This article proposes a variable sampling interval (VSI) $\bar{X}$ control chart using weighted standard deviation (WSD) method for skewed populations. The WSD method decomposes the standard deviation of a quality characteristic into upper and lower deviations and adjusts control limits and warning limits of a control chart in accordance with the direction and degree of skewness. A control chart constant is derived for estimating the standard deviation of skewed distributions with the mean of sample standard deviations. The proposed chart is compared with the conventional VSI $\bar{X}$ control chart under some skewed distributions. Simulation study shows that the proposed WSD VSI chart can control the in-control average time to signal (ATS) as an adequate level better than the conventional VSI chart, and the proposed chart can detect a decrease in the process mean of a quality characteristic following a positively skewed distribution more quickly than the standard VSI chart.

In this paper, we deal with a Steiner Ring Star (SRS) problem arising from the design of survivable telecommunication networks. We develop two mixed integer programming formulations for the SRS problem by implementing Miller-Tucker-Zemlin (MTZ) and Sarin-Sherali-Bhootra (SSB) subtour elimination constraints, and then apply the reformulation-linearization technique (RLT) to enhance the lower bound obtained by the LP relaxation. By exploiting the ring-star structure of underlying network, we devise some valid inequalities that tighten the LP relaxation. Computational results demonstrate the effectiveness of the proposed solution procedure.

The recent keyword advertising does not reflect the individual customer searching pattern because it is focused on each keyword at the aggregate level. The purpose of this research is to observe processes of customer searching patterns. To be specific, individual deal-proneness is mainly concerned. This study incorporates location as a control variable. This paper examines the relationship between customers' searching patterns and probability of purchase. A customer searching session, which is the collection of sequence of keyword queries, is utilized as the unit of analysis. The degree of deal-proneness is measured using customer behavior which is revealed by customer searching keywords in the session. Deal-proneness measuring function calculates the discount of deal prone keyword leverage in accordance with customer searching order. Location searching specificity function is also calculated by the same logic. The analyzed data is narrowed down to the customer query session which has more than two keyword queries. The number of the data is 218,305 by session, which is derived from Internet advertising agency's (COMAS) advertisement managing data and the travel business advertisement revenue data from advertiser's. As a research result, there are three types of the deal-prone customer. At first, there is an unconditional active deal-proneness customer. It is the customer who has lower deal-proneness which means that he/she utilizes deal-prone keywords in the last phase. He/she starts searching a keyword like general ones and then finally purchased appropriate products by utilizing deal-prone keywords in the last time. Those two types of customers have the similar rates of purchase. However, the last type of the customer has middle deal-proneness; who utilizes deal-prone keywords in the middle of the process. This type of a customer closely gets into the information by employing deal-prone keywords but he/she could not find out appropriate alternative then would modify other keywords to look for other alternatives. That is the reason why the purchase probability in this case would be decreased Also, this research confirmed that there is a loyalty effect using location searching specificity. The customer who has higher trip loyalty for specificity location responds to selected promotion rather than general promotion. So, this customer has a lower probability to purchase.

This paper proposes a real time pricing model for smart grid considering consumers' behavior, real time price elasticity, and exogenous price. Based on the proposed model, we found the weight of utility over cost is the most sensitive factor compared to other factors. Also, if the electricity price is set to be changed too sensitively to energy consumption, it is warned that real time pricing sometimes can cause increment of peak-time demand and volatility. Finally, real time pricing could be less efficient when the difference between the maximum and the minimum consumption level is small.

Financial products entail either gains or losses, and customers' psychological reaction to these gains and losses affect the selection of the financial products. This study explains the financial customers' behavior by introducing consumers' psychological variables such as regulatory focus and construal levels. According to the regulatory focus theory, there are two distinct motivational orientations called promotion focus and prevention focus. And, construal level theory proposes that people use more abstract and higher levels of construal to represent objects that are more distant on psychological distance. We have incorporated these two psychological variables into financial consumer behaviors. In the experiment 1, the results have showed that promotion focused customers prefer fund products to deposit products, whereas prevention focused customers have showed the opposite result. In the experiment 2, both regulatory focus and construal level were considered. Specifically, under the high level message, promotion focused customers have showed higher preference to fund products than the prevention focused customers, and no significant difference for the deposit products. On the contrary, given the low level message, prevention focused customers have showed higher preference to both fund and deposit products than the promotion focused customers. Therefore, it comes to the conclusion that it will be efficient for the financial companies to use high level messages for the promotion focused customers and low level messages for the prevention focused customers. Implications and limitations are discussed to establish more effective marketing strategies based on the results of this study.

Retail shops often experience purchase dependence in which some items are purchased together by customers due to their unknown interior associations. This paper develops an inventory model considering partial backordering under purchase dependence and compares the performance of the inventory model that ignores purchase dependence. Computational analyses show that purchase dependence should be incorporated as an important factor of inventory replenishment policy because the impact of purchase dependence can be more significant as the lost portion of the unmet demand orders increases and the item set is more correlated in terms of order demand.

PSS (Product-Service System) is a competitive strategy for a service company or a servitized manufacturer. We investigate the product-service integration effect in a mobile phone service industry. Using choice-based conjoint analysis, we measure main and interaction effects of product and service. We collected a sample of size 171 from a college student group in Seoul, Korea. We find the existence of the interaction effect of product and service in PSS and show the direction of PSS strategy using main and interaction effect.

The stochastic dominance approach is to form a portfolio that stochastically dominates a predetermined benchmark portfolio such as KOSPI. This study is to search a set of portfolio weights for the first-order stochastic dominance with maximum utility defined in terms of mean and variance by managing the constraint set and the objective function in an iterative manner. A nonlinear programming algorithm was developed and tested with promising results against Korean stock market data sets.