A Novel Fuzzy Integrated Customer Needs Prioritization Software Tool for Effective Design of Online Shopping Websites

2017 ◽  
Vol 8 (4) ◽  
pp. 23-42
Author(s):  
Ashish K. Sharma ◽  
Sunanda Khandait
Keyword(s):  
Decision Making ◽  
Quality Function Deployment ◽  
Online Shopping ◽  
Real Life ◽  
Software Tool ◽  
Visual Basic ◽  
Website Design ◽  
Customer Needs ◽  
Technical Requirements ◽  
Effective Design

Albeit, online shopping has grown much recently, users' rate of satisfaction has declined due to the ineffective design of online shopping websites. Thus, the companies involved are craving for well-designed websites. Effective website design involves decision making and thus this paper considers Quality Function Deployment (QFD) as it is a strong decision-making tool. However, QFD uses crisp scoring approach that generates uncertainty and vagueness resulting in impreciseness and inconsistency in results. The issue can be addressed using fuzzy integration. QFD involves prioritization of Customer Needs (CNs) and Technical Requirements (TRs). However, the paper focuses on only CNs prioritization. Also, the existing software's lack the indispensable fuzzy support feature to handle the uncertainty and vagueness. Thus, the paper presents a novel fuzzy integrated customer needs prioritization software tool. The tool is built using Visual Basic Dot Net (VB.Net) and MS-Access. A real-life example is presented to demonstrate the viability of the software tool.

A Novel Fuzzy Integrated Customer Needs Prioritization Software Tool for Effective Design of Online Shopping Websites

2021 ◽  
pp. 634-655
Author(s):  
Ashish K. Sharma ◽  
Sunanda Khandait
Keyword(s):  
Decision Making ◽  
Quality Function Deployment ◽  
Online Shopping ◽  
Real Life ◽  
Software Tool ◽  
Website Design ◽  
Customer Needs ◽  
Technical Requirements ◽  
Effective Design ◽  
Decision Making Tool

Albeit, online shopping has grown much recently, users' rate of satisfaction has declined due to the ineffective design of online shopping websites. Thus, the companies involved are craving for well-designed websites. Effective website design involves decision making and thus this paper considers Quality Function Deployment (QFD) as it is a strong decision-making tool. However, QFD uses crisp scoring approach that generates uncertainty and vagueness resulting in impreciseness and inconsistency in results. The issue can be addressed using fuzzy integration. QFD involves prioritization of Customer Needs (CNs) and Technical Requirements (TRs). However, the paper focuses on only CNs prioritization. Also, the existing software's lack the indispensable fuzzy support feature to handle the uncertainty and vagueness. Thus, the paper presents a novel fuzzy integrated customer needs prioritization software tool. The tool is built using Visual Basic Dot Net (VB.Net) and MS-Access. A real-life example is presented to demonstrate the viability of the software tool.

Study on Conversion of Customer Needs in Product Development

2010 ◽  
Vol 102-104 ◽  
pp. 801-806
Author(s):  
Fu Hong Zeng ◽  
Lan Hua Zhou
Keyword(s):  
Decision Making ◽  
Programming Model ◽  
House Of Quality ◽  
Specific Product ◽  
Customer Needs ◽  
Resource Limitations ◽  
Technical Requirements ◽  
Target Values ◽  
Multi Attribute Decision Making ◽  
The Right

In order to translate the Customer Needs (CN) for the specific product into the right Technical Requirements (TR), the structure of conventional House of Quality (HOQ) is modified to have HOQ fit in with the needs of multi-attribute decision-making. Then, an Objective Programming Model (OPM) based on HOQ is constructed, which fully considers the design team's experience, and the interdependence between CN and TR, and the inner-dependences within themselves, along with resource limitations, and multi-objective nature of the problem. The target values of TR are obtained by solving the OPM using MATLAB, which can fully meet the CN. Finally an example is given, and the OPM is proved to be reasonable and effective.

scholarly journals The Application of Quality Function Deployment in Car Seat Industry

2020 ◽  
Vol 11 (1) ◽  
pp. 35-42
Author(s):  
Humiras Hardi Purba ◽  
Sunadi Sunadi ◽  
Suhendra Suhendra ◽  
Else Paulina
Keyword(s):  
Quality Function Deployment ◽  
Marketing Strategies ◽  
Quality Function ◽  
Customer Needs ◽  
Car Seat ◽  
The Third ◽  
Continuous Quality ◽  
Technical Requirements ◽  
The Right ◽  
Qfd Method

The research aimed to ensure the right design of new products based on customer needs and to improve competitiveness based on renewal marketing strategies and customer needs in the car seat industry. Customer satisfaction ratings were used to compare with competitors. Then, the Quality Function Deployment (QFD) was implemented for the analysis. The research used total sampling or complete enumeration. So, the sample size was the same as the population size. Based on calculations using the QFD method, it shows that the seat option has the highest percentage of technical requirements in the car seat industry around 27,39%. The second factor is material about 25,94%, and the third factor is the damping characteristic about 19,17%. For continuous quality improvement in the future, a lot of customer needs regarding the seat car need to be developed.

scholarly journals The Design and Evaluation of DACADE Visual Tool: Theoretical Implications

2018 ◽  
Vol 7 (1) ◽  
pp. 90-95
Author(s):  
Madihah Sheikh Abdul Aziz ◽  
Gitte Lindgaard ◽  
Mohd Syarqawy Hamzah ◽  
T. W. Allan Whitfield
Keyword(s):  
Decision Making ◽  
Transfer Of Learning ◽  
Software Tool ◽  
Design Decision ◽  
User Testing ◽  
Visual Tool ◽  
Design Students ◽  
Effective Design ◽  
User Motivation ◽  
Analyze Data

A goal of every designer is to create successful products for consumers. In creating a successful product, it is crucial for a designer to understand consumers’ perceptions of a product early in the design process. Nevertheless, design students lack the necessary data collection and user testing skills to support effective design decision-making. Consequently, their products might not be acceptable to the intended consumers and are thus likely to fail in the marketplace. For design students to acquire those skills, design curricula should incorporate statistical courses teaching the concepts of data and user testing. We addressed this challenge by developing an automated visual tool named DACADE, assisting design students to systematically collect and analyze data. This paper reports the theoretical implications discovered during the process from designing through to implementing and evaluating DACADE concerning the transfer of learning, the appropriateness of graphics used in a software tool, and user motivation in a learning environment.

Design, Development and Comparison of Heuristic Driven Algorithms Based on the Crossed Domain Products’ Reviews for User’s Summarization

2020 ◽  
Vol 13 (5) ◽  
pp. 884-892
Author(s):  
Sartaj Ahmad ◽  
Ashutosh Gupta ◽  
Neeraj Kumar Gupta
Keyword(s):  
Decision Making ◽  
Online Shopping ◽  
Recent Time ◽  
Design Development ◽  
Different Types ◽  
Feature Based ◽  
Use Of Internet ◽  
Day By Day ◽  
Better Than

Background: In recent time, people love online shopping but before any shopping feedbacks or reviews always required. These feedbacks help customers in decision making for buying any product or availing any service. In the country like India this trend of online shopping is increasing very rapidly because awareness and the use of internet which is increasing day by day. As result numbers of customers and their feedbacks are also increasing. It is creating a problem that how to read all reviews manually. So there should be some computerized mechanism that provides customers a summary without spending time in reading feedbacks. Besides big number of reviews another problem is that reviews are not structured. Objective: In this paper, we try to design, implement and compare two algorithms with manual approach for the crossed domain Product’s reviews. Methods: Lexicon based model is used and different types of reviews are tested and analyzed to check the performance of these algorithms. Results: Algorithm based on opinions and feature based opinions are designed, implemented, applied and compared with the manual results and it is found that algorithm # 2 is performing better than algorithm # 1 and near to manual results. Conclusion: Algorithm # 2 is found better on the different product’s reviews and still to be applied on other product’s reviews to enhance its scope. Finally, it will be helpful to automate existing manual process.

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