Introduction
Mergers and acquisitions refer has been described as a process whereby two or more firms come together in other to benefit from an increase in size. (Moles and Terry, 1997).
A consideration is paid to a subordinate firm by the dominant firm to the shareholders who give up their interest in the firm in exchange for the consideration received. (Moles and Terry, 1997). A merger is technically referred to as “uniting of interest” which is a fusion between two or more companies of roughly equal significance. In this case, two or more companies agree to transfer their capital towards forming a new company. An example could be two banks of equal size fuse decide to fuse their assets towards the formation of a larger bank. (Moles and Terry, 1997). In an acquisition, the acquired firm (the subordinate firm) is referred to as the target the acquiring firm is referred to as the bidder (the dominant firm) while. (Myers and Brealey, 2002).
In general, the hypothesis is that following an acquisition, shareholders of both the bidder and the target realize an increase in wealth, which is reflected in an increase in their share prices. Merged companies are always assumed to benefit from an increase in efficiency of operations after the merger. For example, Iqbal and Shetty (1995: p. 58) Bidders use corporate acquisitions as a means of gaining control of the resources of the target and to in turn implement value-maximizing strategies (Iqbal and Shetty 1995: p. 58). Merger companies benefit from operational strategies like; increased market power, improved production techniques, economies of scale, etc. (Iqbal and Shetty, 1995; Brealey & Myers, 2002). A lot of small firms may suffer from lack of ability required to produce and market their product in a large scale, though they may have a unique product. (Brealey and Myers, 2002). After a take over, such firms can take advantage of engineering and marketing provided by the larger company to make use of the uniqueness of their product and produce on a larger scale, therefore creating a competitive advantage for the company. It may be faster, cheaper and more convenient to amalgamate with a larger firm that already has the engineering and sales ability than for the small firm to develop engineering and sales talent from scratch, (Brealey and Myers, 2002). Merged firm become worth more than when they operate separately since each of the firms has something that the other does not have and can therefore combine their resources (complementary resources). In other words, mergers indicate that 1+1 could be more than 2. Takeovers also occur because management’s rewards are tied to the size of the company. Management of the firm bidding belief that taking over another firm will subsequently lead to an increase in size and thus an increase in compensation and other economies of scale. (Firth, 1997).
In order to determine the operational consequences of the mergers, we are using Air France-KLM and a case study. We are going to be looking at how the merger of these two airlines has resulting to operational changes by using the AIR-CO model. This model will show us how to evaluate the difference before the merer and after the merger.
Literature review
Airline organisations go as far back as 1919 immediately after the First World War and is considered today as one of the largest industries in the world (combined with leisure) taking about 11% of consumer income and employs one-ninth of the work force (about 29million jobs) (Hanlon 2007; Air Transport Action Group, 2005)
There has been protest about increasing protest against expanding airports. Surprisingly, airlines contribute just 4% of the total Carbon dioxide compared to 34% by power generators and 20% by road transport (Hanlon 2007)
The phenomenon of domestic airline mergers started in the 1980s which reduced domestic competition creating room for economic literatures (Clougherty, 2002)There were mainly two respond as to why airlines would want to merge; the first being to gain efficiency by reducing operating cost (supported by Levine and Brueckner) and the second theory was airlines merge to gain market power and raise fares (supported by U.S. General Accounting Office, 1988, Borenstein, Werden and Kim) (Clougherty, 2002).
To justify that fact that airlines merge to gain efficiency, a data provided by Bailey, Graham and Kaplan (1985) shows an increase in hubbing in the early eighties at Dallas St Worth from 11.2% in 1979 to 28% in 1983 as a result of passengers changing hubs to their ultimate destination (Brueckner and Spiller, 1991). On the other hand if two airlines merge and realise an increase in congestion, it might affect them negatively if a new airline starts operating in the market as passengers will switch to the new airline especially if the operating airline was a monopoly (Brueckner and Spiller, 1991). Mergers continue at a rapid pace and an important factor for consolidation has been to remove entry restrictions on geographical and product market that are generally believed to affect operating efficiency and profitability (Houston et al 2001). Mergers of industries can be attributed to the fact of changing technology which has completely changed industries like the airline industry and the banking sector, making these industries to provide a wider range of services to reach to customers across the globe. (Houston et al, 2001).
Several mergers between airlines has led to the concentration at selected airports (Brueckner and Spiller, 1991). This can be seen in merger of TWA-Ozark where TWA already controlled 85% of the departures at St Louis Airport and Ozark 79% at Minneapolis St Paul and therefore cause the protest of Antitrust Devision of US department of Jutice to disapprove the deal because of the power they will gain and also to fight anti competitive effects (Brueckner and Spiller, 1991).
Many airports today are actually constantly approaching their capacity limit as air traffic increase to an average of 5% per annum and also high pressure from environmental safety groups
Also mergers and acquisitions in banks have been significantly influenced by creating the single market for financial services, as well as introducing the euro evident by increasing bank mergers and acquisitions following the introduction of the European Monetary Union. (Altunbas and Ibáñez, 2004). The European financial sector has been reshaped by banks merging in the EU and this is expected to continue for years (Altunbas and Ibáñez, 2004).
In successful corporate in is suggested that takeovers shareholders of the target company benefit from positive abnormal returns witnessing an abnormal share price increase of 20% from merger activities and 30% in tender offers. Bidding firms on the other hand realise no change in returns in mergers but a positive abnormal returns in tender offers (Jensen and Ruback, 2003). Caruso and Palmucci (2008) in a recent study argued that the market reaction to a mergers or an acquisitions is not captured by previous studies because these studies consider the announcement date of the merger as the event date which is not the case because event date may not accurately capture all market reaction in a less efficient market due to information being leaked out before the announcement date.
Event Study Analysis
The event study methodology is used to investigate the reaction of investors to the announcement of mergers in most European countries. The main assumption behind the event study methodology is that stock markets are sufficiently efficient enough to evaluate the impact of new information ( in this case, the announcement of a bank merger) on expected future profits of the merging banks. In general, the methodology involves five main steps including (Dasgupta et al., 1997): (1) identification of the event of interest (bank merger announcement); (2) selection of the sample set of firms to include in the analysis; (3) prediction of a “normal” (or expected return) within the event window in the absence of he event; (4) estimation of the abnormal return within the event window, where the abnormal return is defined as the difference between the expected (or predicted) return and the actual returns; and (5) testing whether the abnormal returns is statistically different from zero. Several approaches can be employed t estimate the expected return. These include the single-index model (constant return model), the market model and the capital asset pricing model. In this paper we employ the market model. According to the market model developed by Fama et al. (1969) there is a linear relationship between the return on any security and the return on the market portfolio (or market index) that can be expressed as follows (Dasgupta et al., 1997):
(1)
Where is the return on the market portfolio index at day t; and are ordinary least squares (OLS) parameters from an estimation period preceding the event window and ranging from t =+31 to t= -9 (Brown and Warner, 1985) cited in Meschi and Metais (2006) and Miyajima and Yafeh (2007); t is a time index, i = 1, 2, 3,…N, stands for security, is the expected return on security i, during period t assuming that there is no merger announcement. The abnormal return on the bank given that the bank merges is given by:
(2)
Substituting for the expected return calculated in equation (2) in (1) we can now get an expression for the abnormal return as follows:
(3)
The abnormal returns are usually hypothesised to be equal to zero. The null hypothesis can thus be stated as follows:
Against the alternative
We test the null hypothesis at the 5 percent level of significance. The abnormal returns will therefore be jointly determined with a conditional mean of zero and a conditional variance (Dasgupta et al., 1997):
(4)
Where L is the estimation period length (that is, the number of days used for estimation) and is the mean return on the market portfolio. As the estimation period (L) increases the conditional variance of the abnormal returns [] approaches the variance of the residuals ().
The abnormal return can be estimated for each individual bank at each point in time. In order to draw a general conclusion about the abnormal return observations for the different banks it is necessary to aggregate the abnormal returns. For any given number of banks, the sampled aggregated abnormal returns (AARt) at each time instant t within the event window is computed as follows:
(5)
For a large estimation window L, the variance is given by
(6)
To test for the impact persistence of the impact of the event on a particular bank over a period, the abnormal returns for the given bank can be added to obtain the cumulative abnormal returns (CARi(T1, T2) over the period (T2-T1) as follows:
(7)
Where Ta≤T1<t< T2≤Tb€ event window, and Ta and Tb are the lower and upper limits of the event window, respectively. Asymptotically, as L becomes larger and larger, the variance of the cumulative abnormal returns on bank i becomes:
(8)
We state the null hypothesis that the average cumulative abnormal return is zero and formulate the a Z-test for the hypothesis as follows:
Which reads the cumulative abnormal return on bank i is normally distributed with mean 0 and variance, ;
(9)
We can also perform an aggregation of the cumulative abnormal returns across time and across all banks. The average cumulative abnormal return is defined as:
(10)
Where N is the number of banks. The variance is given by
(11)
A null hypothesis is also stated that the average cumulative abnormal return is equal to zero. The following Z test is used to test this hypothesis:
(12)
The observed or actual return for each firm will be estimated using the daily close share prices of each of the firms under study. That is:
(13)
(14)
(Brealey and Myers, 2002, Ross et al, 1999).
Where Pi,t is the share price of firm i, at day t and Pi,t-1 is the share price of firm i at day t-1.
However, is better to use the continuously compounded returns since they exhibit better statistical properties. (Bodie et al, 2005). The continuously compounded return is calculated as follows:
(15)
The event study methodology has been employed in numerous studies of different types of events. Meschi and Metais (2006) for example, used it to study the abnormal returns arising from the announcement of a merger. Miyajima and Yafeh (2007) used it to study the impact of the Japanese Banking crises on non-financial firms. However, a number of problems have been identified with the methodology. The performance of the company is often gauged on a benchmark index. Sweeney (1991) suggests that event studies using mean adjustment typically assume that significant abnormal returns occur as a result of the event window rates of return being higher, on average than those predicted by the underlying asset pricing model that the researcher has employed. An alternative explanation for significant abnormal returns is that the benchmark’s period mean may be lower than the one predicted by the pricing model. This indicates that there are “two sources of randomness” that can explain abnormal returns. Sweeney suggest that despite the presence of these two sources of randomness, usual cumulative abnormal return (CAR) event studies take account of only one source of randomness thereby overstating the significance levels. The case is more complicated when the market model is employed. To mitigate these effect CAR studies employ formulas that correctly adjust the standard error for any single abnormal return to capture the fact that the market model parameters used are subject to estimation error. No adjustment is necessary for one-period windows. However for longer windows the market model fails to take into consideration the fact that the estimation errors are correlated across abnormal returns in the window. Sweeney (1991) suggests that for a long benchmark period and a window that is substantial relative to the benchmark period, the adjustment will be approximately the same like in the mean-adjustment case.
Types of mergers
There are three main types of mergers known as Horizontal merger, Vertical mergers and conglomerate.
Horizontal mergers
This is the type of merger that occurs between two companies producing similar goods and is mostly at the same stage of production. Examples of such mergers include (Moles and Terry, 1997). This is the most common type of mergers these days especially in the banking sector.
Vertical integration
This occurs when a company mergers with another company of a different level of production of its production path (Moles and Terry, 1997). Forward vertical integration is when a company at a lower stage of production merges with s company of a higher stage of product while backward vertical intergratio is when a company at a higher stage of production merges with another at a lower stage of production (Moles and Terry, 1997).
Conglomerate
These are mergers where a company merges with another company that does not produce or offer the same product as it does (Moles and Terry, 1997). This type of merger is mostly for the financial benefits rather than synergy as with the other mergers.
Reasons for mergers
Most companies merge to gain Synergy coupled with other factors that is they merge to for greater performance than when they are on their own.
– The well knows reason for a merger is for the company to gain economies of large. Economies of scale are the advantages a company will enjoy as a result of increase in its size by causing average cost to decline (Moles and Terry, 1997).
Internal economies of scale are the advantages a firm within an organization will enjoy as a result of in crease in size or a merger (Moles and Terry, 1997). Internal economies o scale includes making use of larger and more efficient machinery or technology, advantage of as a result of bulk purchase, therefore reducing costs and the ease to obtain loan when they merge (Moles and Terry, 1997).
Company’s overview
KLM
KLM (Koninklijke Luchtvaart Maatschappij; in Dutch, Royal Aviation Company; English translation: Royal Dutch Airlines) is Royal Dutch Airlines and worldwide company based in the Netherlands that was founded on the 7th of October 1919 with its first office opened in Heerengracht, The Hague (present headquarter now Amstelveen) and is the oldest airline company still operating under its original name (KLM.com, January 2009)
In 1920, KLM’s first pilot, Jerry Shaw, flew from London Croydon to Schiphol and in May 1924, it flew its first intercontinental flight, from Amsterdam to Batavia and in 1934, its first transatlantic flight, from Amsterdam to Curacao (KLM.com, February 2009)
Until the outbreak of the Second World War; KLM started a continuous service from Amsterdam to Batavia in 1929, which made it the world’s longest-distance scheduled service at that time (KLM.com, February 2009)
The airline was closed during the Second World War and only resumed service in 1945 and from 1946 to 1960, the airline started flying to destinations like New York and Tokyo. (KLM.com, February 2009)
Over a certain period, KLM acquired some interests in companies and also merged with others to create a worldwide network. (KLM.com, February 2009)
In July 1989, the company acquired a 20% interest in US Northwest Airlines; two year later, they merged NLM Cityhopper (founded in 1966) and NetherLines to create KLM cityhopper and in same year increased its interest in charter carrier Transavia from 40% to 80%.
Totady, the company serves over 23 million passengers a year and employs 33,000 from 78 countries of which 28.000 work in the Netherlands and 5,000 in other parts of the world with an annual over EURO 8.5 billion from revenue and other income.
KLM today also owns 100% interest in transavia.com, 50% interest in Martinair
Holland and 26% interest in Kenya Airways.
Air France
Air France was founded in 1933 from a merger of four leading French transport companies with 259 air crafts and servicing 38,000 km in all. The Paris New York rout was born in 1946 and the airline moved to a new air port at Paris-Charles de Gaulle in 1974
In the year 1976 the Concorde was launched flying over 200km per hour. Air France and UTA merged in 1992 making Air France on of the largest transport companies in the world at that time and it got listed in the stock exchange in 1999. Air France formed the Sky Team Alliance together with Delta, Aeromexico and Korea air.
Air France – KLM Merger
Since the merger of KLM and air France in 2004, Air France-KLM has become the world’s largest airline partnership[1]
KLM together with its partner Northwest Airlines officially joint SkyTeam alliance after its merger with Air France on the 13th of September 2004 which brought about siginifant implication for the airline as well as their competitors and potential to redistribute traffic amongst their major air ports (Jan Veldhuis, 2005; Dennis, 2004)
AIR-CO Model
In order to illustrate the consequences of ther merger between Air France and KLM, we will use the AIR-CO model. We will be looking at how this model is help in the two main phases of the merger of these two airline companies known as the network intergration phase and the Network realisation phase (Veldhuis, 2005). This model also shows the effect of mergers on passengers.
This model mostly describes the compation between alternative routs with each roust consisting of different components and moves away from competition between airlines and airports giving us the best picture of the operational consequences (Veldhuis, 2005).
To better illustrate this model, we are going to consider trips between Northwest Europe and another destination in the world as shown in the example below that compares trips from Utrecht to Singapore showing alternatives.
Table 1
Access Air-port | Conn. Type | Alliance | Air-line(s) from access airport | Hub(s) | Frequency | Business trips | Leisure trips | ||
| Total gen. Costs (€) | Prob.(%) | Total gen. Costs (€) | Prob. (%) | |||||
AMS | Direct | STAR | SQ | — | 4 | 1338 | 17 | 770 | 4 |
AMS | Direct | Wings | KL | — | 7 | 1302 | 41 | 763 | 8 |
FRA | Direct | STAR | LH,SQ | — | 21 | 1676 | 4 | 939 | 1 |
AMS | Indirect | STAR | LH,BD | FRA, LHR | 29 | 1624 | 9 | 781 | 24 |
AMS | Indirect | OneWorld | BA | LHR | 10 | 1650 | 3 | 786 | 8 |
AMS | Indirect | SkyTeam | AF | CDG | 6 | 1666 | 1 | 789 | 4 |
AMS | Indirect | Wings | KL,MH | KUL | 9 | 1611 | 3 | 778 | 8 |
BRU | Indirect | STAR | LH,BD | FRA,LHR | 29 | 1832 | 2 | 864 | 4 |
DUS | Indirect | STAR | LH,BD | FRA,LHR | 27 | 1824 | 1 | 869 | 4 |
Other route alternatives | 7 | 9 | |||||||
Total effective demand (%) | 88 | 74 | |||||||
No travel (hidden demand) (%) | 12 | 26 | |||||||
Total potential demand (%) | 100 | 100 |
Source Veldhuis, 2005Full-size table
This Case study is going to be limited to markets between the Northwest Europe hinterland Benelux, Northern France (including Île-de-France) and the Western part of Germany (Ruhrgebiet and Rheinland-Pfalz) and Singapore because these are the most affect areas by this merger
26,000 return strips a year to Singapore are estimated to occure before the merger takes place and use all four alliance competitors as shown on the table ( Veldhuis, 2005Full-size table
)
Total demand (*1000) | 260 | ||
By Airport: | By Alliance | ||
AMS Amsterdam | 67 | STAR | 151 |
BRU Brussels | 42 | OneWorld | 33 |
CDG Paris | 62 | SkyTeam | 30 |
DUS Düsseldorf | 41 | Wings | 45 |
FRA Frankfurt | 41 | ||
Other airports | 7 | By Region | |
Netherlands | 64 | ||
Belgium | 40 | ||
Germany | 90 | ||
France | 67 | ||
Source Veldhuis, 2005Full-size table
This model will only look at those trips between the hinterland and Singapore.
1) Indirect frequencies between Amsterdam/Paris and Singapore, before and after integration
From | Via | To | Before integration | After integration | ||||
Frequency to hub | Frequency from hub | Indirect frequency | Frequency to hub | Frequency from hub | Indirect frequency | |||
AMS | CDG | SIN | 46 | 7 | 6.1 | 94 | 7 | 6.5 |
AMS | ICN | SIN | 1 | 7 | 0.9 | 7 | 7 | 3.5 |
AMS | KUL | SIN | 13 | 35 | 9.5 | 13 | 35 | 9.5 |
Total AMS-SIN | 16.5 | 19.5 | ||||||
CDG | AMS | SIN | 49 | 7 | 6.1 | 95 | 7 | 6.5 |
CDG | ICN | SIN | 14 | 7 | 4.7 | 14 | 7 | 4.7 |
CDG | KUL | SIN | 4 | 35 | 3.6 | 4 | 35 | 3.6 |
Total CDG-SIN | 14.4 | 14.8 |
Source: Jan Veldhuis (2005)
It can be seen from the table that only 46 Air France-flights to Paris were connected to the 7 AF-flights out of Paris to Singapore before the company merged with an indirect frequency of 6.1 weeks for Air France flight leaving Amsterdam through Paris to Singapore (Veldhuis, 2005). This increased to a frequency of 6.5 weeks of KLM flights connecting to Air France flights therefore causing a marginal increase and an additional 48 KLM flights to Paris. Before the merger, there was only one flight leaving Amsterdam every week to Seoul to Singapore, but this has been increased to seven flight after the merger and has increased the frequency from 0.9 to 3.5 (Veldhuis, 2005).
After the merger of the Air France-KLM, three a three alliance system started offering fights from the hinterland to Singapore as opposed to the four alliance systems before the merger (Veldhuis, 2005). The following table shows a before and after summary of the direct and indirect frequency shares of the alliances and expected increase in airfares due to reduced level of competition (Veldhuis, 2005).
Before integration | After integration | Airfare Increase (%) | ||||||
STAR | One World | Sky Team | Wings | STAR | One World | Sky Team | ||
AMS Amsterdam | 40 | 7 | 3 | 50 | 40 | 7 | 53 | 0.3 |
BRU Brussels | 56 | 20 | 12 | 12 | 56 | 20 | 24 | 0.2 |
DUS Düsseldorf | 56 | 19 | 12 | 13 | 56 | 19 | 25 | 0.2 |
FRA Frankfurt | 90 | 4 | 2 | 3 | 90 | 4 | 6 | 0.0 |
CDG Paris | 50 | 7 | 39 | 4 | 50 | 7 | 43 | 0.2 |
Source Veldhuis, 2005Full-size table
From the table we can see that Sky Team has dominated in Amsterdam and also also realised some increase in Paris and other areas. The faire also increase by 0.3% in Amsterdam and 0.2% in Paris. This reduction in competition has affected the rout to Singapore the least and therefore is not reflected on the table above (Veldhuis, 2005).Full-size table
The merger of Air France and KLM has affected the alliance on a significantly positive level with demand increasing n the hinterland from 76,000 to 80,000 passenger trips on the Singapore route as shown on the table below (Veldhuis, 2005).
Before integration (1000) | Increase (1000) | Increase (%) | After integration (1000) | |
STAR Alliance | 151 | −3 | −2.1 | 148 |
OneWorld | 33 | −1 | −2.5 | 32 |
SkyTeam+Wings | 76 | 4 | 5.2 | 80 |
Total | 260 | 0 | 0.0 | 260 |
Source Veldhuis, 2005Full-size table
The load factors increased from 1 to 1.5 percentage points as a result of increase in passengers causing an average of 5 passenger per flight with the same 14 weekly flights (Veldhuis, 2005). The hinterland did not experience any increase in traffic even after the merger of the company, but still realised an increase in passengers of 4,000 while other alliances have their passengers decrease by a collective 4,000 (SAR Alliance by 3,000 and OneWorld by 1,000) (Veldhuis, 2005).
As a result of increase in passengers, merger has realised an increase in revenue. The following table shows revenue before and after the merger and the impact on all three major alliances.
Alliances | Before integration (€million) | Increase (€million) | Increase (%) | After integration (€million) |
STAR Alliance | 138 | −2 | −1.7 | 136 |
One World | 26 | −1 | −2.1 | 25 |
Sky Team+Wings | 72 | 3 | 4.1 | 75 |
Total | 236 | 0 | 0.1 | 236 |
Source Veldhuis, 2005Full-size table
We can see from the table that Sky Team has increased its revenue from EURO 72million to EURO75million, that is and percentage increase of 4% despite the fact that fares were increased. This increase in revenue is mostly as a result of increase in direct flights to destinations and improving indirect connections(Veldhuis, 2005). As indicated earlier, the service levels of direct connections are unchanged. Fares for direct travel destinations are slightly lover and have not been changed resulting to a small increase in the revenue as a whole (Veldhuis, 2005).
The merger between these two airlines also had an impact on airports at the hinterland. This can be seen on the table below.
Before integration (1000) | Increase (1000) | Increase (%) | After integration (1000) | |
AMS Amsterdam | 67 | 1 | 1.2 | 68 |
BRU Brussels | 42 | −1 | −1.5 | 41 |
CDG Paris | 62 | 0 | 0.0 | 62 |
DUS Düsseldorf | 41 | −1 | −1.3 | 41 |
FRA Frankfurt | 41 | 0 | 0.8 | 42 |
Other airports | 7 | 0 | 0.5 | 7 |
Total | 260 | 0 | 0.0 | 260 |
Source Veldhuis, 2005Full-size table
The most significant changes of the Sky Team are those that occurre in Amsterdam and Paris as seen on the table above, with Amsterdam having a traffic increase of 1.2% (from 67,000 to 68,000) and Paris has no increase in traffic(Veldhuis, 2005). The reason for this changes was illustrated in table one where value added due to the merger was limited in Paris but was greater in Amsterdam which resulted to the increase of 1.2% in O/D traffic to Singapore though this was as a result of increase users of the indirect rout (Veldhuis, 2005).Frankfurt also had a significant increase in traffic of 0.8% as shown on the table above. Though there was not improvement in the services at Frankfurt, the explaination for this is that, airfares at Frankfurt were negligible and insignificant compared to that in Amsterdam and other bases (Veldhuis, 2005).
The Final impact is that on the passengers which are neglected at the early stages of the merger but still got some effects (Veldhuis, 2005). The positive effect here is the increase in indirect flights from Schiphol , and therefore passenger using this airport and are concentrated on at the Dutch part of the hinterland benefit from such service which is significant to them (Veldhuis, 2005).
The main negative effect this integration has had on passengers in the increase in airfares which came as a result on the Sky Team dominating the market (Veldhuis, 2005). This increase in airfare occurred at all airports except Frankfort and large in Amsterdam (Veldhuis, 2005). This confirm the second phenomenon of why companies meger, stating they merger to gain market power and increase fare prices. The table below summarises the positive and negative effect of this merger and how they balance each other especially the Singapore rout (Veldhuis, 2005).
Passengers (1000) | ||||||
Potential Demand | Effective Demand | Consumer surplus | ||||
Before Integration | Increase | Increase (%) | After Integration | Incr. €/PD | ||
Amsterdam | 31 | 24 | 0 | 0.2 | 24 | 0.34 |
North/Holland | 4 | 3 | 0 | 0.2 | 3 | 0.26 |
Utrecht | 8 | 6 | 0 | 0.2 | 6 | 0.22 |
S.Holland/Zeeland | 17 | 13 | 0 | 0.2 | 13 | 0.16 |
North East NL | 3 | 2 | 0 | 0.2 | 2 | 0.25 |
Gelderland | 7 | 5 | 0 | 0.1 | 5 | 0.15 |
North Brabant | 9 | 6 | 0 | 0.1 | 6 | 0.09 |
Limburg | 7 | 5 | 0 | −0.1 | 5 | −0.12 |
Flanders | 11 | 8 | 0 | −0.1 | 8 | −0.27 |
Brabant | 34 | 26 | 0 | −0.1 | 26 | −0.31 |
North East Belg. | 5 | 3 | 0 | −0.1 | 3 | −0.16 |
Wallonie/Luxemb | 3 | 2 | 0 | −0.1 | 2 | −0.25 |
NR Westfalen | 91 | 68 | 0 | −0.1 | 68 | −0.09 |
Rheinland-Pfalz | 31 | 22 | 0 | 0.1 | 22 | 0.14 |
North West France | 13 | 10 | 0 | −0.1 | 10 | −0.39 |
Île de France | 64 | 49 | 0 | 0.0 | 49 | −0.28 |
North East France | 13 | 8 | 0 | −0.1 | 8 | −0.25 |
Total | 350 | 260 | 0 | 0.0 | 260 | −0.08 |
Source Veldhuis, 2005Full-size table
The effect of the merger has been positive but small in the Dutch hinterland even without the integration of network. While demand remain the same or decreases in other parts of the hinterland as shown on the table above, the Netherlands has and increase in traffic of 0.2% as a result of improved services for indirect flights being stronger than fare increase in Amsterdam (Veldhuis, 2005). This affected consumer behaviour and consumer surplus in different regions which were small but positive in The Netherlands (EURO 0.34 per Passenger in Amsterdam Region) but Negative in other regions. (decrease of € 0.28 per passenger in the Parisian Île-de-France region) (Veldhuis, 2005).
From 2010 the airline will have no commitment with the Dutch state and therefore will have the complete right to make adjustments to its network (Veldhuis, 2005).
The airline has a combined 14 weekly flights leaving Amsterdam and Paris respectively and they could be allocated to either Amsterdam or Paris therefore leaving on of the hubs with no direct flights to Paris (Veldhuis, 2005).
– Implication in Randstad area (i.e.The North-western part of The Netherlands, including the Amsterdam and Rotterdam areas)
The total transportation of return flights by passengers per year between Randstad and Singapore area amount to 48,000 and can be seen in the table below (Veldhuis, 2005).
Passengers | Revenues (€million) | Average airfare (€) | ||
(1000) | Share (%) | |||
STAR | 22.111 | 46 | 19.486 | 881 |
OneWorld | 5.479 | 11 | 4.225 | 771 |
SkyTeam | 20.321 | 42 | 20.045 | 986 |
Total | 47.911 | 100 | 44.116 | 921 |
Source Veldhuis, 2005Full-size table
Direct flights offered by STAR alliance from Amsterdam to Singapore and connection via Frankfurt, has given it the largest share while OneWorld has the least due to its indirect flights via London (Veldhuis, 2005) and Air France and KLM together have 42% due to its direct flight offer at KLM from Amsterdam and also through connections at Paris (Veldhuis, 2005).
From the table, we can also observe that Sky Team has the highest revenues and the highest airfare. Airfares are estimated using AIR-CO-model and depend on the competition levels (Veldhuis, 2005). Sky team has the highest average airfare of EURO986 and the lowest is from OneWorld (€771) but revenues from Sky Team are higher because they provide direct flights while OneWorld aprovides only indirect connections from Amsterdam (Veldhuis, 2005).
The position of OneWorld shows how firms with indirect connections find it difficult in the start and serve the mostly the leisure market with unattractive destinations and difficult to change fares like direct flight companies (Veldhuis, 2005).
Now we are going to look at the effect in the Randstad – Singapore market of some alternative allocation principle from all flights, that is all 14 weekly flights
Passengers and revenues by alliance in the Randstad–Singapore market using alternative frequency allocation principles Source Veldhuis, 2005Full-size table
)
Frequency allocation CDG/AMS | |||||||||
14/0 | 12/2 | 10/4 | 8/6 | 7/7 | 6/8 | 4/10 | 2/12 | 0/14 | |
% change from 7/7 allocation | Levels | % change from 7/7 allocation | |||||||
Total market | −5.7 | −4.1 | −2.1 | −0.6 | 47.911 | 0.5 | 1.3 | 1.8 | 2.2 |
STAR | 20.7 | 19.5 | 11.4 | 3.5 | 22.111 | −3.1 | −8.5 | −12.9 | −16.6 |
OneWorld | 12.2 | 12.2 | 7.3 | 2.3 | 5.479 | −2.1 | −5.7 | −8.7 | −11.4 |
SkyTeam | −39.3 | −34.2 | −19.4 | −5.9 | 20.321 | 5.2 | 13.8 | 20.6 | 26.3 |
Revenue SkyTeam | −47.2 | −41.6 | −23.7 | −7.2 | 20.045 | 6.4 | 17.1 | 25.8 | 33.1 |
Consumer surplus (€) | −21.22 | −17.15 | −9.95 | −3.12 | 2.86 | 7.89 | 12.20 | 15.98 |
Source Veldhuis, 2005Full-size table
If in the year 2010 all flight are located in Schiphol, overall service serve at Schiphol will in crease from 7 to 14 direct weekly flights causing a market generation effect of 2.2% and reducing the generalised user cost leading to an increase in consumer surplus of €16 (Veldhuis, 2005).
Though demand will increae by 2.2% on flights from Randstad to Singapore, Sky team dominace will alsi increase in Schiphol causing an increase in frequency share in the market from 53% to 67% and therefore and increase in airfare in the market by 0.6% (Veldhuis, 2005).. This increase will have a negative impact on the demandcausing a market growth of just 2% but Sky Team may find their market increase by 26% while two other alliances may find their market decrease by 10% (Veldhuis, 2005)
Sky Team will also realise an increase in yields because there are more direct flights accompanied by higher fares and me result to a revenue increase of 33% (Veldhuis, 2005).
The effect will be negative if all 14 flights are allocated at Charles de Gaulle causing a negative market with a decrease demand of 5.7% making the negative effect of allocating to Charles de Gaulle stranger than the positive effect of allocating to Schiphol (Veldhuis, 2005)
With no doubt the company will benefit more by allocating to Schiphol will give better better to passenger in Randstad area and to the alliance as a whole (Veldhuis, 2005) but will yield more benefit to the passengers than to the alliance at Île-de-France region (Veldhuis, 2005). This model is sued to know which location is most suitable for the alliance to use in order to maximise revenue (Veldhuis, 2005).
This model has been used to show two phases of a company’s merger; that is the first phase which is when the network intergrates and the second phase which is network rationalisation(Veldhuis, 2005). These two phases gives the operational consequences of these two airlines merging together, both positive and negative.
Passengers enjoy the benefits of more indirect flights when the companies merge but there is significant value added as the airlines already had sufficient indirect flights but airfares increase as the Sky team has become dominant in most of it’s routs in the first phase (Veldhuis, 2005).
The rationalisation phase the overall network might possibly change and may also affect passengers positively or negatively which may cause some airports to loose connections while the other gain more (Veldhuis, 2005). Passenger will enjoy consumer surplus in airports where connections have been gained. (Veldhuis, 2005).
- Conclusions
Having looked at the model and the possibility of moving to one airport in 2010, it can be observed that, it will be mor advantages for Shy Team to move all 14 weekly flights to Schiphol than to Paris because of the great benefits the merger will gain. (Veldhuis, 2005). There will be value added to Sky Team if it has to allocate to Schiphol like, increase market share and growth, increase in revenue and the ability to raise fares. Some other argue it is better to allocate in Charles de Gaulle based on the fact that Air France is bigger than KLM and also the size (and location) of the Île-de-France market in more than that of Randstad. Singapore line is dominated by STAR because there are only four weekly direct flights from Schiphol, but that will change if more direct weekly flights leave Schiphol and they do at Charles de Gaulle (Veldhuis,
(Jan Veldhuis, 2005)
One can therefore conclude that mergers and acquisitions do create value for shareholders but only if investors have confidence the system. We therefore recommend that there should be increased monitoring of the activities of managers to ensure that they do not involve in the provision of non-performing loans, which in turn reduce investors’ confidence in the airline system. This paper has been limited only to two airline companies as well as to target airlines because data was unavailable for the other airline outlined. In addition, target airlines seem to disappear following the merger and acquisition thus making it difficult to observe any data for these banks. This paper therefore recommends a further study of airline mergers in the U.K using a larger sample and observing more data on stock prices of the companies concerned.
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[1] http://corporate.klm.com/en/home