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The purpose of this study is to review the capital budgeting literature over the past decade.

Specifically, over the years 2004–2013, we review works appearing in the major academic journals in accounting, finance, and management. Further, we review the specialized academic journals in management accounting. We examine the frequency of articles by journal and year published, the type of research method applied, and the topic area studied. We then review the research findings by topic area.

We find 110 articles appearing in the selected journals. While the articles increase in frequency, the research methods applied are predominantly analytical and archival in nature with relatively few experiments, case studies, or surveys. Some progress is observed for capital budgeting techniques and new methods for structuring uncertainty. The studies find that the size of capital budgets is about right for companies with high financial reporting quality, for liquid companies, during periods of normal cash flow, when the budget is financed by equity, for companies when they first go public or first go private. Tax rates and financial reporting methods for depreciation and tax expenses distort capital budgets. Organization structure and performance measurement can distort capital budgeting. Individual differences, especially optimism and honesty, can influence capital budgeting decisions.

This review is limited to the major journals in accounting, finance, and management; and the specialized journals in management accounting. There is much research to be done on capital budgeting, especially case studies of actual practice and experiments related to individual and group decision processes.

This chapter addresses social embeddedness effects on ex ante management of economic transactions. We focus on dyadic embeddedness, that is the history of prior transactions between business partners and the anticipation of future transactions. Ex ante management through, for example, contractual arrangements is costly but mitigates risks associated with the transaction, such as risks from strategic and opportunistic behavior. Dyadic embeddedness can reduce such risks and, hence, the need for ex ante management by, for instance, making reciprocity and conditional cooperation feasible. The chapter presents a novel theoretical model generating dyadic embeddedness effects, together with effects of transaction characteristics and management costs. We stress the interaction of the history of prior transactions and expectations of future business. Hypotheses are tested using new and primary data from an extensive survey of more than 900 purchases of information technology (IT) products (hard- and software) by almost 800 small- and medium-sized enterprises (SMEs). Results support, in particular, the hypotheses on effects of dyadic embeddedness.

The global Islamic financial landscape is changing with rapid advances in technology. The increasingly tech-savvy demography is presenting both opportunities and challenges to the industry. With the advances in e-finance and mobile technologies, financial technology (Fintech) innovations emerged by combining the e-finance, Internet, social networking services, social media, artificial intelligence (AI) and big data analytics. Fintech promises to reshape the Islamic financial landscape by improving processes’ efficiencies, cost-effectiveness, increased distribution, Sharīʿah compliance and financial inclusion. As far as the Islamic fund management industry is concerned, AI seems to be the keyword. Islamic fund managers have recently started to incorporate AI and big data analytics into their strategy in the process of making accurate decisions based on facts and figures, which eliminates any biases and personal intuition. This disruption in status quo is raising new issues, new concerns and new exciting opportunities. While disruption may carry negative connotations, the industry players have been embracing the innovation and potential revolution the technology could offer. Thus, the objective of this chapter is to discuss legal aspects of Fintech and its impact on the Islamic fund management industry in Malaysia. This chapter introduces a historical overview of Fintech and its evolution in the Islamic fund management industry. This chapter further provides an overview of the legal and regulatory aspects of Fintech with regards to the industry. Finally, legal issues and challenges are identified and discussed. Being a legal research, this chapter adopts a qualitative method by analysing the relevant literatures on the subject. This chapter is expected to provide an insight into the application of Fintech and its impact on the Islamic fund management industry in Malaysia.

This study empirically examines how firms manage real options over time in the context of the U.S. venture capital industry. It tracks the venture-capital funding histories of U.S. portfolio companies founded during 1989–1993, and their outcomes, until 2004. An examination of sequential investments suggests asymmetries in the management of successful and unsuccessful companies. Signals of a company's progress, such as the number of its patents, are significant predictors of VC investment practices in the case of successful companies, but not in the case of unsuccessful companies. In contrast, VC firm characteristics, such as experience in the company's industry, IPO experience, and geographic proximity, appear to explain variance in investment policies for unsuccessful companies, but not successful ones. This suggests that signals of progress are relatively easier to interpret when real options perform well over time, and investors can perhaps apply them equally effectively. In contrast, signals of failure are more ambiguous and complex; and firm-level differences are more pronounced in the management of unsuccessful options.

This paper focuses on the potential advantages of strategic investment models in examining firm investment behavior. Strategic investment models are derived from rigorous modeling techniques grounded on formal analytical models, and they have been widely applied in corporate finance and economics to examine the problem of firm underinvestment. In this paper, we present an overview of strategic investment models, including empirical applications that highlight their methodological strengths. We conclude that the empirical application of such investment models in the context of strategic management research presents research opportunities in many new directions.

The goal of this paper is to develop a model which may be used to demonstrate costs and benefits of risk management investments in the context of value-based management.

This paper answers the question of how to quantify changes in company value caused by risk management measures on a theoretical basis. First, a review of empirical studies allowing assertions about the cost and utility of risk management investments is presented. The results of these studies point to a nonlinear shape of the curve and form a basis for the development of a seemingly plausible cost/utility correlation.

In this paper, a model will be developed which can be used to demonstrate costs and benefits of risk management investments in the context of value-based management. It is assumed that at first, risk management expenditures without measurable monetary utility will have to be made. Furthermore, it is assumed to increase more than proportionally, then less than proportionally, until further investments in risk management activities yield only minimal increases in utility and cannot improve company value any further.

By inserting the yet-to-be-determined actual cost/benefit relationship for a company or industry sector into the EVA equation, it is possible to display the effects of risk management measures on the company value. This procedure is principally combinable with the analysis of other value-based control parameters, that is, the Discounted Cash Flow concept or the Cash Value Added methodology.

Risk management is increasingly gaining scientific and public interest, especially since the global financial crisis. Scientists and practical users espouse the benefits of risk management systems in this context. However, the extent to which investments in risk management systems can improve the value of a company remains still unclear.

We could determine that at first risk management expenditures will not result in a monetarily measurable benefit. The remaining slope of the curve is derived as increasing more than proportionally at first, then less than proportionally, until further investments into risk management activities yield almost no additional increase in benefits. In this paper, three different functions are offered to describe the shape of the curve identified. They differ in regard to their free parameters and hence in their flexibility of application. The higher flexibility of functions #2 and #3 is balanced by the disadvantage of increasing formal complexity, possibly leading to an increased effort for implementation and application.

To harness the relationships developed in this paper for practical use, further research should target the identification and empirical verification of dependencies between the parameters and principal company index values.

In the build-up of an investment decision, the existence of both active and passive investment vehicles triggers a puzzle for investors. Indeed the confrontation between active and index replication equity funds in terms of risk-adjusted performance and alpha generation has been a bone of contention since the inception of these investment structures. Accordingly, the objective of this chapter is to distinctly underscore whether an investor should be concerned in choosing between active and diverse passive investment structures.

The survivorship bias-free dataset consists of 776 equity funds which are domiciled either in America or Europe, and are likewise exposed to the equity markets of the same regions. In addition to geographical segmentation, equity funds are also categorised by structure and management type, specifically actively managed mutual funds, index mutual funds and passive exchange traded funds (‘ETFs’). This classification leads to the analysis of monthly net asset values (‘NAV’) of 12 distinct equally weighted portfolios, with a time horizon ranging from January 2004 to December 2014. Accordingly, the risk-adjusted performance of the equally weighted equity funds’ portfolios is examined by the application of mainstream single-factor and multi-factor asset pricing models namely Capital Asset Pricing Model (Fama, 1968; Fama & Macbeth, 1973; Lintner, 1965; Mossin, 1966; Sharpe, 1964; Treynor, 1961), Fama French Three-Factor (1993) and Carhart Four-Factor (1997).

Solely examination of monthly NAVs for a 10-year horizon suggests that active management is equivalent to index replication in terms of risk-adjusted returns. This prompts investors to be neutral gross of fees, yet when considering all transaction costs it is a distinct story. The relatively heftier fees charged by active management, predominantly initial fees, appear to revoke any outperformance in excess of the market portfolio, ensuing in a Fool’s Errand Hypothesis. Moreover, both active and index mutual funds’ performance may indeed be lower if financial advisors or distributors of equity funds charge additional fees over and above the fund houses’ expense ratios, putting the latter investment vehicles at a significant handicap vis-à-vis passive low-cost ETFs. This chapter urges investors to concentrate on expense ratios and other transaction costs rather than solely past returns, by accessing the cheapest available vehicle for each investment objective. Put simply, the general investor should retreat from portfolio management and instead access the market portfolio using low-cost index replication structures via an execution-only approach.

The battle among actively managed and index replication equity funds in terms of risk-adjusted performance and alpha generation has been a grey area since the inception of mutual funds. The interest in the subject constantly lightens up as fresh instruments infiltrate financial markets. Indeed the mutual fund puzzle (Gruber, 1996) together with the enhanced growth of ETFs has again rejuvenated the active versus passive debate, making it worth a detailed analysis especially for the benefit of investors who confront a dilemma in choosing between the two management styles.

Purpose – Institutional investors need to move beyond first- and second-generation interpretations of Corporate Social Responsibility (CSR) and Socially Responsible Investment (SRI) (based on negative filters), and also beyond third and fourth generations (based on positive and integrated filters), which are more sophisticated but still limited, and toward a fifth generation of SRI and CSR. A fifth-generation model systematically incorporates critical intangibles, such as human capital analysis, into the Environmental, Social, and Governance (ESG) investment process.

Methodology – This chapter incorporates a literature review and draws on a range of qualitative research and case studies on the current and potential role of regulators to regulate nontraditional measures of value.

Findings – The power of institutional investors is currently based on incomplete information from listed companies on how they create value, yet it rests on superior knowledge and insight into the workings of the companies in which they invest, and is only as strong as the quality of the information it uses to make investment decisions on behalf of clients.

Research implications – More research on the role of human capital analysis, and its regulatory consequences, is required.

Practical implications – Regulators need to act within the context of these fifth-generation models in order to create the environment for more transparent investment recommendations.

Originality of chapter – This chapter contributes a qualitative and conceptual perspective to the debate on the role of regulation beyond the global financial crisis.

The purpose of this chapter is to discuss the potential contribution of the option applications to economic instability. To this end, the chapter briefly reviews the extant literature on financial option pricing and its applications to corporate assets and liabilities. It focuses on the direct relationship between the volatility of the underlying asset and the value of the option. It shows that the theory of option applications by its one-sided emphasis on the value-creating role of volatility promotes excessive risk-taking. Then the chapter discusses how the theory of option applications through the educational system encourages economic agents to make excessively risky decisions. Furthermore, the interactions among these risk-welcoming agents lead to an economic system which becomes increasingly risky. This risky economy, combined with the fact that more than half of the value of the option applications is constituted by the highly volatile value of the options embedded in such applications, translates into wide variations in real investments and the economy.

We study the events that motivate CEOs to underinvest in R&D long-term projects (CEO myopia). Based on the existing literature in earnings management and agency theory, myopia is likely to become more problematic under five circumstances: when the CEO nears retirement (the CEO horizon problem), R&D projects have very long time horizons (the project horizon problem), the firm’s financial health is deteriorating (the cover-up problem), ownership structure is heavily weighted toward insider owners (minority owner oppression problem), and when the threat of hostile takeover increases (the entrenchment problem). We setup a dynamic simulation model in which rational CEOs maximize the total value of their bonus compensation over their tenure. Our findings related to the five circumstances are consistent with the extant literature. However, we found an unexpected stable, nonlinear (inverted U-shaped) relationship between CEO tenure and R&D investment. We discuss the theoretical implications of our model and offer suggestions for future research.