Social games where players play together with others in multiplayer mode are currently emerging and attracting attention in the media after the success of e.g. Pokemon GO. Nevertheless, little is known about the profitability of social players. Previous gaming research that has profiled different types of players has focused on games played alone, without social mechanics (cf. Vahlo et al., 2017). From a marketing perspective, it is also interesting to study the effects of merely watching game play or browsing new game ads as a mode of entertainment, and what kind of effect that has on future behaviour. Passive participation as a type of aesthetic entertainment has been acknowledged in eSports context (Seo, 2013). This paper analyses big data of a gaming company on an individual player level, including different types of single play and multiplayer gaming sessions and in-game purchase behaviour data. We compare the effects of social and non-social ingame mechanics on how individuals spend money in-game over time, frequency of play, sessions as well as the length of played sessions in minutes during the gamers’ whole lifecycle. The anonymized repository data includes gaming behaviour, in-game purchase behaviour related to the use of one specific digital game in the USA. The game can be played both alone, and with others as a team. We used structural equation modeling to analyse the behavior of 23 049 randomly selected players, who have played the game for at least one week. The data included the individual players’ total session history during their play lifecycle. Interestingly, social play with other people is a strong predictor of money spent in the long term. Social play also prompts long-term interest in the game, as friends invite and encourage each other to play with or against other virtual teams. Nevertheless, social play is not for everyone! The results help to optimize player journeys and to make strategic decisions that support long term profitability of gaming companies.

This study aims to examine how the mobile social network service experience affects value co-creation and customer lifetime value. The mobile social network service experience includes mobile convenience, social compatibility, social risk, and cognitive effort. The research hypotheses with structural equation modeling are tested. In mobile SNS context, value co-creation behaviors essentially determine customer lifetime value of mobile shopping apps. Value co-creation behaviors have received little attention in mobile shopping. The mobile SNS experience strongly influences value co-creation behaviors. This study is based on a sample of mobile SNS users nationwide in Korea. Therefore, the generalizability of the findings has to be tested. Furthermore, the study examines customer lifetime value, which is good sales predictor of mobile shopping apps. Moreover, the research model included the positive and negative determinants on mobile SNS experience. Future researches examine other use intentions of mobile SNS. Value co-creation behaviors substantially affect customer lifetime value. Mobile shopping apps should increase customer lifetime value from mobile SNS experience and value co-creation. This study shows how individual mobile SNS user provides mobile shopping apps with profit through value co-creation. This study is the first to examine how mobile SNS users enhance value co-creation and how value cocreation behaviors affect customer lifetime value of mobile SNS users.

In this empirical study, an attempt is made to show how the Customer Lifetime Value (CLV) can be computed by modeling multiple components of the customer and firm behavior. Specifically, attention will be given to modeling (1) the probability that a customer is likely to buy, (2) the quantity of purchase given that they will buy, and (3) the cost of marketing to each customer. Once the authors compute each of these inputs, they combine them to compute CLV using the net present value concept. The authors will examine multiple ways of computing purchase probabilities depending on the customer’s buying pattern. They will also discuss the estimation challenges in obtaining such inputs for computing CLV. The authors will demonstrate the implementation with a case study for a fashion retailer and what kind of managerial actions can be taken. Finally, a generalizable framework for all fashion retailers to maximize profits will be presented and discussed.

Customers are regarded as the key intangible assets of a company. It is necessary to have the capability to anticipate customer value. The study discusses the relationship among customer value anticipation, product innovativeness, and customer lifetime value from customer perspective. 178 MBA students were surveyed by questionnaire in this study. The results show that customer perceived customer value anticipation can significantly influence product innovativeness. Product innovativeness not only positively affects customer lifetime value, but also plays a partial mediating role between customer value anticipation and customer lifetime value. Both functional and emotional advertising can play a moderating role on the relationship between product innovativeness and customer lifetime value. At the end, managerial implications are discussed.

Supply chain management and e-procurement system built in the company, are set goal of internal process improvement. This paper show how SLV(Supplier Lifetime Value) can be used to structure the supplier in automotive part manufacturer, the method of selection is described and a detailed example of how SLV can be used and allocation of order Quantity for the selected suppliers also are provided, and aims at giving a method to realization profitable supplier relation using search for SL V system development which is making corporation with supplier, in the favor of decision supplier.

Last 2003, the CRM mayor was not lively glaringly. At beginning of the year, it may be said that gained result fewer than half of that is forecasted. Enterprises are seen that there are a lot of occasions that did not carry CRM project that planned very first time in practice or put off investment program until 2004 altogether. This can see that it is thing which CRM's accuracy of data analysis process drops up to now and investment of enterprises is unprepared. In this paper, It consolidates the necessity on a LTV (Life Time Value) and analyzes data which is concerned of Customer Value. Under the these environments, defines the LTV rule that can improve the customer value. And then, Scheduling plays an important role in shop floor planning. Therefore, this study tries to proposed that Scheduling by customer needs group for minimizing the problem.

We can be acquire the conformation about on the due date of supplier by using the A TP(A vail able to Promise) function of management about real and concurrent access on the supply chain, also decide the affect about product availability due to forecasting or customer's orders through the A TP. Under the these environments, defines the A TP rule that can improve the customer value and data flow related the LTV(Life Time Value) and builds on a algorithm. In this paper, It consolidates the necessity on a LTV (Life Time Value) and analyzes data which is concerned of Customer Value. Under the these environments, defines the LTV rule that can improve the customer value. And then, Scheduling plays an important role in shop floor planning. Therefore, this study tries to proposed that Scheduling by customer needs group for minimizing the problem.

In the recent environment of globalization where fierce competitions exist between manufacturers, SRM(Supplier Relationship Management) plays important role in the strategies of companies, and managements of companies try their best efforts in establishing the strategy to accomplish the innovative relationship between supply chain channels. The structure of the partnerships we develop with not only customers but also suppliers will in many cases determine the degree of success of the relationship. A successful partnership provides an opportunity for shared risk while maximizing the opportunity for mutual success whether it's with supplier. To follow this paper show how SLV(Supplier Lifetime Value) can be used to structure the supplier in automotive part manufacturer, This method of selection is described, and a detailed example of how SLY can be used and allocation of order quantity for the selected suppliers also are provided.

There is only one server available and arriving work require services from this server. Job are processed by the machine one at a time. The most common objective is to sequence jobs on the severs so as to minimize the penalty for being late, commonly called tardiness penalty Based on other objectives, many criteria may serve as s basis for developing job schedules. Therefore, this study tries to proposed that Scheduling by customer needs group for minimizing the problem and reducing inventory, product development time, cycle time, and order lead time.

Scheduling plays an important role in shop floor planning. A scheduling shows the planned time when processing of a specific job will start on each machine that the job requires. It also indicates when the job will be completed on every process. Thus, it is a timetable for both jobs and machines. There is only one server available and arriving work require services from this server. Job are processed by the machine one at a time. The most common objective is to sequence jobs on the severs so as to minimize the penalty for being late, commonly called tardiness penalty. Based on other objectives, many criteria may serve as s basis for developing job schedules. The process also comprises all strategic planning, capital investments, management decisions, and tasks necessary to create a new product. manufacturing processes must be created so that the product can be produced in the product facility. Purchasing new equipment and training workers may be required if new technology is to be used. Tools, fixtures, and the sequence of steps in the manufacturing processes must all be developed to allow rapid, high-quality, cost effective production. Also, it may be needed to be rearrange the production facility to adapt to the new manufacturing processes. Therefore, this study tries to proposed that Scheduling by customer needs group for minimizing the problem and reducing inventory, product development time, cycle time, and order lead time.

Today's environment of enterprise is changing, They have to face customer' demands with the right product, the right service and supply them at the right time. And also cut down logistics and inventory cost and bring up the profit as much as they can. This means the change of putting enterprise first in importance to putting customer first importance. therefore to correspond to customer's demand, shorting lead time is becoming a essential condition. The answer to this changes of environment is supply chain management. In this paper, It consolidates the necessity on a LTV(Life Time Value) and analyzes data which is concerned of Customer Value. Under the these environments, defines the LTV(Life Time Value) rule that can improve the customer value. We solved this problems using AHP(Analytic Hierarchy Process) for consistency at relationship matrix, AHP(Analytic Hierarchy Process) is based on Saaty's consistency rate. If consistency rate is under 0.1 point, preference rate's weights are acceptable. This study develop a program for AHP weights and support Satty's consistency rate.

Today's environment of enterprise is changing. They have to face customer' demands with the right product, the right service and supply them at the right time. And also cut down logistics and inventory cost and bring up the profit as much as they can. This means the change of putting enterprise first in importance to putting customer first importance. therefore to correspond to customer's demand, shorting lead time is becoming a essential condition. The answer to this changes of environment is supply chain management. In the Supply chain, The ATP function doesn't only give customers to conformation of delivery. It can be used by the core function with ATP rule that can reconcile supplies and demands on the supply chain. Therefore We can be acquire the conformation about on the due date of supplier by using the ATP function of management about real and concurrent access on the supply chain, also decide the affect about product availability due to forecasting or customer's orders through the ATP. In this paper, It consolidates the necessity on a CTP and analyzes data which is concerned of ATP. Under the these environments, defines the ATP rule that can improve the customer value and data flow related the LTV(Life Time Value) and builds on a algorithm.