Estimating Housing Prices: A Proposal with Spatially Correlated Data

The price of housing per square meter and the trend observed over the last few years is one of the issues that most concerns Spanish citizens and subsequently their political and economic representatives. However, in spite of the importance of space in the real estate market, official averages do not take into account the spatial correlation of housing prices. In order to solve this handicap, we propose the kriging the mean method to estimate mean housing prices. This method provides the best unbiased linear estimation taking into account spatially correlated data.     

Forecasting with vector autoregressive models of data vintages: US output growth and inflation

Vintage-based vector autoregressive models of a single macroeconomic variable are shown to be a useful vehicle for obtaining forecasts of different maturities of future and past observations, including estimates of post-revision values. The forecasting performance of models which include information on annual revisions is superior to that of models which only include the first two data releases. However, the empirical results indicate that a model which reflects the seasonal nature of data releases more closely does not offer much improvement over an unrestricted vintage-based model which includes three rounds of annual revisions.     

Team vision in product development: How knowledge strategy matters

In today’s more complex multinational and technologically sophisticated environment, the group has re-emerged in importance as the project team. Work teams are important to organizations in general, but are especially critical in product development because they span many functional areas including engineering, marketing, manufacturing, finance, etc., and new product teams must frequently be composed of individuals from different backgrounds and perspectives. In these circumstances, this paper addresses the contingency role that knowledge strategy plays in explaining the relationship between team vision and product development performance. After studying the team vision on 78 new product developments from a wide variety of firms, we found that effective team vision varies depending on the knowledge strategy—defined in terms of punctuated equilibrium in the explorative cycle, low ambidexterity and high ambidexterity. Our results demonstrate that while trade-off is positively associated with success in all strategies, clarity is only associated with low ambidexterity strategies and strategy-fit is only associated with high ambidexterity strategies.     

Corrigendum to “Dynamic multidimensional assessment of sustainability at the macro level: The case of Austria” [Ecological Economics 68 (2009) 2560-2573]

This paper explores the issue of sustainability at the macro scale employing multi-criteria decision aid (MCDA) methods. The incommensurability of values and the essentially multi-dimensional and dynamic nature of sustainability challenge the use of composite measurement indices. This determined the choice of MCDA methods. Austria was chosen as a case study, due to the wide availability of data, especially on indicators of strong sustainability. The structure of the multi-criteria problem comprised the evolution of different sustainability dimensions over time. The process for selecting criteria included a critical assessment of institutional sustainability agendas (UN, EU and Austrian Government) and theoretical recommendations.After an assessment of MCDA methods, the NAIADE method demonstrated the most suitable properties for sustainability assessment. The application of this outranking approach was undertaken in two separate settings: long-term from 1960 to 2003 and medium-term, 1995-2003 with varying numbers of criteria. The response of results to the addition of evaluating criteria and periods was tested. The degree of credibility for accepting preference relations was also employed for sensitivity analysis.According to the results of the long-term assessment, especially in the weak sustainability setting, sustainable progress is taking place in Austria. In the medium term, in the stronger sustainability setting and, especially as the number of criteria increases, more incomparable periods appear and trends are less determined. Moreover, it is shown how results crucially depend on the methodological choices. This is one of the first applications of the multi-criteria tools to the dynamic analysis of sustainability at the macro scale.     

Google Analytics for measuring website performance

Performance measurement of tourism websites is becoming a critical issue for effective online marketing. The aim of this article is to analyse the effectiveness of entries (visit behaviour and length of sessions) depending on their traffic source: direct visit, in-link entries (for instance, en.wikipedia.org), and search engine visits (for example, Google). For this purpose, time series analysis of Google Analytics data is made use of. This method could be interesting for any tourism website optimizer.     

Interactive design of personalised tourism routes

The tourism sector has evolved in recent times, with a transformation in tourists’ preferences and behaviour. They are increasingly abandoning standard tours in favour of more personalised options. New technologies offer easy access to a large amount of tourism information. However, this also means it is difficult for a decision-maker to assess all the possible alternatives for designing a customised trip. Making such decisions may well require the resolution of conflicting objectives. Therefore, in this paper we develop a tool that provides each tourist with the itinerary best suited to their needs. This itinerary can include the desired different activities on an established schedule, bearing in mind the tourist’s wishes and needs, along with the characteristics of the area. This is done by using a mathematical model and interactive multi-criteria techniques. Finally, we will carry out a practical application in the Autonomous Region of Andalusia.     

Corporate governance and impression management in annual results press releases

We study the association between corporate governance and impression management in annual results press releases (ARPRs). Press releases constitute a timely vehicle to communicate firm performance to third parties but they can be manipulated to distort readers’ perceptions of corporate achievements. We predict that governance mechanisms actively monitor managerial disclosures, improving firm transparency and thus reducing impression management in ARPRs. The results confirm that strong governance limits impression management, consistent with governance monitoring effectively reducing self-serving disclosures by management. Our evidence suggests that management disclosure practices respond, at least partly, to informative motivations. We also show that strong governance firms are more likely to release an ARPR.     

Knowledge absorptive capacity: New insights for its conceptualization and measurement

The processes for absorbing external knowledge become an essential element for innovation in firms and in adapting to changes in the competitive environment. Despite the huge growth in the absorptive capacity literature, a methodological gap still remains about a certain ambiguity in the definition of the construct specifying its theoretical domain and dimensionalization, and a lack of validation of the construct in most studies. The aim of this paper is to contribute to the literature on absorptive capacity through the creation and validation of two scales, justified with a thorough analysis of the literature, to measure the key components of the absorptive capacity construct: potential and realized absorptive capacities. The study includes confirmatory factor analysis on a sample of 952 Spanish firms to verify that the scales meet the psychometric properties the literature requires. The study results confirm the validity of the proposed scales and support their consolidation as a commonly used instrument with which to measure absorptive capacity.     

REAL‐TIME FORECASTING OF INFLATION AND OUTPUT GROWTH WITH AUTOREGRESSIVE MODELS IN THE PRESENCE OF DATA REVISIONS

We examine how the accuracy of real‐time forecasts from models that include autoregressive terms can be improved by estimating the models on ‘lightly revised’ data instead of using data from the latest‐available vintage. The benefits of estimating autoregressive models on lightly revised data are related to the nature of the data revision process and the underlying process for the true values. Empirically, we find improvements in root mean square forecasting error of 2–4% when forecasting output growth and inflation with univariate models, and of 8% with multivariate models. We show that multiple‐vintage models, which explicitly model data revisions, require large estimation samples to deliver competitive forecasts. Copyright © 2012 John Wiley & Sons, Ltd.