A decision-making model to support the design of a strategic supply chain configuration

Abstract

Purpose The purpose of this paper is to apply an empirically based approach to develop a decision-making model that comprehensively incorporates the potential affecting factors and the related significant drivers that support network designers in selecting the appropriate strategic supply chain configuration or checking the coherence of an existing supply chain structure in four industry sectors. Design/methodology/approach The decision-making model is developed based on an empirical study that integrates multiple case studies and statistical analyses. In total, 113 best-in-class manufacturing firms in four sectors are studied to investigate their strategic supply chain configurations and the information of identified affecting drivers. The factor analysis and regression analysis are conducted to classify the drivers into five factor groups, and to identify the significant drivers used to develop the decision-making model. Findings The findings of this research are three-pronged. First, 12 significant drivers related to 5 factor groups affecting strategic supply chain network design (SCND) are identified. Second, a decision-making model is developed to support users in strategic SCND. Last, the main characteristics of various strategic supply chain configurations are summarized in four industry sectors. Research limitations/implications The authors identified valuable insights for both academics and practitioners based on the identified significant affecting drivers and the developed decision-making model. In addition, this study also proposes two potential research lines on the study of additional contextual affecting factors and decision issues in strategic SCND. Originality/value This study could be the first attempt to use an empirically based method to develop a decision-making model aimed at supporting the preliminary design of a supply chain network. Therefore, the drawbacks of a pure qualitative conceptual model and optimization model are eliminated.

The relationship between cost leadership competitive strategy and firm performance

“…The strategy attributes determine its structure, which in turn influences its ability to achieve long-term objectives (Lofving et al , 2014). Over the years, to accelerate the progress and development, many strategies and their attributes have been generated in the field of strategic management (Song et al , 2018). The organisations which previously adopted modern strategies are now claiming the success in achieving competitive advantages (Dayan et al , 2017; Sangwa and Sangwan, 2018a).…”

“…On the evidence of forces involved in Porter’s framework, recent studies claim that a firm can generate competitive strategy of cost leadership or differentiation and can deliver better performance (Kharub and Sharma, 2016, 2017a). The strategy should be developed after comprehensive analysis of relevant proficiencies (Kathuria et al , 2007; Song et al , 2018). Although the relevant proficiencies (productivity improvement programs (PIPs)) for a manufacturing firm are comprised of many domains such as total productive maintenance, capacity building measures, reliability centred maintenance and lean manufacturing (Sangwan et al , 2018), the quality management (QM) has been considered as a most reliable PIP among others (Kaynak, 2003; Das et al , 2008; Kharub and Sharma, 2015; Sangwa and Sangwan, 2018b).…”

İkili Sözel Gösterim Tabanlı Bilişsel Haritanın Tedarik Zinciri Konfigürasyonunda Kullanımı

“…Arashpour ve diğerleri [15] prefabrike ürünlerin gelişmiş imalatında TZK parametrelerinin eniyilemesini gerçekleştirdi. Song ve diğerleri [16] tedarik zinciri ağı tasarımını etkileyen faktörleri içeren bir karar verme modeli önerdi. Srai ve diğerleri [17] kimya sektöründe TZK'yi analiz etmek için bir karar verme modeli sundu.…”

Assessing batteries supply chain networks for low impact vehicles

“…As a matter of fact, low temperatures do not allow a complete potential of the battery (Sarpal et al , 2018) and are proved to be harmful for battery life too (Ahmadian et al , 2018). Similarly, high temperatures lead to rapid reactions of anodes with a consequent accelerated aging of the system (Song et al , 2018). Therefore, the storage thermal conditions can impact the battery degradation up to 50 per cent (Ambrose and Kendall, 2017).…”