal that performance and sustainability marketing are the most influential dimensions in facilitating big data adoption. While restaurants prioritize performance improvements and brand image, government and academic stakeholders emphasize internal driving forces such as corporate social responsibility and perceived behavioral control. Big data adoption has been shown to support timely decision-making, enhance customer loyalty, and promote sustainable competitive advantages in Taiwan’s restaurant sector. This study contributes a novel hybrid evaluation framework grounded in the quintuple helix model of innovation to assess sustainability strategies in the restaurant industry. This study provides empirical insights into how Taiwanese restaurants can effectively integrate big data and sustainability marketing, bridging a gap in practical applications within the current literature.