This paper aims to critically examine the potential barriers to the implementation and adoption of Robotic Process Automation (RPA) in the beef supply chain. The beef supply chain has been challenging due to its complex processes, activities, and management. The beef industry has relied heavily on the human workforce in the past; however, RPA adoption allows automating tasks that are repetitive and strenuous in nature to enhance beef quality, safety and security. There are considerable potential barriers to RPA adoption as organisations have not focused on trying to eliminate them due to various reasons. Previous studies lack knowledge related to potential barriers to RPA adoption, so this creates a research gap and requires attention. Statistical data and information are extracted using secondary data relevant to RPA adoption in the beef supply chain. A business process model is formed which uses values or variables using existing statistical data and information. Simulation of the process model is carried out using Simul8 software and analyses of different scenarios help in choosing the best approach for RPA adoption. Results have identified the potential barriers in RPA adoption through the simulation process thus ensuring RPA performs with more potential. Analysis of ‘what-if’ scenarios allows organizational and employee-level improvements along with enhancing RPA’s accuracy. The process model is a generic model for use in real-life scenarios and can be modified by organisations according to their own business needs and requirements. The study contributes in theoretical and practical aspects as it allows decision-makers and managers to adopt RPA in a robust manner and adds to scientific knowledge by identification of potential barriers to RPA adoption.
Background: Knowledge transfer has been an important aspect in supply chain systems; however, there are many factors that affect the impact of transfer effectiveness. In previous studies, less attention has been given to the process of knowledge transfer and therefore, this paper highlights the significance of the process of knowledge transfer in supply chain processes. Enhanced supply chain networks have better performance when knowledge sharing is present, and it is important to identify and eliminate any supply chain complexity to improve the supply chain processes. Methods: A systematic review on the literature has been conducted to critically identify and evaluate the factors of supply chain complexity which impact knowledge transfer. Findings: The findings highlight the key benefits of effective knowledge transfer in supply chain systems by identifying risks associated with supply chain networks. Conclusion: The balanced power of facilitating knowledge transfer in supply chain processes helps in supply chain partnerships and reduces the supply chain complexity. This paper has both theoretical and practical contributions as it adds to the literature by identifying the factors of supply chain complexity drivers which are impacting the knowledge transfer.
Sustainable beef production is a global challenge in present times. This research paper aims to investigate the financial risks and barriers in the adoption of robotic process automation (RPA), which has emerged as a strategic catalyst for achieving sustainability in the beef sector. Beef manufacturers constantly strive to achieve sustainability and a competitive advantage in order to gain enhanced beef productivity at low operational costs. There is a gap in the research, as there is a lack of knowledge about the financial aspects, barriers, and challenges influencing the RPA adoption process in the beef supply chain. To bridge this gap, secondary research is used to extract statistical data and information relevant to the RPA adoption process in beef supply chains, considering financial aspects. This study utilises a simulation method adopting a process model created in previous research and analyses different scenarios based on financial parameters using values or variables in Simul8 software. The scenario analysis allows for the identification of financial risks in the adoption of RPA and evaluates the simulation results from a sustainability perspective. The scenario analysis highlights the financial risks and barriers in the adoption of RPA in beef supply chains through process simulation, using financial parameters as a basis. KPI values, income statements, and carbon emission reports are generated to evaluate the main bottlenecks at various beef supply chain stages, thus allowing business users to conduct a thorough cost analysis. Successful adoption of RPA can lead to reduced supply chain complexity, thus improving financial and operational efficiency, which results in increased beef productivity, quality, and shelf life. This study is extremely important as it assesses scenarios from a sustainability perspective and contributes to academic knowledge and professional practice. It provides a process model to support the financial and ethical decision-making of managers or stakeholders, while helping the beef sector adopt RPA with greater ease. The process model can be adopted or modified according to the financial circumstances and individual requirements of business users. Furthermore, it provides decision-makers with the knowledge to eliminate or prevent financial barriers, thus advancing and accelerating the adoption of RPA. Robust adoption of RPA assists beef supply chains in gaining higher productivity at reduced costs, thus creating sustainable value.
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