Investigating task coordination in globally dispersed teams:a structural contingency perspective

Task coordination poses significant challenges for globally dispersed teams (GDTs). Although various task coordination mechanisms have been proposed for such teams, there is a lack of systematic examination of the appropriate coordination mechanisms for different teams based on the nature of their task and the context under which they operate. Prior studies on collocated teams suggest matching their levels of task dependence to specific task coordination mechanisms for effective coordination. This research goes beyond the earlier work by also considering additional contextual factors of GDT (i.e., temporal dispersion and time constraints) in deriving their optimal IT-mediated task coordination mechanisms. Adopting the structural contingency theory, we propose optimal IT-mediated task coordination portfolios to fit the different levels of task dependence, temporal dispersion, and perceived time constraint of GDTs. The proposed fit is tested through a survey and profile analysis of 95 globally dispersed software development teams in a large financial organization. We find, as hypothesized, that the extent of fit between the actual IT-mediated task coordination portfolios used by the surveyed teams and their optimal portfolios proposed here is positively related to their task coordination effectiveness that in turn impacts the team's efficiency and effectiveness. The implications for theory and practice are discussed

Finnish Enterprise Agile Transformations : A Survey Study

Peer reviewe

Baseline study of employability related activities in Scottish colleges

In October 2004, the Scottish Funding Council (SFC)'s predecessor bodies, theSFEFC and the SHEFC, publishedLearning to Work(SFC 2004), a discussion paperabout how Scotland's colleges and universities can help to enhance learners'employability. In subsequent dialogue with stakeholders, there was agreement thatemployability should be a specific focus for quality enhancement in the college sectorfrom 2006-07. As a basis for further development, the SFC commissioned this studyto provide information on the range of current activities and practices in Scotland'scolleges which contribute to enhancing employability

Lived Experiences of Women in Collegiate Esports Leadership

A leadership gender gap exists in politics, business, and higher education, and there appears to be one in collegiate esports. Researchers have conducted studies on some aspects of esports; however, we know little about women’s experiences leading collegiate esports programs. The purpose of this qualitative study - a descriptive (transcendental) phenomenology – was to explore and describe the essence of women’s lived experiences in leading collegiate varsity esports programs at higher education institutions. In-depth interviews were the research method. Seven women employed as collegiate varsity esports coaches or directors described their historical context, present experiences in the profession, and how this experience is meaningful. NVivo qualitative software was used for organizing, analyzing, and coding data for themes and commonalities. This preliminary work led to the development of textural and structural descriptions and, finally, the essence of women’s experiences as collegiate esports coaches and directors. Ultimately, the essence of the lived experiences of a woman in collegiate esports leadership funneled down to meaningful managing with excellence using skills developed through previous life experiences. Meaningful managing with excellence is that “condition or quality without” which being a woman in collegiate esports leadership “would not be what it is.

Agile Processes in Software Engineering and Extreme Programming: 18th International Conference, XP 2017, Cologne, Germany, May 22-26, 2017, Proceedings

agile software development; lean development; scrum; project management; software developmen

Resilience and Adaptive Capacity in Hospital Teams

Introduction Resilient Healthcare, a field derived from Resilience Engineering, provides a set of theoretical principles for understanding quality and safety in complex systems. So far, these principles have been used to capture individual, departmental, and organisational proactive responses to variable conditions and how this flexibility, involving anticipating, monitoring, responding, learning, and coordinating, contributes to safety. Empirical exploration of Resilient Healthcare has primarily taken place in specific healthcare settings such as emergency departments and surgery, with specific activities such as flow procedures, anaesthesia, blood transfusion, nurse handover, electronic charting, and patient discharge. Understanding healthcare work beyond these limited settings and activities is important, as most patient encounters in the hospital occur in ward settings beyond surgery and emergency care. The role of the team in flexible adaptation also needs to be explored, as effective teamwork is widely recognised as a contributor to healthcare safety.Healthcare teams are diverse and their need for adaptive capacity, the challenges they face, and their ability to coordinate are also likely to be different. Current research on healthcare teams involves teams that are easily defined, such as resuscitation teams, surgical teams, or teams in a simulation lab. Thus, the full range of healthcare teams and their capacity to adapt has not yet been captured. To better understand how to improve teamwork and safety, we must first understand how teams are already adapting to variable conditions in complex organisations. This includes aspects such as the clinical and organisational challenges they face, the dynamics of the team, how flexible teamworking can be supported, as well as more broadly understanding and categorising the different types of teams that exist in healthcare. Aims and objectives The aim of this PhD was to investigate how adaptive capacity is hindered or supported by organisational and contextual factors in different types of hospital teams.The study objectives were to: 1. Review the concept of adaptive teamwork, synthesising available cross-disciplinary research, clarifying key definitions, and identifying factors that might impact team adaptive capacity 2. Develop an empirically derived typology for classifying types of hospital teams based on their structure, membership, and function3. Identify the misalignments, adaptions, pressures, and trade-off decisions of hospital teams in practice 4. Understand differences between types of hospital teams, both in the misalignments and pressures they experience and in the adaptations and trade-off decisions they make, using mixed qualitative methods in two hospitals in England Methods The study was conducted in three phases: - Phase 1: A scoping review of adaptive teamwork Phase one involved a scoping literature review to systematically map existing research on adaptive teamwork and to identify gaps in knowledge. The primary research question was: What do we know about the structure and function of adaptive teams in practice? - Phase 2: Theory development Phase two involved analysis of data previously collected by the larger research team to better understand work-as-done and team structure in hospital teams. The data included 88.5 hours of hospital ethnography on five different hospital wards. An inductive-deductive approach to data analysis was undertaken. - Phase 3: A case study of adaptive teamwork in England Phase three consisted of data collection in two hospitals situated within one Trust (one large and one community hospital), with five teams per hospital (two total teams of each type). In total, 144 hours and 54 minutes of ethnography were completed across the two hospitals and 24 semi-structured interviews were conducted. The overarching aim of the case study was to investigate how adaptive capacity is hindered or supported by organisational and contextual factors in different types of teams. This phase was conducted in a directed rather than exploratory way, building on the data from phase two and increasing the depth of understanding of all five team types. In this phase, both interview and observational data were analysed using the typology and two frameworks produced in phase two. The England case study will eventually contribute to a comparative, cross-country analysis to synthesise and compare findings between countries and healthcare systems (Anderson, Aase, et al., 2020). Ethics and dissemination The overall Resilience in Healthcare research programme that this study is part of has been granted ethical approval by the Norwegian Centre for Research Data (Ref.No. 8643334). Ethical approval to conduct the study in England was granted through King’s College London Research Ethics Office (LRS/DP-21/22-26055). HRA REC approval was 10also granted (22/HRA/1621; IRAS 312079). A research passport was obtained, and letter of access received from local Trust R&D.Results The phase one scoping review included 204 documents and mapped their geographies, fields, settings, and designs. Terminology used to describe elements of the adaptive process were compared. A new conceptualisation of the team adaptive cycle was proposed, along with a new definition for team adaptive capacity. Future opportunities for research were proposed, including the opportunity to study adaptive teams in situ and to consider differences in team adaptive capacity based on unique team features. The second phase of the study resulted in the conceptualisation of: a typology of healthcare teams (paper under review), the Concepts for Applying Resilience Engineering Model 2.0 (published paper), and the Pressures Diagram (published paper). Building on this, the third phase suggested that teams’ adaptive strategies varied based on team type, although demand-capacity misalignments occurred across all team types, suggesting that team type impacts adaptive capacity. While adaptations supported teams’ abilities to overcome misalignments, they also required resources and were more or less possible depending on team type. Likewise, while pressures occurred across all team types, trade-off decisions varied depending on the team type. These findings have implications for team training, workforce planning, and resourcing, and can inform future work that aims to strengthen adaptive capacity and teamworking.Conclusions Overall, this thesis makes unique and important contributions to the literature on both resilient healthcare and adaptive teamwork. It has developed multiple new practical and theoretical models and typologies that have subsequently been used internationally in research. A novel approach combining teamwork and resilient healthcare theory was used successfully to understand and compare healthcare misalignments, adaptations, pressures, and trade-offs in five different team types. The finding that adaptive strategies and trade-off decisions differ based on team type challenges existing teamwork improvement practices, which take a one-size-fits-all approach to conceptualising and training teams. The results provide foundational knowledge to guide future intervention design, which may potentially bring about wider changes in training and sustaining successful teams and supporting their adaptive capacity

Structuring AI Teammate Communication: An Exploration of AI\u27s Communication Strategies in Human-AI Teams

In the past decades, artificial intelligence (AI) has been implemented in various domains to facilitate humans in their work, such as healthcare and the automotive industry. Such application of AI has led to increasing attention on human-AI teaming, where AI closely collaborates with humans as a teammate. AI as a teammate is expected to have the ability to coordinate with humans by sharing task-related information, predicting other teammates’ behaviors, and progressing team tasks accordingly. To complete these team activities effectively, AI teammates must communicate with humans, such as sharing updates and checking team progress. Even though communication is a core element of teamwork that helps to achieve effective coordination, how to design and structure human-AI communication in teaming environments still remains unclear. Given the context-dependent characteristics of communication, research on human-AI teaming communication needs to narrow down and focus on specific communication elements/components, such as the proactivity of communication and communication content. In doing so, this dissertation explores how AI teammates’ communication should be structured by modifying communication components through three studies, each of which details a critical component of effective AI communication: (1) communication proactivity, (2) communication content (explanation), and (3) communication approach (verbal vs. non-verbal). These studies provide insights into how AI teammates’ communication ii can be integrated into teamwork and how to design AI teammate communication in human-AI teaming. Study 1 explores an important communication element, communication proactivity, and its impact on team processes and team performance. Specifically, communication proactivity in this dissertation refers to whether an AI teammate proactively communicates with human teammates, i.e., proactively pushing information to human teammates. Experimental analysis shows that AI teammates’ proactive communication plays a crucial role in impacting human perceptions, such as perceived teammate performance and satisfaction with the teammate. Importantly, teams with a non-proactive communication AI teammate increase team performance more than teams with a proactive communication AI as the human and the AI collaborate more. This study identifies the positive impact of AI being proactive in communication at the initial stage of task coordination, as well as the potential need for AI’s flexibility in their communication proactivity (i.e., once human and AI teammates’ coordination pattern forms, AI can be non-proactive in communication). Study 2 examines communication content by focusing on AI’s explanation and its impact on human perceptions in teaming environments. Results indicate that AI’s explanation, as part of communication content, does not always positively impact human trust in human-AI teaming. Instead, the impact of AI’s explanations on human perceptions depends on specific collaboration scenarios. Specifically, AI’s explanations facilitate trust in the AI teammate when explaining why AI disobeys humans’ orders, but hinder trust when explaining why AI lies to humans. In addition, AI giving an explanation of why they ignored the human teammate’s injury was perceived to be more effective than AI not providing such an explanation. The findings emphasize the context-dependent characteristic of AI’s communication content with a focus on AI’s explanation of their actions. iii Study 3 investigates AI’s communication approach, which was manipulated as verbal vs. non-verbal communication. Results indicate that AI teammates’ verbal/nonverbal communication does not impact human trust in the AI teammate, but facilitates the maintenance of humans’ situation awareness in task coordination. In addition, AI with non-verbal communication is perceived as having lower communication quality and lower performance. Importantly, AI with non-verbal communication has better team performance in human-human-AI teams than human-AI-AI teams, whereas AI with verbal communication has better team performance in human-AI-AI teams than human-human-AI teams. These three studies together address multiple research gaps in human-AI team communication and provide a holistic view of the design and structure of AI’s communication by examining three specific aspects of communication in human-AI teaming. In addition, each study in this dissertation proposes practical design implications on AI’s communication in human-AI teams, which will assist AI designers and developers to create better AI teammates that facilitate humans in teaming environments

Developing and Facilitating Temporary Team Mental Models Through an Information-Sharing Recommender System

It is well understood that teams are essential and common in many aspects of life, both work and leisure. Due to the importance of teams, much research attention has focused on how to improve team processes and outcomes. Of particular interest are the cognitive aspects of teamwork including team mental models (TMMs). Among many other benefits, TMMs involve team members forming a compatible understanding of the task and team in order to more efficiently make decisions. This understanding is sometimes classified using four TMM domains: equipment (e.g., operating procedures), task (e.g., strategies), team interactions (e.g., interdependencies) and teammates (e.g., tendencies). Of particular interest to this dissertation is accelerating the development of teammate TMMs which include members understanding the knowledge, skills, attitudes, preferences, and tendencies of their teammates. An accurate teammate TMM allows teams to predict and account for the needs and behaviors of their teammates. Although much research has highlighted how the development of the four TMM domains can be supported, promoting the development of teammate TMMs is particularly challenging for a specific type of team: temporary teams. Temporary teams, in contrast to ongoing teams, involve unknown teammates, novel tasks, short task times (alternatively limited interactions), and members disbanding after completing their task. These teams are increasingly used by organizations as they can be agilely formed with individual members selected to accomplish a specific task. Such teams are commonly used in contexts such as film production, the military, emergency response, and software development, just to name a few. Importantly, although these teams benefit greatly from teammate TMMs due to the efficiencies gained in decision making while working under limited deadlines, the literature is severely limited in understanding how to support temporary teams in this way. As prior research has suggested, an opportunity to accelerate teammate TMM development on temporary teams is through the use of technology to selectively share teammate information to support these TMMs. However, this solution poses numerous privacy concerns. This dissertation uses four studies to create a foundational and thorough understanding of how recommender system technology can be used to promote teammate TMMs through information sharing while limiting privacy concerns. Study 1 takes a highly exploratory approach to set a foundation for future dissertation studies. This study investigates what information is perceived to be helpful for promoting teammate TMMs on actual temporary teams. Qualitative data suggests that sharing teammate information related to skills/preferences, conflict management styles, and work ethic/reliability is perceived as beneficial to supporting teammate TMMs. Also, this data provides a foundational understanding for what should be involved in information-sharing recommendations for promoting teammate TMMs. Quantitative results indicate that conflict management data is perceived as more helpful and appropriate to share than personality data. Study 2 investigates the presentation of these recommendations through the factors of anonymity and explanations. Although explanations did not improve trust or satisfaction in the system, providing recommendations associated with a specific teammate name significantly improved several team measures associated with TMMs for actual temporary teams compared to teams who received anonymous recommendations. This study also sheds light on what temporary team members perceive as the benefits to sharing this information and what they perceive as concerns to their privacy. Study 3 investigates how the group/team context and individual differences can influence disclosure behavior when using an information-sharing recommender system. Findings suggest that members of teams who are fully assessed as a team are more willing to unconditionally disclose personal information than members who are assessed as an individual or members who are mixed assessed as an individual and a team. The results also show how different individual differences and different information types are associated with disclosure behavior. Finally, Study 4 investigates how the occurrence and content of explanations can influence disclosure behavior and system perceptions of an information-sharing recommender system. Data from this study highlights how benefit explanations provided during disclosure can increase disclosure and explanations provided during recommendations can influence perceptions of trust competence. Meanwhile, benefit-related explanations can decrease privacy concerns. The aforementioned studies fill numerous research gaps relating to teamwork literature (i.e., TMMs and temporary teams) and recommender system research. In addition to contributions to these fields, this dissertation results in design recommendations that inform both the design of group recommender systems and the novel technology conceptualized through this dissertation, information-sharing recommender systems