Jing Quan, Bo Zeng and LuYun Wang
Equally weighted factors and initial data from behavioural sequences are used for calculating the degree of grey incidence in Deng’s grey incidence analysis. However, certain grey…
Abstract
Purpose
Equally weighted factors and initial data from behavioural sequences are used for calculating the degree of grey incidence in Deng’s grey incidence analysis. However, certain grey information cannot be directly obtained, and the correlation coefficients of each sequence at different times are of different importance to the system. The purpose of this paper is to propose an improved grey incidence model with new grey incidence coefficients and weighted degree of grey incidence. Some grey information can be obtained more easily by using the grey transformation sequences, and the maximum entropy method is used to calculate the weights of new grey incidence coefficients, so the new degree of grey incidence was distinguished more effectively by the proposed model.
Design/methodology/approach
New grey incidence coefficients are defined using transformation sequences of the initial data. To overcome the shortcomings arising from the use of equal weights, the maximum entropy method is proposed for determining the weights of the grey incidence coefficients. The resulting model optimises the classical models and evaluates the influencing factors more effectively. The effectiveness of the model was verified by a numerical example. Furthermore, the model was used for analysing the main influencing factors of the tertiary industry in China.
Findings
The proposed model optimises the classical models, and the application example shows that urbanisation has the greatest effect on employment in the tertiary sector.
Originality/value
An improved grey incidence model is proposed that improves the grey incidence coefficients and their weights, and has better performance than the classical models. The model was successfully used in the analysis of the influence factors of the tertiary industry in China. The results indicate that the model can reflect the significance of incidence coefficients at different time points; therefore, their fluctuation can be effectively controlled.
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Luyun Xu, Xin Yin, Hong Gong and Deming Zeng
A firm's inventions provide technical information for product planning and technical support for new product development (NPD). In the knowledge-based theory, inventing is…
Abstract
Purpose
A firm's inventions provide technical information for product planning and technical support for new product development (NPD). In the knowledge-based theory, inventing is regarded as a process of knowledge combination. This paper aims to classify the firm's inventive capabilities based on the combinatorial view and investigate the effects of inventive capabilities on NPD performance.
Design/methodology/approach
Four types of inventive capabilities are identified concerned with the knowledge used to combine in the inventive activities. By utilizing a dataset of 572 firms from China's automotive manufacturing industry, the roles of different inventive activities in the generation of new inventions are compared. Then the effects of different inventive capabilities on NPD performance are empirically examined by using negative binomial regression analysis.
Findings
The time series for the number of patented inventions derived from different types of combinations generally exhibits a steady upward trend, and the number of patents derived from recombination is much higher. The empirical results demonstrate that the inventive capabilities associated with reused recombination and creative recombination exhibit positive effects on NPD performance, and the inventive capabilities associated with novel combination and original combination exhibit non-linear effects on NPD performance.
Originality/value
The findings contribute to NPD literature by investigating the effects of different inventive capabilities on NPD performance. This study also provides guidelines for manufacturing managers to improve NPD performance by building appropriate inventive capabilities.
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Kevin Z. Chen, Luyun Yu, Wen Lin and David L. Ortega
The purpose is to understand the factors affecting Chinese diet selections and propose strategies for revolutionizing Chinese diets toward healthy ones.
Abstract
Purpose
The purpose is to understand the factors affecting Chinese diet selections and propose strategies for revolutionizing Chinese diets toward healthy ones.
Design/methodology/approach
This study implemented an online discrete choice experiment to identify the factors affecting diet selections among urban Chinese consumers. Four different diet patterns were used to label each of the product alternatives in the experiment, which varied in taste and cost. Specifically, implying the healthiness and sustainability of a diet, the diet alternatives included the average diet, the Chinese Food Guide Pagoda diet, the EAT-Lancet diet and the Flexitarian diet. Using consumer data from six provincial capital cities, we used random parameter logit models to estimate their preferences.
Findings
Diet type and diet cost were found to be more important in urban Chinese consumers' diet selections than the ability to customize taste. The average diet, although not healthy and sustainable, was preferred most by respondents, signaling the challenges of shifting the consumer diet in China. Increasing the cost of the average diet can significantly promote sustainable healthy diet choices among urban Chinese residents. In other words, improving the affordability of sustainable healthy diets would have the potential to fuel the diet revolution in China.
Originality/value
Instead of choices of a single food item, this paper focused on the individual selection of a diet, where different food products can act as substitutes or as complements for one another. We also proposed a way to assess individual preferences and valuations for several different diets.