Cost Inefficiency of Japanese Railway Companies and Impacts of COVID-19 Pandemic and Digital Transformation
Abstract
:1. Introduction
2. Literature Review
2.1. Stochastic Frontier Analysis (SFA)
2.2. Efficiency Analysis of the Railway Sector
2.3. Efficiency Analysis of Public Transport Other Than the Railway Sector
2.4. The Impact of the COVID-19 Pandemic and Digital Transformation
2.5. The Method to Improve Cost Inefficiency
2.6. Position of This Study
3. Methodology
3.1. Methodology
- (i)
- (percentage of local lines’ operating kilometers): to examine whether inefficiency increases with a higher percentage of local routes and fewer users.
- (ii)
- (number of transformer substations): to examine whether the cost of operating equipment represented by transformer substations, including overhead line facilities and other ground infrastructure required for electric railways, affects inefficiency.
- (iii)
- (population density of railway operating areas: to examine whether population density in relation to the number of railway passengers affects inefficiency.
- (iv)
- (railway usage rate): to examine whether railway usage rate affects inefficiency.
- (v)
- (dummy variable of regional core city) and (dummy variable of local areas): to examine whether there are differences in inefficiency according to city size and location.
3.2. Data
- (i)
- Percentage of operating kilometers of local lines: We used data from the Annual Report on Railway Statistics. Specifically, this is the ratio of all local lines’ operating kilometers, calculated as an average daily transit capacity (transit density) of local lines with less than 2000 passengers/day to the total operating kilometers. Here, the limit of 2000 passengers/day is determined by Japan National Railways as a guideline for discontinuing railway lines.
- (ii)
- Number of transformer substations: We used data from the annual securities reports of each railway company. This number represents the total number of traction substations owned by each railway company.
- (iii)
- Population density of railway operating areas: We used census data for the population and the area of each prefecture. As the census is conducted every 5 years, the most recent census data are used for several years. For example, 2005 data were used from 2005 to 2009 and 2010 data were used from 2010 to 2014. Specifically, we used the population density of the prefecture in which each railway company operates. If the operating area extended over several prefectures, the population density was calculated using the average value.
- (iv)
- Railway usage rate. We used data from the inter-prefectural passenger table of the Inter-Regional Travel Survey in Japan. However, as we could not access data on private car use, we used the percentage of railway users relative to that of the entire public transport system. Specifically, we calculated the rate for the four JR companies (JR-EAST, JR-CENTRAL, JR-WEST, and JR-KYUSHU) and for the OPR companies using Equation (6):
- (v)
- Dummy of regional core city: It takes 1 if the operating area includes an ordinance-designated city, excepting three metropolitan areas (Tokyo, Kanagawa, Saitama, Chiba, Osaka, Kyoto, Hyogo, Nara, Wakayama, Aichi, Gifu, and Mie prefectures), that is, Fukuoka, Kumamoto, Hiroshima, Okayama, Shizuoka, Hamamatsu, Niigata, or Sendai City, and 0 otherwise.
- (vi)
- Dummy of local areas: It takes 1 if the three metropolitan areas and regional core city are not included in the operating area, and 0 otherwise.
3.3. Flow of Analysis
4. Results and Discussion
4.1. Estimation Results for Stochastic Cost Frontier Function
4.2. Estimation Results of Cost Inefficiency
4.3. Comparison of Cost Inefficiency Before and during the COVID-19 Pandemic
4.4. Measures for Efficiency Improvement
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Fiscal Year | The Number of Surplus Companies | The Number of Loss-Making Companies |
---|---|---|
2019 | 25 | 1 |
2020 | 0 | 26 |
2021 | 5 | 21 |
No. | Company | 2019 (a) | 2020 (b) | 2021 (c) | Percentage in 2020 to 2019 (b)/(a) | Percentage in 2021 to 2019 (c)/(a) |
---|---|---|---|---|---|---|
1 | JR-EAST | 254,877 | 252,115 | 248,331 | 98.9% | 97.4% |
2 | KEIO | 14,713 | 14,582 | 14,404 | 99.1% | 97.9% |
3 | KEISEI | 13,933 | 13,524 | 13,804 | 97.1% | 99.1% |
4 | SHIN-KEISEI | 2465 | 2469 | 2683 | 100.2% | 108.8% |
5 | TOBU | 37,895 | 38,329 | 38,294 | 101.1% | 101.1% |
6 | SEIBU | 20,247 | 20,115 | 20,100 | 99.3% | 99.3% |
7 | TOKYU | 19,995 | 20,065 | 19,440 | 100.4% | 97.2% |
8 | KEIKYU | 15,823 | 15,761 | 15,546 | 99.6% | 98.2% |
9 | ODAKYU | 20,998 | 20,883 | 20,614 | 99.5% | 98.2% |
10 | SOUTETSU | 5052 | 5215 | 4941 | 103.2% | 97.8% |
11 | CHICHIBU | 2075 | 1649 | 1729 | 79.5% | 83.3% |
12 | FUJIKYU | 723 | 532 | 662 | 73.6% | 91.6% |
13 | JR-CENTRAL | 112,178 | 104,671 | 103,473 | 93.3% | 92.2% |
14 | MEITETSU | 40,075 | 39,522 | 38,685 | 98.6% | 96.5% |
15 | JR-WEST | 189,530 | 182,932 | 175,333 | 96.5% | 92.5% |
16 | NANKAI | 16,347 | 15,760 | 15,714 | 96.4% | 96.1% |
17 | KINTETSU | 56,638 | 55,820 | 53,302 | 98.6% | 94.1% |
18 | KEIHAN | 13,240 | 13,169 | 11,937 | 99.5% | 90.2% |
19 | KEIFUKU | 940 | 934 | 920 | 99.4% | 97.9% |
20 | HANKYU | 21,889 | 21,827 | 21,766 | 99.7% | 99.4% |
21 | HANSHIN | 8404 | 8410 | 8391 | 100.1% | 99.8% |
22 | KOBE | 4308 | 4154 | 4138 | 96.4% | 96.1% |
23 | SANYO | 6847 | 6871 | 6819 | 100.4% | 99.6% |
24 | HIRODEN | 4817 | 4817 | 4208 | 100.0% | 87.4% |
25 | JR-KYUSHU | 63,352 | 59,658 | 59,767 | 94.2% | 94.3% |
26 | NISHITETSU | 8686 | 8435 | 8302 | 97.1% | 95.6% |
Company | Region | Start Year and Month | Number of Implemented Lines | Time to Move Up the Last Train (Minutes) | Source |
---|---|---|---|---|---|
JR-EAST | KANTO | March 2021 | 17 | 3–37 | (JR-EAST 2020) |
KEIO | KANTO | March 2021 | 2 | 10–30 | (KEIO 2020) |
KEISEI | KANTO | March 2021 | 5 | 10–20 | (KEISEI 2020) |
TOBU | KANTO | March 2021 | 3 | 9–15 | (TOBU 2021) |
SEIBU | KANTO | March 2021 | 10 | 20–30 | (SEIBU 2020) |
TOKYU | KANTO | March 2021 | 7 | 8–26 | (TOKYU 2021) |
KEIKYU | KANTO | March 2021 | 4 | 14–30 | (KEIKYU 2020) |
ODAKYU | KANTO | March 2021 | 3 | 7–23 | (ODAKYU 2020) |
SOTETSU | KANTO | March 2021 | 2 | 15–20 | (SOTETSU 2021) |
JR-CENTRAL | CHUKYO | March 2022 | 2 | 15–21 | (JR-CENTRAL 2021) |
MEITETSU | CHUKYO | May 2021 | 5 | 5–30 | (MEITETSU 2021) |
JR-WEST | KANSAI | March 2021 | 12 | 10–30 | (JR-WEST 2020b) |
NANKAI | KANSAI | May 2021 | 2 | 15–17 | (NANKAI 2021) |
KINTETSU | KANSAI | July 2021 | 14 | 8–29 | (KINTETSU 2021) |
KEIHAN | KANSAI | September 2021 | 5 | 13–21 | (KEIHAN 2021) |
KEIFUKU | KANSAI | March 2021 | 1 | 15 | (KEIFUKU 2021) |
HANKYU | KANSAI | March 2021 | 3 | 13–32 | (HANKYU 2021) |
HANSHIN | KANSAI | March 2021 | 1 | 10–14 | (HANSHIN 2021) |
KOBE | KANSAI | March 2021 | 2 | 15–21 | (KOBE 2021) |
JR-KYUSHU | FUKUOKA | March 2021 | 2 | 18–20 | (JR-KYUSHU 2020) |
NISHITETSU | FUKUOKA | March 2021 | 1 | 13–30 | (NISHITETSU 2020) |
Company | Reduction in the Number of Stations with Staffed Ticket Counters | Source |
---|---|---|
JR-EAST | 300 (2021–2025) | (JR-EAST 2021) |
JR-WEST | 160 (2020–2022) | (JR-WEST 2020a) |
JR-KYUSHU | 48 (2022) | (JR-KYUSHU 2021) |
CHICHIBU | 27 (2022) | (CHICHIBU 2022) |
NISHITETSU | 24 (2020) 9 (2022) | (NISHITETSU 2020) (NISHITETSU 2022) |
Company | Region | Line Name | Operating Kilometers | Date of Abolition |
---|---|---|---|---|
JR-EAST | TOHOKU | Ofunato | 43.7 | 1 April 2020 |
JR-EAST | TOHOKU | Kesennuma | 55.3 | 1 April 2020 |
No. | Company Name | Business Type | Service Area |
---|---|---|---|
01 | JR-EAST | JR | KANTO, TOHOKU, CHUBU (Yamanashi, Nigata, Nagano, Shizuoka) |
02 | KEIO | OPR | KANTO (Tokyo) |
03 | KEISEI | OPR | KANTO (Tokyo, Chiba) |
04 | SHIN-KEISEI | OPR | KANTO (Chiba) |
05 | TOBU | OPR | KANTO (Tokyo, Saitama, Gunma, Tochigi, Chiba) |
06 | SEIBU | OPR | KANTO (Tokyo, Saitama) |
07 | TOKYU | OPR | KANTO (Tokyo, Kanagawa) |
08 | KEIKYU | OPR | KANTO (Tokyo, Kanagawa) |
09 | ODAKYU | OPR | KANTO (Tokyo, Kanagawa) |
10 | SOTETSU | OPR | KANTO (Kanagawa) |
11 | CHICHIBU | OPR | KANTO (Saitama) |
12 | FUJIKYU | OPR | CHUBU (Yamanashi) |
13 | JR-CENTRAL | JR | KANTO (Tokyo, Kanagawa), CHUBU (Shizuoka, Nagano, Yamanashi), CHUKYO (Aichi, Gifu, Mie), KANSAI (Shiga, Kyoto, Osaka) |
14 | MEITETSU | OPR | CHUKYO (Aichi, Gifu, Mie) |
15 | JR-WEST | JR | CHUBU (Nigata, Nagano), HOKURIKU, KANSAI, CHUGOKU, KYUSHU (Fukuoka) |
16 | NANKAI | OPR | KANSAI (Osaka, Wakayama) |
17 | KINTETSU | OPR | CHUKYO (Aichi Mie), KANSAI (Osaka, Kyoto, Nara) |
18 | KEIHAN | OPR | KANSAI (Osaka, Kyoto) |
19 | KEIFUKU | OPR | HOKURIKU (Fukui), KANSAI (Kyoto) |
20 | HANKYU | OPR | KANSAI (Osaka, Kyoto, Hyogo) |
21 | HANSHIN | OPR | KANSAI (Osaka, Hyogo) |
22 | KOBE | OPR | KANSAI (Hyogo) |
23 | SANYO | OPR | KANSAI (Hyogo) |
24 | HIRODEN | OPR | CHUGOKU (Hiroshima) |
25 | JR-KYUSHU | JR | KYUSHU |
26 | NISHITETSU | OPR | KYUSHU (Fukuoka) |
Variable Name | Minimum Value | Maximum Value | Average Value | Standard Deviation |
---|---|---|---|---|
Railway operating expenditure (million yen) | 1147 | 1,715,178 | 170,278 | 348,194 |
Passenger-kilometer (million passenger kilometers) | 18 | 137,598 | 13,406 | 26,987 |
Labor price | 1194 | 9905 | 5577 | 1533 |
Capital price | 0.01 | 36.86 | 0.15 | 1.80 |
Fuel price | 16.70 | 65.63 | 33.99 | 9.29 |
Number of personnel | 97 | 54,697 | 5680 | 10,535 |
Power cost (million yen) | 46 | 71,577 | 8167 | 14,380 |
Depreciation cost (million yen) | 105 | 298,807 | 34,033 | 66,131 |
Salary cost (million yen) | 262 | 297,516 | 32,717 | 58,231 |
Car kilometer (million passenger kilometers) | 0.89 | 2343 | 275 | 509 |
Percentage of local lines operating kilometers | 0.00 | 0.54 | 0.07 | 0.14 |
Number of substations | 1 | 339 | 43.92 | 74.07 |
Population density | 181 | 6403 | 1824 | 1662 |
Railway usage rate | 0.06 | 0.66 | 0.48 | 0.14 |
Dummy of regional core city | 0.00 | 1.00 | - | - |
Dummy of local areas | 0.00 | 1.00 | - | - |
Variable | Coefficient | Standard Error | t-Value | |
---|---|---|---|---|
β0 | Constant term | 0.0155 | 0.1153 | 0.1344 |
β1 | Passenger-kilometers | 0.2477 *** | 0.0378 | 6.5461 |
β2 | Labor price/Capital price | 0.7876 *** | 0.0362 | 21.7366 |
β3 | Fuel price/Capital price | 0.8416 *** | 0.0532 | 15.8068 |
δ0 | Constant term | 0.2795 *** | 0.093 | 3.0052 |
δ1 | Percentage of local lines operating kilometers | −0.0001 | 0.0003 | −0.4658 |
δ2 | Number of substations | −0.0001 *** | 0.0000 | −15.145 |
δ3 | Population density | −0.6801 *** | 0.2457 | −2.7674 |
δ4 | Railway (JR/OPR) usage rate | 0.2107 *** | 0.0538 | 3.914 |
δ5 | Dummy of regional core city | −0.3352 *** | 0.0731 | −4.5863 |
δ6 | Dummy of local areas | 0.4352 *** | 0.0743 | 5.851 |
lnsigma2 | 0.0317 *** | 0.0547 | 5.7998 | |
Γ | 0.8396 *** | 0.0350 | 23.9845 | |
loglikelihood | 411.9217 | - | - | |
Number of observations | 416 | - | - | |
LR test of the one-sided error | 213.8084 | - | - |
No. | Company | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | Average |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Event | Financial crisis | Financial crisis | Great East Japan Earthquake | Before COVID-19 | During COVID-19 | |||||||||||||
1 | JR-EAST | 1.0796 | 1.0968 | 1.0780 | 1.0524 | 1.0556 | 1.0495 | 1.0491 | 1.0413 | 1.0373 | 1.0380 | 1.0536 | 1.0591 | 1.0530 | 1.0447 | 1.0504 | 1.1949 | 1.0646 |
2 | KEIO | 1.0155 | 1.0164 | 1.0173 | 1.0178 | 1.0251 | 1.0216 | 1.0197 | 1.0168 | 1.0145 | 1.0138 | 1.0147 | 1.0180 | 1.0173 | 1.0155 | 1.0159 | 1.0434 | 1.0190 |
3 | KEISEI | 1.0405 | 1.0408 | 1.0407 | 1.0317 | 1.0451 | 1.0527 | 1.0522 | 1.0422 | 1.0331 | 1.0320 | 1.0383 | 1.0477 | 1.0441 | 1.0361 | 1.0426 | 1.2047 | 1.0515 |
4 | SHIN-KEISEI | 1.0269 | 1.0275 | 1.0288 | 1.0271 | 1.0365 | 1.0357 | 1.0308 | 1.0233 | 1.0192 | 1.0181 | 1.0204 | 1.0265 | 1.0254 | 1.0236 | 1.0251 | 1.0834 | 1.0299 |
5 | TOBU | 1.0354 | 1.0356 | 1.0360 | 1.0320 | 1.0255 | 1.0430 | 1.0360 | 1.0299 | 1.0214 | 1.0202 | 1.0223 | 1.0276 | 1.0263 | 1.0234 | 1.0324 | 1.0880 | 1.0334 |
6 | SEIBU | 1.0315 | 1.0251 | 1.0280 | 1.0241 | 1.0318 | 1.0288 | 1.0263 | 1.0182 | 1.0161 | 1.0163 | 1.0177 | 1.0220 | 1.0206 | 1.0185 | 1.0211 | 1.0732 | 1.0262 |
7 | TOKYU | 1.0255 | 1.0324 | 1.0269 | 1.0266 | 1.0403 | 1.0327 | 1.0354 | 1.0259 | 1.0220 | 1.0192 | 1.0201 | 1.0283 | 1.0247 | 1.0223 | 1.0141 | 1.0386 | 1.0272 |
8 | KEIKYU | 1.0213 | 1.0213 | 1.0244 | 1.0213 | 1.0327 | 1.0306 | 1.0303 | 1.0248 | 1.0196 | 1.0190 | 1.0204 | 1.0283 | 1.0264 | 1.0210 | 1.0242 | 1.0964 | 1.0289 |
9 | ODAKYU | 1.0288 | 1.0274 | 1.0277 | 1.0248 | 1.0374 | 1.0326 | 1.0277 | 1.0208 | 1.0179 | 1.0165 | 1.0182 | 1.0248 | 1.0223 | 1.0203 | 1.0212 | 1.0762 | 1.0278 |
10 | SOTETSU | 1.0304 | 1.0300 | 1.0339 | 1.0286 | 1.0135 | 1.0279 | 1.0273 | 1.0209 | 1.0183 | 1.0182 | 1.0209 | 1.0262 | 1.0239 | 1.0214 | 1.0200 | 1.1153 | 1.0298 |
11 | CHICHIBU | 1.0540 | 1.0492 | 1.0458 | 1.0352 | 1.0462 | 1.0397 | 1.0395 | 1.0326 | 1.0287 | 1.0258 | 1.0301 | 1.0414 | 1.0372 | 1.0345 | 1.0365 | 1.1493 | 1.0454 |
12 | FUJIKYU | 1.1173 | 1.1389 | 1.1115 | 1.0781 | 1.1257 | 1.1085 | 1.0944 | 1.0620 | 1.0479 | 1.0589 | 1.0790 | 1.1203 | 1.1153 | 1.1266 | 1.2375 | 1.6133 | 1.1397 |
13 | JR-CENTRAL | 1.0796 | 1.0854 | 1.0832 | 1.0791 | 1.1284 | 1.1137 | 1.0897 | 1.0759 | 1.0473 | 1.0421 | 1.0449 | 1.0558 | 1.0460 | 1.0371 | 1.0491 | 1.3425 | 1.0875 |
14 | MEITETSU | 1.1182 | 1.1235 | 1.1372 | 1.1163 | 1.1543 | 1.1383 | 1.1148 | 1.0978 | 1.0848 | 1.0623 | 1.0709 | 1.0954 | 1.0775 | 1.0638 | 1.0564 | 1.2413 | 1.1096 |
15 | JR-WEST | 1.0760 | 1.0845 | 1.0884 | 1.0749 | 1.1079 | 1.0982 | 1.0888 | 1.0781 | 1.0550 | 1.0499 | 1.0570 | 1.0691 | 1.0583 | 1.0579 | 1.0447 | 1.1337 | 1.0764 |
16 | NANKAI | 1.0465 | 1.0709 | 1.0743 | 1.0747 | 1.1196 | 1.0982 | 1.0979 | 1.0884 | 1.0527 | 1.0492 | 1.0479 | 1.0607 | 1.0609 | 1.0869 | 1.0989 | 1.2808 | 1.0880 |
17 | KINTETSU | 1.0723 | 1.0598 | 1.1335 | 1.1257 | 1.1500 | 1.1456 | 1.1340 | 1.1117 | 1.0772 | 1.0688 | 1.0718 | 1.0910 | 1.0798 | 1.0812 | 1.0873 | 1.2979 | 1.1117 |
18 | KEIHAN | 1.0381 | 1.0414 | 1.0442 | 1.0435 | 1.0518 | 1.0534 | 1.0500 | 1.0467 | 1.0314 | 1.0282 | 1.0285 | 1.0313 | 1.0291 | 1.0360 | 1.0278 | 1.0745 | 1.0410 |
19 | KEIFUKU | 1.0369 | 1.0358 | 1.0476 | 1.0348 | 1.0414 | 1.0384 | 1.0390 | 1.0389 | 1.0346 | 1.0353 | 1.0337 | 1.0483 | 1.0521 | 1.0535 | 1.0566 | 1.2368 | 1.0540 |
20 | HANKYU | 1.0304 | 1.0356 | 1.0357 | 1.0307 | 1.0416 | 1.0406 | 1.0364 | 1.0321 | 1.0225 | 1.0212 | 1.0214 | 1.0238 | 1.0239 | 1.0290 | 1.0325 | 1.1303 | 1.0367 |
21 | HANSHIN | 1.0458 | 1.0828 | 1.0763 | 1.0739 | 1.1172 | 1.1207 | 1.1006 | 1.0880 | 1.0612 | 1.0440 | 1.0455 | 1.0478 | 1.0444 | 1.0566 | 1.0345 | 1.1345 | 1.0734 |
22 | KOBE | 1.0609 | 1.0741 | 1.0746 | 1.0646 | 1.0831 | 1.0725 | 1.0587 | 1.0622 | 1.0410 | 1.0382 | 1.0420 | 1.0531 | 1.0523 | 1.0572 | 1.0519 | 1.1765 | 1.0664 |
23 | SANYO | 1.1793 | 1.1678 | 1.1723 | 1.1409 | 1.1720 | 1.1172 | 1.1068 | 1.1240 | 1.0564 | 1.0538 | 1.0632 | 1.0864 | 1.0699 | 1.0734 | 1.0931 | 1.1961 | 1.1170 |
24 | HIRODEN | 1.5361 | 1.5372 | 1.5750 | 1.5197 | 1.5978 | 1.5986 | 1.5677 | 1.5770 | 1.5630 | 1.5448 | 1.5907 | 1.6176 | 1.5878 | 1.6036 | 1.5201 | 2.1363 | 1.6046 |
25 | JR-KYUSHU | 1.0822 | 1.0500 | 1.0783 | 1.0647 | 1.0902 | 1.0875 | 1.0631 | 1.0809 | 1.0515 | 1.0482 | 1.1075 | 1.0366 | 1.0338 | 1.0303 | 1.0308 | 1.1050 | 1.0650 |
26 | NISHITETSU | 1.0493 | 1.0551 | 1.0956 | 1.0958 | 1.1058 | 1.1165 | 1.1045 | 1.0905 | 1.0606 | 1.0608 | 1.0649 | 1.0821 | 1.0728 | 1.0597 | 1.0495 | 1.1813 | 1.0841 |
Average | 1.0753 | 1.0787 | 1.0852 | 1.0746 | 1.0953 | 1.0901 | 1.0816 | 1.0750 | 1.0590 | 1.0555 | 1.0633 | 1.0719 | 1.0664 | 1.0667 | 1.0682 | 1.2094 | 1.0823 |
No. | Company | Region | “FY 2005–FY 2019” | FY 2020 | Average Value for “FY 2005–FY2020” | Order | |||
---|---|---|---|---|---|---|---|---|---|
Lowest (Best) Cost Inefficiency | Fiscal Year | Highest (Worst) Cost Inefficiency | Fiscal Year | Highest Cost Inefficiency During Whole Period | |||||
1 | JR-EAST | TOHOKU KANTO CHUBU | 1.0373 | (2013) | 1.0968 | (2006) | 1.1949 | 1.0646 | 14 |
2 | KEIO | KANTO | 1.0138 | (2014) | 1.0251 | (2009) | 1.0434 | 1.0190 | 1 |
3 | KEISEI | KANTO | 1.0317 | (2008) | 1.0527 | (2010) | 1.2047 | 1.0515 | 12 |
4 | SHIN-KEISEI | KANTO | 1.0181 | (2014) | 1.0365 | (2009) | 1.0834 | 1.0299 | 7 |
5 | TOBU | KANTO | 1.0202 | (2014) | 1.0360 | (2007) | 1.0880 | 1.0334 | 8 |
6 | SEIBU | KANTO | 1.0161 | (2013) | 1.0318 | (2009) | 1.0732 | 1.0262 | 2 |
7 | TOKYU | KANTO | 1.0192 | (2014) | 1.0403 | (2009) | 1.0386 | 1.0272 | 3 |
8 | KEIKYU | KANTO | 1.0190 | (2014) | 1.0327 | (2009) | 1.0964 | 1.0289 | 5 |
9 | ODAKYU | KANTO | 1.0165 | (2014) | 1.0374 | (2009) | 1.0762 | 1.0278 | 4 |
10 | SOTETSU | KANTO | 1.0135 | (2009) | 1.0339 | (2007) | 1.1153 | 1.0298 | 6 |
11 | CHICHIBU | KANTO | 1.0258 | (2014) | 1.0540 | (2005) | 1.1493 | 1.0454 | 11 |
12 | FUJIKYU | CHUBU | 1.0479 | (2013) | 1.2375 | (2019) | 1.5977 | 1.1397 | 25 |
13 | JR-CENTRAL | KANTO CHUBU GHUKYO KANSAI | 1.0371 | (2018) | 1.1284 | (2009) | 1.3425 | 1.0875 | 20 |
14 | MEITETSU | CHUKYO | 1.0564 | (2019) | 1.1543 | (2009) | 1.2413 | 1.1096 | 22 |
15 | JR-WEST | HOKURIKU KANSAI CHUGOKU KYUSHU | 1.0447 | (2019) | 1.1079 | (2009) | 1.1337 | 1.0764 | 18 |
16 | NANKAI | KANSAI | 1.0479 | (2015) | 1.1196 | (2009) | 1.2808 | 1.0880 | 21 |
17 | KINTETSU | KANSAI | 1.0598 | (2006) | 1.1500 | (2009) | 1.2979 | 1.1117 | 23 |
18 | KEIHAN | KANSAI | 1.0278 | (2019) | 1.0534 | (2010) | 1.0745 | 1.0410 | 10 |
19 | KEIFUKU | KANSAI HOKURIKU | 1.0337 | (2015) | 1.0476 | (2007) | 1.2368 | 1.0540 | 13 |
20 | HANKYU | KANSAI | 1.0212 | (2014) | 1.0416 | (2009) | 1.1303 | 1.0367 | 9 |
21 | HANSHIN | KANSAI | 1.0345 | (2019) | 1.1207 | (2010) | 1.1345 | 1.0734 | 17 |
22 | KOBE | KANSAI | 1.0382 | (2014) | 1.0831 | (2009) | 1.1765 | 1.0664 | 16 |
23 | SANYO | KANSAI | 1.0538 | (2014) | 1.1723 | (2007) | 1.1961 | 1.1170 | 24 |
24 | HIRODEN | CHUGOKU | 1.5201 | (2019) | 1.5978 | (2009) | 2.1363 | 1.6046 | 26 |
25 | JR-KYUSHU | KYUSHU | 1.0303 | (2018) | 1.0902 | (2009) | 1.1050 | 1.0650 | 15 |
26 | NISHITETSU | KYUSHU | 1.0495 | (2019) | 1.1165 | (2010) | 1.1813 | 1.0841 | 19 |
Average | 1.0513 | 1.1038 | 1.2088 | 1.0823 |
2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
The lowest (best) inefficiency value | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 3 | 11 | 3 | 0 | 0 | 2 | 5 | 0 |
The second highest (worst) inefficiency value | 1 | 1 | 5 | 0 | 14 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
The highest (worst) inefficiency value | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 26 |
Average of Best Practice Railway Companies | Average of the Other Railway Companies | |||||
---|---|---|---|---|---|---|
Before COVID-19 Pandemic in 2019 | During COVID-19 Pandemic in 2020 (Year on Year Rate) | Growth Rate | Before COVID-19 Pandemic in 2019 | During COVID-19 Pandemic in 2020 (Year on Year Rate) | Growth Rate | |
Operating kilometers (km) | 133.6 | 133.6 | 100.0% | 1140 | 1134 | 99.4% |
Number of stations | 83 | 84 | 100.1% | 306 | 304 | 99.4% |
Number of rolling stocks | 1028 | 1022 | 99.5% | 1984 | 1984 | 100.0% |
Number of transported passengers (thousand passengers) | 597,630 | 421,460 | 70.5% | 710,490 | 505,988 | 71.2% |
Passenger-kilometers (million passenger-kilometers) | 7541 | 5092 | 67.5% | 18,624 | 10,660 | 57.2% |
Car kilometer (thousand kilometers) | 136,728 | 137,251 | 100.4% | 371,850 | 362,859 | 97.6% |
Number of employees in the railway sector | 2520 | 2535 | 100.6% | 7204 | 7140 | 99.1% |
No. | Company | The Difference in Cost Inefficiency between FY 2020 and FY 2019 | No | Company | The Difference in Cost Inefficiency between FY 2020 and FY 2019 | No | Company | The Difference in Cost Inefficiency between FY 2020 and FY 2019 |
---|---|---|---|---|---|---|---|---|
1 | JR EAST | 0.1445 | 11 | CHICHIBU | 0.1128 | 21 | HANSHIN | 0.1000 |
2 | KEIO | 0.0275 | 12 | FUJIKYU | 0.3758 | 22 | KOBE | 0.1246 |
3 | KEISEI | 0.1621 | 13 | JR CENTRAL | 0.2934 | 23 | SANYO | 0.1030 |
4 | SHIN-KEISEI | 0.0583 | 14 | MEITETSU | 0.1849 | 24 | HIRODEN | 0.6162 |
5 | TOBU | 0.0556 | 15 | JR WEST | 0.0890 | 25 | JR KYUSHU | 0.0742 |
6 | SEIBU | 0.0521 | 16 | NANKAI | 0.1819 | 26 | NISHITETSU | 0.1318 |
7 | TOKYU | 0.0245 | 17 | KINTETSU | 0.2106 | Average | 0.1398 | |
8 | KEIKYU | 0.0722 | 18 | KEIHAN | 0.0467 | Minimum | 0.0181 | |
9 | ODAKYU | 0.0550 | 19 | KEIFUKU | 0.1802 | Maximum | 0.6088 | |
10 | SOTETSU | 0.0953 | 20 | HANKYU | 0.0978 | Standard deviation | 0.1240 |
Order | No. | Company | Region | Cost Inefficiency of Average Value for “FY 2005–FY2020” | Operating Kilometers (km) | Number of Stations | Number of Rolling Stocks | Passenger-Kilometers (Million Passenger-Kilometers) (a) | Number of Employees in the Railway Sector (b) | (a)/(b) |
---|---|---|---|---|---|---|---|---|---|---|
19 | 26 | NISHITETSU | KYUSHU | 1.0841 | 106.1 | 72 | 311 | 1574 | 600 | 2.62 |
20 | 13 | JR-CENTRAL | KANTO, CHUBU, GHUKYO, KANSAI | 1.0875 | 1970.8 | 405 | 4827 | 63,427 | 18282 | 3.46 |
21 | 16 | NANKAI | KANSAI | 1.0880 | 154.8 | 100 | 696 | 3922 | 2195 | 1.78 |
- | - | SEMBOKU | KANSAI | 1.09※ | 14.3 | 6 | 112 | 441 | 258 | 1.70 |
22 | 14 | MEITETSU | CHUKYO | 1.1096 | 444.2 | 275 | 1070 | 7260 | 4085 | 1.77 |
23 | 17 | KINTETSU | KANSAI | 1.1117 | 501.1 | 286 | 1933 | 10,590 | 7226 | 1.46 |
24 | 23 | SANYO | KANSAI | 1.1170 | 63.2 | 49 | 236 | 891 | 715 | 1.24 |
25 | 12 | FUJIKYU | CHUBU | 1.1397 | 26.6 | 18 | 33 | 48 | 254 | 0.18 |
- | - | TOYO-KOSOKU | KANTO | 1.15※ | 16.2 | 9 | 110 | 552 | 304 | 1.81 |
26 | 24 | HIRODEN | CHUGOKU | 1.6046 | 35.1 | 82 | 300 | 197 | 1728 | 0.11 |
- | - | OSAKA-KOSOKU | KANSAI | 1.78※ | 28.0 | 18 | 88 | 311 | 241 | 1.29 |
Categorization of Efficiency Improvement Measures | Items of Efficiency Improvement Measures |
---|---|
Operation |
|
Streamline facilities |
|
Ticketing |
|
Energy-saving |
|
Peak shift(reduce the number of trains operating during peak periods) |
|
DX Investment Category | Operation | Streamline Facilities | |||||||
---|---|---|---|---|---|---|---|---|---|
Order | Group | No. | Company Name | Autonomous Driving•Driver Only Operation | Smart Maintenance | Customer Service Automation | Operational Efficiency by DX | Asset Management | Wireless Railway Car Control Systems |
1 | 1 | 02 | KEIO | ○ | ○ | ○ | |||
2 | 06 | SEIBU | ○ | ○ | ○ | ○ | |||
3 | 09 | ODAKYU | ○ | ○ | ○ | ||||
4 | 08 | KEIKYU | ○ | ○ | ○ | ||||
5 | 05 | TOBU | ○ | ○ | ○ | ||||
6 | 07 | TOKYU | ○ | ○ | ○ | ○ | |||
7 | 10 | SOTETSU | ○ | ○ | ○ | ○ | |||
8 | 2 | 04 | SHIN-KEISEI | ||||||
9 | 20 | HANKYU | ○ | ||||||
10 | 11 | CHICHIBU | |||||||
11 | 18 | KEIHAN | ○ | ○ | ○ | ○ | |||
12 | 01 | JR-EAST | ○ | ○ | ○ | ○ | ○ | ||
13 | 19 | KEIFUKU | |||||||
14 | 03 | KEISEI | |||||||
15 | 25 | JR-KYUSHU | ○ | ○ | ○ | ○ | ○ | ||
16 | 15 | JR-WEST | ○ | ○ | ○ | ○ | ○ | ||
17 | 3 | 21 | HANSHIN | ○ | |||||
18 | 13 | JR-CENTRAL | |||||||
19 | 22 | KOBE | |||||||
20 | 16 | NANKAI | ○ | ○ | |||||
21 | 26 | NISHITESU | ○ | ○ | |||||
22 | 4 | 17 | KINTETSU | ○ | ○ | ○ | |||
23 | 14 | MEITETSU | ○ | ○ | ○ | ○ | |||
24 | 23 | SANYO | ○ | ||||||
25 | 12 | FUJIKYU | |||||||
26 | 24 | HIRODEN | ○ |
DX Investment Category | Ticketing | Streamline Facilities | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Order | Group | No. | Company Name | Prepaid Transportation IC Cards | Cashless | Ticketless•QR Code | Smartphone Payment | Credit Card Touch Payments | Common System Infrastructure Development | Apps ※1 | MaaS ※2 | Point Service ※3 |
1 | 1 | 02 | KEIO | ○ | ||||||||
2 | 06 | SEIBU | ○ | ○ | ○ | ○ | ||||||
3 | 09 | ODAKYU | ○ | ○ | ○ | ○ | ○ | |||||
4 | 08 | KEIKYU | ○ | ○ | ○ | |||||||
5 | 05 | TOBU | ○ | ○ | ○ | ○ | ||||||
6 | 07 | TOKYU | ○ | ○ | ○ | |||||||
7 | 10 | SOTETSU | ○ | ○ | ○ | ○ | ○ | |||||
8 | 2 | 04 | SHIN-KEISEI | ○ | ||||||||
9 | 20 | HANKYU | ○ | ○ | ○ | ○ | ○ | |||||
10 | 11 | CHICHIBU | ○ | ○ | ||||||||
11 | 18 | KEIHAN | ○ | ○ | ○ | ○ | ||||||
12 | 01 | JR-EAST | ○ | ○ | ○ | ○ | ○ | ○ | ||||
13 | 19 | KEIFUKU | ○ | ○ | ||||||||
14 | 03 | KEISEI | ○ | |||||||||
15 | 25 | JR-KYUSHU | ○ | ○ | ○ | ○ | ||||||
16 | 15 | JR-WEST | ○ | ○ | ○ | ○ | ○ | ○ | ○ | |||
17 | 3 | 21 | HANSHIN | ○ | ○ | ○ | ○ | ○ | ||||
18 | 13 | JR-CENTRAL | ○ | ○ | ○ | ○ | ||||||
19 | 22 | KOBE | ||||||||||
20 | 16 | NANKAI | ○ | ○ | ○ | |||||||
21 | 26 | NISHITETSU | ○ | ○ | ○ | ○ | ○ | |||||
22 | 4 | 17 | KINTETSU | ○ | ○ | ○ | ○ | |||||
23 | 14 | MEITETSU | ○ | ○ | ||||||||
24 | 23 | SANYO | ○ | |||||||||
25 | 12 | FUJIKYU | ○ | |||||||||
26 | 24 | HIRODEN | ○ | ○ |
DX Investment Category | Service | New Business | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Order | Group | No. | Company Name | Marketing Analysis | Travel Web Reservation | Banking Services | Real-Digital Hybrid | EC Mall | Digital Service ※4 | Community Symbiosis Business | Digital Business | Open Innovation |
1 | 1 | 02 | KEIO | ○ | ○ | ○ | ||||||
2 | 06 | SEIBU | ○ | ○ | ||||||||
3 | 09 | ODAKYU | ○ | ○ | ○ | |||||||
4 | 08 | KEIKYU | ○ | |||||||||
5 | 05 | TOBU | ○ | ○ | ○ | |||||||
6 | 07 | TOKYU | ○ | ○ | ○ | |||||||
7 | 10 | SOTETSU | ○ | |||||||||
8 | 2 | 04 | SHIN-KEISEI | |||||||||
9 | 20 | HANKYU | ○ | ○ | ○ | |||||||
10 | 11 | CHICHIBU | ||||||||||
11 | 18 | KEIHAN | ○ | ○ | ○ | ○ | ||||||
12 | 01 | JR-EAST | ○ | ○ | ○ | ○ | ○ | ○ | ○ | |||
13 | 19 | KEIFUKU | ○ | |||||||||
14 | 03 | KEISEI | ||||||||||
15 | 25 | JR-KYUSHU | ○ | |||||||||
16 | 15 | JR-WEST | ○ | ○ | ○ | |||||||
17 | 3 | 21 | HANSHIN | ○ | ○ | |||||||
18 | 13 | JR-CENTRAL | ○ | |||||||||
19 | 22 | KOBE | ○ | |||||||||
20 | 16 | NANKAI | ○ | ○ | ○ | ○ | ||||||
21 | 26 | NISHITETSU | ○ | ○ | ○ | ○ | ||||||
22 | 4 | 17 | KINTETSU | ○ | ○ | ○ | ○ | ○ | ||||
23 | 14 | MEITETSU | ○ | ○ | ○ | |||||||
24 | 23 | SANYO | ||||||||||
25 | 12 | FUJIKYU | ||||||||||
26 | 24 | HIRODEN |
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Endo, H.; Goto, M. Cost Inefficiency of Japanese Railway Companies and Impacts of COVID-19 Pandemic and Digital Transformation. Economies 2024, 12, 196. https://doi.org/10.3390/economies12080196
Endo H, Goto M. Cost Inefficiency of Japanese Railway Companies and Impacts of COVID-19 Pandemic and Digital Transformation. Economies. 2024; 12(8):196. https://doi.org/10.3390/economies12080196
Chicago/Turabian StyleEndo, Hideaki, and Mika Goto. 2024. "Cost Inefficiency of Japanese Railway Companies and Impacts of COVID-19 Pandemic and Digital Transformation" Economies 12, no. 8: 196. https://doi.org/10.3390/economies12080196
APA StyleEndo, H., & Goto, M. (2024). Cost Inefficiency of Japanese Railway Companies and Impacts of COVID-19 Pandemic and Digital Transformation. Economies, 12(8), 196. https://doi.org/10.3390/economies12080196