Jose Aragon

Environmental research has usually highlighted that the existence of slack resources in an organization helps allocate investment to innovative initiatives. However, the existing literature has paid very limited attention to how slack resources can influence the effects of focused and diversified innovations in different ways. Agency theory scholars claim that a manager’s first preference when confronted with discretionary resources will not generate positive investments for the firm, but their own opportunistic preferences. The differences between focused and diversified environmental innovations allow us to gain a better understanding of the financial impact of being focused and how slack resources matter in this context. We analyze a longitudinal sample of 5845 environmental patents from the 75 largest companies in the electrical components and equipment industry worldwide. Our results show that high levels of slack resources reduce the existing positive relationship between focused environmental innovations and a firm’s financial performance. These results contribute to delineating the theoretical and empirical implications of focused versus diversified environmental innovations and extend the literature on ethical dilemmas concerning managers’ use of slack resources in the firm.

Opportunistic behaviors are considered ethically and strategically troublesome since they disrupt otherwise mutually beneficial relationships. Previous literature has shown that firms attempt to protect their investments from opportunism by generating a large amount of patented marginal innovations in domains central to their industry. However, this approach may generate some ethical dilemmas by preventing firms and societies from more radical, collaborative, and much-needed environmental progress. We extend the environmental innovation literature using strategic and ethical lenses to analyze the potential of an alternative, divergent way to provide financial opportunities for a focal firm without aiming to prevent innovative opportunities for competitors. Our longitudinal analysis of 6768 environmental patents from 59 large companies worldwide in the electrical components and equipment industry shows that high levels of innovation intensity, environmental scope, bargaining power, and environmental expertise increase the incidence of patented environmental innovations related to domains in which industry competitors are less focused (i.e., technological divergence). We also show a positive relationship between this divergence and market-based firm performance. Our results suggest that pursuing innovative divergence to avoid opportunism may make ethical and market sense and we also identify the organizational factors that can support these efforts.

With the advent of the cloud computing model allowing a shared access to massive computing facilities, a surging demand emerges for the protection of the intellectual property tied to the programs executed on these uncontrolled systems. If novel paradigm as confidential computing aims at protecting the data manipulated during the execution, obfuscating techniques (in particular at the source code level) remain a popular solution to conceal the purpose of a program or its logic without altering its functionality, thus preventing reverse-engineering on the program even with the help of computing resources. The many advantages of code obfuscation, together with its low cost, makes it a popular technique. This paper proposes a novel methodology for source code obfuscation that can be used together with other traditional obfuscation techniques, making the code more robust against reverse engineering attacks. Three program complexity metrics are used to define three different single-objective combinatorial optimization versions of the problem, which are solved and analysed. Additionally, three multi-objective problems are defined, those considering each of the selected metrics together with the program execution time, in order to avoid strong obfuscations penalizing the performance. The goal of the defined problems is to find sequences of LLVM optimizations that lead to highly obfuscated versions of the original code. These transformations are applied to the back-end pseudo-assembly code (i.e., LLVM Intermediate Representation), thus avoiding any further optimizations by the compiler. Classical genetic algorithms (GAs) are used to solve the studied problems, namely a basic cellular GA for the single-objective problems and the popular NSGA-II for the multi-objective ones. The promising results show the potential of the proposed technique.

The influence of externally focused organizational capabilities on the generation of proactive environmental strategies was examined under contingenteffects of uncertainty in the general business environment in 134 North American and European ski resorts. Capabilities of strategic proactivity and continuous innovation were found to be associated with proactive environmental strategies. Managerial perceptions of uncertainty in the general business environment were found to moderate the deployment of the capability of continuous innovation at all levels of uncertainty and stakeholder engagement at low and average levels of uncertainty. The study contributes to the resource-based view by illuminating an important contingency under which these capabilities are likely to be deployed to generate such a strategy.

Over the last two decades, corporate sustainability has been established as a legitimate research topic among management and organization scholars. This introductory article explores potential avenues for advances in research on corporate sustainability by readdressing some of the fundamental aspects of the sustainability debate and approaching some novel perspectives and insights from outside the corporate sustainability field. This essay also sketches out how each of the six articles of this special issue contribute to the literature by going back to some of the conceptual roots of sustainability and/or by offering novel perspectives for research on corporate sustainability. As these six articles and the outlook on future research opportunities show, broadening the inquiry of corporate sustainability in terms of topics, theories, and methodologies holds considerable potential to improve our understanding of how decision makers and organizations respond to sustainability.

With the advent of the cloud computing model allowing a shared access to massive computing facilities, a surging demand emerges for the protection of the intellectual property tied to the programs executed on these uncontrolled systems. If novel paradigm as confidential computing aims at protecting the data manipulated during the execution, obfuscating techniques (in particular at the source code level) remain a popular solution to conceal the purpose of a program or its logic without altering its functionality, thus preventing reverse-engineering on the program even with the help of computing resources. The many advantages of code obfuscation, together with its low cost, makes it a popular technique. This paper proposes a novel methodology for source code obfuscation that can be used together with other traditional obfuscation techniques, making the code more robust against reverse engineering attacks. Three program complexity metrics are used to define three different single-objective combinatorial optimization versions of the problem, which are solved and analysed. Additionally, three multi-objective problems are defined, those considering each of the selected metrics together with the program execution time, in order to avoid strong obfuscations penalizing the performance. The goal of the defined problems is to find sequences of LLVM optimizations that lead to highly obfuscated versions of the original code. These transformations are applied to the back-end pseudo-assembly code (i.e., LLVM Intermediate Representation), thus avoiding any further optimizations by the compiler. Classical genetic algorithms (GAs) are used to solve the studied problems, namely a basic cellular GA for the single-objective problems and the popular NSGA-II for the multi-objective ones. The promising results show the potential of the proposed technique.