Selected Research Projects

We will develop quantitative supply chain models with single and dual sales channels, in which a manufacturer sells its product through a retailer and/or an on-line channel. Customers are two-dimensionally heterogeneous in their purchasing effort through each channel. During each period, the manufacturer decides the wholesale price for selling to the retailer, and both the manufacturer and the retailer decide the retail prices to customers. After seeing the prices, customers make a purchase decision by weighing the benefit of purchasing from one channel as against the other during the current period as well as against the benefits of waiting and then purchasing in the future. The firms realize this and dynamically set their prices to take into account such customer behavior. Also, the customers have rational expectations, and in equilibrium can predict the pricing policy of the firms. Both firms aim to maximize their total profit over a finite planning horizon.

We will firstly analyze the single-channel model, in which the sales channel can be either centralized or decentralized. We will derive the unique sub-game perfect Nash equilibrium (SPNE) of this dynamic game and investigate whether and how price skimming arises in the retail price and the wholesale price. Then we will focus on the dual-channel model with various channel structures, and study the cases with identical and non-identical retail prices.

By means of comparisons, we will investigate how different channel structures affect the equilibrium pricing strategies and the firms’ profitability, in particular, to what extent, dual-channel structures can mitigate the strategic behaviors of consumers. Moreover, how much profit each firm and the supply chain would lose when implementing the myopic pricing policy will also be examined. Finally, we will consider price commitment and quantity decisions and study their impact.

Based on these properties, we will characterize the optimal control policies of the systems, such as warehouse space rental, inventory replenishment, product assortment. Meanwhile, we will study the properties of the optimal policies to obtain managerial insights. For some of the problems that have complicated optimal policy that are difficult to implement in practice, we will further develop simple and effective heuristics. More importantly, we will collect real data and use them to validate our models and analyze practical implications of our research outcomes.

We expect the project will not only contribute to the warehousing and inventory management literature but also provide solutions and guidelines on recently emerging problems in warehouse management.

This research leverages our recent work in the active RFID traceability technologies. Our system is developed with the capability to determine the indoor location of an active tag. This system was installed inside two wards (11A & 11C) of Prince of Wales Hospital for a 4-month formal pilot study with patient and medical staff participation to improve patient care.

Based on the user feedbacks collected, we find that time and space play an important role in shaping human behaviors, inferring human interactions, and influencing epidemic spread of infectious diseases in a healthcare institute. Our research aims at enhancing the capability of tracking the movement of people and tracing the infection of a hospital-acquired disease for each individual in order to monitor and control the epidemic spread of nosocomial infections. To achieve this goal, we plan to conduct the following research activities:

• network models of dynamic human behaviors for an enhanced spatial-temporal analysis to determine human interaction patterns and contacts in a relatively close community,
• epidemic models to track and trace nosocomial infections based on the time-varying contact networks to increase our understanding of transmission mechanisms in hospital,
• traceability analysis of tracking the mobility and infection for each individual to identify risk behaviors by linking both the network and epidemic models,
• effective and efficient control strategies against epidemic spread under different scenarios to take advantage of the network structure and disease dynamics.

This research is unique. First, since our focus is on the movement of people, our methods are very different from those used to track products in a supply chain. Further, we plan to conduct the traceability analysis of the dynamic interactions and infections of people at individual level for network epidemiology study in hospital. This differs from either the popular modeling of a static network or the traditional epidemiology study for a large region. Finally, many spatial-temporal analyses and epidemiology models are developed for outdoor applications while this work deals with indoor activities.

The Tree Guard Monitoring System will make use of various sensor technologies to continuously monitor tree statuses and detect for any abnormal activity being done to a tree, like sawing and hammering. In addition, the TGMS will utilize various wireless technologies to form a scalable wireless mesh network for transmitting various sensor data to a control server. The control server will further analyze the incoming sensor data and determine whether to issue a warning signal to corresponding management and operation parties. Moreover, historical data will be analyzed for deriving activity patterns to improve the detection accuracy as well as establish preventive or predictive measures to safe guard those trees.

The project will develop the hardware devices having sensing and wireless communication capabilities for being attached to trees. Each device will be capable of synthesizing various streams of sensor data to detect abnormal activities. The project will also develop the data communication protocols to support various communication transmissions between different components in the mesh network. Monitoring and analytics software will be developed to convert sensor information into warning signals.

We believe that firms can develop benefits and competitive advantages from isomorphic IT innovations with the right beacons (processes and driving force). In this study we argue that firms can indeed become heterogeneous under institutional pressure following the right processes and making the right decisions and call this concept Heteromorphism.

We posit that IT innovations under institutional pressure can create a critical mass, where firms end up with only assets and resources. Mere assets and resources do not necessarily benefit firms, as the capability to make good use of the assets and resources is critical. We argue that firms can learn to make good use of these assets and resources once they get hands on experience with the technology in the development of capabilities that are unique. Such unique capabilities can make a firm distinctive from other firms and be leveraged to bring competitive advantages. This view is supported by recent IT innovations, effective bandwagon with high degree of confidence, that mindless adoptions are common and yet sustained competitive advantages can be subsequently created.

This study utilizes two theories with rather competing results to discuss Heteromorphism, namely institutional theory and the resource based view. We depart from the traditional institutional theory by investigating why institutional pressure does not necessarily lead to isomorphic IT innovations. Instead we study how firms can derive unique capabilities under institutional pressure through a learning process. We will first develop and theorize the Heteromorphism concept through in-depth case studies. Subsequently, a large scale confirmatory study will be designed and conducted to ensure the generalizability of Hetermorphism.

The aim of this project is to study approximation algorithms for dynamic remanufacturing systems with stochastic product returns and customer demands. The key feature is that demands and product returns in different periods are correlated. A major domain of applications is remanufacturing systems where product returns in one period depend on demands in the previous periods, which are often observed in practice. The prior studies on dynamic remanufacturing systems mostly assume independent demands and returns to avoid the well-known curse of dimensionality of the dynamic programming formulation, i.e., the state space becomes so large that the optimal policy is computationally intractable. But such simplification greatly hinders the practical applicability of the results. Therefore, we will exploit novel approaches to formulate and analyze such remanufacturing systems. Specifically, we will evaluate decisions and construct approximation policies and algorithms based on alternative cost accounting schemes. The policies aim to balance various costs such as inventory holding, demand backlogging, and remanufacturing/manufacturing costs. More importantly, these policies are easily computable and implementable and will be proved to have constant worst-case performance guarantees.

We will firstly analyze a basic model where a remanufacturing firm determines manufacturing and remanufacturing quantities periodically to minimize its costs under correlated demands and product returns. And then we will study more complex systems with product return disposal, manufacturing/remanufacturing capacity constraints, and multi-type of product returns. Each of these extensions will require novel ideas to design cost accounting schemes and derive provably good approximation algorithms. To further demonstrate the value of our approximation policies, we will compare their performance to the myopic policies that are widely adopted as heuristics for problems with a large state space as well as those that ignore the correlation between returns and demands. This project is the first attempt to develop computationally efficient policies with constant performance guarantees for remanufacturing systems.

The reason of our focus on uncertainty and risk is the increasing importance of robust planning and robust investment decisions in the modern telecommunication environment. Traditional telecommunication networks were dominated by public monopolies which provided only a few mature services with fairly predictable user demand. Unfortunately, this predictability is a feature of the past! Due to the fast evolution of modern high speed networks, deregulation, quick development of new services with shorter life cycle, unpredictable user response to introduction of new services, modern networks operate in the presence of substantial uncertainty. The emergence of a multitude of new actors, which assume new roles and engage in complex relations of competition and collaboration, further complicates the situation and compounds the risks. Traditional planning methods are not adequate for design of networks in this new environment due to their essential lack of capability to treat this instability and uncertainty. New planning methods are needed which would facilitate design of robust networks. These networks will be able, within reasonable bounds, to absorb unpredictable user reaction to new services, technological change and other uncertainties without consuming unreasonable amount of critical resources. Our aim is to develop planning tools for design of robust networks using the latest developments in optimization technology integrated with some ideas developed recently for evaluation of industrial projects. These tools will be useful both for industrial actors and for governmental regulatory bodies.

Existing e-service serves each client individually, although at any one time, there could be more than one client accessing instances of the same service. A complex e-service can now be composed by stitching together different e-services choreographed to accomplish a complicated task. A holistic view of e-service however, must take hold with a conceptualization of e-service with not limited to one, but more parties participating and/or interacting among themselves to complete the functional realization of the service. Party e-service conceptualization is proposed to highlight the collaborative nature of e-business, and at current articulation, e-service, does not address interactivity nature of multi-party business processes. Concept of party eservice considers the nature of the provider, service targets, service availability, client relationship and client interaction.

This study employs the design science approach to first establish the design theory for party e-services as 1st party and 2nd party as current practices, and 3rd party to complete the necessitated services online. The design theory will be presented as a set of principles which are grounded on existing body of knowledge in e-service and new requirements for facilitating collaborative e-business. We follow up with an architectural consideration, based on the conceptual principles, creating a design artifact as a model reference for technological innovation specification. Finally, we validate the artifact using an example of logistics shipment planning through an e-service platform only as a 3rd party e-service and not any other party e-service. Such e-service enables modern shipment planning that demands a forwarding agent not only to work closely with designated or any online shippers, logistics service providers and consignees to formulate a desirable shipment plan, but also to achieve real-time shipment monitoring, and in-process corrective actions for deviations of the shipping process.

To reach the objective, an innovative information infrastructure is to be designed to facilitate on-target visibility by plug-and-sync of parties of a RFID-enabled supply chain.

The infrastructure is designed based on the practice of the key players of a complete garment brand name supply chain (i.e. from supply accessories, manufacturing, distribution, to retailing) under IDS Group. The RFID adoption strategy and supply chain process re-engineering are developed based on a careful in-depth analysis of current practice using Supply-Chain Operations Reference-model (SCOR). Intellectual property is expected in the infrastructure design, the plug-and-sync design and implementation, and the SCOR-based RFID adoption framework and practice.

Firstly, analysis on the cargo flows and trade flows within Greater China, as well as between Greater China and overseas will be conducted. In-depth study on the nature of impacts of direct links on trade flows and cargo flows will also be investigated.

Secondly, expert knowledge on the impact of cargo flows, due to the introduction of Direct Link, from industry experts in China, Taiwan and Hong Kong will be collected and analyzed. Opinions on operational difficulties and services needed for the transition period will also be collected. Other than the development of the policy, other issues such as customs matters, documentations, logistics facilities and supports, supply chain network/hub effects that may influence the cargo flows and trade flows within Greater China will also be studied.

Lastly, selected case studies will be conducted to further understand the operations, in which the companies could have taken advantage of the policy. The characteristics of their business models, before and after the implementation of the policy, will be studied. Challenges and potential business opportunities will be investigated.

Our study helps to assist logistics industry to sustain in the drastic changes of direct links or take advantage of impending changes by repositioning their strengths and creating new service productions for the shippers.