Pursuing sustainable development creates competitiveness for manufacturing firms in the market, however the financial pressure of adopting sustainable environmental practices is still a major concern. Few studies were found on the inter-relationships between supply chain management practices, environmental sustainability, and firm financial performance. Moreover, manufacturing companies are compelled by different pressure groups across the globe to maintain environmental standards while conducting their business and supply chain activities. Therefore, the current study aims to investigate the impact of supply chain practices on environmental sustainability and financial performance. In addition, the role of environmental sustainability as a mediator between supply chain management and financial performance was analyzed to improve sustainable development. A well-designed questionnaire was administered to manufacturing companies in Jordan for data collection. A total of 376 responses were analyzed and the proposed hypotheses were tested by using Structural Equation Modelling (SEM) approach. The results reveal that environmental sustainability was tested significantly and influenced by supply chain practices such as relationship with customers, postponement, level of information sharing, and information quality. Whereas environmental sustainability had a significant direct effect on financial performance. Finally, environmental sustainability mediated the relationship of all supply chain management practices with financial performance except strategic supplier partnership dimension. The study provides policy guidelines to decision makers while simultaneously assists the managers to improve sustainability practices in manufacturing companies.

Purpose: The purpose of this paper is to develop a theoretical model that explains the impact of big data analytics capabilities (BDAC) on company's supply chain innovation capabilities and sustainable supply chain performance. BDAC is represented through two dimensions of big data technological capabilities (BDTC) and big data personal capabilities (BDPC). Moreover, the relationships between BDTC and BDPC with sustainable supply chain performance through the mediation effect of supply chain innovation capabilities are examined.Design/methodology/approach: The study used a quantitative research approach. A survey of 400 Jordanian manufacturing companies was carried out to conduct this research. However, the responses of 207 managers were valid to be used in the analysis. In this study, the SmartPLS software was used to perform structural equation modeling using a partial least squares approach (PLS-SEM) and to examine the measurement and structural model's validity and reliability.Findings: According to the results of this study, BDPC has a significant positive impact on supply chain innovation capabilities. Furthermore, the findings indicate that supply chain innovation capabilities are the most influential predictor of sustainable supply chain performance and act as a positive significant mediator in the relationship between BDPC and firm sustainable performance. Surprisingly, the study found that BDTC had no significant effect on supply chain innovation capabilities. Besides that, no significant relationship exists between BDTC and firm sustainable performance via the mediation effect of supply chain innovation capabilities.Originality/value: This study provides an integrated research model that incorporates BDAC, supply chain innovation capabilities, and sustainable supply chain performance in order to analyze supply chain innovation and sustainable supply chain performance. This suggests that the scope of the study is broader in terms of predicting sustainable supply chain performance. As a result, the study intends to fill a gap in the literature by explaining how BDAC affects supply chain innovation capabilities and firms sustainable performance. In addition, the role of supply chain innovation capabilities as a mediator between BDAC and sustainable supply chain performance is investigated.

In recent decades, the forest industry has been growingly expanded due to economic conditions, climate changes, environmental and energy policies, and intense demand changes. Thus, appropriate planning is required to improve this industry. To achieve economic, social and environmental goals, a supply chain network is designed based on a multi-period and multi-product Mixed-Integer Non-Linear Programming (MINLP) model in which the objective is to maximize the profit, minimize detrimental environmental effects, improve social effects, and minimize the number of lost demands. In addition, to improve forest industry planning, strategic and tactical decisions have been implemented throughout the supply chain for all facilities, suppliers and machinery. These decisions significantly help to improve processes and product flows and to meet customers’ needs. In addition, because of the presence of uncertainty in some parameters, the proposed model was formulated and optimized under uncertainty using the hybrid robust possibilistic programming (HRPP-II) approach. The $\epsilon$-constraint technique was used to solve the multi-objective model, and the Lagrangian relaxation (LR) method was utilized to solve the model of more complex dimensions. A case study in Northern Iran was conducted to assess the efficiency of the suggested approach. Finally, a sensitivity analysis was performed to determine the impact of important parameters on objective functions. The results of this study show that increasing the working hours of machines instead of increasing their number, increasing the capacity of some facilities instead of establishing new facilities and expanding the transport fleet has a significant impact on achieving predetermined goals.

Purpose: This study aims to examine the impact of supply chain digitalization (SCD) on supply chain performance (SCP) with the integration of supply chain agility (SCA) and supply chain resilience (SCR) in manufacturing firms. Additionally, it investigates the moderating role of environmental dynamism (ED) in these relationships in the context of manufacturing firms.Design/methodology/approach: A quantitative research design was employed, utilizing a structured questionnaire to collect data. The sample consisted of 374 valid responses from various managerial levels within manufacturing firms in Jordan. A purposive sampling technique was used to ensure that participants had relevant expertise in supply chain management. The data were analyzed using structural equation modeling (SEM) through Smart PLS software to test the proposed hypotheses.Findings: The study found that SCD positively impacts SCP by enhancing both SCA and SCR. Digital technologies were shown to improve supply chain visibility, speed of decision-making and resource efficiency, which are essential for maintaining performance under uncertain conditions. Furthermore, ED significantly moderates the relationship between digitalization and SCP, indicating that the benefits of digitalization on SCA and SCR are more pronounced in highly dynamic environments.Originality/value: This study contributes to the literature by offering an investigation on the role of SCD in influencing SCA, SCR and ultimately SCP in manufacturing firms. It also sheds light on the moderating effect of ED, providing a deeper understanding of the conditions under which digital transformation in supply chains is most beneficial. The study was based on three theoretical foundations: the resource-based view (RBV), the dynamic capabilities theory (DCT) and the contingency theory (CT).