Firms in international trade: importers’ and exporters’ heterogeneity in Italian manufacturing industry

Combining data on structural characteristics and economic performance for a large sample of Italian firms with data on exporting and importing activity, we uncover evidence supporting recent theories on firm heterogeneity and international trade, together with some new facts. In particular, we find that importing is associated with substantial firm heterogeneity. First, we document that trade is more concentrated than employment and sales, and show that importing is even more concentrated than exporting both within sectors and along the sector- and country-extensive margins. Second, while supporting the fact that firms involved in both are the best performers, we also find that firms involved only in importing activities perform better than those involved only in exporting. Our evidence suggests there is a strong self-selection effect in the case of importers and the performance premia of internationalised firms correlate relatively more with the degree of geographical and sectoral diversification of imports.

Business life cycle and capital structure: evidence from Chinese manufacturing firms

This paper uses a panel data-fixed effect approach and data collected from Chinese public manufacturing firms between 1999 and 2011 to investigate the impacts of business life cycle stages on capital structure. We find that cash flow patterns capture more information on business life cycle stages than firm age and have a stronger impact on capital structure decision-making. We also find that the adjustment speed of capital structure varies significantly across life cycle stages and that non-sequential transitions over life cycle stages play an important role in the determination of capital structure. Our study indicates that it is important for policy-makers to ensure that products and financial markets are well-balanced.

Bio-inspired ant colony optimization based clustering algorithm with mobile sinks for applications in consumer home automation networks

With the fast development of wireless communications, ZigBee and semiconductor devices, home automation networks have recently become very popular. Since typical consumer products deployed in home automation networks are often powered by tiny and limited batteries, one of the most challenging research issues is concerning energy reduction and the balancing of energy consumption across the network in order to prolong the home network lifetime for consumer devices. The introduction of clustering and sink mobility techniques into home automation networks have been shown to be an efficient way to improve the network performance and have received significant research attention. Taking inspiration from nature, this paper proposes an Ant Colony Optimization (ACO) based clustering algorithm specifically with mobile sink support for home automation networks. In this work, the network is divided into several clusters and cluster heads are selected within each cluster. Then, a mobile sink communicates with each cluster head to collect data directly through short range communications. The ACO algorithm has been utilized in this work in order to find the optimal mobility trajectory for the mobile sink. Extensive simulation results from this research show that the proposed algorithm significantly improves home network performance when using mobile sinks in terms of energy consumption and network lifetime as compared to other routing algorithms currently deployed for home automation networks.