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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 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.

Facing the challenges posed by the pandemic of COVID-19, this paper aims to contribute to the resilience of businesses through the development of a real options approach (ROA) that provides alternatives and opportunities for a decision process under situations when future events and outcomes are unknown and not capable of being known from current information.

This paper involves a stochastic modelling process in generating a set of absolute option values, using available data and scenarios from the COVID-19 pandemic event. The modelling and simulations using ROA suggest how strategic portfolios resolve the growing problem during the endemic to all but in the most isolated societies.

This study finds the emergent correlation between circuit breakers and lockdowns, which have brought about a “distorted gravity” effect (inverse growth of global businesses and trades). However, “time-to-build” real options (i.e. deferral, expand, switch and compound exchange) start to function in the adaptive-transformative capabilities for growth opportunities of both government and corporate sectors. Significantly, some sectors grow faster than others while the compound exchange remains primarily challenging. Clearly, the government and corporate sectors are entangled, inevitably, the decoherence allows for the former to change uncertainty in the latter; therefore, government sector options change option values in the corporate sector.

The ROA by empirically focusing on both government and corporate sectors demonstrates under conditions of uncertainty how options in decision-making generate opportunities that hitherto have not been recognised and exercised upon by research in the immediate context of the COVID-19 pandemic. Importantly, the ROA provides an insightful concatenation (capability–behaviour approach) that drives resilience.

To propose a new investment-income valuation model by real options approach (ROA) for old community renewal (OCR) projects, which could help the government attract private capital's participation.

The new model is proposed by identifying the types of options private capital has in the OCR project, selecting the option model most suitable for private capital investment decisions, improving the valuation model through the triangular fuzzy numbers to take into account the uncertainty and flexibility, and demonstrating the feasibility of the calculation model through an actual OCR project case.

The new model can valuate OCR projects more accurately based on considering uncertainty and flexibility, compared with conventional methods that often underestimate the value of OCR projects.

The investment-income of OCR projects shall be re-valuated from the lens of real options, which could help reveal more real benefits beyond the capital growth of OCR projects, enable the government to attract private capital's investment in OCR, and alleviate government fiscal pressure.

The proposed OCR-oriented investment-income valuation model systematically analyzes the applicability of real option value (ROV) to OCR projects, innovatively integrates the ROV and the net present value (NPV) as expanded net present value (ENPV), and accurately evaluate real benefits in comparison with existing models. Furthermore, the newly proposed model holds the potential to be transferred to various social welfare projects as a tool to attract private capital's participation.

The Public–Private Partnership (PPP) modality plays an important role in the procurement of global infrastructure projects. Regarding PPP's complex transaction structure, pricing of a PPP project is critical to both parties where the government pursues a high value for money (VFM) and the investor strives to maximize its financial gains. Despite the straightforward win–win principle, a formidable compromise is often the case to end up with a fairly acceptable price, subject to many determinants such as the risk profile, expected return, technological innovation and capacities of both parties. Among them, this study chooses to examine the “managing flexibility” (MF) capacity of investors in pricing of a PPP project, in light of the widely recognized importance of a real-option perspective toward the long term, complex and uncertain PPP arrangement. This study addresses two major questions: (1) how is MF in PPP projects to be valued and (2) how are PPP projects to be priced when considering a project's MF value.

A binomial tree model is used to evaluate the MF value in PPP projects. Based on the developed MF pricing model, net present value (NPV) and adjusted VFM value are then calculated. Finally, a multi-objective decision-making method (MODM) was adopted to determine the optimal level of returns based on invested capital (ROIC), return on operation maintenance (ROOM) and concession period.

The applicability and functionality of the proposed model is investigated using a real project case. For a given return, extended NPV and adjusted VFM value were calculated and analyzed using sensitivity analysis. Factor influence is shown by the model to be dependent on factor impact on cash flow. Subsequently, a multi-objective decision-making (MODM) model was adopted to determine the optimal level of returns, where the solution approximates the real-world bidding price. Results confirm that the pricing model provides a reliable and practical PPP proposal pricing tool.

This study proposes an integrated framework for valuing MF in PPP projects and thus more accurately determine optimal pricing of PPP projects than revealed in extant research. The model offers a practical tool to aid in the valuation of PPP projects.

The aggressive competition in the real estate market forces real estate developers to tackle the challenge of selecting the best project construction phasing alternative. The real estate industry is characterized by high costs, high profit and high risks. The schedules of real estate projects are also characterized by having large number of repetitive activities that are executed over a long duration. The repetitiveness, long duration of execution, the high amounts of money involved and the high risk made it desirable to leverage the impact of changes in phasing plans on net present value of amounts incurred and received over the long execution and selling duration. This also changes the project progress, and delivery time as well as their respective impact on customer degree of satisfaction. This research addresses the problem of selecting the best phasing alternative for real estate development projects while maximizing customer satisfaction and project profit.

The research proposes a model that generates all construction phasing alternatives and performs decision-making to rank all possible phasing alternatives. The proposed model consists of five modules: (1) Phasing Sequencing module, (2) Customer Satisfaction module, (3) Cash-In calculation module, (4) Cost Estimation module and (5) Decision-making module. A case study was presented to demonstrate the practicality of the model.

The proposed model satisfies the real estate market's need for proper construction phasing plans evaluation and selection against the project's main success criteria, customer satisfaction and project profit. The proposed model generates all construction phasing alternatives and performs multi-criteria decision making to rank all possible phasing alternatives. It quantifies the score of the two previously mentioned criteria and ranks all solutions according to their overall score.

The research proposes a model that assist real estate market's need for proper construction phasing plans evaluation and selection against the project's main success criteria, customer satisfaction and project profit. The proposed model can be used to conclude general guidelines and common successful practices to be used by real estate developers when deciding the construction phasing plan. In this study the model is based on business models where all the project units are sold, rental cases are not considered. Also, the budget limitations that might exist when phasing is not considered in the model computations.

The model can be used as a complete platform that can hold all real estate project data, process revenues and cost information for estimating profit, plotting cash flow profiles, quantifying the degree of customer satisfaction attributable to each phasing alternative and providing recommendation showing the best one. The model can be used to conclude general guidelines and common successful practices to be used by real estate developers when tackling the challenge of selecting construction phasing plans.

The purpose of the study is applying and comparing models that predict optimal time for new product exit based on its demand pattern and survivability. This is to decide whether or not to continue investing in new product development (NPD).

The study investigates the optimal time for new product exit within the hi-tech sector by applying three models: the dynamic learning demand model (DLDM), the generalized Bass model (GBM) and the hazard model (HM). Further, for inter- and intra-model comparison, the authors conducted a simulation, considering Weiner and exponential price functions to enhance generalizability.

While higher price volatility signifies an unstable technology, greater investment into research and development (R&D) and marketing results in higher product adoption rates. Imitators have a more prominent role than innovators in determining the longevity of hi-tech products.

The study conducts a comparison of three different models considering time-varying parameters. There are four scenarios, considering variations in advertising intensity and content, word-of-mouth (WOM) effect, price volatility effect and sunk cost effect.

Business case (BC) analyses are performed in many different business fields, to create a report on the feasibility and competitive advantage of an intervention within an existing organisation to secure commitment from management to invest. However, most BC research papers on decisions regarding internal funding are either based on anecdotal insights, on analyses of standards from practice, or focused on very specific BC calculations for a certain project, investment or field. A clear BC process method is missing.

This paper aims to describe the results of a systematic literature review of 52 BC papers that report on further conceptualisation of what a BC process should behold.

Synthesis of the findings has led to a BC definition and composition of a 20 step BC process method. In addition, 29 relevant theories are identified to tackle the main challenges of BC analyses in future studies to make them more effective. This supports further theoretical development of academic BC research and provides a tool for BC processes in practice.

Although there is substantial scientific research on BCs, there was not much theoretical development nor a general stepwise method to perform the most optimal BC analysis.

The purpose of this paper is to investigate the current capital budgeting practices in Bangladeshi listed companies and provide a normative framework (guidelines) for practitioners.

Data were collected with a structured questionnaire survey taking from the chief financial officers (CFOs) of companies listed in the Dhaka Stock Exchange in Bangladesh. Garnered data were then analyzed using descriptive and inferential statistical techniques.

The results found that net present value was the most prevalent capital budgeting method, followed closely by internal rate of return and payback period. Similarly, the weighted average cost of capital was found to be the widely used method for calculating cost of capital. Further, results also revealed that CFOs adjust their risk factor using discount rate.

The findings of this study might help the firms, policymakers and practitioners to take a wise decision while evaluating investment projects. Additionally, this study’s findings enrich the existing body of knowledge in the field of capital budgeting practices by providing more reliable and comprehensive analysis taking samples from a developing economy.

Based on the dynamic capabilities view, the current study aims to empirically investigate the effects of organizational learning culture (OLC), strategic reconfiguration (SREC) and digital transformation (DT), altogether, on Egyptian private hospitals' strategic renewal in the face of the COVID-19 pandemic.

This study adopted a cross-sectional design to collect the data used to carry out mediation analysis. A self-administered questionnaire was used to collect data from a sample consisted of 264 Egyptian private hospitals. The smart partial least square structural equation modeling technique (PLS-SEM) was adopted to test the hypotheses.

The results demonstrate that OLC directly and positively affects SR. Besides, SREC and DT partially and serially mediate the OLC-SR relationship.

The sample size was small, covering only Egyptian private hospitals. The results may be different in the manufacturing sector and in other countries. The study was cross-sectional which is limited to trace long-term effects of OLC, SREC and DT on SR. Accordingly, a longitudinal study may be undertaken.

Private hospitals' managers must actively explore and dig out valuable resources in order to discover potential information and trends endeavor to redesign internal structures, and reconfigure their current resources, structures and strategies to achieve strategic renewal. The findings also provide new insights to mangers of private sectors' institutions and direct their attention toward adopting the strategic renewal option to survive amidst crises instead of retrenchment, persevering, or quitting business.

The study's results imply that health care providers have sought to improve the capacities of their health care systems to address the patient-level social needs through continuous learning, internal reconfigurations and the transformation toward digitalization to renew their services.

This study therefore contributes to SR literature by being the first empirical study to introduce an integrative model for the antecedents of SR amidst the pandemic.