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This study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective model.

In dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC contexts.

The research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain management.

This study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain management.

This research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and decision-makers with insights to make informed and resilient decisions in supply chain management.

This paper aims to examine the antecedents of adoption intention of profit-sharing investment deposits (PSID) among Moroccan customers.

Applying an extended version of diffusion of innovation (DOI) theory and using a non-probability sampling technique with convenience approach, a quantitative survey was developed and administered to 171 Islamic banking users. Structural equation modeling was then used to evaluate the significance of relationships between the various variables under study using SPSS 21.0 and AMOS 26.0 statistical packages.

Empirical findings of the structural analysis indicated a significant direct relationship between adoption intention and six out of seven variables: perceived relative advantage, perceived compatibility, perceived complexity, perceived risk, religiosity and social influence, all of which had a significant effect on Moroccan customers’ intention to invest their funds in profit-sharing based deposit instruments, whereas customer awareness exerted an insignificant positive effect.

The absence of a longitudinal study tracking the actual adoption behavior is the main limitation of this study. Furthermore, data were collected solely from Islamic banking users. Finally, despite being insightful, the empirical findings should be generalized with caution since the sample was purposely selected by the banks’ management.

This study implied that participatory banks should pay substantial attention to risk perceptions, as PSID adoption intention is typically inhibited by high perceived risks associated with these products. Moreover, this study provides great indications to Moroccan regulators and policymakers on a number of issues related to this emerging business.

To the best of the authors’ knowledge, this paper represents the first attempt to confirm the effectiveness of the Rogers’ DOI in examining the intention to adopt a financial innovation in the Moroccan context. It is also the first of its kind to address customers’ apprehensions regarding profit-sharing investment products.

Acknowledging, on the one hand, the increasing fragility of supply chains and the number of risks involved in supply chain operations and, on the other hand, the role of small- and medium-sized enterprises (SMEs) in supply chains and the high exposure of these firms to risks of different types, this study aims to examine the relationship between supply chain risk management (SCRM) and innovation performance in SMEs. Furthermore, the impact of technological turbulence on this relationship was studied to take into account recent technological changes.

Structural equation modelling was carried out on a sample of Turkish SMEs to test the hypotheses developed.

The findings presented allow the authors to better understand the link between SCRM and innovation performance in SMEs. More precisely, empirical evidence is provided about the impact of SCRM components such as maturity and ability on innovation performance. Furthermore, the findings show the impact of technological turbulence on both SCRM and innovation performance.

By focusing on SCRM in SMEs, this paper contributes to the body of knowledge with regard to SCRM in general and with regard to SMEs in particular; research on the latter has only started recently. Moreover, by having studied SMEs from a developing country (other than China), this paper helps to develop a broader and more diverse perspective of SCRM.