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Secondary markets in the information technology industry, where used or refurbished equipment is traded, have been growing steadily. For original equipment manufacturers (OEMs) in this industry, the importance of secondary markets has grown in parallel, not only as a source of revenue, but also because of their impact on these firms' competitive advantage and market strategy. Recent articles in the press have severely criticized some OEMs who are perceived to be actively trying to eliminate the secondary market for their products. Other OEMs have policies that enhance their secondary markets. The goal of this paper is to understand how an OEM's incentives and optimal strategies vis-à-vis the secondary market are shaped contingent on her relative competitive advantage, product characteristics, and consumer preferences. The critical trade-off that we examine is whether the indirect benefit from maintaining an active secondary market (the resale value effect) can outweigh the potentially negative effect of the sales of used products at the expense of new product sales (the cannibalization effect). To that end, we develop a durable good model where the OEM can directly affect the resale value of her product through a relicensing fee charged to the buyer of the refurbished equipment. We analyze the OEM's strategy in both the monopoly and the duopoly cases, characterize the optimal relicensing fee set by the OEM, and draw conclusions on the conditions that favor stimulating or deterring the secondary market. This paper was accepted by Candace A. Yano, operations and supply chain management.

This paper studies the interaction between default and liquidity for corporate bonds that are traded in an over-the-counter secondary market with search frictions. Bargaining with dealers determines a bond's endogenous liquidity, which depends on both the firm fundamental and the time-to-maturity of the bond. Corporate default decisions interact with the endogenous secondary market liquidity via the rollover channel. A default-liquidity loop arises: Assuming a relative illiquid secondary bond market in default, earlier endogenous default worsens a bond's secondary market liquidity, which amplifies equity holders' rollover losses, which in turn leads to earlier endogenous default. Besides characterizing in closed form the full interdependence between liquidity and default for credit spreads, our calibrated model can jointly match empirically observed credit spreads and liquidity measures of bonds across different rating classes.

We explore two recent phenomena in equity crowdfunding platforms: the development of dedicated secondary markets and the crucial role of institutional investors (lead investors in terms of pledge). First, we propose a theoretical model in which crowd and lead investors choose to finance campaigns posted by entrepreneurial firms that are heterogeneous with respect to their target and long-term return. We suppose that lead investors make huge pledges in the highest return campaigns but bear the cost of illiquidity whereas the crowd invests in all campaigns. The platform sets up a secondary market to enhance asset liquidity, but all entrepreneurial firms with successful campaign are not automatically listed. If they are listed, second-hand transactions send signals on the chance of success of the funded campaigns. Theoretical results show that increasing the number of lead investors or their pledge improves fundraising but always reduces access to the secondary market for some entrepreneurial firms. If the lead investors’ cost of illiquidity is particularly low, it may even decrease the share of entrepreneurial firms that have access to the secondary market. We then test these predictions using data scraped from one of the most important ECF platforms that covers the period November 2018–October 2020. We empirically show that the number of lead investors and their pledge are positively correlated with the success of the fundraising campaign and negatively correlated with the access the entrepreneurial firms have to the secondary market. These results suggest that the illiquidity of shares is not of first importance for lead investors, who tend to make long-term commitments to crowdfunding campaigns. The implementation of secondary market is thus a useful tool to attract crowd investors but should be finely monitored by the platform to retain lead investors.Plain English SummaryThe development of secondary markets and the increasing role of institutional investors (lead investors in terms of pledge) are recent phenomena in the world of equity crowdfunding platforms. We question why all funded entrepreneurial firms are not automatically listed when secondary markets open. Second-hand transactions offer a valuable exit option for investors but may send perturbing signals through too much price share volatility and possible loss of confidence from entrepreneurs and investors. The role of the platform is then to select funded campaigns authorized to be listed on its secondary market. We show both theoretically and empirically that increasing the number of lead investors or their pledge improves fundraising but surprisingly reduces access to the secondary market for some entrepreneurial firms. This suggests that the illiquidity of shares does not really matter for lead investors, who tend to make long-term commitments. In conclusion, our study provides practical implications for equity crowdfunding platforms that seek to organize the opening of secondary markets.

In the Spanish electricity market, after the daily market is held in which prices are set for the next day, the secondary and tertiary markets take place, which allow companies more accurate adjustment of the electricity they are able to offer. The objective of this paper is to predict the final price reached in these markets by predicting the supply curve in advance, which is the aggregate of what companies offer. First, we study a procedure to represent the supply curves, and then we consider different machine learning approaches to obtain the day-ahead supply curves for the secondary market. Finally, the predictions of the supply curves are crossed with the system requirements to obtain the expected price predictions. Histogram-Based Gradient Boosting is the best performing algorithm for predicting supply curves. The most relevant variables for the prediction are the lagged values, the daily market price, the price of gas and values of the wind recorded in the Spanish provinces.

We investigate the impact of secondary market options on season ticket buyers’ ticket purchase and usage decisions. Sports franchises derive significant portions of their revenues from season ticket holders. A development that may affect season ticket management is the growth of legal secondary markets. We develop a structural model that integrates both the supply and demand sides of the secondary market into season ticket buyers’ ticket purchase and usage choices. We use a panel data set that combines season and single ticket purchase records with ticket usage data to investigate the value of secondary markets. We estimate that the secondary market increases the team’s season ticket revenues by about $1 million per season. At the level of the individual season ticket customer, we estimate an increase in customer lifetime value ranging from $1,327 in the lowest quality seat tier to $2,553 in the highest. In terms of value to the customer, the average dollar value of having a secondary market is $138 per season ticket. Across segments, the secondary market provides the equivalent of a 4% discount in the premium seat tier versus an 11% discount in the economy seat tier. Whereas the secondary market creates more value in the premium-ticket tier segments, the secondary market has the most impact on behavior in the low price oriented segment.

Throughout this article, an alternative depreciation method for electric vehicles (EVs) is presented, addressing the challenge of information asymmetry—a common issue in secondary markets. The proposed method is contrasted with traditional models, such as the Straight-Line Method (SLM), the Declining Balance Method, and the Sum-of-Years Digits (SYD) method, as these classic approaches fail to adequately consider key factors such as mileage and secondary aspects like battery degradation and rapid technological obsolescence, which critically impact the residual value of used EVs. The presented approach employs an adverse selection model that incorporates buyers’ and sellers’ perceptions of vehicle quality from the information recorded on e-commerce platforms, improving the depreciation estimation. The results show that the proposed method offers greater accuracy by leveraging asymmetric information extracted from web portals. Specifically, the method identifies a characteristic intersection point, marking the moment when the model aligns most closely with the data obtained through traditional methods in terms of precision. The analysis through the density of price estimations by vehicle model year indicates that, beyond 1.8 months, the proposed model provides more reliable results than traditional methods. The proposed model allows buyers to identify undervalued assets and sellers to obtain a fair market value, mitigating the risks associated with adverse selection, reducing uncertainty, and increasing market transparency and trust. It fosters equitable pricing between buyers and sellers by addressing the implications of adverse selection, where sellers—possessing more information about the vehicle’s condition than buyers—can dominate market transactions. This model restores balance by ensuring fairer valuation based on vehicle usage, primarily addressing the lack of critical data available on e-commerce platforms, such as battery certifications, among others.

The objective of the paper is to verify hypotheses regarding integration and cointegration (relation) of mean apartment prices on the primary and secondary market in Szczecin. Both transaction prices as well as offer prices of apartments were investigated. The analysis period encompasses the years of 2006 – 2022 (quarterly data). An ADF test was employed to examine the integration of time series, taking into consideration a deterministic component in the form of a quadratic function. Only the time series of mean offer prices and transaction prices on the primary market proved to be integrated in the first degree. The time series of mean offer prices and transaction prices on the secondary market were not integrated, they occurred to be trend stationary series. A two-step Engle-Granger test was employed to analyze the cointegration of time series, which confirmed the cointegration of mean offer prices and transaction prices on the primary market. The relations between individual price types were examined with the use of a procedure which entailed analyzing (with an ADF test) difference stationarity between prices. From the empirical studies it arises that, in Szczecin, transaction and offer prices on the primary market follow one another. On the secondary market, offer and transaction prices are trend stationary and they converge. On the other hand, prices on the primary market diverge from prices on the secondary market (the primary market diverges from the secondary market). This concerns both offer prices as well as transaction prices.

This study conducts a comparison analysis on the efficiency of bookbuilding and secondary market proportional offering (hereafter, SMP offering) in the China stock market. SMP offering as described in this paper is not a follow-on offering, but an initial offering applicable to investors in the secondary market. Specifically, as a unique type of fixed price offering, SMP offering only allows the existing investors who are holding shares (of any listed firms) in the secondary market to subscribe to IPO shares. The amount of IPO shares available to be subscribed by the existing investors is proportional to market value of shares held by them in the secondary market. We find some interesting evidence showing that, compared with bookbuilding, SMP offering is more efficient for pricing IPOs, particularly, in a volatile market. SMP offering leads to lower underpricing and lower cross-sectional variation of short-run returns of IPOs. Also, SMP offering is better able to counteract adverse market conditions in the form of low market return and/or high market volatility. Our results are robust to various alternative tests, e.g., the Heckman (Econometrica 47:153–161, 1979) two-stage procedure and an out-of-sample test, after controlling for the problem of endogeneity and for the influence of the exchange of listing, respectively.

We consider a finite-horizon, multiechelon inventory system in which the surplus of stock can be sold (i.e., disposed) in the secondary markets at each stage in the system. What are called nested echelon order-up-to policies are shown to be optimal for jointly managing inventory replenishments and secondary market sales. Under a general restriction on model parameters, we establish that it is optimal not to both sell off excess stock and replenish inventory. Secondary market sales complicate the structure of the system, so that the classical Clark and Scarf echelon reformulation no longer allows for the decomposition of the objective function under the optimal policy. We introduce a novel class of policies, referred to as the disposal saturation policies , and show that there exists a disposal saturation policy, determined recursively by a single base-stock level at each echelon, that achieves the decomposition of this problem. The resulting optimal replenishment policy is shown to be the echelon base-stock policy. We demonstrate the heuristic performance of this disposal saturation policy through a series of numerical studies: except at extreme ranges of model parameters, the policy provides a very good approximation to the optimal policy while avoiding the curse of dimensionality. We also conduct numerical studies to determine the value of the secondary markets for multistage supply chains and assess its sensitivity to model parameters. The results provide potentially useful insights for companies seeking to enter or develop secondary markets for supply chains. This paper was accepted by Martin Lariviere, operations management.