Energy Efficiency Research And Development: Consumption- And Environment-Centric Perspectives

The quest to develop technologies with minimal adverse environment impact has led to investments in research and development (R&D) targeted at developing energy-efficient technologies or improving the energy efficiency of existing technologies. Despite the increased focus on energy efficiency R&D, studies that examine their impact on environmental performance over time are lacking. Invoking the rebound effect and the ecological modernization theory, we hypothesize relationships between energy efficiency R&D with energy consumption, and emissions, and test them using panel data for OECD countries from 1987 to 2009. Econometric analysis suggests that energy efficiency R&D is negatively associated with per capita emission only. This suggests that any investment in energy efficiency achieves the objective of reducing the adverse environmental impact, thus positively contributing to the environment. The results further suggest that concerns about energy efficiency R&D may be misplaced as it is reducing adverse environmental impact without any significant association with energy consumption. Thus, the rebound effect, which postulates that increased energy efficiency results in more energy consumption, is not valid in the present context. We further examine the growth of improvement in environmental performance over time and show that the effectiveness of energy efficiency R&D remains consistent over time. This suggests that carbon neutral policies are plausible. Implications for research and practice are discusse

Do Shareholders Value Green Information Technology Announcements?

Using the natural resource-based view (NRBV) and signaling theory, we conducted an event study using the Fama-French four-factor (FFM4) model to determine how shareholders react to company announcements about adopting information technology (IT) to address environmental issues. We found that green IT announcements generate positive abnormal returns and increase share trading volume. Initiatives that use IT to support decision making (ITDSS) cause positive stock market reactions. Firms with good environmental performance records enjoy positive market returns from ITDSS and direct IT assets and infrastructure (ITASSETS) announcements. In contrast, shareholders react negatively to announcements regarding sustainable products and services (SPDTSVC). Combining the NRBV with signaling theory provides deeper theoretical insights than either theory alone. The findings could serve as the basis for further research and theory development on the different types of green IT and impacts on market value. The results help explain how firm characteristics and different types of green IT announcements impact market value, and they have significant implications for how firms plan and allocate their resources to support green initiatives

Sustainable Information Systems: Does It Matter?

Using the Natural Resource Based View (NRBV) as our theoretical lens, green IS or sustainable IS is conceptualized as comprising the different dimensions of sustainability practices that can create competitive advantage for the organization. This study examines (i) the impact of adoption of sustainable IS on organizational performance; and (ii) the impact of the extent of adoption of sustainable IS on organizational performance. Analyzing secondary data on sustainable IS and performance measures of 115 global organizations, we find that the adoption of sustainable IS is positively associated with market valuation and innovativeness but not with profitability. However, sustainable IS organizations that have greater extent of adoption realize better profitability, market valuation and innovativeness. Implications of results for research and practice are discussed

Sales and Operations Planning:The effect of coordination mechanisms on supply chain performance

Sales and Operations Planning (S&OP) is a means of facilitating cross-functional coordination, such as across the marketing-operations interface, but adopters of S&OP have not all benefited from S&OP to the same extent. This paper investigates the effect of S&OP on supply chain performance using the perspective of coordination and contingency theories. A structural equation model was developed in which six S&OP coordination mechanisms were hypothesized to contribute to improved supply chain performance. The model was tested using a global survey of 568 experienced S&OP practitioners. Our results indicate that Strategic Alignment and Information Acquisition/Processing are the mechanisms that most significantly enable superior S&OP outcomes. However, we find that a highly formalized S&OP Procedure inhibits supply chain performance. Furthermore, using a contingency theory perspective, increasing firm size and increasing experience in S&OP amplify the negative effect of a standardized S&OP Procedure upon supply chain performance. Our results suggest that organizational bricolage may be a coordinating mechanism of effective S&OP programs and that managers should empower ambidextrous S&OP teams to maintain balance using self-governing event-driven processes. This paper makes a novel contribution to the S&OP literature by providing evidence of a theoretical construct (organizational bricolage), which may trigger a re-evaluation of the efficacy of prescriptive S&OP procedures that have been advocated by some researchers and practitioners

Connectivity strategies to enhance the capacity of weight-bearing networks

The connectivity properties of a weight-bearing network are exploited to enhance it's capacity. We study a 2-d network of sites where the weight-bearing capacity of a given site depends on the capacities of the sites connected to it in the layers above. The network consists of clusters viz. a set of sites connected with each other with the largest such collection of sites being denoted as the maximal cluster. New connections are made between sites in successive layers using two distinct strategies. The key element of our strategies consists of adding as many disjoint clusters as possible to the sites on the trunk $T$ of the maximal cluster. The new networks can bear much higher weights than the original networks and have much lower failure rates. The first strategy leads to a greater enhancement of stability whereas the second leads to a greater enhancement of capacity compared to the original networks. The original network used here is a typical example of the branching hierarchical class. However the application of strategies similar to ours can yield useful results in other types of networks as well.Comment: 17 pages, 3 EPS files, 5 PS files, Phys. Rev. E (to appear

Stability of shortest paths in complex networks with random edge weights

We study shortest paths and spanning trees of complex networks with random edge weights. Edges which do not belong to the spanning tree are inactive in a transport process within the network. The introduction of quenched disorder modifies the spanning tree such that some edges are activated and the network diameter is increased. With analytic random-walk mappings and numerical analysis, we find that the spanning tree is unstable to the introduction of disorder and displays a phase-transition-like behavior at zero disorder strength $\epsilon=0$. In the infinite network-size limit ($N\to \infty$), we obtain a continuous transition with the density of activated edges $\Phi$ growing like $\Phi \sim \epsilon^1$ and with the diameter-expansion coefficient $\Upsilon$ growing like $\Upsilon\sim \epsilon^2$ in the regular network, and first-order transitions with discontinuous jumps in $\Phi$ and $\Upsilon$ at $\epsilon=0$ for the small-world (SW) network and the Barab\'asi-Albert scale-free (SF) network. The asymptotic scaling behavior sets in when $N\gg N_c$, where the crossover size scales as $N_c\sim \epsilon^{-2}$ for the regular network, $N_c \sim \exp[\alpha \epsilon^{-2}]$ for the SW network, and $N_c \sim \exp[\alpha |\ln \epsilon| \epsilon^{-2}]$ for the SF network. In a transient regime with $N\ll N_c$, there is an infinite-order transition with $\Phi\sim \Upsilon \sim \exp[-\alpha / (\epsilon^2 \ln N)]$ for the SW network and $\sim \exp[ -\alpha / (\epsilon^2 \ln N/\ln\ln N)]$ for the SF network. It shows that the transport pattern is practically most stable in the SF network.Comment: 9 pages, 7 figur

Cascade-based attacks on complex networks

We live in a modern world supported by large, complex networks. Examples range from financial markets to communication and transportation systems. In many realistic situations the flow of physical quantities in the network, as characterized by the loads on nodes, is important. We show that for such networks where loads can redistribute among the nodes, intentional attacks can lead to a cascade of overload failures, which can in turn cause the entire or a substantial part of the network to collapse. This is relevant for real-world networks that possess a highly heterogeneous distribution of loads, such as the Internet and power grids. We demonstrate that the heterogeneity of these networks makes them particularly vulnerable to attacks in that a large-scale cascade may be triggered by disabling a single key node. This brings obvious concerns on the security of such systems.Comment: 4 pages, 4 figures, Revte

Quasistatic Scale-free Networks

A network is formed using the $N$ sites of an one-dimensional lattice in the shape of a ring as nodes and each node with the initial degree $k_{in}=2$. $N$ links are then introduced to this network, each link starts from a distinct node, the other end being connected to any other node with degree $k$ randomly selected with an attachment probability proportional to $k^{\alpha}$. Tuning the control parameter $\alpha$ we observe a transition where the average degree of the largest node $$ changes its variation from $N^0$ to $N$ at a specific transition point of $\alpha_c$. The network is scale-free i.e., the nodal degree distribution has a power law decay for $\alpha \ge \alpha_c$.Comment: 4 pages, 5 figure

A model for cascading failures in complex networks

Large but rare cascades triggered by small initial shocks are present in most of the infrastructure networks. Here we present a simple model for cascading failures based on the dynamical redistribution of the flow on the network. We show that the breakdown of a single node is sufficient to collapse the efficiency of the entire system if the node is among the ones with largest load. This is particularly important for real-world networks with an highly hetereogeneous distribution of loads as the Internet and electrical power grids.Comment: 4 pages, 4 figure

Sulphonylurea Usage in Melioidosis Is Associated with Severe Disease and Suppressed Immune Response

10.1371/journal.pntd.0002795PLoS Neglected Tropical Diseases84