GMC 2025

Introduction

Two additional special issues at the Global Marketing Conference, Hong Kong, 24-27 Jul 2025; Deadline 15 Feb

POSTING TYPE: Revisits

Posted by: Kyung Hoon Kim

Call for Papers

2025 Global Marketing Conference (GMC) Track on Envisioning the Future of Hospitality and Tourism Research: Innovative Theorization, Advanced Data, and New Insights.

Sponsored by Tourism Management (2-year IF: 10.9, ABCD: A*) and

International Journal of Contemporary Hospitality Management (2-year IF: 9.10, ABDC: A)

Track Chairs:

Xingyu Huang, Ph.D., Department of Marketing, School of Business and Management, Royal Holloway, University of London, UK, xingyu.huang@rhul.ac.uk.

Hyunsu Kim, Ph.D., Department of Management, College of Business and Economics, California State University, Fullerton, USA, hyunsukim@fullerton.edu.

Kevin Kam Fung So, Ph.D., White Lodging-J.W., Jr. Marriott School of Hospitality and Tourism Management, Purdue University, USA, kevinso@purdue.edu.

Xiang (Robert) Li, Ph.D., School of Sport, Tourism and Hospitality Management, Temple University, USA, robertli@temple.edu.

Extended abstracts or full papers for conference submissions must be received by January 15, 2025

The 2025 Global Marketing Conference (GMC) () will be held in Hong Kong, China on July 24 – 27, 2025. The theme of this year’s conference is “Marketing & Management Transformation in the Age of Digital Challenges.” We warmly welcome submissions for consideration for the “Envisioning the Future of Hospitality and Tourism Research: Innovative Theorization, Advanced Data, and New Insights” track of the 2025 GMC (), sponsored by Tourism Management (2-year IF: 10.9, ABDC: A*) and International Journal of Contemporary Hospitality Management (2-year IF: 9.10, ABDC: A).

The unprecedented technological advancements have introduced a transformative era in the hospitality and tourism sectors, redefining how companies are managed and operated, how service is produced and delivered, and how data are gathered and utilized (Lv et al., 2022; Xiang, 2018). Fueled by the increasing adoption of digital platforms, richer data, and AI-driven strategies, the business landscape is becoming more dynamic. This widespread and multifaceted transformation places hospitality and tourism research at a pivotal moment, undergoing significant shifts that necessitate a re-evaluation of existing theories, methodologies, and a deeper understanding of industry dynamics.

Against this backdrop, significant concerns have been raised in the literature. For example, from a theoretical development perspective, Jafari and McCabe (2024) indicate that we seem no closer to developing a coherent theory of hospitality and tourism than we were 50 years ago. Similarly, Cai and

McKenna (2021) critique the current state of information technology and tourism research, urging a broader and more critical reexamination of its paradigmatic boundaries through reflective theorization within a wider social context. McCabe (2024) argues that the constant evolution of hospitality and tourism practices presents significant opportunities for theorizing, calling for future research to not only develop new theories but also refine existing ones to better reflect contemporary industry dynamics.

The transformation is further accelerated by innovative methodological advances. The nature and forms of data, for instance, have become increasingly rich and vastly complex, driving significant progress in analytical techniques including, but not limited to, textual analysis (H. Li et al., 2023; Zheng et al., 2023), image analysis (He et al., 2022; M. Zhou et al., 2023), video analysis (Guo et al., 2024; Zhu & Cheng, 2024), eye-tracking (P. Li et al., 2023; Wang & Sparks, 2016), voice mining (Wang et al., 2024), large language modeling (Liu et al., 2023), machine learning (Viverit et al., 2023), neural network (Binesh, 2024), and neuroscience (S. Li et al., 2023). In a similar vein, data from sources like user-generated content and physiological indicators, when processed and analyzed using innovative techniques, can open new research avenues and challenge the conventional wisdom that relies on traditional methods (Q. Zhou et al., 2023). However, despite the availability of new data collection methods, the field seems to remain heavily dependent on consumer-generated, self-reported surveys and online experimental data (Dolnicar et al., 2024). Thus, there is a growing need to effectively utilize and integrate multifaceted data sources (e.g., non-consumer data, unstructured data, time-spatial data), fostering more comprehensive, valid, and generalizable insights into hospitality and tourism.

To generate new research insights, scholars have highlighted specific areas where advanced methodologies and next-generation theorizing can be effectively applied, such as digital transformation, big data analytics, and the evolving landscape of AI and its applications. For example, digital transformation necessitates that organizations reconstruct game-changing efficiencies, achieve breakthroughs in customer experience and value, ensure scalability, and optimize strategic agility (Busulwa et al., 2022). Additionally, given that AI is significantly transforming businesses, researchers in hospitality and tourism are increasingly interested in exploring how AI will shape the future of the industry, including its impact on business management and customer interactions (Kim et al., 2024; Liu & Xu, 2023; Yin et al., 2024). Other emerging technologies such as automation (Tussyadiah, 2020), service robots (McCartney & McCartney, 2020; So et al., 2024), AR/VR (Bird et al., 2023; Fan et al., 2022) and blockchain (Filimonau & Naumova, 2020; Önder & Gunter, 2022), combined with their roles in service innovation, will continue to transform service operations and influence how people live and engage in hospitality and tourism consumption, thus presenting new directions for research that shapes the future of the hospitality and tourism management discipline.

The evolving dynamics highlighted above have called for a rigorous academic inquiry to develop a comprehensive understanding of how the future of hospitality and tourism will likely unfold in the coming years. Therefore, this conference track seeks path-setting studies that enrich existing scholarship with creative and impactful contributions to the fast-changing hospitality and tourism academia and industry. Accordingly, we aim to collectively envision the future of hospitality and tourism research through innovative theorization, advanced data, and new insights. Potential topics in hospitality and tourism include, but are not limited to, the following:

  • How do theories interact with rapidly evolving technological developments and practices?
  • How are existing theories reexamined, challenged, and reshaped to better reflect the shifting dynamics of academia and industry?
  • What are the emerging theories, models, frameworks, and concepts for understanding and addressing academia and industry challenges?
  • What are the types of diverse data sources (e.g., non-consumer data, unstructured data, time-spatial data) being leveraged to gain insights into the rapidly evolving hospitality and tourism industry?
  • How can advanced analytic techniques be effectively applied to enhance and refine existing knowledge or enable the discovery of new insights?
  • How can the development of data and analytical methods challenge and refine traditional measurements and metrics?
  • How do innovative data sources and analytical techniques pave the way for emerging research opportunities (e.g., AI, digital transformation, sustainability, wellness, resilience)?
  • How do evolving technologies drive the re-evaluation of existing business models and strategies?
  • How do technological advancements and industry transformations influence ethical concerns such as social responsibility, privacy, fairness, and security?
  • What new research directions are enabled by the intersection of technological developments and the hospitality and tourism industry?
  • What opportunities and challenges could arise for the hospitality and tourism academia and industry during and after this transformative era?

Submission guidelines

Scholars should submit their extended abstracts or full conference papers by January 15, 2025. A Word or PDF document containing the manuscript should be submitted through the conference submission portal:. Submission guidelines can be found at: 2025 Global Marketing Conference in Hong Kong (). An automatic e-mail response will be sent to the contact author once the manuscript has been received by the conference. If authors do not receive confirmation of their submission within 2 weeks, please send an email to2025gmc.hospitalitytourism@gmail.com.

This conference track is sponsored by two prestigious journals:Tourism ManagementandInternational Journal of Contemporary Hospitality Management. Selected papers from the track will be recommended for publication consideration by Tourism Management and International Journal of Contemporary Hospitality Management. All selected papers submitted in full will be subject to the journals’ formal double-blind review process. A recommendation to submit a full paper does not guarantee conditional acceptance or publication.

Journal of Current Issues and Research in Advertising– Special Issue

“AI-Enabled Brand Touchpoints”

Submission Deadline for the 2025 GMC at Hong Kong: February 15, 2025

Since the end of 2022, hardly any other topic has changed the brand, marketing, and advertising world as much as AI (Huang & Rust, 2021; Deryl et al., 2023, Gao et al., 2023). Now that the initial hype has slowly died down, the focus is shifting toward more meaningful and effective applications of AI—such as enhancing creativity (e.g., Pagani & Wind, 2024; Bohren et al., 2024) and brand control (Li et al., 2023; Sarstedt et al., 2024)—as well as improving efficiency in brand management, communication, and advertising (Dell’Acqua et al., 2023). In addition to the direct use of generative AI, particularly for creating brand touchpoints (e.g. design, Moureau et al., 2023), AI is also an integral part of other technology-based brand touchpoints like social robotics (Choi et al., 2022) and virtual influencers (Baumgarth et al., 2021; Laszkiewicz & Kalinska‐Kula, 2023).

The management and technology perspective needs to be expanded to include a consumer perspective on the impact of AI- and technology-based touchpoints. This perspective provides answers to questions such as the effect of disclosing AI as the source of advertising and other touchpoints on brand authenticity (Kirkby et al., 2023) and creative judgment (Grassini & Koivisto, 2024).

In addition to established brands, emerging and small and medium-sized enterprises (SME brands) are uniquely positioned to leverage AI for rapid scalability, creativity, and efficiency. However, they also face challenges in integrating AI effectively due to resource constraints (Schönberger, 2023).

Finally, the use of technology-based brand touchpoints is connected with legal and ethical challenges like copyright issues (Drott, 2021), deepfakes (Campbell et al., 2022), and AI bias (Akter et al., 2022; Atari et al., 2023).

This special issue aims to contribute to a better understanding of this broad and dynamic field of AI-enabled brand touchpoints and to provide brand management with scientifically sound recommendations through innovative, theoretically sound, and evidence-based research results. For this special issue, we welcome conceptual and empirical papers that use quantitative and qualitative methodological approaches to advance research regarding developments in AI and technology-enabled brand touchpoints.

Suggested topics include but are not limited to:

  • Use of generative AI to develop brand touchpoints (advertising, brand communication, service, design, product innovation)
  • Use of AI-powered social robots and voice assistants as brand touchpoints
  • AI-powered virtual influencers as brand touchpoints
  • Ensuring “brand rules” of brand touchpoint creation (e.g. brand consistency) in AI tools
  • Effects of disclosing AI as the source of the brand touchpoints
  • Changes in brand touch work in companies and advertising agencies through AI
  • AI creativity in brand management, brand work, and advertising
  • Augmented brand intelligence by combining AI and humans
  • AI and technology in advertising for SMEs and Emerging Brands
  • Use of AI to analyze brand touchpoints
  • Ethical and legal limits of using AI in brand work and advertising
  • Sustainability & AI-enabled brand touchpoints

Submission information

Conference (GMC) at Hong Kong submission page: . Full paper or extended abstract submissions to the 2025 GMC at Hong Kong should follow the 2025 GMC submission guidelines (). The manuscript’s title page should include the corresponding author’s name, affiliation, mailing address, telephone number, and e-mail address. Names and contact information for other authors should be included as well. All manuscripts submitted must not have been published, accepted for publication, or be currently under consideration elsewhere. Accepted papers will be presented at the 2025 GMC at Hong Kong and selected papers will be invited to be submitted as full papers for the JCIRA special issue. Full paper submissions are encouraged while 5-page extended abstracts can also be submitted.

We welcome submissions from non-GMC members but will give special consideration to manuscripts submitted to the 2025 Global Marketing Conference at Hong Kong.

Submission deadline for 2025 Global Marketing Conference at Hong Kong is 15th February 2025.

Journal of Current Issues and Research in Advertising

Journal of Current Issues and Research in Advertising will publish a special issue on AI and Technology-Enabled Brand Touchpoints with the best papers presented at the following track in the 2025 GMC at Hong Kong called‘AI and Technology-Enabled Brand Touchpoints’. Guest Editors: Prof. Hyejin Bang, Department of Business Administration, College of Business, Kookmin University, 77 Jeongneung-Ro, Seongbuk-Gu, Seoul, 02707 (South Korea), hjbang@kookmin.ac.kr. Prof. Carsten Baumgarth, HWR Berlin – Berlin School of Economics and Law, Badensche Straße 52, 10825 Berlin(Germany), carsten.baumgarth@hwr-berlin.de.

Direct inquiries to the Special Issue Co-Editors:

Hyejin Bang1 (hjbang@kookmin.ac.kr)

Carsten Baumgarth2 (carsten.baumgarth@hwr-berlin.de)

1 Department of Business Administration, College of Business, Kookmin University, Seoul (Republic of Korea)

2 Department of Business Administration, HWR Berlin – Berlin School of Economics and Law, Berlin (Germany).

For more information:

Journal of Current Issues and Research in Advertising:

2025 Global Marketing Conference at Hong Kong:

References:

Akter, S., Dwivedi, Y. K., Sajib, S., Biswas, K., Bandara, R. J., & Michael, K. (2022). Algorithmic bias in machine learning-based marketing models.Journal of Business Research,144, 201-216.

Atari, M., Xue, M. J., Park, P. S., Blasi, D., & Henrich, J. (2023). Which humans?.

Baumgarth, C., Kirkby, A., & Kaibel, C. (2021). When fake becomes real: The innovative case of artificial influencers. In Creativity and marketing: The fuel for success (pp. 149-167). Emerald Publishing Limited.

Bohren, N., Hakimov, R., & Lalive, R. (2024). Creative and Strategic Capabilities of Generative AI: Evidence from Large-Scale Experiments.

Campbell, C., Plangger, K., Sands, S., & Kietzmann, J. (2022). Preparing for an era of deepfakes and AI-generated ads: A framework for understanding responses to manipulated advertising.Journal of Advertising,51(1), 22-38.

Choi, S., Liu, S. X., & Choi, C. (2022). Robot–brand fit the influence of brand personality on consumer reactions to service robot adoption.Marketing Letters,33(1), 129-142.

Dell’Acqua, F., McFowland III, E., Mollick, E. R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., … & Lakhani, K. R. (2023). Navigating the jagged technological frontier: Field experimental evidence of the effects of AI on knowledge worker productivity and quality.Harvard Business School Technology & Operations Mgt. Unit Working Paper, (24-013).

Deryl, M. D., Verma, S., & Srivastava, V. (2023). How does AI drive branding? Towards an integrated theoretical framework for AI-driven branding.International Journal of Information Management Data Insights,3(2), 100205.

Drott, E. (2021). Copyright, compensation, and commons in the music AI industry.Creative Industries Journal,14(2), 190-207.

Gao, B., Wang, Y., Xie, H., Hu, Y., & Hu, Y. (2023). Artificial intelligence in advertising: advancements, challenges, and ethical considerations in targeting, personalization, content creation, and ad optimization.Sage Open,13(4), 21582440231210759.

Grassini, S., & Koivisto, M. (2024). Understanding how personality traits, experiences, and attitudes shape negative bias toward AI-generated artworks.Scientific Reports,14(1), 4113.

Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing.Journal of the Academy of Marketing Science,49, 30-50.

Kirkby, A., Baumgarth, C., & Henseler, J. (2023). To disclose or not disclose, is no longer the question–effect of AI-disclosed brand voice on brand authenticity and attitude.Journal of Product & Brand Management,32(7), 1108-1122.

Laszkiewicz, A., & Kalinska‐Kula, M. (2023). Virtual influencers as an emerging marketing theory: A systematic literature review.International Journal of Consumer Studies,47(6), 2479-2494.

Li, P., Castelo, N., Katona, Z., & Sarvary, M. (2023). Language models for automated market research: A new way to generate perceptual maps.Available at SSRN 4241291.

Moreau, P., Prandelli, E., & Schreier, M. (2023). Generative Artificial Intelligence and Design Co-Creation in Luxury New Product Development: The Power of Discarded Ideas.Available at SSRN 4630856.

Pagani, M., & Wind, Y. (2024). Unlocking Marketing Creativity Using Artificial Intelligence.Journal of Interactive Marketing, 10949968241265855.

Sarstedt, M., Adler, S. J., Rau, L., & Schmitt, B. (2024). Using large language models to generate silicon samples in consumer and marketing research: Challenges, opportunities, and guidelines.Psychology & Marketing,41(6), 1254-1270.

Schönberger, M. (2023). Artificial Intelligence for Small and Medium-Sized Enterprises: Identifying Key Applications and Challenges. Journal of Business Management, 21, 89-112.

Thomas, V. L., & Fowler, K. (2021). Close encounters of the AI kind: Use of AI influencers as brand endorsers.Journal of Advertising,50(1), 11-25.