This paper investigates the R&D project portfolio selection problem. Despite its importance and impact on real world projects, there exist few practical techniques that help construct an non-dominated portfolio for a decision makers satisfaction. One of the difficulties constructing the portfolio is that such project portfolio problem is, in nature, a multi-attribute decision-making problem, which is an NP-hard class problem. This paper investigates the R&D project portfolio selection problem. Despite its importance and impact on real world projects, there exist few practical techniques that help construct an non-dominated portfolio for a decision makers satisfaction. One of the difficulties constructing the portfolio is that such project portfolio problem is, in nature, a multi-attribute decision-making problem, which is an NP-hard class problem. In order to obtain the non-dominated portfolio that a decision maker or a user is satisfied with, we devise a user-interface algorithm, in that the user provides the maximum/minimum input values for each project attribute. Then the system searches the non-dominated portfolio that satisfies all the given constraints if such a portfolio exists. The process that the user adjusts the maximum/minimum values on the basis of the portfolio found continues repeatedly until the user is optimally satisfied with. We illustrate the algorithm proposed, and the computational results show the efficacy of our procedure.

Through collaboration between buyers and suppliers, their companies try to achieve their own objectives and competitive advantages. And it is known that trust between them also would influence the effects of collaboration, which would increase their performances. In this study, above three domains of constructs : trust, collaborative behavior, performance are handled. From gathering data about a mobile networks industry and building a research model, we acquire the results of the study. Through nine hypotheses, the study show the results. The end of this paper describes managerial implications for collaborative performance and SCM strategy.

In the mobile communication service market, this study represents an attempt to forecast the subscribers of the IMT-2000 service market using the questionnaire of experts which is the qualitative technique is used. In this study, by using the substitution model of next generations among products in order to analyze the IMT-2000 demand of service, a demand was predicted. And by estimating the market demand prospect in which it becomes the important factor of the IMT-2000 service diffusion according to each bandwidth frequency the politically necessary approaching direction about the frequency was presented. It will be able to become the important part to not only the business carrier but also the policy maker to examine a prospect toward the subscriber of the IMT-2000 service. As a result, the market demand was exposed to be most big when the SKT 800MHz, and the KTF 800(900)MHz were used as the additional frequency. And it was likely to reach to the IMT-2000 number of subscribers to about 35.750 thousand peoples in the future at 2015.

This paper considers a profit-based unit commitment problem with fuel consumption constraint and maintenance cost, which is one of the key decision problems in electricity industry. The nature of non-linearity inherent in the constraints and objective functions makes the problem intractable which have led many researches to focus on Lagrangian based heuristics. To solve the problem more effectively, we propose mixed integer programming based solution algorithm linearizing the complex non-linear constraints and objectives functions. The computational experiments using the real-world operation data taken from a domestic electricity power generator show that the proposed algorithm solves the given problem effectively.

In recent warfare, the performance improvement of air weapon systems enables an aircraft to strike multiple targets on a single sortie. Further, aircrafts attacking targets may carry out an operation as a strike package that is composed of bombers, escort aircrafts, SEAD (Suppression of Enemy Air Defenses) aircrafts and etc. In this paper, we present an aircraft allocation model that allocates multiple targets to a single sortie in the form of a strike package. A mixed integer programming is developed and solved by using a commercially available software. The new model is better than existing ones because not only it allocates aircrafts to multiple targets but also it models the concept of the strike package. We perform a computational experiment to compare the result of the new model with that of existing ones, and perform sensitivity analysis by varying a couple of important parameters.

Information strategy planning (ISP) pursues alignment of business strategy and IT (Information Technology) strategy as well as derivation of feasible and valuable IT projects. However, conventional ISP methodology hardly obtains the objectives because of its intrinsic shortcomings. Diverse ways are proposed for the improvement of the conventional methodology including, for example, combination of EA (Enterprise Architecture) with ISP. Meanwhile, six-sigma methodology which is characterized by quantification, scientific and systematic approach, customer orientation, process orientation has been gaining considerable attention and extending its application scope continuously. In this paper, an innovative ISP methodology is proposed by decomposing activities, methods, and tasks from conventional ISP process and reorganizing them into DMADOV six-sigma framework. In addition, the usefulness and applicability of the newly proposed methodology are provided using an electronics company example. The methodology enhance the possibility of producing future oriented and beneficial IT projects by associating IT strategy and the projects in the form of quantified causal relationship. Besides, it can also increase the objectivity of IT vision and strategy.

This study is focused on the problem of seat allocation for group travel demand in airlines. We first explain the characteristic of group demand and its seat allocation process. The group demand in air travel markets can be classified into two types : incentive and package groups. Allocating seats for group demand depends on the types of group demand and the relationship between airlines and travel agents. In this paper we concentrate on the package group demand and develop an optimization model for seat allocation on the demand to maximize the total revenue. With some assumptions on the demand distribution and the linear approximation technique, we develop a mixed IP model for solving our problem optimally. From the computational experiments, we can find our optimization model can be applied well for real-world application.

As to more efficiently manage the inventory in the retail supply chain and to meet the customer demand in a timely manner, vendor-managed inventory (VMI) has been widely accepted, which manages inventory in the retail supply chain via sharing information and collaborating with the retailers. Applying VMI generates vendor-managed inventory/distribution problem (VMIDP), which involves inventory management for both the vendor and the retailers, and the design of vehicle routes for delivery, to minimize the total operating cost in the supply chain. In this paper, we suggest a mixed integer programming (MIP) model to obtain the optimal solution for VMIDP in a two-echelon retail supply chain, and develop an efficient heuristic based on the operating principles of the MIP model. To evaluate the performance of the heuristic, its solution was compared with the one of the MIP model on a total of twenty seven test problems. As a result, the heuristic found optimal solutions on seven problems in a significantly reduced time, and generated a 4.3% error rate of total cost in average for all problems. The heuristic is applied to the case problem of the local famous franchise company together with GIS, showing that it is capable of providing a solution efficiently in a relatively short time even in the real world situation.

Recently, DMB service markets experience a rapid change with terrestrial DMB test-broadcasting for the nation-wide coverage and paid interactive data broadcasting being offered utilizing TPEG and BIFS technologies. This warrants a reexamination of a consumers' adoption intentions for DMB service. This paper uses a survey data set to analyze DMB adoption intentions and the choice between terrestrial DMB and satellite DMB services according to preferred contents and other media usage characteristics. Empirical results show that consumer who prefer TV, music, and movie contents are more likely to adopt DMB service, whereas consumers with high intentions for HSDPA subscription are less likely to adopt DMB service. This implies that continuing development of killer application and the analysis of substitutes or complements of other media are crucial for the increase of DMB adoption intentions. It is found that the more consumers prefer sports, movies and entertainment/game and put higher values in the quality of the contents, the more likely they adopt satellite DMB service. Meanwhile, the more consumers prefer TV, drama and news contents, and are sensitive to the subscription fees, they are more likely to adopt terrestrial DMB service. Therefore, it seem that consumers' DMB adoption between terrestrial and satellite services is crucially related with types and characteristics of contents offered.

Conjoint Analysis is marketers' favorite methodology for finding out how buyers make trade-offs among competing products and suppliers. Thousands of applications of conjoint analysis have been carried out over the past three decades. The conjoint analysis has been so popular as a management decision tool due to the availability of a choice simulator. A conjoint simulator enables managers to perform 'what if' question accompanying the output of a conjoint study. Traditionally the First Choice Model (FCM) has been widely used as a choice simulator. The FCM is simple to do, easy to understand. In the FCM, the probability of an alternative is zero until its value is greater than others in the set. Once its value exceeds that threshold, however, it receives 100%. The LOGIT simulation model, which is also called as "Share of Preference", has been used commonly as an alternative of the FCM. In the model part worth utilities aren't required to be positive. Besides, it doesn't require part worth utilities computed under LOGIT model. The simulator can be used based on regression, monotone regression, linear programming, and so on. However, it is not free from the Independent from Irrelevant Alternatives (IIA) problem. This paper proposes the EBA (Elimination-By-Aspects) model as a useful conjoint-like method. One advantage of the EBA model is that it models choice in terms of the actual psychological processes that might be taking place. According to EBA, when choosing from choice objects, a person chooses one of the aspects that are effective for the objects and eliminates all objects which do not have this aspect. This process continues until only one alternative remains.

One of characteristics of firms having successfully developed new products is that they are practicing strategic learning, that is, organizational learning for preparing the future. In this context, we attempts to examine the effect of strategic learning on the proficiency of new product development activities and new product outcome, in an empirical way. In addition, we Investigated the moderating effect of new product innovativeness on the relationship among strategic learning, proficiency of new product development activities, and new product outcome. The analysis results show that the strategic learning has a positive impact on both the proficiency of new product development activities and new product outcome. And it was found that the impact of strategic learning on the proficiency of new product development activities is increasing when firms developing new products with high degree of innovativeness. However, the impact of strategic learning on new product outcome was not different according to new product innovativeness. This results shed some insight on the role of strategic learning in the new product development management.

In this paper, we examined the difference of the effects of buying factors in two consumer segments divided by the innovative behavior for digital convergence products, and developed relevant managerial implications. As the digital convergence product could be understood as a innovative bundling product, the buying factors of the digital convergence products were clustered in 3 groups : common innovation-bundling factors, innovation factors and bundling factors. Tests for the difference of regression coefficients of the purchasing factors in the two markets show that (1) the early market is affected by both of the common innovation-bundling factors and the innovation factors, while the mainstream market is affected by all of the common innovation-bundling factors. the innovation factors and the bundling factors, (2) the early market is more affected by the technical benefit, while the mainstream market is more affected by the pragmatic benefit, and (3) both of the two markets are affected by the compatibility and the message communicability. The relevant managerial implications for the successive diffusion of the digital convergence products can include (1) in the entire period of the diffusion. enhancing the compatibility between consumer and product concept, performing constant and differentiated marketing communication activities, (2) in the early market of the diffusion, introducing unique innovative product which provides obvious and differential synergy through the convergence, appealing to the technical benefit, and (3) in the mainstream market of the diffusion, improving the qualities and features of individual products for the digital convergence product, appealing to the pragmatic benefit, reducing the complexity of product.

While CRM has recently attracted a lot of attention among academics and practitioners, most academic research in this area has focused on consumer markets, but CRM in industry markets is less focused research area so far. Companies in industry market have suspected effects of the relationship between CRM's activities and performance which is related to customer satisfaction and customer loyalty. The main purpose of this research support CRM strategy development. Therefore, this research is focused on as follows; first, defining the concept of CRM and performance second, identifying the customer relationship's characteristics and CRM relational activities in industrial markets third, verifying the relationship between customer satisfaction and customer loyalty in the case of Steel industry which is whether the CRM relational activities have effects on customer loyalty directly, or indirectly through customer satisfaction.