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The study examines the IPO resilience grounded on the firm’s intrinsic factors.

We examine the association of IPO performance and post-listing firm’s performance with issuers' pre-listing financial and qualitative traits using panel data regression.

IPOs floated in the Indian market from July 2009 to March 31, 2022, evince the notable influence of issuers' pre-IPO fundamentals and legitimacy traits on IPO returns and post-listing earning power. Where the pandemic’s favorable impact is discerned on the post-listing year earning power of the issuer firms, the loss-making issuers appear to be adversely affected by the Covid disruption. Perhaps, the successful listing equipped the issuers with the financial flexibility to combat market challenges vis-à-vis failed issuers deprived of desired IPO proceeds.

High initial returns followed by a declining pattern substantiate the retail investors to be less informed vis-à-vis initial investors, valuers and underwriters, who exit post-listing after profit booking. Investing in the shares of the newly listed ventures post-listing in the secondary market can shield retail investors from the uncertainty losses of being uninformed. The IPO market needs stringent regulations ensuring the verification of the listing valuation, the firm’s credentials and the intent of utilizing IPO proceeds. Healthy development of the IPO market merits reconsidering the listing of ventures with weak fundamentals suspected to withstand the market challenges.

Given the tremendous rise in the new firm venturing into the primary market and the spike in IPOs countering the losses immediately post-opening, the study examines the loss-making and young firms IPOs separately, adding novelty to the study.

This paper aims to review, discuss and synthesize the literature focusing on the Indian initial public offering (IPO) market. Understanding the Indian IPO market can help answer broader corporate finance questions. The growing number of IPOs in the Indian context, coupled with the increasing importance of the Indian economy in the global market, makes this review an essential topic.

The systematic literature review methodology was adopted to review 111 papers published between 2002 and 2021. The authors used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach during the review process. Additionally, the authors use a bibliometric review methodology to examine the pattern and trend of research in this area of interest. Furthermore, the authors conduct a critical review and synthesis of the top 20 papers based on citations. The authors also use a co-citation network and manual content analysis method to identify key research themes.

This review helps in identifying major themes of research in this area of interest. The authors find that majority of the research has focused on IPO performance whereas post-IPO performance needs critical attention as well. The authors develop a comprehensive framework and future research agenda based on their discussion.

Meta-analysis of the literature can be conducted to gain better insights into the findings of prior studies.

This review paper develops a comprehensive overview on Indian IPO market which can be of interest not only to Indian scholarship. India as an economy is increasingly gaining attention at the global level. Hence, the future research objectives as illustrated in the study can be of interest for the global scholarship also.

To the best of the authors’ knowledge, this is the first comprehensive review paper that examines, synthesizes and outlines the future research agenda on Indian IPO studies. This review can be useful for researchers, business policymakers, finance professionals and anyone else interested in the Indian IPO market.

This study aims to focus on assessing the psychometric properties necessary to validate the internal structure of the TOURQUAL scale.

A quantitative research study was conducted in collaboration with the Brazilian Network of Tourism Observatories, comprising 927 respondents surveyed between October 2021 and May 2022. The data analysis involved the application of descriptive statistics and exploratory factor analysis, in alignment with the principles outlined in the Standards for Educational and Psychological Testing 2014 to validate the scale.

The findings of this study validate the TOURQUAL scale as a robust tool for assessing the perceived quality of tourist services, with results demonstrating one-dimensionality and replicability.

To the best of the authors’ knowledge, this study is the first to assess the psychometric properties for validating the internal structure of the TOURQUAL scale.

This paper aims to identify the primary motivations for clothing donations to the immediate social environment. Furthermore, a model that describes the relationship between these motivations, donation tendency and meaning in life is developed and tested.

A mixed method is applied. In the first study, interviews were conducted with 11 people determined with maximum diversity. With the factors that evolved in the first study, a survey method was applied in the second study, and 346 data were collected by convenience sampling.

Individual (independent and interdependent self-construals) and religious motivations for donating clothes to the immediate social surroundings emerge from the interview results. The second study focuses on the relationship between the concept of meaning in life and donation and the possible drivers of donation identified in the first study. A positive relationship was hypothesised between independent self-construal/ intrinsic religiosity/donation tendency and life meaning, as well as between interdependent self-construal and donation tendency. The research results validated all of the hypotheses. The relationship between independent self-construal/intrinsic religiosity and donating behaviour was statistically insignificant.

The current study's findings contain three features that support and enrich previous literature. The first thing is to identify the motivations for the donation tendency. The second issue is considering the meaning of life in terms of its motivations. The final point is to think about donating from a mixed-method perspective. This perspective, in particular, has the potential to provide a comprehensive understanding of the phenomena under discussion.

Climate change poses risks to society and the demand for carbon literacy within small and medium-sized enterprises is increasing. Skills and knowledge are required for organizational greenhouse gas accounting and science-based decisions to help businesses reduce transitional risks. At the University of Copenhagen and the University of Northern British Columbia, two carbon management courses have been developed to respond to this growing need. Using an action-based co-learning model, students and business are paired to quantify and report emissions and develop climate plans and communication strategies.

This paper draws on surveys of businesses that have partnered with the co-learning model, designed to provide insight on carbon reductions and the impacts of co-learning. Data collected from 12 respondents in Denmark and 19 respondents in Canada allow for cross-institutional and international comparison in a Global North context.

Results show that while co-learning for carbon literacy is welcomed, companies identify limitations: time and resources; solution feasibility; governance and reporting structures; and communication methods. Findings reveal a need for extension, both forwards and backwards in time, indicating that the collaborations need to be lengthened and/or intensified. Balancing academic requirements detracts from usability for businesses, and while municipal and national policy and emission targets help generate a general societal understanding of the issue, there is no concrete guidance on how businesses can implement operational changes based on inventory results.

The research brings new knowledge to the field of transitional climate risks and does so with a focus on both small businesses and universities as important co-learning actors in low-carbon transitions. The comparison across geographies and institutions contributes an international solution perspective to climate change mitigation and adaptation strategies.

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

This study aims to develop a model for integration of information and communication technologies (ICTs) in resource sharing practices for enhanced service delivery in academic libraries in Southeast Nigeria. Seven objectives guided the study; ICT-based resource sharing practices in academic libraries in Southeast Nigeria; ICT infrastructure for resource sharing; ICT needs of librarians for resource sharing practices; stages of ICT integration in resource sharing; perception of librarians towards ICT-based resource sharing; challenges to integration of ICT in resource sharing practices; design a model for the integration of ICT into resource sharing; all in academic libraries in Southeast Nigeria.

The research design adopted for this study is the mixed research design containing the “descriptive survey” research design and the “research and development, R&D.” The population of the study is 164, comprising all of the librarians in federal universities in Southeast Nigeria. All of the librarians of the five federal universities will be involved in the study. Hence, there was no sampling. The instrument for data collection is a structured questionnaire.

The findings of the study revealed that 88.8% of the librarians use ICT to boost the volume of resources; while 74% of the librarians were positive in all responses pertaining to ICT-based resource sharing practices in the libraries. The study also revealed that ICT infrastructures in the library for resource sharing are highly available and applicable; while computers and internet networks are the most needed gadgets for the operations. Libraries in Southeast Nigeria are in the applying and transforming stages of ICT adoption at a 69.7% response rate; while the librarians have a strong belief and understanding that a lot can be achieved in resource sharing through ICT; and would recommend such. Poor electrification, inadequate funding and unavailability of some ICT technologies were equally identified as challenges. The study conclusively developed a resource sharing model, the Southeast Federal University Library Connect; accessible at https://southeastfeduniconnect.njh.com.ng

The research study is one of the few types of research that has developed a functional model for resource sharing in academic libraries in Southeast Nigeria.

The purpose of this study is to identify the process of virtual influencer stickiness in the age of influencer marketing, which has received little attention in the literature. This is essential because the research creates a theoretical model of follower loyalty/stickiness to virtual influencer techniques from the standpoint of influencer marketing, which has a substantial effect on the evolution of the global marketing world.

In 2022, 302 people who currently follow an Instafamous virtual influencer took part in an Instagram self-administered online survey.

The findings show that both expertise and trustworthiness have a positive and significant influence on parasocial interaction, which in turn has a significant influence on virtual engagement and stickiness.

This research will specifically assist international readers in understanding how to harness and increase the efficiency and efficacy of interactive marketing strategies and methods to engage and retain followers of Instafamous virtual influencer. Moreover, the findings will be beneficial to opinion leaders, brand managers, company investors, entrepreneurs and service designers.

1. The study pioneers a holistic virtual follower stickiness mechanism that comprises the role of source credibility, parasocial interaction, informational influence and virtual follower’s engagement and their interrelationship to each other.

2. This study is based on parasocial interaction theory and source credibility theory to understand the relationship between virtual followers and influencers stickiness process at social media platforms.

3. In addition, the study examined the subsequent effects of sources of credibility components on parasocial interaction; as well as, on virtual follower engagement and stickiness.

4. This study also categorized and examined the moderating effects exerted by the genres of informative influence of virtual influencer.

The study pioneers a holistic virtual follower stickiness mechanism that comprises the role of source credibility, parasocial interaction, informational influence and virtual follower’s engagement and their interrelationship to each other.

This study is based on parasocial interaction theory and source credibility theory to understand the relationship between virtual followers and influencers stickiness process at social media platforms.

In addition, the study examined the subsequent effects of sources of credibility components on parasocial interaction; as well as, on virtual follower engagement and stickiness.

This study also categorized and examined the moderating effects exerted by the genres of informative influence of virtual influencer.

This study aims to characterize the properties of natural cellulose fiber from the pseudo-stems of the curcuma zedoaria plant.

The fiber was extracted using the biological retting process (cold-water retting). The intrinsic fiber properties obtained were used to evaluate the possibility of using fiber for textile applications.

The average length of a curcuma zedoaria fiber was 34.77 cm with a fineness value of 6.72 Tex. A bundle of curcuma zedoaria fibers was comprised of many elementary fibers. Curcuma zedoaria had an irregular cross-section, with the lumen having a varied oval shape. Curcuma zedoaria fibers had tenacity and elongation value of 3.32 gf/denier and 6.95%, respectively. Curcuma zedoaria fibers had a coefficient of friction value of 0.46. Curcuma zedoaria fibers belong to a hygroscopic fiber type with a moisture regain value of 10.29%.

Extraction and Characterization of Curcuma zedoaria Pseudo-stems Fibers for Textile Application.

Domestic violence is an intimate relationship that causes physical, sexual or mental suffering. The ongoing coronavirus pandemic has had a ruinous effect globally, particularly in increasing the rate of domestic violence. Thus, this study aims to assess the prevalence of domestic violence against women during the COVID-19 pandemic and its associated factors.

A community-based cross-sectional study was conducted on Bench Sheko Zone residents from May to June 2021. Participants in the study were selected by multistage sampling technique. The collected data were coded, entered into EpiData 3.1 and analyzed by using SPSS version 20. Bi-variable and multiple logistic regression analysis models were fitted. Odds ratio was used at a 95% confidence level, and P-value < 0.05 was used to declare statistical significance.

A total of 1,512 eligible women participated, with a 98.3% response rate. The proportion of domestic violence against women was 42.5%. The prevalence of psychological violence was 30.4%, followed by physical violence at 20.2% and sexual violence accounted for 9.6%. Variables, such as rural residency, women with no formal education, partner who had no formal education, women with monthly income of less than 25,00 Ethiopian birr and partner who was current substance user, were found to be associated with domestic violence against women.

Domestic violence against women is still an important public health problem in Ethiopia. Special attention should be paid to identified predictors to reduce domestic violence beyond designing prevention and control strategies along with coronavirus pandemic intervention plan.

The findings of this study show domestic violence against women is still an important public health problem in Ethiopia. Special attention should be paid to identified predictors to reduce domestic violence beyond designing prevention and control strategies, along with the coronavirus pandemic intervention plan.