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This study aims to show how hedonic methods can be used to compare the performance of the public and private sector housing markets in Costa Rica.

Hedonic price indexes are computed using the adjacent-period method. Average housing quality is measured by comparing hedonic and median price indexes. The relative performance of the public and private sector residential construction is compared by estimating separate hedonic models for each sector. A private sector price is then imputed for each house built in the public sector, and a public sector price is imputed for each house built in the private sector.

The real quality-adjusted price of private housing rose by 12 per cent between 2000 and 2013, whereas the price of private housing rose by 9 per cent. The average quality of private housing rose by 45 per cent, whereas that of public housing fell by 18 per cent. Nevertheless, the hedonic imputation analysis reveals that public housing could not be produced more cheaply in the private sector.

The quality of public housing has declined over time. The hedonic analysis shows that the decline is not because of a lack of competition between construction firms in the public sector. An alternative demand side explanation is provided.

This study applies hedonic methods in novel ways to compare the relative performance of the public and private housing sectors in Costa Rica. The results shed new light on the effectiveness of public sector housing programs.

The purpose of this paper is to (1) investigate the effect of freshness on consumers' willingness to pay, (2) derive static and dynamic pricing strategies and (3) compare the effect of these pricing strategies on a retailer's revenue and food waste. This investigation helps to reveal the potentials of dynamic pricing strategies for building more sustainable business models.

The authors conduct an online experiment to measure consumers' willingness to pay for fresh and three-days’ old strawberries. The impact of freshness on willingness to pay is analysed using univariate tests and regression analysis. Pricing strategies are compared using a Monte Carlo simulation.

The results of this study show that freshness largely determines consumers' willingness to pay and price sensitivity. This renders dynamic pricing a promising strategy from an economic point of view. The results of the simulation study show that food waste can be reduced by up to 53.6% with a dynamic pricing instead of a static pricing strategy in the case that there are as many consumers as strawberry packages in the inventory. Revenue can be increased by up to 10% compared to a static pricing strategy based on fresh strawberries.

This study suggests that food retailers can improve their revenue when switching from static to dynamic pricing. Furthermore, in most cases, food retailers can reduce food waste with a dynamic instead of a static-pricing strategy, which might help to improve their image through a more sustainable business model and attract additional consumers.

This study is the first to analyse the possibility of using food freshness to design a dynamic pricing strategy and to analyse the impact of such a pricing strategy on both, a retailer's revenue and a retailer's food waste.

The intention of this article is to show possible contributions of the concept of autonomous cooperation to enable complex adaptive logistics systems (CALS) to cope with increasing complexity and dynamics and therefore to increase the systems' information-processing capacity by implementing autopoietic characteristics. In order to reach this target, the concepts of CALS and autopoietic systems will be introduced and connected. The underlying aim is to use the concept of self-organization as one of their essential similarities to lead over to the concept of autonomous cooperation as the most narrow view on self-organizing systems, which is discussed as a possible approach to enable systems to handle an increasing quantity of information. This will be analyzed from both a theoretical and an empirical point of view.

This paper aims to develop a methodology to accurately and timely measure movements in housing markets by constructing a continuously estimated house price index.

The continuous index, which is extracted from an additive model that includes the temporal and the locational effects as smooth functions, can be interpreted as an extension of the classical hedonic time-dummy method. The methodology is applied to housing sales from Sydney, Australia, between 2001 and 2011, and compared to three types of discrete indexes.

Discrete indexes turn out to approach the continuously estimated index with decreasing period lengths but eventually become wiggly and unreliable because of fewer observations per period. The continuous index, in contrast, is stable, has favourable robustness properties and is more objective in several ways.

The resulting index tracks movements in the housing market precisely and in “real-time” and is hence suited for monitoring and assessing housing markets. Because turbulence in housing markets is often a harbinger of financial crises, such monitoring tools support policymakers and investors in tailoring their decisions and reactions. Additionally, the index can be evaluated arbitrarily frequently and therefore is well suited for use in property derivatives.

This paper aims at presenting the theoretical concepts of the transdisciplinary case study approach (TCS), which is a research and teaching approach developed and elaborated at the Swiss Federal Institute of Technology (ETH), as a means of transition support.

The paper reveals the historical roots of case studies, transdisciplinarity and sustainable development as teaching and research paradigms. The TCS approach is presented, which has been developed at ETH for supporting transition management of regional, urban, and organizational systems. This approach is entrenched by an ontology that reveals the basic characteristics of ill‐defined transition problems, an epistemology that refers to Probabilistic Functionalism and distinguishes between multi‐layered systemic and normative epistemics, a methodology that includes a set of methods for case representation (including modelling and projection), assessment, and strategy building, and a project management model that refers to more than a dozen TCSs in the field of sustainable development. Problems of validity of TCSs as a research methodology are discussed.

Three major strengths of the TCS approach presented in the paper are: that it is based on three sound paradigms, which focus on different, relevant characteristics of complex, human‐environment systems; i.e. the case study approach, transdisciplinarity and sustainable development, that it is strictly organized according to an elaborated and consistent theoretical framework that includes ontological, epistemological, methodological, and organizational considerations, and that it is itself subject to an ongoing inquiry and adaptation process. All theoretical considerations of the paper are clarified be elaborated examples from the more than 10 years experience with TCS of the authors.

The paper gives a comprehensive overview of the theoretical foundation of TCS that might assist other scientists engaged in case study research and teaching to further develop their approaches. Additionally, relevant topics for further research in the field of TCS are presented which hopefully induce an inspiring discussion among case study researchers.

As far we know, this paper is one of the first that presents a comprehensive and theoretically sound overview of applying transdisciplinary case studies as means of sustainability learning. Thus, it can be seen as a first, crucial step for establishing the new research field of TCS research and a sound research community of complex, transdisciplinary problem solving towards sustainability learning.

In micro cold forming, the high degree of technological dependencies between manufacturing, quality inspection and handling technologies leads to an extremely complex planning of process chains. In addition, the lack of standardised processes and interfaces further complicates the planning. The paper aims to discuss these issues.

In order to provide consistent and comprehensive planning of micro manufacturing processes, this paper discusses a method, which integrates the planning of process flows, the planning of technological dependencies and capabilities, as well as of the corresponding material flow.

The paper presents the micro-process chain planning and analysis (μ-ProPlAn) framework. It consists of a specific modelling method, a simultaneous engineering procedure model for the model creation, as well as of methods for the analysis of technological dependencies and logistic key values along the modelled process chains.

As the results presented in this paper originate from an on-going research project, the paper focuses on a detailed presentation of the modelling methodology and the procedure model.

In practice, the μ-ProPlAn framework provides process designers in the field of micro manufacturing with tools and methods to clearly depict the interdependencies between and within a product's different manufacturing stages.

By following a simultaneous engineering approach, μ-ProPlAn aims to reduce the efforts in process design by supporting the design of manufacturing processes in the early stages of the product design and by providing suitable methods for the analysis of these process chains.

We assessed attempts by federal and state agencies to utilize a Community Oriented Policing and Problem Solving (COPPS) approach to address endangered species and natural resource protection issues in two watersheds in Washington State involving listed species of salmon, steelhead and bull trout. In the wake of the listing of these species, NOAA Fisheries and the Washington Department of Fish and Wildlife (WDFW) joined to implement a multi-party collaboration to enforcement termed Resource-Oriented Enforcement (ROE). We sought to determine if federal and state resource agencies can collaborate effectively and if collaborative approaches can achieve short- and long-term resource protection goals. A citizen mail survey (n=800+ in each location) and extensive personal interviews with key actors were conducted to assemble evidence on the degree of success achieved in implementing ROE. Observed results suggest that collaboration can

The evolution of tourism must be framed into policies that aim a development model perspective for the destinations, based on the analysis of economic, political, and social indicators. Therefore, emerging destinations, located in territories with low population density, should be a target of a careful strategy policy, considering the characteristics of the region. In particular, the disaster caused by the pandemic context (i.e., COVID-19) implied profound changes in tourism thinking, planning, and development of regions in Portugal and throughout the world. The present chapter proposes the creation of a tourism monitoring system for Arouca (Portugal), a territory classified as Low-Density Territory, with specific characteristics. The monitoring will involve the planning and management of database, at the disposal of all stakeholders, ensuring that the tourism flows in analysis do not get overwhelmed, allowing the discussion of opportunities and threats for the territory, based on the partnership between the population, public and private sector, adjusted to the social, cultural, economic, and environment perception. Will also be considered the perspective of the local community from Arouca's region, the main actors from the territory such as Geopark Association of Arouca and the City Council, according to the surveys used as data basis of this study, along with statistics analysis.

Insofar as the digital layer cannot be detached from the current democratic challenges of the 21st century including neoliberalism, scales, civic engagement and action research-driven co-production methodologies; this chapter advances trends, aftermaths and emancipatory strategies for the post-pandemic technopolitical democracies. Consequently, it suggests a democratic toolbox encompassing four intertwined trends, aftermaths and emancipations including (1) the context characterised by the algorithmic nations, (2) challenges stemming from data sovereignty, (3) mobilisation seen from the digital rights perspective and (4) grassroots innovation embodied through data co-operatives. This chapter elucidates that in the absence of coordinated and interdependent strategies to claim digital rights and data sovereignty by algorithmic nations, on the one hand, Big Tech data-opolies, and on the other hand, the GDPR led by the European Commission might bound (negatively) and expand (positively), respectively, algorithmic nations' capacity to mitigate the negative side effects of the algorithmic disruption in Western democracies.