The Incentive To Participate In Open Source Projects: A Signaling Approach

This paper examines the incentives of programmers to contribute to open source software projects on a voluntary basis. In particular, the paper looks at this incentive changes as (i) performance becomes more visible to the relevant audience, (ii) effort has a stronger impact on performance, and (iii) performance becomes more informative about talent. In all three cases, it is shown that whether we start from a stable interior equilibrium or an unstable interior equilibrium

Adware, Shareware, and Consumer Privacy

Programmers can distribute new software to online users either for a fee as shareware or bundle it with advertising banners and distribute it for free as adware. In this paper we study the programmers' choice between these two modes of distribution in the context of a model that take explicit account of the strategic interaction between programmers who develop software, firms that advertise their products through ad banners, and consumers who buy software and consumer products. Adware allows advertisers to send targeted information to specific consumers and may therefore improve their purchasing decisions. At the same time, adware also raises privacy concerns. We study the effect of programmers' choice between shareware and adware on consumers' welfare through its effect on the beneficial information that consumers receive about consumers products on the one hand and their loss of privacy on the other hand. We also examine the implications of improvements in the technology of ad banners and the desirability of bans on the use of adware

The Incentive To Participate In Open Source Projects: A Signaling Approach

This paper examines the incentives of programmers to contribute to open source software projects on a voluntary basis. In particular, the paper looks at this incentive changes as (i) performance becomes more visible to the relevant audience, (ii) effort has a stronger impact on performance, and (iii) performance becomes more informative about talent. In all three cases, it is shown that whether we start from a stable interior equilibrium or an unstable interior equilibrium

Quantity Competition under Resale Price Maintenance when Most Favored Customers are Strategic

Legal studies usually treat a policy of a manufacturer or retailer as socially harmful if it reduces product output and increases the price. We consider a two-period model where the first-period price is fixed by resale price maintenance (RPM) and resellers endogenously decide to use another "collusion suspect," meet-the-competition clause with a most-favored-customer clause (MFC), to counteract strategic customer behavior. As a result of MFC, second-period (reduced) price increases, and resellers' inventories decrease. However, customer surplus may increase and aggregate welfare increases in the majority of market situations. MFC can not only decrease the losses in welfare and resellers' profits due to strategic customers but, under reseller competition, may even lead to higher levels of these values than with myopic customers, i.e., to gains from increased strategic behavior. MFC may create "MFC-traps" for resellers, where one of possible market outcomes yields a gain from increased strategic behavior while another results in a reseller profit less than the worst profit in any stable outcome without MFC. With growing competition, benefits or losses from MFC can be higher than losses from strategic customer behavior

Twilight: A Differentially Private Payment Channel Network

Payment channel networks (PCNs) provide a faster and cheaper alternative to transactions recorded on the blockchain. Clients can trustlessly establish payment channels with relays by locking coins and then send signed payments that shift coin balances over the network\u27s channels. Although payments are never published, anyone can track a client\u27s payment by monitoring changes in coin balances over the network\u27s channels. We present Twilight, the first PCN that provides a rigorous differential privacy guarantee to its users. Relays in Twilight run a noisy payment processing mechanism that hides the payments they carry. This mechanism increases the relay\u27s cost, so Twilight combats selfish relays that wish to avoid it using a trusted execution environment (TEE) that ensures they follow its protocol. The TEE does not store the channel\u27s state, which minimizes the trusted computing base. Crucially, Twilight ensures that even if a relay breaks the TEE\u27s security, it cannot break the integrity of the PCN. We analyze Twilight in terms of privacy and cost and study the trade-off between them. We implement Twilight using Intel\u27s SGX framework and evaluate its performance using relays deployed on two continents. We show that a route consisting of 4 relays handles 820 payments/sec

Gaining Benefits from Joint Forecasting and Replenishment Processes: The Case of Auto-Correlated Demand

In this paper we consider a cooperative, two-level supply chain consisting of a retailer and a supplier. As in many practical settings, the supply chain members progressively observe market signals that enable them to explain future demand. The demand itself evolves according to an auto-regressive time series. We examine three types of supply chain configurations. In the first setting, the retailer and the supplier coordinate their policy parameters in an attempt to minimize systemwide costs, but they do not share their observations of market signals. In the second setting, resembling many original vendor-managed inventory (VMI) programs, the supplier takes the full responsibility of managing the supply chain's inventory, but the retailer's observations of market signals are not transferred to him. In our third setting, reminiscent of collaborative forecasting and replenishment partnerships, inventory is managed centrally, and all demand related information is shared. We propose a set of stylized models to study the three settings and use them to provide managerial insights into the value of information sharing, VMI, and collaborative forecasting.Collaborative Forecasting, CPFR, Supply Chain Management, VMI

The Effect of Collaborative Forecasting on Supply Chain Performance

We consider a cooperative, two-stage supply chain consisting of two members: a retailer and a supplier. In our first model, called local forecasting, each member updates the forecasts of future demands periodically, and is able to integrate the adjusted forecasts into his replenishment process. Forecast adjustments made at both levels of the supply chain can be correlated. The supply chain has a decentralized information structure, so that day-to-day inventory and forecast information are known locally only. In our second model, named collaborative forecasting, the supply chain members jointly maintain and update a single forecasting process in the system. Hence, forecasting information becomes centralized. Finally, we consider as a benchmark the special case in which forecasts are not integrated into the replenishment processes at all. We propose a unified framework that allows us to study and compare the three types of settings. This study comes at a time when various types of collaborative forecasting partnerships are being experimented within industry, and when the drivers for success or failure of such initiatives are not yet fully understood. In addition to providing some managerial insights into questions that arise in this context, our set of models is tailored to serve as building blocks for future work in this emerging area of research.Collaborative Forecasting, CFAR, CPFR, Supply Chain Management

On the Benefits of Collaborative Forecasting Partnerships Between Retailers and Manufacturers

This paper studies the potential benefits of collaborative forecasting (CF) partnerships in a supply chain that consists of a manufacturer and a retailer. To reflect the reality in production environments, we propose a scorecard that captures inventory considerations, production smoothing, and adherence-to-plans. We present a prescriptive convex-cost production planning model for the manufacturer, and a replenishment model for the retailer. We use our integrative reference model to study the potential benefits of CF partnerships. Overall, we find that the benefits of CF depend on the following key characteristics of the supply chain: the relative explanatory power of the supply chain partners, the supply side agility, and the internal service rate. CF is expected to bring high benefits to the supply chain when the manufacturer has the largest relative explanatory power. But quite disappointingly, in these cases a CF partnership does not appear to be valuable to the manufacturer. When the retailer is the dominant observer of market signals, CF typically yields a "win-win" outcome. In order to effectively act upon the information exchanged via CF, the supply side needs to be sufficiently agile. The benefits reported in this paper should be considered as conservative. This is because CF partnerships often bring better information, improved decision support technologies, as well as process improvement to the trading partners. Consequently, the supply side agility can be improved. If this indeed happens, the compound benefits of CF can be dramatically higher than our conservative estimates. Finally, we provide a qualitative discussion of the possible role of internal service rates in supply chains, either as planning parameters to improve performance, or as a mechanism for sharing the benefits of CF between the trading partners.collaborative forecasting, supply chain management, optimal control, production planning, production smoothing, inventory-production