Development of a team measure for tacit knowledge in software development teams

In this paper we operationally define and measure tacit knowledge at the team-level in the software development domain. Through a series of three empirical studies we developed and validated the team tacit knowledge measure (TTKM) for software developers. In the first study, initial scale items were developed using the repertory grid technique and content analysis. In Study 2, supplied repertory grids were administered to novices and experts to establish differential items, and Study 3 validated the TTKM on a sample of 48 industrial software development teams. In developing the TTKM we explored the relationships between tacit knowledge, explicit job knowledge and social interaction and their effect on team performance as measured by efficiency and effectiveness. In addition we assess the implications for managing software development teams and increasing team performance through social interaction.     

Charismatic leadership and tacit knowledge sharing in the context of enterprise systems learning: the mediating effect of psychological safety climate and intrinsic motivation

Drawing upon charismatic leadership and intrinsic motivation theory, we developed a theoretical model to examine the impact mechanism of leader charisma on individuals’ tacit knowledge-sharing behaviour in the context of an Enterprise Systems learning team. We conducted a survey-based field study to examine the theoretical model and hypotheses. A total of 153 questionnaires were distributed to employees from more than 20 branches of the Beidahuang Group in China and 117 valid questionnaires were returned. Results from partial least squares analysis suggest that leader charisma has a strong influence on psychological safety climate, which in turn has a positive impact on individuals’ intrinsic motivation and their tacit knowledge-sharing behaviour. Our research findings unpack the impact mechanism of charismatic leadership on tacit knowledge sharing, and provide guidelines for the team leader to exhibit charismatic leadership traits in order to promote a psychological safety climate and facilitate an effective knowledge sharing of enterprise systems.     

The effect of Facebook use on office workers’ job performance and the moderating effects of task equivocality and interdependence

As office workers’ use of social networking sites (SNSs) has increased, so has research interest in the effect of SNS use on job performance. The present study employs data collected from South Korean office workers to examine how the use of the SNS Facebook affects job performance and to investigate the moderating effects of task characteristics (task equivocality and task interdependence). The results show that Facebook use for work has a positive effect on job performance, although the time spent on Facebook use does not have a significant effect on job performance. Moreover, task interdependence is associated with a decrease in the effect of Facebook use for work on job performance. In other words, task interdependence has a negative moderating effect on the impact of Facebook use for work on job performance. The reason is that Facebook is particularly advantageous for enhancing performance in tasks where the level of interdependence is low because it is a medium with relatively low synchrony and is unsuitable for one-to-one relationship building. This study has implications for companies that are concerned about formulating policies related to employees’ use of SNSs.     

Acquiring and sharing tacit knowledge in software development teams: An empirical study

ContextSharing expert knowledge is a key process in developing software products. Since expert knowledge is mostly tacit, the acquisition and sharing of tacit knowledge along with the development of a transactive memory system (TMS) are significant factors in effective software teams.ObjectiveWe seek to enhance our understanding human factors in the software development process and provide support for the agile approach, particularly in its advocacy of social interaction, by answering two questions: How do software development teams acquire and share tacit knowledge? What roles do tacit knowledge and transactive memory play in successful team performance?MethodA theoretical model describing the process for acquiring and sharing tacit knowledge and development of a TMS through social interaction is presented and a second predictive model addresses the two research questions above. The elements of the predictive model and other demographic variables were incorporated into a larger online survey for software development teams, completed by 46 software SMEs, consisting of 181 individual team members.ResultsOur results show that team tacit knowledge is acquired and shared directly through good quality social interactions and through the development of a TMS with quality of social interaction playing a greater role than transactive memory. Both TMS and team tacit knowledge predict effectiveness but not efficiency in software teams.ConclusionIt is concluded that TMS and team tacit knowledge can differentiate between low- and high-performing teams in terms of effectiveness, where more effective teams have a competitive advantage in developing new products and bringing them to market. As face-to-face social interaction is key, collocated, functionally rich, domain expert teams are advocated rather than distributed teams, though arguably the team manager may be in a separate geographic location provided that there is frequent communication and effective use of issue tracking tools as in agile teams.     

Development of a reduced human user input task allocation method for multiple robots

Task allocation mechanisms are employed by multi-robot systems to efficiently distribute tasks between different robots. Currently, many task allocation methods rely on detailed expert knowledge to coordinate robots. However, it may not be feasible to dedicate an expert human user to a multi-robot system. Hence, a non-expert user may have to specify tasks to a team of robots in some situations. This paper presents a novel reduced human user input multi-robot task allocation technique that utilises Fuzzy Inference Systems (FISs). A two-stage primary and secondary task allocation process is employed to select a team of robots comprising manager and worker robots. A multi-robot mapping and exploration task is utilised as a model task to evaluate the task allocation process. Experiments show that primary task allocation is able to successfully identify and select manager robots. Similarly, secondary task allocation successfully identifies and selects worker robots. Both task allocation processes are also robust to parameter variation permitting intuitive selection of parameter values.     

Team task analysis: identifying tasks and jobs that are team based

This paper presents initial information on the development and validation of three team task analysis scales. These scales were designed to quantitatively assess the extent to which a group of tasks or a job is team based. During a 2-week period, 52 male students working in 4-person teams were trained to perform a complex highly interdependent computer-simulated combat mission consisting of both individual- and team-based tasks. Our results indicated that the scales demonstrated high levels of interrater agreement. In addition, the scales differentiated between tasks that were predetermined to be individual versus team based. Finally, the results indicated that job-level ratings of team workflow were more strongly related to team performance than were aggregated task-level ratings of team-relatedness or team workflow. These results suggest that the scales presented here are an effective means of quantifying the extent to which tasks or jobs are team based. A research and practical implication of our findings is that the team task analysis scales could serve as criterion measures in the evaluation of team training interventions or predictors of team performance.     

Individual learning goal orientations in self‐managed team‐based organizations: A study on individual and contextual variables

Previous research has shown the importance of individual learning goal orientation for both job and task performance and consequently organizational performance. Despite its importance, knowledge on the antecedents of learning goal orientation remains scarce, especially in the context of self‐managing team‐based organizations. In fact, most of the research on goal orientation antecedents has been focused on individual characteristics, belief, and ability, while the contextual factors that might influence them remain unspecified. We build on and further extend earlier studies by jointly exploring the role of individual and contextual factors affecting individual learning orientation. In particular, this study combines individual informal social network, self‐efficacy, performance feedbacks, and team identification into a model that explains individuals' learning goal orientation within self‐managing team‐based organizations. The model was empirically tested on a sample of 104 individuals belonging to an R&D organization relying on self‐managing teams. Results show that performance feedback has a negative direct effect, while team identification has a positive direct effect on individual learning goal orientation. In addition, we found that individual self‐efficacy is a mediator of the relationships between performance feedback and brokerage in the advice network and individual learning goal orientation. Finally, we did not find a relationship between centrality in the friendship network and individual learning goal orientation.     

Knowledge sharing,innovation and firm performance

This study investigates the quantitative relationship between knowledge sharing, innovation and performance. Based on the literature review, we develop a research model positing that knowledge sharing not only have positive relationship with performance directly but also influence innovation which in turn contributes to firm performance. This model is empirically tested using data collected from 89 high technology firms in Jiangsu Province of China. It is found that both explicit and tacit knowledge sharing practices facilitate innovation and performance. Explicit knowledge sharing has more significant effects on innovation speed and financial performance while tacit knowledge sharing has more significant effects on innovation quality and operational performance.     

基于交叉层级数据共享的多任务模型

针对多任务学习模型中相关度低的任务之间存在的负迁移现象和信息共享困难问题,提出了一种基于交叉层级数据共享的多任务模型。该模型关注细粒度的知识共享,且能保留浅层共享专家的记忆能力和深层特定任务专家的泛化能力。首先,统一多层级共享专家,以获取复杂相关任务间的公共知识;然后,将共享信息分别迁移到不同层级的特定任务专家之中,从而在上下层之间共享部分公共知识;最后,利用基于数据样本的门控网络自主选择不同任务所需信息,从而减轻样本依赖性对模型的不利影响。相较于多门控混合专家（MMOE）模型,所提模型在UCI census-income数据集上对两个任务的F1值分别提高了7.87个百分点和1.19个百分点;且在MovieLens数据集上的回归任务的均方误差（MSE）值降低到0.004 7,分类任务的AUC值提高到0.642。实验结果表明,所提出的模型适用于改善负迁移现象的影响,且能更高效地学习复杂相关任务之间的公共信息。     

Effects of sleep loss on team decision making: motivational loss or motivational gain?

OBJECTIVE: To examine the effects of 30 hr of sleep loss and continuous cognitive work on performance in a distributed team decision-making environment. BACKGROUND: To date, only a few studies have examined the effect of sleep loss on distributed team performance, and only one other to our knowledge has examined the relationship between sleep loss and social-motivational aspects of teams (Hoeksema-van Orden, Gaillard, & Buunk, 1998). METHOD: Sixteen teams participated; each comprised 4 members. Three team members made threat assessments on a military surveillance task and then forwarded their judgments electronically to a team leader, who made a final assessment on behalf of the team. RESULTS: Sleep loss had an antagonistic effect on team decision-making accuracy and decision time. However, the performance loss associated with fatigue attributable to sleep loss was mediated by being part of a team, as compared with performing the same task individually - that is, we found evidence of a "motivational gain" effect in these sleepy teams. We compare these results with those of Hoeksema-van Orden et al. (1998), who found clear evidence of a "social loafing" effect in sleepy teams. CONCLUSION: The divergent results are discussed in the context of the collective effort model (Karau & Williams, 1993) and are attributable in part to a difference between independent and interdependent team tasks. APPLICATION: The issues and findings have implications for a wide range of distributed, collaborative work environments, such as military network-enabled operations.     

Usage and impact of technology enabled job learning

Individuals use technology to experiment with new ways of carrying out their tasks and in doing so they learn more about their jobs. The current study examines the role of technology enabled job learning as a key component in the complex relationship between information systems use and technology outcomes. Data from 308 end-users were analyzed to evaluate the relationships between system use and technology enabled job learning, and technology enabled job learning and technology outcomes. Technology enabled job learning was conceptualized in terms of how computer applications helped individuals learn and better perform their jobs. System use was conceptualized in terms of decision support, work integration, and customer service. Technology outcomes were conceptualized in terms of management control, task innovation, task productivity, and customer satisfaction. Results suggest that systems use has a significant, positive effect on job learning, and that job learning has a significant, positive effect on technology outcomes. Post hoc analyses were then conducted to examine the potential mediating role of job learning between systems use and technology outcomes. The findings from this research lead to a greater understanding of how patterns of systems use influence organizationally relevant outcomes through technology-enabled job learning.     

Examining the effects of communication training and teamcomposition on the decision making of Patriot air defense teams

An experiment investigating the effect of communication training and three group composition variables was performed with Patriot air defense teams for two different types of aircraft identification tasks. It was predicted that communication training would significantly enhance communication quantity and quality and, in turn, team performance for both tasks. Although the training did sometimes improve team communication processes, it did not improve team performance. The variable that had the biggest positive effect on communication quality and team performance was the number of hours a team had worked together. This effect was only found, however, for the type of task for which Patriot teams routinely train. It did not transfer to the less frequent and more cognitively stressing task where there is conflicting information about unknown aircraft, as in the USS Vincennes tragedy     

Exploring the effects of trust,task interdependence and virtualness on knowledge sharing in teams

The sharing of knowledge within teams is critical to team functioning. However, working with team members who are in different locations (i.e. in virtual teams) may introduce communication challenges and reduce opportunities for rich interactions, potentially affecting knowledge sharing and its outcomes. Therefore, using questionnaire‐based data, this study examined the potential effects of different aspects of virtuality on a knowledge‐sharing model. Social exchange theory was used to develop a model relating trust to knowledge sharing and knowledge sharing to team effectiveness. The moderating effects of virtuality and task interdependence on these relationships were examined. A strong positive relationship was found between trust and knowledge sharing for all types of teams (local, hybrid and distributed), but the relationship was stronger when task interdependence was low, supporting the position that trust is more critical in weak structural situations. Knowledge sharing was positively associated with team effectiveness outcomes; however, this relationship was moderated by team imbalance and hybrid structures, such that the relationship between sharing and effectiveness was weaker. Organizations should therefore avoid creating unbalanced or hybrid virtual teams.     

Adaptive generalisation

Adaptive generalisation is the ability to use prior knowledge in the performance of novel tasks. Thus, if we are to model intelligent behaviour with neural nets, they must be able to generalise across task domains. Our objective is to elucidate the aetiology of transfer of information between connectionist nets. First, a method is described that provides a standardised score for the quantification of how much task structure a net has extracted, and to what degree knowledge has been transferred between tasks. This method is then applied in three simulation studies to examine Input-to-Hidden (IH) and Hidden-to-Output (HO) decision hyperplanes as determinants of transfer effects. In the first study, positive transfer is demonstrated between functions that require the vertices of their spaces to be divided similarly, and negative transfer between functions that require decision regions of different shapes. In the other two studies, input and output similarity are varied independently in a series of paired associate learning tasks. Further explanation of transfer effects is provided through the use of a new technique that permits better visualisation of the entire computational space by showing both the relative position of inputs in Hidden Unit space, and the HO decision regions implemented by the set of weights.This research was supported by an award from the Economic and Social Research Council, Grant No R000233441. An earlier version of this paper appears in the Proceedings of the Second Irish Networks Conference, Belfast 1992.     

The contingent effects of leadership on team collaboration in virtual teams

Decision-making in virtual teams creates challenges for leaders to structure team processes and provide task support. To help advance our knowledge of leadership in virtual teams, we explore the interaction effects between leadership styles and media richness on task cohesion and cooperative climate, which in turn influence team performance in decision-making tasks. Results from a laboratory study suggest that transactional leadership behaviors improve task cohesion of the team, whereas transformational leadership behaviors improve cooperative climate within the team which, in turn, improves task cohesion. However, these effects of leadership depend on media richness. Specifically, they occur only when media richness is low. Our results also suggest that task cohesion leads to group consensus and members’ satisfaction with the discussion, whereas cooperative climate improves discussion satisfaction and reduces time spent on the task.     

基于知识架构的持续学习情感分类方法

当情感分类模型依次学习多个领域的情感分类任务时，从新任务中学到的参数会直接修改模型原有参数，由于缺少对原有参数的保护机制，降低了模型在旧任务上的分类准确率。为缓解灾难遗忘现象对模型性能的影响，并增加任务间的知识迁移，提出一种用于中文情感分类的基于知识架构的持续学习方法。在Transformer编码层中，采用任务自注意力机制为每个任务单独设置注意力变换矩阵，通过区分任务特有的注意力参数实现知识保留。在TextCNN的全连接层中，利用任务门控注意力(HAT)机制控制每个神经元的开闭，为每个任务训练特定的网络结构，仅激活对任务重要的神经元加强知识挖掘，提升分类效率与准确率。在JD21中文数据集上的实验结果表明，该方法的Last ACC和负类F1值相比于基于HAT的持续学习方法分别提升了0.37和0.09个百分点，具有更高的分类准确率，并且有效缓解了灾难遗忘现象。     

Communication and personality profiles of global software developers

ContextPrior research has established that a small proportion of individuals dominate team communication during global software development. It is not known, however, how these members’ contributions affect their teams’ knowledge diffusion process, or whether their personality profiles are responsible for their dominant presence.ObjectiveWe set out to address this gap through the study of repository artifacts.MethodArtifacts from ten teams were mined from the IBM Rational Jazz repository. We employed social network analysis (SNA) to group practitioners into two clusters, Top Members and Others, based on the numbers of messages they communicated and their engagement in task changes. SNA metrics (density, in-degree and closeness) were then used to study practitioners’ importance in knowledge diffusion. Thereafter, we performed psycholinguistic analysis on practitioners’ messages using linguistic dimensions that had been previously correlated with the Big Five personality profiles.ResultsFor our sample of 146 practitioners we found that Top Members occupied critical roles in knowledge diffusion, and demonstrated more openness to experience than the Others. Additionally, all personality profiles were represented during teamwork, although openness to experience, agreeableness and extroversion were particularly evident. However, no specific personality predicted members’ involvement in knowledge diffusion.ConclusionTask assignment that promotes highly connected team communication networks may mitigate tacit knowledge loss in global software teams. Additionally, while members expressing openness to experience are likely to be particularly driven to perform, this is not entirely responsible for a global team’s success.     

Variation at work: alternations between physically and mentally demanding tasks in blue-collar occupations

Abstract

The aims of this questionnaire study were to describe the occurrence and desired number of alternations between mental and physical tasks in industrial and non-industrial blue-collar work, and determine to which extent selected personal and occupational factors influence these conditions. On average, the 122 participating workers (55 females) reported to have close to four alternations per day between mental and physical tasks, and to desire more alternations than they actually had. They also expressed a general preference for performing a physical task after a mental task and vice versa. In univariate regression models, the desired change in task alternations was significantly associated with gender, age, occupation, years with current work tasks and perceived job control, while occupation was the only significant determinant in a multiple regression model including all factors. Our results suggest that alternations between productive physical and mental tasks could be a viable option in future job rotation.

Practitioner Summary: We addressed attitudes among blue-collar workers to alternations between physically and mentally demanding tasks. More alternations were desired than those occurring in the job, and workers preferred performing a physical task after a mental and vice versa. Alternating physical and mental tasks could, thus, be a viable option in job rotation.     

定性与定量相结合的任务调度方法

针对在复杂产品虚拟样机协同设计阶段的任务调度中存在的问题,建立了定性与定量相结合的调度模型,提出了基于遗传算法的模型求解策略.调度模型通过引入调度主、客体的隐性知识,综合考虑定性指标与定量指标对协同设计的影响;模型求解策略能在满足任务约束的前提下快速求得模型的最优解.实例结果表明,该调度模型及模型求解策略是有效的,能大幅缩短协同设计时间.     

A specialized framework for medical diagnostic knowledge-based systems.

For a knowledge-based system (KBS) to exhibit an intelligent behavior, it must be endowed with knowledge enabling it to represent the expert's strategies. The elicitation task is inherently difficult for strategic knowledge, because strategy is often tacit, and, even when it has been made explicit, it is not an easy task to describe it in a form which may be directly translated and implemented into a program. This paper describes a Specialized Framework for Medical Diagnostic Knowledge-Based Systems that can help an expert in the process of building KBSs in a medical domain. The framework is based on an epistemological model of diagnostic reasoning which has proven to be helpful in describing the diagnostic process in terms of the tasks that it is composed of. It allows a straightforward modeling of diagnostic reasoning at the knowledge level by the domain expert, thus helping to convey domain-dependent strategies into the target KBS.