scholarly journals Visual e-commerce values filtering framework with spatial database metric

2020 ◽  
Vol 17 (3) ◽  
pp. 983-1006
Author(s):  
M. Kopecky ◽  
P. Vojtas
Keyword(s):  
User Behavior ◽  
Spatial Database ◽  
Synthetic Data ◽  
Combinatorial Search ◽  
Fuzzy Information ◽  
Additional Method ◽  
Analytic Hierarchy ◽  
Low Dimensions ◽  
Customer Preference ◽  
Linear Relaxations

Our customer preference model is based on aggregation of partly linear relaxations of value filters often used in e-commerce applications. Relaxation is motivated by the Analytic Hierarchy Processing method and combining fuzzy information in web accessible databases. In low dimensions our method is well suited also for data visualization. The process of translating models (user behavior) to programs (learned recommendation) is formalized by Challenge-Response Framework ChRF. ChRF resembles remote process call and reduction in combinatorial search problems. In our case, the model is automatically translated to a program using spatial database features. This enables us to define new metrics with visual motivation. We extend the conference paper with inductive ChRF, new representation of user and an additional method and metric. We provide experiments with synthetic data (items) and users.

Evaluation of retail service quality using analytic hierarchy process

2014 ◽  
Vol 42 (6) ◽  
pp. 521-541 ◽  
Author(s):  
Madhurima Deb ◽  
Ewuuk Lomo-David
Keyword(s):  
Service Quality ◽  
Analytic Hierarchy Process ◽  
Action Plan ◽  
Sustainable Competitive Advantage ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Customer Preference ◽  
Retail Service ◽  
Retail Service Quality ◽  
Hierarchy Process

Purpose – The deployment of analytic hierarchy process (AHP) to help the retail industry to recognize which retail service quality (RSQ) dimensions require attention to create a sustainable competitive advantage. The purpose of this paper is to use a comparative evaluation model to compare retail stores (supermarkets) across several RSQ dimensions, validated and tested RSQ model in the context of Indian supermarkets and explore the existence of RSQ gap by studying the difference between customers’ perception and expectations. Design/methodology/approach – This study deploys AHP in which the decision problem is broken down into hierarchy; thus customer preference involves the structuring of a hierarchy in terms of the overall objective, the selection criteria and the decision alternatives. AHP technique allows pairwise comparisons to be made among the alternatives with respect to the service dimensions. Findings – This study validated the formal RSQ scale developed by Dabholkar et al., (1996) by a modification that led to making it more suitable to the Indian context. Research limitations/implications – This research does not provide guidance on different course of action to be taken. Though this study identifies which service dimensions require improvement, it does not provide guidance on an appropriate action plan to address deficiencies. Practical implications – Prospective and existing retailers can use this instrument effectively to measure the quality of their services as perceived by customers in comparison to their competition. This work will not only help the supermarkets to improve their competitive positioning in the marketplace but will help them to identify areas of services needing improvement on priority basis. Originality/value – Application of AHP to determine the best customer preference is the first ever done in RSQ studies. It does open up another dimension for further studies.

scholarly journals INFORMATION TECHNOLOGY OF STAFF SELECTION IN THE OFFICE OF A LOGISTICS ENTERPRISE IN CONDITIONS OF FUZZY INFORMATION

2021 ◽  
Vol 1 (92) ◽  
pp. 87
Author(s):  
Aleksandr Kononykhin ◽  
Bohdan Chornyi ◽  
Ihor Shaposhnyk ◽  
Daria Bolohova
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Analytic Hierarchy Process ◽  
Clear Understanding ◽  
Main Task ◽  
Fuzzy Information ◽  
Analytic Hierarchy ◽  
Logistics Enterprise ◽  
Logistics Company ◽  
Hierarchy Process

The main task in choosing candidates for filling a vacancy is to meet the demand for employees in qualitative and quantitative terms. Hiring an employee is preceded by a clear understanding of the functions he will execute, tasks and job responsibilities, rights and interactions in the organization. Based on the set-out requirements, appropriate people selected for a specific position. Staff selection remains a challenge for many companies (problem).  For solving these problems, it is necessary to develop information technology for the staff selection in the office of a logistics enterprise, which will provide a decision-making process in various situations for tasks of varying computational complexity(methodology). The work goals  to improve the organizational management of staff support through the development of information technology for staff selection in the office of a logistics company. To achieve this goal, you need to solve the following tasks to develop the structure of information technology for the process of staff selection in the office of a logistics company; to formulate an example of staff selection by using analytic hierarchy process. As a result of developed information technology for staff selection in the office of a logistics enterprise includes:  requirements formation for the office staff for the logistics enterprise; goal formation and its decomposition, including decision-making of multi-criteria and fuzzy information, information support and rule base staff selection model in the office of a logistics enterprise; multi-criteria discrete optimization; results evaluation. The practical aspect of  example of staff selection in logistics office considered the usage of the analytic hierarchy process. A hierarchy of problems ‘to choose the best candidates’ creates a matrix of pairwise comparisons for all criteria. The first level is to select the best candidate. The second level is to evaluate the criteria for candidates.  The third level is to fulfil the vacancy of a logistics enterprise. The difference of the developed information technology lies in the usage of fuzzy initial information, which makes it possible to be more adequately and fully evaluate applicants for vacant vacancies (originality).

scholarly journals Integrating Kano Model, AHP, and QFD Methods for New Product Development Based on Text Mining, Intuitionistic Fuzzy Sets, and Customers Satisfaction

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Ming Li ◽  
Jie Zhang
Keyword(s):  
Decision Making ◽  
Product Development ◽  
New Product Development ◽  
Quality Function Deployment ◽  
New Product ◽  
Kano Model ◽  
Analytic Hierarchy ◽  
Customer Preference ◽  
Intuitionistic Fuzzy ◽  
Hierarchy Process

Online reviews are crucial to any online business that wants to increase sales on the Internet. Customer reviews have information about product attributes, customer requirements (CRs), and shopping experience; mining reviews provide the direction of decision-making for new product development and design (NPDD). Besides, the information of customer preference has vagueness and uncertainty, and the accuracy of decision-making information directly affects the success of NPDD. This paper proposed a methodology that integrates the Kano model (KM), analytic hierarchy process (AHP), and quality function deployment (QFD) methods with intuitionistic fuzzy set (IFS) to solve decision-making problems in NPDD. By the new method, the web crawler technology was first applied to e-commerce web sites to collect raw data, and the representative CRs were extracted through combining LDA model with Apriori algorithm. Second, the intuitionistic fuzzy Kano model (IFKM) is proposed to evaluate adjustment coefficient of CRs and Kano categories via customer preference membership functions. Thirdly, overall weights which contained emotional needs (ENs) and functional needs (FNs) are obtained via intuitionistic fuzzy analytic hierarchy process (IFAHP); thus, the adjusted weights are calculated from IFKM and IFAHP. Next, the intuitionistic fuzzy quality function deployment (IFQFD) is proposed to acquire engineering characteristics (ECs) of weights through combining competition benchmarks and based on technical benchmarks to make goals for a company’s NPDD. Finally, the method was applied to study vertical-configured air conditioner (VAC) as an example. The results showed that the application of text mining and IFS to improve CS is both reliable and scientific.

Using FAHP and CBR to evaluate the intention of adoption of internet banking service: The example of web ATM

2020 ◽  
Vol 39 (3) ◽  
pp. 2869-2879
Author(s):  
Shih-Jui Chang ◽  
Chi-I Hsu ◽  
Chin-Tsai Lin
Keyword(s):  
User Behavior ◽  
Internet Banking ◽  
Three Dimensions ◽  
Case Based Reasoning ◽  
Analytic Hierarchy ◽  
Service Adoption ◽  
Banking Service ◽  
Prediction Mechanism ◽  
Financial Transactions ◽  
Hierarchy Process

This research combines the Fuzzy Analytic Hierarchy Process (FAHP) with Case-Based Reasoning (CBR) to evaluate the intention of adoption of web ATM services. Compared with physical ATM service, web ATM allows users to perform financial transactions over the internet conveniently. Based on literature and considering the characteristics of web ATM, this study constructs a model for web ATM adoption that comprises three dimensions: The knowledge, the potential value, and the security. 222 valid user questionnaires are collected, and factor analysis is used to verify the factor structure of the decision hierarchy. FAHP is then used to calculate the weights of criteria with six experts through pairwise comparisons. Finally, FAHP weights are integrated into a CBR prediction mechanism for evaluating a user’s adoption intention toward web ATM. The results are helpful for financial institutions to understand and to evaluate the user behavior toward internet banking service adoption.

scholarly journals Method of selecting automatic control system of a motor grader

2021 ◽  
pp. 37-44
Author(s):  
Igor Ilge
Keyword(s):  
Automatic Control ◽  
Road Construction ◽  
Large Set ◽  
Fuzzy Information ◽  
Analytic Hierarchy ◽  
Automatic Control Systems ◽  
Effective Use ◽  
Hierarchy Process ◽  
Selection Of ◽  
Theory Of Fuzzy Sets

Problem. Effective use of motor graders is impossible without the use of automatic control systems, especially in modern conditions of large volumes of road construction. However, among the large number of samples of such systems, which differ in various parameters, it is impossible to make an appropriate choice without a scientifically sound approach, taking into account the set of their characteristics. It was found that these systems are characterized by a large set of parameters, with the values of some of them unknown, and the reliability of the values of many parameters is questionable, i.e. the choice must take place in conditions of fuzzy information. The methods of choosing alternatives in conditions of uncertainty described in the literature, in particular when choosing technical systems based on Analytic Hierarchy Process and fuzzy set theory, are analyzed and the latter is taken to develop a method of choosing a motor grader ACS. The goal of the work is to increase the efficiency of motor graders in road construction due to the appropriate choice of ACS. The methodology of constructing the method is the theory of fuzzy sets. The economic, technical-operational and ergonomic groups of criteria for choosing a motor grader ACS are determined and substantiated. The construction of the method was performed to select the ACS in the 3D class. As the alternatives, the systems which are the leaders of this segment were chosen. The above criteria are a set of criteria. The solution to the problem of choice is an alternative that best meets the requirements of the whole set of criteria. The results of the work are the development of a method of fuzzy multicriterion analysis for the selection of a motor grader ACS in the class of 3D systems. Originality lies in constructing the method of choosing a motor grader ACS in conditions of fuzzy information on the basis of reasonable criteria. The practical value is the fact that the use of the developed method will allow to make a scientifically sound choice of the ACS of a motor grader taking into account the whole set of criteria.

scholarly journals Research on Optimization Method of VR Task Scenario Resources Driven by User Cognitive Needs

Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 64
Author(s):  
Qianwen Fu ◽  
Jian Lv ◽  
Zeyu Zhao ◽  
Di Yue
Keyword(s):  
Virtual Reality ◽  
Human Computer Interaction ◽  
Cognitive Load ◽  
Quality Function Deployment ◽  
User Behavior ◽  
Optimization Method ◽  
Analytic Hierarchy ◽  
System Resource ◽  
Resource Characteristics ◽  
Computer Interaction

Research was performed in order to improve the efficiency of a user’s access to information and the interactive experience of task selection in a virtual reality (VR) system, reduce the level of a user’s cognitive load, and improve the efficiency of designers in building a VR system. On the basis of user behavior cognition-system resource mapping, a task scenario resource optimization method for VR system based on quality function deployment-convolution neural network (QFD-CNN) was proposed. Firstly, under the guidance of user behavior cognition, the characteristics of multi-channel information resources in a VR system were analyzed, and the correlation matrix of the VR system scenario resource characteristics was constructed based on the design criteria of human–computer interaction, cognition, and low-load demand. Secondly, analytic hierarchy process (AHP)-QFD combined with evaluation matrix is used to output the priority ranking of VR system resource characteristics. Then, the VR system task scenario cognitive load experiment is carried out on users, and the CNN input set and output set data are collected through the experiment, in order to build a CNN system and predict the user cognitive load and satisfaction in the human–computer interaction in the VR system. Finally, combined with the task information interface of a VR system in a smart city, the application research of the system resource feature optimization method under multi-channel cognition is carried out. The results show that the test coefficient CR value of the AHP-QFD model based on cognitive load is less than 0.1, and the MSE of CNN prediction model network is 0.004247, which proves the effectiveness of this model. According to the requirements of the same design task in a VR system, by comparing the scheme formed by the traditional design process with the scheme optimized by the method in this paper, the results show that the user has a lower cognitive load and better task operation experience when interacting with the latter scheme, so the optimization method studied in this paper can provide a reference for the system construction of virtual reality.

scholarly journals Consumer Preference Analysis for Websites Using e-TailQ and AHP

2018 ◽  
Vol 7 (2.11) ◽  
pp. 14 ◽  
Author(s):  
Loveleen Gaur ◽  
Kumari Anshu
Keyword(s):  
Customer Service ◽  
Relative Weight ◽  
Web Design ◽  
Consumer Preference ◽  
Customer Experience ◽  
Analytic Hierarchy ◽  
Customer Preference ◽  
Five Factors ◽  
Consumer Preference Analysis ◽  
Hierarchy Process

In today’s scenario when the world is going online, websites are the first point of contact for the consumers. It has become a necessity to have a website nowadays to be effective and successful in this internet infiltrated world. A well-thought-out web design plan generates an extraordinary customer experience. In this paper we study the various scales and model given by researchers at different point of time related to website service quality. Here we have taken into consideration the e-Tail Quality (e-TailQ) scale for our study purpose. The model has five factors of online retailing customer experience: website layout, website information, reliability/customer service, fulfilment and security/privacy. These factors were then tested based on the Analytic Hierarchy Process (AHP) model which is based on an exponential scale to calculate each criterion’s relative weight. The research is an endeavor to move further in measuring customer preference towards the service qualities offered by the websites and developing a more focused approach.  

scholarly journals On the Analytic Hierarchy Process Structure in Group Decision-Making Using Incomplete Fuzzy Information with Applications

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 609
Author(s):  
Atiq ur Rehman ◽  
Andrii Shekhovtsov ◽  
Nighat Rehman ◽  
Shahzad Faizi ◽  
Wojciech Sałabun
Keyword(s):  
Decision Making ◽  
Fuzzy Information ◽  
Decision Matrix ◽  
Analytic Hierarchy ◽  
Preference Relations ◽  
Fuzzy Preference Relations ◽  
Quantitative Results ◽  
Process Structure ◽  
Hierarchy Process ◽  
Fuzzy Preference

The multi-criteria decision-making (MCDM) problem has a solution whose quality can be affected by the experts’ inclinations. Under essential conditions, the fuzzy MCDM method can provide more acceptable and efficient outcomes to select the best alternatives. This work consists of a consensus-based technique for selecting and evaluating suppliers in an incomplete fuzzy preference relations (IFPRs) environment utilizing TL-transitivity (Lukasiewicz transitivity). The suggested method is developed based on the criteria of the Analytical Hierarchy Process (AHP) Fframework, and the decision matrix is construtced using consistent fuzzy preference relations (FPRs). We use the symmetrical decisional matrix approach. A variety of numerical explanations and an analysis of quantitative results illustrate the suggested methodology’s logic and effectiveness.

Supplier Evaluation and Selection System of Embedded E-Commerce Platform Based on Big Data

2022 ◽  
Vol 15 (2) ◽  
pp. 1-18
Author(s):  
Jiangnan He ◽  
Ying Qian ◽  
Xiaoyin Yin
Keyword(s):  
Analytic Hierarchy Process ◽  
Evaluation System ◽  
User Behavior ◽  
Entropy Method ◽  
Supplier Evaluation ◽  
Selection System ◽  
Analytic Hierarchy ◽  
Aggregated Data ◽  
The Analytic Hierarchy Process ◽  
Hierarchy Process

For e-commerce companies, it is easier to obtain a large amount of aggregated data about user behavior with the help of embedded network platforms, which contains valuable information that helps to form effective decision-making. This article first gives a detailed introduction to the evaluation and selection of e-commerce and suppliers; then puts forward the analytic hierarchy process and entropy method; finally, the AHP analytic method is used to build a supplier evaluation system and a selection system. The experimental results of this paper show that after obtaining the entropy AHP weights through the analytic hierarchy process, these 8 suppliers can be ranked and selected. Using the ABC classification method, classification is based on the ranking of suppliers. Among them, Class A suppliers account for 12.5%, which plays a key role in the construction of the evaluation and selection system of e-commerce suppliers.

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