Strategic consensus between functions and the role of supply chain technology as moderator

Titik Kusmantini, Tulus Haryono, Wisnu Untoro, Ahmad Ikhwan Setiawan


Purpose: This study aims to identify whether the degree of fit of the correlation between high supply chain and manufacturing strategy will result in a better performance.

Design/methodology/approach: Strategic alignment test between the functions uses 102 SMEs in Yogyakarta as, Indonesia with purposive sampling technique. The data are collected by distributing questionnaires to the companies that qualify the criteria of the sample, respondent target are procurement manager, production and IT.

Findings: Samples are grouped into two ideal types of strategies used mean split technique. 53 SMEs adopt ASCS (Agile Supply Chain Strategy) and 49 SMEs adopt LSCS (Lean Supply Chain Strategy). Two of the strategy groups have a low value of misfit score; it means that the degree of fit between supply chain strategy and manufacturing strategy is high. The result of simple regression test by using one side technique shows that a regression coefficient values is negative both in LSCS and ASCS group, but the hypothesis test is only proven on ASCS group while LSCS group is not significant.

Research limitations/implications: (1) The empirical finding of bivariate fit model test encourage a research space to explore the other contingent variable besides manufacturing strategy. For example, business and information technology strategy; (2) The measurement of the company performance becomes the objective of the success of the alignment of supply chain strategy with the contingent variable which should be specified using the performance variable of the supply chain.

Originality/value: The use of Euclidean distance formula is expected to cover the technical limitations of contingency test by using interaction approach between the complex variables; the value of misfit score reflects the extent to which program alignment between the company functions.


Misfit score, Euclidean distance, mean split, contingent variables simple regression technique

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Licencia de Creative Commons 

This work is licensed under a Creative Commons Attribution 4.0 International License

Journal of Industrial Engineering and Management, 2008-2024

Online ISSN: 2013-0953; Print ISSN: 2013-8423; Online DL: B-28744-2008

Publisher: OmniaScience