Can Ecological Product Win Consumers in China？ A Study on the Effect of Product Attributes and Consumers＇ Face Consciousness on Ecological Product Preference

This research explores what product attributes consumers value and how consumer face consciousness influences ecological product preference. Study I shows that environmental attribute enhances product preference to a greater extent when consumers value gentleness-related attributes more than strength-related attributes. However, when the strength-related attributes are valued, the benefit of environmental attribute is attenuated, and sometimes even leads to greater preference for non-ecological products. Study lI reveals that Chinese consumers with high face consciousness show a significant difference between explicit and implicit preferences for ecological products. In other words, these consumers believe in only their own preference for ecological products. In contrast, Chinese consumers with low face consciousness show no difference between explicit and implicit preferences, i.e., they believe that other people prefer ecological products as much as they do.

A Case Retrieval Projection Pursuit Model for Configuration Design of a Product Family

The paper studies on case-based reasoning of uncertain product attributes in configuration design of a product family. Interval numbers characterize uncertain product attributes. By interpolating a number of certain values randomly to replace interval numbers and making projection pursuit analysis on source cases and target cases of expanded numbers, we can get a projection value in the optimal projection direction. Based on projection value, we can construct a case retrieval model of projection pursuit that can handle coexisting certain and uncertain product attributes. The application examples of chainsaw configuration design show that case retrieval is highly sensitive to reliable results.

Product Customer Demand Mining and Its Functional Attribute Configuration Driven by Big Data

The maturity of big data analysis theory and its tools improve the efficiency and reduce the cost of massive data mining.This paper discusses the method of product customer demand mining based on big data,and further studies the configuration of product function attributes.Firstly,the Hadoop platform was used to perform product attribute data participle and feature word extraction based on Apriori algorithm was used to mine product customer demand information.And then the MapReduce model on the big data platform was applied into efficient parallel data processing,obtaining product attributes with research value,and their weights and attribute levels.After that,the cloud model and the MNL model were employed to construct the product function attribute configuration model,and the improved artificial bee colony algorithm was used to solve the model.The optimal solution of the product function attribute configuration model was got.Finally,an example was given to illustrate the feasibility of the proposed method in this paper.

Site selection of self-driving and recreational vehicle camps in China:An investigation using analytic hierarchy process and entropy

Self-driving and recreational vehicle(RV)camps are a new form of industry module with the integration of transportation and tourism in China,thus the scientific and reasonable site selection plays an important role in the success of camps’construction and operation.In terms of relying resources and development factors,camps can be divided into five categories:scenic-spot-based,transportation-based,environment-based,project-based and leisure and vacation-based.According to whether it is of excludability and competitiveness,the camps in China mainly embody the attribute of private products.Based on the combination of subjective evaluation and objective calculation,the evaluation model of spatial site selection is constructed and the weight of each index is calculated by using analytic hierarchy process(AHP)method and entropy coefficient method.The results show that traffic condition factor is the priority to the selection of campsite,and whether it is on the popular main self-driving route and the grade of trunk roads are the dominant indices.The second factor taken into consideration is the social factors,in which government policy supports and land cost play a key role.The third factor is the market,in which the urban economic level,partnership with the government and tourist resource conditionsare of great importance.The fourth factor of the campsite selection includes natural elements,in which the quality of ecological environment and water source conditions are mostly considered.In the future,it is suggested that a camp pattern of"public goods"plus"private goods"should be built and the construction of camps in underdeveloped areas should be highly developed so as to form camp spatial network from individual points to a series of campsite and finally the campsite group in China will be set up.