Abstract A new strategy is introduced for estimating population size and networked population characteristics. Sample selection is based on a multi-wave snowball sampling design. A generalized stochastic block model is posited for the population's network graph. Inference is based on a Bayesian data augmentation procedure. Applications are provided to simulated populations and an empirical population. The results demonstrate that statistically efficient estimates of the size and distribution of the population can be achieved.
The study aim was to compare different predictive models in one repetition maximum (1RM) estimation from load-velocity profile (LVP) data. Fourteen strength-trained men underwent initial 1RMs in the free-weight back squat, followed by two LVPs, over three sessions. Profiles were constructed via a combined method (jump squat (0 load, 30–60% 1RM) + back squat (70–100% 1RM)) or back squat only (0 load, 30–100% 1RM) in 10% increments. Quadratic and linear regression modeling was applied to the data to estimate 80% 1RM (kg) using 80% 1RM mean velocity identified in LVP one as the reference point, with load (kg), then extrapolated to predict 1RM. The 1RM prediction was based on LVP two data and analyzed via analysis of variance, effect size (g/ηp2), Pearson correlation coefficients (r), paired t-tests, standard error of the estimate (SEE), and limits of agreement (LOA). p < 0.05. All models reported systematic bias < 10 kg, r > 0.97, and SEE < 5 kg, however, all linear models were significantly different from measured 1RM (p = 0.015 <0.001). Significant differences were observed between quadratic and linear models for combined (p < 0.001; ηp2 = 0.90) and back squat (p = 0.004, ηp2 = 0.35) methods. Significant differences were observed between exercises when applying linear modeling (p < 0.001, ηp2 = 0.67–0.80), but not quadratic (p = 0.632–0.929, ηp2 = 0.001–0.18). Quadratic modeling employing the combined method rendered the greatest predictive validity. Practitioners should therefore utilize this method when looking to predict daily 1RMs as a means of load autoregulation.
This study investigated the inter-day and intra-device reliability, and criterion validity of six devices for measuring barbell velocity in the free-weight back squat and power clean. In total, 10 competitive weightlifters completed an initial one repetition maximum (1RM) assessment followed by three load-velocity profiles (40–100% 1RM) in both exercises on four separate occasions. Mean and peak velocity was measured simultaneously on each device and compared to 3D motion capture for all repetitions. Reliability was assessed via coefficient of variation (CV) and typical error (TE). Least products regression (LPR) (R2) and limits of agreement (LOA) assessed the validity of the devices. The Gymaware was the most reliable for both exercises (CV < 10%; TE < 0.11 m·s−1, except 100% 1RM (mean velocity) and 90‒100% 1RM (peak velocity)), with MyLift and PUSH following a similar trend. Poorer reliability was observed for Beast Sensor and Bar Sensei (CV = 5.1–119.9%; TE = 0.08–0.48 m·s−1). The Gymaware was the most valid device, with small systematic bias and no proportional or fixed bias evident across both exercises (R2 > 0.42–0.99 LOA = −0.03–0.03 m·s−1). Comparable validity data was observed for MyLift in the back squat. Both PUSH devices produced some fixed and proportional bias, with Beast Sensor and Bar Sensei being the least valid devices across both exercises (R2 > 0.00–0.96, LOA = −0.36–0.46 m·s−1). Linear position transducers and smartphone applications could be used to obtain velocity-based data, with inertial measurement units demonstrating poorer reliability and validity.
This paper explores the impact of turnover and restructuring on labour productivity in the Polish economy over the period 1988-1993. Changes in aggregate productivity are decomposed into elements corresponding to productivity growth among survivors, market share growth by survivors and the contributions of entering and exiting firms. The traditional entry and exit effects begin to work as transition to a market economy progresses. However, initial productivity improvements are due to changes to market shares of the existing firms following the break-up of large enterprises. Regression analysis shows that changes in the firm-level productivity are affected by restructuring and a more competitive economic environment.
ABSTRACTUsing a matched sample of 1959 firms and 27,263 employees from the UK Workplace Employee Relations Survey, we examine the effects of the management buyout (MBO) organizational form on employee discretion and supervision. Our findings suggest that for MBO firms, supervision is lower where there is a higher proportion of craft and skilled service workers but is not lower for other occupational groups. Using random effects ordered probit analysis, we find that employees' discretion over their work practices is higher in MBO firms; and that the probability of higher discretion is greater where there is a higher proportion of craft and skilled service employees. Our findings are consistent with: (i) MBOs reducing hierarchical tiers and the number of supervisory staff, which increase employees' span of control and their discretion; and (ii) organizational change via an MBO being 'skill biased' in favour of craft and skilled service employees.
This paper explores the influence of acquisition costs on the choice between the takeover and joint venture modes of obtaining the resources required for diversifying expansion. It uses the conditions created by privatisation in the UK utility sector as a natural experiment to examine the determinants of mode choice across groups of firms with unusually homogeneous opportunity sets. The empirical design is able to incorporate acquirer, target and geographical market variables as explanatory factors in mode choice. It is shown that the form of diversifying expansion adopted is highly sensitive to the anticipated costs of using the acquisition process.
This paper examines corporate governance in management buy‐outs and buy‐ins and in particular considers the problems faced by venture capitalists as active investors. Evidence is presented based on large scale surveys and case studies. The study suggests the importance of achieving a balance between the independence of venture capitalists as monitors of management and the need for cooperation in their relationships with managers in buy‐outs and buy‐ins. The study also questions the adequacy with which financiers as active investors have taken account of the differing attributes of each type of transaction, particularly in relation to access to information and the roles of management. The costs of closely monitoring smaller investments may often exceed the benefits, which helps explain why the greater control found in buy‐ins is more likely to be indirect rather than greater board representation. The evidence suggests the need for a flexible approach to governance under which the forms adopted take account of the specific circumstances of a particular enterprise.