Research on the influence of relation embeddedness on innovation performance of manufacturing supply chain alliances using expert fuzzy rule –intermediary role of shared mental model

2021 ◽  
pp. 1-8
Author(s):  
Guo Lifang ◽  
Cui Yuwen ◽  
Wu Yamin ◽  
Ma Jiaqi
Keyword(s):  
Supply Chain ◽  
Mental Model ◽  
Fuzzy Rule ◽  
Innovation Performance ◽  
Market Demand ◽  
Shared Mental Model ◽  
Rule Based System ◽  
Manufacturing Supply Chain ◽  
Intermediary Role

The innovation and development of manufacturing supply chain alliance is an important way for enterprises to meet the increasing market demand and maintain the competitive advantage. From the perspective of embeddedness, the research model of relation embeddedness on innovation performance of manufacturing supply chain was constructed based on AMOS. Shared mental model was selected as intermediary variable to study the influence of relation embeddedness, shared mental model and innovation performance of manufacturing supply chain alliances. Expert fuzzy rule based system is utilized for measuring the performance of manufacturing supply chain alliances. The conclusion shows that relation embeddedness is significantly positive shared mental model and innovation performance. Shared mental model is positively affects alliance innovation performance and plays a part of intermediary role between relational embedding and alliance innovation performance. Practice implicates that enhance the level of relation embeddedness can promote the formation of shared mental model and improve the innovation performance of manufacturing supply chain alliance.

An Intelligent Process Development Using Fusion of Genetic Algorithm with Fuzzy Logic

2015 ◽  
pp. 44-81 ◽  
Author(s):  
Kunjal Bharatkumar Mankad
Keyword(s):  
Genetic Algorithm ◽  
Process Development ◽  
Intelligent System ◽  
Mathematical Formulation ◽  
Research Work ◽  
Fuzzy Rule ◽  
Genetic Operators ◽  
Rule Based System ◽  
Intelligent Process

Intelligent System (IS) can be defined as the system that incorporates intelligence into applications being handled by machines. The chapter extensively discusses the role of Genetic Algorithm (GA) in the search and optimization process along with discussing applications developed so far. A very detailed discussion on the Fuzzy Rule-Based System is presented along with major applications developed in different domains. The chapter presents algorithm of implementing intelligent procedure to decide whether a patient is prone to heart disease or not. The procedure evolves solutions using genetic operators and provides its decision automatically. The chapter presents discussion on the results achieved as a result of prototypical implementation of the evolutionary fuzzy hybrid model. The significant advantage of the presented research work is that applications that do not have any mathematical formulation and still demand optimization can be easily solved using the designed approach.

scholarly journals Supply Chain Coordination under Trade Credit and Quantity Discount with Sales Effort Effects

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Zhihong Wang ◽  
Shaofeng Liu
Keyword(s):  
Supply Chain ◽  
Analytical Model ◽  
Hybrid Model ◽  
Trade Credit ◽  
Supply Chain Coordination ◽  
Market Demand ◽  
Quantity Discount ◽  
Model Combining ◽  
Effort Effect

The purpose of this paper is to investigate the role of trade credit and quantity discount in supply chain coordination when the sales effort effect on market demand is considered. In this paper, we consider a two-echelon supply chain consisting of a single retailer ordering a single product from a single manufacturer. Market demand is stochastic and is influenced by retailer sales effort. We formulate an analytical model based on a single trade credit and find that the single trade credit cannot achieve the perfect coordination of the supply chain. Then, we develop a hybrid quantitative analytical model for supply chain coordination by coherently integrating incentives of trade credit and quantity discount with sales effort effects. The results demonstrate that, providing that the discount rate satisfies certain conditions, the proposed hybrid model combining trade credit and quantity discount will be able to effectively coordinate the supply chain by motivating retailers to exert their sales effort and increase product order quantity. Furthermore, the hybrid quantitative analytical model can provide great flexibility in coordinating the supply chain to achieve an optimal situation through the adjustment of relevant parameters to resolve conflict of interests from different supply chain members. Numerical examples are provided to demonstrate the effectiveness of the hybrid model.

An Intelligent Process Development Using Fusion of Genetic Algorithm with Fuzzy Logic

2016 ◽  
pp. 312-348
Author(s):  
Kunjal Bharatkumar Mankad
Keyword(s):  
Genetic Algorithm ◽  
Process Development ◽  
Intelligent System ◽  
Mathematical Formulation ◽  
Research Work ◽  
Fuzzy Rule ◽  
Genetic Operators ◽  
Rule Based System ◽  
Intelligent Process

Intelligent System (IS) can be defined as the system that incorporates intelligence into applications being handled by machines. The chapter extensively discusses the role of Genetic Algorithm (GA) in the search and optimization process along with discussing applications developed so far. A very detailed discussion on the Fuzzy Rule-Based System is presented along with major applications developed in different domains. The chapter presents algorithm of implementing intelligent procedure to decide whether a patient is prone to heart disease or not. The procedure evolves solutions using genetic operators and provides its decision automatically. The chapter presents discussion on the results achieved as a result of prototypical implementation of the evolutionary fuzzy hybrid model. The significant advantage of the presented research work is that applications that do not have any mathematical formulation and still demand optimization can be easily solved using the designed approach.

A model for examining the effects of communication on innovation performance: emphasis on the intermediary role of strategic decision-making speed

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fariborz Rahimnia ◽  
Homa Molavi
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Innovation Performance ◽  
Strategic Decision ◽  
Equation Modeling ◽  
Strategic Decision Making ◽  
Decision Making Process ◽  
Content Type ◽  
Intermediary Role

PurposeIn recent years, rapid changes in the economic situation and high levels of competition have increased the need for innovation in order to gain success. In such circumstances, organizational strategists are considered as critical in determining the success or failure of organizations. Using innovation in various aspects of organizational operations is the most important factor to achieve sustainable competitive advantages in industry. As a result, analyzing the effective factors involved in promoting the efficiency of innovative activities in the organization and ways of achieving it are of utmost importance. Thus, this paper examines the relationship between communication and innovation performance with respect to the intermediary role of strategic decision-making process speed.Design/methodology/approachThe present study has used quantitative methodology and questionnaire to collect data from 450 managers and members who are involved in the decision-making process in 150 companies operating in the food-industry sector. Data analysis was done by using structural equation modeling and AMOS software.FindingsThe results of the data analysis suggest that communication and strategic decision-making speed possess a significant positive impact on innovation performance. Also, strategic decision-making speed has sufficiently played the intermediary role between communication and innovation performance.Originality/valueThis survey specifies the effects of communication on the success of making fast strategic decision and innovation performance which aid Iranian food companies to tackle one of the managerial challenges: postponing strategic decisions due to lack of efficient communication to get information. In addition, to the best of the authors' knowledge, this essay is a first in Iran.

scholarly journals Collaborative Regulation and Supply Chain Resilience: A Conceptual Paper

2018 ◽  
Vol 56 ◽  
pp. 05002
Author(s):  
Osaro Aigbogun ◽  
Zulkipli Ghazali ◽  
Radzuan Razali
Keyword(s):  
Supply Chain ◽  
Regulatory Control ◽  
Working Relationships ◽  
Control Mechanisms ◽  
Supply Chain Resilience ◽  
Supply Chain Relationships ◽  
Manufacturing Supply Chain ◽  
Conceptual Paper ◽  
Conceptual Study

This paper is a conceptual study that introduces the role of collaborative regulation into the supply chain resilience debate. The manufacturing supply chain ofhalalpharmaceuticals in Malaysia forms the context of the paper. In this paper, a critical review of previous studies on supply chain resilience, joint working relationships between supply chain actors, and collaborative involvement of regulatory authorities in supply chain relationships was carried out. Collaborative regulation for improved supply chain resilience is the coordinated, consistent, and strategic activities that includes: effective, as well as regular coordination and interactions; knowledge and information sharing, verification, and periodical monitoring, as well as enforcement of collaborative approaches to policy and regulatory control mechanisms via coercive force of isomorphism. The arguments put forward, contribute to improving knowledge, by specifying the conditions in which supply chain resilience is stronger in highly regulated contexts. This is an aspect that is ill reflected in the supply chain management literature.

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