Flexible Systems in HR

Editorial special issueThe final publication is available at Springer via http://dx.doi.org/10.1007/s40171-016-0125-5Research on the concept of ‘flexibility’ has produced a substantive scholarly in recent decades and has evolved as a focal area of management research (Mønsted 1991; Sushil 1994; Skipper et al. 2014; Krishna et al. 2015). According to Sushil (2001) ‘Flexibility offers freedom of choice and is highly context specific’. Here, ‘context specific’ refers to the role of contingencies within flexibility which might render it as a form of a firm’s dynamic capability. The dynamic capability scholarship argues that in order to achieve excellence, organizations should develop capabilities complementary to their competencies (Teece et al. 1997; Helfat and Peteraf 2009). Thus, flexible HR practices can help organizations in achieving sustainable competitiveness through creating, integrating, reconfiguring, and building on its human resource base. For example, organizations can achieve competitive edge by customizing training and development programs

The impact of formative testing on study behaviour and study performance of (bio)medical students: a smartphone application intervention study.

BACKGROUND: Formative testing can increase knowledge retention but students often underuse available opportunities. Applying modern technology to make the formative tests more attractive for students could enhance the implementation of formative testing as a learning tool. This study aimed to determine whether formative testing using an internet-based application ("app") can positively affect study behaviour as well as study performance of (bio)medical students. METHODS: A formative testing app "Physiomics, to the next level" was introduced during a 4-week course to a large cohort (n = 461) of Dutch first year (bio)medical students of the Radboud University. The app invited students to complete 7 formative tests throughout the course. Each module was available for 3-4 days to stimulate the students to distribute their study activities throughout the 4-week course. RESULTS: 72% of the students used the app during the course. Study time significantly increased in intensive users (p < 0.001), while no changes were observed in moderate (p = 0.07) and non-users (p = 0.25). App-users obtained significantly higher grades during the final exam of the course (p < 0.05). Non-users more frequently failed their final exam (34%, OR 3.6, 95% CI: 2.0-6.4) compared to moderate users (19%) and intensive users (12%). Students with an average grade <6.5 during previous courses benefitted most from the app, as intensive (5.8 ± 0.9 / 36%) and moderate users (5.8 ± 0.9 / 33%) obtained higher grades and failed their exam less frequently compared to non-users (5.2 ± 1.1 / 61%). The app was also well appreciated by students; students scored the app with a grade of 7.3 ± 1.0 out of 10 and 59% of the students indicated that they would like the app to be implemented in future courses. CONCLUSIONS: A smartphone-based application of formative testing is an effective and attractive intervention to stimulate study behaviour and improve study performance in (bio) medical students

Computer-aided DSM-IV-diagnostics – acceptance, use and perceived usefulness in relation to users' learning styles

BACKGROUND: CDSS (computerized decision support system) for medical diagnostics have been studied for long. This study was undertaken to investigate how different preferences of Learning Styles (LS) of psychiatrists might affect acceptance, use and perceived usefulness of a CDSS for diagnostics in psychiatry. METHODS: 49 psychiatrists (specialists and non-specialists) from 3 different clinics volunteered to participate in this study and to use the CDSS to diagnose a paper-based case (based on a real patient). LS, attitudes to CDSS and complementary data were obtained via questionnaires and interviews. To facilitate the study, a special version of the CDSS was created, which automatically could log interaction details. RESULTS: The LS preferences (according to Kolb) of the 49 physicians turned out as follows: 37% were Assimilating, 31% Converging, 27% Accommodating and 6% Diverging. The CDSS under study seemed to favor psychiatrists with abstract conceptualization information perceiving mode (Assimilating and Converging learning styles). A correlation between learning styles preferences and computer skill was found. Positive attitude to computer-aided diagnostics and learning styles preferences was also found to correlate. Using the CDSS, the specialists produced only 1 correct diagnosis and the non-specialists 2 correct diagnoses (median values) as compared to the three predetermined correct diagnoses of the actual case. Only 10% had all three diagnoses correct, 41 % two correct, 47 % one correct and 2 % had no correct diagnose at all. CONCLUSION: Our results indicate that the use of CDSS does not guarantee correct diagnosis and that LS might influence the results. Future research should focus on the possibility to create systems open to individuals with different LS preferences and possibility to create CDSS adapted to the level of expertise of the user