PROBABILISTIC MODELING OF STRATEGIC MARKETING MANAGEMENT FACTORS IN MSMES: A STUDY OF MINTZBERG'S 5PS AND SELF-RELIANCE PILLARS

Strategic marketing management has become a very important aspect of organizational stability and competitiveness in the fast-changing environment of the Micro, Small, and Medium Enterprise (MSMEs). The paper explores probabilistic modelling of the strategic marketing management factors through the combination of Mintzberg 5P framework- Plan, Ploy, Pattern, Position, and Perspective model and pillars of self-reliance that are fundamental to sustainable enterprise development. The mixed-method approach enabled the collection of data on MSMEs in various sectors to measure the probabilistic impact of these strategic dimensions on the organizational performance, adaptability, and long-term viability. The research uses the advanced statistical and probabilistic modelling methods to analyse the interconnection between strategic intent, operations patterns, and self-reliant practices. The results indicate that an optimal pace between planned (Plan and Ploy) and unplanned (Pattern, Position, Perspective) strategies coupled with the support of self-reliance pillars (financial autonomy, technological ability, and human capital growth) is an effective approach to the MSMEs in the context of strategic responsiveness and market sustainability. The study adds to the theoretical discourse on strategic marketing management in smaller businesses and provides practical implications on the practitioners who want to promote self-reliant, adaptable, and growth-driven MSMEs.

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Publication Details

Journal
International Journal of Apllied Mathematics
Published
2025-10-15
DOI
https://doi.org/10.12732/ijam.v38i6s.398
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
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article

PROBABILISTIC MODELING OF STRATEGIC MARKETING MANAGEMENT FACTORS IN MSMES: A STUDY OF MINTZBERG'S 5PS AND SELF-RELIANCE PILLARS

K. Venkateswara Raju
1 citations
International Journal of Apllied Mathematics
Big Data and Business Intelligence
2.28
article

PROBABILISTIC MODELING OF STRATEGIC MARKETING MANAGEMENT FACTORS IN MSMES: A STUDY OF MINTZBERG'S 5PS AND SELF-RELIANCE PILLARS

K. Venkateswara Raju
article en
1 citations

Abstract

Strategic marketing management has become a very important aspect of organizational stability and competitiveness in the fast-changing environment of the Micro, Small, and Medium Enterprise (MSMEs). The paper explores probabilistic modelling of the strategic marketing management factors through the combination of Mintzberg 5P framework- Plan, Ploy, Pattern, Position, and Perspective model and pillars of self-reliance that are fundamental to sustainable enterprise development. The mixed-method approach enabled the collection of data on MSMEs in various sectors to measure the probabilistic impact of these strategic dimensions on the organizational performance, adaptability, and long-term viability. The research uses the advanced statistical and probabilistic modelling methods to analyse the interconnection between strategic intent, operations patterns, and self-reliant practices. The results indicate that an optimal pace between planned (Plan and Ploy) and unplanned (Pattern, Position, Perspective) strategies coupled with the support of self-reliance pillars (financial autonomy, technological ability, and human capital growth) is an effective approach to the MSMEs in the context of strategic responsiveness and market sustainability. The study adds to the theoretical discourse on strategic marketing management in smaller businesses and provides practical implications on the practitioners who want to promote self-reliant, adaptable, and growth-driven MSMEs.

International Journal of Apllied MathematicsVol. 38(6s)
Openalex Percentile: Top 8%
Big Data and Business Intelligence
2.28
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PROBABILISTIC MODELING OF STRATEGIC MARKETING MANAGEMENT FACTORS IN MSMES: A STUDY OF MINTZBERG'S 5PS AND SELF-RELIANCE PILLARS — K. Venkateswara Raju · International Journal of Apllied Mathematics (2025) | TGRS Research Map | TGRS