Ying Li

Bio: Ying Li is an academic researcher from Shandong University. The author has contributed to research in topics: Flexibility (engineering) & Supply chain. The author has an hindex of 7, co-authored 10 publications receiving 143 citations. Previous affiliations of Ying Li include Zhejiang University.

The impact of product complexity and variety on supply chain integration

Abstract: Purpose The purpose of this paper is to examine the antecedents of supply chain integration (SCI) at the product level. More specifically, it aims to show the relationship between product-level characteristics (i.e. product complexity and product variety) and different dimensions of SCI (i.e. internal, supplier and customer integration). Design/methodology/approach A survey-based research design is developed to measure different dimensions of SCI, product complexity and product variety. The authors use structural equation modelling to test the related hypotheses. Findings This research shows that internal integration is an enabler to supplier and customer integration. The results also show that under high product complexity, firms tend to implement internal and supplier integration, while product complexity does not have a direct impact on customer integration. Product variety is confirmed to be positively related to all dimensions of SCI. Originality/value This paper contributes to the SCI literature by first, providing empirical evidence which supports the study of the product design-supply chain interface; and second, exploring the relationships between product complexity, variety and internal, supplier and customer integration based on a governance view.

Risk management and firm performance: the moderating role of supplier integration

Abstract: The purpose of this paper is to scrutinize the performance effects of supply chain risk management (SCRM). Besides financial performance, two aspects of operational performance are examined: operational efficiency and flexibility. Moreover, the authors explore the moderating role of supplier integration in the relationship between SCRM and operational performance.,A survey-based methodology was adopted. Based on the data from an international survey, this study applied the structural equation modeling and latent moderated structural equations approach to test the hypotheses.,The results indicate that SCRM positively influences both operational efficiency and flexibility, and has an indirect effect on financial performance. In addition, supplier integration enhances the impact of SCRM on operational flexibility, but does not moderate the relationship between SCRM and operational efficiency.,This study extends the existing literature by providing a comprehensive analysis of the performance effects of SCRM. It also provides managerial insights on both risk management and supplier integration.

The Impact of Intellectual Capital on Supply Chain Collaboration and Business Performance

Abstract: This paper aims to investigate the influence of intellectual capital (IC) on supply chain collaboration (SCC) and business performance. Two mechanisms of SCC are considered, including interorganizational communication (IOC) and shared vision (SV). Based on knowledge-based view, this study explains how IOC and SV mediate the impact of IC on business performance. Structural equation modeling was used to test the hypothesized relationships based on the survey data of 1008 firms in the manufacturing industry. The results demonstrate that IC promotes IOC directly and influences the establishment of SV indirectly through IOC in the supply chain context. In addition, IOC mediates the relationship between IC and business performance. This study establishes the interface between internal knowledge base and external supply chain relationships by examining IC as an antecedent for SCC, and it also contributes to knowledge management literature by revealing that the organization's knowledge resources can influence its performance through collaborative supply chain relationships.

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Abstract: Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms.

Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem

Abstract: We consider heuristic algorithms for the resource-constrained project scheduling problem. Starting with a literature survey, we summarize the basic components of heuristic approaches. We briefly describe so-called X -pass methods which are based on priority rules as well as metaheuristic algorithms. Subsequently, we present the results of our in-depth computational study. Here, we evaluate the performance of several state-of-the-art heuristics from the literature on the basis of a standard set of test instances and point out to the most promising procedures. Moreover, we analyze the behavior of the heuristics with respect to their components such as priority rules and metaheuristic strategy. Finally, we examine the impact of problem characteristics such as project size and resource scarceness on the performance.

Analysis of the innovation strategies for green supply chain management in the energy industry using the QFD-based hybrid interval valued intuitionistic fuzzy decision approach

Abstract: This study aims to analyze the innovation strategies for the green supply chain management with QFD (quality function deployment) multidimensionally. The novelty of the study is to define the criteria of green supply chain for each stage of QFD and propose a hybrid model by IVIF (interval-valued intuitionistic fuzzy) DEMATEL (decision making trial and evaluation laboratory) and IVIF MOORA (Multi-Objective Optimization by Ratio Analysis) respectively. The results demonstrate that understanding the customer expectations with customer relation management is the most important innovation strategy for the green supply chain management in energy industry with the consecutive stages of QFD whereas benchmarking the competitive market environment has relatively the last seat in the ranking. Hence, it is recommended that energy companies should have an effective customer relationship management. In this context, these companies should make a detailed analysis to learn what their customers directly expect from them. With the help of this issue, these companies should generate their product and services based on these expectations. Additionally, it is also stated that new service and product development is also essential for energy companies to improve their innovativeness. For this purpose, a research and development department should be created, and the qualified people should be employed. Additionally, different opinions should be collected from various parties, such as customers, employees, and suppliers. Since customers who are satisfied will prefer these companies, the energy companies can catch the opportunity to increase their market share.