The article's proposed engineering uses are based on theories presented in the reviewed research articles and on findings from online investigations into companies that claim to use nanoengineering in their wares. Several pre-existing online consumer inventories and nanotechnology news were examined as part of the internet inquiry. The data about the nanoparticles (NP), or nanostructure, used in commercially available products comes from the remarks made by the manufacturer. Nanoengineered coating agents and textile additives are examples of commercial items developed for industrial clients that fall under the aforementioned uses.

Despite noticeable research interest, the labor-intensive Readymade Garments (RMG) industry has rarely been studied from the perspective of workers’ productivity. Additionally, previous studies already generalized that rewards and organizational commitment lead to employee productivity. However, extant research focused on the RMG industry of Bangladesh, which consists of a different socio-cultural, economic, and political environment, as well as profusion dependency on unskilled labor with an abundance supply of it, hardly considered job satisfaction as a factor that may affect the dynamics of compensations or rewards, commitment, and employee productivity. To address this research gap, this study analyzes the spillover effect of compensation, organizational commitment, and job satisfaction on work productivity in Bangladesh’s readymade garments (RMG) industry. Besides, it delves into the analysis of job satisfaction as a mediator among these relationships. We examined the proposed model by analysing cross-sectional survey data from 475 respondents using the partial least squares-structural equation model in Smart PLS 4.0. The findings show that higher compensation and organizational commitment levels lead to higher levels of job satisfaction, leading to greater productivity. This research also discovered that job satisfaction is a mediator between compensation and productivity and commitment and productivity, respectively. Results further show that increased organizational commitment and competitive wages are the two keyways to boost job satisfaction and productivity in the RMG industry. Relying on the findings, this study outlines pathways for organizational policymakers to improve employee productivity in the labor-intensive industry in developing countries.

This article explores the application of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework in the context of integrating self-driving tractors into agricultural practices. With a focus on understanding the factors influencing the acceptance and adoption of this transformative technology, we delve into the implications for farmers, industry stakeholders, and the future of sustainable agriculture and rural tourism.

We studied the role of industry-academic collaboration (IAC) in the enhancement of educational opportunities and outcomes under the digital driven Industry 4.0 using research and development, the patenting of products/knowledge, curriculum development, and artificial intelligence as proxies for IAC. Relevant conceptual, theoretical, and empirical literature were reviewed to provide a background for this research. The investigator used mainly principal (primary) data from a sample of 230 respondents. The primary statistics were acquired through a questionnaire. The statistics were evaluated using the structural equation model (SEM) and Stata version 13.0 as the statistical software. The findings indicate that the direct total effect of Artificial intelligence (Aint) on educational opportunities (EduOp) is substantial (Coef. 0.2519916) and statistically significant (p < 0.05), implying that changes in Aint have a pronounced influence on EduOp. Additionally, considering the indirect effects through intermediate variables, Research and Development (Res_dev) and Product Patenting (Patenting) play crucial roles, exhibiting significant indirect effects on EduOp. Res_dev exhibits a negative indirect effect (Coef = −0.009969, p = 0.000) suggesting that increased research and development may dampen the impact of Aint on EduOp against a priori expectation while Patenting has a positive indirect effect (Coef = 0.146621, p = 0.000), indicating that innovation, as reflected by patenting, amplifies the effect of Aint on EduOp. Notably, Curriculum development (Curr_dev) demonstrates a remarkable positive indirect effect (Coef = 0.8079605, p = 0.000) underscoring the strong role of current development activities in enhancing the influence of Aint on EduOp. The study contributes to knowledge on the effective deployment of artificial intelligence, which has been shown to enhance educational opportunities and outcomes under the digital driven Industry 4.0 in the study area.