PUTTING THE PIECES OF THE PUZZLE TOGETHER: USING NVIVO FOR A LITERATURE REVIEW

Transcription

1 PUTTING THE PIECES OF THE PUZZLE TOGETHER: USING NVIVO FOR A LITERATURE REVIEW Jenine Beekhuyzen Schl f ICT, Griffith University, Brisbane, Australia jenine@griffith.edu.au Abstract This paper discusses the jurney f an infrmatin systems PhD research student using Nviv fr a literature review. In this paper Nviv is prpsed as a tl t help any researcher accmplish a rigrus and transparent literature review. Here a practical example f such a prcess is presented in seven steps, using a well-knwn qualitative research sftware that has in recent years mved frm the margins t the mainstream. Keywrds: qualitative, literature review, methdlgy, cding, nviv, methd 4th QUALIT Cnference Qualitative Research in IT & IT in Qualitative Research, 2007 Wellingtn, New Zealand 1

2 Track Title Intrductin Qualitative research is a smewhat recent inquiry paradigm within the histry f research traditins. Interpretive qualitative research is a much debated apprach but it is als nw an accepted apprach fr the investigatin f infrmatin systems and rganisatins (Hirschheim and Klein 1989:; Walsham 1992:; Klein and Myers 1999:; Myers 1999). This apprach allws an understanding f technlgical phenmena within a scial cntext, frm the perspective f thse invlved. Even newer t research traditins is the use f qualitative sftware t supprt data analysis. T give an example, in 1984 the first versin f the Australian sftware Nud*ist was released 1 with subsequent versins (f Nud*ist/Nviv) t fllw ver the years. Widespread adptin f the sftware was held up fr many years fr varius reasns; ne significant ne being the lack f acceptance by university prfessrs f the validity f using sftware t aid qualitative research, particularly interpretive qualitative research. The argument being that a sftware tl must surely mve the researcher further away frm the data they are analysing; this being an ppsing bjective t the nature f the philsphical assumptins that underlie this apprach. In my wn persnal experience as a user f the sftware in its many versins (N4, N6, Nviv2 & Nviv7) fr 7 years and als as a qualified trainer in its use, I have fund the experience t be the ppsite f this argument. I find myself as clse t the data as I can imagine pssible, with sme f the extra features f the sftware (like search and queries) being f benefit ver traditinal methds f qualitative data analysis that use flders, clured highlighter pens and phtcpiers. Qualitative research sftware has its criticisms, and it is imprtant t acknwledge these. Hwever it is als imprtant t explre the benefits and value that using such sftware can add t the research prcess, including hw it can adequately supprt, and pssibly enhance the research prcess. Within the research prcess, ding a literature review is rarely discussed in detail. While the purpse and bjectives f cnducting a literature review are generally clear, the prcess fr actually carrying ut the literature review is cmplex, cntinuus and can be difficult t explain. Hwever this paper attempts t d just that, make explicit the prcess f cnducting a literature review using qualitative research sftware. Therefre this paper discusses my jurney as an infrmatin systems PhD research student using Nviv7 fr my literature review. My research apprach is interpretive and my research data is qualitative. My ethngraphy takes a cultural perspective t understanding the attitudes, mtivatins and behaviurs f music users. The research papers that make up the literature review fr such a prject are als qualitative data and they need t be analysed in a way that gives the researcher the ability t decnstruct, analyse and synthesise them in a useful and relevant way. Cding literature is a frm f qualitative data analysis and in this paper Nviv7 is prpsed as such a tl t help any researcher accmplish this. Presented here are the reasns why I have chsen such an apprach, as well as a practical example f such a prcess with qualitative research sftware that has in recent years, mved frm the margins t the mainstream. Using Qualitative Research Sftware Researchers have asked: why bther t use sftware fr qualitative data analysis? (Barry 1998) Even thugh these cncerns are smewhat utdated, it is imprtant t discuss them and hw they relate t this research. Nviv7 is a qualitative data analysis tl that is traditinally and verwhelmingly used t manage and cde empirical (r field) data (Caldeira and Ward 2003:; Bhattacharyya 2004:; Patashnick and Rich 2004). This primary data ften cnsists f dcuments cntaining qualitative text such as interviews, fcus grups, questinnaires/surveys and bservatin ntes. It is als used fr secndary data in dcumentary analysis, such as reprts, websites, and s and ther many ther surces including images. Nviv7 (its predecessrs Nviv2 and Nud*ist versins) and its cmpetitrs (Atlas, Leximancer etc) have been used fr all types f research acrss many disciplines. It can be useful fr almst all types f prjects that include qualitative research. It can be apprpriated fr many purpses; its uses ranging frm a prject management tl t 1 by Lyn and Tm Richards f QSR Qualitative Slutins & Research, Melburne, Australia 4th QUALIT Cnference Qualitative Research in IT & IT in Qualitative Research, 2007 Wellingtn, New Zealand

3 Beekhuyzen / Putting the pieces f the puzzle tgether hlding all f the data and details fr a full empirical study. Traditinally it has been used mstly fr data cllected in the field but nw it is being used mre regularly fr reviewing literature; see the recent paper by Bandara (2006) in which she presents an illustrative demnstratin f Nviv2 fr research management hwever di Gregri started the discussin back in 2000 when she demnstrated the tls in Nviv2 s tlkit which she believes supprt the varius prcesses and strategies invlved in cnstructing arguments frm the literature (2000). Mre recently, sme ther papers n hw t use the sftware fr research have been published, and are useful in prviding advice t researchers (Dean and Sharp 2006:; Wds and Wickam 2006). Di Gregri believes that while sftware such as Endnte and ther bibligraphical tls are essential t the research prcess, these packages were nt designed fr the analysis f data. She claims that a dedicated sftware analysis package is needed t supprt the analysis prcesses invlved in a literature review (2000). This paper builds n previus research by agreeing that Nviv7 can be a useful tl fr this. Als it adds t the literature by presenting a detailed practical accunt f using the sftware fr a literature review in pstgraduate research. Despite the earlier mentined criticisms f using any sftware fr qualitative research, it is nw being used widely in research higher degree prgrams (Kaczynski 2004) and encuraged by university prfessrs. Value in it fr managing the large data set cllected in qualitative research, its ability t allw the researcher t ask questins f data, t categrise and theme data, and t have a rigrus and transparent research prject have been recgnised (Beekhuyzen, Cabraal, Singh and vn Hellens 2006). Hwever this data generally refers t empirical data, thus this paper prvides a different apprach in using Nviv7 fr a literature review. And althugh Nviv7 and ther qualitative sftware are primarily used in qualitative studies fr empirical data, there dn t appear t be any cncrete arguments t suggest that it wuld be impractical t use Nviv7 fr a literature review in a quantitative study. Therefre the infrmatin presented in this paper is als useful fr researchers cnducting a literature review in a quantitative study. In this paper, the use f Nviv7 t manage the literature review in a PhD research study is discussed in detail. T prvide a cntext fr this discussin, I present my wn PhD study that is investigating Digital rights management and the nline music experience. At the time f writing this paper, just ver ne-year and cnfirmatin f the PhD is cmpleted (r 1/3 rd ), as is a substantial part f the literature review. This paper utlines the prcess fr ding the literature review in this prject, and gives advice t thers cnsidering using sftware t aid their literature analysis. The Research Cntext The evlutin f the technlgy has seen a mve nline t access digital music ver the Internet, mving frm the mre traditinal ptin f cmpact discs (CDs) purchased frm physical stres t using nline music stres, nline cmmunities and peer-t-peer netwrks. There are many ways fr peple t purchase music thrugh these new nline mediums, as well as varying ptins fr accessing free music. Sme f this free music is licensed fr free use while ther is unauthrised fr cpying and sharing, thus breaching cpyright law. A result f this new music scenari is the huge grwth f nline music sales, paralleled by cntinued reprting f music piracy reducing music sales and revenues. A dwnlad culture is emerging enabling users t get music frm a range f nline surces, nt all f them legal. Hwever, when buying a sng and dwnlading it frm an nline stre, in mst instances it is prtected by digital rights management (DRM) technlgy. Digital rights management (DRM) is a security measure t prtect digital versins f (music) cntent frm being cpied. Because f the cpyright issues underlying DRM, music users are finding themselves in difficult legal situatins when using nline music. There are suggestins that the technlgical cntrls impsed by the recrd labels are impinging n fair use, cnstraining cnvergence and placing practical restrictins n the legitimate use f nline music thus actually changing the way that peple use music. T be able t develp systems that supprt rather than impinge n music users, it is imprtant t understand hw the current prblems might shape the future f the industry. It is imprtant t knw what peple are ding with music; hw are they getting music, their use f technlgy, if technlgy is limiting their use and hw they share music with friends. This ethngraphic study is investigating the cultural aspects f music cnsumptin and use thrugh bservatins f fur nline music-sharing cmmunities, fcus grups and up t 30 semi-structured pen-ended interviews with university student music users. Additinally, interviews with 10 music artists and 10 music industry stakehlders 4th QUALIT Cnference Qualitative Research in IT & IT in Qualitative Research, 2007 Wellingtn, New Zealand

4 Track Title including thse frm recrd labels and music industry assciatins, the legal prfessin, the media, and cnsumer grups will be held. T try t understand this changing music industry, the fllwing questins are asked. What are the relatinships between digital rights management and the attitudes, mtivatins and behaviur f peple engaging in nline music? a. Hw d peple use digital nline music and what cnstitutes their nline music experience? b. What are the scial elements f nline music and hw imprtant is sharing music? c. Is technlgy prtectin such as digital rights management changing the user s music experience? d. What are the benefits t individuals t persnalise digital music in an nline envirnment? The varius stakehlders will be cnsulted as much as pssible t give an accurate picture f the current situatin as it relates t music users. And f curse these questins are still changing and are nt finalised. In terms f the empirical data being cllected t answer these questins, bservatins, fcus grups, and interviews will be cnducted in the next phase f this study. Using Research Sftware I have chsen t use Nviv7 and ther sftware fr very specific reasns. Firstly, I have been using Nviv7 (and its predecessrs) fr seven years in different prjects. My experience started when I was given the task f learning hw t use Nud*ist4 fr a prject in the summer f 2000/2001. I learnt hw t use it, gave a seminar n its usefulness and used it t manage and cde empirical data frm a Wmen in IT prject I am invlved in. In 2001 I went n t use the same versin f sftware fr my Hnurs research. Since then I have been wrking fr a number f years as part f a large prject team (separated by gegraphy) in which we als used Nud*ist6. As a team, we have fund the sftware useful fr ur prject n Internet banking in that it has helped t facilitate grup cmmunicatin and auditing f the prject, meaning it was a useful way t keep track f what has been dne in the prject, by wh, when and why in terms f cding. Its use is discussed further in Beekhuyzen, Cabraal, Singh and vn Hellens (2006). Using Nviv7 t manage mst dcuments relative t my PhD research, I have fund it t be a useful tl fr cding text and fr supprting thery generatin thrugh identifying patterns (Fetterman 1998:82&96). I have fund it t be a gd prject management tl fr rganising nearly all aspects f my PhD research prject but even s, I find it relatively easy t analgise hw I wuld manage the research prject withut technlgy (using highlighter pens and a phtcpier). I argue that it is imprtant t be able t d this. S far, the sftware has enabled me t manage my ntes and ideas abut the suddenly large cllectin f published research papers (electrnic dcuments) and web links I have, as well managing details abut the many external (hard cpy) surces such as jurnal papers, bks and reprts. Cmbining these abilities as well as being able t cde/categrise the summarised details f these surces int themes and being able t search acrss cdes/themes are by far its greatest benefit and fr me justifies its use. But by n means is Nviv7 the nly ptin fr a research prject and it is nt used in islatin. It can be used exclusively but its use shuld als be cnsidered alngside ther tls such as Excel and Endnte. In the prject presented here, Excel is used t manage the bservatin data, as Nviv7 is deemed inapprpriate fr this task. As the bservatin data is tabulated in lists, using a tl such as Nviv7 is limiting fr this. In terms f using Endnte, it is a bibligraphic reference management tl as ppsed t a data analysis tl and it is used in cmpliment t Nviv7 and Excel. In this research Endnte is used t manage the bibligraphic details f all f my literature surces. Even thugh Endnte enables the researcher t add abstracts and sme references t what might be cnsidered cdes (i.e. keywrds), Nviv7 takes it a step further by allwing much greater flexibility in assigning any number f pieces f texts (cding) t any number f cncepts (ndes). It als enables cmplex search functins that wrk n the cded text and ndes, tasks nt available in Endnte r Excel. Basically the Nviv7 activity f cding literature brings tgether all f yur ideas (that yu have purpsively cded) abut a particular cncept r theme. By ding this, it is then easy t pen just that nde (cncept/theme) t read filtered infrmatin abut just that tpic, and use this t write up yur literature review. Ding the (smetimes labrius) task f cding situates the researcher in a psitin t use the advanced features f Nviv7, thus finding real value in using the sftware. 4th QUALIT Cnference Qualitative Research in IT & IT in Qualitative Research, 2007 Wellingtn, New Zealand

5 Beekhuyzen / Putting the pieces f the puzzle tgether Set fr purpse, all sftware has limitatins and benefits. As it is used in this research, Nviv7 is limited in its platfrm dependency (n Windws I usually use a Mac) and its ccasinal instability (service packs are released regularly and new versins can be unstable), hwever the benefits are nt utweighed. Being able t manage the large amunt f literature, being able t quickly identify certain themes, and easy categrisatin f the varius empirical studies and the methds used are imprtant benefits. In future stages f the research, having literature and empirical research in the ne accessible place als has its advantages: when writing up the dissertatin, direct links between the literature and the empirical data can be identified and substantiated. In the cming mnths during data cllectin, the Nviv7 prject being used fr the literature review here will be expanded fr use with the fcus grup and interview transcripts as well as mre literature. It will als be used t refer t digital audi-recrdings. The findings f the bservatins (nt the actual data) will als be intrduced s the data can be triangulated with that f the fcus grups and interviews. Seven Steps t Analysing the Literature This sectin discusses the essential steps invlved in ding a literature review using qualitative research sftware. There are many steps invlved in this prcess, with the fllwing seven essential steps cvering the basics f cding research surces fr yur literature review. These steps can be reiterated r added t with mre cding phases. In Nviv7 (r it can be generally applied t the use f ther qualitative research sftware), the example f my PhD and the actual literature I reviewed is used t put the steps in a practical cntext. Please keep in mind that this is just ne apprach and while nt intending t be a best practice guide, it des aim t be a practical example f cnducting a literature review in a qualitative research prject. Step 1: install the sftware The sftware must be installed befre yu begin. It needs t be tested and shuld be updated with the latest service pack befre use. Released updates shuld als be applied peridically during use. Many universities nw have a site license making access t the sftware relatively simple. Step 2: read and summarise literature There is n substitute fr reading literature, hwever it is up t each researcher t find their wn way t d it prductively. One way t d this is t take ntes while reading the surce. This can be dne by using a highlighter t mark imprtant cncepts r qutes. Anther way (and can be used cmplimentary) is t make ntes in the margin r in a separate ntebk. A further useful tactic when reading research papers is t d a summary at the cnclusin f reading, stating the paper s purpse, methd, apprach and results. Regardless f the apprach, the relevant summary infrmatin and any additinal ntes and cmments can all be imprted int Nviv7 fr cding and inclusin in yur literature analysis. Each researcher has their wn style f reading academic papers; electrnic/hard cpy, duble-spaced/ntes in the margin, highlighting/pencil/pen. Althugh these differences may seem slight t the uninfrmed, they are imprtant persnal preferences that allw a researcher t feel cmfrtable in their wrk. Withut them, a researcher can feel unrganised and unprductive. It is suggested yu find the style that suits yu, prepare and enjy it. At this starting pint, I create my new PhD Nviv7 prject. Once established, I create a new dcument in my prject called prject jurnal, which I write in each time I d any wrk within the sftware (see figure 1). I start my entry by inserting the date/time (under insert menu) and then writing what I did in Nviv7 that day. This is a useful way t track yur cding prcess, and frms part f yur audit prcess. 4th QUALIT Cnference Qualitative Research in IT & IT in Qualitative Research, 2007 Wellingtn, New Zealand

6 Track Title Figure 1. Prject Jurnal Step 3: imprt literature One f the mst difficult tasks in using sftware t manage literature is the sheer amunt f research papers and bks. In a dctral prject (r any research prject fr that matter), the number f surces might reach 1000 r mre. Managing the physical papers in these numbers is challenging, as is managing them in the digital envirnment. Therefre it is necessary t make this prcess manageable and t suit the schedule f each individual researcher. The ther challenge is managing the cmbinatin f electrnic and hard cpy papers. Ideally it wuld be useful if all f ur research papers were available and accessible in electrnic frm, hwever this is nt always practical. Sme jurnals and many cnferences still d nt publish their prceedings nline, and bks bviusly have limitatins. Even with sme electrnic dcuments such as pdf s, at the time f writing these are nt supprted in the current versin f Nviv. Thus managing these different data surces is discussed belw. Yur chice n hw t stre yur many research papers and surces in yur Nviv7 prject will impact n the size f yur prject, hwever this shuldn t be the nly cnsideratin. The tw chices prpsed here are: Imprting the full versin f each f the individual surces int Nviv7 and using externals Imprting summaries f each surce int Nviv7 If yu chse t imprt the full versin f each f the individual surces int Nviv7, there are benefits in keeping track f all f the individual surces in the ne place (bks and hard cpy papers can als be stred as individual external dcuments in Nviv7 giving infrmatin abut their existence s they are prperly included in the literature review). In having them listed individually, it is easy t see hw many research surces are included in the prject and hw many references (pieces cded) exist in each surce. The ther ptin is t imprt summaries f each surce, much like abstracts that can be recrded in (r imprted frm) Endnte. These can be imprted individually fllwing the prcess as suggested abve, r they can be imprted after being cllated in a wrd dcument. The latter is the prcess chsen fr use in this prject because I felt that while it is useful fr managing references, using Endnte alne was limiting fr the analysis task f the literature review. As mst researchers can appreciate, the enrmus amunt f papers reviewed in this PhD research 4th QUALIT Cnference Qualitative Research in IT & IT in Qualitative Research, 2007 Wellingtn, New Zealand

7 Beekhuyzen / Putting the pieces f the puzzle tgether (as in any PhD research) was verwhelming in the beginning. There was anxiety t chse a methd fr rganising the papers, their methds and results. The methd chsen was t put a summary f each paper read cnsecutively int a wrd dcument ver a 3-mnth perid, including the title, the endnte entry (which displays the authr and year published) and any web link t an nline versin f the paper. After this time perid (which was arbitrarily based n my prgress), a new dcument is started s that the cmpleted dcument with summaries culd be imprted int Nviv7, and cding n them can begin immediately. This results in fur large summary dcuments after ne year f reviewing the literature. T explain further, after reading each paper in hard cpy I type the ntes frm it int Wrd, and any (pssibly) relevant qutes are als included. At this time the full reference t the paper is added int endnte and then the citatin is placed in the text f the wrd dcument. Althugh the live reference des nt translate int Nviv7, i.e. it can t be updated r edited, it is pssible t g back t the riginal literature summary dcument t fllw the reference. At the time f placing the citatin in the wrd dcument, the title f the paper is als included. Once cmpleted, the dcument/s are imprted int Nviv7 using the dcuments imprt functin. At this time yu have the ptin t make each dcument int a case; if chsen it then allws yu t add attributes t each case (dcument) such as date imprted (date), number f summaries in the dcument (number), surce type (jurnal/cnf/bk/web) and whether it has been cded (yes/n). Once imprted int Nviv7, I created a flder under dcuments called myntes fr my summary dcuments as well as categries created under externals int the varius surces: jurnals, cnferences, bks, web etc (see figure 2). Each f the imprted dcuments (had yu chsen the 1 st ptin abve) shuld be either imprted r mved int the desired flder. Duble-clicking n the flder will reveal its cntents. Figure 2. Imprted Summaries; Dcuments and Externals Als if yu chse the 1 st ptin abve, yu wuld classify all individual surces under the literature flder (as displayed in figure 2). The reasn fr classifying these dcuments under the literature flder is because yu may decide t use Nviv7 fr yur empirical data as well. In this case, yu are able t separate the types f data and d searches and queries n specific data sets, as well as n data and literature tgether. This will help when writing up 4th QUALIT Cnference Qualitative Research in IT & IT in Qualitative Research, 2007 Wellingtn, New Zealand

8 Track Title the thesis and wrking n linking the empirical data back t the literature review. Alternatively, t d the same searching n abstracts (ptin 2) yu wuld search the ntes and empirical data tgether. It is imprtant t nte that because f the lack f supprt f pdf files in this versin f Nviv (althugh this feature is prmised t be included in future versins), the ptin f the paper summaries was chsen. Once pdf supprt is included, it may make the ther ptin mre feasible fr a prject such as this. Nte: if yu chse t imprt summaries f yur dcuments rather than imprting full individual dcuments, it des take a little extra wrk t g back t the surce as the actual surce dcument is nt listed at the tp f the cding (this link refers t the summary dcument rather than an attached jurnal paper name fr example). Step 4: cding 1 st rund Once the summary dcument r individual dcuments are imprted int Nviv7, cding, r rganising (r even decnstructing), the literature can begin. Firstly, pen the dcument yu want t start with. Then frm the navigatin menu (bttm left f screen), chse ndes, free ndes and the windw fr these is displayed (althugh it will be empty at this starting pint). Having the dcument detail windw and the nde windw pen at the same time allws us t create ndes and cde while reading thrugh the dcument; the nde windw is displayed at the tp f the screen and the dcument is displayed belw. One difficulty is that nce we start creating mre than 30 r s ndes, seeing them all and cding t them with the detail view shwing n the bttm can get difficult. One way t vercme this is t mve the detail view t the right f the screen ( view detail right ). This allws yu t see mre than 50 ndes at ne time and is a lgical way fr many peple t wrk at cding selecting text and placing it in cncepts (i.e. ndes - dragging frm right t left, rather than bttm t tp). Once yu start reading yur first dcument, yu start cding. Ndes shuld be cnsidered as cntainers fr ideas and are created t stre ideas r text abut related cncepts tgether. When yu see cncepts in the literature that yu want t cde, highlight the text, right click and create a new free nde frm the selectin. Anther ptin is t click in the white space f the free nde windw (n tp), right click and create new free nde. Once created, highlight the relevant text, and simply drag it ver the free nde yu want t cde it t. This will cde the text t that nde. Cntinue this prcess f creating new ndes and cding at them until yu reach the end f yur dcument. Figure 3. Ndes fr Cding 4th QUALIT Cnference Qualitative Research in IT & IT in Qualitative Research, 2007 Wellingtn, New Zealand

9 Beekhuyzen / Putting the pieces f the puzzle tgether T give an example, at the start I created a ndes fr cncepts such as music use, technlgy, nline stres and thers (see figure 3). I cded text frm the summary and external dcuments in my surces that relate t these specific cncepts as I have identified them. If a nde categry didn t exist yet, I simply created it as needed. A further ptin fr cding is t highlight sme text that yu want t be the name f a new nde, chse inviv and a new nde will be created with that highlighted text cded there and the name f the nde is the text yu highlighted. This is prbably nt s useful having nly a few wrds cded here s g t the cding spread selectin ptin t get the cntext f the cded text. When ging thrugh this prcess, there are sme imprtant things t remember. First is that any piece f text can be cded infinite times. Hwever just because this is technically pssible, it desn t mean that it is recmmended practice. Generally yu will find that a piece f text is rarely cded at mre than 10 ndes at this pint in the cding prcess (f curse there are exceptins). S try t keep yur cdes rather brad and high level at this stage. Yu will break them dwn int detail sn enugh. But if yu find yu are cding it at mre ndes than this in this instance f 1 st rund cding, then yu might be guilty f cding at t lw a level. This is an imprtant cnsideratin because if yu try t cde at t lw a level in this first instance at this early stage, yu will find yu will feel as thugh yu will never reach the end f the cding, and that it is redundant and smewhat useless. The ther pint t nte is that nt every part f the dcument needs t be cded. There is n prblem in leaving parts f the dcument uncded; these can be cded in a later phase, r left uncded indefinitely. Nt all parts f every paper r summary ntes are relevant hwever yu will find that a larger percentage f the summary ntes will be cded cmpared t the amunt cded if the individual full papers that are imprted. This is because the summaries have already been filtered s that they include what yu have decided is the mst relevant infrmatin, whereas the full papers are just that, cmplete papers will all details. Als useful when creating ndes is t add a descriptin t explain what the nde means. Yu may have a clear idea tday what yu mean but this is almst certain t change in six mnths time. The varius steps utlined s far are imprtant t fllw, and jumping ahead can cause anxiety and frustratin early n. On this nte, my persnal apprach is that it is imprtant t disregard any thughts f structure during this step, hwever I acknwledge that sme ther researchers and trainers apprach this differently by starting with structure. I believe that creating structure and rganising ndes at this time can cause disruptin t yur cding and thught prcesses. Cding a dcument is a very different prcess t structuring and shuld be kept as separate phases in the research prcess. This prcess f cding 1 st rund (r brad cding) shuld be repeated until all imprted dcuments are cded nce. Once dne, then structuring the ndes can begin befre yu start n mre detailed cding. Step 5: structuring ndes One yu have sme free ndes and they have been cded t, and yu have reached smething f a stp pint in the literature review (maybe finished the 1 st rund f cding n all dcuments), it is then time t think abut structure. Yu might find that yu dn t want t include this phase in yur research prcess, r yu might want t include it at a later time (r even earlier), f which all are plausible and valid chices. Structure at this pint refers t tree ndes. Free ndes can be mved arund t frm tree ndes i.e. tree ndes cnsist f siblings (ndes n the same level) and children (sub-ndes). Thus by creating tree ndes yu infer sme frm f hierarchy. The prcess f structuring yur free ndes int tree ndes is dne by cpying a free nde, and pasting it in the apprpriate place in the tree nde structure. Cpying is used in case a mistake is made in mving it; this is a safety measure t ensure we dn t lse any f ur cding (and pssibly even a fallback because f the missin f an und buttn in previus versins f the sftware). In chsing which free ndes wuld be apprpriate as tree ndes, ne way t decide at this pint is t find the ndes yu want t break dwn further (i.e. int sub-categries). By putting them as tp-level tree ndes, it is then easy t pen the tp-level tree nde (which was previusly a free nde) and cde n frm here. Cding n refers t cding frm the already cded nde (which was dne in the 1 st rund f cding). This is a useful apprach as it allws yu t cde frm ne cncept (i.e. culture) and break this dwn int sub categries (i.e. nrms, values, 4th QUALIT Cnference Qualitative Research in IT & IT in Qualitative Research, 2007 Wellingtn, New Zealand

10 Track Title beliefs, rituals), withut being distracted by irrelevant data/literature (it has been filtered ut). This next phase f cding is discussed in step 6 belw 2 nd rund cding. In my prject I mved the DRM definitin free nde t a tree nde and brke it dwn int tech-based with 18 references and rights-based with 7 references frm the literature indicating the different ways f defining digital rights management (see figure 4). I als fund I had ther definitins cded at this high-level nde s I created a new nde fr general definitins. Figure 4. Definitins The ther part t the nde structuring that can be carried ut at this time is t include any cncepts frm mdels, theretical r cnceptual framewrks frm the literature that yu are using t guide yur research. These can be set up as tree ndes, as they usually are hierarchical r at least presented in a cnnected way. Tree ndes allw representatin f this structure and cnnectins, and nw is a gd time t set them up fr cding. Even if yu decide nt t cde t them in step 6, yu can d it at any ther time. Structuring may als refer t free ndes. After the first rund f cding I fund that sme free ndes were dubled up r there were mre than ne with a similar descriptin. These were merged tgether. In my prject, I created 94 free ndes in the 1 st rund f cding. The structuring I did within the free ndes included: bittrrent was expanded t include P2P (peer-t-peer) - merged watermarking and fingerprinting were merged int TPM (technlgical prtectin measures) recrd labels were merged int crprate a nde describing all crprate interests in nline music INDICARE (a Eurpean nline music prject) was merged int DRM studies/prjects DMCA (the US digital cpyright law) was merged int legal The ther ndes t set up here are the relatinship ndes. At this pint, yu may have sme ideas abut relatinships yu have fund r intend t lk fr in the literature (hunches). These can be cded at the relatinship nde rather 4th QUALIT Cnference Qualitative Research in IT & IT in Qualitative Research, 2007 Wellingtn, New Zealand

11 Beekhuyzen / Putting the pieces f the puzzle tgether than at individual ndes; the relatinship is a cnnectin f tw ndes and yu cde evidence f that relatinship existing frm the data. It is als suggested that yu get very familiar with yur ndes and their structure befre cding further. Yu might find it useful t print a cpy f yur nde listing and keep it beside yu r n the wall in frm f yu when cding. This helps t vercme the earlier discussed prblem f viewing all f yur ndes at ne time n the screen. Step 6: cding 2 nd rund This rund f cding is fcused n breaking dwn the already created ndes int sub-ndes, r cding n. As mentined previusly, cding n refers t cding frm an already cded nde. Fr example, a free nde called culture is cded in step 4. Once relevant literature is cded there, and all imprted dcuments are cded, the free nde culture is mved t be a tp-level tree nde. Added t this tp-level nde are sub-ndes (r children) which are categries r cncepts generated as being cnnected and r/deriving frm the tp-level nde. T cntinue the example, cncepts f culture fund in the literature may include nrms, values, beliefs and rituals; these are created as sub-ndes r child ndes, and then frm within the culture nde, cntinue t cde int the lwer-level ndes just created. S in essence, yu are cding data that has already been cded in Step 4. This apprach has the bnus f having a fcus n the filtered literature fr further cding. These sub-ndes (r children) can then be further brken dwn int mre child ndes if required until yu are happy that yur cding is cmplete (r at least smewhat cmplete fr nw). Step 7: analysis Once yu have cded t a level yu are happy with (and it need nly be happy fr nw), yu need t make sme sense f what yu have cded. Putting a literature review tgether is much like a jigsaw puzzle; arranging all f the pieces s that they firstly make lgical sense, and then telling a stry with the final picture. It is nt an easy task t write a gd literature review, regardless f all f the advice n hw t d s (Webster and Watsn 2002). Unfrtunately it is ut f the scpe f this paper t discuss the literature analysis in detail hwever in the fllwing sectin I have highlighted sme useful tactics fr making the mst f yur cded literature. Anther reasn fr discussing this nly briefly is that analysis is shaped by yur chsen research methdlgy and underlying research assumptins and is greatly determined by individual prject needs and characteristics, s thus it is difficult t discuss in general terms. But using the prcess discussed thus far brings literature n yur defined cncepts and tpics tgether, allwing fr a fcus n related literature that frms yur literature review. Cding tips There are a number f features f Nviv7 that are particularly useful during yur literature analysis. These include searching fr cmmn terms, and the use f cding stripes, links and relatinships. There are als sme generic ndes that are useful fr a range f prjects, and these are ften nt cnsidered. Searching cmmn terms It is a useful task t search fr cmmn terms that have appeared in the literature that yu want t be sure t cde. Yu may already have these terms cded, depending n the details f yur previus cding, but yu may nt have them all cvered. T be sure, in my prject I searched fr terms such as Australia, security, privacy, Apple/Sny/Micrsft, itunes, ipd, definitin and many mre. Cding Stripes Cding stripes are useful indicatrs. During cding they can be used t get a quick view as t whether and where a piece f text has been cded answering the questin did I cde that? Smetimes it is difficult t tell if a piece f 4th QUALIT Cnference Qualitative Research in IT & IT in Qualitative Research, 2007 Wellingtn, New Zealand

12 Track Title text was dragged t the intended place, s mving the muse ver the displayed stripes gives a clear and quick answer. Cding stripes may als have benefit as they shw ther literature cded at a particular nde. This may indicate links in cncepts, establishing a thread between the literature, which culd then be made explicit in the writing f yur literature review. Links See als links are a useful feature t create links between yur ideas and the literature. I used see als links rather than creating a new nde fr a cuple f reasns. One reasn is that these links are clearly indicated in the dcument by a red squiggle underline. Als at this pint I felt my list f free ndes was quite lng and I didn t want t add t it, hwever I felt it was imprtant t recrd the ideas, the thinking and the cnnectins, and have a clear link t access them at a later time. Anntatins are als useful fr jtting dwn ntes abut ideas, and fr linking t ideas in ther parts f the prject (i.e. ther dcuments r ndes). Useful Ndes In my review f the literature I have fund that creating sme ther mre generic ndes is useful. Fr instance, I created the fllwing ndes and cded relevant text t them: Statistics Gd qutes Justificatin fr my study Histry Definitins Empirical studies Methd T fllw up Questinable statements Stakehlders: artists, crprate, users Ideas fr interviews I als fund that creating a number f mems (like a small dcument think f a sticky nte) can als be useful. The mems I created fr recrding thughts were: Nviv experiences Methdlgical prblems If yu have smething that yu want t cde and dn t knw where t cde it, simply create a free nde r a mem. Try nt t spend time wrrying abut where it shuld g, even if yu create a nde called t d later and cde it there then at least it is stred fr later access. These are just a number f extra things that yu can d in yur prject. Yu will find the mre yu use the sftware, the mre cnfident and thus explrative yu will becme. Cnclusin This paper discusses the prcess f using Nviv7 fr a literature review in a PhD research prject, hwever the practical steps utlined can be applied t many different research prjects. As discussed early in this paper, qualitative research sftware is nw becming mre mainstream in its use, particularly by research higher degree students. The prcess f literature analysis and synthesis is rarely discussed in detail, apart frm discussins in university research curses and sme research textbks. Because f this, as researchers we need t make mre effrt t share 4th QUALIT Cnference Qualitative Research in IT & IT in Qualitative Research, 2007 Wellingtn, New Zealand

13 Beekhuyzen / Putting the pieces f the puzzle tgether this infrmatin. Part f the challenge f ging thrugh the prcess f a literature review is the lack f detailed and practical help cmpared t ther parts f the research prcess. By explaining ur prcesses, we can help t infrm thse just starting ut by giving them examples f hw it has been dne successfully (r nt s successfully is ften still useful). In the mst part, Nviv7 is used t analyse empirical data hwever this paper has attempted t shw its applicability fr cnducting a large-scale literature review. The varius necessary steps fr setting up and cding the literature are the intermediate utcme f ne particular PhD prject and give sme guidance n hw anther may g abut ding similar tasks. This paper presents a practical accunt f cnducting a literature review in a qualitative research prject. References Bandara, W. (2006). Using Nviv as a research management tl: A case narrative. Prceedings f QualIT2006: Quality and Impact f Qualitative Research, Brisbane, Australia, Nvember, Griffith University. Barry, C. A. (1998). "Chsing qualitative data analysis sftware: Atlas/ti and Nudist cmpared." Scilgical Research Online 3(3): 4. Beekhuyzen, J., A. Cabraal, S. Singh and L. vn Hellens (2006). Cnfessins f a virtual team. Prceedings f QualIT2006: Quality and Impact f Qualitative Research, Brisbane, Australia, Griffith University. Bhattacharyya, S. (2004). If Yu Build It They Will Cme: Creating a Field fr Prject Based Apprach in Learning Science thrugh Qualitative Inquiry and Technlgy Integratin Prceedings f QualIT2004: The Way Frward, Brisbane, Australia, Nvember, Griffith University. Caldeira, M. M. and J. M. Ward (2003). "Using resurce-based thery t interpret the successful adptin and use f infrmatin systems and technlgy in manufacturing small and medium-sized enterprises." Eurpean Jurnal f Infrmatin Systems 12: Dean, A. and J. Sharp (2006). "Getting the mst frm NUD*IST/NViv." The Electrnic Jurnal f Business Research Methds 4(1): di Gregri, S. (2000). Using Nviv fr yur literature review. Strategies in Qualitative Research: Issues and Results frm Analysis using QSR Nviv and Nud*ist, Lndn, September, Institute f Educatin. Fetterman, D. M. (1998). Ethngraphy: Secnd editin: Step-by-step. Lndn, SAGE Publicatins. Hirschheim, R. and H. K. Klein (1989). "Fur paradigms f infrmatin systems develpment." Cmmunicatins f the ACM 32(10): Kaczynski, D. (2004). Curriculum develpment fr teaching qualitative data analysis nline. Prceedings f QualIT2004: Internatinal Cnference n Qualitative Research in IT & IT in Qualitative Research, Brisbane, Australia, Nvember, Griffith University. Klein, H. K. and M. D. Myers (1999). "A set f principles fr cnducting and evaluating interpretive field studies in infrmatin systems." MIS Quarterly 23(1): Myers, M. D. (1999). Qualitative research in infrmatin systems, IS Wrld. Patashnick, J. and M. Rich (2004). "Researching human experience: Vide interventin/preventin assessment (VIA)." Australian Jurnal f Infrmatin Systems 12(2): Walsham, G. (1992). Interpreting infrmatin systems in rganizatins. New Yrk, Jhn Wiley & Sns. Webster, J. and R. T. Watsn (2002). "Analyzing the past t prepare fr the future: Writing a literature review." MIS Quarterly 26(2): 13. Wds, M. and M. Wickam (2006). Methdlgical implicatins f sftware use: an empirical investigatin f sftware prgrams n literature analysis using n6 and nviv. Prceedings f QualIT2006: Quality and Impact f Qualitative Research, Brisbane, Australia, Nvember, Griffith University. 4th QUALIT Cnference Qualitative Research in IT & IT in Qualitative Research, 2007 Wellingtn, New Zealand