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Ready-made garments (RMG) are one of the most critical sectors in the economy of the South Asian region in terms of the labor force employed and export earnings. This research study aims to determine the Corporate Social Responsibility Stakeholders dimension and its influence on textile firms Performance. The study used organizational legitimacy as mediating variable between the CSR stakeholders and firms’ performances. The research study was used in the quantitative analysis approach to determine the cause and effect of the relationship between CSR and Textile firm’s financial and non-financial performance. Though the study collected primary data & secondary data from 250 respondents using survey questionnaires, the researcher obtained secondary data by analyzing the audited annual and sustainability reports of various RMG companies. We have collected data by conducting a focus group interview forming a team of employers, top-level managers, and CSR officers. We asked them all the questions, filled it, tapped it, reserved it for the interpretations. We have surveyed 67 industries, but it enabled us to collect the data from the 50 sectors—the data collected from 2016 April to 2018 December. Our study has some limitations in that the sample size is small compared to the other research. SPSS-23 & MS-Excel were used to analyze the collected data. CSR practices benefitted RMG companies in terms of long-term sustainable development by increasing the firm’s financial and non-financial performance of the RMG sector.

This study aims to evaluate the impact of human resource management practices (HRMPs) on employee attitudes and behavior (EAB). The population of this study was all employees of cement manufacturing firms (CMC) in the southern region of Bangladesh. Data was gathered using structured questionnaires following convenient sampling technique. The data was analyzed using SPSS-23 statistical package program. A robust and significant linear association between HRMPs and EAB was found. Further, HRM practices, including compensation & rewards (CR) and motivation (MV) were discovered to be dominant predictors of EAB. According to the study, variations in EAB of 77.10% were caused by independent predictors such as recruitment and selection (RS), training and development (TD), performance appraisals (PA), compensation and rewards (CR), motivation (MV), and maintenance (MT) in CMC in the southern part of Bangladesh. Nevertheless, it is apparent from the study's findings that manufacturing organizations that have implemented progressive HRM practices in a systematic and integrated manner are having an enormous influence on EAB. This study only focused on one industry and one type of organizational structure. According to the study, findings should not be extensively generalized. Future research should incorporate other aspects, such as organizational learning and organizational capacity, to construct a new model of HRM practices.

This paper examines the consequences of banks’ performance on bank risk. The paper forms a theoretical model and delivers empirical evidence to identify that banks suffer in performance as the loans become bad. Using panel data from a sample of five (05) South-Asian emerging economies from 2011 to 2019, we have found that the banks are highly influenced by the development of non-performing loans (NPLs). We have primarily used Return on Asset (ROA) followed by Return on Equity (ROE) as a substitution to the performance of the banks and NPL as the proxy of bank risk. Simultaneous regression applying 3sls finds that Non-Performing Loan (NPL) hinders banks' growth, negatively affecting their profitability.

As the inclination to FDI shifts from developed to developing economies, investors are flocking to emerging markets, particularly to the Next-11 nations, which render additional growth and investment opportunities. Meanwhile, these countries have become popular FDI destinations; the goal of this study is to look at the major factors that make these countries appealing to FDI destinations. As a result, this research examines the factors that influenced FDI inflows into these nations from 1995 to 2019. Market size, trade openness, natural resource availability, economic stability, and infrastructure facilities are among the potential explanatory factors identified in this research. On the panel data set, which includes data from 11 nations, a fixed-effect model is used. The data show that market size, trade openness, natural resource availability, and economic stability are all possible predictors of FDI inflows to these nations, whereas infrastructure appears to be a minor one.  

In the arena of economic analysis, the wealth of a nation is getting more and more attention to be a better indicator to evaluate the status of an economy. This paper had studied the aggregate household wealth of different nations of the world, 106 countries, for the year 2009-2018. During these years, only two countries of the world, China and the USA have managed to increase their wealth tremendously over the last decade while others experienced a slow pace in the growth of wealth. To satisfy the query of how efficient these countries were in maximizing their wealth, a stochastic frontier approach (SFA) has been used to predict the technical efficiency dependent variable and then generalized methods of moments (GMM) and other models have been used to find out the determinants of this efficiency. The study had come up with the result that land, labor, and capital mainly contributed to the output of wealth maximization while past year level of efficiency, export, and import played the main roles in determining the wealth maximizing efficiency status of a nation. It is found that there is a negative relationship between past-year efficiency with current years and the more a country imports, the less efficient the country is while the more it exports, the more efficient the country is in maximizing wealth. 

Research Originality: This study investigates the relationship between inventory management and profitability within the textiles industry in Bangladesh, emphasizing the key factors that significantly enhance the industry's profitability. Research Objectives: This analysis investigates how various factors, including total assets, total equity, total revenue, share capital, retained earnings, finished items, work in progress, and raw materials, impact profit after tax (PAT). Research Methods: The data spans from 2011 to 2023 and encompasses 46 textile companies listed on the Dhaka Stock Exchange (DSE). To conduct this study, different models like Pooled Ordinary Least Square (POLS), Second Stage Least Square (2SLS), Generalized Method of Moments (GMM) are utilized. Empirical Results: Through the application of techniques including Pooled Ordinary Least Squares (POLS), Two-Stage Least Squares (2SLS), and the Generalized Method of Moments (GMM), we have established that total assets exhibit a significant negative correlation with PAT in both the POLS and 2SLS models. On the other hand, there is a notable positive correlation between total revenue and retained earnings on PAT across all 2SLS, POLS, and GMM models. The share capital shows a negative correlation with PAT in all three models: 2SLS, POLS, and GMM. The main independent variable, which is our fundamental focus, shows that finished goods have a positive correlation with PAT; however, this correlation lacks significance. The raw materials exhibited a negative correlation with PAT, and this relationship is significant. The correlation between Packing Materials and PAT is notably positive. This study highlights the importance of strategies that could facilitate sustainable growth in the textile industry.

This study investigates the relationship between exposure to online promotional content and changes in business image evaluations and purchase intention toward informal clothing enterprises in Bangladesh. Based on the O-S-O-R framework, the study conceptualizes online promotional content as the stimulus, post-exposure business image as the post-orientation construct, and purchase intention as the response, considering age group and frequency of social media usage as pre-orientation factors. Using a nonprobability purposive sampling approach with self-selected participation, the study implemented a one-group pretest-posttest design through an online questionnaire administered to 391 respondents in Bangladesh. Analyses included descriptive statistics, reliability tests, exploratory factor analysis, paired-samples t tests, Spearman correlations, and linear regression. Results indicated statistically significant increases between pre-exposure and post-exposure for business image (mean difference = −1.297, t = −50.945, p < .001) and purchase intention (mean difference = −1.254, t = −39.308, p < .001). Age group was negatively associated with post-exposure business image, whereas frequency of social media use was positively associated with it. Post-exposure business image was also a strong predictor of purchase intention (β = .486, p < .001, R² = .236). This study contributes to the literature by extending extant research on digital consumer response in informal small-business clothing retail in Bangladesh and suggests that well-designed promotional content is positively associated with business evaluations and purchase-related intentions. Since this study used a one-group pretest-posttest design, the results should be interpreted as evidence of association rather than causation.

This qualitative study explores the complex factors that affect the acceptance of digital technologies (ADT) in the setting of a least developed country (LDC). In-depth interviews using purposive and convenience sampling techniques were conducted with business professionals (n=40) in Bangladesh, acknowledging the distinct challenges and opportunities that these settings present. Qualitative research offers the chance to delve into professional experiences and obtain comprehensive insights into how they view digital technologies in the real world. In order to provide a theoretical framework for future research, this study employed grounded theory and thematic analysis to explain the factors of the acceptance of digital technologies (ADT). This study proposed five factors to re-conceptualize ADT based on three theories. The study offered a novel insight into factors for ADT from the viewpoints of varied professions, which provided a framework that may serve as the basis for explaining ADT.

The research investigates how goal contagion impacts the acceptance of digital technologies and also explores the moderating effect of COVID-19 and survival instinct within the interconnection between goal contagion and the acceptance of digital technologies. The research has undertaken partial least squares structural equation modeling to identify the direct as well as moderating effects based on a sample of 250 individuals across diverse firms in Bangladesh. The research also involved the Importance-Performance Map Analysis approach (IPMA) to explore key areas of importance and performance, thus providing a holistic understanding of key factors impacting the acceptance of digital technologies. Then, an ANN model analysis was used to determine how important the components determined by the PLS-SEM study were in terms of relative influence. The study revealed that others’ behavior and situational context have a significant impact on goal contagion. The outcome also showed that goal contagion has a significant impact on the acceptance of digital technologies; besides, survival instinct and COVID-19 have a statistically significant moderating effect between goal contagion and the acceptance of digital technologies. The IPMA findings showed that COVID-19 and goal contagion are the most important factors for the acceptance of digital technologies. The ANN findings revealed that situational context is the most contributing construct for goal contagion. The findings also demonstrated that COVID-19 and goal contagion are the most influential constructs for the acceptance of digital technologies. The findings of this research contribute significantly to the relevant knowledge by promoting a theoretical framework for comprehending the factors that influence the acceptance of digital technologies. Furthermore, this research illustrates valuable insights for companies that are planning to make strategic decisions regarding their digital technologies.

  This study aims to explore the effect of foreign direct investment on the educational attainment.  This paper employed the POLS and 2SLS models. In Pooled Ordinary Least Square Model, educational attainment in primary, lower secondary, upper secondary and masters’ level have the significant positive relationship with foreign direct investment. In Two stage Least Square Model, educational attainment in primary, lower secondary, upper secondary, tertiary and masters’ level have the significant positive relationship with foreign direct investment. This study contributes to look at the impact foreign direct investment on educational attainment. Panel data from 38 Asian countries was gathered for this study, which spanned the years 2011 to 2022. The study results have important policy implications as they are directly linked to the United Nations’ Sustainable Development Goals (SDGs) Target 4.1, which aims to guarantee that all girls and boys get free, equitable, and high-quality primary and secondary education by 2030, resulting in relevant and effective learning outcomes.