In the past few years, reverse logistics practices have successfully managed to gain more attention in various industries and among supply chain researchers and experts. This is due to globalization, environmental concerns, and customer requirements, which have asserted industries’ concerns for reverse logistics management. In E-commerce, the process of reverse logistics originates with parcel refusal, undelivered goods, and exchanges. In developing countries like Pakistan, the adoption and implications of reverse logistics are still at their early stages. E-commerce companies give more attention to forward logistics and ignore logistics’ upstream flow in the supply chain. This study aims to identify, as well as list, the barriers and obtain the solutions to those identified barriers, and rank the barriers and their solutions so that logisticians and experts can solve them as per their priority. From the extensive literature review and experts’ opinions, we have found 14 barriers in implementing effective reverse logistics. Eight solutions to those barriers were also found from the literature review. This paper proposed the methodology based on fuzzy analytical hierarchy process (fuzzy-AHP), which used to get the weights of each barrier by using pairwise comparison, and fuzzy technique for order performance by similarity to ideal solution (fuzzy-TOPSIS) method, which was adopted for the final ranking of solutions to reverse logistics. The case of the Pakistan E-commerce industry is used in the proposed method.

Industry 4.0 and supply chain 4.0 are hot topics in the current business and technological era. This paper provides a literature review, past and current insights, and knowledge of supply chain 4.0 and Industry 4.0 in the context of sustainability. Literature shows that Industry 4.0 has a significant impact on the sustainability of the supply chain network. This paper also explains the different technologies of Industry 4.0, contributing to the sustainability of the supply chain in business. A total of 55 papers are reviewed in this study. We proposed a framework that identifies the effect of Industry 4.0 technologies on the supply chain. This research study used the systematic literature review methodology in Industry 4.0 and supply chain sustainability. The data was collected from (ScienceDirect, IEEE Xplore, and Google Scholar) databases. The Prisma framework was used to select articles for this study and only journal papers were selected for reviewing the literature. This study’s uniqueness concerns its integration of the two independent subjects (Industry 4.0 and supply chain sustainability) to develop the framework explaining the effects of the technologies of Industry 4.0 on supply chain sustainability. Moreover, this research extends the existing knowledge of current fields.

Recently, the demand for third-party logistics providers has become extremely relevant and the key subject for businesses to enhance their service quality and minimize logistics costs. The key success factor for an e-commerce business is product delivery, and the third-party logistics service provider is responsible for that. Each 3PLP has its own business characteristics, meaning it is important to select the most suitable logistics provider for the e-commerce business. This study uses a combination of grey relational analysis (GRA) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, assisting decision makers in choosing the best logistics service provider for their e-business. A case study of an e-commerce company based in Faisalabad, Pakistan, was selected to demonstrate the steps of the proposed methods. In this process, seven criteria of logistics suppliers were considered, and then the best alternatives among four logistics provider companies were selected using the proposed method.

With the increasingly fierce competition in the global shipbuilding industry, shipbuilding enterprises need to maintain competitiveness and cope with rapid changes. In this case, shipbuilding enterprises need to establish effective supply chain management. Among them, choosing the right supplier is one of the most critical activities. The supplier selection of shipbuilding enterprises is considered a complex multicriteria decision-making (MCDM) problem that attracts much attention due to intuitionistic fuzzy sets to deal with possible imprecision and fuzziness in real life. Based on this, this paper proposes a new method based on the intuitionistic fuzzy SWARA (stepwise weight assessment ratio analysis) and COPRAS (complex proportional assessment) method to select shipbuilding enterprise suppliers which is a new research area. First of all, different weights are given to each expert evaluation result according to their position, educational background, and working years. The supplier index’s weight is determined based on the intuitionistic fuzzy SWARA method, and it is easy to understand and operate. The ranking of suppliers is determined by the intuitionistic fuzzy COPRAS method. This method considers all kinds of uncertainties and evaluates the utility index and the cost index of alternative suppliers. Finally, taking a shipbuilding enterprise as an example, applying the intuitionistic fuzzy SWARA-COPRAS method is illustrated. Compared with other methods and sensitivity analysis, it shows that the intuitionistic fuzzy multicriteria decision-making method is effective and stable in shipbuilding enterprises.

Background: Coal production and marketing enterprises can significantly reduce transportation costs and improve their competitiveness by choosing appropriate road transportation companies. Methods: Based on this, a trapezoidal fuzzy SWARA-COPRAS method is proposed to select coal transportation companies. The trapezoidal fuzzy SWARA method is used to determine the index weight of coal transportation companies. The ranking of coal transportation companies is determined using the trapezoidal fuzzy COPRAS method. Results: Taking a coal production and marketing enterprise in Hubei, China as an example, the application of the trapezoidal fuzzy SWARA-COPRAS method is illustrated, and the coal transportation companies are sorted and analyzed for sensitivity. Conclusions: Compared with the results of other methods, the effectiveness and practicability of the trapezoidal fuzzy SWARA-COPRAS method are verified.