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Digital Marketing in Practice: Platforms, AI, Trust and Market Solutions
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Digital Marketing in Practice: Platforms, AI, Trust and Market Solutions

A Special Issue of Journal of Theoretical and Applied Electronic Commerce Research (ISSN 0718-1876).

Deadline for manuscript submissions: 30 November 2026 | Viewed by 16431

Editor

Prof. Dr. Klaus Solberg Söilen

E-Mail Website
Guest Editor
School of Business, Innovation and Sustainability, Halmstad University, Kristian IV:s väg 3, 301 18 Halmstad, Sweden
Interests: digital marketing

Special Issue Information

Dear Colleagues,

Digital marketing is a field defined less by abstract debate than by a constant stream of concrete problems that demand practical solutions. Firms face challenges such as last-mile optimization in e-commerce, rapidly shifting platform demographics (for example, changing age patterns on TikTok), trust formation in digital health applications, data integration across channels, and the effective use of AI in customer interaction. These problems are operational and strategic at the same time—and they evolve faster than traditional academic cycles.

The aim of this Special Issue, titled “Digital Marketing in Practice: Platforms, AI, Trust and Market Solutions”, is therefore explicitly applied. We invite contributions that engage directly with real-world problems and offer well-argued, practically relevant solutions. Submissions should clearly state the concrete problem being addressed and explain why solving it matters—academically, managerially, or societally. Theory and methods are welcome, but they must be instrumental: used to explain, design, or evaluate solutions that have clear relevance beyond the paper itself.

The thematic scope is intentionally broad and spans the core domains of contemporary digital marketing, including platforms, analytics, artificial intelligence, customer experience, trust, content, logistics, pricing, and digital ecosystems. There are no rigid boundaries. The single guiding criterion is usefulness.

This Special Issue particularly welcomes contributions from scholars and practitioners who combine solid research competence with an interest in applied problem-solving and industry relevance. The overarching goal is to generate insights that are directly valuable to firms operating in digital markets and, ultimately, to the consumers they serve.

Prof. Dr. Klaus Solberg Søilen
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Theoretical and Applied Electronic Commerce Research is an international peer-reviewed open access monthly 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 1400 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

  • digital marketing
  • applied digital marketing
  • platform strategies
  • e-commerce optimization
  • customer trust
  • AI in marketing
  • data-driven marketing

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (6 papers)

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Research

21 pages, 2310 KB  
Article
Authenticity, Trust, and AI Skepticism in Green Advertising: How AI and Human Endorsers Influence Purchase Intention in E-Commerce
by Song Yi Suh
J. Theor. Appl. Electron. Commer. Res. 2026, 21(9), 295; https://doi.org/10.3390/jtaer21090295 - 1 Sep 2026
Viewed by 895
Abstract
Despite the growing use of artificial intelligence (AI) endorsers in advertising, evidence of their effectiveness remains mixed. This study examines how AI and human endorsers influence purchase intention in green e-commerce advertising through the parallel and sequential roles of perceived authenticity and perceived [...] Read more.
Despite the growing use of artificial intelligence (AI) endorsers in advertising, evidence of their effectiveness remains mixed. This study examines how AI and human endorsers influence purchase intention in green e-commerce advertising through the parallel and sequential roles of perceived authenticity and perceived trust. It also investigates whether AI skepticism moderates the relationship between endorser type and perceived authenticity. In a between-subjects experiment, 521 South Korean adults were randomly assigned to view a green advertisement featuring either a human or an AI endorser. The results indicate that endorser type did not directly affect purchase intention. Instead, its influence began with authenticity, which mediated the effect independently and also initiated a sequential pathway through trust. Trust therefore functioned only downstream of authenticity and did not independently mediate the relationship. AI skepticism moderated the effect of endorser type on authenticity, with the human endorser’s authenticity advantage narrowing as skepticism increased. The sequential indirect effect also weakened at higher levels of AI skepticism. These findings position endorser type as a source cue whose influence begins with authenticity judgments and may subsequently extend through trust. The study advances research on AI endorsers and green advertising by identifying the mechanisms and boundary conditions that underlie the effects of endorser type. For practitioners, the findings highlight the importance of substantiating environmental claims and testing AI and human endorsement strategies across relevant audience segments. Full article
(This article belongs to the Special Issue Digital Marketing in Practice: Platforms, AI, Trust and Market Solutions)
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32 pages, 3117 KB  
Article
From Service Touchpoint to Governance Interface: Anthropomorphic AI, Complaint Severity, and Trust in C2C Platform Complaint Handling
by Cong Sun, Xinyu Li and Xing Meng
J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 215; https://doi.org/10.3390/jtaer21070215 - 8 Jul 2026
Viewed by 986
Abstract
Unlike B2C service failures, where firms respond to their own failures within a dyadic firm–customer relationship, C2C platform complaints often originate from third-party sellers. In such triadic platform–seller–consumer interactions, AI customer service agents become front-end governance interfaces through which consumers judge platform fairness, [...] Read more.
Unlike B2C service failures, where firms respond to their own failures within a dyadic firm–customer relationship, C2C platform complaints often originate from third-party sellers. In such triadic platform–seller–consumer interactions, AI customer service agents become front-end governance interfaces through which consumers judge platform fairness, rule enforcement, and institutional reliability. This study examines anthropomorphic AI as a task-contingent governance cue in C2C platform complaint handling. Across two scenario-based experiments, we test how AI role framing, anthropomorphism, and complaint severity jointly shape consumer evaluations. Study 1 shows that high anthropomorphism increases service recovery satisfaction when AI is framed as a relational representative, but not when framed as a rule-based arbitrator. Study 2 reveals significant three-way interactions among complaint severity, role framing, and anthropomorphism for satisfaction, platform trust, and continuance intention. Under low severity, high anthropomorphism benefits both roles; under high severity, its benefit remains mainly for the relational representative and weakens for the rule-based arbitrator. Mechanism analyses show that social presence explains responses under low severity, whereas both social presence and procedural justice shape evaluations under high severity. Together, these findings identify governance-task fit as a key condition for the value of anthropomorphic AI in platform complaint handling, showing when human-like AI builds trust and when it may undermine governance credibility. Full article
(This article belongs to the Special Issue Digital Marketing in Practice: Platforms, AI, Trust and Market Solutions)
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18 pages, 2536 KB  
Article
Digital Marketing Practices as Drivers of Organizational Culture Change During Second-Generation Succession in Family Firms
by Maija Dobele, Jelizaveta Prilucka and Klaus Solberg Söilen
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 162; https://doi.org/10.3390/jtaer21060162 - 27 May 2026
Viewed by 649
Abstract
Family firms are central to global economic stability and employment. Generational transitions, however, involve not only the transfer of leadership but also changes in organizational structures and culture. As digitalization becomes increasingly important for competitiveness, successors are introducing digital marketing practices that may [...] Read more.
Family firms are central to global economic stability and employment. Generational transitions, however, involve not only the transfer of leadership but also changes in organizational structures and culture. As digitalization becomes increasingly important for competitiveness, successors are introducing digital marketing practices that may influence organizational culture during leadership transitions. While previous research has examined digital transformation in family businesses, limited attention has been given to the role of digital marketing as a mechanism of cultural change during generational succession. This article addresses the question: How do second-generation successors use digital marketing practices to shape organizational culture during generational transitions in family firms? Drawing on practice theory and Schein’s model of organizational culture, the study explores how cultural change unfolds through everyday practices within organizations. The research employs a qualitative multiple-case study approach based on semi-structured interviews with representatives from 35 family firms in Latvia. The findings identify key digital marketing practices implemented by second-generation successors and illustrate how these practices influence organizational culture during the transition process. The results suggest that digital marketing can both reinforce existing organizational values and selectively reshape organizational identity and legitimacy. The study highlights digital marketing as a culturally legitimate tool through which successors can influence decision-making processes, coordination mechanisms, and authority structures during generational succession. Full article
(This article belongs to the Special Issue Digital Marketing in Practice: Platforms, AI, Trust and Market Solutions)
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26 pages, 1213 KB  
Article
The Role of Algorithmic Anthropomorphism, Transparency, and Fairness in Shaping Consumer Purchase Intentions in E-Commerce: Evidence from Türkiye
by Gulfem Yagmurdur, Yan Meng and Savas Gayaker
J. Theor. Appl. Electron. Commer. Res. 2026, 21(5), 159; https://doi.org/10.3390/jtaer21050159 - 21 May 2026
Cited by 2 | Viewed by 2245
Abstract
Artificial intelligence (AI) is increasingly being deployed in various sectors of e-commerce. Consequently, it becomes necessary to identify the impact of algorithmic design parameters on buyer behaviour. This study examines the impact of algorithmic anthropomorphism (ANT), algorithmic transparency (TRAN) and perceived algorithmic fairness [...] Read more.
Artificial intelligence (AI) is increasingly being deployed in various sectors of e-commerce. Consequently, it becomes necessary to identify the impact of algorithmic design parameters on buyer behaviour. This study examines the impact of algorithmic anthropomorphism (ANT), algorithmic transparency (TRAN) and perceived algorithmic fairness (FAIR) on consumer purchase intentions (PI) in the Turkish e-commerce market. In addition, this study examines technology acceptance—operationalised through the Technology Acceptance Model (TAM)—as a boundary condition, with particular attention to the differential moderating roles of perceived ease of use (PEOU) and perceived usefulness (PU). A structured questionnaire was distributed among 384 online consumers in Türkiye via Qualtrics. A confirmatory factor analysis (CFA) established the psychometric adequacy of the measurement model (all AVE > 0.50, all CR > 0.87; HTMT < 0.85 across theoretically distinct constructs). The proposed model was tested using the PROCESS macro for sequential mediation and moderation analyses, with bootstrap confidence intervals based on 5000 resamples. The results reveal that: (1) algorithmic anthropomorphism positively affects both algorithmic transparency and perceived algorithmic fairness; (2) algorithmic transparency has a significant positive effect on both perceived fairness and purchase intention; (3) perceived algorithmic fairness mediates the relationships between algorithmic anthropomorphism and purchase intention, as well as between algorithmic transparency and purchase intention; and (4) although the composite technology acceptance level (TAL) measure does not significantly moderate the anthropomorphism–purchase intention path (p = 0.075), disaggregating TAL into its sub-dimensions reveals that PEOU significantly moderates this relationship (p < 0.001), whereas PU does not (p = 0.199). The composite-TAL result is therefore not statistically supported, but the dimension-specific PEOU finding is robust. These findings offer theoretical contributions to AI-driven consumer behaviour research and practical implications for the design of algorithmic e-commerce systems in emerging digital markets. Full article
(This article belongs to the Special Issue Digital Marketing in Practice: Platforms, AI, Trust and Market Solutions)
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25 pages, 1318 KB  
Article
AI Labels, Perceived Authenticity, and Consumer Trust in User-Generated Reviews
by Dariia Drozd and Klaus Solberg Söilen
J. Theor. Appl. Electron. Commer. Res. 2026, 21(5), 154; https://doi.org/10.3390/jtaer21050154 - 14 May 2026
Cited by 4 | Viewed by 6984
Abstract
With growing interest in the effects of AI disclosure on user-generated content, empirical studies have produced mixed results. While some studies report negative consequences of disclosure, others suggest that transparent AI use does not necessarily reduce perceived authenticity or product evaluations. There is [...] Read more.
With growing interest in the effects of AI disclosure on user-generated content, empirical studies have produced mixed results. While some studies report negative consequences of disclosure, others suggest that transparent AI use does not necessarily reduce perceived authenticity or product evaluations. There is still limited knowledge about how AI disclosure in online reviews influences consumer perceptions when AI is presented as a support tool rather than a replacement for human input. To address this gap, the present study examines how AI disclosure and AI-related review cues influence consumer trust. The study compares three labeled review scenarios—reviews without AI-related information, AI-assisted labeled reviews, and AI-generated labeled reviews. The textual content of the reviews remained constant across conditions, while only AI-related labels and images were varied. This study also examines how these labeled scenarios relate to perceived authenticity and whether perceived authenticity mediates the relationship between labeled review scenarios and consumer trust. Based on survey data from 370 users of digital marketplaces in Latvia, analyzed using repeated-measures ANOVA, pairwise comparisons, and mediation analysis, this study found that: (1) reviews labeled as AI-generated showed the lowest levels of consumer trust and perceived authenticity, whereas AI-assisted labeled reviews were evaluated more favorably than AI-generated labeled reviews; (2) differences across the three scenarios were statistically significant for both consumer trust and perceived authenticity; and (3) perceived authenticity significantly mediated the relationship between labeled review scenarios and consumer trust. This study contributes to the literature by providing a more nuanced understanding of how AI disclosure and AI-related review cues shape consumer trust. It suggests that the key issue is not AI disclosure alone, but how AI-related cues shape perceived authenticity and, in turn, consumer trust. Full article
(This article belongs to the Special Issue Digital Marketing in Practice: Platforms, AI, Trust and Market Solutions)
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27 pages, 3391 KB  
Article
AI-Powered Customer Service in Online Retail: Product-Type Differences, Information Asymmetry, and Seller Interventions
by Shuyuan Bai, Xinquan Wang and Jun Xia
J. Theor. Appl. Electron. Commer. Res. 2026, 21(3), 97; https://doi.org/10.3390/jtaer21030097 - 23 Mar 2026
Cited by 1 | Viewed by 3055
Abstract
The rapid integration of AI customer service in e-commerce raises an important managerial question: Can AI effectively reduce product-related information asymmetry and improve sales performance across different product types? While prior research highlights both the uncertainty-reducing benefits of information and the risks of [...] Read more.
The rapid integration of AI customer service in e-commerce raises an important managerial question: Can AI effectively reduce product-related information asymmetry and improve sales performance across different product types? While prior research highlights both the uncertainty-reducing benefits of information and the risks of algorithm aversion, little is known about how AI customer service performs under varying levels of product uncertainty and information asymmetry. Using a difference-in-differences design with fixed effects across time, products, shops, and categories, we examine the impact of replacing customer service with AI on sales outcomes, distinguishing between search and experience goods. We further test how the depth and breadth of product information moderate these effects. Our findings indicate that AI customer service reduces sales for experience goods but not for search goods, unless accompanied by sufficient informational depth and breadth. We argue that this effect arises because AI technically inherits and amplifies the information asymmetry inherent in experience products, while greater informational depth and breadth of product information can mitigate this amplified asymmetry. Additionally, we find that this mitigating effect is more pronounced among products with high return rate. These findings clarify when AI-generated information mitigates product uncertainty and when it exacerbates it. Our results provide actionable guidance for firms seeking to deploy AI strategically in digital commerce environments. Full article
(This article belongs to the Special Issue Digital Marketing in Practice: Platforms, AI, Trust and Market Solutions)
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