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This chapter discusses how the real options theory can be useful for understanding the adoption of human resources management (HRM) practices. The authors review how the real options theory has provided insights into the processes through which firms manage uncertainties involved in the adoption of HRM practices. The authors offer propositions for future HRM research from the real options perspective. The authors contend that analyzing HRM practice adoptions through the lens of real options theory can enhance our understanding of the mechanisms through which firms choose which HRM practices to adopt and how they adjust the timing, scale, and methods of investment in these practices. Specifically, the authors suggest that differences in information relevant to valuation of HRM options are the source of distinct choices of HRM options across firms. Finally, the authors propose advancing knowledge on HRM practice adoptions by using a portfolio of options approach, as well as considering factors like competitors, path dependence, and switching options.

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 chapter explores the strategic responsiveness of commodity multinationals operating in developing countries to the uncertainties raised by the emergent European Union (EU) sustainability regulation. The study applies deductive theory triangulation to derive five response propositions, subsequently contrasted with inductive insights from an exploratory single-case study. The research involves in-depth interviews with a mix of senior and middle management and numerous external stakeholders. Empirical findings are discussed through storytelling and retrospective sensemaking and cross-checked against corporate documents, archive material, and online articles for added validation. This chapter concludes that an authentic commitment to corporate social responsibility and creating shared value can enhance the multinational enterprise (MNE)’s resilience and responsiveness to regulatory uncertainty, especially when combined with early signal scanning and real options reasoning. Through varied, first-hand insights, the case study demonstrates the role of reputation, core values, and ethical leadership in support of effective stakeholder engagement capabilities and the MNE’s ability to develop viable collaborative solutions to uncertainties implied by evolving sustainability regulation and stakeholder expectations. Taking an evolutionary view, this chapter introduces a process perspective on sustainability transition, relevant to firms seeking a shift in focus from mere compliance toward strategic responsiveness founded on adaptability and renewal.

Mauritius’s residential real estate sector has undergone an increase in foreign investment over the past decades. This study aims to establish if the increasing level of foreign real estate investments (FREI) has increased land demand and land prices. The study also aims to depict whether the relation between FREI and land prices prevails at an aggregate and/ or a regional level.

Data from 26 regions, classified as urban, rural and coastal is collected on an annual basis over the period 2000 to 2019, and a dynamic panel regression framework, namely, an autoregressive distributed lag model, is used to take into account the dynamic nature of land price modeling.

The findings show that, at the aggregate level, in the long-term, FREI does not have a significant influence on land prices, while in the short term, a positive significant relationship is noted between the two variables. A regional breakdown of the data into urban, rural and coastal was done. In the long term, only in coastal regions, a positive significant link was observed, whereas in urban and rural regions FREI did not influence land prices. In the short term, the positive link subsists in the coastal regions, and in rural regions also land prices are positively affected by FREI.

Unlike other studies which have used quite general measures of FREI, the present research has focused on FREI mainly undertaken in the residential real estate market and how these have affected residential land prices. This study also contributes to research on the determinants of land prices which is relatively scarce compared to research on housing prices.

The main objective of this study was to design a dynamic adaptive decision support model for healthcare organizations facing deep uncertainties by considering promising dynamic adaptive approaches. The main argument for this is that healthcare organizations have to make strategic decisions under deep uncertainty, but lack an approach to deal with this.

A Dynamic Adaptive Decision Support model (DADS) is designed using the Design Science Research methodology. The evaluation of an initial model leads, through two case studies on ongoing and strategic decision-making, to the final design of this needed model for healthcare organizations.

The research reveals the relevance of the designed dynamic and adaptive tool to support strategic decision-making for healthcare organizations. The final design of DADS innovates Decision Making under Deep Uncertainty (DMDU) approaches in an organizational context for ongoing and strategic decision-making.

The designed model applies the Dynamic Adaptive Policy Pathways approach in an organizational context and more specifically in health care organizations. It further integrates Corporate Real Estate Management knowledge and experience to develop a most needed tool for decision-makers in healthcare. This is the first DADS designed for an organization facing deep uncertainties in a rapidly changing healthcare environment and dealing with ongoing and strategic decision-making.

This study aims to show the difference between the two types of oil price volatility resulting from either increases or decreases in oil prices and find evidence of the differential effect of oil price volatility on firms' environmental initiatives.

This paper examines how volatility in crude oil prices affect corporate environmental responsibility among US firms (excluding oil and gas producers) between 2002 and 2020, with a particular focus on the differential impact of oil price volatility.

The authors find that a one standard deviation increase in oil volatility resulting from positive changes in oil prices corresponds to a 12.7% decrease in environmental score, while the same increase in volatility from negative changes in oil prices leads to a 5.5% decrease in environmental score. Financial constraints are identified as a potential channel through which oil price volatility influences environmental activities. Specifically, a one standard deviation increase in oil volatility from positive price changes leads to an 18% decrease in environmental score for firms with high financial constraints, compared to an 8% decrease for firms with low financial constraints.

This study builds on the research of Phan et al. (2021) and Maghyereh and Abdoh (2020). Pan et al. reveal a negative association between oil price uncertainty and corporate social responsibility in the oil and gas sector, yet they overlook 1) the asymmetric impacts of oil price changes and sectoral disparities. Moreover, 2) their inclusion of a year-fixed effect undermines their findings’ reliability, as the oil price volatility variable remains constant across all firm-year observations, and including a year-fixed effect diminishes its explanatory power.

This paper aims to examine the performance efficiency of 56 real estate assets within the rental sector in the UAE to evaluate the relative operation efficiency in relation to revenue generation.

The data envelopment analysis (DEA) approach was used to measure the relative operational efficiency of the studied assets in relation to the revenue performance. This method could produce a more informed and balanced approach to performance measurement.

The outcomes show that scores of efficiencies ranging from 7% to 99% in some of the models. The results showed that on average buildings are 75% relatively less efficient in maintenance, in term of revenue generation, than the benchmark set. Likewise, on average, the inefficient buildings are 60% relatively less efficient in insurance. Result also shows that 95% of the building assets in the sample are by and large operating at decreasing returns to scale. This implies that managers need to considerably reduce the operational resources (input) to improve the levels of revenue.

This study recommends that the FM operational variables that were found to inefficiently contribute to the revenue should be re-examined to test the validity of the findings. This is necessary before generalising or interpolating the results that are presented in this study.

The information obtained about operational performance can help FM managers to understand which improvements in the productivity of inefficient FM resources are required, providing insight into how to reduce operating costs and increase revenue.

This paper adds value in using new FM operational parameters to evaluate the efficiency of the performance of built assets.

This paper aims to investigate how mixed-reality (MR) can be used to enhance inclusivity in synchronous working activities where groups of people may be present either face-to-face or online – focusing on blended learning in the higher education (HE) context.

In a research methods module, 140 university master’s-level students were given the option to attend and engage in seminars/practical sessions either in a real lecture room or online through a virtual version of an equivalent environment, accessible on everyday devices. The MR platform provided two-way video “windows” enabling all students on the module to freely interact with staff and their peers. Attendance was recorded throughout the semester and survey data was captured after all sessions (33% response rate). In addition, student activity was video recorded within both the real and virtual spaces.

Attendance was high throughout the semester and students were very positive about this novel approach to their education. Students chose to either engage purely in-person, online or as a mixture of the two; performance on the module was not impacted by this decision. The survey highlighted several factors that impacted on students’ choice of learning space, including those related to intrinsic characteristics of individual students (e.g. desire for traditional/novel social interactions) and those related to extrinsic influences (e.g. weather and travel demands). Video analysis revealed numerous differences in the behaviours exhibited across the virtual and real spaces, related to individual versus team mentalities.

Conclusions are drawn regarding how MR can be used in HE and potentially other work-related contexts to enhance engagement, a sense of community and ultimately learning/productivity outcomes.

This study investigated how a large (>100) cohort of students responded to an MR blended learning experience across a whole semester. In this respect, to the best of the author’s knowledge, this is the first study to consider such issues at this scale in a university education setting.