Sunanda Khandait

Work place: Dept. of Information Technology, KDK College of Engineering, Nagpur

E-mail: prapti_khandait@yahoo.co.in

Website:

Research Interests: Neural Networks, Pattern Recognition, Computer Architecture and Organization, Image Processing, Data Structures and Algorithms

Biography

Dr. Mrs. Sunanda P. Khandait is presently working as a Professor and Head in IT department of KDK college of Engineering, Nagpur, India. She has a rich experience of more than 22 years. She has published more than 30 research papers in credit in National and International Journals and Conferences. She has also published a couple of Book Chapters. She is an Approved Supervisor of Nagpur University for PhD in Computer Science and Technology. Her thrust areas include Databases, Image Processing, Pattern Analysis and Recognition, Data Processing and Mining, Fuzzy, Neural Network etc.

Author Articles
A Novel Software Tool to Generate Customer Needs for Effective Design of Online Shopping Websites

By Ashish K. Sharma Sunanda Khandait

DOI: https://doi.org/10.5815/ijitcs.2016.03.10, Pub. Date: 8 Mar. 2016

Effective design of online shopping websites is the need of the hour as design plays a crucial role in the success of online shopping businesses. Recently, the use of Quality Function Deployment (QFD) has been reported for the design of online shopping websites. QFD is a customer driven process that encompasses voluminous data gathered from customers through several techniques like personal interview, focus groups, surveys etc. This massive, unsorted and unstructured data is required to be transformed into a limited number of structured information to represent the actual Customer Needs (CNs) which are then utilized in subsequent stages of QFD process. This can be achieved through brainstorming using techniques like Affinity Process. However, integrating the Affinity Process within QFD is tedious and time consuming and cannot be dealt with manually. This generates a pressing need for a software tool to serve the purpose. Moreover, the researches carried out so far have focused on QFD application, post the generation of CNs. Also, the available QFD softwares lack the option to generate CNs from collected data. Thus, the paper aims to develop a novel software tool that integrates Affinity Process with QFD to generate customers' needs for effective design of online shopping websites. The software system is developed using Visual Basic Dot Net (VB.Net) that integrates a MS-Access database.

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