scholarly journals Application of Recommender System for Spending Habits Based Campaign Management

Proceedings ◽  
2021 ◽  
Vol 74 (1) ◽  
pp. 7
Author(s):  
Tuğçe Süheyla Kaya ◽  
Murat Gezer ◽  
Sevinç Gülseçen
Keyword(s):  
Customer Satisfaction ◽  
Recommender System ◽  
Credit Card ◽  
Recommendation System ◽  
Least Square ◽  
Bank Credit ◽  
Private Bank ◽  
Campaign Management

Nowadays, banks are working on finding a suitable campaign for every customer profile. With this study, we aimed to develop a recommendation system that will direct the customer to the appropriate campaign. With the data received from a private bank, credit card transactions of the users were analyzed, and spending habits were modeled. We aimed to recommend the most suitable campaign to the users through the created models. Within the scope of the study, 662.088 credit card transactions performed by 4997 customers within three months were analyzed, and three campaigns were proposed for each customer as a result of the study. The ALS (Alternating Least Square) algorithm was used on Spark to establish the recommendation system. The primary purpose of the study is to increase customer satisfaction by finding unique users based on spending habits instead of campaigns that are applied collectively to customers by making a personalized campaign offer.

Design and Implementation of E-Commerce Recommendation System Based on Ontology Technology

2014 ◽  
Vol 978 ◽  
pp. 244-247 ◽  
Author(s):  
Yi Wang ◽  
Hao Yuan Ou ◽  
Jian Ming Zhang
Keyword(s):  
Customer Satisfaction ◽  
Electronic Commerce ◽  
Customer Relationship Management ◽  
Recommender System ◽  
Recommendation System ◽  
Effective Means ◽  
Relationship Management ◽  
Customer Relationship ◽  
Semantic Structure ◽  
Design And Implementation

Electronic commerce recommendation system can effectively retain customers, effective means to improve the electronic commerce system sales. This paper first analyzes the E-commerce recommender system based on ontology, and applies it to the clothing e-commerce website customer relationship management and personalized commodity recommendation; semantic structure through ontology has to commodity recommendation. The paper presents design and implementation of E-commerce recommendation system based on ontology technology so as to effectively improve customer satisfaction.

scholarly journals Pengaruh Promosi dan Kepuasan Nasabah Terhadap Peningkatan Pemasaran Kartu Kredit Pada BANK MEGA.Tbk Cabang Makassar

2018 ◽  
Author(s):  
Sofyan Hamid Indar
Keyword(s):  
Customer Satisfaction ◽  
Credit Card ◽  
Bank Credit

This study aims to determine the effect of promotion and customer satisfaction to Mega Bank credit card marketing, both partial and simultaneous.This study uses a sample of 30 respondents, where respondents will be asked for feedback on the questions in the questionnaire were distributed, this research also use Software SPSS.21 as a tool to calculate the data to be used.Research found that having an negative and significant promotion of the sale of Mega Bank credit card while the customer satisfaction and significant effect on the Mega Bank credit card while at the same test between variables promotion and customer satisfaction significantly influence kredi card sales at Bank Mega Branch Makassar

A Consuequence of Statisfaction and Loyalty: How Brand nd Purchase Intention Affect Its (An empirical study of Bengkulu)

2020 ◽  
Vol 7 (2) ◽  
pp. 61-70
Author(s):  
Fachri Eka Saputra ◽  
Fedyah Anggriani
Keyword(s):  
Customer Satisfaction ◽  
Customer Loyalty ◽  
Purchase Intention ◽  
Partial Least Square ◽  
Least Square ◽  
Primary Data ◽  
Price Fairness ◽  
Online Questionnaire ◽  
Positive Effect ◽  
Descriptive Method

The purpose of this study as to determine how the effect of waterpark image and price fairness on customer satisfaction and its implications for customer loyalty at Waterpark Wahana Surya Bengkulu. The measurement of this study uses 14 indicator items which are distributed using an online questionnaire. The number of samples in this study were 136 respondents and the data were analyzed using SEM PLS (Partial Least Square). Date were collected using a questionnaire using a Likert scale. This research used descriptive method with a quantitative approach. The type of data used in this study is primary data. The results of this study prove that 1. waterpark image has a positive effect on price fairness, 2. Waterpark image has a positive effect on customer satisfaction, 3. Fairness of price has a positive effect on customer satisfaction, 4. Waterpark image has a positive effect on customer loyalty, 5. Fairness of price has a positive effect on customer loyalty, 6. Customer satisfaction has no effect on customer loyalty.

Identifying Attack Models for Securing Cluster-Based Recommendation System

2020 ◽  
Vol 14 ◽  
Author(s):  
Amreen Ahmad ◽  
Tanvir Ahmad ◽  
Ishita Tripathi
Keyword(s):  
Collaborative Filtering ◽  
Recommender System ◽  
Recommendation System ◽  
Relevant Information ◽  
System Function ◽  
Recommendation Algorithm ◽  
Underlying Network ◽  
Entire Dataset ◽  
Attack Models ◽  
Wide Usage

: The immense growth of information has led to the wide usage of recommender systems for retrieving relevant information. One of the widely used methods for recommendation is collaborative filtering. However, such methods suffer from two problems, scalability and sparsity. In the proposed research, the two issues of collaborative filtering are addressed and a cluster-based recommender system is proposed. For the identification of potential clusters from the underlying network, Shapley value concept is used, which divides users into different clusters. After that, the recommendation algorithm is performed in every respective cluster. The proposed system recommends an item to a specific user based on the ratings of the item’s different attributes. Thus, it reduces the running time of the overall algorithm, since it avoids the overhead of computation involved when the algorithm is executed over the entire dataset. Besides, the security of the recommender system is one of the major concerns nowadays. Attackers can come in the form of ordinary users and introduce bias in the system to force the system function that is advantageous for them. In this paper, we identify different attack models that could hamper the security of the proposed cluster-based recommender system. The efficiency of the proposed research is validated by conducting experiments on student dataset.

scholarly journals The Influence of Food Service Quality and Innovation Production on Local Product of Thailand: Study of Creative Agriculture

2020 ◽  
Vol 11 (5) ◽  
pp. 469
Author(s):  
Waleerak Sittisom ◽  
Thammarak Srimarut
Keyword(s):  
Data Analysis ◽  
Customer Satisfaction ◽  
Service Quality ◽  
Food Service ◽  
Partial Least Square ◽  
Least Square ◽  
Raw Material ◽  
Primary Data ◽  
Local Product ◽  
Product Promotion

Creative agriculture is a vast and deep knowledge of a product from its preparation from raw material to the end consumer of the product. Hence creative agriculture deals with deep analysis, production process, and commercialization, of a product. The present study explored the relationship between food service quality, innovation in production, customers’ satisfaction, and local product promotion. Both the foodservice quality and innovation in production increase customer satisfaction and local product promotion. An increased level of customer satisfaction is also promising for the increment in local product promotion. A survey from 300 food engineers working with different food providing companies, were the respondents of the present study for the collection of primary data. Then, a statistical software, named Partial Least Square (PLS) was used for the finalization of the data analysis process. The results achieved from the data analysis were used for the accomplishment of the end results of the present study.

Customer satisfaction with sommelier services of upscale Chinese restaurants in Hong Kong

2019 ◽  
Vol 31 (4) ◽  
pp. 532-554 ◽  
Author(s):  
Tommy Lau ◽  
Man Lai Cheung ◽  
Guilherme D. Pires ◽  
Carol Chan
Keyword(s):  
Hong Kong ◽  
Customer Satisfaction ◽  
Service Quality ◽  
Customer Loyalty ◽  
Positive Impact ◽  
Partial Least Square ◽  
Least Square ◽  
Survey Method ◽  
Content Type ◽  
The Impact

Purpose The abolishment of the wine tax in Hong Kong has led to increased wine consumption and increased demand for wine-related professionals, such as sommeliers. Yet the importance of sommeliers’ value-adding performance in the context of upscale Chinese restaurants has not been examined. To address this gap, the SERVQUAL framework is adopted to examine the influence of sommeliers’ service quality (SQ) on customer satisfaction (CS) and loyalty in the context of upscale Chinese restaurants in Hong Kong. Design/methodology/approach The survey method is used to collect data from 302 units of the population of interest, partial least square-structural equation modelling (PLS-SEM) is used to test the links between constructs. Findings Four of the seven dimensions of sommeliers’ service quality, namely, empathy, tangibles, credibility and assurance, have a significant positive impact on customer satisfaction and customer loyalty, whereas the impact of perceived value and responsiveness on customer satisfaction and customer loyalty is positive but only marginally significant. Reliability has a weak and non-significant impact on customer satisfaction and customer loyalty. Research limitations/implications Examining a small number of upscale Chinese restaurants in Hong Kong limits generalisation of the findings to other contexts. Replication of the research in different contexts will enhance generalizability. In terms of implications, the discussion highlights the importance of sommeliers’ service performance on customers’ SQ perceptions SQ, CS and loyalty, all of which are important variables for restaurateurs. Originality/value To the best of the authors’ knowledge, this is the first study of the influence of the quality of sommelier’s SQ on CS and loyalty in upscale Chinese restaurants in Hong Kong. Given the lack of attention to this service role in the literature, the study contributes theory from which further understanding can develop.

scholarly journals Application of Improved Recommendation System Based on Spark Platform in Big Data Analysis

2016 ◽  
Vol 16 (6) ◽  
pp. 245-255 ◽  
Author(s):  
Li Xie ◽  
Wenbo Zhou ◽  
Yaosen Li
Keyword(s):  
Big Data ◽  
Recommender System ◽  
Recommendation System ◽  
Parallel Implementation ◽  
Implementation Process ◽  
Recommendation Algorithm ◽  
Filtration Problem ◽  
Information Filtration ◽  
Similarity Information ◽  
Better Than

Abstract In the era of big data, people have to face information filtration problem. For those cases when users do not or cannot express their demands clearly, recommender system can analyse user’s information more proactive and intelligent to filter out something users want. This property makes recommender system play a very important role in the field of e-commerce, social network and so on. The collaborative filtering recommendation algorithm based on Alternating Least Squares (ALS) is one of common algorithms using matrix factorization technique of recommendation system. In this paper, we design the parallel implementation process of the recommendation algorithm based on Spark platform and the related technology research of recommendation systems. Because of the shortcomings of the recommendation algorithm based on ALS model, a new loss function is designed. Before the model is trained, the similarity information of users and items is fused. The experimental results show that the performance of the proposed algorithm is better than that of algorithm based on ALS.

Antecedents of switching intention in the mobile telecommunications industry

2018 ◽  
Vol 30 (4) ◽  
pp. 1087-1111 ◽  
Author(s):  
Farzana Quoquab ◽  
Jihad Mohammad ◽  
Norjaya Md Yasin ◽  
Nor Liza Abdullah
Keyword(s):  
Customer Satisfaction ◽  
Structural Equation ◽  
Telecommunications Industry ◽  
Switching Cost ◽  
Partial Least Square ◽  
Least Square ◽  
Mediating Effect ◽  
Loyalty Programs ◽  
Content Type

Purpose This study sheds some light on factors that affect customer switching intention in the Malaysian mobile phone service industry. More particularly, the purpose of this paper is to examine the effect of service quality (SQ), customer satisfaction, switching cost and consumer innovativeness (CI) on service switching intention (SWI); the mediating role of customer satisfaction; and the moderating role of service switching cost on the relationship between CI and SWI. Design/methodology/approach Data were collected using a self-administered questionnaire survey that yielded 535 responses. Using structural equation modelling approach, the partial least square software, version 3 was utilised to test the study hypotheses. Findings Results reveal that customer satisfaction, service switching cost and CI directly affect SWI. However, no significant relationship was found between SQ and SWI. Again, data supported the mediating effect of customer satisfaction as well as the moderating effect of service switching cost. Research limitations/implications It is expected that the findings from this study will enable policymakers, managers and marketers to formulate better strategies and effectively implement loyalty programs, preventing their customers from switching. Originality/value This study contributes to the existing literature by testing switching costs as the quasi moderator. Moreover, this is a pioneer study to consider CI as the antecedent of SWI.

scholarly journals Movie Recommenadation System

2021 ◽  
Vol 9 (4) ◽  
pp. 13-16
Author(s):  
Gandhali Malve ◽  
Lajree Lohar ◽  
Tanay Malviya ◽  
Shirish Sabnis
Keyword(s):  
Machine Learning ◽  
Recommender System ◽  
Recommendation System ◽  
Learning Algorithms ◽  
Recommendation Systems ◽  
Machine Learning Algorithms ◽  
The Internet ◽  
Amount Of Information ◽  
System Recommendation ◽  
User Ratings

Today the amount of information in the internet growth very rapidly and people need some instruments to find and access appropriate information. One of such tools is called recommendation system. Recommendation systems help to navigate quickly and receive necessary information. Many of us find it difficult to decide which movie to watch and so we decided to make a recommender system for us to better judge which movie we are more likely to love. In this project we are going to use Machine Learning Algorithms to recommend movies to users based on genres and user ratings. Recommendation system attempt to predict the preference or rating that a user would give to an item.

scholarly journals The Effect of Service Quality, Trust, Brand Image on Customer Satisfaction (Study on Cimb Niaga Tabungan Bisnis PT. Bank Cimb Niaga Tangerang Bintaro Branch)

2020 ◽  
Vol 5 (8) ◽  
pp. 1767-1772
Author(s):  
Defi Alfianto ◽  
Dr. Tafiprios, SE,. MM
Keyword(s):  
Data Analysis ◽  
Customer Satisfaction ◽  
Service Quality ◽  
Brand Image ◽  
Partial Least Square ◽  
Least Square ◽  
Survey Method ◽  
Questionnaire Data ◽  
Analysis Method ◽  
Convenience Sampling

In this researchpintends to analyze the influence of service quality, trust, brand image and customer satisfaction. The object of this research is the customer of bank cimb niaga branch tanggerang bintaro the number of samples specified is a total of 100 respondents by using slovin calculation method. The sample withdrawal method uses Convenience Sampling. The method performed for data collection using the survey method, with research instruments is a questionnaire. Data analysis method using SEM Partial Least Square (PLS).. Penelitian has proven telah that thequality of service has a positive and significant effect on customer satisfaction,trust kepercayaan has a positive and significant effect on customer satisfaction,and the brand image has a positive and significant effect on pt customer satisfaction. Bank CIMB Niaga Tangerang Bintaro Branch

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