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Evaluation method of path selection for smart supply chain innovation

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Abstract

The smart supply chain innovation (SSCI) has become the key way for enterprises to enhance their competitiveness. Therefore, it is very important for the current supply chain enterprises to choose a reasonable innovation path. Through the literature review method, this paper summarizes the four main evaluation indicators of path selection for smart supply chain innovation, which are technical indicators, organizational environment indicators, operational efficiency indicators, risk prevention and control indicators. According to the characteristics of evaluation index, the improved Fuzzy Entropy-Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is proposed. This method considers the situation that the original data contains both interval value and fixed value data. Firstly, the standardized decision matrix is constructed, and then the optimal index weight is established by Fuzzy Entropy method. Secondly, this paper calculates the weighted decision matrix by using the method of sub item weighting of hierarchical indicators. Finally, the improved TOPSIS method is used to determine the relative closeness of each scheme. According to the weighted decision matrix, the innovation path index of the smart supply chain (SSC) is further calculated. We use the actual case of a company to analyze the evaluation method for three different SSCI paths. This paper provides a reference for the path selection of SSCI from the aspects of theory and practice.

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Notes

  1. JD.com is a comprehensive online retailer in China, and one of the most popular and influential e-commerce websites in the field of e-commerce in China.

  2. In order to protect the privacy of the company, the company investigated in this paper is called Company A.

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Acknowledgements

This research was funded by Major Program of the National Social Science Foundation of China (grant number No. 18ZDA060). The reviewers’ comments are also highly appreciated.

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Correspondence to Weihua Liu.

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Appendix 1

Appendix 1

Authors

Content of relevant literature on path of SSCI

Technical factors

Organizational environment

Operational efficiency

Risk prevention and control

Technical difficulty

Technical application

Internal organizational environment

External organizational environment

Innovation time and cost

Expected effect

Risk identification

Risk control

Ageron et al. (2013)

Artsiomchyk and Zhivitskaya (2015)

 

 

Barczak et al. (2019)

 

Bechtsis et al. (2018)

 

  

Bitzer and Bijman (2015)

 

Chang et al. (2019)

Chung et al. (2018)

 

 

Chien and Huynh (2018)

   

Dai et al. (2015)

 

 

Chung and Moon (2019)

 

 

Ehie and Ferreira (2019)

 

 

Ferrer et al. (2011)

  

 

Gao et al. (2017)

 

  

Hu et al. (2020)

 

Ju et al. (2016)

   

Kabadurmus (2020)

 

  

Hahn (2020)

 

 

Kim et al. (2015)

 

 

Lii and Kuo (2016)

  

 

Kusi-Sarpong et al. (2019)

Liu and Tang (2014)

 

 

Luomaranta and Martinsuo (2019)

Lv and Qi (2019)

Mandal (2015)

   

Mandal (2016)

Mukundan and Thomas (2016)

 

Oke et al. (2013)

 

Pan et al. (2019)

  

Reimann et al. (2019)

  

 

Sabahi and Parast (2019)

 

 

Sabri et al. (2018)

   

Shamout (2019)

 

 

Shan et at. (2020)

Shibin et al. (2018)

 

 

Shete et al. (2020)

 

 

Silva et al. (2019)

  

Skippari et al. (2017)

 

 

Sodero et al. (2019)

  

Spieth and Schneider (2016)

  

 

Storer and Hyland (2011)

   

Trimi and Berbegal-Mirabent (2012)

 

  

Ucler (2017)

 

 

Yang et al. (2015)

Yoon et al. (2016)

  

 

Zhang (2015)

  

Liu, Deng, et al. (2020), Liu, Liang, et al. (2020))

Liu et al. (2015)

 

 

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Liu, W., Wang, S. & Wang, J. Evaluation method of path selection for smart supply chain innovation. Ann Oper Res 322, 167–193 (2023). https://doi.org/10.1007/s10479-021-04031-1

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