Purpose

The paper aims to analyse the contextual relationship and dependency amongst enablers for lean manufacturing implementation in Bulgarian small and medium-sized enterprises (SMEs).

Design/methodology/approach

In this study, the interpretive structural modelling (ISM) technique was used to develop a hierarchical structural model for enablers. Also, the interpretive ranking process (IRP) was used to analyse and rank enablers with reference to performance variables. For the ISM approach, a structural self- integration matrix was developed with the help of experts’ suggestions and opinions. Cross-impact matrix multiplication applied to classification (MICMAC) analysis was used to analyse the relationship amongst enablers. A total of nine experts were chosen for collecting the primary data in which seven experts belong to the industry and two experts were academicians. The dominant relationship amongst the enablers was analysed through IRP modelling.

Findings

A total of 11 enablers were identified for the purpose of this study. The model shows that “leadership and commitment by management”, “human resource management”, “customer relation management”, “supplier relation management” and “information technology system” are the most significant enablers for lean implementation in Bulgarian SMEs as these are positioned at the bottom levels in ISM model. MICMAC analysis shows that five enablers fall in the independent factor, two enablers in linkage factor and four enablers in the dependant factor while there is no enabler in the autonomous factor. ISM and IRP models show that “continuous improvement” is an essential enabler for the successful implementation of lean in Bulgarian SMEs. This study also helps to explain the comparative analysis of ISM and IRP, which indicates that IRP is a more robust modelling approach than ISM, as it incorporates the relationship of enablers with performance variables.

Research limitations/implications

ISM and IRP modelling approaches are based solely on expert opinions and responses. This limitation can be overcome with the help of empirical study.

Practical implications

This study supports the professionals/experts to prioritise and manage enablers at strategic and tactical levels while implementing lean manufacturing practices in Bulgarian SMEs. The models developed in the study will be helpful for practitioners to understand and analyse the interdependence of enablers for lean manufacturing implementation.

Originality/value

This study helps to identify and prioritise enablers that affect lean manufacturing adoption using ISM and IRP approaches. Literature shows that numerous authors have used the ISM approach but the use of IRP approach is limited. The models were developed in the study, totally dependent on data collected from the experts to ensure their real-life validity.

中文翻译：

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保加利亚中小企业精益制造实践的相互依赖性分析：解释性结构建模和解释性排名建模方法

目的

本文旨在分析保加利亚中小企业 (SME) 实施精益制造的推动因素之间的上下文关系和依赖性。

设计/方法/方法

在本研究中，解释性结构建模 (ISM) 技术用于为促成因素开发分层结构模型。此外，解释性排名过程 (IRP) 用于分析和参考绩效变量对促成因素进行排名。对于 ISM 方法，在专家建议和意见的帮助下开发了结构性自整合矩阵。应用于分类的交叉影响矩阵乘法（MICMAC）分析用于分析促成因素之间的关系。一共选择了9位专家进行一手数据采集，其中行业专家7位，院士2位。通过 IRP 建模分析了促成因素之间的主导关系。

发现

本研究共确定了 11 个促成因素。该模型表明，“管理层的领导和承诺”、“人力资源管理”、“客户关系管理”、“供应商关系管理”和“信息技术系统”是保加利亚中小企业精益实施的最重要推动因素，因为这些定位在 ISM 模型的底层。MICMAC分析表明，独立因素中有5个促成因素，连锁因素中有2个促成因素，从属因素中有4个促成因素，而自主因素中没有促成因素。ISM 和 IRP 模型表明，“持续改进”是保加利亚中小企业成功实施精益的重要推动因素。这项研究也有助于解释 ISM 和 IRP 的比较分析，

研究限制/影响

ISM 和 IRP 建模方法完全基于专家意见和响应。在实证研究的帮助下，可以克服这种限制。

实际影响

本研究支持专业人士/专家在保加利亚中小企业实施精益制造实践的同时，在战略和战术层面优先考虑和管理促成因素。研究中开发的模型将有助于从业者理解和分析精益制造实施的推动因素之间的相互依存关系。

原创性/价值

这项研究有助于使用 ISM 和 IRP 方法识别和优先考虑影响精益制造采用的推动因素。文献表明，许多作者使用了 ISM 方法，但 IRP 方法的使用是有限的。这些模型是在研究中开发的，完全依赖于从专家那里收集的数据，以确保它们在现实生活中的有效性。