Business Decision Making - Investigating the Leisure Industries - Assignment Example

Business Decision Making - Investigating the Leisure Industries Types of Heuristics On daily basis, we often consistently settle on choices, decisions, and judgment especially when we can do something or not, believe in somebody, the course to take and how to react to someone’s actions. Fortunately, the brain makes things less demanding as it utilizes production speculation technique referred to as heuristics (Pleskac, 2007). Heuristic is a mental alternative way that helps in rapidly settling on choices and judgment without the need to invest considerable measure of energy either scrutinizing or breaking down of data. The following are the main six sort of division of the Heuristics: the recognition heuristic, the minimalist strategies, the lexicographic strategy, take the last strategy, sequential decision making, and elimination by aspect. Goodwin & Wright (2014) assert that heuristic is used for multiple making decisions that involve several or multiple objectives. For an instant, in this case a choice is to be made in picking two alternatives which are either to choose Egypt or Edinburg. Goldstein & Gigerenzer (2002) argues that recognition heuristic is the simplest of all the heuristics hence can be introduced as fast and frugal in this particular program. This is due to the fact that individuals tend to have good recognition memory. In this type of heuristic, when an individual perceives one of two things, he or she will judge the perceived thing to be more prominent in whatever measurements associated with recognition. Oppenheimer (2003) argues that the size of the city is positively associated with recognition hence through the recognition heuristic, it will predict that the recognized cities will be judged as larger in comparison with the cities that are not recognized. This type of heuristic is useful in settling on choice rapidly though it gives an illusion of a good choice by excluding other opportunities such as prior hypothesis. For an instant, some individuals may choose the most visited countries and cheap countries while other may opt for either Egypt or Edinburg due to safety and security reasons. Miao & Mattila (2007) illuminates that information results in confidence in making judgment in reference to the price of the consumers and their decisions. Notion of Smart The Smart technique is based on a model that is additive linearly. It implies that the overall of an alternative is calculated as the total sum of the performance score of every criterion multiplied with that criterion’s weight (DTU Transport, 2014). Goodwin & Wright (2014) explain that the application of SMART is associated with its transparency and simplicity despite the fact that it may not always capture details inclusive of the complexities of a particular decision. It can be ideal for illuminating the crucial aspects of the problem and their relation. Goodwin & Wright (2014) claim that there are eight stages of analysis that helps in the decision making as illustrated in the appendix below. The making of decision can incorporate the use of value of tree that has a connection with SMART analysis. The use of value tree helps in minimizing risks and also illuminates the type of investment to indulge in, as well as the benefits to be received. The two kinds of attributes for the division of the tree are costs and benefits. In a taxi firm, the cost indicate where the decision maker is to spend money on issues such as the hiring of drivers who are having their own cars, the need to rent cars with the preemption of investing more money. The tree also reveals the benefits associated with setting up a taxi company through the use of the mobile app. When this is employed, there will be no need of either renting an office or hiring many workers. The5 criteria for judging the tree is completeness, operationally, absence of redundancy, decomposability, and minimum size. Das & Teng (1999) assert that SMART is related to logical incrementalist mode. The logical incrementalist mode stipulates that the process of decision making is a consistent movement towards a broad, global goal. Das & Teng (1999) elaborate further by stating that logical incrementist mode is in terms of step by step processes of fulfilling the goals of establishing a taxi company. In addition, the cognitive biasness due to illusion of manageability can be employed in this circumstance. It is possible due to the one step at a time movement with the likely believe that small steps at a time can be managed and situations can also be controlled. The concept of simulation Brabazon (1997) elaborates that simulation is a simple tool and concept that is useful for management accountant. Hans (2001) argue that the aim of simulation is to not only to be fast but also accurate. Juan Ignacio (2012) adds that the methodology that encompasses interdisciplinary strategy gaming with regards to real life simulation cases results into the reduction the cost of training and an improvement on the investment returns in the process of training. Simulation concept helps the decision maker in the partitioning the likely appraisal tasks into sections that are smaller. In addition, Goodwin and Wright (2014) extrapolates that simulation is vital in building a travel company since the decision maker can estimate the probability of distribution for the market size, market share to be achieved, and the launching costs among others (Goldstein & Gigerenzer, 2002). However, the challenge is on the divisions carried out which requires the decision makers to decide on their joint impact by taking responsibility on the probability of the returns of investments. Most of the problems are due to large number of the elements where every circumstance can be infinite and huge. As per Goodwin & Wright (2014), if an assumption is made that the travel firm is to be constructed in a country; several factors such as the number of tourists should be considered. One of the most effective and adaptable simulations is Monte Carlo simulation. Brabazon (1997) states that Monte Carlo simulation is not only simple but can also be easily implemented through the use of spreadsheets (Vangheluwe, 2001). This type of simulation is employed to comprehend the impact of risk, project management, and uncertainty in financials, cost and prediction of models. In Monte Carlo simulation, there is random selection of value for every task based on estimate range. Moreover, the results of the model are recorded after which the process is repeated (Juan-Ignacio & Macías, 2012). The 7 stages of the application of simulation are: formulation of a model, analysis of preliminary sensitivity, assessing the probability of simulation, performing simulation, sensitivity analysis of the result of simulation, and comparison of the alternative course of action (Goodwin & Wright, 2014). Bayes’ Theorem   Triola (ND) illuminates that to comprehend Baye’s theorem is the recognition of sequential events where new information is retrieved from subsequent events and used to revise the chances (probability) of the first event. Westbury (ND) asserts that Baye’s Rule is a simple technique of calculating probabilities that are conditional. Triola (ND) explains that prior probability is an initial value of probability obtained originally before the retrieval of additional information. On the other hand posterior probability is the value of probability that has been revised using information that was obtained later. The theorem may be ideal in making decisions concerning building of structure such as houses. However, despite the fact that the conception of the theorem is relatively simple, the Baye’s Rule can be quite difficult for the beginners to either comprehend or understand. Westbury (ND) illustrates that studies have revealed that all kinds of individuals even those trained in probability theory-tend to be poor at the estimation of probabilities that are conditional. The cognitive bias associated with the theorem is insensitivity to the outcome of the probabilities since managers are likely to employ few vital values in description of situation instead of computation or even the use of standard statistics in reference to probabilities (March & Shapira, 1987). The biasness can have implication in the case of building a house. References List: Westbury, C (Not Dated). Bayes’ For Beginners. Retrieved on 27th May 2015 from: https://www.ualberta.ca/~chrisw/BayesForBeginners.pdf   Das, T.k & Bing-Sheng, T (1999). Cognitive biases and strategic decision process: and integrative perspective. Journal of Management Studies. Retrieved on 27th May 2015 from: http://web.a.ebscohost.com/ehost/detail/detail?vid=2&sid=d0d4a6fc-6d3c-4e2f-b1330982e7cb27ae%40sessionmgr4003&hid=4106&bdata=JnNpdGU9ZWhvc3QtbG12ZQ%3d%3d #db=buh&AN=2697470  Triola, M, F (Not Dated). Bayes Theorem. Retrieved on 27th May 2015 from: http://faculty.washington.edu/tamre/BayesTheorem.pdf Goodwin, P & Wright, G (2014). Decision Analysis for Management Judgment. United States: John Wiley & Sons. Brabazon, T (1997). Using simulation in Business Decision, Management Accounting: Magazine for Chartered Management Accountants.75 (2) p36- 65. Retrieved on 27thMay2015from:http://web.a.ebscohost.com/ehost/detail/detail?vid=4&sid=a2316b07-8139-45b5-b368-59b3a33b1401%40sessionmgr4005&hid=4109&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=buh&AN=9702165806> Vangheluwe, H (2001). Modelling and Simulation Concepts. Retrieved on 27th May 2015 from: http://www.cs.mcgill.ca/~hv/classes/MS/MSconcepts.pdf  Juan-Ignacio, L, B & Macías, E, M (2012). Simulation for Education in Business Decision-Making. Retrived on 27th may 2015 from: http://www.scs.org/magazines/2012-04/index_file/Files/Latorre.pdf   Riskamp (Not Dated). What is Monte Carlo Simulation? Retrived on 27th May 2015 from:https://www.riskamp.com/files/RiskAMP%20%20Monte%20Carlo%20Simulation.pdf DTU Transport (2014). The simple Multi Attribute Rating Technique (SMART). Multi-criteria decision analysis for use in transport decision making. Retrieved on 27th May 2015 form: http://www.systemicplanning.dk/SMART.pdf Das, T.K & Teng, B. S. (1999). Conginitive biases and strategic decision process: an intergrative perspective. Retrived on 27th May 2015 from: http://web.a.ebscohost.com/ehost/detail/detail?vid=1&sid=fa756eee-1005-405b-bc9e-a01f41b56ca8%40sessionmgr4003&hid=4109&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=buh&AN=2697470    Gigerenzer, G & Gaissmaierm, W. (2011). Heuristic Decision Making. Retrieved on 27th May 2015 from: http://citrixweb.mpib-berlin.mpg.de/montez/upload/PaperOfTheMonth/gigerenzer_gaissmaier_2011-1-2.pdf Goldstein, D.G & Gigerenzer, G. (2002). Models of Ecological Rationality: The Recognition Heuristic. 109(1) 75-90 Pleskac, T (2007). A signal detection analysis of the recognition heuristic. Retrieved on 27th May 2015 from: https://www.msu.edu/~pleskact/research/paers/pleskac_2007.pdf Miao l. & Mattila A.S. (2007) Journal of Hospitality & Tourism Research, Vol. 31, p.530-545 Oppenheimer, D.M, 2003. Not so fast! (and not so frugal!): rethinking the recognition heuristic. Cognition, Volume 90, B1-B9. Appendix These stages are the main stages for analyzing and could be the procedure to take alternative actions. Stage.1: First of all, the person who will set up the taxi company has to be decided. Stage. 2: And the decision maker should be aware and consider of all of alternatives for applying the taxi company. Stage.3: Also, the decision maker should consider the attribute such as, the cost of hire drivers, car rental fee and create a new server for mobile app. Stage. 4: The performance of the attribute should be measured by classical approach. Stage. 5: And the attribute needs to be ranked that which one is priority. Stage. 6: For each alternative, the decision maker should take a weighted average of the worths assigned to that alternative. Stage. 7: Before the final decision, the decision maker need to make a temporary decision. Stage. 8: Now on, the sensitivity analysis can be performed to view how to relate.                       Read More