Purpose – This paper aims to examine the determinants of socioeconomic factors on housing prices and their differential effects among regions. Design/methodology/approach – This study employs a hierarchical linear model to analyze the housing and socioeconomic data of 363 metropolitan statistical areas (MSAs) in the USA. Findings – This study generates four findings. First, the population, the percentage of the elderly in population, violent crime rates, and foreclosure rates produce greater effects on housing prices in the Northeast than those in the West. Second, the population produces a greater effect on housing prices in the Northeast than those in the Midwest. Third, mortgage rates produce less significant effects on housing prices in the Northeast than those in the Midwest. Fourth, the population, the percentage of the elderly in population, and rent-income ratio produce greater effects on housing prices in the Northeast than those in the South. Research limitations/implications – Based on data collected for 2010, this study analyzes socioeconomic factors on the demand side under the implicit assumption that supply side remains constant. Future research can lift the restriction on fixed supply assumption. Practical implications – The results can provide information to buyers and sellers about how socioeconomic factors affect housing prices. Moreover, this study also provides useful information for the government to design and implement relevant housing policies. Originality/value – This is the pioneering study to examine the differential effect of socioeconomic factors on metropolitan housing prices among regions by employing dummy regional variables to detect changes in slope coefficients. These detailed conclusions would enhance the efficiency of transaction in housing markets.
Chain organization has become the most prevalent form of the restaurant industry. Facing asymmetric information, however, many chains encounter difficulties in monitoring chain store managers who serve different markets. A proper incentive scheme for store managers must be designed to solve the agency problem. However, measuring performance is a critical element of any incentive system. Thus, this study examined the appropriate performance measures of assessing the performance of a store manager. Results revealed that emphasizing quality-related performance measures of assessing store managers produces significant effects on chain growth. Furthermore, placing greater emphasis on quality-related performance measures produces a greater effect on chain growth if the operation can be easily standardized. Contrary to the negative effect of stock-based compensation, bonus-based compensation could strengthen the positive relationship between quality-related performance measures and chain growth. The alignment among quality-related performance measures, operation standardization, and reward modes was considered crucial for managing restaurant chains.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.