Relationship Between Sustainable Development and Financial Performance: International Empirical Research

The aim of this paper is to clarify the relationship between companies' sustainable behavior and their financial performance (FP), which has been studied for several years without reaching a consensus on the effect and the direction of it. Hypotheses are tested for an unbalanced sample of 1960 multinational non‐financial listed companies from 25 countries and one administrative region for the period between 2002 and 2010. Due to the use of an international database and the differences among countries, it is possible to observe divergence between institutional settings. For this reason, a corporate governance system (Anglo‐Saxon, Germanic, Latin and Asian) is used as characteristic of the macro‐environment. Results obtained via the generalized method of moments estimator allow us to support the existence of a positive bidirectional relationship between corporate social responsibility and FP, evidencing the existence of a synergistic circle. The use of market value indicated that investors are able to identify economic, social and environmental practices generating a positive effect on FP. These relationships differ between corporate governance systems, due to the specific characteristics of each system. Findings are robust for each sustainable sub‐index (society, human rights, environmental and board). Copyright © 2013 John Wiley & Sons, Ltd and ERP Environment     

Measurement of Quality of Life and Well‐Being in France: The Drivers of Subjective Well‐Being

Ever since the publication of the Stiglitz Report, France has been heavily involved in the measurement of well‐being. The French Statistical Institute (INSEE) has expanded the scope of its existing surveys. It has also launched an innovative experimental survey which, drawing upon a single statistical source, aims for the first time to explore the different dimensions of both objective and subjective quality of life, as highlighted in the Stiglitz Report. It allows us to study, at the individual level, correlations between these dimensions and the accumulation of deprivations. It has enabled us to better understand the links between determinants generally referred to as objective dimensions of quality of life (such as health or education) and subjective well‐being. This information is of paramount importance for policy makers who cannot act directly on the level of people's satisfaction but can only act upon the levers of objective dimensions. This paper presents the main findings of the experimental survey.     

Barriers to the investment in the Concentrated Solar Power sector in Morocco: A foresight approach using the Cross Impact Analysis for a large number of events

The Scenario Analysis methods have often been used by policy makers as an instrument to manage uncertainty and to support the shaping of long-term economy policies. In this research, we apply Scenario Analysis in order to identify the barriers affecting the decision to invest in the Concentrated Solar Power (CSP) sector in Morocco. Our results aim at facilitating the process of defining different paths in strategic political and policy actions. Using data from a survey on a panel of experts, the Cross Impact Analysis (CIA) and the Cross Impact Matrix System (SMIC) techniques are applied. The advantage of these techniques is that they allow including in the analysis the interlinkages between the events that will define the future scenarios. However, their limitation is that the number of events analyzed cannot be too high since the information collected from the experts increases exponentially according to the number of events introduced. We thus expand our analysis with a new methodological approach, combining the use of prospective and statistics techniques. This approach allows addressing the mentioned limitation and applying these techniques, initially restricted to 6 events in its common application, to a large number of events. The results show that uncertainty and informality would be key factors in promoting the arrival of companies in this sector. Additionally, regarding companies that already have a presence in Morocco’s renewable energy sector, an increase in activity would be achieved through improvements in the easing of financial and legal barriers.     

Do environmental regulations hamper small enterprises' market entry? Evidence from China

Due to the serious increase of environmental pollution in China, environmental regulations have become significantly stringent. Such regulations are playing an increasingly important role in the development of small enterprises (SEs) in China, especially in SEs' market entry. However, existing studies pay little attention to this issue. This paper investigates for the first time the effect of environmental regulations on SEs' market entry and the mechanism of environmental regulation effects in China. We consider two sets of panel data for the periods 2003–2010 and 2012–2015 in China. We also use the fixed effect model and the instrumental variable method to explore the role of environmental regulations in SEs' market entry. The results show that, overall, environmental regulations play a significantly positive and robust role in SEs' market entry. However, the mechanisms associated with the effect of environmental regulations on different innovative types of SEs differ. Environmental regulations promote the market entry of SEs with product innovation, but this impact is not significant for SEs with research and development (R&D) activities and R&D institutions. Our findings indicate that China's SEs prefer product innovation, which is a lower level innovative type, over R&D innovation, as a means to avoid the negative impact of stringent environmental regulations.     

Information congruity in scarcity appeal: A structural equation modeling study of time-limited promotions

Although market scarcity such as time restriction is widely used in retail advertisements, its impact on product message processing and product evaluation is still subject to controversy. In this study, analyses through structural equation modeling indicated that (i) scarcity had no impact on product message processing, (ii) scarcity had a direct impact on product evaluation as a heuristic cue when the value inferred from scarcity was congruous with the worth derived from product message, and (iii) scarcity lost its impact on product evaluation when the value inferred from scarcity was incongruous with the worth derived from product message, and the incongruity prompted scrutiny of product message, resulting in a mediated impact of product message on product evaluation through product message processing. In conclusion, the results supported an information congruity theory of market scarcity.     

An explainable machine learning approach to improve take-off time predictions

Accurate aircraft trajectory predictions are necessary to compute exact traffic demand figures, which are crucial for an efficient and effective air traffic flow and capacity management. At present, the uncertainty of the take-off time is one of the major contributions to the loss of trajectory predictability. In the EUROCONTROL Maastricht Upper Area Control Centre, the predicted take-off time for each individual flight relies on the information received from the Enhanced Traffic Flow Management System. However, aircraft do not always take-off at the times reported by this system due to several factors, which effects and interactions are too complex to be expressed with hard-coded rules. Previous work proposed a machine learning model that, based on historical data, was able to predict the take-off time of individual flights from a set of input features that effectively captures some of these elements. The model demonstrated to reduce by 30% the take-off time prediction errors of the current system one hour before the time that flight is scheduled to depart from the parking position. This paper presents an extension of the model, which overcomes this look-ahead time constraint and allows to improve take-off time predictions as early as the initial flight plan is received. In addition, a subset of the original set of input features has been meticulously selected to facilitate the implementation of the solution in an operational air traffic flow and capacity management system, while minimising the loss of predictive power. Finally, the importance and interactions of the input features are thoroughly analysed with additive feature attribution methods.     

Public–private partnerships in Social Impact Bonds: facilitating competition or hindering transparency?

ABSTRACT

The use of Social Impact Bonds (SIBs), which introduces the potential for investor profit in public service provision, has been widely discussed. Some argue that SIBs might promote government transparency because outcome data collection and evaluation are part of contractual terms. On the other hand, some argue that SIBs might hinder government transparency because more contractual parties might lead to more uncertain data ownership and because the profit motive transforms information into a competitive advantage. This paper looks at SIBs in five countries, examining how transparency differed between SIB and non-SIB financed programmes at the same social service provider. On the positive side, SIBs led to more and longer collection of outcome data and the publication of evaluations. On the negative side, it was found that SIBs tend to generate significant obstacles to the release of data to academic researchers and that sponsored evaluations do not measure impacts.     

A game of give and take: The introduction of multi-layer (water) safety in the Netherlands and Flanders

At the beginning of the 21st century, the Netherlands and Flanders introduced a risk-based approach to flood risk management (FRM), labelled as multi-layer (water) safety. In contrast to a flood defence approach, risk-based management stresses the need to manage both the consequences and probability of a flood. The concept has developed differently in the two countries, as we conclude from a discursive-institutionalist research perspective. The Netherlands is characterised by a high institutionalization of the traditional flood defence discourse and a more closed policy arrangement, whereas in Flanders, the flood defence discourse is less institutionalized and the arrangement is more open. In both countries we see an opening of the arrangement preceding the establishment of multi-layer (water) safety, but at the same time, actors stress different aspects of the concept in order to increase its compatibility with the existing policy arrangement. In the Netherlands, the focus is on probability management, in Flanders on consequence management. In the Netherlands, multi-layer (water) safety as a concept could be established because it stabilises the system in the short-term by reinforcing the importance of flood defence, whereas in Flanders, policymakers were receptive to the concept because it supports a shift of responsibility towards actors outside traditional water management.     

The composite iteration algorithm for finding efficient and financially fair risk-sharing rules

We consider the problem of finding an efficient and fair ex-ante rule for division of an uncertain monetary outcome among a finite number of von Neumann–Morgenstern agents. Efficiency is understood here, as usual, in the sense of Pareto efficiency subject to the feasibility constraint. Fairness is defined as financial fairness with respect to a predetermined pricing functional. We show that efficient and financially fair allocation rules are in one-to-one correspondence with positive eigenvectors of a nonlinear homogeneous and monotone mapping associated to the risk sharing problem. We establish relevant properties of this mapping. On the basis of this, we obtain a proof of existence and uniqueness of solutions via nonlinear Perron–Frobenius theory, as well as a proof of global convergence of the natural iterative algorithm. We argue that this algorithm is computationally attractive, and discuss its rate of convergence.     

The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms

The impact of the industrial and digital (information) revolutions has, undoubtedly, been substantial on practically all aspects of our society, life, firms and employment. Will the forthcoming AI revolution produce similar, far-reaching effects? By examining analogous inventions of the industrial, digital and AI revolutions, this article claims that the latter is on target and that it would bring extensive changes that will also affect all aspects of our society and life. In addition, its impact on firms and employment will be considerable, resulting in richly interconnected organizations with decision making based on the analysis and exploitation of “big” data and intensified, global competition among firms. People will be capable of buying goods and obtaining services from anywhere in the world using the Internet, and exploiting the unlimited, additional benefits that will open through the widespread usage of AI inventions. The paper concludes that significant competitive advantages will continue to accrue to those utilizing the Internet widely and willing to take entrepreneurial risks in order to turn innovative products/services into worldwide commercial success stories. The greatest challenge facing societies and firms would be utilizing the benefits of availing AI technologies, providing vast opportunities for both new products/services and immense productivity improvements while avoiding the dangers and disadvantages in terms of increased unemployment and greater wealth inequalities.