Measuring Sharedness of Team-Related Knowledge: Design and Validation of a Shared Mental Model Instrument

Many researchers have explored how people share and construct similar mental models in teams. They have claimed that successful team performance depends on a shared mental model of team members about task, team, equipment and situation. Most of the literature has illustrated simplified relationships between a team's mental model and their performance without a valid instrument addressing the confined and relevant constructs of a shared mental model. This paper describes the instrument development steps and the conceptual framework for factors associated with shared mental models. After development and refinement, the instrument was finalized for use to measure team-related knowledge. The final instrument consists of 42 items that are linked to the five emergent factors of shared mental models including general task and team knowledge, general task and communication skills, attitude toward teammates and task, team dynamics and interactions, and team resources and working environment.     

Generalized estimator of population mean by using conventional and non-conventional measures in the presence of measurement errors

In survey research, it is assumed that reported response by the individual is correct. However, given the issues of prestige bias, self-respect, respondent's reported data often produces estimated values which are highly deviated from the true values. This causes measurement error (ME) to be present in the sample estimates. In this article, the estimation of population mean in the presence of measurement error using information on a single auxiliary variable is studied. A generalized estimator of population mean is proposed. The class of estimators is obtained by using some conventional and non-conventional measures. Simulation and numerical study is also conducted to assess the performance of estimators in the presence and absence of measurement error.     

Impact of having a high-risk pregnancy on future postpartum contraceptive method choice

BackgroundTo compare the knowledge and preference of preconceptional contraception to future postpartum contraceptive method choice in high-risk pregnancies.Research questionDoes a high-risk pregnancy condition affect future postpartum contraceptive method choice?MethodWomen hospitalised at the High Risk Pregnancy unit of a tertiary research and training hospital were asked to complete a self-reported questionnaire that included demographic characteristics, presence of unintended pregnancy, contraceptive method of choice before the current pregnancy, plans for contraceptive use following delivery and requests for any contraceptive counselling in the postpartum period.FindingsA total of 655 pregnant women were recruited. The mean age, gravidity and parity of the women were 27.48 ± 6.25 years, 2.81 ± 2.15 and 1.40 ± 1.77, respectively. High-risk pregnancy indications included 207 (31.6%) maternal, 396 (60.5%) foetal and 52 (7.9%) uterine factors. All postpartum contraceptive choices except for combined oral contraceptives (COCs) usage were significantly different from preconceptional contraceptive preferences (p < 0.001). High-risk pregnancy indications, future child bearing, ideal number of children, income and education levels were the most important factors influencing postpartum contraceptive choices. While the leading contraceptive method in the postpartum period was long-acting reversible contraceptive methods (non-hormonal copper intrauterine device Cu-IUD, the levonorgestrel-releasing intrauterine system (LNG-IUS) (40%), the least preferred method was COCs use (5.2%) and preference of COCs use showed no difference between the preconceptional and postpartum periods (p = 0.202). Overall 73.7% of the women wanted to receive contraceptive counselling before their discharge.ConclusionA high-risk pregnancy condition may change the opinion and preference of contraceptive use, and also seems to affect the awareness of family planning methods.     

Estimation of finite population mean in stratified sampling using scrambled responses in the presence of measurement errors

This study focuses on the estimation of population mean of a sensitive variable in stratified random sampling based on randomized response technique (RRT) when the observations are contaminated by measurement errors (ME). A generalized estimator of population mean is proposed by using additively scrambled responses for the sensitive variable. The expressions for the bias and mean square error (MSE) of the proposed estimator are derived. The performance of the proposed estimator is evaluated both theoretically and empirically. Results are also applied to a real data set.     

A theory of instrumental and existential rational decisions: Smith,Weber, Mauss,Tönnies after Martin Buber

This paper proffers a dialogical theory of decision-making: decision-makers (DMs) are engaged in two modes of rational decisions, instrumental and existential. Instrumental rational decisions take place when the DM views the self externally to the objects, whether goods or animate beings. Existential rational decisions take place when the DM views the self in union with such objects. While the dialogical theory differs from Max Weber’s distinction between two kinds of rationality, it follows Martin Buber’s philosophical anthropology. The paper expounds the ramifications of the dialogical theory in understanding structures of exchange considering assessments of diverse thinkers.

     

Estimation of finite population mean in simple random sampling and stratified random sampling using two auxiliary variables

In this article, we propose a new class of estimators to estimate the finite population mean by using two auxiliary variables under two different sampling schemes such as simple random sampling and stratified random sampling. The proposed class of estimators gives minimum mean squared error as compared to all other considered estimators. Some real data sets are used to observe the performances of the estimators. We show numerically that the proposed class of estimators performs better as compared to all other competitor estimators.     

Supervisor commitment to employees: Does agreement among supervisors' and employees' perceptions matter?

Using 322 matched employee–supervisor dyads, we investigate how level and direction of employee–supervisor (dis)agreement on supervisor's affective commitment to the employee relate to organizational commitment, emotional exhaustion, leader–member exchange, and job performance. Results from polynomial regression and response surface analyses indicate that level of employee–supervisor agreement matters: the most beneficial outcomes appear when supervisors and employees agree that the supervisor is highly committed to the employee whereas the least favorable outcomes appear when dyads' members agree that the supervisor has low commitment to the employee. Direction of employee–supervisor disagreement is also important as employee overestimation of supervisor commitment is associated with more favorable outcomes than employee underestimation. However, for two of the outcomes (organizational commitment and emotional exhaustion), the effect of employee–supervisor disagreement was attributable to a main effect of employee perceptions of supervisor commitment. We discuss the implications of these findings for the understanding of employee–supervisor relationships.     

Human resource development competencies as predictors of agricultural extension agents' performance in Yemen

Human resource development (HRD) issue is recognized as a significant factor for survival of organizations and professionals, including those in the sector of agricultural extension. Few empirical studies have examined the influence of HRD competency variables on agricultural extension agents' performance. The authors argue that HRD competency variables such as leadership development, communication, programme planning, programme implementation and programme evaluation could predict agricultural extension agents' performance. Questionnaire data were collected from a sample of 290 extension agents in Yemen to discover if HRD competencies affect the performance of extension agents. Regression analysis shows that three variables – competencies in programme implementation, programme evaluation and programme planning – contributed significantly to the performance of extension agents. These predictors explain 42.2% of the variance in the job performance model.