Gender differences in job satisfaction among gig workers in Bangladesh.

The gig economy (temporary, contract, and freelance online jobs rather than permanent positions) is a component of the fourth industrial revolution and preview of future work. The rise of digital platforms has increased career opportunities and income potential, particularly for women. Yet, the sex-disaggregated evidence regarding platform usage, employment characteristics, and working motivations and satisfaction remains untapped. Using data from a quantitative survey of Bangladeshi gig workers (242 men and 201 women) conducted in 2022, this paper addresses these gaps between male and female workers. The gig economy appears to be gender-segregated across digital platform usages and working categories. Women tend to prioritize digital work options for managing multiple responsibilities, while men are often driven by the potential for higher income. This study conceptually utilized the two-factor theory and empirically ordered a probit model to identify gender differences in job satisfaction. Job satisfaction was significantly increased by work-life balance, monthly income, and social-media connection, while an increase in working hours, complexity in payment systems, and unstable networks all led to a decrease in job satisfaction. The findings have implications for the future growth of the gig economy, provide new insights into gender differences in job satisfaction, and underscore the need for gender-sensitive policies in the online labor market.

Rice farmers' preferences for seed quality, packaging, and source: A study from northern Bangladesh.

The use of quality seeds is crucial to improve rice yield, food security, and farmers' livelihoods. The large informal seed system, limited access to quality seeds, and low seed replacement rate challenge increasing rice yield. Despite robust government initiatives to support the seed system, progress has been slow. Besides, the need for farmers' behavioural change, enhanced coordination, and communication at the local level has not received adequate attention. We investigate rice farmers' preferences for quality seed, packet sizes, types, and sources, and assess the impact of utilizing good quality seed. We collected quantitative data from 1196 rice farmers in northern Bangladesh in 2019. To identify major factors influencing farmers' preferences regarding quality seed, packet sizes, packet types, and seed sources, we employed ordered logit and multinomial logit models. Additionally, we used the propensity score matching procedure to assess the impact of good quality and formal seed sources on the rice yield. The findings revealed that farmers strongly prefer using seeds from formal sources despite limited accessibility. Of the total farmers, 34% use public source seeds, 33% use private source seeds, and the rest rely on their own saved seeds. The use of good quality seeds increased rice yields from the base yield by 0.07-0.28 t/ha. We found about a 48% gap in accessing good-quality seeds, indicating significant potential for scaling up the seed systems. Farmers using formal seed sources yielded 0.03-0.15 t/ha more than informal seed users. Farmers strongly prefer 5 kg packets due to their cost-effectiveness, easy storage, and handling convenience. Additionally, farmers prefer polycoated jute sacks for their versatility, multi-purpose applications, and resistance to pests. The econometric model results showed that farmers' preferences were significantly influenced by gender, farm type, crop yield, seed price, market distance, various stakeholders' advice, and seed supply systems' constraints. The government should implement policies and programs to strengthen a well-connected seed network in rural areas, promoting inclusivity, and enhancing rice productivity. Besides, farmers' needs and preferences should be considered in designing and implementing seed-related initiatives to foster sustainable agricultural development.

Spatiotemporal mapping of rice acreage and productivity growth in Bangladesh.

Technological advancements have long played crucial roles in rice productivity and food security in Bangladesh. Seasonal variation over time and regional differences in rice production, however, pose a threat to agricultural sustainability but remain unexplored. We performed a spatial-temporal mapping of rice cultivation area, production, and yield from 2006-2007 to 2019-2020 using secondary data for disaggregating 64 districts in Bangladesh. Growth and multivariate approaches were employed to analyze time-series data. Results showed that Mymensingh had the highest rice cultivated area and production, while Bandarban had the lowest. The 14 years highest average rice yield was found in Gopalganj and Dhaka (3.63 tons/ha), while Patuakhali (1.73 tons/ha) had the lowest. For the Aus, Aman, and Boro, the rice cultivation area in 19 districts, 11 districts, and 13 districts declined significantly. The overall rice production increased significantly in most districts. For the Aus, Aman, and Boro seasons, the rice yield in 54, 50, and 37 districts demonstrated a significant upward trend, respectively. The adoption rate of modern varieties has risen dramatically. However, there are notable variances between regions and seasons. A significant increasing trend in Aus (0.007% to 0.521%), Aman (0.004% to 0.039%), and Boro (0.013% to 0.584%) were observed in 28, 34, and 36 districts, respectively, with an increase of 1% adaptation of HYV. Predictions revealed that rice cultivation area and production of Aus, Aman, and Boro seasons will be increased in most of the regions of Bangladesh by 2030. Based on spatiotemporal cluster analysis, the five identified cluster groupings illustrated that clusters lack spatial cohesion and vary greatly seasonally. This suggests increasing rice production by expanding cultivable land, adopting high-yielding varieties, and integrating faster technological advancement in research and extension. The findings will assist scientists in developing region-specific production technologies and policymakers in designing decentral region-specific policies to ensure the future sustainability of rice production.

Identification of influential weather parameters and seasonal drought prediction in Bangladesh using machine learning algorithm.

Droughts pose a severe environmental risk in countries that rely heavily on agriculture, resulting in heightened levels of concern regarding food security and livelihood enhancement. Bangladesh is highly susceptible to environmental hazards, with droughts further exacerbating the precarious situation for its 170 million inhabitants. Therefore, we are endeavouring to highlight the identification of the relative importance of climatic attributes and the estimation of the seasonal intensity and frequency of droughts in Bangladesh. With a period of forty years (1981-2020) of weather data, sophisticated machine learning (ML) methods were employed to classify 35 agroclimatic regions into dry or wet conditions using nine weather parameters, as determined by the Standardized Precipitation Evapotranspiration Index (SPEI). Out of 24 ML algorithms, the four best ML methods, ranger, bagEarth, support vector machine, and random forest (RF) have been identified for the prediction of multi-scale drought indices. The RF classifier and the Boruta algorithms shows that water balance, precipitation, maximum and minimum temperature have a higher influence on drought intensity and occurrence across Bangladesh. The trend of spatio-temporal analysis indicates, drought intensity has decreased over time, but return time has increased. There was significant variation in changing the spatial nature of drought intensity. Spatially, the drought intensity shifted from the northern to central and southern zones of Bangladesh, which had an adverse impact on crop production and the livelihood of rural and urban households. So, this precise study has important implications for the understanding of drought prediction and how to best mitigate its impacts. Additionally, the study emphasizes the need for better collaboration between relevant stakeholders, such as policymakers, researchers, communities, and local actors, to develop effective adaptation strategies and increase monitoring of weather conditions for the meticulous management of droughts in Bangladesh.