Investigation on the Consumption Values of Hong Kong People on Tie Products

This study aims at investigating the consumption values of Hong Kong people on necktie. Based on the Sheth-Newman-Gross Model of consumption values on consumers’ choice decision as conceptual framework, results from the focus group interview, a questionnaire was designed and adopted for conducting the survey. Data collected from 245 respondents were analysed using the Factor Analysis to review the important elements of consumers’ decision of purchasing tie products. Implications on the results on the Functional value were reviewed and discussed in details. Interesting elements such as fabric hand-feel were also identified as influential associated in Hong Kong consumers’ selection of necktie. Since, both fibre content and fabric handle were also found as major selection criteria for fabric materials, the study was focused on the analysis of functional value of the product and further extended to study the handle preference for Hong Kong customers, in which a subjective handle assessment of a wide range of tie fabrics being newly developed and introduced in the market was conducted and objective fabric physical and mechanical properties were measured. Important fabric handle attributes that influence the consumers’ preference on tie fabrics were identified and their objective translation by fabric physical and mechanical properties were also obtained. The investigation provides decision support to necktie manufacturers and retailers through scientific and quantitative recommendations for product development of tie products and material selection.

Comprehensive optimized GM(1,1) model and application for short term forecasting of Chinese energy consumption and production

In order to improve prediction accuracy of the grey prediction model and forecast China energy consumption and production in a short term, this paper proposes a novel com- prehensively optimized GM（1,1） model, also named COGM（1,1）, based on the grey modeling mechanism. First, the relationship of the background value formula and its whitenization equation is analyzed and a new method optimizing background values is proposed to eliminate systemic errors in the modeling process. Second, the solving process of the new model is derived. For parameter estimation, a set of auxiliary parameters are used to change grey equation＇s form. Then, original parameters are re- stored by an equations system. After solving the whitenization equation, initial value in time response function is established by least errors criteria. Finally, a numerical case and comparison with other grey prediction models are made to testify the new model＇s effectiveness, and the computational results show that the COGM（1,1） model has a better property and achieves higher precision. The new model is used to forecast China energy con- sumption and production, and the ability of energy self-sufficiency is further analyzed. Results indicate that gaps between consump- tion and production in future are predicted to decline.