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Boards of directors in SMEs: An empirical evidence of board task performance

Boards of directors in SMEs: An empirical evidence of board task performance

This paper contributes to the literature on boards of directors in several ways. Firstly, it enhances our understanding of what makes boards effective. In this sense, our empirical examination moves beyond board demographic characteristics to consider outcome variables besides corporate financial performance. This purpose was pursued through an empirical test of the impact of several board characteristics on board performance. Secondly, recent studies point out that contextual perspectives are needed to assess the relationship between corporate governance and firm performance, to demonstrate that, in some contexts, certain board designs may be recommended, but, in other contexts, other designs may be more suitable (Minichilli, Zattoni, Nielsen, & Huse, 2012; García-Ramos & García- Olalla, 2014). In keeping with those studies, we focus our analysis on Spanish SMEs. As mentioned, most studies on boards of directors are limited to large listed firms and, with few exceptions, this type of analysis has been conducted on SMEs. Moreover, as Basco & Voordeckers (2015) point out, Spain provides an interesting laboratory for examining these firms because formal institutions such as the weak legal system in protecting minority shareholders, informal institutions such as the high overlap between family and business and high levels of ownership concentration (La Porta, López-de-Silanes, & Shleifer, 1999; Arosa, Iturralde & Maseda, 2010; Gupta & Levenburg, 2010; Sánchez-Marin, Baixauli-Soler & Lucas-Perez, 2011) may affect the board of directors. Moreover, this paper also considers the formal working structures that operate to maximize board performance. The authors link this process to the need for an effective and clearly defined working style on the board (Demb & Neubauer 1992). The authors explore the antecedents of board task performance by testing hypotheses on existing formal board structures and board member involvement.
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Peer settings induce cheating on task performance

Peer settings induce cheating on task performance

(C) Table 1: Experimental design: four session types. 3.1.2 Compensation Schemes As stated in the introduction, we run these four conditions for two different compensation schemes: a piece rate and a fixed wage. With respect to the first, we use Ariely et al.’s (2008) and Pascual-Ezama et al.’s (2013) setup of a linearly decreasing piece rate as it offers an interesting setting for observing the strength of the motivational effect induced by peer settings. Any peer effect that can be observed in addition to the strong motivational instru- ment of a piece rate speaks for peer settings being a very strong motivator. Implementing a declining piece rate allows us to measure task performance in how many tasks they de- cided to work on, or phrased differently: when they quit working. Thus we can compare reservation wages between the four experimental conditions. In accordance with Ariely et al. (2008), participants earn 55 cents for the first riddle, 50 cents for the second riddle, and so on. That is, the piece rate declines by 5 cents per completed riddle. The eleventh riddle is the last one to pay any monetary amount different from zero.
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Reporting and interpreting task performance in go/no-go affective shifting tasks

Reporting and interpreting task performance in go/no-go affective shifting tasks

In conclusion, writing this opinion piece was motivated by increased interest in and inconsistent reporting and interpretation of the affective shifting task as indicated by both the number of publications in recent years and personal requests that I received about this task. Because of its briefness and simplicity, I think that food-related affective shifting tasks represent a promising tool for the investigation of impulsive reactions toward food cues. Although versions of the task have already been employed in students ( Loeber et al., 2013; Meule and Kübler, 2014; Meule et al., 2014 ), individuals with bulimia ( Mobbs et al., 2008 ), obese adults ( Mobbs et al., 2011; Loeber et al., 2012 ), and adolescent, psychiatric inpatients ( Deux et al., 2017 ), it appears that different task designs and analyses lead to a rather confusing literature. Some of this confusion may be resolved by standardized reporting of task performance (e.g., reaction times, omission errors, and commission errors as a function of both block type and condition) and careful interpretation of this task performance (e.g., whether it is the distractors that lead participants to commit errors or whether it is the targets that lead participants to also respond to the distractors). I hope that this paper may provide a useful guidance for researchers who are interested in using this task, whether food-related or in other fields of research.
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Effects of Motor Versus Cognitive Task Prioritization During Dual-Task Practice on Dual-Task Performance in Young Adults

Effects of Motor Versus Cognitive Task Prioritization During Dual-Task Practice on Dual-Task Performance in Young Adults

A detailed description of the methods used to assess motor and cognitive task performance has been published previously ( Kiss et al., 2018 ). During the dynamic balance task, participants were asked to stand on a stability platform (Lafayette Instrument, Model 16,030, Lafayette, USA) consisting of a 65 cm × 107 cm wooden platform, which allowed a maximum deviation of 15° from the horizontal to either side (Figure  1). A safety rail (105  cm above the platform) mounted to the stability platform ensured that participants did not fall if they lost their balance. The motor task required participants to remain in balance (i.e., to keep the stability platform in a horizontal position) for as long as possible during each 90-s trial (Figure 1A). A timer measured time in balance at a sampling rate of 25  Hz. Time in balance was defined as time when the platform was within ±3° of horizontal position. Platform position data were exported from the analysis software PsymLab and used to calculate the root-mean-square error (RMSE) in degrees.
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Peer Effects in Cheating on Task Performance

Peer Effects in Cheating on Task Performance

Table 1: Experimental design: four session types. 3.1.2 Compensation Schemes As stated in the introduction, we run these four conditions for two different compensation schemes: a piece rate and a fixed wage. With respect to the first, we use Ariely et al.’s (2008) and Pascual-Ezama et al.’s (2013) setup of a linearly decreasing piece rate as it offers an interesting setting for observing the strength of the motivational effect induced by peer settings. Any peer effect that can be observed in addition to the strong motivational instru- ment of a piece rate speaks for peer settings being a very strong motivator. Implementing a declining piece rate allows to measure motivational effects (or task performance) not only in how quickly participants worked on the task, but also on how many tasks they decided to work, or phrased differently: when they quit working. This allows us to compare reservation wages between the four experimental conditions. In accordance with Ariely et al. (2008), 9 Ariely et al. (2008) have a third condition, in which cheating is possible but cannot be observed ex-
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Individual differences in dual-target RSVP task performance relate to entrainment but not to individual alpha frequency

Individual differences in dual-target RSVP task performance relate to entrainment but not to individual alpha frequency

The results of the present study do not provide evidence that at the inter-individual level entrainment to the 10 Hz distracter stream typical for the AB paradigm or larger power during the distracter stream period are negatively related to AB task performance. On the contrary, the results indicate that performance in the AB paradigm benefits from entrainment. Though in contrast to a number of AB-specific findings and theories [ 7 , 14 , 15 ], the observation of a positive correlation between entrainment and performance is in line with findings from detec- tion tasks. Here it has been reported that a visual target presented in phase with an entraining sequence—as is the case for targets in the AB paradigm—is more easily detected than a target presented with a phase shift, with the difference being the more pronounced the longer the entraining sequence [ 22 ]. The positive effect of a longer period of entrainment for identifica- tion and processing of a single target has also been demonstrated in the RSVP-based Atten- tional Awakening paradigm [ 23 – 25 ]. But also several findings from AB studies are difficult to integrate with the idea that entrainment or power increases to the RSVP stream are detrimen- tal to AB task performance: For instance, taking an intra-individual differences approach Jan- son and colleagues [ 4 ] observed an interaction between correct report of T2 and total power at the RSVP and the IAF frequencies: while high power in the RSVP frequency in the pre-target distracter stream was linked to correct report of T2, the opposite pattern emerged for IAF power. As another example, the positive effect of introducing temporal jitter in the RSVP stream on AB task performance [ 15 ] could not be replicated in a later study [ 16 ].
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Serial or overlapping processing in multitasking as individual preference: Effects of stimulus preview on task switching and concurrent dual-task performance

Serial or overlapping processing in multitasking as individual preference: Effects of stimulus preview on task switching and concurrent dual-task performance

processing to optimize task switching in terms of reduced switch costs and higher net multitasking efficiency compared to a strictly serial processing manner. A similar effect emerged at least on a descriptive level when comparing the dual-task efficiency of switchers and alternaters in the second experiment. However, neither in the first nor the second experiment the effects of overlapping processing were so strong to actually turn dual-task cost effects in dual-task benefits as would have been reflected in positive ODTPE scores. This was probably due to the fact that in both experiments overlapping processing was only applied in a limited number of trials only and hence could not fully compensate other cost effects. This certainly has prevented a more positive effect of this strategy on overall dual- task efficiency. One reason for this could be a lack of enough practice as needed to fully establish this strategy. Another reason might be the high similarity of the two tasks with respect to the specific processing resources (Wickens, 2002). This might have made task interleaving and overlapping processing particularly difficult and prone to negative side effects. However, it is remarkable that the subgroup of switchers in the second experiment nevertheless were able to realize actual time benefits associated with task switches in up to 47% of switch trials. This shows the potential benefits of a strategy combining task
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Perceptual-cognitive function and unplanned athletic movement task performance: a systematic review

Perceptual-cognitive function and unplanned athletic movement task performance: a systematic review

Researchers have attempted to increase test contextuality and ecological validity by means of combining a typical athletic motor task with a time-constrained decision-making component. Besier et al. [ 7 ] instructed their participants to perform straight runs towards a screen, which spontaneously displayed the direction of an immediate cutting maneuver. Interestingly, these unplanned side cuts were associated with unfavorable knee biomechanics when compared to a pre-planned task indicating the cutting direction already before the run. The findings of Besier et al. [ 8 ] are in line with a later systematic review of experimental trials, showing that unplanned movements lead to changes in lower limb kinetics and kinematics, which are suggestive of an increased injury risk [ 9 ].
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Skill memory escaping from distraction by sleep--evidence from dual-task performance

Skill memory escaping from distraction by sleep--evidence from dual-task performance

Figure 1. Experimental procedure. The experiment consisted of a Training followed by a Retrieval session. Sleep group (SG), nighttime-awake group (NA) and daytime-awake group (DA) performed a dual task (concomitant SRTT and WPAT; upper part). The daytime-awake-subsequent-WPAT group (DAs) performed a single task (SRTT alone then followed by the WPAT; lower part). Training session (left part). SRTT was arranged in blocks (in yellow), for which the trial sequence was fixed, followed by blocks (in green) with random sequences of trials. Numbers in the bottom mark block’s position in the general sequence whereas, numbers on the top indicate the number of trials administered within each block. ‘‘Practice’’ (light blue) indicates the initial practice block, which was not included in the analyses. The WPAT (distractor task) was continuously performed throughout the entire SRTT session. The first and the last fixed sequence blocks (i.e.: block 2 and block 6), followed by the random sequence block 3 and 7, respectively were considered to investigate changes in performance across Training. For clarity, block 2 and block 3 were labeled as ‘‘Training 1’’ whereas block 6 and block 7 were labeled as ‘‘Training 2’’. The difference between mean RTs to random and sequential blocks was the dependent variable being analyzed. Retention interval between training and retrieval sessions (middle part). The sleep group slept the two nights after Training before doing Retrieval in the morning. The nighttime-awake group, instead, stayed awake throughout the first night after Training and slept the second night. The daytime-awake group trained in the morning and was retested in the evening of the same day during which they stayed awake. Retrieval session (right part). Block 9 (fixed trial sequence) and block 10 (random trial sequence) were labeled as Retrieval. The same random minus fixed block difference as in the training session was taken to investigate the RT performance. The task was immediately followed by one bock (in purple) in which a generation task was administered.
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Multiscale temporal neural dynamics predict performance in a complex sensorimotor task

Multiscale temporal neural dynamics predict performance in a complex sensorimotor task

Although the presence of LRTCs does not constitute conclusive proof of the existence of criticality in a neural system, it is nonetheless consistent with this hypothesis [10, 7]. The main finding of our study is that LRTCs are advantageous for brain function, as has been conjectured, for critical dynamics. Previous research has revealed that Hurst exponents in the amplitude dynamics of ongoing oscillations correlate with Hurst exponents in motor tapping [14] and with Hurst exponents of subliminal-stimulus detection [15]. These studies, however, did not provide direct evidence that the presence of LRTCs predicts task performance as shown in our study. Indeed, it is exactly performance itself not its variability which is most important for understanding the functional significance of LRTCs. In general our work contributes to growing evidence that power-law neuronal dynamics might be beneficial for brain functioning as shown previously for dynamic stimulus range [8, 9], information capacity [5] and information transmission [5]. The fact, that we could predict task performance from LRTCs determined during the training session, indicates that power-law dynamics are subject-specific. This is in line with findings that LRTCs are genetically defined [54] and have significant test-retest reliability [56] showing stability of individual LRTCs across many days. In addition, the existence of subject-specific LRTCs is further confirmed by demonstrating that LRTCs are sensitive biomarkers of pathological neuronal activity in a variety of diseases such as Schizophrenia [57], Parkinson’s [58] and Alzheimer Disease [59].
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Knowledge of Previous Tasks: Task Similarity Influences Bias in Task Duration Predictions

Knowledge of Previous Tasks: Task Similarity Influences Bias in Task Duration Predictions

information they remember and more emphasis on what they perceive differentiates the current task from previous similar tasks. Accordingly, through the use of verbal protocols ( Ericsson and Simon, 1980 ), Buehler et al. (1994) found that predictions are typically based on aspects of focal tasks, but when people are prompted to consider their previous task performance just before making a time prediction, the temporal underestimation indicative of the planning fallacy is reduced. Buehler et al.’s (1994) research suggests that people tend to take an ‘inside’ perspective when making task duration predictions, but when they incorporate what information they remember about previous tasks into their predictions, they do a better job of judging when tasks will finish. Although the inside–outside account makes no prediction about the role memory for previous task performance in the task duration prediction process, the work of Buehler et al. (1994) highlights the benefit of taking such an outside perspective when making time predictions. The role of memory for previous task performance is central to another account of the planning fallacy which claims that people use distributional information but inaccurately recall it when making time predictions ( Roy et al., 2005 ). This memory-bias account states that people consider previous task information but their memory for such information is biased, which leads to biased predictions. Roy and Christenfeld (2007) suggest that because people rarely closely monitor the durations of the tasks they perform in daily life, the planning fallacy (and the overestimation of future task duration) is a result of memory being for estimated or perceived duration rather than actual duration. Support for this claim comes from the retrospective time estimation literature, where autobiographical events ( Burt, 1992 ) and public events ( Burt and Kemp, 1991 ) are remembered as being shorter than was actually the case. There is growing support for
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Association of task-specific cerebral glucose metabolism with cognitive performance

Association of task-specific cerebral glucose metabolism with cognitive performance

studies which tried to localize regions in the brain, which are correlates of this mental operation. In a review article (120) several foci of activation during the task performance could be identified, including the superior parietal (known to implement spatial maps), frontal, and inferotemporal cortices. Although the activation was bilateral in most regions, activity in the right parietal cortex and the left frontal cortex was more significant than on the opposite side. Moreover, increased brain activity was consistently correlated with the amount of mental rotation performed (more rotation/difficulty means more activity ) (120). This increased activity is, in line with earlier findings, accompanied by longer times to complete the task as well as higher error rates. Therefore it can be stated, that the angle of rotation is proportional to task difficulty and that this difficulty can be related to higher activity in the brain (122). Activity in motor regions was sometimes also involved in performing mental rotation tasks. It has been suggested, that this activity could be explained by a motor simulation strategy used by the participant to solve the task (i.e., mental representation of a motoric manipulation of the object). The prominently identified motor region was the medial superior portion of the precentral sulcus, usually indicated as the supplementary motor area (SMA). The SMA is typically involved in motor imagery tasks and motor control, as it is projecting to the primary motor cortex and the spinal cord (120).
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Modality compatibility in task switching depends on processing codes and task demands

Modality compatibility in task switching depends on processing codes and task demands

Modality compatibility denotes the match between sensory stimulus modality and the sensory modality of the anticipated response effect (for example, vocal responses usually lead to auditory effects, so that auditory–vocal stimulus–response mappings are modality-compatible, whereas visual–vocal mappings are modality incompatible). In task switching studies, it has been found that switching between two modality-incompatible mappings (auditory-manual and visual–vocal) resulted in higher switch costs than switching between two modality-compatible mappings (auditory–vocal and visual-manual). This finding suggests that with modality-incompatible mappings, the anticipation of the effect of each response primes the stimulus modality linked to the competing task, creating task confusion. In Experiment 1, we examined whether modality- compatibility effects in task switching are increased by strengthening the auditory–vocal coupling using spatial-verbal stimuli relative to spatial-location stimuli. In Experiment 2, we aimed at achieving the same goal by requiring temporal stimulus discrimination relative to spatial stimulus localisation. Results suggest that both spatial-verbal stimuli and temporal discrimi- nation can increase modality-specific task interference through a variation of the strength of anticipation in the response-effect coupling. This provides further support for modality specificity of cognitive control processes in task switching.
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Task as workplan, task in process: Welche Aufschlüsse gibt eine Unterrichtsaufzeichnung zu Lernaufgaben im Fach Deutsch?

Task as workplan, task in process: Welche Aufschlüsse gibt eine Unterrichtsaufzeichnung zu Lernaufgaben im Fach Deutsch?

Für die folgenden Analysen ist sowohl das Verhältnis von „demand“ und „support“ relevant als auch die Dimensionen der Verknüpfung einzelner Aufgaben und der Inszenierung von Aufgaben. Während „demand“ die fachspezifische Anforderung als Wissens- bzw. Könnensziel – als Zielgröße des Lernens – bezeichnet, verweist „support“ auf die Hilfestellungen, die eine Aufgabe bietet, um die an sie gebundene Anforderung zu erfüllen (vgl. Legutke 2006, S. 141). Was die Frage der Aufgabenverknüpfung betrifft, so geht es zum einen um die Position einer Aufgabe in einer Lernsequenz und zum anderen um differenzierte Arrangements von Aufgaben als Antwort auf unterschiedliche Lernermerkmale. Der Aspekt der Aufgabeninszenierung verlangt demgegenüber vor allem die Bestimmung des Entscheidungsspielraums, der den Lernern durch die Aufgabe eingeräumt wird. Hier zeigt die Stunde deutliche Defizite – sowohl in der Hinführung zum Thema und zur Aufgabe als auch bei der Besprechung der Ergebnisse, sodass die Inszenierung zur eigentlichen Zielgröße dieses Beitrags gerät. Ich werde zunächst die Aufgaben als Plan vorstellen, und zwar sowohl unter Berücksichtigung ihrer Einbettung und Verknüpfung untereinander als auch im Hinblick auf das Verhältnis von „demand“ und „support“. In einem zweiten Schritt wird die unterrichtliche Realisation anhand von Filmsequenzen analysiert und kommentiert. Abschließend soll die Frage beantwortet werden, welche Erkenntnis hinsichtlich der Aufgabenqualität aus dem Vergleich von „task as workplan“ und „task in process“ resultiert.
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Task Recommendation in Crowdsourcing Platforms

Task Recommendation in Crowdsourcing Platforms

A primary challenge for task recommendation is the very dynamic nature of task markets. In contrast to e-commerce or media platforms, where items remain avail- able indefinitely, a task disappears from the platform, as soon as the micro-task is completed or the job position is assigned. Many tasks on micro-task markets are provided in so-called campaigns, providing several same tasks on the platform at the same time, e.g., to find many contributors for a survey. However, as soon as one campaign is completed, the task is also not available on the platform anymore. Well studied recommender systems used in e-commerce or media recommendation are often based on collaborative approaches, which rely on the fact that a single item can be interacted with by more than one user. Therefore, such approaches cannot be directly applied to task recommendation problems. Content-based recommender ap- proaches, using the given information of items to identify relevant recommendations can be applied instead. Different user studies show that the similarity of tasks is an essential factor for workers when selecting tasks and should be considered by rec- ommendations [ 14 , 146 ]. To exploit the potential of the available information about workers and tasks on the platform, methods to determine the similarity of tasks have to be identified. Such similarities help to relate completed tasks from the history of the workers with tasks which are currently available on the platform. They could also be used to identify workers with similar interests and therefore broaden the rec- ommendation possibilities. The demands of the workers and the perceived similarity of tasks are discussed in Chapter 4 .
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Nexus#: a distributed hardware task manager for task-based programming models

Nexus#: a distributed hardware task manager for task-based programming models

About 19% in case of the very fine grain tasks in matrix-250, and as the matrix size and hence larger number of tasks of larger granularity increases, Nexus# has about 10% performance imp[r]

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Common Cognitive Control Processes Underlying Performance in Task-Switching and Dual-Task Contexts

Common Cognitive Control Processes Underlying Performance in Task-Switching and Dual-Task Contexts

Despite the commonalities between task-switching and dual-task- ing, there are only a few studies and theoretical considerations about how the performance costs in task-switching and dual-tasking might be related (e.g., Band, Jolicoeur, Akyürek, & Memelink, 2006 ; Oriet & Jolicoeur, 2003 ; Pashler, 2000 ; Sigman & Dehaene, 2006 ). For instance, by implementing T1-T2 switches and T1-T2 repetitions into dual-task trials, Band and van Nes ( 2006 ) as well as Lien et al. ( 2003 ) observed, in addition to a PRP effect, switch costs in T2. The cost was comparable across SOAs. Lien et al. ( 2003 ) concluded from the switch costs in T2 that time is needed for processes involved in the disengagement of T1 and the engagement of T2, and thus, that the shifting component is in- volved in dual-tasking (see also Liepelt, Strobach, Frensch, & Schubert, 2011 , for similar conclusions derived from studies on practice effects in dual-tasking; for a review, see, e.g., Strobach & Schubert, 2017 ). They argued that the missing absorption of switch costs in T2 during the waiting period for the availability of the response-selection bottleneck (i.e., additivity of SOA and T1-T2 transition) suggests that these proc- esses, at least partially, occur after response selection for T1 and before response selection for T2, and modified the response-selection bot- tleneck accordingly.
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Job polarization, task prices and the distribution of task returns

Job polarization, task prices and the distribution of task returns

the SOC classification to the GSOEP as well. 17 Note further that this approach implicitly assumes that the task content of each occupation is similar in Europe and in the US. 18 ISCO-88 does not have a major group for Sales occupations, differently from the national classifications based on the Standard Oc- cupational Classification. Part of sales occupations are with service occupations. Others are spread in the other major groups. However, according to Acemoglu and Autor ( 2011 ), whereas service workers do a non-routine manual job, salesmen involve mainly routine cognitive tasks. Therefore, we create an extra occupational category for Sales occupations. By confronting the UK 1990 SOC and the US 2010 SOC, we classify workers as salesmen if their ISCO-88 code is one of the following: 3415, 3416, 3417, 9113, 5220, 5230. Notice as well that recent analyses, based on the classification of Dorn ( 2009 ), exclude agricultural workers (see Goos et al. , 2014 ; Autor and Dorn , 2013 ;
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The Effect of a Structured Method on Mental Model Accuracy and Performance in a Complex Task

The Effect of a Structured Method on Mental Model Accuracy and Performance in a Complex Task

4.3. Subject Demographics It is possible that the demographics of the subjects who participated in the experiment will have had an influence on the results of this study and, therefore, on their generalizability. To analyze these potential factors, a generalized linear model has been estimated that relates performance to different demographic variables. Model 5 in Table 7 presents the results in which performance in the complex task is explained by age, gender, the number of economics lectures attended, prior work experience, as well as prior experiment participation and major field of study. A Chi-squared test with 36 degrees of freedom leads to a non-significant result with p = 0.09. The residual deviance is not significant at the five percent level, but the model should still be interpreted with caution due to the low p-value.
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The Leadership Task Model

The Leadership Task Model

Time Optimization is often something leaders do for themselves but not for their employees where the performance leverage is greater. Perhaps the most common complaint of employees is that they “have too much to do and too little time to do it”. Due to “time hurriedness”, leaders often “dump” tasks rather than taking the time to delegate to develop employees. A major task of the good leader is the workload balance of the employees.. The basic message is that optimizing the work time usage of their followers is a key leadership task that increases overall work productivity. Time optimization starts with task allocation, which needs to be based on a realistic “time to completion” estimate and the actual work time capacities of an employee. Another scheme of leaders to optimize their time schedule instead of their employees’ is to get their followers attention whenever they need, not taking into account that the employee might need to interrupt their current work activities. This behavior causes frustration and work time losses. Another common scheme for work interruptions and productivity losses are meetings. Here a major lack of planning and facilitation of the meetings can be observed. The consciousness of the Good Leader needs to be as interdependent and complex as the world s/he leads. From Leading Self (Me-level) arises maturity. From Leading Others (You-level) arises innovative and engaged human resources. From Leading the Organization (Us-level) arises an aligned and synergetic culture. To have the wisdom to be aware of what is real and the courage to do what works to get sustainable results, that is what you need to do to be a Good Leader.
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