Matrix Representation of Solution Concepts in the Graph Model for Conflict Resolution with Probabilistic Preferences and Multiple Decision Makers

Group Decision and Negotiation - In this paper, matrix methods are developed to determine stable states in the graph model for conflict resolution (GMCR) with probabilistic preferences with n...     

The Quality of Smallholder Coffee in South Sumatra: The Production of Low-Quality Coffee as a Response to World Demand 1

Improving the quality of Indonesia's coffee exports has been a priority of government and the Association of Indonesian Coffee Exporters for some years. Efforts to achieve this objective have, however, been hampered by misconceptions about the reasons why coffee producers and traders at each point in the marketing network do not deliver a higher quality product. The research reported here shows that price premia for higher quality coffee are not large enough to encourage greater quality enhancement. The world market for low to medium grades, used in the production of instant coffee, is much larger than that for high-quality coffee, and this preference is transmitted in the form of low incentives to improve the product. Failure to understand this has led to government policies which at best do not solve the quality problem and at worst exacerbate it.     

Cardinality-based equality of opportunities

We study possible rankings of opportunity profiles. An opportunity profile is a list of opportunity sets, one for each agent in the society. We compare profiles on the basis of the notion of “equality of opportunities”. Our main results show the necessary and sufficient conditions for this comparison to be made using exclusively the information provided by two cardinal measures: the number of common alternatives in all sets of a given profile and the difference between the number of alternatives in the individual sets. We also show that, under additional axioms, we can combine these criteria only in a weighted procedure or in some lexicographic refinements of a weighted procedure.      

A note on forecasting international tourism demand in Spain

This paper considers the extent to which price and income proxy variables help in forecasting tourist demand in Spain. Contrary to some recent studies, we found that the inputs' contribution in terms of fitting and forecasting is nil when compared with alternative univariate models. Whether these findings are the results of the restrictions embedded in building the proxy inputs or in a poor specification of the dynamics of these models remains to be seen. We also contend that when dealing with medium, long-term forecasting comparisons, the use of the traditional aggregate accuracy measures like RMSE and MAPE help very little in discriminating among competing models. In these situations, predicted annual growth rates may be a better alternative.     

LIQUIDITY,MONEY CREATION AND DESTRUCTION,AND THE RETURNS TO BANKING*

We build on our earlier model of money in which bank liabilities circulate as a medium of exchange. We investigate optimal bank behavior and the resulting provision of liquidity under a range of central bank regulations. In our model, banks issue inside money under fractional reserves, facing the possibility of excess redemptions. Banks consider the float resulting from money creation and make reserve‐management decisions that affect aggregate liquidity conditions. Numerical examples demonstrate positive bank failure rates when returns to banking are low. Central bank interventions may improve banks' returns and welfare through a reduction in bank failure.     

External cooperation and entrepreneurial orientation in industrial clusters

ABSTRACT

The aim of this paper is to examine the relationship between external cooperation and entrepreneurial orientation (EO). This relationship is explored in cluster environment, wherein entrepreneurial organizations compete and cooperate simultaneously to pursue opportunities. The following hypothesis is tested: External cooperation is positively correlated with entrepreneurial orientation. The hypothesis is tested with a correlation analysis on a sample of 77 small-sized enterprises operating in the Malopolska region in Poland, wherein several clusters are active. Additionally, the regression analysis is conducted to examine the associations between inter-organizational cooperation and EO dimensions. The findings confirm that external cooperation is positively correlated with EO. This observation is confronted with a pro-competitive approach that is a constitutional element of the entrepreneurship concept. Moreover, the findings show that the correlation between external cooperation and a firm’s performance is stronger than between some other EO dimensions and performance. Additionally, the findings show the important role of relationships between organizations and their clients. In the paper, several remarks for development of the theory are discussed, including the need for incorporating inter-organizational cooperation into a set of entrepreneurial traits and reflecting it in entrepreneurial orientation scales. The findings confirm the importance of that direction of theory development that focuses on inter-organizational collaboration in the context of entrepreneurship.     

Accelerators as start-up infrastructure for entrepreneurial clusters

ABSTRACT

Infrastructure is commonly conceptualized as a set of facilities that play a critical role in facilitating activities by individuals and organizations. Conventionally, infrastructure is tightly linked to publicly funded projects that facilitate access to key resources and enable diverse activities. Within entrepreneurial clusters research, infrastructure includes universities, research institutions and telecommunication technologies that facilitate entrepreneurial activities. These capital-intensive investments seek to facilitate start-ups emergence by aiding access to markets and development of ideas. Accelerators facilitate the same activities and have only recently been conceptualized as start-up infrastructure. This study builds upon this research stream by elaborating on how accelerators can play this meaningful role at the cluster level. Specifically, and by relying on the analysis of empirical evidence from three distinct studies, we uncover how accelerators provide tangible and intangible dimensions of start-up infrastructure to form a positively reinforcing cycle of entrepreneurial activities. Additionally, our findings allow us to push further the idea that start-up infrastructure development can be an endogenous process involving multiple actors within the cluster. Our empirical findings and the theoretical insights derived from them have meaningful implications for the aforementioned literature, as well as start-up practitioners and policymakers linked to the funding of entrepreneurial clusters.     

Using clustering ensemble to identify banking business models

The business models of banks are often seen as the result of a variety of simultaneously determined managerial choices, such as those regarding the types of activities, funding sources, level of diversification, and size. Moreover, owing to the fuzziness of data and the possibility that some banks may combine features of different business models, the use of hard clustering methods has often led to poorly identified business models. In this paper we propose a framework to deal with these challenges based on an ensemble of three unsupervised clustering methods to identify banking business models: fuzzy c‐means (which allows us to handle fuzzy clustering), self‐organizing maps (which yield intuitive visual representations of the clusters), and partitioning around medoids (which circumvents the presence of data outliers). We set up our analysis in the context of the European banking sector, which has seen its regulators increasingly focused on examining the business models of supervised entities in the aftermath of the twin financial crises. In our empirical application, we find evidence of four distinct banking business models and further distinguish between banks with a clearly defined business model (core banks) and others (non‐core banks), as well as banks with a stable business model over time (persistent banks) and others (non‐persistent banks). Our proposed framework performs well under several robustness checks related with the sample, clustering methods, and variables used.