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The purpose of this paper is to integrate land use and option pricing theories using case study analyses to compare a portfolio of uses comprising single and mixed‐use development on the same site and assess the effects on the risk‐return profile of potential development schemes. The integration of land use development based on highest and best use (HBU) is tested against a combination of uses on the selected sites at a point in time in the downswing of the real estate cycle.

The proposed methodology integrates the development valuation approach with option theory in which both consider the relationships of cost and value associated with alternative development options. The approach used in this paper addresses the broader consideration of project coordination inclusive of land use flexibility and opportunity costs endogenously associated with development strategies. By investigating the uncertainty of economic options specific to the development process, the methodology considers the significance of complementary components of strategic decisions and entrepreneurial effort within a return/risk management strategy.

The stochastic model when compared to the real option model enhances strategic decisions and development project management by allowing the consideration of single/mixed‐use alternatives. The development process is facilitated by the research findings whereby alternative uses are tested to maximise the potential use of the site. The analyses consider optimal funding strategies in developing and investing for a range of use options on regeneration sites.

The significant insights apparent from the research is the quantification of the strategic specification of development as a productive process and an investment endeavour. The proposed model enables a comparison of a HBU based on a single development, a mixed‐use development or a combination of uses as the difference between the scenarios impacts on land value and profit measures, especially where these measures are calculated as distributive residuals.

The stochastic model developed in this paper provides a value‐added contribution to real estate literature by considering the complexity of the interrelationships between urban land economics, land use theory, valuation appraisal methodologies, portfolio analysis and option pricing as applied in the development of regeneration schemes.

This study forms part of a larger project funded by Cariplo Foundation. The purpose of this paper is to focus on the scope to exploit the full potential and upgrade the functions of abandoned or under-utilized typical highland Alpine pasture systems (made by a complex of grazing fields, buildings for temporal animal and human recovery and dairy production, identified as Malga system or Alpeggio), by adopting the property investor’s point of view.

This study has adapted the traditional property development processes to rural buildings, thus generating an analysis model that proves able to define a new destination of use whenever the project considers the reuse of existing facilities.

The proposed model analyzes the technological, functional and territory features of the building to be upgraded, to assess the technical feasibility of the changeover project and identify the highest and best use of Malga-systems. The model has been applied to all the Malga-systems in the Orobie Bergamasche Park; it performed a comprehensive assessment of the development potential of the Malga-systems in the same Park.

The design of the model took into consideration the specificities of the Orobie Bergamasche Park; nevertheless, the method can be taken as an example to be applied to any grazing land in the Alps.

This research provides the real estate market with a new analysis tool that is specific for the rural buildings, and suitable to streamline the procedures designed to upgrade these properties and to infuse new life into the territories that are experiencing a period of hardship and/or decay.

Mergers and acquisitions and consolidation activities contribute to the supply of technical facilities in the real estate market. The disposal of these special‐purpose assets poses unique challenges, including financial risk, redeployment of highly trained workforces and specialised equipment, and unknown timeframes. This paper will set out to take a deeper look into the internal corporate rationalisation process and the challenges and issues inherent in the disposal of special purpose assets.

In this chapter, the authors interrogate the structures, natures, processes, and variables that shape globalized collegiate desegregation. The authors pay attention to the history of segregation in South African culture, then proceed to current efforts to dismantle and rebuild the country’s educational enterprise. Drawing parallels with segregation policy in the United States, the authors argue that both nations may draw from global lessons about systemic global anti-Black oppression and its structural forms (e.g., apartheid, inequities in higher education). More specifically, the authors ground arguments in an analysis of the linguistic hegemony that continues to inculcate the college-aspiring students of South Africa. Understanding fundamental desegregation characteristics of racial hegemonic nations (e.g., United States) vis-à-vis racial and linguistic hegemonic nations (e.g., South Africa) is imperative to increase understanding of democratization of educational systems throughout the world.

The purpose of this paper is to describe and analyze the effects of campus sustainability planning to annual campus energy inflows and outflows in California higher education. The paper also offers a preliminary statistical analysis for the evaluation of impact factors on energy outflows and a link between energy outflows and building utilization.

The paper reports two campus examples University of California Merced and California State University Stanislaus, analyzing 36-months’ campus energy outflows data. It uses statistical linear regression analysis to determine the most significant impact factors to energy outflows and what is their relationship. Finally, the paper draws on building utilization data and presents sustainability management strategies for campus energy conservation which make the most of building utilization and contributes to campus sustainability planning efforts.

Statistics analysis considered ten multiple models of linear regression to identify the greatest impact factors on campus energy outflows. Interestingly, the overshadowing positive impact factor is renewable energy credits (RECs) which is expected as is required by California energy law. After removing RECs, cost of RECs and cost of electricity from further statistical analysis, we re-compute linear regression for the remaining variables, and natural gas outflows have the strongest – negative – relationship with energy outflows. In this study, it is demonstrated how sustainability planning applies to campus green building design criteria; how much do sustainable campus buildings cost; how sustainability planning affects the inflows and outflows of energy during the period of one academic year; and what are the direct benefits of campus sustainability planning and design to faculty, students, staff, administrators, environment and society.

The research is focused on two campus examples in California higher education and may have overlooked some campus sustainability plans and energy data from other California campuses. Nevertheless, it is a fairly comprehensive analysis of campus sustainability planning efforts and their effects on energy conservation.

Campus sustainability plans and their effect on campus energy inflows and outflows are very important. Understanding the details and potential effects of impact factors to energy conservation can help broader adoption and implementation of sustainability planning.

As an emerging method for campus sustainability efforts, statistical analysis of multiple linear regression models allows colleges and universities to examine energy conservation and align it with campus sustainability planning operational, academic and administrative functions in an integrated manner. To date, very little scholarly attention has been paid to the effects of sustainability planning on campus-level energy conservation, and no prior attempt has been made to consider how they might be analyzed statistically.

The power battery is the core of a new energy vehicle and plays a vital role in the rise of the new energy vehicle industry. As the number of waste batteries increases, firms involved in the industry need to properly dispose them, but what party is responsible remains unclear. To reduce environmental impacts, governments introduce two subsidy policies, i.e. collection subsidies, which are provided to the collecting firms, and dismantling subsidies, which are provided to the dismantling firms.

Based on the different characteristics of the subsidies, we develop a stylized model to examine the collection strategies and the preferences over the subsidies.

We derive several insights from analysis. First, the collection strategies depend on the fixed collection cost. Second, the key factor determining the firm's subsidy preference is the efficiency of dismantling. Finally, if the primary target is the collection rate, governments prefer to provide collection subsidies. If consider the environmental impact, the choice of subsidies has to do with the efficiency of dismantling. Moreover, from a social welfare perspective, the raw material cost and the efficiency of dismantling are core indicators of decision.

This work develops the first analytical model to study two power battery subsidies and investigate the optimal collecting strategies and subsidy preferences. The insights are compelling not only for the manufacturer and the third party but also for policymakers.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IMDS-08-2019-0450

The literature on project finance appraisal contains several ambiguities mainly concerning the correct method of equity cash flow (ECF) determination. This vagueness can lead to serious misevaluation of these projects. The purpose of this paper is to present and justify a correct method of ECF determination for project finance evaluation.

Based on the analysis of the specificity of project finance ventures and the study of existing literature, the authors propose a coherent model of ECF estimation that avoids misevaluating project finance ventures.

This paper demonstrates that the potential dividends methodology of ECF estimation, used commonly in the corporate finance world, leads to the erroneous valuation of project finance investments. Moreover, simulations demonstrate that the scale of this misevaluation is an increasing function of the debt covenant duration, the required rate of return, and the investment outlay dispersion over time. The proposed model of proper project finance valuation, despite inconsistency with assumptions of the fair value concept, is best suited for project finance venture appraisal, taking into consideration the inherently specific timing of the ECF.

This paper rectifies, clarifies, and extends the range of existing solutions for the project finance valuation and the application of the concepts of actual dividends and potential dividends in different valuation contexts. Furthermore, it proposes a simple and coherent method to value project finance ventures. Additionally, it offers evidence of the scale of NPV misevaluation in project finance, which occurs when the potential dividends approach is utilized.

The purpose of this paper is to examine millennial customer perceptions of food trucks and to identify factors that can foster their behavioral intentions pertaining to food trucks.

The study is based on a sample of 247 millennial customers of various food truck vendors in the United States and was assessed using ordinary least squares regression analysis.

Food truck image and employee friendliness were found to impact both customer satisfaction and word of mouth behavior; however, the other hypotheses were not supported.

There were two limitations. The first was that one of the constructs did not achieve the minimum average variance extracted. The second was that data collection was done in a single city in the United States; therefore, future research could overcome these limitations through a refinement of the construct’s items and targeting more cities.

There has been limited academic research on the millennial customer perceptions of the food truck phenomenon. This research addresses that gap through a field study that examines factors that contributed to the growth and popularity of food trucks among millennials

Despite the existence of multiple asset replacement theories, the economic life replacement method remains a major practical technique for making rational machine replacement decisions. The purpose of this paper is to bridge this method with comprehensive data analytic tools and make it applicable it to modern business reality with abundant data on operating and replacement costs.

This study employs operations research, discrete and continuous optimization, applied mathematical modeling, data analytics, industrial economics and real options theory.

Constructed stochastic algorithms extend the deterministic economic life method and are compared to the contemporary theory of stochastic asset replacement based on real options and dynamic programming. It is proven that both techniques deliver similar results when the cost volatility is small. A major theoretic finding is that the cost uncertainty speeds up the replacement decision.

This research suggests that the proposed stochastic algorithms may become an important tool for managerial decisions about replacement of many similar machines with detailed data on operating and replacement costs.

Compared to the real options replacement theory, major advantages of the proposed algorithms are that they work equally well for any distribution of age-dependent stochastic operating cost. The algorithms are tested on a real industrial case about replacement of medical imaging devices. Numeric simulation supports obtained analytic outcomes.

This study aims to draw upon research from strategic human resource management (HRM) and strategic management to examine how HRM demands influence the likelihood that chief executive officers (CEOs) will staff top management with a human resource (HR) executive.

The theory and hypotheses developed in this study are tested on a sample of US initial public offering firms from the calendar year 2007, using logistic regression.

The results of hypothesis tests suggest that HR executive presence in top management is positively related to the HRM demands faced by a CEO stemming from product/service innovation strategies, the number of HRs employed by the firm and CEO’s financial orientation.

The results of this study may not generalize to other settings. This study does not simultaneously consider the role of other structural forms which may increase or reduce the degree of HRM demands faced by the CEO. This study extends prior research on executive job demands by expanding the understanding of factors which give rise to HRM sources of executive job demands. Study results suggest that CEOs with financial orientations are more likely to staff their top management teams with an HR executive, which suggests that in the face of executive job demands stemming from a particular functional area, CEOs delegate responsibility for that function to another member of top management. This finding suggests that CEOs can, and in fact do, recognize the limitations engendered by their experiences and that when confronted with a specific type of executive job demand that does not align with their expertise, they take steps to address their individual limitations by appointing others that are more capable of addressing the particular source of executive job demand.

Study results suggest that product/service innovation strategies, CEO’s financial background and the number of HRs employed by the firm increase the likelihood of HR functional representation in top management.

The theory and results of this study extend the focus of extant research on factors giving rise to HRM’s functional representation in top management. Although prior research has emphasized the role of ownership characteristics and risk preferences in the adoption of this structural form, this study examines the role of CEO HRM demands. This approach allows for the integration of the upper echelons theory with the strategic HRM literature and provides an empirical examination of CEO job demands arising from the HRM function.