Dynamic managerial capabilities: Scale development and validation

Studies on dynamic managerial capabilities still have a rather theoretical nature, and there is great difficulty in finding a valid, reliable instrument to measure this construct. The present study contributes to solving this problem: It aims to develop and validate a scale to measure dynamic managerial capabilities. In this investigation, we develop a scale for three factors related to dynamic managerial capabilities: human capital, managerial cognition (already described in the literature), and relationship networks. The prominent finding in this research is the factor that is referred to here as relationship networks.     

Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations

Bio-economic modelling has become a useful tool for anticipating the outcomes of policies and technologies before their implementation. Advances in mathematical programming have made it possible to build more comprehensive models. In an overview of recent studies about bio-economic models applied to land-use problems in agriculture and forestry, we evaluated how aspects such as uncertainty, multiple objective functions, system dynamics and time have been incorporated into models. We found that single objective models were more frequently applied at the farm level, while multiple objective modelling has been applied to meet concerns at the landscape level. Among the objectives, social aspects are seldom represented in all models, when being compared to economic and environmental aspects. The integration of uncertainty is occasionally a topic, while stochastic approaches are more frequently applied than non-stochastic robust methods. Most multiple-objective models do not integrate uncertainty or sequential decision making. Static approaches continue to be more recurrent than truly dynamic models. Even though integrating multiple aspects may enhance our understanding of a system; it involves a tradeoff between complexity and robustness of the results obtained. Land-use models have to address this balance between complexity and robustness in order to evolve towards robust multiple-objective spatial optimization as a prerequisite to achieve sustainability goals.     

Information and Knowledge as Antecedents of Consumer Attitudes and Intentions to Buy and Recommend Fair-Trade Products

The authors propose and empirically test a causal model to understand how the availability of fair-trade information and consumer knowledge about this issue affect consumers’ attitudes and intentions toward fair-trade products. The model is built upon the attitude-behavior paradigm and the premises of agency theory. It is tested through structural equation modeling with a sample of 292 Spanish consumers. The findings are that consumers do not have good knowledge about fair trade and that this is significantly determined by the lack of information about this in the market. It is also observed that consumers’ perceptions about the availability of fair-trade information have negative effects on their concern about this issue and that such information as is available is not effective in reducing consumer skepticism. The research represents an extension of previous fair-trade literature because the role of information and communication in improving consumer attitudes and buying intentions has rarely been explored in the case of ethical products.     

The Impact of Institutional Differences on Derivatives Usage: a Comparative Study of US and Dutch Firms

This paper examines the influence of institutional differences on corporate risk management practices in the USA and the Netherlands. We compare results to surveys in each country using a strategy that corrects for differences over industry and size classes across the Dutch and US samples. We document several differences in the firms’ uses and attitudes towards derivatives and attempt to attribute them to the differences in the institutional environments between the USA and the Netherlands. We find that institutional differences appear to have an important impact on risk management practices and derivatives use across US and Dutch firms.     

Attitudes Towards Immigration: a Trade-Theoretic Approach

The paper uses a three-factor (capital, low- and high-skill labor), two-household (low- and high-skill individuals), two-sector trade model to analyze the determinants of voter attitudes towards immigration under direct democracy, and to identify factors that would be coherent with both the observed increase in the skilled–unskilled wage differential and the stiffening attitudes towards low-skill capital-poor immigration. If the import-competing sector is intensive in the use of low-skill labor, and capital is the middle factor, an improvement in the terms of trade or neutral technical progress in the exporting sector leads nationals to oppose immigration of capital-poor low-skill households. An increase in income inequality is also likely to stiffen attitudes towards this type of capital-poor, low-skill immigration prevalent in Europe until recently.     

Output-inflation tradeoffs in 34 countries

This article examines the responsiveness of real output to the variability of inflation and aggregate demand. In the manner of Lucas (1973), estimates of the output-inflation tradeoff are computed for a large sample of countries. This measure is then correlated with the variances of the inflation rate and the growth rate in nominal income. Because differences in inflation variance (and hence the tradeoff) are viewed as the outcomes of differences in demand variance, correlations between these two variables are also reported. Cross-time and cross-country results provide a good measure of support for Lucas and the notion that attempts to exploit the tradeoff weaken it.     

Issues in the estimation and application of latent structure models of choice

Our paper provides a brief review and summary of issues and advances in the use of latent structure and other finite mixture models in the analysis of choice data. Focus is directed to three primary areas: (1) estimation and computational issues, (2) specification and interpretation issues, and (3) future research issues. We comment on what latent structure models have promised, what has been, to date, delivered, and what we should look forward to in the future.     

Vulnerability and industrial hazards in industrializing countries: an integrative approach

The extra vulnerability of industrializing countries to environmental problems and industrial accidents cannot be understood or solved by a ‘normal’ scientific analysis. Aspects of the social and institutional context must be included, through analyses based on post-normal science. The standard two-dimensional classification of PNS is modified to have axes ‘social ‘and institutional vulnerabilities’ and ‘complexity of technological hazards’. The analysis is mainly applied to the case of the relatively rare accidents with catastrophic potential. In these, the deaths per accident in India, Mexico and Brazil are much greater than in the industrialized countries. This discrepancy arises partly from location of such plants near residential communities for marginalized workers and their families. Other socio-political factors are relevant, as the role of these countries in the global production system, the enforcement of safety and planning laws, quality of housing, and lifestyle of residents. Reducing the vulnerability of industrializing countries will therefore require major social policies and a comprehension of the limits of the normal scientific and economic approaches to such problems.