This study explores the effect of delayed differentiation on a multiproduct vendor-buyer integrated inventory system with rework to identify its potential benefits and provide managers with in-depth information for operational decision-making. The main considerations of the proposed study include a multiproduct fabrication plan to increase machine utilization, a rework process to ensure product quality, and a multi-shipment policy to distribute the end products. In addition, these products sharing an intermediate part for which a two-stage fabrication scheme is adopted, wherein the common parts are produced at the first stage and the end products are manufactured at the second stage. The aim is to reduce the overall system costs and shorten the replenishment cycle time. Mathematical modeling and optimization methods were employed to derive the closed-form optimal replenishment cycle time and delivery decisions. We demonstrated the applicability of our research results through numerical examples and revealed that for both linear and nonlinear relationships between the common intermediate part's completion rate α and its practical value at α, our proposed two-stage production scheme with delayed differentiation is considerably beneficial vis-à-vis single-stage schemes in saving overall system costs and reducing the replenishment cycle time.

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Choosing a middle manager with management competency and capabilities will have a decisive influence on the organization's development for international shipping service providers. There is ambiguity and uncertainty in the decision-making environment during the selection of a middle manager and many evaluation criteria must be considered. The main purpose of this article is to construct a fuzzy multiple criteria decision-making (MCDM) model for international shipping service providers to use when selecting a middle manager. First, some methods and concepts of the fuzzy theory are introduced in this article. Five steps of evaluation model of fuzzy MCDM algorithms are then proposed to choose a best middle manager. Finally, an international shipping case is presented and the proposed fuzzy MCDM model is illustrated step by step. It can be seen from the demonstration that this evaluation model can be used to effectively select the best middle manager.

The main purpose of this article is to use the fuzzy analytic hierarchy process (AHP) method to empirically study the key competency and capabilities affecting the selection of middle managers for global shipping logistics service providers (GSLSPs). To facilitate this theme for obtaining key competency and capabilities, a list of five management competency with twenty-five capabilities are preliminary summarized. Subsequently, the proposed fuzzy AHP method is applied to measure relative weights for evaluating these competency and capabilities. The appraisal approach is then to perform empirical survey via AHP expert questionnaires. Finally, the empirical results show that: (1) ‘professional competency’ is the most important management competency affecting the selection of middle managers for GSLSPs. (2) In order of relative importance, the top six key management capabilities affecting the selection of middle managers for GSLSPs are the ‘capability to manage work pressure,’ ‘capability to manage crisis,’ ‘capability to lead team awareness,’ ‘capability to manage interpersonal networks perfectly,’ ‘capability to use logistics expertise to enhance work efficiency,’ and ‘capability to effectively build team spirit and work atmosphere,’ respectively. Furthermore, concluding remarks are provided in this article.

Adaptation of information technology in business applications enables enterprises to understand customer behaviors and use customer‐related knowledge to increase competitiveness, adjust product market position, and build customer loyalty. The Internet and computer telephony integrated (CTI) applications, in particular, enhance the communication channels among members of extended enterprises (e.g., customers and suppliers). Thus, Customer Relationship Management (CRM) has become a key focus of modern enterprise operations with the help of modern Internet and CTI techniques. A company can achieve the customer‐centric business model and the one‐to‐one marketing strategy by using contact center applications and data mining methodologies. With the increasing number of communication channels, telephone‐based contact centers are no longer sufficient to build and maintain good customer relations. Multi‐channel contact centers that integrate phone, fax, e‐mail, web, and PDAs enable managers to respond to customer queries, complaints and service requests. An improved CRM program not only provides greater access but also provides the means to analyze customer interaction data. Corporations gain benefits such as enhanced customer loyalty and brand enhancement by transforming data collected through multiple communication channels into meaningful knowledge. This research uses a multi‐channel contact center (CC) as a basis to model customer interaction processes, define key performance indicators (KPIs) of CC, and develop CC evaluation methods to measure customer satisfaction and service quality of a contact center based on the set KPIs.