Technological,management, and persistent innovation in small and medium family firms: The influence of professionalism

We examine the effect of professional management on innovation in family‐owned firms. Since professionalism is a critical but controversial issue that can influence the innovative capacity of family businesses, we aim to determine if professional management improves innovation outcomes from a comprehensive perspective. Using a sample of 583 Spanish family firms, we demonstrate that professionalism in management exerts a positive influence on innovation from both technological (product and process innovation) and management perspectives. We also find that firms managed by external professionals are willing to develop higher innovative activity and that professionalism contributes positively to persistent innovation. Copyright © 2016 ASAC. Published by John Wiley & Sons, Ltd.     

A Longitudinal Examination of the Appraisal Smoothing Hypothesis

Appraisal smoothing, the reduced variability of real estate return series, has been attributed to appraisers being influenced by their own previous value estimates. This hypothesis is tested experimentally. Expert apppraisers from Atlanta were asked to value a hypothetical apartment project in Phoenix. Eight months later, these experts were asked to update their original appraisals given certain market and property changes. At this time, an independent group of Atlanta experts was asked to appraise the property based on the updated conditions. Results support the hypothesis of insufficient adjustment from previous value judgments.     

Grey Relational Analysis and Neural Network Forecasting of REIT returns

This study employs the Grey Relational Analysis (GRA) and Artificial Neural Network (ANN) to measure the impact of key elements on the forecasting performance of real estate investment trust (REIT) returns. To manage risks from a real estate price bubble, the findings of GRA suggest that the REIT is best influenced by industrial production index, lending rate, dividend yield, stock index and its own lagged performance. Consequently, this paper adjusts the parameters from GRA and inserts the key elements into the fitted ANN model by comparing the learning effect of the Back-propagation Neural Network (BPN). This study found that the ranking provided by the GRA is significant in correcting prediction errors using the learning outcome of the BPN. The neural network model proved to minimize error function and was able to adjust weighted values in order to enhance prediction accuracy.     

The Challenges of China

First of all,I want to say that I have been living in China three years and a half and in September when it will be my fourth year,I will go back to my country,Spain.In this time,I have learnt some things about China and everything I have learnt has been by trying to understand