Shaping Dimensions of Urban Complexity: The Role of Economic Structure and Socio-Demographic Local Contexts

Social Indicators Research - Diversification in urban functions—a key component of urban complexity—was analysed using Pielou’s evenness indexes for 12 socioeconomic dimensions...     

Modelling Corruption Perceptions: Evidence from Eastern Europe and Central Asian Countries

Social Indicators Research - This work proposes a multidimensional framework that is based on a latent class model to identify various types of corruption and to outline their importance. A dataset...     

Loss-based approach to two-piece location-scale distributions with applications to dependent data

Two-piece location-scale models are used for modeling data presenting departures from symmetry. In this paper, we propose an objective Bayesian methodology for the tail parameter of two particular distributions of the above family: the skewed exponential power distribution and the skewed generalised logistic distribution. We apply the proposed objective approach to time series models and linear regression models where the error terms follow the distributions object of study. The performance of the proposed approach is illustrated through simulation experiments and real data analysis. The methodology yields improvements in density forecasts, as shown by the analysis we carry out on the electricity prices in Nordpool markets.

     

Some notes on Church's thesis and the theory of games

This paper considers games in normal form played by Turing Machines. The machines are fed as input all the relevent information and then are required to play the game. Some impossibility results are derived for this set-up. In particular, it is shown that no Turing Machine exists which will always play the correct strategy given its opponent's choice. Such a result also generalizes to the case in which attention is restricted to economically optimizing machines only. The paper also develops a model of knowledge. This allows the main results of the paper to be interpreted as stemming out of the impossibility of always deciding whether a player is rational or not in some appropriate sense.     

Using Expert Models in Human Reliability Analysis—A Dependence Assessment Method Based on Fuzzy Logic

In human reliability analysis (HRA), dependence analysis refers to assessing the influence of the failure of the operators to perform one task on the failure probabilities of subsequent tasks. A commonly used approach is the technique for human error rate prediction (THERP). The assessment of the dependence level in THERP is a highly subjective judgment based on general rules for the influence of five main factors. A frequently used alternative method extends the THERP model with decision trees. Such trees should increase the repeatability of the assessments but they simplify the relationships among the factors and the dependence level. Moreover, the basis for these simplifications and the resulting tree is difficult to trace. The aim of this work is a method for dependence assessment in HRA that captures the rules used by experts to assess dependence levels and incorporates this knowledge into an algorithm and software tool to be used by HRA analysts. A fuzzy expert system (FES) underlies the method. The method and the associated expert elicitation process are demonstrated with a working model. The expert rules are elicited systematically and converted into a traceable, explicit, and computable model. Anchor situations are provided as guidance for the HRA analyst's judgment of the input factors. The expert model and the FES‐based dependence assessment method make the expert rules accessible to the analyst in a usable and repeatable way, with an explicit and traceable basis.     

CUSTOMER OWNERSHIP AND QUALITY PROVISION IN PUBLIC SERVICES UNDER ASYMMETRIC INFORMATION

The implementation of projects producing external effects is often a source of disagreement and conflict between hosting and nonhosting communities. The article focuses on the impact of participatory ownership on conflict resolution and social welfare in the presence of asymmetric information and imperfect quality monitoring. We show that in such situations the participatory solution may help solve deadlocks that money transfers to a for‐profit operator cannot solve. The analysis highlights three main factors behind this fact. First, a customer‐owned cooperative internalizes, at least partially, the external effects generated by the project. Second, the alignment of cooperative members' preferences with those of the social planner reduces (in some cases eliminates) the distortions caused by information asymmetries. Third, cooperatives require less costly monitoring than their for‐profit counterparts. We also show that cooperatives' productive inefficiency with respect to for‐profits may emerge endogenously as a consequence of a lower pressure to compete on costs for the market. (JEL H23, L33, P13)     

Strategic choices and strategic management accounting in large manufacturing firms

Journal of Management and Governance - This study examines the relationship between strategic choices and the use of strategic management accounting (SMA) techniques in large manufacturing...     

Measuring the Behavioural Component of the S&P 500 and its Relationship to Financial Stress and Aggregated Earnings Surprises

Scholars in management and economics have shown increasing interest in isolating the behavioural dimension of market evolution. Indeed, by improving forecast accuracy and precision, this exercise would certainly help firms to anticipate economic fluctuations, thus leading to more profitable business and investment strategies. Yet, how to extract the behavioural component from real market data remains an open question. By using monthly data on the returns of the constituents of the S&P 500 index, we propose a Bayesian methodology to measure the extent to which market data conform to what is predicted by prospect theory (the behavioural perspective), relative to the (standard) subjective expected utility theory baseline. We document a significant behavioural component that reaches its peaks during recession periods and is correlated to measures of financial volatility, market sentiment and financial stress with expected sign. Moreover, the behavioural component decreases around macroeconomic corporate earnings news, while it reacts positively to the number of surprising announcements.     

A neural network clustering model for miscellaneous components production planning

The growing importance of providing service to customers, e.g. post-sale assistance, supplying of spare parts, upgrading and integration of new elements in installed systems, enhances the importance of planning and management of upgrading parts in most manufacturing industries. These parts are generally characterized by high technical heterogeneity and have a highly variable and difficult to forecast demand. In some areas (especially the most dynamic, e.g. high-tech products), these kinds of components are quite common, and represent a very strong relation between the manufacturing firm and the market. These parts are generally too many to be efectively supported on a planning database system with individual records and too heterogeneous ( and sometimes with a too high value) to be supported all together in a single record. In this paper, we want to study the application of adaptive techniques for the clustering of these components in classes based on the similarities in their market behaviour in order to build an optimal database for planning production and supplying of these components.