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This study examines the use of dark humor in brand-to-brand communications on social media and its impact on consumers' brand perceptions. In particular, this study looks at roasting messages in which a brand humorously insults its peers.

The authors used a sampling method to recruit 286 participants from the United States. They employed an ANOVA and Tukey's post hoc analysis to test the hypotheses, as well as Hayes' PROCESS to test the mediation and moderation effects, including Johnson–Neyman procedure.

The authors found that not all customers find roasting messages funny. Rather, consumers' personality and age will influence their perceived humor of the messages and their brand evaluations. Customers who are young and extroverted are likely to believe roasting messages to be funny. They thus perceive the brand to be cooler and more sincere when using such a communication approach, compared to when the brand neutrally interacts with others. Meanwhile, brands may find less success with old and introverted customers.

This research sheds light on how the consumers' perception of humor in a roasting type of brand-to-brand communication has an impact on consumers' psychological perceptions of brand coolness and brand sincerity. To guide practitioners, it explored how the interaction between a consumer's personality and age moderates the aforementioned relationship.

The uncertainty of getting admission into universities/institutions is one of the global problems in an academic environment. The students are having good marks with highest credential, but they are not sure about getting their admission into universities/institutions. In this research study, the researcher builds a predictive model using Naïve Bayes classifiers – machine learning algorithm to extract and analyze hidden pattern in students’ academic records and their credentials. The main purpose of this research study is to reduce the uncertainty for getting admission into universities/institutions based on their previous credentials and some other essential parameters.

This research study presents a joint venture of Naïve Bayes Classification and Kernel Density Estimations (KDE) to predict the student’s admission into universities or any higher institutions. The researcher collected data from the Kaggle data sets based on grade point average (GPA), graduate record examinations (GRE) and RANK of universities which are essential to take admission in higher education.

The classification model is built on the training data set of students’ examination score such as GPA, GRE, RANK and some other essential features that offered the admission with a predictive accuracy rate 72% and has been experimentally verified. To improve the quality of accuracy, the researcher used the Shapiro–Walk Normality Test and Gaussian distribution on large data sets.

The limitation of this research study is that the developed predictive model is not applicable for getting admission into all courses. The researcher used the limited data attributes such as GRE, GPA and RANK which does not define the admission into all possible courses. It is stated that it is applicable only for student’s admission into universities/institutions, and the researcher used only three attributes of admission parameters, namely, GRE, GPA and RANK.

The researcher used the Naïve Bayes classifiers and KDE machine learning algorithms to develop a predictive model which is more reliable and efficient to classify the admission category (Admitted/Not Admitted) into universities/institutions. During the research study, the researcher found that accuracy performance of the predictive Model 1 and that of predictive Model 2 are very close to each other, with predictive Model 1 having truly predictive and falsely predictive rate of 70.46% and 29.53%, respectively.

Yes, it is having a significant contribution for society; students and parents can get prior information about the possibilities of admission in higher academic institutions and universities.

The classification model can reduce the admission uncertainty and enhance the university’s decision-making capabilities. The significance of this research study is to reduce human intervention for making decisions with respect to the student’s admission into universities or any higher academic institutions, and it demonstrates many universities and higher-level institutions could use this predictive model to improve their admission process without human intervention.

This paper aims to review, systematize and map the extant literature on private equity (PE) and study the underlying research agenda for investment selection and value creation in portfolio firms of PE investors. The PE investment process entails the preinvestment stage, where PE investors screen the target firms, and the postinvestment stage, where PE investors monitor the funded firms. With the motive to understand both stages, this review consolidates the findings of existing literature.

This research adopts a systematic literature review approach to study the underlying themes in PE investment literature. To adequately profile the key research areas, the authors have adopted citation classics in addition to keyword search and drawn the most significant papers in this field of research based on citation metrics.

The review presents a heterogeneous set of themes by encapsulating the relevant PE literature and identifies significant and emergent themes within the broad research area of investment and performance. The foundational themes found are selection determinants for PE investments, value creation in PE investments and selection vs value-adding effect of PE investors. While the emergent themes are the relative performance of PE investments; sources of value creation; skill, luck and social capital in PE; and resource dependency vis-à-vis PE. Each theme or subtheme chalks out the underlying research agendas for future researchers.

To build an understanding of the selection determinants and value creation, this review addresses the need to synthesize and align the PE literature concerning pre and post investment stages. PE is a fertile research area that is systematically captured in this review by identifying themes, subthemes and avenues for future research.

Purpose: This study links SDG goal 9 of industry, innovation strategies and another infrastructural environment to branding relating to destination and interactive marketing. Digital marketing tools with various applications aim to offer hi-tech services to customers in interactive marketing services, namely multiple goods and services, data and innovative techniques in the tourism and travel sector. Exploring the study would add to the existing literature supporting interactive marketing procedures and destination branding. Branding relating to destinations fosters tourists around the globe facilitating economic growth and development and supporting the local economies.

Need for the Study: It is observed from the literature that very few studies have been identified across the globe from various researchers on the interactive marketing and destination branding that ensures brand loyalty and reassesses the intent of the tourists just before the epidemic pandemic in the form of COVID-19. Artificial Intelligence, as part of information technology, offers various interactive marketing services in the form of different social media marketing strategies, attractive websites for tourists and travel providers and image building on destination branding. This study would help fill the marketing gap, which results in branding relating to destination, brand loyalty and reassessing the intent of various tours and travel plans just before the pandemic.

Methodology: The study focused on the literature, demonstrating the stimulus organism methodology and examining the impact of potential marketing strategy, which is interactive focusing on the destination branding, loyalty relating to the brand and also procedures to revert with the intent that would motivate and facilitate the customer’s confidence showering the loyalty relating to the brand in the travel and tourism sector.

Findings and their Practical Implications: The study revealed that the marketing relating to interactive methodologies in the hi-tech digital approaches ought to be carried out to create opportunities for prospective tourists willing to get information about various tourists destinations with the help of various marketing techniques such as different social media applications, easy access of websites for accessing the tourist destinations and relevant information, accessing images pertinent to the tourism destinations with the ease of chat box and providing suitable audios and video sources to the potential customers.

India is the birthplace of four major religions which are Hinduism, Jainism, Buddhism, and Sikhism. It is a country where people of all religions live in peace and harmony. Many tourists experience different forms of harassment during their pilgrimage journey, for example, fleecing, extortion of money, harassment by beggars, persistence by vendors and priests, fraud, sexual harassment, and other unacceptable behaviors. In order to appreciate the extent of harassment encountered by tourists, an in-depth study was conducted on the reviews provided by tourists on TripAdvisor's (Indian) website. This study characterizes harassments through ethnographic research approach of published reviews. A total of 260 reviews of 28 top Hindu temples are considered for all the states and union territories where the top Hindu pilgrim centers are located, (excluding Nagaland) according to TripAdvisor. The concerned reviews are categorized and further investigated through a primary data collection in proportion with the reviews received in respective temple sites in the study. through structural equation modeling (SEM). Important factors have been identified for future policy issues and recommendations in these most crowded places with unique mass tourism practices.

This study aims to understand the effect of cultural dimension (individualism/ collectivism) on promotional rewards (social or economic) resulting in incentivizing consumers to engage in electronic word-of-mouth (eWOM), further impacting their repurchase intentions.

In Study 1, a 2 (culture: individualism vs collectivism) × 2 (promotional rewards: social vs economic) between-subjects design was used. Structural equation modeling was used to test the hypotheses. In Study 2, culture was measured instead of just being manipulated. The authors used regression analysis in this study.

Owing to the characteristics of collectivistic individuals, consumers in collectivistic cultures were more likely to respond to social rewards as an incentive to engage in eWOM. However, consumers in individualistic cultures were more motivated to engage in eWOM when economic rewards were offered.

Despite the global nature of eWOM, little research has explored the effects of cultural traits on consumer response to amplified eWOM strategy. Additionally, though many organizations now offer various promotional incentives to reviewers, little research has explored the effects of promotional offers on a reviewer’s subsequent behavior, and no research has explored the relationship between cultural dimensions and current and future response to promotional eWOM rewards.

Distressed companies create panic among investors. The overall effect comes on the economy and leads to a degraded image and value of all the companies operating in a country. These distressing situations are harmful to the efficient development of a country in process of development. Financial distress (FD) is when a company or individual cannot promise to pay their obligations on time. Therefore, to analyze the threatening impacts of FD, the current study aims to reveal the impact of FD on the debt ratio (proxy of capital structure) of firms working in India.

Panel data analysis (PDA) has been used in the current study to analyze the data and generate novel results. The authors have considered the secondary data of firms present in the S&P BSE 100 index for ten financial years, i.e. 2010 to 2019.

This study has established that FD has no significant impact on the firm's capital structure. In addition, it has also been proved that asset size, learner's index, market capitalization and operating profit margin (OPM) have no interacting impact on the association between FD and the capital mix of firms.

As per the authors’ observation, no such study has been conducted till now that involves finding out the moderating impact of four different but significant factors of the business environment (assets size, learner's index, market capitalization and OPM) on the association between FD and capital structure of companies operating in a such an extensive and diverse economy.

System dynamics has several applications in the built environment, and few studies indicate that it has potential in evaluating sustainability. Sustainability in the built environment involves numerous entities and multiple trade-offs. Hence, a Multi-Criteria Decision-Making (MCDM) method is ideal for promoting sustainability-based decision-making in the built environment. Therefore, this study integrates system dynamics with an MCDM method to enable the sustainability assessment by capturing the time-induced dynamic changes affecting long time sustainability performance of buildings.

Conventional sustainability assessment tools in the built environment lack a comprehensive evaluation that balances the needs of the society, economy and environment. This study develops a system dynamics-based framework to enable sustainability-conscious decision-making and policy analysis in the built environment.

Various material, technology and water-related policies specific to the buildings are investigated for a case study building. It is found that the effect of penetration of renewable energy technology to the tune of 80% and above in the energy mix is a much superior policy in sustainability improvement in comparison to material and water-related policies. The study also demonstrates the effect of weights assigned for the different indicators on sustainability-based decisions.

The study provides a methodological framework for a sustainability-based decision support system for the built environment that enables dynamic performance evaluation by coupling system dynamics with the MCDM. This coupling further strengthens system dynamics as a decision-making and policy analysis for sustainability evaluation in the built environment.

Ensuring adequate access to food to all has remained a major challenge of the 21^st century. To aid the effort of hunger alleviation, many studies have quantified the prevalence of undernourishment (PoU), mostly at the national level. There has been limited attention to understanding the intra-country variation in undernourishment estimates.

Unlike past studies, this study tracks the substantial regional heterogeneity in the undernourishment status within Nepal. Employing Food and Agriculture Organization's methodology and Nepal Living Standards Survey data from 1995, 2003 and 2011, household energy consumption and requirements are computed to determine regional undernourishment.

Nepal's PoU declined between 1995 and 2003 but increased after 2003 affecting approximately 7.6 million Nepalese in 2011. The Terai domain – Provinces 2 and 5 – are found to be the most vulnerable to undernourishment concerns likely because of economic and natural shocks. Province 4 achieved higher progress in alleviating undernourishment during 2003, but its PoU doubled in 2011 (as in Province 6).

By examining where and how many are undernourished within Nepal, this study has provided a more accurate picture of the PoU for better-targeting assistance to improve the livelihood of its citizens.

Past studies indicate substantial variation in food access and PoU within Nepal. While they provide some answers to “where and how many” questions for some districts, provinces, belts and urban/rural domains at the cross-sectional level (or for selected locales), few have examined intra-Nepal heterogeneity, especially over time. Therefore, this study explores where and how many within Nepal have been undernourished during the past three decades.