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The purpose of this paper is to demonstrate how offering control on data usage and offering money can increase willingness to share private information with a data broker.

Personal data are collected for internet users with a Web questionnaire. In an experimental framework, compensations control money are manipulated and consumers’ data sharing is explained by sensitivity and regulatory focus.

Offering control increases willingness to disclose personal data, even sensitive one, but the effect is not moderated by regulatory focus. Offering monetary compensation has a negative, but small, effect on willingness to share personal data, and the effect is moderated by regulatory focus.

Offering a large amount of money is a double-edged offer, as it creates a signal that increases potential negative effect of disclosing personal data to unknown third party.

The purpose of this paper is to determine the status, drivers, and barriers to data governance at the health professional regulatory authorities in Kenya. This study aims to develop a model that can be used to establish a formal data governance program at these regulatory authorities.

This study used data governance decision areas based on the study of Khatri and Brown (2010). Qualitative and quantitative research methods were used in this study to collect data.

This paper identified maintenance of quality of data, achieving customer satisfaction, ensuring data security and control, and achieving operational efficiency as the drivers of data governance at the regulatory authorities. The authorities are faced with lack of data governance awareness, lack of management ownership and support, as well as limited funding and resource allocations as barriers to data governance. This study proposed that for the authorities to increase their data governance, they need to identify their data as an asset, initiate more data quality management mechanism, restrict access to their data, create awareness, and increase management, ownership and support.

A data governance program for healthcare workforce data is necessary for healthcare planning which influences national policy in the healthcare and the overall delivery of health services in a country.

The paper proposes a model that health professional regulators in developing countries that are facing limited resources can be used to establish a formal data governance program.

Financial crime presents a serious threat to the stability and integrity of the global financial system. To combat illicit financial activities, regulatory bodies worldwide have implemented various measures, including the requirement for financial institutions to assess the financial crime risks they are exposed to in the jurisdictions they operate in. These risks include inadequate anti-money laundering and countering the financing of terrorism frameworks and other financial crime risks that have significant strategic implications for firms’ geographical footprints and customer risk classifications. This paper aims to make a contribution to the literature by undertaking a cross-country analysis of 158 countries to shed light on what drives perceived jurisdiction risk of the UK financial services firms.

Capturing firms’ perceptions of financial crime risk requires significant data collection efforts, including surveys and interviews with key personnel. This can be highly resource-intensive and may require access to sensitive information that firms may be reluctant to share. Furthermore, the dynamic nature of financial crime risks means that perceptions can change rapidly in response to changes in the regulatory and geopolitical landscape. As a result, capturing and monitoring firms’ perceptions of financial crime risks requires ongoing monitoring and analysis. Capturing firms’ perceptions of financial crime risks at a cross-jurisdictional level is a particularly complex and challenging task that requires careful consideration of a range of factors. As a result of data limitations, empirical investigation of the factors underlying the firms’ perceptions of jurisdiction risk is in its infancy. This paper uses regulatory financial crime data from the UK in a multivariate regression analysis, following a general-to-specific approach where any redundant variables were removed from the general model sequentially.

Results suggest that perceived jurisdiction risk is significantly and positively associated with evasion of tax and regulations, while it is significantly and negatively associated with political stability and regulatory stringency. These have important implications for home and host supervisors with respect to the factors that drive perceived jurisdiction risks and the evaluation of the nature of inherent financial crime risks within regulated firms. The findings confirm the critical role of the shadow economy, political stability and regulatory rigor in shaping jurisdiction risk perceptions. From a policy standpoint, the findings support the case for taking prompt policy action to identify, prioritize and implement specific and targeted measures with respect to the shadow economy, political stability and rigor of regulations to improve international firms’ perceptions of jurisdiction risk.

While there exists different measures of financial crime risk, it is notoriously challenging to capture firms’ perceptions of it, particularly at a cross-jurisdiction level. This is because financial crime risks can vary significantly across different jurisdictions due to differences in legal and regulatory frameworks, cultural norms and levels of economic development. This makes it difficult for firms to compare and evaluate the financial crime risks they face in different jurisdictions. Besides, firms’ perceptions of financial crime risks can be influenced by a range of subjective factors, including personal experiences, media coverage and hearsay. These perceptions may not always align with objective risk assessments, which are based on more systematic and empirical methods of risk measurement. This paper contributes to the existing literature by undertaking a cross-country analysis drawing on a unique set of UK regulatory financial crime data, which is based on a total of 1,900 annual financial crime data regulatory return (REP-CRIM) submissions to the UK’s Financial Conduct Authority.

Machine learning is having a major impact on banking, law and other organisations. The speed with which this technology is developing to undertake tasks that are not only complex and technical but also time-consuming and that are subject to constantly changing parameters is astounding. The purpose of this paper is to explore the extent to which machine learning can be used as a solution to lighten the compliance and regulatory burden on charitable organisations in the UK; so that they can comply with their regulatory duties and develop a coherent and streamlined action plan in relation to technological investment.

The subject is approached through the analysis of data, literature and domestic and international regulation. The first part of the study summarises the extent of current regulatory obligations faced by charities, these are then, in the second part, set against the potential technological solutions provided by machine learning as of July 2021.

It is suggested that charities can use machine learning as a smart technological solution to ease the regulatory burden they face in a growing and impactful sector.

The work is original because it is the first to specifically explore how machine learning as a technological advance can assist charities in meeting the regulatory compliance challenge.

Purpose – The purpose of this paper is to show that the effects of industry regulation on worker earnings are reconsidered using a wider array of industries and differentiating between industry‐opposed and industry‐supported legislation. Design/methodology/approach – Primary data from the Current Population Surveys are used in this paper with data on regulatory legislation from Cahan and Kaempfer. A difference‐in‐difference approach is used to compare wage changes pre‐ and post‐legislation, in industries with opposed or supported legislation, with those unaffected by legislation. The relative contribution of union and non‐union wage changes to the overall wage changes are also examined. Findings – The paper finds that regulatory legislation opposed by the industry did not affect earnings growth relative to industries not subject to regulatory legislation. Legislation supported by the industry led to slower relative earnings growth. Union wage differentials increased in industries with legislation regardless of industry opposition or support. Relative earnings declined among non‐union workers in industries that received legislation. The effects vary across industries with the results suggesting that some legislation led to increased product competition, while some legislation affected labor market competition. Research limitations/implications – The paper shows that data on regulatory legislation are limited by the lack of detailed information. For example, it is only known whether legislation was passed that was opposed or supported by the industry. Future research should replicate this analysis with more complete data. Practical implications – Also the paper sees that regulatory legislation does not need to completely regulate or deregulate an industry to affect workers. As such, policy makers should consider the effects of proposed legislation on workers in the affected industries. Originality/value – This paper directly tests whether the wage effects from regulation differ depending on industry opposition or support for the legislation. As such, this paper is innovative because it differentiates between different types of legislation in examining the effect of legislation on wages and the union differentials.

This study aims to examine the impact of regulation and other micro- and macro-economic factors on banks’ productivity growth. It investigates the impact of different regulatory reforms on banks’ performance of total factor productivity (TFP) and its component efficiencies, along with their association with bank-specific variables of profitability and equity, and with macro-level variables of economy and freedom. That is, through analysing the influence of regulatory and supervisory policies related to Basel accords pillars of capital and market discipline through private monitoring; restrictions on bank activities; and economic and financial freedoms on TFP growth and year-end performance in banking.

The authors examine TFP for commercial banks in response to regulatory reforms on an international scale. To estimate the TFP, the authors use a non-parametric frontier technique by calculating the Malmquist output-oriented index, following Delis et al. (2011) and Worthington (1999). The components of the Malmquist index are ratios of distance functions making its estimation a straightforward technique using activity analysis or data envelopment analysis methods. This allows controlling for efficiency changes depending on the reallocation of production frontiers signalling the technical change and the technical efficiency at once.

Results show that high capital requirements enhance productivity growth in North and Latin American banks, but not in European African or Asian banks. Supervisory powers drive bank productivity growth in all regions except Europe and Central Asia. Restrictions on real estate, insurance and securities activities impede productivity change in all income level groups but not in high-income economies. The results also show that market volatility and Z-score drive technological change and scale efficiency growth, but negatively impact pure technical efficiency.

This paper contributes to the literature by examining the relationship between the implementation of regulatory standards and the performance of the banking sector following a structural model of the banking firm and the concept of optimisation. An additional contribution of this study is that it examines economies with different levels of income based on the gross national income per capita. The study summarises bank-specific data used to synthesise the banks’ productivity (inputs and outputs) and country-specific economic and regulatory compliance data over 19 years (1999-2017). The extent of this data set coverage makes it most recent and most conclusive of variables to provide a significant contribution to the literature on bank regulation and efficiency effect.

Post 1991, given the advent of liberalization and economic reforms, the Indian telecom sector witnessed a remarkable growth in terms of subscriber base and reduced competitive tariff among the service providers. The purpose of this paper is to estimate the impact of regulatory announcements on systemic risk among the Indian telecom firms.

This study employed a two-step methodology to measure the impact of regulatory announcements on systemic risk. In the first step, CAPM along with the Kalman filter was used to estimate the daily β (systemic risk). In the second step, event study methodology was used to assess the impact of regulatory announcements on daily β derived from the first step.

The results of this study indicate that regulatory announcements did impact systemic risk among telecom firms. The study also found that regulatory announcements either increased or decreased systemic risk, depending upon the type of regulatory announcements. Further, this study estimated the market-perceived regulatory risk premiums for individual telecom firms.

The regulatory risk premium was either positive or negative, depending upon the different types of regulatory announcements for the telecom sector firms. Thus, this study contributes to the theory of literature by testing the buffering hypothesis in the context of Indian telecom firms.

The study findings will be useful for investors and policy-makers to estimate the regulatory risk premium as and when there is an anticipated regulatory announcement in the Indian telecom sector.

This is one of the first research studies in exploring regulatory risk among the Indian telecom firms. The research findings indicate that regulatory risk does exist in the telecom firms of India.

In this paper, the authors examine the association between the banking regulatory regime and the quality of bank earnings. We further investigate whether the banking agency regulatory characteristics moderate the association between banking regulation and earnings quality.

Using panel data spanning 29 years over the period 1991 to 2019, the authors model bank earnings quality as a function of scores for banking regulation for 170 banks in the East African region using both the feasible generalized least squares (FGLS) and generalized method of moments (GMM) estimation methods.

The results, which are robust for endogeneity among other checks, reveal a positive impact of bank regulatory mechanisms on the quality of bank earnings. The authors further establish differential impact of specific regulatory mechanisms, with some contributing positively toward earnings management while others contributing negatively toward earnings management. The differential impacts of banking regulation on earnings quality are also manifested in the country-level analyses.

First, the study utilises a mix of bank-specific, country-specific as well as economy-specific variables in one dataset. Second, the authors utilise survey-based data using the World Bank's Bank Regulation and Supervision Surveys (BRSS) for the periods 1999 to 2019. The authors assume that the bank regulatory mechanisms in place pre-1999 are close to the mechanisms in place as per the 1999 BRSS. Given limitations in data availability, the authors are not able to control for banks engaging in multiple activities such as insurance, underwriting of securities, FinTechs, among others.

The results are useful in bridging the gap between theory and practice regarding the expected effect of strict banking regulations on the quality of earnings in Eastern African Banks. For the positive impact of banking regulation on bank earnings quality to be felt, the institutional, social and environmental specificities of the five selected countries need to be adequately developed and taken into consideration.

This study is perhaps the first to utilise a large dataset of commercial banks from countries in a developing region characterised by relatively lower enforcement and dynamism in the banking regulation. Further, in-depth studies on the association between banking regulation and earnings quality remain sparse.

The near‐collapse of the world's financial system in 2008 brought into focus significant limitations in the data and analysis tools available to mitigate potential risks across the financial system. It has raised calls to provide comprehensive data and adequate tools to identify and relieve systemic risk. In this paper, an infrastructure is proposed to address the need for a new information system in systemic regulation.

The proposed infrastructure is developed using the Fed's Bank Holding Company Supervision Manual as a guideline. The model uses a data fusion approach that allows integration of inspection data, external data, and other regulatory data of different granularity. A proprietary application known as Decision Making Toolbox (DMT) is being developed with three‐tier architecture.

The integrated all‐in‐one approach will enhance the efficiency, scope, and quality of studies applied to systemic regulation and will facilitate easy decision making for effective regulation.

This concept integrates data and measures that are needed for systemic regulation. It facilitates easy decision making, by regulators with an integrated all‐in‐one information infrastructure, for effective regulation.

In spite of the extensive literature on the regulation of air transport services, until the development of the Quantitative Air Services Agreements Review (QUASAR) methodology no systematic review existed of the degree of liberalization granted through air services agreements. The chapter lays out QUASARs key features, and presents the main results its application has generated. It then elaborates on how the methodology could be further refined and extended to other segments of the air transport industry yet uncovered. Based on QUASAR, the chapter critically evaluates some commonly held beliefs about the liberalization of international passenger transport and then moves on to explore the technical feasibility of creating a liberal multilateral regime for air transport services. QUASAR has demonstrated that, although the air transport sector has experienced some liberalization over the past few years, this has been, overall, rather marginal. The skies are not truly open.