Technology Management for Accelerated Recovery during COVID-19: A Data-Driven Machine Learning Approach

Objective- The research looks forward to extracting strategies for accelerated recovery during the ongoing Covid-19 pandemic. Design - Research design considers quantitative methodology and evaluates significant factors from 170 countries to deploy supervised and unsupervised Machine Learning techniques to generate non-trivial predictions. Findings - Findings presented by the research reflect on data-driven observation applicable at the macro level and provide healthcare-oriented insights for governing authorities. Policy Implications - Research provides interpretability of Machine Learning models regarding several aspects of the pandemic that can be leveraged for optimizing treatment protocols. Originality - Research makes use of curated near-time data to identify significant correlations keeping emerging economies at the center stage. Considering the current state of clinical trial research reflects on parallel non-clinical strategies to co-exist with the Coronavirus

Strategic Perspective of Services Marketing

According to reports and research, the services sector has emerged as one of the biggest employers across different world economies during the last two decades. As per the UNCTAD, November 2021, the services sector pulled out following the trend of an overall expansion, trade-in services. However, tourism is still below pre-pandemic ranks at $6 trillion in 2021. While analyzing the regional picture, trade growth persisted patchy in the third quarter of 2021, considering decreased regional differences in comparison to the first half of the year. In fact, the growth of the services sector’s output has led to employment growth in these economies. In present times, it is of utmost importance to manage services in a more strategic manner, so that economic stability turns into a sustainable feature for the service businesses. According to the Organisation for Economic Co-operation and Development (OECD) member countries, more than 70 percent of the employed labor force worked in the services sector in 2017; among high-income industrialized OECD member countries, except for Greece, this proportion exceeded 80 percent.  With the advancement of technology, consumerism, digitalization, and never before consumer movements, the services sector has been witnessing drastic changes. Contrary to (Dacko, 2012) services marketing, now a day is not only an approach but is also a strategy to be pursued by all firms. Managers and executives of the Service industry should carefully adapt the marketing mix composition to identify the best services strategy to achieve their marketing and business objectives. To date services marketing has received little strategic attention in the services marketing literature. Most of the research in the service sector has been concentrated on SDL and service ecosystems. As per (Pomering & Johnson, 2018) it has been proposed that service organization has strengthened sustainability in terms of environment and society through decision making. This paper is an attempt to propose a model, considering the services as an integral part of any organization. The proposed model is relevant to organizations irrespective of the fact whether they offer tangible goods or intangible services or both in some proportion. The methodology adopted is qualitative and exploratory. Authors have reviewed extensive literature and coupled the same with monitoring of industry trends to come up with the model for service marketing. The model may be applied as a strategic tool, to design and allocate the marketing mix components for enhanced visibility in the market

Reinforcing Positive Cognitive States with Machine Learning: An Experimental Modeling for Preventive Healthcare

Societal evolution has resulted in a complex lifestyle where we give most attention to our physical health leaving psychological health less prioritized. Considering the complex relationship between stress and psychological well-being, this study bases itself on the cognitive states experienced by us. The presented research offers insight into how state-of-the-art technologies can be used to support positive cognitive states. It makes use of the brain-computer interface (BCI) that drives the data collection using electroencephalography (EEG). The study leverages data science to devise machine learning (ML) model to predict the corresponding stress levels of an individual. A feedback loop using “Self Quantification” and “Nudging” offer real-time insights about an individual. Such a mechanism can also support the psychological conditioning of an individual where it does not only offer spatial flexibility and cognitive assistance but also results in enhanced self-efficacy. Being part of quantified self-movement, such an experimental approach could showcase personalized indicators to reflect a positive cognitive state. Although ML modeling in such a data-driven approach might experience reduced diagnostic sensitivity and suffer from observer variability, it can complement psychosomatic treatments for preventive healthcare

Training & Development, Organizational Commitment and Turnover Intentions in SMEs

Training and development is an important tool for motivating employees and increasing organizational performance. Therefore, we have developed a new model in which we have empirically tested four direct relationships, three mediating relationships, and one moderating effect. We have collected the data from selected SMEs in Karachi. A total of 410 questionnaires were distributed, and 385 valid responses were available. The instrument was adapted from earlier studies. We have used Smart PLS for data analysis. Of the four direct hypotheses, we found support for two of them. Similarly, we only found support for one indirect hypothesis and no support for the moderating relationship. The study found that antecedents “availability of training and managerial support for training†stimulate organizational commitment. However, we did not find any support for the “association between motivation to learn and organizational commitment†in Karachi SMEs. In contrast to earlier literature, we found that “organizational commitment stimulates turnover intentions.†Organizational commitment mediates (1) availability of training and turnover intentions, and (2) managerial support and turnover intentions. However, the study did not support organizational commitment’s mediating role on motivation to learn and turnover intentions. Similarly, constituent attachment did not have a moderating effect in our study

Database Marketing: OLD WINE IN A NEW BOTTLE!!!

The database marketing field is growing day by day.Lots of people have their inboxes filled on a daily basis withemail messages advertising items that they might want to buy.The list is produced by companies who conduct studies and isthen sold to other companies who market yet more businessesproducts. The current availability of on-line direct marketingdatabases provides numerous opportunities for marketingprofessionals to improve their marketing strategies and tactics.Database marketing is as old as the World Wide Web.It is no longer merely a case of shopping for a database oftelephone numbers and cold calling them in the hopes ofcreating a sale. Data base marketing, now a days is being usedas the foundation for developing a market segmentationapproach to identify new prospects and thus providing amechanism for organizing the company's marketing activities.Lifetime value analysis, a concept that plays a major role inCRM, is used to group prospects into 'good', 'better,' and 'best'categories and thus provide an understanding of the likelyresponsiveness of these segments. Emphasis is a new marketing program to appeal to these prospective customers.Many people also see a disadvantage in the database approachof marketing by believing it is too intrusive. Databasemarketing involves large amounts of information aboutcustomers that is used as a basis for future advertising.However, proponents claim there is nothing wrong with usingcompiled information about customers, and deny anyintrusion.This paper, which will be a descriptive one, author ishighlighting the recent trends of database marketing. how itcan be more effective, what are the bottlenecks, in doing thesame. Further the paper will also argue, about the origin andusage of these so called new and efficient efforts

In vitro antimicrobial activity of essential oils and their acetylenic constituents

The emergence of new infections and increase of bacterial drug resistance has prompted interest for the development of new antibacterial agents from natural sources.This study is an attempt to assess the therapeutic potential of plant constituents as new antimicrobial drugs. The essential oils from six Asteraceae species belonging to the genus Erigeron, Aster, and Senecio were evaluated for their antibacterial activity against six bacteria namely Pseudomonas aeruginosa, Bacillus subtilis, Escherichia coli, Aeromonas hydrophilla, Klebsiella pneumonia, and Streptomyces candidus using agar well diffusion method. The results revealed (Z)-lachnophyllum (<68 %) and 2(E), 8(Z)-matricaria esters (<62 %) as the major acetylenic constituents in four Erigeron species. E. mucronatus showed the highest activity against Gram-positive bacteria S. candidus (8.3 mm, MIC 5 µL/mL) and B. subtilis (11.0 mm, MIC 10 µL/mL). (Z)-Lachnophyllum and 2(E), 8(Z)-matricaria esters showed maximum activity against S. candidus (MICs 5 µL/mL). The results showed that the oils containing acetylenic constituents have potential as natural agents for treatment of infections caused by these bacteria

Implications of Belt and Road Initiative for Supply Chain Management: A Holistic View

Belt and Road Initiative (BRI), one of the largest logistics and transportation infrastructures to date, has focused on much work in the economics and political sciences. However, little research has been done on how BRI can affect supply chain management on the whole. Since BRI is a large-scale logistics infrastructure-building project, it is clear that it will have several implications for supply chains. This study aimed to fill this gap in supply chain management literature within the context of the BRI. In particular, this paper aimed to unveil the potential challenges and threats that BRI may bring to supply chain management. Using 20 semistructured interviews with supply chain managers located on the BRI lane in South Asian countries (Pakistan, India, Bangladesh, etc.), this study posed six distinct implications of BRI for logistics and supply chain management. This article concludes by articulating its contributions to theory and practice and, finally, limitations and future research directions

<i>In vitro</i> antimicrobial activity of essential oils and their acetylenic constituents

63-68The emergence of new infections and increase of bacterial drug resistance has prompted interest for the development of new antibacterial agents from natural sources.This study is an attempt to assess the therapeutic potential of plant constituents as new antimicrobial drugs. The essential oils from six Asteraceae species belonging to the genus Erigeron, Aster, and Senecio were evaluated for their antibacterial activity against six bacteria namely Pseudomonas aeruginosa, Bacillus subtilis, Escherichia coli, Aeromonas hydrophilla, Klebsiella pneumonia, and Streptomyces candidus using agar well diffusion method. The results revealed (Z)-lachnophyllum (E), 8(Z)-matricaria esters (Erigeron species. E. mucronatus showed the highest activity against Gram-positive bacteria S. candidus (8.3 mm, MIC 5 µL/mL) and B. subtilis (11.0 mm, MIC 10 µL/mL). (Z)-Lachnophyllum and 2(E), 8(Z)-matricaria esters showed maximum activity against S. candidus (MICs 5 µL/mL). The results showed that the oils containing acetylenic constituents have potential as natural agents for treatment of infections caused by these bacteria

Susceptibility of males in second wave of Covid and infection in young: A comparison of two waves

Many countries have seen a two-wave pattern in reported cases of coronavirus disease-19 during the 2020 pandemic, with a first wave during spring followed by the current second wave in late summer and autumn. Empirical data show that the characteristics of the effects of the virus do vary between the two periods. Differences in age range and severity of the disease have been reported, although the comparative characteristics of the two waves still remain largely unknown. This was a challenging time, but we should faith on science to help us get through these pandemic and future ones. Differences in age range and severity of the disease will reported, although the comparative characteristics of the two waves still remain largely unknown. Those characteristics will be compared in this study using data from two equal periods of 3 and a half months. The first period, between 15th March and 30th June, corresponding to the entire first wave, and the second, between 1st July and 15th October, corresponding to part of the second wave. The most frequent signs and symptoms has been be noted. Several differences in mortality risk factors have also been observed. These results might help to understand the characteristics of the second wave and the behaviour and danger of SARS-CoV-2 in India. Further studies are needed to confirm our findings

Swaha yogya hagu oushadiya annabhe krishi (Production technology of edible and medicinal mushrooms)

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