Service staff attitudes, organisational practices and performance drivers

We provide conceptual and empirical insights elucidating how organizational practices influence service staff attitudes and behaviors and how the latter set affects organizational performance drivers. Our analyses suggest that service organizations can enhance their performance by putting in place strategies and practices that strengthen the service-oriented behaviors of their employees and reduce their intentions to leave the organization. Improved performance is accomplished through both the delivery of high quality services (enhancing organizational effectiveness) and the maintenance of frontline staff(increasing organizational efficiency). Specifically, service-oriented business strategies in the form of organizational-level service orientation and practices in the form of training directly influence the manifest service-oriented behaviors of staff. Training also indirectly affects the intention of frontline staff to leave the organization; it increases job satisfaction, which, in turn has an impact on affective commitment. Both affective and instrumental commitment were hypothesized to reduce the intentions of frontline staff to leave the organization, however only affective commitment had a significant effect.

The efficacy of the Sortino ratio and other benchmarked performance measures under skewed return distributions

This paper will investigate the suitability of existing performance measures under the assumption of a clearly defined benchmark. A range of measures are examined including the Sortino Ratio, the Sharpe Selection ratio (SSR), the Student’s t-test and a decay rate measure. A simulation study is used to assess the power and bias of these measures based on variations in sample size and mean performance of two simulated funds. The Sortino Ratio is found to be the superior performance measure exhibiting more power and less bias than the SSR when the distribution of excess returns are skewed.

Integrity determination of RTK solutions in precision farming applications

Integrity of Real Time Kinematic (RTK) positioning solutions relates to the confidential level that can be placed in the information provided by the RTK system. It includes the ability of the RTK system to provide timely valid warnings to users when the system must not be used for the intended operation. For instance, in the controlled traffic farming (CTF) system that controls traffic separates wheel beds and root beds, RTK positioning error causes overlap and increases the amount of soil compaction. The RTK system’s integrity capacity can inform users when the actual positional errors of the RTK solutions have exceeded Horizontal Protection Levels (HPL) within a certain Time-To-Alert (TTA) at a given Integrity Risk (IR). The later is defined as the probability that the system claims its normal operational status while actually being in an abnormal status, e.g., the ambiguities being incorrectly fixed and positional errors having exceeded the HPL. The paper studies the required positioning performance (RPP) of GPS positioning system for PA applications such as a CTF system, according to literature review and survey conducted among a number of farming companies. The HPL and IR are derived from these RPP parameters. A RTK-specific rover autonomous integrity monitoring (RAIM) algorithm is developed to determine the system integrity according to real time outputs, such as residual square sum (RSS), HDOP values. A two-station baseline data set is analyzed to demonstrate the concept of RTK integrity and assess the RTK solution continuity, missed detection probability and false alarm probability.