Customer Tiered Purchase Forecast by Mobile Edge Computing Based on Pareto/NBD and SVR

Mobile edge computing is trending nowadays for its computation efficiency and privacy.The rapid development of e-commerce show great interest in mobile edge computing due to numerous rise of small and middle-sized enterprises(SMEs)in the internet.This paper predicts the overall sales volume of the enterprise through the classic ARIMA model,and notes that the behavior and arrival differences between the new and old customer groups will affect the accuracy of our forecasts,so we then use Pareto/NBD to explore the repeated purchases of customers at the individual level of the old customer and the SVR model to predict the arrival of new customers,thus helping the enterprise to make layered and accurate marketing of new and old customers through machine learning.In general,machine learning relies on powerful computation and storage resources,while mobile edge computing typically provides limited computation resources locally.Therefore,it is essential to combine machine learning with mobile edge computing to further promote the proliferation of data analysis among SMEs.

The Effect of Emotion on Consumer Behavior in the Fan Economy

Fans’customer behavior is highly susceptible to emotions.Emotions play an important role in the interaction of consumers and objects of interest in the fan economy.Based on the bounded rationality hypothesis of game participants,the game model is constructed by using the emotional function.On this basis,we used the dynamic system theory to dynamically replicate the equations of the general 2×2“Eagle Pigeon”evolutionary game,analyzed the behavior of both sides in the evolution,and got the equilibrium point between the two sides of the game to explain the mechanism of influence of emotions on customer behavior in fan economy.

Application of Markov decision process in customer behaviour

Customer is the source of business income,a stable customer base is the guarantee of enterprise survival and development of enterprises by using Markov decision process,decision-makers in the new decision point in time,to the latest state of observation system and adopt an original decision,decided in a well-posed option set an action sequence,and then choose to create value and total revenue in this sequence the most significant behavior,obtain the best marketing strategy,formulate relevant enterprise actual customer,dynamic programming model.

Retailers,You Can Get Omni-Shopper’s Satisfaction!

This paper evaluates the influence that information processing routes have on omni-shopping behavior,as well as analyzing the consequences of this behavior for retailers through a cognitive-affective approach.A sample of 705 mobile phone users was used for this purpose.The results obtained using the binomial logit model in a first phase and later with an application of structural equations,reflect that omni-shoppers have a more planned purchasing behavior than those who develop a one-stop shopping behavior.They search for information in a rational and deep way,spending time and effort.As for the consequences that the omni-channel behavior has for retailers,it has been found that those omni-shoppers who experience negative emotions with the retailer,have a low perceived value of the company and their satisfaction will also be negative.

A Study of Service Quality of Fantawild ASEAN Legend Theme Park,Nanning,China

At present,Chinese theme parks are popping up more and more.There are not many theme parks in China that can operate stably for a long period of time.The development prospect of Nanning Fantawild ASEAN Legend Theme Park is good.However,the question of how to maintain and improve the competitiveness of Nanning Fantawild ASEAN Legend Theme Park,attract more visitor volume,and create the most attractive theme park in Nanning is the question of the future sustainable survival and development of Nanning Fantawild ASEAN Legend Theme Park.This paper combines theory and practice,referring to a large amount of relevant information and literature from home and abroad,and summarizing the existing experiences and achievements.Therefore,visitors who have visited the ASEAN Legends Theme Park at Fantawild Joy World in Nanning were selected as the respondents.Firstly,this paper synthesises relevant theories such as service quality theory and(6W1H)customer behaviour.A set of questionnaires was designed for the visitors of Nanning Fantawild.The study analyzes the factors affecting the service quality of Nanning Fantawild ASEAN Legend Theme Park as well as the factor analysis of customer behaviour.Based on the empirical research and analysis of the results,methods and suggestions for improving the service quality of Nanning Fantawild ASEAN Legend Theme Park are proposed.This paper uses SPSS statistical software to analyze the results by means of reliability and validity analysis,descriptive statistics analysis,and analysis of variance.The results were concluded that the customers’overall satisfaction with the service quality of Nanning Fantawild ASEAN Legend Theme Park is shown in the question phase of each level dimension,with the reliability dimension showing the lowest level of satisfaction.It is of great practical significance to improve the competitiveness of Nanning Fantawild ASEAN Legend Theme Park in China.Finally,there were no significant mean differences in the relationship between different gender,age,education,status,income,and service quality dimensions.

Customer Joining Behavior and Regulation Strategy in Visible Multi-Server Queues with Synchronous Vacations of Partial Servers

This paper studies customer joining behavior and system regulation strategy in nonexhaustive visible M/M/m queues with synchronous vacations of a part of the servers.Once this part of the servers are idle,they take multiple vacations simultaneously(vacation period).Until there are customers waiting in the queue,they are reactivated and all servers are busy or idle(busy period).The authors call this part of the servers as“partial servers”.In view of the fully visible queue and the almost visible queue,the authors obtain customers’equilibrium joining threshold strategies and their socially optimal joining threshold strategies,respectively,and observe that customer joining behavior in equilibrium generally makes the system overcrowded,which makes the equilibrium social welfare lower than the optimal social welfare.After regulation,interestingly,for optimizing social welfare,the system manager hopes not only customers arriving in vacation period pay attention to the number of partial servers,but also customers arriving in busy period should care about it rather than ignore.Moreover,arranging more servers for vacation does not necessarily lead to the decrease of social welfare on condition that the number of partial servers is close to m.As for the information advantage of the fully visible case,it is not obvious for increasing social welfare and even unfavorable to servers’profit unless the number of partial servers is big enough.Furthermore,given the different composition of social welfare,there exists the optimal number of partial servers and the optimal arrival rate of customers for maximizing social welfare.

Hierarchical and distributed demand response control strategy for thermostatically controlled appliances in smart grid

Thermostatically controlled appliances(TCAs)have great thermal storage capability and are therefore excellent demand response(DR) resources to solve the problem of power fluctuation caused by renewable energy.Traditional centralized management is affected by communication quality severely and thus usually has poor realtime control performance. To tackle this problem, a hierarchical and distributed control strategy for TCAs is established. In the proposed control strategy, target assignment has the feature of self-regulating, owing to the designed target assignment and compensating algorithm which can utilize DR resources maximally in the controlled regions and get better control effects. Besides, the model prediction strategy and customers’ responsive behavior model are integrated into the original optimal temperature regulation(OTR-O), and OTR-O will be evolved into improved optimal temperature regulation. A series of case studies have been given to demonstrate the control effectiveness of the proposed control strategy.