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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.

Meta-synthesis of the research evidence adds value to the process of literature reviewing, providing useful knowledge for researchers, practitioners and policymakers. The aim of the chapter is to explain what meta-synthesis involves and how it illuminates our understanding of concepts. Previous papers on meta-synthesis (by the author) have reviewed research strategies in information behaviour research and methods for meta-synthesis, discussed application of meta-synthesis to research on information behaviour of women, and proposed methods suitable for integrating information literacy research. Meta-synthesis methods have been applied to many areas of social science research. The literature review examines how to reduce the risks involved in suitable for integrating qualitative research or qualitative and quantitative research; outlines the main approaches used in meta-synthesis before explaining the processes used in a meta-synthesis of research on information behaviour of women, reflects on the meta-synthesis methods used, and which might have been used, and shows what meta-synthesis achieves. Meta-synthesis should be used more in information behaviour research, but it is a rigorous process, requiring time and effort to get useful results. On the other hand, meta-synthesis provides more new knowledge, and a deeper understanding of our ideas, than a conventional literature review.

We derive marginal conditions of optimality (i.e., Euler equations) for a general class of Dynamic Discrete Choice (DDC) structural models. These conditions can be used to estimate structural parameters in these models without having to solve for approximate value functions. This result extends to discrete choice models the GMM-Euler equation approach proposed by Hansen and Singleton (1982) for the estimation of dynamic continuous decision models. We first show that DDC models can be represented as models of continuous choice where the decision variable is a vector of choice probabilities. We then prove that the marginal conditions of optimality and the envelope conditions required to construct Euler equations are also satisfied in DDC models. The GMM estimation of these Euler equations avoids the curse of dimensionality associated to the computation of value functions and the explicit integration over the space of state variables. We present an empirical application and compare estimates using the GMM-Euler equations method with those from maximum likelihood and two-step methods.

The campaign for striker replacement legislation, which began in the late 1980s and had effectively ended by the mid-1990s, was the most important political battle over labor legislation since the defeat of the Labor Law Reform Bill in 1978. Striker replacement was the AFL-CIO’s top legislative priority in the early 1990s and, coming quickly after the passage of NAFTA, which labor had opposed, the defeat of its campaign solidified organized labor’s reputation for failure in legislative battles. As yet, however, the political campaign for striker replacement legislation has attracted surprisingly little attention from industrial relations scholars.

The accounting academy is facing two critical challenges: an increasing disconnect between academia and practice and a growing shortage of faculty. Recently, the Pathways Commission proposed that accounting programs more fully embrace professionally oriented faculty. This proposal is attractive because it would increase faculty numbers and bring a stronger practice orientation to the academy. Although there may be benefits associated with this proposal, there may also be significant unintended consequences. In this paper, we use two analogs from the NFL to highlight the risks in relying on practice-oriented faculty to solve our problems. We offer a series of reflection questions to promote further conversations on the Pathways Commission’s proposal.

Many dynamic problems in economics are characterized by large state spaces which make both computing and estimating the model infeasible. We introduce a method for approximating the value function of high-dimensional dynamic models based on sieves and establish results for the (a) consistency, (b) rates of convergence, and (c) bounds on the error of approximation. We embed this method for approximating the solution to the dynamic problem within an estimation routine and prove that it provides consistent estimates of the modelik’s parameters. We provide Monte Carlo evidence that our method can successfully be used to approximate models that would otherwise be infeasible to compute, suggesting that these techniques may substantially broaden the class of models that can be solved and estimated.

Companies are increasingly leveraging digital technologies toward innovation strategies that deliver novel features to customers sequentially through successive new product generations (i.e., successive innovation). Extant literature examining successive innovation is both limited and fragmented across marketing and management literatures. Our goal is to synthesize literature on concepts related to successive innovation (such as versioning and upgrades) to identify the core dimensions of successive innovation and provide a cohesive framework to guide future research in this domain.

Given the equivocality in understanding the conceptual domain of successive innovation, we review and synthesize literature across three disciplinary domains: marketing, management, and information and decision sciences. Based on the emerging patterns from the literature review, we develop a conceptual framework of successive innovation with the aim of moving the discussion toward greater theoretical clarity.

Based on the literature review and synthesis, we identify three core-dimensions that define successive innovation and compare these across digital and physical product realms: coexistence, embeddedness, and adoption controllability.

Our proposed conceptual dimensions of successive innovation, and discussion of differences across physical and digital product domains, offer important directions for future research and a common vocabulary.

As physical and digital successive innovations can differ in coexistence, embeddedness, and adoption controllability, firms need to consider relevant barriers to adoption of successive product generations and select appropriate strategies to promote and communicate successive innovation. Our proposed successive innovation conceptual dimensions help managers comprehend the complexity of arranging such innovation in business and consumer segments.

Our contribution to the emerging literature on successive innovation is threefold. First, by conducting a comprehensive literature review, we integrate insights from different fields of inquiry (i.e., marketing, management, and information and decision sciences). Second, based on the synthesis of the literature, we offer a conceptual framework of successive innovation, which aims to move the discussion toward greater theoretical clarity. Third, based on our review and conceptual framework, we discuss a set of future research directions to guide academic research efforts.

During recent years, financial economists have made a significant contribution to the rapid development of a vibrant and growing literature on organization structure and corporate governance. In reviewing the development of this literature, it becomes easy to see how the seminal contributions of Ronald Coase (awarded the Nobel Prize in Economics in 1991) have become the cornerstone of a new institutional economics. In particular, researchers following in Coase’s footsteps have clarified the conditions under which voluntary contracts between private agents can resolve a wide variety of so-called “agency problems.” More than just representing an important discovery of the significance of transaction costs and property rights for the institutional structure and functioning of the economy, Coase’s work has become an important foundation for the theory of contracts and for the whole field of “organization economics.”

Mergers and acquisitions strategies are not risk-free, potential problems in achieving success include integration difficulties, inadequate evaluation of target, inability to achieve synergy, and complexity. Such strategies can fail for many reasons including inadequate evaluation of targets or inadequate pre-decision control mechanisms. Mergers and acquisitions are reviewed in this chapter as strategic investment decision-making perspective. Established financial analyses remain important in appraising investment choices, despite their limiting assumptions and their recognised shortcomings in capturing strategic project dimensions. However, managers balance these economic analyses with less-structured, strategic analyses underpinned by informed judgement. The fact that empirical studies reveal a continued reliance on judgement by investment decision-makers does not mean that rational economic analysis is a futile exercise. What studies of practice do seem to suggest is that the theory and practice of strategic investment decision-making need to take into account both economically rational and intuitive decision processes. Reflecting on the research evidence, we conclude that strategic investment appraisal will be best supported by approaches that (i) couple sound economic analysis with the development of managerial judgement and (ii) take account of the broader decision-making context within which both economic and strategic analyses are used.