4. FINDINGS
The results of the analysis are included in this Chapter. They are discussed in the next
chapter and compared with previous results. The main 'effect' variables used to analyse
the effect of various 'causes' are the adherence to schedules and budgets and the
composite measure of these effects called Technology Transfer Effectiveness (TTE). This
measure is discussed. The validity of the results is examined. The effects of company
characteristics, technology transfer experience, newness of technology, business
improvement initiatives and travel and links on technology transfer experience are
assessed. Satisfaction, commitment and the quality of training and documentation are
measured. The effect of R&D at the subsidiaries on technology transfer effectiveness is
measured. Finally, the specific practices listed by respondents as being of benefit or not to
the technology transfer process are listed.
The statistical significance of some results is measured using a t-test from the Excel
data analysis package. The two sample, two tail t-test assuming equal sample variance is
used. A 5% significance level is used for most analyses.
4.1. Technology Transfer Effectiveness (TTE)
The major measure used to determine the effectiveness of technology transfer when
comparing different hypotheses was the composite value TTE (Technology Transfer
Effectiveness). This value is composed of the adherence to project start-time schedule,
the project end-time schedule and to the project budget. If the project was on-time
starting, on-time finishing and on budget it would score 3.0. If the transfer was faster or
cheaper than planned the TTE would be less than 3.0. If the project was delayed or over-
budget the TTE would exceed 3.0.
Table 5. TTE score key. The value for each company is the average of these three.
| Score
| Start time
| Finish time
| Budget (reversed)
|
| 1
| Advanced more than three
months.
| Advanced more than three
months.
| Much less than expected
(>10%).
|
| 2
| Advanced less than three
months.
| Advanced less than three
months.
| Slightly less than expected
(0-10%).
|
| 3
| Not rescheduled.
| Not rescheduled.
| On budget.
|
| 4
| Delayed by less than three
months.
| Delayed by less than three
months.
| Slightly more than
expected (0-10%).
|
| 5
| Delayed by more than
three months.
| Delayed by more than
three months.
| Much more than expected
(>10%).
|
Similar metrics were used by Szulanski (1996) in his study of 'internal stickiness'. He also
used metrics based on satisfaction with the transferred technology, the quality of the
working relationship, commitment to the transfer by both transferor and transferee and the
quality of training and technical and managerial skills. However, as the measures of these
criteria are more subjective, or may be considered causal to good technology transfer
rather than effects of good transfer, they were not considered dependent variables for the
purposes of this analysis.
4.2. Validity
The first checks of the data will be to examine the validity of the responses. Validity
checks were made of the overall response and of the position of the respondent.
4.2.1. Response rate
There was only a 49% response rate and only 39% of questionnaires were sent back with
valid responses to most questions. As such how do we know if the responses received are
representative of the population? One method used to examine the validity of the
response to a mail survey is to compare the first responses received with the later ones. In
this case the responses returned prior to receipt of the reminder letter are compared with
those sent before. The overall average TTE is 3.28. The average TTE of the usable
responses of the first 49 questionnaires is 3.33 and the later 20 responses average 3.15.
The lower the score the more effective the technology transfer. The score would be 3.0 if
the project started on time, and finished on time and on budget. Possibly, the firms that
returned the forms later after being reminded were slightly more successful at transferring
technology. It could be speculated that they were less enticed by the offer of the results
because they felt less concerned about their own technology transfer success. While the
TTE score for the later questionnaires is lower, the difference is not large enough to
conclude with statistical certainty using a two sided t-test that it is different (P[T<=t] =
0.31).
It could also be speculated that the firms who did not respond did not do so because
even with the promise of confidentiality, they were still uncomfortable sharing information
about their difficulties with outsiders. The TTE of the 9 anonymous questionnaires
received was 3.46 which is much higher than the average and higher than the TTE for all
questionnaires returned before receipt of the reminder letter. The single worst response
with a TTE of 5.0 was anonymous. If these responses are omitted the TTE of the early
questionnaires is 3.30, which is close to the overall average score of 3.28. However, as
with the comparison of early and late questionnaires the difference between anonymous
responses and the others is not statistically large enough to conclude that it is actually
different (P[T<=t] = 0.20).
Because there is a difference in the overall TTE value between the first to respond, the
last to respond, and the anonymous responses we can not conclude with certainty that the
firms which did not return the questionnaires would have had similar experiences. It is
possible that the firms who responded had had more problems with technology transfer
and were enticed to respond by the offer of the results to improve their performance next
time. Or it could be that those that did not respond included those with the worst
experiences who did not wish to share them with outsiders. However, the differences are
not statistically significant, and in any case there is still a good body of responses to allow
a variety of comparisons to be made. And while we can not be sure about the accuracy of
the overall measure, we can be satisfied that there are sufficient responses for comparing
the importance of different techniques to the technology transfer process.
4.2.2. Position of Questionnaire Respondent
Another check that can be made on the validity is the position of the person completing
the questionnaire. It is possible that people in different positions may respond differently
even to the relatively unsubjective questions that constitute the TTE measurement. The
position of the respondents to the survey are shown below.
Table 6. The relationship of TTE score to the position of the survey respondent.
| Position of Respondent
| Number
| TTE
|
| High-level manager of the Irish operation with overall
responsibility for the transferred process.
| 33
| 3.20
|
| Project manager of the transfer operation.
| 8
| 3.21
|
| Manager of a portion of the technology transfer process.
| 6
| 3.67
|
| Otherwise involved in the transfer operation.
| 4
| 3.42
|
| Not directly involved, but familiar with the process.
| 5
| 3.33
|
The majority of questionnaires were completed by the overall manager to whom they were
addressed. The responses by them and by the project managers of the transfer operations
are more positive than the responses made by others with less overall responsibility. There
are many reasons why this is the case. Perhaps the overall managers are less concerned
with the operational details of the transfer that concern those working on them. Perhaps,
they wish to portray the transfer in the best possible light, which is not so important to
those with less responsibility in the transfer operation. It is difficult to know for sure.
However, because the majority of questionnaires were filled in by the overall manager, the
bias based on position should not have too significant an effect on other comparisons
made in this study. In any case, the difference noted is not large enough to be statistically
certainty that it is different.
4.3. The Effects of Company Characteristics on TTE
4.3.1. Nationality
The majority of firms responding (36, 62%) and surveyed (61%) were American. The
next largest number of respondents were German with six responding corresponding to
10% of the total responding. Only seven questionnaires in total were sent to German
companies indicating a very high response rate. Four (6%) UK firms responded which
was the same percentage as surveyed. The remainder were a variety of nationalities. The
responses by the American firms (36) are compared with the others (22).
The American firms scored better for technology transfer with a TTE of 3.20
compared with 3.51 for European firms. Companies with dual American and European
nationality were omitted from the analysis.
Table 7. The effect of nationality experience on the TTE score.
| Nationality
| Number
| TTE
| Start
| Finish
| Budget
|
| European Overall
| 17
| 3.51
| 3.35
| 3.53
| 3.65
|
| American
| 35
| 3.20
| 3.11
| 3.34
| 3.14
|
| Japanese
| 1
| 2.33
| 1.00
| 3.00
| 3.00
|
| UK
| 4
| 3.83
| 3.75
| 3.75
| 4.00
|
| Germany
| 6
| 3.39
| 3.33
| 3.50
| 3.33
|
| Netherlands
| 3
| 3.56
| 3.00
| 3.67
| 4.00
|
| France
| 2
| 3.17
| 3.00
| 3.00
| 3.50
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
The scores for individual countries were 3.83 for UK, 3.39 for Germany, 3.56 for
Netherlands, 3.17 for France, and 2.33 for Japan. However, the number of respondents
for each was low so the data may not be reliable. It is interesting to note that the Japanese
figure is much lower than any other country. This is consistent with the perception that
Japanese firms are very accomplished at establishing overseas manufacturing operations.
However, with only one respondents providing TTE data, the figure may not be accurate.
The data indicate that American firms are more effective than European firms for
technology transfer. Using a two tail t-test the difference in the budget variable is
significant at the 5% level (P[T<=t] = 0.044). It can be stated that American companies
are more likely to meet their when transferring technology to Ireland. The American
companies are better in all three categories and the overall TTE value is significant using a
two-tail t-test at the 10% level (P[T<=t] = 0.091) or a one-tail t-test at the 5%
significance level (P[T<=t] = 0.046).
Japanese firms may be even better which suggests that cultural and language
differences can be overcome. However, with only one company we can not categorically
state anything.
4.3.2. Duration since Establishment
Mudumba (1998) investigated the role of duration in multinational investment strategies.
He found that duration was one factor that would be considered when making investment
decisions, but by no means the only one. In this study the effect of duration on
effectiveness of technology transfer is considered. Intuitively it could be expected that
duration of establishment would have a positive effect on technology transfer efficiency.
An investigation of the number of years established in Ireland compared with the
calculation of TTE found the following. The number of years established was nearly
identical to the number of years manufacturing in Ireland. The analysis of the effect of the
number of years manufacturing in Ireland would similar trends.
Table 8. The effect of duration of establishment on the TTE score.
| Number of years established in Ireland
| Num.
| TTE
| Start
| Finish
| Budget
|
| 0-5
| 10
| 3.17
| 3.00
| 3.30
| 3.20
|
| 6-10
| 10
| 3.53
| 3.60
| 3.70
| 3.30
|
| 11-20
| 17
| 3.11
| 2.93
| 3.13
| 3.27
|
| 21-30
| 16
| 3.33
| 3.20
| 3.53
| 3.27
|
| >30
| 5
| 3.33
| 3.00
| 3.40
| 3.60
|
| total
|
| 3.28
| 3.15
| 3.40
| 3.29
|
The effect is not linearly increasing with age. Firms under 5 years and between 11-20
years have the best TTE scores while firms between them in age, 6-10 years have the
worst scores. Older firms are closer to the overall average. This does not suggest a clear
reason. Examining the components of the TTE reveals that the 6-10 firms are not
significantly worse than the 0-5 and 11-20 in terms of meeting budgets, but are much
worse for start times and end times.
4.3.3. Size
The sizes of the responding companies was measured both in terms of number of emplyees
and in terms of annual sales. The sizes are shown below.
Table 9. The effect of size (number employed) on the TTE score.
| Number of people employed
| Num.
| TTE
| Start
| Finish
| Budget
|
| 1-50
| 6
| 3.13
| 2.80
| 3.40
| 3.20
|
| 51-100
| 14
| 3.15
| 2.92
| 3.23
| 3.31
|
| 101-300
| 19
| 3.35
| 3.28
| 3.44
| 3.33
|
| 300-500
| 10
| 3.40
| 3.60
| 3.60
| 3.00
|
| >500
| 7
| 3.38
| 3.00
| 3.57
| 3.57
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
Table 10. The effect of size (annual sales) on the TTE score.
| Annual Sales
| Num.
| TTE
| Start
| Finish
| Budget
|
| <£1M
| 0
|
| -
| -
| -
|
| £1-10M
| 10
| 3.48
| 3.33
| 3.67
| 3.44
|
| £10-50M
| 15
| 3.42
| 3.33
| 3.60
| 3.33
|
| £50-100M
| 11
| 2.93
| 2.80
| 3.10
| 2.90
|
| >£100M
| 15
| 3.24
| 3.00
| 3.43
| 3.29
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
There are different trends in both sets of data depending on the method of measuring size.
Firms with fewer employees (<100) have a better score for technology transfer than bigger
firms (>100). Firms with higher sales <£50M) have a better score for technology transfer
than smaller firms (>100). There are 2 fewer firms in this analysis because some chose not
to disclose annual sales, but this is unlikely to account for the difference. Firms with sales
of £50-100M have the best score and overall firms with sales greater than £50M score
better than firms with fewer sales.
A question was also asked about the percentage exported. The vast majority (47 of
56) export more than 90% of their production. Therefore no meaningful examination of
these data was possible.
4.3.4. Degree of Autonomy
Questions were asked about the degree of autonomy of the firms in areas related to human
resources, R&D decisions, financial plans, product specifications and customer
relationships. The categories were based on those used by Taggart (1998) in his study of
the complexity of R&D conducted at multinational firms in the UK. The summary of
responses is shown in Table 6.
Table 11. The degree of autonomy exercised by firms in several key areas.
| Degree of autonomy
| Little
| Small
amount
| Moderate
amount
| Considerable
autonomy
| Total
control
|
| Hiring and recruitment
| 0
| 1
| 1
| 15
| 41
|
| Pay and Conditions
| 0
| 2
| 4
| 27
| 25
|
| R&D Decisions
| 16
| 9
| 18
| 11
| 4
|
| Financial plans (budgets,
etc.)
| 0
| 2
| 15
| 33
| 8
|
| Product and Quality
Specifications
| 2
| 14
| 15
| 13
| 14
|
| Customer relations
(marketing, etc.)
| 10
| 15
| 7
| 11
| 14
|
Typical firms have considerable autonomy about HR decisions, moderate autonomy about
financial plans and less autonomy about R&D decisions. Autonomy about product and
quality decisions and customer relations are more variable.
The effect of autonomy on technology transfer is shown in Table 8. Average TTE is
shown for each grouping. If there are fewer than 5 data the number is less reliable and is
shown in italics. The TTE score is better in firms with greater autonomy over HR and
financial matters. There is no apparent correlation between the degree of autonomy in
other matters and TTE score.
Table 12. The effect of autonomy on the TTE score.
| Degree of autonomy
| Little
| Small
amount
| Moderate
amount
| Considerable
autonomy
| Total
control
|
| Hiring and recruitment
|
| 3.67
| 3.67
| 3.45
| 3.20
|
| Pay and Conditions
|
| 4.00
| 3.42
| 3.37
| 3.09
|
| R&D Decisions
| 3.22
| 3.19
| 3.35
| 3.30
| 3.33
|
| Financial plans (budgets,
etc.)
|
| 3.67
| 3.40
| 3.35
| 2.57
|
| Product and Quality
Specifications
| 2.67
| 3.44
| 3.07
| 3.26
| 3.46
|
| Customer relations
(marketing, etc.)
| 3.11
| 3.42
| 3.38
| 3.09
| 3.33
|
A reason for this could be that Irish subsidiaries that have considerable autonomy over
HR and financial matters can hire who they need and spend what they need to ensure that
the technology transfer process runs as smoothly as possible.
4.4. The Effects of Technology Transfer Experience on TTE
4.4.1. Number of Previous Technology Transfers to Ireland
In his seminal work, Teece (1977) examined the effect of several factors on the cost of
technology transfer. The number of previous transfers, the number of times the
technology had previously been transferred, the age of technology, experience and size of
the transferee and the amount of R&D carried out by the transferree in terms of
percentage sales were all examined. These issues are examined to some degree in this
study, although the success of the transfer is not measured in absolute cost terms as in the
Teece study, but in terms how well the transfer met its planned timetable and budget. It is
probable that firms familiar with the relationships discovered by Teece would make
allowances for this in their scheduling and budgeting.
An enquiry was made about the number of prior transfers. However the options
covered the incorrect range and the majority responded four or more. No particular trend
is apparent from the data.
Table 13. The effect of technology transfer experience on the TTE score.
| Number of previous transfers
| Num.
| TTE
| Start
| Finish
| Budget
|
| none
| 7
| 3.19
| 3.00
| 3.00
| 3.57
|
| one
| 7
| 3.43
| 3.14
| 3.71
| 3.43
|
| two
| 7
| 3.14
| 2.86
| 3.29
| 3.29
|
| three
| 3
| 3.33
| 3.67
| 3.33
| 3.00
|
| four or more
| 32
| 3.29
| 3.19
| 3.45
| 3.23
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
Respondents were also asked the total number of technology transfers conducted by
the firm. This may not be identical to the answers in Table 13 because respondents may
have answered questions about an earlier transfer. However, it does allow a comparison
of technology transfer performance compared to technology transfer experience. Another
caveat to be noted when examining answers to this topic is that different respondents may
have varied opinions as to what constitutes a 'major technology transfer'. The total
number of technology transfers compared to TTE are shown in Table 14. Curiously, the
most and least experienced firms have the best TTE scores, especially due to scheduling
components. However, there are only 4 firms with more than 20 transfers so the data are
somewhat questionable. As the judgement criteria relate to performance against the
planned schedule and budget and not the overall cost examined by Teece, it is not too
surprising that start-up technology transfers are good when compared to later transfers. It
is likely that more planning and resources were allocated to these technology transfers.
Table 14. The effect of technology transfer experience on the TTE score.
| Number of major technology transfers
| Num.
| TTE
| Start
| Finish
| Budget
|
| 0-1
| 6
| 2.94
| 2.67
| 2.67
| 3.50
|
| 2-5
| 21
| 3.40
| 3.29
| 3.67
| 3.24
|
| 6-10
| 13
| 3.44
| 3.25
| 3.75
| 3.33
|
| 10-20
| 9
| 3.26
| 3.33
| 3.22
| 3.22
|
| >20
| 4
| 3.00
| 2.75
| 3.00
| 3.25
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.4.2. Number of Previous Transfers of the Technology
The number of previous transfers of the technology has an effect on the technology
transfer performance (Zander and Kogut, 1995). Those surveyed were asked the number
of previous transfers of the technology to other manufacturing sites. The majority of
transfers were the first to any manufacturing site and all of the remainder except one were
the second transfer of the technology. Examining the data shows that technology transfer
is more efficient for the second implementation, especially in terms of meeting the
schedule. This is consistent with previous observations. However, it should be noted that
applying a 2-tail t test to compare the data for one implementation with those for two did
not find a difference that met the 95% significance level. There was a 30% chance that the
difference was due to chance (P[T<=t] = 0.315). Further t-tests were conducted to check
the significance of the differences of the start-time, finish-time and budget. When the
technology transfer is the second implementation of a technology difference, it is
significantly more likely to finish on schedule than the first implementation of a technology
(P[T<=t] = 0.037). Differences in start schedule and budget were not significant. This
result that subsequent transfers are more likely to finish on schedule is consistent with the
finding of Zander and Kogut (1995) that the number of previous implementations has an
effect on the speed of transfer.
Table 15. The effect of number of transfers of the same technology on the TTE score.
| Number of previous transfers
| Number
| TTE
| Start
| Finish
| Budget
|
| First implementation
| 40
| 3.32
| 3.18
| 3.54
| 3.26
|
| Second implementation
| 15
| 3.13
| 3.00
| 3.00
| 3.40
|
| Third implementation
| 1
| 3.67
| 4.00
| 4.00
| 3.00
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.5. The Effects of the Uniqueness of the Technology on TTE
4.5.1. The effect of the number of 'News'
Another relationship investigated was whether the transfer involved a new site, new
people, or a new process. In general Japanese firms will try to limit technology transfers
so that at most only one of these is new. The number of 'news' was scored as 0, 1, 2 or 3
depending on whether none or all three of these were new for the studied transfer. The
effect of this on TTE is shown in Table 16. The expected effect is not seen and the score
was best for the cases where all three were new, although with only 5 data the score can
be questioned. In any case the difference is not statistically significant.
Table 16. The effect of number of 'news' on the TTE score.
| Number of 'news' (site, people, process)
| Number
| TTE
| Start
| Finish
| Budget
|
| None
| 12
| 3.25
| 3.08
| 3.42
| 3.25
|
| One
| 20
| 3.38
| 3.35
| 3.45
| 3.35
|
| Two
| 19
| 3.22
| 3.06
| 3.39
| 3.22
|
| Three
| 5
| 3.13
| 2.80
| 3.20
| 3.40
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.5.2. The effect of uniqueness of technology
Zander and Kogut (1995) studied the relationship between the uniqueness of the
technology and speed of transfer. Technology that is common throughout an industry is
more easily transferred than unique technology. The effect of the uniqueness of TTE on
the transferred technology is shown below. There is no apparent correlation.
Table 17. The effect of uniqueness of technology on the TTE score.
| Uniqueness of Technology
| Number
| TTE
| Start
| Finish
| Budget
|
| Only used in Irish plant and by R&D.
| 16
| 3.25
| 2.94
| 3.38
| 3.44
|
| Only used by the company, but in more
than one manufacturing site.
| 19
| 3.30
| 3.11
| 3.44
| 3.33
|
| Used by a small number of firms.
| 12
| 3.39
| 3.25
| 3.58
| 3.33
|
| Common technology to anyone in the
industry.
| 8
| 3.21
| 3.38
| 3.13
| 3.13
|
| Common technology in many industries.
| 1
| 2.67
| 4.00
| 3.00
| 1.00
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.5.3. Defections of employees to competitors
Zander and Kogut (1995) also examined defections to competitors expecting that firms in
industries with a higher degree of mobility of employees between competitors were more
likely to have speedy knowledge transfer. This is observed in this study. The TTE for the
firms who have lost employees to competitors is lower than for those who have not.
However, application of t-test comparisons does not confirm it with 95% confidence
although the one tail t-test does meet the 90% confidence level (P[T<=t] = 0.077 for one
tail t-test).
Table 18. The relationship between defections to competitors and TTE score.
| Have any employees left the firm to the
benefit of a competitor?
| Number
| TTE
| Start
| Finish
| Budget
|
| No
| 44
| 3.34
| 3.23
| 3.49
| 3.30
|
| Yes
| 8
| 2.97
| 2.70
| 3.00
| 3.20
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.6. Importance of Travel and Links on TTE
It is widely accepted that there is no substitute for travel in order to best absorb all aspects
of technology to be transferred (e.g. Farrell, 1991). Travel in both directions is analysed,
both by employees of the Irish firm to head office or other sites and also by employees of
head office and other sites to the Irish site.
4.6.1. Travel abroad by Irish employees
The effect numbers of people travelling on TTE is shown in Table 19. The efficiency of
technology transfer is marginally better for firms with five or more employees travelling,
although the effect is not that significant. The majority of firms fall into this category.
There is no way of telling from the responses given, what the travel needs were in terms of
the scale of the project.
Table 19. The effect of number of travellers from Ireland on the TTE score.
| Number of Irish employees travelling
abroad
| Number
| TTE
| Start
| Finish
| Budget
|
| 0-1
| 3
| 3.78
| 3.33
| 4.00
| 4.00
|
| 2
| 3
| 3.33
| 3.33
| 3.33
| 3.33
|
| 3
| 10
| 3.27
| 3.20
| 3.40
| 3.20
|
| 4
| 7
| 3.38
| 3.29
| 3.43
| 3.43
|
| 5 or more
| 30
| 3.24
| 3.03
| 3.38
| 3.31
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.6.2. Travel to Ireland by employees from abroad
We see the same trend when examining the number of overseas employees travelling to
Ireland. Ignoring 0-1 travelling (only 2 data), there is an improvement in TTE with an
increasing number of travellers. This effect is most especially marked on project start
time. A t-test was used to compare sending 5 or more employees to Ireland with sending
fewer. The improvement on the start time schedule as a result of this easily meets the
95% confidence level (P[T<=t] = 0.021 for two tail t-test). This benefit due to travel
supports the finding made by Ghoshal and Bartlett (1988) that the positive benefits of
normative integration through organisational socialisation improves a multinational
company subsidiary's ability to contribute to different normative tasks.
Table 20. The effect of number of travellers to Ireland on the TTE score.
| Number of Overseas employees
travelling to Ireland
| Number
| TTE
| Start
| Finish
| Budget
|
| 0-1
| 2
| 3.00
| 3.00
| 3.00
| 3.00
|
| 2
| 16
| 3.40
| 3.38
| 3.56
| 3.25
|
| 3
| 7
| 3.48
| 3.43
| 3.86
| 3.14
|
| 4
| 5
| 3.33
| 3.50
| 3.25
| 3.25
|
| 5 or more
| 23
| 3.20
| 2.83
| 3.26
| 3.52
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.6.3. Changes to amount of travel from Ireland with subsequent transfers
But does the need for foreign travel decease with subsequent transfers? Respondents
were asked whether travel had increased or decreased relative to earlier transfers. The
data show that for over half of firms responding, more trips were made by Irish employees
than for previous transfers. The TTE value for these firms was close to average. The
small number of firms whose employees made fewer trips scored better. The effect is
statistically significant on the budget line.
Table 21. The effect of increasing the number of Irish travellers on the TTE score.
| Number of trips by Irish employees
compared to earlier technology transfers
| Number
| TTE
| Start
| Finish
| Budget
|
| More
| 29
| 3.29
| 3.07
| 3.46
| 3.32
|
| Same
| 16
| 3.38
| 3.25
| 3.50
| 3.38
|
| Fewer
| 8
| 3.13
| 3.38
| 3.25
| 2.75
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.6.4. Changes to amount of travel to Ireland with subsequent transfers
The same number of firms had more trips by overseas employees to Ireland as less when
compared to previous transfers. The same trend is seen as for trips by Irish employees.
The firms that require fewer trips to Ireland have a better TTE score than those that
required more travel. The score was better for budget and start schedule and was average
for finish schedule. The effect was not as marked as the effect of decreasing the number
of Irish travellers on the budget.
Table 22. The effect of increasing the number of travellers to Ireland on the TTE
score.
| Number of trips by overseas employees
to Ireland compared to earlier
technology transfers
| Number
| TTE
| Start
| Finish
| Budget
|
| More
| 19
| 3.39
| 3.21
| 3.58
| 3.37
|
| Same
| 14
| 3.31
| 3.15
| 3.31
| 3.46
|
| Fewer
| 19
| 3.19
| 3.16
| 3.42
| 3.00
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
The reason for this result is probably that money is saved when fewer people travel. This
benefits the bottom line. There are many cases when travel is necessary. However, these
results suggest that there is no significant benefit being gained from extra travel.
4.6.5. The effect of a key employee responsible for technology transfer
Some firms have an individual especially responsible for technology transfer. It is likely
that this person will make many trips each year to other company locations and to
vendors. It is possible that firms have such a person employed when technology transfers
are more difficult and more frequent. Examining the data shows that the firms that do not
have a key employee responsible for technology transfer have a better TTE score than the
firms that do. However, the result is not statistically significant. The effect is greatest on
start-time. For the firms that do have a key employee responsible for technology transfer
the TTE is lower when more trips are made. The score for firms where the key employee
makes eight trips or more is similar to the score for firms without a key employee. The
firms with the highest TTE are those with a key employee who makes 5 or fewer trips
each year.
Table 23. The effect of a key employee responsible for technology transfer on the
TTE score.
| Key Employee responsible for
technology transfer
| Number
| TTE
| Start
| Finish
| Budget
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
| no
| 17
| 3.08
| 2.81
| 3.25
| 3.19
|
| yes
| 39
| 3.36
| 3.28
| 3.46
| 3.33
|
| If yes, number of trips each year
|
| one trip
| 3
| 3.33
| 3.00
| 3.67
| 3.33
|
| two or three trips
| 12
| 3.50
| 3.50
| 3.67
| 3.33
|
| four or five trips
| 11
| 3.48
| 3.55
| 3.36
| 3.55
|
| six or seven trips
| 6
| 3.22
| 3.00
| 3.33
| 3.33
|
| eight or more trips
| 7
| 3.05
| 2.86
| 3.29
| 3.00
|
4.6.6. Strength of links with the main R&D site
Hansen (1999) proposed that firms with weak ties may be more efficient at sharing
knowledge across the organisation than those with stronger ties. To examine this thesis
firms were asked to rate the strength of links between the Irish operation and the main
R&D site. Comparing firms with strong and weak links, there is no significant difference
in TTE score.
Table 24. The effect of strength of links on the TTE score.
| Strength of links
| Number
| TTE
| Start
| Finish
| Budget
|
| Strong
| 40
| 3.23
| 3.05
| 3.33
| 3.33
|
| Weak
| 13
| 3.25
| 3.25
| 3.42
| 3.08
|
| Non-existent
| 1
| 4.00
| 4.00
| 5.00
| 3.00
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.7. Satisfaction and Commitment
4.7.1. Satisfaction with transferred technology
In his study Szulanski (1996) found that the greatest impediments to internal knowledge
transfer were factors such as the recipient's lack of absorptive capacity, causal ambiguity
and arduous relationship between source and recipient. Satisfaction could be used as a
metric for such analysis. But in order to allow meaningful comparisons with other aspects
of this study TTE will again be used as the major metric for determining effects. A
comparison of satisfaction data shows reasonable correlation with TTE.
Table 25. A comparison of technology transfer satisfaction with TTE score.
| Satisfaction with technology transfer
| Number
| TTE
| Start
| Finish
| Budget
|
| Very satisfied.
| 22
| 2.95
| 2.68
| 3.05
| 3.14
|
| Satisfied.
| 30
| 3.42
| 3.47
| 3.50
| 3.30
|
| Neither satisfied nor dissatisfied.
| 0
|
| Slightly disappointed.
| 2
| 4.17
| 3.50
| 5.00
| 4.00
|
| Very disappointed.
| 1
| 4.33
| 3.00
| 5.00
| 5.00
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
| Satisfaction with performance of
transferred technology
| Number
| TTE
| Start
| Finish
| Budget
|
| Very satisfied.
| 18
| 2.96
| 2.72
| 3.06
| 3.11
|
| Satisfied.
| 28
| 3.33
| 3.21
| 3.43
| 3.36
|
| Neither satisfied nor dissatisfied.
| 3
| 3.44
| 3.33
| 3.33
| 3.67
|
| Slightly disappointed.
| 4
| 3.75
| 4.25
| 4.00
| 3.00
|
| Very disappointed.
| 2
| 4.17
| 3.50
| 5.00
| 4.00
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.7.2. Commitment to technology transfer process
A good working relationship is consistent with better TTE scores. Commitment at both
sides correlates very slightly with TTE score, but in most cases commitment was only at
the highest levels so there is not much data for drawing conclusions. There are no obvious
difference in the TTE score with respect to managerial capability and the technical know-
how of the technology-receiving workforce.
Table 26. The importance of a good working relationship on the TTE score.
| Working Relationship of technology
exporting and importing teams
| Number
| TTE
| Start
| Finish
| Budget
|
| Excellent understanding
| 19
| 3.07
| 2.84
| 3.11
| 3.26
|
| Good understanding
| 32
| 3.36
| 3.22
| 3.56
| 3.31
|
| Neutral
| 3
| 3.56
| 3.67
| 3.67
| 3.33
|
| Poor or strained understanding
| 1
| 3.67
| 5.00
| 3.00
| 3.00
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
Table 27. The effect of commitment of exporting sites on the TTE score.
| Commitment of exporting site to
technology transfer
| Number
| TTE
| Start
| Finish
| Budget
|
| Very committed.
| 26
| 3.19
| 2.96
| 3.31
| 3.31
|
| Committed
| 21
| 3.38
| 3.45
| 3.40
| 3.30
|
| Neutral.
| 7
| 3.33
| 3.00
| 3.71
| 3.29
|
| Not committed
| 2
| 3.17
| 3.00
| 3.50
| 3.00
|
| Difficult
| 0
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
Table 28. The effect of commitment of exporting sites on the TTE score.
| Commitment of Irish top management
to technology transfer
| Number
| TTE
| Start
| Finish
| Budget
|
| Very committed.
| 51
| 3.27
| 3.10
| 3.42
| 3.30
|
| Committed
| 4
| 3.42
| 3.75
| 3.25
| 3.25
|
| Neutral.
| 0
|
| Not committed
| 0
|
| Difficult
| 1
| 3.00
| 3.00
| 3.00
| 3.00
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.7.3. The effect of qualifications and capability
In his study Szulanski (1996) found that any weaknesses in the qualifications or
capabilities of the technology transferee were an impediment to transfer. Their effect was
measured.
Table 29. The effect of level of qualification of the Irish workforce on the
TTE score.
| Were the Irish staff well trained and
educated to readily absorb new
technology?
| Number
| TTE
| Start
| Finish
| Budget
|
| Most definitely.
| 35
| 3.25
| 3.18
| 3.32
| 3.24
|
| yes, sort of.
| 18
| 3.30
| 3.11
| 3.50
| 3.28
|
| no opinion
| 2
| 3.83
| 3.00
| 4.00
| 4.50
|
| no, not really
| 0
|
| Definitely not.
| 1
| 3.00
| 3.00
| 3.00
| 3.00
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
Table 30. The effect of managerial capability on the TTE score.
| Irish managerial capability of absorbing
new technology
| Number
| TTE
| Start
| Finish
| Budget
|
| Very strong
| 30
| 3.24
| 3.03
| 3.38
| 3.31
|
| Strong
| 23
| 3.30
| 3.22
| 3.43
| 3.26
|
| no opinion
| 2
| 3.67
| 4.00
| 3.50
| 3.50
|
| Weak
| 1
| 3.00
| 3.00
| 3.00
| 3.00
|
| Very weak
| 0
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.7.4. Training and documentation
The ease with which operators are trained in the transferred technology correlates with a
better TTE score. Also, there was a slightly better TTE score when the quality of training
in the transferred process was perceived as better. The improved scores are mainly as a
result of better scheduling, both start time and finish time. The latter can be intuitively
understood because being able to complete training speedily will allow the project to
completed in good time. The correlation between quality of training and good adherence
to the start schedule is less clear. Perhaps, when the project starts in good time, it allows
more effort to be spent on training that might otherwise have to be spent on other matters.
There is no obvious correlation between the TTE score and the quality of documentation.
Table 31. The correlation of ease of training in new technology with the
TTE score.
| Ease of training operators in
transferred technology
| Number
| TTE
| Start
| Finish
| Budget
|
| Very easy.
| 10
| 2.87
| 2.60
| 2.80
| 3.20
|
| Easy.
| 18
| 3.22
| 3.12
| 3.29
| 3.24
|
| Neither easy nor difficult.
| 21
| 3.48
| 3.29
| 3.71
| 3.43
|
| Difficult.
| 6
| 3.56
| 3.50
| 3.67
| 3.50
|
| Very difficult.
| 1
| 2.67
| 4.00
| 3.00
| 1.00
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
Table 32. The correlation of quality of training in new technology with the
TTE score.
| Quality of training in transferred
process
| Number
| TTE
| Start
| Finish
| Budget
|
| Excellent
| 17
| 3.21
| 3.00
| 3.38
| 3.25
|
| Good
| 28
| 3.26
| 3.18
| 3.29
| 3.32
|
| Adequate.
| 10
| 3.47
| 3.30
| 3.80
| 3.30
|
| Poor
| 1
| 3.00
| 3.00
| 3.00
| 3.00
|
| Useless
| 0
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
Table 33. The correlation of documentation quality of new technology with
TTE score.
| Quality of documentation for
transferred technology
| Number
| TTE
| Start
| Finish
| Budget
|
| Complete, easy to understand
documentation was received for the entire
process.
| 16
| 3.33
| 3.00
| 3.60
| 3.40
|
| Adequate documentation for most of the
transferred process was received.
| 28
| 3.26
| 3.21
| 3.29
| 3.29
|
| Basic documentation was provided.
| 7
| 3.10
| 2.86
| 3.00
| 3.43
|
| Poor documentation was received for the
process.
| 4
| 3.58
| 3.75
| 4.25
| 2.75
|
| No documentation was received for the
process.
| 0
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.8. Application of New Business Processes to Technology Transfer
4.8.1. Application of Business Improvement Initiatives to Technology Transfer
In a recent study Quazi and Bartels (1998) studied the application of TQM principles to
international technology transfer processes. In this study, those surveyed were asked
whether they had applied TQM or its newer incarnation, 6?, to the technology transfer
process. The effect on TTE was examined. The same question was asked about other
business improvement methods - Business Process Engineering, Benchmarking, Integrated
Technologies and Lean Thinking. In the analysis around 50% of firms had applied TQM
or 6? and benchmarking to technology transfer. There was no benefit with the TTE value
close to average. Fewer firms applied the other 3 methods and those who did had lower
TTE values.
Table 34. The effect of application of business improvement initiatives to the
TTE score.
| Process Improvement Method
| Number
| TTE
| Start
| Finish
| Budget
|
| Business Process Reengineering (BPR)
| 10, 18%
| 3.10
| 3.30
| 3.10
| 2.90
|
| Total Quality Management (TQM) or 6?
| 27, 52%
| 3.30
| 3.21
| 3.57
| 3.11
|
| Benchmarking
| 29, 48%
| 3.28
| 3.19
| 3.31
| 3.35
|
| Integrated Technologies
| 9, 16%
| 3.08
| 3.00
| 3.00
| 3.25
|
| Lean Thinking
| 15, 27%
| 3.24
| 3.14
| 3.43
| 3.14
|
| Total
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.8.2. The effect of Internet usage on TTE
The effect of usage of the Internet on technology transfer was also examined. The use of
the World Wide Web for international technology transfer was studied Hoetker (1997). In
the survey respondents were asked to rate the extent of their usage of the Internet for
technology transfer. The responses were rated extensive use, limited use or no use. There
is no apparent effect due to Internet usage on technology transfer performance, TTE.
Firms that made limited usage of the Internet scored slightly better than those that made
either extensive usage or no use.
Table 35. The effect of Internet usage on the TTE score.
| Extent of Internet Usage for
Technology transfer
| Number
| TTE
| Start
| Finish
| Budget
|
| Extensive usage
| 9
| 3.46
| 3.00
| 3.38
| 3.25
|
| Limited usage
| 32
| 3.23
| 3.18
| 3.29
| 3.32
|
| No usage.
| 12
| 3.36
| 3.30
| 3.80
| 3.30
|
| Total
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.9. Research and Development
4.9.1. Effect of duration of R&D in Ireland on TTE
An increasing number of pharmaceutical and medical device firms are carried our research
and development in Ireland. The question was asked about whether firms had research
facilities and for how long they had had them. The results are compared with TTE scores.
There is no positive benefit on TTE score to having R&D facilities in Ireland. Duration of
R&D does not make much difference.
Table 36. The effect of Irish based R&D facilities on the TTE score.
| R&D facilities in Ireland
| Number
| TTE
| Start
| Finish
| Budget
|
| None
| 26
| 3.24
| 3.16
| 3.28
| 3.28
|
| 0-1 year
| 14
| 3.24
| 3.07
| 3.29
| 3.36
|
| 2-5 years
| 9
| 3.70
| 3.44
| 4.11
| 3.56
|
| 6-10 years
| 3
| 2.33
| 2.00
| 2.67
| 2.33
|
| 11-20 years
| 5
| 3.42
| 3.50
| 3.50
| 3.25
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.9.2. Effect of complexity of R&D in Ireland on TTE
In his study of the complexity of R&D in affiliates of multinational firms in the UK,
Taggart (1998) graded the complexity of R&D from 0-6. In this survey the participants
were asked to rate the R&D conducted at their site using similar criteria. The comparison
is then made to TTE. Again there is no apparent benefit to conducting R&D on
technology transfer performance. Fewer firms do no R&D (18) than firms that have no
R&D facilities (26). This indicates that some firms conduct research without specific
facilities. Categories 2 and 4 are the most popular for those conducting research of firms
who conduct R&D. Because the vast majority of multinational firms operating in Ireland
export most of their production categories 1 and 3 are not important. Only 4 firms carry
out the most advanced R&D. These firms (category 5) have the best TTE score, although
their limited number makes this result questionable. The next category down (4) had the
poorest TTE score and it is considerably worse than companies conducting no R&D.
Table 37. The effect of complexity of Irish based R&D on the TTE score.
| Complexity of R&D conducted in Ireland
| Number
| TTE
| Start
| Finish
| Budget
|
| None
| 18
| 3.25
| 3.18
| 3.29
| 3.29
|
| Basic customer technical services.
| 2
| 3.17
| 3.50
| 3.50
| 2.50
|
| Ability to adapt manufacturing processes to
local needs and requirements.
| 11
| 3.18
| 3.09
| 3.18
| 3.27
|
| Capability to develop new and improved
products and/or processes for use in the
Irish market or Irish manufacturing sites.
| 3
| 3.00
| 2.67
| 3.33
| 3.00
|
| Capability to develop new and improved
products and/or processes for use world-
wide.
| 18
| 3.49
| 3.35
| 3.76
| 3.35
|
| Competence to develop new forms and
levels of technology for corporate parent.
| 4
| 2.92
| 2.25
| 2.75
| 3.75
|
| mean
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.9.3. Global product development
Subramaniam et al. (1998) studied the usage of global product development teams. In this
survey the companies were asked about he usage of cross-national teams for product and
process development and about Irish participation in such teams. The majority of firms
use such teams and there are Irish members on most of these teams. The TTE scores are
slightly better for companies that use global teams and are better again when there is Irish
participation. However, the results are not statistically significant. This demonstrates that
the inclusion of Irish based employees in product and process development may marginally
improve the efficiency of the technology transfer process.
Table 38. The effect of global R&D teams on the TTE score.
| Usage of global teams for product and
process development
| Number
| TTE
| Start
| Finish
| Budget
|
| Global teams
| 39, 70%
| 3.24
| 3.13
| 3.38
| 3.21
|
| Global teams with Irish members
| 38, 68%
| 3.19
| 3.05
| 3.30
| 3.22
|
| Total
|
| 3.28
| 3.15
| 3.40
| 3.29
|
In their study of knowledge creating companies, Nonaka and Takeuchi (1995) proposed 4
different product development processes which were described using mostly sporting
analogies. These analogies were described and the participants in the survey were asked
to pick the analogy that best described their firm's new product development process. The
results are listed below and compared with TTE. The rugby approach is most popular in
the medical device and pharmaceutical industries. The relay approach is not popular in
the industries studied where more overlap of different stages is required. The one result
here is not enough to draw a meaningful conclusion. Companies using the more modern
American Football method in which a project manager co-ordinates the various 'special
teams' score slightly better than companies using the more traditional rugby approach.
Table 39. The effect of new product development approach on the TTE score.
| New Product development process
| Number
| TTE
| Start
| Finish
| Budget
|
| Relay
| 1
| 3.00
| 3.00
| 3.00
| 3.00
|
| Sashimi
| 13
| 3.33
| 3.08
| 3.54
| 3.38
|
| Rugby
| 33
| 3.29
| 3.22
| 3.41
| 3.25
|
| American Football
| 7
| 3.10
| 2.86
| 3.14
| 3.29
|
| Total
|
| 3.28
| 3.15
| 3.40
| 3.29
|
4.10. Recommended Practices
In addition to the specific questions requiring a numerical or multiple choice response, two
open-ended questions were asked which sought information about specific practices which
aided and which hindered the technology transfer process.
4.10.1. Recommended practices and methods
Forty-eight respondents provided an answer to the question which asked them to list
specific practices or methods which aided the technology transfer process. Twenty-eight
answered the question which asked for a list of specific practices or methods, or absence
of practices, which hindered the technology transfer process. The full list of responses is
given in Appendix C.
Excel string functions were used to analyse the responses to find the out which
practices were referred to most often. Verb roots were used instead of full words in some
cases to allow all variants of the same idea to be counted. The word which appears most
frequently is project (20 times). On most occasions as project management (11 times), but
also as project planning, project team etc. Indeed, the word management appears with the
next greatest frequency (15 times) and words with the root plan are also common (8
times). Clearly the point stressed most often in the responses is the importance of good
project management or planning.
Table 40. The frequency with which words appear in answers to best practice.
| Word
| Frequency
| Word
| Frequency
|
| project
| 20
| train
| 6
|
| manag
| 15
| planning
| 5
|
| team
| 12
| procedure
| 4
|
| project management
| 11
| document
| 4
|
| meet
| 10
| procedure
| 4
|
| communicat
| 9
| review
| 4
|
| plan
| 8
| conferenc
| 3
|
| visit
| 7
| validation
| 2
|
Words containing team are the next most frequent (12 times). Good teamwork is
stressed as being important by many of the respondents. The importance of meetings (10
mentions), good communication (9 times) and visits (7 mentions) are also stressed. Other
practices mentioned several times are training (6 times), procedures (4) times and
documentation (4 times). Therefore the practices that were considered most important
overall by the respondents are project management/planning, teamwork, communications
(also meetings and visits), training, clear procedures and documentation.
Other practices of interest mentioned a few times are conferences calls, validation
procedures, benchmarking, information sharing, the use of existing production methods,
contract with specialist equipment companies, supplier management, risk analysis,
ISO9002 and good on-site management.
4.10.2. Practices and methods not recommended
Fewer respondents (28) noted practices that hindered and the string analysis used to
analyse the best practices was not useful. The word used most often and only 3 times was
validation. The opposites of the best practices all receive a few mentions, e.g. poor
planning, training issues, poor communication and documentation. Inadequate
communications and incompatible goals due to causal ambiguity and an arduous
relationship between recipient and source are frequent complaints. 'Moving goalposts' is
mentioned. Also mentioned are lack of delegation, the Atlantic Ocean, language, supplier
issues, inadequate specifications, different machine safety directives, climate control,
inadequate resources and scale-up issues.
There is a greater variety of problems mentioned than good practices, even with
around half the number of responses. In general the problems can be grouped together
and are opposite to the good practices most frequently mentioned. Good planning,
communications, teamwork, training, procedures and documentation would prevent most
of the problems mentioned from occurring.