Service product family optimization design for demand-driven older adult home care.

Introduction: Diversification of demand leads to a wide range of older adults home care services and services market flexibility. In order to quickly respond to changing market demand, during the standard functioning of individual services, enterprises will choose the optimal combination of packages to meet the market's expected demand and preferences to ensure that the enterprise can be in the uncertainty of the market regulation and has a relatively stable source of customers. The ability of companies to design older adults care service product families based on their operational strategy and financial position, thereby increasing their ability to enter emerging markets, is a key challenge. Methods: Firstly, the demand of the initial older adults group is obtained. Secondly, the attributes of each service item are classified using the Kano model. Finally, the actual operation constraints of the enterprise are incorporated, taking into account customer preference. Critical configuration problems such as module type, customer demand, probability of selection, and cost are also considered. The genetic algorithm is used to maximize the enterprise profit while considering customer preference. The efficacy of the approach is illustrated by the design exemplification of an older adult home care services firm. Results: This research suggests a novel method to product family design for older adults care services. The method determine the optimal older adults home care service product architecture system. Discussion: The article discusses three aspects of model parameters, potential constraints and extended application of the model for different contexts to expand the applicability and relevance of the study.