Customer firms exercise various sources of power to influence their suppliers' behaviors or decisions. In this study we aim to examine the effects of customers' sources of power on their supplier's performance improvement. This study posits that a customer's expert, referent, and reward power positively influence a supplier's performance directly as well as indirectly through increased supplier-customer integration. On the contrary, the customer's coercive power is expected to worsen the supplier's operational performance because of increasing distrust, dissatisfaction, and conflict with the customer. Data collected from 1,229 firms from Korea, China, Hong Kong, Taiwan, and the U.S. are used to test the hypotheses. Expert power proves to be the most effective source of customer power in improving a supplier's inventory cost, delivery, and flexibility performance. In contrast, coercive power deteriorates significantly all supplier performance variables. Academic and managerial implications are presented and future research directions are also discussed.

In this paper, we evaluate the strength of three families of cutting planes for a lot-sizing problem. Lot-sizing problem is very basic MIP model for production planning and many strong valid inequalities have been developed for a variety of relaxations in the literature. To use three families of cutting planes in Branch-and-Cut framework, we develop separation algorithms for each cut and implement them in CPLEX. Then, we perform computational study to compare the effectiveness of three cuts for randomly generated instances of the lot-sizing problem.

Even though ruin probability is a fundamental value to determine the insurance premium and policy, the complexity involved in computing its exact value forced us resort to an approximate method. In this paper, we first present an exact method to compute ruin probability under the assumption that the claim size has a GPH distribution, Then, for the arbitrary claim size distribution, we provide a method computing ruin probability quite accurately by approximating the distribution as a GPH. The validity of the proposed method demonstrated by a numerical example. The GPH approach seems to be valid for heavy-tailed claims as well as usual light-tailed claims.

We study the problem of multiple response optimization (MRO) and focus on the selection of input levels which will produce desirable output quality. We propose an interactive multiple objective optimization approach to the input design. The earlier interactive methods utilized for MRO communicate with the decision maker only using the response variable values, in order to improve the current response values, thereby resulting in the corresponding design solution automatically. In their interaction steps of preference articulation, no account is taken of any active changes in design variable values. On the contrary, our approach permits the decision maker to change the design variable values in its interaction stage, which makes possible the consideration of the preference or economics of the design variable side. Using some typical value functions, we also demonstrate that our method converges reasonably well to the known optimal solutions.

This paper presents the issue that is predicting the movement of an agent in an enclosed space by using the MDP (Markov Decision Process). Recent researches on the optimal path finding are confined to derive the shortest path with the use of deterministic algorithm such as $A^*$ or Dijkstra. On the other hand, this study focuses in predicting the path that the agent chooses to escape the limited space as time passes, with the stochastic method. The MDP reward structure from GIS (Geographic Information System) data contributed this model to a feasible model. This model has been approved to have the high predictability after applied to the route of previous armed red guerilla.

Firms have reexamined and restructured their supply chain based on a long-term and partnership perspective as a firm's competitive advantage increasingly relies on its supply chain capability. A number of scholar works has provided evidence to support the positive effects of supply chain collaboration; however, the relationship between collaboration and performance is still inconclusive. This study refuses to have blinded faith on supply chain collaboration, but rather this paper suggests that the contribution of collaboration to supply chain performance improvement can be limited and vary along the contextual characteristics of a buyer-supplier relationship. Moreover, we argue that the relationship between supply chain collaboration and performance can be curvilinear. This paper provides and test hypotheses regarding the relationship between supply chain collaboration and performance. By using data of the Manufacturing Panel Survey (MPS), this study empirically validates the hypotheses. Overall, the results of the study support our hypotheses about a limited contribution of supply chain collaboration to manufacturing performance, which is opposite to a conventional expectation. Particularly, the effects of supply chain collaboration differ depending on the dimensions of performance such as customer satisfaction, quality, cost, delivery, and flexibility as well as the dependency in the buyer-supplier relationship. Moreover, the results of the study indicate that supply chain collaboration and performance may have curvilinear relationships in a certain context. Through a comprehensive model and empirical evidence, this study presents a better understanding of supply chain collaboration and provokes an open discussion about the effects of collaboration. This study also provides insightful implications for managers of buyers as well as suppliers who wish to foster stronger supply chain performance via a deep buyer-supplier relationship and collaboration.

There has been a lack of research that has addressed firm performance associated with the mechanism among dependence, conflict and cooperation in the context of B2B relationships. Building on current knowledge regarding key constructs of dependence, conflict, and cooperation, the authors examine the primary assumption underlying firm performance and presents a process model of key constructs on firm performance using two moderators (relationship length and firm type). In so doing, a professional online research firm conducts panel survey and a total of 200 responses are used to test our proposed model. The results show that both conflict-cooperation and cooperation-firm performance linkages are significant, but other proposed links are insignificant. While the moderating effect of firm type is not significant, the dependence-performance link is moderated by relationship length, particularly in the stage of the initial relationships. These results has implications for a better understanding of B2B relationships from the initial stage to the sustainable stage.