The Operational and Financial Consequences of Mergers and Acquisitions: Case Study of Air France-KLM.
Table of contents
3.1) Operational Consequences Using the AIR-CO Model 10
3.2) Financial consequences. 23
3.1.4) Return on Asset Ratio. 24
3.1.5) Return on capital employed (ROCE) 25
3.1.9) Net working capital net 26
PART 1
1.1) INTRODUCTION
This research is designed to give an overview of what consequences companies will face after they merge. This particular topic is of interest because of the changes companies undertake to do this.
In the past decade, so many companies either decided to merge together to form a bigger power and take control over the market, or they have acquired other small companies to control the production of goods and services. Today’s mergers are not merely about growing in size; there are other factors and opportunities companies gained when companies merge together.
Since the year 2000, there has been a lot of integration taking place between two larger companies or a large company taking over a smaller company. For example JP Morgan Chase and Co. purchased Bank One Cooperation in 2004 and the merger of KLM and Air France in 2004 to form Air France-KLM
This study will focus on the merger of Air France and KLM. The integration between these two airlines drew a lot of attention in 2004 because these two companies were about to create one of the worlds’s most powerful companies in the airline industries and therefore caused other companies in the industry like Easy Jet to challenge this merger. In February 2004, EasyJet filed a report to the European high commission claiming that this merger will damage competition in the industry.
1.2) Research Objectives
The main objective of this project is to give the consequences of the integration between KLM and Air France. After looking at some theories about mergers and Acquisitions, we will go further to look at the overview of the two companies before they merged which will include a short history. The main part of this project is to look at what has changed since these two companies merged. We will be answering questions as to why these two companies merged using theories and relating them to the company. This project will look at both operational and financial changes that have occurred in the two companies after the merger by using some financial data and comparing them before and after integration.
PART 2
2.1) Research Approach
In order to answer the questions set in the objective of this report, a research has been carried out using mostly secondary data. The secondary data was gathered from websites, journals and books. A theoretical research was carried out on what kind of operational changes and financial changes can take place when two or more companies integrate.
Mergers and acquisitions 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 the 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). (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, 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 such as 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 takeover, 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). The merged firm become worth more than when two firms operated 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 and after the merger.
Part 2
2.2) Air France KLM
In order to well understand the operational effect of the integration between Air France and KLM, I have used information that was provided by Jan Veldhuis in his journal the ‘Impacts of the Air France–KLM merger for airlines, airports and air transport users’. This journal gives clear information on the impact of the integration between the two companies on their passengers. The model is used was Air Transport Network Competition Model (AIR-CO) (2004) that was designed by Amsterdam Aviation Economics in 2004 to examine the implications of the merger on passengers, airlines and airports.
In his calculations using this model he describes the effect the merger has had on the company by showing the before and after data of the company. This model focuses on the following findings by Jan Veldhuis.
- In his model Jan Veldhuis (2005) illustrates competition between route alternatives, and considers potential trips between Northwest Europe and a destination elsewhere in the world.
- He also analyses the demand for air transport between Northwest Europe and Singapore and also compares demand with the various alliances. The main alliances he used were STAR, OneWorld, Sky Team and Wings.
- Given all data needed, he used this model to calculate the indirect connection and frequency of passengers at hubs. In his presented data, he shows the before and after integration frequencies between Amsterdam/Paris and Singapore.
- Using this model, he also calculated the frequency shares and airfare changes at the four alliances on the routes to Singapore, before and after integration (Jan Veldhuis 2005)
- He also used the model to calculate the impact of the network system on passenger’s trip before and after the integration and comparing them with other alliances.
- He goes further, calculating the revenue each alliance receives on this route to Singapore, showing the before and after figures
- This model also shows the change in the number of passenger trips at each airport. This shows how the number has changed after integration
- This Model also shows the impact the integration of these companies will have on its passengers.
All the above calculations carried out by Jan Veldhuis refer to the operational consequences of the integration.
Financial Ratios
Apart from using the AIR-Co model to determine the impact of mergers on the companies, a financial analysis can also be used. This can be done by calculation the necessary financial ratios of the company and evaluating the before and after results
2.3) Ratios Analysis
The Formulas for Calculating Financial Ratios are presented in the following Table:
Ratio | Formula[1] |
Leverage ratios: | |
Debt-to-equity ratio | (Long-term debt + leases)/equity |
Liquidity Ratios: | |
Net working capital to total assets | (Current assets – current liabilities)/total assets |
Current ratio | Current assets/current liabilities |
Quick ratio | (Cash + short-term securities + receivables)/current liabilities |
Efficiency Ratios: | |
Sales to asset ratio (asset turnover ratio) | Sales/average total assets |
Inventory turnover | Cost of goods sold/average inventory |
Receivables turnover | Sales/average receivables |
Profitability Ratios: | |
Net profit margin | (EBIT-tax)/sales |
Return on assets (ROA) | (EBIT-tax)/average total assets |
Return on equity (ROE) | Earnings available to common stockholders/average equity |
Operating Margin | Operating Income/Net sale |
Return on capital employed | Net Income/Capital Employed |
Asset Turnover Ratio | Sales/total assets |
2.4) Event Study Analysis
The event study methodology is used to investigate the reaction of investors to the announcement of the Air France-KLM merger. The main assumption behind the event study methodology is that stock markets are sufficiently efficient to evaluate the impact of new information ( in this case, the announcement of a merger) on expected future profits of the merging companies. In general, the methodology involves five main steps including (Dasgupta et al., 1997): (1) identification of the event of interest (In this case airline 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. (Dasgupta et al., 1997): This study will however be limited only to the first four steps. Several approaches can be employed to 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 merger given that the airline 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)
Limitation of information
Though this model is effective in calculating changes that occurred after the integration of both airlines, there are some limitations to information provided.
- Firstly, the routes used in the calculations to come out with results are limited. Jan Veldhuis’ calculations are based mostly on the Northwest Europe and Singapore routs, they do not show calculations on the other routs.
- The second limitation to his work is that is did not measure the change in performance of the alliances as a whole and not the individual companies. It does not give detail information on the impact of KLM or Air France after the integration separate from the other airline companies in their Alliance.
- The formula used to calculate the operational consequences as done my Jan Veldhuis in his work. This information provided has already been calculated and the necessary data taken by Jan Veldhuis.
PART 3
3.1) Operational Consequences Using the AIR-CO Model
In order to illustrate the consequences of the 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 integration phase and the Network realisation phase (Veldhuis, 2005). This model also shows the effect of mergers on passengers.
This model mostly describes the competition between alternative routes with each route 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; Cost distribution (Utrecht-Singapore)
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, 2005
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 occur before the merger takes place and use all four alliance competitors as shown on the table ( Veldhuis, 2005Full-size table
)
Table 2; Air Transport passenger demand in the market between Northwest Europe and Singapore, by airport, airline alliance and region
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, 2005
Table 3 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 caused 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 flights 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).
Table 4 Frequency shares and airfare changes of the four alliances on the routes to Singapore, before and after integration
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, 2005
From the table we can see that Sky Team has dominated in Amsterdam and 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 in the hinterland from 76,000 to 80,000 passenger trips on the Singapore route as shown on the table below (Veldhuis, 2005).
Table 5 Impact of network integration: passenger trips on the route to Singapore by alliance
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 passengers 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.
Table 6 Impact of network integration: revenues on the route to Singapore by alliance
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 any 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.
Table 7 Impact of network integration: passenger trips on the route to Singapore by airport
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 occur 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 change 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 route (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 explanation 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 on the passengers who were neglected in the early stages of the merger but were still effected (Veldhuis, 2005). The positive effect here is the increase in indirect flights from Schiphol, and therefore passengers using this airport who 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 is the increase in airfares which came as a result of the Sky Team dominating the market (Veldhuis, 2005). This increase in airfares occurred at all airports except Frankfort and largely in Amsterdam (Veldhuis, 2005). This confirms the second phenomenon of why companies merge, stating they merge to gain market power and increase fare prices. The table below summarises the positive and negative effects of this merger and how they balance each other out, especially the Singapore route (Veldhuis, 2005).
Table 8 Impacts for air transport users of network integration on the routes to Singapore:
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 an 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 to the Dutch state and therefore will have the compete better 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 one 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).
Table 9 Passengers and revenues by alliance in the Randstad–Singapore market
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 provides 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 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 (Veldhuis, 2005). )
Table 10 Passengers and revenues by alliance in the Randstad–Singapore market using alternative frequency allocation principles
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 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 increase by 2.2% on flights from Randstad to Singapore, Sky team dominance will also 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 demand causing 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)
Certainly, the company will benefit by allocating to Schiphol and this will give better service to passengers in the 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 integrates and the second phase which is network rationalisation (Veldhuis, 2005). These two phases give 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 its routes 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 lose connections while the others gain more (Veldhuis, 2005). Passengers will enjoy consumer surplus in airports where connections have been gained. (Veldhuis, 2005).
3.2) Financial consequences
3.1) Ratio Analysis
These ratio analyses are based on individual financial statement data from the financial year 2003/2004 for both KLM and Air France and also the financial year 2004/2005 for Air France-KLM after the merger.
This year’s have been chosen because this in the period the merger took place and therefore will give a real picture of what happened immediately after the merger. These ratios below are based on their financial statements and are the most important ratios from all other ratios
Ratios
| KLM before Merger | Air France before Merger | Air France-KLM |
Operating margin | 2.1%
| 1.12% | 10.15% |
Profit Margin | 0.41%
| 0.75%
| 9.01%
|
Return on equity | 0.016 | 0.023 | 0.028 |
Return on Asset | 0.0029 | 0.0072
| 0.074 |
Return on capital employed (ROCE) | 0.50%
| 0.48%
| 10.5%
|
Asset Turnover Ratio | 0.73
| 0.95
| 0.82
|
Current Ratio | 0.96
| 0.55
| 0.91
|
Quick Ratio | 0.94
| 0.53 | 0.85
|
Net working capital Ratio | (0.0093)
| (0.24)
| (0.02)
|
3.1.1) Operating profit
This is also known as return on sales ratio and shows what proportion of the company’s revenue is left over before taxes and other expenses are paid (Dyson, 2004)
Looking at the operating profit, this shows that after the merger, both company are better together in the case of paying for fix assets like interests on loans. Their operating margin combined is better than the individual margins
3.1.2) Profit margin
This indicates how much of net profit is made from each euro of revenues earned from sales and other income (Dyson, 2004)
In the financial year 2004, the profit margin for KLM for the financial year 2003/2004, which was before the merger, was 0.41% and that for Air France, was 0.75%. This profit margin increased to over 9% since the merger of the company. This maybe due to increase in revenue relative to expenses as fares have been increased
3.1.3) Return on Equity
This is shows how much profit is made from every euro of investor’s equity. The higher the figure, the better (Dyson, 2004)
KLM experienced a great deal of increase in equity ratio after the merger compared to Air France. KLM experienced an increase in equity ratio of more than 1%.This shows that for every Euro of owners’ equity invested in Air France-KLM, the company makes a profit of 2.8 Euro cents. This means the KLM has benefited from good investment decisions Air France used to offer because thy realised such a greater increase in profits on owners’ equity compared to Air France
3.1.4) Return on Asset Ratio
This explains how much profits is made from every euro of total assets employed in the company (Dyson, 2004)
The company experienced a very high asset turnover ratio of more than 7%. This implies the company is now making good use of its assets to generate profit as a whole than they used to as individual companies. High levels of passenger frequency and increased air fares may have caused an increase in revenue and therefore an increase in return on equity.
3.1.5) Return on capital employed (ROCE)
Shows how much profit is earned on every euro of capital employed (Dyson, 2004).
Return on capital employed after the integration of both companies increased more than ten times compared to when the companies used to operate individually. This means as a group the company has more ability to pay any loans or cost incurred on its assets. This was not the case before the merger as both companies could barely pay back any assets or capital invested in the company. This is as a result of increased net profits in the company.
3.1.6) Assets turnover
This shows how much of the total owners equity is being financed by debt (Dyson, 2004).
As an integrated company, KLM stands to benefit most from the revenue being generated. The asset turnover increased for KLM but Air France experienced a fall in its asset turnover as an integrated company. This indicates Air France is not utilising its assets as well as an integrated company as they used to when they were on their own.
3.1.7) Current Ratio
This ratio is shown to indicate if a company can meet its short time liabilities or in other words pay its short term debts with the first year (Dyson, 2004).
The result of this merger has reduced the ability of KLM to pay its short tem debts by just a few pennies. This fall is insignificant to the company compared to the increase ability to pay short term debts by Air France. This mean that for every euro the company owes of and has to pay within the next 12 months, they have 91 cents available to pay.
3.1.8) Quick Ratio
This ratio calculates the ability for a company to clear it’s immediate short term debts like payable and those short term loans that require immediate payments (Dyson, 2004).
As a merger, the company can pay 85 cents of a euro that they owe. This gives great advantage to Air France than to EasyJet
3.1.9) Net working capital net
This is also used to calculate the liquidity of a company and how they can pay short term debts (Dyson, 2004). If the current assets are less than the current liability, this is known as a deficit (Dyson, 2004).
Air France still gets more benefit are a merger with KLM in this case. The deficit for KLM increase as it merged with Air France.
3.3) Stock Analysis
In this section of the paper, an analysis of the stock price behaviour a few days before the merger and a few days after the merger is conducted. An event window of 40 days is specified and the behaviour of the returns as well as the abnormal returns is analysed. The returns are analysed instead of the stock price because returns are scale free and uncorrelated. That is, they exhibit random walks. (Fama and French 1991). For example, returns do not have a unit of measurement whereas stock prices are measured in the currency in which they are denominated. These properties of returns make them more appropriate for analysis than returns because they can be compared across companies.
Figure 1: Actual Returns for Air France-KLM (04/04/2004 – 05/05/2004)
Figure 1 shows the actual returns of KLM over the event window 31 days before the merger and 9 days after the merger. Consistent with the efficient market hypothesis, one can observe that the returns exhibit random walks indicating that one cannot predict the outcome of the returns in future. (Fama and French, 1991; Bodie et al, 2002). One can observe that on the first day of the invent window the returns witnessed a jump in value from 0% to approximately 10% and droped on between the 2nd and 3rd day to approximately -1.0%. the returns maintained some slight fluctuations from the 2nd day of the event wndow right up to the 24th day when the fluctuations increased. It can also be noted that the returnw were mostly positive over the period. The returns turned negative on the 25th day of the event window.
Figure 2: Abnormal Returns
The abnormal returns also show great fluctuations over the event window. One can observe that the abnormal returns were also mostly positive over the first half of the event window. Above 3 days up to the merger the abnormal witnessed an upturn thus indicating a positive reaction to the merger. The table below shows that the average abnormal return as well as the average ordinary return was negative.
Ordinary Return | Abnormal Return | ||
Average Return | -0.2% | -0.2% | |
Standard Deviation | 0.026641 | 0.016355 | |
Median | 0.0% | -0.19% |
Conclusion
Having looked at the evaluation of both Schiphol and Charles De Gaulle, there is the possibility that Air France-KLM will be moving to Schiphol in 2010 because of advantages that outweigh those that Paris De Gaulle provides. The company will be making a lot of profit and revenue if they have to move to Amsterdam though this might cause an increase in fares. According to Jan Veldhuis (2005), some have argued to favour France saying the airline should locate to Paris given that Air France is a bigger company than KLM.
The company has also gained some advantages as a result of merging:
- As a merger, both companies can now share their technology and create a greater force in their technical potential. KLM can make use of those technologies they lacked and which were available to Air France and vice versa.
- The second and greatest advantage is the external growth and market share the company has gained. Air France-KLM is one of the biggest airline companies today. They have formed a superpower that has taken most of the market in Europe. Their increase in market share can be explained by their increase in direct flight connections to many destinations.
- Increased revenue since the merger is one advantage the company has enjoyed since they merged. As shown above in the financial ratios, the company has increased its profitability ratio by about nine times compared to what they used to earn as independent companies.
Looking at the financial consequences, especial the liquidity ratio, Air France has benefited from KLM more despite Air France being the larger company. Most of the technical and operation benefits were gained by KLM because of the experience Air France has had over the years.
In general, 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 get involved 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 merger and acquisition thus making it difficult to observe any data for these mergers. This paper therefore recommends further study of airline mergers done using a larger sample and observing more data on stock prices of the companies concerned.
Appendices
Air France income statement 2004 before the merger
Consolidated income statement (In EUR millions) | |
Year ended | March 31, 2004 |
Notes | |
Operating revenues | 12337 |
External expenses | -6,754 |
Salaries and related costs | -4,079 |
Taxes other than income tax | -186 |
Gross operating result | 1,318 |
Charge to depreciation/amortization, net | -1,184 |
Charge to operating provisions, net | -46 |
Gain on disposal of flight equipment, net | 7 |
Other operating income and charges, net | 44 |
Operating income | 139 |
Restructuring costs | -22 |
Net financial charges | -60 |
Gains on disposals of subsidiaries and affiliates, net | 5 |
Pre-tax income (loss) | 62 |
Share in net income of equity affiliates | 53 |
Amortization of goodwill | -15 |
Income (loss) before income tax and minority interests | 100 |
Income tax | -2 |
Income (loss) before minority interests | 98 |
Minority interests | -5 |
NET INCOME (LOSS) | 93 |
Earnings (loss) per issued share | 0 |
Earnings (loss) per share | |
Basic | 0 |
Dilute | 0 |
Air France 2003 Balance sheet
Consolidated balance sheet (In EUR millions) | |
ASSETS at March 31 | 2004 |
Notes | |
Consolidation goodwill | 95 |
Intangible fixed assets | 149 |
Flight equipment | 6951 |
Other property and equipment | 955 |
Investments in equity affiliates | 336 |
Other investments | 268 |
Total fixed assets | 8754 |
Inventory | 151 |
Trade receivables | 1651 |
Income tax receivable | 101 |
Other accounts receivable | 494 |
Marketable securities | 1478 |
Cash | 330 |
Total current assets | 4205 |
Total assets | 12959 |
Common stock | 1868 |
Additional paid-in capital | 261 |
Retained earnings (accumulated deficit) | 1942 |
Cumulative translation adjustment | -9 |
Stockholders’ equity | 4062 |
Minority interests | 23 |
Stockholders’ equity and minority interests | 4085 |
Provisions for liabilities and charges | 1039 |
Short and long-term debt and obligation under capital leases | 4380 |
Trade payables | 1226 |
Income tax liability | 24 |
Advance ticket sales and loyalty program | 1008 |
Other payables | 1200 |
Total liabilities | 8874 |
Total liabilities and stockholders’ equity | 12959 |
Ratios
KLM 2003 Income statement
Consolidated statement of earnings 2003/ 2004 | |
Traffic revenue | |
Passenger | 4234 |
Cargo | 963 |
Other revenue | 680 |
Operating revenues | 5877 |
Operating expenses | 5757 |
Operating result | 120 |
Financial income and expense | -101 |
Results on sale of assets | -1 |
Results of holdings | 13 |
Pretax result | 31 |
Taxes | -7 |
After tax result | 24 |
Share of third parties | |
Net income (loss) | 24 |
KLM Balance sheet 2003/2004
Consolidated balance sheet 2003/204 | |
Current assets | 1781 |
Fixed assets | 6256 |
Total assets | 8037 |
Current liabilities | 1856 |
Long-term debt | 4228 |
Provisions | 279 |
Deferred credits | 186 |
Group equity | 1488 |
Total liabilities | 8037 |
Air France-KLM Income statement 2007 and 2008
Financial data in Euro (Values in Millions (Except for per share items) | ||
2006 | 2005 | |
Period End Date | 31/03/2006 | 31/03/2005 |
Period Length | 12 Months | 12 Months |
Stmt Source | ARS | ARS |
Stmt Source Date | 26/06/2007 | 03/07/2006 |
Stmt Update Type | Reclassified | Restated |
Revenue | 21,448.00 | 18,978.00 |
Other Revenue, Total | 4 | 5 |
Total Revenue | 21,452.00 | 18,983.00 |
Cost of Revenue, Total | 12,127.00 | 7,382.00 |
Gross Profit | 9,321.00 | 11,596.00 |
Selling/General/Administrative Expenses, Total | 6,585.00 | 7,623.00 |
Research & Development | 0 | 0 |
Depreciation/Amortisation | 1,656.00 | 1,561.00 |
Interest Expense (Income), Net Operating | 0 | 0 |
Unusual Expense (Income) | -6 | -1,351.00 |
Other Operating Expenses, Total | -367 | 1,823.00 |
Operating Income | 1,455.00 | 1,927.00 |
Interest Income (Expense), Net Non-Operating | 0 | 0 |
Gain (Loss) on Sale of Assets | 0 | 0 |
Other, Net | -38 | -11 |
Income Before Tax | 1,200.00 | 1,697.00 |
Income Tax – Total | 256 | 133 |
Income After Tax | 944 | 1,564.00 |
Minority Interest | -8 | 14 |
Equity In Affiliates | -23 | 73 |
U.S. GAAP Adjustment | 0 | 0 |
Net Income Before Extra. Items | 913 | 1,651.00 |
Total Extraordinary Items | 0 | 59 |
Discontinued Operations | 0 | 59 |
Net Income | 913 | 1,710.00 |
Air France-KLM balance Sheet 2007 and 2008
Financial data in Euro (Values in Millions (Except for per share items) | ||
2006 | 2005 | |
Period End Date | 31/03/2006 | 31/03/2005 |
Stmt Source | ARS | ARS |
Stmt Source Date | 03/07/2006 | 26/06/2007 |
Stmt Update Type | Updated | Reclassified |
Assets | ||
Cash and Short Term Investments | 3,811.00 | 2,625.00 |
Cash & Equivalents | 2,946.00 | 2,047.00 |
Short Term Investments | 865 | 578 |
Total Receivables, Net | 3,980.00 | 2,937.00 |
Accounts Receivable – Trade, Net | 2,518.00 | 2,272.00 |
Accounts Receivable – Trade, Gross | 2,625.00 | 2,374.00 |
Provision for Doubtful Accounts | -107 | -102 |
Receivables – Other | 1,462.00 | 665 |
Total Inventory | 340 | 382 |
Prepaid Expenses | 294 | 304 |
Other Current Assets, Total | 68 | 82 |
Total Current Assets | 8,493.00 | 6,330.00 |
Property/Plant/Equipment, Total – Net | 12,972.00 | 12,289.00 |
Goodwill, Net | 208 | 205 |
Intangibles, Net | 428 | 437 |
Long Term Investments | 3,289.00 | 3,457.00 |
Note Receivable – Long Term | 0 | 0 |
Other Long Term Assets, Total | 1,089.00 | 476 |
Other Assets, Total | 0 | 0 |
Total Assets | 26,479.00 | 23,194.00 |
Liabilities and Shareholders’ Equity | ||
Accounts Payable | 2,039.00 | 1,901.00 |
Payable/Accrued | 0 | 0 |
Accrued Expenses | 0 | 0 |
Notes Payable/Short Term Debt | 102 | 262 |
Current Port. of LT Debt/Capital Leases | 1,260.00 | 1,044.00 |
Other Current Liabilities, Total | 4,690.00 | 3,768.00 |
Total Current Liabilities | 8,091.00 | 6,975.00 |
Total Long Term Debt | 7,826.00 | 7,889.00 |
Long Term Debt | 3,158.00 | 2,881.00 |
Capital Lease Obligations | 4,668.00 | 5,008.00 |
Deferred Income Tax | 839 | 313 |
Minority Interest | 119 | 111 |
Other Liabilities, Total | 1,870.00 | 1,997.00 |
Total Liabilities | 18,745.00 | 17,285.00 |
Redeemable Preferred Stock | 0 | 0 |
Preferred Stock – Non Redeemable, Net | 0 | 0 |
Common Stock | 2,290.00 | 2,290.00 |
Additional Paid-In Capital | 430 | 384 |
Retained Earnings (Accumulated Deficit) | 5,072.00 | 3,254.00 |
Treasury Stock – Common | -58 | -19 |
Other Equity, Total | 0 | 0 |
Total Equity | 7,734.00 | 5,909.00 |
Total Liabilities & Shareholders’ Equity | 26,479.00 | 23,194.00 |
Total Common Shares Outstanding | 265.23 | 268.08 |
Total Preferred Shares Outstanding | 0 | 0 |
References
Fama, E., L. Fisher, M. Jensen, and R. Roll (1969), “The Adjustment of Stock Prices to New Information,” International Economic Review, pp. 1-21.
Iqbal Z., Shetty S. (1995). The Impact of merger outcome, bid order, payment method, and managerial resistance on sock returns to bidders in multiple-bidder merger contests. International Review of Economics and Finance, vol. 4, No. 1, pp. 57-67.
Moles P., Terry N. (1997). Mergers and Acquisitions” The Handbook of International Financial Terms. Oxford University Press. Oxford Reference Online. Oxford <http://www.oxfordreference.com/views/ENTRY.html?subview=Main&entry=t181.e4855>
Myers S. C., Brealey R. A. (2002). Principles of Corporate Finance. 7th edition. McGraw-Hill Irwin.
Susmita Dasgupta, Benôit Laplante, Nlandu Mamingi. (1997). Capital market responses to environmental performance in developing countries The World Bank Development Research Group
Susmita Dasgupta, Benôit Laplante, Nlandu Mamingi. (1997). Capital market responses to environmental performance in developing countries The World Bank Development Research Group
Veldhuis. J., 2005. Journal of air Transport management. Impacts of the Air France–KLM merger for airlines, airports and air transport users, doi:10.1016/j.jairtraman.2004.11.006 , Elsevier B.V.
Brown, S. and J. Warner, (1985). “Using Daily Stock Returns: The Case of Event Studies,” Journal of Financial Economics, pp. 3-31.
[1] Formulas are taken from Brealey and Myers (2002: p. 825). Principles of Corporate Finance 7th Edition.