Background: As the Internet of Things (IoT) has become more prevalent in recent years, digital twins have attracted a lot of attention. A digital twin is a virtual representation that replicates a physical object or process over a period of time. These tools directly assist in reducing the manufacturing and supply chain lead time to produce a lean, flexible, and smart production and supply chain setting. Recently, reinforced machine learning has been introduced in production and logistics systems to build prescriptive decision support platforms to create a combination of lean, smart, and agile production setup. Therefore, there is a need to cumulatively arrange and systematize the past research done in this area to get a better understanding of the current trend and future research directions from the perspective of Industry 4.0. Methods: Strict keyword selection, search strategy, and exclusion criteria were applied in the Scopus database (2010 to 2021) to systematize the literature. Results: The findings are snowballed as a systematic review and later the final data set has been conducted to understand the intensity and relevance of research work done in different subsections related to the context of the research agenda proposed. Conclusion: A framework for data-driven digital twin generation and reinforced learning has been proposed at the end of the paper along with a research paradigm.

Background: Digital and smart supply chains are reforming the food chain to help eliminate waste, improve food safety, and reduce the possibility of a global food catastrophe. The globe currently faces numerous food-related issues, ranging from a lack of biodiversity to excessive waste, and from ill health caused by excessive consumption to widespread food insecurity. It is time to look back at how technology has tackled food supply-chain challenges related to quality, safety, and sustainability over the last decade. Moreover, continuous transformations of the food supply chain into a more sustainable business model with utmost resilience is the need of the hour due to COVID-19 disruptions. Method: This study aimed to systematize literature (2010–2021) in the described context and propose a future research direction, with the assistance of a systematic review and bibliometric analysis on the research agenda proposed above. Results: The findings reveal that technological Industry 4.0 (IR 4.0) tools face specific barriers due to the scope and objective of the application. Conclusion: The Internet of Things has received more attention than any other IR 4.0 tool. More integration between the specialized tools is needed to address this issue. Furthermore, the authors have proposed a food supply chain-based operational framework on technological inclusion to facilitate the roadmap for food supply chain 4.0 for more resilience and food supply chain viability.

The recent technological inclusions in supply chains are encouraging practitioners to continuously rethink and redesign these supply chains. Organizations are trying to implement sustainable manufacturing and supply chain practices to utilize their resources to the full extent in order to gain a competitive advantage. Circular supply chain management acts as the main pathway to achieve optimal circular business models; however, research in this area is still in its infancy and there is a need to study and analyze how the benefits of technology can be leveraged in conventional models to impact circular supply chains and build smart, sustainable, circular business models. To gain better familiarity with the future research paradigms, a detailed systematic literature review was conducted on this topic to identify the dynamics of this field and domains deserving further academic attention. A holistic and unique review technique was used by the authors to capture maximal insights. A total of 96 publications from 2010 to 2021 were selected from the Web of Science core collection database through strict keyword search codes and exclusion criteria, with neat integration of systematic and bibliometric analyses. The findings of this study highlight the knowledge gaps and future research directions, which are presented at the end of this paper.

This paper presents the concerns in manufacturing supply chain. Further this study investigates the role of information technology (IT) and information sharing (IS) in manufacturing supply chain and determines its impact towards supply chain integration (SCI), supply chain performance (SCP), and manufacturing firm performance (FP) in Malaysia. The theoretical framework was proposed for the study on the basis of existing literature. The study administered a survey questionnaire to collect data from manufacturing firms in Malaysia with 112 respondents. A multiple regression analysis is conducted to establish the relationship between IT, IS, SCI, and FP. The study finds that IT and sharing has significant positive effect towards and performance. Firms that use IT and practice IS across partners in the supply chain are more likely to integrate their internal and external value chain for better performance both within and across the manufacturing firms in the supply chain. This study can be of interest to the manufacturing industry as well as other industry practitioners interested in improving the performance of the organization and supply chain in total. For supply chain practitioners, this results indicate that the firms should adopt IT and IS practices to strategically improve SCI. This in turn will also improve the supply chain network and firm’s performance. This study employs a newly developed framework which depicts the causal relationship between IT, IS, SCI, Supply Chain Performance, and FP in Malaysia. Furthermore, it closes a gap in existing literature by examining the effect IT and communication (ICT) practices toward manufacturing firms’ performance and SCP in a single setting. In addition, the current study attempted to construct a model which would estimate and interpret SCP and FP simultaneously, and to evaluate this model in an empirical fashion.

Background: The expansion of oil palm agriculture across the nations, especially in countries such as Malaysia and Indonesia, is growing at exacerbated levels. However, there is still a lack of awareness of the environmental, social, and economic challenges among the sector, ranging from the combination of ecological, economic, and ecosystem sustainability to the livelihoods of plantation workers and small holder communities. Small holders struggle to attain the primary standards on market governance, debt-free livelihood enhancements, certification norms, proper land rights and usage, outsourcing quality seeds, harvesting technologies, labor usage, etc. Method: There is a need to systematize the existing literature toward one that addresses the most fundamental and urgent questions that govern the palm oil small holder sustainability in the palm oil supply chain. The objective of this article is two-fold. One approach was to undertake an integrated systematic review and thematic scientific mapping of the last 10 years of research effort (2009–2020) on the specified research agenda, using data from the Web of Science (WoS) core collection database. Another objective was to gain insights and research direction. Results: The defined gaps and insights from the study helped to form the basis for developing a conceptual framework for achieving the sustainability and livelihood of small holders in the palm oil sector. Conclusions: There is a stringent need to focus on the sustainability factors of small holders in the palm oil upstream logistics to address and improve the overall efficiency of the supply chain.

The purpose of this research paper is to demonstrate the adaptability of lean six sigma using the DMAIC method in reducing the time spent on recruiting new employees for the Supply Chain Logistics Department. Six Sigma is a data-driven, disciplined technique and methodology for reducing defects in any phase, to achieve six standard deviations between the mean and the closest design limit, as modeled by the DMAIC method (Define, Measure, Analyze, Improve, and Control). DMAIC is a method for optimizing, improving, and securing business processes and designs. The DMAIC improvement phase is a key component of Sig Sigma tools. The study focuses on the time spent in the recruiting process of new hires for the supply chain logistics site. The recruiter was interviewed to gather secondary data. Using the Lean Six Sigma DMAIC approach, process efficiency has increased, processes have become faster, and data is more easily accessible. Following the implementation of improvement solutions, the time from the improvement stages can be reduced with the current process using lean six sigma approaches. The company was able to make significant improvements by utilizing its lean six sigma implementation skills, saving time and money while improving quality. The study evaluates prior research and makes recommendations for future research.