A framework to measure supply chain management efficacy in humanitarian supply environments
- Authors: Linford, Pierre
- Date: 2015
- Subjects: Humanitarian intervention , Business logistics
- Language: English
- Type: Thesis , Doctoral , DBA
- Identifier: http://hdl.handle.net/10948/8155 , vital:25131
- Description: Supply chain management in the for-profit commercial environment is a broad, far-reaching field of study, impacting on a society’s standard of living. Commercial supply chain management is the science of balancing customer service levels with least total costs. In other words, the for-profit supply chain management practitioner is concerned with customer service levels, consumer value, shareholder value, total cost optimisation and ultimately maximising long term sustainable return on investment. Commercial supply chain management differs from military supply chain management in that the latter also focuses on service delivery, but the cost is almost irrelevant. In military operations, successful results (winning the battle) far surpass the total cost parameter or the return on investment. One of the major differentiating factors between commercial supply chain management (CSCM) in the for-profit theatre and humanitarian supply chain management (HSCM) in the not-for-profit supply environments hinges on strategic intent and how to measure success. In CSCM, return on investment (ROI) is key and in HSCM, the ability to create impact becomes paramount. Regarding spend, both CSCM and HSCM are concerned with optimising operational spend, optimal utilisation of capital goods and infrastructure as well as minimising the cost of goods, works and services. Commercial supply chain managers want to spend as little as possible on operational expenses similarly to their humanitarian counterparts but humanitarian supply chain managers are also concerned about underspending of donor funded programming. Humanitarian programming often happens under difficult and dangerous circumstances. This requires a special cadre of professionals who are willing to serve the most vulnerable without exploitation and are able to deliver value often with limited or even broken infrastructure, unreliable supply and under insecure conditions. Humanitarian supply chain management leadership requires a DBA thesis balanced approach between long term strategic views whilst managing the short term outcomes. Also, humanitarian leadership needs to balance decision-making between long term strategic interventions and the ability, maturity and cost structures at functional and executional levels. This conundrum is the fundamental difference between commercial supply chain management and humanitarian supply chain management. Once one understands and respects these nuances, one can measure performance and reward appropriate corrective behaviour. Zig Ziglar once said: “If you aim at nothing, you will hit it every time”. The question that has been asked for so long has been “how to measure supply chain management efficacy in humanitarian supply environments?” This study addresses this question of developing a framework to measure supply chain efficacy in humanitarian supply environments with the view to create an enabling environment within which service levels could enhance the impact of donor funding whilst the needs of intended beneficiaries are better served. During field research, ten key focus areas and sixty-five supply chain management elements were identified. These sixty-five elements were tested via two surveys making use of the Delphi technique. Four of the sixty-five SCM elements were eliminated following the second survey due to high disagreement between the respondents, and a further two were eliminated based on expert opinion feedback from the respondents leaving fifty-nine elements being significantly important for inclusion in the framework. Three additional elements were identified by the respondents but not empirically verified and therefore not included in the proposed frameworks but could be included in future research. Fifty-seven of the sixty-five elements can be directly controlled by the SCM function. However, four of these fifty-seven elements were eliminated during the second survey and a further two were eliminated reviewing the feedback from respondents leaving fifty-one elements under the direct control of the SCM function.
- Full Text:
- Date Issued: 2015
- Authors: Linford, Pierre
- Date: 2015
- Subjects: Humanitarian intervention , Business logistics
- Language: English
- Type: Thesis , Doctoral , DBA
- Identifier: http://hdl.handle.net/10948/8155 , vital:25131
- Description: Supply chain management in the for-profit commercial environment is a broad, far-reaching field of study, impacting on a society’s standard of living. Commercial supply chain management is the science of balancing customer service levels with least total costs. In other words, the for-profit supply chain management practitioner is concerned with customer service levels, consumer value, shareholder value, total cost optimisation and ultimately maximising long term sustainable return on investment. Commercial supply chain management differs from military supply chain management in that the latter also focuses on service delivery, but the cost is almost irrelevant. In military operations, successful results (winning the battle) far surpass the total cost parameter or the return on investment. One of the major differentiating factors between commercial supply chain management (CSCM) in the for-profit theatre and humanitarian supply chain management (HSCM) in the not-for-profit supply environments hinges on strategic intent and how to measure success. In CSCM, return on investment (ROI) is key and in HSCM, the ability to create impact becomes paramount. Regarding spend, both CSCM and HSCM are concerned with optimising operational spend, optimal utilisation of capital goods and infrastructure as well as minimising the cost of goods, works and services. Commercial supply chain managers want to spend as little as possible on operational expenses similarly to their humanitarian counterparts but humanitarian supply chain managers are also concerned about underspending of donor funded programming. Humanitarian programming often happens under difficult and dangerous circumstances. This requires a special cadre of professionals who are willing to serve the most vulnerable without exploitation and are able to deliver value often with limited or even broken infrastructure, unreliable supply and under insecure conditions. Humanitarian supply chain management leadership requires a DBA thesis balanced approach between long term strategic views whilst managing the short term outcomes. Also, humanitarian leadership needs to balance decision-making between long term strategic interventions and the ability, maturity and cost structures at functional and executional levels. This conundrum is the fundamental difference between commercial supply chain management and humanitarian supply chain management. Once one understands and respects these nuances, one can measure performance and reward appropriate corrective behaviour. Zig Ziglar once said: “If you aim at nothing, you will hit it every time”. The question that has been asked for so long has been “how to measure supply chain management efficacy in humanitarian supply environments?” This study addresses this question of developing a framework to measure supply chain efficacy in humanitarian supply environments with the view to create an enabling environment within which service levels could enhance the impact of donor funding whilst the needs of intended beneficiaries are better served. During field research, ten key focus areas and sixty-five supply chain management elements were identified. These sixty-five elements were tested via two surveys making use of the Delphi technique. Four of the sixty-five SCM elements were eliminated following the second survey due to high disagreement between the respondents, and a further two were eliminated based on expert opinion feedback from the respondents leaving fifty-nine elements being significantly important for inclusion in the framework. Three additional elements were identified by the respondents but not empirically verified and therefore not included in the proposed frameworks but could be included in future research. Fifty-seven of the sixty-five elements can be directly controlled by the SCM function. However, four of these fifty-seven elements were eliminated during the second survey and a further two were eliminated reviewing the feedback from respondents leaving fifty-one elements under the direct control of the SCM function.
- Full Text:
- Date Issued: 2015
Factors affecting supply chain integration in public hospital pharmacies in Kenya
- Authors: Kamau, George Michungu
- Date: 2015
- Subjects: Supply and demand , Materials management , Business logistics
- Language: English
- Type: Thesis , Doctoral , DBA
- Identifier: http://hdl.handle.net/10948/7915 , vital:24321
- Description: The purpose of this study was to develop and empirically test the Supply Chain Integration Framework (SCI framework) in order to develop a framework to address the inefficiencies experienced in the public hospital pharmacies’ Supply Chain (SC) in Kenya. Supply Chain Management (SCM) can be regarded as a vibrant business entity that is changing and evolving continually because of constant changes in technology, competition and customer demands. The study investigated and analysed how the independent variables, namely SCI initiatives, performance improvement drivers, organisation environmental forces, workforce and management support, financial factors, flow and integration, regulatory framework and information sharing and technology influenced the SCI. The SCI was categorised into three components namely: customer order fulfilment, supplier collaboration and dedicated SC as the dependent variable. The literature reviewed established that globalisation and intensive worldwide competition, alongside technological developments, creates a completely new operating environment for organisations. The researcher reviewed various models and theories related to SCI which include systems theory, value chain models and value ecology models among others. An SCI framework was then developed to capture the interacting variables within the SCI network that could be adopted for the public hospital pharmacies in Kenya. The study was conducted using a survey questionnaire (Annexure B) that comprised both open and closed ended questions that were distributed to managers in public hospitals and pharmacies in Kenya. The population for the survey was 154 public hospital pharmacies in Kenya, with the final sample comprised of 280 respondents. The study was conducted using a survey questionnaire (Annexure B) that comprised both open and closed ended questions that were distributed to 325 respondents in 154 public hospitals and pharmacies in Kenya. The population for the survey was 154 public hospital pharmacies in Kenya, with the final sample comprised of 280 respondents. Exploratory factor analysis was used to ascertain the validity of the measuring instrument and the Cronbach alpha coefficients were used to measure the reliability of the measuring instruments. Key preliminary tests performed were the Kaiser-Meyer-Olkin test (KMO test) of sample adequacy, the Bartlett’s test of sphericity and the Kolmogorov-Smirnov test (Z-Statistic test) for normality and multi-collinearity diagnostic. Analysis of Variance (ANOVA) and multiple linear regressions were the main statistical procedures used to test the regression model fit and the significance of the relationships hypothesised among various variables in the study. Statistical softwares, namely Statistica 10 (2010) and Statistical Package for Social Sciences (SPSS) Version 18, were used to analyse quantitative data. The study identified five statistically significant relationships between customer order fulfilment and workforce and management support, financial factors, flow and integration, information sharing and technology, supplier collaborations and dedicated SCI. In addition, a total of six statistically significant relationships exist between the supplier collaborations and SCI initiatives i.e. performance improvement drivers, workforce and management support, financial factors, flow and integration, information sharing and technology adoption as well as dedicated SCI. Furthermore, four statistically significant relationships were found between dedicated SCI and SCI initiatives, workforce and management support, financial factors, flow and integration, information sharing and technology adoption.
- Full Text:
- Date Issued: 2015
- Authors: Kamau, George Michungu
- Date: 2015
- Subjects: Supply and demand , Materials management , Business logistics
- Language: English
- Type: Thesis , Doctoral , DBA
- Identifier: http://hdl.handle.net/10948/7915 , vital:24321
- Description: The purpose of this study was to develop and empirically test the Supply Chain Integration Framework (SCI framework) in order to develop a framework to address the inefficiencies experienced in the public hospital pharmacies’ Supply Chain (SC) in Kenya. Supply Chain Management (SCM) can be regarded as a vibrant business entity that is changing and evolving continually because of constant changes in technology, competition and customer demands. The study investigated and analysed how the independent variables, namely SCI initiatives, performance improvement drivers, organisation environmental forces, workforce and management support, financial factors, flow and integration, regulatory framework and information sharing and technology influenced the SCI. The SCI was categorised into three components namely: customer order fulfilment, supplier collaboration and dedicated SC as the dependent variable. The literature reviewed established that globalisation and intensive worldwide competition, alongside technological developments, creates a completely new operating environment for organisations. The researcher reviewed various models and theories related to SCI which include systems theory, value chain models and value ecology models among others. An SCI framework was then developed to capture the interacting variables within the SCI network that could be adopted for the public hospital pharmacies in Kenya. The study was conducted using a survey questionnaire (Annexure B) that comprised both open and closed ended questions that were distributed to managers in public hospitals and pharmacies in Kenya. The population for the survey was 154 public hospital pharmacies in Kenya, with the final sample comprised of 280 respondents. The study was conducted using a survey questionnaire (Annexure B) that comprised both open and closed ended questions that were distributed to 325 respondents in 154 public hospitals and pharmacies in Kenya. The population for the survey was 154 public hospital pharmacies in Kenya, with the final sample comprised of 280 respondents. Exploratory factor analysis was used to ascertain the validity of the measuring instrument and the Cronbach alpha coefficients were used to measure the reliability of the measuring instruments. Key preliminary tests performed were the Kaiser-Meyer-Olkin test (KMO test) of sample adequacy, the Bartlett’s test of sphericity and the Kolmogorov-Smirnov test (Z-Statistic test) for normality and multi-collinearity diagnostic. Analysis of Variance (ANOVA) and multiple linear regressions were the main statistical procedures used to test the regression model fit and the significance of the relationships hypothesised among various variables in the study. Statistical softwares, namely Statistica 10 (2010) and Statistical Package for Social Sciences (SPSS) Version 18, were used to analyse quantitative data. The study identified five statistically significant relationships between customer order fulfilment and workforce and management support, financial factors, flow and integration, information sharing and technology, supplier collaborations and dedicated SCI. In addition, a total of six statistically significant relationships exist between the supplier collaborations and SCI initiatives i.e. performance improvement drivers, workforce and management support, financial factors, flow and integration, information sharing and technology adoption as well as dedicated SCI. Furthermore, four statistically significant relationships were found between dedicated SCI and SCI initiatives, workforce and management support, financial factors, flow and integration, information sharing and technology adoption.
- Full Text:
- Date Issued: 2015
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