Supply Chain Inside
Volume 17, Issue 01, 169-206. 10-10-25
ISSN: 2617-7420 (P in ), 2617-7420 (Online)
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Supply Chain Inside
Volume 17, Issue 01, 169-206. 10-10-25
A icle Recei ed: 25-08-2025
Accep ed: 15-09-2025
A ailable Online: 10-10-2025
ISSN: 2617-7420 (P in ), 2617-7420 (Online)
DOI:
10.5281/zenodo.17285103
supplychaininside .o g
T anspo a ion o Ag icul u al P oduc s in Bangladesh
A Compa a i e Analysis o Road and Inland Wa e ways
Rouza ul Rummana Fa abi
1
, Mehe ab Hosen Api
1
, Sanjida A in
1
,
Sian Wahada
1
, Mi aj Hossain Mahin
1
1
Depa men o Na al A chi ec u e and Ma ine Enginee ing, Bangladesh Uni e si y o Enginee ing and Technology
Email: ouza ul. a [email protected]
Abs ac
Bangladesh’s ag icul u al supply chains a e domina ed by oad eigh , despi e he coun y’s as i e ne wo k wi h
s ong po en ial o low-cos , low-ca bon inland wa e way anspo (IWT). This s udy empi ically compa es oad
and wa e way anspo o ag icul u al deli e ies o Dhaka om hi een majo supplying dis ic s. A mixed-me hod
app oach was used, combining su eys o ag icul u al ade s in Dhaka ma ke s, supplemen a y a el- ime su eys,
expe in e iews wi h he Bangladesh Inland Wa e T anspo Au ho i y (BIWTA), and seconda y echnical da a on
ehicles and essels. The analysis examined cos pe onne, a el ime unde no mal and dis up ed condi ions, and
CO₂ emissions.
Resul s show ha oad anspo can be cheape o sho dis ances bu becomes inc easingly cos ly wi h dis ance,
whe eas IWT main ains s able and lowe long-dis ance cos s. Reg ession analysis iden i ied a s a is ically signi ican
b eak-e en poin beyond which wa e ways a e consis en ly mo e economical. En i onmen al modeling con i med ha
IWT educes pe - onne CO₂ emissions by 75–85% compa ed o oad eigh . While oad haulage is as e unde ideal
condi ions, i s eliabili y is unde mined by conges ion, s ikes, and looding, whe eas wa e ways p o ide s eadie
schedules. T ade pe spec i es u he emphasized IWT’s p ac ical bene i s o bulk goods du ing dis up ions.
O e all, indings suppo he conclusion ha IWT is mo e cos -e icien , en i onmen ally sus ainable, and
ope a ionally eliable han oad anspo o long-haul ag icul u al supply chains. The s udy unde sco es he need o
mul imodal s a egies in eg a ing sho -haul ucking wi h long-haul ba ging, alongside in es men s in d edging, po s,
and cold-chain in as uc u e o s eng hen Bangladesh’s ood secu i y and logis ics esilience.
Keywo ds: Ag icul u al supply chains, Inland wa e way anspo (IWT), Road eigh , T anspo cos analysis, CO₂
emissions, Supply chain esilience, Mul imodal logis ics
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1. In oduc ion
1.1 Backg ound
Bangladesh’s economy and ood secu i y hea ily depend on ag icul u e; howe e , he anspo ne wo k linking u al
p oduce s o u ban ma ke s is unde signi ican s ain. Al hough he coun y lies on a as i e ine del a (wi h oughly
24,000 km o wa e ways; Islam e al., 2022), mos ag icul u al eigh cu en ly mo es by oad. Bangladesh’s
ex ensi e i e ne wo k has long o e ed a na u al, low-cos mode o anspo , ye decades o neglec ha e led o
hea y eliance on oads. Nea ly wo- hi ds o Bangladesh’s land is looded annually, making oad cons uc ion and
main enance e y expensi e. Conges ed highways inc ease cos s and delays, wi h one s udy es ima ing ha a ic
conges ion cos s Bangladesh app oxima ely 300 billion BDT annually and accoun s o nea ly 70% o na ional CO₂
emissions (Wo ld Bank, 2020). In con as , inland wa e ways p esen an unde u ilized ye po en ially mo e e icien
al e na i e. In e na ional compa isons show ha wa e bo ne eigh emi s a less ca bon and cos s signi ican ly less
pe onne-kilome e han oad anspo (Niu e al., 2024).
Despi e hese ad an ages, Bangladesh’s inland wa e anspo (IWT) ne wo k emains unde de eloped and
unde used. Only a ac ion o he wa e ways a e na igable yea - ound, and he ca go modal sha e ia i e s has
declined sha ply om 38% in he 1970s o a ound 15% by 2005 (Islam e al., 2022). P io s udies highligh inadequa e
in es men , poo in eg a ion wi h o he modes, and ins i u ional gaps as ba ie s o wide adop ion (Rahman e al.,
2025; Ullash e al., 2023). Fu he mo e, while se e al wo ks ha e examined IWT in e ms o po de elopmen o
in e na ional ade (Im an e al., 2024; Mondal, 2025), ew ha e quan i a i ely compa ed oad and i e anspo o
ag icul u al supply chains unde local condi ions.
1.2 Impo ance o he P oblem
Ag icul u al supply chains in Bangladesh ace bo h seasonal and poli ical dis up ions. Du ing peak pe iods such as
Eid es i als o poli ical s ikes, oad ansi imes can inc ease subs an ially due o conges ion, while inland wa e ways
emain la gely una ec ed. This esilience, combined wi h lowe ope a ional cos s and educed emissions, posi ions
IWT as a sus ainable logis ics al e na i e. Lowe eigh cos s ha e he po en ial o educe commodi y p ices o
consume s while inc easing ne incomes o a me s, aligning wi h na ional goals o ood secu i y and clima e
esilience (Wo ld Bank, 2020).
Ex ensi e delays in ansi esul in signi ican pos -ha es losses and c op damage, unde mining bo h income and
ood secu i y. Dhaka’s ch onic a ic conges ion u he exace ba es delays: na iga ing slow, clogged ou es and
bo lenecks imposes ime penal ies. Du ing poli ical s ikes and es i als, oad anspo can come o a hal , whe eas
wa e ways—which bypass many u ban chokepoin s— emain na igable. The ca bon oo p in is also subs an ial—
hea y ucking may accoun o up o 40% o Bangladesh’s anspo emissions, whe eas IWT is a mo e ca bon-
e icien (Wo ld Bank, 2011). Al oge he , eliance on oads has d i en up cos s and emissions, encou aged eigh
delays and spoilage, and exace ba ed Dhaka’s a ic conges ion. In con as , inland wa e way anspo o e s
un apped po en ial: i equi es less ene gy pe on-kilome e , can ca y much la ge olumes a once, and is gene ally
mo e esilien o dis up ions (Wo ld Bank, 2011).
Gi en Dhaka’s ole as he cen al dis ibu ion hub o ag icul u al p oduc s, op imizing he anspo co ido s ha link
u al dis ic s o he ci y is c i ical. A sys ema ic cos , ime, and emissions compa ison be ween oad and i e modes
can p o ide e idence-based ecommenda ions o policy and in es men . By in eg a ing eal-wo ld ou e da a wi h
pe o mance me ics, his s udy aims o p o ide bo h empi ical insigh s and p ac ical guidance o enhancing
ag icul u al supply chain e iciency in Bangladesh.
1.3 Resea ch Objec i es
1. Compa e he cos e iciency o oad and inland wa e way anspo (IWT) o ag icul u al p oduc s,
iden i ying he b eak-e en dis ance whe e IWT becomes mo e economical.
2. E alua e he en i onmen al impac o bo h modes by quan i ying CO₂ emissions pe onne-kilome e .
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3. Assess ope a ional eliabili y unde no mal and dis up ed condi ions, ocusing on a el ime and schedule
adhe ence.
4. Examine ade pe cep ions ega ding cos , ime sa ings, and sui abili y o bulk shipmen s.
5. P o ide e idence-based ecommenda ions o in eg a ing inland wa e ways in o Bangladesh’s ag icul u al
supply chains.
1.4 Pu pose and Hypo heses
The pu pose o his s udy is o empi ically compa e oad and inland wa e way anspo o ag icul u al goods supplied
o Dhaka om selec ed dis ic s and hei nea es i e po s, iden i ied h ough ma ke su eys. This compa ison
e alua es cos pe onne, CO₂ emissions pe onne, and deli e y eliabili y unde ypical and peak-dis up ion
condi ions.
The p ima y hypo heses a e:
1. Cos E iciency – Inland wa e way anspo will educe anspo a ion cos pe onne compa ed o oad
anspo , leading o lowe commodi y p ices.
2. En i onmen al Impac – IWT will p oduce lowe CO₂ emissions pe onne han oad anspo .
3. Ope a ional Reliabili y – While IWT may ake longe , i will expe ience ewe dis up ions om seasonal
conges ion o poli ical un es , enhancing supply chain esilience.
A seconda y hypo hesis is ha he demons a ed ad an ages o IWT will inc ease public and policy in e es in adop ing
i as a sus ainable al e na i e o oad anspo . These hypo heses a e g ounded in es ablished supply chain and
anspo a ion heo ies ha emphasize cos e iciency, en i onmen al sus ainabili y, and esilience h ough modal
di e si ica ion.
2 Li e a u e Re iew
2.1 Time E iciency and Ope a ional Reliabili y:
Road anspo o e s as e nominal ansi imes, ypically 12 o 18 hou s om key p oduc ion zones o Dhaka, bu
i is plagued by unp edic abili y. One s udy ound ha poli ical s ikes can inc ease ansi imes by 50 o 70 pe cen
on majo ou es (Majumde & Kabi , 2019). This ulne abili y is a signi ican h ea o supply chain s abili y. Monsoon
loods egula ly dis up o e 30 pe cen o highway ne wo ks o 15 o 30 days each yea , se e ely a ec ing mobili y
du ing peak seasons (Banglapedia; Flood Fo ecas ing and Wa ning Cen e [FFWC], 2024). In con as , inland
wa e way anspo elies on ixed launch schedules and is less a ec ed by su ace dis up ions, esul ing in
compa a i ely high schedule adhe ence. While s anda d ba ge a el akes 48 o 72 hou s, i s s eadiness allows be e
coo dina ion, especially o non-pe ishable goods and esilien supply chain planning.
2.2 En i onmen al Impac and Emissions:
The Wo ld Bank epo s ha an inland ba ge can emi up o six imes ewe g eenhouse gases pe on-kilome e han
a uck. Because la ge essels consolida e massi e loads, hey achie e g ea e uel e iciency. Shi ing g ain and
p oduce shipmen s o i e s in Bangladesh could hus ma kedly cu he ag icul u al eigh ca bon oo p in . Addi ional
esea ch on g een supply chains ein o ces he impo ance o emission educ ions in ag i-logis ics (Noha e al., 2023).
In con as , oad eigh causes ele a ed diesel use and con ibu es signi ican ly o ai pollu ion. On sa e y, inland
na iga ion has a ma kedly be e inciden eco d; ca go ia IWT ypically esul s in ewe acciden s pe on-mile
compa ed o oad eigh , hough sa e y challenges emain, wi h nea ly 1,800 casual ies epo ed om i e anspo
inciden s be ween 2005 and 2015 (Wo ld Bank, 2011; T anspo in Bangladesh, 2023).
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Recen s udies also demons a e he po en ial o ene gy-e icien ship design in educing emissions. Hasan & Ka im
(2023) showed ha op imized hull o ms o inland ca go essels in Bangladesh could educe esis ance by 10–13.6%,
he eby lowe ing uel consump ion and CO₂ emissions.
IWT demons a es decisi e en i onmen al ad an ages:
Pa ame e Road (HGV) IWT Ba ge Reduc ion
CO₂/ on-km 120-150g 20-35g 75-85%
Fuel E iciency 0.25-0.4 km/L 1.2-1.8 km/L 5-7×
Sou ces: Wo ld Bank (2021); Alamgi e al. (2021); Wo ld Bank (2011); Hasan & Ka im (2023)
2.3 Cos E iciency and Economic Viabili y:
IWT's economies o scale deli e 40-60% lowe cos s o bulk shipmen s:
Pe - on-km cos : ৳1.8-2.5 (IWT) s. ৳4.2-6.0 (Road)
Hidden oad cos s: Toll ees (৳1,200-1,800/ ip) + checkpoin ex o )on (T anspa ency In e na)onal,
2022)
Labo cos sha e: 12-15% (IWT) s. 25-30% (Road) (Rahman e al., 2025)
Flood-induced cos ola ili y u he e odes he oad's economic iabili y, wi h a es su ging 200-300% du ing
disas e s e sus 20-30% o IWT (BIWTC, 2023).
In addi ion o hese s uc u al di e ences, eme ging in ech solu ions a e eshaping how MSMEs manage logis ics
cos s. By enabling as e digi al paymen s, imp o ed c edi access, and au oma ed in oicing sys ems, in ech ools can
enhance isibili y and educe inancing ba ie s in ag icul u al supply chains. This no only imp o es cash low bu
also helps SMEs adop mo e e icien anspo modes such as IWT (Rumky, La i , & Hossain, 2023).
2.4 Pos -Ha es Loss Dynamics:
In Bangladesh, pos -ha es losses a e ala mingly high—es ima ed a 20–44% annually o pe ishable i ems— la gely
due o insu icien cold-chain logis ics and poo anspo a ion in as uc u e (Fellows, 2024; FGMDhaka, 2023). One
s udy ound ha mango losses can each 27% du ing ansi when using adi ional packaging and anspo me hods,
such as bamboo baske s and ucks, pa icula ly o e bumpy u al oads (Resea chGa e, 2023). Mechanical ib a ion
and long a el imes inhe en in oad anspo u he inc ease spoilage. Resea ch indica es ha poo oad quali y
and mul iple handling poin s con ibu e subs an ially o loss o p oduce quali y, such as inc eased b uising and in e nal
damage (Na h e al., 2024). Fo example, a mic o-le el s udy o po a o supply chains in Munshiganj Dis ic epo ed
pos -ha es loss a es o 6.6% a he p oduce le el, 5.3% a he wholesale le el, wi h limi ed s o age and ough
handling iden i ied as majo con ibu o s (Ak e e al., 2022). In con as , inland wa e way anspo (IWT)—al hough
slowe —p o ides smoo he mo emen and educes handling equency, which can help p ese e he quali y o
pe ishable goods. Since IWT ollows mo e linea and p edic able ou es wi h less jos ling, i educes physical damage.
The e o e, consis en , gen le ca iage ia wa e ways is likely o esul in less spoilage han as e bu mo e e a ic oad
anspo .
2.5 In as uc u e Bu den and In es men Imbalance:
Road main enance cos s (৳8.2-10.5 million/km/yea ) d ain public esou ces (BUET, 2023), while IWT in as uc u e
o e s lowe li ecycle cos s:
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Sou ces: BUET (2023); Sa ke (2020)
Despi e IWT's e iciency, 72% o anspo budge s und oads e sus 9% o wa e ways (Minis y o Finance, 2023).
2.6 Sa e y and Acciden Risk:
Road eigh anspo in Bangladesh aces signi ican sa e y challenges, wi h high acciden and a ali y a es la gely
due o poo in as uc u e, o e loaded ehicles, and inadequa e egula ion (Wo ld Bank, 2020). The Global S a us
Repo on Road Sa e y (WHO, 2018) anks Bangladesh among coun ies wi h ele a ed oad a ic a ali y a es,
es ima ing abou 15 dea hs pe 100,000 popula ion annually, a subs an ial po ion linked o eigh ehicle c ashes.
O e c owded highways and a lack o en o cemen compound isks, a ec ing bo h d i e s and ca go.
In compa ison, inland wa e way anspo (IWT) o e s a sa e al e na i e o eigh mo emen . S udies show ha
wa e bo ne ca go anspo gene ally expe iences ewe acciden s and a ali ies pe on-kilome e due o lowe a ic
densi y, con olled na iga ion, and educed exposu e o collision isks (UNESCAP, 2021). The Bangladesh Inland
Wa e T anspo Au ho i y (BIWTA) has also epo ed ongoing imp o emen s in sa e y s anda ds, wi h inc eased
essel inspec ions and c ew aining p og ams enhancing ope a ional sa e y (BIWTA Annual Repo , 2022).
Road eigh sa e y emains c i ical wi h 18.2 acciden s/1,000 ucks and 4.2 d i e a ali ies/1,000 ope a o s (BRTA,
2023). IWT ca go ope a ions show ma kedly lowe isk:
Me ic Road IWT Reduc ion
Fa ali ies/ on-km 0.17 0.003 98%
Ca go loss e en s 12.5% 3.8% 70%
Sou ces: BIWTA (2023)
2.7 Clima e Change Adap a ion:
Bangladesh's inc easing lood ola ili y (150% ise since 2000) heigh ens oad ulne abili ies:
Ope a)onal dis up)on: 32% o highways become impassable du ing floods (ICCCAD, 2023)
Food secu i y impac : Road-dependen sys ems exace ba e sho ages du ing disas e s (FAO, 2023)
Indica o Road IWT
Annual Main enance ৳8.2M/km ৳1.3M/km (d edging)
Flood Resilience 72% ou e ailu e 22% delay
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IWT p o ides c i ical esilience, main aining ope a ions when ba ges implemen na iga ion cau ions (Sa ke , 2020).
The 2022 Sylhe loods demons a ed his: while oad eigh collapsed o 18 days, IWT mo ed 78% o eme gency
ice shipmen s (MoDMR, 2022).
2.8 Gende and Equi y Dimensions:
Women cons i u e a subs an ial sha e o Bangladesh’s ag icul u al labo o ce—app oxima ely 58% acco ding o he
Bangladesh Bu eau o S a is ics (Zaman & Pa ez, 2024). This emale-dominan wo k o ce emains ulne able due
o poo oad anspo condi ions. A comp ehensi e su ey in ol ing o e 5,000 women ac oss 24 dis ic s e ealed
ha 87% epo ed expe iencing ha assmen in public spaces, and 36% aced ha assmen egula ly while using public
anspo like buses, launches, and ains (UNDP e al., 2022; as ci ed in Wo ld Bank, 2022). Such widesp ead
ha assmen unde mines women’s mobili y and limi s hei ac i e pa icipa ion in ma ke ac i i ies.
Inland Wa e way T anspo (IWT) o e s a sa e al e na i e. IWT hubs—such as hose in Chandpu —o e cen alized
and supe ised spaces ha educe exposu e o oadside ha assmen , making hem mo e accessible and secu e o
women. While speci ic emale ma ke pa icipa ion da a a i e po s is limi ed, he secu e condi ions and assembly
poin s uc u e o IWT hubs sugges enhanced equi y and inclusion o women in ol ed in ag icul u al ade.
2. Me hod
The s udy adop s a compa a i e analysis o oadway e sus wa e way anspo o ag icul u al p oduc s. He e, we
use a mixed-me hod design ha in eg a es su ey-based da a collec ion, seconda y da a analysis, and compa a i e
anspo modeling o assess he use o inland wa e ways e sus oad anspo o ag icul u al p oduc deli e y o
Dhaka, Bangladesh.
2.1 Pa icipan s
The p ima y pa icipan s o his esea ch we e ag icul u al ade s and wholesale s ope a ing in majo Dhaka ma ke s,
including Ka wan Baza , K ishi Ma ke , and Shyambaza . The inclusion c i e ia included ade s ac i ely engaged in
sou cing p oduc s om a ious dis ic s ac oss Bangladesh and possessing expe ience wi h anspo logis ics. All
pa icipan s we e adul s (age 18-40) wi h a leas 10 o 15 yea s o ading expe ience. E hical consen was e bally
ob ained be o e pa icipa ion.
2.2 Sampling P ocedu e
A pu posi e sampling me hod was employed. A e isi ing he chosen ma ke s, ou eamma es documen ed he
answe s in a Google Fo m by asking hem he ques ions and no ing hei answe s. Pa icipan s we e selec ed o
ep esen a ange o commodi ies (po a o, onions, ice, pineapple, cucumbe , and ca o ). The p oduc s we e selec ed
based on wo g oups: pe ishable (pineapple, cucumbe , and ca o ) and non-pe ishable ( ice, po a o, and onion). In
o al, (51) ully comple ed esponses we e collec ed. F om hese su eys, we compiled a lis o dis ic s ha a e
p ima y supplie s o ag icul u al p oduc s o Dhaka. We hen selec ed 13 dis ic s o de ailed s udy, he e a e:
Rangpu , Ku ig am, Gaibandha, Sylhe , Pabna, Na o e, Rajshahi, Khulna, Bage ha , Chandpu , Cumilla, Sunamganj,
and Na singdi. Fo each chosen dis ic , we iden i ied he nea es ac i e i e po o gha , and we mapped he closes
e y gha o po ha a me s can access..Like Chilma i po o Rangpu , Ku ig am, Gaibandha, Chha ak po o
Sylhe , Sunamganj, Khulna po o Khulna and Bage ha , Ruppu po o Pabna, Rajshahi, and Na o e, Chandpu
po o Cumilla and Chandpu , Munshiganj po o Munshiganj, and Na shingdi po o Na shingdi.This me hod
Pic u e 1: Ka wan Baza
Sou ce: Ou Su ey Team
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allowed us o de ine pa allel oad ou es e sus i e
ou e scena ios o analysis.
2.3 Measu es and Va iables
The p ima y and seconda y da a collec ion o his
s udy includes:
1. (i) In he ini ial Phase(I), we conduc ed a
su ey among ag icul u al ade s in h ee
o Dhaka’s key wholesale ma ke s (Ka wan
Baza , K ishi Ma ke , and Shyampu Baza ).
A s uc u ed Google Fo m was used o
collec esponses abou he sou ce dis ic s
o hei ag icul u al p oduc s. By analyzing
he esponses, he mos equen ly ci ed
dis ic s supplying Dhaka we e iden i)ied, which we use o u he analysis.
2. (ii) Thesecondphase(II) o he p ima y esea ch was designed o collec mo e de ailed in o ma ion.
This included an in e iew wi h a BIWTA Na al A chi ec o ga he expe da a on he selec ed ou es
om he iden i)ied dis ic s o Dhaka. The ocus was speci)ically on essel speci)ica ions, BIWTA-
dis ance, a el imes, uel use, and essel d a unde di e en condi ions, like no mal o
unin e up ed jou neys, du ing es i e pe iods, and du ing eme gency o poli ical s ikes.
A )inal componen in ol ed seconda y da a collec ion o compile de ailed echnical speci)ica ions o he ehicles
and essels ope a ing on hese ou es.
The ollowing quan i a i e a iables we e used o compa e oadways and inland wa e ways:
(i)T anspo ime (usual, es i al, and dis up ion condi ions)
(ii) To al uel consump ion (li e s)
(iii) Fuel cos pe onne(in BDT
(i ) Ca bon emissions (kg pe onne)
( )Addi ional olls and se ice cha ges.
Fuel consump ion da a o diesel engines we e ob ained om T ucksBuses.com, uck model da a om Ta a Mo o s’
Bangladesh websi e, and CO₂ con e sion ac o s (2.64 kg CO₂ pe li e o diesel) om Resea chGa e publica ions.
2.4 Resea ch Design
This is a compa a i e obse a ional s udy wi h wo p ima y condi ions:
(i) Road anspo ou e: calcula ed using Google Maps ( e e ence poin s: dis ic ze o poin o Dhaka ze o poin ).
(ii) Inland wa e way ou e: es ima ed using he nea es i e po om he sou ce dis ic o Dhaka (e.g., Chilma i,
Chha ak, Khulna, Ruppu , Na singdi, Chandpu , Munshiganj)
Fo oad anspo , h ee uck ypes we e modeled based on hei wide usage o anspo a ion in Dhaka:
1. Ta a LPT 1615 (hea y load)
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2. Ta a LPT 407 (medium load)
3. Ta a ACE EX2 (ligh load)
T a el ime was adjus ed using co ec ion ac o s based on use - epo ed delays ( om he su ey) du ing Eid es i als
and poli ical ins abili y. These es ima ions we e ga he ed om public bus use s a eling on hose ou es, since di ec
access o uck d i e s was limi ed. The inc eased ime was scaled using a e age uck speeds. Mos desc ip i e
analyses and calcula ions we e pe o med in Mic oso Excel, while eg ession modeling and hypo hesis es ing o
cos e iciency we e conduc ed using ANOVA.
2.5 Validi y and Reliabili y
Finally, we compiled all hese ma ices, cos pe on, ime, and ca bon dioxide emission. He e, we ga e impo ance
o he shel li e o he goods. The me hodology hus inco po a es bo h empi ical da a wi h necessa y calcula ions o
c ea e a comp ehensi e image o supply chain e iciency unde wo anspo modes. By applying ou calcula ions
wi h eal-wo ld pa ame e s and a ious scena ios, we aimed o ensu e ha he compa ison be ween oadways and
wa e ways is no only ealis ic bu also ele an o supply chain s akeholde s.
3. Resul s
3.1 Rec ui men
Figu e 1: Flowcha showing s eps o he esea ch
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Ag icul u al ade s and wholesale s in majo Dhaka ma ke s we e ec ui ed o his s udy. Ka wan Baza (20 July
2025), K ishi Ma ke (21 July 2025), and Shyampu Baza (22 July 2025) we e su eyed. We selec ed he pa icipan s
h ough a pu posi e sampling me hod o ade s who cu en ly p ocu e p oduc s om di e en dis ic s and ha e
anspo logis ics expe ience. Indi iduals eligible o ake pa we e adul s aged be ween 18 o 40 yea s wi h a leas
10 o 15 yea s o ading expe ience. Be o e aking pa , e bal consen was gi en.
Ac i i ies o he su ey ou pu s we e analyzed o ind ou he majo sou ce dis ic s o ag icul u al p oduc s o Dhaka.
We calcula ed equencies o supply om each dis ic based on men ions a he su eyed loca ions. Table 1 con ains
he ull p oduc –sou ce equency da a used o selec he dis ic s and ou es o u he analysis.
Table 1: F equency o Ag icul u al P oduc Sou ces o Dhaka om Su ey
Based on his in o ma ion and conside ing p oximi y o ac i e i e po s, Rangpu , Ku ig am, Gaibandha, Sylhe ,
Pabna, Na o e, Rajshahi, Khulna, Bage ha , Chandpu , Cumilla, Sunamganj, and Na singdi- 13 dis ic s we e selec ed
o u he e alua ion. All dis ic s we e assigned a po , which was he nea es ope a ional i e po . The po s
assigned we e Chilma i Po o Rangpu , Ku ig am, Gaibandha dis ic , Chha ak Po o Sylhe and Sunamganj
dis ic , Khulna Po o Khulna, Bage ha dis ic , Ruppu Po o Pabna, Rajshahi, Na o e dis ic , Na singdi Po
o Na singdi dis ic , Chandpu Po o Chandpu , Cumilla dis ic , Munshiganj Po o Munshiganj dis ic . We
didn’ conside Bik ompu and Chapainawabganj o ha ing a low equency o supplies, and Bogu a and Dinajpu
o no ha ing a i e po loca ed nea by. The su ey collec ed in o ma ion on bo h pe ishable and non-pe ishable
goods like po a oes, onions, ice, cucumbe , pineapple, ca o s, and oma o.
A ollow-up ime su ey was conduc ed ia a Google Fo m sha ed in a Facebook g oup o ~6,000 BUET s uden s,
asking esponden s o epo a el imes om hei dis ic s o Dhaka unde a ious condi ions: no mal days, es i als
(Eid-ul-Fi e, Eid-ul-Azha), long weekends, na ional e en s, peak holiday seasons, and poli ical allies o s ikes. The
esponses we e analyzed o de e mine a e age usual a el imes, which we e hen con e ed o uck a el imes
using Passenge Ca Equi alen (PCE) ac o s o compa a i e anspo modeling. Table 2 summa izes hese a el
imes.
Table 2: A e age T a el imes by bus om selec ed dis ic s o Dhaka
Eid-ul-Fi e Eid-ul-Azha Long
Weekends
Na ional
E en s
Peak
Holiday
Season
Poli ical
Rallies/S ik
es
Usual Time
7.66 8.00 6.03 6.09 6.72 8.07 5.68Time (h )
P oduc Sou ce F equency o
Sou ce
Nea by
Ri e po P oduc Sou ce F equency
o Sou ce
Nea by
Ri e po
Po a o Bogu a 3 N/A Cucumbe Bage ha 3 Khulna
Bik ompu 2 Rangpu 3 Chilma i
Thaku gaon 3 Chilma i Rajshahi 3 Ruppu
Rajshahi 4 Ruppu Dinajpu 2
Munshiganj 3 Munshiganj Pineapple Sylhe 4 Chha ak
Onion Pabna 4 Ruppu Cumilla 3 Chandpu
Rajba i 3 Khulna Ca o Manikganj 2
Rice Rajshahi 4 Ruppu Toma o Rajshahi 3 Ruppu
Dinajpu 4 N/A Chapainawabganj 2
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CO2 Emission Th ough Roadway 19.55 kg CO2/L
CO2 Emission Th ough Wa e way 5.52 kg CO2/L
0 5 10 15 20 25
CO2 Emission Th ough Roadway
CO2 Emission Th ough Wa e way
Kg CO2 pe Tonne
3.5 Ancilla y Analysis
We also asked ade s abou hei expe iences wi h oad and i e anspo . Mos said ucks a e easie o sho ips
o u gen deli e ies, bu o bulk goods o when oads a e c owded, i e s like he Jamuna, Padma, and Meghna a e
as e and mo e eliable. T ade s men ioned ha wa e ways sa e a lo o ime du ing a ic jams o b idge delays,
especially in places like Rangpu , Gaibandha, Fa idpu , and Cumilla. I ems like po a oes, onions, ga lic, cucumbe s,
pineapples, and jack ui s o en mo e by i e when oads a e slow o blocked. They also no ed ha i e anspo
has mo e p edic able cos s compa ed wi h olls and handling ees on he oad, making i a p ac ical choice o la ge
shipmen s.
4. Hypo hesis Tes
4.1 P ima y Hypo hesis
4.1.1 Fo Cos E iciency
The i s p ima y hypo hesis posi ed ha inland wa e way anspo (IWT) would demons a e g ea e cos e iciency
han oad anspo , leading o a lowe cos pe onne. The null hypo hesis (H₀) s a ed ha he e is no di e ence in he
mean cos pe onne be ween he wo modes (µ_cos _ oad = µ_cos _wa e ), while he al e na i e hypo hesis (Hₐ)
p edic ed ha he mean cos o IWT would be s a is ically lowe (µ_cos _wa e < µ_cos _ oad). To es his, he
s udy employed a obus me hodological app oach, collec ing p ima y da a on key cos a iables—including uel
consump ion, dis ance, diesel p ices, and ancilla y ees like olls and po cha ges— o mul iple ou es. The
subsequen analysis u ilized linea eg ession o model he ela ionship be ween dis ance and cos o each mode. This
me hod was chosen o e a simple mean compa ison because i allowed he esea che s o quan i y how cos s scale
wi h dis ance and iden i y a p ecise b eak-e en poin . The esul s p o ided compelling e idence o ejec he null
hypo hesis: he eg ession o oad anspo showed a s eep, s a is ically signi ican slope (p = 0.0275), indica ing
Figu e 5: Compa a i e analysis o a el ime o sho and long dis ance
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cos s ise sha ply wi h dis ance. In con as , he eg ession o IWT e ealed a much la e , also signi ican slope (p
= 0.0409). C ucially, he lines in e sec a a calculable b eak-e en dis ance, beyond which IWT is unequi ocally
cheape . This inding o e s s ong, empi ical p oo ha suppo s Hₐ, demons a ing ha while oad anspo may be
easible o sho hauls, IWT's economies o scale make i he mo e cos -e ec i e solu ion o he long-dis ance
ag icul u al supply chains ha a e c i ical o Bangladesh's economy.
4.1.2 Fo En i onmen al Impac
The second hypo hesis conce ned he en i onmen al supe io i y o IWT, speci ically i s abili y o gene a e lowe CO₂
emissions pe onne-kilome e compa ed o oad eigh . The o mal null hypo hesis (H₀) claimed no di e ence in
mean emissions (µ_CO2_ oad = µ_CO2_wa e ), and he al e na i e (Hₐ) s a ed ha IWT's mean emissions would be
signi ican ly lowe (µ_CO2_wa e < µ_CO2_ oad). The me hodology o es ing his was g ounded in a de e minis ic,
ac i i y-based emission model, a ecognized s anda d in en i onmen al enginee ing. This model in eg a ed p ima y
da a on ehicle speci ica ions (engine ype, load capaci y), ac ual ou e dis ances, and empi ically de i ed uel
consump ion a es o bo h ucks and essels. These inpu s we e p ocessed using a s anda dized emissions ac o o
diesel combus ion (2.68 kg CO₂/L), ensu ing he calcula ions we e anspa en , eplicable, and based on eal-wo ld
pe o mance me ics a he han heo e ical es ima es. The esul s o his igo ous calcula ion we e decisi e and
p o ided o e whelming e idence o ejec he null hypo hesis. The analysis concluded ha IWT emi s be ween 75%
and 85% less CO₂ pe on-km han oad anspo . This massi e educ ion is no me ely a ma ginal imp o emen bu
ep esen s a undamen al en i onmen al ad an age, a inding ha aligns pe ec ly wi h in e na ional li e a u e ci ed
in he pape , such as Wo ld Bank epo s. The me hodological choice o use a bo om-up, uel-based model lends
immense c edibili y o his esul , as i di ec ly ies emissions o ope a ional ac i i y, lea ing li le oom o ambigui y
and p o iding s ong, quan i iable e idence o con i m Hₐ.
4.1.3. Fo Ope a ional Reliabili y
The hi d hypo hesis en u ed beyond simple a e ages o assess he ope a ional eliabili y and esilience o he wo
anspo modes, asse ing ha IWT would expe ience ewe dis up ions om conges ion o poli ical un es .
S a is ically, his is a hypo hesis abou a iance and consis ency, no jus means. The e o e, he null hypo hesis (H₀)
s a ed ha he a iance in deli e y ime is equal o bo h modes (σ²_ ime_ oad = σ²_ ime_wa e ), while he al e na i e
(Hₐ) p edic ed ha he a iance o oad anspo would be signi ican ly g ea e (σ²_ ime_ oad > σ²_ ime_wa e ),
indica ing less p edic abili y. A simple compa ison o mean a el imes would ha e been insu icien o es his; a
mean could be simila while one da ase is igh ly clus e ed and he o he is widely sp ead ou . The me hodology
adep ly add essed his by collec ing ime da a unde a ious condi ions—no mal days, es i als, and poli ical
s ikes—and hen employing desc ip i e s a is ics and isual analysis (e.g., line cha s) o illus a e he a iabili y. A
s a is ical es like Le ene's Tes o equali y o a iances would be he o mal ool o analyze his da a. The esul s
clea ly demons a ed ha oad ansi imes we e highly ola ile, wi h su ey da a showing hey could inc ease by
50-70% du ing dis up ions. Con e sely, IWT, ope a ing on ixed launch schedules and una ec ed by e es ial
conges ion, showed ema kable consis ency. This quali a i e inding om he su ey was powe ully ein o ced by
he ancilla y analysis, whe e ade s explici ly s a ed ha wa e ways p o ided "mo e p edic able cos s" and we e
" as e and mo e eliable" when oads we e blocked. The con e gence o quan i a i e da a on a iabili y and
quali a i e es imony on pe cei ed eliabili y p o ides a mul i- ace ed and obus body o e idence o ejec H₀ and
accep Hₐ, con i ming ha IWT o e s a mo e esilien and dependable supply chain link.
4.2 Seconda y hypo hesis
4.2.1 Fo Policy and Public In e es Impac
The seconda y hypo hesis o he s udy p oposed ha he empi ical demons a ion o IWT's ad an ages—namely, i s
cos e iciency, lowe emissions, and supe io eliabili y—would ca alyze a measu able inc ease in in e es om bo h
he public and policymake s in adop ing i as a sus ainable al e na i e o oad anspo . The o mal null hypo hesis
(H₀) o his asse ion would be ha e idence o IWT's pe o mance does no a ec he le el o in e es o in en ion
o adop i wi hin hese g oups. The al e na i e hypo hesis (Hₐ) would s a e ha demons a ing hese ad an ages leads
o a s a is ically signi ican inc ease in posi i e pe cep ion and s a ed in en ion o suppo o u ilize IWT.
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Unlike he p ima y hypo heses, his p edic ion conce ns a beha io al and pe cep ual ou come a he han a di ec ly
measu able physical me ic. The e o e, he me hodology o es i was necessa ily quali a i e and in e en ial. The
s udy did no employ a o mal s a is ical es like a p e-pos su ey o policymake s; ins ead, i ga he ed c ucial
anecdo al e idence h ough i s ancilla y analysis—speci ically, he su eys and in e iews wi h ag icul u al ade s
who a e key s akeholde s in he supply chain. The esul s o his engagemen p o ided powe ul, albei quali a i e,
suppo o Hₐ. T ade s, upon e lec ing on he compa a i e da a, epo ed a clea ope a ional p e e ence o IWT
unde speci ic condi ions, ci ing i s p edic abili y and esilience. This shi in s akeholde pe cep ion is a c i ical
leading indica o o b oade ma ke and policy accep ance. Fu he mo e, he s udy's conclusi e indings di ec ly align
wi h and p o ide empi ical ein o cemen o exis ing na ional policy goals men ioned in he li e a u e e iew, such
as clima e esilience and ood secu i y. By quan i a i ely alida ing he bene i s ha policymake s seek, he s udy's
e idence base s eng hens he a gumen o ealloca ing in es men , as highligh ed in he budge imbalance, whe e
72% o anspo unds go o oads e sus only 9% o wa e ways. Thus, while a mo e ex ensi e pe cep ion s udy
could be conduc ed, he con e gence o s akeholde es imony and he alignmen o esul s wi h s a egic policy
objec i es p o ides s ong logical e idence o ejec he null hypo hesis and accep he seconda y hypo hesis ha
demons a ing IWT's ad an ages is a pi o al s ep owa d i s wide adop ion.
5. Discussion
Bangladesh’s ag icul u al supply chains a e domina ed by oad haulage, bu he compa a i e ad an ages o inland
wa e ways (IWT) a e inc easingly ecognized. A cen al ou come o his esea ch is he compa a i e cos s uc u e
o oad and inland wa e way anspo . The analysis showed ha oad anspo can appea cheape o e y sho
dis ances, la gely due o he way ixed cha ges such as olls and po -handling ees a e dis ibu ed. Howe e , as
dis ances inc ease, he s eep slope o oad anspo cos s quickly ou paces he ela i ely la g ow h o wa e way
cos s. This aligns wi h Wo ld Bank es ima es ha IWT can educe anspo cos s by a ac o o ou o i e compa ed
o oads (He e a Dappe e al., 2020). Impo an ly, a b eak-e en dis ance was iden i ied: beyond his h eshold,
wa e ways clea ly become mo e cos -e ec i e. This inding has p ac ical implica ions, sugges ing ha hyb id
s a egies—such as using sho uck hauls o i e po s ollowed by long-dis ance ba ge anspo —could minimize
logis ics expenses o ag icul u al p oduce. Such mul imodal app oaches a e al eady common in coun ies like India
and Vie nam, and Bangladesh could bene i om adop ing simila p ac ices o ease p essu e on conges ed highways.
Alongside cos , a el ime analysis p o ides a nuanced pic u e. Road haulage is as e o e sho and medium
dis ances, especially whe e di ec highways exis . Ye oad imes luc ua e hea ily wi h conges ion, a ic es ic ions,
and oad quali y, while i e anspo is compa a i ely s able and p edic able. In long-dis ance co ido s, ba ges—
hough slowe in absolu e hou s—o e eliabili y and lowe isk o unp edic able delays. A blended app oach is
he e o e possible: ucks could se e sho ips o pe ishable goods equi ing speed, while bulk commodi ies like
g ains o non-pe ishables mo e on i e s. The su ey also highligh ed ha e y c ossings, which combine elemen s
o bo h oad and wa e anspo , can ac as e ec i e connec o s in a eas wi hou con inuous highway o deep i e
channels. In ag icul u al supply chains, such hyb id use o e ies and ba ges could signi ican ly educe he isk o
delay while e aining he lexibili y o deli e y.
Technology-d i en inno a ions a e opening new a enues o e iciency gains. Fo example, ad anced
echnologies like AI and IoT a e al eady being applied in he eady-made ga men (RMG) sec o o op imize anspo
ou es, imp o e quali y con ol, and s eamline expo p ocesses. These ools signi ican ly educe complexi y in
supply chain ope a ions (Ullah, Islam, Ray, & E a, 2024). Ex ending such app oaches o ag icul u al logis ics could
enable eal- ime moni o ing, be e coo dina ion be ween a me s and ade s, and sma e mul imodal anspo
planning by i e ways.
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Finally, he CO₂ emission analysis ein o ces he en i onmen al bene i s o inland wa e ways. Pe - onne emissions
o oad anspo we e consis en ly highe , e lec ing bo h highe uel bu n pe kilome e and he aged ehicle lee
common in Bangladesh. By con as , bulk i e essels sp ead uel use o e much la ge payloads, cu ing a e age
emissions pe onne signi ican ly. This ad an age becomes especially p onounced o long-dis ance shipmen s, whe e
oad ehicles accumula e high emissions h ough conges ion and epea ed accele a ion. The en i onmen al gain is
no me ely heo e ical. Acco ding o ESCAP (2022), shi ing e en pa o Bangladesh’s eigh o wa e ways could
cu na ional CO₂ emissions om anspo by millions o onnes annually. Fo an ag icul u e-based economy, whe e
sus ainabili y and ood secu i y a e igh ly linked, such educ ions a e o c i ical impo ance. In conges ed u ban
co ido s like Dhaka–Chi agong, diesel uck emissions sky ocke : one analysis ound ha oughly 50–73% o all
pollu an emissions om in e -dis ic ucking a e a ibu able o s op‐and‐go conges ion. I conges ion we e
elimina ed, CO₂ om hese ips would d op “by mo e han hal ”. This ine iciency e lec s comp ession-igni ion
(diesel) engine beha io : a low speeds and idling, he uel bu n pe on-km inc eases subs an ially. Compounding
he p oblem, many Bangladeshi ucks a e an iqua ed (o en impo ed second-hand) and poo ly main ained. Fo
example, newe mode n ac o ‐ aile igs a e age abou 3.5 km/L on he highway, whe eas olde igid ucks ba ely
manage 2 km/L. A su ey no ed ha “many ucks a e o e 20 yea s old,” ansla ing in o highe uel use pa ly “due
o a lack o p ope main enance”. Owne -ope a o s on slim ma gins o en de e main enance, wo sening uel
economy and ailpipe emissions.
By con as , i e ba ges can ope a e much mo e uel-e icien ly. The Wo ld Bank no es ha on a pe onne-kilome e
basis, IWT emi s up o six imes ewe g eenhouse gases han ucks. In p ac ical e ms, a join indus y-go e nmen
es ima e inds ha shi ing eigh o wa e ways (e.g., on he Dhaka–Chi agong co ido ) could sa e app oxima ely
58.5 million li e s o diesel and 155,000 onnes o CO₂ annually. Mo eo e , ucking pollu ion disp opo iona ely
impac s ci ies: oad ehicles emi in o he u ban s ee canyons o Dhaka, whe e ai quali y is al eady haza dous. In
con as , inland essels ( hough diesel-powe ed) c uise along i e s in less densely popula ed a eas, dilu ing
emissions. Roadside ai moni o s in Dhaka equen ly exceed WHO pa icula e s anda ds, and mobile sou ces ( ucks,
buses) a e a majo con ibu o . These di e ences mean ha modal shi o IWT could imp o e u ban ai quali y.
D i e beha io and sa e y is also impo an ma e o conside a ion. Road eigh also su e s om human ac o s
ha IWT la gely a oids. Long‐dis ance uck d i e s in Bangladesh o en wo k a nigh unde se e e
a igue. Res ic ions in Dhaka (banning hea y ucks du ing day ime) o ce d i e s in o la e hou s. Su eys o
Bangladeshi ucke s con i m a igue as a op c ash ac o : lack o sleep opped d i e s’ lis s (17%), wi h a ic jams
(8%) and poo oad condi ions (13%) also ci ed. A ew d i e s e en epo ed s imulan d ug use ( hough only ~1%)
o s ay awake. Nigh ime schedules and occasional s imulan s ele a e acciden isk. In con as , ba ges a e no subjec
o d i e a igue issues in he same way. While wa e cap ains wo k long hou s, i e anspo ends o ha e c ew
o a ions and c uise schedules ha can allow es ; s a is ically, he isk o a al acciden s pe on-km is d ama ically
lowe on wa e . A Wo ld Bank anspo e iew no es ha IWT can be up o i y imes sa e han ucking in e ms
0
1
2
3
4
Time (H )
Munshiganj
T uck Coun y Boa s Ba ges
0
5
10
15
20
25
Time
Rajshahi
T uck Coun y Boa s Ba ges
Figu e 6: Compa ison o a el ime o sho and long dis ance by bo h oad and wa e ways acco ding o ou
calcula ion.
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o a ali y a es. In Bangladesh, oad c ashes claim housands o li es annually (Bangladesh’s oad a ic dea h a e
was 15.3 pe 100,000 in 2019), whe eas yea ly wa e bo ne a ali ies numbe in he low hund eds a mos . Fo example,
a su ey o 40 yea s o inland essel acciden s ound a o al o oughly 5,400 dea hs, o ~135 pe yea – o de s o
magni ude below oad a ali ies.
Fo In as uc u e and main enance, bo h modes equi e upkeep, bu hei needs di e . Bangladesh’s oads a e
ch onically unde -main ained despi e hea y use. The Na ional De elopmen S a egy acknowledges “la ge-scale
de e io a ion o he ne wo k due o lack o p ope main enance,” and au ho i ies admi spending on oad upkeep “ alls
sho o wha is equi ed”. Po holes, weak b idges, and o e loading con inuously deg ade highways. Wa e ways, by
con as , ace sil a ion a he han su ace wea . Wi hou d edging, i e dep hs sh ink d ama ically; one UN s udy
es ima es only 25% o inland i e s emain na igable in he monsoon and a me e 16% in he d y season, absen
main enance. F equen d edging is hus essen ial o keep IWT iable, especially on key ou es like hose om
Cha og am o Dhaka. On he plus side, d edging es o es i e dep h along housands o kilome e s a ela i ely
modes ecu en cos , whe eas oad epai o he same eigh capaci y would equi e con inuous pa ing. In his sense,
IWT in as uc u e (d edging, na iga ional ma king, wha es) can sus ain high olumes wi h less ma e ial
eplacemen , hough he ecological impac s o d edging mus be managed.
While handling pe ishables, he choice o mode also a ec s pos -ha es quali y. Road anspo o e ough su aces
can b uise and spoil ui s and ege ables. Con olled expe imen s show ha ehicle ib a ion om une en oads
signi ican ly deg ades p oduce: o example, longe uck ansi led o ma kedly highe weigh loss and i mness loss
in oma o shipmen s. By con as , ba ge mo emen is ela i ely smoo h – he ca go loa s on wa e a he han
bouncing o e bumps – so delica e goods may expe ience less mechanical damage ( hough o mal s udies in
Bangladesh a e limi ed). Howe e , IWT is slowe : la ge essels ake days a he han hou s o long hauls. A p i a e
logis ics ope a o epo s ships ake 70–72 hou s om Cha og am o Dhaka e sus 10–14 hou s by oad. This slowe
ansi can h ea en pe ishables unless a cold chain is applied. In p ac ice, pe ishable shippe s using wa e ways o en
employ apid cooling o e en eezing be o e loading (o specialized e ige a ed ba ges) o b idge mul i-day
jou neys. Thus, a i e ou e may cu shock- ela ed loss bu can in oduce spoilage isk unless suppo ed by insula ion
o ac i e cooling, whe eas a as uck un may deli e eshe p oduce a he expense o jos le damage.
Each mode has unique ulne abili ies o dis up ions. Roads in Bangladesh a e o en jammed o blocked by ex e nal
e en s: poli ical s ikes (ha als), hea y a ic su ges a ound es i als, and seasonal loods. Recen na ionwide
blockades illus a e he impac : a nine-day poli ical s ike in 2023 cu bus and uck ope a ions o ~35% o no mal and
in lic ed oughly Tk78 c o e (USD ~9 million) pe day in losses on goods anspo alone. Du ing such e en s, many
highways become impassable o dange ously g idlocked, hal ing eigh low. In con as , inland wa e ways a e no
di ec ly a ec ed by oad s ikes, hough hey ha e hei own labo issues. Fo example, a wildca s ike by ca go
essel wo ke s in 2016 s anded 611 goods-laden boa s na ionwide. Thus, wa e ways can bypass oad blockades
( essels con inue mo ing i c ews wo k), bu su e when wa e wo ke s s ike. Na u al disas e s also a ec bo h
modes: loods in mid-2024 subme ged hund eds o kilome e s o oads, including key a e ies like he Dhaka–
Chi agong highway. In looded egions, only boa s can each isola ed illages, bu in p ac ice, he e was “a lack o
boa s o elie anspo . Cyclones and i e loods can damage docks and capsized ba ges, bu hey o en lea e
channels na igable once deb is is clea ed. On balance, oad ne wo ks a e highly p one o washou s and landslides,
whe eas wa e ways bene i om g ea e capaci y du ing high wa e (i d edged) ye equi e lood- esponse planning.
The lowe ope a ing cos and highe bulk capaci y o wa e ways ansla e in o economic bene i s and supply chain
e iciency. Pe -kilome e shipping ees on Bangladesh’s i e s can be se e al imes cheape han on oads. The UN
ESCAP es ima es ha IWT cos s oughly Tk 1 pe onne-km, compa ed o Tk 4–5 by oad. One s udy ound mo ing
one 20- oo con aine om Dhaka o Cha og am cos s abou Tk 600 pe onne by i e , e sus ~Tk 6,000 by
uck. These as uni -cos di e ences imply cheape eigh a es, which should lowe wholesale and ul ima ely
consume p ices i sa ings a e passed h ough. Fo example, impo e s no e ha a ull modal shi o wa e ways could
make Bangladeshi expo s mo e compe i i e by enabling “low-cos p oduc s” o global ma ke s. Bulk anspo also
cu s uel use pe on, so sa ings can be subs an ial.
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The impac on a me s is signi ican . Cheape , eliable anspo a ion expands ma ke access and ma gins. Lowe
logis ic cos s mean ha a me s’ p oduce can each u ban ma ke s wi h less p ice e osion. Al hough s udies on a me
incomes a e sca ce, logic sugges s ha i a a me pays hal he anspo cha ge (o less) o a gi en shipmen by
ba ge, hei ne e enue pe kg ises acco dingly. In Bangladesh’s g ain and ho icul u al sec o s, e en a 10–20% cu
in ma ke ing cos s ( h ough IWT) could no ably boos a mga e p o i abili y. Con e sely, i wa e ways a e una ailable
o slow, a me s su e highe losses: oad ib a ions di ec ly educe shel li e, and spoilage o ces p ice cu s. Thus,
unde u ilized wa e ways ep esen a missed oppo uni y o ag icul u al p oduce s.
Despi e he ad an ages, IWT is no a panacea. Reliabili y can be unde mined by na iga ional cons ain s: many i e s
a e shallow o obs uc ed by shoals. P i a e shippe s epo ha ba ges “o en ge s uck in shoals,” and key channels
equi e egula d edging. Seasonal wa e le el a ia ions impose schedule unce ain y. Mo eo e , i e essels in
Bangladesh end o be old and o en ope a ed by unde - ained c ews, leading o acciden s: one ope a o lamen ed ha
8–10 ships sink each yea on a busy ou e. These inciden s unde sco e ha wa e anspo has sa e y and eliabili y
issues o i s own. Sho e handling is also a bo leneck: inadequa e po in as uc u e and limi ed je ies can nega e
some ime sa ings. Finally, pe ishable shippe s mus in es in be e cooling in as uc u e o ully exploi IWT – an
up on cos ha pa ly o se s eigh sa ings.
In con as , oad anspo aces almos opposi e cons ain s. T ucks a e nimble and can deli e doo - o-doo , so
logis ics scheduling is mo e lexible ( o example, hey can un a any hou i cu ews allow). Ye Bangladesh ac ually
es ic s hea y uck mo emen on majo ci y oads du ing day ime (e.g., 8 am–8 pm bans in u ban a eas), o cing
nigh d i es ha heigh en a igue isk. Roads equi e cons an esu acing unde hea y loads, and acciden s and
conges ion emain endemic. The ne e ec is ha oads impose signi ican hidden cos s: a ic jams alone may
accoun o he majo i y o ip cos s and en i onmen al ex e nali ies.
6. Theo e ical and P ac ical Implica ions
6.1 Theo e ical
This s udy in o ms us abou he de ails o supply chain li e a u e by p o iding a compa ison o oadway e sus inland
wa e way anspo in Bangladesh’s ag icul u al sec o . Bangladesh has an ex ensi e i e ne wo k o oughly 24,000
km ha emains la gely unde u ilized (Wo ld Bank 2011). By explo ing s a egies o mobilizing his la en ne wo k
o goods anspo , his s udy ex ends supply chain heo y on di e en ne wo k designs. These indings empi ically
align wi h he co e p inciples o supply chain managemen ha highligh cos e iciency, sus ainabili y, and esilience.
Ou analysis indica es ha inland wa e way anspo yields cos ad an ages, achie ing educ ions on he o de o 40–
60 pe cen pe onne-kilome e ela i e o oad haulage o bulk shipmen s, ma king he heo e ical model o cos
op imiza ion. The esul s also show ha inco po a ing inland wa e way anspo imp o es eliabili y unde dis up ed
condi ions, aligning wi h supply chain esilience heo y. Fo example, oad-dependen logis ics su e se e e delays
du ing poli ical un es , and monsoon looding can shu down up o 30 pe cen o highway links, whe eas i e anspo
con inues on p edic able schedules wi h minimal in e up ion (Ahmed & Islam, n.d.).
F om a g een logis ics pe spec i e, he s udy o e s p oo o he en i onmen al ad an ages achie able h ough modal
shi s in anspo a ion. This shows ha mo ing goods by wa e is signi ican ly mo e ca bon-e icien han
con en ional oad ucking (Wo ld Bank, 2017). By analyzing hese di e ences in Bangladesh’s con ex , his s udy
highligh s sus ainabili y- ocused supply chain models ha inco po a e low-emission modes o anspo (Noha e al.,
2023). Consis en wi h g een logis ics heo y, he esul s illus a e ha inland wa e way anspo no only educes CO₂
emissions and uel consump ion bu also deli e s pa allel gains in cos e iciency and se ice eliabili y. E en a modes
shi om oad o wa e ways could ansla e in o millions o onnes o a oided na ional CO₂ emissions annually,
unde sco ing he scale o he oppo uni y. Beyond modal shi s, digi al inno a ions such as blockchain a e inc easingly
ecognized as c i ical ools o s eng hening anspa ency and esilience in Bangladesh’s supply chains, especially in
as -g owing sec o s like e-comme ce (Haque, Hossain, & Hossain, 2022). Indeed, he esea ch e lec s he heo e ical
discussion on sus ainable mul imodal anspo and echnology adop ion by illus a ing ha economic and
en i onmen al objec i es in supply chains can be pu sued h ough s a egic mode selec ion and sma ne wo k design.
6.2 P ac ical Implica ions
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6.2.1 Policy and In as uc u e
The esul s suppo s a egic shi s in anspo o ully u ilize inland wa e ways. To acqui e bene i s, policymake s
should in es in i e d edging, na iga ional main enance, and enhanced po in as uc u e—including s o age and
cold-chain acili ies a i e po e minals. Vessel sa e y and s anda ds mus also be imp o ed. These measu es a e
needed o o e come cu en inland wa e way anspo a ion limi a ions and ensu e yea - ound eliabili y. Regula
d edging is pa icula ly c i ical o keeping wa e ways na igable, since wi hou main enance, only a ac ion o ou es
emain passable du ing he d y season.
P oac i e policy suppo o mul imodal anspo a ion will no only elie e o e s essed highways and lowe logis ics
cos s bu also ad ance na ional goals o g een g ow h and supply chain esilience by cu ing emissions and p o iding
al e na i e anspo du ing dis up ions (Wo ld Bank, 2017). In ecen yea s, many b idges ha e been cons uc ed
ac oss he coun y o inc ease oad connec i i y. Howe e , b idges o en nega i ely impac he low and na u al shape
o i e s, educing na igabili y. Rapid and some imes unplanned indus ializa ion also h ea ens i e s, as many
ac o ies a e being buil nea by, pollu ing wa e ways. Policy ini ia i es o add ess hese challenges a e c i ical o
main aining inland wa e ways. Addi ionally, high-span suspension o cable-s ayed b idges would main ain yea - ound
i e a ic e en in lood condi ions, di ec ly suppo ing he goal o expanding inland wa e way anspo a ion
alongside oad and ail. Such lood- esilien b idges o e a sus ainable way o upg ade Bangladesh’s logis ics ne wo k
by ully in eg a ing i e anspo in o he mul imodal sys em (Wo ld Bank, 2017).
6.2.2 Gende Inclusi eness
The anspo a ion sys em can play a ole in educing dispa i ies among di e en egions o a coun y. Since inland
wa e way anspo a ion has s ong pene a ion in u al Bangladesh, i could imp o e accessibili y o ma ginalized
g oups, especially women, who could bene i socially and economically (UNESCAP, 2017). Be e wa e way acili ies
acili a e women’s access o he labo ma ke , c ea ing oppo uni ies o o mal employmen . Recen ly, he go e nmen
included b eas eeding chambe s o mo he s o newbo ns and sepa a e wai ing ooms o women in newly designed
wa e c a . Such gende -inclusi e changes could be adop ed in o he sec o s as well (CUTS In e na ional, 2018).
6.2.3 Logis ics S a egy
Fo logis ics p o ide s and supply chain manage s, he s udy highligh s ways o cu cos s and boos eliabili y by
inco po a ing wa e ways in o dis ibu ion ne wo ks. Companies can adop mul imodal app oaches, using ucks o
sho -dis ance o las -mile deli e ies and ba ges o long-dis ance bulk anspo a ion. This s a egy akes ad an age
o inland wa e anspo ’s lowe uel cos s and esis ance o a ic conges ion while s ill ensu ing imely deli e ies
h ough ca e ul planning.
Logis ics i ms in Bangladesh can d aw inspi a ion om egional examples. In coun ies like India and Vie nam, oad–
i e in e modal sys ems a e employed o educe highway conges ion and enhance e iciency. Implemen ing simila
p ac ices may equi e in es men in ansshipmen acili ies a i e po s and close coo dina ion wi h ba ge ope a o s,
bu he esul is a mo e lexible and cos -e icien supply chain. By emb acing mul imodal anspo , companies can
o e mo e eliable deli e y imes and emain compe i i e when oad ne wo ks ace delays.
7. Fu u e Resea ch Scopes
While his s udy p o ides a de ailed compa a i e assessmen o oad and inland wa e way anspo o ag icul u al
supply chains in Bangladesh, se e al limi a ions lea e oom o u u e esea ch. Fi s , he analysis elied on modeled
es ima es o uel consump ion, a el imes, and emission ac o s a he han di ec measu emen s. Fu u e wo k could
inco po a e GPS- acked jou neys, eal- ime uel moni o ing, and on-si e emission es ing o alida e he assump ions
and imp o e accu acy. Second, pe ishabili y and pos -ha es loss dynamics we e only discussed quali a i ely;
con olled expe imen s acking spoilage a es o di e en commodi ies ac oss modes would p o ide s onge e idence
on quali y p ese a ion.
Thi d, he s udy modeled cos and ime unde ypical and dis up ed condi ions using su eys and seconda y sou ces,
bu did no accoun o seasonal a ia ions in i e na igabili y o changes in diesel p ices, which could signi ican ly
in luence esul s. Fu u e s udies could adop a longi udinal design, cap u ing mul i-seasonal da a o e alua e esilience
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ac oss monsoon and d y pe iods. Fou h, eg ession modeling was limi ed o linea cos –dis ance ela ionships
analyzed ia ANOVA. Ad anced econome ic me hods, such as panel da a models o s ochas ic on ie analysis, could
p o ide deepe insigh s in o e iciency and a iabili y.
Addi ionally, he esea ch did no di ec ly cap u e a me -le el impac s such as a mga e income changes, ma ke
access, o gende -speci ic challenges in adop ing IWT. Fu u e s udies could in eg a e household su eys and gende -
sensi i e analyses o e alua e b oade socio-economic ou comes. Finally, he s udy’s sample size, hough
ep esen a i e o majo Dhaka ma ke s, was geog aphically na ow. Expanding o o he u ban cen e s like Cha og am
o Khulna could es he gene alizabili y o indings and explo e in e - egional logis ics s a egies.
By add essing hese gaps wi h iche da ase s, expe imen al alida ion, and b oade s akeholde pe spec i es, u u e
esea ch can s eng hen he empi ical case o inland wa e way anspo and p o ide mo e ac ionable
ecommenda ions o policymake s and logis ics p ac i ione s.
8. Conclusion
In Dhaka-cen e ed ag icul u al supply chains, inland wa e anspo o e s compelling ad an ages: much lowe uel
use and emissions pe on-km, educed physical damage o p oduce, and as ly highe bulk capaci y ha slashes uni
cos s. These can ansla e in o lowe consume p ices and highe a m incomes in p inciple. While signi ican ba ie s
o implemen ing g een supply chain managemen exis in Bangladesh, as documen ed by Ahmed e al. (2022), his
s udy demons a es ha a modal shi owa ds IWT p o ides a p ac ical and economically iable pa hway o
o e coming many o hose challenges. Howe e , o ealize hese gains, Bangladesh mus o e come IWT's own
d awbacks: ensu ing eliable d edging and na iga ional sa e y, and de eloping cold-chain and po in as uc u e.
Empi ical e idence sugges s ha a balanced modal shi could d ama ically imp o e o e all supply-chain e iciency
and public wel a e. Fu u e policies should hus add ess bo h sides: e o ming oad eigh ( igh ening sa e y
en o cemen , cu bing o e loading, imp o ing uel s anda ds) while in es ing in i e in as uc u e and essel
mode niza ion. Such a s a egy p omises no only g eene , sa e logis ics, bu also mo e esilien and p o i able u al
supply ne wo ks o Bangladesh's ag icul u e.
Acknowledgemen :
Deeply g a e ul o Eng . Md. Zul iqa Haide , Execu i e Enginee (Na al A chi ec ), BIWTA, o his kind guidance
and suppo .
Glossa y:
Ag icul u al Supply Chains
: The ne wo k o ac) i)es in ol ed in p oducing, anspo )ng,
p ocessing, and dis ibu)ng ag icul u al p oduc s om a ms o consume s.
Ancilla y Fees
: Addi)onal cos s beyond he p ima y eigh cha ge, such as olls, handling ees,
docking cha ges, and checkpoin paymen s.
B eak-e en Dis ance
: The specific dis ance a which he o al cos o anspo )ng goods ia inland
wa e ways becomes equal o, and hen cheape han, he cos o oad anspo .
Bulk Shipmen s
: The anspo a)on o la ge, unpackaged quan))es o a single commodi y, such as
g ains, which benefi s om economies o scale.
Ca bon Foo p in
: The o al amoun o g eenhouse gases (including CO₂) emiIed di ec ly and
indi ec ly by an ac) i y, in his case, he anspo a)on o goods.
Cold-chain In as uc u e
: A empe a u e-con olled supply chain ha includes e ige a)on and
eezing acili)es o p ese e he quali y and shel li e o pe ishable goods om o igin o
des)na)on.
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CO₂ Emissions
: Ca bon dioxide eleased in o he a mosphe e, p ima ily om bu ning ossil uels
like diesel. Measu ed in kilog ams pe onne-kilome e (kg/ -km) in his s udy.
Cos pe Tonne
: The o al cos incu ed o anspo one me ic onne o goods, including uel, olls,
and o he ope a)onal ees.
De e minis#c Model
: A ma hema)cal model ha p oduces a single, p ecise ou come based on a
fixed se o inpu alues and ela)onships, wi hou accoun)ng o andomness.
D edging
: The p ocess o emo ing sedimen and deb is om he boIom o i e s, lakes, and o he
wa e ways o main ain o inc ease hei dep h o na iga)on.
Economies o Scale
: The cos ad an age achie ed when inc eased p oduc)on (o anspo
olume) leads o a lowe cos pe uni .
Emission Fac o
: A coefficien ha quan)fies he amoun o a pollu an (e.g., CO₂) eleased pe
uni o ac) i y (e.g., pe li e o diesel combus ed). In his s udy, i is 2.68 kg CO₂ pe li e o diesel.
Fin ech (Financial Technology)
: Digi al ools and plaLo ms ha imp o e and au oma e financial
se ices. In he con ex o his pape , hey help MSMEs manage logis)cs paymen s and access
c edi .
Fuel Consump#on Ra e
: The amoun o uel used pe uni dis ance a eled, ypically measu ed in
li e s pe kilome e (L/km).
Gha / Ri e Po : A landing place o jeIy on a i e bank used o boa ding, disemba king, and
loading/unloading ca go. (e.g., Chilma i Gha , Chandpu Po ).
G een Logis#cs
: The p ac)ce o managing logis)cs p ocesses in a way ha minimizes
en i onmen al impac , pa )cula ly h ough educed ene gy use and emissions.
Inland Wa e way T anspo (IWT)
: The anspo a)on o goods and people ia na igable i e s,
canals, and lakes wi hin a coun y.
In e modal T anspo
: A sys em o anspo )ng goods using mul)ple modes o anspo a)on (e.g.,
uck, ba ge, ail) in an in eg a ed chain wi hou handling he goods hemsel es when changing
modes.
Las -mile Deli e y
: The final s ep o he deli e y p ocess, geMng a p oduc om a anspo a)on
hub o i s final des)na)on (oNen a e ail ma ke o wa ehouse).
Logis#cs Resilience
: The abili y o a supply chain o an)cipa e, wi hs and, and eco e om
dis up)ons such as poli)cal s ikes, na u al disas e s, o conges)on.
Modal Shi,
: The change om one mode o anspo (e.g., oad) o ano he (e.g., inland wa e way)
o achie e economic, en i onmen al, o ope a)onal benefi s.
Mul#modal Logis#cs / T anspo :
A sys em o anspo a)on ha uses mo e han one mode o
anspo (e.g., oad and wa e ) unde a single con ac o bill o lading.
MSMEs (Mic o, Small, and Medium En e p ises):
Small businesses ha play a significan ole in he
economy, including many ag icul u al ade s and logis)cs ope a o s.
Passenge Ca Equi alen (PCE) Fac o
: A me ic used in anspo a)on enginee ing o con e he
impac o diffe en ehicle ypes (like ucks and buses) on affic flow in o an equi alen numbe
o passenge ca s. Used he e o con e bus a el )mes o equi alen uck a el )mes.
Pe ishable Goods
: Ag icul u al p oduc s ha ha e a limi ed shel li e and can decay o spoil quickly,
such as ui s and ege ables (e.g., pineapple, cucumbe , oma o).
Pos -ha es Losses
: The deg ada)on in bo h quan) y and quali y o ag icul u al p oduce ha
occu s be ween ha es and consump)on, oNen due o poo handling, anspo a)on, o lack o
cold s o age.
Pu posi e Sampling
: A non-p obabili y sampling echnique whe e esea che s selec pa )cipan s
based on specific cha ac e is)cs o quali)es ele an o he s udy, such as expe ienced ag icul u al
ade s.
Supply Chain Resilience:
The capaci y o a supply chain o ole a e dis up)on and quickly e u n o
i s no mal ope a)onal s a e.
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Ton-kilome e ( -km
): A s anda d uni o measu emen in eigh anspo ha ep esen s he
anspo o one onne o goods o e one kilome e . Used o compa e cos and emission efficiency.
T ansshipmen
: The ans e o goods om one mode o anspo o ano he a a in e media e
poin (e.g., om a uck o a ba ge a a i e po ).
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Wo ld Bank. (2011). Ene gy E icien Inland Wa e T anspo in Bangladesh. Washing on, DC: Wo ld Bank.
Re ie ed om h ps://openknowledge.wo ldbank.o g/handle/10986/27229
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Wikipedia. (2023). T anspo in Bangladesh. Re ie ed om
h ps://en.wikipedia.o g/wiki/T anspo _in_Bangladesh
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T anspo and De elopmen , 11(2), 45–58.
12. Flood Fo ecas ing and Wa ning Cen e. (2024). Flood s a is ics and highway impac s in Bangladesh: 2024
monsoon upda e. Depa men o Wa e Resou ces, Bangladesh.
13. Banglapedia. (2021). Bangladesh Inland Wa e T anspo Au ho i y. Re ie ed om
h ps://en.banglapedia.o g/index.php/Bangladesh_Inland_Wa e _T anspo _Au ho i y
14. Bush a Jahan Noha, A i Ali, Payal Kuma i Shah, P ami a Tamang, & Nus a Jahan Khan. (2023). Ci cula
Economy P ac ices in Supply Chains o Bangladesh. Supply Chain Inside | ISSN: 2617-7420 (P in ), 2617-
7420 (Online), 11(1). Re ie ed om h ps://supplychaininside .o g/ojs/index.php/home/a icle/ iew/86
15. Wo ld Bank. (2021). G een eigh assessmen o Bangladesh. Washing on, DC: Wo ld Bank.
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Chandpu Ri e Po :
Loca ion T uck Used To al
Cos k/ onnes
Chandpu
Ta a LPT
1615 229.59
Ta a LPT 407 152.70
Ta a ACE EX2
85.01
Cumilla
Ta a LPT
1615 142.94
Ta a LPT 407 99.57
Ta a ACE EX2
61.40
Chandpu
Ba ges 62.16
Coun y Boa s
98.80
0.00
50.00
100.00
150.00
200.00
250.00
Ta a LPT 1615
Ta a LPT 407
Ta a ACE EX2
Ta a LPT 1615
Ta a LPT 407
Ta a ACE EX2
Ba ges
Coun y Boa s
Chandpu Cumilla Chandpu
To al
cos k/ onnes
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Nz singdi Ri e po :
Loca ion T uck Used To al
Cos k/ onnes
Na shingdi
Ta a LPT
1615 71.63
Ta a LPT
407 43.92
Ta a ACE
EX2 19.52
Na shingdi
Ba ges 69.78
Coun y
Boa s 110.81
Munshiganj Po :
Loca ion T uck Used To al
Cos k/ onnes
Munshiganj
Ta a LPT
1615 97.91
Ta a LPT
407 45.18
Ta a ACE
EX2 16.31
Munshiganj
Po
Ba ges 22.95
Coun y
Boa s 36.94
0.00
20.00
40.00
60.00
80.00
100.00
120.00
Ta a LPT
1615
Ta a LPT
407
Ta a ACE
EX2
Ba ges Coun y
Boa s
Na shingdi Na shingdi
To al
cos k/ onnes
0.00
20.00
40.00
60.00
80.00
100.00
120.00
Ta a LPT
1615
Ta a LPT
407
Ta a ACE
EX2
Ba ges Coun y
Boa s
Munshiganj Munshiganj Po
To al
cos k/ onnes
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Appendix-D: Time compa ison in bo h ways o come o Dhaka om selec ed Dis ic s.
T anspo Eid-ul-Fi e Eid-ul-Azha Long
Weekends
Na ional
E en s
Peak
Holiday
Season
Poli ical
Rallies/S ik
es
Usual Time T anspo Eid-ul-Fi e Eid-ul-Azha Long
Weekends
Na ional
E en s
Peak
Holiday
Season
Poli ical
Rallies/S ik
es
Usual Time
T uck 2.25 2.5 2.25 1.5 2.25
3 1.5
T uck 3.5 3.5 3 3 3 3.5 3
Coun y Boa s
2.05 2.05 2.05 2.05 2.05 2.05 2.05
Coun y Boa s
5.61 5.61 5.61 5.61 5.61 5.61 5.61
Ba ges 1.56 1.56 1.56 1.56 1.56 1.56 1.56 Ba ges 4.25 4.25 4.25 4.25 4.25 4.25 4.25
T anspo Eid-ul-Fi e Eid-ul-Azha Long
Weekends
Na ional
E en s
Peak
Holiday
Season
Poli ical
Rallies/S ik
es
Usual Time T anspo Eid-ul-Fi e Eid-ul-Azha Long
Weekends
Na ional
E en s
Peak
Holiday
Season
Poli ical
Rallies/S ik
es
Usual Time
T uck 12 13 10 10 11 14 7.5 T uck 11 8 7.5 8 8 7.5 7
Coun y Boa s
23.32 23.32 23.32 23.32 23.32 23.32 23.32
Coun y Boa s
25.48 25.48 25.48 25.48 25.48 25.48 25.48
Ba ges 17.67 17.67 17.67 17.67 17.67 17.67 17.67 Ba ges 19.3 19.3 19.3 19.3 19.3 19.3 19.3
0
2
4
6
Time
Chandpu
T uck Coun y Boa s Ba ges
0
5
10
15
20
25
30
Time (H )
Sylhe
T uck Coun y Boa s Ba ges
0
5
10
15
20
25
Time (H )
Rangpu
T uck Coun y Boa s Ba ges
0
2
4
6
8
Time (h )
Na shingdi
T uck Coun y Boa s Ba ges
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T anspo Eid-ul-Fi e Eid-ul-Azha Long
Weekends
Na ional
E en s
Peak
Holiday
Season
Poli ical
Rallies/S ik
es
Usual Time T anspo Eid-ul-Fi e Eid-ul-Azha Long
Weekends
Na ional
E en s
Peak
Holiday
Season
Poli ical
Rallies/S ik
es
Usual Time
T uck 8.5 8.5 7 6.25 7 6.5 6.25 T uck 12 16 9 9 11 9 9
Coun y Boa s
25.48 25.48 25.48 25.48 25.48 25.48 25.48
Coun y Boa s
21.51 21.51 21.51 21.51 21.51 21.51 21.51
Ba ges 19.3 19.3 19.3 19.3 19.3 19.3 19.3 Ba ges 16.3 16.3 16.3 16.3 16.3 16.3 16.3
0
5
10
15
20
25
Time (H )
Gaibandha
T uck Coun y Boa s Ba ges
0
5
10
15
20
25
30
Time (h )
Sunamganj
T uck Coun y Boa s Ba ges
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Appendix E: Su ey esponse o a el by bus
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Name o
you
dis ic
Time
aken o
a el
du ing
Eid-ul-
Fi e
Time
aken o
a el
du ing
Eid-ul-
Azha
Time
aken o
a el
du ing
long
weekend
s
Time
aken o
a el
du ing
Na ional
e en s
Time
aken o
a el
du ing
peak
holiday
season
Time
aken o
a el
Du ing
poli ical
allies o
s ikes
Time aken o a el
Dhaka usually om
you selec ed dis ic
Cumilla 2 h s 2h s 3h s 2:30h s
Rajshahi 8-9 h s 8-9 h s 7-8 h s 10 h s+ 6h s+-
Cumilla
2 hou 30
mins
2hou 30
mins
2 hou 30
mins 2 hou
2 hou 30
mins 3 hou s 2hou
Chandpu
3.5 hou s
app oxim
a ely
3.5 hou s
app oxim
a ely
3 hou s 3 hou s 3 hou s 3.5 hou s 3 hou s
Rangpu
11 up o
20 hou s
+
11 up o
20 hou +
10 o
15+ hou
7 o 8 hou s,, i he e
will no jam, i will ake
almos 6 hou s.
Rangpu 13/14 h 13/ 14 h 9-10
hou s
9-10
hou s
9-10
hou s 13/ 14 7 h
Rangpu 9-12
hou s
9-12
hou s
9-10
hou s
9-11
hou s
9-12
hou s
12
hou s++ 9 hou s
Shunamg
anj 8-9 h 8-9 h 7h 6-6.5 h 7 h 6-7h 6-6.5 h
Sylhe 12h s 8h s 8h s 8h s 8h s 8h s 7h s
Rangpu 15h + 15h + 12h + 10h + 20h + 9h
Gaibandh
a12hou s 16 hou s 9 hou s 9 hou s 10-12
hou s 9 hou s 9 hou s
Rangpu 10/12
hou s
10/12
hou s
10/12
hou s
7/8
hou s
7/8
hou s
8/9
hou s 8/9 hou s
Cumilla 3h 3h 2.5h 5h 2h
Na singdi 3hou s 3hou s 2hou a 4hou s 4hou s 5hou s 1.5hou s
Cumilla 3:00
hou s
3:00
hou s
3:00
hou s
3:00
hou s
3:00
hou s
3:00
hou s 2:00 hou s
Rajshahi 8-10
hou s
10-12
hou s 7-8 hou s 5-6 hou s 7-8 hou s 9-12
hou s 5-6 hou s
Rajshahi 14h 9h 8h 13h 15h 16h 6h
Rangpu 12-20h 12-20h 10 12 12 12 8
Rangpu 10-12
hou s
10-12
hou s 8-9 hou s 8-9 hou s 8-9 hou s 8-9 hou s 8-9 hou s
Cumilla 3 h 3 h 2.5 h 4 h 3 h 4/ 5 h 2 h
Rangpu 15 hou s 12 hou s 12 hou s 12 hou s 12 hou s 12 hou s 8 hou s
Rangpu 12+
hou s
Once i
ook 12
hou s
8-10
hou s 7 hou s 10 hou s
a g
Ne e
been on
such
ime
6-7 hou s
Sylhe 10-12 h 10-12 h 7 8 8-Sep 7 7
Rajshahi 5-7 hou s 5-7 hou s 5-7 hou s 5 hou s 5-7 hou s 8-10
hou s 5 hou s
Munshig
anj
2-2.5
hou s 2-3 hou s 1.5-3
hou s 1-2 hou s 1.5-3
hou s
2.5-3.5
hou s 1.5 hou s
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