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Public construction authorities need to evaluate the level of competition in the submitted bids for a certain project before awarding the contract. A lack of adequate competition is a reason for rejecting all bids and reissuing an invitation to bid for the project. This paper aims to present an analysis of the adequacy of competition in public construction projects.

The paper uses five competition indicators to correlate the level of competition effect obtained with the number of contractors competing for the project. The analysis is based on the bid opening results for 917 public construction projects in Jordan that include 6,309 bids, with an average number of 6.88 bids per project.

The results illustrate that there is an improvement in the competition effect over the five analyzed competition indicators as the number of bidders increases. However, the rate of improvement decreases with the increase in bidders. The empirical analysis performed does not support the proposition that an optimum number of bidders exists in competitive bidding for construction projects or the proposition that a higher number of bidders may lead to higher bid prices. However, the indicators developed in this study found that at least 5 bidders are recommended and after 8 bidders, the rate of improvement continues at much slower rate.

The current research presented a multifaceted method for assessing the minimum number of bidders needed to ensure a competitive bidding process. Moreover, the research used actual data from 917 public projects.

A critical factor to the success of IPOs is investor demand, which can be observed from the IPO subscription pattern. Therefore, the objective of this study is to review the studies on the demand of IPOs, including empirical and theoretical literature, due to the substantial growth of IPOs over the last two decades.

This study extracted secondary data regarding IPO demand published from 1988 to 2022 from the Scopus database. We conducted a meta-literature review for qualitative and quantitative methods on the resulting 284 articles using citation analysis (Harzing’s Publish or Perish and VOS viewer software) and content analysis.

The findings revealed significant elements of the literature, including countries, institutions, journals, authors, articles and topics. Based on the IPO literature review and analyses, this paper developed future research questions to facilitate an extension of the research. Additionally, this paper developed a dual perspective of the present state of IPO research. First, it asserts that the demand for IPOs is not limited to certain countries, jurisdictions or vintages. Second, there are very few studies on demand for IPOs available despite IPOs’ economic worth.

To the best of the authors’ knowledge, this is the first study of its kind to present an empirical evaluation of demand for IPOs using inclusive mapping.

Empirical examinations of initial public offering (IPO) initial returns often rely heavily on linear regression models. However, these models can prove inefficient owing to their susceptibility to outliers, a common occurrence in IPO data. This study introduces a machine learning method, known as random forest, to address issues that linear regression may struggle to resolve.

The study’s sample comprises 352 fixed-priced IPOs from the year 2004 until 2021. A unique aspect of this research is its application of the random forest method. The accuracy of random forest in comparison to other methods is evaluated. The findings indicate that the random forest model significantly outperforms other methods in all of the evaluated aspects.

The variable importance measure indicates that investors’ demand, divergence of opinion among investors and offer price are the most crucial predictors of IPO initial returns. These determinants hold particular significance due to the widespread use of the fixed-price method in Malaysia, as this method amplifies the information asymmetry in the IPO market.

To the best of the authors’ knowledge, this study is among the pioneering works in Malaysian literature to apply the random forest method to address the constraints of conventional linear regression models. This is achieved by considering a more extensive array of factors and acknowledging the influence of outliers. Additionally, this study adds value to Malaysian literature by ranking and identifying the ex-ante information that best signals the issuing firm’s quality. This contribution facilitates prospective investors’ decision-making processes and provides issuing firms with effective means to communicate their value and quality to the IPO market.

This study aims to investigate the impact of facial-based perceived trustworthiness on stock valuation, particularly, in the initial public offering (IPO). IPO settings provide the opportunity to investigate whether information asymmetry resulting from company newness in the market would influence the incorporation of soft information in the form of executive facial trustworthiness in stock valuation.

We use a recent machine learning algorithm to detect facial landmarks and then calculate a composite facial trustworthiness measure using several facial features that have previously been observed in neuroscience and psychological studies to be the most determining factor of perceived trustworthiness. We then regress the facial trustworthiness of IPO firm executives to IPO underpricing.

Utilizing machine learning algorithms, we find that the facial trustworthiness of the company executive negatively impacts the extent of IPO underpricing. This result implies that investors incorporate the facial trustworthiness of company executives into stock valuation. The IPO underpricing also shows that the cost of equity is higher when perceived trustworthiness is low. With regard to the higher information asymmetry in IPO transactions, such a negative impact implies the role of facial trustworthiness in alleviating information asymmetry.

This study provides evidence of the impact of top management personal characteristics on firms’ financial transactions in the Indonesian context. From the perspective of investors and other fund providers, this study shows evidence that heuristics still play an important role in financial decision-making. This is also an indication of investor reliance on soft information. Our research method also provides a new opportunity for the use of machine-learning algorithms in processing non-conventional types of data in finance research, which is still relatively rare in emerging markets like Indonesia. To the best of our knowledge, our study is the first to use personalized measures of trust generated through machine-learning algorithms in IPO settings in Indonesia.

This study aims to outline the research field of initial public offerings (IPOs) pricing and performance by combining bibliometric analysis with a systematic literature review process.

The study uses over three decades of IPO publication records (1989–2020) from Scopus and Web of Science databases. An analysis of keyword co-occurrence and bibliometric coupling was used to gain insights into the evolution of IPO literature.

The study categorized the IPO research field into four primary clusters: IPO pricing and short-run behaviour, IPO performance and influence of intermediaries, venture capital financing and top management and political affiliations and litigation risks. The results offer a framework for delineating research advancements at different stages of IPOs and illustrate the growing interest of researchers in IPOs in recent years. The study identified future research potential in the areas of corporate governance, earning management and investor sentiments related to IPO performance. Similarly, the study highlighted the opportunity to test multiple theoretical frameworks on alternative investment platforms (SME IPO platforms) operating under distinct regulatory environments.

To the best of the authors’ knowledge, this paper represents the first instance of using both bibliometric and systematic review to quantitatively and qualitatively review the articles published in the area of IPO pricing and performance from 1989 to 2020.

Initial Public Offering (IPO) is a major milestone for a company. It allows a private company to issue shares to a much broader group of investors and become public. But conclusive evidence of the driving forces behind investors’ demand is yet to be identified. Therefore, the major purpose of this study is to assess the level of investors’ demand in IPO and how investors’ demand in IPOs is affected.

The study will employ 80 IPO companies of a Muslim-majority country, Bangladesh, starting from 2013 to 2021 with application of linear and quantile regressions. Apart from that, t-test will be used to compare means of groups of Shariah-compliant and non-Shariah-compliant firms and IPOs under fixed-price and book-building mechanism.

Oversubscription is higher for IPOs issued through fixed-price method compared to book-building method, but no significant difference is found in oversubscription for Shariah firms compared to non-Shariah firms based on t-tests. The authors found IPO size, firm size, IPO risk, proportion of shares offered to public, and bank interest rate to have significant impact on the IPO demand. Some models found non-Shariah compliance status of IPO companies to be a significant factor for the investors to demand IPO. Quantile regression results found board independence to have a positive association with larger, less-subscribed firms and board size to have a negative relation with IPO demand, for smaller firms with high demand.

Future studies may apply the findings to other settings, especially into the reasons behind preference for non-Shariah-compliant firms and higher demand for IPOs during higher interest rate. Equity issuing firms and issue managers can benefit from this study by wisely deciding on the proportion of shares for public, issue size and board of director composition. Shariah considerations cannot be ignored given that more information on Shariah compliance is disseminated among investors despite current non-preference for Shariah-compliant IPOs. On the other hand, institutional investors and general investors should consider firm-specific, governance and macroeconomic factors in IPO investment. Likewise, regulators would do well to bring in quality IPOs with characteristics mentioned in this study for ensuring stability of the market.

The main contribution of the study is identifying determinants of IPO demand: faith, governance, macro issues – understanding whether one or many of the above factors drive investor demand in IPOs of a Muslim-majority country will be the main contribution.

This study aims to examine the potential of Sharia status as ex ante information to signal the quality of an issuing firm by improving the decision-making process of potential investors when assessing initial public offerings (IPOs) in an environment where information asymmetry is pronounced. Potential investors face challenges in evaluating and determining the true value of IPO issues, which inherently influences their decision-making. Consequently, this results in pronounced price fluctuations in IPO shares, leading to higher underpricing.

This study uses a sample of 350 IPOs listed on the Kuala Lumpur Stock Exchange (KLSE) between 2004 and 2021 to examine the signaling role of Sharia-compliance status. A three-model approach is used to ensure that the study's objectives are met. The first model investigates the effect of Sharia status on underpricing to determine whether the main beneficiary of such a signal is the investor or the issuer. The second model examines the effect of Sharia status on investor demand to determine if such a signal influences prospective investors' investment decision-making processes. The third model inspects the effect of Sharia status on investor divergence of beliefs to measure the signal's ability to reduce information asymmetry within the Malaysian IPO market.

The Malaysian IPO market relies heavily on the fixed-price mechanism, which exacerbates high information asymmetry, affecting potential investors' behavior, asset price formation and return generation on the first day of listing. The study results indicate that Sharia status does not have any signaling role in the Malaysian IPO market. This is because investors in the Malaysian market are driven by ex ante information that helps unveil relevant information that leads to capital gains. Furthermore, most new issues in the Malaysian IPO market fall under Sharia status, diluting the relevance of such information for prospective investors in determining profitable investments.

The findings highlight the challenges faced by issuing firms in estimating market demand due to limited premarket insights and the difficulties prospective investors face in identifying the quality of issuing firms. Efforts to provide more information on investor demand can reduce uncertainty and facilitate more informed decision-making.

This research stands as one of the pioneering efforts to provide an empirical explanation of the potential signaling influence of Sharia status in an emerging IPO market.

The purpose of this paper is to analyse five biases in the valuation of financial investments using a mental time travel framework involving thought investments – with no objective time passing.

An investment’s initial value, together with any periodic funding cash-flows, are mentally projected forward (at an expected rate of return) to give the value at the investment horizon; and this projected value is mentally discounted back to the present. If there is a difference between the initial and present values, then this can imply a bias in valuation.

The study identifies (and gives examples of) five real-world valuation biases: biased funding cash-flow estimates (e.g., mega infrastructure projects); biased rate of return projections (e.g., market crises, tech stock carve-outs); biased discount rate estimates (e.g., dual-listed shares, dual-class shares, short-termism, time-risk misperception, and long-termism); time-duration misestimation or perception bias when projecting (e.g., time-contracted projections which lead to short-termism); and time-duration misestimation or perception bias when discounting (e.g., time-extended discounting which also leads to short-termism). More than one bias can be operating at the same time and we give an example of low levels of retirement savings being the result of the biased discounting of biased projections. Finally, we consider the effects of the different biases of different agents operating simultaneously.

The paper examines key systematic misestimation and psychological biases underlying financial investment valuation pricing anomalies.

Given the coincidental and sustained rise in house prices and foreign capital flows in Kenya, this study aims to understand whether a long-run relationship exists between real diaspora remittances and real house prices.

This study uses data from 2004-Q1 to 2020-Q4 and applies an autoregressive distributed lag model for estimation.

The results indicate that a positive and significant relationship exists between real remittances and real house prices in Kenya in the long run.

To the best of the authors’ knowledge, there is no study exploring the relationship between real remittance inflows and house prices in Kenya, after controlling for other key macroeconomic determinants of house prices. This study addresses this research gap.

This paper explores the drivers and inhibitors of the transition of entrepreneurial family firms from small to large firms. We adopt two contrasting theoretical perspectives, i.e. agency and stewardship, to explore the effects of family power on size transition.

We adopted an original research design that leverages a unique longitudinal database built starting from the list of the 500 best Italian manufacturing family firms published by the AUB Monitor in 2018. Specifically, we tested our hypotheses using a comprehensive set of financial and governance data from 89 Italian manufacturing family firms covering a 10-year period. To test our hypotheses, we conducted a survival analysis using a Cox regression.

We find an inverted U-shaped relationship between family involvement in ownership and size transition: size transition is more likely to happen at intermediate levels of family involvement in ownership. Additionally, our analysis shows that family involvement in the board of directors negatively impacts size transition, while the presence of a family CEO has a positive influence.

To the best of our knowledge, this study represents the first exploration of the phenomenon of size transition within entrepreneurial family firms. We believe it was worthwhile for two reasons. First, small size is frequently regarded as a weakness when competing in international markets, investing in R&D, or rewarding shareholders. Second, since small family firms are the major contributors to the world economy, understanding the factors that facilitate their transition to large firms can have a significant impact on overall economic development and prosperity.