THE "EVERYTHING'S DIFFERENT, EVERY TIME" INNOVATION MANAGEMENT PROBLEM: A PROMISING MODEL DEVELOPMENT

2015 ◽  
Vol 19 (05) ◽  
pp. 1550057
Author(s):  
GLENN BROPHEY ◽  
ANAHITA BAREGHEH ◽  
DAVID HEMSWORTH ◽  
MARK WACHOWIAK ◽  
DEAN HAY ◽  
...  
Keyword(s):  
Decision Making ◽  
Innovation Management ◽  
Model Development ◽  
Opportunity To Learn ◽  
Management Problem ◽  
New Paradigm ◽  
Continuous Innovation ◽  
Management Actions ◽  
Novel Approach ◽  
Context Specific

This study reports on the testing of a promising approach for aiding decision-making during innovation. By focusing on the effects of risk/action dyads on success (the Risk/Action/Success (R/A/S) framework), and because perceived risks do appear repeatedly even though they emanate from differing contexts, the model offers an opportunity to learn from what worked best before. Using Artificial Neural Networks, this novel approach allows for generalisation and applicability of specific innovation management actions that are context specific. For academics, the proposed approach contributes to the risk-management literature by proposing a new paradigm for understanding and analysing innovation processes and identification of the most frequently occurring risks as seen by managers directly involved in continuous innovation. In addition, the model offers the capacity to use quantitative techniques to model the overlapping risks and actions during innovation-related decision-making. For practitioners, it can provide specific recommendations in the form of success-sorted lists of actions taken by other innovation managers that faced similar risks. This paper presents the theoretical and practical rationales underpinning this R/A/S framework and reports on the viability of this approach using pilot data.

scholarly journals STRATEGY, PROCESSES, CULTURE, AND FUNDING THE GROUNDWORK FOR SUSTAINABLE INNOVATION

2021 ◽  
Vol 11 (4) ◽  
pp. 88-100
Author(s):  
Joaquim José Carvalho Proença
Keyword(s):  
Small Groups ◽  
Innovation Management ◽  
Experimental Methods ◽  
Mentoring Programs ◽  
Problem Solution ◽  
Management Problem ◽  
Constructivist Approach ◽  
Continuous Innovation ◽  
Uncertainty Factor ◽  
Definition Of

What does it take for organizations to innovate? Although, there several classifications that define Innovation Management they can be grouped into four categories: Strategy, Processes, Culture, and Funding. While strategy focus on the idea of organizations being proactive to fast adapt to changes and exploit opportunities, processes are determinant for the definition of the problems, validate and test solutions that fit the market. Meanwhile, culture is being necessary to leverage innovation and introduce practices for knowledge management and continuous innovation. The research focused on why and how, bringing relevance to the context of the organizations, either social or technological, experimental methods, partner value, and internal mechanisms for innovation orientation. The goal is to provide an integral vision and balanced practical approach for the development of products, services, business model redesign in a sustainable manner. It is an attempt to manage the uncertainty factor and at the same time identify and generate opportunities through the ability to intervene proactively in the market with stakeholders and technical systems. In this way, it overcomes the management problem-solution shorter cycle, within a micro constructivist approach of small groups, of mentoring programs.

scholarly journals Development and Delivery of Species Distribution Models to Inform Decision-Making

BioScience ◽  
2019 ◽  
Vol 69 (7) ◽  
pp. 544-557 ◽  
Author(s):  
Helen R Sofaer ◽  
Catherine S Jarnevich ◽  
Ian S Pearse ◽  
Regan L Smyth ◽  
Stephanie Auer ◽  
...  
Keyword(s):  
Decision Making ◽  
Species Distribution ◽  
Species Distribution Models ◽  
Model Development ◽  
Model Assessment ◽  
Distribution Models ◽  
Regulatory Decision ◽  
Methodological Choices ◽  
Management Actions ◽  
Model Predictions

Abstract Information on where species occur is an important component of conservation and management decisions, but knowledge of distributions is often coarse or incomplete. Species distribution models provide a tool for mapping habitat and can produce credible, defensible, and repeatable information with which to inform decisions. However, these models are sensitive to data inputs and methodological choices, making it important to assess the reliability and utility of model predictions. We provide a rubric that model developers can use to communicate a model's attributes and its appropriate uses. We emphasize the importance of tailoring model development and delivery to the species of interest and the intended use and the advantages of iterative modeling and validation. We highlight how species distribution models have been used to design surveys for new populations, inform spatial prioritization decisions for management actions, and support regulatory decision-making and compliance, tying these examples back to our model assessment rubric.

Adaptive management: making recurrent decisions in the face of uncertainty

2021 ◽  
pp. 313-328
Author(s):  
James D. Nichols
Keyword(s):  
Decision Making ◽  
Adaptive Management ◽  
Model Development ◽  
State Variables ◽  
Vital Rates ◽  
Information State ◽  
Management Actions ◽  
Wise Decision ◽  
The Face ◽  
Development State

The key to wise decision-making in disciplines such as conservation, wildlife management, and epidemiology is the ability to predict consequences of management actions on focal systems. Predicted consequences are evaluated relative to programme objectives in order to select the favoured action. Predictions are typically based on mathematical models developed to represent hypotheses about management effects on system dynamics. For populations ranging from large mammals to plant communities to bacterial pathogens, demographic modelling is often the approach favoured for model development. State variables of such models may be population abundance, density, occupancy, or species richness, with corresponding vital rates such as rates of reproduction, survival, local extinction, and local colonisation. A key source of uncertainty that characterises such modelling efforts is the nature of relationships between management actions and vital rates. Adaptive management is a form of structured decision-making developed for decision problems that are recurrent and characterised by such structural uncertainty. One approach to incorporating this uncertainty is to base decisions on multiple models, each of which makes different predictions according to its underlying hypothesis. An information state of model weights carries information about the relative predictive abilities of the models. Monitoring of system state variables provides information about system responses, and comparison of these responses with model-based predictions provides a basis for updating the information state. Decisions emphasise the better-predicting model(s), leading to better decisions as the process proceeds. Adaptive management can thus produce optimal decisions now, while simultaneously reducing uncertainty for even better management in the future.

Information technology support for integrated supply chain modeling

2008 ◽  
Vol 27 (1) ◽  
pp. 3-13
Author(s):  
Charu Chandra ◽  
Jānis Grabis
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Supply Chain ◽  
Process Modeling ◽  
Service Oriented Architecture ◽  
Model Development ◽  
Integrated Models ◽  
Supply Chain Modeling ◽  
Decision Making Models ◽  
Integrated Supply Chain

Multiple interrelated decision-making models are frequently used in supply chain modeling. Model integration is a precondition for efficient development and utilization of these models. This paper discusses use of modern information technology (IT) techniques and methods for integration of supply chain decision-making models. The overall approach to using IT at various stages of model development is presented. Data and process modeling techniques are used to developed semi-formalized representation of integrated models. These models support integration of decision-making components with other parts of supply chain information system. Process modeling is also used to describe interrelationships among multiple decision-making models. This representation is used as the basis for implementation of integrated models. The service-oriented architecture is proposed as an implementation platform. The presented discussion serves as the basis for further developments in developing integrated supply chain decision-making models.

scholarly journals Integrating Value Considerations in the Decision Making for the Design of Biorefineries

2020 ◽  
Vol 26 (6) ◽  
pp. 2927-2955
Author(s):  
Mar Palmeros Parada ◽  
Lotte Asveld ◽  
Patricia Osseweijer ◽  
John Alexander Posada
Keyword(s):  
Decision Making ◽  
Complex Systems ◽  
Research And Development ◽  
Design Process ◽  
Design Decision ◽  
Value Sensitive Design ◽  
Design Practice ◽  
Novel Approach ◽  
Design Alternatives ◽  
Biobased Production

AbstractBiobased production has been promoted as a sustainable alternative to fossil resources. However, controversies over its impact on sustainability highlight societal concerns, value tensions and uncertainties that have not been taken into account during its development. In this work, the consideration of stakeholders’ values in a biorefinery design project is investigated. Value sensitive design (VSD) is a promising approach to the design of technologies with consideration of stakeholders’ values, however, it is not directly applicable for complex systems like biorefineries. Therefore, some elements of VSD, such as the identification of relevant values and their connection to a technology’s features, are brought into biorefinery design practice. Midstream modulation (MM), an approach to promoting the consideration of societal aspects during research and development activities, is applied to promote reflection and value considerations during the design decision making. As result, it is shown that MM interventions during the design process led to new design alternatives in support of stakeholders' values, and allowed to recognize and respond to emerging value tensions within the scope of the project. In this way, the present work shows a novel approach for the technical investigation of VSD, especially for biorefineries. Also, based on this work it is argued that not only reflection, but also flexibility and openness are important for the application of VSD in the context of biorefinery design.

HEALTH TECHNOLOGY ASSESSMENT AND PERSONALIZED MEDICINE: ARE ECONOMIC EVALUATION GUIDELINES SUFFICIENT TO SUPPORT DECISION MAKING?

2014 ◽  
Vol 30 (2) ◽  
pp. 179-187 ◽  
Author(s):  
Don Husereau ◽  
Deborah A. Marshall ◽  
Adrian R. Levy ◽  
Stuart Peacock ◽  
Jeffrey S. Hoch
Keyword(s):  
Decision Making ◽  
Economic Evaluation ◽  
Personalized Medicine ◽  
Health Technology Assessment ◽  
Technology Assessment ◽  
Health Technology ◽  
Population Based ◽  
New Paradigm ◽  
Current Guidance ◽  
Support Decision Making

Background: Many jurisdictions delivering health care, including Canada, have developed guidance for conducting economic evaluation, often in the service of larger health technology assessment (HTA) and reimbursement processes. Like any health intervention, personalized medical (PM) interventions have costs and consequences that must be considered by reimbursement authorities with limited resources. However, current approaches to economic evaluation to support decision making have been largely developed from population-based approaches to therapy—that is, evaluating the costs and consequences of single interventions across single populations. This raises the issue as to whether these methods, as they are or more refined, are adequate to address more targeted approaches to therapy, or whether a new paradigm for assessing value in PM is required.Objectives: We describe specific issues relevant to the economic evaluation of diagnostics-based PM and assess whether current guidance for economic evaluation is sufficient to support decision making for PM interventions.Methods: Issues were identified through literature review and informal interviews with national and international experts (n = 10) in these analyses. This article elaborates on findings and discussion at a workshop held in Ottawa, Canada, in January 2012.Results: Specific issues related to better guiding economic evaluation of personalized medicine interventions include: how study questions are developed, populations are characterized, comparators are defined, effectiveness is evaluated, outcomes are valued and how resources are measured. Diagnostics-based PM also highlights the need for analyses outside of economic evaluation to support decision making.Conclusions: The consensus of this group of experts is that the economic evaluation of diagnostics-based PM may not require a new paradigm. However, greater complexity means that existing approaches and tools may require improvement to undertake these more analyses.

scholarly journals A Novel Approach to Fuzzy Soft Set-Based Group Decision-Making

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Qinrong Feng ◽  
Xiao Guo
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Comparison Analysis ◽  
Fuzzy Soft Set ◽  
Soft Sets ◽  
Novel Approach ◽  
Decision Making Problem ◽  
Fuzzy Soft Sets ◽  
Effective Group

There are many uncertain problems in practical life which need decision-making with soft sets and fuzzy soft sets. The purpose of this paper is to develop an approach to effectively solve the group decision-making problem based on fuzzy soft sets. Firstly, we present an adjustable approach to solve the decision-making problems based on fuzzy soft sets. Then, we introduce knowledge measure and divergence degree based on α-similarity relation to determine the experts’ weights. Further, we develop an effective group decision-making approach with unknown experts’ weights. Finally, sensitivity analysis about the parameters and comparison analysis with other existing methods are given.

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