Carrots and sticks for new technology: Abating greenhouse gas emissions in a heterogeneous and uncertain world

Many governments use technology incentives as an important component of their greenhouse gas abatement strategies. These “carrots” are intended to encourage the initial diffusion of new, greenhouse-gas-emissions-reducing technologies, in contrast to carbon taxes and emissions trading which provide a “stick” designed to reduce emissions by increasing the price of high-emitting technologies for all users. Technology incentives appear attractive, but their record in practice is mixed and economic theory suggests that in the absence of market failures, they are inefficient compared to taxes and trading. This study uses an agent-based model of technology diffusion and exploratory modeling, a new technique for decision-making under conditions of extreme uncertainty, to examine the conditions under which technology incentives should be a key building block of robust climate change policies. We find that a combined strategy of carbon taxes and technology incentives, as opposed to carbon taxes alone, is the best approach to greenhouse gas emissions reductions if the social benefits of early adoption sufficiently exceed the private benefits. Such social benefits can occur when economic actors have a wide variety of cost/performance preferences for new technologies and either new technologies have increasing returns to scale or potential adopters can reduce their uncertainty about the performance of new technologies by querying the experience of other adopters. We find that if decision-makers hold even modest expectations that such social benefits are significant or that the impacts of climate change will turn out to be serious then technology incentive programs may be a promising hedge against the threat of climate change.climate change, technology policy, uncertainty, agent-based modeling, exploratory modeling, social interactions

Dissent And Games In Decision Making: Case Of Solar Technologies

Faculty Research Day 2018: Faculty Competitive Poster WinnerResearch in decision modeling has mainly focused on the ranking of alternative choices based on a consensus of experts and decision makers. However, a decision model can also be used represent rational conflict and dissent. This is illustrated by the example of a hierarchical decision model (HDM) to assess alternative solar photovoltaic (PV) technologies. Multiple perspectives are considered for consensus and conflict. The perspectives include: social, technical, economic, environmental, and political (STEEP). HDM is an appropriate method for determining the outcome for scenarios that consider one dominant perspective as well as the case where all the perspectives are relatively important. Prior research in this area involved the assessment of PV technologies based on the cooperation or consensus of experts. This study focuses on dissent that may lead to conflict. Dissent is evident if only one dominant perspective is considered to evaluate the alternate PV technologies. One dominant perspective implies conflict by the proponents of the other perspectives deemed “unimportant”. By using such a decision modeling approach, outcomes for both consensus and dissent scenarios are observable and comparable. Research is planned to develop this decision modeling approach to form a branch of game theory with a large number of players and decision elements

THE EFFECTS OF FOUNDATION COURSE AND AGE IN DECISION TECHNOLOGY THE EFFECTS OF FOUNDATION COURSE AND AGE IN DECISION TECHNOLOGY TRAINING EFFECTIVENESS

In business, decision technologies are commonly and widely used among managers and analysts. The lack of skills surrounding this decision technology can create organization disadvantages. Therefore, effective training would hopefully prevent these disadvantages from such ubiquitous technology and potentially provide a competitive advantage for those organizations adopting training. Based on behavior modeling, “Improving Computer Training Effectiveness of Decision Technologies: Behavior Modeling and Retention Enhancement” Yi and Davis (2001) indicated that a combination of retention enhancement and hands-on practice produced better cognitive outcomes. Since information technology is dynamic, and time sensitivity is its critical issue, the effects of age among participants were examined

Farmers' Perceptions about Spatial Yield Variability and Precision Farming Technology Adoption: An Empirical Study of Cotton Production in 12 Southeastern States

This paper examines how cotton farmers' perceptions about their spatial yield variability influence their decision to adopt precision farming technologies. Utilizing cross-section survey data from 12 Southeastern states and a two-step econometric modeling approach, we find that farmers who perceive their yields as more spatially heterogeneous will more likely use site specific information gathering technologies and apply their inputs at a variable rate. In addition, our empirical analysis shows that perceptions about future profitability and importance of precision farming, along with socio-economic factors, also drive the technology adoption decision. These results have implications for producers contemplating the variable rate management decisions, as well as dealers selling these precision farming technologies.Multinomial logit, endogeneity, variable rate input applications, site specific information gathering technology, yield perceptions, Agribusiness, Farm Management, Production Economics, Productivity Analysis, Q12, Q16,

Real-time Spatial Detection and Tracking of Resources in a Construction Environment

Construction accidents with heavy equipment and bad decision making can be based on poor knowledge of the site environment and in both cases may lead to work interruptions and costly delays. Supporting the construction environment with real-time generated three-dimensional (3D) models can help preventing accidents as well as support management by modeling infrastructure assets in 3D. Such models can be integrated in the path planning of construction equipment operations for obstacle avoidance or in a 4D model that simulates construction processes. Detecting and guiding resources, such as personnel, machines and materials in and to the right place on time requires methods and technologies supplying information in real-time. This paper presents research in real-time 3D laser scanning and modeling using high range frame update rate scanning technology. Existing and emerging sensors and techniques in three-dimensional modeling are explained. The presented research successfully developed computational models and algorithms for the real-time detection, tracking, and three-dimensional modeling of static and dynamic construction resources, such as workforce, machines, equipment, and materials based on a 3D video range camera. In particular, the proposed algorithm for rapidly modeling three-dimensional scenes is explained. Laboratory and outdoor field experiments that were conducted to validate the algorithm’s performance and results are discussed

Modeling for policy decisions: Potential and problems

AbstractBecause decision modeling involves the construction of an explicit, mathematically describable structure of the pertinent elements of a clinical problem, the relative effectiveness of alternative approaches to care can be identified; costly procedures become apparent; new technologies can be assessed in relation to the old in terms of effectiveness and costs; the marginal benefit to be achieved by duplicative or alternative practices can be determined. All of this can be accomplished in terms of patient outcome and without the bias and self-interest of which the profession has been accused. Furthermore, if a resource allocation or reimbursement decision made in the name of cost containment eliminates or limits access to effective diagnostic or therapeutic technologies, the impact of that decision on effective care can be explicitly and quantitatively expressed through decision modeling. When such analyses are based on patient outcome, they are difficult to ignore and provide a pivotal point for discussions and eventual compromise

Unified Approach in the DSS Development Process

The structure of today's decision support environment become very complex due to new generation of Business Intelligence applications and technologies like Data Warehouse, OLAP (On Line Analytical Processing) and Data Mining. In this respect DSS development process are not simple and needs an adequate methodology or framework able to manage different tools and platforms to achieve manager's requirements. The DSS development process must be view like a unified and iterative set of activities and operations. The new techniques based on Unified Process (UP) methodology and UML (Unified Modeling Language) it seems to be appropriate for DSS development using prototyping and RAD (Rapid Application Development) techniques. In this paper we present a conceptual framework for development and integrate Decision Support Systems using Unified Process Methodology and UML.Decision Support Systems, Unified Process, UML, Prototyping, DSS Tools

Fuzzy argumentation for trust

In an open Multi-Agent System, the goals of agents acting on behalf of their owners often conflict with each other. Therefore, a personal agent protecting the interest of a single user cannot always rely on them. Consequently, such a personal agent needs to be able to reason about trusting (information or services provided by) other agents. Existing algorithms that perform such reasoning mainly focus on the immediate utility of a trusting decision, but do not provide an explanation of their actions to the user. This may hinder the acceptance of agent-based technologies in sensitive applications where users need to rely on their personal agents. Against this background, we propose a new approach to trust based on argumentation that aims to expose the rationale behind such trusting decisions. Our solution features a separation of opponent modeling and decision making. It uses possibilistic logic to model behavior of opponents, and we propose an extension of the argumentation framework by Amgoud and Prade to use the fuzzy rules within these models for well-supported decisions

Design of a Data Warehouse Model for a University Decision Support System

Data Warehouse (DW) can be a valuable asset in providing a stress-free access to data for reporting and analysis. Regrettably, building and preserving an active DW is usually associated with numerous hitches ranging from design to maintenance.  Research in the field of data warehousing has led to the emergence of vital contemporary technologies to aid design, management, and use of information systems that is capable of conveying a Decision Support System (DSS) to organizations. Nevertheless, in the face of persistent achievement and evolution of the field, abundant research is still left unturned across many diverse areas of the data warehousing. The objective of the paper therefore, is to design a DW database model for a University DSS using a dimensional modeling and techniques. A proposed DW database model with specific focus on modeling and design has been realized in this study.  The researchers have demonstrated on how a DW database model can be realized using the dimensional modeling and technique. Keywords: Data Warehouse, Modeling, Decision Support System, Decision Making

Event-Cloud Platform to Support Decision- Making in Emergency Management

The challenge of this paper is to underline the capability of an Event-Cloud Platform to support efficiently an emergency situation. We chose to focus on a nuclear crisis use case. The proposed approach consists in modeling the business processes of crisis response on the one hand, and in supporting the orchestration and execution of these processes by using an Event-Cloud Platform on the other hand. This paper shows how the use of Event-Cloud techniques can support crisis management stakeholders by automatizing non-value added tasks and by directing decision- makers on what really requires their capabilities of choice. If Event-Cloud technology is a very interesting and topical subject, very few research works have considered this to improve emergency management. This paper tries to fill this gap by considering and applying these technologies on a nuclear crisis use-case