SUPPLY CHAIN MANAGEMENT

TOPIC NAME: SUPPLY CHAIN MANAGEMENT

Author, Sunidhi Mallick

Author Remko, v. H., Johnson, et all

Purpose – Many supply chain reconfiguration programs are launched each year. Despite a wealth of knowledge existing in the general management domain, there has been little work within the supply chain management domain on change. That which does exist deals with change to a technical – as opposed to non-technical – system. This leaves out many of the social and behavioral aspects of change. This paper aims to address this gap. Design/methodology/approach The paper synthesized the general management and supply chain literature on change to create a framework to explore change within three supply chains. A multiple case study approach was adopted for the research. Longitudinal and quasi-longitudinal data were gathered and template analysis utilized to explore the cases contexts and the design choices they made in each of the change programmes. Findings – In all three cases, the change is non-linear and required re-planning and learning throughout the change effort to build the capacity and capability for change. In all three cases, the success of the change is facilitated through the use of cross-functional teams. Originality/value – Change leaders were involved in the research through co-authorship and a unique set of cross-case lessons learned were generated. The framework used in the analysis incorporates considerations previously ignored in the supply chain literature, including the non-linear, non-processual nature of change.

Abstract 2

Author  Trebilcock, B.

The study of change management in a supply chain context is an emergent field of study. Therefore, the most appropriate methodology for such a nascent area is a qualitative method ([23] Edmondson and McManus, 2007). A case study approach was used for this research as this allows the exploration of complex, messy phenomena ([24] Eisenhardt, 1989; [61] Yin, 2008). The process of change is undoubtedly messy and complex, and [25] Ellram (1996) recommends the use of case studies for the study of implementation and change issues. Moreover, case study research allows the collection of rich, explanatory information ([45] Mentzer and Flint, 1997) and allows researchers to build theory and connect with practice ([43] McCutcheon and Meredith, 1993).

As change occurs over time, a process orientation to the study was adopted ([44] Mohr, 1982; [41] Langley, 1999). This is as opposed to the more traditional “variance” type of research where constructs and causal impacts are the focus of the study, rather than change(s) over time. [42] Langley (2007) suggests that a process approach to the examination of the transition process rather than transition outcomes only is more appropriate. This is because traditional cross-sectional models provide a partial picture of the world that evacuates the role of time and assumes an equilibrium state.

Every so often, new technologies come along that threaten to upend the world as people know it. Such was the case in 2003 when Walmart announced its famous RFID mandate that required its top suppliers to put RFID tags on shipping crates and pallets. As RFID startups proliferated like convenience stores, many predicted the end of barcodes and a new level of real time supply chain visibility. Despite the hype, Walmart abandoned the initiative a few years later. Yet that wasn’t the end of the story. Twelve years after the mandate, RFID is alive and well in the retail supply chain. RFID isn’t so much a disruption as a complement to existing solutions. Fast forward, and supply chain managers are hearing about the wonders of robots, 3D printing, and wearable data collection technologies. Many are predicting that our supply chains will never be the same once these disruptive technologies take hold.

Abstract 3

Author Wang T, Chen H et all

In order to carry out practical innovation of the intelligent logistics system and promote the practicality of the intelligent logistics system and supply chain management process, this study aims to optimize the design of the intelligent logistics system and supply chain management under edge computing (EC) and the Internet of Things (IoT). The flower pollination algorithm performs the positioning function in the intelligent logistics system and supply chain management. Based on the research on the design of the intelligent logistics system and supply chain management under the EC and IoT, this thesis analyzes the positioning of intelligent logistics systems and supply chain management through the flower pollination algorithm. The eXtreme Gradient Boosting (XGBoost) model is used to predict user information in the system of supply chain management information. Finally, the operation of intelligent logistics and supply chain management systems, the prediction model of supply chain management under XGBoost, and the change of supply chain management and material flow are analyzed. The results show that with the increase in the number of iterations, the optimized algorithm improves the comparison distance error by 53.57%, which has high accuracy and can meet the requirements of positioning and tracking of the intelligent logistics system and logistics status query in supply chain management. The waiting time of the intelligent logistics system is shorter than that of the supply chain management system, and the average waiting time of the system increases by 121.252 ms. The XGBoost model can well predict user information under supply chain management. After discussing the changes of the intelligent logistics system from 2018 to 2020, it is found that the operation efficiency of the supply management system is higher with the increase of the system operation days. The intelligent logistics system has a significant impact on the development of the logistics industry. This research gives a reference for establishing the intelligent logistics system and supply chain management system.

Abstract 4

Author Greer BM, Ford MW,

The coordination required to successfully implement supply chain initiatives suggests that supply chain management change processes may possess some unique characteristics. Yet, empirical studies are scarce to support this logic. Using an empirical design and data obtained from managers,  drawing largely from Lewin’s change process conceptualization, this study compares the process of supply chain management change to non-supply management change.

Further investigation into monitoring and control of supply chain management change is advised.

Supply Chain Management and Planned Change

Because there are many different viewpoints and definitions for SCM (Larson, Poist, and Halldorsson 2007), it is important to identify the definition that we are using in this study. SCM is defined as the systematic, strategic coordination of the traditional business functions within a particular company and across businesses within the supply chain, for the purposes of improving the long-term performance of the individual companies and the supply chain as a whole (Mentzer et al. 2001, p. 18). This definition permits consideration of a broad range of changes enacted across all relevant business functions as organizations manage upstream and downstream flows of products, services, capital, and information. Moreover, this perspective helps capture a range of behavior that promotes effective SCM such as mutual information sharing; mutual risk sharing, aligned customer focus, process integration, and long-term relationship building. (Chen and Paulraj 2004; Lambert, Cooper, and Pagh 1998). This definition is also consistent with the missions and definitions established by both the Council of Supply Chain Management Professionals (CSCMP, formerly CLM-Council of Logistics Management) and the Institute of Supply Management (ISM). This is important since these organizations are a major and primary source of knowledge for supply chain professionals (Larson, Poist, and Halldorsson 2007).

Abstract 5

Author Jing-Yan, M., Shi, et all

As the global pharmaceutical market continues to expand, the demand for pharmaceutical supply chain is increasing. In the context of “Industry 4.0”, the pharmaceutical supply chain sector needs to accelerate digital construction. Pharmaceutical companies need to strengthen risk management in order to cope with supply disruptions. From the perspective of sustainable development, the pharmaceutical supply chain can achieve sustainable supply performance in social, economic and environmental dimensions through digital transformation. There is a lack of research on the digital transformation of   pharmaceutical supply chain management. Further research is needed on what specific digital management pharmaceutical companies need to enhance to improve supply performance. This study uses empirical analysis to examine the impact of digital transformation on sustainable supply chain performance and to explore the role of information sharing and traceability as mediators. The aim is to guide the pharmaceutical supply chain to clearly manage the development of digital transformation and obtain sustainable supply performance. This study presents hypotheses based on cutting-edge theoretical findings. In total, 298 Chinese pharmaceutical company supply chain managers were surveyed and Structural equation analysis was conducted using SPSS26.0 and AMOS24.0. The results show that digital transformation significantly and positively impacts sustainable supply chain performance. Traceability plays a mediating role. The mediating role of information sharing is not significant. However, information sharing and traceability as two separate trends can have synergistic effects that together affect sustainable supply performance. The conclusion is that the pharmaceutical supply chain should accelerate digital construction, eliminate the uneven development of digital technology among supply chain members, and reduce the impact of technological uncertainty on performance. Companies are enhancing supply chain security management through information sharing and traceability systems, and are continuously focusing on the role of digital transformation as a driver for sustainable development.

Abstract 6

Author Gelphman, M.

Manufacturers and the entire chain of distribution, including OEMs, ODMs, EMS, resellers, integrators et al, face the daunting task of evaluating their existing supply chain operation (if it even exists). Many are finding that they must create and then maintain a new architecture for a successful SCM model. This model involves key supply chain partners where the demand for “open communication” forces continual collaboration that transcends yesterday’s business levels. The key to a successful SCM model rests on two key factors. The first is change acceptance by management. Managers at all levels and within all elements of the supply chain itself must be willing to do more listening and less speaking to formulate policy. Accepting and incorporating SCM strategies as a fundamental change agent helps companies realize the desired cost savings and enables them to turn supply chain innovation into a market advantage.

The second key to successful SCM implementation is open collaboration among all the partners throughout the entire supply chain. The supply partnership means sharing information across firewalls, partnering or co-opting the competition and providing the tools to accommodate the increase in communications and ultimately sales.

By viewing the supply chain as a source for competitive advantage as well as investor value, it forces companies to marry their marketing and sales strategies to operations. It is critical not to let internal politics thwart the change needed to implement a successful SCM program.

 Abstract 7

Author v Meier, K,

There are many academic contributions dealing with the impact of additive manufacturing on supply chains (Ben-Ner and Siemsen, 2017; Durach, 2017; Gravier and Roethlein, 2018; Brown, 2018; Rogers et al., 2016; Sasson and Johnson, 2016; Nyman and Sarlin, 2014). But how future supply chain design may differ from today is still vague. In this article, possible scenarios are discussed and decision support is provided for the management, which is responsible for long-term strategic decisions Future developments and especially the development speed of additive manufacturing are not predictable. Therefore, the expected scenarios may differ from reality and lead to a different supply chain design. There will also be industries that can use additive manufacturing much more intensively than others – not least because of the technological restrictions of the manufacturing process. Corporate culture and the overcoming of technical challenges are a decisive factor.

Abstract 8

Author Cai, C., Hao et all

Globalization has prompted enterprises worldwide to increasingly seek the optimal supply chain configuration. However, outsourcing, shortened product life cycles, and a reduced supply base severely weaken supply chain risk tolerance. With the emergence of blockchain, enterprises see an opportunity to mitigate supply chain risks. The purpose of our research is to explore supply chain managers’ intention to adopt blockchain technology from the perspective of supply chain risk management. Using a survey sample of 203 managers in China and the USA, we explored the impact of four perceived benefits of blockchain technology on supply chain risk resistance by extending the technology acceptance model. The results show that the traceability, transparency, information sharing, and decentralization of blockchain can enhance the perceived usefulness of blockchain in supply chain resilience and responsiveness, and the ability to withstand disruption risks and supply and demand coordination risks encountered in the supply chain, thus promoting the adoption of the technology. In addition, the relationships between supply chain resilience and blockchain technology adoption and between supply chain responsiveness and blockchain technology adoption are more salient for managers with high levels of uncertainty avoidance. Supply chain risk management plays a vital role in all organizations, and the application of new technologies in supply chain risk management has attracted widespread attention. In order to understand the willingness of enterprises to adopt blockchain in the supply chain, the literature on supply chain risk management, blockchain, and blockchain technology adoption is reviewed in turn.

Abstract 9

 Author Zhao, Hailei,

Green supply chain finance is a new financing method that focuses on corporate restructuring and promotes corporate capital flow and the development of environmental protection. This paper used BP neural network technology to study the green financing of the supply chain under the sustainable ecological environment. The method played an important role in the trial. Due to the more uncertain factors faced and the more complex environment, the risks of green supply chain finance are more hidden, diverse, and complex. The BP neural network is relatively mature in both network theory and performance. Its outstanding advantages are its strong nonlinear mapping ability and flexible network structure. The positive effect of BP neural network on green financial risk management is verified by experiments. Green supply chain finance is an innovative model of green finance. This experiment studies the risk management of green finance in supply chain and the evaluation index of green finance risk management through BP neural network method, and shows that the evaluation results are highly scientific. In addition, based on the green supply chain model, the historical data of different regions provide a scientific basis for the sustainable ecological development of the region. This paper provides guidance for the sustainable development of green finance in the supply chain and makes contributions to promoting the development of green economy. In order to control the risks of supply chain financing business, the risks of supply chain financing business are classified and analyzed, and specific project risk levels and points are determined to propose control measures to ensure effective control of the business risks.

Abstract 10

Author Dewhurst, F., Spring at all,

This paper explores the limited but diverse multidisciplinary literature and the “theory/practice” gap in the area of supply chain management and the impact on the supply chain of preparing for the year 2000. The aim of this research is to examine the Y2K phenomenon as an example of an environmental shock to organisations and their supply chains, with special reference to: managerial response, stockpiling and SCM practice. Any lessons that can be learned from studying this event could provide useful information for future significant environmental changes (e.g. EU currency conversion, changes to trading and market environments resulting from e-commerce, the EU Working Time Directive).

The response of any organisation, large or small, to any environmental change, such as the Y2K problem, depends on its ability to perceive, sense, recognise, understand and react to these changes. For many SMEs, the responsibility for environmental sensing and problem recognition falls to the owner/manager and therefore her/his ability and willingness to perceive, interpret and respond to such environmental changes will be crucial to the SME’s success.

Conclusion

The first abstract by Remko et al. discusses the gap in supply chain management literature regarding non-technical aspects of change management within supply chains. The authors conducted multiple case studies to explore the dynamics of change within supply chains. They found that change in supply chains is non-linear, requiring ongoing re-planning and learning. Cross-functional teams play a crucial role in facilitating change. This research involves change leaders and provides cross-case lessons learned.

Trebilcock’s abstract emphasizes the use of qualitative methods, particularly case studies, to understand change management in supply chains. The study focuses on the complex and messy nature of change processes and suggests that a process-oriented approach is more suitable for understanding changes over time, as opposed to variance-focused research. Trebilcock also discusses the significance of open collaboration in managing supply chain change.

 

Wang and Chen’s abstract delves into the optimization of intelligent logistics and supply chain management using edge computing and the Internet of Things. They employ the flower pollination algorithm for positioning in the logistics system and use the XGBoost model for predicting user information. The results indicate improved accuracy and shorter waiting times for intelligent logistics systems. The research highlights the impact of intelligent logistics systems on the logistics industry.

Greer and Ford’s abstract focuses on supply chain management change processes and their unique characteristics. The study uses empirical data and compares supply chain management change to non-supply chain management change, drawing from Lewin’s change process conceptualization. It emphasizes the need for further investigation into monitoring and control of supply chain management change.

Jing-Yan et al.’s abstract addresses the need for digital transformation in the pharmaceutical supply chain in the context of Industry 4.0. The study explores the impact of digital transformation on sustainable supply chain performance, with a focus on information sharing and traceability as mediators. The results suggest that digital transformation positively impacts supply chain performance, with traceability playing a significant mediating role.

Gelphman discusses the challenges faced by manufacturers and distribution chains in evaluating and maintaining their supply chain operations. The abstract emphasizes the importance of open collaboration among supply chain partners and the need for change acceptance by management. Successful supply chain management is seen as a source of competitive advantage and investor value.

Meier’s abstract reviews academic contributions on the impact of additive manufacturing on supply chains and discusses possible scenarios for future supply chain design. It highlights the uncertainty of future developments in additive manufacturing and suggests that industries may adopt it at different intensities due to technology limitations and corporate culture.

Cai and Hao’s abstract explores the adoption of blockchain technology in supply chain management to mitigate supply chain risks. The study focuses on the impact of perceived benefits of blockchain, such as traceability and transparency, on supply chain resilience and responsiveness. It underscores the importance of supply chain risk management and new technologies in this context.

Zhao Hailei’s abstract discusses the use of BP neural network technology to study green supply chain finance in a sustainable ecological environment. The research focuses on risk management and the evaluation of green finance through BP neural network methods. The results indicate the positive impact of BP neural networks on green financial risk management.

 

Dewhurst et al. examine the Y2K phenomenon as an environmental shock to organizations and their supply chains. The study looks at managerial responses, stockpiling, and supply chain management practices in the context of Y2K preparation. The research aims to provide lessons that can be applied to future environmental changes affecting supply chains.

 

 

 

Reference

1. Remko, v. H., Johnson, M., Godsell, J., & Birtwistle, A. (2010). Changing chains: Three case studies of the change management needed to reconfigure European supply chains.International Journal of Logistics Management, 21(2), 230-250. https://doi.org/10.1108/09574091011071933

 

2. Trebilcock, B. (2015). 3 State of Disruption: Technologies May Change Supply Chain Management in the Supply Chain.Supply Chain Management Review, 19(3), 26. https://www.proquest.com/trade-journals/3-state-disruption-technologies-may-change-supply/docview/1683366481/se-2

 

 

3. Wang T, Chen H, Dai R, Delong Z. Intelligent logistics system design and supply chain management under edge computing and internet of things. Computational Intelligence and Neuroscience: CIN. 2022;2022. https://www.proquest.com/scholarly-journals/intelligent-logistics-system-design-supply-chain/docview/2717516177/se-2. doi: https://doi.org/10.1155/2022/1823762.

 

4. Greer BM, Ford MW. MANA

GING CHANGE IN SUPPLY CHAINS: A PROCESS COMPARISON. Journal of Business Logistics. 2009;30(2):47-VII. https://www.proquest.com/scholarly-journals/managing-change-supply-chains-process-comparison/docview/212666420/se-2.

 

5. Jing-Yan, M., Shi, L., & Kang, T. (2023). The Effect of Digital Transformation on the Pharmaceutical Sustainable Supply Chain Performance: The Mediating Role of Information Sharing and Traceability Using Structural Equation Modeling.Sustainability, 15(1), 649. https://doi.org/10.3390/su15010649

 

6. Gelphman, M. (2003). The new change agent: Supply chain management.Wireless Design & Development, 11(8), 4. https://www.proquest.com/trade-journals/new-change-agent-supply-chain-management/docview/218928570/se-2

 

 

7. Meier, K. (2020). Additive manufacturing – driving massive disruptive change in supply chain management. [Additive manufacturing] Journal of Work-Applied Management, 12(2), 221-231. https://doi.org/10.1108/JWAM-05-2020-0024

 

8. Cai, C., Hao, X., Wang, K., & Dong, X. (2023). The Impact of Perceived Benefits on Blockchain Adoption in Supply Chain Management.Sustainability, 15(8), 6634. https://doi.org/10.3390/su15086634

 

9. Zhao, Hailei. 2023. “Risk Management of Supply Chain Green Finance Based on Sustainable Ecological Environment.”Sustainability 15(9):7707. doi: https://doi.org/10.3390/su15097707.

 

 

10. Dewhurst, F., Spring, M., & Arkle, N. (2000). Environmental change and supply chain management: a multi-case study exploration of the impact of Y2000.Supply Chain Management, 5(5), 245. https://doi.org/10.1108/13598540010350510