Marketing

Enpara.com: Digital Bank at a Crossroad

By: Sunil Gupta

September 2026 |
Teaching Note |
Faculty Research

Teaching Note for HBS Case No. 518-030.

Quantum Computing: Faster than You Think

By: E. Ofek and Orna Dan

August 2026 |
Technical Note |
Faculty Research

Once considered a distant theoretical concept, quantum computing has accelerated dramatically, fueled by billions of dollars in venture capital and government funding, alongside major breakthroughs by tech giants and pure-play startups. Introducing the field for a business audience, this note provides an accessible primer on fundamental quantum mechanics—such as superposition, entanglement, and interference—and explains the differences between competing hardware architectures and gate-based versus annealing systems. It explores how quantum computing is expected to complement, rather than replace, classical computing systems, and maps the emerging ecosystem of technology giants, pure-play companies, software providers, cloud platforms, and government-backed infrastructure. The note also details potential breakthrough applications across industries, including life sciences (accelerated drug discovery), financial services (portfolio optimization), and aerospace (materials science). Additionally, it examines the synergistic relationship between quantum computing and artificial intelligence (AI), the rise of Quantum-as-a-Service (QaaS) business models, and the geopolitical race for quantum supremacy highlighted by massive U.S. federal incentives. Finally, it outlines the lingering hurdles of achieving fault tolerance and the profound cybersecurity perils, such as the threat to current global encryption standards. By juxtaposing rapid technological progress and expanding public-market support with modest revenues and unresolved engineering challenges, the note equips readers to assess where quantum computing may create value, how organizations can prepare, and why commercialization remains uncertain.

Starbucks Korea's Tank Day: When the Machines Forgot

By: Das Narayandas and Kerry Herman

August 2026 |
Case |
Faculty Research

Pop Mart: Beyond the Labubu Craze

By: Elie Ofek, Brian Mao Fu and Mengjie Cheng

August 2026 |
Case |
Faculty Research

Pop Mart reported that revenues nearly tripled in 2025, yet its share price fell 22% the same day. At the center of both stories was Labubu—a scruffy, sharp-toothed designer toy character that had become a global cultural phenomenon, appearing on the handbags of international celebrities and selling out in stores from Beijing to New York. But as investors questioned whether the company could sustain its remarkable growth, one issue overshadowed all others: had Pop Mart built a truly repeatable system for creating globally resonant intellectual property, or had Labubu been a fortunate convergence of timing, design, and cultural moment? As founder and CEO Grant Wang looked ahead, he faced a series of interconnected decisions. How should the company allocate resources across existing and emerging IPs, international expansion, category extensions, films, theme parks, and other new ventures? Moreover, could Pop Mart broaden its audience while staying relevant to its core consumers, and scale without sacrificing the artistic authenticity and operational discipline that had defined its success?

Keywords: Toy Industry; Business Model; Trends; Global Strategy; Intellectual Property; Growth and Development Strategy; Resource Allocation; Product Development; Organizational Change and Adaptation; Success; Creativity; Culture; Business Strategy; Competitive Advantage; Expansion; Entertainment and Recreation Industry; China

Recursive Mentalizing and Public Salience in the Perception of Common Knowledge

By: Julian De Freitas, Y. Huang and Steven Pinker

August 18, 2026 |
Article |
Proceedings of the National Academy of Sciences

Common knowledge—what everyone knows that everyone knows, ad infinitum—is theoretically required for coordination. But a finite mind cannot represent infinitely embedded propositions, and even a few are cognitively taxing. We propose that people perceive common knowledge by combining a capacity-limited ability for recursive mentalizing with an intuitive sense of public salience: when an event is jointly and openly witnessed, they infer that recursively embedded beliefs are licensed. We probed participants’ attributions of embedded beliefs to characters in fictitious vignettes. Study 1 presented narratives in which the information available to characters was either asymmetrical, reciprocal, or public. Participants indicated their confidence in the characters’ beliefs with 0, 2, 4, 6, and 18 embeddings (the latter judged indirectly). Ratings showed (i) a decline with number of embeddings, reflecting cognitive load, (ii) modest overattribution of embedded beliefs in the non-public conditions, (iii) far higher attribution of embedded beliefs in the public conditions, and (iv) high indirect judgments that arbitrarily deep beliefs were justified. Study 2 replicated these findings with animated videos in which the characters’ information was private, reciprocal, doubly reciprocal, or public. Together, the studies indicate that people attribute common knowledge to observers of a publicly salient event, while being susceptible to capacity-driven recursion collapse and heuristic extrapolation (false embedded beliefs). This can explain how humans achieve coordination from sparse cues, yet sometimes miscoordinate when publicness is absent or embedding grows complex.

Keywords: Knowledge; Cognition and Thinking; Perception

Read Now

AthenaHQ: Building Brands for AI Search

By: Julian De Freitas and George Gonzalez

August 2026 |
Case |
Faculty Research

Former Google Search product manager Andrew Yan is the co-founder and CEO of AthenaHQ, a Y Combinator–backed startup that helps brands monitor, protect, and optimize their visibility across conversational AI engines like ChatGPT, Claude, and Gemini. Founded in 2025, AthenaHQ built a platform that enables companies to track their share of voice, correct factual errors in AI responses, and manage their reputation across generative answer engines. The startup serves over 100 enterprise clients, including major consumer brands, B2B software companies, and marketing agencies. Facing a call with a global automaker whose newest vehicle has quietly vanished from chatbot recommendations, Yan evaluates the platform's expansion as he confronts core industry dilemmas: how AI disintermediates traditional marketing, who should own generative engine optimization inside an organization, and how to prove value on an unattributable channel.

Keywords: Entrepreneurship; Business Startups; AI and Machine Learning; Technology Adoption; Disruptive Innovation; Brands and Branding; Expansion; Technology Industry; California

The Innovation Problems AI Can’t Solve

By: Julian De Freitas, Ayelet Israeli, Gideon Nave, Artem Timoshenko and Olivier Toubia

August 14, 2026 |
Article |
Harvard Business Review (website)

Generative AI can accelerate innovation, but the article argues that its default use often reinforces the human bottlenecks it is meant to solve. In ideation, models steer teams toward familiar ideas and make people more fixated on them. In screening, polished AI-generated pitches can be mistaken for better ideas, while AI recommendations may encode existing bias. In consumer research, simulated customers can speed testing but miss the irrational behaviors that shape real adoption. After launch, AI can summarize vast feedback, yet still help teams justify prior beliefs. The authors’ central advice is diagnostic: before applying AI, leaders should ask whether the bottleneck is informational, judgment-based, or incentive-driven, and preserve direct contact with customers where it matters most for grounding.

Keywords: AI and Machine Learning; Innovation Leadership