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Capital markets are the backbone of an economy. COVID-19 has created an unacceptable and unpredictable economic environment worldwide, resulting in a significant setback for securities exchanges. India also experienced two waves of this pandemic, which led to a significant downturn in the capital market.

Researchers have endeavored to study the impact of the first and second waves of COVID-19 on the performance of various sectoral stocks in India. The performance of selected sectoral indices of the Bombay Stock Exchange was compared with the market performance of the S&P BSE 100. An event study was conducted to analyze the normal return, abnormal return (A.R.), and t-statistics of A.R. for various sectoral stocks. In addition, the abnormal returns of sectoral stocks between the first and second waves of COVID-19 in India were compared

The results of the tests showed heterogeneous A.R. between different sectors in both the first and second waves of COVID-19 in India. Positive investor outlook and government financial support programs for various sectors helped them recover from the second wave of COVID-19.

The study analyzed the impact of the peak of the first and second waves of COVID-19 on selected sectoral indices. There may be several reasons for the performance of this particular stock index. However, we have tried to analyze the best possible reasons for this turbulence in the performance of stocks of selected sectoral indices. The study can be further analyzed to examine the long-term impact of such a pandemic on other sectors.

The study is based on the panic behavior of investors during such a pandemic. No one was prepared for this and expected this pandemic to last this long. This pandemic has taught so many lessons to everyone involved. Investors need to be prepared and cautious for such unforeseen disasters before making any investment decision. They need to analyze which industry can survive under such circumstances, and then they should invest there. Industries and enterprises must adapt and improve by honestly looking at their weaknesses and trying to meet investors' expectations.

Experiential learning is considered to be a crucial factor in students' perceived learning outcomes. This study aims to explore the development of a mechanism in hospitality education and to analyze the learning outcomes (i.e. perceived quality, perceived value and learning satisfaction) using experiential learning (i.e. previous learning experience and personalized learning environment).

The course design consisted of two activities (instructing and learning activities) and three phases (before, during and after class) using the Moodle version 3.5 online platform as the educational and training site to sustain e-learning archives and activities. A longitudinal survey using a sample of 207 hospitality students in blended e-learning environment indicates positive relationships among the previously mentioned factors.

Results indicated that both previous learning experience and personalized learning environment have positive direct effects on perceived quality and perceived value, while both perceived quality and perceived value have positive direct effects on learning satisfaction. Furthermore, both perceived quality and perceived value mediate the relationship between previous learning experience and learning satisfaction, as well as the relationship between personalized learning environment and learning satisfaction.

These findings sustain the value of experiential learning, particularly the curriculum, student and faculty development in sustainable development education for hospitality.

The purpose of this study is to investigate how proximity to metropolitan areas and local creative talent impact a company’s access to venture capital (VC). We analyze the interplay between these factors and test our hypotheses using USA county data.

This empirical study uses multivariate regression analyses to analyze VC investment distribution across the USA at the county level between the years 1990–2011.

Our findings suggest that an increase in the local creative workforce correlates with higher levels of VC funding, regardless of metro location, but has a more significant impact in metro areas, indicating the complementary nature of these factors. Furthermore, the tech industry benefits more from the local creative workforce and is less sensitive to geographic location. Our results suggest that non-metro locations with a rich local creative culture can be as effective in attracting VC as metro locations with a mediocre local creative culture. This study contributes to our understanding of the optimal geographic location for companies seeking VC.

One of the limitations of our research is the research timeline. Since “creative class” was not measured by the U.S. Department of Agriculture (USDA) after 2011, we cannot analyze the recent effects of creative class on VC. However, given the fact that technology-related industries increasingly dominated the VC industry in recent years, our results on tech-related industries can shed light on the future expectations of the creative class in the VC industry moving forward.

Some companies might find it advantageous to locate outside metro areas where the creative workforce is more abundant and accessible. Our results support this trend by demonstrating that companies must consider the tradeoff between these two factors and recognize that locating in metro areas may not always be the optimal choice for every company. A tradeoff may exist between location and the cost of accessing creative talent.

Our results suggest that non-metro locations with a rich local creative culture can be as effective in attracting VC as metro locations with a mediocre local creative culture.

The existing literature emphasizes the importance of studying various factors that can help distribute VC and entrepreneurial activities across the country instead of just being concentrated in specific areas like metro regions. Although previous studies have examined broader institutional and country-level factors, local creative culture has not been considered in the context of its impact on the geographical distribution of VC. Our research highlights creative culture as a new local factor that affects VC distribution among USA counties.

This study aims to analyze and synthesize literature on consumer privacy-related behavior and intelligent device-to-device interactions within the Internet of Things (IoT).

We conducted a systematic review using Elsevier’s Scopus database, focusing on studies published in English from 2000 to 2023. The review targeted articles within selected social sciences and business disciplines, specifically concerning consumer behavior in IoT contexts.

We categorized the privacy literature into three thematic clusters: legislation and policy, business implications and consumer behavior. Within the consumer behavior cluster, our analysis indicates a shift from general Internet and e-commerce privacy concerns prior to 2016, toward issues related to advertising and policy between 2017 and 2018, and increasingly toward pronounced concerns in technological systems, particularly IoT, from 2019 onwards. We identify eight distinct areas of privacy concern within IoT and propose a framework that links antecedents and privacy concerns to subsequent attitudes and behaviors. This framework highlights varying patterns of information disclosure and bridges theoretical constructs with empirical research in IoT privacy.

Originality lies in enhancing the Antecedents-Privacy Concerns-Outcomes (APCO) macro-model by integrating diverse theoretical perspectives on technological and individual-specific antecedents, alongside privacy concerns and beliefs. This comprehensive integration enriches the framework, enabling it to predict and categorize consumer behavior in IoT environments more effectively. The revised model provides a robust tool for understanding privacy-related behavior within the IoT, significantly enriching its theoretical relevance and practical applicability.