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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 paper addresses the following research question: how do decision-makers use heuristics in their international business (IB) environment? Whereas, the literature has focused on entrepreneurial companies, here contrasting approaches to learning and using heuristics in international marketing (IM) decisions are examined and discussed.

The paper aims to address a gap in the study of micro-foundations of internationalization, exploiting research from other disciplinary fields. It combines a multidisciplinary literature review and longitudinal case studies to illustrate different approaches in learning and using heuristics by international marketers.

International marketers can adopt “closed” heuristics that are consolidated and consistently followed, or “open” heuristics, which are constantly being adapted and learned. Established multinationals learn heuristics in international marketing decision-making, following both “closed” and “open” models.

This paper offers an original contribution by presenting different approaches not yet examined in the literature, focusing on how international marketers make decisions through learning and using heuristic rules. The focus is on established exporters, in contrast to the literature that has largely paid attention to the effectiveness of heuristics in new entrepreneurial firms.

Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team interacts when making BMI decisions. The paper also investigates how group biases and board members’ risk willingness affect this process.

Empirical data were collected through 26 in-depth interviews with German managing directors from 13 companies in four industries (mobility, manufacturing, healthcare and energy) to explore three research questions: (1) What group effects are prevalent in BMI group decision-making? (2) What are the key characteristics of BMI group decisions? And (3) what are the potential relationships between BMI group decision-making and managers' risk willingness? A thematic analysis based on Gioia's guidelines was conducted to identify themes in the comprehensive dataset.

First, the results show four typical group biases in BMI group decisions: Groupthink, social influence, hidden profile and group polarization. Findings show that the hidden profile paradigm and groupthink theory are essential in the context of BMI decisions. Second, we developed a BMI decision matrix, including the following key characteristics of BMI group decision-making managerial cohesion, conflict readiness and information- and emotion-based decision behavior. Third, in contrast to previous literature, we found that individual risk aversion can improve the quality of BMI decisions.

This paper provides managers with an opportunity to become aware of group biases that may impede their strategic BMI decisions. Specifically, it points out that managers should consider the key cognitive constraints due to their interactions when making BMI decisions. This work also highlights the importance of risk-averse decision-makers on boards.

This qualitative study contributes to the literature on decision-making by revealing key cognitive group biases in strategic decision-making. This study also enriches the behavioral science research stream of the BMI literature by attributing a critical influence on the quality of BMI decisions to managers' group interactions. In addition, this article provides new perspectives on managers' risk aversion in strategic decision-making.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

When the probability of each model is known, a natural idea is to select the most probable model. However, in many practical situations, the exact values of these probabilities are not known; only the intervals that contain these values are known. In such situations, a natural idea is to select some probabilities from these intervals and to select a model with the largest selected probabilities. The purpose of this study is to decide how to most adequately select these probabilities.

It is desirable to have a probability-selection method that preserves independence. If, according to the probability intervals, the two events were independent, then the selection of probabilities within the intervals should preserve this independence.

The paper describes all techniques for decision making under interval uncertainty about probabilities that are consistent with independence. It is proved that these techniques form a 1-parametric family, a family that has already been successfully used in such decision problems.

This study provides a theoretical explanation of an empirically successful technique for decision-making under interval uncertainty about probabilities. This explanation is based on the natural idea that the method for selecting probabilities from the corresponding intervals should preserve independence.

The literature on economic forecasting, is showing an increase in criticism, of the inaccuracy of forecasts, with major implications for economic, and fiscal policymaking. Forecasts are subject to the systemic uncertainty of human systems, considerable event-driven uncertainty, and show biases towards optimistic growth paths. The purpose of this study is to consider approaches to improve economic foresight.

This study describes the practice of economic foresight as evolving in two separate, non-overlapping branches, short-term economic forecasting, and long-term scenario analysis of development, the latter found in studies of climate change and sustainability. The unique case of Ireland is considered, a country that has experienced both steep growth and deep troughs, with uncertainty that has confounded forecasting. The challenges facing forecasts are discussed, with brief review of the drivers of growth, and of long-term economic scenarios in the global literature.

Economic forecasting seeks to manage uncertainty by improving the accuracy of quantitative point forecasts, and related models. Yet, systematic forecast failures remain, and the economy defies prediction, even in the near-term. In contrast, long-term scenario analysis eschews forecasts in favour of a set of plausible or possible alternative scenarios. Using alternative scenarios is a response to the irreducible uncertainty of complex systems, with sophisticated approaches employed to integrate qualitative and quantitative insights.

To support economic and fiscal policymaking, it is necessary support advancement in approaches to economic foresight, to improve handling of uncertainty and related risk.

While European Union Regulation (EC) 1466/97 mandates pursuit of improved accuracy, in short-term economic forecasts, there is now a case for implementing advanced foresight approaches, for improved analysis, and more robust decision-making.

Building economic resilience and adaptability, as part of a sustainable future, requires both long-term strategic planning, and short-term policy. A 21st century policymaking process can be better supported by analysis of alternative scenarios.

To the best of the authors’ knowledge, the article is original in considering the application of scenario foresight approaches, in economic forecasting. The study has value in improving the baseline forecast methods, that are fundamental to contemporary economics, and in bringing the field of economics into the heart of foresight.

In a rapidly changing world, organisations are constantly presented with threats and opportunities and the need to be responsive and resilient. This necessitates developing risk and uncertainty management capabilities within organisations. This article aims to consider risk and uncertainty competence, knowledge, skills, attitudes and the behaviours required by contemporary managers to protect their organisations from threat and harm, whilst seizing opportunity and reward.

This article presents answers to three fundamental questions: (1) Do all managers (those not specialising in risk management) need to be competent in risk and uncertainty management? (2) What does risk competence mean? and (3) How can managers develop the capabilities to become risk competent? The content can be used by practicing managers or educators to develop individual and ultimately organisational risk competence.

All contemporary managers should have some degree of risk competence. Risk competence behavioural indicators and requisite risk knowledge and skills are identified and discussed.

This article provides a contemporary view on risk and uncertainty management competence, drawing on relevant competence frameworks and the existing risk literature.

The purpose of this paper is to present a conceptual framework for integrating strategic thinking factors, organisational performance and the decision-making process.

The methodology involves a synthesis of literature and proposes a framework that explores the relationship between strategic thinking enabling factors, organisational performance and the moderating effect of decision-making styles.

The framework includes strategic thinking enabling factors (systems perspective, focused intent, intelligent opportunism, thinking in time and hypothesis-driven analysis), organisational performance and the moderating effect of decision-making styles (intuitive and rational).

This research results in a conceptual model only; it remains to be tested in actual practice. The expanded conceptual framework can serve as a basis for future empirical research and provide insights to practitioners into how to strengthen policy development in a strategic planning process.

A paradigm shift in the literature proves that strategic management and decision-making styles are vital in determining organisational performance. This paper highlights the importance of decision-making styles and develops a framework for strategic management by analysing the existing strategic management literature.

Leaders have been facing serious challenges in managing organizations during COVID-19, which has brought the need for implementing sudden technological change across the globe. Hence, it was important to identify effective leadership styles to successfully manage the transformational process during the period. Therefore, the current study aims to explore and compare the effectiveness of transformational and ethical leadership (EL) in terms of achieving organizational goals during COVID-19 in public and private sector organizations in Pakistan.

Comparative research was carried out to find out the effectiveness of transformational and EL during and pre-COVID-19 in public and private sector organizations using the lens of social exchange theory. Data was collected from 214 respondents representing 67.6% of public and 32.4% of private sector organizations of Pakistan at two different points in time. Detailed comparative analyses were conducted in AMOS version 24 to assess the effectiveness of leadership styles before and during COVID-19 times.

On the whole, transformational leadership (TL) was found to have a greater impact on organizational effectiveness (OE) in comparison with EL in both pre-and during COVID-19 situations. Moreover, the effectiveness of TL significantly increased and the same decreased for EL during COVID-19. Additional analyses indicated that TL was effective for the private sector and EL for public sector organizations during COVID-19.

The study has not considered the mediating mechanisms of employee motivation, engagement and performance in the relationship between transformational and EL styles and OE, which can be explored in the future.

These results have important implications for private and public sector organizations and suggest that the adoption of a TL style will generate better results in the private sector and an EL style in public sector organizations to achieve OE in uncertain situations such as COVID-19.

The study shows that leadership with more care and concern for humanity tends to perform better in terms of generating results for OE. Therefore, both transformational and EL are based on individualized consideration for employees and are effective during COVID-19 in private and public sector organizations in Pakistan.

The study has carried out the comparative analyses in three different ways, including leadership styles (transformational and ethical), type of organization (private and public) and time frames (pre and during COVID-19), which is a true contribution of the research in the Pakistani context.

This paper aims to provide a multidisciplinary framework that allows an integrated understanding of reasons of success or failure in equity crowdfunding (ECF), a Fintech digital innovation of the traditional entrepreneurial finance, defining a future research agenda.

A systematic literature review (SLR) has been conducted on 127 documents extracted from two multidisciplinary repositories (Elsevier’s Scopus and Clarivate Analytics Web of Science) for the period between 2015 and early 2022. After a systematized series of inclusion and exclusion criteria, in line with the objectives and conceptual boundaries, a final list of 32 peer-reviewed articles written in English was analyzed by the authors through a meta-synthesis and thematic analysis to identify the key themes and dominant concepts.

Results show that the body of literature is recent and fast growing. The proposed integrative framework of existing research indicates that the outcome of an ECF campaign is related to signals conveyed by entrepreneurs in the form of hard information (firm characteristics, financial information, business characteristics and project description) and soft information (intellectual capital, human capital, social capital and social media network), catalyzed by digital media that facilitate also personal interactions between entrepreneurs and investors. Similarly, external factors (investors and campaign characteristics, with the fundamental role of ECF platform managers in building trust between entrepreneurs and investors) allow for the alleviation of information asymmetries. The present study sheds light on which signal mechanisms are decisive in improving the outcome, taking into consideration various disciplines which follow different but complementary perspectives.

Entrepreneurs should adapt to the transition toward the digital era, exploiting alternative financial instruments and learning effective signaling strategies, within a large variety of skills requested. Platform managers can obtain more focused information on selected entrepreneurial projects more efficiently.

Although it is fast-growing, the field of research is very recent, still fragmented and limited to the perspective/discipline followed. This SLR is, to the best of the authors’ knowledge, the first multidisciplinary and integrative analysis of reasons that motivates success, or failure, of an equity-based crowdfunding campaign. The digital nature of ECF encourages future research to move toward more pioneering and unconventional theories and research methods. Hence, the authors add to the existing literature by proposing future patterns of research based on an integration of highly technological skills and behavioral/psychological approaches.