This case presents a study of how QR code menus have emerged as a popular and sustainable solution for the hospitality industry in the wake of the COVID-19 pandemic. The case explores the environmental benefits of QR code menus in the restaurant industry by drawing on existing literature and examining how QR code menus can reduce paper waste, lower carbon footprint, and promote sustainable practices. The case also discusses how QR code menus contribute to several United Nations Sustainable Development Goals (SDGs), such as SDG 12 (Responsible Consumption and Production), SDG 13 (Climate Action), and SDG 17 (Partnerships for the Goals). The case concludes that QR code menus offer various benefits for restaurants and customers, such as reducing waste, enhancing customer experience, supporting local and organic food producers, and promoting responsible consumption and production. The case also suggests that QR code menus are not only a digital transformation tool but also a step towards creating a more eco-friendly and resilient restaurant industry.

This session explores the impact of AI and robotics on marketing, consumer research, innovation, and societal challenges. AI applications are revolutionizing areas such as product design, customer service, advertising, healthcare, education, branding, and business model management.

The session will feature a roundtable discussion with academics sharing insights on AI and robotic technologies and their broader implications for researchers, marketers, and society.

Potential discussion topics include (but are not limited to):

• Key uses of AI and robotics in domains like product recommendations, education, design, innovation, and customer engagement, along with their contributions to society, the economy, and the environment
• Barriers and facilitators of AI and robotics adoption, including cultural and regional differences, societal factors, and varying consumer perceptions
• The role of AI and robotics in enhancing decision-making, well-being, and marketing strategies
• Growing concerns around data governance, labour markets, consumption patterns, and future research priorities
• Ontological and ethical dilemmas arising from the potential realization of Artificial General Intelligence (AGI)

The session will consist of a one-hour roundtable followed by a 30-minute Q&A.

Participants will gain insights into how AI advancements can be utilized in marketing strategies,ensuring alignment with public interest and fostering interdisciplinary partnerships to strengthenresearch and secure funding.

This paper examines how brand museums, as themed environments, commodify and transfer the cultural heritage of organisations to their stakeholders. We conduct a qualitative study based on six in-depth interviews with top management professionals at the IKEA Museum. Rooted deeply in the Swedish socio-cultural ecosystem, the IKEA Museum uses various strategies to commodify its cultural heritage, such as displaying historical artefacts, creating interactive exhibits, narrating stories of innovation and social responsibility, and offering co-creation opportunities to visitors. In doing so it plays a prominent role in enabling cultural transfer and fosters intergenerational cultural memory among its stakeholders. The theoretical conceptualization is presented by proposing the Synthesis of Cultural Transfer, Value Outcomes, and Intergenerational Memory framework (SCTIM), and implications are discussed.

Purpose - This research aims to understand the dynamics that drive consumer engagement of multinational brands' social media posts on platform X, formerly known as Twitter. Taking the emotional tone of posts into account, the effect of vivid, interactive, informative, entertaining and practical features of posts on consumer interactions are evaluated across English- and Turkish-speaking markets.

Methodology - Inspired by the conceptual framework proposed in previous literature, features were extracted computationally using natural language processing from platform X posts of 33 Fortune 500 brands from various industries from June 2016 to June 2021. Following evaluation of regression models on alternative distributions of the dependent variable, which is total number of likes, shares and comments, random subspace regression using bootstrap resampling was applied to calculate an importance score and evaluate the effect of features.

Findings - Consumers in English- and Turkish-speaking markets perceive and engage with content differently. While informative and entertaining posts resonate more with English speakers, emotions play a broader role for Turkish speakers. English-speaking audience prefers happy and vivid daytime messages with questions, while Turkish-speaking audience is drawn to angry messages, lean toward nighttime posts.

Originality - This research is a pioneer to evaluate the factors that influence brands' platform X post engagements across markets of different cultural orientation. Beyond assessing the distinctions in brand post elements, the role of emotional content in brand messages were also analyzed across English- and Turkish-speaking markets.

The fast fashion industry, known for its rapid production cycles and cost-efficiency, faces mounting pressure to align with global sustainability goals. This research explores the transformative potential of Artificial Intelligence (AI) in the sector, proposing a comprehensive framework for its responsible adoption. The study introduces six interconnected pillars: Environmental Performance and Sustainability, Supply Chain Optimization, Design and Production Innovation, Consumer Engagement and Personalization, Ethical and Social Considerations, and Economic Implications. These pillars collectively address key challenges such as resource efficiency, transparency, ethical accountability, and financial barriers to AI implementation. The research adopts a conceptual design grounded in a multidisciplinary literature review, synthesizing insights from sustainability science, AI ethics, and business innovation. By offering actionable strategies tailored to the fast fashion value chain, the framework aims to balance technological advancement with ecological and social responsibility. This work provides a roadmap for industry stakeholders, policymakers, and researchers to navigate the complexities of AI integration, ensuring equitable access to innovative technologies while promoting environmental stewardship and economic growth.

Entrepreneurial ecosystems (EEs) represent interconnected networks of actors, institutions, and resources that drive innovation and business growth. With the rise of Generative Artificial Intelligence (GenAI), a transformative technology capable of creating new content autonomously, the dynamics within these ecosystems are undergoing significant change. This study explores how GenAI influences the structure and functioning of EEs by acting as both an enabler and a constraint.

As an enabler, GenAI fosters innovation by enhancing creativity, optimising decision-making, and democratising access to advanced technological resources. For small and medium enterprises (SMEs) and entrepreneurs, GenAI offers tools to streamline product development, create personalised marketing content, and reduce costs associated with creative and operational processes. Furthermore, GenAI strengthens ecosystem dynamics by facilitating collaboration, enabling knowledge sharing, and promoting inclusivity through accessible technological solutions.

However, the integration of GenAI also introduces challenges. Ethical concerns, such as data privacy, intellectual property, and algorithmic bias, pose risks to trust and equity within ecosystems. Additionally, GenAI's disruptive potential may lead to job displacement and societal resistance, particularly in creative and knowledge-intensive industries. Policymakers and practitioners must address these issues by fostering responsible AI adoption and developing regulatory frameworks that ensure transparency, accountability, and fairness.

The aim of this study is to conceptualise a framework that situates GenAI within the entrepreneurial ecosystem context, highlighting its economic, social, and institutional impacts. By integrating insights from entrepreneurial ecosystems (i.e. Stam, 2015), innovation studies, and AI ethics, this research contributes to a deeper understanding of how GenAI can support resilient and dynamic ecosystems while addressing the ethical and societal implications of its deployment. We examine how does GenAI influences the structure and functioning of EE? Through examining this question, we aim to illuminate not only the avenues through which GenAI can foster innovation and scalability within entrepreneurship but also the ethical considerations critical to safeguarding the integrity and inclusivity of these ecosystems.

Our findings offer actionable insights for entrepreneurs, policymakers, and educators, emphasising the need for strategies that harness the potential of GenAI to foster innovation and inclusivity while mitigating its risks.  This study contributes to UNSDG Goal 8, which promotes entrepreneurship, development-orientated policies, and the proliferation of small and medium enterprises (UNSDG 2015). With this study, we aim to lay the foundation for future empirical research and policy initiatives aimed at leveraging GenAI for sustainable entrepreneurial growth.

This paper aims to conduct an interdisciplinary systematic literature review of fake news research and to advance the socio-technical understanding of digital information practices and platforms in business and management studies. The paper applies a focused, systematic literature review method to analyze articles on fake news in business and management journals from 2010 to 2020. The paper analyzes the definition, theoretical frameworks, methods, and research gaps of fake news in the business and management domains. It also identifies some promising research opportunities for future scholars. The paper offers practical implications for various stakeholders who are affected by or involved in fake news dissemination, such as brands, consumers, and policymakers. It provides recommendations to cope with the challenges and risks of fake news. The paper discusses the social consequences and future threats of fake news, especially in relation to social networking and social media. It calls for more awareness and responsibility from online communities to prevent and combat fake news. The paper contributes to the literature on information management by showing the importance and consequences of fake news sharing for societies. It is among the frontier systematic reviews in the field that cover studies from different disciplines and focus on business and management studies.

As global cooperation to develop and launch CBDCs further unfolds, the revolutionary innovation presents an emerging research field. This paper aims to provide a framework of CBDC by stressing its differences from other available digital currencies and cash in terms of advantages and disadvantages. The CBDC outlook, in its current and future, is presented. Additionally, an exploration of the prevalent themes in a cross-sectional analysis of tweets posted between 17 and 25 March 2021 with the #CBDC hashtags are presented to complement the discussion on the emerging landscape for informing the policy – and decision-makers on the opportunities and challenges involved.

This study examines consumer evaluations of robotic service failures caused by human interference by integrating service context, robot appearance, and individual anthropomorphism tendencies into a unified model. Two between-subjects experiments were conducted. In Study 1 (N = 402), participants interacted with a healthcare or food-service bot that failed due to verbal interference. Healthcare service failure elicited significantly more negative attitudes and lower failure tolerance than food service failure, and failure tolerance fully mediated the relationship between context and attitudes. In Study 2 (N = 213), we employed a 2 × 2 design (healthcare vs. food services × human-like vs. machine-like robot) and measured perceived deservingness and trait anthropomorphism. Human-like robots were judged most harshly when failing in healthcare (vs. food) services, whereas machine-like robots received similar evaluations across contexts. Perceived deservingness of the robot mediated this interaction. Moreover, the moderated-mediation effect occurred only among individuals with low to medium anthropomorphism tendencies. By positioning failure tolerance and deservingness judgments as core mechanisms in human–robot interaction, our findings advance theoretical understanding of moral attributions in service failure. Practically, they highlight the importance of matching robot anthropomorphic cues to service criticality: less human-like designs in high-stakes environments, while more human-like appearances may be appropriate in lower-stakes settings.