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Investment opportunities, corporate governance quality, and firm performance in the UAE
No full textInternational audiencePurpose – This paper examines the influence of investment opportunities on firm performance and evaluates corporate governance practices in the United Arab Emirates (UAE) to determine whether corporate governance quality moderates that influence.Design/methodology/approach – A fixed-effects regression was employed to examine the influence of investment opportunities on firm performance and the role of corporate governance quality as a moderator for all listed firms on the Abu Dhabi Stock Exchange (ADX) and the Dubai Financial Market (DFM). We examined 501 firm-year observations for the period when the corporate governance code in the UAE was coming into force, from 2008 to 2012.Findings – The regression results indicate that investment opportunities have a negative influence on firm performance. The corporate governance index used here shows that the level of corporate governance practiced in the UAEis weak.Wealso find that strong corporate governance ameliorates the negative influence of investment opportunities, which supports our hypotheses. The sub-indices of corporate governance that matter the most for moderating investment opportunities are board functioning and ethics.Practical implications – The results of this paper reflect the need to examine corporate governance in the context of the external environment represented by investment opportunities in our study. The findings could raise awareness of the importance of strong corporate governance practices, not only to directly improve firm performance but also through its influence on external variables. Legislators, regulators and other interested parties could use these results to examine practices in the UAE following the implementation of the corporate governance code.Originality/value – This study contributes to the literature by evaluating the role that corporate governance quality and its components could play in firm performance and indirectly moderating other external factors (such as investment opportunities)
Do mutual funds have consistency in their performance?
No full textInternational audienceUsing a comprehensive data set of 714 Chinese mutual funds from 2004 to 2015, the study investigates these funds’ performance persistence by using the Capital Asset Pricing model, the Fama-French three-factor model and the Carhart Four-factor model. For persistence analysis, we categorize mutual funds into eight octiles based on their one year lagged performance and then observe their performance for the subsequent 12 months. We also apply Cross-Product Ratio technique to assess the performance persistence in these Chinese funds. The study finds no significant evidence of persistence in the performance of the mutual funds. Winner (loser) funds do not continue to be winner (loser) funds in the subsequent time period. These findings suggest that future performance of funds cannot be predicted based on their past performance
The investor that could and would: The effect of proactive personality on sustainable investment choice
No full textInternational audienceThis paper investigates the influence of exposure to environmental images and proactive personality on investor preferences for sustainable investment. Building on Barbara Fredrickson’s broaden and build theory of positive emotions, we investigated how exposure to images of nature in a healthy (positive) versus damaged (negative) state interacts with the proactive personality trait in influencing an investor’s willingness to forego financial return to invest in a sustainable investment option. The results of our experiment indicate that to stimulate sustainable investment, investors should be exposed to positive environmental pictures and that this effect is stronger for highly proactive individuals. These results suggest that proactive individuals in particular view sustainable investing as a way to promote environmental preservation. Our results hold even after controlling for wealth effects
Protecting Environment or People? Pitfalls and Merits of Informal Labour in the Congolese Recycling Industry
No full textInternational audienceDespite the fact that informal labour is a widespread phenomenon, the business ethics literature tends to describe it as a problem that needs to be overcome, rather than contemplating its merits. Informal labour is linked to poor working conditions, low-income and insufficient protection. However, it is also a survival strategy and upholds essential services, such as waste collection and recycling. Through the lens of postmodern ethics, we analyse 45 interviews with formal and informal waste management workers in Kinshasa. The study explores the functioning and limits of recycling services in a metropolis, focusing on the experience of African workers and entrepreneurs. A complex picture of ethical challenges and individual business and survival strategies emerges from the analysis. Our findings demonstrate that labour decisions of voiceless people cannot be reduced to being rational or desperate choices, but that they reflect a careful elaboration of currently available options and strategies for the future. The study contributes to our understanding of entrepreneurship in a post-conflict context, the role of informal labour in the functioning of formal businesses in Africa and the contribution of postmodern theory to the study of businesses in non-Western societies
A New Hybrid Wavelet-Neural Network Approach for Forecasting Electricity
No full textInternational audienceThis study investigates the performance of a novel neural network technique in the problem of price forecasting. To improve the prediction accuracy using each model’s unique features, this research proposes a hybrid approach that combines the -factor GARMA process, empirical wavelet transform and the local linear wavelet neural network (LLWNN) methods, to form the GARMA-WLLWNN process. In order to verify the validity of the model and the algorithm, the performance of the proposed model is evaluated using data from Polish electricity markets, and it is compared with the dual generalized long memory -factor GARMA-G-GARCH model and the individual WLLWNN. The empirical results demonstrated the proposed hybrid model can achieve a better predicting performance and prove that is the most suitable electricity market forecasting technique
The drivers of Bitcoin trading volume in selected emerging countries
No full textInternational audienceWhile most of the debates about cryptocurrencies are centered on the global Bitcoin market, in thisarticle, we focus on local Bitcoin trading volume in 21 emerging countries. In particular, we attempt todetermine the drivers of Bitcoin trading volume in these countries over the period August 1st, 2015 – June2nd, 2018. Based on VECM and ARDL models, we find evidence of significant relationship between thelocal Bitcoin trading volume in each country and the associated banking system access, especially in theshort-run. Moreover, altcoins (Ethereum, Ripple) prices are shown to affect positively and significantlythe local Bitcoin trading volume for most countries in the long-run (VECM results) and the short-run (ARDL results)
An integrated production scheduling and delivery route planning with multi-purpose machines: A case study from a furniture manufacturing company
No full textInternational audienceRecently, many modern industries have adopted joint scheduling of production and distribution decisions. Such coordination is necessary in make-to-order (MTO) businesses, where it is challenging to achieve timely delivery at minimum total cost and meet the requirements for high customization. To deal with these challenges, a practical production configuration and delivery method is required, in addition to a closer link between production and distribution schedules. Hence, in this study, we address an integrated production scheduling-vehicle routing problem with a time window, where it is assumed that production is performed in a flexible job-shop system. Our framework is modeled as a novel bi-objective mixed integer problem, in which the first objective function aims to minimize a sum of the production and distribution scheduling costs, and the second objective function tries to minimize a weighted sum of delivery earliness and tardiness. To practically validate the application of our framework, a case study from a furniture manufacturing company producing customized goods is considered, and experimental data are derived. Based on the real data, the model is first optimally solved by an e-constraint method, and then a Hybrid Particle Swarm Optimization (HPSO) algorithm is developed to solve the model for medium- and large-sized problems in a reasonable time. We discuss the benefits of integration by comparing the results of the proposed model with that of the separate approach. The results show that the company can establish a proper rational balance between cost and customer concerns, and they can use the integration policy as a lever to improve customer satisfaction without the system experiencing a significant increase in total operational cost
Split-share reforms and capital structure adjustment in China: a dynamic panel fractional estimation
No full textInternational audienceThe purpose of this study is to explain the adjustment rate toward the target capital structure of Chinese nonfinancial listed firms and to investigate the impacts of the split-share reforms (2005–2006) on the capital structure adjustment rate
Information and Operational Decision Sciences: The Interplay of Information Technology and Operational Decision Sciences
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On the predictability of crude oil market: A hybrid multiscale wavelet approach
No full textInternational audiencePast research indicates that forecasting is important in understanding price dynamics across assets. We explore the potentiality of multiscale forecasting in the crude oil market by employing a wavelet multiscale analysis on returns and volatilities of Brent and West Texas Intermediate crude oil indices between January 1, 2001, and May 1, 2015. The analysis is based on a shift-invariant discrete wavelet transform, augmented by an entropy-based methodology for determining the optimal timescale decomposition under different market regimes. The empirical results show that the five-step-ahead wavelet forecast that is based on volatilities outperforms the random walk forecast, relative to the wavelet forecast that is based on returns. Optimal wavelet causality forecasting for returns is suggested across all frequencies (i.e., daily–yearly), whereas for volatilities it is suggested only up to quarterly frequencies. These results may have important implications for market efficiency and predictability of prices on the crude oil markets