Jason C.H. Chen

An overview of research on revenue management: current issues and future research

The paper provides a comprehensive review of the recent development of revenue management in different industries. We discuss research on different revenue management strategies including pricing, auctions, capacity control, overbooking and forecasting. Related issues such as economic concerns, customer perception, competition and consolidation, implementation, performance evaluation, and common techniques and approaches used for solving revenue management problems are also discussed. Finally, we give our suggestion on some important areas that warrant further research.

Decision consolidation: criteria weight determination using multiple preference formats

In multiple criteria decision making (MCDM), decision makers (DMs) always give preferences information on alternatives, criteria or decision matrices. Since the DMs may have diverse cultural and educational background and value systems, their preference would be expressed in different ways. This is especially true in cyberspace. In this study, the DMs are asked to express their preferences on a variety of criteria using any one of the following preference formats: preference orderings, utility values, multiplicative preference relation, selected subset, fuzzy selected subset, normal preference relation, fuzzy preference relation, linguistic terms, and pairwise comparison. In addition, we propose a uniformity method and an aggregating method to provide both convenience and accuracy in generating the final outcome and higher DM satisfaction. Finally, the validity of using multiple preference formats in criteria weight determination is verified through an experiment.

Location and allocation decisions for multi-echelon supply chain network - A multi-objective evolutionary approach

This paper aims at multi-objective optimization of single-product for four-echelon supply chain architecture consisting of suppliers, production plants, distribution centers (DCs) and customer zones (CZs). The key design decisions considered are: the number and location of plants in the system, the flow of raw materials from suppliers to plants, the quantity of products to be shipped from plants to DCs, from DCs to CZs so as to minimize the combined facility location and shipment costs subject to a requirement that maximum customer demands be met. To optimize these two objectives simultaneously, four-echelon network model is mathematically represented considering the associated constraints, capacity, production and shipment costs and solved using swarm intelligence based Multi-objective Hybrid Particle Swarm Optimization (MOHPSO) algorithm. This evolutionary based algorithm incorporates non-dominated sorting algorithm into particle swarm optimization so as to allow this heuristic to optimize two objective functions simultaneously. This can be used as decision support system for location of facilities, allocation of demand points and monitoring of material flow for four-echelon supply chain network.

Technopreneurship in Native American businesses: current issues and future with a case study

Economic issues combined with increased competitiveness resulting from globalisation and higher production costs and increased emphasis on customer quality and responsiveness have put pressure on existing companies to become more competitive. Many companies have looked toward information technologies to assist them in making this transition and to obtain the flexibility necessary to compete well into the future. This paper examines a tribally owned manufacturing enterprises efforts to implement new strategies for expansion and diversification. It will assess the problems and make recommendations as related to management tools including management information systems. The tribal enterprises core capabilities and structure for transformation into more high-tech industries with the government are also described.

Application of particle swarm intelligence algorithms in supply chain network architecture optimization

In todays globalization, the success of an industry is dependent on cost effective supply chain management under various markets, logistics and production uncertainties. Uncertainties in the supply chain usually decrease profit, i.e. increase total supply chain cost. Demand uncertainty and constraints posed by the every echelon are important factors to be considered in the supply chain design operations. Optimization is no longer a luxury but has become the order of the day. This paper specifically deals with the modeling and optimization of a three echelon supply chain network using the particle swarm optimization/intelligence algorithms.

Internet grocery business in Japan: current business models and future trends

The launch of a wave of Internet grocery retailers over the last six years presents a serious challenge to the traditional supermarket business model. The Internet grocery landscape changed radically in July 2001 when the top Internet grocer, Webvan, filed for bankruptcy. With the bankruptcy of Webvan, almost all the major stand‐alone online grocers in the USA have disappeared. Indeed, traditional supermarkets such as Albertsons and Safeway have recently been expanding into the online arena. In Japan, major traditional supermarkets have been seriously working on establishing online services in the metropolitan area with a “brick‐and‐click” model. Examines strategic reasons for today’s Japanese supermarkets to try establishing online grocery businesses. Also addresses critical success factors and current limitations based on socioeconomic conditions, Japanese culture, and expected future trends.

A bi-objective optimization of supply chain design and distribution operations using non-dominated sorting algorithm: A case study

Abstract This paper considers simultaneous optimization of strategic design and distribution decisions for three-echelon supply chain architecture consisting of following three players; suppliers, production plants, and distribution centers (DCs). The key design decisions considered are: the number and location of plants in the system, the flow of raw materials from suppliers to plants, the quantity of products to be shipped from plants to distribution centers, so as to minimize the combined facility location, production, inventory, and shipment costs and maximize fill rate. To achieve this, three-echelon network model is mathematically represented and solved using swarm intelligence based Multi-objective Hybrid Particle Swarm Optimization algorithm (MOHPSO). This heuristic incorporates non-dominated sorting (NDS) procedure to achieve bi-objective optimization of two conflicting objectives. The applicability of proposed optimization algorithm was then tested by applying it to standard test problems found in literature. On achieving comparable results, the approach was applied to actual data of a pump manufacturing industry. The results show that the proposed solution approach performs efficiently.

A generic service model for secure data interchange

Purpose – The paper aims to propose a model that attempts to build an innovative common gateway compliant with RosettaNet Standards for the secure message exchange between electronic businesses in this age of internet economy.Design/methodology/approach – The use of RosettaNet Standards is to achieve the effectiveness and efficiency of message exchange, and consequently gain mutual benefits by means of agile response for cross‐organizational co‐operation. This common message gateway is built and implemented as an organizations front‐end interface, but is seamlessly integrated with businesss back‐end information systems for the message exchange with the business partners of the organization. The proposed common gateway service model provides organizations with low cost, high efficiency, high security of message exchange and transmission over the internet. A prototyping system is also built and tested in a local network devices manufacturing company with its suppliers to examine its feasibility and effici...

Virtual health/electronic medical record: current status and perspective

Information technology (IT) is a critical resource for improving todays business competitiveness. IT is transforming and redefining the ways companies do business. However, many healthcare providers do not proactively manage or improve the efficiency and effectiveness of their services with redesign of their processes using IT. Survival in a competitive business environment demands continuous improvements in quality and service, while rigorously maintaining core values. The healthcare industry, which now accounts for roughly 12% of our GDP, has sadly lagged behind in this transforming process. Lack of competition, resistance to change, and capital cost are all to blame. However, there is progress. Many hospitals and physician groups are now digitising their records and clinical data. This paper describes the steps involved in the development of an Electronic Medical Record (EMR) and then discusses a specific company (Rockwood Clinic) and its struggle to enter the digital age.

IT induction in the food service industry

As part of the business strategy in a competitive environment, for an organization to induct information technology (IT) appropriately, business process reengineering (BPR) must be conducted. We propose a process that incorporates both management information systems and strategic management concepts for the IT induction. First, we develop a business competition strategy based on Porter’s five competitive forces; second, using concepts developed in the field of information systems the business processes are reengineered to improve effectiveness and efficiency; and finally, IT strategy is developed to achieve these goals. A real‐life case in the food service industry is used to illustrate this process.