The Experts below are selected from a list of 44979 Experts worldwide ranked by ideXlab platform

Richard R Reilly - One of the best experts on this subject based on the ideXlab platform.

  • understanding antecedents of new Product Development speed a meta analysis
    Journal of Operations Management, 2010
    Co-Authors: Jiyao Chen, Fariborz Damanpour, Richard R Reilly
    Abstract:

    New Product Development (NPD) speed is a key component of time-based strategy, which has become increasingly important for managing innovation in a fast-changing business environment. This meta-analytic review assesses the generalizability of the relationships between NPD speed and 17 of its antecedents to provide a better understanding of the salient and cross-situationally consistent factors that affect NPD speed. We grouped the antecedents into four categories of strategy, project, process, and team, and found that process and team characteristics are more generalizable and cross-situationally consistent determinants of NPD speed than strategy and project characteristics. We also conducted subgroup analyses and found that research method variables, such as level of analysis, source of data, and measurement of speed, moderate the relationships between NPD speed and its antecedents. We apply the study’s findings to assess several models of NPD speed, such as the balanced model of Product Development, the strategic orientation and organizational capability model, the compression versus the experiential model, the centrifugal and centripetal model, and the Product Development Cycle time model. We also discuss the implications of our findings for research and practice.

  • understanding antecedents of new Product Development speed a meta analysis
    Journal of Operations Management, 2010
    Co-Authors: Jiyao Chen, Fariborz Damanpour, Richard R Reilly
    Abstract:

    Abstract New Product Development (NPD) speed is a key component of time-based strategy, which has become increasingly important for managing innovation in a fast-changing business environment. This meta-analytic review assesses the generalizability of the relationships between NPD speed and 17 of its antecedents to provide a better understanding of the salient and cross-situationally consistent factors that affect NPD speed. We grouped the antecedents into four categories of strategy, project, process, and team, and found that process and team characteristics are more generalizable and cross-situationally consistent determinants of NPD speed than strategy and project characteristics. We also conducted subgroup analyses and found that research method variables, such as level of analysis, source of data, and measurement of speed, moderate the relationships between NPD speed and its antecedents. We apply the study's findings to assess several models of NPD speed, such as the balanced model of Product Development, the strategic orientation and organizational capability model, the compression vs. the experiential model, the centrifugal and centripetal model, and the Product Development Cycle time model. We also discuss the implications of our findings for research and practice.

Jiyao Chen - One of the best experts on this subject based on the ideXlab platform.

  • understanding antecedents of new Product Development speed a meta analysis
    Journal of Operations Management, 2010
    Co-Authors: Jiyao Chen, Fariborz Damanpour, Richard R Reilly
    Abstract:

    New Product Development (NPD) speed is a key component of time-based strategy, which has become increasingly important for managing innovation in a fast-changing business environment. This meta-analytic review assesses the generalizability of the relationships between NPD speed and 17 of its antecedents to provide a better understanding of the salient and cross-situationally consistent factors that affect NPD speed. We grouped the antecedents into four categories of strategy, project, process, and team, and found that process and team characteristics are more generalizable and cross-situationally consistent determinants of NPD speed than strategy and project characteristics. We also conducted subgroup analyses and found that research method variables, such as level of analysis, source of data, and measurement of speed, moderate the relationships between NPD speed and its antecedents. We apply the study’s findings to assess several models of NPD speed, such as the balanced model of Product Development, the strategic orientation and organizational capability model, the compression versus the experiential model, the centrifugal and centripetal model, and the Product Development Cycle time model. We also discuss the implications of our findings for research and practice.

  • understanding antecedents of new Product Development speed a meta analysis
    Journal of Operations Management, 2010
    Co-Authors: Jiyao Chen, Fariborz Damanpour, Richard R Reilly
    Abstract:

    Abstract New Product Development (NPD) speed is a key component of time-based strategy, which has become increasingly important for managing innovation in a fast-changing business environment. This meta-analytic review assesses the generalizability of the relationships between NPD speed and 17 of its antecedents to provide a better understanding of the salient and cross-situationally consistent factors that affect NPD speed. We grouped the antecedents into four categories of strategy, project, process, and team, and found that process and team characteristics are more generalizable and cross-situationally consistent determinants of NPD speed than strategy and project characteristics. We also conducted subgroup analyses and found that research method variables, such as level of analysis, source of data, and measurement of speed, moderate the relationships between NPD speed and its antecedents. We apply the study's findings to assess several models of NPD speed, such as the balanced model of Product Development, the strategic orientation and organizational capability model, the compression vs. the experiential model, the centrifugal and centripetal model, and the Product Development Cycle time model. We also discuss the implications of our findings for research and practice.

Fariborz Damanpour - One of the best experts on this subject based on the ideXlab platform.

  • understanding antecedents of new Product Development speed a meta analysis
    Journal of Operations Management, 2010
    Co-Authors: Jiyao Chen, Fariborz Damanpour, Richard R Reilly
    Abstract:

    New Product Development (NPD) speed is a key component of time-based strategy, which has become increasingly important for managing innovation in a fast-changing business environment. This meta-analytic review assesses the generalizability of the relationships between NPD speed and 17 of its antecedents to provide a better understanding of the salient and cross-situationally consistent factors that affect NPD speed. We grouped the antecedents into four categories of strategy, project, process, and team, and found that process and team characteristics are more generalizable and cross-situationally consistent determinants of NPD speed than strategy and project characteristics. We also conducted subgroup analyses and found that research method variables, such as level of analysis, source of data, and measurement of speed, moderate the relationships between NPD speed and its antecedents. We apply the study’s findings to assess several models of NPD speed, such as the balanced model of Product Development, the strategic orientation and organizational capability model, the compression versus the experiential model, the centrifugal and centripetal model, and the Product Development Cycle time model. We also discuss the implications of our findings for research and practice.

  • understanding antecedents of new Product Development speed a meta analysis
    Journal of Operations Management, 2010
    Co-Authors: Jiyao Chen, Fariborz Damanpour, Richard R Reilly
    Abstract:

    Abstract New Product Development (NPD) speed is a key component of time-based strategy, which has become increasingly important for managing innovation in a fast-changing business environment. This meta-analytic review assesses the generalizability of the relationships between NPD speed and 17 of its antecedents to provide a better understanding of the salient and cross-situationally consistent factors that affect NPD speed. We grouped the antecedents into four categories of strategy, project, process, and team, and found that process and team characteristics are more generalizable and cross-situationally consistent determinants of NPD speed than strategy and project characteristics. We also conducted subgroup analyses and found that research method variables, such as level of analysis, source of data, and measurement of speed, moderate the relationships between NPD speed and its antecedents. We apply the study's findings to assess several models of NPD speed, such as the balanced model of Product Development, the strategic orientation and organizational capability model, the compression vs. the experiential model, the centrifugal and centripetal model, and the Product Development Cycle time model. We also discuss the implications of our findings for research and practice.

Laura Vallejotorres - One of the best experts on this subject based on the ideXlab platform.

  • integrating health economics into the Product Development Cycle a case study of absorbable pins for treating hallux valgus
    Medical Decision Making, 2011
    Co-Authors: Laura Vallejotorres, Lotte Maria Gertruda Steuten, Alan Girling, Bonny Parkinson, Martin Buxton
    Abstract:

    Background. The probability of reimbursement is a key factor in determining whether to proceed with or abandon a Product during its Development. The purpose of this article is to illustrate how the methods of iterative Bayesian economic evaluation proposed in the literature can be incorporated into the Development process of new medical devices, adapting them to face the relative scarcity of data and time that characterizes the process. Methods. A 3-stage economic evaluation was applied: an early phase in which simple methods allow for a quick prioritization of competing Products; a mid-stage in which developers synthesize the data into a decision model, identify the parameters for which more information is most valuable, and explore uncertainty; and a late stage, in which all relevant information is synthesized. A retrospective analysis was conducted of the case study of absorbable pins, compared with metallic fixation, in osteotomy to treat hallux valgus. Results. The results from the early analysis suggest absorbable pins to be cost-effective under the beliefs and assumptions applied. The outputs from the models at the mid-stage analyses show the device to be cost-effective with a high probability. Late-stage analysis synthesizes evidence from a randomized controlled trial and informative priors, which are based on previous evidence. It also suggests that absorbable pins are the most cost-effective strategy, although the uncertainty in the model output increased considerably. Conclusions. This example illustrates how the method proposed allows decisions in the Product Development Cycle to be based on the best knowledge that is available at each stage

  • integrating health economics modeling in the Product Development Cycle of medical devices a bayesian approach
    International Journal of Technology Assessment in Health Care, 2008
    Co-Authors: Laura Vallejotorres, Lotte Maria Gertruda Steuten, Martin Buxton, Alan Girling, Richard J Lilford, Terry Young
    Abstract:

    Objectives: Medical device companies are under growing pressure to provide health-economic evaluations of their Products. Cost-effectiveness analyses are commonly undertaken as a one-off exercise at the late stage of Development of new technologies; however, the benefits of an iterative use of economic evaluation during the Development process of new Products have been acknowledged in the literature. Furthermore, the use of Bayesian methods within health technology assessment has been shown to be of particular value in the dynamic framework of technology appraisal when new information becomes available in the life Cycle of technologies. Methods: In this study, we set out a methodology to adapt these methods for their application to directly support investment decisions in a commercial setting from early stages of the Development of new medical devices. Results and Conclusions: Starting with relatively simple analysis from the very early Development phase and proceeding to greater depth of analysis at later stages, a Bayesian approach facilitates the incorporation of all available evidence and would help companies to make better informed choices at each decision point.

Martin Buxton - One of the best experts on this subject based on the ideXlab platform.

  • integrating health economics into the Product Development Cycle a case study of absorbable pins for treating hallux valgus
    Medical Decision Making, 2011
    Co-Authors: Laura Vallejotorres, Lotte Maria Gertruda Steuten, Alan Girling, Bonny Parkinson, Martin Buxton
    Abstract:

    Background. The probability of reimbursement is a key factor in determining whether to proceed with or abandon a Product during its Development. The purpose of this article is to illustrate how the methods of iterative Bayesian economic evaluation proposed in the literature can be incorporated into the Development process of new medical devices, adapting them to face the relative scarcity of data and time that characterizes the process. Methods. A 3-stage economic evaluation was applied: an early phase in which simple methods allow for a quick prioritization of competing Products; a mid-stage in which developers synthesize the data into a decision model, identify the parameters for which more information is most valuable, and explore uncertainty; and a late stage, in which all relevant information is synthesized. A retrospective analysis was conducted of the case study of absorbable pins, compared with metallic fixation, in osteotomy to treat hallux valgus. Results. The results from the early analysis suggest absorbable pins to be cost-effective under the beliefs and assumptions applied. The outputs from the models at the mid-stage analyses show the device to be cost-effective with a high probability. Late-stage analysis synthesizes evidence from a randomized controlled trial and informative priors, which are based on previous evidence. It also suggests that absorbable pins are the most cost-effective strategy, although the uncertainty in the model output increased considerably. Conclusions. This example illustrates how the method proposed allows decisions in the Product Development Cycle to be based on the best knowledge that is available at each stage

  • integrating health economics modeling in the Product Development Cycle of medical devices a bayesian approach
    International Journal of Technology Assessment in Health Care, 2008
    Co-Authors: Laura Vallejotorres, Lotte Maria Gertruda Steuten, Martin Buxton, Alan Girling, Richard J Lilford, Terry Young
    Abstract:

    Objectives: Medical device companies are under growing pressure to provide health-economic evaluations of their Products. Cost-effectiveness analyses are commonly undertaken as a one-off exercise at the late stage of Development of new technologies; however, the benefits of an iterative use of economic evaluation during the Development process of new Products have been acknowledged in the literature. Furthermore, the use of Bayesian methods within health technology assessment has been shown to be of particular value in the dynamic framework of technology appraisal when new information becomes available in the life Cycle of technologies. Methods: In this study, we set out a methodology to adapt these methods for their application to directly support investment decisions in a commercial setting from early stages of the Development of new medical devices. Results and Conclusions: Starting with relatively simple analysis from the very early Development phase and proceeding to greater depth of analysis at later stages, a Bayesian approach facilitates the incorporation of all available evidence and would help companies to make better informed choices at each decision point.