Inventory management decisions for effective inventory management in the South African automotive component manufacturing industry: pre-and since COVID-19
- Authors: Delport, Jason
- Date: 2022-12
- Subjects: Inventory management , Automobile industry and trade
- Language: English
- Type: Master's theses , Theses
- Identifier: http://hdl.handle.net/10948/59511 , vital:62145
- Description: Globalisation has enabled the automotive industry to source various automotive products worldwide. It assisted in increasing the economic growth of countries as it allowed the flow of goods and capital between countries and created many employment opportunities locally. Emerging markets, especially Africa, forms a pivotal part of the global automotive industry. The South African automotive industry as the largest manufacturing and third largest economic sector in South Africa, has been acknowledged by government as a prime source of economic growth. The South African manufacturing businesses, in particular the automotive component manufactures (ACMs) are reliant on inventory for automotive manufacturing. In 2019, the world was hit by the Coronavirus virus outbreak known as COVID-19, which became a global health pandemic that significantly affected the global economy. The pandemic and lockdown measures implemented, seriously affected the automotive industry, in particular inventory management as it led to raw materials inventory shortages due to delivery delays. Therefore, the primary objective of this study was to investigate the inventory management decisions influencing effective inventory management in the South African automotive component manufacturing (SAACM) industry prior to Covid-19 and whether and how it changed since the Covid-19 pandemic. The comprehensive literature review identified four inventory management decisions as independent variables (inventory forecasting, inventory storage, inventory control and inventory staff capabilities management) and effective inventory management as the dependent variable in the proposed hypothesised model. The model was tested to establish the influence of the identified four inventory management decisions on effective inventory management in ACMs prior to Covid-19 and then again since Covid-19. A quantitative research approach was followed to collect data required for the hypothesis testing. Nonprobability sampling in particular judgemental sampling was utilised for this study by selecting respondents employed by ACMs in South Africa as logistics managers, supply chain managers, production supervisors, master production schedulers, cycle count operators and warehouse staff. A selfadministered internet-based questionnaire was used to obtain the data from the target sample comprising 200 respondents, of which 162 were usable for further statistical analysis. Data was analysed first for prior to and then for since Covid-19 using Statistica Version 14 computer software. Exploratory factor analysis (EFA) was used to extract the variables and validate the measuring instrument. The Cronbach's alpha values for reliability were confirmed for each of the variables identified in the two sets of EFAs. All four independent variables (inventory v management decisions) and the dependent variable (effective inventory management) for prior to as well as since Covid-19 were found to be valid and reliable and retained for further analyses. The results of the Pearson product moment correlation coefficients reported mostly weak and moderate associations between variables for both prior to and since Covid-19. The results of the multiple regression analysis (MRA) for prior to Covid-19 found four statistically significant relationships between the four independent variables - inventory forecasting management, inventory storage management, inventory control management and inventory staff capabilities management and the dependent variable effective inventory management. The results of the MRA for since Covid-19 found two statistically significant relationships between two independent variables inventory forecasting management and inventory resource management and the dependent variable effective inventory management. The tested hypothesised model provides a framework for further testing in future ACM inventory management studies in other countries. Business managers and inventory management staff of global ACMs can use it as a guide for effective inventory management; on which specific inventory management decisions to always pay attention to and, which inventory management decisions to pay attention to when a long-lasting pandemic occurs such as Covid-19. It is recommended that regardless of the Covid-19 pandemic, inventory managers in ACMs in South Africa should consider inventory forecasting management methods such as demand forecasting, determining the economic order quantity (EOQ) for all inventory item orders and materials requirement planning (MRP). They should also use an inventory information sharing system and inventory replenishment procedure to ensure inventory is managed effectively. During a prolonged pandemic such as Covid-19, inventory managers in ACMs in South Africa should pay particular attention to inventory resource management specifically regarding re-order inventory levels and classifying all inventory items according to the importance of using ABC analysis. They should further offer employees inventory training to remain abreast of new inventory developments in the industry and for career advancement. , Thesis (MCom) -- Faculty of Business and Economics Science, School of Applied Accounting, 2022
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- Date Issued: 2022-12
Information technology (IT) measures needed In the automotive industry to prepare for a pandemic
- Authors: Marwayi, Sisanda
- Date: 2022-04
- Subjects: Information technology , Automobile industry and trade
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10948/57864 , vital:58292
- Description: Information Technology is the application of technology to solve business or organisational problems on a broad scale. The COVID-19 pandemic has brought a standstill to many businesses, including that of the automotive industry, where production was brought to halt, car sales plummeted and automotive industry employees were forced to work remotely. This study sought to understand the measures needed to be taken by the automotive industry in preparation for a pandemic. This study followed a deductive approach and the use of surveys was selected as a data collection tool. At the time of the study, the study population was permanently employed automotive industry employees based in Nelson Mandela Bay, working in administrative departments. These employees had access to ICT tools provided by the targeted company. The study aimed to investigate the IT measures needed by the automotive industry in preparation for a pandemic. More specifically, the study investigated IT infrastructure, financial support and communication, as well as IT skills and training, needed by the automotive industry in the Nelson Mandela Bay area for successful remote working. The empirical results were obtained from 127 automotive industry employees. The aim was to determine the extent of Remote Work Assessment in the Nelson Mandela Bay automotive industry and whether IT infrastructure, Communication, Financial support, IT skills, IT personnel support and IT training were the strongest determinants of measuring IT needs in preparation for a pandemic. The findings of the study indicated that IT infrastructure, Communication, IT skills, IT personnel support and IT training were important determinants of Remote Work Assessment. The study also revealed that only financial support was deemed as an insignificant determinant of Remote Work Assessment. Furthermore, recommendations were made to automotive industry leaders and management to facilitate improved working conditions with government. This can lead to significantly better forecasting and vi measurement of IT needs for future pandemic preparation in the automotive industry in the Nelson Mandela Bay area. , Thesis (MA) -- Faculty of Business and Economic Sciences, 2022
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- Date Issued: 2022-04
Technical skills and knowledge transfer for an aging workforce in the automotive industry
- Authors: Mahlalela, Gaven
- Date: 2022-04
- Subjects: Automobile industry and trade , Transportation -- Automotive
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10948/57771 , vital:58248
- Description: This study highlighted the importance of technical skills, knowledge transfer and its drivers. Organisations face a dilemma when incumbent tacit knowledge owners vacate employment without transferring invaluable intellectual property to other stakeholders (Khumalo, 2012). Once this knowledge is lost, it may be impossible to recover and difficult to hide from competitors (De Long, 2004). Knowledge transfer among employees is a critical enabler of organisational learning. In the context of the South African automotive industry, the volatility of the industry has seen many Original Equipment Manufacturers (OEM) and their suppliers shedding jobs. Furthermore, the replacement of the old automotive training board by the Sector of Education and Training (SETA) has created more complex challenges. Automotive companies are struggling to absorb the financial burden that comes with training skills transfer, due to the reduced workforce that is overloaded by work to cope in the current economic climate. The drivers of technical skills and knowledge transfer were investigated in a particular automotive company in Port Elizabeth, South Africa. A mail survey was directed to 168 technical employees in an automotive manufacturing plant. The survey tested the dependent variable (technical skills and knowledge transfer), and independent variables were its drivers (management of scarce skills, succession planning, trainee characteristics, training design and work environment). The survey had 50 questionnaire items. Statistical analysis was used to analyse the research questions through descriptive statistics, Pearson correlation and multiple regression analysis. The empirical results found that all of the independent variables showed positive correlations with the dependent variable, however succession planning, followed by work environment showed the most significant relationship with technical skills and knowledge transfer in an automotive organisation. , Thesis (MA) -- Faculty of Business and Economic science, 2022
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- Date Issued: 2022-04