Purpose: This study explores the connection between intellectual capital (IC) components and the competitive advantage (CA) of the hospitality sector in Jordan through the mediating role of service innovation as well as the moderating role of big data analytics capabilities.Design/methodology/approach: Data were collected through a self-administered questionnaire from the hospitality sector with a sample of 402 respondents. Data were analysed using SmartPLS, a bootstrapping technique was used to analyse the data. The mediating effect for service innovation and the moderating effect for big data analytics capabilities were performed.Findings: The results showed that the proposed moderated-mediation model was accepted because the relationships between the constructs were statistically significant. The results of the data analysis supported a positive relationship between human capital, structural capital and relational capital and the CA as well as a mediating effect of service innovation. The findings confirmed that there is a moderating relationship for big data analytics capabilities between service innovation and CA. The results illustrate the importance of IC and service innovation in enhancing CA in the Jordanian hospitality sector in light of the big data analytics capabilities.Research limitations/implications: This cross-sectional study provides a snapshot at a given moment in time, a methodological limitation that affects the generalisation of the limitation's results, and the results are limited to one sector.Originality/value: This research developed a theoretical model to incorporate IC components, service innovation, big data analytics capabilities and CA. This paper offers new theoretical and practical contributions that add value to the innovation and CA literature by testing the moderated-mediation model of these constructs in the hospitality sector which has been greatly affected by the coronavirus disease 2019 (COVID-19) pandemic. This study is distinguished from other studies by highlighting the role of IC and service innovation in enhancing CA as service innovation contributes to the formation of many organisational advantages in the Jordanian hospitality sector.

Purpose: This study explores the connection between big data analytics capabilities and the competitive advantage of the manufacturing sector in Jordan through the mediating role of green radical innovation and green incremental innovation as well as the moderating role of a data-driven culture.Design/methodology/approach: For the purpose of this study, 356 questionnaires were analysed. Convergent validity and discriminant validity tests were performed through structural equation modelling in the Smart-PLS programme, and the data reliability was confirmed. A bootstrapping technique was used to analyse the data. The mediating effect for green radical and green incremental innovation and the moderating effect for data-driven culture were performed.Findings: The empirical results showed that the proposed moderated-mediation model was accepted because the relationships between the constructs were statistically significant. The results of the data analysis supported a positive relationship between big data analytics capabilities and the competitive advantage as well as a mediating effect of green radical innovation and green incremental innovation. It was confirmed that there is a moderating relationship for data-driven culture between green radical innovation, green incremental innovation and competitive advantage.Research limitations/implications: This cross-sectional study provides a snapshot at a given moment in time, a methodological limitation that affects the generalization of its results, and the results are limited to one country.Originality/value: This research developed a theoretical model to incorporate big data analytics capabilities, green radical innovation, green incremental innovation, data-driven culture, and competitive advantage. This study provides new findings that bridge the existing research gap in the literature by testing the moderated mediation model with a focus on the organizational benefits of big data analytics capabilities to improve levels of green innovation and competitive advantage in the Jordanian manufacturing sector.

Purpose: This paper aims to investigate hypothesized relationships between the Internet of things (IoT) and big data analytics (BDA) with supply chain visibility (SCV) and operational performance (OP) in the pharmaceutical manufacturing sector in Jordan. The paper also aims to test the conceptual model related to the indirect effects of SCV.Design/methodology/approach: To achieve the objectives of this paper, a conceptual model was developed through a review of the current literature. Data analysis was performed by covariance-based structural equation modelling using Amos 25 software, and the convergent validity, discriminant validity, reliability and confirmatory factor analysis were verified. Then the hypotheses were tested.Findings: The results of the study indicate that there is a positive and statistically significant relationship between the IoT and BDA on SCV and OP. The relationship was positive and statistically significant between SCV and OP. In addition, support for the mediation hypothesis that SCV mediates the relationship among IoT, BDA and OP was confirmed.Originality/value: This paper provides new theoretical and managerial contributions that have not been covered in previous studies, and it is considered the first study that uses this conceptual model with this mechanism in terms of the theoretical lens and empirical application. This paper contributes to understanding the dynamic mechanisms of the IoT and BDA in enhancing OP, which contributes to creating a supply chain capable of facing various environmental fluctuations and pressures. This study presents new implications that can be used in the supply chain literature.

Purpose: This study investigates the impact of big data analytics capabilities on green supply chain performance. Moreover, it assesses the mediating effect of the green innovation and moderating effect of technological intensity.Design/methodology/approach: This study is based on primary data that were collected from the food and beverages manufacturing sector operating in Jordan. A total of 420 samples were used for the final data analysis. Data analysis was performed via structural equation modeling (SEM) using SmartPLS 3.3.9.Findings: The results of the data analysis supported a positive relationship between big data analytics capabilities and the green supply chain performance as well as a mediating effect of green innovation. It was confirmed that technological intensity moderated the relationship of green innovation on green supply chain performance.Research limitations/implications: The study faced many limitations such as the method of collecting primary data, which relied on a questionnaire only and the use of cross-sectional data, as well as studying one context and in one country.Practical implications: The findings can guide managers and policymakers in the Jordanian food and beverage manufacturing sector on how to manage organizational capabilities related to big data analytics to enhance green supply chain performance and improve green innovation in these firms.Originality/value: This study developed a theoretical and empirical model to investigate the relationship between big data analytics capabilities, green innovation, technological intensity and green supply chain performance. This study offers new theoretical and managerial contributions that add value to the supply chain management and innovation literature by testing the moderated mediation model of these constructs in the food and beverages manufacturing sector in Jordan.

In light of global environmental concerns growing, environmental awareness within firms has become more important than before, and many scholars and researchers have argued the importance of environmental management in promoting sustainable organizational performance, especially in the context of supply chains. Thus, the current study aimed at identifying the impact of the components of green intellectual capital (green human capital, green structural capital, green relational capital) on green supply chain performance in the manufacturing sector in Jordan, as well as identifying the moderating role of big data analytics capabilities. To achieve this aim, we developed a conceptual model of Structural Equation Modelling-Partial Least squares and tested through the Smart-PLS software on a sample of 438 respondents. Empirical results showed that each of the components of green intellectual capital and big data analytics explains 71.1% of the variance in green supply chain performance and that all components of green intellectual capital have a statistically significant impact on green supply chain performance. The results also revealed that the relationship between green relational capital and green supply chain performance is moderated through big data analytics capabilities. Finally, this study made a theoretical and managerial implications to the supply chain literature and industry.