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ABSTRACTProduct recalls are often associated with quality failures and may negatively affect customer satisfaction and firm performance. Motivated by counterintuitive anecdotal evidence on the positive relationship between recalls and sales, we develop an endogenous consumer reference model with stochastic quality levels and consumer valuation of gain‐loss utility to examine the consumer's willingness to buy in the event of a recall. A consumer makes purchasing decisions by evaluating gain‐loss values against a quality reference point. The theory of endogenous reference points incorporates the consumer's expectations of buying into forming a reference point based on the consumer's beliefs about quality outcomes (Kőszegi & Rabin, 2006, 2007). The uncertainty of the consumer's quality expectations combined with the consumer's personal equilibrium makes the reference point endogenous, generating predictions different from those under conventional exogenous reference point and in the case of deterministic quality expectations. We find that a product recall may revise the consumer's belief toward a more negative quality outcome, and therefore, a lower reference point, when quality expectations are uncertain and the consumer's reference point is endogenous. The consumer expects a greater gain from buying the product against the lower reference point, leading to a higher willingness to buy. In addition, we find that supply chain offshoring, which may be associated with consumer evaluation of gain‐loss utility or consumer loss aversion, may complicate the effect of recalls on a consumer's willingness to buy. These results suggest that firms should consider consumer preferences under uncertainty when designing and developing their global supply chain strategies in quality management.

As global public health is under threat by the 2019-nCoV and a potential new wave of large-scale epidemic outbreak and spread is looming, an imminent question to ask is what the optimal strategy of epidemic prevention and control (P&C) measures would be, especially in terms of the timing of enforcing aggressive policy response so as to maximize health efficacy and to contain pandemic spread. Based on the current global pandemic statistic data, here we developed a logistic probability function configured SEIR model to analyse the COVID-19 outbreak and estimate its transmission pattern under different "anticipate- or delay-to-activate" policy response scenarios in containing the pandemic. We found that the potential positive effects of stringent pandemic P&C measures would be almost canceled out in case of significantly delayed action, whereas a partially procrastinatory wait-and-see control policy may still be able to contribute to containing the degree of epidemic spread although its effectiveness may be significantly compromised compared to a scenario of early intervention coupled with stringent P&C measures. A laissez-faire policy adopted by the government and health authority to tackling the uncertainly of COVID19-type pandemic development during the early stage of the outbreak turns out to be a high risk strategy from optimal control perspective, as significant damages would be produced as a consequence.