Impact of movie-watching on cross-selling revenue in shopping malls: Implications for post-pandemic recovery

The COVID-19 pandemic has prompted consumers to postpone in-store purchases and shift to online shopping, decreasing overall retail spending. As the global lockdown eases and shoppers return to offline stores and malls, shopping malls seek to facilitate in-store consumer experiences at entertainment facilities. Given the importance of entertainment facilities to the cross-selling revenue of shopping malls, we investigate the relationship between consumers' movie-watching and subsequent (hedonistic) grocery purchases. Our analysis of a panel database that includes transaction details at the consumer level shows that movie-watching is negatively correlated with consumer spending. Furthermore, consumers' psychological states induced by content and contextual factors moderate the negative effect of movie-watching;after watching a fantasy (as compared to thriller) genre or watching a movie in a less crowded theater, consumers are more likely to make hedonic purchases at the supermarket. These findings provide theoretical and managerial implications for retail operators exploring cross-selling opportunities post-pandemic. © 2023

Comparison of the performance properties of spunlaid non-woven fabrics used as face mask

Face masks have an effect of preventing the spread of infectious diseases such as coronavirus disease 2019 (COVID-19). With these masks, it is primarily aimed to prevent the environment from being contaminated by the user. However, in the COVID-19 outbreak, many countries made it mandatory to use masks in areas with high human circulation such as marketplaces, shopping malls and hospitals, and then in all areas outside the home. Some tests such as filtration efficiency, microbial load, resistance to body fluids, flammability and breathability are performed to determine the protection potential and wearing comfort of face masks. In this study, we investigated the bacterial filtration efficiency (%), microbial load (cfu/g), breathability (Pa/cm2) and air permeability values of five different face masks obtained by combining polypropylene (PP) nonwoven layers in different weights (accordance with EN 14683:2019 + AC:2019, EN ISO 11737-1:2018 and TS 391 EN ISO 9237 Standards). The surface morphologies of the nonwoven fabrics were characterized by scanning electron microscope (SEM). It was observed that the weight change in spunbond masks (1–4) was directly proportional to bacterial filtration efficiency and differential pressure, and inversely proportional to air permeability. In addition, SEM analysis showed that the average fiber diameter of the meltblown layer was at least 5.80 times smaller than the spunbond layers, and as a result, dramatic differences were also observed in the air permeability and differential pressure values of the Spunbond-Meltblown-Spunbond (SMS) mask (5) compared to spunbond masks.

A Conceptual Framework for Post Lockdown Digital Marketing Strategy for Malls for developing Loyalty and e-Word of Mouth

Loyalty programs are often used by industry sector in different modes. Visits to shopping malls were based on entertainment, shopping and also to avail different services. Experiences of the prolong lockdown has redefined people's perspective towards public places such as malls. The Covid-19 pandemic inculcated people to behave with prudence while shopping by trading off between available options after the lockdown and isolated themselves from public places. In this context, shopping malls may use loyalty programs to attract consumers along memorable experiences. Contradiction to normal days, loyalty to shopping malls have declined during the Covid 19. Hence, this study proposed a novel conceptual framework for post lockdown digital marketing strategy for malls for developing loyalty and e-word of mouth to benefit entrepreneurs and customers. © 2021 IEEE.

Influencing Factors on Consumer's Perception: On-site to OnlineDuring Covid-19 Pandemic in Thailand

The midst of Covid-19, Thailand has been hit with lock down on the department stores. The government announce lockdown along with the uncertain situations of the Covid-19 pandemic have caused both business and consumer change their shopping behavior. This situation has been affecting the urban lifestyle among consumers who enjoys going to department store. The objective of this study is to investigate the influencing factors that affect the consumer's perception on visiting the department store. The statistical analysis on factor analysis was conducted with 400 questionnaires. The questionnaires focus on the decision on the decision of the consumer's consumption during Covid-19. This study aims to investigate 4 factors which are services of the mall, consumers' satisfactions, Modernization of the shopping malls, and public relations of the shopping mall. The results finding suggest that social media online has significant influent factor to the consumer' s perception on their decision of department store services.This research can assist business in adapting to the new uncertainty situation of pandemic.

A Research on The Effect of Covıd-19 on Consumer Habits: Turkey-Libya Comparison

The COVID-19 pandemic appears to have profound effects on all countries. Shopping centers, which are the areas most affected by the epidemic, have started to lose their former importance. It is known that there are significant changes in the behavioral tendencies and attitudes of consumers. Identifying these changes in the behavior of consumers, who have an important role in shopping center organizations, has become a necessity for shopping centers to regain their former importance. The study was carried out to determine the change in attitudes of people visiting shopping malls during the COVID-19 epidemic. To determine the attitudes of consumers in Turkey and Libya towards shopping malls and to question the changes, data were collected with a total of 600 people using the online survey technique. Then, the differences in the attitudes of male and female participants were questioned by using an independent sample t-test in the SPSS 22 program. As a result of the test, it was determined that there were significant differences (p<0.005) between the attitudes of female participants in Turkey and male participants in Libya. In the study, it was concluded that there are more changes in the attitudes of female consumers compared to men, especially in Turkey, and that there is no significant difference between male and female consumers in Libya as in Turkey. (English) [ FROM AUTHOR] COVID-19 pandemisinin bütün ülkeler üzerinde derin etkileri olduğu görülmektedir. Salgından en çok etkilenen alanlar olan alışveriş merkezleri ise artık eski önemlerini kaybetmeye başlamıştır. Tüketicilerin davranış eğilimleri ve tutumlarında da önemli değişimlerin olduğu bilinmektedir. Alışveriş merkezi organizasyonları üzerinde önemli bir role sahip olan tüketicilerin davranışlarındaki bu değişimlerin tespit edilmesi alışveriş merkezlerinin tekrar eski önemlerini kazanmaları açısından bir gereklilik haline gelmiştir. Çalışma alışveriş merkezlerini ziyaret eden kişilerin COVID-19 salgını süresince tutumlarında oluşan değişimi tespit etmek amacıyla gerçekleştirilmiştir. Türkiye ve Libya'daki tüketicilerin alışveriş merkezlerine karşı olan tutumlarını tespit etmek ve değişimleri sorgulamak amacıyla toplamda 600 kişiyle çevrimiçi anket tekniği kullanılarak veriler toplanmıştır. Daha sonra kadın ve erkek katılımcıların tutumlarındaki farklılıklar SPSS 22 programında bağımsız örneklem t-testi yapılarak sorgulanmıştır. Test sonucunda Türkiye'deki kadın katılımcıların ve Libya'daki erkek katılımcıların tutumları arasında önemli farklılıklar (p<0,005) olduğu tespit edilmiştir. Çalışmada özellikle Türkiye'de kadın tüketicilerin erkeklere oranla tutumlarındaki değişimlerin daha fazla olduğu, Libya'daki kadın ve erkek tüketicilerde ise Türkiye'de olduğu kadar belirgin bir farklılık olmadığı sonuçlarına ulaşılmıştır. (Turkish) [ FROM AUTHOR] Copyright of Eastern Geographical Review is the property of Eastern Geographical Review and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Implementation of Algorithm of People Counting and Blob Analysis Using OpenCv and Python

For the last few months, the world is suffering from epidemic COVID-19. It is found that till all people are vaccinated, we all must take the precautionary measures of using hand sanitizers, face masks and the most important is following social distancing. Computer vision technology can play a vital role in this crucial scenario. The advanced video processing algorithms provide fast computational capability, provides a possibility to use video tracking and counting people in real-time. The adoption of this measure not only serves as a crisis plan for pandemic but also provides a range of benefits in long term. In this paper, we propose an algorithm that analyzes a video sequence detects people to yield frequency of people along the direction of path traversal which can be implemented in the open-access building such as malls, airports, shopping centers, etc. It can be easily integrated into already existing systems if there are already installed surveillance cameras. The result obtained can be used for purpose of statistics in the circumstances of any calamity occurrence for the rescue team to take relevant measures to rescue the people. This paper gives the solution using blob analysis using Open-CV and python.

Automated Inspection of Face Mask and Social Distancing Using Artificial Intelligence

According to the data obtained by the World Health Organization, COVID-19, and the global pandemic has severely impacted the world and infected more than hundreds of million people worldwide which includes more than three million deaths. This global pandemic enforced governments across the world to impose lockdowns in order to prevent the virus transmissions. Reports indicate that wearing face masks and following safe social distancing are two of the enhanced safety protocols need to be followed in public places in order to prevent the spread of the virus. To ensure the public safety in environment, we propose an efficient Computer Vision based approach that focused on the real-time automated monitoring of people to detect both safe social distancing and face masks in public places by implementing the model to monitor the activity and detect violations through camera. After detection of breach, the system sends to control center at state police headquarters and also give alarm to public. In this proposed system, modern deep neural network based model have been mixed with geometric techniques for building a robust model which covers three aspects of detection, tracking, and validation. Thus, the proposed system helps the society in saving time and reducing the spread of corona virus. It could be practiced effectively in current situation when lockdown is eased to inspect persons in public gatherings, shopping malls, etc. Automated inspection reduces manpower to inspect the public and can be used in any place to ensure safety.