• Examining the Role of Procurement 4.0 towards Remanufacturing Operations and Circular Economy

      Bag, S.; Dhamija, P.; Gupta, S.; Sivarajah, Uthayasankar (2021)
      Procurement digitalisation can provide significant opportunities for excellence in remanufacturing operations. The close attention of firms is required during the configuration of procurement 4.0 resources for applying front end and base technologies in order to develop the correct set of these resources. Based on Resource Based View theory, this research examines the role of resources influencing procurement 4.0 for driving productivity in remanufacturing operations and circular economy performance. The survey data for this research was gathered from working professionals in South Africa and results reveal that technological resources are necessary in procurement 4.0, which can in turn improve the productivity in remanufacturing operations. An upsurge in performance in remanufacturing operations can enhance the circular economy outcome. To the best of authors’ knowledge, this study is the first to provide insight for researchers, practitioners and academics with an empirical test of digital procurement on remanufacturing operations and of circular economy performance in an emerging economy like South Africa.
    • An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance

      Bag, S.; Gupta, S.; Kumar, A.; Sivarajah, Uthayasankar (2021-01)
      This study examines the effect of big data powered artificial intelligence on customer knowledge creation, user knowledge creation and external market knowledge creation to better understand its impact on B2B marketing rational decision making to influence firm performance. The theoretical model is grounded in Knowledge Management Theory (KMT) and the primary data was collected from B2B companies functioning in the South African mining industry. Findings point out that big data powered artificial intelligence and the path customer knowledge creation is significant. Secondly, big data powered artificial intelligence and the path user knowledge creation is significant. Thirdly, big data powered artificial intelligence and the path external market knowledge creation is significant. It was observed that customer knowledge creation, user knowledge creation and external market knowledge creation have significant effect on the B2B marketing-rational decision making. Finally, the path B2B marketing rational decision making has a significant effect on firm performance.
    • Role of technological dimensions of green supply chain management practices on firm performance

      Bag, S.; Gupta, S.; Kumar, S.; Sivarajah, Uthayasankar (2020)
      Purpose The research study aims to investigate green supply chain management (GSCM) elements as part of a complete system. It aims to understand the special properties of the GSCM system under the moderating effects of product complexity and purchasing structure. Design/methodology/approach A thorough literature review led to the building of the conceptual framework. Six constructs were identified using systems theory. These constructs include green supply chain technological dimensions (particularly, Artificial Intelligence (AI) based), green supply chain strategy, green supply chain process, product complexity, purchasing structure, and firm performance. The instrument was scientifically developed for gathering survey responses using complete design test methods. The conceptual model was eventually tested based on survey data collected from 250 automotive components and allied manufacturers in the emerging economy of South Africa. Findings The results indicate that GSCM technological dimensions (AI-based) positively influence GSCM strategy. Further, GSCM strategy was found to positively influence the GSCM process. The GSCM processes have significant effects on environmental performance, social performance, and financial performance. The product complexity has a significant moderation effect on the paths GSCM strategy and GSCM process. Originality/value The findings from multivariate data analysis provide a better understanding of GSCM system dynamics and are helpful to key decision-makers. This unique model has elevated GSCM theory to a new level. There are limited studies available in the existing GSCM literature using systems theory. This study will offer an advanced/comprehensive understanding to readers in this relatively new concept.