Matching Items (11)

Evaluating New Trends in Raising Capital

Description

In the modern digital age, new methods of raising capital for entrepreneurs are being explored and developed at a rapid rate. This is in part due to new legislation aimed

In the modern digital age, new methods of raising capital for entrepreneurs are being explored and developed at a rapid rate. This is in part due to new legislation aimed at democratizing the funding process for startup-sized businesses, and also due to the growing mistrust in the big banks following the recent financial crisis of 2008. Today, many entrepreneurs are turning to the Internet and crowdsourcing in order to raise the funds they need to get their business ideas off the ground. This trend is more commonly known as crowdfunding. Crowdfunding is not as narrow of an industry as some may think. It goes much deeper than just the commonly known platforms such as Kickstarter or Indiegogo. There are four different crowdfunding methods that exist today, as well as hundreds of websites known as crowdfunding platforms created in order to facilitate these methods as a third party intermediary. My thesis aims to research, break down, study, and compare the various methods of crowdfunding. In addition, I explore the modern uses of the more traditional methods of raising capital for entrepreneurs such as angel investors, venture capital, bank/Small Business Association loans, and bootstrapping. This research includes both primary and secondary research. For my primary research, I interviewed three subject matter experts on the capital markets, and conducted two case studies regarding crowdfunding campaigns. In my secondary research, I used credible published studies, blogs and articles with expert testimonials, and other trustworthy resources such as encyclopedias and professional reports. In the end, I compare and contrast the various methods of raising capital explored throughout the paper, and provide my recommendations regarding each method for entrepreneurs interested in raising funds for their next venture. We live in an exciting time, and there are a lot of interesting new developments emerging as the capital markets continue to integrate with the modern digital age. I hope this thesis will help entrepreneurs, investors, and anyone else who may have interest in the modern capital markets or fundraising develop a better understanding of new trends in raising capital today.

Contributors

Agent

Created

Date Created
  • 2015-12

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Individual vs. Collaborative Crowdsourcing in HCI Design

Description

Crowdsourcing has become a popular method for collecting information from a large group of people at a low cost. This thesis looks at whether crowdsourcing is viable to collect data

Crowdsourcing has become a popular method for collecting information from a large group of people at a low cost. This thesis looks at whether crowdsourcing is viable to collect data for Human Computer Interaction research and comparing collaborative crowdsourcing with individual crowdsourcing. It was hypothesized that collaborative crowdsourcing would provide higher quality results than individual crowdsourcing due to intrinsic motivation. The research draws upon the use of three things: top 10 usability problems, heuristic evaluation and WAMMI survey to measure the two groups. The two groups used these tools to analyze the website: Phoenix.Craigslist.com. The results were compared against each other and against a heuristic evaluation score given by an HCI researcher to determine their accuracy. The results of the experiment failed to confirm this hypothesis. In the end, both groups provided accurate results and were only marginally different from each other.

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Agent

Created

Date Created
  • 2018-05

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Input-Elicitation Methods for Crowdsourced Human Computation

Description

Collecting accurate collective decisions via crowdsourcing
is challenging due to cognitive biases, varying
worker expertise, and varying subjective scales. This
work investigates new ways to determine collective decisions
by prompting

Collecting accurate collective decisions via crowdsourcing
is challenging due to cognitive biases, varying
worker expertise, and varying subjective scales. This
work investigates new ways to determine collective decisions
by prompting users to provide input in multiple
formats. A crowdsourced task is created that aims
to determine ground-truth by collecting information in
two different ways: rankings and numerical estimates.
Results indicate that accurate collective decisions can
be achieved with less people when ordinal and cardinal
information is collected and aggregated together
using consensus-based, multimodal models. We also
show that presenting users with larger problems produces
more valuable ordinal information, and is a more
efficient way to collect an aggregate ranking. As a result,
we suggest input-elicitation to be more widely considered
for future work in crowdsourcing and incorporated
into future platforms to improve accuracy and efficiency.

Contributors

Agent

Created

Date Created
  • 2020-05

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An Explanation of Crowdfunding and its Exciting Future

Description

This paper intends to inform the reader about the current state of crowdfunding, also known as crowdsourced funding, as of early May 2014. Crowdfunding has proven to be an interesting

This paper intends to inform the reader about the current state of crowdfunding, also known as crowdsourced funding, as of early May 2014. Crowdfunding has proven to be an interesting alternate to other more common financing vehicles with its ability to unite people over common ideas and projects without requiring the contribution of large amounts of capital. Further, the changing legal landscape invites a new era of deregulation that makes crowdfunding easier than ever before. This paper contains explanations of the different types of crowdfunding, platforms (websites), and the international landscape particularly of the US and Europe as well as statistics regarding the predicted future growth of the industry.

Contributors

Agent

Created

Date Created
  • 2014-05

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REAL-TIME AND CROWD SOURCING BASEBALL STATISTICS IN A MOBILE APPLICATION

Description

The area of real-time baseball statistics presents several challenges that can be addressed using mobile devices. In order to accurately record real-time statistics, it is necessary to present the user

The area of real-time baseball statistics presents several challenges that can be addressed using mobile devices. In order to accurately record real-time statistics, it is necessary to present the user with a concise interface that can be used to quickly record the necessary data during in-game events. In this project, we use a mobile application to address this by separating out the required input into pre-game and in-game inputs. We also explore the use of a mobile application to leverage crowd sourcing techniques, which address the challenge of accuracy and precision in subjective real-time statistics.

Contributors

Agent

Created

Date Created
  • 2013-05

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A Running Start: A Crowd-Sourced Database of Due Diligence to Invoke Section 108

Description

Explains the urgent need for libraries to engage in preservation of irreplaceable content on VHS and other obsolete video formats in their collections, and presents a database of titles for

Explains the urgent need for libraries to engage in preservation of irreplaceable content on VHS and other obsolete video formats in their collections, and presents a database of titles for which due diligence as required by Section 108 of US Copyright has already been completed.

Contributors

Agent

Created

Date Created
  • 2016-10-21

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Attention harvesting for knowledge production

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

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.

Contributors

Agent

Created

Date Created
  • 2019

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Understanding and Leveraging Crowd Development in Crowdsourcing

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

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.

Contributors

Agent

Created

Date Created
  • 2017

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A Simplified Pavement Condition Assessment and its Integration to a Pavement Management System

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

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.

Contributors

Agent

Created

Date Created
  • 2018