This month, we feature research from INSEAD faculty and their collaborators on the neuroscience behind the pain of paying; how teams with members who contribute unequally approach rewards; and how the right framework can unlock better strategic thinking. In addition, recently published case studies explore two of today’s most pressing business topics: the infrastructure powering the AI boom and the swift rise of China’s robotics sector.  

Does spending money activate pain circuits in the brain? 

The “pain of paying” has shaped behavioural economics for decades, but it’s at odds with standard economic models, which assume that we evaluate prices purely in terms of opportunity cost. This theoretical tension has significant implications: If spending money causes affective pain, then consumer choice is guided not just by budget constraints but also hedonic costs that depend on the person, context and even the way payment is made. 

Research by Hilke Plassmann and her co-authors offers converging evidence from two studies showing that payment decisions activate affective pain-processing circuits. This is the first causal evidence that the pain of paying is a genuine pain experience – one that actively shapes how we value things economically. As payment systems continue evolving to reduce friction and salience (e.g. credit cards, contactless methods and single-click checkouts), understanding this affective dimension is critical for predicting and improving financial decision-making. 

Read the full paper 

Why asymmetric teams adopt equal reward sharing 

Teams are ubiquitous in modern workplaces, both within firms (e.g. committees, working groups, partnerships) and across organisations (e.g. joint ventures, alliances, franchises, co-productive service relationships). Perhaps counterintuitively, equal output sharing is surprisingly common, even in teams where members contribute to different extents. But why would a team with members who are unequal in productivity adopt this practice? 

In their working paper, Guillaume Roels, Ilia Tsetlin and their collaborators identify the conditions under which sharing rewards equally is optimal despite heterogeneous costs and productivity. When output can be separated into distinct group contributions, equal reward sharing within each group is optimal, provided certain conditions hold at the group level. Outside of that, it typically isn’t. The findings align with what we see in practice: Sharing rewards equally is more prevalent in partnership settings and among small teams, but less so in large teams that may involve non-separable production technologies. 

Read the working paper 

How decision makers can discover alternative strategies  

Generating strategic alternatives is a critical but challenging part of strategic decision-making. In this working paper, Hyunjin Kim and Nety Wu argue that frameworks can help decision makers discover strategic alternatives by supporting two cognitive functions: seeing (making the relevant choice dimensions visible) and combining (organising them into mutually exclusive alternatives). 

Across four randomised experiments involving 1,033 MBA students and executives, as well as 1,000 managers, the researchers tested how frameworks shape the ways decision makers generate and select alternatives. Their findings? Frameworks broaden the range of strategic options people consider and improve how these alternatives are structured. However, these benefits come at a cost: Frameworks also narrow the variation in options across decision makers, and their benefits are diminished when attention is split across multiple frameworks at the same time. 

Read the working paper 

Can AI buildouts be executed responsibly? 

In 2018, Crusoe was founded as a climate startup, pioneering technology to convert natural gas waste from oil well sites into clean energy for high-performance computing – first for Bitcoin and later for AI. But fast forward to 2026 and the company looks very different. Today, Crusoe is one of the world’s leading developers of AI data centre infrastructure, actively scaling up new natural gas power generation to feed its rapidly expanding data centre campuses. 

This case study by Pierre Hillion and his co-author unpacks the sheer scale of physical resources, capital and infrastructure required to create the facilities powering the AI boom. It discusses the infrastructure race this technology has triggered and the constraints AI infrastructure developers face today. Through Crusoe’s story, the authors explore the systemic costs of the AI data centre buildout and raise the question: Can this be done responsibly? 

Read the case study 

Shaping the future of embodied intelligence 

China’s robotics ecosystem is experiencing monumental growth – and shows no signs of slowing down anytime soon. In this case study, Guoli Chen and his co-authors examine the rapid evolution of the embodied intelligence robotics sector through the lens of Unitree Robotics, a leading Chinese company specialising in high-performance, affordable quadruped and humanoid robots. It shows how Unitree has leveraged vertical integration, cost leadership and agile innovation to make advanced robotics dramatically more accessible.  

They dissect Unitree’s business model canvas, strategic positioning, competitive advantage and value chain, and compare the company with rivals such as Boston Dynamics, Agility Robotics and Tesla. The case study reveals how the embodied intelligence industry – which integrates advanced robotics, as well as AI-driven perception and control systems – is tackling both technological and commercial challenges.  

Read the case study