Suchergebnisse

Along with rapid urbanization, illegal construction of houses has become increasingly prevalent in many urban villages in China. In some cities the major groups engaging in such behaviors are local government organizations and firms, but in other cities it has mostly been individuals
who have engaged in this illegal activity. Focusing on the theory of planned behavior, we obtained data from 678 residents of urban villages in a city of Southwestern Hubei Province, and used the logit model to identify and assess the factors influencing urban villagers' decisions to
engage in illegal construction behavior. Findings indicated that residents were more likely to engage in illegal construction if their relatives had done so, showing some degree of herd behavior. Social networks were also found to matter, in that those who knew more law enforcement officers
were more likely to engage in illegal construction behavior and it was less likely that a resident who was new to a village would do so. These findings are helpful in setting up regulation policies that will better prevent illegal construction behaviors.

ABSTRACTThis article investigates how different decisions can be reached when decision makers consult a binary rating system and a scale rating system. Since typically decision makers use rating information to make binary decisions, it is particularly important to compare the scale system to the binary system. We show that the only N‐point scale system that reports a rater's opinion consistently with the binary system is one where N is odd and is not divisible by 4. At the aggregate level, however, we illustrate that inconsistencies persist regardless of the choice of N. In addition, we provide simple tools that can determine whether the systems lead decision makers to the same decision outcomes.

AbstractSeller reputation, generated by buyer feedback, is critical to fostering trust in online marketplaces. Marketplaces or sellers may choose to compensate buyers for providing feedback. Signaling theory predicts that only sellers of high‐quality products will reward buyers for truthful feedback, especially when a product lacks any feedback and when the seller is not established. We confirm these hypotheses using Taobao's reward‐for‐feedback mechanism. High‐quality products, especially without established feedback, are chosen for feedback rewards, which cause sales to increase by 36%. Marketplaces and consumers can therefore benefit from allowing sellers to buy feedback and signal their high‐quality products in the process.