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The purpose of this paper is to describe the way real estate data collection and dissemination can be improved.

The paper investigates that how information entropy fits into real estate research and data using Kelly betting as a framework.

Availability of real estate data is constrained by a host of impediments, paywalls and other archaic practices that limit the way it can be used to make worthwhile progress in the field.

Real-estate data will become available. Those who try to keep data close and restrict their common use will become irrelevant.

Entropy indicates uncertainty and chaos. Using this highly developed and respected area of science as context one can see how real estate research suffers from its present mindset.

A significant amount of research has examined the relationship between transformational leadership and positive follower outcomes such as organizational citizenship behavior (OCB) and task performance. Building on the social exchange theory and referent cognitions theory, this paper explores the propositions that transformational leadership, OCB and task performance relationship are mediated by leader member exchange (LMX) and distributive justice. The purpose of this paper is to explore the underlying mechanism that has a potential to influence the transformational leadership and follower outcomes relationship. The authors also discuss the implications for management theory and practice.

The primary goal of the research is theory building, so the paper is using a conceptual research design.

The authors find the assumption that the supervisors evaluate the performance of their employees and the performance evaluation has a strong influence on the allocation of rewards to be reasonable. Despite being reasonable, in some circumstances, the rewards allocation maybe dictated by upper management or the HR department; thus, the authors will need to gather a few more details in the survey to address this limitation.

This study presents a research model which emphasizes on the role of LMX and distributive justice in the linkage of transformational leadership and positive work outcomes. More specifically, the authors argue that follower outcomes such as OCB and task performance are a result of not only the high-quality LMX between transformational leaders and followers but also the distributive justice perceptions of followers.

The Healthy Work Place (HWP) study investigated methods to improve clinicians’ dissatisfaction and burnout. The purpose of this paper is to identify factors that influenced study enrollment and completion and assess effects of initial clinic site enrollment rates on clinician outcomes, including satisfaction, burnout, stress and intent to leave practice.

In total, 144 primary care clinicians (general internists, family physicians, nurse practitioners and physician assistants) at 14 primary care clinics were analyzed.

In total, 72 clinicians enrolled in the study and completed the first survey (50 percent enrollment rate). Of these, 10 did not complete the second survey (86 percent completion rate). Gender, type, burnout, stress and intervention did not significantly affect survey completion. Hence, widespread agreement about most moral/ethical issues (72 percent vs 22 percent; p=0.0060) and general agreement on treatment methods (81 percent vs 50 percent; p=0.0490) were reported by providers that completed both surveys as opposed to just the initial survey. Providers with high initial clinic site enrollment rates (=50 percent providers) obtained better outcomes, including improvements in or no worsening of satisfaction (odds ratio (OR)=19.16; p=0.0217) and burnout (OR=6.24; p=0.0418).

More providers experiencing workplace agreement completed the initial and final surveys, and providers at sites with higher initial enrollment rates obtained better outcomes including a higher rate of improvement or no worsening of job satisfaction and burnout.

There is limited research on clinicians’ workplace and other factors that influence their participation in survey-based studies. The findings help us to understand how these factors may affect quality of data collecting and outcome. Thus, the study provides us insight for improvement of quality in primary care.

The purpose of this paper is to adapt the design-based learning (DBL) approach for entrepreneurship education. Having in mind the aim to improve the innovative thinking competence of nascent entrepreneurs that operate at the fuzzy front end of innovation, the research identifies key characteristics of the co-design-based learning (Co-DBL) approach for nurturing entrepreneurs in the digital age.

The exploratory research is based on qualitative and quantitative analysis. To get feedback and to evaluate the progress of innovative thinking competence of Co-DBL participants, the pre- and post-co-design workshop surveys were administrated. The statistical analysis of the surveys was carried out to determine the effects of the Co-DBL.

The research has revealed key dimensions relevant to Co-DBL in entrepreneurial learning (features of the project, facilities for project activities, features of the teaching process, features of learning context and assessment) and found the corresponding characteristics. The results of the current study show the perspective of the suggested Co-DBL approach in entrepreneurial learning to improve creativity, analyticity, intuition and flexibility of thinking of nascent entrepreneurs.

This paper presents a new look at co-design that can be applied to entrepreneurship education to enhance innovative thinking, improve the ability of nascent entrepreneurs to identify and create opportunity and to tolerate ambiguity and conditions of uncertainty in the search and development of innovative solutions.

Reports on the Royal Mail′s ′Customer First′ TQM process, where service quality is based on the needs of both external and internal customers. Describes how their performance measurement system ‐ the Customer Perception Index (CPI) ‐ was designed and how its results are used. Concludes that the flexibility of the CPI is its most important feature and that measurement systems have to evolve in order to remain useful.

The purpose of this paper is to show how an optimization model previously published by the authors is employed to study the effects of rent control on income optimization for the owner and the manager, as well as on the principal‐agent relationship. The model explains effects on management, maintenance and housing quality observed under rent control.

The optimization model is developed by applying a transaction cost framework to the context of income structures in investment properties and their management. Rent control is introduced into the model as a rent maximum.

Under rent control, the manager is forced to optimize income solely through cost control, without motivation to provide above minimum services. The owner is unable to optimize income. Income and funds available for management and maintenance are reduced by costs uncontrollable by the owner. Consequently, management and maintenance are reduced, if not eliminated, resulting in deterioration of the housing stock, notwithstanding minimum habitability standards imposed by regulators. This dilemma argues against dropping management entirely and interferes with the owner's quest to find the right incentive structure for the agent.

Rent control is modeled as a cap on rents. Many rent control policies employ a maximum in rent increase instead, with the maximum often linked to inflation. As the results of the model are in line with real‐world observations, this simplification seems to be non‐critical.

Rent control was implemented with the intent to provide affordable housing to the less fortunate in society. Economic and social effects of rent control have since been heatedly discussed, in the public arena and in academia. This paper supports the view that rent control has unintended, negative consequences not only for the property owner, but also for the property manager (who is at the brink of elimination) and for the tenant (as housing quality deteriorates). This paper therefore encourages a renewed discussion and review of rent control policies.

The paper expands existing literature by analyzing the effects of rent control on property management. By using an optimization model, theory‐based results are provided that supplements real‐word observations, which is interesting for both academics and practitioners. Furthermore, the applicability of the previously developed optimization model is strengthened.

The purpose of this paper is to propose a new way to measure risk in real estate investment, which departs from traditional statistical methodology borrowed from finance.

An argument is advanced for the use of so‐called coherent risk measures for real estate investment decisions. Central to this class of measure is the computation of spectral risk, a measure that covers the spectrum of an individual's risk aversion function. Intuition being hard to observe, empirical data from two large databases are presented as support.

At the heart of the controversy is a discussion of the nature of risk and how it should be measured. This paper seeks common ground where peace may be made between these two warring factions. Scenarios are tested wherein different risk aversion functions are used to compute spectral risk for different sectors. Ex‐post analysis shows that reasoning of this nature can lead to improved risk‐adjusted investment results.

The route to finding an appropriate risk measure for real estate investment has been tortuous. It is not certain that the destination has been reached. Complicating the task is a considerable gap between academic and practitioner methodology, the former relying on the mathematics of objective probability, the latter dwelling quite successfully in a habitat of subjective risk measures.

It is widely accepted that risk represents a cost to society. Real estate, as a repository of roughly half the world's wealth, can be viewed as having risk of a structurally different nature. The better understanding of this risk reduces the cost to society.

For practitioners, spectral measures offer formal support for something they have been doing their entire careers: evaluating risk subjectively. The simple dot product of weights and ordered outcomes is an extension of the widely used “Best case – Worse case – Most likely” methodology that has served professionals well for decades. Perhaps a by‐product of spectral measures is to bring academics and field gladiators closer together. If there is merit to a new way of thinking about risk independent of its implementation, real estate investment could benefit from that thinking. Among those who doubt that everything is “normal” are those who believe that previous attempts to explain risk in real estate have fallen far short of the mark. The challenge to those still not satisfied by the spectral approach is to offer an alternative that represents both a departure from and an improvement of the old methods.