Risk Management in Logistics Support Technology for the Automotive Industry - Research Proposal Example

Dissertation Proposal Risk Management in Logistics Support Technology for the Automotive Industry Table of Contents Table of Contents 2 Rationale and Discussion 3 Topic Aims and Objectives 4 Preliminary Literature Review 6 Risk Management 6 Logistics Support Technology 9 Risk Management and Logistics in the Automotive Industry 10 Preliminary Research Methodology 13 Research Approach 13 Qualitative Analysis 15 Quantitative Exploration 17 Preliminary Project Plan 17 Bibliography 19 Appendices B: Qualitative and Quantitative Case Study Draft Research Instruments 27 Rationale and Discussion Risk management and opportunity research are used to understand obstacles in reaching business goals. Risk management research proposes to identify significant risks and their potential for negative impact, and the values of opportunities that have an impact on the business decision-making process. Business opportunities also involve risks, it is important especially in the volatile automotive industry to examine what risks are viewed as opportunities, and what risks must be avoided to improve the logistic technology of an ever-changing supply chain. Kathleen DesMarteau (2005) recognizes the following key points as being a component of the risks and logistics management, which function as internal and external risks: Lost of capacity (plant is down, inventory theft) Loss of transportation (mode, infrastructure failure) Loss of supply (bankruptcy, quality failure) Loss of human resources (strikes, deaths, unavailable work force) Loss of communication (telephone lines down) Loss of demand (customer bankruptcy, quality failure) This project is to examine risk management in logistics technology as it relates to the business process of the automotive industry with the goal to produce a model for risk management. The project is descriptive in nature. It seeks to quantify the types of risks manufacturing management has experiences and models used to develop resolutions. This will be accomplished using experimental simulation models. Therefore, the problem statement is to: Identify risk management in logistic support technology as it applies to the automotive industry's manufacturing management with the goal of developing a model to overcome risks. The research question is: What are the impacts of risk management on the logistics supply technologies within the automotive industry Topic Aims and Objectives The topic of this research proposal is to explore risk management strategies and options for logistics support technology within the automotive industry. Risk management strategy is an important concept that allows a business operating within an industry to explore its research, development, and product release stages to reduce loss in operational and financial capacities. Logistics support technology is important for the automotive industry to maintain supply and meet demand. The automotive industry was chosen for this research proposal because it has multiple journals, magazines, corporate financial and stock information as well as strategy easily available to the public. Therefore, this research proposal has three main aims. The literature review will explore risk management, logistics support technology and the implications of these within the automotive industry. This will allow for a comprehensive look at the overall risk and product strategies employed by the automotive industry in general. The research methodology will have the objective of narrowing risk management strategy based on major manufacturing facilities. This will include international, national, and corporate stakeholder risk management. The second objective of the research is to describe logistics support technology including financial and technological information (as cost and return on investment) based on the major manufacturer's publicized information available from journals and corporate websites. The final objective of the research is to create a standardized model of risk management in logistics support technology using this information. This is an exploratory research proposal, outlined in Table 1: Proposal. Preliminary Literature Review The literature review has three main aims: to describe risk management; explore new product development; to apply implications to the automotive industry. The literature review uses a mixture of scholarly journals, textbooks, and automotive industry magazines to do so. Risk Management Kerzner (1998) first identifies risk planning as "the process of developing and documenting an organized, comprehensive and interactive strategy and methods for identifying and analyzing risk issues, developing risk handling plans, and monitoring how risks have changed", to the small business owner, this means that a step by step analysis of proposed risks and their possible changes is an inherent part of risk management. Secondly, he describes risk assessment as "the process of identifying and analyzing program areas and critical technical process risks to increase the likelihood of meeting cost, performance and schedule objectives", this will assist the risk management model by answering to the critical processes that create risks and the businesses' responses in those areas. The risk identification process is also described by Kerzner (1998) as "process of examining the program areas and each critical technical process to identify and document the associated risk". In risk identification, the internal and external factors are described and levelled according to their significance to the program area. For example, while a flood may be a risk, that is minimal if the business currently has a leaking roof. Risk analysis "is the process of examining each identified risk issue to estimate the likelihood of a risk and predict the impact on the project", this is the point at which the facility defines the proposed impact of the risk, in the flood example, the possibility of flooding would be compared to the urgency of the leaking roof in an analysis to decide which has the greater and most imminent impact on the business. (Kerzner, 1998) Finally, in the risk management strategy, Kerzner (1998) points out that continued monitoring, called risk monitoring, is "the process that systematically tracks and evaluates the performance of risk handling actions against established metrics throughout the acquisitions process and provides inputs to updating risk handling strategies, as appropriate". To the small business owner, this is the flexibility in strategy that allows it to be applied over the lifecycle of the business, with the future goal to continually minimize risks before they develop into crises. Webber (2006) identifies risk management as "the art of making decisions in the face of uncertainty", where an "analysis can help us understand the nature of that uncertainty and dimension of the risks we are taking, but they can also provide false comfort and engender undue confidence". Risk management strategies answer to the concerns of management by assessment and development of an applicable plan to overcome associated risks. This practice allows for proactive decision making to assess what can go wrong, their implications and impacts, and implement strategies to overcome risks. Systematic assessment and responses to risks is often used in management (Kerzner, 2006). This allows for management and organizations to have a risk management process that encompasses the identification, mitigation, and continuous tracking procedures that prevail through the business life cycle. Furthermore, a risk management strategy "includes both the process and implementation approach for the project", which allows a step by step answer to the defined issue. This is "of primary importance for achieving effective risk management", yet it is "generally far easier to improve a deficient process than remedy a problematic project environment that is unsupportive or hostile towards risk management" (Kerzner, 2006). Therefore, risk management strategy must be developed and employed before the risk becomes a 'deficient process' or crisis in a 'problematic environment'. Risk management is important "when the overall stakes are high and/or a great deal of uncertainty existsIt forces us to focus on the future where uncertainty exists and develop suitable plans of action to prevent potential issues from becoming problems and adversely impacting the project" (Kerzner, 2006). The risk management process, however, should be designed to do more than just identify potential risks. The process must also include a formal planning activity, analysis to estimate the likelihood and predict the impact on the project of identified risks, a handling strategy for selected risks, and the ability to monitor the progress in reducing these selected risks to the desired level. (Kerzner, 2006) It is important to validate the best practices in risk management in small business enterprise and how it impacts its success or failure. This currently assists business managers to know what the potential risks in the industry are, and to what degree the impact will be an opportunity or risk towards the business's needs. Logistics Support Technology In logistics support and supply chain management, the key issues are the unforeseen risks caused by lack of management strategies, especially in relationship to technology and communication as significant factors that inhibit the logistics support (Atkinson, 2004). Logistic support technology in industrial supply chains should include "a collaborative supply chain framework is composed of five connecting features of collaboration, namely collaborative performance system, information sharing, decision synchronisation, incentive alignment, and integrated supply chain processes" (Simatupang and Sridharan, 2005). Furthermore, the appropriate and integrative application of "Software as electronic commerce platform for manufacturers and wholesale distributors" with a focus on education and implementation of supply chain management software could have a significant impact on the manner that supply chains function within the companies (Karpinski 1999). Logistics support is necessary at the local, managerial, and corporate levels of the business. This concept has a significant impact on the various phases of the business process, where the changes that occur can be related to the flow of information and products (Desel & Erwin, 2000). Logistics support technology is ever changing and often used to renovate the managed and integrated processes that create a capable and viable business environment (Chan and Qi, 2003). The crucial tenants of logistics support technology is that it reduces tension between inter-organisational departments and business partners, particularly when there is friction within the logistics process (McCormack & Johnson, 2000). The business process specifically related to the main focus of the supply chain and communication in logistics support technology includes: (1)Further integration of activities between suppliers and customers across the entire supply chain; (2) on-going changes in supply chain needs and required flexibility from IT; (3) more mass customization of products and services leading to increasing assortments while decreasing cycle times and inventories; (4) the locus of the driver's seat of the entire supply chain and (5) supply chains consisting of several independent enterprises (Akkermans et al, 2003). The benefits of using strong logistics support technology to promote supply chain management needs are that it connects information management (McCormack & Johnson, 2000); promotes cost saving activities through efficiency and communication (Horvath, 2001), and reduces financial risk in unsuccessful supply chains (Cross, 2000). Risk Management and Logistics in the Automotive Industry In his book, Project Management, Dr. Kerzner (2006) identifies the process of risk management strategy as having several characteristics. Kerzner (2006) identifies risk planning as "the process of developing and documenting an organized, comprehensive and interactive strategy and methods for identifying and analyzing risk issues, developing risk handling plans, and monitoring how risks have changed". To logistics support, this means that a step by step analysis of proposed risks and their possible changes to operational and technical support must occur. The practical use of logistics support is further highlighted by risk assessment, where Kerzner (2006) describes risk assessment as "the process of identifying and analyzing program areas and critical technical process risks to increase the likelihood of meeting cost, performance and schedule objectives". In the practical application of logistics supportability, risk management is modelled as a response to the critical processes and "each critical technical process to identify and document the associated risk" (Kerzner, 2006). In relationship to the risk management component of logistics support, Wu et al, 2000) explains that automobile manufacturing organisations are currently being subjected to increased risk in business, regulatory and legislative pressures that require them to regularly re-engineer themselves. This means the viable automotive manufacturer must be able to effectively manage such activities, a manufacturing systems management (MSM) framework is required, which helps to define the necessary activities needed to regulate and optimise a manufacturing system as it progresses through its life cycle (Wu et al, 2000). MSM incorporates both risk management by regulating activities and logistics support through optimization of the manufacturing life cycle. The automotive industry original equipment manufacturers (OEM) respond to this supply chain management pressure by shifting from variant and multiple product lines to massive customisation (Graessler, 2003). Gran Svensson (2000) examines the vulnerability of supply chains in the automotive industry as being limited to the inbound logistic flow of OEM's. Svensson (2000) finds that when the OEM's supply chain logistics fail, it is mainly due to categories of disturbance and sources of disturbance stemming from the implementation of SCM technology rather than the technology itself. He (Svesson, 2000) finds that disturbance occurs directly as inadequate business process structure, and indirectly as gaps in the actual supply chain communication. The conclusion is that specific criteria of an inbound logistic flow indicate how vulnerable the logistics technology is according to the developed conceptual framework of risk management in response to that vulnerability (Svesson, 2000). Microsoft has developed automotive logistic support software solutions that help the automotive dealers' communication bilaterally with manufacturers (Automotive News, 2006). Software technology which allows business to business communications is essential to the vast automotive industry where constant logistics support is necessary to minimize technological and financial risks. The success of logistics supportive technology is founded on the ability to communicate throughout the internal organisation and external organisations. Accurate and relevant information sharing that is open and prompt can support the supplier-customer relationship (Anderson and Weitz, 1989). The market and end-consumer heavily drive the supplier-customer relationship in the automotive market. This creates a competition force that is almost unparalleled in other industries, and pressures supply chain managers to manufacture faster products with less lead times (Gress et al, 2005). This is further expanded by the use of technology in the logistics support risk management systems. For example, General Motors has been working jointly with software vendors to develop and implement a parallel version of simulation software for mass production analysis applications (Gress et al, 2005). By 2001, this technology was matured in the form of distributed memory processing of draw die simulations in a networked distributed memory computing environment (Gress et al, 2005). In 2004, this technology was refined to massively parallel processing and extended to line analysis through a dedicated computing environment (Gress et al, 2005). This supports the theory of logistics support technology as preparedness for risk management leads to improved manufacturing and processing, as well as continued and open communication (Mukhopadhyay, Kekre and Kalathur 1995). Preliminary Research Methodology Researching the risk management and logistics support technology raises the concern that much of the gathered information will be from secondary qualitative resources such as journal articles and major manufacturers, therefore is subjective to interpretation. This means that the approach to the information gathering must be defined as an inductive and descriptive phenomenology approach. The second component of the research methodology is the paradigm that will be utilized to explore the information. This was selected as the rational planning school, which focuses on strategic management to formulate a final recommendation. Research Approach The main methods of case study research are describing, explaining, understanding, criticising and analysing. Descriptive research is used when the research question is understood (Ghauri and Gronhaug, 2002). In the research approach, the data measurements are dependent on the obtainment of required information and the quality of the information. The outcome of the research therefore is dependent on the measurement procedures used in the collection of the data, and this in turn is dependent on the types of data collection (Ghauri and Gronhaug, 2002). McDonough and McDonough (1997) note that descriptive research aims to describe the significant events within the context itself (i.e. it provides a 'rich account' of the whole situation rather than minimising it) and that interventionist research intervenes by manipulating variables that can be identified and attempting to isolate the influence of one or more on the process. The descriptive research method is to gather information through natural observations, surveys and interviews. The research approach uses inductive reasoning to asses theories and information. In general, deductive research is theory-testing and inductive research is theory-generating. The inductive approach is used to build the theory from the data gathered to explore possible conclusions. Analyzing current theories and existing risk management strategy and logistic support technology methods, especially in relation to the usage, changes, and limitations of current automotive industry methods will be largely based on qualitative research, with some specific financial quantitative research included. This method will also be used to develop a framework for understanding the fundamental relationship between the risk management strategy and logistic support technology. Maxwell (1996) notes that the strengths of qualitative research derive from its inductive approach; it focuses on specific situations or people and its emphasis on words rather than numbers. He argues that the strategy starts from the research context and develops as the event unfolds. The study helps the investigator to understand the meaning of the situation the investigator is studying. The investigator allows the evidence he is studying to attach meaning to the situation through empirical information and observations (Creswell, 2003). The research approach in this study is inductive and descriptive phenomenology. These two paradigms of research allow the methodology to use a qualitative description to formulate a recommendation when the question is not strictly defined by quantitative measures. This approach was chosen because the objectives of this research is not to quantify amounts spent on marketing strategy, but rather to subjectively explore the automotive industry's risk management and logistics support technologies. Qualitative Analysis Qualitative analysis allows for an evaluation of the results to be made on the empirical views and new information to be gathered in a timely and inexpensive manner where other methods are based on information that is already in existence. The most common information sources of it are interviews, questionnaires, and observations etc. compared with quantitative approach, qualitative approach is more flexible but seems incapable in analysing research data. Collection of information will be by multiple sources to include documents and publications of major manufacturers within the automotive industry. This will allow the research to develop beyond core statistics into recorded responses. Case studies have been used in varied investigations, particularly in sociological studies, but increasingly, in instruction. Yin (1993) has identified some specific types of case studies: Exploratory, Explanatory, and Descriptive. This will be a descriptive case study analysis. The case study allows for a multi-perspective analysis, where multiple sources of data are examined to come to a conclusive meaning in relationship to the accounting methods. While the case study analysis has sometimes been considered a generalisation, Yin (1993) also describes this method as a template to develop empirical results, but asserts that there is a caution towards generalisation. This means that not all empirical evidence from a case study can be lumped into one category because of various factors, such as organisational behaviour and management strategy that would affect the outcome of the case study. Yin (1993) further identifies sources of evidence for data collection in the case study protocol: documentation, archival records, interviews, direct observation, participant observation, and physical artefacts. For this research, the primary focus is on documentation within the case study analysis. Qualitative document study will include case study analysis of the automotive industry because the case study is a helpful way of establishing valid and reliable evidence for the research process as well as presenting findings result from the research (Yin, 1993). In the case study, documentation on the usage of both risk management and logistics technology applications will be analysed. The result will come from an analysis of all-available qualitative experiences, processes and recommendations of major manufacturers. The case study is organised so that an approach towards a model of risk management and logistics support implementation can be developed in chronological order to portray the mannerisms of both methodologies. Quantitative Exploration The case study analysis of the automotive industry will include some quantitative exploration as the total cost and total revenue analysis relationships between risk management and logistics support based on information gained from review of annual corporate reports and industry reports. This is completed by specific data gathering from documented sources. By separating the physical components of the case study in relationship to cost, this research will be able to statistically define the cost controls of risk and logistics in the automotive industry with as little error as possible. After the quantitative information has been gathered and evaluated the qualitative and quantitative analysis will be entwined to define trends and concepts in the final documentation and proceeding recommendation. The evaluation method of the quantitative data will be based on the mathematical relationships of averages in cost and return on investment. This will also look for mathematical correlations between individual major manufacturers compared to the automotive industry. Lastly, the quantitative analysis will include an examination of trends and fluxes based on cost of logistics support and cost of risk management procedures. Preliminary Project Plan The project plan further seeks to modify the future of risk incidence and intensity of threats or opportunities and their possible impact on business performance within the logistics support technologies. The stated project plan components are adapted from Banham, (2004): Examine high-level oversight of risks on a portfolio basis, rather than discrete management by different risk overseers. (What are the risks of ineffective logistics, and what are the benefits of effective logistics) Assess risk across the enterprise instead of looking at it on a per-project basis. (What are the questions an organization needs to ask in developing a logistics technology) Assess the controls in place to handle each risk and identify any gaps. (Where does logistics technology fail in the automotive industry) Determine authority and responsibility and examine resource allocation. (Who is responsible for failures, and who can help avoid these-management, employees, corporate) Extract risk management in the logistics technology from qualitative case study analysis of the automotive industry. Examine quantitative financial, operational, and other costs involved with risk management and logistics technology (including software) in the automotive industry. Develop a model to monitor and evaluate the effectiveness of the organization's risk management within logistics support technologies. Bibliography Akkermans, Henk A., et al, (2003), 'The Impact of Erp on Supply Chain Management: Exploratory Findings from A European Delphi Study', European Journal of Operational Research, 146 (2), pp284. Anderson, E and Weitz,B, (1989), "Determinants of Continuity In Conventional Industrial Channel Dyads", Marketing Science, 8, pp 310-323. Atkinson, James (2004), "Connecting The Missing Link", Contract Journal, 425(6494), pp20-21. Automotive News (2006), "Microsoft Offers Dealers Plug-And-Play Software", Automotive News, 80 (6190), pp20-20. Banham, Russ (2004), "Enterprising Views Of Risk Management: Businesses Can Use Erm To Manage A Wide Variety Of Risks", Journal Of Accountancy, 197(6) pp 65. Chan, F., & Qi, Hj. (2003), "An Innovative Performance Measurement Method for Supply Chain Management", Supply Chain Management: An International Journal, 8 (3), pp 209-223. Creswell, J.W. (2003), "Research Design. Qualitative, Quantitative and Mixed Methods Approaches", Thousand Oaks, CA: Sage USA. Cross, G.J. (2000), "How E-Business Is Transforming Supply Chain Management", Journal of Business Strategy, 21(2), pp36-43. Desel, J. & Ervin, T. 2000. "Modelling, Simulation And Analysis Of Business Processes. Business Process Management" Berlin: Springer Verlag Desmarteau, Kathleen (2005), "Forum Explores Supply Chain's Future", Apparel Magazine, 47 (4), pp6-12. Ghauri, P.N., Grohaug, K. (2002) "Research methods in business studies: A practical guide", 1st edition, Prentice Hall, London. Graessler, Iris (2003) Impacts Of Information Management On Customised Vehicles And After-SalesServices. International Journal Of Computer Integrated Manufacturing, Oct2003, Vol. 16 Issue 7/8, P566, 5p; Gress, Jeffrey J.; Xu, Siguang; Joshi, Ramesh; Wang, Chuan-Tao; Paul, Sabu. (2005) Massively Parallel Processing For Fast And Accurate Stamping Simulations. Aip Conference Proceedings, 2005, Vol. 778 Issue 1, P152-157, 6p Horvath, L. (2001). Collaboration: The Key To Value Creation In Supply Chain Management. Supply Chain Management: An International Journal, 6 ( 5) Pp 205-207. Karpinski, Richard (1999) Supply-Chain Software Digs Deeper. Internet Week; Issue 779, P9, 1/8p Kerzner, Harold 1998. "Project Management- A Systems Approach To Planning, Scheduling, And Controlling." Sixth Edition, John Wiley & Sons, Inc. Kerzner, Harold 2006 "Project Management A Systems Approach To Planning, Scheduling, And Controlling" 9th Edition. John Wiley And Sons New York. Maxwell, J. A. 1996 "Qualitative Research Design: An Interactive Approach." 1st Edition Thousand Oaks: Sage Publications USA. Mccormack, K. & Johnson, W. 2000. "Business Process Orientation: Gaining The E-Business Competitive Advantage." Delray Beach, Fl: St Lucie Press. Mccormack, K. & Johnson, W. 2000. "Business Process Orientation: Gaining The E-Business Competitive Advantage." Delray Beach, Fl: St Lucie Press. Mcdonough, J. And Mcdonough, S. 1997 "Research Methods For English Language Teacher." 1st Edition Arnold: London Mukhopadhyay, T., Kekre, S., And Kalathur, S. (2002). Business Value Of Information Technology: A Study Of Electronic Data Interchange. Mis Quarterly: June Pp. 137-157. Simatupang, T.M. And Sridharan, R. (2005). An Integrative Framework For Supply Chain Collaboration. International Journal Of Logistics Management 16 (2), Pp. 257-274. Svensson, Gran (2000) A Conceptual Framework For The Analysis Of Vulnerability In Supply Chains. International Journal Of Physical Distribution & Logistics Management, 2000, Vol. 30 Issue 9, P731, 20p; Webber, Susan 2006 Management's Great Addiction. Across The Board May/Jun2006, 43 (3), P43-48, 6p Wu, B.; Kay, J. M.; Looks, V.; Bennett, M.. 2000 The Design Of Business Processes Within Manufacturing Systems Management. International Journal Of Production Research, 11/20/2000, Vol. 38 Issue 17, P4097-4111, Yin, Robert 1993 "Case Study Research: Design And Methods" 2nd Edition London. Sage Publications, Inc; Appendices A: Annotated Bibliography for Case Study (articles not included in research proposal) Anderson, Edward G.; Joglekar, Nitin R.. 2005 A Hierarchical Product Development Planning Framework. Production & Operations Management, Fall2005, Vol. 14 Issue 3, p344-361, 18p, 3 charts, 2 diagrams; Describes uncertainty in new product development (NPD) planning embraces market, creative, technological, and process dimensions to a much greater extent than in non-NPD project planning within the firm and across the supply chain (logistics). Azevedo, Amrico L.; Toscano, Cesar; Sousa, Jorge P.; Soares, Antonio L.. 2004 An Advanced Agent-Based Order Planning System For Dynamic Networked Enterprises. Production Planning & Control, Mar2004, Vol. 15 Issue 2, p133-144, 12p; Defines and explains the opportunities for competitive advantage that arise from reinforcing core competencies and innovative capabilities of the individual companies through risk management and logistics support technologies. Hammant, J.; Disney, S.M.. 1999 Modelling The Consequences Of A Strategic Supply Chain Initiative Of An Automotive Aftermarket. International Journal of Physical Distribution & Logistics Management, 1999, Vol. 29 Issue 9/10, p535, 16p, 5 charts, 5 diagrams, 1 graph; Presents information on a study which describes the use of a decision support system in part of a strategic supply chain initiative of an international automotive aftermarket organization in 1996-1997. Harrison, Alan. 2004. Outsourcing in the Automotive Industry: the Elusive Goal of TIER 0.5. Manufacturing Engineer, Feb/Mar2004, Vol. 83 Issue 1, p42-45, 4p; Examines risk management and logistic supply as relative to automotive company outsourcing engineering and operational capabilities. Howell, Larry J.; Hsu, Jamie C.. 2002. Globalization Within The Auto Industry. Research Technology Management, Jul/Aug2002, Vol. 45 Issue 4, p43, 7p; Abstract: Focuses on the benefit of globalization to General Motors (GM). Incentive for GM to form automotive alliances; Risk involved in the globalization of a company; Factor which would help accelerate the globalization process. (AN 6932286) Kohlert, Helmut. 2006 From Risk to Opportunity. Russia and Ukraine in the Focus of Medium-Sized Machinery Builders and Automotive Suppliers from the State of Baden-Wrttemberg, Germany. Problems & Perspectives in Management, 2006 Issue 4, p4-11, 8p; Examines the differences between the automotive suppliers and the machinery builders. The article concludes with the connecting and discerning factors between countries. # 2. Add Added Korevaar, P.; Schimpel, U.; Boedi, R.. 2007. Inventory Budget Optimization: Meeting System-Wide Service Levels In Practice. IBM Journal of Research & Development, May/Jun2007, Vol. 51 Issue 3/4, p447-464, 18p Describes both academic and manufacturing approach to risk management in the logistics technology. Explains the most important requirements and constraints considered are a detailed cost structure, different packaging sizes, capacity constraints, several storage zones, the decision whether or not to stock a product, stochastic lead times, highly sporadic demands, and the stability of the optimization result over time. Meyr, Herbert. 2004 Supply Chain Planning In The German Automotive Industry. OR Spectrum, Oct2004, Vol. 26 Issue 4, p447-470, 24p Examines needs of logistics supply chain management and technology to further increase order to realize short delivery times, high delivery reliability and a fast responsiveness. Ramdas, Kamalini; Fisher, Marshall; Ulrich, Karl. 2003 Managing Variety for Assembled Products: Modeling Component Systems Sharing. Manufacturing & Service Operations Management, Spring2003, Vol. 5 Issue 2, p142, 15p; Component sharing using the same version of a component across multiple products is an approach adopted by many assembled-product manufacturers to achieve high final product variety with lower component variety and cost. Highlights risks in supply chain logistics. Roudebush, Clair. 2005 Machine Safeguarding. Professional Safety, Oct2005, Vol. 50 Issue 10, p20-24, 5p; Focuses on a process for determining tolerable risk. Tolerable risk is defined as risk that is accepted for a given task and hazard combination. The fundamental goal of tolerable risk assessment involves analyzing equipment tasks and incorporating safety-related designs and modifications that provide both improved productivity and maintainability. Singh, P. J.; Smith, A.; Sohal, A. S. 2005 Strategic supply chain management issues in the automotive industry: an Australian perspective. International Journal of Production Research, 8/15/2005, Vol. 43 Issue 16, p3375-3399, 25p, 7 charts; Describes major automotive manufacturers are focusing on their logistics supply chains for sources of competitive advantage. Examines significant risks to the industry from supply chain logistics. Tabeta, Naoki; Rahman, Shashidur. 1999 Risk Sharing Mechanism In Japan's Auto Industry: The Keiretsu Versus Independent Parts Suppliers. Asia Pacific Journal of Management, Dec99, Vol. 16 Issue 3, p311, 20p, 7 charts; Gives historic risk management strategies based on the logistics support technology of subcontractor-automaker contracts. Appendices B: Qualitative and Quantitative Case Study Draft Research Instruments General to specific format Type of data Data sources Data uses Examples of types of information to collect Risk management Theoretical review Text books Establish framework for literature review Current models of risk management generally applied by theory Logistics technology Theoretical review Text books Establish framework for literature review Current models of logistics technology generally applied by theory Supply chain logistics Corporate information: cost and implementation Journal articles Establish connection between risk management and logistics Current usage in the automotive industry as basis for proposal model Automotive industry Industry analysis Journal articles Establishes needs of risk management and logistics technology Current uses of risk management and logistics technology in the industry as a whole, also to establish gaps in both. Major manufacturers Corporate information: risk, logistics, costs, roi Corporate websites and stakeholder information published by major manufacturers as well as journal articles Establishes current methods and costs of logistics technology to examine importance of risk management Current costs of risk management and logistics technology in the industry as a whole, also to establish gaps in both. Read More