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- Member of: ASU Electronic Theses and Dissertations
Description
Although many examples have demonstrated the great potential of a human crowd as an alternative supplier in creative problem-solving, empirical evidence shows that the performance of a crowd varies greatly even under similar situations. This phenomenon is defined as the performance variation puzzle in crowdsourcing. Cases suggest that crowd development influences crowd performance, but little research in crowdsourcing literature has examined the issue of crowd development.
This dissertation studies how crowd development impacts crowd performance in crowdsourcing. It first develops a double-funnel framework on crowd development. Based on structural thinking and four crowd development examples, this conceptual framework elaborates different steps of crowd development in crowdsourcing. By doing so, this dissertation partitions a crowd development process into two sub-processes that map out two empirical studies.
The first study examines the relationships between elements of event design and crowd emergence and the mechanisms underlying these relationships. This study takes a strong inference approach and tests whether tournament theory is more applicable than diffusion theory in explaining the relationships between elements of event design and crowd emergence in crowdsourcing. Results show that that neither diffusion theory nor tournament theory fully explains these relationships. This dissertation proposes a contatition (i.e., contagious competition) perspective that incorporates both elements of these two theories to get a full understanding of crowd emergence in crowdsourcing.
The second empirical study draws from innovation search literature and tournament theory to address the performance variation puzzle through analyzing crowd attributes. Results show that neither innovation search perspective nor tournament theory fully explains the relationships between crowd attributes and crowd performance. Based on the research findings, this dissertation discovers a competition-search mechanism beneath the variation of crowd performance in crowdsourcing.
This dissertation makes a few significant contributions. It maps out an emergent process for the first time in supply chain literature, discovers the mechanisms underlying the performance implication of a crowd-development process, and answers a research call on crowd engagement and utilization. Managerial implications for crowd management are also discussed.
This dissertation studies how crowd development impacts crowd performance in crowdsourcing. It first develops a double-funnel framework on crowd development. Based on structural thinking and four crowd development examples, this conceptual framework elaborates different steps of crowd development in crowdsourcing. By doing so, this dissertation partitions a crowd development process into two sub-processes that map out two empirical studies.
The first study examines the relationships between elements of event design and crowd emergence and the mechanisms underlying these relationships. This study takes a strong inference approach and tests whether tournament theory is more applicable than diffusion theory in explaining the relationships between elements of event design and crowd emergence in crowdsourcing. Results show that that neither diffusion theory nor tournament theory fully explains these relationships. This dissertation proposes a contatition (i.e., contagious competition) perspective that incorporates both elements of these two theories to get a full understanding of crowd emergence in crowdsourcing.
The second empirical study draws from innovation search literature and tournament theory to address the performance variation puzzle through analyzing crowd attributes. Results show that neither innovation search perspective nor tournament theory fully explains the relationships between crowd attributes and crowd performance. Based on the research findings, this dissertation discovers a competition-search mechanism beneath the variation of crowd performance in crowdsourcing.
This dissertation makes a few significant contributions. It maps out an emergent process for the first time in supply chain literature, discovers the mechanisms underlying the performance implication of a crowd-development process, and answers a research call on crowd engagement and utilization. Managerial implications for crowd management are also discussed.
ContributorsLiu, Zhongzhi (Author) / Kull, Thomas (Thesis advisor) / Dooley, Kevin (Committee member) / Oke, Adegoke (Committee member) / Arizona State University (Publisher)
Created2017
Description
Road networks are valuable assets that deteriorate over time and need to be preserved to an acceptable service level. Pavement management systems and pavement condition assessment have been implemented widely to routinely evaluate the condition of the road network, and to make recommendations for maintenance and rehabilitation in due time and manner. The problem with current practices is that pavement evaluation requires qualified raters to carry out manual pavement condition surveys, which can be labor intensive and time consuming. Advances in computing capabilities, image processing and sensing technologies has permitted the development of vehicles equipped with such technologies to assess pavement condition. The problem with this is that the equipment is costly, and not all agencies can afford to purchase it. Recent researchers have developed smartphone applications to address this data collection problem, but only works in a restricted set up, or calibration is recommended. This dissertation developed a simple method to continually and accurately quantify pavement condition of an entire road network by using technologies already embedded in new cars, smart phones, and by randomly collecting data from a population of road users. The method includes the development of a Ride Quality Index (RQI), and a methodology for analyzing the data from multi-factor uncertainty. It also derived a methodology to use the collected data through smartphone sensing into a pavement management system. The proposed methodology was validated with field studies, and the use of Monte Carlo method to estimate RQI from different longitudinal profiles. The study suggested RQI thresholds for different road settings, and a minimum samples required for the analysis. The implementation of this approach could help agencies to continually monitor the road network condition at a minimal cost, thus saving millions of dollars compared to traditional condition surveys. This approach also has the potential to reliably assess pavement ride quality for very large networks in matter of days.
ContributorsMedina Campillo, Jose Roberto (Author) / Kaloush, Kamil (Thesis advisor) / Underwood, Benjamin S (Thesis advisor) / Mamlouk, Michael (Committee member) / Stempihar, Jeffery (Committee member) / Arizona State University (Publisher)
Created2018
Description
Traditionally, emergency response is in large part the role and responsibility of formal organizations. Advances in information technology enable amateurs or concerned publics to play a meaningful role in emergency response. Indeed, in recent catastrophic disasters or crises such as the 2010 Haiti earthquake and the 2011 Japan earthquake and nuclear crisis, participatory online groups of the general public from both across the globe and the affected areas made significant contributions to the effective response through crowdsourcing vital information and assisting with the allocation of needed resources. Thus, a more integrative lens is needed to understand the responses of various actors to catastrophic crises or disasters by taking into account not only formal organizations with legal responsibilities, but also volunteer-based, participatory groups who actively participate in emergency response. In this dissertation, I first developed an “event-driven” lens for integrating both formal and volunteer-based, participatory emergency responses on the basis of a comprehensive literature review (chapter 1). Then I conducted a deeper analysis of one aspect of the event-driven lens: relationships between participatory online groups and formal organizations in crisis or disaster situations. Specifically, I explored organizational and technical determinants and outcomes of forming such relationships (chapter 2). As a consequence, I found out three determinants (resource dependence, shared understanding, and information technology) and two outcomes (inter-organizational alignment and the effectiveness of coordinated emergency response) of the relationship between participatory online groups and formal organizations and suggested seven hypotheses. Furthermore, I empirically tested these hypotheses, focusing on the 2015 Nepal earthquake case (chapter 3). As a result, I found empirical evidence that supports that shared understanding and information technology improve the development of the relationship between participatory online groups and formal organizations. Moreover, research findings support that the development of the relationship enhances inter-organizational coordination. Lastly, I provide implications for future research (chapter 4). This dissertation is expected to contribute to bridging the disconnect between the emergency management literature and the crisis informatics literature. The theoretical insight from inter-organizational relations (IOR) theory provides another contribution.
ContributorsPark, Chul Hyun (Author) / Johnston, Erik W., 1977- (Thesis advisor) / Schugurensky, Daniel, 1958- (Committee member) / Williams, Linda (Committee member) / Kapucu, Naim (Committee member) / Arizona State University (Publisher)
Created2016
Description
This dissertation seeks to understand and study the process of attention harvesting and knowledge production on typical online Q&A communities. Goals of this study include quantifying the attention harvesting and online knowledge, damping the effect of competition for attention on knowledge production, and examining the diversity of user behaviors on question answering. Project 1 starts with a simplistic discrete time model on a scale-free network and provides the method to measure the attention harvested. Further, project 1 highlights the effect of distractions on harvesting productive attention and in the end concludes which factors are influential and sensitive to the attention harvesting. The main finding is the critical condition to optimize the attention harvesting on the network by reducing network connection. Project 2 extends the scope of the study to quantify the value and quality of knowledge, focusing on the question answering dynamics. This part of research models how attention was distributed under typical answering strategies on a virtual online Q&A community. The final result provides an approach to measure the efficiency of attention transferred into value production and observes the contribution of different scenarios under various computed metrics. Project 3 is an advanced study on the foundation of the virtual question answering community from project 2. With highlights of different user behavioral preferences, algorithm stochastically simulates individual decisions and behavior. Results from sensitivity analysis on different mixtures of user groups gives insight of nonlinear dynamics for the objectives of success. Simulation finding shows reputation rewarding mechanism on Stack Overflow shapes the crowd mixture of behavior to be successful. In addition, project proposed an attention allocation scenario of question answering to improve the success metrics when coupling with a particular selection strategy.
ContributorsYu, Fan, Ph.D (Author) / Janssen, Marcus A (Thesis advisor) / Kang, Yun (Committee member) / Castillo-Chavez, Carlos (Committee member) / Arizona State University (Publisher)
Created2019
Description
Computational social choice theory is an emerging research area that studies the computational aspects of decision-making. It continues to be relevant in modern society because many people often work as a group and make decisions in a group setting. Among multiple research topics, rank aggregation is a central problem in computational social choice theory. Oftentimes, rankings may involve a large number of alternatives, contain ties, and/or be incomplete, all of which complicate the use of robust aggregation methods. To address these challenges, firstly, this work introduces a correlation coefficient that is designed to deal with a variety of ranking formats including those containing non-strict (i.e., with-ties) and incomplete (i.e., unknown) preferences. The new measure, which can be regarded as a generalization of the seminal Kendall tau correlation coefficient, is proven to satisfy a set of metric-like axioms and to be equivalent to a recently developed ranking distance function associated with Kemeny aggregation. Secondly, this work derives an exact binary programming formulation for the generalized Kemeny rank aggregation problem---whose ranking inputs may be complete and incomplete, with and without ties. It leverages the equivalence of minimizing the Kemeny-Snell distance and maximizing the Kendall-tau correlation, to compare the newly introduced binary programming formulation to a modified version of an existing integer programming formulation associated with the Kendall-tau distance. Thirdly, this work introduces a new social choice property for decomposing large-size problems into smaller subproblems, which allows solving the problem in a distributed fashion. The new property is adequate for handling complete rankings with ties. The property is leveraged to develop a structural decomposition algorithm, through which certain large instances of the NP-hard Kemeny rank aggregation problem can be solved exactly in a practical amount of time. Lastly, this work applies these rank aggregation mechanisms to novel contexts for extracting collective wisdom in crowdsourcing tasks. Through this crowdsourcing experiment, we assess the capability of aggregation frameworks to recover underlying ground truth and the usefulness of multimodal information in overcoming anchoring effects, which shows its ability to enhance the wisdom of crowds and its practicability to the real-world problem.
ContributorsYoo, Yeawon (Author) / Escobedo, Adolfo R (Thesis advisor) / Mirchandani, Pitu B (Committee member) / Pavlic, Ted P (Committee member) / Chiou, Erin K (Committee member) / Arizona State University (Publisher)
Created2021