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Risk and Safety Management in the Leisure, Events, Tourism and Sports Industries

Risk and Safety Management in the Leisure, Events, Tourism and Sports Industries. Mark Piekarz , Ian Jenkins and Peter Mills. Chapter 4 – Risk Management Research, Models and Tool Application ( Part 1 - Research ). These relate to the chapter objectives in Chapter 4

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Risk and Safety Management in the Leisure, Events, Tourism and Sports Industries

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  1. Risk and Safety Management in the Leisure, Events, Tourism and Sports Industries Mark Piekarz, Ian Jenkins and Peter Mills

  2. Chapter 4 – Risk Management Research, Models and Tool Application (Part 1 - Research)

  3. These relate to the chapter objectives in Chapter 4 To explain the difference between theories, tools and models. To explain the basic principles of the research process and where data can be accessed from.

  4. - This is the first lecture based around risk research, tools and analysis. - Analysing risk is a key component of the practical risk process (H & S, project and strategic risk analysis) - Analysis is most complex stage - In order to analyse you need data, information and to apply models and tools. - This lecture focuses just on the research methods which can be used for data collection.

  5. AN OVERVIEW OF THE PROCESS STAGES AND THE METHODS OF RESEARCH WHICH CAN BE USED

  6. KEY CONCEPTS AND TERMS IN RESEARCH METHODS Types of data: Primary data relates to data which is collected first hand by the individual or organisation. Secondary data relates to data which someone else has collected, Quantitative, which refers to data which is expressed numerically, such as looking at accident data. Qualitative, which can be more descriptive of an event or situation, such as reviewing a case study which looks at how an accident came about. Types of variables: Independent (the variable that can theoretically cause the independent variable to change - change the independent variable and measure the effects on the dependent. Dependent (this is the variable affected). Intervening (what modifies any changes). Examples of methods of data collection: Interviews, team meetings or risk clinics: can use a variety of formal (Delphi techniques) and informal techniques (e.g. mind mapping) Observationsand direct inspection of facilities, locations or countries (the latter is sometimes known as the grand tour approach). Interviews and meetings can have a formal structure with a set of pre-designed questions, or be informal, where ideas are encouraged to freely develop, or even a mix of the two.

  7. KEY CONCEPTS 1: PROBABILITY AND HOW TO MAKE AN ASSESSMENT OF RISK Key approaches which vary in the degree of accuracy and the amount of research needed: Professional judgements: Basedon past experience s and knowledge (known as heuristics and explored in Chapter 7). Analysis of specific case studies: Focus on one or two case studies in more detail, which can reveal insights into the factors of causation, the failures in systems and the critical paths which lead to the outcomes of the event. Identifying frequency of similar events: For some activities which are new, or have little precedent, looking at the frequency of past events may not be an option, such as tour operators developing services in a new destination, or sports or adventure activities taking place in less familiar environments. Identification of frequency of past events: Classic method, ground in positivist scientific methods. Here it can be a process of looking at the frequency of past incidents to try and: a) identify all the key risks, then b) build up an assessment of the likelihood of these risk events occurring in the future. It should also be noted that whilst frequency and probability are sometimes used inter-changeably, these are in fact different concepts, as observing frequency is a means to build up probability estimates.

  8. COLLECTING DATA A great deal has been said about why it is important to collect data, with the previous section giving some indication of how data can be collected. The next critical point to consider is just where data can be collected from. See chapter 4 for examples of databases which can be accessed. Examples of incident data to build up frequency profiles to inform probability and outcome assessments: accidents in a sport, which resulted in death or disability; event or stadium accidents from around the world; transport accidents in different countries and regions; acts of criminality or terrorism; incidents of natural disasters, from earthquakes, tsunamis, hurricanes, etc.; disease outbreaks; incidents of political instability, such as riots, demonstrations and strikes.

  9. CONTEXTUALISATION AND APPLICATION TO THE DIFFERENT SECTORS At the end of the chapter in the book, a variety of examples are given to illustrate how these concepts can be applied to specific industry sector examples. The relevant sector examples can be selected and considered here.

  10. CONCLUSION Need to collect data to inform the analysis and make the tools work. The type of data used can depend on the risk assessment. Research is vital in risk management, which can range from case studies to statistical incident data.

  11. Thank You Name:Dr Mark Piekarz Email: m.piekarz@worc.ac.uk

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