Usage Context-Based Design (UCBD) has become an area of growing interest in engineering design research, due to the increasingly important role that usage context plays in customers' choices. In this paper, a usage context-based choice modeling framework (UCBCM) is presented to bridge the gap between engineering product design and customers' choice of new products by using hybrid electric vehicles (HEV) as an example. Uniquely, Different from existing choice modeling works, the product performances are explicitly modeled as a function of product design variables, customer profile, and usage context to reflect the heterogeneity in customer preference and usage context. Furthermore, the multinomial logic choice model is integrated with the ordered logit model to study the impact of vehicle design on consumer's choice. Forecasting future demand for alternative fuel vehicles, such as hybrid electric vehicles and plug-in hybrid electric vehicles, is a challenging yet promising task. It is not only of interest for consumers and vehicle manufacturers, but also critical for policy makers in support of their energy saving strategies. Many aspects are involved in consumers' decision making process when they are shopping for a new vehicle, which calls for a comprehensive modeling framework to incorporate the heterogeneous usage context and customer preference into the traditional engineering product design process. In this paper, a systematic taxonomy is laid out based on established literature in marketing domain to provide foundation for usage context based design. Further, a comprehensive framework of usage context based choice modeling is presented to capture the usage context's impact on product performance and customer preference. Uniquely, product performances, one type of customer desired attributes, are explicitly modelled as a function of product design variables, customer profile, and usage context, which reflects heterogeneity in customer preference and their usage context. The case study of hybrid electric vehicle illustrates the usefulness of the modeling framework and demonstrates the importance of modeling usage context using revealed preference data. The results show that both product performance and customer preference are influenced by usage context. Further, the choice model is integrated with the ordered logit model to study the impact of vehicle design on consumer's choice of HEVs. Several interesting implications are reported. For instance, customers who drive primarily under local condition prefer hybrid electric vehicles while the highway drivers don't. In the what-if-scenario analysis, it is shown that customers change their choice in response to the change of performance ratings in distinctive usage context. The key contribution of this work is to bridge the gap between engineering product design and customers' choice of new products through the usage context based choice modeling framework. The presented framework can greatly benefit the traditional engineering design by linking the product design to customers' choice. Moreover, an optimization problem can be formulated using the proposed framework to determine the optimal performance targets for engineering design. For example, in the case of HEV battery design, performance targets include MPG city and highway measured as well as vehicle horsepower and torque.
Usage context-based choice modeling for hybrid electric vehicles
2011
12 Seiten, 4 Bilder, 3 Tabellen, 35 Quellen
Aufsatz (Konferenz)
Englisch
Choice Modeling for Usage Context-Based Design
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