Understanding Consumer Behavior toward Social Enterprise Products

Social enterprise is an emerging global trend to solve society’s major problems through the means of business. After microfinance, Yunus Social Business (Bangladesh) is now getting worldwide attention for its distinctive principles and application. This study attempted to investigate the impact of consumer knowledge and understanding about the social enterprises on their buying behavior. Moreover, consumers’ perceived ethical and environmental awareness or rational considerations have also been investigated. Descriptive statistics shows that 26% respondents have clear understanding about social enterprise and 80% respondents believe that social enterprises can contribute to achieve sustainable development goals (SDGs). Findings of regression analysis show that consumers’ purchase decisions are not influenced by their prior knowledge about social enterprise, ethical perception, and attitude, rather their decision is highly influenced by the information available on the product (P value.001, β.602) and rational behavior that are stimulated through the rational pricing and availability of the product (P value.000, β.258). Thus, the study draws conclusion that to get increased consumer response, social enterprises should provide adequate information about their social and environmental mission and must maintain highest quality and ethical standards to create a trusted brand for all ethical, ecological, and rational consumers

Improving Language Modelling with Noise-contrastive estimation

Neural language models do not scale well when the vocabulary is large. Noise-contrastive estimation (NCE) is a sampling-based method that allows for fast learning with large vocabularies. Although NCE has shown promising performance in neural machine translation, it was considered to be an unsuccessful approach for language modelling. A sufficient investigation of the hyperparameters in the NCE-based neural language models was also missing. In this paper, we showed that NCE can be a successful approach in neural language modelling when the hyperparameters of a neural network are tuned appropriately. We introduced the 'search-then-converge' learning rate schedule for NCE and designed a heuristic that specifies how to use this schedule. The impact of the other important hyperparameters, such as the dropout rate and the weight initialisation range, was also demonstrated. We showed that appropriate tuning of NCE-based neural language models outperforms the state-of-the-art single-model methods on a popular benchmark

An Empirical Assessment on Job Satisfaction of Public Knowledge Employees in Bangladesh

Globalization, reorganization of public sectors and sustainable development of human resource management propel researchers and practitioners to exert considerable attention on employees’ job satisfaction for sustainable and socially responsible organizational development. But little could be known about the satisfaction of knowledge employees, especially in the public sectors. This paper deals with the assessment of the level of job satisfaction and job satisfaction factors of public knowledge employees in Bangladesh. The flow and essence of the paper have been drawn from the empirical analysis of the data of 64 respondents from 7 agricultural and livestock research institution under the Ministry of Local Government, Ministry of Agriculture, and Ministry of Fisheries and Livestock and 4 related universities in Bangladesh. The relationships among variables were assessed by factor analysis, reliability, descriptive statistics, correlations, regression and ANOVA. The major finding is that the job satisfaction of public knowledge employees is significantly dependent upon work motivation and fair treatment. Keywords: Job satisfaction, knowledge employees, public sector

Economic Factors behind Social Entrepreneurship in Bangladesh

Bangladesh has pool of entrepreneurs whereas there are also new establishments; new employment opportunities and so are the income sources. For the better measurement of entrepreneurship characteristics, the growth and different indicators impact on entrepreneurship needs to be identified. Thus this paper tries to find out the key economic indicators of entrepreneurship in the context of Bangladesh. The research is based on secondary research; has used entrepreneurship as a dependent variable proxied by self-employment and seven independent variables—per capita income, unemployment rate, labor force, industrial structure change, capital, human capital and literacy rate. Two regression models have been used encompassing the stated variable data from year 2008 to 2018. In the first regression analysis it has been tried to identify whether the model can be constructed with the overall economic variables with the self employment. At second regression model it has been tried to find out whether there is the explain ability of the variables result in the regression analysis and what is the degree and pattern of the relationship. The research shows that literacy rate and human capital have aligned with the self employment. But all the other variables are not matched with the self employment and could not provide the support for self employment to thrive. And the linear regression analysis shows that per capita income, labor force and literacy rate play the most important role in case of nourishing self employment. Unemployment rate is found as contradictory with the findings in the context of Bangladesh

NOVEL APPROACHES FOR CATALYTIC DIRECT AMIDE FORMATION

Abstract The significance of amides as a component of biomolecules and synthetic products has triggered the development of catalytic direct amidation methods which involve reaction of a carboxylic acid and amine to form an amide with water as the only by-product. These methods evade the need for stoichiometric activation or coupling reagents and hence, are important green chemical processes. Investigations into direct amide formation began with the development a mild reaction conditions for the direct amidation reaction with known arylboronic acid catalysts in two different model reactions and compared with both reported and potential organometallic catalysts (Zr and Fe based). After a systematic evaluation of solvent, temperature and catalyst, ambient reaction conditions were applied in the direct amidation of amino-acid derivatives in order to exploit these more economical reagents for peptide synthesis which is both little used and little explored. Protected amino acid derivatives showed slow reactivity compared to simple amine-carboxylic acid combinations and hence high catalyst loadings were required, though did proceed at 65~68 °C generally avoiding racemisation. However, an interesting synergistic catalytic effect was observed during dipeptide formation using mixture of two arylboronic acid catalysts (1:1) in the direct amidation reaction at lower temperatures, although the process was particularly slow. This impressive result led to explore more about the effect of ‘Cooperative Catalysts’, particularly, on the less reactive acid-amine combination. As a consequence, some commercially important synthesis has been reviewed through this novel cooperative catalysis to ensure their real applicability in industries. Acceptance of the practicability and general applicability of this new approach depends upon the understanding of the mechanism of the cooperative catalysis. In order to reveal the mechanism of the cooperative catalysis the direct amide formation reactions were followed by the real time monitoring technology (React-IR) and HPLC. However, further investigations are required to understand the mechanistic intricacies of this cooperative catalysis. Further, the role of H-bonding in the amide bond formation with significantly inert acid (pivalic acid) towards the amine to form amide has been attempted. In order to accelerate the catalytic activity the use of a potential catalyst promoter, ‘ANB 209’ in the direct amidation reactions was also examined. Improvements in catalysts activity or alterations in catalyst would need further study so that the direct amide formation becomes a common tool for a wide range of carboxylic acid and amine partners. The effect of different substituents on the α-position of carboxylic acid with various amine substrates was investigated to understand the exceptional direct amide formation of the synthesis of mandipropamid, a well known fungicide. Both uncatalysed and catalysed direct amidations of mandelic acid was done with different amine substrates at different temperatures, resulting different rate of amide formation. Finally, the application of two novel borinic acid (R1RBOH) compounds in the direct amide formation reactions has been assessed for the first time, which displayed in some cases the potential to act as catalysts for direct amide formation. Further research will likely to accelerate the developments of this type of catalysts in direct amidations

Investment in Microenterprises for Scaling up Business Growth: Evidence from Social Business Project

Promoting entrepreneurship among the youth and women is an emerging global trend for inclusive sustainable development. This study aims to unlock the potential of social business investments in microenterprises for turning unemployment into entrepreneurship and scaling up business growth. According to Prof Yunus, “social business is selfless business to solve social problems” based on seven principles. The study has selected 264 enterprises of Nobin Udyokta (NU) meaning new entrepreneurs under Nobin Udyokta Project (NUP) of Grameen Telecom Trust (GTT). NUs and GTT have co-investments under equity participation for at least one or more than 1 year. NUs are basically emerging micro entrepreneurs, who are often disproportionately burdened with multi-dimensions of poverty and lack of working capital, which inhibits business growth. Findings of regression analysis show that social business fund can significantly influence the growth of NU enterprises and increased investment can also create more employments. Therefore, this study is having value to the promoter, advocates, investors in social enterprises, and policy makers seeking strategy for reducing poverty and unemployment through entrepreneurship for sustainable development leaving no one behind

Export, Import, Economic Growth, and Carbon Emissions in Bangladesh: A Granger Causality Test under VAR (Restricted) Environment

Purpose: This paper examines the causal and cointegrating relationship between economic growth and CO2 emissions in a multivariate framework by including imports and exports as others control variables for an emerging economy like Bangladesh. Design/methodology: The paper applied vector error correction model (VECM) Granger casualty test for assessing the direction of causality and variance decomposition to explain the magnitude of the forecast error variance determined by the shocks to each of the explanatory variables over time. LB (Q-stat) test is to determine data properties and WILD test is to assess short run causality from independent variables to dependent variable. Findings: The study results revealed that variables are integrated in the same order. The results of Johansen Juselius cointegration tests indicate that there is a unique long-term or equilibrium relationship among variables. Again, Granger causality test revealed that short run unidirectional causality are running from carbon dioxide emission to exports, GDP to import, and from import to carbon dioxide emissions. Variance decomposition function shows that the positive shocks in error term will produce positive effects on all variables in the long run. Therefore, a concerted effort from all national and international stakeholders, i.e., enterprises, consumers, and governments are expected to take measures to offset carbon emission and pursue environment-friendly trade plan for better managing the cities and regions in order to fight against global warming and climate change risk

A Spectral Method that Worked Well in the SPiCe'16 Competition

We present methods used in our submission to the Sequence Prediction ChallengE (SPiCe’16) 1 . The two methods used to solve the competition tasks were spectral learning and a count based method. Spectral learning led to better results on most of the problems

An Improved Crowdsourcing Based Evaluation Technique for Word Embedding Methods

In this proposal track paper, we have presented a crowdsourcing-based word embedding evaluation technique that will be more reliable and linguistically justified. The method is designed for intrinsic evaluation and extends the approach proposed in (Schnabel et al., 2015). Our improved evaluation technique captures word relatedness based on the word context

Challenges of Enforcing Regulations in Artificial Intelligence Act --- Analyzing Quantity Requirement in Data and Data Governance

To make Artificial Intelligence (AI) systems and services accountable and regulated in the European Union market, in April 2021, the European Union Parliament published a proposal `Laying Down Harmonised Rules on Artificial Intelligence (Artificial Intelligence Act)', widely known as Artificial Intelligence Act (AI Act). Since then, many concerns have been raised in terms of compliance and whether the regulations are enforceable. However, to the best of our knowledge, none of them provided an explicit technical analysis of the challenges in enforcing the regulation. Among 85 Articles in the AI Act, we emphasize on the Article 10, the central regulatory requirement for data and data governance. In this paper, we have analyzed a specific requirement, the data quantity, to show the challenges of enforcing this requirement in a principled way. In our analysis, we have used deep learning modeling and machine learning generalization theory