Team Selection Research Articles

Research on the Influence of Inconsistency Between Anchor Image and Product Image on Consumers' Purchase Intention

In recent years, the live broadcast industry has been booming, but some anchors have realized that their images are not consistent with the images of recommended products, which will affect consumers' purchasing intentions. This paper takes consumer perception as the theoretical basis to construct a hypothesis model and takes situational experiment as the research method. Finally, the conclusion is drawn that the inconsistency between anchor image and product image will have a negative effect on consumers' purchase intention, and consumers' perception of anchor professionalism and perceived product reliability play a mediating role between the two. The text puts forward a new explanation mechanism in theory, and has some enlightening effect on the selection of anchor team in practice.

EXPERIENCE IN DEVELOPING OF THE UNIVERSITY INFORMATION SYSTEM

The process of development and functionality of the university information system “Digital Profile & Electronic Portfolio Management System for Employees, Teachers and Students (E-TUTOR)” – the programme designed for organisational, administrative, technical and informational support of the educational organisation activities when implementing basic professional educational programmes in accordance with the federal state educational standards of higher education – is described in the article. The choice of design methodology and approaches to the selection of the development team is presented with the description of the development tool as well as the system functionality; the ways of the system development are outlined.

Considerations Perceived by Coaches as Specific to Coaching Elite Women’s Soccer Teams

This study investigated challenges perceived by coaches when working with elite women’s soccer teams. Six men and four women coaches with experience in the first Norwegian League or Norwegian national team participated. Semi-structured interviews were carried out, and the data was analyzed using thematic interpretational analysis. Participants identified professionalism, early-career termination, mental characteristics, intrateam communication, romantic relationships, access to the locker rooms (men only), and team selection (women only) as the specific challenges they face when coaching these teams. The findings are discussed in relation to ensuring that good performance and development are achieved when coaching elite women’s soccer teams and helping future coaches optimize their coaching techniques when working with elite women players.

Inter-Object Navigation of Unmanned Aerial Vehicles to Increase the Efficiency and Accuracy of Inspection of Power Lines

The purpose of the work is to improve the accuracy and efficiency of a power line section inspection for a fault detection using unmanned aerial vehicles. The goal was achieved by using a unified computing and measurement platform on multicopter and aircraft drones and by simplifying the interaction between them and by using the inter-object navigation sensors. The most significant results were the development of a method of route planning by drones over different parts of the power grid and a method of inter-object navigation. The drone route planning problem was represented by a multiagent variation of the classical traveling salesman problem and was solved by the ant colony method. The method of inter-object navigation was distinguished by the representation of the power grid topology by high and low intensity graphs, involving a different number and types of drones in the inspection process. The application of the developed methods made it possible to increase the accuracy of power line inspections by 27-73%, and the efficiency by 2-8 times. Solving the problem of multicriteria optimization of the drone team flight route planning made it possible to reduce the cost of monitoring critical infrastructure facilities while improving its efficiency and accuracy. Thus, the conducted research has shown the effectiveness of the proposed approach for the monitoring of power facilities, route selection, number and composition of search teams. The direction for further research is to improve the ant algorithm.

Resting-state heart rate variability after stressful events as a measure of stress tolerance among elite performers.

Introduction: A common trait of elite performers is their ability to perform well when stressed by strong emotions such as fear. Developing objective measures of stress response that reliably predict performance under stress could have far-reaching implications in selection and training of elite individuals and teams. Prior data suggests that (i) Heart rate and heart rate variability (HR/HRV) are associated with stress reaction, (ii) Higher basal sympathetic tone prior to stressful events is associated with higher performance, and (iii) Elite performers tend to exhibit greater increase in parasympathetic tone after a stressful event. Methods: The current study assesses the predictive utility of post-stressful event HR/HRV measures, an under-studied time point in HR/HRV research, in the context of military personnel selection. Specifically, we examined the relationship between a comprehensive set of HR/HRV measures and established questionnaires related to stress tolerance, experimental evaluation of executive function during stress induction, and ecologically valid selection assessment data from a week-long Special Operations Forces selection course (N = 30). Results: We found that post-stressful event HR/HRV measures generally had strong correlations with the neuroticism facet of the NEO personality inventory as well as the general and distress facets of the defensive reactivity questionnaire. HR/HRV measures correlated reliably with a change in executive function measured as a decrease in verbal fluency with exposure to a well-validated stressor. Finally, we observed a divergent pattern of correlation among elite and non-elite SOF candidates. Specifically, among elite candidates, parasympathetic nervous system (PNS) measures correlated positively and sympathetic nervous system (SNS) measures correlated negatively with evaluation of stress tolerance by experts and peers. This pattern was not present in non-elite candidates. Discussion: Our findings demonstrate that post-stressful event HR/HRV data provide an objective non-invasive method to measure the recovery and arousal state in direct reaction to the stressful event and can be used as metrics of stress tolerance that could enhance selection of elite individuals and teams.

Project management in a partner network in the context of teamwork and project team selection

Collaboration and teamwork represent a unique form of human activity that involves interdependence and shared responsibility in achieving goals and completing tasks, as well as the ability to complete tasks efficiently and communicate effectively. Nowadays, the ability to collaborate in a team is one of the most desired social competences. This publication presents selected problems in the field of project team management. The paper deals with the selection of a project team, including a project manager based on the adopted profile of requirements and competences with the example of an international project. The publication is based on selected literature on the subject, a review of secondary research results, and the results of the author's research on the traits, skills, and competences that should characterize a project manager and project team members.

CQ-motivation: the X-factor in Global Project Teams?

Global project teams (GPTs) have emerged in the 21st century as the primary construct by which complex and often high-stakes changes of global scale are planned and delivered. Data from the field of GPT practice includes the recurrent observation that some GPT practitioners seem to thrive in the cross-cultural context of the GPT, while others flounder. This research paper explores how cultural diversity influences motivation and performance within the GPT. It extracts themes of interest from a detailed literature review and further explores them in the context of a field study of 79 GPT practitioners in 21 countries. CQ-motivation emerges as a potent predictor of motivation and performance in the GPT. The study concludes that GPT team selection processes which actively leverage CQ-motivation, project manager ownership, and the prioritisation of attitude over functional skills, will be supportive of superior GPT performance.

Developing school football team selection tests in light of contemporary trends

Developing school football team selection tests in light of contemporary trends

Exploration and Practice of Coordinated Development of Teachers and Students in Innovation and Entrepreneurship Education of Artificial Intelligence

Among application-oriented universities, there are problems of incomplete teaching staff construction, emphasis of student training, lacking learning motivation, and lack of cooperation and exchange platform. Based on analyse of current situation of artificial intelligent talents cultivation, it was proposed about problems of improvement of teachers’ ability and student training, and targeted solutions were advised. It was thought that goals of AI talents cultivation were the developer teacher and experienced and applied student, whose development paths were established, which can be carried on by coordinated development of teachers and students. The cultivation system was structured by innovative undertaking platform construction of teachers and students, team selection mechanism, diversified study driving, building a teaching team of teachers and students, and capability development drived by integration of expertise and innovation.

Differences in the Voting Patterns of Experts, Peers, and Fans - Analyzing the NFL’s All-Star Team Selections

Differences in the Voting Patterns of Experts, Peers, and Fans - Analyzing the NFL’s All-Star Team Selections

Designer Selection for Complex Engineering System Design Projects Considering the Disciplines Demanded

Currently, technological advances and developments are leading to the rapid emergence of high-end technology products, accompanied by a variety of customer requirements, which will lead to engineering system design projects becoming more complex. Therefore, complex engineering design projects require designers with multidisciplinary backgrounds who can work together and approach complex problems. However, when company supervisors assign designers with interdisciplinary knowledge to complex projects, the knowledge gap of each discipline between designers will cause communication conflicts, which directly affects the efficiency of team communication and complex project execution. Therefore, it is very important for the design company to select a portfolio of designers with efficient interdisciplinary background communication. Thus, the main objective of our research is to propose a method to support company supervisors and their approach to the design team selection problem for complex engineering system design projects with consideration of the project’s required basic technical competence, personal competence, and multidisciplinary knowledge communication between the designers. The proposed method can help design firms to select the best multidisciplinary collaborative design team for complex engineering system design projects.

Micro-level network dynamics of scientific collaboration and impact: Relational hyperevent models for the analysis of coauthor networks

AbstractWe discuss a recently proposed family of statistical network models—relational hyperevent models (RHEMs)—for analyzing team selection and team performance in scientific coauthor networks. The underlying rationale for using RHEM in studies of coauthor networks is that scientific collaboration is intrinsically polyadic, that is, it typically involves teams of any size. Consequently, RHEM specify publication rates associated with hyperedges representing groups of scientists of any size. Going beyond previous work on RHEM for meeting data, we adapt this model family to settings in which relational hyperevents have a dedicated outcome, such as a scientific paper with a measurable impact (e.g., the received number of citations). Relational outcome can on the one hand be used to specify additional explanatory variables in RHEM since the probability of coauthoring may be influenced, for instance, by prior (shared) success of scientists. On the other hand, relational outcome can also serve as a response variable in models seeking to explain the performance of scientific teams. To tackle the latter, we propose relational hyperevent outcome models that are closely related with RHEM to the point that both model families can specify the likelihood of scientific collaboration—and the expected performance, respectively—with the same set of explanatory variables allowing to assess, for instance, whether variables leading to increased collaboration also tend to increase scientific impact. For illustration, we apply RHEM to empirical coauthor networks comprising more than 350,000 published papers by scientists working in three scientific disciplines. Our models explain scientific collaboration and impact by, among others, individual activity (preferential attachment), shared activity (familiarity), triadic closure, prior individual and shared success, and prior success disparity among the members of hyperedges.

Development of an algorithm for determining the individual factor structure of gymnasts' preparedness for the selection of teams in sports aerobics

The purpose of the research is to develop an algorithm for team composition in sports aerobics and to determine the factor structure of the fitness of gymnasts in sports aerobics, taking into account the psychophysiological capabilities of athletes.
 Material and methods. The following research methods were used to solve the tasks: analysis of literary data; evaluation of the results of competitive activities; determination of functional and psychophysiological state [8–10], physical development and physical fitness, vestibular stability; pedagogical testing; methods of mathematical statistics using multivariate analysis and computer programs "ESXEL" and "SPSS".
 The results. For team composition in sports aerobics, we developed an algorithm for determining the possibilities of combining athletes into groups for team performances. The main feature of this algorithm was the use of multidimensional analysis tools for the selection of athletes for teams in sports aerobics. Based on the determination of the general structure of the athletes' fitness through factor analysis, individual factor values ​​of the fitness structure were determined for each athlete. Then a hierarchical cluster analysis of the test indicators was conducted and team compositions were selected based on the groups formed as a result of the cluster analysis. Next, programs for performances were created and training programs were developed for each group.
 Conclusions. The team selection algorithm based on the psychophysiological indicators of athletes is effective, accessible, and allows you to quickly determine the optimal options for combining athletes into groups for performances in various competitive categories; and therefore will contribute to increasing the efficiency of the training process and competitive performance.

Tracking Student Outcomes Through Instructional Choices in Physical Education

This study used self-determination theory to provide a better understanding of learner motivation in a physical education program. Students participated in a sports unit with choice in activities, equipment, partners, and competition as opposed to a traditional teacher-led activity unit. The objective was to determine differences in motivation and perceptions of physical education in grade school children. An alternating treatment design was used in which students experienced both a teacher-led unit and a student choice–driven sports unit. Fifty fifth-grade students from a suburban school in the Western United States participated in this study. Students were assessed through a number of parameters: physical activity enjoyment, situational motivation, fourth- and fifth-grade student attitudes toward physical education, pedometer readings, and interviews. This study used t tests and repeated-measures analyses of variance to explore differences based on condition (i.e., choices and/or teacher led) and gender, as well as common comparisons (i.e., trustworthiness measures) for the interview data. Students displayed significantly higher enjoyment ratings when they had the choice condition second (from the alternating treatment design), immediately before posttests, and boys rated enjoyment of physical education significantly higher than did girls. In another measure, the group with choices of the hockey unit was predominantly more active in the sport than those participating in the teacher-led activity. The interview themes elicited the following responses: (a) students expressed a desire for instructional choices, but not in team selections; (b) students loved sports, but they also wanted more fitness; and (c) students identified and valued instructional choices. The findings suggest that competence plays a critical role in physical education, and when students can choose the level of competition and play in small group games, they feel more competent, play more, and have higher enjoyment ratings within the physical education program.

A Graph Matching Model for Designer Team Selection for Collaborative Design Crowdsourcing Tasks in Social Manufacturing

In order to find a suitable designer team for the collaborative design crowdsourcing task of a product, we consider the matching problem between collaborative design crowdsourcing task network graph and the designer network graph. Due to the difference in the nodes and edges of the two types of graphs, we propose a graph matching model based on a similar structure. The model first uses the Graph Convolutional Network to extract features of the graph structure to obtain the node-level embeddings. Secondly, an attention mechanism considering the differences in the importance of different nodes in the graph assigns different weights to different nodes to aggregate node-level embeddings into graph-level embeddings. Finally, the graph-level embeddings of the two graphs to be matched are input into a multi-layer fully connected neural network to obtain the similarity score of the graph pair after they are obtained from the concat operation. We compare our model with the basic model based on four evaluation metrics in two datasets. The experimental results show that our model can more accurately find graph pairs based on a similar structure. The crankshaft linkage mechanism produced by the enterprise is taken as an example to verify the practicality and applicability of our model and method.

Strategy Selection in Teams: Exploring How Teams Coordinate Responses to Time Pressure

Effective teamwork in dynamic environments relies on the ability to adapt individual as well as collective behavior to respond to varying and uncertain demands. This paper describes an experiment conducted to analyze a two-person team’s strategy selection during a simulated search and retrieve task using Blocks World for Teams (BW4T). The experiment imposes different levels of temporal demands on teams to characterize how individual strategy selection affects team strategy and performance. Hollnagel’s Contextual Control Models are used as the basis for analyzing the experiment data and identifying the control mode of the team and its individual members during the task. Results from the experiment show that control modes are adapted at both the individual and team level to maintain performance under varying temporal demands. The results from the experiment point to the need to have system design support a range of individual and team control strategies to facilitate effective coordination and adaptation in teams.

Examining racial discrimination in fantasy team selection: the case of Czech soccer fans

PurposeRecently, efforts to fight discriminatory behaviour in many sports and to eliminate racial preferences among fans have intensified. However, uncovering discriminatory preferences may not be easy as they may be deeply rooted and even unconscious. This paper aims to discuss the aforementioned issues.Design/methodology/approachUnfortunately, professional soccer and fantasy sports participation serves as a vehicle for explicit racial discrimination at a micro-level, but does it translate to the macro-level through fantasy team selection? The current study explored the potential of implicit racial discrimination in Czech participants in the English Premier League.FindingsDiscriminatory behaviour in this context is defined by a consumer demonstrating preference for a white player over a non-white player in the fantasy soccer labour market when both players are performing at equal levels. Controlling for additional factors such as nationality and historically dominant team biases and accessing a more homogenous sample, the results confirmed previous research that racial discrimination cannot be found in team selection decisions among fantasy soccer participants in the Czech Republic. The manifestations of racism are still present at Czech stadiums and among Czech athletes. This contradiction is the major finding of this paper.Originality/valuePrevious research found no evidence of racial discrimination among participants controlling for some game factors. However, the study had many limitations including a heterogeneous sample and not controlling for additional factors of participant bias. Given those concerns, the current study analysed line-up decisions of English Premier League participants, but did so with participants solely within the Czech Republic, a more homogenous sample, controlling for additional important factors that could impact racial discrimination among fantasy participants.

Understanding relationship between topic selection and academic performance of scientific teams based on entity popularity trend

PurposeProper topic selection is an essential prerequisite for the success of research. To study this, this article proposes an important concerned factor of topic selection-topic popularity, to examine the relationship between topic selection and team performance.Design/methodology/approachThe authors adopt extracted entities on the type of gene/protein, which are used as proxies as topics, to keep track of the development of topic popularity. The decision tree model is used to classify the ascending phase and descending phase of entity popularity based on the temporal trend of entity occurrence frequency. Through comparing various dimensions of team performance – academic performance, research funding, relationship between performance and funding and corresponding author's influence at different phases of topic popularity – the relationship between the selected phase of topic popularity and academic performance of research teams can be explored.FindingsFirst, topic popularity can impact team performance in the academic productivity and their research work's academic influence. Second, topic popularity can affect the quantity and amount of research funding received by teams. Third, topic popularity can impact the promotion effect of funding on team performance. Fourth, topic popularity can impact the influence of the corresponding author on team performance.Originality/valueThis is a new attempt to conduct team-oriented analysis on the relationship between topic selection and academic performance. Through understanding relationships amongst topic popularity, team performance and research funding, the study would be valuable for researchers and policy makers to conduct reasonable decision making on topic selection.

Some metaheuristic algorithms for solving multiple cross-functional team selection problems.

We can find solutions to the team selection problem in many different areas. The problem solver needs to scan across a large array of available solutions during their search. This problem belongs to a class of combinatorial and NP-Hard problems that requires an efficient search algorithm to maintain the quality of solutions and a reasonable execution time. The team selection problem has become more complicated in order to achieve multiple goals in its decision-making process. This study introduces a multiple cross-functional team (CFT) selection model with different skill requirements for candidates who meet the maximum required skills in both deep and wide aspects. We introduced a method that combines a compromise programming (CP) approach and metaheuristic algorithms, including the genetic algorithm (GA) and ant colony optimization (ACO), to solve the proposed optimization problem. We compared the developed algorithms with the MIQP-CPLEX solver on 500 programming contestants with 37 skills and several randomized distribution datasets. Our experimental results show that the proposed algorithms outperformed CPLEX across several assessment aspects, including solution quality and execution time. The developed method also demonstrated the effectiveness of the multi-criteria decision-making process when compared with the multi-objective evolutionary algorithm (MOEA).

Contribution of person-team fit parameters to teamwork effectiveness in construction project teams

PurposeThough affective commitment has been thought to be critical in team selection, it is yet to be integrated into current models on team selection primarily due to lack of understanding of its contribution to teamwork effectiveness and performance. This study tests the contribution of complementary person team-fit (CF), supplementary person team-fit (SF) and affective commitment (AC) to teamwork effectiveness in construction project teams. By this examination, a theoretical case is made for the inclusion of affective commitment in team selection and deployment in construction project delivery.Design/methodology/approachBy using a deductive questionnaire survey on project team participants and experienced human resource managers in recruitment and team selection in project organizations, structural equation model (SEM) was used to test the contribution of CF, SF and AC parameters to teamwork effectiveness from a total of 105 responses gathered from project team participants in project delivery.FindingsThe SEM revealed that, CF, SF and AC together account for about 81% predictive effect to teamwork effectiveness which is higher than joint effect of CF and SF in existing models in team selection and deployment. By this, it can be affirmed that, in considering CF, SF and AC in an integrated manner in team selection and deployment, higher team effectiveness can be achieved that can stimulate high performing teams and effectiveness in project delivery.Originality/valueThe findings give theoretical assertiveness to extending consideration of competence and values in team selection to embrace affections and commitment to engender effectiveness in teamwork, cohesion, collaboration and performance. This present novel attempts to include affective commitment in teamwork toward higher team effectiveness.