Through RQ 1, we investigated what market research measures that have the strongest
explanatory power for satisfaction with reliability. We found that on the US market, measures of downtime, especially the number of occasions with downtime, are more relevant than failure frequencies like the number of problems per time or distance unit.
The results for the US market indicate that one should be careful with putting to much focus on the number of problems experienced, which is a much emphasised measure today. The amount of downtime seems to deserve more focus.
For the European markets, we do not have access to measures of downtime through the studied survey. The measure with the strongest explanatory power available is the average number of problems among all trucks. It is important to note is that the data from the survey of the European markets does not seem to support analyses to be made based on the number of problems, the way we have measured it. Measuring reliability is not a prioritised objective of the European study as I have understood it, so I am not criticising the work of the survey supplier. It is rather a matter of what is ordered. Problems are tracked in multiple ways throughout the corporation already, but I think it adds additional value to get indications on the customer satisfaction, repurchase intentions etc. of those who state what problems they have had. The survey of the US market shows that this can be done, so I would suggest that more accurate measures of failure frequency and maybe more importantly downtime are incorporated into a slightly extended study for the European markets.
In RQ 2 and 3, we looked at the strength of reactions to changes in reliability. The reactions were studied as changes in both satisfaction with reliability and reliability image. The strength of the reactions to improvements and deterioration of reliability were to be compared. The analysis shows that the reactions are, at least for most changes in reliability more or less unpredictable. For large changes, the reactions are quite as expected, but the number of occurrences supporting this is low. The unpredictability of reactions yields a poor fit for our regression model and comparing the average strengths of reactions to changes in reliability is not relevant neither for satisfaction nor image. This means that we can not answer whether
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satisfaction and image are path dependant features or not. Having much stronger reactions to deteriorations that to improvements, which we would expect, would stress manufacturers to be careful with introducing technology that could generate poor reliability.
We tested in RQ4 if good workshop service could compensate substantially for poor reliability. The analysis shows that good workshop service generally improves satisfaction, but those customers who are dissatisfied with reliability but satisfied with workshop service are less satisfied than those who are satisfied with reliability but dissatisfied with workshop service. The overall satisfaction was measured through repurchase intention and willingness to recommend. This does not mean that there is no meaning with trying to provide excellent service. The analysis shows that good service clearly improves satisfaction. However, it
suggests that we can never ignore reliability no matter how good service we can provide. Also, it is probably cheaper for the manufacturer to do it right the first time, i.e. building trucks with few problems, rather than building low quality trucks and provide excellent service.
RQ 5 is a qualitative analysis of how customers reason regarding reliability. Interviews with seven Swedish fleet managers revealed among other things that personal relationships between customers and sales staff are immensely important, that statistics is not frequently used by customers to evaluate trucks and that the impressions of brands among customers are based on a large variety of inputs. One of the managerial implications of these results is that the staff in the organisation must be trained well so that they are equipped to be able to build relationships with customers.
Another conclusion from the interview sessions was that customers do not seem to have a large acceptance for problems that are due to new technology. This means that there is clearly a risk in introducing more new technology than one is forced to by legal requirements. What is then the rationale of introducing more technology than other competitors, when the deteriorated reliability will have consequences in the customer satisfaction? There are examples of brands that have produced reliable trucks that have been based on more mature technology than that of competitors. This has given them a very good customer satisfaction.
However, not providing state-of-the-art technology has hindered them from getting a premium image, and without a premium image it is impossible to charge as much as the premium brands can do. In spite the risk of losing customer satisfaction, premium brands must probably continue applying new technology not to loose their status.
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In the last research question a model is created to create an initial understanding of how a changed durability of the driveline might affect the business performance of the Volvo Group.
The connections between the constituents can at this point not be deeply analysed, while there is a lack of data in the organisation. This finding stresses that the area of durability must be explored better and measuring field durability must be done in a more consistent and systematic way than is currently done. Also, it is not always a lack of knowledge that is the problem. In many cases, knowledge exists somewhere in the organisation, but while the organisation is very large and the communication between departments could be better, the knowledge available is not diffused as would be appropriate.
As we have stated before, the interviews have been a very interesting part of this thesis and we think that they provide many valuable points even if it comes from a small number of people. The interviewees make purchasing decisions for some of the largest fleets in Sweden and satisfying these customers as well as other customers is integral to Volvo. A striking feature of the overall results is that the quantitative analyses are sensitive to validity of the measures and some of the most important results overall are concerned with personal relations, which is almost impossible to measure quantitatively. An overall conclusion is therefore that Volvo and other truck manufacturers must continue to keep a good communication with their customers in order to really understand why customers are satisfied or dissatisfied and also to be able to follow changes in needs and wants of its customers.
A general recommendation, that is not based on the results of my analyses but rather something I have realised when talking to people within Volvo is that if Volvo wants to stand out even more when it comes to reliability and durability, there are two prerequisites:
• Obtain superior quality.
• Make the customers understand and believe it.
The customers in Sweden that we have interviewed claim not to care much about advertising, but rather listen to people. For improved durability or reliability to be worthwhile, one must have a strong strategy for communicating it.
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