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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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      <title>Dependence structure between energy uncertainty index and airlines stocks returns and volatility: A short communication</title>
      <link>https://trid.trb.org/View/2533873</link>
      <description><![CDATA[This study evaluates the performance of interlinks between energy uncertainty index and airlines stock returns and volatility by applying the wavelet coherence analytical methodology. For stock returns, American Airlines exhibits notable lead-lag effects, while Air China and Air France show varied patterns. In terms of volatility, American Airlines' volatility aligns with energy uncertainty across phases. Air France's volatility both leads and lags, and Air China shows minimal co-variation. The policy implications are provided at the end of the study.]]></description>
      <pubDate>Tue, 20 May 2025 11:38:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2533873</guid>
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      <title>Measuring the Operational Efficiency of the Six Airlines in China</title>
      <link>https://trid.trb.org/View/2282879</link>
      <description><![CDATA[Applying the method of Data Envelopment Analysis (DEA) through building the CCR and BCC models with two inputs and two outputs. The authors analyze the technical efficiency, pure technical efficiency, scale efficiency, technique efficiency change, pure technical efficiency change, scale efficiency change and Malmquist productivity index of Chinese major airlines(including Air China, China Eastern, China Southern, Hainan Airlines, Shanghai Airlines and Shandong Airlines) from 2000 to 2004. The research found a lasting decreasing technical efficiency trend in these five years, the Malmquist productivity index fluctuate in the round of 1. Knowing from each year, there are two MPI > 1 and two MPI < 1 in industry; it shows the status that big in both ends and low in the middle.]]></description>
      <pubDate>Tue, 17 Sep 2024 13:45:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2282879</guid>
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      <title>Enhancing airline connectivity: An optimisation approach for flight scheduling in multi-hub networks with bank structures</title>
      <link>https://trid.trb.org/View/2423556</link>
      <description><![CDATA[While one salient characteristic of hub airports lies in connecting passengers, the full-service airlines in North America concentrate their networks spatially over a number of hubs. Having witnessed the emerging multi-hub network, this paper investigated the flight scheduling problem under a multi-hub configuration, taking a well-defined bank structure and airport operational restrictions into account. An integrated non-convex Mixed-Integer Nonlinear Programming (MINLP) approach was proposed to enhance airline connectivity, considering different combinations of traffic flow direction and connecting times. To verify the scalability and effectiveness of the proposed model, a comprehensive case study has been undertaken with real-world scheduling data from Air China, which was solved by a novel problem-specific Selective Simulated Annealing (SSA) algorithm. Substantial improvements were achieved without sacrificing the scheduling efficiency. Precisely, the programme adjusted the flights during a typical operational day in a timely manner. The post-optimisation outcomes have witnessed its effectiveness with a 17.97%, 17.06%, 22.41% and 53.86% increase in airline connectivity at its four major hub airports (Chengdu Shangliu, Beijing Capital, Shanghai Pudong and Hongqiao) in China, respectively. A clear pattern of the bank structure also confirms its positive impact on airline connectivity under the multi-hub network configuration. Lastly, a comparative analysis for the distribution of all feasible connections further highlights the critical challenge concerning the role of the hubs in a multi-hub network. More specifically, Air China’s multi-hub network systematically performs better on Domestic-International routes, due to flight schedule, frequencies, geographical placements and detours. Among the four hub airports, Beijing Capital International Airport stands out as a dominant one, which implies its potential to serve as a robust international hub airport.]]></description>
      <pubDate>Tue, 10 Sep 2024 17:06:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2423556</guid>
    </item>
    <item>
      <title>A heuristic-based multi-objective flight schedule generation framework for airline connectivity optimisation in bank structure: An empirical study on Air China in Chengdu</title>
      <link>https://trid.trb.org/View/2350778</link>
      <description><![CDATA[As the first step of airline schedule planning, flight scheduling plays a pivotal role in shaping an airline’s competitiveness, defining its profitability and establishing service levels by determining the timetable for potential city pairs. Although full-service carriers consider the bank structure as an effective method to improve flight connectivity and optimise aircraft utilisation, existing literature lacks models specially focused on optimising flight schedules within the bank structure. This paper effectively addresses the existing gap by proposing an integrated multi-objective flight scheduling model to optimise airline connectivity in bank structure. The generalised formulation allows airlines to maximise their connectivity while controlling the traffic flow during flight scheduling, offering more flexibility to adjust parameters according to their specific needs. By formulating the problem as an integrated tail-dependent one, this study measures the impact of aircraft routing decisions on the set of feasible flight pairings continuously. Further, a novel heuristic-based Selective Simulated Annealing (SSA) algorithm is designed to implement and solve the proposed model promptly. Computational results demonstrate the applicability and effectiveness of the proposed approach, revealing that the systematic consideration of flight interactions leads to significant improvements in airline connectivity and aircraft utilisation. Notably, in test instances for over 200 daily flights, the proposed approach yields a solution that significantly increases airline connectivity by 18.58% while respecting the operational constraints. Validated with historical flight schedule data, the resolution approach serves as an efficient data-driven decision-making tool, which enables airlines to respond to the fast-changing air transportation market dynamics in real-time. In addition, this paper discusses and concludes with managerial insights regarding bank length verification and flight schedule optimisation.]]></description>
      <pubDate>Wed, 27 Mar 2024 15:40:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2350778</guid>
    </item>
    <item>
      <title>Understanding airline price dispersion in the presence of high-speed rail</title>
      <link>https://trid.trb.org/View/1710200</link>
      <description><![CDATA[This paper examines the price dispersion among China's “Big Three”, namely, Air China, China Eastern and China Southern in the presence of high-speed rail (HSR). It has been found that HSR is positively and significantly associated with airline price dispersion on the long-haul routes, which may suggest that the presence of HSR can facilitate airline cooperation in setting prices and outputs, thereby leading to greater price dispersion. However, on the short-haul routes where HSR is highly substitutable, the HSR competition effect dominates, and smaller price dispersion is observed. All the market structure and competition variables included in this study support the conclusion that price dispersion is greater in more concentrated and more densely travelled markets. The contribution of airline cost to price dispersion is limited.]]></description>
      <pubDate>Mon, 29 Jun 2020 11:21:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/1710200</guid>
    </item>
    <item>
      <title>Risk Assessment on Air China Joining Star Alliance</title>
      <link>https://trid.trb.org/View/1270950</link>
      <description><![CDATA[The paper firstly analyzed the risk Air China may face when it joins Star Alliance, and identify and measure it. Additionally the paper identified the risks faced by Air China when it cooperated with Star Alliance through the environmental analysis and flow chart method. Secondly, airline alliance risk fuzzy comprehensive assessment model was proposed using the relevant knowledge including AHP (analytic hierarchy process), fuzzy comprehensive evaluation, and the risk characteristics of airline alliances. The index system of evaluation was established and the index weight was computed. Through consultation to the experts and careful filtration, indicators of first class risk and second class risk were screened out. Then, the weight of each indicator through AHP was figured out. Finally, the risk degree about Air China cooperating with Star Alliance was evaluated through the risk fuzzy comprehensive assessment model, and some preventive measures were provided and recommended to degrade the degree of risk level for Air China.]]></description>
      <pubDate>Wed, 27 Aug 2014 10:50:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/1270950</guid>
    </item>
    <item>
      <title>Evaluating Competitiveness Using Fuzzy Analytic Hierarchy Process: A Case Study of Chinese Airlines</title>
      <link>https://trid.trb.org/View/1278041</link>
      <description><![CDATA[This article reports on a case study of the Chinese aviation industry, focusing on competitiveness.  The authors propose fuzzy analytic hierarchy process (FAHP) to use for resolving the uncertainty and imprecision in the evaluation of airlines' competitiveness.  The authors first present a review of the relevant research on industrial international aviation competitiveness, then discuss a theoretical framework for the study of aviation competitiveness.  They establish an index system with five first-order indicators and 17 second-order indicators, set up a Chinese aviation competitiveness model based on simple fuzzy numbers from the fuzzy analytic hierarchy process, and use their model to evaluate the competitiveness of five major Chinese airlines: Air China, China Southern Airlines, China Eastern Airlines, Hainan Airlines, and Shanghai Airlines. The authors propose and consider 7 aviation competitiveness factors:  cost, efficiency of asset operations, scale of production and operation, brand, service, main factors of production, and cultural factors. They conclude that this approach is effective and useful, particularly when subjective judgments on performance ratings and attribute weights are not accessible or reliable. However, additional refinements are necessary because data on the airlines can be difficult to collect and thus incomplete.]]></description>
      <pubDate>Fri, 24 Jan 2014 14:30:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/1278041</guid>
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    <item>
      <title>Market Conduct of the Three Busiest Airline Routes in China</title>
      <link>https://trid.trb.org/View/1251574</link>
      <description><![CDATA[This paper studies the market conduct of the three busiest routes dominated by the three largest airlines in China. The competition strategies of the three largest Chinese carriers are found to be different from each other. In general, the market behavior of Air China is consistent with that described in the Cournot solution. Both China Southern Airlines and China Eastern Airlines demonstrate competitive behaviors somewhere between Bertrand and Cournot. However, the former is closer to Cournot, whereas the latter is closer to Bertrand. The authors find that the Cournot model seems consistent with the competition between China Eastern Airlines and Air China. Their results suggest that Stackelberg competition develops with China Eastern Airlines as the leader and China Southern Airlines as the follower. They also find that China Eastern Airlines adopts a low-price strategy to compete for market share. Due to its lowest costs, Air China earns the highest profits among the three airlines. The authors also find that the competition among the three carriers becomes more intense over time.]]></description>
      <pubDate>Mon, 03 Jun 2013 09:22:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/1251574</guid>
    </item>
    <item>
      <title>Attitude Adjustment</title>
      <link>https://trid.trb.org/View/849764</link>
      <description><![CDATA[In this article the authors discuss the shift in business strategy for major air carriers whose bases of operations are found in China. This shift has gone from conservative in terms of forming organizational alliances to open to greater levels of cooperation. This move was at least in part allowed for by the country’s increasing compliance with international standards, thus allowing for better competitiveness in the market. One major shift in strategy that has yet to take place for airlines based in China is to switch from a point-to-point networking plan to the vastly more efficient hub network. The article explains that, by using hubs, carriers based in the U.S. maintain a 60 percent market share as well as larger profit margins. A number of business propositions including mergers and buy-outs as well as projections for the expansion of this group of carriers are described.]]></description>
      <pubDate>Thu, 28 Feb 2008 09:08:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/849764</guid>
    </item>
    <item>
      <title>Clear target</title>
      <link>https://trid.trb.org/View/845879</link>
      <description><![CDATA[Subtitle: Air China wants Shanghai Airlines, to develop a balanced business across the country.]]></description>
      <pubDate>Mon, 28 Jan 2008 10:59:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/845879</guid>
    </item>
    <item>
      <title>Against All Odds: Chinese LCCs are Moving Forward with Different Development Models Despite Numerous Hurdles</title>
      <link>https://trid.trb.org/View/842327</link>
      <description><![CDATA[This article surveys the low-cost carriers (LCCs) that are beginning to experience success in China. The industry as a whole enjoyed a collective net profit of $311 million in 2006, compared to a roughly $100 million loss in 2005. However, much of that profitability is due to the operations of Air China. Now, the LCCs in China are starting to grow. They are using strategies beyond simple cost saving, such as efficiency improvements and differentiated operating models. Costs are fairly fixed, with monopoly suppliers for items like fuel, and fixed fees for landing charges, aviation supplies and MRO. Different LCCs are described, including East Star Airlines, based in Wuhan, Juneyao Airlines, based in Shanghai, and Spring Airlines, based in Shanghai as well. Challenges for all of them include slot shortages at major airports such as Shanghai and aircraft acquisition, which is centrally managed.]]></description>
      <pubDate>Mon, 31 Dec 2007 07:38:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/842327</guid>
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    <item>
      <title>War for Profit: Led By a Former General, Air China Aims to Become the Country's Leading and Most Profitable Airline</title>
      <link>https://trid.trb.org/View/839854</link>
      <description><![CDATA[Air China (CA) is seeking to become the country’s largest and most profitable airline as the Chinese airline industry is still recovering from costs imposed by government-mandated consolidation, a drop in business from the post-9/11 SARS outbreak in Asia, and an increasingly competitive domestic market. CA’s earnings rose threefold in the first half of 2007, and it has expansion plans. Currently, 80 percent of its profit is generated on international routes. The airline is making plans to expand its domestic business, while focusing on routes with heavy concentrations of business travelers. It has, for example, 12 daily flights connecting Beijing and Shanghai. CA is also investing heavily in its Beijing operations and plans to be a major presence in Shanghai and Hong Kong. Other strategies, such as selling off smaller operations and imposing cost controls, are also discussed. It is the only mainland carrier to have hedged fuel, resulting in major savings when prices jumped.]]></description>
      <pubDate>Fri, 30 Nov 2007 07:25:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/839854</guid>
    </item>
    <item>
      <title>China's Big Three : the road to a Super PRC carrier?</title>
      <link>https://trid.trb.org/View/838514</link>
      <description><![CDATA[]]></description>
      <pubDate>Mon, 15 Oct 2007 13:31:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/838514</guid>
    </item>
    <item>
      <title>Consolidation push</title>
      <link>https://trid.trb.org/View/812586</link>
      <description><![CDATA[Subtitle: China Eastern seeks foreign partner as domestic takeover looms.]]></description>
      <pubDate>Tue, 10 Jul 2007 10:17:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/812586</guid>
    </item>
    <item>
      <title>Air China oversubscribed but doubts linger over stock</title>
      <link>https://trid.trb.org/View/796221</link>
      <description><![CDATA[]]></description>
      <pubDate>Tue, 16 Jan 2007 09:43:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/796221</guid>
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