Antecedents and consequences of team potency in software development projects

Akgün, Ali E.; Keskin, Halit; Byrne, John C.; İmamoğlu, Salih Zeki

doi:10.1016/j.im.2007.08.001

Cited by 63 publications

(44 citation statements)

References 37 publications

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“…The group potency construct is usually defined as "a collective belief regarding the team's ability to be successful" (as cited by [9]). The importance of the construct was, and continues to be, its strong relationship to group performance [10], [11], [12]. This strong relationship between group potency and performance has been found at both the individual and group levels, although the strength between the two variables has been shown to be higher at the group level [13].…”

Section: Group Potencymentioning

confidence: 96%

“…Both of these factors allow team members to learn about each other's skills and capabilities, hence increasing the group's overall collective confidence. Finally, group size was found to be related to group potency [12], because, as [14] argues, groups with insufficient (or too many) members feel less confident about the team's ability to complete the task.…”

Section: Group Potencymentioning

confidence: 99%

“…In a similar study, charismatic leadership was found to be related to group potency [15], [16], because, as the author explained, the presence of a leader helps guide other members toward the team's goals. Other researchers have found that a team's skill level, knowledge, and performance can have a positive effect on group potency [12], [10], largely because such factors tend to increase a group's confidence levels and, thus, affect the member's perception of the group's abilities. In a similar manner, researchers have determined that there is a positive relationship between group potency and communication and cooperation [10], [16].…”

Section: Group Potencymentioning

confidence: 99%

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Classification of Group Potency Levels of Software Development Student Teams

et al. 2015

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Abstract-This paper describes the use of an automatic classifier to model group potency levels within software development projects. A set of machine learning experiments that looked at different group characteristics and various collaboration measures extracted from a team's communication activities were used to predict overall group potency levels. These textual communication exchanges were collected from three software development projects involving students living in the US, Turkey and Panama. Based on the group potency literature, group-level measures such as skill diversity, cohesion, and collaboration were developed and then collected for each team. A regression analysis was originally performed on the continuous group potency values to test the relationships between the group-level measures and group potency levels. This method, however, proved to be ineffective. As a result, the group potency values were converted into binary labels and the relationships between the group-level measures and group potency were re-analyzed using machine learning classifiers. Results of this new analysis indicated an improvement in the accuracy of the model. Thus, we were able to successfully characterize teams as having either low or high potency levels. Such information can prove useful to both managers and leaders of teams in any setting.

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Section: Group Potencymentioning

confidence: 96%

Section: Group Potencymentioning

confidence: 99%

Section: Group Potencymentioning

confidence: 99%

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Classification of Group Potency Levels of Software Development Student Teams

et al. 2015

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“…In short, the principles of Streamline development postulated that software development was organized as a series of activities centered around the product and executed mainly in cross-functional teams responsible for the design, implementation and partially testing of their part of the product (e.g. a feature) [25]. This was found to be rather typical process design that addressed market pull in Lean development [26].…”

Section: Streamline Development Sdmentioning

confidence: 99%

Release Readiness Indicator for Mature Agile and Lean Software Development Projects

Staron

Meding

Palm

2012

Lecture Notes in Business Information Processing

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Abstract. Large companies like Ericsson increasingly often adopt the principles of Agile and Lean software development and develop large software products in iterative manner -in order to quickly respond to customer needs. In this paper we present the main indicator which is sufficient for a mature software development organization in order to predict the time in weeks to release the product. In our research project we collaborated closely with a large Agile+Lean software development project at Ericsson in Sweden. This large and mature software development project and organization has found this main indicator -release readiness -to be so important that it was used as a key performance indicator and is used in controlling the development of the product and improving organizational performance. The indicator was developed and validated in an action research project at one of the units of Ericsson AB in Sweden in one of its largest projects.

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“…Research has indicated that CCE is one of the most important influences on performance (Akgun, Keskin, Byren & Imamoglu, 2007). Thus, this research collected the process and product performance data of each ISD student team.…”

Section: Reliability and Validitymentioning

confidence: 99%

Student team projects in information systems development: Measuring collective creative efficacy

Cheng

Yang

2011

AJET

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For information systems development project student teams, learning how to improve software development processes is an important training. Software process improvement is an outcome of a number of creative behaviours. Social cognitive theory states that the efficacy of judgment influences behaviours. This study explores the impact of three types of team knowledge: domain knowledge, methodological knowledge and implementation knowledge, as well as achievement motivation on student teams' collective creative efficacy (CCE) during information system development. This research also discusses the correlation between CCE and project performance using data from 98 student teams. Because of the difference in project characteristics, we divided the teams into "actual demand" project teams (having a real business case) and "suppositional demand" (having no real case, just an artificial or simulated case) project teams. The results show that achievement motivation positively influences CCE, either in "actual demand" teams or in "suppositional demand" teams. Domain knowledge is significantly correlated to CCE in "actual demand" teams, but methodological knowledge and implementation knowledge significantly influenced CCE in "suppositional demand" teams. CCE is not significantly related to project performance in "actual demand" teams. However, CCE is related to process performance and product performance in "suppositional demand" teams. Whilst this study explores issues in team project learning activities for students in information systems, some suggestions are made for educational designers using similar activities in other disciplines.

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Antecedents and consequences of team potency in software development projects

Cited by 63 publications

References 37 publications

Classification of Group Potency Levels of Software Development Student Teams

Classification of Group Potency Levels of Software Development Student Teams

Release Readiness Indicator for Mature Agile and Lean Software Development Projects

Student team projects in information systems development: Measuring collective creative efficacy

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