Gert-Jan de Vreede

Collaboration technology in teams and organizations: Introduction to the special issue

Information technology advances in recent years have facilitated new forms of information and knowledge sharing. Teams and organizations are increasingly exploring and adopting new technologies to support collaborative work. Such technologies range from collaboration and communication technologies that connect members of virtual teams across national and international boundaries to social media technologies that allow teams and organizations to disseminate and gather information from within and outside their institutional boundaries. The widespread availability of smart phones has given whole societies opportunities to participate in large-scale sensemaking, problem solving, and efforts to organize collaborative action. Some of the more popular modern collaboration technologies that have been widely employed in organizations include wikis, social networks, crowdsourcing, tagging plugins, and mashups (Andriole 2010; Van Osch et al. 2015; Go and You 2016). Awiki is a web-based application that allows users to collaboratively develop and modify web pages. The most wellknown example of a wiki is Wikipedia, the online encyclopedia that has been developed and maintained by thousands of volunteers for over 15 years. A wiki system can facilitate knowledge acquisition and support collaboration and communication among members of an organization. Specifically, wikis have the potential to serve as dynamically evolving organizational knowledge repositories by harvesting fragmented knowledge contributed by users. Compared to traditional knowledge management systems (KMSs), wiki systems put less emphasis on centralized control, strict discipline, and extensive monitoring, while users do not need to possess significant technical expertise to participate in the contribution process (Hasan and Pfaff 2006). Experiences with the organizational application of wikis have shown that although wikis require constant contributions to ensure sustainability, they provide a low-cost solution to knowledge management in terms of the creation and deployment of knowledge repositories (Almeida and Rocha 2011; Standing and Kiniti 2011; Arazy and Gellatly 2012). Furthermore, studies suggest that wikis are more effective in facilitating tacit and informational knowledge sharing among organization members than traditional KMSs (Cress and Kimmerle 2008; Standing and Kiniti 2011). Organizations can employ social network technologies both internally and externally. Using internal social networks, individuals can shorten their learning cycle by exploring shared experiences of colleagues (Lin and Hsueh 2006). * Kewen Wu kew259@mail.usask.ca

Evaluating Team Collaboration Quality: The Development and Field Application of a Collaboration Maturity Model

Abstract The quality of collaboration directly affects the quality of an organization’s outcomes and performance. Trends like globalization and increased product and service complexity have pushed organizations to become more and more reliant on collaboration in distributed, cross-disciplinary, cross-cultural, virtual teams. The present research is based on an applied science/engineering (AS/E) research paradigm to address an important class of unsolved problems—measuring the quality of collaboration within and across organizational boundaries. This paper presents a collaboration maturity model (Col-MM) to assess an organization’s team collaboration maturity as a first step toward a generalizable solution to that class of problems. The Col-MM is intended to be sufficiently generic to be applied to different organizational and team settings and usable by practitioners for conducting self-assessments. The Col-MM was developed during a series of focus group meetings with professionals (business unit managers). The model was then piloted and subsequently applied in a field study in an automotive company. This paper reports on the development and field application of the Col-MM. It contributes to the collaboration science literature, theory, and practice through a detailed AS/E study that develops a maturity model and a system for administering it that provides proof of value and effective use in the field.

Understanding trust influencing factors in social media communication

Trust in social media communication is investigated.Interpersonal communication, group communication and mass communication are compared.We recruit 115 WeChat users to conduct semi-structured interviews.Traffic light model and trust cognitive onion model are used to analyze data.Calculative based trust is proven to be important in WeChat communication. Based on five types of trust, this research explores trust influencing factors in peer-to-peer interpersonal communication, group communication and mass communication. Previous research has mainly focused on trust and the corresponding antecedents in electronic commerce communication and online collaboration. This study extends the literature on trust influencing factors in social media communication. A trust traffic light model is used to illustrate the importance of keywords, drawn from interviews with 115 participants who use WeChat frequently. Salient trust factors were found and further elaborated through qualitative analysis. Furthermore, we developed a trust cognitive onion model to illustrate the interactions of trust factors.

A mixed method investigation of sharing economy driven car-hailing services: Online and offline perspectives

Abstract This exploratory research investigates factors affecting online and offline service quality with respect to a sharing economy driven car-hailing commerce. It further validates the relationships between service quality, satisfaction, and loyalty in the sharing economy driven business context. Building on relevant literature and 71 qualitative interviews, we identified information congruity, competence, and empathy as key factors in online service quality. Offline service quality factors include structural assurance and platform responsiveness. These five factors were included in a model for user loyalty investigation, which was tested on data from 294 questionnaires from Chinese mobile car-hailing service users. Attitudes towards the sharing economy were validated to moderate the relationship between service quality and loyalty. This study contributes to the theoretical development of service quality management, specifically in the context of emerging sharing economy driven car-hailing mobile markets.

A Novel Inexpensive Use of Smartphone Technology for Ecological Momentary Assessment in Middle-Aged Women

BACKGROUND Commercially available mobile and Internet technologies present a promising opportunity to feasibly conduct ecological momentary assessment (EMA). The purpose of this study was to describe a novel EMA protocol administered on middle-aged womens smartphones via text messaging and mobile Internet. METHODS Women (N = 9; mean age = 46.2 ± 8.2 y) received 35 text message prompts to a mobile survey assessing activity, self-worth, and self-efficacy over 14 days. Prompts were scheduled and surveys were administered using commercial, Internet-based programs. Prompting was tailored to each womans daily wake/sleep schedule. Women concurrently wore a wrist-worn accelerometer. Feasibility was assessed via survey completion, accelerometer wear, participant feedback, and researcher notes. RESULTS Of 315 prompted surveys, 287 responses were valid (91.1%). Average completion time was 1.52 ± 1.03 minutes. One participants activity data were excluded due to accelerometer malfunction, resulting in complete data from 8 participants (n = 252 [80.0%] valid observations). Women reported the survey was easily and quickly read/completed. However, most thought the accelerometer was inconvenient. CONCLUSIONS High completion rates and perceived usability suggest capitalizing on widely available technology and tailoring prompting schedules may optimize EMA in middle-aged women. However, researchers may need to carefully select objective monitors to maintain data validity while limiting participant burden.

Leading interdisciplinary creative teams: Challenges and solutions

1. Introduction Sven Hemlin, Carl Martin Allwood, Ben R. Martin, and Michael D. Mumford Part 1: Theoretical Section 2. Leading Scientists and Engineers: Cognition in a Socio-Technical Context Michael D. Mumford, David Peterson, and Isaac Robledo 3. What Connects Leadership and Creativity? The Mechanisms through Which Leaders May Influence Follower and Team Creativity Leif Denti and Sven Hemlin 4. Leadership, Innovation, and Technology: The Evolution of the Creative Process Samuel T. Hunter, Nicole Ginther, and Joshua Fairchild Part 2: Empirical Section 5. Academic Leadership of High-Performing Research Groups Maaike Verbree, Inge van der Weijden, and Peter van den Besselaar 6. Generation and Life Cycle Effects on Academic Leadership Maaike Verbree, Inge van der Weijden, and Peter van den Besselaar 7. Time to Create: Pathways to Earlier and Later Creative Discoveries in Noble Prize Winners Dawn L. Eubanks, Michael E. Palanski, Juani Swart, Michelle Hammond, and Joy Oguntebi Part 3: Implications Section 8. Succession Planning for Scientific Positions: Identifying, Developing, and Retaining Leaders for Innovation Ginamarie S. Ligon, Kate T. Dembroski, Robyn C. Mapp, Gamesa Zongrone, and Bianca M. Zongrone 9. Leading Interdisciplinary Creative Teams: Challenges and Solutions Roni Reiter-Palmon, Triparna de Vreede, and Gert-Jan de Vreede 10. Leadership and Followership in Science and Technology Michael E. Gorman 11. Creative Leadership: Meaning and Value for Science, Technology, and Innovation Gerard Puccio, Marie Mance, and Jeffery Zaco-Smith 12. Conclusions Sven Hemlin, Carl Martin Allwood, Ben R. Martin, and Michael D. Mumford

Convergence on Self - Generated vs. Crowdsourced Ideas in Crisis Response: Comparing Social Exchange Processes and Satisfaction with Process

Social media allow crowds to generate many ideas to swiftly respond to events like crises, public policy discourse, or online town hall meetings. This allows organizations and governments to harness the innovative power of the crowd. As part of this setting, teams that process crowd ideas must engage in social exchange processes to converge on a few promising ideas. Traditionally, teams work on self-generated ideas. However, in a crowdsourcing scenario, such as public participation in crisis response, teams may have to process crowd-generated ideas. To better understand this new practice, it is important to investigate how converging on crowdsourced ideas affects the social exchange processes of teams and resulting outcomes. We conducted a laboratory experiment in which small teams working in a crisis response setting converged on self-generated or crowdsourced ideas in an emergency response context. Our findings suggest that teams converging on selfgenerated ideas have better social exchange processes in terms of dominance and coordination. We found support that evaluation and coordination positively affect team member satisfaction under both experimental conditions. Implications for research and practice are discussed.

A Definition of Community Crowdsourcing Engagement and Application

Crowdsourcing refers to the use of technologies to gather the collective effort and wisdom from an undefined group of online users for organizational innovation and/or problem solving. A critical challenge for crowdsourcing users and providers is to engage online participants to make sustained contributions. This research in progress paper proposes a behavioural perspective on the definition and measurement of participant engagement in community crowdsourcing, a crowdsourcing model where all participants can see and react to everyone else ideas. In our research, we propose to conceive participant engagement as a set of engaging behaviours and evaluate it through the magnitude, temporal intensity, diversity, and recency of these behaviours. We illustrate the construct operationalization by the Participant Engagement Index (PEI) that quantifies engaging behaviours in the context of MindMixer, a community crowdsourcing service provider. We further provide an initial illustration of the PEI’s utility through the analysis of field project data from MindMixer. We expect that our study will provide guidance for future research into existing and new practices to study and improve the active and sustained participation of crowds in open collaboration forums.

A content engagement score for online learning platforms

Engagement on online learning platforms is essential for user retention, learning, and performance. However, there is a paucity of research addressing latent engagement measurement using user activities. In this work in progress paper, we present a novel engagement score consisting of three sub-dimensions - cognitive engagement, emotional engagement, and behavioral engagement using a comprehensive set of user activities. We plan to evaluate our score on a large scale online learning platform and compare our score with measurements from a user survey-based engagement scale from the literature.

The Choice Is Yours: The Role of Cognitive Processes for IT-Supported Idea Selection

The selection of good ideas out of hundreds or even thousands has proven to be the next big challenge for organizations that conduct open idea contests for innovation. Cognitive load and attention loss hinder crowds to effectively run their idea selection process. Facilitation techniques for the reduction and clarification of ideas could help with such problems, but have not yet been researched in crowd settings that are prevalent in idea contests. This research-in-progress paper aims to contribute to this research gap by investigating IT-supported selection techniques that differ in terms of selection direction and selection type. A laboratory experiment using eye-tracking will investigate variations in selection type and selection direction. Moreover, the experiment will test the effects on the decision-making process and the number and quality of ideas in a filtered set. Findings will provide explanations why certain mechanisms work for idea selection. Potential implications for theory and practice are discussed.