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This paper addresses the increasingly rapid and disruptive changes caused by technology innovations impacting commercial real estate (CRE) and how leaders in today's CRE business environment can better anticipate, and even experiment with, disruptive technologies while maintaining current business assets and practices.

This qualitative research is based in systems theory, through which the impact of disruptive technology innovation cycles on business models is described for tactical and strategic utility.

The advent of the fourth industrial revolution (Industry 4.0) is characterized by a convergence of multiple technological innovations including artificial intelligence, the Internet of things, smart buildings, autonomous agents, and automated decision-making. Industry 4.0 promises a future of discontinuities and disruptive innovation superseding the deployment of digital technologies enabled by Industry 3.0. Ambidextrous leaders need to maintain two concurrent foci: one on the current CRE business environment for incremental improvements and one on new opportunities made possible by the next technology innovation cycle.

By anticipating the inflection points of nonlinear technology adoption cycles, CRE leaders can reduce risks and increase innovative opportunities as participants in the next disruptive cycle rather than falling victim to it.

This work examines CRE market disruptions caused by technology innovation cycles through the lens of systems theory. A connection is made between the nonlinear nature of technology disruption cycles within the CRE business environment and how CRE leadership can better anticipate and prepare for change through ambidextrous thinking.

The purpose of this paper is to examine the pricing of vacant lots in master planned golf course communities (GCCs) over the period of 2000-2016. The authors compare the longitudinal pricing behavior of different lot types during this economic cycle and examine the causes of the property bubble and subsequent deterioration of the business model with the arrival of the Financial Economic Crisis (FEC).

The authors construct spatial hedonic models for three master planned GCCs in Pickens County, South Carolina and use interaction dummies to examine the pricing of different types of vacant lots before and after the FEC.

The authors find that there is a collapse in value for interior lots in the GCCs compared to interior lots in the county. As interior lots comprise over 50 percent of inventory in a typical master planned GCC, this loss of real estate value threatens the viability of such communities in the aftermath of the FEC.

The research results inform real estate investors, real estate developers, current homebuyers and potential homebuyers of the impacts of the FEC on master planned GCCs and some of the risks associated with such developments.

This is the first paper the authors are aware of that indicates the financial viability of master planned GCCs is associated with the pricing fragility of interior lots during cyclical markets. While demand for premium quality lots suffers, there is a collapse in demand for interior lots during the crisis.

Volatility, Uncertainty, Complexity and Ambiguity (VUCA) are terms the military have coined to describe the environment they often operate in. This paper examines how this decision-making framework can be used to better inform real estate investment and development. In celebration of this journal's 40th anniversary, we also explore how VUCA can be related to and expand on the teachings of Dr. James A. Graaskamp who published his seminal piece on the Fundamentals of Real Estate Development (1981) the same year. In that piece, he highlights the importance of paying attention to the human factor, the consumers of real estate.

This is a thought piece on an alternative decision-making framework that can help capture the dynamic environment that commercial real estate investors and developers are currently working in. VUCA captures the difficulty of predicting the future in a world of accelerating, unpredictable change. This is particularly important in today's rapidly changing world caused not only by the current COVID-19 pandemic but also the exponential growth of the proptech industry as well as the increasing risks and opportunities associated with climate change that continues to impact the built environment.

This is not a traditional research project with empirical findings. We are presenting an alternative framework for thinking about making investment decisions in these current volatile, uncertain, complex and ambiguous times today and in the future. In addition, the importance of multidisciplinary training and the human factor are stressed.

There are no limitations to this research as it is the ideas of the authors. Implications are to help real estate investors, developers and educators better understand the environment that they are working in.

VUCA captures better the dynamic nature of real estate investments compared to traditional analysis. It helps one better analyze the risks and returns but also to acknowledge that there is a lot you cannot predict and there are many exogenous variables that can, at times, completely change the rules of the game. Flexibility and adaptability are essential tools for working in a VUCA environment. In addition, the human factor plays an increasingly important role and real estate investors and developers that clearly understand this and focus on the consumer will likely be more successful.

We believe that this is the first time that VUCA has been used in the real estate academic literature.

This paper addresses decision-making for commercial real estate (CRE) firms and professionals within the context of rapid technological innovations capable of business model disruption. It considers the paradoxical notion of the need for CRE firms to become ambidextrous by simultaneously exploiting their existing business model and exploring possible opportunities and threats. The paper develops a practical approach, the paradox map, for dealing with this paradoxical problem.

This qualitative research draws on work from organizational management, leadership, social sciences and technology. This research frames the definition and development of an ambidextrous mindset and its components. Paradox management is explored as a possible source of useful tools.

The ambidextrous mindset is a paradox in that exploit and explore are ongoing interrelated opposing forces. Further, the mindset is the product of a number of sub-paradoxes that act as levers for its development and adjustment. The paradox map is developed to facilitate dealing with numerous paradoxes.

The paradox map is a useful tool for commercial real-estate firms to understand and develop an ambidextrous mindset.

Commercial real estate is experiencing a wave of substantive technological disruption in the proptech marketplace and beyond. This paper attempts to clarify the paradox of innovation and its underlying sub-paradoxes to help professionals navigate the interrelated landscape of exploiting past products and exploring innovations.

The purpose of this exploratory paper is to examine the efficient market theories and to argue that a new paradigm or an expanded paradigm is needed for the valuation of real estate. This may actually not be a new paradigm but it may be necessary to go back in time to make the valuation models that are used more realistic and to try to include the realities that there are many diverse actors in the real estate marketplace and their actions are important and should not be assumed away. Behavior matters and the models for pricing real estate need to take this into account.

The paper examines some of the emerging models in other disciplines and works to relate them to the real estate marketplace in general but, more importantly, to help to explain the most recent bust of the global real estate markets.

The paper finds that there is a need to consider an alternative paradigm for the valuation of real estate and complexity theory as well as the adaptive system models that specifically take into account that the various actors in a real estate marketplace could be used to help better explain the emergent nature of real estate values.

This is the first paper to one's knowledge that argues for a shift in thinking to include complexity economics and agent‐based modeling as potential solutions to gain a better understanding of how real estate markets react.

The purpose of this exploratory paper is to examine the lack of reliability of traditional neo-classical models and to argue that it is due to the hidden complexity and non-linearity that may operate at times in residential housing markets. As a result, market efficiency may be a special case, rather than the prevailing rule. An alternative framework that incorporates the higher order concepts of complexity – based on the non-linear, emergent behavior of multiple agents – is required to model discontinuities and imbalances in the housing markets.

The paper examines the building block concepts required to model the complexity of the housing market and analyzes their implications. These implications can be counter-intuitive and help explain the failure of policy makers to model the recent bust in global housing markets.

The paper finds that policy makers need to adopt an analytical framework that incorporates non-linearity, emergence and other building blocks of complexity in order to construct representative financial models that help understand systemic imbalances that may afflict residential housing markets.

This is the first paper to one's knowledge that argues that policy makers should adopt an alternative theoretical framework based on complexity concepts in order to create more effective financial models; such models should include indicators that provide early warning signals of potential discontinuities in housing markets.

The purpose of this paper is to explore the relationship between low-wealth business founders in the USA and external startup funding. Specifically, the authors test whether a founders’ low personal net worth is correlated with a lower probability of acquiring funding from outside sources during the business creation process.

The authors use a double-hurdle Cragg model to jointly estimate: first, the decision to acquire external financing; and second, the amount received. The sample is the US-based Panel Study of Entrepreneurial Dynamics II (PSED II). The PSED II tracks business founders attempting to start ventures from 2005 to 2012.

Receipt of outside financing during business formation is largely determined by the business founder’s personal finances (controlling for human capital, venture type and industry, and whether money was sought in the first place). A higher household net worth results in larger amounts of external funding received. Low-wealth business founders, therefore, are less likely to get external funds, and they receive lower amounts when they do. The disparity between low-and high-wealth business founders is more pronounced for formal, monitored sources of external financing such as bank loans.

Because the study eliminates survivor bias by using a nationally representative sample of business founders who are in the venture creation process, the findings apply to both successful business founders and those who disengaged during the business creation process. The authors offer insights into the sources and amounts of external funds acquired by individuals across all levels of wealth. The authors accomplish this by disaggregating business founders into wealth quintiles. The study demonstrates the importance of personal wealth as a factor in acquiring external startup financing compared to human capital, industry, or personal characteristics.

If the ability to acquire external funding is significantly constrained, the quality of the opportunity and the skill of the business founder may be less a determinant of success at creating a new business as prior studies have suggested. Consequently, entrepreneurship (as measured by business formation) as a path toward upward, socioeconomic mobility will be afforded only to those individuals with sufficient financial endowments at the outset.

Unlike prior studies, the data used are not subject to survivor bias or an underrepresentation of self-employment. The statistical model jointly estimates acquisition of financing and the amount received. This resolves selection and censoring problems. Finally, the dependent variables directly measure liquidity constraints in the context of business formation, that is, before a new venture is created. Prior research contexts have typically studied existing businesses, and are therefore not true examinations of conditions affecting business creation.