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Consumers get innumerable product options, making it crucial to study their selection among brands vs. new brands. The study explores how in a post-COVID world, the online purchase behavior of Generation Z female consumers is impacted for new-brand beauty products. Using qualitative methods, the authors explored the online purchase behavior of Generation Z females for the purchase of beauty products in emerging economies and how blockchain technology (BCT) can play a crucial role in influencing consumer decision-making. Five focus group discussions were conducted. The study's findings reveal four key themes-"It's too hard to be an innovator," "Online stigma," "New brand reservations," and "BCT and new brands purchase decisions." The authors portray that Generation Z consumers don't feel competent enough to buy new brands online without extrinsic motivation. They do not entirely trust the information marketers provide them in the current form. They are expected to buy new brands online if the authenticity of the complete product details can be verified using blockchain mechanisms.
ABSTRACT
Purpose: The paper explores how consumer behavior for purchasing impulse products changed in the complex and disruptive (emergency) situation of the COVID-19 pandemic when the customer is shopping in-home and not visiting the offline stores in an emerging economy context. This paper further explores how digital transformations like the use of blockchain technology can aid offline/omnichannel retailers in reviving sales via permission marketing for impulse products. Design/methodology/approach: The authors followed a qualitative research design and conducted 24 personal interviews with millennials and 15 interviews with offline/omnichannel retailers from an emerging economy. The data collected were analyzed using the thematic analysis procedure. Findings: The authors discuss their findings under three themes – customers' conscious impulse buying during the pandemic, customers' unconscious impulse buying during the pandemic, and a viable solution for retailers in response to the pandemic. Practical implications: The authors suggest that marketers primarily from an offline/omnichannel store should adapt to permission marketing and use technologies like blockchain for the digital transformation of their marketing strategies. Doing so can help offline retailers minimize future damages in the retail sector during emergency situations. Originality/value: This paper is one of the first that explores how impulse – pure, suggestion, planned and reminder – purchases got affected during the COVID-19 pandemic disruptions in an emerging economy. This paper is also one of the first to explore the role of permission marketing and digital transformation by the use of blockchain in helping offline retailers in forming swift trust and practice trust-based marketing. © 2022, Emerald Publishing Limited.
ABSTRACT
In the COVID-19 situation, face masks have become an essential part of our daily life. As mask occludes most prominent facial characteristics, it brings new challenges to the existing facial recognition systems. This paper presents an idea to consider forehead creases (under surprise facial expression) as a new biometric modality to authenticate mask-wearing faces. The forehead biometrics utilizes the creases and textural skin patterns appearing due to voluntary contraction of the forehead region as features. The proposed framework is an efficient and generalizable deep learning framework for forehead recognition. Face-selfie images are collected using smartphone's frontal camera in an unconstrained environment with various indoor/outdoor realistic environments. Acquired forehead images are first subjected to a segmentation model that results in rectangular Region Of Interest (ROI's). A set of convolutional feature maps are subsequently obtained using a backbone network. The primary embeddings are enriched using a dual attention network (DANet) to induce discriminative feature learning. The attention-empowered embeddings are then optimized using Large Margin Cosine Loss (LMCL) followed by Focal Loss to update weights for inducting robust training and better feature discriminating capabilities. Our system is end-to-end and few-shot;thus, it is very efficient in memory requirements and recognition rate. Besides, we present a forehead image dataset (BITS-IITMandi-ForeheadCreases Images Database1) that has been recorded in two sessions from 247 subjects containing a total of 4,964 selfie-face mask images. To the best of our knowledge, this is the first to date mobile-based forehead dataset and is being made available along with the mobile application in the public domain. The proposed system has achieved high performance results in both closed-set, i.e., CRR of 99.08% and EER of 0.44% and open-set matching, i.e., CRR: 97.84%, EER: 12.40% which justifies the significance of using forehead as a biometric modality.
ABSTRACT
COVID-19 has significantly increased interest in remote working. The phenomenon of this increase was examined in this paper by examining tweets on Twitter by analysis the sentiments of people working remotely. Data were collected by downloading tweets by using keywords “#remoteworking.” The study also explored magazines like HR people matters, HBR, and articles from reputed journals, and by visiting regularly NASSCOM Web site and newspapers. Compiled data are then refined through data mining techniques, and then, sentiment analyses have been deployed. Sentiment index was found greater than one which reflected that people are very happy with having remote working. It was also found that the issue of remote work increased nearly 15 times in a year, reaching an epidemic peak in March 2020. The study has shown that in the post-COVID period it will stay permanently. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Purpose The paper explores how consumer behavior for purchasing impulse products changed in the complex and disruptive (emergency) situation of the COVID-19 pandemic when the customer is shopping in-home and not visiting the offline stores in an emerging economy context. This paper further explores how digital transformations like the use of blockchain technology can aid offline/omnichannel retailers in reviving sales via permission marketing for impulse products. Design/methodology/approach The authors followed a qualitative research design and conducted 24 personal interviews with millennials and 15 interviews with offline/omnichannel retailers from an emerging economy. The data collected were analyzed using the thematic analysis procedure. Findings The authors discuss their findings under three themes - customers' conscious impulse buying during the pandemic, customers' unconscious impulse buying during the pandemic, and a viable solution for retailers in response to the pandemic. Practical implications The authors suggest that marketers primarily from an offline/omnichannel store should adapt to permission marketing and use technologies like blockchain for the digital transformation of their marketing strategies. Doing so can help offline retailers minimize future damages in the retail sector during emergency situations. Originality/value This paper is one of the first that explores how impulse - pure, suggestion, planned and reminder - purchases got affected during the COVID-19 pandemic disruptions in an emerging economy. This paper is also one of the first to explore the role of permission marketing and digital transformation by the use of blockchain in helping offline retailers in forming swift trust and practice trust-based marketing.
ABSTRACT
Not only a particular nation but the whole world today has become victim of global pandemic i.e. Covid-19 or Novel coronavirus. India is also one which is suffering with the same and the resultant of such is nation wide lockdown by the government of India. With the implementation of the lockdown, several organisations and establishments whether they are private or public has been closed. As the period of lockdown has been increased time to time it lead to several consequences such as economic failures disturbing the country's economy. Thus, in this article the author will discuss the covid-19 and employment issues with perspective of labour law and the objective behind such will be whether such issues are lawful or unlawful in the light of provisions of labour law.
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Pregnant women are one of the most important groups who need special attention during this Covid-19 pandemic. Women's physiological changes in the immune system during pregnancy put them and their neonates at increased risk of negative outcomes of COVID-19 infection but the data is still scarce to comment upon. A case of asymptomatic SARS-CoV-2 infected mother and its effect on neonate is reported. This is the first case where the evidence of cytokine storm in neonate has been demonstrated in the presence of transplacental acquired IgG antibodies.
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COVID-19 has been announced as a Global Communal Health Extremity by WHO on January 2020. Meaningful preventive solutions have been taken with smartphone selfie/geofencing apps toward managing mandatory home quarantine and physical distancing. In the post-COVID world, fast screening and strict quarantine can play a crucial role in bringing back normality. Quarantine being offered at home can be a comfortable solution for both government and patients. On the other hand, it can be hazardous if not strictly followed and adequately realized. However, the existing geofencing/face selfie apps take static photographs and location data at certain time intervals that can allow patients to violate the rules between those periods, thus failing to ensure active user identity. To realize unbreached home quarantine policies, this article introduces a CUBA-HQM smartphone app that performs continuous user biometric authentication (CUBA) augmented with geofencing using AI technology. The purpose of continuous tracking is to strictly control the spread of infectious diseases in society by monitoring the individual move in/out in the quarantine zone.
ABSTRACT
COVID-19 is a global catastrophe affecting over 200 nations worldwide. The RT-PCR and antibody based detection assay are considered as a standard diagnostic method and are expensive, time-consuming with low sensitivity (40–80%) making it imperative to look for alternatives. COVID-19 patients display severe lung damage which can be spotted in chest X-ray and CT scan which can be analyzed by computational methods for confirmation of the disease. Apart from above techniques, we have discussed battery of computational intelligence tools like docking, molecular dynamics and quantum mechanics (QM), the novel biosensor based diagnostic tool has been developed. The biosensor involves hybridization of SARS-CoV-2 RNA with cDNA to form RNA (viral)–cDNA (probe) hybrid, with intercalation of transition metal Osmium-Ruthenium (II) redox probe that release electrons. The electrons generated by redox metal measured by respective electrodes and detect even miniscule quantities of viral-RNA in the sample. The computational methods support efficient measurement of interaction of redox probe with viral genetic material and intercalation of the Osmium-Ruthenium (II) redox probe between RNA-cDNA hybrid. The computational docking offers proof of concept with better sensitivity, speed and accuracy, by presenting stronger interaction of RNA–DNA hybrid with Osmium (II) redox probe as compared DNA-DNA hybrid in RT-PCR. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.