Stigmergy in Open Collaboration: An Empirical Investigation Based on Wikipedia

2023 | Journal of Management Information Systems | Citations: 0

Authors: Zheng, Lei; Mai, Feng; Yan, Bei; Nickerson, Jeffrey V.

Abstract: Participants in open collaboration communities coproduce knowledge despite minim ... Expand

Abstract: Participants in open collaboration communities coproduce knowledge despite minimal explicit communication to coordinate the efforts. Studying how participants coordinate around the knowledge artifact and its impacts are critical for understanding the open knowledge production model. This study builds on the theory of stigmergy, wherein actions performed by a participant leave traces on a knowledge artifact and stimulate succeeding actions. We find that stigmergy involves two intertwined processes: collective modification and collective excitation. We propose a new measure of stigmergy based on the spatial and temporal clustering of contributions. By analyzing thousands of Wikipedia articles, we find that the degree of stigmergy is positively associated with community members' participation and the quality of the knowledge produced. This study contributes to the understanding of open collaboration by characterizing the spatial-temporal clustering of contributions and providing new insights into the relationship between stigmergy and knowledge production outcomes. These findings can help practitioners increase user engagement in knowledge production processes in order to create more sustainable open collaboration communities. Collapse

Topics: participatory design Wikipedia data quality electronic mail anonymity

Methods: design methodology cluster analysis literature sample robustness check instrumental variables estimation

How synchronous participation affects the willingness to subscribe to social live streaming services: the role of co-Interactive behavior on Twitch

2023 | European Journal of Information Systems | Citations: 0

Authors: Bründl, Simon; Matt, Christian; Hess, Thomas; Engert, Simon

Abstract: Social computing has transformed the content industry. Content providers have ch ... Expand

Abstract: Social computing has transformed the content industry. Content providers have changed from providing merely content to offering social content experiences that allow users not only to passively consume content but also to actively participate. As the latest development, social live streaming services (SLSS) have emerged that enable so-called co-interactive behaviour, i.e., the live interplay between users while co-experiencing content. Yet, it remains unclear how co-interactive behaviour affects the monetisation of social live content. Based on a data set of 868,940 users from 59 gaming channels of the freemium-based SLSS Twitch, we empirically show that co-interactive behaviour has a stronger effect on users’ willingness to subscribe (WTS) than passive and active behaviour. Since we find that a user’s reciprocated interactions also directly increase other users’ WTS, our results call for dismantling the current dichotomy of user participation and social influences in IS research. We suggest a social-experiential perspective that integrates social influences as an inherent part of users’ participation experiences. This novel interactive second-person perspective contributes to research on user engagement and value capture on social content platforms, and it allows SLSS providers to obtain a more precise picture of user value to better develop or adapt their monetisation strategies. Collapse

Topics: participatory design social influence user behavior Twitch application programming interface

Methods: design methodology propensity score matching experimental group descriptive statistic logistic regression

Theories: general systems theory

Understanding the Role of Language Style of Government Response in E-participation: Evidence from a Citizen Inquiry Forum in China

2022 | Americas Conference on Information Systems | Citations: 0

Authors: Zhou, Mingxi; Liu, Luning; Feng, Yuqiang

Abstract: In response to the "Internet + Public Service" reformation, Chinese government ... Expand

Abstract: In response to the "Internet + Public Service" reformation, Chinese government organizations increasingly use e-participation platforms to interact with citizens, making how government respond to citizens' inquiry increasingly critical in citizen participation. This study is one of the few attempts to study the effect of language style of government response on citizen participation. Based on the language expectancy theory, we hypothesize that government response using appropriate formal and emotional language will change citizen e-participation behavior. Using text data from 11,194 users in a Chinese citizen inquiry forum, we found that emotional language has the positive impact on citizens' continuous participation significantly. And both emotional language and formal language can promote citizens' participation quality. Moreover, we identified the complementary effects of two languages on e-participation. This study has implications for both researchers and practitioners. Collapse

Topics: government system intrinsic motivation participatory design Python

Methods: survival analysis logistic regression descriptive statistic hazard function regression analysis method

Theories: expectancy theory of motivation

“What can I(S) do for you?”: How technology enables service providers to elicit customers’ preferences and deliver personalized service

2020 | Information & Management | Citations: 0

Authors: Bonaretti, Dario; Bartosiak, Marcin; Lui, Tsz-Wai; Piccoli, Gabriele; Marchesani, Daniele

Abstract: This research studies the effective use of an IT-enabled Customer Service System ... Expand

Abstract: This research studies the effective use of an IT-enabled Customer Service System (CSS) in the hospitality sector. Drawing on Effective Use Theory, we study how digital representations of customers’ preferences support service providers in the service personalization process. Our model posits customers’ preferences elicitation as the antecedent of CSS’ effective use, which yields superior customer value. This representational perspective matches recent efforts to study customer value as cocreated by customers and service providers. Based on a longitudinal dataset of 118,647 hotel reservations, we explain how digital representations of customers’ preferences enable service providers to personalize service and increase customer value. Collapse

Topics: usability personalization information system use participatory design online review

Methods: design methodology longitudinal research chi squared test logistic regression archival research

Theories: representation theory service-dominant logic

PRIORITIZING AND ORGANIZING THE MODELING OF THE LONG TAIL OF BUSINESS PROCESSES

2020 | European Conference On Information Systems | Citations: 0

Authors: Fischer, Marcus; Imgrund, Florian; Janiesch, Christian

Abstract: Design activities such as process modeling always face a trade-off between qual ... Expand

Abstract: Design activities such as process modeling always face a trade-off between quality and quantity. That is, process management initiatives typically focus on modeling and managing only a few high-value processes at a time, while neglecting processes that yield potentially lower returns. Due to complexity and resource constraints, incorporating additional processes would become uneconomical. We draw upon implications from the theory of long tail economics and its application to business process management to address these shortcomings. We cooperated with a German small and medium-sized enterprise to analyze the prioritization of their processes for modeling and management to derive generalizable recommendations. In summary, we have found that companies can use a limited number of variables to prioritize their processes. As expected, the prioritized processes show a decreasing importance and feasibility to change the processes. However, processes exhibit a uniform dysfunctionality. Consequently, we recommend companies to continue to manage a handful high-value processes centrally. However, they should supplement their approach with self-regulated and distributed modeling and management for lower-valued yet dysfunctional processes to improve them continuously. Collapse

Topics: business process management decision making organizational success requirements analysis participatory design

Methods: qualitative interview survey business process modeling logistic regression design requirement

From Lurkers to Workers: Predicting Voluntary Contribution and Community Welfare

2020 | Information Systems Research | Citations: 13

Authors: Kokkodis, Marios; Lappas, Theodoros; Ransbotham, Sam

Abstract: In an online community, users can interact with fellow community members by volu ... Expand

Abstract: In an online community, users can interact with fellow community members by voluntarily contributing to existing discussion threads or by starting new threads. In practice, however, the vast majority of a community’s users (≈90%) remain inactive (lurk), simply observing contributions made by intermittent (≈9%) and heavy (≈1%) contributors. Our research examines increases and decreases of types of user engagement in online communities using hidden Markov models. These models characterize latent states of user engagement from trace user activity or lack of activity. The resulting framework then differentiates lurkers who can later become workers (i.e., engaged in the community) from those who will not. Differentiating lurkers who can be engaged from those who cannot enables managers to anticipate and proactively direct their resources toward the users who are most likely to become or remain workers (i.e., heavy contributors), thereby promoting community welfare. Analysis of 533,714 posts from an online diabetes community shows that incorporating latent user engagement variables can significantly improve the accuracy of welfare prediction models and guide managerial interventions. Application of our framework to five additional communities of various contexts demonstrates its generalizability. Collapse

Topics: online community participatory design user behavior social network pseudonymity

Methods: machine learning XGBoost deep learning logistic regression longitudinal research

Nudging users into digital service solutions

2020 | Electronic Markets | Citations: 13

Authors: Schneider, David; Klumpe, Johannes; Adam, Martin; Benlian, Alexander

Abstract: With the ubiquity and prevalence of advanced technologies in society, transactio ... Expand

Abstract: With the ubiquity and prevalence of advanced technologies in society, transactions have become increasingly digital, requiring new user identity verification mechanisms. Electronic identification (eID) enables user identity authorization in online environments. Although eID plays a central role in government initiatives worldwide to digitalize citizen transactions, eID adoption remains surprisingly low. Drawing on digital nudging theory and e-government literature, we examine how eID adoption can be increased by changing the decision environment in which users choose eID. In a controlled experiment with 161 participants, we investigate the effect of default options (eID vs. offline ID as default) and popularity signals (presence vs. absence of social proof) on users’ eID adoption behavior. Both nudges increase eID adoption, but default options are a double-edged sword as they simultaneously fuel privacy concerns towards the government, attenuating the effect of default option on eID adoption. These concerns can be mitigated by adding social proof cues. Collapse

Topics: information privacy concern government system website privacy technology adoption

Methods: experiment mediation analysis survey survey design theory development

An investigation of Social Support Exchange and Communication Patterns among Chinese on Online Discussion Forum

2020 | HICSS | Citations: 0

Authors: Wang, Xi; Tan, Tianyi; Tong, Xing; Zheng, Bowen; Zhu, Yushan

Abstract: Online Health Communities (OHCs), frequently adopted as online discussion forums ... Expand

Abstract: Online Health Communities (OHCs), frequently adopted as online discussion forums for online users to communicate on health issues, have been used worldwide. By analyzing a representative breastcancer-related OHC from mainland China—Baidu Discussion Forum, this study attempts to investigate social support exchange and communication patterns through user-generated content by data mining approaches. According to the outcomes, emotional support seeking and providing presents itself to be a more critical theme among Chinese users than other types of social support. In addition, almost half of the users on Baidu Discussion Forum have simple patterns of involvement, and a fairly small proportion of highly active Chinese users are quite influential in shaping the connections of the social support network. Meanwhile, the off-topic discussions which are not directly on health concerns are not frequently touched by Chinese people. This may impact the longevity of both users and threads, and undermine the foundation of OHCs in the long term. The findings have practical implications for researchers and health practitioners targeting on the Chinese population. Collapse

Topics: user-generated content cross cultural research participatory design user behavior peer-to-peer model

Methods: natural language processing machine learning social network analysis decision tree classification computational algorithm

A big data analytics framework for detecting user-level depression from social networks

2020 | International Journal of Information Management | Citations: 0

Authors: Yang, Xingwei; McEwen, Rhonda; Ong, Liza Robee; Zihayat, Morteza

Abstract: Depression is one of the most common mental health problems worldwide. The diagn ... Expand

Abstract: Depression is one of the most common mental health problems worldwide. The diagnosis of depression is usually done by clinicians based on mental status questionnaires and patient's self-reporting. Not only do these methods highly depend on the current mood of the patient, but also people who experience mental illness are often reluctantly seeking help. Social networks have become a popular platform for people to express their feelings and thoughts with friends and family. With the substantial amount of data in social networks, there is an opportunity to try designing novel frameworks to identify those at risk of depression. Moreover, such frameworks can provide clinicians and hospitals with deeper insights about depressive behavioral patterns, thereby improving diagnostic process. In this paper, we propose a big data analytics framework to detect depression for users of social networks. In addition to syntactic and syntax features, it focuses on pragmatic features toward modeling the intention of users. User intention represents the true motivation behind social network behaviors. Moreover, since the behaviors of user's friends in the network are believed to have an influence on the user, the framework also models the influence of friends on the user's mental states. We evaluate the performance of the proposed framework on a massive real dataset obtained from Facebook and show that the framework outperforms existing methods for diagnosing user-level depression in social networks. Collapse

Topics: social network Facebook personality social influence big data

Methods: machine learning survey computational algorithm decision tree classification random forest classification

Theories: speech act theory big five model

Value Cocreation for Service Innovation: Examining the Relationships between Service Innovativeness, Customer Participation, and Mobile App Performance

2020 | Journal of the Association for Information Systems | Citations: 0

Authors: Ye, Hua (Jonathan); Kankanhalli, Atreyi

Abstract: Service innovation is critical to firms’ competitive advantage and, thus, firms ... Expand

Abstract: Service innovation is critical to firms’ competitive advantage and, thus, firms desire to make their services increasingly innovative. However, the relationship between the innovativeness and performance of a new service is unclear. Conflicting findings and the related literature suggest that service innovativeness is multidimensional and its impact on performance could be nonlinear. However, limited research has studied these aspects, both theoretically and empirically. Furthermore, prior research has mainly considered customers as inputs to value creation, which may not capture their precise role. Drawing on service-dominant logic, we propose two dimensions of service innovativeness, namely novelty and intensity, which differentially influence the performance of a new service. We further posit that customers are part of the value cocreation process, thereby directly and indirectly affecting new service performance. The model was tested using a panel dataset of 234 mobile apps over 14 months. Results indicate important asymmetries in the impacts of novelty and intensity on mobile app performance: novelty shows a curvilinear relationship with mobile app performance whereas intensity shows a positive linear relationship. Furthermore, customer participation positively impacts mobile app performance and positively moderates the effects of intensity and novelty on mobile app performance. Collapse

Topics: mobile application innovation management business process innovation Android mobile application market

Methods: instrumental variables estimation logistic regression Granger causality statistical hypothesis test regression analysis method

Theories: service-dominant logic