All Publications
The clothing sector is one of the biggest polluters in the world. Aware of the growing number of environmentally conscious consumers, several fashion brands aim to become more sustainable. Artificial intelligence (AI), defined as “a system’s ability to interpret external data correctly, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation,” may be applied to fast fashion as a means of greening the apparel industry. This chapter explains how AI can enhance the sustainable production and consumption of clothing products. First, it provides an overview of AI and analyzes and decodes its potential and associated risks and challenges. Numerous examples describe AI’s application to the retail and clothing industries, such as supply chain optimization and fostering eco-responsible consumption patterns. Second, this chapter illustrates how AI can help the fashion industry significantly reduce its carbon footprint. Third, three case studies of fashion companies that have started implementing artificial intelligence into their operations to improve sustainability are put forward, including two fast-fashion companies (H&M and Zara) and one luxury fashion retail platform (Farfetch). Finally, the chapter concludes with suggestions for the future of fast fashion.
With the digital transformation of higher education, academia is confronted with turmoil and profound change, not to mention potential disruption. Specifically, advances in artificial intelligence (such as ChatGPT), big data, virtual and augmented reality technology, as well as the future Metaverse, will strongly impact the future world of universities. The Covid-19 pandemic undoubtedly accelerated and accentuated the academic community's digitalisation and brought new entrants from the edtech (e.g. Spanish startup ThePower Business School) and big tech (e.g. Google's Career Certificates) sector to the fore. Higher education institutions will have to face an increasingly competitive landscape and need to think of ways to protect themselves from said competition and disruptive tendencies. This chapter will mainly focus on business schools and the case of management education.
Since their beginnings, virtual worlds have experienced two major media hypes in their short lifetime?the first in 2003 after the launch of Second Life and the second in 2021, with Mark Zuckerberg announcing his strategy for the Metaverse. Most academic research on virtual worlds emerged between these two peaks of interest. This article delves into the enduring relevance of such research, contrasting the two hype cycles. It analyzes the reasons behind current caution expressed by companies and offers insights into the future trajectory of the Metaverse and which crucial developments are needed for sustained traction in virtual worlds.
It all began when the world’s first business school, the European School of Commerce Paris (ESCP), was established in 1819. Criticism notwithstanding, business schools have since continued their path in higher education without facing existential metamorphoses. Covid-19, however, has accelerated business schools’ digital transformation, calling into question the concept of business school itself. Business schools are in a new competitive landscape and profound structural changes seem inevitable. This concise text offers insights into how business schools should rethink their approach to management education, differentiate themselves from new players in the higher education market, and find innovative ways of doing things. The book is a survival toolkit for leadership teams across the world. It examines the rationale of business school and how it has evolved. The purpose of research is explained, and the teaching of management is explored. Kaplan analyzes the current business model in the digital environment. He looks at the business of accreditations and rankings and branding and community-building as strategies to address competition. The book concludes by looking at change leadership at business schools. It will interest both leaders of established academic institutions and alternative educational providers from edtech and big tech planning to enter the management education market.
"Artificial intelligence is shaking up economies around the world as well as society at large and is predicted to be either the best or worst thing to happen to humanity. This book looks at what exactly artificial intelligence is, how it can be classified, how it differentiates from other concepts such as machine learning, big data, blockchain, or the Internet-of-Things, and how it has evolved and might evolve over time. Providing a clear and unbiased picture of artificial intelligence, the book provides critical analyses of the advantages and disadvantages, opportunities and threats of AI progress for business and civilization. Solutions and possible directions of how humanity might deal with rapid development and evolutions will be given and discussed, and consider regulation, employment, ethics, education and international cooperation. Unlike existing literature, this book provides a comprehensive overview of AI based on detailed analysis and insight. Finally, several real-life examples from various sectors and industries, including for profit organizations, higher education, and government, will substantiate and illustrate the presented concepts, classifications, and discussions. This book is of interest to researchers, educators, students, and practitioners alike who desire to understand AI in its broad lines and discover the latest research and studies within the field"
This book analyses higher education's digital transformation and potential disruption from a holistic point of view, providing a balanced and critical account from a variety of interdisciplinary viewpoints. It looks at case studies on educational and emerging technology, their impact, the potential risk of digitalization disrupting higher education, and also offers a glimpse into what the future of digitalization will likely bring. Researchers and practitioners from countries including New Zealand, Russia, Eswatini, India, and the USA, bring together their knowledge and understanding of this rapidly evolving field. The contributors analyse academia's digitalization along the broad topics of the sector's general digital (r)evolution. The book looks at changes in instructional formats from the Massive Open Online Courses to Small Private Online Courses and artificial intelligence. This work also provides analysis on how skills, competences and social networks demanded by future jobs and job markets can be further integrated into higher education.
This case tells the story of Marie-Claire, a student at ESMOD, the World’s First Fashion School (est. 1841), who is currently interning at a recently founded, Berlin-based, fast-fashion retailer, primarily operating online, with only a few brick-and-mortar stores in Germany, Austria, and Poland. During this three-month internship, her main task is to look at how artificial intelligence (AI) could be applied to fast fashion, and specifically how AI could render the industry more environmentally sustainable. One of the tasks involves formulating a benchmark and comparison of three big fast-fashion players: H&M, Shein, and Zara. Moreover, Marie-Claire will analyze how AI might change the future of fashion. She will consider the opportunities extended by AI, and reflect upon potential challenges arising from its application to overcome and watch out for. Although this case addresses the combination of high tech with fashion, more precisely, the application of artificial intelligence to the fashion industry, its key insights and takeaways, apply to a much broader spectrum of sectors and industries. On a side note, the case also illustrates the differing contexts of AI advances between China, the US, and Europe.
So as not to face potential disruption, universities will need to actively engage in the sector’s evolution as opposed to passively observing its revolution. To stay competitive, they will need to adapt pedagogy and content to ongoing changes lest they risk their irrelevance. They are advised to create occasions for relationship and community building, fostering students’ affection for and attachment to their alma mater, and to avoid the university’s being abstract in students’ minds. Instead of the current standard of one-time, early-life degrees (intermittence), lifelong learning and persistence over alumni’s entire professional careers appear to be academia’s model for the future. Universities must assure higher applicability of taught material to job requirements, as employers are increasingly launching own corporate universities offering nano- and micro-degrees. Finally, affiliation with edtech start-ups and big tech companies might be necessary to ensure the funding needed to navigate academia’s new online reality and thus bypass isolation.
This case tells the story of Guillaume, a business school student, who is currently interning at the Louvre in Paris. One of his tasks involves him formulating a benchmark and comparison of three world-famous museums regarding their applications of artificial intelligence (AI): Beijing’s Palace Museum, NYC’s Metropolitan Museum of Art, and the aforementioned Louvre. Furthermore, Guillaume must analyze how AI might change the future of museums in particular and cultural enterprises in general. He will think about the opportunities with regards to AI as well as reflect upon potential challenges arising from the application of AI to overcome and watch out for. The three museums studied in this case represent China, the US, and Europe, and as such illustrate the various stages of AI use and progress in these regions of the world, with superpowers China and the US clearly in the lead, and Europe lagging behind in this technological (r)evolution. Although this case addresses the combination of high tech with cultural heritage, more precisely the use of AI in museums, its key insights and takeaways apply to a much broader spectrum of sectors and industries.
The COVID-19 pandemic resulted in a change in mind-sets in many university leadership teams and faculty members worldwide, previously somewhat vulnerable to the sector's digitalization. Academia proved capable of flexibility, going beyond their reputation of being change-averse, moving entire curricula online within days. Yet, to benefit from higher education's digitalization, propelled by the pandemic, future pedagogical innovation is vital so as not to make other sectors' errors of merely transferring the offline into the online world. Moreover, higher education will need to find responses to several (further) academic, budgetary, legal, and operational issues induced by the sector's digital transformation, potentially leading to its disruption. However, higher education also must evade false ideas such as believing that physical buildings will become redundant due to academia's digitalization: On the contrary, facilities will be more critical than ever.
