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This paper examines whether family control exerts any influence on corporate cash holdings in Indian listed firms. It also examines how this accumulated cash of family firms impacts firm value.

The study uses dynamic panel data regression estimated using two-step system generalized method of moments (GMM) on S&P BSE 500 firms during 2009–2018 for testing the repercussions of family control on the cash levels of a firm. Further, fixed effects regression has been employed for the valuation analysis.

Estimation results showed that family control negatively impacts cash holdings in Indian firms. Further, the cash accumulation by family firms adversely affects the market valuation of the firm. These findings signal a principal–principal (P-P) agency conflict in Indian family firms, i.e. friction between family owners and minority shareholders' interests. Minority shareholders fear that a part of the cash reserves will be used by family members for personal benefits. Thus, they discount cash reserves in family firms.

The study adds to the determinants of corporate cash holdings in emerging markets. To the best of the authors’ knowledge, this is the first study from India investigating family control as a determinant of cash policy. It sheds light on the P-P agency conflict in Indian family firms. P-P agency conflict is less researched in cash holdings literature as opposed to the principal–agent managerial disputes. Also, the study uses a more comprehensive definition of family control rather than just considering the ownership as used in prior cash holding research.

Introduction: The insurance sector provides security to society by pooling resources to manage risks. Insurers’ improved ability to analyse risks by examining vast amounts of granular data has considerably refined this technique. Compiling and analysing the fine data sets is now transformed into the ‘Big Data’ technique. The introduction of big data analytics (BDA) is transforming the insurance industry and the role data plays in insurance.

Purpose: This chapter will attempt to examine the applications and role of big data in the insurance sector and how big data affects the different insurance segments like health insurance, property and casualty, and travel insurance. This chapter will also describe the disruptive impact of big data on the insurance market.

Methodology: Systematic research is carried out by analysing case studies and literature studies, emphasising how BDA is revolutionary for the insurance market. For this purpose, various articles and studies on BDA in the insurance market are selected and studied.

Findings: The execution of big data is continuously increasing in the insurance sector. The performance of big data in the insurance market results in cost reduction, better access to insurance services, and more fraud detection that benefits the customers and stakeholders. Therefore, big data has revolutionised the insurance market and assisted insurers in targeting customers more precisely.

The purpose of this paper is to explore the extent of corruption in India, Fiji and Ethiopia and survey citizen perception of how e‐governance could fight corruption. The main objective is to investigate and explore the potential of e‐governance applications in three countries representing three different regions of Asia, Africa, and Oceania.

A survey was conducted over 918 citizens in India, Ethiopia and Fiji using convenience random sampling. A structured questionnaire was used. The main emphasis of the survey was on citizen perception about corruption and poor service. It further asked respondents on how e‐governance can cut corruption.

Benefits of e‐governance in developing countries are the same as those in developed countries but there are many potential benefits that remain unreaped by developing countries as a consequence of their unlimited use of e‐governance. Based on these assertions, the researchers tried to evaluate and assess the potential of e‐governance initiatives in India, Ethiopia and Fiji. By exploring the role of e‐governance for reducing corruption that has afflicted the entire public sector in these countries, the main finding is that e‐governance is positively related to government, “citizen relationship and corruption reduction”.

This study is highly empirical and does not provide case studies to further extend on the findings.

The implications of the research are that information communication technology (ICT) needs to be effectively integrated in the development agenda of government plans in Ethiopia and Fiji. Government agencies in Ethiopia and Fiji do not seem to be much motivated to build sound government‐citizen partnerships. Citizens can see little of the internal workings of government. However, for India, where there are many e‐governance projects underway, and which is normally considered to be awakening to the challenges of e‐governance and which has to date many success stories relating to e‐governance, it is surprising to see that citizens find various existent formats of corruption and non‐transparent service delivery activities. It is quite evident that bureaucracy is more or less opaque and very little attention has been paid to improving transparency, including through the use of e‐governance processes. Time, cost and red‐tape procedures are major constraints in public service delivery.

The paper explores a problem that is of practical importance using principal‐agent theory, which is very applicable to the public sector context.

Introduction: Big data is that disruptive force that affects businesses, industries, and the economy. In 2021, insurance analytics will include more than simply analysing statistics. According to current trends, new insurance big data analytics (BDA) methods will enable firms to do more with their data. The insurance business has traditionally been conservative, but adopting new technology is no longer only a current trend; it must be competitive. Big data technologies aid in processing a huge amount of data, improve workflow efficiency, and lower operating costs.

Purpose: Some of the most recent developments in big data for insurance and how insurers may use the information to stay ahead of their competitors are discussed in this chapter. This chapter’s prime purpose is to analyse how artificial intelligence (AI), blockchain, and mobile technology change the outlook and working of the insurance sector.

Methodology: To achieve our research purpose, we analyse case studies and literature that emphasise how BDA revolutionises the insurance market. For this purpose, various articles and studies on BDA in the insurance market will be selected and studied.

Findings: From the analysis, we find that the use of big data in the insurance business is growing. The development of BDA has proven to be a game-changing technology in insurance, with a slew of benefits. The insurance sector is now grappling with the risks and opportunities that modern technology presents. Big data offers opportunities that every company must avail of. We can safely argue that big data has transformed the insurance sector for the better. The BDA’s consequences have enabled insurers to target clients more accurately. This chapter highlights that new tools and technologies of big data in the insurance market are increasing. AI is emerging as a powerful technology that can alter the entire insurance value stream. The transmission of any type of digital proof for underwriting, including the use of digital health data, might be a blockchain use case (electronic health record (EHR)). As digital forensics becomes easier to include in underwriting, it must expect price and product design changes in the future. In the future, the internet of things (IoT) and AI will combine to automate insurance processes, causing our sector to transform dramatically. We highlight that these technologies transformed insurance practices and revolutionalised the insurance market.

Over the years, public sector reforms in emerging economies have focused on improving national budget systems and financial management practices to promote sustainable development. In the context of the COVID-19 crisis, this article examines whether the strength or effectiveness of national budget systems and related financial management practices moderates the impact of fiscal policy measures on economic recovery and resilience.

The article uses bivariate correlations and difference-in-difference analyses to examine the relationship between budget system effectiveness, government stimulus measures and forecasts of economic recovery and resilience. The analysis uses data from the Public Expenditure and Financial Accountability (PEFA) program, International Monetary Fund (IMF) and World Bank.

The article finds that estimates of economic recovery and resilience are higher in countries with more reliable budget processes and more transparent public finances. Also, the strength or effectiveness of the budget system before the pandemic appears to moderate the impact of government stimulus measures on economic recovery and resilience over a medium-term forecast horizon.

This is a prospective analysis based on economic forecasts from the IMF, which are subject to change in the coming years. In addition, the analysis uses subjective budget system indicators, which present measurement challenges that often influence this area of research. Better comparative data in the future, for example, large administrative datasets, will enable researchers to explore these issues with less estimation bias.

The findings are relevant for policymakers and budget officials in developing countries in Africa who are engaged in plans to improve national budget systems and enhance resilience to crises, such as the COVID-19-induced economic crisis. The findings also have implications for developing countries beyond Africa with similar economic and fiscal conditions.

The findings have implications for economic and budgetary planning for the social sector as well as the efficient delivery of public services in developing countries. Public managers have a critical role to play in adapting national budget systems and financial management reforms within complex and evolving economic circumstances even after the coronavirus pandemic.

The authors use novel and latest data on country responses to the COVID-19 pandemic as well as medium-term economic forecasts to examine the relationship between national budget systems and post-pandemic economic recovery and resilience in the African context. Previous research has only addressed these issues in the context of industrialized countries, and a limited number of empirical studies examine these relationships. The findings also have significant value for policymakers outside Africa who are facing similar challenges related to the coronavirus pandemic.

This study aims to extend Bowman's risk–return paradox to Asian emerging markets and explain its causes under the prospect theory.

The study is conducted on a cross-sectional sample of 4,609 firms across nine Asian emerging countries. The two stage least squares (2SLS) estimation technique is used to evaluate the three objectives of the study, i.e. Bowman's risk–return paradox, significance of firm-specific risk and prospect theory explanation of Bowman's paradox.

The authors challenge the two basic financial economics arguments that higher risk is rewarded with higher return, and firm-specific risk is diversifiable. The empirical findings confirm the negative impact of firm-specific and systematic risk on firm return, thus, corroborates the Bowman's explanation of risk–return trade-off. However, the authors did not find empirical evidence to support prospect theory's explanations of Bowman’s paradox in Asian emerging markets.

A holistic approach is adopted to analyze the various aspects of Bowman's paradox and its causes for the same time period, variables and sample. The authors also rectified several methodological limitations observed in previous studies, i.e. the use of same proxies for firm return and risk, endogeneity and survivorship issues. Furthermore, the findings of this study will enable managers to formulate critical viewpoint on firm-specific risk and systematic risk and take informed strategic decisions regarding optimum utilization of their firm's key resources in Asian emerging markets.

This paper aims to investigate the effect of metaphor “Digital India-Power to Empower” on citizens’ intention to adopt the e-governance while taking citizens’ attitude and emotional attachment with Digital India as mediating variables between citizens’ involvement and intention to adopt e-governance.

After reviewing the extant literature and using the learning from Technology Acceptance Model-Extension (TAME), a conceptual model has been proposed. The model is empirically tested on 224 respondents from India using structural equation modeling technique.

The paper suggested that the metaphoric promotion of E-Governance leads to a higher intention to adopt E-Governance. Metaphoric promotion has a positive influence on citizen involvement with E-Governance, which leads to positive attitude toward E-Governance. This positive attitude leads to citizens’ emotional attachment with E-Governance, which in turn leads to citizens’ positive behavioral intention to adopt E-Governance. In addition, there is a significant difference in attitude toward E-Governance with respect to education level and metro city dwelling, but there is no difference in intention to adopt E-Governance with respect to education and metro city dwelling.

As there is a dearth of research on the usage of metaphor by government and its effect on citizens’ adoption of E-Governance, a conceptual model has been prepared by using learning from metaphor studies majorly in non-government services.

As marketing and metaphors are rarely spoken words in E-Governance research, present study starts the much-needed conversation. In the past, adoption of E-Governance is studied in terms of technology attributes using TAM Model. The present study is first to explore the behavioral impact of E-Governance metaphoric promotion on citizens’ intention to adopt E-Governance based on TAME model. It raises the issue of marketing foundation of E-Governance in mobilizing the citizens’ intention to adopt the E-Governance.

This study examines the effects of comparable companies, within the same industry, on cash-holding (CH) levels of a specific firm in the Stock Exchange of Thailand (SET). Peer effects are hypothesized to affect a firm's average CH levels.

The authors use data of listed firms in the Thai stock markets from 1995 to 2018. The sample consists of 5,277 firm-year observations. The authors perform robustness tests by incorporating gross domestic product, economy and competitiveness.

Peer firms' CH levels correspond positively to the specific firm's CH. This strengthens further for firms with high cash flow volatility during periods of high competition. Unfavorable economic periods also motivate the association between a firm's CH and peer firms' CH.

A policy on CH should account for cash held by peer firms. Firms can justify their CH policy as compatible with peers' cash flows, especially during periods of competitiveness and an unfavorable economy.

The authors provide novel evidence on how emerging markets' CH levels differ from those in developed markets and propose adjusted explanations for the rivalry- and information-based theories. The findings add substantial knowledge to corporate finance by arguing that CH policies are based on peer firms' strategic moves.

This chapter focuses on performance measurement and management systems (PMMS) in the inter-municipal cooperation context by considering the development of new capabilities required to exploit the digital governance potentialities in which data integration is essential. The analysis relied on the advent of digital governance, the Italian public informative systems reform, as well as on local governments (LG) renewals through the Union of Municipalities (UMs) – one of the most widespread structured forms of inter-municipal cooperation – based on the sustainability of local service delivery. Through a review of the literature and the conceptual outcomes resulting from the analysis of the dynamic capabilities (DCs) theory applied to digital governance, this chapter aims at suggesting a useful contribution for an effective improvement of PMMS in the public sector networks, with the consequent improvement of resilience in policy management. Thus, the broad information required by the UMs and the complexity of its administration together with the constraints regarding the need to share a common vision and strategy, plan objectives, targets, measurement, and evaluation processes are considered. In particular, three propositions have been developed as guidelines for achieving coordination, coherence, and integration of measuring and managing performances in public networks. This evidence will offer insights allowing scholars and practitioners a practical understanding of whether and how DCs – applied to digital governance – address PMMS challenges within an inter-municipal cooperative context.