Optimization and coordination of South-to-North Water Diversion supply chain with strategic customer behavior

The South-to-North Water Diversion （SNWD） Project is a significant engineering project meant to solve water shortage problems in North China. Faced with market operations management of the water diversion system, this study defined the supply chain system for the SNWD Project, considering the actual project conditions, built a decentralized decision model and a centralized decision model with strategic customer behavior （SCB） using a floating pricing mechanism （FPM）, and constructed a coordination mechanism via a revenue-sharing contract. The results suggest the following： （1） owing to water shortage supplements and the excess water sale policy provided by the FPM, the optimal ordering quantity of water resources is less than that without the FPM, and the optimal profits of the whole supply chain, supplier, and external distributor are higher than they would be without the FPM; （2） wholesale pricing and supplementary wholesale pricing with SCB are higher than those without SCB, and the optimal profits of the whole supply chain, supplier, and external distributor are higher than they would be without SCB; and （3） considering SCB and introducing the FPM help increase the optimal profits of the whole supply chain, supplier, and external distributor, and improve the efficiency of water resources usage.

MODELING COMMERCIAL PROCESSES AND CUSTOMER BEHAVIORS TO ESTIMATE THE DIFFUSION RATE OF NEW PRODUCTS

This paper presents a generic mathematical model for depicting the diffusion of an innovative product on a given market. Our approach relies on a probabilistic modeling of each customer behavior with respect to the commercial process which is used to promote such a product. We introduce in particular the concept of coherent market that corresponds to a market which can be analyzed in a uniform way within our model. This last notion allows us to recover the classical empirical results that were discovered and widely studied by E.M. Rogers and his school. We explain finally how to use our approach as a support for analytic predictive marketing.

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.

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.

Self-concept and Marketing Strategies

This contribution of this paper is devoted to the research results in the field of self-expression and self-image of the individual in the world of information processing and cognition. Marketing strategies help make decisions that will help us to bring the subject to market activities. The current trend is a knowledge-based society, skills, abilities, information, storage, and transmission. Our marketing strategy focuses on four key issues： production, respectively service, price, distribution channels, and advertising. It is important to know how to develop an individual＇s current self-image. Implementation strategies are then engaged in transforming decisions into concrete action, meaning, and the decision has to be taken with regard to flexibility and acceptance. The sample consists of 4,420 respondents, men and women in three age groups： 0-15 years, 16-40 years, and 41-60 years. All responded to one question, ＂Where is your center？＂ Respondents had to show on their body. The question was chosen very sensitive, not to predict the answer. Terms soul, psyche, personality would be very manipulative, and therefore were excluded. In line with expectations, the majority of respondents have shown to their head, chest, and abdomen, but were also unconventional answers, in accordance with the preferred self-image and values of the individual. Lessons from research outputs were analyzed by the following processes： general description, item-total correlation, exploratory factor analysis of individual areas, and correlation analysis of individual items. It was found that medium correlations between area of body abdomen and age to 15 years were significant. Mean item-total correlation for areas of body were： Head was 0.35 and chest 0.43, and abdomen 0.22. In the descriptive statistics it was found that most respondents preferred the chest, followed by the head and abdomen. As for the distribution of respondents into three age groups, we found differences between men and women. Next, it was analyzed the relationship between the areas of the body and gender. Statistically significant differences were found on the chest, where women scored more than men, and it was also found significant differences in the abdominal area, where men scored more than women.

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.

URMG: Enhanced CBMG-Based Method for Automatically Testing Web Applications in the Cloud

To satisfy the rapid growth of cloud technologies, a large number of web applications have been developed and deployed, and these applications are being run in clouds. Due to the scalability provided by clouds, a single web application may be concurrently visited by several millions or billions of users. Thus, the testing and performance evaluations of these applications are increasingly important. User model based evaluations can significantly reduce the manual work required, and can enable us to determine the performance of applications under real runtime environments. Hence, it has become one of the most popular evaluation methods in both industry and academia. Significant efforts have focused on building different kinds of models using mining web access logs, such as Markov models and Customer Behavior Model Graph （CBMG）. This paper proposes a new kind of model, named the User Representation Model Graph （URMG）, which is built based on CBMG. It uses an algorithm to refine CBMG and optimizes the evaluations execution process. Based on this model, an automatic testing and evaluation system for web applications is designed, implemented, and deployed in our test cloud, which is able to execute all of the analysis and testing operations using only web access logs. In our system, the error rate caused by random access to applications in the execution phase is also reduced, and the results show that the error rate of the evaluation that depends on URMG is 50% less than that which depends on CBMG.

OPTIMAL PRICING AND INVENTORY POLICY WITH ORDER CANCELATIONS UNDER THE CASH-ON-DELIVERY PAYMENT SCHEME

Considering a periodic review system where the online seller allows the customers to pay when the products are delivered to them(referred as cash-on-delivery payment scheme in this paper),the authors investigate the seller's joint pricing and inventory control policy with a finite planning horizon.In particular,the authors incorporate the customers' possible order cancellation behavior with the cash-on-delivery scheme.It can be proven that the base-stock list price policy is optimal under mild conditions.The authors also analyze the impact of the customers' forward looking behavior on the optimal policy.

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.