Volume 3, Issue 1 (1-2021)                   sjamao 2021, 3(1): 9-16 | Back to browse issues page

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Farah Kordmahaleh A, Farah Kordmahaleh H. The Impact of Supply-Chain and Quality Management Procedures on the Innovation Performance of Small and Medium Enterprises. sjamao. 2021; 3 (1) :9-16
URL: http://sjamao.srpub.org/article-7-90-en.html
Master of Industry-Systems Engineering, Tehran, Iran.
Abstract:   (427 Views)
Small and medium-sized organizations are considered as the engine of economic development and employment. The share of small and medium-sized organizations for more than 95% of businesses is creating 50% of value added worldwide and depending on the country, production between 60% to 90% of all new jobs. The present paper, with examining the information obtained from 73 small, medium-sized manufacturing enterprises, studied the relationship between information sharing in the supply chain and innovation performance of the organization by considering factors such as quality management and supplier-specific investment. In this study, 4 main hypotheses regarding the relationship between chain information sharing, supply of quality management, supplier-specific investment, and the effect of relationship between quality management and supplier-specific investment on innovation performance of the organization have been examined. The results of the study indicated that information sharing in the supply chain has a positive and direct effect on quality management and supplier-specific investment. The results also showed that the impact of information sharing in the supply chain on the specific investment of the supplier is higher than its impact on quality management. Finally, the impact of quality management on organizational innovation performance is far greater than the impact of supplier-specific investment on organizational innovation performance.
Full-Text [PDF 368 kb]   (488 Downloads)    
Type of Study: Research | Subject: Project، Program and Portfolio Management
Received: 2020/12/15 | Accepted: 2021/01/15 | Published: 2021/01/30

1. Lee Y, Shin J, Park Y. The changing pattern of SME's innovativeness through business model globalization. Technol Forecast Soc Change, 2012; 79(5): 832-842. [DOI:10.1016/j.techfore.2011.10.008]
2. Zhou H, Li L. The impact of supply chain practices and quality management on firm performance: Evidence from China's small and medium manufacturing enterprises. Int J Prod Econ. 2020; 107816. [DOI:10.1016/j.ijpe.2020.107816]
3. Sousa Jabbour A, Ndubisi NO, Seles B. Sustainable development in Asian manufacturing SMEs: progress and directions. Int J Prod Econ. 2020; 225. [DOI:10.1016/j.ijpe.2019.107567]
4. Xiao C, Yu C, Yue M. Life cycle of small and medium-sized enterprises based on external environmental perspective. Empirical Research that Takes 5 Metropolises Including Shenzhen as Samples. Systems Engineering. Theor Pract. 2009; 29(1). [DOI:10.1016/S1874-8651(10)60030-0]
5. Shou Y, Shao J, Lai K-h, Kang M, Park Y. The impact of sustainability and operations orientations on sustainable supply management and the triple bottom line. J Clean Prod. 2019; 240: 1-13. [DOI:10.1016/j.jclepro.2019.118280]
6. Wu L, Subramanian N, Abdulrahman M, Liu C, Lai K-h, Pawar K. The impact of integrated practices of lean, green, and social management systems on firm sustainability performance-evidence from Chinese fashion auto-parts suppliers. Sustain. 2015; 7: 3838-3858. [DOI:10.3390/su7043838]
7. Teixeira C, Lopes I, Figueiredo M. Classification methodology for spare parts management combining maintenance and logistics perspectives. J Manag Analyt. 2018; 5(2): 116-135. [DOI:10.1080/23270012.2018.1436989]
8. Lambert DM, Cooper MC. Issues in supply chain management. Indust Market Manag. 2000; 29(1): 65-83. [DOI:10.1016/S0019-8501(99)00113-3]
9. Mohammaddust F, Rezapour S, Farahani RZ, Mofidfar M, Hill A. Developing lean and responsive supply chains: A robust model for alternative risk mitigation strategies in supply chain designs. Int J Prod Econ. 2017; 183: 632-653. [DOI:10.1016/j.ijpe.2015.09.012]
10. Sangari MS, Hosnavi R, Zahedi MR. The impact of knowledge management processes on supply chain performance: An empirical study. Int J Logist Manag. 2015; 26(3): 603-626. [DOI:10.1108/IJLM-09-2012-0100]
11. Chen IJ, Paulraj A. Towards a theory of supply chain management: the constructs and measurements. J Operat Manag. 2004; 22(2): 119-150. [DOI:10.1016/j.jom.2003.12.007]
12. Banerjee M, Mishra M. Retail supply chain management practices in India: A business intelligence perspective. J Retailing Consum Serv. 2015.
13. Bicocchi N, Cabri G, Mandreoli F, Mecella M. Dynamic digital factories for agile supply chains: an architectural approach. J Indust Inform Integrat. 2019; 15: 111-121. [DOI:10.1016/j.jii.2019.02.001]
14. Zhou L, Chong A, Ngai E. Supply chain management in the era of the internet of things. Int J Prod Econ. 2015; 159: 1-3. [DOI:10.1016/j.ijpe.2014.11.014]
15. Wong C, Lai K, Bernroider E. The performance of contingencies of supply chain information integration: the roles of product and market complexity. Int J Prod Econ. 2015; 165: 1-11. [DOI:10.1016/j.ijpe.2015.03.005]
16. Zhou H, Benton WC. Supply chain practice and information sharing. J Oper Manag. 2007; 25: 1348-1365. [DOI:10.1016/j.jom.2007.01.009]
17. Kang M, Mahoney J, Tan D. Why firms make unilateral investments specific to other firms: the case of OEM suppliers. Strat Manag J. 2009; 30: 117-135. [DOI:10.1002/smj.730]
18. Deloitte. Rising Innovation in China. China Innovation Ecosystem Development Report. Deloitte, China. 2019.
19. Hong J, Liao Y, Zhang Y, Yu Z. The effect of supply chain quality management practices and capabilities on operational and innovation performance: evidence from Chinese manufacturers. Int J Prod Econ. 2019; 212: 227-235. [DOI:10.1016/j.ijpe.2019.01.036]
20. Hanafizadeh P, Zare Roasan A. Method of analyzing multilevel structures using smartpls software. First Edition. Termeh Publishing. 2012.
21. Gefen DD, Straub A. Practical guide to factorial validity using PLS-Graph: Tutorial and annotated example. Communications of the AIS. 2005; 16: 91-109. [DOI:10.17705/1CAIS.01605]
22. Cronbach L. Coefficient alpha and the internal structure of tests. Psychometrika, 1951; 16(3): 297-334. [DOI:10.1007/BF02310555]
23. Fornell C, Larcker D. Evaluating struc¬tural equation models with unobservable variables and measurement error. J Market Re¬s. 1981; 18(1): 39-50. https://doi.org/10.2307/3151312 [DOI:10.1177/002224378101800104]
24. Huber F, Herrmann A, Frederik M, Vogel J, Vollhardt K. Kausalmodellierung mit Partial Least Squares- Eine anwendungsorientierte Einführung. Wiesbaden: Gabler. 2007

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