Believability in Business 1Believability in Business Research                   by           Edgardo Donovan       BUS 504...
Believability in Business 2                              Believability in Business Research                               ...
Believability in Business 3       Researchers may face tremendous career pressure to cater to a particular worldview in or...
Believability in Business 4research are time, manpower, and money necessary to conduct the sometimes tediouswork of gather...
Believability in Business 5       Many academics and business practitioners prefer scrutinizing hypotheses throughextensiv...
Believability in Business 6                                            Measurements are seldom if ever perfect. Particular...
Believability in Business 7BIBLIOGRAPHYI. Works Cited       Berry, Michael. (2008). Understanding variables. Retrieved on ...
Believability in Business 8Dereshiwsky, M. (1998). Understanding variables. Northern Arizona UniversityHelberg, Clay. (200...
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Believability in Business Research

  1. 1. Believability in Business 1Believability in Business Research by Edgardo Donovan BUS 504 – Dr. Roger Rensvold Module 5 – Case Analysis Monday, March 18, 2008
  2. 2. Believability in Business 2 Believability in Business Research Do the findings and conclusions of the research relate to the objectives? Did the researcher actually investigate what they thought they were investigating? If someone else had done this research, would they have produced similar results and findings? Is there anything about the research which limits the findings to the specific situation researched, or do they have wider applications? TONY OULTON Journal of Small Business Management, 2007 n his work "Management Research for Information", Tony Oulton provides a simple multi-question framework to better assess the believability of business research. This discussion is very helpful in approaching the issue of how much importance we must give tobusiness research and whether we can adopt methodologies that help discern betweenbelievable research and work of lesser quality. In order for research to believable it has to involve a careful balancing act ofdeveloping abstract theory that can be operationalized in a way that culturally resonateswithin its prospective audience. As researchers and consumers of research, we mustbecome sensitive to the fact that theory not only is a tool used to explain things but that italso greatly shapes the way we see the world. It is only natural for a student to ask "What will get me good marks?" PAUL HUTCHISON www.angelfire.com/biz/rumsby/ARES.html, 2008
  3. 3. Believability in Business 3 Researchers may face tremendous career pressure to cater to a particular worldview in order to improve their chances of their work being widely accepted. This mayhappen without the researcher even being aware of it and may lead them to perceivepatterns supporting their theses where they do not exist. Human beings depend so heavily on patterns in their day-to-day lives that they tend to see patterns even when they don’t exist. If you look at the night-time sky, you probably do not see a random arrangement of stars, but rather, the Big Dipper, or the Southern Cross, or Orion’s Belt. Some of you even see astrological patterns and portents that can be used to predict the future. MICHAEL BERRY www.crm2day.com, 2008 Ideally, good believable research should be structured within a contextualframework to better resonate within its intended audience while maintaining a certaindegree of intellectual independence so as to not overly skew the research model to favoracceptance potential over methodological integrity. Organizations commission or pay for research that may be either of a descriptive orcausal inquiring nature hoping that the insight gained will help it better achieve itsorganizational mission. Quality descriptive studies are very useful because they providecontext for many human experiences. The casual reader may peruse an almanac or thestock prices page of the Wall Street Journal to gather information that they will use to drawconclusions about their geographic area and financial holdings respectively. Descriptivestudies are also very useful because they provide many of the raw materials used toformulate causal studies. In so doing a researcher identifies a trend or phenomena andsupports it with data from descriptive studies. Some of the challenges of descriptive
  4. 4. Believability in Business 4research are time, manpower, and money necessary to conduct the sometimes tediouswork of gathering huge of amounts of first-hand quantitative data. Some of the challengesof quality causal research are to be able to take large amounts of descriptive data, findpatterns, derive a thesis, and then conduct further research from a myriad of sources toadd depth to the supporting tenets of your thesis. Planning is one of the most critical phases of complex causal research. Constructinga research model is not easy. It forces you pick subject matter in which you will try to proveor disprove a hypothesis. When complex causal research studies are concerned, one mustdevise a research model that minimizes the structural limitations of previous contextualresearch attempts. It must also be flexible enough so that its structure conforms to thenature of the quantitative and qualitative data one will gather and not vice-versa. Intuition and experience researching related subject matter may help during theplanning phase. Unfortunately, some research projects are not planned well and are limitedby quantitative or qualitative metrics based on preconceived notions. At times this isrealized when it is too late to start over increasing the pressure for the research team tocompensate for what their project lacks in substance by molding the research results tosupport a thesis popular within the academic community. Quasi-experimentation should pursue publicly specified methods that try both to verify causal relationships and to falsify them through the judicious use of experimental designs, statistical analyses, and a critically appraised common sense that is heavily dependent on past knowledge in a particular substantive area. T.D. COOK Beyond Method, 2008
  5. 5. Believability in Business 5 Many academics and business practitioners prefer scrutinizing hypotheses throughextensive series of qualitative and quantitative data analysis. In the business world,companies may be interested in understanding the dynamics behind workforce retentionor predicting the adoption of new technologies in the marketplace. Examples of qualitativedata may be series of workforce retention or technology adoption related questionnairesgiven to groups of people with a particular target segment. This type of data may take on areliable quantitative form if the questionnaire distribution penetrates over 8o percent ofthe target segment or is deemed representative of a myriad of specific target segmentclassifications. The value of the qualitative questionnaires would be its degree of validityconcerning how the various questions can effectively elicit contextual responses relevant toone’s retention or technology adoption propensity. The core value of statistical methodology is its ability to assist one in making inferences about a large group (a population) based on observations of a smaller subset of that group (a sample). In order for this to work correctly, a couple of things have to be true: the sample must be similar to the target population in all relevant aspects; and certain aspects of the measured variables must conform to assumptions which underlie the statistical procedures to be applied. CLAY HELBERG www.execpc.com/~helberg/pitfalls/, 2008 Every research project is limited in the amount of available manpower, time, andmoney at it its disposal. In an ideal world we would seek out primary sources ofinformation wherever possible but for practical purposes many people heavily rely onsecondary data.
  6. 6. Believability in Business 6 Measurements are seldom if ever perfect. Particularly when dealing with noisy data such as questionnaire responses or processes which are difficult to measure precisely, we need to pay close attention to the effects of measurement errors. Two characteristics of measurement which are particularly important in psychological measurement are reliability and validity. CLAY HELBERG www.execpc.com/~helberg/pitfalls/, 2008 A foolproof method for ascertaining the reliability of primary and secondary datadoes not always exist. Certain types of scientific quantitative primary research can beproduced via experiments enabling us to verify results in terms of weight, speed, size,chemical composition, and other physical metrics. However, many secondary sourcescannot be proven reliable 100% of the time. Sometimes, even what we consider to be aprimary source of information is not foolproof. Much of what we know of ancient Rome isbased off of the accounts of Pliny the younger. We cannot go back in time and verify thateverything he wrote was true. Remembering to inquire about how people think and why they decide to supportcertain positions is a life-long critical analysis tool. A structured learning environment thatstimulates and supports this type of inquiry is conducive towards helping PhD candidatesbecome better research consumers and possibly future research producers. Although mypositions regarding Tony Oulton’s work have not changed much since the beginning of thiscourse, I have definitely gained greater depth of knowledge concerning some of the subjectareas concerning research believability.
  7. 7. Believability in Business 7BIBLIOGRAPHYI. Works Cited Berry, Michael. (2008). Understanding variables. Retrieved on 11 April 2008 from http://www.crm2day.com/library/EpAZpuAFyAzpbJTtYp.php Cook, T.D. (1983). Quasi-Experimentation: Its Ontology, Epistemology, and Methodology. In Gareth Morgan (Ed.), Beyond Method. Helberg, Clay. (2008). Pitfalls of data analysis. Retrieved on 11 April 2008 from http://www.execpc.com/~helberg/pitfalls/ Hutchinson, Paul. (2007). Discussion on the process of doing research. Retrieved on 11 April 2008 from http://www.angelfire.com/biz/rumsby/ARES.html Oulton, Tony. (1995). Management research for information. Library Management.II. Works Consulted Berry, Michael. (2008). Understanding variables. Retrieved on 11 April 2008 from http://www.crm2day.com/library/EpAZpuAFyAzpbJTtYp.php Chappie, Mike. (2008). Data mining: an introduction. Retrieved on 11 April 2008 from http://databases.about.com/od/datamining/a/datamining.htm Cook, T.D. (1983). Quasi-Experimentation: Its Ontology, Epistemology, and Methodology. In Gareth Morgan (Ed.), Beyond Method.
  8. 8. Believability in Business 8Dereshiwsky, M. (1998). Understanding variables. Northern Arizona UniversityHelberg, Clay. (2008). Pitfalls of data analysis. Retrieved on 11 April 2008 fromhttp://www.execpc.com/~helberg/pitfalls/Hutchinson, Paul. (2007). Discussion on the process of doing research. Retrieved on 11 April2008 from http://www.angelfire.com/biz/rumsby/ARES.htmlMalhotra, Y. (2007). Scientific method, and evolution of scientific thought. Retrieved on 11April 2008 from http://www.brint.com/papers/science.htm.Murray, David (1998). Group-randomized trials. Oxford University Press.National Academy of Sciences. (2007). On being a scientist. Retrieved on 11 April 2008 fromhttp://www.nap.edu/readingroom/books/obas/.Oulton, Tony. (1995). Management research for information. Library Management.Thomson, Laura. (2008). Can the creation of community networks enhance social capital inrural Scotland? Retrieved on 11 April 2008 fromhttp://www.caithness.org/laurathompson/chapter_one.htmTrochim, W. (2007). Research methods website. Retrieved on 11 April 2008 fromhttp://www.socialresearchmethods.net/index.htm.

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