Orig­i­nal source pub­li­ca­tion: Car­valho, J. Á. e F. de Sá-Soares (2022). Sis­temas de Infor­mação—Uma Reflexão sobre a Natureza da Área Cien­tí­fica de Sis­temas de Infor­mação: Da Inves­ti­gação Cien­tí­fica à Prática Profis­sional. In Ramos, I., R. D. Sousa e R. Quaresma (Eds.), Sis­temas de Infor­mação—Diag­nós­ti­cos e Prospeti­vas, pp. 21–44, Lis­boa: Edições Sílabo.
The final pub­li­ca­tion is avail­able here.

Infor­ma­tion Sys­tems—A Reflec­tion on the Nature of the Sci­en­tific Field of Infor­ma­tion Sys­tems: From Sci­en­tific Research to Pro­fes­sional Prac­tice

João Álvaro Car­valho and Fil­ipe de Sá-Soares

Uni­ver­sity of Minho, Por­tu­gal

1. Introduction

We can con­sider that the sci­en­tific field of infor­ma­tion sys­tems (IS) emerged in the 1960s with the real­iza­tion that the use of com­put­ers (elec­tronic, dig­i­tal) to process infor­ma­tion in orga­ni­za­tions/enter­prises con­sti­tutes itself a dis­tinct field of aca­d­e­mic inter­est. Being a young sci­en­tific field, it is not sur­pris­ing that its nature and legit­i­macy might be, from time to time, ques­tioned or, some­times, not at all under­stood. Indeed, its inher­ent inter­dis­ci­pli­nar­ity makes its scope dif­fuse and allows the exis­tence of dif­fer­ent per­spec­tives, anchored in each one of the mul­ti­ple fields that con­trib­ute to it.

This arti­cle should be under­stood as an essay in which the nature of the sci­en­tific field of IS is pre­sented and jus­ti­fied, reveal­ing the posi­tion of its authors on the sub­ject. There­fore, it does not cor­re­spond to a report of empir­i­cal research. It will present and debate the objects of inter­est of the sci­en­tific field, the pro­fes­sional pro­files to which it is asso­ci­ated and the meth­ods of sci­en­tific inquiry it uses.

The point of men­tion­ing pro­fes­sional pro­files asso­ci­ated with the IS field is sig­nif­i­cant. On the one hand, the IS field has been asso­ci­ated with voca­tional train­ing con­cerns since its incep­tion—the prepa­ra­tion of pro­fes­sion­als that, in enter­prises, make it eas­ier to obtain and use infor­ma­tion tech­nol­ogy (IT)—com­put­ers and related tech­nolo­gies—to achieve some kind of busi­ness ben­e­fit. On the other hand, it is easy to rec­og­nize that a sig­nif­i­cant part of the body of knowl­edge that con­sti­tutes the field has a clear ori­en­ta­tion towards actions that seek the suc­cess of enti­ties that use IT in order to, some­how, process the infor­ma­tion they are deal­ing with.

The arti­cle begins by pre­sent­ing brief his­tor­i­cal ref­er­ences to the IS field (Sec­tion 2) to make it eas­ier to under­stand how the field emerged. A char­ac­ter­i­za­tion of the field in terms of its objects of inter­est and pos­si­ble units of analy­sis fol­lows (Sec­tion 3). This sec­tion also defends the impor­tance of con­sid­er­ing the IS field asso­ci­ated with a range of pro­fes­sional activ­i­ties. Sec­tion 4 presents the main pro­fes­sional func­tions of the IS field and how they relate to the objects of inter­est above exposed. These func­tions are used to jus­tify the use of the expres­sion “engi­neers and man­agers of infor­ma­tion sys­tems” to des­ig­nate pro­fes­sion­als of IS. The con­duc­tion of IS pro­fes­sional func­tions legit­imizes the recog­ni­tion of a body of knowl­edge of its own, whose com­po­nents are pre­sented in Sec­tion 5. The dif­fer­ent com­po­nents of a body of knowl­edge of a sci­en­tific field that includes a pro­fes­sional side are the basis for dis­tin­guish­ing dif­fer­ent types of research activ­i­ties and, tak­ing into account the nature of the IS field, high­light­ing the inevitabil­ity of using a wide range of research meth­ods (Sec­tion 6). The con­clu­sions (Sec­tion 7) present work pro­pos­als whose start­ing point are the ideas pre­sented in this essay.

2. The Emergence of the Scientific Field of Information Systems

The require­ments for the recog­ni­tion of a sci­en­tific field are dif­fuse. Machlup and Mans­field [1983] describe, with irony, the cri­te­ria for what can be con­sid­ered a sci­en­tific dis­ci­pline: “what a num­ber of peo­ple, respected for hav­ing read widely and for being read by other widely read peo­ple, have claimed to be dis­ci­plines” (p. 3). Con­sid­er­ing the diver­sity of pub­lished books and sci­en­tific arti­cles, exist­ing sci­en­tific jour­nals and aca­d­e­mic com­mu­ni­ties, infor­mal and for­mal, that it is pos­si­ble to find, in the light of that cri­te­ria there will be no doubts about the legit­i­macy of the IS sci­en­tific field/dis­ci­pline. Other ele­ments asso­ci­ated with the exis­tence of a sci­en­tific field include pro­fes­sor posi­tions (pro­fes­sor­ships), aca­d­e­mic train­ing pro­grams (bach­e­lor’s degrees, mas­ter’s degrees, doc­tor­ates), aca­d­e­mic text­books, uni­ver­sity depart­ments and research units that for­mal­ize and struc­ture around the sci­en­tific field. The emer­gence of this type of ele­ments makes it eas­ier to iden­tify the ori­gins of the sci­en­tific field inso­far as it reveals its for­mal man­i­fes­ta­tions, an addi­tional sign of some matu­rity and accep­tance. In the case of the IS field, such man­i­fes­ta­tions emerged dur­ing the 1960s. Exam­ples include pro­fes­sor­ship in admin­is­tra­tive data pro­cess­ing at Stock­holm Uni­ver­sity, Swe­den, 1965 [Bubenko, Jr. 2009]; grad­u­ate courses (mas­ter’s and doc­tor­ate) in Man­age­ment Infor­ma­tion Sys­tems, Uni­ver­sity of Min­nesota, USA, 1968 [Davis 2015]; research cen­ter at the Uni­ver­sity of Min­nesota—Man­age­ment Infor­ma­tion Sys­tems Research Cen­ter (MISRC), 1968 [Davis 2015]; and the book Man­age­ment Infor­ma­tion Sys­tems: Text and Cases, pub­lished in 1966 [Dear­den and McFar­land 1966].

The name used—man­age­ment infor­ma­tion sys­tems (MIS)—reflects the ini­tial focus of the field: the use of com­put­ers to pro­duce infor­ma­tion capa­ble of improv­ing deci­sion-mak­ing and increase man­agers’ con­trol of enter­prises. It could be said that this focus replaces a pre­vi­ous con­cern cen­tered on effi­cient infor­ma­tion pro­cess­ing, asso­ci­ated with des­ig­na­tions such as auto­matic data pro­cess­ing or elec­tronic data pro­cess­ing. How­ever, as the scope of com­put­ers appli­ca­tion expanded, new areas of inter­est have emerged [Bacon and Fitzger­ald 1996]. Deci­sion Sup­port Sys­tems, Strate­gic Infor­ma­tion Sys­tems, End-User Com­put­ing, Infor­ma­tion Resource Man­age­ment and Infor­ma­tion Sys­tems Man­age­ment are exam­ples of des­ig­na­tions that have been emerg­ing in the sub­se­quent decades and that reflect new con­cerns about the use of com­put­ers in enter­prises. At the same time, in reac­tion to the reper­cus­sions that the oper­a­tion of com­puter and plat­form appli­ca­tions have been hav­ing in con­texts other than that of enter­prises, the IS field has been incor­po­rat­ing other con­cerns and inter­ests, such as e-democ­racy, infor­ma­tion soci­ety, smart cities, cyber war­fare, etc.

3. Characterization of the IS Field

3.1 Objects of Interest and Relevant Phenomena

What we now call IS is there­fore a sci­en­tific field that involves any man­i­fes­ta­tions of IT (com­put­ers and other con­comi­tant tech­nolo­gies of auto­matic pro­cess­ing of infor­ma­tion, either in terms of appli­ca­tions and infra­struc­tures), which includes dif­fer­ent types of infor­ma­tion objects, and which encom­passes a diverse range of sit­u­a­tions and con­texts where infor­ma­tion tech­nolo­gies are used in infor­ma­tion pro­cess­ing.

IS thus involves the com­bi­na­tion of three areas of inter­est: IT, infor­ma­tion, and the human endeav­ors and social sit­u­a­tions in which IT oper­ates. Fig­ure 1 seeks to illus­trate that the com­bi­na­tion of these three areas leads to the emer­gence of a space, of an inter­dis­ci­pli­nary nature, where IS objects of inter­est are included—area marked 1.2.3 in Fig­ure 1.

Fig­ure 1: The cien­tific field of Infor­ma­tion Sys­tems (IS) as a space where three areas inter­sect (inter­dis­ci­pli­nary) whose objects of inter­est are infor­ma­tion tech­nolo­gies, infor­ma­tion, and human endeav­ors and social sit­u­a­tions

Fig­ure 1 also shows the pos­si­bil­ity of inter­sect­ing spaces, which involve only two of those areas (1.2, 1.3 and 2.3). These are hinge spaces that are both rec­og­nized as IS and also as part of any of the other areas involved. The Fig­ure also shows the spaces where each of those areas is con­sid­ered in iso­la­tion, with­out inter­sect­ing with the oth­ers, i.e., with­out the ele­ments of the other areas tak­ing rel­e­vance. Con­se­quently, these are spaces that are already out­side the IS field.

The cen­tral area is par­tic­u­larly inter­est­ing and chal­leng­ing. From the point of view of research involves address­ing a com­bi­na­tion of objects of inter­est—at dif­fer­ent lev­els of analy­sis—which brings with it the need to resort to a wide vari­ety of research meth­ods. And, in the dimen­sion of pro­fes­sional prac­tice, implies the use of approaches that, because they include human and social aspects, as well as tech­ni­cal arti­facts, are some­times referred to as socio-tech­ni­cal approaches.

Fig­ure 2 aims to com­ple­ment the char­ac­ter­i­za­tion of the IS field.

Fig­ure 2: Units of Analy­sis in the Sci­en­tific Field of Infor­ma­tion Sys­tems

This char­ac­ter­i­za­tion presents var­i­ous pos­si­bil­i­ties for the units of analy­sis in IS. In the area of human endeav­ors and social sit­u­a­tions there is the wide range of sit­u­a­tions that con­tex­tu­al­ize the oper­a­tion of IT that may be the object of atten­tion in IS. Based on the indi­vid­ual, two aspects are con­sid­ered: (i) the aspect that involves the indi­vid­ual in the con­text of work, car­ried out within the frame­work of a enter­prise oper­at­ing in a mar­ket, and (ii) the aspect of leisure and life in soci­ety that can be seen at var­i­ous lev­els of involve­ment. In the back­ground, the envi­ron­ment is also rep­re­sented, the human­ity’s com­mon home, which has been dra­mat­i­cally affected by the activ­i­ties of human beings and whose safe­guard­ing is also of inter­est to the field of IS.

With regard to infor­ma­tion, Fig­ure 2 men­tions two facets of human beings that involve the cre­ation and con­sump­tion of infor­ma­tion: cog­ni­tion and com­mu­ni­ca­tion. Cog­ni­tion refers to the cre­ation and use of knowl­edge and involves var­i­ous processes that are the object of study in cog­ni­tive psy­chol­ogy, such as, pat­tern recog­ni­tion, atten­tion, mem­ory, visual images, lan­guage, prob­lem res­o­lu­tion, and deci­sion-mak­ing [Reed 1996]. Cog­ni­tive psy­chol­ogy focuses on men­tal processes that take place in a human brain. How­ever, we can eas­ily iden­tify their cor­re­spon­dents occur­ring on com­puter media. In fact, cog­ni­tive psy­chol­ogy and com­puter sci­ence have been influ­enc­ing each other. The works of authors such as Allen Newell, Her­bert Simon, John McCarthy and Mar­vin Min­sky, con­sid­ered the founders of arti­fi­cial intel­li­gence, are rec­og­nized for their rel­e­vance both to the cog­ni­tive sci­ences and to com­put­ing. For its part, com­mu­ni­ca­tion refers to social processes which ulti­mately cor­re­spond to attempts to influ­ence other(s). Com­mu­ni­ca­tion involves the pro­duc­tion of mes­sages by a sender who expects that they are received, under­stood, accepted and lead to some form of effect, pos­si­bly some action, on the part of the recip­i­ents of those mes­sages [Stan­ton 1990]. IT has been play­ing an impor­tant role in com­mu­ni­ca­tion (see the fre­quent use of the term “infor­ma­tion and com­mu­ni­ca­tion tech­nolo­gies”—ICT), espe­cially in sup­port of the trans­mis­sion of mes­sages inher­ent to the com­mu­ni­ca­tion between the devices used to medi­ate com­mu­ni­ca­tion. Beyond trans­mis­sion, made pos­si­ble by the net­works that inter­con­nect the count­less com­put­ing devices in the world, the action of IT has implied the estab­lish­ment of pro­to­cols, stan­dards and tech­no­log­i­cal mech­a­nisms that ensure that the trans­mit­ted sig­nals are prop­erly processed to guar­an­tee the effec­tive inter­con­nec­tion of dif­fer­ent com­put­ing devices, pro­duced by dif­fer­ent man­u­fac­tur­ers. So, nowa­days, we are no longer sur­prised that any com­put­ing device is capa­ble of send­ing and receiv­ing mes­sages to/from any other com­put­ing device. More recently, we have seen efforts to extend the abil­ity of com­put­ing devices to learn the con­tent of a mes­sage by includ­ing addi­tional infor­ma­tion pro­vid­ing sup­ple­men­tary ele­ments related to the con­text of the com­mu­ni­ca­tion or the inten­tion behind the emis­sion of the mes­sage (prag­mat­ics and social lev­els of Stam­per’s semi­otic lad­der [1973, 1996], [Falken­berg et al. 1998]). These efforts mainly seek to address con­cerns of stan­dard­iza­tion that form the basis of the so-called Seman­tic Web.

Finally, with regard to the IT area, Fig­ure 2, on the left-hand side, begins by dis­tin­guish­ing between IT appli­ca­tions and IT infra­struc­ture. The for­mer include tech­nolo­gies that are directly related to the exe­cu­tion of busi­ness activ­i­ties or other activ­i­ties within the scope of human endeav­ors and social sit­u­a­tions. The lat­ter includes tech­nolo­gies that make it pos­si­ble for the for­mer to func­tion, but which are not directly involved in those activ­i­ties. Infra­struc­ture tech­nolo­gies can be con­cep­tu­al­ized in sev­eral lay­ers, cor­re­spond­ing to suc­ces­sive lev­els of dis­tance from IT appli­ca­tions (e.g., data­base man­age­ment sys­tem, oper­at­ing sys­tem, com­mu­ni­ca­tions infra­struc­ture, device dri­vers, firmware, and hard­ware). On the other hand, the com­po­nents that typ­i­cally make up an IT appli­ca­tion (inter­face, com­put­ing mech­a­nisms, stor­age mech­a­nisms and com­mu­ni­ca­tion or trans­mis­sion mech­a­nisms) are made explicit.

3.2 Activities on the Objects of Interest

The char­ac­ter­i­za­tion of a sci­en­tific field can­not be lim­ited to a descrip­tion of its objects of inter­est and rel­e­vant phe­nom­ena. The nature of the activ­i­ties on the objects of inter­est need to be defined. The ques­tion is whether the IS field should be under­stood as cor­re­spond­ing only to one area of research whose results essen­tially con­trib­ute to enrich­ing under­stand­ing of the phe­nom­ena it encom­passes, or whether it also involves activ­i­ties in which its body of knowl­edge is applied by (IS) pro­fes­sion­als to prob­lem-solv­ing and the cre­ation of devel­op­ment oppor­tu­ni­ties for indi­vid­u­als, enter­prises or soci­ety. This arti­cle takes the view that that the IS field com­prises the two types of activ­i­ties men­tioned.

Fig­ure 3 seeks to rep­re­sent this under­stand­ing and illus­trate the com­ple­men­tary role of these two types of activ­i­ties and their rela­tion­ship with the body of knowl­edge of the field. The left-hand side of Fig­ure 3 illus­trates the role of research and devel­op­ment activ­i­ties to expand the body of knowl­edge of IS. The right-hand side shows the IS pro­fes­sional activ­i­ties that apply that body of knowl­edge in inter­ven­tions that, in some way, affect the objects of inter­est.

Fig­ure 3: Scope of the IS sci­en­tific field, includ­ing research and devel­op­ment activ­i­ties and pro­fes­sional inter­ven­tion activ­i­ties in sit­u­a­tions involv­ing the field’s objects of inter­est; the dashed cir­cle on the right in the fig­ure empha­sizes that IS research also cov­ers the activ­i­ties of IS pro­fes­sion­als

The assump­tion that the IS field encom­passes a branch of research and devel­op­ment and a branch of pro­fes­sional activ­i­ties has impor­tant con­se­quences. On the one hand, it requires the def­i­n­i­tion of the typ­i­cal func­tions of IS pro­fes­sion­als. On the other hand, it requires broad­en­ing the range of forms of research to be con­sid­ered under research and devel­op­ment activ­i­ties, in order to con­tem­plate the cre­ation of knowl­edge related to the prac­tices of IS pro­fes­sion­als and the means and ways of work­ing.

4. IS Professional Functions

This sec­tion describes the typ­i­cal pro­fes­sional func­tions of an IS pro­fes­sional. These func­tions focus on the objects of inter­est pre­vi­ously pre­sented, thus involv­ing the pro­cess­ing of infor­ma­tion, by human and com­pu­ta­tional arti­facts, within the scope of human endeav­ors and social sit­u­a­tions. The func­tions con­sid­ered are:¹

1. Infor­ma­tion cura­tion
This func­tion involves look­ing after an enter­prise’s infor­ma­tion, seek­ing to guar­an­tee the avail­abil­ity of the infor­ma­tion nec­es­sary for the well-being of the enter­prise and the pur­suit of its activ­i­ties. It includes sub-func­tions, such as, cat­a­loging and orga­niz­ing infor­ma­tion objects; orga­niz­ing descrip­tions of infor­ma­tion objects in order to facil­i­tate their use, both by humans and by arti­facts, and using com­puter lan­guages that facil­i­tate the pre­sen­ta­tion of infor­ma­tion on dig­i­tal sup­ports.

2. Enliven­ment of infor­ma­tional objects through infor­ma­tion tech­nol­ogy
It involves the use of IT to gen­er­ate new infor­ma­tion that brings ben­e­fits for the enter­prise (goal-seek­ing entity) (solv­ing exist­ing prob­lems, iden­ti­fy­ing oppor­tu­ni­ties, etc.). It includes sub-func­tions, such as, research­ing, select­ing, installing and oper­at­ing IT appli­ca­tions capa­ble of pro­cess­ing and pre­sent­ing infor­ma­tion in a man­ner appro­pri­ate to the needs iden­ti­fied and the intended uses for the infor­ma­tion; and search­ing, select­ing, installing and exploit­ing IT plat­forms that sup­port and enable col­lec­tion, stor­age and retrieval, pre­sen­ta­tion and dis­sem­i­na­tion of infor­ma­tion tak­ing into account intended uses for infor­ma­tion.

3. Devel­op­ment of IT appli­ca­tions
It involves design­ing and build­ing IT appli­ca­tions, mainly by com­bin­ing high-level com­po­nents (con­tent man­age­ment plat­forms, data­base man­age­ment plat­forms, work­flow man­age­ment plat­forms, com­po­nent libraries, etc.). It cov­ers the devel­op­ment of inter­face chan­nels with users and other appli­ca­tions or ser­vices, mech­a­nisms for infor­ma­tion stor­age, com­put­ing mech­a­nisms, and com­mu­ni­ca­tions mech­a­nisms. The devel­op­ment of IT appli­ca­tions includes estab­lish­ment of the require­ments that the appli­ca­tion must meet; the require­ments may have been pre­vi­ously defined (and will have to be inter­preted and val­i­dated) or may have to be iden­ti­fied or defined. The devel­op­ment process of IT appli­ca­tions, in addi­tion to estab­lish­ing require­ments, involves the design of the appli­ca­tion archi­tec­ture, its con­struc­tion and the ver­i­fi­ca­tion (test) that it meets the require­ments.

4. Implan­ta­tion of IT appli­ca­tions
It involves prepar­ing and mak­ing IT appli­ca­tions avail­able in the envi­ron­ment where they will be used. It encom­passes the fol­low­ing sub-func­tions: select­ing and acquir­ing or get­ting appli­ca­tion pack­ages—typ­i­cally COTS prod­ucts (Com­mer­cial-Off-The-Shelf)/RUSP (Ready to Use Soft­ware Prod­ucts);² installing and con­fig­ur­ing IT appli­ca­tions; trans­fer­ring exist­ing infor­ma­tion to the new IT appli­ca­tion; ver­i­fy­ing (tests) that the IT appli­ca­tion exhibits the expected behav­ior and is able to meet the expec­ta­tions of the inter­ven­tion that frames the implan­ta­tion process; adjust­ing the new IT appli­ca­tion to the exist­ing IT infra­struc­ture and adapt­ing this infra­struc­ture to the new IT appli­ca­tion; prepar­ing the enter­prise for oper­a­tion of the new IT appli­ca­tion.

The enter­prise’s prepa­ra­tion for the oper­a­tion of the new IT appli­ca­tion focuses on orga­ni­za­tional and social aspects, includ­ing: redefin­ing processes/activ­i­ties of the enter­prise, train­ing of the enter­prise’s employ­ees and man­ag­ing orga­ni­za­tional change.

5. Upkeep­ing of the port­fo­lio of IT appli­ca­tions
This func­tion seeks to ensure the proper func­tion­ing of all IT appli­ca­tions in oper­a­tion in an enter­prise. It includes related sub-func­tions with: ensur­ing inte­gra­tion or inter­op­er­abil­ity between IT appli­ca­tions; updat­ing, upgrad­ing, over­haul­ing and tun­ing IT appli­ca­tions; opti­miz­ing IT appli­ca­tions with regard to effi­ciency, secu­rity, etc.

6. Design of IS archi­tec­tures
The term design includes draw­ing up, updat­ing and revis­ing archi­tec­tures of IS. IS archi­tec­tures are rep­re­sen­ta­tions that encom­pass the var­i­ous aspects of IS—tak­ing into account the pur­pose of the sys­tems (and sub­sys­tems) and mak­ing explicit the inter­con­nec­tions between activ­i­ties, infor­ma­tion, exter­nal enti­ties (envi­ron­ment), peo­ple and/or orga­ni­za­tional units, IT appli­ca­tions and IT infra­struc­tures.

IS archi­tec­tures show the orga­ni­za­tional struc­tures related to infor­ma­tion pro­cess­ing and make it eas­ier to visu­al­ize the role that IT can play in these struc­tures.

IS archi­tec­tures are used in vir­tu­ally all pro­fes­sional func­tions of IS and also play an impor­tant role in the par­tic­i­pa­tion of IS pro­fes­sion­als in busi­ness inter­ven­tions involv­ing other spe­cial­ties of enter­prise man­age­ment. Whether in inter­ven­tions that require a holis­tic per­spec­tive of the enter­prise (e.g., strate­gic plan­ning, orga­ni­za­tional design, etc.), or in inter­ven­tions aimed at spe­cific sec­tors of enter­prises (e.g., pro­duc­tion, mar­ket­ing, sales, human resources, finance, etc.) or (trans­ver­sal) aspects of the enter­prise (e.g., imple­men­ta­tion of mech­a­nisms for qual­ity man­ag­ing, imple­men­ta­tion of knowl­edge man­age­ment and orga­ni­za­tional learn­ing mech­a­nisms, pro­mot­ing change in enter­prise cul­ture, etc.). In these inter­ven­tions, IS archi­tec­tures sup­port the pre­sen­ta­tion of the poten­tial of IT and the under­tak­ing of activ­i­ties that involve chang­ing the pro­cess­ing of infor­ma­tion, in par­tic­u­lar those aimed at achiev­ing the ben­e­fits aris­ing from the use of infor­ma­tion and IT.

7. Set­ting up of infor­ma­tion-cen­tered, IT-enhance­able enter­prise capa­bil­i­ties
The smooth run­ning and well-being of enter­prises involves var­i­ous capa­bil­i­ties cen­tered on infor­ma­tion that in some way con­trib­ute to their effi­ciency, auton­omy, sus­tain­abil­ity and adap­ta­tion to changes in the envi­ron­ment. It is not easy to iden­tify a com­plete and coher­ent list of these capa­bil­i­ties. In fact, these capa­bil­i­ties are asso­ci­ated with dif­fer­ent per­spec­tives on the func­tion­ing of the enter­prise that empha­size dif­fer­ent facets of that func­tion­ing or that delimit some aspect of the enter­prise in a dif­fer­ent way. In some cases, dif­fer­ent capa­bil­i­ties even cor­re­spond to dif­fer­ent per­spec­tives on the same aspect. What all capa­bil­i­ties have in com­mon is that they are heav­ily depen­dent on infor­ma­tion pro­cess­ing and exist in all enter­prises, regard­less of their size or activ­ity sec­tor.

The fol­low­ing list seeks to include capa­bil­i­ties that have been be the object of atten­tion in the IS field: coop­er­a­tion; coor­di­na­tion (by orches­tra­tion or by chore­og­ra­phy); com­mand and con­trol; com­pet­i­tive intel­li­gence; def­i­n­i­tion of poli­cies; orga­ni­za­tional design; process design; plan­ning and con­trol of projects; con­tin­u­ous improve­ment; busi­ness intel­li­gence; knowl­edge man­age­ment; orga­ni­za­tional learn­ing; and inno­va­tion. Under­ly­ing these capa­bil­i­ties, one can also con­sider the deci­sion-mak­ing capa­bil­ity, which in turn involves: gath­er­ing infor­ma­tion; iden­ti­fy­ing prob­lems and oppor­tu­ni­ties; gen­er­at­ing alter­na­tives; choos­ing alter­na­tive; imple­ment­ing the cho­sen alter­na­tive and mon­i­tor­ing the con­se­quences of deci­sions taken. As all these capa­bil­i­ties are based on infor­ma­tion pro­cess­ing, it is under­stood that they can be the object of (re)struc­tur­ing (and even trans­for­ma­tion) by the appli­ca­tion of IT.

This func­tion (7) involves: ana­lyz­ing and diag­nos­ing the capa­bil­ity in ques­tion; design­ing the orga­ni­za­tional capa­bil­ity, tak­ing into account the pos­si­bil­i­ties of IT; plan­ning the orga­ni­za­tional changes nec­es­sary in the enter­prise to imple­ment the new ver­sion of these capa­bil­i­ties and imple­ment­ing these changes (in col­lab­o­ra­tion with other orga­ni­za­tional experts).

8. Over­sight of IT infra­struc­tures
Over­sight involves select­ing, installing, con­fig­ur­ing and adjust­ing IT plat­forms (e.g. DBMS, DW, WFMS, BI, etc.) that sup­port IT appli­ca­tions; defin­ing require­ments (func­tional and per­for­mance) for ser­vices and IT plat­form infra­struc­ture; nego­ti­at­ing require­ments and ser­vice level agree­ments (SLA) for an enter­prise’s IT infra­struc­ture; and audit­ing of an instal­la­tion and of com­pli­ance with the ser­vice level agree­ments of the IT infra­struc­ture. It is con­sid­ered that the design and imple­men­ta­tion of the IT infra­struc­ture for a per­sonal instal­la­tion or for a micro/small busi­ness are also func­tions of an IS pro­fes­sional.

9. Con­trol of the fit between the infor­ma­tion sys­tems archi­tec­ture and the real­ity
This func­tion involves assess­ing the cor­re­spon­dence between the IS archi­tec­ture (as a rep­re­sen­ta­tion of the infor­ma­tion sys­tem) and the way the enter­prise effec­tively han­dles infor­ma­tion. It also includes estab­lish­ing and mon­i­tor­ing inter­nal con­trol mech­a­nisms designed to pre­vent and detect the occur­rence of errors and irreg­u­lar­i­ties in infor­ma­tion manip­u­la­tion activ­i­ties. In the event of sig­nif­i­cant gaps, inquiries and cor­rec­tions are car­ried out. Scrutiny actions can focus on sev­eral aspects related to the enter­prise’s infor­ma­tion sys­tem, such as, the qual­ity of the gov­er­nance of IT and IS, the integrity of IS, the effec­tive­ness of IT and IS with regard to meet­ing the enter­prise’s objec­tives, the qual­ity of infor­ma­tion objects han­dled by the enter­prise, the effi­ciency of IT and the need and suf­fi­ciency of the com­pe­ten­cies, processes and resources assigned to the infor­ma­tion sys­tems and tech­nol­ogy func­tion. Con­duct­ing the eval­u­a­tion activ­ity requires spe­cial atten­tion to pro­vi­sions con­tained in leg­is­la­tion, reg­u­la­tions and con­trac­tual oblig­a­tions that affect IS-related processes, as well as nor­ma­tive ref­er­ences which aim to stan­dard­ize good prac­tices in the man­age­ment and exploita­tion of IT and IS.

10. Stud­ies on the impact of infor­ma­tion sys­tems and tech­nol­ogy on soci­ety
The stud­ies help for­mu­late poli­cies (at local, regional, national, multi­na­tional or global level) in rela­tion to the social, eco­nomic, polit­i­cal and cul­tural issues that might be affected by IT-related devel­op­ments.

It involves activ­i­ties such as: iden­ti­fy­ing impacts and influ­ences (econo­met­rics) of the use of IT in indi­vid­u­als, enter­prises, mar­kets or soci­ety; gen­er­at­ing sce­nar­ios and explor­ing sim­u­la­tions on sce­nario rep­re­sen­ta­tions, and pro­duc­ing jus­ti­fied rec­om­men­da­tions to achieve desir­able sce­nar­ios or to avoid unde­sir­able ones.

11. Admin­is­tra­tion of the infor­ma­tion sys­tems and tech­nol­ogy unit
Meta-func­tion aimed at improv­ing the pro­duc­tiv­ity of the resources allo­cated to the infor­ma­tion sys­tems and tech­nol­ogy func­tion, tak­ing into account the poli­cies of the enter­prise. It includes report­ing to the enter­prise’s exec­u­tive man­age­ment.

It should be noted that in the list of func­tions pre­sented above, we have tried to limit those falling within the cen­tral zone of Fig­ure 1. Var­i­ous other activ­i­ties can be added by expand­ing to other areas of the fig­ure, either zones 1.2, 1.3 and 2.3, or zones 1, 2 and 3. In any case, in each one of the func­tions it will be able to rec­og­nize foci or propen­si­ties for cer­tain objects in Fig­ure 1 (IT, infor­ma­tion or human endeav­ors and social sit­u­a­tions). Table 1 shows these foci, through a pic­to­r­ial rep­re­sen­ta­tion of the inten­sity with which each of the pro­fes­sional func­tions deals with each of the objects of inter­est. This rep­re­sen­ta­tion is based on the dia­gram in Fig­ure 1.1, assum­ing three lev­els of inten­sity for each object (low, medium and high), sig­naled by dif­fer­ent degrees of com­ple­tion (the nature of the “Admin­is­tra­tion of infor­ma­tion sys­tems and tech­nol­ogy func­tion” meta-func­tion—has been marked dif­fer­ently from the other func­tions). Table 1 also indi­cates which of the func­tions cor­re­spond to what you would expect from pro­fes­sion­als in the begin­ning of their careers. These are the roles that should be priv­i­leged in ini­tial train­ing study cycles (1^st cycle—bach­e­lor’s degree), either because they cor­re­spond to posi­tions that are more in demand on the job mar­ket, either because they require lower lev­els of matu­rity on the part of their per­form­ers in the con­text of the early stages of the IS pro­fes­sional’s career.

Table 1: Cat­e­go­riza­tion of Infor­ma­tion Sys­tems Pro­fes­sional Roles

The set of func­tions described above forms the core of a pro­file that we denom­i­nate by engi­neer­ing and man­age­ment of infor­ma­tion sys­tems. Engi­neer­ing and man­age­ment are dif­fuse con­cepts that com­ple­ment each other and that over­lap. Both are related to iden­ti­fy­ing and solv­ing prob­lems. Both cases also involve the exer­cise of design in the sense used by Simon [1981] in his book The Sci­ences of the Arti­fi­cial:

“Every­one designs who devises courses of action aimed at chang­ing exist­ing sit­u­a­tions into pre­ferred ones.” (p. 129).

Engi­neer­ing refers to func­tions related to arti­facts whose nature, phys­i­cal, chem­i­cal or bio­log­i­cal, is a source of restric­tions to its ideation, struc­tur­ing, imple­men­ta­tion and oper­a­tion. For its part, man­age­ment refers to look­ing after sit­u­a­tions where humans are present. But it also includes delib­er­ate struc­tur­ing of such sit­u­a­tions or influ­enc­ing them so they evolve to some state con­sid­ered pre­fer­able. Thus, engi­neer­ing and man­age­ment are dis­tin­guished.

How­ever, it is com­mon that in sit­u­a­tions where humans are present there are also arti­facts oper­at­ing (with greater or lesser auton­omy) that result from the engi­neer­ing work. On the other hand, these arti­facts, once inte­grated into the sit­u­a­tions for which they were con­ceived (or where they ended up being exploited) need to be mon­i­tored so that their per­for­mance can be con­trolled and adjusted. Fur­ther­more, many (per­haps most) of the social sit­u­a­tions that are the object of man­age­ment’s atten­tion can be con­sid­ered arti­fi­cial in the sense they were inten­tion­ally cre­ated by humans. Although their dynam­ics is not dom­i­nated by the laws of phys­i­cal, chem­i­cal or bio­log­i­cal nature, but by the “laws” of human and social behav­ior, at some point these arti­fi­cial enti­ties are also the object of ideation, struc­tur­ing and real­iza­tion. It is in these senses that engi­neer­ing and man­age­ment com­ple­ment each other and even over­lap, thus con­tribut­ing to their dis­tinc­tion becom­ing blurred.

The objects of inter­est in the IS field, as pre­sented in Sec­tion 3, con­trib­ute to rein­forc­ing the indis­tinct­ness men­tioned above.

Firstly, because they include an arti­fact—infor­ma­tion—which although lacks a sub­strate, it depends lit­tle on the laws to which that sub­strate is sub­ject. The impor­tance of this arti­fact lies in the mean­ing attrib­uted to it by peo­ple in the con­text of human endeav­ors and social sit­u­a­tions. Thus, although its con­cretiza­tion is affected by the laws of physics, in the ideation and struc­tur­ing of infor­ma­tion, the processes of cog­ni­tion and com­mu­ni­ca­tion where the infor­ma­tion will be used are par­tic­u­larly impor­tant.

Sec­ondly, the ideation, struc­tur­ing and real­iza­tion of the IT arti­facts, although lim­ited by phys­i­cal ele­ments—com­put­ers and their inter­con­nec­tions—is mainly restricted by aspects of infor­ma­tion pro­cess­ing. These aspects are related to sequences of oper­a­tions—algo­rithms—that fol­low rules of rea­son­ing anchored in cog­ni­tive oper­a­tions.

The engi­neer and man­ager of infor­ma­tion sys­tems, there­fore, deals with aspects related to infor­ma­tion pro­cess­ing, tak­ing advan­tage of IT, in enter­prises and other social sit­u­a­tions (pur­pose­ful enti­ties seek­ing to achieve goals).

5. IS Body of Knowledge

Car­ry­ing out these pro­fes­sional func­tions requires engi­neers and man­agers of infor­ma­tion sys­tems to apply knowl­edge that con­sti­tutes the body of knowl­edge of the IS field. The term “body of knowl­edge” is used here in a broad sense, not imply­ing the exis­tence of a broad con­sen­sus, in the sci­en­tific and pro­fes­sional com­mu­ni­ties, regard­ing the con­tent of such a body knowl­edge, nor does it imply the exis­tence of any repos­i­tory that intends to sys­tem­atize this body of knowl­edge. In any case, it is a term appro­pri­ate to refer to knowl­edge, of any kind, that is applied in the exer­cise of pro­fes­sional func­tions and that inte­grates the com­pe­ten­cies nec­es­sary for car­ry­ing out these func­tions. Like any other body of knowl­edge, it will com­prise var­i­ous types of knowl­edge:

B1—Con­cept schemes, clas­si­fi­ca­tions and other forms of knowl­edge essen­tially descrip­tive, used to describe and char­ac­ter­ize phe­nom­ena rel­e­vant to IS. This type of knowl­edge cor­re­sponds, glob­ally, to the the­o­ries for analy­sis (type I the­o­ries) of Gre­gor’s [2016] clas­si­fi­ca­tion.

B2—The­o­ries that reflect an under­stand­ing of the rel­e­vant phe­nom­ena in IS. These the­o­ries cover the prin­ci­ples of infor­ma­tion pro­cess­ing and the reg­u­lar­i­ties in human and social behav­ior related to the infor­ma­tion pro­cess­ing and the adop­tion and use of com­puter arti­facts. These are the­o­ries that involve causal rela­tion­ships or, at least asso­ci­a­tion between the con­structs involved. This type of knowl­edge cor­re­sponds to the the­o­ries of types II, III and IV of the clas­si­fi­ca­tion of Gre­gor [2016], respec­tively: pre­dom­i­nantly explana­tory the­o­ries, pre­dom­i­nantly pre­dic­tive the­o­ries and explana­tory/pre­dic­tive the­o­ries.

B3—Meth­ods, tech­niques and tools and any form of action-ori­ented knowl­edge, namely the actions inher­ent in the above func­tions enun­ci­ated (cf. Sec­tion 4), and also archi­tec­tures (typ­i­cal struc­ture) of IT arti­facts, both in terms of appli­ca­tions and infra­struc­ture. This type of knowl­edge cor­re­sponds to type V the­o­ries (the­o­ries for design and action [Gre­gor 2016]). Meth­ods, tech­niques and tools are means to achieve cer­tain ends. They are not knowl­edge obtained by dis­cov­ery, but by inven­tion. This type of knowl­edge can thus be con­sid­ered to cor­re­spond to tech­nol­ogy [Ortega y Gas­set 1983; Polanyi 1956].

C4—Tech­no­log­i­cal rules that cap­ture knowl­edge about the effec­tive­ness of the tech­nol­ogy, con­sid­er­ing the opti­mum con­di­tions for its appli­ca­tion as well as pos­si­ble unde­sir­able side effects that have already been iden­ti­fied. Tech­no­log­i­cal rules are defined by van Aken as being “pieces of gen­eral knowl­edge, link­ing an inter­ven­tion or arti­fact with a desired out­come or per­for­mance in a given field of appli­ca­tion” [van Aken 2004, p. 228]. This type of knowl­edge is not explic­itly men­tioned by Gre­gor, but could fall under the type V the­o­ries (the­o­ries for design and action [Gre­gor 2016]), inso­far as it cor­re­sponds to fun­da­men­tal knowl­edge for decid­ing which meth­ods, tech­niques, tools and pro­ce­dures to be used when car­ry­ing out pro­fes­sional func­tions.

The devel­op­ment of the IS body of knowl­edge is the mis­sion of the IS research activ­i­ties dis­cussed below.

6. IS Research

The nature of the objects of inter­est in the IS field, as well as their char­ac­ter­is­tic mutual inter­de­pen­dence, and the fact that it encom­passes a dimen­sion of pro­fes­sional prac­tice, make the IS field par­tic­u­larly chal­leng­ing in terms of sci­en­tific research and tech­no­log­i­cal devel­op­ment. The chal­lenges involve two fronts: the range of research activ­i­ties that can exist and the range of applic­a­ble research meth­ods.

6.1 Types of Research Activities and Research Results in IS

The fol­low­ing three types of research activ­i­ties can be dis­tin­guished and cor­re­spond mainly to the pro­duc­tion of knowl­edge types B2, B3, and B4³ iden­ti­fied above and whose pur­poses are:

R1—Basic research: Under­stand­ing rel­e­vant IS phe­nom­ena. This type of research leads to the pro­duc­tion of type B2 knowl­edge pre­sented in Sec­tion 5.

R2—Applied or trans­la­tional research: Con­vert­ing (trans­lat­ing) under­stand­ing about IS phe­nom­ena (type B2 knowl­edge) in meth­ods, tech­niques, tools and other forms of tech­nol­ogy that sup­port the action, in par­tic­u­lar the actions asso­ci­ated with the func­tions of IS pro­fes­sion­als. This type of research leads to the pro­duc­tion of type B3 knowl­edge. Type R2 research typ­i­cally involves the proof of con­cept of the pro­posed tech­nol­ogy. The proof of con­cept aims to demon­strate the “func­tional fea­si­bil­ity” [Nuna­maker et al. 2015] of a tech­nol­ogy. This demon­stra­tion is made at a stage when the tech­nol­ogy is being cre­ated. Thus, proof of con­cept typ­i­cally takes place in a arti­fi­cial envi­ron­ment (in a lab­o­ra­tory). Some­times the demon­stra­tion inher­ent to the proof of con­cept is car­ried out in a real con­text, i.e., in a typ­i­cal con­text of its actual use (in the field). In such cases, it takes place in the con­text of what are usu­ally called pilot projects, i.e., in exploratory sit­u­a­tions, lim­ited in scope and con­trolled, to obtain evi­dence on the effec­tive­ness of the tech­nol­ogy in ques­tion. Using the con­cept of tech­nol­ogy readi­ness level, and using the acronym TRL (Tech­nol­ogy Readi­ness Level), it is about tech­nol­ogy with TRL 3 or 4, or pos­si­bly TRL 6 or 7.⁴

R3—Clin­i­cal research (eval­u­a­tion of tech­nol­ogy while it is being applied): Eval­u­at­ing the effec­tive­ness of the tech­nol­ogy. This type of research leads to the pro­duc­tion of C4 type of knowl­edge. Tech­nol­ogy assess­ment focuses on tech­nol­ogy that is at a high level of readi­ness, namely tech­nol­ogy which is already avail­able and in oper­a­tion (TRL 9). This type of research cor­re­sponds to mak­ing the value test, i.e., it aims to estab­lish in which con­di­tions tech­nol­ogy is a gen­er­a­tor of value [Nuna­maker et al. 2015]. The des­ig­na­tion of clin­i­cal research, pre­sented above, has its ori­gins in the field of med­i­cine where this type of research is well estab­lished. This des­ig­na­tion makes it clear that this is a form of research that takes place in a real con­text—in clin­i­cal prac­tice—involv­ing pro­fes­sion­als of the field (doc­tors in the case of med­i­cine). In the case of IS field, this type of research requires the involve­ment of IS pro­fes­sion­als who, in the con­text of their pro­fes­sional activ­i­ties seek to con­trib­ute to the advance­ment of the body of knowl­edge of the field, eval­u­at­ing the tech­nol­ogy they apply. And not just the tech­nol­ogy they pro­vide to solve the prob­lems they face, but also the tech­nol­ogy they use in car­ry­ing out their pro­fes­sional func­tions.

In the IS field, it is not com­mon to dis­tin­guish between the dif­fer­ent types of research pre­sented above. The empha­sis is more on dis­tin­guish­ing between dif­fer­ent types of research results. The tax­on­omy pro­posed by Gre­gor [2016] in which research results are referred to as “the­ory” illus­trates this focus well. How­ever, the dis­tinc­tion made makes it eas­ier to rec­og­nize the exis­tence of dif­fer­ent forms of research that lead to the cre­ation of dif­fer­ent forms of knowl­edge. In the case of sci­en­tific fields that include a strand of pro­fes­sional activ­ity, this dis­tinc­tion also facil­i­tates fram­ing the research aimed at these pro­fes­sional activ­i­ties and their devel­op­ment through the sys­tem­atic eval­u­a­tion of pro­fes­sional prac­tices and tech­no­log­i­cal knowl­edge that under­lies them—the clin­i­cal research where tech­nol­ogy is eval­u­ated (R3).

Given the pro­fes­sional activ­ity of the IS sci­en­tific field, it is impor­tant to con­sider the role of IS pro­fes­sion­als in research. Not as objects of study (some­thing that can also hap­pen, par­tic­u­larly in type R1 research), but tak­ing a lead­ing role in the pro­fes­sional com­mu­nity in which they fit, trans­lated into the involve­ment (pos­si­bly lead­er­ship) on research projects. It would be nat­ural for these projects to be of type R2 or R3.

In the first case (type R2 projects), since they are aware of the sit­u­a­tions faced by enter­prises and the ways to deal with these sit­u­a­tions, IS pro­fes­sion­als will be par­tic­u­larly well placed to find new solu­tions to the prob­lems and chal­lenges faced by enter­prises and also to design new meth­ods, tech­niques and tools for their pro­fes­sional activ­i­ties. In research con­ducted by IS pro­fes­sion­als, it is under­stand­able that the link between the new tech­nol­ogy and the the­o­ret­i­cal knowl­edge that sup­ports and explains it is made a pos­te­ri­ori. In other words, the cre­ation of tech­nol­ogy (knowl­edge of type B3) does not result from a search for pos­si­ble appli­ca­tions for knowl­edge of type B2. The cre­ation of tech­nol­ogy can appear intu­itively. The con­nec­tion with type B2 knowl­edge will be made after the cre­ation of the tech­nol­ogy, namely by under­stand­ing the new tech­nol­ogy, its lim­i­ta­tions and poten­tial exten­sions.

In the sec­ond case (type R3 projects), the IS pro­fes­sional adopts a reflec­tive and con­tin­u­ous improve­ment atti­tude. It reflects on its actions, seek­ing to mea­sure the effec­tive­ness, effi­ciency or use­ful­ness—the value—of the tech­nol­ogy it pro­vides and/or of the meth­ods, tech­niques and tools applied. In this way, IS pro­fes­sion­als com­bine their pro­fes­sional action with the appli­ca­tion of sci­en­tific inquiry meth­ods and tech­niques in order to be able to mea­sure accu­rately that value. This mea­sure­ment will form the basis to under­stand the pos­si­ble need to improve solu­tions and the exist­ing resources and work tools.

It is also to be expected that research con­ducted by IS pro­fes­sion­als will be in con­texts other than lab­o­ra­tory research. These will be con­texts in which the dimen­sion of cre­at­ing new knowl­edge (research) is com­bined with the res­o­lu­tion of con­crete prob­lems, such as the con­text of the s0-called Design Sci­ence Research (DSR), as described by Hevner et al. [2004]. Or con­texts involv­ing prob­lem-solv­ing in spe­cific sit­u­a­tions, with the par­tic­i­pa­tion of dif­fer­ent stake­hold­ers in these sit­u­a­tions and the use of mul­ti­dis­ci­pli­nary approaches that make up mode 2 of knowl­edge pro­duc­tion described by Gib­bons [2000].

6.2 IS Research Methods and Approaches

The term “method” is widely used in research con­text. It is used to refer to ways or means of car­ry­ing out an under­tak­ing or exe­cut­ing any action, it can be applied to var­i­ous aspects of the process of research, at dif­fer­ent lev­els of con­cern. In the con­text of this arti­cle, we are inter­ested in focus­ing our atten­tion on the ways in which researchers have access to the phe­nom­ena they want to study and be able to make the obser­va­tions they con­sider nec­es­sary or pos­si­ble.

Fig­ures 1 and 2, which were used to char­ac­ter­ize the IS field, are also use­ful for jus­ti­fy­ing that, in IS it is pos­si­ble (and nec­es­sary) to use a wide range of research meth­ods. These Fig­ures explain the classes of phe­nom­ena that are objects of inter­est in the field—phe­nom­ena involv­ing infor­ma­tion, IT and human endeav­ors and social sit­u­a­tions—and present some of the pos­si­ble sub­classes. The diver­sity of con­texts in which IT oper­ates stand out (see, for exam­ple, the right-hand side of Fig­ure 2). These Fig­ures also seek to illus­trate the inter­dis­ci­pli­nary nature of IS field.

It should come as no sur­prise, then, that in IS research it is pos­si­ble to rec­og­nize the use of research meth­ods typ­i­cal of very dif­fer­ent fields, which, since they oper­ate at dif­fer­ent lev­els of analy­sis, require spe­cific research meth­ods. Such fields include the human sci­ences (e.g., cog­ni­tive sci­ences and psy­chol­ogy), orga­ni­za­tion and man­age­ment sci­ences, social sci­ences (e.g., soci­ol­ogy and eco­nom­ics), tech­nol­ogy and engi­neer­ing.

It is under­stand­able, then, that in IS research it is pos­si­ble to find the range of research meth­ods estab­lished in all those fields, includ­ing: com­puter sim­u­la­tion; lab­o­ra­tory exper­i­ments, either involv­ing sim­u­lat­ing the rel­e­vant phe­nom­ena, or car­ry­ing out tests that enable the eval­u­a­tion of the effec­tive­ness of the tech­nol­ogy (often using cap­tured records in real sit­u­a­tions that are used as bench­marks); field exper­i­ments (quasi-exper­i­men­tal stud­ies), car­ried out in a basic research logic (R1), trans­la­tional (R2) or clin­i­cal (R3); mis­cel­la­neous field stud­ies, includ­ing case stud­ies, sur­veys, or also the use of focus groups and other ways of obtain­ing opin­ions and per­cep­tions from respon­dents rec­og­nized as priv­i­leged; stud­ies based on doc­u­ments; stud­ies based on sec­ondary data, with stud­ies that use data cor­re­spond­ing to records cre­ated by sen­sors and other devices that inte­grate IT appli­ca­tions or plat­forms gain­ing impor­tance.

The choice of one of the many meth­ods listed depends, essen­tially, from the answers to two ques­tions:

1. Is it pos­si­ble to pro­duce instances of the phe­nom­ena under study, so that they can be stud­ied in a sys­tem­atic and con­trolled way?

2. Is it pos­si­ble to inter­fere with the phe­nom­e­non in some way by chang­ing the con­di­tions where it occurs?

Note that the “is it pos­si­ble” being used in these two ques­tions is related to var­i­ous aspects. Not only the nature of the phe­nom­e­non (for exam­ple, it is not pos­si­ble to make col­lec­tive action move­ments/ini­tia­tives hap­pen, made pos­si­ble by social net­works tech­nol­ogy such as “Indig­na­dos” [Vicente and Novo 2014]), but also prac­ti­cal aspects, such as the avail­abil­ity of resources (finan­cial and oth­ers), the fea­si­bil­ity of obtain­ing respon­dents in quan­tity and qual­ity, or as well as eth­i­cal aspects.

Clearly, the con­fi­dence to be had in the results obtained depends on the research meth­ods used. The hier­ar­chy of research meth­ods con­sid­er­ing the qual­ity of the empir­i­cal evi­dence they pro­duce is still not com­mon in the IS field, although it is well estab­lished in med­i­cine (cf., for exam­ple, [GRADE 2004] and [Djul­be­govic and Guy­att 2007]).

7. Conclusion

This arti­cle presents a per­spec­tive of the IS field that reflects the aca­d­e­mic expe­ri­ence of their authors, namely their involve­ment in research, teach­ing and ser­vice activ­i­ties, as well as in the cre­ation/refor­mu­la­tion of teach­ing pro­grams lead­ing to aca­d­e­mic degrees (study cycles/pro­grams).

This aca­d­e­mic expe­ri­ence takes place in a depart­ment—the Depart­ment of Infor­ma­tion Sys­tems—which is part of an engi­neer­ing school—the School of Engi­neer­ing at the Uni­ver­sity of Minho (UMinho). Thus, although in UMinho’s higher edu­ca­tion in infor­ma­tion sys­tems also par­tic­i­pates the School of Eco­nom­ics and Man­age­ment, the design of teach­ing pro­grams tends to fol­low the mod­els of engi­neer­ing edu­ca­tion. On the other hand, the engi­neer­ing school con­trib­utes to rein­forc­ing the idea that the IS field inte­grates an aspect of pro­fes­sional activ­ity.

The des­ig­na­tion “Engi­neer­ing and Man­age­ment of Infor­ma­tion Sys­tems” used in this arti­cle to refer to IS pro­fes­sion­als coin­cides with the des­ig­na­tion used in the UMinho for the main cycle of stud­ies in IS—the inte­grated mas­ter’s degree in Engi­neer­ing and Man­age­ment of Infor­ma­tion Sys­tems.⁵ This des­ig­na­tion seeks, in the first place, to empha­size the ori­en­ta­tion towards a pro­fes­sional activ­ity. The name also sug­gests an align­ment with engi­neer­ing and the con­sid­er­a­tion of char­ac­ter­is­tics closer to man­age­ment. The des­ig­na­tion is used in the Depart­ment of Infor­ma­tion Sys­tems in addi­tion to oth­ers that empha­size the sci­en­tific field where the train­ing is inte­grated—“infor­ma­tion sys­tems” or “infor­ma­tion sys­tems and tech­nolo­gies”, with the last of these des­ig­na­tions result­ing from the influ­ence of the arti­cle by Bacon and Fitzger­ald [1996] men­tioned above.

With this essay, the authors seek to con­trib­ute to the ongo­ing efforts related to the def­i­n­i­tion of cur­ric­u­lar rec­om­men­da­tions for the IS field and for a debate on the cleav­age between rigor and rel­e­vance that is recur­rently addressed in the IS sci­en­tific com­mu­nity.

To fol­low on from the ideas pre­sented here, the pro­fes­sional roles described in Sec­tion 4 can be used in var­i­ous ways. Pos­si­ble uses fol­low: to pro­vide an addi­tional point of view for the most recente rec­om­men­da­tions cur­ric­ula—MSIS 2016 [Topi et al. 2017] and IS 2020 [Lei­dig and Salmela 2021]; as a frame­work for analy­sis in order to iden­tify which IS pro­files inter­sect those included in the Euro­pean ICT Pro­fes­sional Role Pro­files⁶ or in com­pe­tency frame­works such as SFIA⁷, and also as a frame­work for analy­sis to bet­ter under­stand the cor­re­spon­dence of the infor­mat­ics engi­neer­ing pro­fes­sion of the Order of Engi­neers with the IS pro­file [Machado and Ama­ral 2011].

On the other hand, this essay could con­trib­ute to repo­si­tion­ing the role of IS pro­fes­sion­als in the pro­duc­tion of knowl­edge, point­ing out that rigor and rel­e­vance are both essen­tial in the con­text of research that aims to pro­duce empir­i­cal evi­dence of the tech­nol­ogy’s effec­tive­ness that can guide IS pro­fes­sion­als in the var­i­ous choices they have to make in their daily work.

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Endnotes

¹ The descrip­tion of func­tions is based on an under­stand­ing of var­i­ous con­cepts, which, while sup­ported in the IS lit­er­a­ture, may not cor­re­spond to the most cur­rent uses of the terms they are asso­ci­ated with, namely:

• Goal-seek­ing entity: an indi­vid­ual or col­lec­tive entity with a goal. In pur­suit of the goal, the goal-seeker manip­u­lates infor­ma­tion. Exam­ples of goal-seek­ers are indi­vid­u­als, com­pa­nies, non-profit orga­ni­za­tions, asso­ci­a­tions, state ser­vices, gov­ern­ment agen­cies and reg­u­la­tors.

• Infor­ma­tion: sym­bolic phe­nom­ena, objects or things, exter­nal to the human mind, delib­er­ately cre­ated to be used in the con­text of human activ­i­ties in oper­a­tions that involve some kind of com­mu­ni­ca­tion or cog­ni­tion.

• Infor­ma­tion Tech­nol­ogy (IT): hard­ware, soft­ware and their com­bi­na­tions.

• Infor­ma­tion Tech­nol­ogy Infra­struc­ture: infor­ma­tion tech­nol­ogy that pro­vides the basis for the oper­a­tion of infor­ma­tion tech­nol­ogy appli­ca­tions.

• Infor­ma­tion Tech­nol­ogy Appli­ca­tions: com­puter-based arti­facts that auto­mate or sup­port a goal-seeker’s infor­ma­tion-related activ­i­ties, such as cap­tur­ing, stor­ing and retriev­ing, trans­form­ing, trans­mit­ting and mak­ing infor­ma­tion avail­able.

• Infor­ma­tion Sys­tem (IS): sys­temic view of the goal-seeker from an infor­ma­tion per­spec­tive, i.e., focus­ing on the goal-seeker’s activ­i­ties that manip­u­late infor­ma­tion.

• Infor­ma­tion Sys­tems Archi­tec­ture: rep­re­sen­ta­tion of the infor­ma­tion sys­tem that shows the link between the goal-seeker’s pur­poses, activ­i­ties, infor­ma­tion, peo­ple, infor­ma­tion tech­nol­ogy appli­ca­tions and infor­ma­tion tech­nol­ogy infra­struc­ture.

• Infor­ma­tion Sys­tems and Tech­nol­ogy Func­tion: struc­ture set up by the goal-seeker to boost the use of infor­ma­tion in its activ­i­ties.

² An IT appli­ca­tion implan­ta­tion project may involve an IT appli­ca­tion devel­op­ment sub-project. This will hap­pen if it is under­stood that the devel­op­ment of a tai­lor-made IT appli­ca­tion is nec­es­sary; because there are no suit­able IT appli­ca­tions (COTS/RUSP), or because it is under­stood that it will be the best tech­ni­cal-social-eco­nomic option.

³ Note that type B1 knowl­edge is left out. B1-type knowl­edge estab­lishes ele­men­tary aspects about things in the world, for exam­ple, ontolo­gies and tax­onomies and typolo­gies. The pro­duc­tion of this type of knowl­edge can take place either in basic research (R1) or in applied/trans­la­tional research (R2).

⁴ The con­cept of tech­nol­ogy readi­ness level was cre­ated at NASA in the 1970s. This arti­cle uses the tech­nol­ogy readi­ness level scale in use in the Euro­pean Union—https://enspire.sci­ence/trl-scale-hori­zon-europe-erc-explained

⁵ Fol­low­ing the pub­li­ca­tion of reg­u­la­tions that pre­vent the con­fig­u­ra­tion of an inte­grated mas­ter’s degree in engi­neer­ing, the Inte­grated Mas­ter’s Degree in Engi­neer­ing and Man­age­ment of Infor­ma­tion Sys­tems (MiEGSI) will soon be replaced by a bach­e­lor’s degree and a mas­ter’s degree that will retain the des­ig­na­tion of Engi­neer­ing and Man­age­ment of Infor­ma­tion Sys­tems.

⁶ https://www.cen.eu/work/areas/ict/eed­u­ca­tion/pages/ws-ict-skills.aspx (based on the e-CF com­pe­tency frame­work—https://www.ecom­pe­tences.eu).

⁷ https://sfia-online.org/en