Significance of Task Significance in Online Marketplaces for Work

2022 | HICSS | Citations: 0

Authors: Ren, Yuqing; Curley, Shawn

Abstract: Online marketplaces for work like Amazon Mechanical Turk facilitate the sourcing ... Expand

Abstract: Online marketplaces for work like Amazon Mechanical Turk facilitate the sourcing of low expertise tasks in a fast and cost effective way. In this study, we explore the impact of task significance on work quality by informing workers of the purpose of the task and who benefits from it. Results from a laboratory experiment and a field experiment showed that perceived task significance improved work quality, but only for participants who recalled the purpose statement. In contrast, increasing monetary payment by 50% had no impact on work quality. A majority of participants who received the purpose statement were not able to recall it. Further analysis showed worker attributes such as English ability and personality traits influenced the likelihood of recall whereas rich media format had no effects. Overall, our work highlights the promise of task significance as a way to motivate online workers and the challenge of promoting task significance online. Collapse

Topics: intrinsic motivation personality Wikipedia electronic market ebook

Methods: ANOVA parametric test survey experiment data transformation

Theories: big five model

HEALTHCARE IN THE ERA OF DIGITAL TWINS: TOWARDS A DOMAIN-SPECIFIC TAXONOMY

2022 | European Conference On Information Systems | Citations: 0

Authors: Strobel, Gero; Möller, Frederik; Valk, Hendrik van der

Abstract: The pursuit of physical and mental integrity is a fundamental instinct that has ... Expand

Abstract: The pursuit of physical and mental integrity is a fundamental instinct that has accompanied humankind since the dawn of time. Based on the digitalization modern medicine nowadays no longer has only access to self-collected information, but to information from almost all areas of the patients' lives, which makes it possible to create a digital representation of them. This digital twin opens completely new and until now unthinkable possibilities, not only in the field of monitoring and prevention, moreover it is the key to personalized medicine. However, unlike other domains, the healthcare sector lacks a structured approach to exploit this paradigm. Against this background, based on a systematic literature review and the methodological approach of Nickerson et al. (2013), the paper presents the essential dimension as well as characteristics of digital twins healthcare applications as a taxonomy that has been evaluated against 100 healthcare applications. Collapse

Topics: digital twin health information system production management smart wearable device database system

Methods: structured literature research literature sample simulation cluster analysis design methodology

Interactive Topic Search System Based on Topic Cluster Technology

2021 | Information Systems Frontiers | Citations: 0

Authors: Chen, Lin-Chih

Abstract: In this paper, we develop an interactive hierarchical topic search system. In ou ... Expand

Abstract: In this paper, we develop an interactive hierarchical topic search system. In our system, the generation of topic names is mainly based on the N-gram statistical language model. The construction of hierarchical tree relationships between topics is mainly based on the concept of mathematical sets. In this study, the concept of mathematical sets not only helps the system to construct a topic hierarchy tree quickly, but also allows different users to use different binary operations to generate different interactive search results. In general, this study has the following three advantages. First, the generated topic names are presented in a hierarchical form rather than a flat form. Secondly, the interactive search for this study was achieved by non-stored user search and click history. Therefore, our approach can avoid personal privacy and large storage space issues. Finally, the concept of mathematical sets not only allows us to generate topic trees in linear time, but also allows users to run all possible binary operations to meet various interactive search needs. Collapse

Topics: Google+ search engine privacy source code blog

Methods: experiment computational algorithm language model cluster analysis survey

Using Collaboration Engineering to Mitigate Low Participation, Distraction, and Learning Inefficiency to Support Collaborative Learning in Industry

2021 | Group Decision and Negotiation | Citations: 0

Authors: Cheng, Xusen; Fu, Shixuan; de Vreede, Gert-Jan; Li, Yuanyuan

Abstract: Computer-supported collaborative learning (CSCL) is widely adopted in industry l ... Expand

Abstract: Computer-supported collaborative learning (CSCL) is widely adopted in industry learning, but it still faces challenges, including low participation, distraction, and learning inefficiency. In our study, we follow the design science research method to develop artifacts (a process and discussion platform) to address these CSCL challenges. Collaboration engineering was used as our design theory. A Discussion Platform was designed as a tool to help non-expert practitioner instruct collaborative learning process. We carried out evaluations on the two designed artifacts through 81 managers working in various industries through a mixed-method approach, including survey and qualitative interviews. We find that our designed artifacts receive high satisfaction in industry CSCL and reduce problems of low participation, distraction, and learning inefficiency. We identified several factors that contribute to the problem solving of low participation, distraction and inefficiency in industry CSCL, including usability, expression affordance, process guidance, goal clarity, flexibility affordance, thinkLet instruction, and flow experiences. Collapse

Topics: usability anonymity business process design affordance systems design

Methods: design artifact survey qualitative interview descriptive statistic personal interview

Theories: theory of affordance

A Strategic Group Analysis of Competitor Behavior in Search Advertising

2021 | Journal of the Association for Information Systems | Citations: 0

Authors: Nie, Cheng; Zheng, Zhiqiang (Eric); Sarkar, Sumit

Abstract: Firms compete intensely in sponsored search. Their bidding strategies hinge on ... Expand

Abstract: Firms compete intensely in sponsored search. Their bidding strategies hinge on understanding who competes with whom, how they compete, and how consumers react to competing advertisements. In this context, we investigate how firm competition impacts consumers' click-through behaviors in search advertising from a strategic group perspective. Using search results from Google and consumers' clickstream data, we found strong negative externality for competitors within the same strategic group relative to competitors across strategic groups: firms reap fewer click-throughs when an advertisement of another firm from the same strategic group is also displayed in search results, relative to when other displayed advertisers are not from the same group. This indicates that when competitors from the same strategic group are likely to appear in the results of a sponsored search auction, the focal firm would be better off avoiding head-to-head competition in the auction. However, we did not find empirical evidence of such firm behaviors, suggesting myopia or the inability of firms to avoid such competition. We also show that when multiple firms from the same strategic group appear in search results, the closer the focal firm is located to such competing firms, the more click-throughs the firm accrues. This suggests that firms should stay close to their within-group competitors when they compete in the same search auction. Further, our empirical results indicate that firms are indeed doing so. Using another set of data from Google AdWords reports, we show that our findings are also robust to multi-keyword bidding scenarios. These findings represent the first attempt to understand the impact of strategic groups in search advertising and provide interesting implications for advertisers and search engines. Collapse

Topics: search engine search engine marketing Google+ database system iPad

Methods: LexisNexis regression analysis method experiment cluster analysis longitudinal research

More Is Not Necessarily Better: An Absorptive Capacity Perspective on Network Effects in Open Source Software Development Communities

2020 | Management Information Systems Quarterly | Citations: 0

Authors: Tanya (Ya) Tang; Eric (Er) Fang; Qualls, William J.

Abstract: Previous research has predominantly taken a social network perspective suggestin ... Expand

Abstract: Previous research has predominantly taken a social network perspective suggesting that building more network connections or becoming deeply embedded in a network provides a better position to access network knowledge in open source software communities.This perspective implicitly assumes that accessed network knowledge automatically gets absorbed and transferred to projects, so that building more and deeper network connections is beneficial: Drawing from an absorptive capacity perspective, this research challenges such conventional wisdom, arguing instead that the benefits depend on a project’s absorptive capacity. Network connections provide access to external knowledge in the community; the absorption and transfer of this new knowledge require appropriate internal knowledge and developer roles. With longitudinal data collected from 4,518 open source software development projects hosted at SourceForge, the authors show that knowledge breadth (depth) helps with the absorption of external knowledge achieved from network depth (breadth), but it inhibits the absorption of external knowledge obtained from network breadth (depth). Further, developer roles (e.g., bridge members, role diversity) can mitigate the negative consequences of suboptimal combinations and facilitate effective transfers of absorbed external knowledge across and within projects. These findings provide important theoretical and managerial implications formanaging network connections, knowledge, and developer roles in open source software communities. Collapse

Topics: knowledge creation absorptive capacity knowledge sharing network effect social network

Methods: longitudinal research robustness check simulation descriptive statistic ordinary least square

Theories: absorptive capacity theory

A method for Smart Idea Allocation in crowd-based idea selection

2019 | Decision Support Systems | Citations: 0

Authors: Banken, Victoria; Ilmer, Quirin; Seeber, Isabella; Haeussler, Stefan

Abstract: When evaluating ideas, raters can quickly experience cognitive overload that mig ... Expand

Abstract: When evaluating ideas, raters can quickly experience cognitive overload that might result in poor selection performance. Contest managers have an interest in designing idea evaluation tasks that reduce the expected cognitive load of raters. However, research on how managers can meaningfully allocate ideas to raters to manage cognitive load is limited. Moreover, it is unclear how decision support (systems) should be designed in order to help managers to effectively allocate ideas. This paper addresses this challenge and suggests nine design principles and an approach for Smart Idea Allocation (SIA) as a design artifact, which chunks ideas into small subsets, utilizes cognitive biases, and fairly distributes expected cognitive load among raters. We evaluated the SIA approach on a sample of 525 ideas and compared its performance with a random allocation. Our findings suggest that SIA can utilize potential cognitive biases (salience, herding, and order and anchoring bias) more successfully than a random allocation would, distributes the expected cognitive load more fairly among raters, and requires fewer raters for the evaluation task than a random allocation approach. These findings have implications for research on idea selection and are useful for managers of innovation contests. Collapse

Topics: innovation management decision support crowdsourcing mobile application virtual reality

Methods: optimization model design principle design artifact mathematical model design science

Learning Evolution: A proposal of Serious Game that automatically corrects dictation

2019 | Americas Conference on Information Systems | Citations: 0

Authors: Bououd, Ikram; Fafi, Rania

Abstract: The remarkable use of serious games has gradually pushed them to be present in ... Expand

Abstract: The remarkable use of serious games has gradually pushed them to be present in every single domain, notably in language learning, as new generations are no longer motivated to use traditional learning tools. The development of language learning beckons for more attractive educational tools such as educational games. This paper proposes an interactive 3D game that automatically customizes corrections, provided to a multitude of various types of dictational errors and consequently assesses the learner. Such a game requires high graphical level and natural language processing. It is based on the connection between Unity3D platform and NooJ (Natural language processing) platform. The learning process of the game is based on Kolb's experiential learning theory. Collapse

Topics: Java Python video game Perl

Methods: natural language processing literature study NLTK experiment design science

Theories: theory of language learning theory experiential learning theory

Reluctant Disclosure and Transparency: Evidence from Environmental Disclosures

2019 | Organization Science | Citations: 2

Authors: Fabrizio, Kira R.; Kim, Eun-Hee

Abstract: Strategic management research increasingly examines firms’ strategies for corpor ... Expand

Abstract: Strategic management research increasingly examines firms’ strategies for corporate environmental and social disclosures. There are benefits to being perceived as having superior environmental performance, but firms face increasing pressure to provide more complete disclosures, potentially exposing information that will be viewed negatively by external stakeholders. We examine linguistic obfuscation as a means to balance this tension. In particular, we argue that firms may intentionally make their disclosures more complex and harder to understand, thereby blurring the negative content and increasing information processing costs of the recipient. In the context in which an information intermediary actively collects information from firms and evaluates them, we find that firms with unfavorable news to disclose use linguistic obfuscation in information disclosure to manage the tension between the pressure for more complete disclosures and the desire to project a positive image. We further demonstrate that obfuscation lessens the negative impact of reporting negative information on environmental performance ratings given by information intermediaries. This suggests that firms can and do use linguistic tactics to influence environmental ratings. Collapse

Topics: climate change environmental sustainability data breach risk management price management

Methods: survey robustness check descriptive statistic Wald test ordinary least square

Theories: lemon market theory

Know When to Run: Recommendations in Crowdsourcing Contests

2018 | Management Information Systems Quarterly | Citations: 30

Authors: Mo, Jiahui; Sarkar, Sumit; Menon, Syam

Abstract: Crowdsourcing contests have emerged as an innovative way for firms to solve busi ... Expand

Abstract: Crowdsourcing contests have emerged as an innovative way for firms to solve business problems by acquiring ideas from participants external to the firm. As the number of participants on crowdsourcing contest platforms has increased, so has the number of tasks that are open at any time. This has made it difficult for solvers to identify tasks in which to participate. We present a framework to recommend tasks to solvers who wish to participate in crowdsourcing contests. The existence of competition among solvers is an important and unique aspect of this environment, and our framework considers the competition a solver would face in each open task. As winning a task depends on performance, we identify a theory of performance and reinforce it with theories from learning, motivation, and tournaments. This augmented theory of performance guides us to variables specific to crowdsourcing contests that could impact a solver’s winning probability. We use these variables as input into various probability prediction models adapted to our context, and make recommendations based on the probability or the expected payoff of the solver winning an open task. We validate our framework using data from a real crowdsourcing platform. The recommender system is shown to have the potential of improving the success rates of solvers across all abilities. Recommendations have to be made for open tasks and we find that the relative rankings of tasks at similar stages of their time lines remain remarkably consistent when the tasks close. Further, we show that deploying such a system should benefit not only the solvers, but also the seekers and the platform itself. Collapse

Topics: crowdsourcing recommender system personality logistics management intrinsic motivation

Methods: experiment support vector machine Bayesian network naïve bayes artificial neural network

Theories: performance theory