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The paper aims to propose a clustering model for panel data. More specifically, the paper aims to construct a gray incidence model for panel data to solve the classification with multi-factors and multi-attributes.

The paper opted for a clustering theory study using gray incidence theory based on dynamic weighted function. The paper presents an example to verify the rationality of the new model, which suggests that the new model can reflect the incidence degree of panel data.

The paper provides a new gray incidence model based on a dynamic weighted function that can amplify the characteristics of the sample to some extent. The properties of the new incidence model, such as normalization, symmetry and nearness, are all satisfied. The paper also shows that the new incidence model performs very well on cluster discrimination.

The new model in this paper has supplemented and improved the gray incidence analysis theory for panel data.

This paper aims to explore how lean manufacturing practices (LMPs) predict sustainable performance (SP) in the context of manufacturing small and medium-sized enterprises (SMEs) in less developed countries, like Yemen. In particular, it investigates the mediating effect of corporate social responsibility (CSR) under different levels of competitive intensity (CI).

Hierarchical regression analysis was used to analyze data gathered from a survey of 259 Yemeni manufacturing SMEs.

The findings confirm that LMPs affect CSR, which in turn affects SP. This study also confirms that LMPs have a positive indirect effect on SP through CSR, which diminished in the presence of CI.

This study provides useful insights for policymakers and firms’ managers, who are anticipated to show a higher commitment to CSR in their firms when adopting LMPs to enhance their firms’ SP, especially under a low level of CI.

This paper contributes to expanding knowledge on the effect of LMPs on SP through CSR constrained by the level of CI.