Abstract
Banking sectors have allocated funds for micro and small-scale enterprises’ financing needs. However, the absorption of this fund is still considered low, particularly among the micro- and smallscale processing industries. The present study hence applied the multinomial logistic regression to understand the small industries’ loan decisions. The data were obtained from the 2019 Micro and Small Industry Survey and Financial Institution Statistics. It was found that income and profit did not exhibit a significant effect in both models and regions. However, the interest rate was found to have a positive effect in both models and regions, contradicting the Loanable Fund Theory. Collateral exhibited a positive effect in each region only in the first model. Meanwhile, other variables like age, financial record, business course, cooperative membership, business assistance (i.e., cooperative, noncooperative, and subsidized credit), internet access, and partnership exhibited different effects on small industries’ loan decisions in each model and region.
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