Supply chain collaboration, agility and firm performance: a case of manufacturing SMEs in India.

Autor: Mahesh Prabhu, H., Srivastava, Amit Kumar, Mukul Muthappa, K.C.
Předmět:
Zdroj: Business Process Management Journal; 2024, Vol. 30 Issue 3, p754-769, 16p
Abstrakt: Purpose: The dynamic business environment and intense competition have mandated agility in operations for manufacturing firms. Effective inter-organizational collaboration can make operations more agile. This paper develops an interpretive model to explore the effect of supply chain collaboration (SCC) on supply chain agility (SCA) and, subsequently, on business performance. Design/methodology/approach: A hierarchical model that illustrates the relationship between SCC, SCA and firm performance components is developed using total interpretative structural modeling (TISM). Also, statistical validation of the model has been performed. Findings: The results indicate that the vision and alertness of the firm on the strategic front promote collaboration between supply chain partners. This creates operational agility, helping the firm to absorb fluctuations in demand, thereby enhancing business performance. Research limitations/implications: The opinion of most respondents was considered to develop the TISM framework over the fuzzy one, which necessitates a significantly more extensive data set. However, multiple discussions with participants can eliminate the prejudice of the majority approach. Also, the paper's development and validation were restricted to Indian manufacturing small and medium-sized enterprises (SMEs). The model can potentially be evaluated in large organizations to provide further insights. Originality/value: The study blends the factors of SCC and SCA in a novel way to explain their combined impact on business performance. The TISM model addresses the "why" of theory development in addition to the "what" and "how" of it. Using triangulation in combination with the interpretative tool, this study additionally offers methodological value. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index