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The purpose of this study is to assess how the information disclosed in prospectuses impacted the initial public offering (IPO) underpricing at a time of high government interference amid the ongoing pandemic.

The design of this study has several tracks, namely, a macro-level track, which is represented by the government measures to halt the pandemic; a micro-level track, which is followed by textual analysis of IPO prospectuses; and, finally, a machine learning track, in which the authors use state-of-the-art tools to improve their linear regression model.

The authors found that strict government anti-COVID-19 measures indeed contribute to the reduction of the IPO underpricing. Interestingly, the mere fact of such measures taking place is enough to take effect on financial markets, regardless of the resulting efficiency of such measures. At the micro-level, the authors show that prospectus sentiments and their significance differ across prospectus sections. Using linear regression and machine learning models, the authors find robust evidence that such sections as “Risk factors”, “Prospectus summary”, “Financial Information” and “Business” play a crucial role in explaining the underpricing. Their effect is different, namely, it turns out that the more negative “Risk factors” and “Financial Information” sentiment, the higher the resulting underpricing. Conversely, the more positive “Prospectus summary” and “Business” sentiments appear, the lower the resulting underpricing is. In addition, we used machine learning methods. Consisting of more than 580 IPO prospectuses, the study sample required modern and powerful machine learning tools like Isolation Forest for pre-processing or Random Forest Regressor and Light Gradient Boosting Model for modelling purposes, which enabled the authors to gain better results compared to the classic linear regression model.

At the micro level, this study is not confined to 2020, but also embraces 2021, the year of the record number of IPOs held. Moreover, in this paper, these were prospectuses that served as a source of management sentiment. In addition, the authors used a tailor-made government stringency index. At the micro level, basing the study on behavioural finance hypotheses, the authors conducted both separate and holistic analysis of prospectuses to assess investors’ reaction to different aspects of IPO companies as well as to the characteristics of the IPOs themselves. Lastly, the authors introduced a few innovations to the research methodology. Textual analysis was conducted on a corpus of prospectuses included in a study sample. However, the authors did not use pre-trained dictionaries, but instead opted for FLAIR, a modern open-source framework for natural language processing.

This study aims to analyze the causes and implications of legal uncertainty in the issuance of conventional municipal bonds in Indonesia and to draw lessons from Vietnam’s approach in providing better legal certainty.

This study adopts a normative legal method with a legislative approach and applies a comparative approach. Data sources involve primary and secondary legal materials from both Indonesia and Vietnam.

The legal uncertainty is caused by a lack of coherence and consistency in legislation. Based on Vietnam’s experience, Indonesia can gain valuable insights related to providing strong legal certainty for parties involved in issuing or investing through conventional municipal bonds.

This study focuses on the comparative legal analysis of conventional municipal bonds in Indonesia with Vietnam.

This research provides recommendations for the refinement of legislation regarding conventional municipal bonds to the government.

This study is related to legal certainty as a strategy to attract investment through municipal bonds and to ensure the municipal bond issuance process is transparent and efficient.

This study provides a comparative perspective on the issuance of municipal bonds in Indonesia, with a special focus on Vietnam, emphasizing the urgency of harmonization in legal regulation and the sustainability of legal certainty.

The purpose of this study is to propose a world-class good governance ethics framework that leads to better corporate performance. ethics among managers, executives and members of the board of directors working in public-listed companies brings grave concern because of the increasing number of criminal acts reported by the Security Commission of Malaysia.

This study introduces a world-class good governance ethics framework for curbing criminal acts in public-listed companies in Malaysia. This study used a mixed method to gather data, and the methods used are appropriate for answering the research questions based on the World-Class Good Governance Ethics framework.

The finding of this study reveals high expectations for a corporate organization to improve individual and team performance while undertaking their corporate responsibilities, and a matter of choice, to adopt world-class good governance ethics in their policies and practices.

This study could be a reference for corporate management to regulate policies monitoring management's and employees' conduct at the workplace. This study's theoretical and practical significance would guide the stakeholders in corporate management to regulate governance policies based on the right ethical values and promote personalities with high integrity in management conduct.

This study promotes a world-class good governance ethics framework in curbing criminal acts for better corporate performance. This new framework is formulated based on the concept of a caliph and other essential elements envisaged by the Quranic verses.

This paper aims to study the underpricing phenomenon of initial public offerings (IPOs) of 355 Indian companies issued from 2007 to 2019. The research question this paper empirically examines is whether Indian corporate executives deliberately underprice IPOs from its fair value to attract investors, thereby causing an abnormal spike in the prices on the listing day. The findings of this study challenge a commonly held notion of leaving money on the table by IPO issuing companies. Of the overall average listing day returns of 17%, the deliberate premarket underpricing component is found to be mere 5.3%, while the remaining price fluctuation is, inter alia, a result of market momentum along with the unmet demands of impatient investors.

Following Koop and Li (2001), this study uses Stochastic frontier model (SFM) to study a routine anomaly of disparity between the primary market price (i.e. IPO issue price) and the secondary market price (listing price). The jump in the issue price observed on a listing day is decomposed into deliberate premarket underpricing component that reflects the extent of managerial manipulation and the after-market misvaluation component attributable to information asymmetry and prevailing market volatility.

This paper uses SFM to bifurcate initial returns into deliberate underpricing by managers and after-market mispricing by noise traders. This study finds that a significant part of the initial return is explained through after-market mispricing. This study finds that average initial returns are 17%, deliberate premarket underpricing is 5.3% and after-market mispricing averages 11.9%.

This study can isolate underpricing done at the premarket by estimating a systematic one-sided error term that measures the maximum predicted issue price deviation from the offered price. Consequentially, the disaggregation of initial returns may be especially informative for retail investors in planning their exit strategy from an IPO by separating the strength of the firm's fundamentals and its causal relationship with the initial returns. Substantial proportion of after-market mispricing implies that future research should focus on factors causing after-market mispricing. As underlying causes are identified, tailor-made policy responses can be formulated to benefit investors.

This paper has empirically validated that initial return is a mix of both components, i.e. deliberate underpricing and aftermarket mispricing. This disaggregation of initial returns can prove helpful for investors in planning their exit strategy. This study can help investors to become more aware of the importance of the fundamentals of the firm and its causal relation with the initial returns. This information in turn can help reduce the information asymmetry amongst investors and help them lessen the costs of adverse selection.

A large number of research studies on IPO pricing find overwhelming evidence of underpricing in public issues. This research attempts to decompose the extent of underpricing into deliberate underpricing and after-market mispricing, thereby supplementing the existing literature on the IPO pricing puzzle. To the best of the authors’ knowledge, this study is the first contribution to the literature on initial return decomposition for the Indian capital markets.

The objectives of the study were to identify the effects of blockchain technology (BT) on the university librarians, the impact of BT on the university library services and to reveal the challenges to adopt BT in the university libraries.

A systematic literature review was applied to address the objectives of the study. Around 25 studies published in peer-reviewed journals were selected to conduct the study.

The findings of the study revealed that blockchain technology (BT) has positive effects on the university librarians as it assists them in digital resources management, provision of integrated library services, effective records management and continued professional development. The study also displayed that BT has a positive impact on the university libraries through effective information management, user privacy, collaboration, technological innovation and access control. Results also revealed that technical issues, financial constraints, security problems, skill issues and sociocultural issues created challenges to adopt BT in the university libraries.

The study has offered theoretical implications for future investigators through the provision of innovative literature on the prospectus and challenges associated with blockchain in the context of librarianship. The study has also provided practical implications for management bodies by offering recommendations for the successful adoption of blockchain in the university libraries. Additionally, a framework has been developed to adopt BT successfully in the university libraries for the delivery of smart library services to library patrons.

This study investigates the impact of pre-IPO earnings management on investor demand in the Indian IPO market. It also examines whether earnings management by issuer firms affects IPO valuation, a topic that is underexplored in accounting research.

The study uses the data of 310 IPOs from India during the period 2000–2021. The association between pre-IPO earnings management with investor demand and valuation is tested using cross-sectional ordinary least squares regression models with heteroscedasticity-robust standard errors.

The study finds that the degree of pre-IPO earnings management impacts retail investor demand, measured as their over-subscription multiple. Pre-IPO earnings management is unrelated to institutional investor bidding. Further, this paper suggests no relation between pre-IPO earnings management and IPO valuation.

Future studies could explore various other forms of earnings management and their impact on investor demand and valuation.

The findings of this study will help the investors and regulators to understand the practice of earnings management among IPO firms and how it is related to IPO demand and valuation.

This study contributes to the existing literature on IPO-earnings management and investor demand by documenting that issuer firms engage in earnings management to influence investor demand, particularly retail investor demand. Analysis of IPO valuation reveals that earnings management is mostly unrelated to IPO valuation, contrary to the general perception in the literature.

Building on the venture capital (VC) literature, this paper aims to study the impact of the value added by corporate venture capitalists (CVCs) on their funded companies by comparing its IPO valuation with its independent venture capitalists (IVCs) peers.

This study uses a sample of 3,719 VC-backed ventures, between the years 1998 and 2020. The empirical analysis focuses on the propensity score matching approach, pairing ventures based on their probability of being funded by CVCs, and consequently, interpret the results derived from the valuation multiple ratios between the “nearest neighbors.”

This study finds that companies funded by CVCs can achieve higher valuations at their IPO compared to IVC-backed companies. Moreover, CVC-backed companies outperformance is mainly driven by startups which hold a technological fit with their CVC investor, with higher technological overlaps being translated into more significant valuations.

This study presents systematic evidence to the subject concerning ventures’ type of investors and its effect on the startups’ IPO valuations.

This paper contributes to the enrichment of the industry’s literacy while also easing entrepreneurs’ decisions when choosing a funding partner. CVCs offer a variety of services and support that fits the specific needs of their funded companies.

To the best of the authors’ knowledge, this study is among the first to examine the role of CVCs as a tool to help venture growth.

While known by many names, qualifying exams function as gatekeepers to graduate student advancement to PhD candidacy, yet there has been little formal study on best qualifying exam practices particularly in biomedical and related STEM PhD programs. The purpose of this study is to examine the current state of qualifying exams through an examination of the literature and exploration of university-wide policies.

The authors conducted a literature review of studies on qualifying exams and completed an external evaluation of peer institutions’ and internal institutional qualifying exam requirements to inform our discussion of qualifying exams practices in PhD training at a research-intensive US institutions.

This study identified the need for more research on qualifying exams to establish evidence-based best practices. The authors found a wide variety of qualifying exam formats, with little evidence in support for specific formats. The authors also found little evidence that student expectations are made clear. The lack of evidence-based best practices coupled with insufficient clarity for students has a real potential to disadvantage PhD students, particularly first generation, underrepresented minority, international and/or other trainees who are not privileged or socialized to navigate training environments with vague landmarks such as the qualifying exams.

There are very few studies that evaluate qualifying exams in US doctoral education, particularly in STEM fields, and to the authors’ knowledge, there has been no analysis of campus-wide policies on qualifying exams reported. The lack of evidence for best practices and the need for to evaluate the implementation and effectiveness of qualifying exams are discussed.

This study aims to explore credit scoring regulations, governance, variables and methods used by peer-to-peer (P2P) lending platforms in key players of the Association of Southeast Asian Nations (ASEAN) region’s P2P, Indonesia, Malaysia and Singapore.

This study explores the P2P Lending characteristics of the three countries using qualitative literature review, interview, focus group discussion and desk research.

This study concludes that the credit scoring variables used by the countries’ companies are almost the same. Key drivers of the differences are countries’ regulations, management/business core value and credit scoring data processing methods.

Ultimately, this research provides a comprehensive view for investors, businesses and researchers on the topic of ASEAN credit scoring governance and will help them navigate the complexities and improve their awareness on the importance of credit scoring governance in P2P lending companies.

This research provides an in-depth perspective on how P2P lending companies, credit scoring governance and regulations in the biggest three countries in Southeast Asia.