Tesla's Diner Experiment and the Economics of Firm Boundaries
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In July 2025, Tesla opened a retro-futuristic diner in Hollywood, bringing to life an idea first floated by Elon Musk in a 2018 tweet. The facility combines 80 electric vehicle charging stalls with a two-story restaurant, outdoor movie screens, and waitstaff on roller skates. On the surface, this seems like a clever way to make charging more enjoyable. But the Tesla Diner raises a deeper question about corporate strategy. Why would an electric vehicle manufacturer run a restaurant? And what does this expansion into seemingly unrelated businesses tell us about the future of corporate organization, especially in an era of artificial intelligence?
The answer lies in a framework developed decades ago by economist Ronald Coase, who asked a question that sounds almost too simple: Why do firms exist at all?
Why it matters: Understanding the limits of what companies can efficiently manage helps explain whether Tesla's diversification makes economic sense, and whether AI might reshape those limits entirely.
The Coasean Foundation
Ronald Coase first posed his fundamental question as a 21-year-old student in 1932, and published his answer in 1937 as "The Nature of the Firm." His insight was that firms exist because using the market has costs. As Coase explained in his 1991 Nobel Prize lecture, he realized "there were costs of using the pricing mechanism. What the prices are has to be discovered. There are negotiations to be undertaken, contracts have to be drawn up, inspections have to be made, arrangements have to be made to settle disputes, and so on". These became known as transaction costs.
Firms solve this problem by replacing market transactions with administrative coordination. Rather than negotiating separate contracts for every task, companies bring activities in-house and coordinate them through managerial direction. As Coase put it, firms are "little planned societies" that exist because they can perform coordination "at a lower cost than would be incurred if it were achieved by means of market transactions".
This explains vertical integration. When Tesla builds its own batteries rather than buying them from suppliers, it avoids the transaction costs of negotiating prices, ensuring quality, and managing supplier relationships. By controlling multiple stages of its supply chain, from raw material sourcing to manufacturing, Tesla reduces costs and maintains quality control.
The Natural Limits of the Firm
But if avoiding transaction costs is valuable, why doesn't every company do everything? Coase identified natural limits to firm size. As he wrote in "The Nature of the Firm," there are "decreasing returns to the entrepreneur function," meaning "the costs of organizing additional transactions within the firm may rise". The entrepreneur becomes overwhelmed and "fails to place the factors of production in the uses where their value is greatest". In other words, managers make more mistakes as organizations grow larger and more complex.
This creates a boundary. A firm expands until "the costs of organizing an extra transaction within the firm become equal to the costs of carrying out the same transaction by means of an exchange on the open market". At that point, it makes more sense to buy from outside suppliers than to bring another activity in-house.
These limits explain why companies like Ford and Disney, despite their enormous resources, don't simply do everything. Ford famously pursued extreme vertical integration in the early 20th century, owning iron ore mines, steel mills, rubber plantations, and forests. Henry Ford even established Fordlândia, a rubber plantation in Brazil, though it ultimately failed. While this strategy gave Ford control over its supply chain, the complexity eventually became unmanageable. Modern Ford has moved away from this approach, outsourcing to specialized suppliers who can achieve economies of scale by serving multiple automakers.
Disney operates across multiple business segments, including entertainment, sports, parks, and consumer products. But even Disney draws boundaries. The company incurred over $78 billion in costs and expenses in fiscal 2022, with significant portions going to programming, production, marketing, and administrative functions. Managing this complexity requires enormous coordination overhead. Disney has repeatedly restructured its divisions to manage these costs, recognizing that expanding into every adjacent business would strain its organizational capacity.
Why it matters: Even the largest corporations face fundamental limits on how much complexity they can manage internally.
Transaction Costs and Organizational Overhead
The costs Coase identified fall into several categories. Search and information costs involve finding the right suppliers and determining fair prices. Bargaining and contracting costs include negotiating terms and drawing up agreements. Monitoring and enforcement costs arise from ensuring contract compliance and resolving disputes.
But internal organization has its own costs. As firms grow, they face increasing overhead from additional management layers, bureaucratic processes, and coordination failures. A BCG study found that 80% of senior leaders cited lack of P&L responsibility as a driver of cost growth, while 74% observed that leadership layers and support functions become more inflated and bureaucratic over time. These organizations tend to create new committees, processes, and managers to address emerging issues, which generates more costs and complexity.
The challenge intensifies with organizational scale. Coordination consumes an estimated 50-60% of employees' time in large corporations. This includes email chains, meetings, status updates, and alignment activities that don't directly create value. The context window problem, as some researchers call it, reflects humans' limited capacity to process information and understand complex interdependencies. Organizations compensate by breaking down complexity into individual goals and departmental objectives, but this fragmentation creates misalignment and inefficiency.
Why it matters: Internal coordination costs can exceed the transaction costs of using the market, explaining why companies often choose to outsource rather than expand.
Tesla's Expansive Boundaries
Against this backdrop, Tesla's business model appears unusual. The company operates in electric vehicles, battery production, solar panels, energy storage systems, insurance, and now restaurants. Tesla Energy offers residential and commercial products including Powerwall batteries, solar roofs, and utility-scale Megapacks. The company has developed sophisticated software for energy optimization, including Autobidder for wholesale market bidding and Opticaster for distributed energy resource management. Tesla even sells Full Self-Driving software as a subscription service, creating recurring revenue from vehicle owners.
This diversification seems to violate Coasean logic. Running a diner requires entirely different capabilities than manufacturing electric vehicles. The skills needed to manage food service, kitchen operations, and hospitality have little overlap with automotive engineering or battery chemistry. According to traditional transaction cost economics, Tesla should face decreasing returns to its entrepreneurial function as it stretches into these disparate businesses.
Yet Tesla has pursued vertical integration more aggressively than most automakers. The company controls approximately 80% of its supply chain, including battery cell production, software development, and vehicle assembly. Tesla's Gigafactories produce batteries in-house, reducing costs and ensuring stable supply. This approach contrasts sharply with traditional automakers who source components from suppliers like Bosch, Continental, and Denso.
Why it matters: Tesla's strategy challenges conventional wisdom about the natural boundaries of the firm.
What Would Coase Say?
Applying Coase's framework to Tesla reveals several tensions. The diner concept might reduce transaction costs for charging customers. Rather than coordinating separate businesses for charging, food, and entertainment, Tesla internalizes these functions at a single location. This could create synergies, as the menu can appear automatically on vehicle touchscreens when drivers park. Food delivery can be coordinated with charging times, potentially reducing idle fees and improving the customer experience.
However, the coordination costs appear substantial. Managing restaurant operations requires hiring and training staff, developing menus, ensuring food quality, maintaining health and safety standards, and coordinating supply chains for ingredients. These activities demand expertise Tesla has never developed. The restaurant industry operates on thin margins and faces intense competition. Early reports suggest the Tesla Diner has reduced its menu and limited 24-hour service to charging customers only, indicating possible operational challenges.
Coase would likely question whether Tesla can efficiently manage such diverse operations. As he noted, firms face "increasing overhead costs and increasing propensity for an overwhelmed manager to make mistakes in resource allocation". The entrepreneur's capacity to coordinate becomes strained across dissimilar transactions. A company optimized for manufacturing high-tech vehicles may lack the organizational design needed to run successful restaurants.
Why it matters: The transaction cost framework suggests Tesla may be overextending its organizational capacity by entering the restaurant business.
The AI Wild Card
The crucial question is whether artificial intelligence might change this calculus. AI has the potential to dramatically reduce several categories of transaction costs. Search and information costs fall as AI systems can rapidly process vast amounts of data to identify optimal suppliers and evaluate contracts. Bargaining and contracting costs decline as AI can draft comprehensive agreements and simulate negotiation outcomes. Monitoring costs decrease through real-time data analysis and automated compliance checking.
Research suggests AI reduces market transaction costs more than it reduces internal coordination costs. As one analysis notes, "AI can also assist in bargaining and contracting by writing very good, watertight totally 'complete' contracts, evaluating risks, and even simulating negotiation outcomes". This would favor vertical disintegration, as companies could more easily coordinate with external partners through AI-mediated contracts.
However, AI could also reduce internal coordination costs. Organizations adopting AI report up to 25% reductions in middle management layers. AI-driven coordination systems can process vastly more context than individual humans and maintain more complex priority structures. Rather than breaking down organizational goals into simplified departmental objectives, AI agents could collaborate toward unified objectives while managing intricate interdependencies.
Tesla already uses AI extensively in its operations, from autonomous driving systems to energy optimization software. The company's energy management platform employs machine learning algorithms to forecast demand, optimize battery dispatch, and participate in wholesale markets. This suggests Tesla may be betting that AI will allow it to manage greater organizational complexity than traditional firms could handle.
Yet some researchers warn that AI-driven coordination might create new dependencies. As one study notes, "while AI agents seemingly lower the cost of automating tasks within the firm, they might inadvertently increase the organization's dependence on the external platform". Organizations could find themselves relying on AI platforms that become new gatekeepers, potentially increasing external transaction costs even as internal costs fall.
Why it matters: Whether AI reduces transaction costs more than coordination costs will determine if large firms can successfully manage more diverse businesses.
The Verdict Remains Uncertain
The Tesla Diner represents an experiment in pushing firm boundaries beyond traditional limits. Coase's framework suggests this expansion faces significant challenges. The coordination costs of managing restaurants alongside vehicle manufacturing may exceed the transaction costs of simply allowing independent restaurants to operate near charging stations. The dissimilarity between these businesses and the spatial distribution of operations both increase the costs of internal organization.
Yet if AI substantially reduces coordination costs, Tesla's bet may prove prescient. Companies that successfully deploy AI for internal coordination could manage far more diverse operations than 20th-century firms. The question is whether AI reduces these costs enough to overcome the inherent diseconomies of managing unrelated businesses.
Ford and Disney illustrate the traditional answer. Ford abandoned extreme vertical integration when the coordination costs became overwhelming. Disney manages multiple entertainment-related businesses but faces constant pressure to control overhead and streamline operations. Both companies recognize that internal coordination has limits, and those limits determine what activities belong inside the firm versus in the market.
Tesla appears to be testing whether those limits have shifted. The diner may succeed as a destination that enhances the charging experience and creates brand loyalty. Or it may become, as some critics suggest, "a meme emblem of Musk failures: Overpromise, delay, and ultimately deliver a product that is pricier yet inferior". The economic logic suggests caution, but technological change could rewrite that logic entirely.
Coase understood that firm boundaries are not fixed but result from the ongoing balance between transaction costs and coordination costs. As he noted, "competition" determines the optimal mix of markets and hierarchies. If AI genuinely transforms coordination, we may see firms like Tesla successfully operating businesses that previously seemed too disparate to manage. But if coordination costs remain stubbornly high despite technological advances, Tesla may eventually discover the same limits that constrained Ford and Disney. The diner, in this light, becomes not just a restaurant but a test of whether AI has truly changed the fundamental economics of the firm.
