Search results

The purpose of this paper is to analyze the interaction among some of the major barriers that may hinder the implementation of third-party logistics (TPL) in manufacturing industries.

This paper uses an interpretive structural modeling (ISM) methodology to analyze the interactions among the barriers.

It is beneficial for the management of any firm to be aware of significant barriers and to diagnose those that could be integral to the organization's future survival. Many works have focused on identifying barriers for TPL implementation, but a model for such barriers is lacking. This paper attempts to develop a model for the barriers using an ISM methodology and analyzes the mutual interactions among the barriers. The model differentiates between the barriers so that driving barriers, which can intensify other barriers, and dependent barriers are identified separately.

In this research, eight barriers are considered. Interactions between the barriers are evaluated with the help of the ISM matrix. Of the eight barriers, three barriers, including the lack of application and knowledge of advanced information technology, congested roadways and ports, and fear of employees of the firm, demonstrate both strong driving power and strong dependence power, as illustrated in the MICMAC analysis.

The coronavirus disease 2019 (COVID-19) pandemic created heavy pressure on firms, by increasing the challenges and disruptions that they have to deal with on being sustainable. For this purpose, it is aimed to reveal the role of the smart circular supply chain (SCSC) and its enablers towards achieving Sustainable Development Goals (SDGs) for post-pandemic preparedness.

Total interpretive structural modelling and Matrice d'Impacts Croises Multipication Applique' a un Classement (MICMAC) have been applied to analyse the SCSC enablers which are supported by the natural-based resource view in Turkey's food industry. In this context, industry experts working in the food supply chain (meat sector) and academics came together to interpret the result and discuss the enablers that the supply chain experienced during the pandemic for creating a realistic framework for post-pandemic preparedness.

The results of this study show that “governmental support” and “top management involvement” are the enablers that have the most driving power on other enablers, however, none of them depend on any other enablers.

The identification of the impact and role of enablers in achieving SDGs by combining smart and circular capabilities in the supply chain for the post-pandemic.