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As a crucial element of city planning, an adequately planned logistics center for agricultural products can improve the circulation efficiency of agricultural products, thereby contributing to a convenient lifestyle of urban residents. First, this study analyzed the functional zones of urban green logistics centers for agricultural products based on low-carbon idea. A method was also proposed to calculate the area of each functional zone. Moreover, this study proposed a layout planning innovation method of urban green logistics centers for agricultural products based on logistics motion line analysis and logistics intensity calculation. Lastly, this study analyzed the application processes of the layout planning methodology according to the topographical conditions of Huai’an logistics center project case in China. Results of the case study show that the construction innovation method proposed in this study is scientific, reasonable, and practical. The construction innovation method can be also used for the planning and designing of similar urban logistics centers.

To answer the questions: what roles windows of opportunity act in the catchup process of latecomers, what strategies latecomer enterprises should adopt to size windows of opportunity to catch-up with incumbents even going beyond?

This paper studies the catch-up history of the Chinese mobile phone industry and proposes a sectoral innovation system under scenario of technology paradigm shifts. Then a history-friendly simulation model and counterfactual analysis are conducted to learn how different windows of opportunity and catch-up strategies influence the catch-up performance of latecomers.

Results show latecomers can catch up with technology ability by utilizing technology window and path-creating strategy. However, catching up with the market is not guaranteed. Demand window can help latecomers to catch up with market as it increases their survival rates, different sized windows benefit different strategies. However, it also enlarges incumbents' scale effect. Without technology window technology catch up is not guaranteed. Two windows have combination effects. Demand window affects the “degree” of change in survival rates, while the technology window affects the “speed” of change. Demand window provides security; technology window provides the possibility of a breakthrough for technology ability.

The findings of this paper provide theoretical guidance for latecomer enterprises to choose appropriate catch-up strategies to seize different opportunity windows.

This paper emphasizes the abrupt change of industrial innovation system caused by technology paradigm shifts, which makes up for the shortcomings of previous researches on industrial innovation system which either studied the influence of static factors or based on the influence of continuous changes.

Supplier–supplier coopetition is vital to buyer innovation in reality. However, it has not received enough attention in prior research. Integrating the ability-motivation-opportunity framework of organizational learning perspective and the awareness-motivation-capability framework of competitive dynamics theory, this paper investigates the effect of supplier–supplier coopetition within supplier network on buyer innovation, as well as the contingent role of the relational attributes -- duration and tie strength dispersion of buyer–suppliers relationship at the supplier network level.

Testing this model on the secondary data of supply networks formed by 204 US listed buyer firms in SIC code 28, 35, 36 during 2008–2019, the authors utilize a fixed-effect regression model to investigate the relationship between supplier–supplier coopetition and the focal buyer's innovation.

The authors provide support for the positive influence of supplier–supplier cooperation on buyer innovation and an inverted U-shaped relationship between supplier–supplier competition and the focal buyer's innovation. The buyer–suppliers tie strength dispersion amplified the above two effects, and supplier–supplier cooperation mitigates the effect of supplier–supplier competition on the focal buyer's innovation.

Extending the traditional dyadic view to a network-level view via linking the supplier–supplier dyad and the buyer–suppliers dyad, this paper contributes to a better understanding of supplier–supplier coopetition and its impact on buyer innovation with learning and competitive tension as the underlying explanations, and validates the contingent role of buyer–suppliers relational attributes.

This paper aims to represent an empirical study of what role does structural empowerment play in the relationship between multi-stakeholder value co-creation (VCC) and the success of new product development (NPD).

The hypotheses developed in this paper are tested by using data from 243 manufacturing companies worldwide.

The results show that the VCC activities have significant positive effects on NPD success, and structural empowerment moderates the impact of VCC activities on NPD success, but the moderating effect is not significant for customer involvement.

This study contributes to the research of VCC and discusses the positive role of structural empowerment to enhance the impact of VCC activities on NPD success.

This paper represents an empirical study of how geographic proximity influences the search advantage and the transfer problem of interfirm networks.

By using the data collected from 226 Chinese manufacturing firms, this study examines the proposed hypotheses.

The authors’ findings suggest that (1) geographic proximity is an important antecedent for promoting knowledge transfer, whereas it lowers the degree of knowledge novelty; and (2) geographic proximity also moderates the effects of interfirm networks on knowledge novelty and knowledge transfer.

This study contributes the literature of interfirm network and provides practical implications by addressing the ways in which manufacturing firms can promote knowledge transfer and acquire novel knowledge.

While quantitative survey design represents a default research method in the field of hospitality and tourism, qualitative approaches remain largely sidelined. This is particularly true for netnography, a novel method of scientific enquiry that targets the online interactions of various actors. The present chapter seeks to introduce the netnographic approach, outline its implementation in hospitality and tourism, as well as demarcate it from other methods, such as survey, text mining and content analysis. By giving an overview of recent studies employing netnography, the chapter demonstrates applied examples of ethnographic research online, presents a cross-cultural study on disappointing travel experiences and suggests further research avenues, such as cross-cultural investigation. It concludes by discussing strengths and weaknesses of the netnographic approach. The value of this chapter lies in its reflection of state-of-the-art research in hospitality and tourism based on netnography and the proposition of further directions of research.

In recent years, owing to the rapidly increasing labor costs, the demand for robots in daily services and industrial operations has been increased significantly. For further applications and human–robot interaction in an unstructured open environment, fast and accurate tracking and strong disturbance rejection ability are required. However, utilizing a conventional controller can make it difficult for the robot to meet these demands, and when a robot is required to perform at a high-speed and large range of motion, conventional controllers may not perform effectively or even lead to the instability.

The main idea is to develop the control law by combining the SMC feedback with the ADRC control architecture to improve the robustness and control quality of a conventional SMC controller. The problem is formulated and solved in the framework of ADRC. For better estimation and control performance, a generalized proportional integral observer (GPIO) technique is employed to estimate and compensate for unmodeled dynamics and other unknown time-varying disturbances. And benefiting from the usage of GPIO, a new SMC law can be designed by synthesizing the estimation and its history.

The employed methodology introduced a significant improvement in handling the uncertainties of the system parameters without compromising the nominal system control quality and intuitiveness of the conventional ADRC design. First, the proposed method combines the advantages of the ADRC and SMC method, which achieved the best tracking performance among these controllers. Second, the proposed controller is sufficiently robust to various disturbances and results in smaller tracking errors. Third, the proposed control method is insensitive to control parameters which indicates a good application potential.

High-performance robot tracking control is the basis for further robot applications in open environments and human–robot interfaces, which require high tracking accuracy and strong disturbance rejection. However, both the varied dynamics of the system and rapidly changing nonlinear coupling characteristic significantly increase the control difficulty. The proposed method gives a new replacement of PID controller in robot systems, which does not require an accurate dynamic system model, is insensitive to control parameters and can perform promisingly for response rapidity and steady-state accuracy, as well as in the presence of strong unknown disturbances.

The study focused on improving stiffness and premature failure, the weaknesses of the other retrofitting techniques and the retrofitted beam. A detailed study regarding the section properties and effective length of the angles was also carried out in this study.

In this article, a comprehensive study was carried out using a finite element method to investigate the behavior and performance of steel angles as a retrofitting technique subjected to flexure. A model was developed in ABAQUS and validated with the available experimental works. The model was then applied to examine the beams retrofitted with the steel angles.

From the investigation, the strengthening technique successfully enhanced the flexural capacity and stiffness of the beam. The stiffness of the retrofitted beam achieved more than 2.5 times of the controlled beam. The thickness and flange width of the angles improved both the load capacity and stiffness whereas, web width, having same flange width, improved the stiffness only. This study also illustrates that a premature failure can be minimized by maintaining L/S (length to span) ratio between 0.7 and 1.0 along with the welding to provide the connections between the angles and stirrups.

The developed model and the findings can be used for designing the retrofitting technique for the damaged as well as beams to be increased their capacity.

The research focused on the implication of a new technique of retrofitting, steel angles to improve the stiffness of beam, which is one of the major drawbacks of traditional techniques. Moreover, the research aimed to improve premature failure by bonding the retrofitting materials with the stirrups of the mother beam through welding.

This study aims to propose a consensus model that considers dynamic trust and the hesitation degree of the expert's evaluation, and the model can provide personalized adjustment advice to inconsistent experts.

The trust degree between experts will be affected by the decision-making environment or the behavior of other experts. Therefore, based on the psychological “similarity-attraction paradigm”, an adjustment method for the trust degree between experts is proposed. In addition, we proposed a method to measure the hesitation degree of the expert's evaluation under the multi-granular probabilistic linguistic environment. Based on the hesitation degree of evaluation and trust degree, a method for determining the importance degree of experts is proposed. In the feedback mechanism, we presented a personalized adjustment mechanism that can provide the personalized adjustment advice for inconsistent experts. The personalized adjustment advice is accepted readily by inconsistent experts and ensures that the collective consensus degree will increase after the adjustment.

The results show that the consensus model in this paper can solve the social network group decision-making problem, in which the trust degree among experts is dynamic changing. An illustrative example demonstrates the feasibility of the proposed model in this paper. Simulation experiments have confirmed the effectiveness of the model in promoting consensus.

The authors presented a novel dynamic trust consensus model based on the expert's hesitation degree and a personalized adjustment mechanism under the multi-granular probabilistic linguistic environment. The model can solve a variety of social network group decision-making problems.