Journal of Technology Management for Growing Economies 2021-10-25T10:46:51+0530 Dr. Jaiteg Singh Open Journal Systems <p>The<strong> Journal of Technology Management for Growing Economies</strong> (J. Technol. Manag. Grow. Econ.) was started in 2010 with an intent to extensively cover research work with innovations and management of technology. Technology has a direct impact on our lives. It is a well-known fact that the developed economies are surging ahead to the next level of growth whereas the emerging economies are still reeling under pressure with numerous issues to manage the innovations in multiple domains viz. education, healthcare, transport, energy, environment, agriculture and shelter among others. Here, sharing and management of technology can play a key role in making a difference to the lives of so many people providing a better quality of life. The&nbsp;<strong>J. Technol. Manag. Grow. Econ.</strong> has therefore been created to assess and debate about relevant technologies which could bring about a change in growing economies.</p> <p>The <strong>J. Technol. Manag. Grow. Econ.</strong> is a biannual, open access and fully refereed journal. Being focused on Engineering and Management, it broadly covers contemporary research work on technology and strategies for effective management of research outcomes in these fields. We do not charge any publication fees from prospective authors.</p> <p><strong>J. Technol. Manag. Grow. Econ.</strong> publishes only original, unpublished manuscripts such as Research Papers, Survey Papers, Review Papers, Thesis (or Chapters thereof) and Case Studies. J. Technol. Manag. Grow. Econ. boasts of its fast review process. The manuscripts are blind peer reviewed within two weeks of submission and authors are communicated regarding the same.</p> <p><strong>J. Technol. Manag. Grow. Econ.</strong> has a team of scientists and academicians on its review panel and advisory board. The blind peer review process ensures that only high-quality research papers are selected for final publication. Critical evaluation of research paper is performed by each reviewer of J. Technol. Manag. Grow. Econ., with special emphasis on identification and reporting of plagiarism. At J. Technol. Manag. Grow. Econ., our endeavour is to ensure novelty in each research manuscript being published therein.</p> <p><strong>The areas of interest of J. Technol. Manag. Grow. Econ. include, but are not limited to: </strong></p> <ul class="list5"> <li class="show">Housing and Infrastructure</li> <li class="show">Energy</li> <li class="show">Empowerment of People</li> <li class="show">Water Management</li> <li class="show">Education Engineering and Management</li> <li class="show">Environment</li> <li class="show">Knowledge Management</li> <li class="show">Transportation</li> <li class="show">Technology Transfer and Management</li> <li class="show">Managing Marketing Mix</li> </ul> <p>&nbsp;</p> <p>&nbsp;</p> A Systematic Literature Review of Malcolm Baldrige National Quality Award (MBNQA) 2021-04-29T09:07:05+0530 Setiawan Humiras Hardi Purba <p>Many organizations measure and assess organizational performance as a strategy to improve competitiveness globally, the Malcolm Baldrige National Quality Award (MBNQA) is a prestigious award regarding quality management created in the USA. This paper reviews 50 journals on MBNQA from various countries and found that about 48% of researchers use the Malcolm Baldrige Criteria for Performance Excellence (MBCfPE) approach to measure organizational performance. We also compare MBNQA with other quality awards such as the European Foundation for Quality Management (EFQM) and the Deming Prize to illustrate what criteria we can use in improving Business Excellent Models (BEM). In the future, we will combine this TQM with the development of the Industrial 4.0 era to get a new model for assessing organizational.</p> 2021-04-28T00:00:00+0530 Copyright (c) 2021 Setiawan and Humiras Hardi Purba Impact of Environmental Performance on Financial Performance: Empirical Evidence from Indian Banking Sector 2021-04-29T09:07:25+0530 Parul Munjal P. Malarvizhi <p>There has been long-standing debate over whether or not firms gain economic competiveness from reducing their impact on the environment. Although ample literature is available on association between environmental performance and financial performance across various sectors, little empirical evidence is available in context of Indian banking sector. This research aims to analyze whether there is any significant relationship between environmental performance and financial performance of banks operating in India for a period 2013-14 to 2017-18. Secondary data has been collected for a sample of 83 banks operating in India. Content analysis was applied to extract information about environmental performance disclosed by sample banks followed<br>by construction of environmental disclosure score index. Hierarchical multiple regression was applied to analyze relationship between environmental performance and financial performance after controlling for effects of size, financial leverage and capital intensity. Results exhibit no significant relationship between environmental performance and financial performance of banks operating in India. Findings of this research are expected to provide insight to users and readers of financial statements to have better understanding about the environmental practices carried out by banks. It would also contribute significantly towards decision making for policy makers in Indian banking sector to establish mandatory environmental legislations for reporting on environmental practices in order to improve non financial disclosure and financial performance in Indian banking sector.</p> 2021-04-28T00:00:00+0530 Copyright (c) 2021 Parul Munjal and P. Malarvizhi Real-Time Face Mask Detection using Deep Learning 2021-10-25T10:46:51+0530 Pranad Munjal Vikas Rattan Rajat Dua Varun Malik <p>The outbreak of COVID-19 has taught everyone the importance of face masks in their lives. SARS-COV-2(Severe Acute Respiratory Syndrome) is a communicable virus that is transmitted from a person while speaking, sneezing in the form of respiratory droplets. It spreads by touching an infected surface or by being in contact with an infected person. Healthcare officials from the World Health Organization and local authorities are propelling people to wear face masks as it is one of the comprehensive strategies to overcome the transmission. Amid the advancement of technology, deep learning and computer vision have proved to be an effective way in recognition through image processing. This system is a real-time application to detect people if they are wearing a mask or are without a mask. It has been trained with the dataset that contains around 4000 images using 224x224 as width and height of the image and have achieved an accuracy rate of 98%. In this research, this model has been trained and compiled with 2 CNN for differentiating accuracy to choose the best for this type of model.It can be put into action in public areas such as airports, railways, schools, offices, etc. to check if COVID-19 guidelines are being adhered to or not.</p> 2021-09-28T00:00:00+0530 Copyright (c) 2021 Journal of Technology Management for Growing Economies