Assessing the contribution to innovation of private equity investors: A study on European buyouts

The paper provides an empirical analysis of the patenting activity of a sample of Western European manufacturing firms undergoing a buyout between 1998 and 2004. A panel data design is used to test whether the characteristics of the deal and of private equity (PE) firms can affect acquired companies’ subsequent innovation effort as measured by the number of patents granted by the EPO. Results support the view that the innovation activity of portfolio firms is affected by different types of investors, pursuing different objectives and differing in their risk propensity, expected returns and investment policies. The characteristics of lead investors (size, stage specialization, geographical location) and of the deal (amount invested, presence of multiple investors) are also investigated and are found to differently affect the post-buyout innovation activity of sample firms.     

Evaluating the usability and instructional design quality of Interactive Virtual Training for Teachers (IVT-T)

Educational technology research and development - Simulation offers unique affordances over traditional training (e.g., remote access, mastery learning experiences, immediate feedback) relevant to...     

Measuring the influence of mere exposure effect of TV commercial adverts on purchase behavior based on machine learning prediction models

Since its introduction, television has been the main channel of investment for advertisements in order to influence customers purchase behavior. Many have attributed the mere exposure effect as the source of influence in purchase intention and purchase decision; however, most of the studies of television advertisement effects are not only outdated, but their sample size is questionable and their environments do not reflect reality. With the advent of the internet, social media and new information technologies, many recent studies focus on the effects of online advertisement, meanwhile the investment in television advertisement still has not declined. In response to this, we applied machine learning algorithms SVM and XGBoost, as well as Logistic Regression, to construct a number of prediction models based on at-home advertisement exposure time and demographic data, examining the predictability of Actual Purchase and Purchase Intention behaviors of 3000 customers across 36 different products during the span of 3 months. If we were able to predict purchase behaviors with models based on exposure time more reliably than with models based on demographic data, the obvious strategy for businesses would be to increase the number of adverts. On the other hand, if models based on exposure time had unreliable predictability in contrast to models based on demographic data, doubts would surface about the effectiveness of the hard investment in television advertising. Based on our results, we found that models based on advert exposure time were consistently low in their predictability in comparison with models based on demographic data only, and with models based on both demographic data and exposure time data. We also found that there was not a statistically significant difference between these last two kinds of models. This suggests that advert exposure time has little to no effect in the short-term in increasing positive actual purchase behavior.     

Scaling isometric mid-thigh pull maximum strength in division I Athletes: are we meeting the assumptions?

ABSTRACT

This study examined the validity of various scaling methods, isometric mid-thigh pull (IMTP) peak force using various scaling methods, and the relationships between IMTP peak force and countermovement jump height. Fifty-one collegiate baseball and soccer athletes performed two maximal IMTPs. Absolute peak force was compared between teams and when data were scaled using ratio (RS), traditional allometric (ALLO_Trad), and fitted allometric (ALLO_Fit) scaling. ALLO_Trad and ALLO_Fit validity was violated because different derived exponents existed for baseball (b = 0.20) and soccer (b = 1.20). Soccer athletes produced greater RS peak force compared to baseball (p = 0.012), while no difference existed with absolute, ALLO_Trad or ALLO_Fit (all p > 0.05) peak force. Moderate relationships existed between body mass and absolute (r = 0.402, p = 0.003) and RS (r = -0.328, p = 0.019) peak force, while trivial relationships existed with ALLO_Trad and ALLO_Fit (both r < -0.10, p > 0.05). Trivial relationships existed between countermovement jump height and absolute, RS, ALLO_Trad, and ALLO_Fit (all r < 0.20, p > 0.05) peak force. The current dataset violated allometric scaling assumptions, making it inappropriate to use ALLO_Trad and ALLO_Fit scaling. Practitioners must understand the assumptions, limitations, and purpose of scaling methods.     

Development of expertise in elite and sub-elite British rugby league players: A comparison of practice experiences

Previous studies have investigated how individuals reach an expert level by counting the number of hours engaged in specific practice types. Here we sought to understand and compare the microstructure (e.g. practice tasks undertaken) of these practice hours experienced by elite and sub-elite British rugby league players. Semi-structured interviews explored the practice experiences of eight international and eight domestic level players. A two-staged thematic analysis was used to interpret the data. The analysis revealed that both player groups experienced a rich and narrow landscape of affordances and were exposed to early diversification of sports experiences during childhood. Differences were identified in domestic level players’ experiences of amateur and professional sports, where episodes of negative developmental environments were reported. International players’ practice experiences revealed differences in their professional careers, where exposure to scenario-based practice and dynamic learning environments were reported. The findings suggest that insights from ecological dynamics provide a suitable theoretical framework to guide coaches in the design of practice environments that should consider the physical, psychological, emotional and social dimensions of expertise acquisition.     

An intensive study of the reliability of Rhode Island Pupil Identification Scale

A recent study of the factorial structure of the Rhode Island Pupil Identification Scale (RIPIS), a pupil behavior-observation scale for use by classroom teachers for detecting young children with learning problems, has led to profile scoring. This study describes the procedures and the results of an intensive and comprehensive investigation of the homogeneity of the subscales and their reliabilities as well as those of the two profiles yielded by the scale. All subscales, profiles, and composites were found to be highly internally consistent and stable over a time interval of five months. The authors also wish to show why complex psychometric scales require that more than cursory attention be paid to reliability issues.     

Reliability of a commercially available and algorithm-based kinetic analysis software compared to manual-based software

There is a need for reliable analysis techniques for kinetic data for coaches and sport scientists who employ athlete monitoring practices. The purpose of the study was: (1) to determine intra- and inter-rater reliability within a manual-based kinetic analysis program; and (2) to determine test-retest reliability of an algorithm-based kinetic analysis program. Five independent raters used a manual analysis program to analyse 100 isometric mid-thigh pull (IMTP) trials obtained from previously collected data. Each trial was analysed three times. The same IMTP trials were analysed using an algorithm-based analysis software. Variables measured were peak force, rate of force development from 0 to 50 ms (RFD50) and RFD from 0 to 200 ms (RFD200). Intraclass correlation coefficients (ICC) and coefficient of variation (CV) were used to assess intra- and inter-rater reliability. Nearly perfect reliability was observed for the manual-based (ICC > 0.92). However, poor intra- and inter-rater CV was observed for RFD (CV > 16.25% and CV > 32.27%, respectively). The algorithm-based method resulted in perfect reliability in all measurements (ICC = 1.0, CV = 0%). While manual methods of kinetic analysis may provide sufficient reliability, the perfect reliability observed within the algorithm-based method in the current study suggest it is a superior method for use in athlete monitoring programs.