Bounded socio-technical experiments as agents of systemic change: The case of a zero-energy residential building

Large-scale shifts in dominant technologies are the necessary components of a transition toward sustainability. Such shifts are difficult because, in addition to technological innovation, they require changes in the existing institutions, professional norms, belief systems and, in some cases, also lifestyles. In the languages of cognitive and policy sciences, higher order learning on a scale ranging from individuals to professional and business communities, to the society at large, is needed. Higher order learning is especially crucial in the types of innovations that depend mainly on synthesis of existing technologies and know-how to achieve radical reductions in energy and material consumption, as is the case with high performance buildings. One way to facilitate this type of learning is through experimentation with new technologies and services.Drawing on our earlier concept of a Bounded Socio-Technical Experiment, in this paper we propose a four-level conceptual framework for mapping and monitoring the learning processes taking place in a BSTE, and apply it to an empirical case study of a zero-fossil-fuel residential building in Boston. Three major conclusions are that: learning took place both on the individual and team level, that individual learning primarily (but not exclusively) involved changes in problem definitions; and that team learning consisted of participant turnover until congruence in worldviews and interpretive frames was achieved. This case study also shows that we must think of innovating in building design as both a process and a product, and that both must be considered in the future efforts to replicate this building.This study highlights that technological innovation about technology as much as about people, their perceptions, and their interactions with each other and with the material world. Sustainability will not be reached by technology alone, but by deep learning by individuals, groups, professional societies and other institutions.     

Productive Efficiency of the Swine Industry in Hawaii: Stochastic Frontier vs. Data Envelopment Analysis

Improving productive efficiency is an increasingly important determinant of the future of the swine industry in Hawaii. This paper examines the productive efficiency of a sample of swine producers in Hawaii by estimating a stochastic frontier production function and the constant returns to scale (CRS) and variable returns to scale (VRS) output-oriented DEA models. The technical efficiency estimates obtained from the two frontier techniques are compared. The scale properties are also examined under the two approaches. The industry's potential for increasing production through improved efficiency is also discussed.     

Credit rating dynamics and Markov mixture models

Despite mounting evidence to the contrary, credit migration matrices, used in many credit risk and pricing applications, are typically assumed to be generated by a simple Markov process. Based on empirical evidence, we propose a parsimonious model that is a mixture of (two) Markov chains, where the mixing is on the speed of movement among credit ratings. We estimate this model using credit rating histories and show that the mixture model statistically dominates the simple Markov model and that the differences between two models can be economically meaningful. The non-Markov property of our model implies that the future distribution of a firm’s ratings depends not only on its current rating but also on its past rating history. Indeed we find that two firms with identical current credit ratings can have substantially different transition probability vectors. We also find that conditioning on the state of the business cycle or industry group does not remove the heterogeneity with respect to the rate of movement. We go on to compare the performance of mixture and Markov chain using out-of-sample predictions.     

Learning for Sustainability Transition through Bounded Socio-technical Experiments in Personal Mobility

A bounded socio-technical experiment (BSTE) attempts to introduce a new technology, service, or a social arrangement on a small scale. Many such experiments in personal mobility are ongoing worldwide. They are carried out by coalitions of diverse actors, and are driven by long term and large scale visions of advancing society’s sustainability agenda. This paper focuses on the processes of higher-order learning that occur through BSTEs. Based on the conceptual frameworks from theories of organizational learning, policy-oriented learning, and diffusion of innovation, we identify two types of learning: the first type occurs among the participants in the experiment and their immediate professional networks; the second type occurs in the society at large. Both types play a key role in the societal transition towards sustainable mobility systems. Two case studies, in which the Design for Sustainability Group at Technical University of Delft has participated, provide empirical data for the analysis. One case consists of development of a three-wheeled bike-plus vehicle (Mitka); the second case seeks to solve mobility problems on the Dutch island of Texel. We find that higher order learning of the first type occurs among the BSTE participants and beyond. Learning can be facilitated by deployment of structured visioning exercises, by diffusion of ideas among related BSTEs, by innovative couplings of problems and solutions, and by creating links among related experiments. Government agencies, universities and other intellectual entrepreneurs have key roles to play in making that happen. The cases provide much less insights about the second type of learning. Research on the latter is necessary.     

Genetic engineering in agriculture: New approaches for risk management through sustainability reporting

Genetically modified crops and foodstuff have been highly controversial for environmental, health, and ethical reasons. The controversies have been worldwide, but most prominent in the European Union, for reasons that include distrust of the regulatory authorities, scientists and technocratic decision making. An informal moratorium in the EU came recently to an end, without solving the underlying problems. In response to the criticisms, the European governments have attempted to improve the risk assessment methods and their scientific basis, and to tailor public policies to the growing demand for transparency, accountability, and public participation.This paper proposes a novel approach to including the public in evaluating the impacts of food and agricultural biotechnology and present and future applications modeled after the growing practice of sustainability reporting by companies. The most visible among those, Global Reporting Initiative (GRI), when implemented properly, includes a wide range of stakeholders, including the financial institutions, companies, NGOs and the civil society, in an interactive multi-stakeholder discourse and collaboration. The reporting exercise would open the discussion about the R&D around new GMO products, and could mitigate potential adverse effects in an early stage (Constructive Technology Assessment). We specifically propose initiating a broadly based societal initiative aimed at developing of a new sectoral supplement of GRI Guidelines, specifically designed for the food and agricultural biotechnology sector.This approach can be conceptualized as experimentation on a small scale with a multitude of stakeholders involved (Bounded Socio-Technical Experiment or BSTE) which is an effective venue for higher-order learning among participants. Sustainability reports and BSTEs have been so far applied in limited cases, none of which included highly controversial technologies such as biotechnology; they need further elaboration and testing to become possibly highly effective concepts and tools for mitigating conflicts on the societal implications of emerging technologies, and to lead to better public policies and greater social trust.     

Cost Inefficiency,Size of Firms and Takeovers

This study, using the Cox proportional hazards model, finds that the risk of takeover rises with cost inefficiency. It also finds that a firm faces a significantly higher risk of takeover if its cost performance lags behind its industry benchmark. Moreover, these findings appear to be remarkably stable over the nearly two decades spanned by the sample. The effect of the variables used to measure the risk-size relationship, however, indicates temporal changes. Lastly, the study presents evidence from fixed-effects models of ex post cost efficiency improvements that support the hypothesis that takeover targets are selected based on the potential for improvement.     

Charting the coast: spatial planning for tourism using public participation GIS

Coastal tourism continues to experience sustained growth on a global scale, leading to concerns regarding socio-cultural, economic and environmental impacts. To-date, the explicit integration of tourism development with coastal management has lagged behind more traditional planning concerns, presenting an opportunity and challenge for managers. Spatial planning using public participation geographical information systems (PPGIS) offers one solution for integration that is cognisant of the centrality of place in tourism. PPGIS was used to document spatially explicit data on place values, activities and development preferences along the remote, Aboriginal-managed Port Smith (Purnturrpurnturr) coastline in Western Australia. The research was developed and implemented as a collaborative partnership between Aboriginal custodians and University researchers. Ninety-seven questionnaires containing participatory mapping were conducted with residents and visitors. The participatory mapping approach successfully identified areas of potential conflict and allows tourism planners and managers to implement spatial planning that explicitly recognises and accounts for visitor values and preferences. Tourism, as well as marine spatial planning, can be enhanced by a holistic approach that considers both tangible and intangible socio-spatial data. Such an approach is likely to foster a more nuanced appreciation of what is valued in the landscape, providing greater insights to support sustainable long-term planning.     

Technological substitution forecasting with a model based on biological analogy

Although many models of technological substitution processes exist, only a few deal with multilevel technological substitution and still fewer may be easily applied to forecasting of real multilevel substitution processes. We propose a stochastic model of multilevel technological substitution and a forecasting method based on this model. In the author's opinion, the developed algorithm may be easily applied to forecasting various technological substitution processes. An example of the application of this algorithm to forecasting of world energy consumption is presented. The algorithm makes possible an investigation of the impact of future innovation on the system's behavior.