Should firms differentiate quality to soften competition, or equalize it by sourcing? We study sourcing by inefficient firm 2 from efficient firm 1. We show firm 2 prefers sourcing, if it well improves quality. Otherwise no sourcing even for free. Firm 1 averts sourcing if it has large quality leadership under no-sourcing and low horizontal differentiation. While sourcing pools resource to firm 1, it may yield lower quality than no-sourcing for consumers if firm 1 has small efficiency advantage.

The growing complexity of consulting, new product development, and information technology projects has led firms to increasingly adopt the strategy of collaborative value cocreation with their vendors. Research in this field overlooks value cocreation that often involves a client firm engaging with more than one vendor. We bridge this gap by studying a cocreation environment involving a client, a primary vendor, and a potential secondary vendor.

Firms rely on suppliers for innovation, often through procurement or innovation contests. Supplier ownership and control impact contest outcomes. We analyze the effects on buyer's profits and product innovation, identifying when they align or diverge. Our findings inform optimal supplier base structure and explain recent industry developments. Highly profitable structures may hinder innovation, prompting firms to prioritize long-term innovativeness over short-term profits.

Loot boxes are a primary source of revenue in video game industry. Loot boxes randomly drop items of differing value. To design a loot box, sellers choose the purchase price and drop rates. We show that, in general, the loot box design problem is NP-hard. By restricting the form of player utilities, we can solve the problem exactly in polynomial time when the number of items is fixed. Under different restrictions, we solve the problem approximately in polynomial time with fixed precision.

The degree of modularity embodied by a system overall architecture has clearly received quite some attention in the product/service literature but there has been much less theory established to specifically guide the incentive design for the development of a modular system within an organization. We seek to understand how the product architecture and the sources of uncertainty that affect the value interdependences of such a system, influence the optimal design of individual and team incentives.

In innovation contests, organizers seek solutions from solvers individually or as teams. High-novelty, nondecomposable problems benefit organizers with team submissions despite lower solver efforts. For low-novelty, nondecomposable problems, teams may not benefit organizers. Decomposable problems have specific conditions for organizer benefits. Contests favor team collaboration over in-house innovation. Solvers benefit from teams when novelty is moderate.

We analyze food purchasing patterns among low-income individuals in India using scanner data. Heavy consumption of packaged junk food is observed. A subsidy program is implemented, resulting in decreased snack purchases and increased purchases of complementary foods. Working parents show the strongest effects. No negative impact on nutrient purchases is found. Customized subsidy programs show a tradeoff between nutrient richness and customer appeal.

Interference poses challenges in panel experiments. Aggregating units into clusters is common, but optimal aggregation level is unclear. We propose a randomized design for grid-based units. Our design features randomized spatial clustering and balanced temporal randomization. Theoretical performance, inferential techniques, and simulations validate its superiority.

Challenge: Estimating long-term treatment effects in early-stage experiments is costly. Methodology: We propose a surrogate model using short-term data and historical observations. Results: Verified on WeChat, our method effectively estimates long-term treatment effects. Implications: Our approach reduces experiment duration and provides efficient empirical estimation of long-term effects.

Problem: Content platforms lack effective promotion policies utilizing the diffusion effect. Methodology: We propose a diffusion model, formulate the optimization problem, and introduce D-OLS estimators. Results: We prove submodularity and achieve a 1-1/e-approximation solution. D-OLS estimators are consistent and efficient. Our model improves adoption by 22.48% compared to existing policies. Implications: Our diffusion model enhances content promotion for online platforms.

Organizational support improves worker retention. In K-12 education, teacher crowdfunding platforms bridge resource gaps. We analyze teachers' actions on DonorsChoose and employment data. Crowdfunding reduces attrition rates by 1.7 pp, benefiting projects that personalize classrooms and teaching pedagogy. Identity-relevant resources decrease school and system exit by 1.8-2.4 pp. Findings highlight the role of accessible resources in enhancing worker retention.

AVs revolutionize transportation, but cost barriers persist. Open platforms with human drivers aid deployment. Incentive alignment in the supply chain is vital. We analyze the game involving platforms, AV suppliers, and contractors. Underutilization risk affects profit. Contracting solutions align the chain, ensuring half of optimal profit. Misalignment hampers AV adoption. Contracts mitigate efficiency loss.

Algorithms control pricing and match customers and workers in the gig economy. However, algorithms face several critiques: they lack transparency, can be biased, and can be inefficient. We empirically analyze these issues and show that algorithms lose efficiency from two sources: competition between platforms and misaligned worker incentives. We model workers' strategic responses to variation in pricing and estimate counterfactuals on the effects of minimum wage and transparent pricing policies.

Platforms are able to gather large quantities of data, which can result in high precision predictions regarding consumers purchasing patterns. A fundamental question is whether a platform has the incentives and ability to share such non-verifiable information with its sellers. We demonstrate that cheap-talk information can be exchanged when the platform shares with its sellers region-forecast. In this equilibrium, the platform shares only a region that contains its private information.

Firms rely on expert teams for decision making but face privacy concerns. We propose a mechanism to protect experts' privacy and analyze incentives. The firm garbles experts' reports to address privacy concerns, encouraging truthful reporting. Larger teams may perform worse, and more capable experts may be detrimental to team performance under privacy-conscious conditions.

Tele-driving lets drivers operate vehicles remotely, offering a viable alternative to fully automated ones. It reduces spatial mismatch in ride-hailing, enabling any driver for any customer. We quantify gains by comparing traditional systems to tele-driving. Findings: 1) For impatient customers, optimized driver capacity enhances service or reduces drivers; 2) For patient customers, tele-driving stabilizes systems or cuts drivers with similar service quality.

Rent-to-own (RTO) firms rent products in exchange for a fee and offer the already-rented products for purchase at buyout prices to their renters. Prediction of demand requires a decision model that captures the renters' decision-making process and their ownership and rental utilities. We develop a modular framework that separates utility estimation from identifying the renter's decision process. We build renter decision models, reflecting different degrees of sophistication and alertness.

Digital goods firms routinely utilize renting models for product differentiation: one can try a free or cheap version first, then subscribe to unlock additional functionality. Recent technological advances enable physical goods firms to create products with identical hardware that are digitally controlled to allow for similar differentiation. We present a stylized model to explore when physical goods firms should adopt such differentiation instead of the traditional high- and low-end products.

Consider a platform facilitating matches in the presence of supply congestion. A key attribute of supply is how competitive it will be for demand to obtain the supply after the match. Should the platform reveal current competition levels? To answer this, we partnered with a marketplace and propose a structural model in which workers account for future competition. We conduct counterfactual analysis to study the impact of signaling competition on workers' lead purchasing decisions and revenue.

To address income inequality in "Superstar Markets", we propose income pools - a contract where individuals agree to share a portion of future earnings if they become successful. We develop the first math model and prove that no finite-sized stable pool exists. In response, we consider bounded stable pools and epsilon-stable pools, proving their existence and Pareto properties. Our case study on professional baseball shows a 20%-30% welfare increase, most acutely benefiting the weakest agents.

The gig economy relies on task outsourcing, but gig workers face challenges in finding locations and products. We conduct field experiments using AI-enabled guidance to help shoppers. Technology reduces refunds and benefits less experienced shoppers. However, complex routing algorithms increase consultation time and pickup times. AI improves efficiency and increases revenues, but technology adoption has limits and overuse can reduce productivity.

Motivated by collaboration with a clinic, we study open-shop service networks with two service level measures: macro-level average overall wait time and micro-level probabilities of excessive waits for individual services. In a stylized two-station open-shop network, we analytically show that an advanced customer priority and the buffer strategy can improve macro- and micro-level performance. We provide means to improve customers' experience in open shop service networks not applicable before.

Evidence shows national institutions driving innovation through openness. We focus on 'social globalization' and design innovation. Using the KOF Globalization Index, we find social globalization predicts design innovation. Robust analyses and U.S. design patents support our findings. Personal contact plays a key role. Social globalization fosters design innovation.

Problem: Despite advances, chatbot adoption faces hurdles. This paper explores customer choice between chatbots and live agents. Methodology: Experiments vary chatbot performance and features. Users respond positively to improvements but underutilize chatbots due to algorithm and gatekeeper aversion. Remedies: Highlight time savings for algorithm aversion. Managerial implications: Nudges and queue priority rules reduce costs by up to 22% in congested systems

Facing emergent business challenges, entrepreneurs often seek guidance from experienced advisors. When there are multiple alternatives that could potentially solve the entrepreneur’s problem, advisors can lead the entrepreneur’s exploration by choosing which alternative(s) to suggest and in what sequence. We develop a dynamic game-theoretic model that captures the sequential interaction between an advisor and an entrepreneur.

Patients self-triage for acute care but lack medical knowledge, leading to inaccurate decisions. Virtual triage tools aim to improve self-triage. We develop a queueing game model to assess virtual triage's operational efficacy. Excessive emergency primary care recommendations reduce ED GP visits. Informative virtual triage can worsen system performance. Policy actions should consider decentralized behavior, incentive alignment, and accuracy decisions based on ROC curve.

Problem: Crowdfunding with insiders and outsiders faces reciprocity and information asymmetry. Methodology/Results: High reciprocity hampers information transmission, benefiting outsiders. Information asymmetry lets outsiders gain a larger share. Increased reciprocity reduces investor payoff. Managerial Implications: Limiting investors or investment improves information transmission. Leverage social networks for better crowdfunding.