Applicability of the QCA method
Qualitative Comparative Analysis (QCA) is a methodological approach based on Boolean algebra. It facilitates systematic case comparisons and the investigation of causal complexity by identifying diverse combinations of factors that result in the same outcome (He et al., 2023). QCA combines rich qualitative contextual information with structured quantitative data, enabling the simultaneous treatment of multiple cases. It applies to process data of small and medium-sized cases in social science research (He et al., 2023; Shephard et al., 2020). The advantage of QCA lies in revealing the complexity of certain social phenomena by identifying asymmetrical causal relationships, focusing on the direct consequences resulting from the necessity and sufficiency relationships among the various conditions within cases (Pappas and Woodside, 2021; Ragin, 2008). The QCA method doesn’t emphasize the isolated effects of single variables; instead, it identifies the impact of interactions among multiple variables on the outcome. In situations of asymmetric causal relationships, QCA can offer non-exclusive explanatory pathways for both the presence and absence of a phenomenon (Thomann and Ege, 2020). This study opts for the cs-QCA approach because the necessity of dichotomizing conditions, as mandated by cs-QCA, mirrors the practical decision-making processes in real-world foreclosure auction, which frequently adhere to a binary logic of “either this or that” (Caren and Panofsky, 2005; Grofman and Schneider, 2009; Longest and Vaisey, 2008; Vink and Van Vliet, 2009).
Previous research showed that buyers prefer information presented in a binary format to aid decision-making in market transactions (Wagemann et al., 2016). Although fs-QCA has its advantages, it lacks the clear-cut nature of cs-QCA with its binary conditions, especially when dealing with ordinal or continuous values (Blackman, 2013; He et al., 2023). When addressing foreclosed housing cases in China, utilizing cs-QCA provides two key benefits: first, the outcome variable offers only two possibilities—either a successful or failed transaction. Second, the conditional variables of cost risk (LS, DTC), acquisition risk (IPR), usufruct risk (DPR), and credible commitment (CC) can be distinctly dichotomized. By applying the cs-QCA method to analyze 136 foreclosed housing auction cases across 20 cities, this study aims to explore how different combinations of property-right risks influence the outcomes of foreclosure auctions and uncover the significance of credible commitment in judicial auctions in China.
Case selection and data collection
The Cs-QCA method requires adherence to the “most-similar-case design”, organizing information into a set of conditional variables to control confounding factors and identify causal effects (Thomann and Ege, 2020). This study compiled 136 relevant foreclosure cases from online judicial auction platforms, spanning 20 cities in China. To ensure data reliability and validity, the study adhered to four key principles when selecting cases: (1) properties located in provincial capitals or municipalities, specifically in main urban areas excluding suburbs; (2) transaction prices are comparable to average prices of second-hand properties during that period, excluding villas or high-end properties; (3) cases with clear outcomes after the initial auction, categorized as either “successful” or “failed”, excluding cases of postponements, withdrawals, or suspensions; (4) cases with adequate information to cover all conditional and outcome variables.
To gather comprehensive qualitative data, this study collected Auction Notices, Property Evaluation Reports, Notices of Assistance in Execution, Confirmations of Auction Results, and Notices of Enforcement for 136 cases from Jingdong and Ali online judicial auction platforms. Additionally, the author obtained 152 foreclosure reports of due diligence through personal connections from a real estate agency. These data and documents encompass historical transaction records of auctioned properties, leasing status, and instances of unauthorized occupation, providing abundant information for conditional variables of the QCA method.
Outcome and explanatory variables
Outcome variable
The outcome variable is defined as whether a foreclosed property is sold at the initial auction. Auction outcomes are observable and objectively identifiable on online auction platforms. Typically, there are two post-auction results: successful or failed auctionFootnote 6. To present the auction outcome clearly, this study sets the result as a binary variable: a successful auction is assigned the value of 1, and a failed auction is assigned the value of 0.
Explanatory variables
The cost risk determined by LS and DTC refers to the possibility of homebuyers in the foreclosure market encountering high transaction costs such as various hidden taxes and miscellaneous fees because of information asymmetry. According to China’s “Law of Land Administration”, the lawful acquisition of land-use rights is limited to two methods: leasing and allocation. Under the system of reimbursable use of state-owned land, local governments offer fixed-term land-use rights to developers through bidding, auctioning, or listing. For instance, residential land-use rights typically span 70 years, while land for apartment housing is granted for 40 years. On the other hand, allocated land is gratuitously allocated by local authorities for certain public-interest construction projects such as relocation housing and economic affordable housing. These properties often require additional payment of land leasing fees during second transactions. In the foreclosed housing market, a considerable number of properties fall under the allocated land-use rights, resulting in relatively higher property transaction costs. Additionally, auction notices might not always specify the land status of foreclosed properties, potentially implying significant land leasing fees for buyers. This study categorizes the land status of foreclosed properties as a binary variable: allocated or illegal = 0, leased = 1.
On the other hand, the potential cost risk associated with transaction costs primarily involves undisclosed taxes and unpaid miscellaneous fees. The taxation on foreclosed properties is contingent on their prior transaction history. Buyers may be unaware of any outstanding fees. However, this crucial tax information is often implicit as local courts typically focus on procedural rather than factual aspects when handling property forfeiture. Consequently, detailed tax payment amounts are not typically disclosed by local courts, leaving buyers to estimate tax obligations according to restricted information from online auction announcements. This information asymmetry can lead to substantial transaction costs, potentially impacting buyers’ willingness to participate in auctions. Some interviews with buyers revealed cases where successful bidders had to settle significant fees for property management owed by former owners, amounting to tens of thousands of RMB. Failure to address these fees may result in the buyer being unable to obtain property rights and forfeiting their deposit. The less implicit cost information is disclosed, the higher the uncertain cost for the buyer, potentially leading to transaction failures. In this study, DTC is a binary variable: no disclosure = 0; disclosure of one or more items = 1.
The acquisition risk determined by IPR pertains to the potential of a buyer obtaining ownership after achieving the bid, contingent on the combination of “housing ownership + land-use rights”. This combination is a composite property-rights structure, where the higher the IPR, the lower the risk of acquiring property rights, thereby favoring transactions of foreclosures. Previous research indicates that there exist eight primary categories of properties with varying degrees of property rights integrity in China’s foreclosure market (Qian, 2024). IPR is set as a binary variable: illegal housing/small-property-right housing (IH/SPRH), state-owned enterprise housing/economic affordable housing (SHE/EAH), relocation housing (RH), marketized housing (MH) = 0; apartment housing/commercial housing (AH/CH) = 1.
The usufruct risk determined by DPR refers potential of buyers to utilize usufructuary rights, such as habitation, disposal, and inheritance. Upon entering the foreclosure market, buyers typically evaluate the probability of realizing these usufructs according to restricted information from auction announcements issued by courts. In this regard, the usufruct risk may discourage buyers from bidding (Qian, 2024). The DPR is set as a binary variable to indicate the usufruct risk, which is restricted by incompetent property rights/shared ownership, fraudulent contracts, illegal occupation=0; negotiable tenancy/full DPR = 1.
Property-rights risks are moderated by credible commitments. Existing research indicates that if the executing court provides explicit credible commitments, it may mitigate those risks related to property rights encountered by buyers to a certain extent, thereby enhancing their confidence in auctions and facilitating transactions (Qian, 2024). However, not all courts can offer credible commitments. It is foreseeable that if a court does fulfill its commitments as promised, it can significantly enhance the protection of individual property rights. Credible commitment plays a binary variable in this study: no commitment = 0; one or more commitments = 1.
In summary, Table 2 demonstrates all variables and their description and dichotomization for the cs-QCA method. Table 3 shows descriptive statistics of variables based on 136 cases of foreclosure in China.