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essential-guide-to-qualitative-in-organizational-research

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––––––––––––––––––––––––––––––––––––––––––––––––––– CASE STUDY RESEARCH–––––––––– 329certa<strong>in</strong> questions as you set up <strong>in</strong>terviews and observation periods: have I sampled thisbehaviour/process from a wide enough set of <strong>in</strong>formants? Are there other people who mighthave a different view or explanation of this? Are there any data which do not support mycurrent hypothesis?There is some place for ad hoc or opportunistic data collection; a conversation with areceptionist as you walk <strong>in</strong> one morn<strong>in</strong>g, or a chance meet<strong>in</strong>g by the coffee mach<strong>in</strong>e may giveyou new ideas which then need <strong>to</strong> be <strong>in</strong>corporated <strong>in</strong><strong>to</strong> your <strong>research</strong> design and <strong>in</strong>vestigatedmore thoroughly. This can be a spur <strong>to</strong> further systematic <strong>in</strong>vestigation. Can someone elseshed light on the phenomenon? Are there documentary records you can check? Anobservation may crystallize <strong>in</strong><strong>to</strong> a proposition which can then be exam<strong>in</strong>ed.Manag<strong>in</strong>g data collectionWhile it is tempt<strong>in</strong>g <strong>in</strong> a case study <strong>to</strong> go on collect<strong>in</strong>g more data, thought has <strong>to</strong> be given<strong>to</strong> the opportunity costs and <strong>to</strong> the management of the data collected. Will a further <strong>in</strong>terviewor period of observation add significantly <strong>to</strong> what you already know? Does it allow you <strong>to</strong>be reasonably certa<strong>in</strong> there is no disconfirm<strong>in</strong>g evidence <strong>in</strong> the organization? At some po<strong>in</strong>tyou have <strong>to</strong> decide <strong>to</strong> s<strong>to</strong>p collect<strong>in</strong>g further data.I will not discuss <strong>in</strong> detail the record<strong>in</strong>g of data because that is covered elsewhere. However,thought must be given <strong>to</strong> how you will record data and how you will prevent yourself be<strong>in</strong>goverwhelmed by the data. In many organizations, as an observer, tape-record<strong>in</strong>g will be bothimpractical and <strong>in</strong>advisable for a variety of reasons and it is likely that record<strong>in</strong>g by notebookwill be best. Impressions, <strong>in</strong>sights and theoretical mus<strong>in</strong>gs need <strong>to</strong> be noted, as well as observedand elicited data about the organization and its members.Unless you are a full participant observer, cont<strong>in</strong>ual presence <strong>in</strong> the organization is unlikely<strong>to</strong> be beneficial. Considerable time needs <strong>to</strong> be given <strong>to</strong> writ<strong>in</strong>g up notes of <strong>in</strong>terviews andobservations and this needs <strong>to</strong> be done as soon as possible after the event. Some distanc<strong>in</strong>gfrom the organization is also advisable so the <strong>research</strong>er is not overloaded with impressionsand does not get so close <strong>to</strong> the data that he or she is unable <strong>to</strong> see their wider significance.Analys<strong>in</strong>g the dataData collection and analysis are developed <strong>to</strong>gether <strong>in</strong> an iterative process <strong>in</strong> a case study (acontrast with experiments and surveys). This can be a strength as it allows for theorydevelopment which is grounded <strong>in</strong> empirical evidence. However, a danger is that the<strong>research</strong>er reaches premature closure, hav<strong>in</strong>g been unduly <strong>in</strong>fluenced by particularly vivid,unusual or <strong>in</strong>terest<strong>in</strong>g data. There are several ways <strong>to</strong> guard aga<strong>in</strong>st such tendencies.The first is careful description of the data and the development of categories <strong>in</strong> which <strong>to</strong>place behaviours or processes. The data may be organized around certa<strong>in</strong> <strong>to</strong>pics, key themesor central questions. Then the data need <strong>to</strong> be exam<strong>in</strong>ed <strong>to</strong> see how far they fit or fail <strong>to</strong> fitthe expected categories. Use of tables <strong>to</strong> search for patterns, or group<strong>in</strong>g of similar <strong>to</strong>pics mayhelp <strong>to</strong> exam<strong>in</strong>e certa<strong>in</strong> types of data. Initial <strong>in</strong>terrogations of the data may lead <strong>to</strong> unexpectedor unusual results which may mean that the categories need ref<strong>in</strong><strong>in</strong>g or that events need <strong>to</strong>be <strong>in</strong>terpreted differently. One method may suggest one <strong>in</strong>terpretation while this is notconfirmed by another method. Questions lead <strong>to</strong> further questions. All the time the <strong>research</strong>ermust be alert <strong>to</strong> the need <strong>to</strong> draw on disconfirm<strong>in</strong>g data and possible alternative explanations

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