The growth dynamics of technology-based firms in Scotland

In recent years high growth firms (HGFs) undertaking rapid, transformative growth, have been identified as important contributors to economic growth (Acs et al, 2008; Anyadike-Danes et al, 2009; OECD, 2010). For a wide variety of reasons, notably their contribution to employment growth, high export intensity, strong contribution to productivity growth and innovation, HGFs have been hailed as vital drivers of economic competitiveness (Henrekson and Johansson, 2010). As a consequence, these firms (often referred to as 'gazelles'), have been accorded a central role in many economic development strategies at both national and regional levels, especially during a time of economic austerity where employment growth has been an overriding policy goal for many governments (BERR, 2008; NESTA, 2011; OECD, 2010; Scottish Enterprise, 2011). Yet despite the strong policy focus on the promotion of HGFs in recent times, much remains unknown about these organisations and how best to support them (Henrekson and Johansson, 2010; Anyadike-Danes et al, 2012; Mason and Brown, forthcoming). Scottish Enterprise recently commissioned research on Scotland’s population of HGFs (Mason and Brown, 2010). This was the first comprehensive analysis of these firms ever conducted in Scotland and some of the findings were published in this journal (Brown and Mason, 2010). One of the most significant conclusions from this study was that they are extremely heterogeneous in terms of their age, size, ownership and industry sector. Few fit the stereotypical ‘gazelle’ definition which refers to young high growth firms that are less than five years old. The vast majority are over 10 years old, with some significantly older (Mason and Brown, 2010). Furthermore, only a relatively small proportion of these firms are in high-tech areas of the economy. According to some scholars, there is ‘no evidence that Gazelles are overrepresented in high- technology industries’ (Henrekson and Johansson, 2010, p.240). Despite their strong prioritisation by policy makers, the reality is that the representation of technology based firms (TBFs) in the population of HGFs is roughly on a par with their proportion in the economy (Mason and Brown, forthcoming). In view of these twin priorities of promoting high growth in general and high tech firms in particular, Scottish Enterprise commissioned further research to explore HGFs, especially in high tech areas of the economy. The objectives of this paper are twofold: to provide an update on the level of HGFs in Scotland and to assess the population of TBFs in Scotland. The paper proceeds as follows. First, the terms high growth and technology-based enterprises are defined. Second, the methodology is outlined. Third, the aggregate evidence on the levels of HGFs in Scotland is presented. Fourth, the population of TBFs in Scotland, including analysis of high growth TBFs is profiled. Fifth, some of the key characteristics of high growth TBFs in Scotland are examined. Sixth, some of features of these firms which were captured during the qualitative part of this research process are summarised. The paper finishes with some brief conclusions and issues for further research

MARATHON STRIDE RATE DYNAMICS: A CASE STUDY

The purpose of this study was to investigate stride rate (SR) dynamics of a recreational runner participating in his debut marathon. Tibial accelerometry data obtained during a half marathon (R1) and marathon (R2) were utilised. SR data were extracted utilising novel computational methods and descriptive statistics were utilised for analysis of R2, and comparison of the first half of the marathon (R2half) to R1. Results indicate that the participant employed comparable SR strategy in R1 and R2half. For R2 a combined decreasing trend in SR and increased variance in SR from 30 km (R2 =0.0238) was observed. Results indicate that the participant had the ability to maintain SR strategy for the first half of the marathon, however as fatigue onset occurred this ability decreased. Running strategies on SR during fatigue may be of future use to recreational runners

COMPARISON OF ACCELEROMETRY STRIDE TIME CALCULATION METHODS

The purpose of this study was to investigate how a newly proposed method of stride time calculation, utilising data filtered at 2 Hz, compared to previous methods. Tibial accelerometry data for 6 participants completing half marathon running training were collected. One run was selected for each participant at random, from which five consecutive running strides were ascertained. Four calculation methods were employed to derive each stride time and results were compared. No significant difference was found between methods (p=1.00). The absolute difference in stride time, when comparing the proposed method to previous methods, ranged from 0.000 seconds to 0.039 seconds. Filtered data could offer a simplified technique for stride time output during running gait analysis, particularly when applied during automated data processing for large data sets

A STUDY TO INVESTIGATE THE RELIABILITY AND CONSISTENCY OF THE SPORTS TUTOR TENNIS CUBETM VELOCITY, TRAJECTORY AND LANDING POINTS

The purpose of this study was to investigate the reliability and consistency of the Sports Tutor Tennis CubeTM ball launcher. Five identical (mass, diameter) competition standard tennis balls were each launched twenty-five times and flight was assessed using 3D infra red motion analysis. 3D resultant velocity was found to be 18.9 ± 0.89 m/s, landing points had a coefficient of variation in the lateral direction of 8.28% and 18.4% in the vertical direction Trajectory was also projected to estimate ball carry showing ball flight range (horizontal spread) of 14.9 ± 3.71 m. Results showed that whilst the commercially popular tennis ball launcher was stroke specific, it exhibited a level of variability This could be seen to bring variance to tennis players’ practice that they once thought did not occur with the use of tennis ball machines

A METHOD TO QUANITIFY MOVEMENT VARIABILITY OF HIGHLY SKILLED GOLFERS PERFORMING DRIVER SWINGS

Variability has been described as inherent in the golf swing (Bradshaw et al., 2009), yet its impact on outcome is not understood. It is necessary to quantify the levels of movement variability before this relationship can be examined effectively. Thus, the aim of this study was to develop a method to quantify movement variability of golfers performing driver swings. 16 highly skilled golfers each performed 10 swings wearing retro reflective markers which were tracked by a 3D motion analysis system operating at 400Hz. Movement variability was calculated for each marker using scalene ellipsoid volume methods; a score representative of the 3D variability over 10 trials was then calculated. The variability levels calculated using this method showed increasing variability from the closed end of the chain (malleoli) to the open end of the chain (wrists)

THE CREATION AND VALIDATION OF A LARGE-SCALE COMPUTER MODEL OF THE GOLF SWING

The aim of this study was to create and validate a full-body musculoskeletal model of a golfer performing a swing with their driver club. An elite female participant performed ten shots with her driver while wearing retro-reflective markers. An optical 3-D 6-camera system captured the kinematics of the markers at 400 Hz on the participant for each trial. A launch monitor device recorded the ball and club head conditions at impact. The kinematic data from one representative trial was selected to drive inverse and forward dynamics simulations of the created model. The validation results showed a very high level of agreement between experimental and simulated trajectories for selected markers (mean r = 0.966

THE EFFECT OF THE APPLICATION OF DIFFERENT LEVELS OF MOVEMENT VARIABILITY ON MOVEMENT OUTCOME

The aim of this study was to assess the effect of the application of a previously validated golfer computer model on different levels of movement variability relative to a shot outcome measure: club head velocity. Movement variability was applied to the computer model on six measures sequentially throughout the body of the computer model. Four different levels of variability, 25%, 50%, 75% and 100% variability, were applied to x, y and z positional data of the aforementioned measures. Simulations were then performed with ADAMS/LifeMOD software for each level of movement variability applied to the measures in question. Club head velocity was measured during the simulation. The results suggest that movement variability application at these landmarks does not have an effect on outcome. These results potentially have implications for the coaching of the participant

Scottish care leavers covenant & agenda for change : what's the big idea?

[no abstract available