Significant predictors of micro entrepreneurs by sex disaggregation with climate change experience in Sabak Bernam, Selangor

This paper aims to identify the significant predictors of micro-entrepreneurs in Sabak Bernam, Selangor, through sex-disaggregated analysis. Sex-disaggregated analysis explains the situations and predictors of male and female micro-entrepreneurs experiencing climate change. A total of n=274 respondents were recruited through purposive sampling in Sabak Bernam, a coastal district of Malaysia. Nevertheless, only n=230 respondents who answered that they had climate change experience were reported in this paper. A total of n=130 respondents were micro-entrepreneurs involved in food enterprises, male=3.9% and female=28.30%; agricultural businesses, male=70.13% and female=45.28%; or other types of businesses, male=25.97% and female=26.42%. Two binary logistic regression models were tested for male and female entrepreneurs, respectively. Micro-entrepreneur status was the dependent variable. The predictors were the total number of household members by sex, gender of respondents, four vulnerability categories consisting of older adults, daily-paid workers, youth, and persons with disabilities, five subdistrict locations, monthly household income, and Food Consumption Score classified as poor or low and acceptable. The binary logistic regression model shows that most micro-entrepreneurs were male rather than female. Male micro-entrepreneurs were younger than female micro-entrepreneurs. The six predictors were the total number of male family members, older-adult status, subdistrict locations of Bagan Nakhoda Omar and Pasir Panjang, household income, and Food Consumption Score. A respondent from the Bagan Nakhoda Omar subdistrict was more likely to be a male micro-entrepreneur than a male respondent from the Sungai Panjang subdistrict. Greater monthly household income indicated that a male respondent was more likely to be predicted as a micro-entrepreneur. However, respondents with poor or low Food Consumption Scores were also more likely to be micro-entrepreneurs. The binary logistic regression model shows that female micro-entrepreneurs had two significant predictors: the Pasir Panjang subdistrict and daily-paid worker status. A respondent from the Pasir Panjang subdistrict was more likely to be a female micro-entrepreneur and a daily-paid worker. This paper concludes that the six significant predictors for male entrepreneurs were the total number of male family members, younger age, residence in the Bagan Nakhoda Omar and Sungai Panjang subdistricts, increased household income, and low Food Consumption Score. Only two significant predictors were found for female entrepreneurs: residence in Pasir Panjang and daily-paid worker status. This study is significant for policymakers developing programmes for male and female residents of blue-economy areas.

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