COVID-19 pandemic has made the economy in Indonesia sluggish, especially Small and Medium Enterprises (SMEs). Simultaneously, the SMEs existence in Indonesia is fundamental and considered important by the government since it is able to assist numerous laborers and become an income source for the lower and middle classes of the community. The productivity of SME in a region will undeniably influence the availability of job and, of course, reduce the number of unemployed. Therefore, in this study, the researchers looked at how to improve SMEs performance to continue to exist amid the COVID-19 pandemic, by identifying the relationships between product characteristics, market competitive strategies, and the performance of SMEs. The research was done on SMEs in West Java, Indonesia. The example employed was Batik SMEs in Cirebon with at least 10 years in existence, and the total number of these SMEs was 165. As the basis of a quantitative approach, this study employed survey instruments by distributing a questionnaire. In analyzing the data, it utilized the structural equation modeling (SEM). The result showed a significant relationship between Product Characteristics, Market Competitive Strategy, and Price and Product Success Rate on SMEs Performance. This study’s findings contribute to the SMEs performance literature.

The main aim of the study is to test a house pricing model by combining hedonic and asset-based pricing models. An understanding of the relationship between house pricing and its return (the rental income) helps to establish houses as a significant asset class. The model tested the relationship between house pricing (dependent variable) and the house attributes (independent variables) derived from Freeman’s framework of housing attributes. This study uses a large data-set of 1,899 sample of new, high-end houses purchased between 2016 and 2019 collected from the national capital region of India (Delhi-NCR). The algorithm was built in R-Script, and stepwise multiple linear regression was used to analyze the model. The analysis of the model proves that the three significant variables, namely, carpet area, pay-off, and annual maintenance charges explain the price function. Further, the model is statistically fit. The major contribution of the study is to understand the key factors and their influence on the house pricing. The model will be helpful in risk assessment in the housing investment and enhance the chances of investment. Policy-makers can use information about the underlying valuation drivers of the house prices to stabilize the market and also in framing the tax policies.