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Awarding contracts based solely on the lowest price is unsuitable for every project. Consequently, most procurement systems in developed countries have progressed to the multicriteria selection practices (MSPs) for tender evaluation. MSPs consider a range of quality measures, such as completion time, life cycle cost, functional characteristics, environmental impact and innovation, alongside bid price. This study examines the prevailing MSPs in Sri Lankan public tender evaluations to enhance the effectiveness of the local tender evaluation process.

A desk study approach was employed to collect bidding documents, resulting in the identification of 66 documents. A systematic screening process was then applied to identify those bidding documents that incorporated MSPs. Subsequently, content analysis was conducted to determine the common features of the functions used in MSPs.

The study identified six primary functions related to MSPs incorporated in the bidding documents to procure building and substation projects. Three functions follow the price-to-quality method, while the remaining three follow the quality-to-price method. Among these identified functions, four functions employ objective evaluation criteria, such as thickness, capacity and operational loss. The other two functions utilize subjective evaluation criteria, such as the project’s design and technical specifications. Contract awarding will be based on either the highest score or the lowest bid, depending on the function type.

This study’s originality lies in exploring MSPs in the Sri Lankan public tender evaluation process and in disclosing their characteristics to promote the MSPs in Sri Lanka and developing countries.

This chapter discusses the evolution of online trading, its application in various market structures, and its benefits and potential concerns. Computers were first used in electronic communication networks among brokers and dealers to make trades and for informational purposes. Online brokers became popular with retail investors as the internet spread. Online trading comes with various trading protocols and order types. It enables traders to automate trading decisions and process data more easily using charting tools and customized programs connected to the broker's infrastructure. Electronic trading allows for greater centralization but can also be accompanied by market fragmentation. Market regulation has affected market structure and is still evolving. Centralization allows for more competitive prices and reduces search costs. Decentralized markets could cope better with asymmetric information.

This study aims to provide empirical evidence on the impact of foreign share ownership on the liquidity of the Tunisian Stock Exchange (TSE).

The authors hypothesize in the first strand that stock liquidity could be positively affected by foreign ownership based on the real friction channel. The authors then hypothesize in the second strand, based on the information friction channel, that foreign ownership's impact on stock liquidity could be insignificant or negative and that foreign investors raise the level of information asymmetry. A sample of 318 firm-year observations from Tunisia over the 2012–2017 period and a random-effects estimation were used. Moreover, using the 2SLS estimator, a robustness check framework was applied in order to address any potential reverse causality concerns.

The authors find strong evidence that higher foreign ownership improves stock liquidity. More specifically, firms with higher foreign ownership engender a lower bid-ask spread, a better stock ability to absorb a large amount of trading volume, and a larger depth. These findings are still valid when reverse causality concerns are addressed through the use of the 2SLS estimator.

The paper contributes to the existing literature by focusing on the ownership–liquidity relationship on a frontier market. It provides further empirical support that higher corporate governance quality reduces the information asymmetry problem and enhances stock market liquidity.

This study aims to investigate the effects of IFRS convergence on market liquidity and to analyze the firm-level heterogeneity in liquidity effects based on reporting incentive, firm size, ownership structure and firm leverage.

The empirical analysis is based on firm-fixed effect regression using several proxies of market liquidity as dependent variables. The sample consists of 337 firms listed on the National Stock Exchange (NSE) who shifted to IFRS from the financial year 2016–2017.

The empirical findings indicate that IFRS convergence has contributed to the significant increase in market liquidity in a weaker enforcement country, i.e. India. Additionally, when the study performs the heterogeneity test of IFRS impact, the results indicate the presence of significant cross-sectional differences in such liquidity effects across firms. Thus, altogether the findings suggest that both accounting convergence and firm-level factors are likely to be the mechanism underlying the observed improvement in market liquidity.

In the current literature, there is an ongoing debate about whether the observed post-IFRS effects are driven by the change in accounting standard per se or by other related factors. Therefore, by studying the liquidity effects of IFRS convergence in India, this study provides evidence regarding the sources of the documented IFRS effects. Moreover, the study indicates the significance of firm-level factors in determining the observed liquidity outcomes around IFRS adoption, which is unique to the literature.

This paper examines data protection related ex ante transaction costs borne by the private sector in the context of smart city service (SCS) public tendering in the European Union after the introduction of the General Data Protection Regulation. This study aims to establish the determinants of ex ante transaction costs related to data protection as well as to determine their relevance toward (tender) competition.

A statistical analysis of a survey sample of 72 SCS tender bids.

The potential of relationship management to foster more private sector investment in data protection for SCSs is established, i.e. stronger ties between parties lead to higher private sector investment. Furthermore, it is found that investing more in data protection can further boost both internal capabilities and the organizational reputation of tendering organizations. Finally, the analysis exposes a potential problem concerning the market for data protection originating from the dominant approach concerning SCS tender bid evaluation.

SCS tender bid evaluation is not perceived by the evaluated companies as having data protection as a (core) component. As a consequence, there is no strong competition in that specific area. To induce the private sector to structurally develop SCSs that can be expected to safeguard the fundamental rights of citizens, a more thorough evaluation of data protection aspects of bids imposes itself. Such an overhaul is likely to demand additional public sector resources and expertise.

This paper constitutes an early investigation into data protection related ex ante transaction costs borne by private sector actors. Incentives for data protection investment in the context of public procurement procedures are discussed.

The history of online trading began in the 1960s with the emergence of electronic communication networks, which allowed the electronic execution of trades outside traditional exchanges. The internet revolution led to the development of online brokerage platforms such as E*Trade and Schwab, enabling non-institutional investors to participate in the digital trading revolution. These platforms have evolved to serve the retail investor market, eventually adapting to mobile-first and commission-free models, significantly lowering the barriers to entry for financial markets. Platforms like Robinhood and other fintech firms have rapidly gained market share by offering services and products previously unavailable, such as commission-free trades, mobile trading, and novel products such as fractional shares and cryptocurrency investing. This chapter provides an overview of the history of online trading. It also introduces several new developments in fintech and the online trading industry and discusses various controversies and future implications of new technologies.

The authors examine the role of stock liquidity in CEO equity compensation design. For a sample of publicly traded firms from 2007 to 2020, the authors find that greater stock liquidity is associated with a higher proportion of stock awards relative to the proportion of options in CEO equity compensation. The results of this study suggest that stock price informativeness on the grant date has a differential effect on the preference for the type of equity compensation awarded to CEOs. The empirical results are supported by multivariate analyses using alternative measures of stock liquidity and a two-stage least squares (2SLS) specification that alleviates endogeneity concerns. Furthermore, the authors document that the firm-specific increase in the proportion of stock awards compared to the proportion of stock options is associated with a firm-specific increase in stock liquidity. Collectively, the analyses suggest that stock liquidity as a measure of stock price informativeness contributes to the choice of CEO equity compensation design.

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.