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The Firm Adoption of Technology (FAT) Survey, 2019

Bangladesh, 2019
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Reference ID
BGD_2019_FAT_v01_M
DOI
https://doi.org/10.48529/hgry-h633
Producer(s)
Xavier Cirera, Diego Comin, Marcio Cruz
Collection(s)
The Firm Adoption of Technology (FAT) Survey
Metadata
Documentation in PDF DDI/XML JSON
Created on
Mar 05, 2026
Last modified
Apr 23, 2026
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20302
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Data file: fat_bangladesh_disclosure

Firm-level Adoption of Technology (FAT) Bangladesh survey dataset

Cases: 903
Variables: 515

Variables

c11_02a
Leather goods - basic
c11_02b
Leather goods - fashion
c11_02c
Leather goods - sports
c11_02d
Leather goods - shoes
c11_02e
Leather goods - other
c11_03a
Finishes - screen print
c11_03b
Finishes - embroidery
c11_03c
Finishes - seamless
c11_03d
Finishes - ink or wax
c11_03e
Finishes - waterproofing
c11_03f
Finishes - other
c11_1a1
Provide files for design
c11_1a2
Most common files
c11_1a3
Design drawing - in house
c11_1a4
Design drawing - outsourced (another unit - same firm)
c11_1a5
Design drawing - outsourced (another firm)
c11_1b1
Design - Manual
c11_1b2
Design - Digital or semi-digital
c11_1b3
Design - CAD, 3D, or virtual
c11_1b4
Design - Other
c11_1c
Design - MOST used method
c11_1d
Years using c11_1b2, c11_1b3
c11_2a1
Cutting - in-house
c11_2a2
Cutting - outsourced (another unit - same firm)
c11_2a3
Cutting - outsourced (another firm)
c11_2b1
Cutting - Manual
c11_2b2
Cutting - Machine manually-operated
c11_2b3
Cutting - Semi-automatic machine
c11_2b4
Cutting - Automatic/Computerised (no Laser)
c11_2b5
Cutting - Automatic/Computerised (Laser)
c11_2b6
Cutting - Other
c11_2c
Cutting - MOST used method
c11_2d
Years using c11_2b4, c11_2b5
c11_3a1
Sewing - in-house
c11_3a2
Sewing - outsourced (another unit - same firm)
c11_3a3
Sewing - outsourced (another firm)
c11_3b1
Sewing - Manually
c11_3b2
Sewing - Machine (manually)
c11_3b3
Sewing - Machine (semi-automated)
c11_3b4
Sewing - Machine (automated)
c11_3b5
Sewing - 3D Knitting
c11_3b6
Sewing - Other
c11_3c
Sewing - MOST used method
c11_3d
Years using c11_3b3, c11_3b4, c11_cb5
c11_3e1_bd
Using c11_3b3, c11_3b4, c11_3b5 - Reason 1
c11_3e2_bd
Using c11_3b3, c11_3b4, c11_3b5 - Reason 2
c11_3f_bd
Ratio change - sewing (leather)
c11_4a1
Assembly/Finishing - in-house
c11_4a2
Assembly/Finishing - outsourced (another unit - same firm)
c11_4a3
Assembly/Finishing - outsourced (another firm)
c11_4b1
Assembly/Finishing - manual
c11_4b2
Assembly/Finishing - conveyor/assembly (static/semi-automated)
c11_4b3
Assembly/Finishing - conveyor/assembly (dynamic/automated)
c11_4b4
Assembly/Finishing - injection machine
c11_4b5
Assembly/Finishing - 3D printing
c11_4b6
Assembly/Finishing - Other
c11_4c
Assembly/Finishing - MOST used method
c11_4d
Years using c11_4b3, c11_4b4, c11_4b5
c4_6a
Use sewing machines - Apparel Sector
c4_6b
No. of sewing machines - Apparel Sector
c4_6c1
Sewing machines - no motor - Apparel Sector
c4_6c2
Sewing machines - external motors - Apparel Sector
c4_6c3
Sewing machines - clutch motors - Apparel Sector
c4_6c4
Sewing machines - servo motors - Apparel Sector
c4_6f
Clutch motors replaced by servo? - Apparel Sector
c11_5a_bd
Use sewing machines - Leather Sector
c11_5b_bd
No. of sewing machines - Leather Sector
c11_5c1_bd
Sewing machines - no motor - Leather Sector
c11_5c2_bd
Sewing machines - external motors - Leather Sector
c11_5c3_bd
Sewing machines - clutch motors - Leather Sector
c11_5c4_bd
Sewing machines - servo motors - Leather Sector
c11_5da1_bd
Sewing Machines - NEW purchases 2016-19
c11_5db1_bd
Sewing Machines - SECOND-HAND purchases 2016-19
c11_5da2_bd
Sewing Machines - NEW purchases 2012-15
c11_5db2_bd
Sewing Machines - SECOND-HAND purchases 2012-15
c11_5da3_bd
Sewing Machines - NEW purchases 2011 or before
c11_5db3_bd
Sewing Machines - SECOND-HAND purchases 2011 or before
c11_5e1_bd
Monthly units of electricity (ref_year1)
c11_5e2_bd
Monthly pay per unit (ref_year1)
c11_5e3_bd
Monthly units generate electricity (ref_year1)
c11_5e4_bd
Monthly cost per unit (ref_year1)
c11_5f_bd
Clutch motors replaced by servo? - Leather Sector
c11_5g_bd
Technician - in-house or outside
c11_5h_bd
Subcontract - bigger firms in leather and footwear
c11_5i_bd
Factory manager - ILET graduate
d1a
Purchase/Lease - Equip. or Mach.
d1b
Purchase or Lease - Software License
d1c
Dev., Custom. or Modif. of Machine or Software
d1d
Partnership - Development
d1e
Most contributing partner - Software/Machine Dev
d2a
Most used info. source for decision making
d2a1_bd
Type of firms using info
d2b
Firm with >= 50 employees in around 50 kms
d2c
Business Relationship - >= 50 emp. and around 50 kms
d2d
Business Relationship - Multinational firm
d2e
CEO Experience - Large firm in same sector/multinational firm
d3a
Loan - mach., equip or licensing
d3b
Interest rate on loan
d3c
No. - needed to borrow but not get it
d4a
Formal Incentives - Money, gift, or recognition
d4b
No. KPIs monitored
d4c
Frequency monitoring the KPIs
d4d
Time frame - production targets
d5a
Hired engineers, computer programmers, or eq.
d5b
Challenge to hiring engineers, computer programmers, or equivalent
d5c
Used external consultants or organisations
d5d
Main source of external consultants or organisations
d5e
Why not consultants or organisations
d5f
Adjustment of labour during technological changes
d6a
Did export?
d6b
Direct Exports (% of sales)
d6c
Imported inputs, machines or equipment?
d6d
Avg. final price paid (base = 100)
d6e
Number of days from entry to customs
d6a1_bd
No. of days from main point to custom clear
d7a
Awareness - govt. support program/subsidy for tech. adoption
d7b
Benefitted from any govt. program/subsidy
d7c_1
Govt support - information
d7c_2
Govt support - tech assistance
d7c_3
Govt support - tax incentive
d7c_4
Govt support - grant
d7c_5
Govt support - loan
d7c_6
Govt support - other
e1a
No. of permanent workers, full-time (ref_year1)
e1b
No. of permanent workers, part-time (ref_year1)
e1c
No. of temporary or seasonal workers, full-time (ref_year1)
e1d
No. of temporary or seasonal workers, part-time (ref_year1)
e1e
Average length of temporary or seasonal workers (ref_year1)
e1f
Total share of female workers (ref_year1)
e2a
No. of permanent workers, full-time (ref_year2)
e2b
No. of permanent workers, part-time (ref_year2)
e2c
No. of temporary or seasonal workers, full-time (ref_year2)
e2d
No. of temporary or seasonal workers, part-time (ref_year2)
e2e
Average length of temporary or seasonal workers (ref_year2)
e2f
Total share of female workers by the end of the year (ref_year2)?
e3a
No. of CEOs and Managers (ref_year1)
e3b
No. of Professionals (ref_year1)
e3c1_bd
No. of Manufacturing Supervisors (ref_year1)
e3c2_bd
No. of Other Technicians (ref_year1)
e3d
No. of Clerical support workers (ref_year1)
e3e
No. of Production workers (ref_year1)
e3f
No. of Service or sales workers (ref_year1)
e4a
No. of CEOs and Managers (ref_year2)
e4b
No. of Professionals (ref_year2)
e4c1_bd
Manufacturing Supervisors (ref_year2)
e4c2_bd
Other Technicians (ref_year2)
e4d
No. of Clerical support workers (ref_year2)
e4e
No. of Production workers (ref_year2)
e4f
No. of Service or sales workers (ref_year2)
e4g_bd
No. of Production line supervisors
e4h_bd
No. of Production line workers
e5a
% of workers - completed primary education
e5b
% of workers - completed secondary education
e5c
% of workers - vocational training
e5d
% of workers - completed college degree or more
e5e
No. of workers - engineering or applied science
e5f
No. of workers - MBA, Masters or Doctoral degree
e3g
Workers dedicated to R&D activities?
e3h
No. of workers dedicated to R&D activities?
e6a
Total sales (ref_year1)
e6b
Total sales (ref_year2)
e6c_bd
Sales (ref_year1) - calendar or fiscal year
e6d_bd
Sales (ref_year2) - calendar or fiscal year
e7a
Total labor cost (ref_year1)
e7b
Total material cost (ref_year1)
e7c
Total energy cost (ref_year1)
e7d
Operation cost (ref_year1)
e7e_bd
Cost (ref_year1) - calendar or fiscal year
e8a
Equipment cost (ref_year1)
e8b
Building cost (ref_year1)
e10a
Main product - % share in total sales
e10b
Main product - average markup
f1a_bd
F1.a Using the response options on the card, to what degree are the following fa
f1b_bd
F1.b Using the response options on the card, to what degree are the following fa
f1c_bd
F1.c Using the response options on the card, to what degree are the following fa
f1d_bd
F1.d Using the response options on the card, to what degree are the following fa
f1e_bd
F1.e Using the response options on the card, to what degree are the following fa
f1f_bd
F1.f Using the response options on the card, to what degree are the following fa
f1g_bd
F1.g Using the response options on the card, to what degree are the following fa
f1h_bd
F1.h Using the response options on the card, to what degree are the following fa
f1i_bd
F1.i Using the response options on the card, to what degree are the following fa
f1j_bd
F1.j Using the response options on the card, to what degree are the following fa
f1k_bd
F1.k Using the response options on the card, to what degree are the following fa
f1l_bd
F1.l Using the response options on the card, to what degree are the following fa
f3a_bd
F3a In a typical week over the last year, what percentage of total senior manage
f4a_bd
F4a Over the last complete fiscal year, please estimate the proportion of this e
f4b_bd
F4b Over the last complete fiscal year, please estimate the proportion of this e
f4c_bd
F4c Over the last complete fiscal year, please estimate the proportion of this e
f4d_bd
F4d Over the last complete fiscal year, please estimate the proportion of this e
f4e_bd
F4e Over the last complete fiscal year, please estimate the proportion of this e
country
firm_id
Firm ID
a5a
Sector - group
country_code
firmid
s1a_rev
s1b_rev
s1c_rev
formality
Formal Sector
base_wt
Sampling Weight
survey_year
Survey Year
ref_year1
Reference Year 1
ref_year2
Reference Year 2
s2f
Country
s2e
State/Province
d8a
1st obstacle to adopt technology
d8b
2nd obstacle to adopt technology
d8c
3rd obstacle to adopt technology
d8d
1st reason for the acquisition of technology
d8e
2nd reason for the acquisition of technology
d8f
3rd reason for the acquisition of technology
s1a
Sampling sector
s1b
Sampling size
s1c
Sampling location
old_a5a
Total: 515
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