strategic alliances
TRANSCRIPT
Strategic alliancesas a competitive strategyHow domestic airlines use alliances
for improving performance
James RajasekarCollege of Commerce and Economics, Sultan Qaboos University,
Muscat, Sultanate of Oman, and
Paul FoutsAgeno School of Business, Golden Gate University, San Francisco,
California, USA
Abstract
Purpose – The purpose of this paper is to examine how domestic airlines benefit when they havecode sharing arrangements with international carriers.
Design/methodology/approach – The data for this research study have been collected primarilyfrom three sources. The first database, the digest of statistics no. 400 is from International Civil AviationOrganization (ICAO) based in Montreal, Canada. The second source of data comes from the AirlineBusiness database. The third source of data for this research study is from Official Airline Guide (OAG).Ten years of data from 1994 to 2004 are collected from the databases of ICAO, Airline Business and alsofrom individual airlines. Data such as the revenue passenger miles (RPMs) and load factor are obtainedfrom the ICAO database and data such as alliance pattern are culled from the Airline Business database.
Findings – This research study reveals that code sharing agreements between a domestic andinternational airline will benefit the former by way of increased RPMs, passenger load factor (PLF),and market share. However, the coefficients of the hypothesized variables suggest that the initialgains achieved by the domestic airlines by way of increased RPMs start to erode in the long run. Thus,a domestic airline must form a code sharing agreement with an international airline at the earliest, so asto get the initial increase in RPMs. The effect of code sharing on the market share of domestic airlinesis explicit and consistent throughout this research study. The second dimension in the code sharing isthe multiple alliances between domestic and international airlines. Multiple alliances refer to an airlinehaving more than one code sharing agreement with international carriers. The third factor in thissequence of hypotheses is equity investment by international carriers in domestic airlines. Therelationship between equity investment and its influence on the performance of the targeted firm isalways an interesting topic explored by both the academic researchers and practitioners. However, inthis study, the regression results do not support the hypothesis. That means that mere equityinvestment by international carriers in domestic airlines may not result in increased RPMs, load factorand the market share for domestic airlines. The interesting finding in this particular section is theinfluence of the large size of the alliance partners on all the three dependent variables; RPMs, PLF, andthe market share. Therefore, we can conclude that if both the airlines are large enough and they formcode sharing agreements, then this may result in increased RPMs, PLFs, and market share for thedomestic airlines. Similarly, the study supports the premise that if the partners are unequal, then thedomestic airlines may not be able to increase the RPMs, load factor, and the market share.
Originality/value – This paper reveals that code sharing arrangements reached earlier in thecompetition is better as the benefits tend to reduce after a certain period of time.
Keywords Strategic alliances, Competitive strategy, Airlines
Paper type Research paper
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1056-9219.htm
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International Journal of Commerceand Management
Vol. 19 No. 2, 2009pp. 93-114
q Emerald Group Publishing Limited1056-9219
DOI 10.1108/10569210910967860
IntroductionOne of the most notable trends in recent years has been the growth in the popularity ofalliances between competitors, prospective competitors, and even supply chain members.Hence, investigating what drives one firm to cooperate with another firm has been aninteresting topic for researchers for well over a decade. A number of empirical studies havedocumented the unprecedented growth of inter-firm cooperative agreements in a varietyof industries, and much has been made of the beginning of a new era of cooperation inwhich firms seek partnerships in several facets of their operations (Lei and Slocum, 1991;Chang, 1995).
The international air transport industry plays a key role in the development of theworld economy, stimulating exchanges between countries and facilitating internationaleconomic relations. The liberalization of market access in Europe, North America, andother regions of world air transport has added a new dimension to competition andcustomer orientation in the airline industry. This has resulted in airlines revising theirgrowth and competitive strategies to survive and prosper (Berry, 1994). Airline growthand competitive strategies not only include cost cutting measures and better revenuemanagement tools, but also strategic alliances with other airlines. Airlines formalliances to gain access to global networks within the constraints of the current bilateralair services agreement (ASA) system. In many cases, they have entered into codesharing agreements to maintain or expand network coverage, and international codesharing has now become part of bilateral negotiations.
Airlines use alliances as a means to achieving global service networks, gettingaccess, and establishing identities in new markets without providing aircrafts, andproviding services which would be unprofitable if operated alone. On the other hand,consumers have demonstrated a preference for dealing with airlines with large servicenetworks to minimize their cost of travel, to get better services, and to take advantageof more attractive frequent flyer programs. Alliances can also lead to better access atcongested airports, where landing restrictions, lack of landing and take-off slots, andother constraints would otherwise exist. Moreover, alliances are theorized to reducecosts through economies of scale associated with joint marketing, maintenance, groundfacilities, training, computer reservation systems, and through elimination ofduplication and redundancy in operation (Oum et al., 1996; Borenstein and Rose,1995). Thus, the overall aim of airline alliances is considered to be enhancing partnerairlines’ competitive position and also achieving higher profits for each of the partners.
Though many surveys and research have been done on strategic alliances in theairline industry in general, the positive or negative effects of alliances on the domesticairlines is under researched. A domestic airline is defined as a carrier which flies withinthe borders of a particular country. This study is aimed at filling that gap of knowledgeby systematically studying and analyzing the benefits accrued or not accrued bydomestic carriers while having strategic alliances in the form of code sharing withinternational carriers. The term benefit in this research study is defined by increasedrevenue passenger miles (RPMs), load factor, and market share, as these threevariables are used to measure the productivity and profitability of an airline.
Theoretical framework and hypothesesThere are many theoretical frameworks dealing with strategic alliances. For reasonsranging from vertical disaggregation (Powell, 1990), shrinking product life cycles
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(Ohmae, 1989), growing capital investment requirements (Doz, 1988), to the desire toincrease competitiveness through organizational learning (Senge, 1992), companiesare forming alliances at an ever increasing rate. Popular theories that have beenapplied to strategic alliances include transaction cost economics (Williamson, 1985),game theory (Parkhe, 1993), exchange theory (Gulati, 1995), strategic behavior model(Hagedoorn, 1993), dialectical model (Das and Teng, 1996), and resource-based view ofthe firm (Eisenhardt and Schoonhoven, 1996). Hamel et al. (1989) also asserted thatalliances can be used to learn the skills of the other partner. The authors claimedthat if there was not a mutual learning process, then the alliances would become justoutsourcing agreements without using the full potentials of the strategic allianceconcept.
In this context, air carriers increasingly use strategic alliances to take full advantageof the economies of scale that internationalization offers. As seen in the studyconducted by Park (1997), over the last two decades, air transport has undergone majorchanges owing to the increasing globalization of the industry. One reason for thisevolution is the liberalization of markets, which is characteristic of many industries inthe late twentieth century. Consequently, the competitive landscape of manyindustries, including the airline industry, is changing significantly. Thus, airlines nowhave an opportunity to penetrate formerly inaccessible markets, but they are, at thesame time, also confronted with new entrants into their markets and risk losing aconsiderable percentage of their market share to newly formed low cost airlines. Asevidenced from Schaeffer (1998) study airline alliances are creating trends that areconsolidating control of flights in 82 percent of the market share.
On the other hand, Douglas (2005) found that airline sales teams identify alliancemembership as a critical sales tool, but the airline passengers did not consider thealliance membership as equally valuable. This research study is focused on the impact ofthe alliances on national or domestic airlines. A domestic airline is defined as a carrier,which only flies within the borders of a particular country. Generally, the airlineindustry can be analyzed using various factors such as traffic, costs, load factor, labor,fuel, and maintenance. However, the starting point in analyzing a passenger airline is itstraffic. Though many standards to measure the performance of airlines are available,RPMs or revenue passenger kilometers are preferred by airlines, as well as regulators, asthis measure is superior as an analytical tool because airline revenues most closelycorrespond with RPM/RPK levels.
According to Youssef and Hanson (1994), the rate of change in RPKs can be used asa yardstick to determine whether a carrier is gaining or losing market share. Iatrou andSkourias (2005) also investigated the effects of alliances on the performance of airlinesand concluded that alliances helped increase the RPKs of airlines with alliances by9.4 percent. Wang et al.’s (2004) study also supports that alliances between airlinessignificantly increase the traffic volume and market share for the airlines within thealliance. In recent years, start-up regional and charter carriers typically outperformedthe major airlines in RPK growth because their traffic base is much smaller. The termsuccessfulness in this hypothesis is defined as a proportionate increase in revenuepassenger kilometers of each carrier in the alliance. Ever since the USA deregulated itsairline industry in 1978, other countries have also followed a suit. Many countries inthe European Union have deregulated their airline industries, followed bySouth American nations. Earlier, the national carriers had an advantage of not
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having real competition due to government controls, the protection of ASAs, and entrybarriers in the aviation industry. However, since worldwide deregulation of the airlineindustry, they now face stiff competition from foreign and other newly start-updomestic carriers, especially on the low cost model (low cost airlines). This is alsoevidenced by the study conducted by the Avmark Aviation Economist (1996) thatfound increased liberalization which began in the early 1980s and increasedcompetition that made it more difficult for domestic airlines to survive. Hence:
H1a. Domestic airlines will have increased RPMs if they have code sharingagreements with international carriers.
H1b. Domestic airlines will have increased passenger load factor (PLF) if they havecode sharing agreements with international airlines.
H1c. Domestic airlines will have increased market share if they have code sharingagreements with international airlines.
Single vs multiple alliancesGomes-Casseres (1993) defines alliance networks as those that have loose collections offirms with disparate interests and capabilities. Since the competitive behavior of analliance network is driven by the nature of collaboration among members inside thegroup, each alliance partner should be chosen with care so as to provide the necessaryskills to the alliance as a whole. He also asserts that the alliance networks not onlyreshape rivalry in an industry but also create collective competition. This new structureand dynamics of competition depend on the collective behaviors of allied firms. Hence,the number of member firms in an alliance group affects how the group competes as asingle entity. Having more members, for example, may give the alliance network accessto a broader range of capabilities; a larger overall alliance size also tends to make itharder for the group to unite behind a common strategy (Gomes-Casseres, 1994). Hwangand Burgers (1997) affirm that the alliance networks will only be successful if there is anadvantage to combining the capabilities of two or more firms. He also claims that for thisto occur, each firm must be unable to develop internally the capability offered by theother firm and the combination of capabilities must yield a total value that is greater thanif the capabilities were used separately.
According to a study conducted by International Civil Aviation Organization(ICAO) (1996), airlines that are party to a broader alliance have clearly benefited fromthe code sharing agreement in terms of additional traffic and extra revenue, althoughthis has mainly been at the expense of other carriers. A wider alliance permits eachpartner to reach more destinations and to take advantage of hub-and-spoke efficienciesmuch like those that have driven the development of America’s domestic airline market(Oum et al., 1996). Although each of the partners in the alliance remains independent,the alliance has been projected as a single company for the purpose of attractingpassengers.
Through multiparty alliance, airlines are believed to be utilizing new programswhich help with work force utilization, fleet rationalization, flight planning, electronicticketing, and determining optimal fare and route structures (Spitz, 1998; Tretheway andOum, 1992). Although many major airlines can service new routes, without a supportinginternational hub network they cannot provide profitable service on many
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international routes. However, this can be achieved by having a partner feeding trafficthrough a hub and thereby generating numerous benefits including stimulation traffic.This will not only lower a carrier’s operating costs dramatically, but also allow thecarrier to lower fares and increase flight frequency without the need to make substantialinvestment in additional aircraft (Borys and Jamison, 1989). The partners may alsorealize further cost savings by sharing cargo and passenger terminal facilities,integrating frequent flyer programs, consolidating sales and administrative operations,combining information technologies, and coordinating advertising, and engaging injoint procurement where feasible:
H2a. Multiple alliances foster increased RPMs for domestic airlines than airlinesthat have alliances with one partner.
H2b. Multiple alliances foster increased PLF for domestic airlines than airlines thathave alliances with one partner.
H2c. Multiple alliances foster increased market share for domestic airlines thanairlines that have alliances with one partner.
Equity vs non-equity alliancesResearch by Hagedoorn and Narula (1996) indicates that international alliances are moreequity-oriented, whereas a disproportionate share of domestic alliances is ofa contractual nature. From both a transaction cost economics perspective and astrategic management perspective this preference can be explained in terms of the costof monitoring and keeping control over a long distance agreement. As domestic alliancesare formed in a familiar environment, equity control is probably less prevalent in orderto monitor the agreement than in the case of international alliances where the familiaritywith the behavior of partners is expected to be smaller. Enforcing a contract in anunfamiliar environment is rather difficult compared to enforcing partial control throughan alliance in which equity-sharing gives a firm at least some degree of ownershipadvantages (Dunning, 1994).
Transaction cost economists have classified the governance structures of alliancesin terms of their use of equity ownership (Vonortas, 1990). Equity alliances, as definedby transaction cost economists, take one of two forms (Teece, 1986). They can either beorganized as an equity joint venture, which involves the creation of a new andindependent jointly owned entity, or they can come about when one of the partnerstakes a minority equity position in the other partner or partners. Transaction costeconomists justify treating equity joint ventures and minority equity investments asa single category on the grounds that “a direct equity investment by one firm intoanother essentially creates an equity joint venture between one firm’s existingshareholders and the new corporate investor” (Pisano and Teece, 1989). In both types,the effective shared equity stakes of the firms vary case by case. The important point isthat beyond a certain threshold, the shared ownership structure effectively detersopportunistic behavior. Generally, an airline can purchase only a minority holding ina carrier based in another country and this creates a sort of halfway house, which oftendefeats the original purpose of the deal (Doganis, 1991).
The Mountford and Tacoun (2004) study identified a total of 502 alliances during2004 and of these 56 alliances or 10.8 percent involved equity, a drop of 14.9 percentcompared to 2003. However, this decline in equity alliances as a percentage is partly
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attributable to the steep increase in the number of airline alliances. Some significantnew developments, such as alliances between North American carriers andSouth American carriers, show that equity is in fact creeping back into favor as ameans to cement an alliance. The other body of literature suggests that by providingaccess to new markets with better service to customers and thus reducing costs, thealliances might probably succeed, with or without equity. Many studies also supportthe view that equity participation in an alliance does improve the performance andsurvival rate (Youssef and Hanson, 1994; Ramirez, 1998):
H3a. Alliances involving equity investment by international airlines in domesticcarriers will have increased RPMs for domestic airlines compared to thosewithout the equity arrangement.
H3b. Alliances involving equity investment by international airlines in domesticcarriers will have increased PLF for domestic airlines compared to thosewithout the equity arrangement.
H3c. Alliances involving equity investment by international airlines in domesticcarriers will have increased market share for domestic airlines compared tothose without the equity arrangement.
Partners’ size, performance, and alliance patterns – large partnersThe combined forces of globalization and privatization are leading drivers in the presentsurge of strategic alliances. Selection of the right partner has become one of the mostdifficult and crucial tasks for top management at the airlines. Well-structuredpartnerships can create highly profitable and beneficial global networks,but, conversely, ill-conceived alliances can threaten the very existence of theparticipating carriers. While some of the alliance failures may be attributed tochanges in business conditions, inappropriate partner selection underlies a number ofalliance failures (Borenstein and Rose, 1995). While studies have found organizationalcompatibility to be an important determinant of marketing alliance success (Das andTeng, 1996), they do not address the partner selection issue. In an exception, Doz (1988)proposed that marketing alliances be conceptualized, designed, and managed from theperspective of the customer. They recommend that the usage complementarity thatexists between goods and services be used as a basis for determining partner selection.
Hence, airlines must evaluate many parameters such as size, geographical location,network comparison, fleet, partnership goals, and long-term strategic visions beforethey select a partner for code sharing agreement. To achieve this process in a mostefficient manner, some consulting companies have even developed a computer model toselect airline partners. The computer simulated program uses parameters mentionedabove to short list airline carriers by ignoring unqualified partners, thereby cutting topmanagement’s valuable time in the selection process. The basic foundation of a goodrelationship is the choice of the right partner. But what are the characteristics of the rightpartner? According to Gulati (1995) the partner selection process should first identifyorganizations whose needs, skills, and resources are completely complementary to thoseof the large firm. A second selection criterion is the choice of a partner that is financiallystable and well managed.
Bleeke and Ernst (1994) categorized strategic alliances into six distinct types. Theyare: collisions between competitors (direct competitors as partners), alliances of the
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weak (two or more weak companies form alliances), disguised sales (a weak companyjoins a strong company, usually a direct competitor), bootstrap alliances (a weakcompany joins a strong company, usually a competitor with a complementaryproduct), evolutions to a sale (sale of one partner), and alliances of complementaryequals (involves two complementary partners). The current alliance agreementsbetween the airline carriers also resemble one or more of the above pattern categorizedby Ernst and Bleeke. Hence:
H4a. Code sharing arrangements between a large domestic carrier and a largeinternational carrier will increase the RPMs for domestic airlines.
H4b. Code sharing arrangements between a large domestic carrier and a largeinternational carrier will increase the PLF for domestic airlines.
H4c. Code sharing arrangements between a large domestic carrier and a largeinternational carrier will increase the market share for domestic airlines.
Partners’ size, performance, and alliance patterns – weak or unequal partnersAs discussed in the previous section, partners’ size and performance is one of thesignificant factors that influence the successful outcome of the proposed alliances. Justlike alliances between large partners produce significant benefits for the newly formedalliances, if an alliance is formed between two weak or unequal partners, i.e. either ofthe partners is small or weak, then it may not produce as many benefits as the first typeof alliance. This particular theory was also adopted from the works of Bleeke and Ernst(1994). Alliances between large partners bring more benefits to the alliances becausethey bring different sets of synergies and opportunities, especially when theycomplement each other. These synergies and opportunities can be explored and usedby both the partners for the successful operation of the alliance firm.
The alliance literature suggests that viewing alliances as learning opportunities providean alternative to mutual alliance value creation. Alliances can provide firms with access tothe embedded knowledge of other organizations. This access creates the potential for firmsto internalize partner skills and capabilities. Hennart (1988) referred to this process asgrafting, the process by which organizations increase their store of knowledge byinternalizing knowledge not previously available within the organization. In an alliance, twoor more organizations are brought together because of their complementarity and theirdifferences. However, when small partners strike alliances with large partners, the abovelogic may not work in many cases because the weak or unequal partner’s motive andambition may be diametrically different than the large partner. Hence:
H5a. Code sharing arrangement between domestic and international carriers thatare small or unequal in size will not increase the RPMs for the domesticairlines.
H5b. Code sharing arrangement between domestic and international carriers thatare small or unequal in size will not increase the PLF for the domesticairlines.
H5c. Code sharing arrangement between domestic and international carriers thatare small or unequal in size will not increase the market share for thedomestic airlines.
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Research design and methodologyThe data for this research study have been collected primarily from three sources. Thefirst database, The digest of statistics no. 400, is from ICAO based in Montreal, Canada.This digest contains statistics of all the domestic airlines in the world such as RPMs,cost per mile, miles flown by each flight, number of passengers carried, and PLF asreported by the contracting states. The second source of data comes from the AirlineBusiness (2004) database. This database contains information on all allianceagreements in the airline industry such as airlines that have alliance(s) with othercarriers, the year in which the alliance was formed, number of partners in an alliance,type of alliance, and whether it is an equity or non-equity alliance agreement. The thirdsource of data for this research study is from Official Airline Guide (OAG). Thisdatabase contains information on detailed schedule information of flights for each andevery destination in the world. OAG identifies a code sharing flight by placing a delta(D) mark in the table. Hence, this database has been used to identify airlines that havecode sharing agreements.
Ten years of data from 1994 to 2004 were collected from the databases of ICAO,Airline Business, and also from individual airlines. Data such as the RPMs and loadfactor were obtained from the ICAO database, and data such as alliance pattern wereculled from the Airline Business database. The control variables used in this researchstudy are the age of the airline and previous code sharing experience, and the data forthe same were obtained from individual airlines.
As can be seen from Table I, only 59 airlines satisfied all the conditions necessary tobe a part of the sample list, hence these airlines were chosen as a sample: domesticairlines with code sharing agreements accounted for 37 carriers: North America (fivecarriers), South America (12 carriers), Europe (12 carriers), and Asia (eight carriers).Likewise, domestic airlines without code sharing agreements accounted for 22 carriers:North America (four carriers); South America (six carriers), Europe (nine carriers), andAsia (four carriers).
The primary research question of this study is to investigate the effect ofcode sharing on the RPMs, PLF, and the market share of domestic airlines. Hence, codesharing is the independent variable for H1a, H1b, and H1c. The effect of multiplealliances on firms’ performance is a relatively under researched area in the strategicalliance literature. Many studies that investigated the effect of multiple alliances onfirm performance have not focused on the airline industry. Therefore, multiplealliances is the independent variable for H2a, H2b, and H2c. Multiple alliances refer todomestic airlines having more than one code sharing agreements with the internationalcarriers.
The effect of equity investment on firms’ performance is a well researched and mostattempted topic in the alliance literature. As seen in the literature review, many authorssupport the view that firms that have invested in equity in other firms have morecommitment than others. Consistent with this typology, H3a, H3b, and H3c wereformed and equity investment was made the independent variable for allthese hypotheses.
The term large partners refer to size of the airlines on the basis of each partner’smarket share in their own territories. This particular variable was used in conjunctionwith Bleeke and Ernst’s typology (1994). The authors claim that alliances between largepartners will not only increase the lifespan of the alliance firm, but are also more fruitful
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than other types of alliances. Following this logic, H4a, H4b, and H4c were formed withthe independent variable, large partners.
The independent variable, unequal partners, for the last set of hypotheses in thisresearch study is also derived from the works of Bleeke and Ernst focusing on weak orunequal size of the partners. Unequal in this context refers to weak or an alliance partnerwho is not comparable in market size with the other partner.
The dependent variables used in this research study are RPMs, passenger loadfactor (PLF), and the market share of domestic airlines. The RPM is one of the toolsused by the airline industry to measure the productivity of an airline. Hence,performance increase in the domestic airlines should result in increased RPMs fordomestic airlines. The increase (D) in RPMs was calculated for every year for everyairline by finding the difference between a given year and its preceding year (x 2 x1) asa percentage. The load factor is considered to be a key measure of capacity utilizationby the airline industry experts. As a first step, the increase (D) in load factor wascalculated for every year for each airline in the study by calculating the differencesbetween a year and its preceding year (x 2 x1) as a percentage.
The third dimension in the dependent variable is the market share of domesticairlines. It was hypothesized that all the independent variables will influence the marketshare of the domestic airlines so that the latter will have increased market share, as aresult of forming code sharing agreements with international carriers.
USA South America Europe Asia
1. Air Wisconsin 9. Austral Airlines 27. Finaviation 48. East West Airlines2. Aloha Airlines 10. Lade 28. Kar Air 49. Bourgaq Indonesia3. Midwest Express 11. Laer S.E. 29. Coast Air K/S 50. Mandala Airlines4. Mesa Airlines 12. Brasil-Central 30. Wideroe 51. Archana Airways5. Trans States
Airlines13. Nordeste 31. Sata 52. Jet Airways
6. Atlantic Southeast 14. Rio-Sul 32. Binter Canararias 53. NEPC Airlines7. American Trans
Air15. Tam 33. Binter Medit 54. Sahara India
Airlines8. Southwest
Airlines16. Pantanal 34. SPANAIR S.A. 55. Turkey
17. Tavaj 35. AVIACO 56. Skywest Airlines18. TABA 36. Linjeflyg 57. Dirgantara Air
Services19. Intercontinantal
Columbia37. Gill Airways 58. Vayudoot
20. Aerosanta 38. Isles of Scilly 59. Arkia21. CATA 39. Air Stord22. Dinar 40. Air Nostrum23. Interbrazil Star 41. Augsburg Airways24. Passaredo 42. Air Inter25. Aces 43. ATI26. Imperial Air 44. Air Bristol Ltd
45. Community Express46. Jersey European
Airways47. Knightair
Table I.Domestic airlines selected
for study
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Age of the airlines, previous code sharing experience, regional RPMs of domesticairlines and regional load factor of domestic airlines are control variables used in thisresearch study. Age in this discussion refers to the total number of years an airline is inbusiness. The age and experience of firms in a strategic alliance as well as in aninternational joint venture (IJV) make a significant contribution in creating wealth forboth partners. This is because when firms get older they become more successful andefficient in conducting business. Following this logic, the age of partners wasincorporated as a control variable in all the hypotheses.
The term previous code sharing experience refers to the past code sharing experienceof domestic and international airlines. The strategic alliance literature (Simon, 1999)supports the view that if a firm has previous alliance experience, then it will lead tofurther success when it forms new alliance agreements in the future. The airline industryis a cyclical industry which can be affected by the growth and decline of a country’seconomy. When this happens in a country, the domestic airline industry is also affected.Hence, in order to capture the regional airline industry’s effect on the individual airlines,the regional load factor was calculated for the whole region in which a domestic airlineis operating. This was done by adding the load factors of the entire domestic airlinesoperating in a given region – year by year for the entire period of the study. For similarreasons, the regional RPMs were also calculated.
The descriptive statistics of the sample (Table II) provides mean and standarddeviation values for all the variables used in this study. As the correlation matrix(Table III) for all the variables is not highly correlated, the researcher decided to use allthese variables.
Testing of hypotheses and analysis of variablesH1 predicts that the domestic airlines will have increased RPMs if they have a codesharing agreement with international airlines. An international airline is defined asa foreign carrier in this research study. While domestic airlines strictly carry passengerswithin a country, the international airlines fly passengers out of a country from a specificinternational airport. A significant level of 0.05 has been chosen for comparing theF-ratio and other value in each hypothesis. If the individual values are equal to or less
Variables Mean SD Min. Max.
Age of the domestic airlines 22.028 15.325 2 63Code sharing 1.151 0.359 1 2Equity investment 4.825 5.453 0 19Large partners 0.144 0.353 0 1Load factor of individual airlines 0.028 0.177 20.279 1.5Market share 45.764 15.233 12 91Market share – difference 0.063 0.05 20.091 0.214Previous code sharing experience 3.906 2.98 0 11Regional passenger load factor 0.018 0.12 20.199 1.09Regional revenue passenger miles 0.266 0.701 20.734 9.329Revenue passenger miles of individual airlines 0.87 5.273 20.734 66.527Unequal partners 0.633 0.483 0 1
Note: N ¼ 59
Table II.Descriptive statisticsof variables
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12
34
56
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910
1.A
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Notes:N¼
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Table III.Pearson’s correlation
matrix of variables
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than the standard value (0.05), then the hypothesis will be supported – otherwise itwill not be supported. As shown in Table IV, the probability of the F-ratio (0.004) andthe probability of the independent variable for this hypothesis, code sharing issignificant (0.016).
There were four control variables used in the regression equation for this hypothesis.They are: age of the airlines, previous code sharing experience, market share, and RPMsof the region. Age in this discussion refers to the total number of years an airline is inbusiness. Conventional wisdom suggests that the age of firms in a strategic alliance aswell as in an IJV makes significant contribution in creating wealth for both partnerswhich will lead to the success of the alliance. This is because when firms get older, theyget experience and become more mature in transactions with other businesses.Following this logic, the age of partners was incorporated as a control variable in all thehypotheses.
However, the age as a control variable was not significant in any of the hypotheses inthis research study. Hence, this research study does not support that the age andexperience of a partner firm in a strategic alliance plays a significant role in thesuccessful operation of the alliance including creating wealth for the partners. However,we can conclude that code sharing does increase the RPMs of domestic airlines if theyhave code sharing agreements with international carriers. The data also suggests thatnot only domestic airlines benefit through alliances, but international airlines also shareequal benefits. This is because alliances between domestic and international carriersallow both sides to enhance their attractiveness and brand loyalty through improvedfrequent flyer programs, increased efficiency, and low fares. Therefore, H1a issupported.
H1b predicts that domestic airlines that are part of code sharing agreements withinternational carriers will increase their load factor more than domestic airlines that arenot part of code sharing agreements with international carriers. As shown in Table IV,the probability of the F-ratio for this hypothesis is significant (0.000). However, onecannot judge the validity of a hypothesis just by the F-ratio alone. Hence, in regards tothe probability of code sharing, the independent variable was taken into account. Thisvalue stands at 0.004, which is also significant. This result indicates that there isa significant relationship between increase in load factor and code sharing. Hence, H1bis supported. Based on the regression results, it is supported that domestic airlines mayincrease their PLF, if they have code sharing agreements with international carriers.Similarly, international airlines also increase their PLF when they have code sharingarrangements with domestic carriers.
The third dimension in H1 is the effect of code sharing on the market share ofdomestic airlines. Consistent with Park’s (1997) typology, it is predicted in H1c thatdomestic airlines will increase their market share if they have code sharing agreementswith international carriers. As shown in Table IV, the probability of the F-ratio is verysignificant (0.000) for this hypothesis, which directs us to compare the probability ofthe independent variable, code sharing which is also significant (0.017). Therefore,it appears that there is a positive relationship between increase in the market share ofboth domestic and international airlines and code sharing arrangements with eachother. Therefore, H1c is supported.
Based on the regression results, we can deduce that code sharing between domesticand international airlines may help increase the RPMs, PLF, and market share of both
IJCOMA19,2
104
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Table IV.Regression analysis
of the variables
Alliancesas a competitive
strategy
105
the airlines in general, domestic airlines in particular. The statistical tests reveal thatthe international airlines also benefited in the form of increased passenger miles, PLF,and market share when compared to other international airlines that do not have codesharing arrangements with domestic carriers. However, the extent to which aninternational airline will benefit from an alliance depends on the geographic scope ofthe agreement, the degree of operational and marketing integration between partners,and the division of revenue among partners in the code sharing routes. The controlvariable and previous code sharing was found to be not only significant but alsonegatively correlated with the independent variable, code sharing. This suggests thatairlines should form code sharing agreements earlier which would give better resultsand productivity than if formed later. This is because the effects of code sharingagreements tend to erode after a certain period of time due to other environmentalfactors and competitive scenarios in the industry.
Consistent with the Hwang and Burgers (1997) typology that emphasizes thatmultiple alliances will be more beneficial than single firm alliances, it was predicted inH2a that domestic airlines that have multiple alliances would be more able to increasetheir RPMs than airlines that have single firm alliances. As can be seen from Table IVthe F-ratio for this hypothesis is calculated to be 3.919 giving the probability of 0.002,which is significant. Similarly, the coefficient of the independent variable for thishypothesis, multiple alliances also stands at 0.003 which is significant, suggesting thatthere is a significant relationship between multiple alliances and RPMs. Hence, H2a issupported.
H2b predicts that domestic airlines will be able to increase their PLF if they havecode sharing agreement with more than one international airline instead of having codesharing agreement with only one international airline. As the regression test reveals,the probability of F-ratio is significant (0.000). Likewise, the coefficient of multiplealliances is also significant (0.004), which is the independent variable for thishypothesis. Hence, H2b is supported.
H2c predicts that domestic airlines will be able to increase their market share if theyhave code sharing agreements with multiple international carriers than airlines thathave single firm alliances. As shown in Table IV, the F-ratio for this hypothesis is 6.389giving the probability of 0.000 which is very significant. The correlation of theindependent variable for this hypothesis, multiple alliances is also significant at20.002.Therefore, H2c is supported. This result suggests that there is a positive, significantrelationship between airlines having multiple alliances and increase in market share.Based on the regression results, it can be suggested that multiple alliances betweendomestic and international airlines lead to domestic carriers capturing higher marketshare than airlines that have alliances with single firms.
In summary, H2a, H2b, and H2c are supported. As the web of multi-carriersalliances evolves into a multiplicity of agreements and negotiated agreements,many carriers now find themselves members of multiple alliances, resulting in highlycomplex network systems. Eventually, the same complex networks appear to helpincrease the RPMs, PLF, and the market share of domestic airlines.
It was predicted in H3a that domestic airlines that have more percentage of equityinvestment by international airlines will increase the RPMs more than airlines that donot have equity investment. As shown in Table IV, though the F-ratio is very significantwith the value of 3.845, the coefficient of the independent variable, equity investment is
IJCOMA19,2
106
not significant (20.005). This suggests that there is a negative correlation betweenpercentage of equity investment by international airlines in domestic carriers andincrease in RPMs of domestic airlines. Hence, H3a is not supported. This means thatdomestic airlines are unlikely to increase their RPMs simply by inviting internationalairlines to participate by equity investment.
The second dimension of H3 is the influence of equity investment by internationalcarriers in the domestic carriers that also have code sharing agreements with the former.Following the above logic, it was predicted inH3b that if international airlines have moreequity investment (in percentage) in domestic airlines, it will help the latter increase thePLF compared to other domestic airlines that do not have equity agreement, but havecode sharing agreement. As can be seen from Table I, though the F-ratio is significant(37.119), the coefficient of the independent variable, equity investment, is not significant(20.001). This suggests that there is a negative correlation between equity investmentby international airlines in domestic airlines and an increase in PLF of domestic airlines.Hence, H3b is not supported.
According to Gomes-Casseres (1993), mutual equity investment by partners or by oneof the partners will increase the market share of a firm. He concludes that this is achievedbecause both the firms’ interests are at stake and the partner who invested in equitytakes a more aggressive approach in promoting the interests of the firm in which itinvested equity. Consistent with this typology, it is predicted in H3c that domesticairlines that have more equity investment (as a percentage) from international carrierswill increase market share compared to airlines that do not have equity investment.The calculated F-ratio is significant (7.108) with the probability of 0.002. However, thecoefficient of the independent value, equity investment is not significant with the valueof 0.230 (Table IV). This suggests that there is no significant relationship between higherpercentage of equity investment by international airlines and increase in the marketshare of domestic airlines. Hence, H3c is also not supported.
According to Bleeke and Ernst (1994), there are six types of strategic alliances, onebeing the “alliance of complementary equals”. The authors define this type of allianceas the one that involves two strong and complementary partners that remain strongduring the course of the alliance. Consistent with Bleeke and Ernst’s typology,I predicted in H4a that a code sharing agreement between a large domestic and a largeinternational airline (based on market share held by each carrier in the region served)would increase the RPMs for the domestic airline because of the synergies andopportunities the large international airline brings along with it.
As per the regression test (Table IV), the calculated F-ratio for this model stood at3.969 which gave it a significant probability of 0.002. Similarly, the coefficient of theindependent variable for this hypothesis is also significant (0.003). This means thatthere is a relationship between size of the partner airlines and increase in RPMs.Therefore, H4a is supported.
H4b is focused on the load factor of domestic airlines with reference to the size of thealliance partners as independent variable and it predicted that if a domestic carrier islarge in size (on the basis of market share) and if it has code sharing agreements withlarge (on the basis of market share) international airline(s), then the domestic carrierwill be able to increase its PLF because of the synergies and opportunities the largeinternational carrier provides. Based on the regression testing, the F-ratio is calculatedto be 36.884 which is significant at 0.000 (Table IV). The coefficient of the independent
Alliancesas a competitive
strategy
107
variable for this hypothesis, large partner, is also significant (20.001), suggesting thatthere is a significant relationship between size of the partner airlines and increase inPLF. Therefore, H4b is supported.
H4c predicts that if a domestic carrier is large in size (on the basis of market share)and if it has code sharing agreement with large (on the basis of market share)international airline(s), then the domestic carrier will be able to increase its marketshare because of the synergies and opportunities the large international airline bringsalong with it. As shown in Table IV, the calculated F-ratio for this model is 7.108 whichis significant at 0.000. The coefficient of the independent variable for this hypothesis,large partners, is also significant (0.002), suggesting that there is a positive andsignificant relationship between size of the partner airlines and increase in marketshare of the domestic airlines. Therefore, H4c is supported. Hence, it can be concludedthat if both the airlines – domestic and international – are large in nature, then it maynot only result in increased number of RPMs, but will also result in increased numberof PLFs and market share.
Though it seems that H2 and H4 are inconsistent with each other, the premises onwhich H2 was developed is different than H4. H2a, H2b, and H2c predicted thata domestic airline which has alliances with more than one international airline wouldbenefit from increased RPMs, PLF, and market share. Here, the domestic airline isopting for multiple alliance arrangements because no single international airline holdsmajority of the market share in the region where a domestic airline is a major operator.
However, H4a, H4b, and H4c were developed based on the premises that there isa large domestic and a large international airline available to form the alliance. It alsofactored in the availability of smaller airlines (both domestic and international carriers)to compete against the alliance. In this scenario, the hypothesized variables were testedand supported by the statistical tests, i.e. code sharing arrangement between a largedomestic airline and a large international carrier would result in increased RPMs, PLF,and market share.
H5a predicts that if one of the partners is weak or unequal in size, then the domesticairline will not be able to increase the RPMs. As shown in Table IV, the F-ratio for thishypothesis is 3.853 which gave the probability of 0.002 which is very significant.Similarly, the coefficient of the independent variable for this hypothesis, unequalpartners, is 0.005 which is also significant. Therefore, this result suggests that there isa significant relationship between the size of the partners and increase in RPMs.Therefore, H5a is supported.
H5b predicts that code sharing agreement between small or unequal partners (bothdomestic and international) will not result in increased PLF for the domestic airlinesbecause each partner have their own synergies and strengths that cannot complementeach other. As shown in Table IV, the F-ratio for this hypothesis is 37.726 which gavethe probability of 0.000 which is very significant. Likewise, the coefficient of theindependent variable for this hypothesis, unequal partners is also significant (0.004).This result suggests that there is a significant relationship between the size of thepartners and increase in PLF. Therefore, H5b is supported.
In a similar pattern discussed earlier, none of the control variables were found to besignificant, suggesting that there were no positive correlation between weak orunequal partners. On the other hand, it was proved that if the one of the partners in theairline alliances is unequal or weak, then that would negatively affect the alliance
IJCOMA19,2
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outcome by not resulting in increased RPMs, increased PLFs, and increased marketshare, despite the partners having previous code sharing experience and generalbusiness experience.
When a weak or unequal domestic airline has code sharing agreements with aninternational airline that services the same region as the domestic airline, the alliancemay not produce fruitful outcomes. This could be because a large international airlineprefers a code sharing agreement with an available large domestic carrier so that boththe partners can feed traffic to each other. Following this logic, it was predicted in H5cthat alliances between weak or unequal carriers will not result in increased market sharefor the domestic airlines because each partner has their own synergies and strengthsthat cannot complement each other. This hypothesis was tested using the variable,unequal partners which was derived from the actual market share controlled by bothdomestic and international airlines.
As shown in Table IV, the calculated F-ratio for this hypothesis is 7.117 and theprobability is 0.000 which is significant. Moreover, the coefficient of the independentvariable for this hypothesis, unequal partners, is also significant (0.013). This suggeststhat there is a significant relationship between the size of the partners (unequal) andincrease in market share. Therefore, H5c is supported. The control variable, previouscode sharing experience has negative coefficient in this hypothesis. This meansthat the earlier the code sharing agreements between domestic and internationalairlines, the better the benefits for the domestic airlines by way of increased marketshare.
As seen consistently through this particular data analysis, market share isa prominent dependent variable in a code sharing agreement. If one of the alliancepartners is weak or unequal then the domestic airline will not be able to increase themarket share. So care must be taken before a domestic airline decides to align withan international airline that is weak or unequal in size with regard to the marketshare.
Findings, recommendations, and limitationsThe objective of this study was to investigate the effects of code sharing on RPMs,PLF, and the market share of domestic airlines when they have code sharingagreements with international carriers. The specific reason for focusing on domesticairlines was discussed earlier in this paper, i.e. while many studies supported thepositive (and negative) influences of code sharing on the international airlines, researchon domestic airlines were few. Hence, the focus of this paper is how domestic airlinesbenefit exclusively from the alliances, though the results also suggest thatinternational airlines do benefit along with domestic airlines. The secondaryobjective of this study is to analyze the effects of multiple alliances, equity investmentby international carriers in the alliance partner’s firm, size of the partners (large), andunequal partner size on the dependent variables of this research study – RPMs, PLF,and the market share of domestic airlines.
The regression results of H1 supported our premise that code sharing agreementsbetween a domestic and international airline will benefit the former by way ofincreased RPMs, PLF, and marker share. However, the coefficients of the hypothesizedvariables suggested that the initial gains achieved by the domestic airlines by way ofincreased RPMs start to erode in the long run. Thus, a domestic airline must form
Alliancesas a competitive
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109
a code sharing agreement with an international airline at the earliest, so as to get theinitial increase in RPMs.
Following the same logic that appeared in H1a, H1b was focused on the effect ofcode sharing on the load factor of the domestic airlines. As discussed earlier, thishypothesis was also supported because the test results were found to be significant.The results reveal that the domestic airlines will be able to increase their PLF if theyform code sharing agreements with international carriers. This particular result is veryimportant to any airline, because the load factor is an important mechanism to measurean airline’s productivity. The higher the load factor, the higher the profitability of theairline will be. Since this research study suggested that the domestic airlines wouldbe able to increase their load factor by forming a code sharing agreement withinternational carriers, code sharing must be used as one of the strategic tools not onlyto increase the RPMs, but also to increase the load factor which will eventually lead tobetter performance and productivity.
The effect of code sharing on the market share of domestic airlines is explicit andconsistent throughout this research study. The regression analysis supported H1cwhich posited that code sharing will increase the market share for domestic airlines ifthey have strategic alliance with international airlines. As discussed earlier, codesharing agreements between domestic and international airlines not only resulted inincreased RPMs and PLF for domestic airlines, but also increased the market share ofdomestic airlines. This particular finding will help the domestic airlines to adopt thesame strategy that Japanese multinational corporations follow when they venture intoforeign markets. Japanese companies focus on capturing market share rather than theprofitability of the product itself when launching a new product or entering into a newmarket. In the long run, this helps the company to entrench itself strongly in themarket and so the company slowly turns this dominant position into profitability of theproduct, as its competitors are way behind in market share. Using the same strategy,domestic airlines can first increase the market share and, thereafter, they will be able toincrease their RPMs and the load factor.
The second dimension in the code sharing is the multiple alliances betweendomestic and international airlines. Multiple alliances refer to an airline having morethan one code sharing agreement with international carriers. As discussed earlier,multiple alliances did increase the RPMs, load factor, and the market share of domesticairlines. Therefore, domestic airlines should have multiple alliances with internationalcarriers so that they can achieve the optimal productivity through increased RPMs,PLFs, and market share.
The third factor in this sequence of hypotheses is equity investment byinternational carriers in domestic airlines. The relationship between equity investmentand its influence on the performance of the targeted firm is always an interesting topicexplored by both the academic researchers and practitioners. Consistent with thetypology that corroborates the view that investing firms will have more commitmentand interest in the targeted firms, the next set of hypotheses were formed. H3a, H3b,and H3c predicted that equity investment by international carriers would increase theRPMs, PLF, and market share of the domestic airlines. However, as discussed earlier,the regression results did not support all the three variables, That means equityinvestment by international carriers in domestic airlines may not result in increasedRPMs and load factor and market share.
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The fourth dimension in the hypothesis is size of the partners – both domestic andinternational airlines. As discussed earlier, this classification of the alliance patternwas adopted from the works of Bleek and Ernst, which focused on alliances betweenstrong or large alliance partners. Following this logic, the next set hypotheses wasformed and they predicted that code sharing agreements between large domestic andlarge international airlines would result in increased RPMs, load factor, and marketshare.
The interesting findings in this particular section was the influence of the large size ofthe alliance partners on all the three dependent variables; RPMs, PLF, and the marketshare. Therefore, we can conclude that if both the airlines are large enough and theyformed code sharing agreements, then it may result in increased RPMs, PLFs, andmarket share for the domestic airlines. Only in this section, the load factor issignificantly influenced by the independent variable; in this case, size of the partners.This could be because the independent variable, size of the partners, is a dummyvariable and derived from the actual market share of both the alliance partners. So, wecan construe that both the airlines control a major portion of market share that musthave brought the increased traffic that would have ultimately resulted in increased PLF.
The last dimension in the hypothesis is unequal size or weak partners. Following thesame logic as the equal partners described in the above paragraph, H5a, H5b, and H5cwere formed which predicted that if one of the airlines is unequal in size or even weak onthe basis of market share, then the domestic airlines will not be able to increase theRPMs, load factor, and the market share, respectively. As expected, the unequal or weakpartners did not influence the dependent variables.
One of the important findings of this study is the significant influence of code sharingon the market share of the domestic airlines which has direct managerial implications onthe airline management. As seen consistently in the analysis chapter, every form of codesharing (multiple alliances, large partners, and unequal partners) influences the marketshare significantly, except equity investment. The domestic airlines can significantlyincrease the market share if they can form code sharing agreements with internationalcarriers which will eventually result in increased RPMs and load factor. This is becausewhichever airline controls the market share usually transports passengers more than itsnearest competitor in a region which will ultimately benefit it by way of increased RPMsand load factor.
However, consolidating the market share in the airline market may attract anti-trustor regulatory actions from the governments. As with mergers and other forms ofagreements between carriers, code sharing agreements have the potential to besignificantly anti-competitive, because of the consolidation taking place in the domesticairline market which will eventually limit the passengers’ choice of selecting routes.As long as the domestic airlines create new services, improve existing services, andlower costs and increase efficiency for the benefit of the traveling public, thegovernments may not interfere with the operations of the airlines. Just like any othermarketing alliance, domestic airlines must take a long-term view, match firms’ culturesand styles when forming alliances, define the measures for success, insist on andpractice open communication, and pursue multiple alliances if they intend to succeed inthe market place. Also, the alliance would be stronger if the benefits were distributed in abalanced way to all partners of an alliance. This would ensure the sustainability ofalliance as strategic tool.
Alliancesas a competitive
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111
Limitations and scope for further researchCollection of data for this research involved a complex set of procedures. There hasbeen no systematic collection of data by international or national agencies that wouldenable a thorough analysis in relation to the impact of domestic airlines. The lack ofpublicly available and reliable data, except contacting the individual airlinesthemselves, makes it difficult to conduct a comprehensive analysis of the impact ofthese alliances and, in particular, the long-term effects of alliances on the domesticairline industry. The recent growth in airline alliances, and the likely continuation ofthis trend, makes it imperative that there should be a better process for collecting dataand monitoring the effects of code sharing agreements. Better data would enable theresearchers to more fully assess the benefits and costs of airline alliances and promotea better understanding of the circumstances under which alliances may affectcompetition and enhance the ability of airlines to exercise their market power. Thiswould provide a better foundation for an analysis of the effectiveness of existingpolicies in targeting potential anti-competitive behavior and market power createdthrough airline alliances.
In some cases, where the national governments own a majority stake in nationalflag carriers, the governments heavily influence the flag carriers by way of dictatingwith whom the national carriers must have alliance. Given these circumstances, thenational flag carriers cannot have code sharing agreements with the best possibleinternational airline or the airline of their choice. Therefore, a longitudinal study canbe done focusing on these issues which would enhance our knowledge inunderstanding the cross cultural airline alliances. Future studies on code sharingpractices in the domestic airline industry should include the routes in the Africansubcontinent as this study did not include this region. The recent worldwidederegulation of the airline industry fueled startup carriers which had never existedearlier. As the majority of these airlines came into being only after 2000, futureresearch study including these carriers would be appropriate.
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Further reading
Vernon, R. (1991),TheManager in the International Economy, Prentice-Hall, Englewood Cliffs, NJ.
Corresponding authorJames Rajasekar can be contacted at: [email protected]
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