scholarly journals Examining the Influence of Solar Panel Installers on Design Innovation and Market Penetration

2017 ◽  
Author(s):  
Ekaterina Sinitskaya ◽  
Kelley J. Gomez ◽  
Qifang Bao ◽  
Maria C. Yang ◽  
Erin F. MacDonald
Keyword(s):  
Product Design ◽  
Profit Maximization ◽  
Purchase Decisions ◽  
Market Penetration ◽  
Medium Term ◽  
Design Decisions ◽  
Agent Based ◽  
Design Specifications ◽  
Stakeholder Influence ◽  
Novel Approach

This work uses an agent-based model to examine how installers of photovoltaic (PV) panels influence panel design and the success of residential solar energy. It provides a novel approach to modelling intermediary stakeholder influence on product design, focusing installer decisions instead of the typical solar stakeholder foci of the final customer (homeowners) and the designer/manufacturer. Installers restrict homeowner choice to a subset of all panel options available, and, consequentially, determine medium-term market dynamics in terms of quantity and design specifications of panel installations. This model investigates installer profit-maximization strategies of exploring new panel designs offered by manufacturers vs. exploiting market-tested technology. Manufacturer design decisions and homeowner purchase decisions are modeled. Realistic details provided from installer and homeowner interviews are included. For example, installers must estimate panel reliability instead of trusting manufacturer statistics, and homeowners make purchase decisions based in part on installer reputation. We find that installers pursue new and more-efficient panels over sticking-with market-tested technology under a variety of panel-reliability scenarios and two different state scenarios (California and Massachusetts). Results indicate that it does not matter if installers are predisposed to an exploration or exploitation strategy — both types choose to explore new panels with higher efficiency.

scholarly journals Examining the Influence of Solar Panel Installers on Design Innovation and Market Penetration

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Ekaterina Sinitskaya ◽  
Kelley J. Gomez ◽  
Qifang Bao ◽  
Maria C. Yang ◽  
Erin F. MacDonald
Keyword(s):  
Profit Maximization ◽  
Purchase Decisions ◽  
Risk Averse ◽  
Market Penetration ◽  
Medium Term ◽  
Design Decisions ◽  
Agent Based ◽  
Stakeholder Influence ◽  
Novel Approach ◽  
Strategy Versus

This work uses an agent-based model to examine how installers of photovoltaic (PV) panels influence panel design and the success of residential solar energy. It provides a novel approach to modeling intermediary stakeholder influence on product design, focusing on installer decisions instead of the typical foci of the final customer (homeowners) and the designer/manufacturer. Installers restrict homeowner choice to a subset of all panel options available, and, consequentially, determine medium-term market dynamics in terms of quantity and design specifications of panel installations. This model investigates installer profit-maximization strategies of exploring new panel designs offered by manufacturers (a risk-seeking strategy) versus exploiting market-tested technology (a risk-averse strategy). Manufacturer design decisions and homeowner purchase decisions are modeled. Realistic details provided from installer and homeowner interviews are included. For example, installers must estimate panel reliability instead of trusting manufacturer statistics, and homeowners make purchase decisions based in part on installer reputation. We find that installers pursue new and more-efficient panels over sticking-with market-tested technology under a variety of panel-reliability scenarios and two different state scenarios (California and Massachusetts). Results indicate that it does not matter if installers are predisposed to an exploration or exploitation strategy—both types choose to explore new panels that have higher efficiency.

Strategic Design Decisions for Uncertain Market Systems Using an Agent Based Approach

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Z. Wang ◽  
S. Azarm ◽  
P. K. Kannan
Keyword(s):  
Product Design ◽  
Theoretic Approach ◽  
Competitive Strategies ◽  
Market System ◽  
Design Decisions ◽  
Learning Behaviors ◽  
Agent Based ◽  
Strategic Design ◽  
Game Theoretic ◽  
Design For Market Systems

Market players, such as competing manufacturing firms and retail channels, can significantly influence the demand and profit of a new product. Existing methods in design for market systems use game theoretic models that can maximize a firm’s profit with respect to the product design and price variables given the Nash equilibrium of the market system. However, in the design for uncertain market systems, there is seldom equilibrium with players having fixed strategies in a given time period. In this paper, we propose an agent based approach for design for market systems that accounts for learning behaviors of the market players under uncertainty. By learning behaviors we mean that market players gradually, over time, learn to play with better strategies based on action–reaction behaviors of other players. We model a market system with agents representing competing manufacturers and retailers who possess learning capabilities and based on some prespecified rules are able to react and make decisions on the product design and pricing. The proposed agent based approach provides strategic design and pricing decisions for a manufacturing firm in response to possible reactions from market players in the short and long term horizons. Our example results show that the proposed approach can produce competitive strategies for the firm by simulating market players’ learning behaviors when they react only by setting prices, as compared to a game theoretic approach. Furthermore, it can yield profitable product design decisions and competitive strategies when competing firms react by changing design variables in the short term—case for which no previous method in design for market systems has been reported.

Strategic Product Design Decisions for Uncertain Market Systems Using an Agent Based Approach

2010 ◽  
Author(s):  
Z. Wang ◽  
S. Azarm ◽  
P. K. Kannan
Keyword(s):  
Product Design ◽  
Theoretic Approach ◽  
Competitive Strategies ◽  
Market System ◽  
Design Decisions ◽  
Learning Behaviors ◽  
Agent Based ◽  
Time Period ◽  
Game Theoretic ◽  
Design For Market Systems

Market players, such as competing manufacturing firms and retail channels, can significantly influence the demand and profit of a new product. Existing methods in design for market systems use game theoretic models that can maximize a focal manufacturing firm’s profit with respect to product design and price variables given the Nash equilibrium of the market system. However, in the design for uncertain market systems, there is seldom equilibrium with players having fixed strategies in a given time period. In this paper, we propose an agent based approach for design for market systems that accounts for learning behaviors of the market players under uncertainty. By learning behaviors we mean that market players gradually, over a time period, learn to play with better strategies based on action-reaction behaviors of other players. We model a market system with agents representing competing manufacturers and retailers who possess learning capabilities and are able to automatically react and make decisions on the product design and pricing. The proposed approach provides strategic design and pricing decisions for a focal manufacturer in response to anticipated reactions from market players in the short and long term horizons. Our example results show that the proposed agent based approach can produce competitive strategies for a focal firm over a time period when market players react only by setting prices compared to a game theoretic approach. Furthermore, it can yield profitable product design decisions and competitive strategies when competing firms react by changing design attributes in the short term — a case for which no previous method in design for market systems has been reported.

Design for paraplegia: Preparing product design specifications for a wheelchair

2015 ◽  
Vol 27 (3) ◽  
pp. 79-89
Author(s):  
J.O. Mahmud ◽  
S.A. Khor ◽  
M.S. Mohd Ismail ◽  
J. Mohd Taib ◽  
N.R. Ramlan ◽  
...  
Keyword(s):  
Product Design ◽  
Design Specifications

An agent-based web services solution to collaborative product design

2004 ◽  
Author(s):  
Chun-Che Huang ◽  
Tzu-Laing (. Tseng ◽  
Yongjin Kwon ◽  
Yen Yi Chou
Keyword(s):  
Web Services ◽  
Product Design ◽  
Agent Based ◽  
Collaborative Product Design

scholarly journals Cascading Forgetting in Product Development Challenges and Evaluation

2019 ◽  
Vol 1 (1) ◽  
pp. 2527-2536
Author(s):  
Patricia Kügler ◽  
Claudia Schon ◽  
Benjamin Schleich ◽  
Steffen Staab ◽  
Sandro Wartzack
Keyword(s):  
Product Design ◽  
Information Overload ◽  
Relevant Information ◽  
Knowledge Bases ◽  
Wear Behaviour ◽  
Combustion Engines ◽  
The Novel ◽  
Related Information ◽  
Intentional Forgetting ◽  
Novel Approach

AbstractVast amounts of information and knowledge is produced and stored within product design projects. Especially for reuse and adaptation there exists no suitable method for product designers to handle this information overload. Due to this, the selection of relevant information in a specific development situation is time-consuming and inefficient. To tackle this issue, the novel approach Intentional Forgetting (IF) is applied for product design, which aims to support reuse and adaptation by reducing the vast amount of information to the relevant. Within this contribution an IF-operator called Cascading Forgetting is introduced and evaluated, which was implemented for forgetting related information elements in ontology knowledge bases. For the evaluation the development process of a test-rig for studying friction and wear behaviour of the cam/tappet contact in combustion engines is analysed. Due to the interdisciplinary task of the evaluation and the characteristics of semantic model, challenges are discussed. In conclusion, the focus of the evaluation is to consider how reliable the Cascading Forgetting works and how intuitive ontology-based representations appear to engineers.

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