DATA SCIENCE IN CLOTHING RETAI
L 1
A S udy o Da a Science in he Clo hing Re ail Indus y:
Quali a i e App oach
Doc o al P ojec
P esen ed o he Facul y
School o Business and Managemen
Cali o nia Sou he n Uni e si y
in pa ial ul illmen
o he equi emen s
o
he deg ee o
DOCTOR
OF
BUSINESS ADMINISTRATION
by
Shek Chi E ic Chan
Da e o De ense
Oc obe 21, 2025
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Copy igh Release Ag eemen
Many DBA doc o al candida es decide o copy igh hei p ojec s. This is a good idea i ollow-up
esea ch is an icipa ed o i a uly inno a i e concep is de eloped in he p ojec .
The Uni e si y e ains he igh o use Doc o al P ojec s o academic pu poses such as displaying
hem in a lib a y ha is open o public e iew, making hem a ailable o e iew by o he doc o al
candida es o his ins i u ion, and p o iding copies o e iew by educa ional o p o essional
licensing and acc edi ing agencies.
In he e en he doc o al candida e chooses o copy igh he Doc o al P ojec ; he Uni e si y s ill
e ains i s igh o use he Doc o al P ojec o educa ional pu poses as desc ibed. To documen
he doc o al candida e’s ag eemen wi h his condi ion, he doc o al candida e is o sign and da e
he ollowing s a emen and e u n o he Commi ee Chai wi h a copy a ached o he inal e sion
o he p ojec submi ed o he cou se.
________________________________________________________________________
To: School o Business and Managemen
F om: Shek Chi E ic Chan, Doc o al Candida e
Subjec : Copy igh Ag eemen Release
Da e: Oc obe 2025
I, Shek Chi E ic Chan, Doc o al Candida e, do he eby g an Cali o nia Sou he n Uni e si y
pe mission o use my Doc o al P ojec o educa ional pu poses as desc ibed in his memo andum.
_______________________________________ Oc obe 21, 2025
Shek Chi E ic Chan, Doc o al Candida e Da e
© 2025
Chan Shek Chi E ic
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CALIFORNIA SOUTHERN UNIVERSITY APPROVAL
We, he unde signed, ce i y we ha e ead his Doc o al P ojec and app o e i as adequa e in
scope and quali y o he deg ee o Doc o o Business Adminis a ion.
Doc o al Candida e: Chan Shek Chi E ic
Ti le o Doc o al P ojec : A S udy o Da a Science in The Clo hing Re ail Indus y: Quali a i e
App oach
Doc o al P ojec Commi ee:
Geo ge Single on, DBA
Signed: ________________________________________________
P ojec Chai Da e
Ch is i Sande s Via, DBA
Signed: ________________________________________________ _________
Commi ee Membe Da e
Ke i Wood, PhD
Signed: ________________________________________________ _________
Commi ee Membe Da e
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Oc obe 27, 2025
Oc obe 27, 2025
Oc obe 28, 2025
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DATA SCIENCE IN CLOTHING RETAIL 4
DEDICATION
This disse a ion is dedica ed o all he d eame s and inno a o s who s i e o make he
wo ld a be e place. May his wo k se e as a eminde ha pe se e ance and passion can u n
e en he smalles ideas in o meaning ul con ibu ions.
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ACKNOWLEDGMENTS
I would like o exp ess my g a i ude o my chai , D . Geo ge Single on, o his
excep ional guidance, unwa e ing suppo , and commi men o my success h oughou he
doc o al p ojec jou ney. His insigh and encou agemen ha e been ins umen al in shaping my
wo k. I also ex end my since e hanks o my doc o al p ojec commi ee membe s, D . Ch is i
Sande s Via and D . Ke i Wood; hei in aluable eedback and expe ise ha e g ea ly en iched
my esea ch and helped me na iga e he complexi ies o his p ojec .
Addi ionally, I would like o hank all he pa icipan s who gene ously sha ed hei ime
and insigh s o his esea ch su ey. I am also g a e ul o he s a and acul y a Cali o nia
Sou he n Uni e si y, whose esou ces and suppo p o ided a solid ounda ion o my wo k.
Thei encou agemen and assis ance ha e been in aluable in en iching my academic expe ience.
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ABSTRACT
This quali a i e s udy in es iga ed da a science implemen a ion in he clo hing e ail indus y o
Hong Kong and Macau, add essing he disconnec be ween abundan consume da a and
e ec i e a ge ed ma ke ing. D awing om Technology Accep ance Model amewo ks, he
esea ch examined pe cep ions, challenges, and oppo uni ies h ough in e iews wi h 24
pa icipan s, including e ail owne s, execu i es, and cus ome s. Thema ic analysis e ealed
se e al key indings: e aile s expe ience signi ican echnical in eg a ion challenges and
o ganiza ional esis ance du ing implemen a ion, while also epo ing subs an ial bene i s,
including e enue inc eases and imp o ed o ecas accu acy when success ul; cus ome s alue
pe sonaliza ion con eniences while exp essing p i acy conce ns, aking ac i e measu es o
p o ec hei da a; and egional cul u al and linguis ic ac o s signi ican ly in luence
implemen a ion app oaches. The s udy iden i ied c i ical ba ie s including clo hing-speci ic da a
complexi ies, eal- ime p ocessing limi a ions, and p edic i e modeling challenges in end
o ecas ing. Fu u e oppo uni ies include emo ional esponse moni o ing, dynamic p icing
op imiza ion, and cul u ally adap ed ecommenda ion sys ems. The indings sugges e aile s
should adop phased implemen a ion app oaches, p io i ize c oss-channel da a in eg a ion,
de elop s yle-e olu ion algo i hms, and implemen anspa en op -in sys ems o da a collec ion.
This esea ch con ibu es o unde s anding echnology adop ion in specialized e ail
en i onmen s and p o ides a amewo k o e alua ing da a science implemen a ions ha
balance echnical capabili ies wi h o ganiza ional eadiness and cul u al con ex s.
Keywo ds: da a science, clo hing e ail, a ge ed ma ke ing, pe sonaliza ion, echnology
adop ion
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TABLE OF CONTENTS
ACKNOWLEDGMENTS .........................................................................................................5
ABSTRACT ...............................................................................................................................6
CHAPTER ONE OVERVIEW OF THE STUDY.....................................................................9
Backg ound o he P oblem ...........................................................................................9
S a emen o he P oblem .............................................................................................11
Pu pose o he S udy ....................................................................................................11
Theo e ical F amewo k ................................................................................................14
Signi icance o he S udy .............................................................................................15
Assump ions, Limi a ions and Delimi a ions ...............................................................16
De ini ions and Key Te ms ..........................................................................................20
O ganiza ion and Summa y .........................................................................................21
CHAPTER TWO REVIEW OF RELATED LITERATURE ..................................................23
O e iew o Da a Science ...........................................................................................24
Re iew o Me hodological Issue ..................................................................................25
Resea ch Designs ........................................................................................................25
Me hodological Issues and Complica ions ..................................................................27
The Role o Da a Science in Di e en Fields ..............................................................28
Heal hca e ....................................................................................................................28
Supply Chain Managemen ..........................................................................................30
Finance .........................................................................................................................32
Ma ke ing .....................................................................................................................34
Human Resou ces.........................................................................................................34
Ope a ions Managemen ..............................................................................................36
Big Da a Analy ics F amewo ks, Techniques, and Tools............................................37
F amewo k ...................................................................................................................37
Techniques and Tools ..................................................................................................38
Challenges ....................................................................................................................38
Da a Quali y .................................................................................................................39
Da a P i acy and Secu i y ............................................................................................39
Scalabili y .....................................................................................................................40
Da a In eg a ion ............................................................................................................40
Impac o Da a Science on Inno a ion and Pe o mance .............................................41
Inno a ion ....................................................................................................................41
Pe o mance .................................................................................................................42
P edic i e Analy ics and Machine Lea ning ................................................................43
P edic i e Analy ics .....................................................................................................43
Machine Lea ning ........................................................................................................44
Challenges and Fu u e Resea ch Di ec ions ................................................................45
Sca ci y o Skilled Da a Scien is s ...............................................................................45
Scaling E iciency o La ge Da ase s..........................................................................46
E hical and Responsible Use o A i icial In elligence ................................................46
E ec i eness and Scalabili y o Da a Analysis App oaches .......................................47
Legal and E hical Conce ns in Da a-D i en Resea ch .................................................47
Da a-D i en Ma ke ing and Cus ome Segmen a ion ..................................................49
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Theo e ical F amewo k ................................................................................................50
Summa y ......................................................................................................................51
CHAPTER THREE METHODOLOGY .................................................................................52
Resea ch Me hod .........................................................................................................53
Pa icipan s ...................................................................................................................54
Ins umen s ...................................................................................................................57
Da a Collec ion ............................................................................................................58
Da a Analysis ...............................................................................................................61
E hical Assu ances .......................................................................................................62
Summa y ......................................................................................................................62
CHAPTER FOUR RESULTS .................................................................................................64
Pa icipan s ...................................................................................................................64
Resul s Resea ch Ques ion One ...................................................................................66
Resul s Resea ch Ques ion Two ..................................................................................71
Resul s Resea ch Ques ion Th ee ................................................................................76
Resul s Resea ch Ques ion Fou ..................................................................................81
Summa y ......................................................................................................................87
CHAPTER FIVE DISCUSSION OF THE FINDINGS ..........................................................89
Discussion o Findings .................................................................................................89
Implica ions o P o essional P ac ice .......................................................................126
Recommenda ions o Resea ch ................................................................................128
Conclusion .................................................................................................................130
REFERENCES ......................................................................................................................132
APPENDIX A: In e iew Ques ions .....................................................................................143
APPENDIX B: Ini ial In i a ion Le e .................................................................................146
APPENDIX C: Consen Le e ..............................................................................................147
APPENDIX D: IRB app o al le e .......................................................................................150
APPENDIX E: Si e Pe mission App o al Le e ...................................................................151
APPENDIX F: Expe Panel Re iew o In e iew Ques ions ...............................................152
APPENDIX G: CITI Ce i ica e ............................................................................................155
APPENDIX H: App o ed Academic Re iew 1 ....................................................................156
APPENDIX I: Pa icipan P o iles and Pa icipa ion in Resea ch Ques ion .........................157
APPENDIX J: Codes and Co esponding Themes ................................................................158
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CHAPTER ONE
OVERVIEW OF THE STUDY
Chap e One in oduces he s udy's cen al opic and me hods o gi e a comple e
o e iew o he esea ch. P oblems in using consume da a o a ge ed ad e ising a e he main
ocus o he s udy in he e ail sec o . Acco ding o Dekimpe (2020), despi e ha ing access o a
weal h o consume da a, many e aile s s ill ail o implemen meaning ul and ailo ed
p omo ions, esul ing in cus ome dissa is ac ion and educed chances o po en ial cus ome s
making pu chases. Ex ensi e esea ch in his a ea has e ealed a signi ican gap be ween
consume expec a ions and he ac ual o e ings o s o es (El eky & Elbyaly, 2021). Consume s
expec pe sonalized expe iences and ele an p omo ions, and s o es o en ail o mee hese
expec a ions. To unde s and he eal-wo ld di icul ies and e ec i e ac ics o e ail ma ke ing,
he quali a i e app oach en ails looking a case s udies and alking o p o essionals in he ield.
Backg ound o he P oblem
The e ail indus y, cha ac e ized by i s ene ge ic na u e, aces many challenges, and one
c i ical issue ela es o he adequacy o ocus on p omo ion endea o s (Dekimpe, 2020). Despi e
he endless a ailabili y o clien in o ma ion, nume ous e aile s ba le o con ey pe sonalized
and signi ican sales no ices o hei clien s. Inqui ies ha e demons a ed ha mo e han 50
pe cen o clien s conside insigni ican and unseemly p omo ions as a sou ce o i i a ion
(Accen u e, 2017). This issue has a - eaching esul s, a ec ing e aile s, ma ke e s, and
cus ome s.
S a is ics and in o ma ion alida e and suppo he p esence o his issue. Acco ding o
some s udies, 67 pe cen o consume s expec a pe sonalized expe ience, and only 23 pe cen o
e aile s success ully deli e a ge ed p omo ions (McKinsey, 2021). Wi h he appea ance o
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ma kе ing (El eky & Elbyaly, 2021). Thе s udy's impo ancе еncompassеd quali a i е aspеc s,
ho oughly comp еhеnding s akеholdе s' pе spеc i еs and ac ions in his sе ing. The s udy's
ho ough analysis o hе clo hing е ail sеc o p o idеd speci ic in o ma ion o hе еxis ing body
o li е a u е. This o е s p еcisе insigh s ha can bе usеd o guidе u u е еsеa ch and p ac ical
applica ions in hе b oadе iеld o еchnology adop ion and a gе еd ma kе ing in hе businеss
wo ld.
Assump ions, Limi a ions and Delimi a ions o he S udy
Recognizing he assump ions, limi s, and delimi a ions ha shape he s udy's scope and
in e p e a i e lens was essen ial when doing esea ch. This sec ion desc ibes hese impo an
poin s, elucida ing he s udy's guiding p inciples, he pa ame e s o esea ch, and he limi s o
examina ion. The goal in ackling hese aspec s was o p o ide a clea and p ac ical backg ound
o he s udy so ha i s esul s and ami ica ions may be be e unde s ood.
Assump ions
C eswell and Po h (2023) and Adom e al. (2018) poin ed ou ha he esea ch app oach
in his s udy is hea ily dependen on se e al assump ions. The e is an elemen o isk o
unce ain y in he s udy due o hese assump ions, which a e undamen al bu no ye p o en. The
i s p esump ion was ha he da a on cus ome beha io and p e e ences collec ed by he
appa el e ail indus y was eliable and ypical o he ma ke as a whole. The s udy's
unde s anding o ma ke ing ine iciencies and he p omise o da a science and machine lea ning
was g ea ly in luenced by his p emise, which is c ucial.
Ano he assump ion was ha pa icipan s such as ma ke e s, cus ome s, and expe s in
he ield, in in e iews and ocus g oups, would be o h igh and objec i e when sha ing hei
hough s and expe iences. To ge an accu a e unde s anding o he possibili ies and h ea s
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associa ed wi h using da a science and machine lea ning in a ge ed ma ke ing, his assump ion
was c i ical. The s udy also assumed ha da a science and machine lea ning algo i hms and
echnologies we e ma u e enough o imp o e appa el e ail ma ke ing echniques. To in es iga e
he uses and ad an ages o a ious echnologies, i was essen ial o make his assump ion.
Se e al measu es we e implemen ed o manage o lessen he impac o hese
assump ions. Cus ome da a was c oss-checked wi h nume ous sou ces whe e e easible o
ensu e accu acy and ep esen a ion. To mi iga e he possibili y o bias in quali a i e eplies,
pa icipan s we e ca e ully chosen om a ied backg ounds, and hei esponses we e c i ically
examined o iden i y any ends o dispa i ies. Finally, a ealis ic pic u e o he possibili ies and
cons ain s o he p esen echnical ins umen s was ensu ed by e iewing hei capabili ies
h ough li e a u e e iews and expe con ac s. By es ing hese hypo heses, he aim was o o e
a ai and accu a e assessmen o da a science and machine lea ning's unc ion in he appa el
e ail indus y.
Limi a ions
Acco ding o C eswell (2018), limi a ions in esea ch e e o sho comings, condi ions,
o in luences ha canno be con olled and ha place es ic ions on me hodology o he
gene alizabili y o indings. Fac o s beyond con ol cause se e al cons ain s o he s udy o da a
science and machine lea ning in eg a ion in he ma ke ing s a egies o clo hing e ail. The
possible inaccessibili y o con iden ial in o ma ion held by appa el e ail co po a ions was a
majo es ic ion. The amoun and a ie y o da a ha we e analyzed could be limi ed since many
companies p o ec hei cus ome s' da a and in e nal s a egies. This was lessened by o ming
ag eemen s wi h e ail i ms ha a e open o sha ing da a o by supplemen ing p ima y da a wi h
publicly a ailable da a and seconda y sou ces.
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Da a science and machine lea ning echnologies a e de eloping a a apid pace, which is
ano he cons ain . The cu en me hods and algo i hms may soon be obsole e, which migh
a ec he s udy's use ulness and ele ance in he u u e. To keep his unde con ol, he s udy
cen e ed on gene al ac ics and concep s ins ead o a pa icula echnology, so he esul s we e
applicable e en as hose echnologies e ol ed.
In addi ion o i s quali a i e design, he s udy's esul s demons a ed po en ial
applicabili y o a b oade popula ion. Al hough quali a i e esea ch has inhe en limi a ions in
e ms o gene alizabili y, hese d awbacks a e e ec i ely add essed by he ich and in-dep h
insigh s ha such esea ch p o ides. While quali a i e da a is aluable o speci ics, i does no
always ha e he scope o d aw b oad conclusions. To ackle his, a a ied sample was sough ha
encompasses a ange o demog aphics, i m sizes, and geog aphic loca ions o ga he iewpoin s
om all co ne s o he ma ke .
Las , because quali a i e da a is subjec i e, he s udy can ha e d awbacks. Accomplished
analys s analyzed he da a, which educed indi idual biases and inc eased he dependabili y o
he conclusions. This ensu ed objec i i y. By aking hese s eps, he s udy's alidi y and
us wo hiness may be imp o ed while also add essing i s sho comings.
Delimi a ions
Acco ding o C eswell (2018), delimi a ions in esea ch e e o he speci ic pa ame e s
o bounda ies es ablished o help na ow he scope o he s udy. The decisions made and he
s udy's design la gely de e mined he limi s in e ms o scope and ocus managemen . Though
hey cons ained he s udy in ce ain espec s, hese delimi a ions we e necessa y o keeping he
esea ch s a egy clea , manageable, and ocused.
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Fi s , he appa el e ail indus y in ce ain egions is he exclusi e ocus o he s udy. This
choice was o p o ide a mo e ho ough and con ex ual knowledge o he indus y in pa icula
egions, bu i es ic ed he ele ance o he esul s o o he egions. To coun e ac his, he s udy
o e ed a mo e holis ic iew by discussing how he esul s migh be simila o o di e en om
hose in o he se ings. Also, he s udy examined how egional cha ac e is ics such as consume
beha io , ma ke ma u i y, and echnological in as uc u e in luenced da a science adop ion in
clo hing e ail ope a ions.
Second, he s udy's a ge demog aphics we e speci ic o he appa el e ail sec o ,
including me chan s, ma ke e s, and shoppe s. This na owing o a en ion pe mi ed a deepe
di e in o he li ed eali ies and wo ld iews o hese communi ies. Howe e , his also mean ha
supplie s o egula o y agencies would no be included in he eedback, wo addi ional g oups
whose opinions can be impo an . This es ic ion was acknowledged by he s udy, and ways in
which u u e esea ch migh add ess hese o he pe spec i es we e p oposed.
Selec ing quali a i e esea ch me hodologies as he p ima y app oach was ano he
es ic ion. The capaci y o gene alize indings ac oss he whole sec o was limi ed by his
echnique, e en i i supplied ich, comp ehensi e da a. This was add essed by he esea ch by
ecommending quan i a i e in es iga ions o mo e gene alizable esul s and by p ecisely
de ining he ci cums ances in which he esul s could be mos use ul.
Finally, all he esea ch was conduc ed in acco dance wi h he s a e o he a and cu en
ma ke ends. The s udy ecognized ha hese a iables can change and ha esea che s may
ha e o adjus hei me hods in ligh o new disco e ies. As da a ha is pe inen o he p esen
bu may equi e e-e alua ion in he u u e, he esea ch ocused on he cu en s a e o
echnology and ma ke dynamics.
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De ini ions and Key Te ms
Algo i hmic Bias
Algo i hmic Bias e e s o sys ema ic and epea able e o s in a compu e sys em ha
c ea e un ai ou comes, such as p i ileging one a bi a y g oup o use s o e o he s (Mišić &
Pe akis, 2020).
Da a Mining
Da a Mining is he p ocess o disco e ing pa e ns and knowledge om la ge amoun s o
da a. The da a sou ces can include da abases, da a wa ehouses, he web, and o he in o ma ion
eposi o ies o da a ha a e s eamed in o he sys em dynamically (Mišić & Pe akis, 2020).
Machine Lea ning
Machine Lea ning is a subse o a i icial in elligence in ol ing he s udy and
cons uc ion o algo i hms ha can lea n om and make p edic ions o decisions based on da a.
These algo i hms ope a e by building a model om sample inpu s and making da a-d i en
p edic ions o decisions, a he han ollowing only explici ly p og ammed ins uc ions (El eky
and Elbyaly, 2021).
Omnichannel Ma ke ing
Omnichannel Ma ke ing e e s o he mul ichannel sales app oach ha p o ides he
cus ome wi h an in eg a ed shopping expe ience. The cus ome can be shopping online om a
desk op o mobile de ice, by elephone, o in a b ick-and-mo a s o e, and he expe ience would
be seamless (Wang e al., 2023).
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Pe sonaliza ion
Pe sonaliza ion in ma ke ing is he p ac ice o using algo i hms and da a o deli e
indi idualized messages and p oduc o e ings o cu en o p ospec i e cus ome s, enhancing
he cus ome expe ience and inc easing he e ec i eness o ma ke ing e o s (Accen u e, 2017).
Ta ge ed Ma ke ing
Ta ge ed Ma ke ing is a ma ke ing s a egy ha iden i ies and ca e s o speci ic
demog aphic segmen s wi hin a la ge ma ke , using ailo ed messages o p oduc s ha appeal o
hese speci ic segmen s (Dekimpe, 2020).
O ganiza ion and Summa y
Chap e One aimed o p o ide eade s wi h a comp ehensi e o e iew o he esea ch by
in oducing he cen al opic. The s udy p ima ily ocused on he challenges associa ed wi h
u ilizing consume da a o a ge ed ad e ising wi hin he clo hing e ail sec o in Hong Kong
and Macau. Despi e ha ing abundan access o consume da a, nume ous e aile s s uggle o
implemen e ec i e and pe sonalized p omo ional s a egies. This chap e also del ed in o he
apidly e ol ing landscape o da a-d i en ma ke ing in he e ail indus y, wi h a pa icula
emphasis on he clo hing sec o . Chap e One highligh ed he g owing impo ance o le e aging
big da a and ad anced analy ics o gain insigh s in o consume beha io and p e e ences. Chap e
Two o e s an in-dep h examina ion o exis ing li e a u e on he applica ion o da a science and
machine lea ning in he clo hing e ail sec o , pa icula ly in he con ex o a ge ed ma ke ing.
The esea ch aimed o con ex ualize he s udy wi hin he b oade academic discou se,
highligh ing pi o al heo ies, pas esea ch indings, and he e olu ion o ma ke ing s a egies in
esponse o echnological ad ancemen s. Chap e Th ee con ains he esea ch design and
me hodology o he s udy. The esea ch desc ibed he quali a i e app oach, including he
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selec ion c i e ia o pa icipan s, he me hods o da a collec ion, such as in e iews and ocus
g oups, and he p ocedu es o da a analysis. The chap e also discussed he e hical
conside a ions and s eps aken o ensu e he in eg i y and alidi y o he esea ch. Chap e Fou
p esen s he indings om he da a collec ed. I includes a hema ic analysis o he in e iews and
ocus g oups, highligh ing key ends, pa e ns, and insigh s ega ding he use o da a science and
machine lea ning in he clo hing e ail sec o . This chap e aimed o shed ligh on he p ac ical
implica ions o hese echnologies in ma ke ing and he pe cei ed ba ie s and oppo uni ies as
oiced by indus y expe s and consume s. The inal chap e syn hesizes he indings and o e s
conclusions. Chap e Fi e discussed he implica ions o he s udy o e aile s, ma ke e s, and
policymake s. Chap e Fi e also p o ided ecommenda ions based on he esea ch indings,
sugges ing s a egies o mo e e ec i e use o da a science in ma ke ing. The esea ch concluded
wi h sugges ions o u u e esea ch, acknowledging he limi a ions o he cu en s udy and
p oposing a eas o u he in es iga ion.
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CHAPTER TWO
REVIEW OF RELATED LITERATURE
Da a science has come in o he limeligh since 2014 because o i s capaci y o ex ac
meaning om e y la ge and complex in o ma ion. Companies and o ganiza ions ac oss many
sec o s now ely hea ily on da a scien is s as a esul o he inc easing a ailabili y o da a and he
ad en o new echnology (Ahmed & Yaqoob, 2019). Da a science is bes desc ibed and
unde s ood as an inexo able p og ession, wi h many di e en applica ions ha ha e a ec ed
many di e en p ocesses h oughou he globe. Resea che s and academics examined how da a
science may be a icula ed and applied o pa icula ields, including business, en e ainmen ,
echnology, and inno a ion. Da a science is a ela i ely ecen subjec ha g ew ou o using
compu e s, s a is ics, and ma hema ics, acco ding o esea ch by P ies ley and McG a h (2019).
Da a science is a e y young ield o s udy, and as such, he e is signi ican de elopmen ac oss
all o he dis inguishing ea u es ha de ine he ield. Acco ding o u he s udy insigh s
p o ided by Raban and Go don (2020), he uni ica ion o he no ion o da a science, which cu s
ac oss mul iple a eas o special y, is gaining momen um as a consequence o he con inued
inc ease in scien i ic esea ch. In he ealm o business and indus y, in pa icula , he idea o
da a science has cu ing-edge applica ions. Da a science p oduc s a e desc ibed as impo an
asse s by Medei os e al. (2020) o businesses because hey p o ide access o as s o es o da a
ha ha e been collec ed om many compe ing sou ces and packaged in se e al ways o ease o
consump ion. Ha ing access o da a and da a analy ics enables i ms o ex ac use ul insigh s
and de elop a sophis ica ed, da a-d i en decision-making a chi ec u e ha may aid hem in
in e p e ing he compe i i e and dynamic pa s o he business en i onmen (Vica io & Coleman,
2019). The pu pose o his li e a u e e iew was o p o ide eade s wi h an o e iew o da a
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science s udies, ocusing on he mos pi o al concep s, p ocedu es, and applica ions o he ield.
The ad an ages and disad an ages o da a science applica ions we e analyzed, and a enues o
esea ch expansion we e p oposed.
O e iew o Da a Science
Da a scien is s used an asso men o scien i ic me hods, p ocedu es, algo i hms, and
sys ems o ex ac use ul in o ma ion om a a ie y o da a ypes, including s uc u ed and
uns uc u ed da a (Ahmed & Yaqoob, 2019). To ind hidden ela ionships, ends, and pa e ns in
massi e da ase s, da a scien is s used echniques including s a is ical analysis, machine lea ning,
da a mining, and p edic i e analy ics (Olson, 2017). The e ec s o da a science on he heal hca e
indus y a e discussed by Singh (2018). By s udying la ge and di e se da ase s, he heal hca e
sec o may gain insigh s in o illness pa e ns, pa ien beha io , and he apeu ic esul s. Singh
(2018) likewise highligh ed he ole da a science plays in imp o ing he accu acy and e icacy o
medical diagnoses and ea men s.
Da a science has eme ged as a signi ican ool in he ield o supply chain managemen ,
helping o imp o e ope a ional e iciency and decision-making (Olson, 2017). Supply chain
ope a ions da a, such as in en o y managemen , shipping, and wa ehousing eco ds, may help
businesses imp o e hei e iciency and p oduc i i y. Wang e al. (2017) p o ided a
comp ehensi e e iew o he cu en s a us o big da a analy ics in supply chains. I was clea
om he esul s ha da a science can help i ms imp o e supply chain anspa ency, which in
u n can sa e cos s and imp o e se ices. The au ho s also highligh ed he need o da a
go e nance and da a secu i y o ensu e he co ec and e hical use o da a in logis ics
managemen . Da a science has nume ous po en ial applica ions, as seen by he wide ange o
published wo ks ha explo e his opic. Mode n da a analy ics echniques allow businesses o
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