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ENERGY-EFFICIENT BUILDING PRACTICES AND OPERATIONAL
PERFORMANCE ACROSS STAR-RATED HOTELS IN NAIROBI CITY COUNTY
1Gadison Kipko i Ngeno,
Hospi ali y and Tou ism Sec ion, Tha aka Uni e si y,
gadisonkipko i @gmail.com
Tel. +254745777620
2D . Kipchi chi Samuel Ronoh,
Hospi ali y and Tou ism Sec ion, Tha aka Uni e si y
Kipchi chi . ono@ ha aka.ac.ke
ORCID: h ps://o cid.o g/0000-0001-6377-9099
Tel. +254726126929
Co esponding au ho : gadisonkipko i @gmail.com
ABSTRACT
This s udy examined he impac o ene gy-e icien building p ac ices on he ope a ional pe o mance o s a - a ed
ho els in Nai obi Ci y Coun y, Kenya. Ho els a e among he mos ene gy-in ensi e comme cial es ablishmen s,
incu ing high ope a ional cos s la gely d i en by ligh ing, hea ing, en ila ion, and ai condi ioning (HVAC)
sys ems. The s udy adop ed a desc ip i e co ela ional c oss-sec ional design on 49 s a - a ed ho els in Nai obi
Coun y. Ope a ional manage s we e pu posi ely selec ed as esponden s because o hei di ec in ol emen in
implemen ing and moni o ing sus ainabili y p ac ices. Da a was collec ed h ough s uc u ed ques ionnai es. Bo h
desc ip i e and in e en ial s a is ics we e un in he analysis o da a. The indings e eal a mode a e bu consis en
adop ion o ene gy-e icien p ac ices such as LED ligh ing, sma HVAC sys ems, enewable ene gy in eg a ion,
and s a aining on sus ainable ene gy use. Ho els epo ed no iceable educ ions in mon hly u ili y bills and
o e all ene gy cos s. Reg ession analysis e ealed a mode a ely s ong, s a is ically signi ican ela ionship
be ween ene gy-e icien p ac ices and ene gy cos s (R = .620, R² = .384, p < .001). This implies ha
app oxima ely 38% o he a ia ion in ene gy cos s sa ings can be explained by he ex en o ene gy e iciency
adop ion. I can be concluded ha ene gy-e icien building p ac ices signi ican ly con ibu e o cos sa ings in
s a - a ed ho els. Ho els should p io i ize in es men in mode n HVAC echnologies, ene gy moni o ing sys ems,
and enewable ene gy sou ces o enhance sus ainabili y and educe ope a ional cos s.
Keywo ds:
Ene gy e icien building p ac ices, ope a ional pe o mance, ope a ional manage s, sus ainabili y
INTRODUCTION
The Wo ld T a el and Tou ism Council (WTTC) highligh s he signi ican ole o he hospi ali y indus y in
d i ing global economic g ow h. In 2024, he T a el & Tou ism sec o con ibu ed 10% o global GDP, e lec ing
an 8.5% inc ease om 2023, which i sel had isen 23.2% om 2022. These igu es su pass p e-pandemic le els
o 9.5% in 2019, demons a ing he sec o ’s eco e y and con inued expansion (WTTC, 2024). Employmen has
simila ly g own, eaching app oxima ely 348 million by 2024, exceeding he 2019 p e-pandemic le el o 334
million (S a is a, 2023), wi h o ecas s p ojec ing 449 million employees by 2034, gene a ing 101 million new
jobs globally (WTTC, 2025). Despi e his posi i e ajec o y, he sec o aces pe sis en challenges, including
ising ope a ional cos s and en i onmen al p essu es ela ed o ene gy which h ea en p o i abili y and long- e m
sus ainabili y (Yenidogan e al., 2021).
Ene gy cos s cons i u e a subs an ial po ion o ho el ope a ing expenses, wi h hea ing, cooling, ligh ing, and
laund y se ices accoun ing o a ound 80% o o al cos s (In e na ional Ene gy Agency, 2023). Ine icien ene gy
consump ion no only ele a es ope a ional expenses bu also inc eases he sec o ’s en i onmen al oo p in (Singh
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e al., 2024). Regional and classi ica ion-based dispa i ies in ene gy use a e no able: i e-s a ho els in empe a e
and opical egions o Asia, A ica, and Eu ope consume app oxima ely 429.1 kWh/m² mo e ene gy han one-
s a ho els (Dibene-A iola e al., 2021). In A ica, ho elie s in Abuja, Nige ia, ecognize he impo ance o
sus ainable ene gy managemen bu encoun e challenges such as un eliable elec ici y, cos ly al e na i e ene gy,
and limi ed access o mode n ene gy-sa ing echnologies (Shehu e al., 2019). In Kenya, s udies indica e pa ial
adop ion o ene gy-sa ing measu es: en ou - and i e-s a ho els in Nai obi achie ed an a e age implemen a ion
a e o 55.83% o e h ee yea s (Ogola, 2024), while ho els in Naku u Coun y ha e p ima ily implemen ed low-
cos measu es wi hou explo ing ad anced echnologies o enhance ope a ional pe o mance (N higa, 2018).
To add ess hese challenges, g een building p ac ices o e a p omising app oach by op imizing esou ce
u iliza ion and p omo ing ene gy e iciency (Geng e al., 2019; P akash e al., 2022). Globally, ho els a e
inc easingly adop ing g een ce i ica ion p og ams such as LEED, BREEAM, G een S a , and G een Globe, which
p o ide s uc u ed amewo ks o ene gy conse a ion, sus ainable ma e ial use, and en i onmen ally iendly
ope a ions (Mo amudali & Manawadu, 2018; Se ano e al., 2020; Ronoh e al., 2025). LEED-ce i ied ho els, o
example, ha e demons a ed a leas a 25% educ ion in ene gy consump ion compa ed o non-ce i ied ho els
(Ami i, O elin, & So a i, 2019). Fu he imp o emen s can be achie ed h ough ene gy-e icien appliances,
au oma ed ene gy managemen sys ems, and building e o i s, po en ially educing ene gy cos s by 5–15%,
pa icula ly in high-consump ion a eas such as hea ing, cooling, and ligh ing (EHL Insigh s, 2025; Ka ounidi e
al., 2024). In he UK, such e iciency imp o emen s could sa e he hospi ali y sec o up o 4,300 GWh annually
(Llanso, 2024).
E idence om A ica illus a es he bene i s o sus ainabili y in he hospi ali y indus y (Ronoh e al., 2025); ou -
and i e-s a eso s in Ma sa Alam, Egyp , ha e implemen ed ad anced ligh ing echnologies, educing ene gy
usage while enhancing gues expe ience (El-Sayed & Abed, 2021). Howe e , esea ch in Kenya emains limi ed.
A s udy o 70 h ee- o i e-s a ho els e ealed a ocus on moni o ing ene gy bills a he han implemen ing
ad anced g een solu ions, such as enewable ene gy in eg a ion (Omune e al., 2021). Mo eo e , exis ing g een
ini ia i es end o emphasize wa e managemen , indoo ai quali y, and en i onmen ally p e e ed pu chasing
while neglec ing comp ehensi e ene gy-e icien building p ac ices and lowe - a ed ho els (Shekinah, 2021). This
na ow ocus es ic s he gene alizabili y o indings ac oss ho el ca ego ies.
Gi en hese gaps, his s udy sough o examine he impac o ene gy-e icien p ac ices on ope a ional pe o mance
ac oss s a - a ed ho els in Nai obi Ci y Coun y, add essing bo h he en i onmen al and economic dimensions o
sus ainabili y in he local hospi ali y sec o .
S a emen o he P oblem
S a - a ed ho els in Nai obi Ci y Coun y ace high ope a ional cos s la gely d i en by ine icien ene gy use, which
also con ibu es o en i onmen al deg ada ion. S udies indica e ha only 55.83% o ene gy-sa ing measu es ha e
been implemen ed o e he pas h ee yea s, e lec ing subop imal adop ion o ene gy-e icien p ac ices. These
ine iciencies in la e cos s and unde mine he long- e m sus ainabili y and compe i i eness o he sec o . G een
building p ac ices, pa icula ly ene gy-e icien in e en ions such as LED ligh ing, sma HVAC sys ems, and
building e o i s, ha e been shown o educe ene gy consump ion by 5-15% annually. Howe e , he e is limi ed
li e a u e on he adop ion o ene gy-e icien p ac ices in Kenyan ho els, wi h exis ing s udies ocusing mainly on
basic en i onmen al managemen and highe - a ed ho els, lea ing gaps in unde s anding how ad anced ene gy-
e icien p ac ices impac ope a ional pe o mance ac oss he b oade ho el sec o . This s udy he e o e sough o
assess he e ec s o ene gy-e icien p ac ices on ope a ional pe o mance in s a - a ed ho els in Nai obi Ci y
Coun y.
Objec i e o he S udy
To e alua e he impac o ene gy-e icien building p ac ices on ope a ional pe o mance ac oss s a -
a ed ho els in Nai obi Ci y Coun y.
Resea ch Hypo hesis
H0: The e is no s a is ically signi ican impac o ene gy-e icien building p ac ices on ope a ional
pe o mance ac oss s a - a ed ho els in Nai obi Ci y Coun y.
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LITERATURE REVIEW
S a - a ed ho els a e ega ded o p o iding op-quali y se ices and acili ies, bu hey come wi h a subs an ial
ene gy cos . They use a lo o ene gy (ligh ing, cooking, and HVAC sys ems) o p o ide com o and high-quali y
se ice le els (Oluseyi e al., 2016). Acco ding o he In e na ional Ene gy Agency (2020), ho els consume
app oxima ely 20-30% o he ene gy consumed in he global comme cial building sec o , wi h HVAC sys ems
accoun ing o mo e han hal o he ene gy consumed by luxu y ho els. Ins alling ene gy-e icien appliances,
au oma ed building ene gy managemen sys ems, and building e o i s can educe ho el ene gy cos s by 5% o
15% (EHL Insigh s, 2025).
The impac o ene gy-e icien building p ac ices on ope a ional pe o mance has been he subjec o nume ous
s udies. Dibene-A iola e al. (2021) assessed he ene gy consump ion pa e ns o i e-s a ho els in empe a e and
opical egions ac oss Asia, A ica, and Eu ope. The s udy ound ha p emium ho els use 429.1 kWh/m² mo e
annually han one-s a ho els. This la ge ene gy use demons a es he po en ial o sa ings h ough he use o
ene gy-e icien sys ems. Simila ly, Becchio e al. (2017) looked in o ene gy-e icien HVAC sys ems o e o i s
in olde ho els a ound he Medi e anean, no ably in Ma e a, I aly. The s udy used Ene gy Plus so wa e o simula e
al e na i e HVAC designs wi h he goal o dec easing hea ing and cooling loads. The indings demons a ed ha
ene gy-e icien HVAC solu ions, e en when e o i ed in o olde buildings, can esul in signi ican ene gy
sa ings. Howe e , he s udy iden i ied a gap in cos -e ec i eness esea ch, pa icula ly in ela ion o he economic
iabili y o ad anced HVAC echnologies, such as Poly alen Hea Pumps, when applied o olde ho els. This
highligh s he ele ance o assessing no only ene gy sa ings bu also he economic p ac icali y o adop ing
ene gy-e icien sys ems wi hin Kenya’s ho el sec o .
Simila ly, O e al. (2024) conduc ed a case s udy on h ee ho els in Lagos, Nige ia: he Lagos Con inen al Ho el,
he Fede al Palace Ho el, and he Eko Ho els & Sui es. The esea ch showed ha e o i ing HVAC sys ems wi h
Va iable Speed D i es (VSDs) and cen alized Building Managemen Sys ems (BMS) esul ed in signi ican
ene gy sa ings. Howe e , i did no ho oughly analyze how inc eased Sma HVAC u iliza ion can lead o mo e
gains in esou ce e iciency and en i onmen al pe o mance op imiza ion. Fu he mo e, enewable ene gy sou ces
a e eme ging as a iable op ion o ene gy sa ings and en i onmen al conse a ion in ho els (Vanegas Can a e o,
2020). Mahachi e al. (2015) concep ualized he use o enewable ene gy a Bo swana's Cumbe land Ho el and
Gabo one Sun, iden i ying sola and biogas as he mos p e alen echnologies. Despi e he po en ial, Gabo one
Sun was unable o expand i s sola ins alla ions, and Cumbe land Ho el was unable o use biogas owing o esou ce
cons ain s.
In Kenya, Chomba e al. (2022) e alua ed he impac o ene gy sa ing me hods on cus ome sa is ac ion in s a -
a ed ho els in he M . Kenya egion, which includes Nye i, Laikipia, Embu, Me u, and Tha aka Ni hi coun ies.
The s udy used a desc ip i e esea ch design and su eyed 243 esponden s om 24 ho els. he s udy disco e ed
ha ene gy-e icien equipmen and dayligh op imized building designs imp o e cus ome happiness and
ope a ional e ec i eness. Howe e , he s udy was p ima ily conce ned wi h cus ome iews and did no examine
he di ec impac o hese ene gy conse a ion ini ia i es on he ho els' ope a ional pe o mance such as ene gy
cos educ ions which his s udy sough o add ess.
Concep ual F amewo k
Figu e 1: Concep ual F amewo k
Sou ce: Adop ed om LEED p ac ices, ce i ica ion, and acc edi a ion handbook (Kubba-LEED AP (2009)
and modi ied by he esea che (2025)
Ope a ional pe o mance (ene gy
cos s)
•Financial sa ings
•Cos pe uni o se ice
•U ili y expenses
Ene gy-e icien building p ac ices
•Sma HVAC Sys ems
•Renewable Ene gy In eg a ion
•
Sma Ligh ing Solu ions (mo ion and
occupancy senso s wi h dimmable
ligh ing con ols, LED bulbs)
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METHODOLOGY
The s udy was conduc ed in Nai obi Ci y Coun y, Kenya, ocusing on s a - a ed ho els. A desc ip i e co ela ional
c oss-sec ional design was employed, allowing da a collec ion a a single poin in ime o assess exis ing ends
and ela ionships wi hou manipula ing a iables (Se ia, 2016). This app oach enabled a comp ehensi e and cos -
e ec i e examina ion o ene gy-e icien building p ac ices and hei impac on ope a ional pe o mance ac oss
mul iple ho els while minimizing biases associa ed wi h longi udinal s udies (Babbie, 2016). The a ge popula ion
comp ised ope a ional manage s om he 52 s a - a ed ho els in Nai obi (10 i e-s a , 18 ou -s a , 15 h ee-s a ,
and 9 wo-s a ) acco ding o Tou ism Regula o y Au ho i y o Kenya (2019) in Musembi (2021). Ope a ional
manage s we e pu posi ely selec ed o hei di ec knowledge o sus ainabili y ini ia i es and ope a ional
ou comes. Da a was collec ed using s uc u ed ques ionnai es co e ing demog aphics, ene gy e icien building
p ac ices and ope a ional pe o mance, measu ed on a i e-poin Like scale. A pilo s udy in Mombasa Coun y
wi h six esponden s assessed he cla i y, ele ance, and eliabili y o he ins umen , gi en i s simila hospi ali y
en i onmen o Nai obi (Thabane e al., 2010; Whi ehead e al., 2016). Validi y was ensu ed h ough expe e iew
o ace and con en alidi y, while cons uc alidi y was suppo ed ia li e a u e e iew (Tahe doos , 2016;
No a iqah Zasali e al., 2023; Middle on, 2019). Reliabili y was con i med using C onbach’s alpha, wi h alues
abo e 0.70 indica ing in e nal consis ency (Ta akol & Dennick, 2011). E hical app o als we e ob ained om
ele an au ho i ies, and da a analysis was conduc ed using desc ip i e s a is ics o summa ize esponses,
Pea son’s co ela ion and simple linea eg ession analysis o examine ela ionships be ween ene gy-e icien
building p ac ices and ope a ional pe o mance ac oss s a - a ed ho els in Nai obi Ci y Coun y.
Model’s speci ica ion
Model: Y = β₀ + β₁X1 + ε
Whe e:
• Y = Ope a ional pe o mance
• X1 = Ene gy-e icien p ac ice(s)
• β₀ = In e cep
• β₁ = Coe icien o he independen a iable
• ε = E o e m
FINDINGS AND DISCUSSION
Reliabili y Tes
Be o e he ull deploymen o he ool, eliabili y es s we e un o de ec and esol e any po en ial eliabili y
issues. Speci ically, C onbach’s alpha coe icien s we e used o es ablish he eliabili y o he esea ch ool as
summa ized in able 1.
Table 1 Reliabili y Tes
Cons uc s
N o I ems
C onbach's Alpha
Ene gy e icien building p ac ices
6
.904
Ene gy cos s
5
.919
As shown in Table 1, he eliabili y o he s udy cons uc s indica ed high in e nal consis ency. Ene gy-e icien
building p ac ices, assessed h ough six i ems, exhibi ed a C onbach’s alpha o 0.904, while ene gy cos s,
measu ed wi h i e i ems, demons a ed an alpha o 0.919. These esul s sugges ha he i ems wi hin each
cons uc consis en ly measu e he in ended concep s.
Response Ra e
To es ablish he esponse a e, desc ip i e s a is ics (pe cen ages) we e un as summa ized in Table 2.
Table 2 Response Ra e Ma ix
Ta ge
Responses
Pe cen age
52
49
94%
F om Table 2 he esponse a e o he s udy was high, indica ing e ec i e engagemen om pa icipan s. O he
52 a ge ed esponden s, 49 comple ed he su ey, yielding a esponse a e o 94%. This high pa icipa ion le el
sugges s ha he da a a e ep esen a i e o he a ge popula ion and minimizes po en ial non- esponse bias.
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Desc ip i e S a is ics on Ene gy E icien Building P ac ices
Responden s we e asked o a e he le el o which hey ag eed o disag eed wi h some o he s a emen s ela ing
o he adop ion le els o ene gy e icien building p ac ices. A i e-poin Like scale was used; 1 = No a all, 2 =
Sligh ly, 3 = Mode a ely, 4 = Conside ably, 5 = Fully. S anda d de ia ions and means we e used o analyze he
esul s.
Table 3 Ene gy E icien Building P ac ices
S a emen s
N S a is ic
Mean
S a is ic
S d. De ia ion
S a is ic
Ou ho el has adop ed ene gy-e icien ligh ing
sys ems (e.g., LED, mo ion senso s).
49
3.80
1.080
We ha e in es ed in sma HVAC sys ems (hea ing,
en ila ion, and ai condi ioning).
49
3.57
1.208
We ha e implemen ed enewable ene gy sou ces (e.g.,
sola panels, wind ene gy).
49
3.80
1.099
Ou ho el has pu in place ac i e ene gy op imiza ion
and moni o ing de ices.
49
3.82
1.074
We ha e adop ed isible signage and in o ma ion panels
on ene gy conse a ion ini ia i es.
49
3.57
1.041
Ou ho el conduc s egula aining on sus ainable
ene gy use.
49
3.94
1.144
Valid N (lis wise)
49
Table 3 shows he desc ip i e s a is ics on ene gy-e icien building p ac ices adop ed by ho els. The indings
indica e a mode a e le el o adop ion ac oss di e en measu es. On a e age, esponden s ag eed ha hei ho els
use ene gy-e icien ligh ing (mean = 3.80), sma HVAC sys ems (mean = 3.57), enewable ene gy sou ces (mean
= 3.80), ene gy op imiza ion de ices (mean = 3.82), isible ene gy conse a ion signage (mean = 3.57), and
egula aining on sus ainable ene gy use (mean = 3.94). T aining sco ed he highes , showing g ea e emphasis
on s a awa eness. O e all, ho els ha e emb aced ene gy-e icien p ac ices o a ai ex en , al hough he le el o
implemen a ion di e s ac oss speci ic measu es.
Desc ip i e S a is ics on Ene gy Cos s
To cap u e pe cep ions on ope a ional expenses, esponden s a ed s a emen s on ene gy cos s using le els o
ag eemen and disag eemen . A i e-poin Like scale was used; 1 = S ongly Disag ee, 2 = Disag ee, 3 = Neu al,
4 = Ag ee, 5 = S ongly Ag ee. S anda d de ia ions and means we e used o analyze he esul s.
Table 4 Desc ip i e S a is ics on Ene gy Cos s
Ene gy cos s
N
Mean
S d.
De ia ion
S a is ic
S a is ic
S a is ic
Financial sa ings om ene gy cos s a e e iden in ou ho el.
49
3.94
1.029
Ou ho el has ealized a educ ion in mon hly ene gy u ili y
expenses (elec ici y, uel, e c.).
49
4.08
.862
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Ou ho el’s o e all ene gy cos s ha e dec eased o e ime.
49
4.10
.872
The cos pe uni o se ice/good deli e ed in ela ion o ene gy
use has educed signi ican ly in ou ho els.
49
3.90
.963
O e all, ou ho el is cos -e ec i e in i s use o ene gy.
49
4.04
1.172
Valid N (lis wise)
49
Table 4 p o ides an o e iew o he desc ip i e s a is ics on ene gy- ela ed cos s in ho els. The esul s indica e
ha mos ho els pe cei e no iceable inancial bene i s om ene gy e iciency measu es. Responden s ag eed ha
hei ho els expe ience inancial sa ings om ene gy use (mean = 3.94), educed mon hly ene gy bills (mean =
4.08), and a gene al decline in o e all ene gy cos s o e ime (mean = 4.10). They also no ed a educ ion in he
cos pe uni o se ice deli e ed ela i e o ene gy use (mean = 3.90) and a i med ha hei ho els a e gene ally
cos -e ec i e in ene gy u iliza ion (mean = 4.04). These indings sugges ha ho els a e expe iencing angible
cos sa ings om ene gy e iciency, wi h educ ions in mon hly and o e all ene gy expenses s anding ou mos
s ongly.
Diagnos ics S a is ics
Be o e unning in e en ial s a is ics (co ela ion and eg ession analysis), diagnos ic es s we e un o es ablish
whe he he da a ob ained me he assump ions o O dina y Leas Squa es (OLS).
No mali y es
Skewness and ku osis s a is ics we e used o es ablish whe he he eg ession esiduals we e no mally dis ibu ed
as summa ized in Table 5.
Table 5 No mali y Tes
N
Mean
S d.
De ia ion
Skewness
Ku osis
S a is ic
S a is ic
S a is ic
S a is ic
S d.
E o
S a is ic
S d.
E o
Ene gy cos s
49
4.0122
.85675
-.931
.340
.301
.668
O e all cos
49
4.0014
.74715
-.801
.340
.420
.668
Valid N
(lis wise)
49
F om Table 5, ene gy cos s eco ded a mean o 4.0122 and a s anda d de ia ion o 0.857, wi h skewness o -0.931
and ku osis o 0.301, while o e all cos s had a mean o 4.0014 and a s anda d de ia ion o 0.747, wi h skewness
o -0.801 and ku osis o 0.420. Bo h a iables exhibi skewness alues below -0.5, indica ing no able nega i e
skew, and al hough he ku osis alues all wi hin he commonly accep ed ange o ±1, he obse ed skewness
de ia ions sugges asymme y in he dis ibu ions. These esul s demons a e ha he dis ibu ions de ia e
su icien ly om pe ec no mali y, indica ing ha he assump ion o no mali y is iola ed.
Mul icollinea i y
The mul icollinea i y es s in Table 6 con i med he eliabili y o he eg ession model. The Va iance In la ion
Fac o (VIF) alue o ene gy-e icien building p ac ices is 1.000, indica ing a comple e absence o
mul icollinea i y since alues close o 1 ep esen independen p edic o s. Acco dingly, he model can be
conside ed s a is ically obus and ee om mul icollinea i y p oblems.
Table 6 Mul i-Collinea i y Analysis Tes o Ene gy E icien Building P ac ices and Ope a ional Pe o mance
VIF
Ene gy-e icien building p ac ices and ene gy cos s
1.000
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Linea i y
Linea i y was assessed using sca e plo s, which p o ided a isual ep esen a ion o he ela ionship be ween
Ene gy e icien building p ac ices and ope a ional pe o mance as p esen ed in Figu e 1
Figu e 1: Linea i y Plo o Ene gy E icien Building P ac ices and Ene gy Cos s
The sca e plo in Figu e 1 illus a es he ela ionship be ween ene gy-e icien building p ac ices and ene gy
cos s. The dis ibu ion o da a poin s gene ally ollows an upwa d diagonal end, sugges ing ha he ela ionship
be ween he wo a iables is app oxima ely linea . This con i ms ha he assump ion o linea i y was easonably
me , allowing o he use o O dina y Leas Squa es (OLS) eg ession in subsequen in e en ial analysis.
In e en ial S a is ics
Diagnos ic es s we e conduc ed o assess he sui abili y o he da a o eg ession analysis, and he esul s
indica ed iola ions o he no mali y assump ion (Table 3). Mul iple ans o ma ion a emp s, including
loga i hmic and e lec ion-based app oaches, did no su icien ly no malize he a iables. Consequen ly, elying
solely on o dina y leas squa es (OLS) eg ession would ha e isked biased in e ence. To add ess his limi a ion,
OLS was supplemen ed wi h boo s apping, a esampling echnique ha does no assume no mali y and p o ides
mo e eliable es ima es o s anda d e o s and con idence in e als (E on & Tibshi ani, 1993). In his s udy, he
boo s ap p ocedu e was conduc ed using a simple andom sampling me hod wi h 1,000 esamples, applying a
95% pe cen ile-based con idence in e al. To ensu e eplicabili y, he andom numbe gene a o was se using he
Me senne Twis e algo i hm wi h a ixed seed o 12345. This combined app oach enhanced he obus ness and
ep oducibili y o he eg ession es ima es despi e he dis ibu ional challenges in he da a.
Ene gy E icien Building P ac ices and Ene gy Cos s
Table 7Reg ession Model Summa y
Model
R
R Squa e
Adjus ed R Squa e
S d. E o o he Es ima e
Du bin-Wa son
1
.620
.384
.371
.67952
1.938
The model demons a es a mode a ely s ong link be ween ene gy-e icien building p ac ices and ene gy cos s,
as shown in Table 7 (R = .620). This means ha ho els ha adop mo e ene gy-e icien measu es end o ha e
no iceably lowe ene gy cos s. The R² alue o .384 indica es ha abou 38% o he di e ences in ene gy cos s
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can be explained by ene gy-e icien p ac ices. The adjus ed R² (.371) con i ms he esul is eliable, e en a e
accoun ing o sample size. The s anda d e o o es ima e (.67952) shows ha he p edic ed ene gy cos s a e, on
a e age, ai ly close o he ac ual alues.
Table 8 ANOVA
Model
Sum o Squa es
d
Mean Squa e
F
Sig.
Reg ession
13.531
1
13.531
29.303
.000
Residual
21.702
47
.462
To al
35.233
48
The analysis o a iance (ANOVA), as shown in Table 8, e ealed ha he eg ession model was s a is ically
signi ican , F (1, 47) = 29.30, p < .001. This inding sugges s ha ene gy-e icien building p ac ices signi ican ly
imp o ed he p edic ion o ho el ene gy cos s compa ed o a model wi h no p edic o s. Speci ically, he eg ession
model explained 38.4% o he a iance in ene gy cos s (R² = .384), while he emaining 61.6% was a ibu able
o o he ac o s ou side he model. This indica es ha he adop ion o ene gy-e icien p ac ices con ibu es
meaning ully o cos sa ings, highligh ing hei p ac ical and economic impo ance o ho els.
Table 9 Boo s ap o Coe icien s
Boo s ap
Model
B
Bias
S d. E o
Sig. (2- ailed)
95% CI Lowe
95% CI Uppe
(Cons an )
1.828
-.041
.566
.009
.629
2.884
Ene gy e icien
building p ac ices
.583
.009
.131
.001
.343
.849
The boo s ap analysis u he con i med he s abili y o he eg ession coe icien s, as shown in Table 9. The
uns anda dized coe icien o ene gy-e icien building p ac ices emained consis en wi h he o iginal es ima e
(B = .583), wi h only a minimal bias o .009. The s anda d e o inc eased sligh ly unde boo s apping (SE =
.131), bu he e ec emained s a is ically signi ican (p = .001). Impo an ly, he 95% con idence in e al (.343
o .849) did no include ze o, ein o cing ha he e ec o ene gy-e icien p ac ices on ene gy cos s was bo h
eliable and obus ac oss epea ed esampling. These indings indica e ha he obse ed ela ionship is no
sample-speci ic bu gene alizable wi hin he popula ion.
Co ela ion Analysis
Table 10 Pea son Co ela ion
Ene gy cos s
Ene gy e icien building p ac ices
Pea son Co ela ion
1.000
.620**
.620**
1.000
Sig. (1- ailed)
–
.000
.000
–
N
49
49
49
49
Boo s ap Bias
.000
.003
.003
.000
S d. E o
.000
.101
.101
.000
95% CI Lowe
1.000
.414
.414
1.000
95% CI Uppe
1.000
.809
.809
1.000
Table 10 p esen s he Pea son p oduc -momen co ela ion, e ealing a s a is ically signi ican , mode a ely s ong,
posi i e associa ion be ween ene gy-e icien p ac ices and ene gy cos s, (49) = .62, p < .001. This indica es ha
ho els wi h highe adop ion o ene gy-e icien p ac ices end o achie e g ea e educ ions in ene gy cos s. The
boo s ap con idence in e al o he co ela ion (.41 o .81) was en i ely posi i e, ein o cing he eliabili y o his
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ela ionship. Thus, he indings p o ide bo h s a is ical and p ac ical e idence ha ene gy-e icien p ac ices a e
consis en ly associa ed wi h imp o ed cos sa ings.
These indings align wi h p e ious s udies ha ha e highligh ed he po en ial o ene gy e iciency in lowe ing
ope a ional cos s in ho els. Dibene-A iola e al. (2021) and Becchio e al. (2017) showed ha p emium ho els,
pa icula ly hose in ene gy-in ensi e egions, s and o bene i signi ican ly om ene gy-sa ing measu es,
especially h ough op imized HVAC sys ems. Simila ly, O e al. (2024) epo ed subs an ial sa ings om HVAC
e o i s and he in eg a ion o Building Managemen Sys ems in Nige ian ho els. In he Kenyan con ex , Chomba
e al. (2022) ound ha ene gy-e icien equipmen enhances cus ome sa is ac ion and ope a ional pe o mance,
al hough hei s udy did no di ec ly quan i y cos educ ions. The p esen indings he e o e ex end his body o
knowledge by p o iding empi ical e idence ha ene gy-e icien building p ac ices no only imp o e cus ome
expe iences bu also signi ican ly educe ope a ional ene gy cos s in s a - a ed ho els.
CONCLUSION
The s udy es ablished ha ene gy-e icien building p ac ices ha e a signi ican posi i e impac on educing
ene gy cos s in s a - a ed ho els in Nai obi Ci y Coun y. Ho els ha implemen ed measu es such as ene gy-
e icien ligh ing, sma HVAC sys ems, enewable ene gy, and s a aining epo ed measu able inancial
sa ings. The eg ession esul s demons a ed ha ene gy e iciency explains a subs an ial p opo ion o he
a ia ion in ene gy cos s, con i ming i s impo ance as a s a egic ool o imp o ing ope a ional pe o mance.
RECOMMENDATIONS FOR FUTURE STUDIES
1) Fu u e esea ch could u ilize a Longi udinal App oach: This will help ack changes in ene gy cos s and
ope a ional pe o mance o e ime, p o iding deepe insigh s in o he long- e m impac o ene gy-
e icien p ac ices.
2) Fu u e s udies should ocus on compa a i e analysis o s a - a ed ho els wi h non-s a - a ed o bou ique
ho els o de e mine whe he ene gy e iciency bene i s a e consis en ac oss di e en ca ego ies.
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