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This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.

The purpose of this paper is to gain insight into the contingent use of rational, intuitive and political decision-making in R&D.

This research is based on a study in an R&D department of a multinational high-tech firm in the Netherlands. The study consists of a case study design, focusing on four embedded cases, longitudinally studying each case.

The literature distinguishes three dimensions of innovation decision-making processes: rational, intuitive and political. By studying these interwoven dimensions over time, this study finds that the dominant use of each of these dimensions differs across the innovation process. There is an emphasis on intuitive decision-making in an early phase, followed by more emphasis on political decision-making, and moving to more emphasis on rational decision-making in a later phase of the R&D process. Furthermore, the predominant choice in a specific innovation phase for one of the three decision-making dimensions is influenced by the decision-making dimension that is dominantly employed in the preceding phase.

This study contributes to the innovation decision-making literature by developing and applying a model that distinguishes rational, intuitive and political decision-making dimensions, the interactions among these dimensions in innovation decision-making in R&D, and the contingency of these dimensions upon the innovation phase. It calls for further research into the contingent nature of innovation decision-making processes.

For practitioners this study has two relevant insights. First it highlights the importance and usefulness of intuitive and political decision-making in addition to the prevailing emphasis on rational decision-making. Second, practitioners may be more alert to consciously changing their dominant decision-making approach across the phases of the innovation process. Third, companies may adjust their human resource policies to this study’s findings.

The literature on rational, intuitive and political decision-making is quite extensive. However, research has hardly studied how these decision-making dimensions develop in conjunction, and over time. This paper reports on a first study to do so and finds that the dominant use of these dimensions is contingent upon the phase of the R&D process and on the decision-making dimensions used in earlier phases. The study suggests that using a contingency approach can help to further integrate the debate in research and practice.

Wage employees enter self-employment either directly or in a staged manner and may subsequently undertake multiple stints at self-employment. Extant research on the relationship between entry modes and the persistence and outcomes of self-employment is inconclusive. This study investigates the relationship between wage employees’ initial mode of entry into self-employment and the duration of the subsequent first two stints of self-employment.

This study used a matched longitudinal sample of 9,550 employees who became majority owners of incorporated firms from 2005 to 2016.

The findings demonstrate that the initial mode of entry into self-employment matters for the first two stints at self-employment. Staged entry into self-employment was associated with a shorter first stint and became insignificant for the second stint. Staged entry into self-employment was positively related to the odds of becoming self-employed for the second time in the same firm.

Using a comprehensive and reliable dataset, the paper shifts focus from the aggregated onward journey of novice entrepreneurs (survival as the outcome) to the duration of their self-employment stints. By doing so, the paper offers insights into the process of becoming self-employed and the patterns associated with success/failure in entrepreneurship associated with self-employment duration.

Failure plays a pivotal role in entrepreneurial learning. Knowledge of the learning process that enables an entrepreneur to re-emerge stronger after a failure, though considerable, is fragmented. This paper systematically collects relevant literature, assigns it to the stages of the experiential learning process (concrete experience, reflective observation, abstract conceptualization, active experimentation; Kolb, 1984), evaluates the research coverage of each stage and identifies promising avenues for future research.

This systematic literature review follows the guidelines articulated by Short (2009) and Tranfield et al. (2003), using Web of Science and EBSCO as primary data sources. Kolb’s (1984) experiential learning theory provides a basis for organizing the identified material into a framework of entrepreneurial learning from failure.

The literature provides insights on all stages of the process of entrepreneurial learning from failure. Particularly well elaborated are the nature of failure and its triggering effect for reflection, the factors influencing reflection, the contents of the resulting learning and their application in entrepreneurial re-emergence. Other topics remain under-researched, including alternative modes of recovery, the impact of personal attributes upon reflection, the cognitive processes underlying reflection, the transformation of failure-based observations into logically sound concepts and the application of this learning in non-entrepreneurial contexts.

This review provides the most complete overview of research into the process of entrepreneurial learning from failure. The systematic, theory-based mapping of this literature takes stock of current knowledge and proposes areas for future research.

This study aims to investigate how Germans' misperceptions of the nature of entrepreneurship influence their attitudes towards entrepreneurial failure.

Adopting a multivariate regression analysis, the study used data collected from a commercial online market research panel (N = 2,027) reflecting the overall German working population. Attitudinal items on business failure were used to measure the study variables. The study controlled for age, education, employment status, gender, income, whether the respondent knows a failed entrepreneur and the German federal state in which the respondent resides.

The findings suggest that reservations about failed entrepreneurs become stronger as misperceptions of the nature of entrepreneurship worsen. The results also show that failure reservations vary regionally over the 16 German federal states.

Nationwide efforts regarding the stimulation of entrepreneurship and the acceptance of entrepreneurial failure are insufficient for removing failure reservations, as they neglect regional cultural differences. The results suggest that it is not enough just to invest in efforts to create a failure-friendly culture, and that a better general education about the realities of entrepreneurship is a prerequisite.

The study generates insights into how the overall population in an innovation-driven economy perceives entrepreneurship and entrepreneurial failure. Moreover, the work delves into the reasons why parts of German society reject failed entrepreneurs. Hence, this study can aid the drafting of effective policy initiatives at the regional and national levels.

There has been significant growth in entrepreneurship research over the past several decades. Yet with all of the knowledge gained and presumably improved training of would-be entrepreneurs, firm failure rates remain persistently high. It is argued here that the historical and continued research focus on successful entrepreneurs has limited the field. Entrepreneurs are often considered to possess uniquely positive capabilities relative to the general population; this paper explores the possibility that the majority of entrepreneurs suffer from overconfidence and that this leads most entrepreneurs to make “bad bets” that result in underperformance and firm failure.

In this paper, a qualitative review of the literature was performed.

Based on the literature review, three formal propositions are developed. The first two suggest that the majority of entrepreneurs are overconfident in their personal capabilities and the prospects for their new ventures. It is then proposed that this overconfidence leads to errors in judgment that results in financial underperformance and failure found among most new ventures.

This paper makes an important contribution to the entrepreneurship literature by arguing that overconfidence negatively impacts pre-founding decision-making such that entrepreneurs pursue flawed opportunities. Studying the issues raised in this paper may spur new lines of research and knowledge that lead to better entrepreneurial outcomes.

The authors propose and test a theoretical framework that develops and analyzes precursors to firm acquisitions to determine if acquirers differ from other firms.

The authors use longitudinal, archival data from a sample of the largest firms in the global pharmaceutical industry from 1991 to 2012 with 1,327 firm-year observations.

The authors integrate prior research to show that the firm characteristics involving (1) R&D investment, (2) prior experience and (3) network centrality influence the likelihood that a firm will complete an acquisition.

In contrast to research focusing on the performance of acquiring firms, the authors show that firm characteristics predict acquisition activity by highlighting that acquiring firms differ from other firms. The authors also develop how network synergies can be realized by acquirers that have information advantages from more central network positions.

This paper aims to draw from research on culture, stigma and entrepreneurial activity to hypothesize that the relationship of stigma with the level of entrepreneurial activity differs by the dimensions of national culture, i.e. individualism, masculinity, uncertainty avoidance and power distance.

The hypotheses were tested with data from 15 countries spanning over a 15-year period. Poisson regressions were used.

Results from Poisson regressions supported the hypotheses for the differences based on the “individualism,” “masculinity” and “power distance” dimensions of culture on the relationship between stigma of failure and entrepreneurial activity. However, the hypothesis for the differences based on the “uncertainty avoidance” dimension of culture was not supported.

Fostering entrepreneurship has been important for several countries around the world. A number of factors influence the phenomenon of entrepreneurship. In this paper, research in the areas of culture, stigma and entrepreneurship is brought together to explain how the stigma of failure may be intensified or mitigated in different cultural contexts. The results suggest that policies and attempts to alleviate stigma of failure for promoting entrepreneurship need to consider the complex interactions occurring within the cultural contexts in which entrepreneurs operate. Such initiatives should enhance their effectiveness.

The purpose of this paper is to explore two distinct subsets of dynamic capabilities that need to be deployed when pursuing innovation through inter-organizational activities, respectively, in the contexts of broad networks and specific alliances. The authors draw distinctions and explore potential interdependencies between these two dynamic capability reservoirs, by integrating concepts from the theoretical perspectives they are derived from, but which have until now largely ignored each other – the social network perspective and the dynamic capabilities view.

The authors investigate nanotechnology-driven R&D activities in the 1995–2005 period for 76 publicly traded firms in the electronics and electrical equipment industry and in the chemicals and pharmaceuticals industry, that applied for 580 nanotechnology-related patents and engaged in 2,459 alliances during the observation period. The authors used zero-truncated Poisson regression as the estimation method.

The findings support conceptualizing dynamic capabilities as four distinct subsets, deployed for sensing or seizing purposes, and across the two different inter-organizational contexts. The findings also suggest potential synergies between these subsets of dynamic capabilities, with two subsets being more macro-oriented (i.e. sensing and seizing opportunities within networks) and the two other ones more micro-oriented (i.e. sensing and seizing opportunities within specific alliances).

The authors show that firms differ in their subsets of dynamic capabilities for pursuing different types of inter-organizational, boundary-spanning relationships (such as alliances vs broader network relationships), which ultimately affects their innovation performance.

The authors contribute to the growing body of work on dynamic capabilities and firm-specific advantages by unbundling the dynamic capability subsets, and investigating their complex interdependencies for managing different types of inter-organizational linkages. The main new insight is that the “linear model” of generating more innovations through higher inter-firm collaboration in an emerging field paints an erroneous picture of how high innovation performance is actually achieved.

This study aims to understand and compare how the mechanism of innovative processes in the information technology (IT) industry – the most innovative industry worldwide – is shaped in Poland and the USA in terms of tacit knowledge awareness and sharing driven by a culture of knowledge and learning, composed of a learning climate and mistake acceptance.

Study samples were drawn from the IT industry in Poland (n = 350) and the USA (n = 370) and analyzed using the structural equation modeling method.

True learning derives from mistake acceptance. As a result of a risk-taking attitude and critical thinking, the IT industry in the USA is consistently innovation-oriented. Specifically, external innovations are highly correlated with internal innovations. Moreover, a knowledge culture supports a learning culture via a learning climate. A learning climate is an important facilitator for learning from mistakes.

This study revealed that a high level of mistake acceptance stimulates a risk-taking attitude that offers a high level of tacit knowledge awareness as a result of critical thinking, but critical thinking without readiness to take a risk is useless for tacit knowledge capturing.