Steven Walk - Academia.edu (original) (raw)

Papers by Steven Walk

2011 ASEE Annual Conference & Exposition Proceedings, Sep 4, 2020

Definitions or proposed requirements of technological literacy change as technologies and their a... more Definitions or proposed requirements of technological literacy change as technologies and their applications in the workplace and social interaction diffuse and evolve in complex sociotechnical ecologies. An historic problem encountered by technological literacy advocates is this environment of many moving targets, making the specification of technological literacy criteria and objectives in education a very difficult task. Just when the criteria are defined and proposed, the technology evolves and the criteria are rendered obsolete. An example of this challenge can be found in the history of the adoption of computer programming languages. At separate times, it was considered critical that all students in secondary school should be able to program in BASIC, and all undergraduate engineering students be able to write in FORTRAN, and that all business students be able to program in COBOL. These languages are used in only niche environments, if not altogether rare, today, and certainly are not in any way critical skills expected in the common workplace. Some technologies emerge, peak, and whither quickly, i.e., long before the educational need or level can be addressed. Some technologies diffuse over relatively long periods of time, such that it is difficult to target the level and timing of literacy requirements. Still otherwise promising technologies never reach a significant substitution level, and need not be considered, after all, in a literacy criteria study. The establishment of criteria for assessing technological literacy then, now, and in the future, could significantly be better targeted and more effective if trajectories of diffusing technologies and their applications were available. New techniques in forecasting technology change have given fresh perspectives on acceptance criteria and adoption rates of new technology. Quantitative technology forecasting studies have proven reliable in projecting technological and social change using relatively simple models such as logistic growth and substitution patterns, precursor relationships, constant performance improvement rates of change, and identification of anthropologically invariant behaviors. This paper presents quantitative technology forecasts of the emergence, growth and projected future saturation levels of several computationally and numerically intensive analytical technologiescomputation fluid dynamics, modeling and simulation, and finite element analysis. The trajectories are compared to the emergence and diffusion of the response of academia to provide curricula and course education in these technologies so that students are technologically literate in the use of these technologies upon graduation to research and industry. The results provide insight into the lead-lag time relationships of these computational technologies and their co-evolved literacy components. General conclusions on the advantages of including technological trajectories in technological literacy criteria development derived from the results of this research are given.

He is Founder and Director of the Laboratory for Technology Forecasting. His research interests i... more He is Founder and Director of the Laboratory for Technology Forecasting. His research interests include energy conversion systems, technology and innovation management, and technological forecasting and social change. He is owner and founder of Technology Intelligence, a management consulting company in Norfolk, Va.

His research interests include high voltage electromagnetic phenomena, energy conversion systems,... more His research interests include high voltage electromagnetic phenomena, energy conversion systems, technology management, and technological change and social forecasting. Mr. Walk is owner and founder of Technology Intelligence, a management consulting company in Chesapeake, Virginia, and conducts management workshops introducing innovative strategies for business and technology management. He earned a BSEET degree, Summa cum Laude, at the University of Pittsburgh at Johnstown and a MSEE degree at the University of Pittsburgh, where he was a University Scholar. Mr. Walk can be contacted at the Frank

He is Founder and Director of the Laboratory for Technology Forecasting. His research interests i... more He is Founder and Director of the Laboratory for Technology Forecasting. His research interests include energy conversion systems, technology and innovation management, and technological forecasting and social change. He is Owner and Founder of Technology Intelligence, a management consulting company in Norfolk, Va.

His technical interests are computer engineering technology, production operations, industrial ma... more His technical interests are computer engineering technology, production operations, industrial management, and industrial archeology. He also instructs ethics and senior seminar courses in the university's general education program, and is an advocate of the importance of including technological literacy across the university curriculum. Prior to SSU, he was employed at McDonnell Douglas Corporation (now Boeing), St. Louis, Mo., as an engineer and manager. He is a member of ASEE, AIAA (Associate Fellow), ASEM (Fellow), and ATMAE.

His research interests include power electromagnetic phenomena, energy conversion systems, techno... more His research interests include power electromagnetic phenomena, energy conversion systems, technology management, and technological change and social forecasting. Mr. Walk is owner and founder of Technology Intelligence, a management consulting company in Chesapeake, Virginia, and conducts management workshops introducing innovative strategies for business and technology management. He earned a B.S.E.E.T. degree, Summa cum Laude, at the University of Pittsburgh at Johnstown, and a M.S.E.E. degree at the University of Pittsburgh, where he was a University Scholar.

Strategic planning for energy and the environment, Sep 1, 2012

ABSTRACT This article introduces a decision-making method to expedite the evaluation and selectio... more ABSTRACT This article introduces a decision-making method to expedite the evaluation and selection of alternative energy and energy-cost savings opportunities in a comprehensive energy management plan. The method promises to reduce uncertainty in the selection of a single or field of alternatives because of its application of equal weight criteria, limited threshold ranking, and absolute disqualification rules. When applied in a strategic energy management plan, the method reduces uncertainty by the process of filtering and selecting the best opportunities for energy use improvement and evaluating them against multiple criteria of an organization's energy management objectives. The value of the method is in its simplicity and expediency to identify, assess, and then integrate into the energy management plan the most appropriate opportunities.

In addition to his focus on issues in undergraduate engineering education, Mr. Walk's research in... more In addition to his focus on issues in undergraduate engineering education, Mr. Walk's research interests include technology and innovation management, and technological forecasting and social change. He is owner and founder of Technology Intelligence, a management consulting company in Norfolk, Virginia. Mr. Walk earned BSEET and MSEE degrees from the University of Pittsburgh, where he was a University Scholar.

His research interests include high voltage electromagnetic phenomena, energy conversion systems,... more His research interests include high voltage electromagnetic phenomena, energy conversion systems, technology management, and technological change and social forecasting. Mr. Walk is owner and founder of Technology Intelligence, a management consulting company in Chesapeake, Virginia, and conducts management workshops introducing innovative strategies for business and technology management. He earned a BSEET degree, Summa cum Laude, at the University of Pittsburgh at Johnstown and a MSEE degree at the University of Pittsburgh, where he was a University Scholar. Mr. Walk can be contacted at the Frank

His research interests include high voltage electromagnetic phenomena, energy conversion systems,... more His research interests include high voltage electromagnetic phenomena, energy conversion systems, technology management, and technological change and social forecasting. Mr. Walk is owner and founder of Technology Intelligence, a management consulting company in Chesapeake, Virginia, and conducts management workshops introducing innovative strategies for business and technology management. He earned a BSEET degree, Summa cum Laude, at the University of Pittsburgh at Johnstown, and a MSEE degree at the University of Pittsburgh, where he was a University Scholar. Mr. Walk can be contacted at the Frank

Acta Astronautica, Apr 1, 2011

Projecting technology performance evolution has been improving over the years. Reliable quantitat... more Projecting technology performance evolution has been improving over the years. Reliable quantitative forecasting methods have been developed that project the growth, diffusion, and performance of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These forecasts can be applied at the early stages of space technology planning to better predict available future technology performance, assure the successful selection of technology, and improve technology systems management strategy. Often what is published as a technology forecast is simply scenario planning, usually made by extrapolating current trends into the future, with perhaps some subjective insight added. Typically, the accuracy of such predictions falls rapidly with distance in time. Quantitative technology forecasting (QTF), on the other hand, includes the study of historic data to identify one of or a combination of several recognized universal technology diffusion or substitution patterns. In the same manner that quantitative models of physical phenomena provide excellent predictions of system behavior, so do QTF models provide reliable technological performance trajectories. In practice, a quantitative technology forecast is completed to ascertain with confidence when the projected performance of a technology or system of technologies will occur. Such projections provide reliable time-referenced information when considering cost and performance trade-offs in maintaining, replacing, or migrating a technology, component, or system. This paper introduces various quantitative technology forecasting techniques and illustrates their practical application in space technology and technology systems management.

Naval Engineers Journal, Sep 1, 2010

Planning for the maintenance and sustainability of legacy systems often involves attempting to ti... more Planning for the maintenance and sustainability of legacy systems often involves attempting to time the obsolescence of a component or a system of components. Serious questions arise, such as: When will critical parts no longer be available? Will the next-generation technology replacing the current technology have a serious impact on system maintenance, repair, operation, or performance? When will software systems no longer be supported? These questions, if not outright overlooked, are often answered using qualitative information, such as expert opinions, market forecasts, or supplier assurances. However, reliable quantitative methods have been developed that project the growth and diffusion of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These quantitative technology forecasts can be applied at the early, mid-life, and even end-life stages of Navy technology platforms to better plan legacy system maintenance and sustainability strategies. In practice, a quantitative technology forecast is completed to ascertain the time in the future when a technology trajectory would have a significant impact on the sustainability of a legacy technology, system, or platform. Such future projections provide reliable time-referenced information when considering cost and resource requirement trade-off strategies to maintain or replace a component or system. This paper introduces various quantitative technology forecasting techniques and illustrates their practical applications toward considering legacy system support strategies.

Management Decision, May 31, 2011

Purpose – This paper aims to introduce a new method for the evaluation and selection (filtering) ... more Purpose – This paper aims to introduce a new method for the evaluation and selection (filtering) of alternatives in a complex multi‐criteria decision environment.Design/methodology/approach – The method uses an original modified outranking methodology to select optimal opportunities among competing alternatives for adoption.Findings – The process has application in scenarios such as wherein an executive or manager of a technology‐intensive enterprise faces the significant challenges of making effective investment decisions for new business processes and product technology.Practical implications – As applied in an enterprise technology decision‐making environment, the method reduces uncertainty in the process of filtering and selecting the best technology opportunities evaluated against multiple criteria or business objectives.Originality/value – The value of the method is in its simplicity and expediency to identify, assess, and then isolate the most appropriate technology opportunities among many.

InTech eBooks, Apr 11, 2012

Projecting technology performance and evolution has been improving over the years. Reliable quant... more Projecting technology performance and evolution has been improving over the years. Reliable quantitative forecasting methods have been developed that project the growth, diffusion, and performance of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These forecasts can be applied at the early stages of technology planning to better predict future technology performance, assure the successful selection of new technology, and to improve technology management overall. Often what is regarded as a technology forecast is, in essence, simply conjecture, or guessing (albeit intelligent guessing perhaps based on statistical inferences) and usually made by extrapolating recent trends into the future, with perhaps some subjective insight added. Typically, the accuracy of such predictions falls rapidly with distance in time. Quantitative technology forecasting (QTF), on the other hand, includes the study of historic data to identify one of or a combination of several demonstrated technology diffusion or substitution patterns. In the same manner that quantitative models of physical phenomena provide excellent predictions of systems behavior, so do QTF models provide reliable technological performance trajectories. In practice, a quantitative technology forecast is completed to ascertain with confidence when the projected performance of a technology or system of technologies will occur. Such projections provide reliable time-referenced information when considering cost and performance trade-offs in maintaining, replacing, or migrating a technology, component, or system. Quantitative technology forecasting includes the study of historic data to identify one of or a combination of several recognized universal technology diffusion or substitution patterns. This chapter introduces various quantitative technology forecasting techniques, discusses how forecasts are conducted, and illustrates their practical use through sample applications. 2. Introduction to quantitative technology forecasting Quantitative technology forecasting is the process of projecting in time the intersection of human activity and technological capabilities using quantitative methods. For the purposes of forecasting, technology is defined as any human creation that provides a compelling advantage to sustain or improve that creation, such as materials, methods, or systems that www.intechopen.com Technological Change 104 displace, support, amplify, or enable human activity in meeting human needs. It will be shown how rates of new technology adoption and rates of change in technology performance take on certain characteristic patterns in time.

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), 1991

U.S. Department of Energy Office of Scientific and Technical Information - OSTI OAI, Mar 5, 1991

Strategic Planning for Energy and the Environment, 2012

ABSTRACT This article introduces a decision-making method to expedite the evaluation and selectio... more ABSTRACT This article introduces a decision-making method to expedite the evaluation and selection of alternative energy and energy-cost savings opportunities in a comprehensive energy management plan. The method promises to reduce uncertainty in the selection of a single or field of alternatives because of its application of equal weight criteria, limited threshold ranking, and absolute disqualification rules. When applied in a strategic energy management plan, the method reduces uncertainty by the process of filtering and selecting the best opportunities for energy use improvement and evaluating them against multiple criteria of an organization's energy management objectives. The value of the method is in its simplicity and expediency to identify, assess, and then integrate into the energy management plan the most appropriate opportunities.

Thesis (M.S.)--University of Pittsburgh, 1986. Includes bibliographical references (leaves 77-80).

Naval Engineers Journal, 2010

Planning for the maintenance and sustainability of legacy systems often involves attempting to ti... more Planning for the maintenance and sustainability of legacy systems often involves attempting to time the obsolescence of a component or a system of components. Serious questions arise, such as: When will critical parts no longer be available? Will the next-generation technology replacing the current technology have a serious impact on system maintenance, repair, operation, or performance? When will software systems no longer be supported? These questions, if not outright overlooked, are often answered using qualitative information, such as expert opinions, market forecasts, or supplier assurances. However, reliable quantitative methods have been developed that project the growth and diffusion of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These quantitative technology forecasts can be applied at the early, mid-life, and even end-life stages of Navy technology platforms to better plan legacy system maintenance and sustainability strategies. In practice, a quantitative technology forecast is completed to ascertain the time in the future when a technology trajectory would have a significant impact on the sustainability of a legacy technology, system, or platform. Such future projections provide reliable time-referenced information when considering cost and resource requirement trade-off strategies to maintain or replace a component or system. This paper introduces various quantitative technology forecasting techniques and illustrates their practical applications toward considering legacy system support strategies.

2011 ASEE Annual Conference & Exposition Proceedings, Sep 4, 2020

Definitions or proposed requirements of technological literacy change as technologies and their a... more Definitions or proposed requirements of technological literacy change as technologies and their applications in the workplace and social interaction diffuse and evolve in complex sociotechnical ecologies. An historic problem encountered by technological literacy advocates is this environment of many moving targets, making the specification of technological literacy criteria and objectives in education a very difficult task. Just when the criteria are defined and proposed, the technology evolves and the criteria are rendered obsolete. An example of this challenge can be found in the history of the adoption of computer programming languages. At separate times, it was considered critical that all students in secondary school should be able to program in BASIC, and all undergraduate engineering students be able to write in FORTRAN, and that all business students be able to program in COBOL. These languages are used in only niche environments, if not altogether rare, today, and certainly are not in any way critical skills expected in the common workplace. Some technologies emerge, peak, and whither quickly, i.e., long before the educational need or level can be addressed. Some technologies diffuse over relatively long periods of time, such that it is difficult to target the level and timing of literacy requirements. Still otherwise promising technologies never reach a significant substitution level, and need not be considered, after all, in a literacy criteria study. The establishment of criteria for assessing technological literacy then, now, and in the future, could significantly be better targeted and more effective if trajectories of diffusing technologies and their applications were available. New techniques in forecasting technology change have given fresh perspectives on acceptance criteria and adoption rates of new technology. Quantitative technology forecasting studies have proven reliable in projecting technological and social change using relatively simple models such as logistic growth and substitution patterns, precursor relationships, constant performance improvement rates of change, and identification of anthropologically invariant behaviors. This paper presents quantitative technology forecasts of the emergence, growth and projected future saturation levels of several computationally and numerically intensive analytical technologiescomputation fluid dynamics, modeling and simulation, and finite element analysis. The trajectories are compared to the emergence and diffusion of the response of academia to provide curricula and course education in these technologies so that students are technologically literate in the use of these technologies upon graduation to research and industry. The results provide insight into the lead-lag time relationships of these computational technologies and their co-evolved literacy components. General conclusions on the advantages of including technological trajectories in technological literacy criteria development derived from the results of this research are given.

He is Founder and Director of the Laboratory for Technology Forecasting. His research interests i... more He is Founder and Director of the Laboratory for Technology Forecasting. His research interests include energy conversion systems, technology and innovation management, and technological forecasting and social change. He is owner and founder of Technology Intelligence, a management consulting company in Norfolk, Va.

His research interests include high voltage electromagnetic phenomena, energy conversion systems,... more His research interests include high voltage electromagnetic phenomena, energy conversion systems, technology management, and technological change and social forecasting. Mr. Walk is owner and founder of Technology Intelligence, a management consulting company in Chesapeake, Virginia, and conducts management workshops introducing innovative strategies for business and technology management. He earned a BSEET degree, Summa cum Laude, at the University of Pittsburgh at Johnstown and a MSEE degree at the University of Pittsburgh, where he was a University Scholar. Mr. Walk can be contacted at the Frank

He is Founder and Director of the Laboratory for Technology Forecasting. His research interests i... more He is Founder and Director of the Laboratory for Technology Forecasting. His research interests include energy conversion systems, technology and innovation management, and technological forecasting and social change. He is Owner and Founder of Technology Intelligence, a management consulting company in Norfolk, Va.

His technical interests are computer engineering technology, production operations, industrial ma... more His technical interests are computer engineering technology, production operations, industrial management, and industrial archeology. He also instructs ethics and senior seminar courses in the university's general education program, and is an advocate of the importance of including technological literacy across the university curriculum. Prior to SSU, he was employed at McDonnell Douglas Corporation (now Boeing), St. Louis, Mo., as an engineer and manager. He is a member of ASEE, AIAA (Associate Fellow), ASEM (Fellow), and ATMAE.

His research interests include power electromagnetic phenomena, energy conversion systems, techno... more His research interests include power electromagnetic phenomena, energy conversion systems, technology management, and technological change and social forecasting. Mr. Walk is owner and founder of Technology Intelligence, a management consulting company in Chesapeake, Virginia, and conducts management workshops introducing innovative strategies for business and technology management. He earned a B.S.E.E.T. degree, Summa cum Laude, at the University of Pittsburgh at Johnstown, and a M.S.E.E. degree at the University of Pittsburgh, where he was a University Scholar.

Strategic planning for energy and the environment, Sep 1, 2012

ABSTRACT This article introduces a decision-making method to expedite the evaluation and selectio... more ABSTRACT This article introduces a decision-making method to expedite the evaluation and selection of alternative energy and energy-cost savings opportunities in a comprehensive energy management plan. The method promises to reduce uncertainty in the selection of a single or field of alternatives because of its application of equal weight criteria, limited threshold ranking, and absolute disqualification rules. When applied in a strategic energy management plan, the method reduces uncertainty by the process of filtering and selecting the best opportunities for energy use improvement and evaluating them against multiple criteria of an organization's energy management objectives. The value of the method is in its simplicity and expediency to identify, assess, and then integrate into the energy management plan the most appropriate opportunities.

In addition to his focus on issues in undergraduate engineering education, Mr. Walk's research in... more In addition to his focus on issues in undergraduate engineering education, Mr. Walk's research interests include technology and innovation management, and technological forecasting and social change. He is owner and founder of Technology Intelligence, a management consulting company in Norfolk, Virginia. Mr. Walk earned BSEET and MSEE degrees from the University of Pittsburgh, where he was a University Scholar.

His research interests include high voltage electromagnetic phenomena, energy conversion systems,... more His research interests include high voltage electromagnetic phenomena, energy conversion systems, technology management, and technological change and social forecasting. Mr. Walk is owner and founder of Technology Intelligence, a management consulting company in Chesapeake, Virginia, and conducts management workshops introducing innovative strategies for business and technology management. He earned a BSEET degree, Summa cum Laude, at the University of Pittsburgh at Johnstown and a MSEE degree at the University of Pittsburgh, where he was a University Scholar. Mr. Walk can be contacted at the Frank

His research interests include high voltage electromagnetic phenomena, energy conversion systems,... more His research interests include high voltage electromagnetic phenomena, energy conversion systems, technology management, and technological change and social forecasting. Mr. Walk is owner and founder of Technology Intelligence, a management consulting company in Chesapeake, Virginia, and conducts management workshops introducing innovative strategies for business and technology management. He earned a BSEET degree, Summa cum Laude, at the University of Pittsburgh at Johnstown, and a MSEE degree at the University of Pittsburgh, where he was a University Scholar. Mr. Walk can be contacted at the Frank

Acta Astronautica, Apr 1, 2011

Projecting technology performance evolution has been improving over the years. Reliable quantitat... more Projecting technology performance evolution has been improving over the years. Reliable quantitative forecasting methods have been developed that project the growth, diffusion, and performance of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These forecasts can be applied at the early stages of space technology planning to better predict available future technology performance, assure the successful selection of technology, and improve technology systems management strategy. Often what is published as a technology forecast is simply scenario planning, usually made by extrapolating current trends into the future, with perhaps some subjective insight added. Typically, the accuracy of such predictions falls rapidly with distance in time. Quantitative technology forecasting (QTF), on the other hand, includes the study of historic data to identify one of or a combination of several recognized universal technology diffusion or substitution patterns. In the same manner that quantitative models of physical phenomena provide excellent predictions of system behavior, so do QTF models provide reliable technological performance trajectories. In practice, a quantitative technology forecast is completed to ascertain with confidence when the projected performance of a technology or system of technologies will occur. Such projections provide reliable time-referenced information when considering cost and performance trade-offs in maintaining, replacing, or migrating a technology, component, or system. This paper introduces various quantitative technology forecasting techniques and illustrates their practical application in space technology and technology systems management.

Naval Engineers Journal, Sep 1, 2010

Planning for the maintenance and sustainability of legacy systems often involves attempting to ti... more Planning for the maintenance and sustainability of legacy systems often involves attempting to time the obsolescence of a component or a system of components. Serious questions arise, such as: When will critical parts no longer be available? Will the next-generation technology replacing the current technology have a serious impact on system maintenance, repair, operation, or performance? When will software systems no longer be supported? These questions, if not outright overlooked, are often answered using qualitative information, such as expert opinions, market forecasts, or supplier assurances. However, reliable quantitative methods have been developed that project the growth and diffusion of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These quantitative technology forecasts can be applied at the early, mid-life, and even end-life stages of Navy technology platforms to better plan legacy system maintenance and sustainability strategies. In practice, a quantitative technology forecast is completed to ascertain the time in the future when a technology trajectory would have a significant impact on the sustainability of a legacy technology, system, or platform. Such future projections provide reliable time-referenced information when considering cost and resource requirement trade-off strategies to maintain or replace a component or system. This paper introduces various quantitative technology forecasting techniques and illustrates their practical applications toward considering legacy system support strategies.

Management Decision, May 31, 2011

Purpose – This paper aims to introduce a new method for the evaluation and selection (filtering) ... more Purpose – This paper aims to introduce a new method for the evaluation and selection (filtering) of alternatives in a complex multi‐criteria decision environment.Design/methodology/approach – The method uses an original modified outranking methodology to select optimal opportunities among competing alternatives for adoption.Findings – The process has application in scenarios such as wherein an executive or manager of a technology‐intensive enterprise faces the significant challenges of making effective investment decisions for new business processes and product technology.Practical implications – As applied in an enterprise technology decision‐making environment, the method reduces uncertainty in the process of filtering and selecting the best technology opportunities evaluated against multiple criteria or business objectives.Originality/value – The value of the method is in its simplicity and expediency to identify, assess, and then isolate the most appropriate technology opportunities among many.

InTech eBooks, Apr 11, 2012

Projecting technology performance and evolution has been improving over the years. Reliable quant... more Projecting technology performance and evolution has been improving over the years. Reliable quantitative forecasting methods have been developed that project the growth, diffusion, and performance of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These forecasts can be applied at the early stages of technology planning to better predict future technology performance, assure the successful selection of new technology, and to improve technology management overall. Often what is regarded as a technology forecast is, in essence, simply conjecture, or guessing (albeit intelligent guessing perhaps based on statistical inferences) and usually made by extrapolating recent trends into the future, with perhaps some subjective insight added. Typically, the accuracy of such predictions falls rapidly with distance in time. Quantitative technology forecasting (QTF), on the other hand, includes the study of historic data to identify one of or a combination of several demonstrated technology diffusion or substitution patterns. In the same manner that quantitative models of physical phenomena provide excellent predictions of systems behavior, so do QTF models provide reliable technological performance trajectories. In practice, a quantitative technology forecast is completed to ascertain with confidence when the projected performance of a technology or system of technologies will occur. Such projections provide reliable time-referenced information when considering cost and performance trade-offs in maintaining, replacing, or migrating a technology, component, or system. Quantitative technology forecasting includes the study of historic data to identify one of or a combination of several recognized universal technology diffusion or substitution patterns. This chapter introduces various quantitative technology forecasting techniques, discusses how forecasts are conducted, and illustrates their practical use through sample applications. 2. Introduction to quantitative technology forecasting Quantitative technology forecasting is the process of projecting in time the intersection of human activity and technological capabilities using quantitative methods. For the purposes of forecasting, technology is defined as any human creation that provides a compelling advantage to sustain or improve that creation, such as materials, methods, or systems that www.intechopen.com Technological Change 104 displace, support, amplify, or enable human activity in meeting human needs. It will be shown how rates of new technology adoption and rates of change in technology performance take on certain characteristic patterns in time.

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), 1991

U.S. Department of Energy Office of Scientific and Technical Information - OSTI OAI, Mar 5, 1991

Strategic Planning for Energy and the Environment, 2012

ABSTRACT This article introduces a decision-making method to expedite the evaluation and selectio... more ABSTRACT This article introduces a decision-making method to expedite the evaluation and selection of alternative energy and energy-cost savings opportunities in a comprehensive energy management plan. The method promises to reduce uncertainty in the selection of a single or field of alternatives because of its application of equal weight criteria, limited threshold ranking, and absolute disqualification rules. When applied in a strategic energy management plan, the method reduces uncertainty by the process of filtering and selecting the best opportunities for energy use improvement and evaluating them against multiple criteria of an organization's energy management objectives. The value of the method is in its simplicity and expediency to identify, assess, and then integrate into the energy management plan the most appropriate opportunities.

Thesis (M.S.)--University of Pittsburgh, 1986. Includes bibliographical references (leaves 77-80).

Naval Engineers Journal, 2010

Planning for the maintenance and sustainability of legacy systems often involves attempting to ti... more Planning for the maintenance and sustainability of legacy systems often involves attempting to time the obsolescence of a component or a system of components. Serious questions arise, such as: When will critical parts no longer be available? Will the next-generation technology replacing the current technology have a serious impact on system maintenance, repair, operation, or performance? When will software systems no longer be supported? These questions, if not outright overlooked, are often answered using qualitative information, such as expert opinions, market forecasts, or supplier assurances. However, reliable quantitative methods have been developed that project the growth and diffusion of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These quantitative technology forecasts can be applied at the early, mid-life, and even end-life stages of Navy technology platforms to better plan legacy system maintenance and sustainability strategies. In practice, a quantitative technology forecast is completed to ascertain the time in the future when a technology trajectory would have a significant impact on the sustainability of a legacy technology, system, or platform. Such future projections provide reliable time-referenced information when considering cost and resource requirement trade-off strategies to maintain or replace a component or system. This paper introduces various quantitative technology forecasting techniques and illustrates their practical applications toward considering legacy system support strategies.