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With the rapid change that has taken place with digitalization and data-driven approaches in supply chains, business environment become more competitive and reaching sustainability in supply chains become even more challenging. In order to manage supply chains properly, in terms of considering environmental, social and economic impacts, organizations need to deal with huge amount of data and improve organizations' data management skills. From this view, increased number of stakeholders and dynamic environment reveal the importance of data-driven technologies in sustainable supply chains. This complex structure results in new kind of risks caused by data-driven technologies. Therefore, the aim of the study to analyze potential risks related to data privacy, trust, data availability, information sharing and traceability, i.e. in sustainable supply chains.

A hybrid multi-criteria decision-making (MCDM) model, which is the integration of step-wise weight assessment ratio analysis (SWARA) and TOmada de Decisao Interativa Multicriterio (TODIM) methods, is going to be used to prioritize potential risks and reveal the most critical sustainability dimension that is affected from these risks.

Results showed that economic dimension of the sustainable supply chain management (SSCM) is the most critical concept while evaluating risks caused by data-driven technologies. On the other hand, risk of data security, risk of data privacy and weakness of information technology systems and infrastructure are revealed as the most important risks that organizations should consider.

The contribution of the study is expected to guide policymakers and practitioners in terms of defining potential risks causes by data-driven technologies in sustainable supply chains. In future studies, solutions can be suggested based on these risks for achieving sustainability in all stages of the supply chain causes by data-driven technologies.

This study aims to analyze lean wastes for the poultry sector in Turkey and link lean tools to this study, focusing on identifying each lean waste that affects poultry production and proposing solutions for preventing these lean wastes in the sector. The proposed solutions aim to improve processes by suggesting different lean tools and their applications for the poultry sector.

The study consists of two different applications. First, the waste relationship matrix (WRM) was created to reveal the relationship between seven lean wastes and their importance order. Then, after determining lean tools for eliminating lean wastes, the optimum weight ranking and consistency ratio of the most suitable lean tools were calculated for these wastes and ranked with the best-worst method (BWM).

Results showed that overproduction is the most critical waste that impacts other wastes, followed by defect waste. Due to the nature of the sector, these wastes not only result in economic loss for the company but also in food waste and loss and issues related to animal welfare. Furthermore, the Kaizen approach and 5S implementation are the methods to eliminate these wastes. Detailed discussion on the link between lean tools and lean wastes is provided for the poultry sector.

This is the first study that theoretically and empirically identifies the potential lean waste affecting the poultry sector and provides lean tools for eliminating these wastes. Sector-specific explanations and discussions are presented in the study to show the applicability of lean approaches in the poultry sector to eliminate waste. In addition, this study is the first to integrate the WRM and BWM.

Food supply chains (FSCs) are fast becoming more and more complex. Sustainability is a necessary strategy in FSCs to meet the environmental, economic and societal requirements. Industry 4.0 (I4.0) applications for a circular economy (CE) will play a significant role in sustainable food supply chains (SFSCs). I4.0 applications can be used in for traceability, tracking, inspection and quality monitoring, environmental monitoring, precision agriculture, farm input optimization, process automation, etc. to improve circularity and sustainability of FSCs. However, the factors integrating I4.0 and CE adoption in SFSC are not yet very well understood. Furthermore, despite such high potential I4.0 adoption is also met with several barriers. The present study identifies and analyzes twelve barriers for the adoption of I4.0 in SFSC from an CE context.

A cause-effect analysis and prominence ranking of the barriers are done using Rough-DEMATEL technique. DEMATEL is a widely used technique that is applied for a structured analysis of a complex problems. The rough variant of DEMATEL helps include the uncertainty and vagueness of decision maker related to the I4.0 technologies.

“Technological immaturity,” “High investment,” “Lack of awareness and customer acceptance” and “technological limitations and lack of eco-innovation” are identified as the most prominent barriers for adoption of I4.0 in SFSC.

Successful mitigation of these barriers will improve the sustainability of FSCs through accelerated adoption of I4.0 solutions. The findings of the study will help managers, practitioners and planners to understand and successfully mitigate these barriers.