The New Economics of Industrial Policy

We discuss the considerable literature that has developed in recent years providing rigorous evidence on how industrial policies work. This literature is a significant improvement over the earlier generation of empirical work, which was largely correlational and marred by interpretational problems. On the whole, the recent crop of papers offers a more positive take on industrial policy. We review the standard rationales and critiques of industrial policy and provide a broad overview of new empirical approaches to measurement. We discuss how the recent literature, paying close attention to measurement, causal inference, and economic structure, is offering a nuanced and contextual understanding of the effects of industrial policy. We re-evaluate the East Asian experience with industrial policy in light of recent results. Finally, we conclude by reviewing how industrial policy is being reshaped by a new understanding of governance, a richer set of policy instruments beyond subsidies, and the reality of deindustrialization.

The authors attest that they have nothing to disclose. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. This is a draft of a paper prepared for the Annual Review of Economics. We thank Jessica De Simone for her expert editorial assistance. When citing this paper, please use the following: Juhász R, Lane R, Rodrik D. 2023. The New Economics of Industrial Policy. Annu. Rev. Econ. 16: Submitted. DOI: https://doi.org/10.1146/annurev-economics-081023-024638

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Réka Juhász & Nathan Lane & Dani Rodrik, 2024. " The New Economics of Industrial Policy, " Annual Review of Economics, .

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Please note you do not have access to teaching notes, a literature review exploring the role of technology in business survival during the covid-19 lockdowns.

International Journal of Organizational Analysis

ISSN : 1934-8835

Article publication date: 18 May 2021

Issue publication date: 23 November 2022

The Covid-19 pandemic has affected every aspect of human life. Even though the pandemic length was not too long, a huge volume of research relating to Covid-19 has been published in different contexts. This paper aims to review the literature investigating the impact of Covid −19 on businesses generally and explore studies examining the technology role of business survival during the Covid-19 lockdowns specifically.

Design/methodology/approach

This study implemented the concept of a systematic review approach to review the literature that has been conducted in the business field during the Covid-19 crisis in general. Additionally, it looks into the research examining the role of technology in business survival in the Covid-19 crisis specifically. All studies were conducted in 2020. A total of 53 studies were identified and categorised into different themes. The research methods, theories and locations have also been analysed.

It was found that Covid-19 pandemic has affected all business sectors in several ways. Technology adoption has a critical role for business survival during the Covid-19 crises especially with small businesses. Very limited research has been conducted on the adoption of different technologies during the Covid-19 lockdowns.

Originality/value

This study presents the most frequent themes and topics that have been explored in the literature during the Covid-19 crisis in the business field. It highlights the methods used in addition to the theories and research locations present in this literature. Finally, it proposes the possible implications of this literature review.

  • Literature review

Abed, S.S. (2022), "A literature review exploring the role of technology in business survival during the Covid-19 lockdowns", International Journal of Organizational Analysis , Vol. 30 No. 5, pp. 1045-1062. https://doi.org/10.1108/IJOA-11-2020-2501

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  • DOI: 10.55324/ijoms.v3i8.884
  • Corpus ID: 270189696

Entrepreneurial orientation and funding decisions on the financial performance of small and medium industries

  • Putu Indah Hapsari , I. Gusti , +4 authors Sutrisna Dewi
  • Published in Indonesian Journal of… 30 May 2024
  • Business, Economics

19 References

The effect of entrepreneurial orientation variables on business performance in the sme industry context, orientation of entrepreneurship and innovation in improving the company's performance through business strategy, effect of entrepreneurial orientation on smes’ innovation performance in sri lanka, the effect of entrepreneurial orientation on new venture performance: contingency roles of entrepreneurial actions, entrepreneurial orientation far beyond opportunity: the influence of the necessity for innovativeness, proactiveness and risk-taking, strategic orientation on performance: the resource based view theory approach, why does entrepreneurial orientation affect company performance, a conceptual model of entrepreneurship as firm behavior, the effect of capital structure and sales growth on company profitability and value in the cosmetics manufacturing and household needs manufacturing companies, assessing the psychometric properties of the entrepreneurial orientation scale: a multi-country analysis, related papers.

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ASEAN FTA review: Govt seeks more industry inputs to raise demand pitch

India’s trade deficit with the bloc in 2023-24 widened to $38.46 billion from $7.5 billion, during the implementation of the agreement in 2010.

By Amiti Sen

Prime Minister Narendra Modi with ASEAN leaders in a group photo during the 20th ASEAN-India Summit, in Jakarta on Thursday. (File Photo)

To sharpen its negotiating stance with the ten-member ASEAN , the Commerce Department has sought more inputs from various industry and export promotion bodies on items where deeper tariff concessions can be demanded ahead of the next round of negotiations on the ASEAN-India FTA review in Indonesia next month, sources said.

  • Also read: India seeks greater market access, flexibilities in rules of origin in FTA review with ASEAN

“Commerce Ministry officials are meeting industry and export body representatives to get their views on the items to focus on for greater market access. Other inputs, include those related to non-tariff barriers, are also being solicited,” the source told businessline .

The India-ASEAN FTA, formally known as the ASEAN-India Trade in Goods Agreement (AITGA), has resulted in disproportionate gains for the ASEAN countries which India wants to correct through the review.

In 2023-24, India’s trade deficit with the bloc widened to $38.46 billion from $7.5 billion during the implementation of the agreement in 2010. India exported goods worth $41.2 billion to the region while its imports were valued at $79.66 billion.  

New Delhi is seeking greater market access for its goods, more flexibility in determining rules of origin (ROO) for products through product specific rules, and redressal of non-tariff barriers, to address its growing trade deficit with the bloc, sources have said.

“Since the ASEAN countries, too, are seeking more market access for their goods as part of the review despite India’s attempt to level the uneven field, our negotiators have to pro-actively demand lower duties wherever there is a scope. That is why Commerce Ministry officials are holding meetings with the industry so that there is a better understanding of what it wants,” the source said.

The ten-member ASEAN includes Indonesia, Malaysia, the Philippines, Singapore, Thailand, Brunei, Vietnam, Laos, Myanmar and Cambodia.

Review of AITGA

India had been asking for a review of the AITGA for a long time as its trade deficit with the bloc widened significantly since the trade pact was implemented in January 2010. 

Four meetings of the `joint committee’ for the review of AITIGA have already taken place while the fifth is scheduled in Jakarta on July 29-31, 2024.

In the earlier meetings, India sought product specific rules (PSRs) in ROO determination so that the requirements could be relaxed for high value items where the value addition is low.  ROO are the criteria to determine the origin of a product and establish if it qualifies for duty cuts under a FTA. PSRs can be introduced in the ROO chapter for relaxing rules for certain items where meeting the prescribed ROO is difficult.

In the India-ASEAN FTA, the ROO calls for value addition of 35 per cent whereas for certain industries, like gems and jewellery, the value addition that takes place is less than 10 per cent because the raw material is of high value. 

  • Also read: India, Asean discuss review of trade agreement

Under the AITGA, both sides agreed to progressively eliminate duties on about 75 per cent of goods and reduce tariffs on around 15 per cent of goods. However, the commitments made by the ten ASEAN countries varied considerably. While an open economy like Singapore committed to almost 100 per cent elimination, countries like Indonesia and Vietnam offered much less.

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Usefulness of online reviews of sensory experiences: pre- vs. post-pandemic.

business and economic literature review on the industries

1. Introduction

2. literature review, 2.1. sensory experiences in the service sector, 2.2. online reviews in the hospitality industry, 2.3. the impact of covid-19 on customer experience in the hospitality industry, 2.4. hypothesis development, 3. methodology, 3.1. data description, 3.2. study design, 3.3. different service dimensions, 3.4. sensory experience, 3.5. the quasi-experimental study design, 4. empirical analyses, 4.1. model-free comparison, 4.2. empirical models, 4.2.1. the interaction impact of covid-19 and sensory experiences on review ratings for positive group, 4.2.2. the interaction impact of covid-19 and sensory experiences on review ratings for negative group, 4.2.3. the interaction impact of covid-19 and sensory experiences on review helpfulness for positive group, 4.2.4. the interaction impact of covid-19 and multisensory experiences on review helpfulness for negative group, 5. discussion and implications, 5.1. theoretical contribution, 5.2. practical contribution, 5.3. limitations and future studies, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Review RatingsFrequencyCumulative Percent
1 ≤ R.R. < 410,6667.42%
4 ≤ R.R. < 618,30220.15%
6 ≤ R.R. < 837,61346.32%
8 ≤ R.R. < 1048,77280.25%
R.R. = 1028,386100.00%
Perceived Review HelpfulnessFrequencyCumulative Percent
P.R.H. = 0126,83488.24%
P.R.H. = 112,09096.65%
2 ≤ P.R.H. < 10478399.98%
10 ≤ P.R.H. ≤ 4932100.00%
Traveler TypesFrequencyPercent
Business Traveler14,84310.33%
Couple50,86635.39%
Family with children39,00027.13%
Groups of friends12,0648.39%
Solo traveler26,96618.76%
ComparisonReview Ratingt-Statsp-Value
Pre-COVID-19 period7.8461.500.00
COVID-19 period6.98
ComparisonPerceived Review Helpfulnesst-statsp-value
Pre-COVID-19 period0.2027.180.00
COVID-19 period0.09
Employee KindnessFacilitiesCleanlinessComfortValue for MoneyLocation
StaffRoomCleanComfortPriceLocation
ReceptionBathroomAtmosphereSpacePayWalking
ManagerParkingHairNoiseMoneyMetropolitan
ProfessionalLoungeCarpetQuietChargeDistance
Positive g.Negative g.
Positive treatment g.Positive control g.Negative treatment g.Negative control g.
25,94460,32133,80048,294
Positive g.Negative g.
VariableMeanMinMaxVariableMeanMinMax
R.R.7.86110R.R.7.29110
P.R.H.0.20023P.R.H0.21049
P-sensory2.240100P-sensory2.110100
N-sensory2.410100N-sensory2.580100
ComparisonReview Rating
Treatment g.Control g.t-Statsp-Value
Positive Group8.197.7231.190.00
Negative Group6.997.5032.590.00
ComparisonPerceived Review Helpfulness
Treatment g.Control g.t-statsp-value
Positive Group0.250.1814.790.00
Negative Group0.230.198.510.00
VariableModel (1)
DV: Review Rating
Model (2)
DV: Review Rating
Treatment Group0.442 ***
(0.015)
0.297 ***
(0.018)
Treatment Group * Treatment COVID-19 Period0.095 ***
(0.041)
0.104 ***
(0.046)
COVID-19 Period COVID-1−0.832 ***
(0.024)
−0.858 ***
(0.038)
Positive Facility0.117 ***
(0.015)
0.102 ***
(0.017)
Positive Staff0.602 ***
(0.015)
0.489 ***
(0.017)
Positive Cleanliness 0.133 ***
(0.029)
0.100 ***
(0.032)
Positive Location0.161 ***
(0.01)
0.119 ***
(0.017)
Positive Comfort0.260 ***
(0.019)
0.175 ***
(0.020)
Positive Value for Money0.370 ***
(0.015)
0.289 ***
(0.016)
Negative Facility−0.610 ***
(0.015)
−0.498 ***
(0.018)
Negative Staff−0.857 ***
(0.026)
−0.824 ***
(0.029)
Negative Cleanliness −0.609 ***
(0.023)
−0.510 ***
(0.024)
Negative Location−0.278 ***
(0.018)
−0.282 ***
(0.020)
Negative Comfort−0.395 ***
(0.018)
−0.377 ***
(0.020)
Negative Value for Money−0.249 ***
(0.016)
−0.264 ***
(0.018)
Traveler Type DummyIncludedIncluded
Hotel-level DummyNot IncludedIncluded
InterceptIncludedIncluded
Huber/White/sandwich estimatorIncludedNot Included
Clustered sandwich estimatorNot IncludedIncluded
R 12.21%25.96%
Observations86,26586,265
VariableModel (3)
DV: Review Rating
Model (4)
DV: Review Rating
Treatment Group−0.405 ***
(0.016)
−0.371 ***
(0.017)
Treatment Group * COVID-19 period−0.159 ***
(0.043)
−0.174 ***
(0.044)
COVID-19 period−0.576 ***
(0.040)
−0.559 ***
(0.047)
Positive Facility0.260 ***
(0.018)
0.222 ***
(0.019)
Positive Staff0.631 ***
(0.018)
0.516 ***
(0.021)
Positive Cleanliness 0.363 ***
(0.035)
0.285 ***
(0.035)
Positive Location0.318 ***
(0.015)
0.251 ***
(0.019)
Positive Comfort0.484 ***
(0.022)
0.349 ***
(0.024)
Positive Value for Money0.504 ***
(0.018)
0.412 ***
(0.020)
Negative Facility−0.534 ***
(0.01)
−0.418 ***
(0.019)
Negative Staff−0.884 ***
(0.022)
−0.863 ***
(0.026)
Negative Cleanliness −0.567 ***
(0.021)
−0.469 ***
(0.023)
Negative Location−0.173 ***
(0.017)
−0.202 ***
(0.019)
Negative Comfort−0.290 ***
(0.018)
−0.277 ***
(0.020)
Negative Value for Money−0.189 ***
(0.016)
−0.225 ***
(0.020)
Traveler Type DummyIncludedIncluded
Hotel-level DummyNot IncludedIncluded
InterceptIncludedIncluded
Huber/White/sandwich estimatorIncludedNot Included
Clustered sandwich estimatorNot IncludedIncluded
R212.41%27.07%
Observations 82,09482,094
VariableModel (5)
DV: Review Helpfulness
Model (6)
DV: Review Helpfulness
Treatment Group0.262 ***
(0.025)
0.251 ***
(0.028)
Treatment Group * COVID-19 period−0.075
(0.067)
−0.133 *
(0.075)
COVID-19 period−1.006 ***
(0.062)
−0.900 ***
(0.082)
Review Rating0.298 ***
(0.038)
0.361 ***
(0.071)
Review Rating2−0.022 ***
(0.002)
−0.026 ***
(0.005)
Positive Facility0.134 ***
(0.024)
0.169 ***
(0.026)
Positive Staff0.064 ***
(0.024)
0.076 ***
(0.028)
Positive Cleanliness 0.142 ***
(0.024)
0.111 ***
(0.043)
Positive Location0.356 ***
(0.023)
0.241 ***
(0.028)
Positive Comfort0.164 ***
(0.030)
0.126 ***
(0.033)
Positive Value for Money0.213 ***
(0.024)
0.245 ***
(0.028)
Negative Facility0.126 ***
(0.024)
0.168 ***
(0.025)
Negative Staff0.177 ***
(0.037)
0.129 ***
(0.040)
Negative Cleanliness 0.080 **
(0.036)
0.075 **
(0.036)
Negative Location0.235 ***
(0.027)
0.191 ***
(0.029)
Negative Comfort0.180 ***
(0.028)
0.154 ***
(0.030)
Negative Value for Money0.261 ***
(0.025)
0.249 ***
(0.027)
Review Age−0.213 ***
(0.024)
−0.182 ***
(0.043)
Traveler Type DummyIncludedIncluded
Hotel-level DummyNot IncludedIncluded
InterceptIncludedIncluded
Huber/White/sandwich estimatorIncludedNot Included
Clustered sandwich estimatorNot IncludedIncluded
Pseudo-R22.04%9.32%
Observations 86,26586,265
VariableModel (7)
DV: Review Helpfulness
Model (8)
DV: Review Helpfulness
Treatment Group0.172 ***
(0.027)
0.177 ***
(0.028)
Treatment Group * COVID-19 period0.001
(0.065)
0.005
(0.068)
COVID-19 period−1.067 ***
(0.067)
−0.910 ***
(0.092)
Review Rating0.141 ***
(0.034)
0.215 ***
(0.057)
Review Rating2−0.008 ***
(0.002)
−0.013 ***
(0.004)
Positive Facility0.094 ***
(0.028)
0.135 ***
(0.030)
Positive Staff0.019
(0.027)
0.051 *
(0.031)
Positive Cleanliness 0.175 ***
(0.051)
0.167 ***
(0.050)
Positive Location0.356 ***
(0.023)
0.245 ***
(0.028)
Positive Comfort0.191 ***
(0.033)
0.152 ***
(0.037)
Positive Value for Money0.193 ***
(0.027)
0.221 ***
(0.032)
Negative Facility0.091 ***
(0.024)
0.137 ***
(0.024)
Negative Staff0.220 ***
(0.032)
0.160 ***
(0.037)
Negative Cleanliness 0.092 ***
(0.033)
0.075 ***
(0.034)
Negative Location0.181 ***
(0.026)
0.150 ***
(0.027)
Negative Comfort0.132 ***
(0.027)
0.103 ***
(0.029)
Negative Value for Money0.242 ***
(0.026)
0.224 ***
(0.023)
Traveler Type DummyIncludedIncluded
Hotel-level DummyNot IncludedIncluded
InterceptIncludedIncluded
Huber/White/sandwich estimatorIncludedNot Included
Clustered sandwich estimatorNot IncludedIncluded
R21.87%9.51%
Observations 82,09482,094
HypothesisTest Results
Online Review Generation
Sensory service experiences embedded in the positive aspect of a review have a positive impact on customer satisfaction.Supported
Sensory service experiences embedded in the negative aspect of a review have a negative impact on customer satisfaction.Supported
Online Review Consumption
Sensory service experiences embedded in the positive aspect of a review have a positive impact on perceived review helpfulnessSupported
Sensory service experiences embedded in the negative aspect of a review have a positive impact on perceived review helpfulnessSupported
COVID-19 has no impact on the relationship between sensory information and review helpfulness.Supported
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Kim, J.M.; Park, K.K.-c.; Marjerison, R.K. Usefulness of Online Reviews of Sensory Experiences: Pre- vs. Post-Pandemic. J. Theor. Appl. Electron. Commer. Res. 2024 , 19 , 1471-1492. https://doi.org/10.3390/jtaer19020073

Kim JM, Park KK-c, Marjerison RK. Usefulness of Online Reviews of Sensory Experiences: Pre- vs. Post-Pandemic. Journal of Theoretical and Applied Electronic Commerce Research . 2024; 19(2):1471-1492. https://doi.org/10.3390/jtaer19020073

Kim, Jong Min, Keeyeon Ki-cheon Park, and Rob Kim Marjerison. 2024. "Usefulness of Online Reviews of Sensory Experiences: Pre- vs. Post-Pandemic" Journal of Theoretical and Applied Electronic Commerce Research 19, no. 2: 1471-1492. https://doi.org/10.3390/jtaer19020073

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Assessing the impact of collaborative authorship in Business Economics in Latin America

  • Published: 08 June 2024

Cite this article

business and economic literature review on the industries

  • Claudia N. Gonzalez Brambila   ORCID: orcid.org/0000-0001-7633-5091 1 &
  • Renata Herrerias   ORCID: orcid.org/0000-0001-7200-1254 1  

In this paper we analyze the evolution of Latin American (LATAM) Business Economics (BE) publications in international journals from 2005 to 2019. Using publications in Web of Science Core Collection (WoS), we analyze which characteristics of collaboration result in higher impact, i.e., total number of citations, and journals’ WoS impact factor. Our findings show that the number of publications in journals indexed in the WoS by researchers in LATAM have been rising in terms of the number of publications and impact measured by citations. Moreover, researchers in the region are publishing in journals with higher impact factor. The analysis shows that the main drivers of impact are multilateral and bilateral collaboration, number of countries, number of authors, and the number of categories of knowledge. Specifically, multilateral collaboration is a key factor of influential papers. Other aspects that increase the impact of publications are publishing in English and collaborating with authors from the United States. Our results also suggest a slight decrease in the impact as the number of coauthors increase.

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business and economic literature review on the industries

The Web of Science Core Collection that we use also includes the sub-datasets of: Book Citation Index-Social Sciences & Humanities (BKCI-SSH); Conference Proceedings Citation Index-Social Science & Humanities (CPCI-SSH); Conference Proceedings Citation Index-Science (CPCI-S); and Book Citation Index-Science (BKCI-S). However, because our analysis only includes articles, these sub-datasets were not included.

The first query considered publications from 1966 to 2020. The sample was 33,030 unique articles.

Before excluding articles with more than 10 authors, the data set contained 27,735 articles.

The Journal Impact Factor (JIF) is calculated by dividing the number of current year citations to the source items published in that journal during the previous 2 years. Fifty nine percent of the papers in the sample were published in journals which impact factor appears as “not available” in the Journal Citation Reports of Clarivate.

For example: if a publication is coauthored by three researchers from two countries—let’s say one person from Country A and two persons from Country B-, we assign 0.3333 publication to Country A and 0.6667 publication to Country B.

We identified 20 journals that are indexed in SciELO Citation Index and WoS. The SciELO Citation Index was fully integrated to the collection of Web of Science in January 2014, and it was not included in our search. ( https://blog.scielo.org/es/2014/02/28/scielo-citation-index-en-el-web-of-science/#:~:text=SciELO%20Citation%20Index%20(SciELO%20CI,partir%20de%20enero%20de%202014 ) . Table 11 in the appendix reports the list of journals that are indexed in both WoS and SciELO in our sample and the number of articles published in those journals by year of publication. Appendix tables are available from the authors upon request.

Field baseline expected citations from Web of Science Core Collection considers top 0.01% articles as well. However, considering the number of articles in our sample and the number of groups (315), the resulting number of articles per group is not enough to obtain top 0.01% articles. For instance, the largest group in our sample contains 1079 articles (Table 12 in the appendix, available upon request); each article represents a 0.093% which implies that the most cited article in the group is at the 99.90 percentile.

Table 13 in the appendix reports same statistics for articles grouped by rank and BE categories (available upon request). Numbers in the Table 13 represent the result of ranks based on both year of publication and BE categories.

Table 14 in the appendix reports the evolution of journals’ impact factor between 2005 and 2019 by type of collaboration and Business Economics WoS category (available upon request).

We include the number of WoS categories assuming multidisciplinary journals are listed on multiple WoS categories, therefore, it is possible to see if multidisciplinary articles receive mokore or less attention.

Abramo, G., D’Angelo, A. C., & Murgia, G. (2017). The relationship among research productivity, research collaboration, and their determinants. Journal of Informetrics, 11 (4), 1016–1030.

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Acknowledgements

We gratefully acknowledge the financial support of the Consejo Nacional de Ciencia y Tecnología (A1S9013) and Asociación Mexicana de Cultura, A.C. We also thank Daniel Rubí and Yamil Sanchez for helping with data collection.

This work is supported by the Consejo Nacional de Ciencia y Tecnología, A1S9013.

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Gonzalez Brambila, C.N., Herrerias, R. Assessing the impact of collaborative authorship in Business Economics in Latin America. Scientometrics (2024). https://doi.org/10.1007/s11192-024-05072-6

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Expect the cost of your airfare to continue to rise, an aviation trade group and industry heads warn

FILE - A Boeing 777X plane takes off at the Farnborough Air Show fair in Farnborough, England, on July 18, 2022. The cost of your next flight is likely to go up. That's the word from the International Air Transport Association, which held its annual meeting Monday June 3, 2024 in Dubai, home to the long-haul carrier Emirates. (AP Photo/Frank Augstein, File)

FILE - A Boeing 777X plane takes off at the Farnborough Air Show fair in Farnborough, England, on July 18, 2022. The cost of your next flight is likely to go up. That’s the word from the International Air Transport Association, which held its annual meeting Monday June 3, 2024 in Dubai, home to the long-haul carrier Emirates. (AP Photo/Frank Augstein, File)

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DUBAI, United Arab Emirates (AP) — The cost of your next flight is likely to go up.

That’s the word from the International Air Transport Association, which held its annual meeting Monday in Dubai, home to the long-haul carrier Emirates.

While carriers recover from the groundings worldwide from the coronavirus pandemic, industry leaders told journalists that there are several costs likely to push those ticket prices ever higher.

Part of that comes from worldwide inflation, an ongoing problem since the pandemic started. Jet fuel costs, roughly a third of all airline expenses, remain high. Meanwhile, a global push for the aviation industry to decarbonize has more carriers fighting for the little amount of so-called sustainable aviation fuel, or SAF, available in the market.

“The airlines will continue to do everything they can to keep costs in control as much as possible for the benefit of consumers,” said Willie Walsh, the director-general of the the International Air Transport Association, an industry-trade group. “But I think it’s unrealistic to expect that airlines can continue to absorb all of the costs. ... It’s not something we like to do, but it’s something we have to do.”

Also pressuring the industry is a pandemic hangover in aircraft production as well, they say. Carriers now keep older planes that burn more fuel flying longer. There also aren’t enough new aircraft to expand routes and increase supply to bring down overall prices.

FILE - A North Korean military guard post, top, and South Korean post, bottom, are seen from Paju, South Korea, near the border with North Korea, Friday, May 31, 2024. (AP Photo/Ahn Young-joon, File)

That warning comes as the IATA estimates globally, airline revenue will reach nearly $1 trillion in 2024, a record high. There will be 4.96 billion travelers on airplanes this year, with total expenses for carriers reaching $936 billion — another record high.

But industry profits also are expected to be nearly $60 billion this year.

In particular, Emirates, a main driver for Dubai’s economy, saw record profits of $4.7 billion in 2023 off revenues of $33 billion.

The Emirates’ results track with those for its base, Dubai International Airport . The world’s busiest airport for international travelers had 86.9 million passengers last year, surpassing numbers for 2019 just before the coronavirus pandemic grounded global aviation.

The airport now plans to move to the city-state’s second, sprawling airfield in its southern desert reaches in the next 10 years in a project worth nearly $35 billion .

Tim Clark, the airline’s president, obliquely acknowledged that Monday by saying that he didn’t want people to “get boxes of tissues out and play the violins” when warning that the industry’s profit margins sit in the low single digits. However, he contended that as airlines have grown larger and carriers consolidated, cost savings have quietly been passed onto consumers now able to book flights across the world.

“It is quite amazing that ticket prices are where they are today,” Clark said. “I think the value-for-money proposition that the consumers have had the benefit from for many decades is something that is one of those hidden bits of the narrative.”

Yvonne Manzi Makolo, the CEO of RwandAir, also highlighted the taxes and fees imposed on carriers by the countries they operate in. She specifically cited those paid by carriers flying out of African nations as “already ridiculous.”

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