Modelling tourism flows through gravity models: a quantile regression approach

Gravity models are widely used to study tourism flows. The peculiarities of the segmented international demand for agritourism in Italy are examined by means of a novel approach: a panel data quantile regression. We characterize the international demand for Italian agritourism with a large data set, by considering data of 33 countries of origin, from 1998 to 2010. Distance and income are the major determinants, but we also found that mutual agreements and high urbanization rates in countries of origin are associated with larger flows of incoming tourists.     

Fiscal rule compliance,poverty and social exclusion in the Eurozone

This paper develops a simple model of the effects of fiscal adjustments on poverty. Our theory suggests that in richer countries the effects of fiscal adjustment are stronger the more complex is the poverty measure. By examining a panel of 16 EU countries in the period 2005–2015, the paper finds that structural public balance adjustments may harm the welfare of poorer individuals. The empirical estimation hinges on a comprehensive index of poverty and social exclusion, the AROPE index. The results suggest that rigid fiscal rules require specific alternative policies to sustain the welfare of poorer individuals during downturns.     

Financial Literacy: The Role of the Local Context

In this article, we investigate the role of local factors associated with the financial literacy of Italian adults (no. 945). Using a multilevel regression model, together with the common socioeconomic and sociodemographic variables already used in previous studies, we also add certain environmental variables at the local level. We separately analyze the three indexes that define the OECD financial literacy index—Financial Attitude Index (FAI), Financial Knowledge Index (FKI), and Financial Behavior Index (FBI)—because they show a dynamic of their own in each region. Our findings confirm that the FKI and the FAI are associated to some extent with environmental traits, while the FBI is not. We conclude that not only the sociodemographic and socioeconomic conditions of individuals but also certain features of the regional context where they live have an impact on their financial literacy. Consequences for financial education programs are highlighted.     

A latent class conjoint analysis for the Administrative Clerk figure: insights from ELECTUS

Quality & Quantity - ELECTUS is a multi-centre research project with the aim to stabilize the relationship between universities and companies. Through this project, it is possible to acquire...     

“To Own or Not to Own?” A Study on the Determinants and Consequences of Alternative Intellectual Property Rights Arrangements in Crowdsourcing for Innovation Contests

Firms are increasingly engaging in crowdsourcing for innovation to access new knowledge beyond their boundaries; however, scholars are no closer to understanding what guides seeker firms in deciding the level at which to acquire rights from solvers and the effect that this decision has on the performance of crowdsourcing contests. Integrating property rights theory and the problem‐solving perspective while leveraging exploratory interviews and observations, we build a theoretical framework to examine how specific attributes of the technical problem broadcast by firms affect the seekers’ choice between alternative intellectual property rights (IPR) arrangements that call for acquiring or licensing‐in IPR from external solvers (i.e., with high and low degrees of ownership, respectively). Each technical problem differs in the knowledge required to be solved as well as in the stage of development of the innovation process and seeker firms pay great attention to such characteristics when deciding about the IPR arrangement they choose for their contests. In addition, we analyze how this choice between acquiring and licensing‐in IPR, in turn, influences the performance of the contest. We empirically test our hypotheses analyzing a unique dataset of 729 challenges broadcast on the InnoCentive platform from 2010 to 2016. Our results indicate that challenges related to technical problems in later stages of the innovation process are positively related to the seekers’ preference toward IPR arrangements with a high level of ownership, while technical problems involving a higher number of knowledge domains are not. Moreover, we found that IPR arrangements with a high level of ownership negatively affect solvers’ participation and that IPR arrangement play a mediating role between the attributes of the technical problem and the solvers’ self‐selection process. Our paper contributes to the open innovation and crowdsourcing literature and provides practical implications for both managers and contest organizers.     

Cross-country diffusion of photovoltaic systems: Modelling choices and forecasts for national adoption patterns

In this paper we propose an innovation diffusion framework based on well-known Bass models to analyze and forecast national adoption patterns of photovoltaic installed capacity. This allows for interesting comparisons among several countries and in many cases highlights the positive effect of incentive policies in stimulating the diffusion of such a technology. In this sense, the Generalized Bass Model proves to be essential for modelling and forecasting. On this basis, we observe important differences in the investments made by countries in the PV sector and we are able to identify whether and when these investments obtained the expected results. In particular, from our analysis it turns out that in some cases incentive measures have been certainly effective in facilitating adoption, while in some others these have not been able to produce real feed-back. Moreover, our cross-country approach is able to forecast different stages in PV evolution: whereas some countries have already entered the mature stage of diffusion, others have just begun. This result may suggest various considerations about the competitive advantage of those countries that invested in alternative energy provisions. In spite of a very diversified scenario in terms of historical patterns of diffusion, we may report, as a general result, the fragile role of innovators for this special market and the dominance of imitative behaviour in adoptions.     

Market potential dynamics in innovation diffusion: Modelling the synergy between two driving forces

The presence of a slowdown in new product life cycles has recently received notable attention from many innovation diffusion scholars, who have tried to explain and model it on a dual-market hypothesis (early market-main market). In this paper we propose an alternative explanation for the slowdown pattern, a dual-effect hypothesis, based on a recent co-evolutionary model, where diffusion results from the synergy between two driving forces: communication and adoption. An analysis of the synergistic interaction between communication and adoption, based on the likelihood ratio order or on a weak stochastic order, can inform us of which of the two had a driving role in early diffusion. We test the model on the sales data of two pharmaceutical drugs presenting a slowdown in their life cycle and observe that this is identified almost perfectly by the model in both cases. Contrary to the general expectation, according to which communication should precede adoption, our findings show that adoptions may be the main driver in early life cycle; this may be related to the drug's specific nature.     

Modelling a dynamic market potential: A class of automata networks for diffusion of innovations

Innovation diffusion processes are generally described at aggregate level with models like the Bass Model (BM) and the Generalized Bass Model (GBM). However, the recognized importance of communication channels between agents has recently suggested the use of agent-based models, like Cellular Automata. We argue that an adoption or purchase process is nested in a communication network that evolves dynamically and indirectly generates a latent non-constant market potential affecting the adoption phase.Using Cellular Automata we propose a two-stage model of an innovation diffusion process. First we describe a communication network, an Automata Network, necessary for the “awareness” of an innovation. Then, we model a nested process depicting the proper purchase dynamics. Through a mean field approximation we propose a continuous representation of the discrete time equations derived by our nested two-stage model. This constitutes a special non-autonomous Riccati equation, not yet described in well-known international catalogues. The main results refer to the closed form solution that includes a general dynamic market potential and to the corresponding statistical analysis for identification and inference. We discuss an application to the diffusion of a new pharmaceutical drug.