Chialin Chen

A new methodology for evaluating sustainable product design performance with two-stage network data envelopment analysis

Sustainable product design has been considered as one of the most important practices for achieving sustainability. To improve the environmental performances of a product through product design, however, a firm often needs to deal with some difficult technical trade-offs between traditional and environmental attributes which require new design concepts and engineering specifications. In this paper, we propose a novel use of the two-stage network Data Envelopment Analysis (DEA) to evaluate sustainable product design performances. We conceptualize “design efficiency” as a key measurement of design performance in terms of how well multiple product specifications and attributes are combined in a product design that leads to lower environmental impacts or better environmental performances. A two-stage network DEA model is developed for sustainable design performance evaluation with an “industrial design module” and a “bio design module.” To demonstrate the applications of our DEA-based methodology, we use data of key engineering specifications, product attributes, and emissions performances in the vehicle emissions testing database published by the US EPA to evaluate the sustainable design performances of different automobile manufacturers. Our test results show that sustainable design does not need to mean compromise between traditional and environmental attributes. Through addressing the interrelatedness of subsystems in product design, a firm can find the most efficient way to combine product specifications and attributes which leads to lower environmental impacts or better environmental performances. This paper contributes to the existing literature by developing a new research framework for evaluating sustainable design performances as well as by proposing an innovative application of the two-stage network DEA for finding the most eco-efficient way to achieve better environmental performances through product design.

The effects of strategic alliances and risk pooling on the load factors of international airline operations

Abstract This paper develops a theoretical model and conducts an empirical analysis of the effects of complementary and parallel codesharing on the load factors of international airline operations. The analysis shows that, given the increased demand resulting from the expansion of a global network, only parallel codesharing leads to higher load factors, since parallel alliance airlines can supply fewer seats than their complementary counterparts. These results provide new insights into several managerial and policy issues about airline strategic alliances such as partner selection, cost savings, and supply coordination.

The D-Day, V-Day, and bleak days of a disruptive technology: A new model for ex-ante evaluation of the timing of technology disruption

The recent failure of major PC and smartphone makers in launching new generations of high-tech products in time shows that analyzing and capturing the timing of technology disruption is an important yet less explored research area. This paper conducts theoretical and empirical analyses for ex-ante quantitative evaluation of the timing of technology disruption. We conceptualize the ease and network factors as key determinants of performance improvement for a disruptive technology. A dynamic consumer model is developed to identify two critical times, termed D-Day and V-Day, of technology disruption. We also show that, if the network factor dominates the performance improvement process, there may exist some “bleak days” during which a firm would discontinue a “promising” technology that will eventually disrupt. Empirical tests are conducted with data of hard disk drives, semiconductor technologies, and CPU performance for mobile devices to verify key model assumptions and to show how to estimate the ease and network factors. We also perform a numerical experiment to demonstrate how to forecast the timing of technology disruption. A decision tree and a systematic framework are also developed to operationalize key model parameters and analytical results from a decision-support perspective. This paper contributes to the literature by presenting a novel analytical tool and new insights for high-tech companies to forecast and manage the timing of technology disruption.

Time-to-value, customer learning, and the development of breakthrough products

Breakthrough products often have more complex built-in technology and functionality than their traditional counterparts. Since most customers do not have prior experience with breakthrough products, they usually spend more significant time, money, and/or effort in learning their innovative features. In this paper, we develop a conceptual model with supporting cases to provide some critical insights to the development of breakthrough products from an integrative perspective of design and marketing. Our analysis shows that the amount of learning time has significant impacts on the success of a breakthrough product in todays marketplace where many customers are impatient or not technologically ready. A customer may terminate the learning process before the entire embedded value of a product is realised or even before her utility is maximised due to learning difficulty or product complexity. We also discuss several useful guidelines and strategies that can be used to manage the development of breakthrough products.

Modeling and Simulation Analyses of Healthcare Delivery Operations for Inter-Hospital Patient Transfers

Inter-hospital transfers of patients for different elements of care have been increasingly used as a common strategy for providing quality healthcares through sharing limited resources worldwide. In this paper, the authors study the problem of healthcare delivery operations for inter-hospital patient transfers motivated by a real-world case within the South East Local Health Integration Network of Ontario. The authors use a directed graph to develop a general model for obtaining the solution that minimizes the overall transportation time while satisfying all the inter-hospital transfer requests with identical or different start and end points. The authors also perform simulation analyses to study the fleet sizing problem through evaluating different service performances with different fleet sizes. A number of implementation issues for managing inter-hospital patient transfer services are also discussed.

Sustainable Product Design Performance Evaluation with Two-Stage Network Data Envelopment Analysis

Data Envelopment Analysis (DEA) has traditionally been used to measure the performance of production systems in terms of efficiency in converting inputs into outputs. In this paper, we present a novel use of the two-stage network DEA to evaluate the sustainable product design performances. While sustainable product design has been considered as one of the most important practices for achieving sustainability, one challenge faced by decision makers in both the private and public sectors is how to deal with the difficult technical trade-offs between traditional and environmental attributes which require new design concepts and engineering specifications. To deal with this challenge, we conceptualize “design efficiency” as a key measurement of design performance in terms of how well multiple product specifications and attributes are combined in a product design that leads to lower environmental impacts or better environmental performances. A two-stage network DEA model is developed for sustainable design performance evaluation with an “industrial design module” and a “bio design module.” To demonstrate the applications of our DEA-based methodology, we use data of key engineering specifications, product attributes, and emissions performances in the vehicle emissions testing database published by the U.S. EPA to evaluate the sustainable design performances of different automobile manufacturers. Our test results show that sustainable design does not need to mean compromise between traditional and environmental attributes. Through addressing the interrelatedness of subsystems in product design, a firm can find the most efficient way to combine product specifications and attributes which leads to lower environmental impacts or better environmental performances. We also demonstrate how two-stage network DEA can be used to develop a analytical framework for evaluating sustainable design performances as well as to identify the most eco-efficient way to achieve better environmental performances through product design.