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Rapid response is often the cornerstone of success in many industries, especially manufacturing. In the authors’ opinion, organizational structure will also affect the construction of a fast-response supply chain system. The main purpose of this research examines whether different levels of organizational structure have different effects on the relationship between external integration and firm performance.

This study applied questionnaires to collect data. This study collected 818 questionnaires from manufacturers in China, Hong Kong and Taiwan to verify our proposed model using structural equation modeling.

Results show that response speed perfectly mediates the relationship between external integration and firm performance. Different levels of organizational structure will also affect external integration. Strict organizational structure requires customer integration, while loose organizational structure requires supplier integration to quickly meet customer needs.

Companies can probably determine whether their organizational structure is higher or lower than that of their competitors. If firms can determine that their organization structure is high or low, they can adopt suitable external integrations to enhance quick response and operational performance.

In the relationship between supply chain integration and performance, we consider a mediating variable and moderating variable together. Results explain the reason that the relationship between supply chain integration and performance are inconsistent in previous studies. We have addressed external integration in alignment with organizational structure to provide better service and enhance performance by providing empirical evidence.

Information sharing is one of essential collaboration methods for building effective system-level disruption responses and communication for supply chain resilience. However, supply chain members are often reluctant to share the members' business information for fear of losing competitiveness. To facilitate the cooperation among these members, the supply chain members' should be made aware of the value of information. As a result, the purpose of this paper is to quantify the benefit of information sharing and evaluate its magnitude under various factors.

In this paper, information sharing is measured in a two-stage supply chain containing a manufacturer and a retailer. A demand function is constructed as a linear combination of a first-order autoregressive [AR(1)] process, the retail and reference prices. The values of information sharing are quantified for four scenarios: (1) no information sharing, (2) full information sharing, (3) limited information sharing and (4) partial information sharing. Based on the four scenarios, the conditions for valuable information sharing are determined. In addition, the impact of several demand parameters on the usefulness of information sharing is analyzed.

When the demand function is a pure AR(1) process (i.e. there is no impact from the retail and reference prices), information sharing is always valuable regardless of the autoregressive coefficient. Under the influence of the retail price and consumer behavior via the reference price, information sharing is not always beneficial. The boundaries for useful information sharing are analytically constructed. In addition to full information sharing, this study also quantifies the value of information under a partial sharing scheme. The results indicate that the information is more valuable as long as the information is inducible.

This study highlights several specific conditions for a beneficial information sharing agreement in consideration of consumer behaviors. These conditions enable supply chain members to design a sustainable partnership.

The purpose of this paper is to offer an overview of dietary transition patterns and a discussion of the food-related health issues in China.

The paper builds on a review of the existing literature on food consumption and diet changes in China, and highlights with specific attention to increasing food consumed away from home, the rising demand for fast and processed foods, and the popularizing of western-style foods in Chinese diets.

China’s food consumption patterns rapidly transitioned from one in which grains and vegetables dominated to one having more animal products and more diversification. More foods are consumed away from home and in the form of fast and processed. Income growth played and will continue to play a critical role in shifting the structure of food consumption. On the other hand, China is on a fast track from a lean population to one in which being overweight or obese. The associations between health outputs and food transitions, however, are inconclusive.

The main findings of this study have implications for better understanding the key trends and driving forces of China’s food demand system. Moreover, the results from this review are essential for food-related policymaking in many emerging economies where coexistence of undernutrition, deficiency of micronutrients and overweight and obesity is a common challenge to the society and individual households.

The purpose of this paper is to propose a fast object detection algorithm based on structural light analysis, which aims to detect and recognize human gesture and pose and then to conclude the respective commands for human-robot interaction control.

In this paper, the human poses are estimated and analyzed by the proposed scheme, and then the resultant data concluded by the fuzzy decision-making system are used to launch respective robotic motions. The RGB camera and the infrared light module aim to do distance estimation of a body or several bodies.

The modules not only provide image perception but also objective skeleton detection. In which, a laser source in the infrared light module emits invisible infrared light which passes through a filter and is scattered into a semi-random but constant pattern of small dots which is projected onto the environment in front of the sensor. The reflected pattern is then detected by an infrared camera and analyzed for depth estimation. Since the depth of object is a key parameter for pose recognition, one can estimate the distance to each dot and then get depth information by calculation of distance between emitter and receiver.

Future work will consider to reduce the computation time for objective estimation and to tune parameters adaptively.

The experimental results demonstrate the feasibility of the proposed system.

This paper achieves real-time human-robot interaction by visual detection based on structural light analysis.