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Sustainable Marketing: Consumer Behavior in the Age of Data Analytics

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Economic and Business Aspects of Sustainability".

Deadline for manuscript submissions: 9 March 2026 | Viewed by 5936

Special Issue Editors


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Guest Editor
Department of Marketing, Business School, Hankuk University of Foreign Studies, Seoul, Republic of Korea
Interests: marketing analytics; social media analytics; algorithm marketing

E-Mail Website
Guest Editor
Department of Marketing, Business School, Hankuk University of Foreign Studies, Seoul, Republic of Korea
Interests: artificial intelligence; psychological ownership; consumer desire; product design

Special Issue Information

Dear Colleagues,

The integration of sustainability and consumer behavior is a growing area of interest in the marketing discipline, particularly in the context of data analytics. As consumers become more environmentally conscious, businesses must align their strategies to meet these expectations while leveraging the power of data-driven insights. This Special Issue aims to explore how sustainability initiatives are shaping consumer behavior and how data analytics can optimize marketing strategies in this new paradigm. The purpose of this Special Issue is to bring together cutting-edge research that examines the intersection of sustainability, consumer behavior, and data analytics. We welcome original research articles and reviews that contribute to the understanding of how marketing strategies can be more sustainable while effectively engaging with consumers through data-driven approaches. By doing so, this Special Issue aligns with the broader scope of Sustainability by promoting interdisciplinary research that supports sustainable practices across industries.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Sustainable consumer behavior and decision-making processes;
  • The role of data analytics in shaping sustainability marketing strategies;    
  • Consumer attitudes toward sustainable brands and green marketing;
  • Ethical concerns in data-driven marketing for sustainable products;
  • The impact of AI and machine learning on consumer behavior in sustainability contexts.

We look forward to receiving your valuable contributions that will shape the future of sustainability marketing.

Prof. Dr. Sang-Uk Jung
Dr. John Yang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sustainability marketing
  • consumer behavior
  • data analytics
  • sustainable consumption
  • ethical marketing
  • green marketing
  • AI and machine learning
  • consumer insights
  • behavioral data analysis

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Published Papers (4 papers)

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Research

15 pages, 613 KiB  
Article
Data-Driven Insights into Consumer Satisfaction in E-Learning: Implications for Sustainable Digital Marketing
by Daniel Moise, Elena Goga, Georgiana Rusu, Raluca-Giorgiana Chivu (Popa) and Mihai-Cristian Orzan
Sustainability 2025, 17(14), 6445; https://doi.org/10.3390/su17146445 - 14 Jul 2025
Viewed by 277
Abstract
This study investigates consumer satisfaction in e-learning services by addressing a specific gap in the literature: the limited integration of sustainability principles and behavioral modeling in understanding satisfaction drivers in online education. While existing studies have explored engagement and usability, few have considered [...] Read more.
This study investigates consumer satisfaction in e-learning services by addressing a specific gap in the literature: the limited integration of sustainability principles and behavioral modeling in understanding satisfaction drivers in online education. While existing studies have explored engagement and usability, few have considered how sustainability-related factors influence satisfaction in digital learning environments. Based on a conceptual model involving system quality, service quality, motivation, and cognitive engagement, we applied structural equation modeling (WarpPLS) to a sample of 312 university students from Romania, using mainstream learning management systems (LMS). Data were collected from students at the Bucharest University of Economic Studies using a convenience sampling method. The results show that service quality and cognitive engagement are the strongest predictors of satisfaction. This study offers practical recommendations for improving sustainable digital marketing strategies in e-learning, such as enhancing support services and aligning platform features with eco-conscious consumer expectations. Full article
(This article belongs to the Special Issue Sustainable Marketing: Consumer Behavior in the Age of Data Analytics)
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23 pages, 596 KiB  
Article
Variety-Seeking Shopping Behaviours in the Age of Green Content Marketing, Affiliate Marketing, and Shopping Motives: An Agenda for Future Research Using a TCCM Approach
by Valavadra Sahu, Honorata Barbara Howaniec, Saroj Kumar Sahoo, Simran Babu and Grzegorz Biesok
Sustainability 2025, 17(13), 5708; https://doi.org/10.3390/su17135708 - 20 Jun 2025
Viewed by 567
Abstract
In the evolving digital marketplace, consumer behaviour is increasingly shaped by green marketing strategies, particularly in the context of sustainable consumption. This study aims to examine the mechanisms through which green content marketing and green affiliate marketing influence green variety-seeking shopping behaviours, with [...] Read more.
In the evolving digital marketplace, consumer behaviour is increasingly shaped by green marketing strategies, particularly in the context of sustainable consumption. This study aims to examine the mechanisms through which green content marketing and green affiliate marketing influence green variety-seeking shopping behaviours, with particular attention to the role of green shopping motives and the effectiveness of marketing strategies. As traditional retail methods face limitations, digital marketing channels provide new avenues to engage consumers through personalized and dynamic content. Using the Theory–Context–Characteristics–Methodology (TCCM) framework, this research systematically examines the existing literature to identify key theories, contexts, characteristics, and methodologies relevant to variety-seeking behaviours towards green products. The study explores the psychological and behavioural drivers behind shopping choices, offering insights into why consumers exhibit variety-seeking behaviour when purchasing green products. The results indicate that effective green content and affiliate marketing drive variety-seeking behaviour in green shopping, with consumer motives serving as a key mediating factor. The conceptual model developed in this study provides a structured understanding of how modern marketing strategies shape consumer preferences and engagement with green products. This study offers a future research agenda and practical implications for marketers and retailers. By understanding these influences, businesses can refine their marketing strategies to strengthen green shopping motives, encourage sustainable consumption over traditional consumption, and adapt to the dynamic retail landscape. Full article
(This article belongs to the Special Issue Sustainable Marketing: Consumer Behavior in the Age of Data Analytics)
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30 pages, 3873 KiB  
Article
Multi-Source Data-Driven Personalized Recommendation and Decision-Making for Automobile Products Based on Basic Uncertain Information Order Weighted Average Operator
by Yi Yang, Mengqi Jie and Jiajie Pan
Sustainability 2025, 17(9), 4078; https://doi.org/10.3390/su17094078 - 30 Apr 2025
Viewed by 431
Abstract
The extensive electronic word-of-mouth (eWOM) data generated by consumers encapsulates authentic product experience information. By leveraging advanced data analysis technologies, enterprises can extract sustainable consumer behavior preference knowledge, thereby supporting the optimization of their marketing and management strategies. However, existing data-driven product ranking [...] Read more.
The extensive electronic word-of-mouth (eWOM) data generated by consumers encapsulates authentic product experience information. By leveraging advanced data analysis technologies, enterprises can extract sustainable consumer behavior preference knowledge, thereby supporting the optimization of their marketing and management strategies. However, existing data-driven product ranking processes predominantly focus on single-source eWOM data and rarely mine product insights from a multi-source perspective. Moreover, the quality of eWOM data cannot be overlooked. Consequently, this study uses automobile products as a case example and integrates rating eWOM data, complaint eWOM data, and safety test data to construct a multi-source data-driven personalized product ranking recommendation algorithm. Specifically, an evaluation index system is established for each of the three data types. To model information quality, these data are transformed into basic uncertain information (BUI), which incorporates scoring information and credibility metrics. The XLNet model is employed to convert complaint text data into scoring data, and three targeted credibility evaluation models are developed to assess the reliability of the three data types. Subsequently, BUI is aggregated using the BUI ordered weighted average (BUIOWA) aggregation operator. Based on this, a personalized product ranking method aligned with user preferences is proposed, offering consumers recommendation results that match their preferences. Finally, using automobile products as an illustrative example, this study elucidates the multi-source data-driven personalized product recommendation process and provides managerial implications for enterprises. Full article
(This article belongs to the Special Issue Sustainable Marketing: Consumer Behavior in the Age of Data Analytics)
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18 pages, 536 KiB  
Article
Exploring the Impact of the Green Marketing Mix on Environmental Attitudes and Purchase Intentions: Moderating Role of Environmental Knowledge in China’s Emerging Markets
by Siwen Su and Yannan Li
Sustainability 2024, 16(24), 10934; https://doi.org/10.3390/su162410934 - 13 Dec 2024
Cited by 1 | Viewed by 3964
Abstract
This study examines how the green marketing mix—comprising green product, price, place, and promotion—affects consumers’ environmental attitudes and green purchase intentions, incorporating environmental knowledge as a moderating factor, focusing on a sample of 334 environmentally conscious consumers from second- and third-tier cities in [...] Read more.
This study examines how the green marketing mix—comprising green product, price, place, and promotion—affects consumers’ environmental attitudes and green purchase intentions, incorporating environmental knowledge as a moderating factor, focusing on a sample of 334 environmentally conscious consumers from second- and third-tier cities in China. Structural equation modeling (SEM) was used to analyze the data collected through SPSS 24 and AMOS 26. The results indicate that green promotion, price, and place significantly influenced environmental attitude, while green products did not show a significant effect. Both green products and promotions positively affected green purchase intention, whereas price and place had no notable impact. Environmental attitude strongly influenced green purchase intention, emphasizing its critical role in shaping consumer behavior. Interestingly, higher levels of environmental knowledge weakened the link between environmental attitude and green purchase intention, potentially due to increased skepticism toward environmental claims and the onset of “green fatigue”. By analyzing data from consumers in China’s second- and third-tier cities, this study provides valuable insights into the unique dynamics of green consumer behavior in emerging markets, offering strategic guidance for companies to develop more effective and environmentally responsible marketing approaches. It offers insights for policymakers to promote a sustainable, eco-conscious society. Full article
(This article belongs to the Special Issue Sustainable Marketing: Consumer Behavior in the Age of Data Analytics)
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