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This paper provides a structural model to value startup companies and determine the optimal level of research and development (R&D) spending by these companies.

This paper describes a new variant of float-the-money options, which can act as a financial instrument for financing R&D expenses for a specific time horizon or development stage, allowing the investor to share in the startup's value appreciation over that duration. Another innovation of this paper is that it develops a structural model for evaluating optimal level of R&D spending over a given time horizon. The paper deploys the Gompertz-Cox model for the R&D project outcomes, which facilitates investigation of how increased level of R&D input can enhance the company's value growth.

The author first introduces a time-varying drift term into standard Black-Scholes model to account for the varying growth rates of the startup at different stages, and the author interprets venture capital's investment in the startup as a “float-the-money” option. The author then incorporates the probabilities of startup failures at multiple stages into their financial valuation. The author gets a closed-form pricing formula for the contingent option of value appreciation. Finally, the author utilizes Cox proportional hazards model to analyze the optimal level of R&D input that maximizes the return on investment.

The integrated contingent claims model links the change in the financial valuation of startups with the incremental R&D spending. The Gompertz-Cox contingency model for R&D success rate is used to quantify the optimal level of R&D input. This model assumption may be simplistic, but nevertheless illustrative.

Once supplemented with actual transaction data, the model can serve as a reference benchmark valuation of new project deals and previously invested projects seeking exit.

The integrated structural model can potentially have much wider applications beyond valuation of startup companies. For instance, in valuing a company's risk management, the level of R&D spending in the model can be replaced by the company's budget for risk management. As another promising application, in evaluating a country's economic growth rate in the face of rising climate risks, the level of R&D spending in this paper can be replaced by a country's investment in addressing climate risks.

This paper is the first to develop an integrated valuation model for startups by combining the real-world R&D project contingencies with risk-neutral valuation of the potential payoffs.

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.

This study employs Stein Rokkan's methodological approach to analyse state formation in the Greater Middle East. It develops a conceptual framework distinguishing colonial, populist and democratic pacts, suitable for analysis of state formation and nation-building through to the present period. The framework relies on historical institutionalism. The methodology, however, is Rokkan's. The initial conceptual analysis also specifies differences between European and the Middle Eastern state formation processes. It is followed by a brief and selective discussion of historical preconditions. Next, the method of plotting singular cases into conceptual-typological maps is applied to 20 cases in the Greater Middle East (including Afghanistan, Iran and Turkey). For reasons of space, the empirical analysis is limited to the colonial period (1870s to the end of World War 1). Three typologies are combined into one conceptual-typological map of this period. The vertical left-hand axis provides a composite typology that clarifies cultural-territorial preconditions. The horizontal axis specifies transformations of the region's agrarian class structures since the mid-19th century reforms. The right-hand vertical axis provides a four-layered typology of processes of external intervention. A final section presents selected comparative case reconstructions. To the authors' knowledge, this is the first time such a Rokkan-style conceptual-typological map has been constructed for a non-European region.

Comparative studies have confirmed that the current types of cohabitation (defined as living together as a couple without being married) and the meanings attached to them differ across Europe. This variation could reflect differences in the levels of progress or the stages countries have reached in a common developmental process, as suggested by the theory of the Second Demographic Transition and Kiernan’s stage model of cohabitation. However, it may also indicate that countries are on different developmental paths, as suggested by path dependency theories. To examine whether changes in the prevalence of cohabitation follow a common script, this study analyses types of cohabitation within emerging family formation patterns over cohorts and across countries.

For this purpose, sequence methodology is applied to analyze cohort-specific family trajectories in France, western Germany, Norway, and Italy. In particular, using data from the German National Educational Panel Study (NEPS) and the Generation and Gender Survey (GGS), patterns of union status and co-residence with (own) children between ages 15 and 35 among the 1935–1969 birth cohorts (for Germany, among the 1940–1974 birth cohorts) are compared.

Our findings provide some support for the claim that there were common patterns of change. However, also country-specific variations in family trajectory patterns were detected, which suggests that general processes of change were mediated through country-specific institutions (path dependencies). The empirical evidence for convergence as well as for divergence indicates that both theoretical strands add to our understanding of the spread of cohabitation in European countries.

In recent years, the frequency and severity of cybersecurity incidents have prompted customers to seek out specialized insurance products. However, this has also presented insurers with operational challenges and increased costs. The assessment of risks for health systems and cyber–physical systems (CPS) necessitates a heightened degree of attention. The significant values of potential damages and claims request a solid insurance system, part of cyber-resilience. This research paper focuses on the emerging cyber insurance market that is currently in the process of standardizing and improving its risk analysis concerning the potential insured entity.

The authors' approach involves a quantitative analysis utilizing a Likert-style questionnaire designed to survey cyber insurance professionals. The authors' aim is to identify the current methods used in gathering information from potential clients, as well as the manner in which this information is analyzed by the insurers. Additionally, the authors gather insights on potential improvements that could be made to this process.

The study the authors elaborated it has a particularly important cyber and risk components for insurance area, because it addresses a “niche” area not yet proper addressed in specialized literature – cyber insurance. Cyber risk management approaches are not uniform at the international level, nor at the insurer level. Also, not all insurers can perform solid assessments, especially since their companies should first prove that they are fully compliant with international cyber security standards.

This research has concentrated on analyzing the current practices in terms of gathering information about the insured entity before issuing the cyber insurance policy, level of details concerning the cyber security posture of the insured entity and way such information should be analyzed in a standardized and useful manner. The novelty of this research resides in the analysis performed as detailed above and the proposals in terms of information gathered, depth of analysis and standardization of approach made. Future work on the topic can focus on the standardization process for analyzing cyber risk for insurance clients, to improve the proposal based also on historical elements and trends in the market. Thus, future research can further refine the standardization process to analyze in more depth the way this can be implemented and included in relevant legislation at the EU level.

Proposed improvements include proposals in terms of the level of detail and the usefulness of an independent centralized approach for information gathering and analysis, especially given the re-insurance and brokerage activities. The authors also propose a common practical procedural approach in risk management, with the involvement of insurance companies and certification institutions of cyber security auditors.

The study investigates the information gathered by insurers from potential clients of cyber insurance and the way this is analyzed and updated for issuance of the insurance policy.

This study seeks to offer empirical insights into the role of alternatives analysis within strategic environmental assessment (SEA) in implementing low-carbon development (LCD) as part of Tanzania's efforts to tackle climate change.

The study design is cross-sectional multi-case. It draws on six SEA cases from Tanzania. Data were collected from SEA reports and subsequently analysed qualitatively using content analysis. The analysis framework was derived from the best practice literature and focused on determining whether and how alternatives were identified, assessed and selected and where and how LCD aspects were included.

The findings reveal that the practice of alternatives analysis is generally weak and varied. Gaps identified include neglect of alternatives, lack of transparency, a focus on mitigating harm, lack of inclusiveness and partial integration of LCD considerations.

Many countries are still developing their SEA systems, which requires building on local experience and adapting to local circumstances. Tanzanian SEA practitioners appear to place little weight on alternatives analysis and perform SEA using outdated, impact-based approaches. The study outlines policy recommendations for working more effectively with alternatives in Tanzania and comparable contexts.

There is a noticeable lack of scholarly emphasis on SEA processes that effectively identify, evaluate and select alternatives aligned with explicit societal values and concerns. This study focuses on the alternatives analysis stage, offering novel insights into the potential for constructing a desirable, low-carbon future. The cases studied show that an LCD-focused analysis is feasible and can be improved with the right theoretical and methodological approaches.

This study aims to explore the mediating effect of digital options on the relationship between emerging information technology investments (ITIs) and firm performance (FP). In particular, it analyses the performance impacts of investments in five emerging technologies of IT or non-IT firms.

Secondary data are collected from Chinese A-share listed companies from 2010 to 2018. The authors propose an econometric model focusing on the impact of ITIs on a firm’s market value and profit. A propensity score matching model is applied to control endogeneity.

The ITIs’ effect on FP is found to be completely mediated by digital options, and the reach of digital options plays a more positive role in the relationship between ITIs and Tobin’s Q, whereas the richness of digital options is stronger between ITIs and return on net assets (ROE). The group study shows that the impact of process technologies such as cloud computing and the Internet of Things has a more profound impact on Tobin’s Q, and the knowledge technologies represented by artificial intelligence, blockchain and big data strongly affect ROE. In addition, the positive relationship between ITIs and FP is unrelated to IT/non-IT firms.

First, the data are based on 219 publicly announced emerging ITIs in China and thus may not be generalizable to other cultural/national contexts. Second, there is a lack of a large sample data set of emerging ITI information in China, and the duration of this study is constrained to the relatively short rise of emerging technologies.

This study provides firm decision-makers with practical implications. The results imply that the effect of ITIs on FP depends on digital options, so both IT firms (e.g., Big Tech giants) and non-IT firms (e.g., incumbents) should discover how to balance firm value and profit in their management of emerging technology investment projects with digital options thinking.

To the best of the authors’ knowledge, this is the first empirical study to investigate the relationship between ITIs and FP from the perspective of digital options, exploring five emerging technologies and considering firm life, size, and state ownership in a sample of Chinese listed firms.

The purpose of this study is to analyse and compile the literature on various option pricing models (OPM) or methodologies. The report highlights the gaps in the existing literature review and builds recommendations for potential scholars interested in the subject area.

In this study, the researchers used a systematic literature review procedure to collect data from Scopus. Bibliometric and structured network analyses were used to examine the bibliometric properties of 864 research documents.

As per the findings of the study, publication in the field has been increasing at a rate of 6% on average. This study also includes a list of the most influential and productive researchers, frequently used keywords and primary publications in this subject area. In particular, Thematic map and Sankey’s diagram for conceptual structure and for intellectual structure co-citation analysis and bibliographic coupling were used.

Based on the conclusion presented in this paper, there are several potential implications for research, practice and society.

This study provides useful insights for future research in the area of OPM in financial derivatives. Researchers can focus on impactful authors, significant work and productive countries and identify potential collaborators. The study also highlights the commonly used OPMs and emerging themes like machine learning and deep neural network models, which can inform practitioners about new developments in the field and guide the development of new models to address existing limitations.

The accurate pricing of financial derivatives has significant implications for society, as it can impact the stability of financial markets and the wider economy. The findings of this study, which identify the most commonly used OPMs and emerging themes, can help improve the accuracy of pricing and risk management in the financial derivatives sector, which can ultimately benefit society as a whole.

It is possibly the initial effort to consolidate the literature on calibration on option price by evaluating and analysing alternative OPM applied by researchers to guide future research in the right direction.

India launched Smart City Mission in 2015 with an objective of development of 100 smart cities with a completion deadline in 2019 that was extended till June 2023. Smart City Mission is an important mission in the backdrop that urban population in India is projected to be 67.55 crore in 2035 from 48.30 crore in 2020. Further, by 2035, the percentage of population in India at mid-year residing in ‘urban area’ will be 43.2% as per the United Nations – Habitat's World Cities Report 2022 and it will be just next to China's urban population in 2035 that is projected at 1.05 billion. A recent World Bank report (2022) estimated that India will need to invest US (United States) $840 billion over the next 15 years, i.e. US $55 billion per annum – into urban infrastructure if it has to effectively meet the needs of its fast-growing urban population.

This chapter focuses on financing of sustainable smart cities in India. This chapter summarises financing options explored by the government in the beginning, challenges faced in financing of Smart City Mission in India over a period due to various developments such as pandemic, delay in execution of projects under the Smart City Mission, among others. Finally, suggestions have been given for making financing means effective and sustainable. These suggestions are based on the gaps between the ‘financing means thought of’ in the beginning and ‘financing means actually applied’ while executing Smart City Mission in India. Financing part is worth exploring in the background that India had the fiscal deficit at 3.9% of Gross Domestic Product (GDP) in 2015–2016 and most recently, the country had the fiscal deficit at 6.71% of GDP in FY22. And the country also dealt with the pandemic like other economies and provided COVID-19 vaccine free of cost to all citizens. Insights are useful for any other economy with a similar sustainable and smart city mission while facing resource constraints.

This study advocates the importance of taking an evolutionary perspective in the strategic configuration of closed-loop supply chains (CLSC) in the transition to a circular economy. Building on the supply chain management and industrial dynamics research domains, an evolutionary analytical framework was developed and applied in the empirical context of the ongoing industrial transition to e-mobility.

This study is designed as an in-depth exploratory case study to capture the multi-layer dynamic complexities and their interplay in CSLC development. The empirical investigation was based on two-year interactions between the authors and various departments in a leading European heavy vehicle manufacturer. The proposed evolutionary analytical framework was used for investigating the dynamics of four CLSC configurations through ten possible trajectories.

The findings demonstrate that the evolution of each CLSC configuration comes with multiple challenges and requirements and point out the necessity for the co-development of technologies, product design and production, and infrastructure through long-term relationships among key supply chain actors. However, this evolutionary journey is associated with multiple dilemmas caused by uncertainties in the market and technology developments. All these factors were properly captured and critically analyzed, along with their interactions, thanks to the constructs included in the proposed evolutionary analytical framework.

The proposed evolutionary framework is applicable for examination of SC transformation in the context of market and technology development, and is particularly relevant for transitioning from linear SC to CLSC. The framework offers a single actor perspective, as it does not directly tackle dynamics and effects of actions taken by SC actors.

The developed framework can support SC managers in identifying, framing, and comparing alternative strategies for CLSC configuration in the transition process.

This study proposes the framework for understanding and guiding the evolutionary process of CLSC development. Its uniqueness lies in the integration of concepts from innovation and evolutionary theories coming from industrial dynamics and SCM literature streams.