Search results for: customer behavior model graph

Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

Procedia PDF Downloads 384

Authors: S. R. Nayaka, Putta Swamy

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Graph polynomial is one of the algebraic representations of the Graph. The degree polynomial is one of the simple algebraic representations of graphs. The degree polynomial of a graph G of order n is the polynomial Deg(G, x) with the coefficients deg(G,i) where deg(G,i) denotes the number of vertices of degree i in G. In this article, we investigate the behavior of the roots of some families of Graphs in the complex field. We investigate for the graphs having only integral roots. Further, we characterize the graphs having single roots or having real roots and behavior of the polynomial at the particular value is also obtained.

Keywords: degree polynomial, regular graph, minimum and maximum degree, graph operations

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Authors: David Pham, Yongfeng Zhang

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Graphs are an important structure for data storage and computation. Recent years have seen the success of deep learning on graphs such as Graph Neural Networks (GNN) on various data mining and machine learning tasks. However, most of the deep learning models on graphs cannot easily explain their predictions and are thus often labelled as “black boxes.” For example, Graph Attention Network (GAT) is a frequently used GNN architecture, which adopts an attention mechanism to carefully select the neighborhood nodes for message passing and aggregation. However, it is difficult to explain why certain neighbors are selected while others are not and how the selected neighbors contribute to the final classification result. In this paper, we present a graph learning model called Explainable Graph Attention Network (XGAT), which integrates graph attention modeling and explainability. We use a single model to target both the accuracy and explainability of problem spaces and show that in the context of graph attention modeling, we can design a unified neighborhood selection strategy that selects appropriate neighbor nodes for both better accuracy and enhanced explainability. To justify this, we conduct extensive experiments to better understand the behavior of our model under different conditions and show an increase in both accuracy and explainability.

Keywords: explainable AI, graph attention network, graph neural network, node classification

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Authors: Nileshkumar Vishnav, Aditya Tatu

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A recent approach of representing graph signals and graph filters as polynomials is useful for graph signal processing. In this approach, the adjacency matrix plays pivotal role; instead of the more common approach involving graph-Laplacian. In this work, we follow the adjacency matrix based approach and corresponding algebraic signal model. We further expand the theory and introduce the concept of similarity of two graphs. The similarity of graphs is useful in that key properties (such as filter-response, algebra related to graph) get transferred from one graph to another. We demonstrate potential applications of the relation between two similar graphs, such as nonuniform filter design, DTMF detection and signal reconstruction.

Keywords: graph signal processing, algebraic signal processing, graph similarity, isospectral graphs, nonuniform signal processing

Procedia PDF Downloads 321

Authors: Nattapong Techarattanased, Paweena Sribunrueng

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The objective of this study is to investigate strategies in customer relationship management and customers’ behavior in making decision on buying car insurance of Southeast Insurance Co. Ltd. in Bangkok. Subjects in this study included 400 customers with the age over 20 years old to complete questionnaires. The data were analyzed by arithmetic mean and multiple regressions. The results revealed that the customers’ opinions on the strategies in customer relationship management, i.e. customer relationship, customer feedback, customer follow-up, useful service suggestions, customer communication, and service channels were in moderate level but on the customer retention was in high level. Moreover, the strategy in customer relationship management, i.e. customer relationship, and customer feedback had an influence on customers’ buying decision on buying car insurance. The two factors above can be used for the prediction at the rate of 34%. In addition, the strategy in customer relationship management, i.e. customer retention, customer feedback, and useful service suggestions had an influence on the customers’ buying decision on period of being customers. The three factors could be used for the prediction at the rate of 45%.

Keywords: strategies, customer relationship management, behavior in buying decision, car insurance

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Authors: Azam Abkhiz, Abolghasem Nasir

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To achieve sustainable competitive advantage in the market, it is necessary to provide and improve customer satisfaction and Loyalty. To reach this objective, companies need to identify and analyze their customers. Thus, it is critical to measure the level of customer satisfaction and Loyalty very carefully. This study attempts to build a conceptual model to provide clear insights of customer loyalty. Using Bayesian networks (BNs), a model is proposed to evaluate customer loyalty and its consequences, such as repurchase and positive word-of-mouth. BN is a probabilistic approach that predicts the behavior of a system based on observed stochastic events. The most relevant determinants of customer loyalty are identified by the literature review. Perceived value, service quality, trust, corporate image, satisfaction, and switching costs are the most important variables that explain customer loyalty. The data are collected by use of a questionnaire-based survey from 1430 customers of a home appliances manufacturer in Iran. Four scenarios and sensitivity analyses are performed to run and analyze the impact of different determinants on customer loyalty. The proposed model allows businesses to not only set their targets but proactively manage their customer behaviors as well.

Keywords: customer satisfaction, customer loyalty, Bayesian networks, home appliances industry

Procedia PDF Downloads 107

Authors: M. Ghasemi, F. Eskandari, B. Hamzehei, A. R. Arshi

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Bioelectric activity of nervous cells might be changed causing by various factors. This alteration can lead to unforeseen circumstances in other organs of the body. Therefore, the purpose of this study was to model a single neuron and its behavior under an initial stimulation. This study was developed based on cable theory by means of the Bond Graph method. The numerical values of the parameters were derived from empirical studies of cellular electrophysiology experiments. Initial excitation was applied through square current functions, and the resulted action potential was estimated along the neuron. The results revealed that the model was developed in this research adapted with the results of experimental studies and demonstrated the electrical behavior of nervous cells properly.

Keywords: bond graph, stimulation, nervous cells, modeling

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Authors: Kanmanas Muensak, Somphoom Saweangkun

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The objectives of this research were to study the consumer behavior that affects the customer loyalty of CP Fresh Mart in Bangkok province. The sample of the study comprised 400 consumers over 15 years old who made the purchase through CP Fresh Mart in Bangkok. The questionnaires were used as the data gathering instrument, and the data were analyzed applying Percentage, Mean, Standard Deviation, Independent Sample t-test, Two- Way ANOVA, and Least Significant Difference, and Pearson’s Correlation Coefficient also. The result of hypothesis testing showed that the respondents of different gender, age, level of education, income, marital status and occupation had differences in consumer behavior through customer loyalty of CP Fresh Mart and the factors on customer loyalty in the aspects of re-purchase, word of mouth and price sensitive, promotion, process, and personnel had positive relationship with the consumer behavior through of CP Fresh Mart in Bangkok as well as.

Keywords: consumers in Bangkok, consumer behavior, customer loyalty, CP Fresh Mart, operating budget

Procedia PDF Downloads 294

Authors: U. Mary

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Let be a graph with a finite, nonempty set of objects called vertices together with a set of unordered pairs of distinct vertices of called edges. The vertex set is denoted by and the edge set by. Given two graphs and the wiener index of, wiener index for the splitting graph of a graph, the first Zagreb index of and its splitting graph, the 3-steiner wiener index of, the 3-steiner wiener index of a special graph are explored in this paper.

Keywords: complementary prism graph, first Zagreb index, neighborhood corona graph, steiner distance, splitting graph, steiner wiener index, wiener index

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Authors: Junjie Zhong, Kai Hong, Lei Wang

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Passage Retrieval (PR) plays an important role in many Natural Language Processing (NLP) tasks. Traditional efficient retrieval models relying on exact term-matching, such as TF-IDF or BM25, have nowadays been exceeded by pre-trained language models which match by semantics. Though they gain effectiveness, deep language models often require large memory as well as time cost. To tackle the trade-off between efficiency and effectiveness in PR, this paper proposes Graph Passage Retriever (GraphPR), a graph-based model inspired by the development of graph learning techniques. Different from existing works, GraphPR is end-to-end and integrates both term-matching information and semantics. GraphPR constructs a passage-level graph from BM25 retrieval results and trains a GCN-like model on the graph with graph-based objectives. Passages were regarded as nodes in the constructed graph and were embedded in dense vectors. PR can then be implemented using embeddings and a fast vector-similarity search. Experiments on a variety of real-world retrieval datasets show that the proposed model outperforms related models in several evaluation metrics (e.g., mean reciprocal rank, accuracy, F1-scores) while maintaining a relatively low query latency and memory usage.

Keywords: efficiency, effectiveness, graph learning, language model, passage retrieval, term-matching model

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Authors: Regina Connolly, Murray Scott, William DeLone

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Social media are revolutionary technologies that are transforming the way we communicate, the way we collaborate and the way we influence. Companies are making major investments in platforms such as Facebook and Twitter because they realize that social media are an influential force on customer perceptions and behavior. However, to date there is little guidance on what constitutes an effective deployment of social media and there is no empirical evidence that social medial investments are yielding positive returns. This research develops and validates the components of an effective corporate social media platform in order to examine the impact of effective social media on customer intentions and behavior.

Keywords: service quality, social value, social media, IS success, Web 2.0, customer behaviour

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Authors: Qiuyi Lyu, Bin Gong

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Breadth-First Search(BFS) is a core graph algorithm that is widely used for graph analysis. As it is frequently used in many graph applications, improve the BFS performance is essential. In this paper, we present a graph ordering method that could reorder the graph nodes to achieve better data locality, thus, improving the BFS performance. Our method is based on an observation that the sibling relationships will dominate the cache access pattern during the BFS traversal. Therefore, we propose a frequency-based model to construct the graph order. First, we optimize the graph order according to the nodes’ visit frequency. Nodes with high visit frequency will be processed in priority. Second, we try to maximize the child nodes overlap layer by layer. As it is proved to be NP-hard, we propose a heuristic method that could greatly reduce the preprocessing overheads. We conduct extensive experiments on 16 real-world datasets. The result shows that our method could achieve comparable performance with the state-of-the-art methods while the graph ordering overheads are only about 1/15.

Keywords: breadth-first search, BFS, graph ordering, graph algorithm

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Authors: Prateek Chharia, Biswa Bhusan Ghosh

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Graph coloring is one of the prominent concepts in graph coloring. It can be defined as a coloring of the various regions of the graph such that all the constraints are fulfilled. In this paper various graphs coloring approaches like greedy coloring, Heuristic search for maximum independent set and graph coloring using edge table is described. Graph coloring can be used in various real time applications like student time tabling generation, Sudoku as a graph coloring problem, GSM phone network.

Keywords: graph coloring, greedy coloring, heuristic search, edge table, sudoku as a graph coloring problem

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Authors: Morteza Giti

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As online shopping is becoming increasingly popular, computing customer lifetime value for better knowing the customers is also gaining more importance. Two distinct factors that can affect the value of a customer in the context of online shopping is the number of returned orders and payment method. Returned orders are those which have been shipped but not collected by the customer and are returned to the store. Payment method refers to the way that customers choose to pay for the price of the order which are usually two: Pre-pay and Cash-on-delivery. In this paper, a novel model called RFMSP is presented to calculated the customer lifetime value, taking these two parameters into account. The RFMSP model is based on the common RFM model while adding two extra parameter. The S represents the order status and the P indicates the payment method. As a case study for this model, the purchase history of customers in an online shop is used to compute the customer lifetime value over a period of twenty months.

Keywords: RFMSP model, AHP, customer lifetime value, k-means clustering, e-commerce

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Authors: Zhifei Hu, Feng Xia

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In recent years, Graph neural network has been widely used in knowledge graph recommendation. The existing recommendation methods based on graph neural network extract information from knowledge graph through entity and relation, which may not be efficient in the way of information extraction. In order to better propose useful entity information for the current recommendation task in the knowledge graph, we propose an end-to-end Neural network Model based on multi-stream graph attentional Mechanism (MSGAT), which can effectively integrate the knowledge graph into the recommendation system by evaluating the importance of entities from both users and items. Specifically, we use the attention mechanism from the user's perspective to distil the domain nodes information of the predicted item in the knowledge graph, to enhance the user's information on items, and generate the feature representation of the predicted item. Due to user history, click items can reflect the user's interest distribution, we propose a multi-stream attention mechanism, based on the user's preference for entities and relationships, and the similarity between items to be predicted and entities, aggregate user history click item's neighborhood entity information in the knowledge graph and generate the user's feature representation. We evaluate our model on three real recommendation datasets: Movielens-1M (ML-1M), LFM-1B 2015 (LFM-1B), and Amazon-Book (AZ-book). Experimental results show that compared with the most advanced models, our proposed model can better capture the entity information in the knowledge graph, which proves the validity and accuracy of the model.

Keywords: graph attention network, knowledge graph, recommendation, information propagation

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Authors: Mehmet Hakan Karaata

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In this paper, we first coin a new graph theocratic problem with numerous applications. Second, we provide two algorithms for the problem. The first solution is using a brute-force techniques, whereas the second solution is based on an initial identification of the cycles in the given graph. We then provide a correctness proof of the algorithm. The applications of the problem include graph analysis, graph drawing and network structuring.

Keywords: algorithm, cycle, graph algorithm, graph theory, network structuring

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Authors: Mohammad Iqbal Maiik

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Islamic marketing ethics combines the principle of value maximization with the principles of equity and justice for the welfare of the society. Adherence to the Islamic ethics in the Islamic banking industry can help elevate the standards of both behavior and living of bankers and customers alike. In a rapidly changing marketing environment, the need to be customer-focused has never been as important as it is today. At present where customers are becoming more demanding and increasingly mobile between competing financial providers, being customer-focused is not enough. Islamic banks and more specifically their customer-contact employees (customer relation advisers or officers) need to be perceived by their customers as being Islamic. This study represents an initial step in analyzing the role of Islamic ethical sales behavior as it may be perceived by the customers of Islamic Banks.

Keywords: Islam, ethics, marketing, Islamic banks

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Authors: Severino Gervacio, Velimor Almonte, Emmanuel Natalio

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A simple graph is planar if it there is a way of drawing it in the plane without edge crossings. A planar graph which is not a proper spanning subgraph of another planar graph is a maximal planar graph. We prove that for complete tripartite graphs of order at most 9, the only ones that contain a spanning maximal planar subgraph are K1,1,1, K2,2,2, K2,3,3, and K3,3,3. The main result gives a necessary and sufficient condition for the complete tripartite graph Kx,y,z to contain a spanning maximal planar subgraph.

Keywords: complete tripartite graph, graph, maximal planar graph, planar graph, subgraph

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Authors: Nileshkumar Vaishnav, Aditya Tatu

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An algebraic framework for processing graph signals axiomatically designates the graph adjacency matrix as the shift operator. In this setup, we often encounter a problem wherein we know the filtered output and the filter coefficients, and need to find out the input graph signal. Solution to this problem using direct approach requires O(N3) operations, where N is the number of vertices in graph. In this paper, we adapt the spectral graph partitioning method for partitioning of graphs and use it to reduce the computational cost of the filtering problem. We use the example of denoising of the temperature data to illustrate the efficacy of the approach.

Keywords: graph signal processing, graph partitioning, inverse filtering on graphs, algebraic signal processing

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Authors: Ing-Jen Hung, Tzu-Chien Wang

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Nowadays, customers can interact with firms through miscellaneous online ads on different channels easily. In other words, customer now has innumerable options and limitless time to accomplish their commercial activities with firms, individualizing their own online customer journey. This kind of convenience emphasizes the importance of online advertisement allocation on different channels. Therefore, profound understanding of customer behavior can make considerable benefit from optimizing fund allocation on diverse ad channels. To achieve this objective, multiple firms utilize numerical methodology to create data-driven advertisement policy. In our research, we aim to exploit online customer click data to discover the correlations between each channel and their sequential relations. We use LSTM to deal with sequential property of our data and compare its accuracy with other non-sequential methods, such as CART decision tree, logistic regression, etc. Besides, we also classify our customers into several groups by their behavioral characteristics to perceive the differences between all groups as customer portrait. As a result, we discover distinct customer journey under each customer portrait. Our article provides some insights into marketing research and can help firm to formulate online advertising criteria.

Keywords: LSTM, customer journey, marketing, channel ads

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Authors: Shuo Liu

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In Chinese text classification tasks, redundant words and phrases can interfere with the formation of extracted and analyzed text information, leading to a decrease in the accuracy of the classification model. To reduce irrelevant elements, extract and utilize text content information more efficiently and improve the accuracy of text classification models. In this paper, the text in the corpus is first extracted using the TextRank algorithm for abstraction, the words in the abstract are used as nodes to construct a text graph, and then the graph attention network (GAT) is used to complete the task of classifying the text. Testing on a Chinese dataset from the network, the classification accuracy was improved over the direct method of generating graph structures using text.

Keywords: Chinese natural language processing, text classification, abstract extraction, graph attention network

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Authors: Mehrnoosh Askarizadeh

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The customer’s value has become obvious for the leading companies in today’s competitive environment. Therefore they are constantly trying to improve their relationship with customers. Customer Knowledge has been recognized as a strategic resource and a key to the success of any company. Talking about the Customer Knowledge Management is closely associated with Knowledge Management and Customer Relationship Management (CRM). Recent studies conducted in the fields of Knowledge Management (KM) and Customer Relationship Management (CRM) has explained that the two approaches can have great synergies. In this paper, our aim is to provide an understanding of Customer Knowledge Management (CKM) as an integrated management approach and competence it requires. We describe CKM as an ongoing process of generating, disseminating and using customer knowledge within an organization and between an organization and its customers. In addition, we propose a comprehensive framework of CKM, the ability to integrate customer knowledge into customer relationship management processes.

Keywords: e-commerce, knowledge management (KM), customer relationship management (CRM), customer knowledge management (CKM)

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Authors: Natasha Sharma, Kulbhushan Agnihotri

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Cellular Automata are discrete dynamical systems which are based on local character and spatial disparateness of the spreading process. These factors are generally neglected by traditional models based on differential equations for epidemic spread. The aim of this work is to introduce an SEIR model based on cellular automata on graphs to imitate epidemic spreading. Distinctively, it is an SEIR-type model where the population is divided into susceptible, exposed, infected and recovered individuals. The results obtained from simulations are in accordance with the spreading behavior of a real time epidemics.

Keywords: cellular automata, epidemic spread, graph, susceptible

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Authors: Anocha Rojanapanich

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This research aimed to identify important factors that effect customer satisfaction in boutique hotels and the important factors effecting customer loyalty in returning to boutique hotels. Furthermore, this study also aimed to study demographics, which effect variable factors. Four hundred questionnaires were completed by customers of the boutique hotels. The descriptive statistics used in this paper were percentages, means, and standard deviation (S.D.), while hypothesis testing was done using T-test, Anova, Correlation and Regression to analyze the relationship among those factors. In terms of the purpose in staying, it was found that the largest respondent was for ‘leisure purposes’. While the frequency indicated that most of the customers who stayed ‘once’in the last two years in the hotels had less concern in the hotel’s image than other groups. For customer’s perceived value and income levels had an influence on customer perceived values in both functional value price and emotional value.

Keywords: boutique hotels, customer attitude, customer satisfaction, customer loyalty

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Authors: Yasmeen A. S. Essawy, Khaled Nassar

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With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: building information modeling (BIM), elemental graph data model (EGDM), geometric and topological data models, graph theory

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Authors: N. S. Ajisha

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In today’s competitive world the quality of the service you deliver is one of the important factor that determine customer satisfaction. Service quality is considered to be one important determinant to evaluate customer satisfaction and the relationship between service quality and customer satisfaction is considered as the foundation in researches on customer satisfaction. This research examines to do a gap analysis between the perception and expectation of the services delivered and find relation between the service quality and customer satisfaction. Service quality is found out here using the SERVQUAL model. And it finds out the dimension of service quality which is more important to measure customer satisfaction. The dimensions which we measure using SERVQUAL include the tangibles, reliability, responsiveness, assurance, and empathy. This study involves primary data collection like market survey.

Keywords: customer satisfaction, service quality, retail service quality, Kochi

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Authors: Saieed Akbari, Yousef Bagheri, Amir Hossein Ghodrati, Sima Saadat Akhtar

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Let G be a simple graph with the vertex set V (G) and with the adjacency matrix A (G). The energy E (G) of G is defined to be the sum of the absolute values of all eigenvalues of A (G). Also let n and m be number of edges and vertices of the graph respectively. A regular graph is a graph where each vertex has the same number of neighbours. Given a graph G, its line graph L(G) is a graph such that each vertex of L(G) represents an edge of G; and two vertices of L(G) are adjacent if and only if their corresponding edges share a common endpoint in G. In this paper we show that for every regular graphs and also for every line graphs such that (G) 3 we have, E(G) 2nm + n 1. Also at the other part of the paper we prove that 2 (G) E(G) for an arbitrary graph G.

Keywords: eigenvalues, energy, line graphs, matching number

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Authors: Rohollah Asadian Kohestani, Mustafa Hashemzadeh

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The present paper is the outcome of a field research that was conducted with the study objective of influencing factor's effect on the behavior of customers switching in the Saipa Emdad Khodro Company. To achieve this goal, six factors of service quality, service cost, waiting time to receive services, reputation of organization, costs of switching and the way to respond the needs of customers as the independent variables of research and their effect on the customer switching was studied as the variable related to the research. The statistical society of this research included all customers of the Saipa Emdad Khodro company that possess the vehicles of automobile manufacturing group of Saipa throughout the country and the statistical sample included 150 persons of such customers. The results of this research indicated that all under study factors excluding the reputation factor effect on the behavior of customer switching.

Keywords: customer services, switching cost, service price, customer switching behavior

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Authors: Prashant Verma

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Commercial banks are facing immense pressure, including financial disintermediation, interest rate volatility and digital ways of finance. Retaining an existing customer is 5 to 25 less expensive than acquiring a new one. This paper explores customer churn prediction, based on various statistical & machine learning models and uses under-sampling, to improve the predictive power of these models. The results show that out of the various machine learning models, Random Forest which predicts the churn with 78% accuracy, has been found to be the most powerful model for the scenario. Customer vintage, customer’s age, average balance, occupation code, population code, average withdrawal amount, and an average number of transactions were found to be the variables with high predictive power for the churn prediction model. The model can be deployed by the commercial banks in order to avoid the customer churn so that they may retain the funds, which are kept by savings bank (SB) customers. The article suggests a customized campaign to be initiated by commercial banks to avoid SB customer churn. Hence, by giving better customer satisfaction and experience, the commercial banks can limit the customer churn and maintain their deposits.

Keywords: savings bank, customer churn, customer retention, random forests, machine learning, under-sampling

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Authors: Yuan-Jye Tseng, Ching-Yen Chen

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In the design cycle, a main design task is to determine the external shape of the product. The external shape of a product is one of the key factors that can affect the customers’ preferences linking to the motivation to buy the product, especially in the case of a consumer electronic product such as a mobile phone. The relationship between the external shape and the customer preferences needs to be studied to enhance the customer’s purchase desire and action. In this research, a design for customer preferences model is developed for investigating the relationships between the external shape and the customer preferences of a product. In the first stage, the names of the geometric features are collected and evaluated from the data of the specified internet web pages using the developed text miner. The key geometric features can be determined if the number of occurrence on the web pages is relatively high. For each key geometric feature, the numerical values are explored using the text miner to collect the internet data from the web pages. In the second stage, a cluster analysis model is developed to evaluate the numerical values of the key geometric features to divide the external shapes into several groups. Several design suggestion cases can be proposed, for example, large model, mid-size model, and mini model, for designing a mobile phone. A customer preference index is developed by evaluating the numerical data of each of the key geometric features of the design suggestion cases. The design suggestion case with the top ranking of the customer preference index can be selected as the final design of the product. In this paper, an example product of a notebook computer is illustrated. It shows that the external shape of a product can be used to drive customer preferences. The presented design for customer preferences model is useful for determining a suitable external shape of the product to increase customer preferences.

Keywords: cluster analysis, customer preferences, design evaluation, design for customer preferences, product design

Procedia PDF Downloads 161