SALES AND COLLUSION IN A MARKET WITH STORAGE

Sales are a widespread and well‐known phenomenon documented in several product markets. This paper presents a novel rationale for sales that does not rely on consumer heterogeneity, or on any form of randomness to explain such periodic price fluctuations. The analysis is carried out in the context of a simple repeated price competition model, and establishes that firms must periodically reduce prices in order to sustain collusion when goods are storable and the market is large. The largest equilibrium profits are characterized at any market size. A trade‐off between the size of the industry and its profits arises. Sales foster collusion, by magnifying the inter‐temporal links in consumers' decisions.     

Experimental Games on Networks: Underpinnings of Behavior and Equilibrium Selection

In this paper, we describe a series of laboratory experiments that implement specific examples of a general network structure. Specifically, actions are either strategic substitutes or strategic complements, and participants have either complete or incomplete information about the structure of a random network. Since economic environments typically have a considerable degree of complementarity or substitutability, this framework applies to a wide variety of settings. We examine behavior and equilibrium selection. The degree of equilibrium play is striking, in particular with incomplete information. Behavior closely resembles the theoretical equilibrium whenever this is unique; when there are multiple equilibria, general features of networks, such as connectivity, clustering, and the degree of the players, help to predict informed behavior in the lab. People appear to be strongly attracted to maximizing aggregate payoffs (social efficiency), but there are forces that moderate this attraction: (1) people seem content with (in the aggregate) capturing only the lion's share of the efficient profits in exchange for reduced exposure to loss, and (2) uncertainty about the network structure makes it considerably more difficult to coordinate on a demanding, but efficient, equilibrium that is typically implemented with complete information.     

Penalized likelihood inference in extreme value analyses

Models for extreme values are usually based on detailed asymptotic argument, for which strong ergodic assumptions such as stationarity, or prescribed perturbations from stationarity, are required. In most applications of extreme value modelling such assumptions are not satisfied, but the type of departure from stationarity is either unknown or complex, making asymptotic calculations unfeasible. This has led to various approaches in which standard extreme value models are used as building blocks for conditional or local behaviour of processes, with more general statistical techniques being used at the modelling stage to handle the non-stationarity. This paper presents another approach in this direction based on penalized likelihood. There are some advantages to this particular approach: the method has a simple interpretation; computations for estimation are relatively straightforward using standard algorithms; and a simple reinterpretation of the model enables broader inferences, such as confidence intervals, to be obtained using MCMC methodology. Methodological details together with applications to both athletics and environmental data are given.     

EXTERNAL AIDS FOR SOCIAL MEMORY

Collective or social memories are not just a way for accumulating and preserving but also for sharing and developing knowledge. Indeed, as knowledge is made explicit and elaborated by a community, it enriches the local culture and the current practices, becoming a basis for communication and learning. This paper addresses the concept of 'social memory' in a specific 'community of practice': teachers and students of primary schools. The work is developed within HIPS1 (Hyper Interaction within Physical Space), a three-year (1997-2000) research project funded by the European Commission within the I 3 (I-Cube) Programme. HIPS is a hand-held location-aware tourist guide that delivers information related to the surrounding space mainly reacting to the physical movements of visitors (Benelli et al . 1999). The guide is designed to minimize the boundary between the physical space and the related information through a number of situated and contextual-aware interaction mechanisms. In the paper we present a specific application of HIPS as tool to support the creation of a social memory. First, we illustrate the theoretical framework, the cultural psychology (Vygotsky 1978), which we adopted to design the tool as an external aid for social memory. Afterwards we describe the user study and the design process that resulted in the development of an early prototype. The conclusions are a reflection about the use of new technology to open new learning opportunities for students.     

A note on the decidability of de Finetti's coherence

To check the de Finetti coherence of a putative probability assigned to a classA of events, we must know the possible combinations of truth values (constituents) of any finite class of events inA. Even for a very simple, finite,A this can be impossible. In this case the notion of DF coherence cannot be applied to some or all the putative probabilities on this class of events.     

Decomposition by subpopulations of the Zenga-84 inequality curve and the related index $$\zeta $$: an application to 2014 Bank of Italy survey

Statistical Methods & Applications - This paper describes an innovative procedure to decompose by subpopulations the values assumed by the Zenga-84 inequality curve Z(p). This decomposition...     

Combining Linear and Non-Linear Objectives in Spanning Tree Problems

A classical approach to multicriteria problems asks for the optimization of a suitable linear combination of the objectives. In this work we address such problems when one of the objectives is the linear function, the other is a non-linear one and we seek for a spanning tree of a given graph which optimizes the combination of the two functions. We consider both maximization and minimization problems and present the complexity status of 56 such problems, giving, whenever possible, polynomial solution algorithms.     

Explaining performing R&D through alliances: Implications for the business model of Italian dedicated biotech firms

In recent years management scholars and practitioners have been interested in Research and Development (R&D) partnering, especially in high-tech industries. While the motivations of research partnership formation have been widely explored in literature, little attempt has been undertaken to examine the effects of research partnerships on R&D productivity and the implications for business models of the new ventures. In this paper we try to shed some light on the business models of the young ventures involved in R&D partnerships and their effect on R&D productivity. Our hypotheses are that experience in previous alliances, repeated partnerships and tight relationships have positive effects on R&D productivity while rigid governance structures and public R&D subsidies have negative effects on such productivity. We discuss how these aspects affect the business models of biotech firms. We test our hypotheses on a sample of 55 Italian DBFs (Dedicated Biotech Firms). Results support our hypotheses. Managerial implications and further issues for future research are discussed.     

Robust inference for parsimonious model-based clustering

We introduce a robust clustering procedure for parsimonious model-based clustering. The classical mclust framework is robustified through impartial trimming and eigenvalue-ratio constraints (the tclust framework, which is robust but not affine invariant). An advantage of our resulting mtclust approach is that eigenvalue-ratio constraints are not needed for certain model formulations, leading to affine invariant robust parsimonious clustering. We illustrate the approach via simulations and a benchmark real data example. R code for the proposed method is available at https://github.com/afarcome/mtclust.