Business strategies and the transition to low‐carbon cities

Cities are key drivers of global climate change, with the majority of greenhouse gas (GHG) emissions being tied to urban life. Local actions to mitigate and adapt to climate change are essential for stabilization of the global climate and can also help to address other urban ecological problems such as pollution, decreasing biodiversity, etc. Companies are important urban actors in the development of low‐carbon cities because they provide a multitude of goods and services to city populations and directly influence urban carbon dioxide (CO₂) emissions. This is a new area of research. While studies on corporate sustainability are numerous, there is little, if any, existing research that examines the role of companies in climate change adaptation and mitigation within specific urban areas. Urban ecologists also have not examined how corporate activity affects urban systems. Taking a multi‐disciplinary systems approach, we present a conceptual model of the role of companies in managing urban interactions with the climate system. We also present empirical findings illustrating how one company ‘partners’ with the city of Rotterdam to test electric vehicles as a pilot project for urban climate adaptation and mitigation. Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment.     

Interpretation problems of the partial correlation with nonnormally distributed variables

The partial correlation is a commonly used measure for assessing the bivariate correlation of two quantitative variables after eliminating the influence of one or more other variables. The partial correlation is generally interpreted as the correlation that would result if the variables to be eliminated were fixed (not allowed to vary and influence the other variables), which is referred to in the statistical literature as conditional correlation. The present paper demonstrates, by means of theoretical derivations and practical examples, that when the assumption of multivariate normality is violated (e.g., as a result of nonlinear relationships among the variables investigated) the usual interpretation of the partial correlation coefficient will be basically incorrect. In extreme cases the value of the partial correlation coefficient may be strongly positive, close to 1, whereas the conditional correlation may have a large negative value. To solve this problem the paper suggests to partial out a certain function (in most cases the square) of the variables whose effects are to be eliminated if nonlinear relationships are likely to occur.     

Self-reinforcing effects between housing prices and credit

The financial crisis has brought the interaction between housing prices and household borrowing into the limelight of the economic policy debate. This paper examines the nexus of housing prices and credit in Norway within a structural vector equilibrium correction model (SVECM) over the period 1986q2–2008q4. The results establish a two way interaction in the long-run, so that higher housing prices lead to a credit expansion, which in turn puts an upward pressure on prices. Interest rates influence housing prices indirectly through the credit channel. Furthermore, households’ expectations about the future development of their own income as well as in the Norwegian economy have a significant impact on housing price growth. Dynamic simulations show how shocks are propagated and amplified. When we augment the model to include the supply side of the housing market, these effects are dampened.     

Spanning with futures contracts

Regression-based testing techniques have long been used to quantify whether the efficient frontier of a set of assets spans the frontier of a larger collection of investments. This paper derives regression-based spanning tests for the case in which the investment possibilities set contains, or is constituted by, futures contracts for which marked-to-market margins are explicitly taken into account. Two empirical applications illustrate our results.     

The Creation of Value Through Corporate Reputation

The relationship between social and financial performance (CSP – FP) has been a main objective in the literature on business management, as it would provide an economic justification for the social investment insofar as it contributes to the creation of value. This relationship has been empirically tested by several authors though without using a theoretical model that sustains this relationship. The aim of this article is to propose a theoretical model of the process of the creation of value from the reputation generated by companies, integrating the factors that have been shown to be more relevant in this process from previous research, in such a way that hypotheses are put forward regarding the existence of this relationship and the factors that determine it. Finally, an empirical test is performed using the 100 most prestigious companies operating in Spain during 2004.     

Harnessing a network of experts for competitive advantage: technology scouting in the ICT industry

In order to identify discontinuous technological change and develop appropriate action, companies are increasingly building technology foresight (TF) practices. This paper explores how, using networks of experts, TF capabilities can be built. On the basis of three case studies and 43 interviews, it is shown that building foresight systems through networks of scouts yields several benefits, including the support for sourcing external technologies. Using insights from the three major telecommunication incumbents in Europe, the paper describes and discusses (1) what can be achieved by technology scouting, (2) how a process can be set up, (3) what is important in the design of a scouting network, and (4) the characteristics that should be aimed for when choosing technology scouts. The paper contributes to the methodological base of corporate foresight, to the technology management literature, and to the understanding of how companies can increase their open‐innovation capabilities by extending the intertwinement with their environment.     

Kriging methodology for regional economic analysis: Estimating the housing price in Albacete

Because of the socioeconomic importance of the housing subsector in the local, regional, and national economy and its implications for housing policy, this paper attempts to analyze the spatial behavior of the free housing price in the city of Albacete. To achieve this aim, the authors have used the models and estimators imported from geology called kriging. To do this, it is necessary to know the spatial dependence structure of the process, which is shown in the variogram.     

Heterogeneous Firm‐Level Effects of Knowledge Exchanges on Product Innovation: Differences between Dynamic and Lagging Product Innovators*

Product innovation is the result of a constant interaction between the in‐house research and development (R&D) department and knowledge exchanges with the firm's environment. Knowledge exchanges come in different forms. They break down into information gathering applied in new product development, research cooperation on particular innovation projects, and managing information outflows allowing the consequent appropriation of the results of product innovation through specific methods. The way firms handle knowledge exchanges affects their performance. This paper looks at three related indicators of performance: (1) research intensity (a measure of innovative input); (2) the share of revenue realized through innovative product sales (a measure of innovative output); and (3) their impact on the growth in total revenue. The bulk of the econometric literature looking into these matters only allows general statistical statements on the behavior of an “average” firm. This paper takes on another view by using the quantile regression method to stress the heterogeneity of innovative firms in their dealing with knowledge exchange and the effect this has on their performance. A first key finding is that research intensity is positively influenced by knowledge externalities, research cooperation, and appropriability, and it is through this that these variables affect innovative revenue and also the growth in total revenue. By using quantile regression these relationships are further refined to screen for differences in behavior between dynamic and lagging innovators. This refinement indicates that, in the case of research intensity, the knowledge externalities gain in importance in the higher quantiles and are insignificant in the lower ones. Next, research cooperation remains important in all quantiles, but a higher significance is observed in the higher quantiles as well. Finally, appropriability is extremely important for the lower quantiles, but it becomes insignificant in the highest. These findings corroborate the assumptions made in the literature on open innovation: knowledge externalities and research collaboration are vital for those opening up their firm for new ideas and who are, at the same time, reluctant to protect their findings through specific appropriation measures. In the case of innovative revenue all variables on knowledge exchange operate through the research intensity irrespective of the quantile, although the impact of research intensity on this type of revenue is higher in the upper quantiles. As for the growth in revenue, the effect of the innovative revenue is, again, higher in the higher quantiles. This suggests that dynamic product innovators have the most efficient R&D process and the strongest growers are so, especially, because they are successful product innovators.