scholarly journals RISK MANAGEMENT STRATEGY AND SUPPLY CHAIN PERFORMANCE AMONG MANUFACTURING COMPANIES IN KENYA

2017 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Dr.David Kiarie ◽  
Dr. Patrick Ngugi ◽  
Dr. Kennedy Ogollah

Purpose: The purpose of this study was to determine risk management strategy and supply chain performance among manufacturing companies in KenyaMethodology: The study adopted a cross-section survey of descriptive nature. The target population comprised of the 412 manufacturing companies within Nairobi County that were registered members of KAM. The fisher et al formula for calculating the sample size was used to yield a sample size of199. Data was collected using questionnaires and analyzed using statistical package of social sciences (SPSS) version 21 as a tool of analysis. In trying to explain the relationship between different variables in the study, Odd ratio regression was adopted as an appropriate method of analyzing the relationship between multiple variables requiring simultaneous comparison.Results: The study findings revealed that the constructs of risk identification management strategy combined together influenced supply chain performance as supported by a p value of 0.000.Further, most of the companies had risk analysis and evaluation management strategy in place. The study also concluded that the odds of observing better lead time and odds of improved quality were higher for those companies that conducted whole life costing of suppliers (p value- 0.023) and internal controls of suppliers (p value- 0.049)Policy recommendation: the study recommended that manufacturing companies should put in place a risk analysis and evaluation management strategy to enhance supply chain performance. In particular, companies should consider conducting whole life costing of suppliers and also internal quality of suppliers.

2017 ◽  
Vol 1 (1) ◽  
pp. 1-21
Author(s):  
Dr.David Kiarie ◽  
Dr. Patrick Ngugi ◽  
Dr. Kennedy Ogollah

Purpose: The purpose of this study was to determine risk management strategy and supply chain performance among manufacturing companies in KenyaMethodology: The study adopted a cross-section survey of descriptive nature. The target population comprised of the 412 manufacturing companies within Nairobi County that were registered members of KAM. The fisher et al formula for calculating the sample size was used to yield a sample size of199. Data was collected using questionnaires and analyzed using statistical package of social sciences (SPSS) version 21 as a tool of analysis. In trying to explain the relationship between different variables in the study, Odd ratio regression was adopted as an appropriate method of analyzing the relationship between multiple variables requiring simultaneous comparison.Results: The study findings revealed that the constructs of risk identification management strategy combined together influenced supply chain performance as supported by a p value of 0.000.Further, most of the companies had risk analysis and evaluation management strategy in place. The study also concluded that the odds of observing better lead time and odds of improved quality were higher for those companies that conducted whole life costing of suppliers (p value- 0.023) and internal controls of suppliers (p value- 0.049)Policy recommendation: the study recommended that manufacturing companies should put in place a risk analysis and evaluation management strategy to enhance supply chain performance. In particular, companies should consider conducting whole life costing of suppliers and also internal quality of suppliers.


2017 ◽  
Vol 1 (2) ◽  
pp. 101-118
Author(s):  
Dr.David Kiarie ◽  
Dr. Patrick Ngugi ◽  
Dr. Kennedy Ogollah

Purpose: The purpose of this study was to determine relationship between risk identification management strategy and supply chain performance among manufacturing companies in KenyaMethodology:The study adopted a cross-section survey of descriptive nature .The target population comprised of the 412 manufacturing companies within Nairobi County that were registered members of KAM. The fisher et al formula for calculating the sample size was used to yield a sample size of199. Data was collected using questionnaires and analyzed using statistical package of social sciences (SPSS) version 21 as a tool of analysis.Results: The study findings revealed that the constructs of risk identification management strategy combined together influenced supply chain performance as supported by a p value of 0.000.)Policy recommendation: the study recommended that manufacturing companies should put in place a risk analysis and evaluation management strategy to enhance supply chain performance. In particular, companies should consider conducting whole life costing of suppliers and also internal quality of suppliers.


2017 ◽  
Vol 1 (2) ◽  
pp. 82
Author(s):  
Dr.David Kiarie ◽  
Dr. Patrick Ngugi ◽  
Dr. Kennedy Ogollah

Purpose: The purpose of this study was to determine therelationship between hedging risk management strategy and supply chain performance among manufacturing companies in KenyaMethodology:The study adopted a cross-section survey of descriptive nature .The target population comprised of the 412 manufacturing companies within Nairobi County that were registered members of KAM. The fisher et al formula for calculating the sample size was used to yield a sample size of199. Data was collected using questionnaires and analyzed using statistical package of social sciences (SPSS) version 21 as a tool of analysis.Results: The study findings revealed that the companies that increased buffer stock at various levels in the supply chain. Increasing buffer stock at various levels in the supply chain resulted to decreased lead time, improved quality and reduced cost. Results also showed that most of the companies ‘conducted reduce order cycle times. Conducting reduce order cycle times resulted to decreased lead time, improved quality and reduced cost. Further, the results revealed that most of the companies shared supply chain costs with partners. Sharing supply chain costs with partners resulted to decreased lead time, improved quality and reduced cost.Policy recommendation:the study recommended that manufacturing companies should put in place a risk analysis and evaluation management strategy to enhance supply chain performance. In particular, companies should consider conducting whole life costing of suppliers and also internal quality of suppliers.


2017 ◽  
Vol 1 (2) ◽  
pp. 101
Author(s):  
Dr.David Kiarie ◽  
Dr. Patrick Ngugi ◽  
Dr. Kennedy Ogollah

Purpose: The purpose of this study was to determine relationship between risk identification management strategy and supply chain performance among manufacturing companies in KenyaMethodology:The study adopted a cross-section survey of descriptive nature .The target population comprised of the 412 manufacturing companies within Nairobi County that were registered members of KAM. The fisher et al formula for calculating the sample size was used to yield a sample size of199. Data was collected using questionnaires and analyzed using statistical package of social sciences (SPSS) version 21 as a tool of analysis.Results: The study findings revealed that the constructs of risk identification management strategy combined together influenced supply chain performance as supported by a p value of 0.000.)Policy recommendation: the study recommended that manufacturing companies should put in place a risk analysis and evaluation management strategy to enhance supply chain performance. In particular, companies should consider conducting whole life costing of suppliers and also internal quality of suppliers.


2017 ◽  
Vol 1 (2) ◽  
pp. 119
Author(s):  
Dr.David Mburu Kiarie

Purpose: The purpose of this study was to determine the relationship between risks monitoring and control management strategy and supply chain performance among manufacturing companies in Kenya.Methodology:The study adopted a cross-section survey of descriptive nature .The target population comprised of the 412 manufacturing companies within Nairobi County that were registered members of KAM. The fisher et al formula for calculating the sample size was used to yield a sample size of199. Data was collected using questionnaires and analyzed using statistical package of social sciences (SPSS) version 21 as a tool of analysis.Results: The study findings revealed that the constructs of risk identification management strategy combined together influenced supply chain performance as supported by a p value of 0.000.Further, most of the companies had risk analysis and evaluation management strategy in place.Policy recommendation:the study recommended that manufacturing companies should put in place a risk analysis and evaluation management strategy to enhance supply chain performance.


2017 ◽  
Vol 1 (2) ◽  
pp. 119-135
Author(s):  
Dr.David Mburu Kiarie

Purpose: The purpose of this study was to determine the relationship between risks monitoring and control management strategy and supply chain performance among manufacturing companies in Kenya.Methodology:The study adopted a cross-section survey of descriptive nature .The target population comprised of the 412 manufacturing companies within Nairobi County that were registered members of KAM. The fisher et al formula for calculating the sample size was used to yield a sample size of199. Data was collected using questionnaires and analyzed using statistical package of social sciences (SPSS) version 21 as a tool of analysis.Results: The study findings revealed that the constructs of risk identification management strategy combined together influenced supply chain performance as supported by a p value of 0.000.Further, most of the companies had risk analysis and evaluation management strategy in place.Policy recommendation:the study recommended that manufacturing companies should put in place a risk analysis and evaluation management strategy to enhance supply chain performance.


2017 ◽  
Vol 1 (2) ◽  
pp. 82-100
Author(s):  
Dr.David Kiarie ◽  
Dr. Patrick Ngugi ◽  
Dr. Kennedy Ogollah

Purpose: The purpose of this study was to determine therelationship between hedging risk management strategy and supply chain performance among manufacturing companies in KenyaMethodology:The study adopted a cross-section survey of descriptive nature .The target population comprised of the 412 manufacturing companies within Nairobi County that were registered members of KAM. The fisher et al formula for calculating the sample size was used to yield a sample size of199. Data was collected using questionnaires and analyzed using statistical package of social sciences (SPSS) version 21 as a tool of analysis.Results: The study findings revealed that the companies that increased buffer stock at various levels in the supply chain. Increasing buffer stock at various levels in the supply chain resulted to decreased lead time, improved quality and reduced cost. Results also showed that most of the companies ‘conducted reduce order cycle times. Conducting reduce order cycle times resulted to decreased lead time, improved quality and reduced cost. Further, the results revealed that most of the companies shared supply chain costs with partners. Sharing supply chain costs with partners resulted to decreased lead time, improved quality and reduced cost.Policy recommendation:the study recommended that manufacturing companies should put in place a risk analysis and evaluation management strategy to enhance supply chain performance. In particular, companies should consider conducting whole life costing of suppliers and also internal quality of suppliers.


Author(s):  
Mariam El Hiri ◽  
Abdelali En-Nadi ◽  
Anas Chafi

The big challenge for each company is the implementation of an appropriate risk management strategy. Through this work, we seek to draw up an inventory of Moroccan companies supply chain. The objective is to identify the main risks, their relationship with the performance of the supply chain and to establish an overview of the risk management systems. For this reason, a research model was developed and concretized by quantitative data collected from 29 Moroccan companies. The analysis of the data show that the performance of the supply chain is strongly influenced by the importance of supply chain risk in particular the supplier and demand risks, and leads to insist on the importance of integrating a device adapted to the management of these Risks, especially in the upstream part of the supply chain.


2021 ◽  
Vol 10 (2) ◽  
pp. 17-32
Author(s):  
Pritee Ray

Agricultural supply chain (ASC) plays a vital role for sustainability as it is the main source of food supply. ASC encounters more sources of risk due to seasonality, perishability, and weather conditions, which makes the global food security system complex. This paper develops an optimization model for a perishable product supply chain to decide the optimal risk management strategy that maximizes the decision maker's expected profit under demand and price uncertainty. A base-case scenario is considered to show the impact of risk management strategy on performance improvement. The expected profit of the decision maker is obtained for different combination of strategies, and sensitivity analysis is performed to show the impact of perishability on the percentage of improvement from the base case scenario. The results show that backup supplier strategy is very effective during the yield disruption, but it is not as effective during harvest disruption. Hence, a single approach is inadequate to provide solution in all types of risk scenarios; thus, the combination of approaches is most effective.


2019 ◽  
Vol 69 (6) ◽  
pp. 1205-1225 ◽  
Author(s):  
Scott Dellana ◽  
John F. Kros ◽  
Mauro Falasca ◽  
William J. Rowe

Purpose The purpose of this paper is to explore the mediating effect of supply chain risk management integration (RMI) on the relationship between supply chain logistics performance (LP) and supply chain cost performance (CP), as well as on the relationship between LP and supply chain service performance (SP). The impact of CP and SP on overall firm performance (FP) is also explored. ISO 9001-certified firms and non-certified firms are assessed to determine whether superior risk-based thinking, as required in the latest ISO 9001 standard, has a positive impact on the different relationships. Design/methodology/approach A theoretical model is developed and tested based on the participation of 140 supply chain managers. The proposed structural equation model positively relates LP, RMI, CP and SP. RMI is positively linked to CP and SP, while CP and SP are positively related to overall FP. Two subsamples (a group of 63 ISO 9001-certified firms and a group of 77 non-certified firms) are used to evaluate the model. Findings For certified and non-certified firms, LP is positively related to RMI, CP and SP, and SP and CP are positively related to FP. However, for certified firms, RMI partially mediates the relationship of LP with both CP and SP, while for non-certified firms, RMI does not mediate these relationships. The findings suggest that ISO 9001-certified firms are able to leverage RMI efforts to impact positively on supply chain performance, whereas non-certified firms are not. Research limitations/implications The study findings are based on the perceptions of managers. Even though the majority of the 63 certified firms included in this study were ISO 9001:2015 certified, the model results do not differentiate between companies certified to the 2008 version of the standard and the 2015 version (which specifically requires demonstration of risk-based thinking). Practical implications This study suggests that ISO 9001 provides a framework for risk management processes and collaboration with supply chain partners to positively impact the relationship of LP with cost and SP. Originality/value This is one of the first studies to characterize the benefits of using a structured approach for risk-based thinking that is associated with ISO 9001.


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