scholarly journals The Configuration of Supply Chain Concentration and Staff Structure in Intelligent Manufacturing: A Fuzzy Sets Qualitative Comparative Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jie Ding ◽  
Siqi Wang ◽  
Meilan Chen
Keyword(s):  
Supply Chain ◽  
Comparative Analysis ◽  
Fuzzy Sets ◽  
Business Performance ◽  
Qualitative Comparative Analysis ◽  
Intelligent Manufacturing ◽  
Saturation State ◽  
Sales Personnel ◽  
Manufacturing Enterprises ◽  
Concentration Degree

In traditional manufacturing enterprises, there are common problems of low added value of products, low profit, and poor business performance. As a result, they endeavor to transform themselves into intelligent manufacturing. To help with their transformation, this paper proposes a decision support model for managers to improve the business performance under different configurations of supply chain concentration and staff structure. Through the fuzzy set qualitative comparative analysis, the membership degree is given to the variables, and then the configuration analysis is carried out. We find that, to facilitate intelligent manufacturing, the concentration degree of supply chain or the structure of employee education should be adjusted according to the results from the qualitative comparative analysis of fuzzy sets. Two configuration paths to improve business performance are found. When the supply chain concentration degree is relatively decentralized, manufacturing enterprises should expand the proportion of sales personnel and production personnel. In other words, when the sales personnel and production personnel reach the saturation state, low concentration of suppliers and customers is more conducive to the improvement of business performance. The configuration of high proportion of production personnel and low customer concentration tends to lock enterprises in the lower end of the value chain. Therefore, it is critical for enterprises to improve the education level of employees to transform into intelligent manufacturing and improve their business performance.

scholarly journals A roadmap for applying qualitative comparative analysis in supply chain research

2019 ◽  
Vol 49 (1) ◽  
pp. 99-120 ◽  
Author(s):  
Ivan Russo ◽  
Ilenia Confente ◽  
David Gligor ◽  
Nicola Cobelli
Keyword(s):  
Supply Chain ◽  
Comparative Analysis ◽  
Supply Chain Management ◽  
Customer Satisfaction ◽  
Management Practices ◽  
Theoretical Perspective ◽  
Qualitative Comparative Analysis ◽  
Reverse Supply Chain ◽  
Chain Management ◽  
Content Type

PurposeThe purpose of this paper is to introduce qualitative comparative analysis (QCA) to the field of supply chain management and provide a detailed roadmap that supply chain researchers can utilize when applying this methodology.Design/methodology/approachData collection focused on the evaluation of product returns management practices as perceived by business customers who operate in a supplier–customer context. In order to analyze the data using the QCA approach, a multi-step analysis was developed.FindingsThe results indicate five solutions that lead to high levels of customer satisfaction. The existence of multiple sufficient configurations for customer satisfaction indicates equifinality because multiple alternative solutions can lead to the same outcome.Research limitations/implicationsThe authors make a methodological contribution by applying the QCA method to the field of supply chain management and providing a detailed roadmap that supply chain researchers can utilize.Practical implicationsThe authors provide managers five different and novel combinations of antecedents that lead to higher levels of customer satisfaction.Originality/valueThis study offers supply chain researchers a better understanding of when it is appropriate to use QCA and how to apply this methodology. From a theoretical perspective, past studies focused exclusively on the “net effects” of these antecedents, thus, did not capture the complexity of the relationships between these various antecedents and customer satisfaction. This is a noteworthy contribution as it highlights the complexity of the amalgam of relationships and factors that impact customer satisfaction within the context of reverse supply chain.

Qualitative Comparative Analysis (QCA) and Set Theory

2017 ◽  
Author(s):  
Claudius Wagemann
Keyword(s):  
Comparative Analysis ◽  
Fuzzy Sets ◽  
Political Science ◽  
Set Theory ◽  
Social Scientist ◽  
A Priori ◽  
Qualitative Comparative Analysis ◽  
General Question ◽  
Explanatory Factors ◽  
The Stability

Qualitative Comparative Analysis (QCA) is a method, developed by the American social scientist Charles C. Ragin since the 1980s, which has had since then great and ever-increasing success in research applications in various political science subdisciplines and teaching programs. It counts as a broadly recognized addition to the methodological spectrum of political science. QCA is based on set theory. Set theory models “if … then” hypotheses in a way that they can be interpreted as sufficient or necessary conditions. QCA differentiates between crisp sets in which cases can only be full members or not, while fuzzy sets allow for degrees of membership. With fuzzy sets it is, for example, possible to distinguish highly developed democracies from less developed democracies that, nevertheless, are rather democracies than not. This means that fuzzy sets account for differences in degree without giving up the differences in kind. In the end, QCA produces configurational statements that acknowledge that conditions usually appear in conjunction and that there can be more than one conjunction that implies an outcome (equifinality). There is a strong emphasis on a case-oriented perspective. QCA is usually (but not exclusively) applied in y-centered research designs. A standardized algorithm has been developed and implemented in various software packages that takes into account the complexity of the social world surrounding us, also acknowledging the fact that not every theoretically possible variation of explanatory factors also exists empirically. Parameters of fit, such as consistency and coverage, help to evaluate how well the chosen explanatory factors account for the outcome to be explained. There is also a range of graphical tools that help to illustrate the results of a QCA. Set theory goes well beyond an application in QCA, but QCA is certainly its most prominent variant. There is a very lively QCA community that currently deals with the following aspects: the establishment of a code of standards for QCA applications; QCA as part of mixed-methods designs, such as combinations of QCA and statistical analyses, or a sequence of QCA and (comparative) case studies (via, e.g., process tracing); the inclusion of time aspects into QCA; Coincidence Analysis (CNA, where an a priori decision on which is the explanatory factor and which the condition is not taken) as an alternative to the use of the Quine-McCluskey algorithm; the stability of results; the software development; and the more general question whether QCA development activities should rather target research design or technical issues. From this, a methodological agenda can be derived that asks for the relationship between QCA and quantitative techniques, case study methods, and interpretive methods, but also for increased efforts in reaching a shared understanding of the mission of QCA.

scholarly journals The Impact of Information Technology Capabilities of Manufacturing Enterprises on Innovation Performance: Evidences from SEM and fsQCA

2019 ◽  
Vol 11 (21) ◽  
pp. 5946 ◽  
Author(s):  
Yizhou Chu ◽  
Maomao Chi ◽  
Weijun Wang ◽  
Bo Luo
Keyword(s):  
Information Technology ◽  
Comparative Analysis ◽  
Fuzzy Set ◽  
Product Innovation ◽  
Qualitative Comparative Analysis ◽  
Process Innovation ◽  
Digital Transformation ◽  
Innovation Performance ◽  
Manufacturing Enterprises ◽  
It Capabilities

With the development of national strategies (such as Industrial 4.0 and Made in China 2025), how to build digital enterprises and cultivate innovation capabilities of enterprises has become a critical problem to Chinese manufacturing enterprises. However, the literature on the specific path of information technology (IT) capabilities to the innovation of enterprises is still lacking a body of relevant empirical research. In particular, it has not yet thought to explore the information technology capabilities, digital transformation, and then innovation performance of manufacturing enterprises. By performing a questionnaire investigation for 138 Chinese manufacturing enterprises, this study adopted both a fuzzy-set qualitative comparative analysis (fsQCA) and structural equation modeling (SEM) to explore the set relations of the conjunctions and conditions and the statistical associations by studying the relationships among information technology capabilities, digital transformation and innovation performance. The results show that the positive impacts of information technology capabilities on the process innovation performance and the digital transformation, as well as the positive impacts of digital transformation on both process innovation performance and product innovation performance. Specifically, digital transformation takes on a new function of partial mediation of IT capabilities and process innovation performance, and digital transformation functions as a complete mediator for IT capabilities and product innovation performance. The combinations of causal recipes related to innovation performance are provided by a fuzzy-set qualitative comparative analysis (fsQCA). Through the analyses of SEM and fsQCA, this research develops the formation mechanisms of both process innovation performance and product innovation performance, and provides guidance for both IT and innovation management of manufacturing enterprises in China.

scholarly journals Standards of Good Practice in Qualitative Comparative Analysis (QCA) and Fuzzy-Sets

2010 ◽  
Vol 9 (3) ◽  
pp. 397-418 ◽  
Author(s):  
Carsten Q. Schneider ◽  
Claudius Wagemann
Keyword(s):  
Data Analysis ◽  
Comparative Analysis ◽  
Fuzzy Sets ◽  
Good Practice ◽  
Qualitative Comparative Analysis ◽  
Research Approach ◽  
Analytical Technique ◽  
Work In Progress ◽  
Methodological Tool

AbstractAs a relatively new methodological tool, QCA is still a work in progress. Standards of good practice are needed in order to enhance the quality of its applications. We present a list from A to Z of twenty-six proposals regarding what a “good” QCA-based research entails, both with regard to QCA as a research approach and as an analytical technique. Our suggestions are subdivided into three categories: criteria referring to the research stages before, during, and after the analytical moment of data analysis. This listing can be read as a guideline for authors, reviewers, and readers of QCA.

Qualitative comparative analysis: Crisp and fuzzy sets in business and management

2016 ◽  
Vol 69 (4) ◽  
pp. 1261-1264 ◽  
Author(s):  
Norat Roig-Tierno ◽  
Kun-Huang Huarng ◽  
Domingo Ribeiro-Soriano
Keyword(s):  
Comparative Analysis ◽  
Fuzzy Sets ◽  
Qualitative Comparative Analysis ◽  
Business And Management

scholarly journals Research on the Path of Manufacturing Enterprises Supply Chain Integration from the Configuration Perspective

Processes ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1746
Author(s):  
Hongxiong Yang ◽  
Yunpeng Wang
Keyword(s):  
Supply Chain ◽  
Qualitative Comparative Analysis ◽  
Supply Chain Integration ◽  
Necessary Condition ◽  
Integration Path ◽  
Risk Avoidance ◽  
Manufacturing Enterprises ◽  
Five Factors ◽  
Synergistic Mechanism ◽  
Policy Supply

In digital transformation and development, supply chain integration has become a key strategy to improve supply chain synergy efficiency and enhance enterprise competitiveness. Based on the survey data of 185 manufacturing enterprises in Tianjin, the fuzzy set qualitative comparative analysis (fs QCA) method is used to explore the synergistic mechanism of government policy, supply chain partnership, information sharing, risk avoidance, and intelligence degree on supply chain integration and the interaction among them. The results show that: (1) a single factor does not constitute a necessary condition for promoting supply chain integration, but the formation and development of supply chain partnership plays a universal role in promoting supply chain integration; (2) the “multiple concurrent” of five factors constitute the diversified configuration of a driving supply chain integration path, that is, the driving supply chain integration path has the characteristic of “all roads lead to the same destination”; (3) there is a “sharing” type, a “cooperative” type, and a “cooperative-sharing” type three equivalent path, whereby the formation of supply chain partnership can enhance the trust between manufacturing enterprises and suppliers and customers, increase the transaction frequency of upstream and downstream enterprises, and improve the cooperation efficiency. The utility model can effectively reduce the “long whip” problem caused by the information asymmetry, and improve the operational efficiency and stability of the whole supply chain. The purpose of this study is to inspire manufacturing enterprises in the context of digital supply chain integration to improve the collaborative efficiency of the supply chain.

scholarly journals Condições à cooperação brasileira na África (2003–2010)

2019 ◽  
Vol 14 (3) ◽  
Author(s):  
David Beltrão Simons Tavares Albuquerque ◽  
Eduardo Matos Oliveira
Keyword(s):  
Comparative Analysis ◽  
Fuzzy Sets ◽  
Qualitative Comparative Analysis ◽  
Per Capita

A proposta desse trabalho é buscar os aspectos estruturais da inserção brasileira na África, por meio da análise das condições necessárias e suficientes para o estabelecimento de projetos de cooperação brasileira na África entre os anos de 2003 a 2010. As quatro condições observadas, por meio da análise teórica e empírica de recentes trabalhos, foram se um país tem como língua matriz o português, o grau de estabilidade política, o PIB per capita e o déficit alimentar. O artigo busca complementar as linhas teóricas tradicionais, as quais identificam os possíveis incentivos dos Estados subdesenvolvidos para promover a cooperação, a fim de indicar quantitativa e qualitativamente as políticas da Cooperação Sul-Sul (CSS) brasileira na África e seus respectivos impactos. Foi empregada, para tanto, a técnica de análise Qualitative Comparative Analysis fuzzy-sets (QCAfs). A variável dependente (qualitative outcome) abordará uma gradação de intervalo entre potenciais parceiros e não-parceiros, por meio da análise dos projetos e das condições existentes. Os resultados observados apontam como condição suficiente a presença da Língua Portuguesa.

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