Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, 2010. / "June 2010." Cataloged from PDF version of thesis. / Includes bibliographical references. / BS Grupo is a Peruvian entrepreneurial venture begun in 2000. The company has grown relatively fast, becoming a leading training provider in Peru. The venture delivers high level and specialized training services in the the areas of mining and information technologies, and on specific topics, such as project, maintenance, and quality management. Although it has experienced relatively fast growth, BS Grupo has missed market opportunities and has delayed the deployment of strategic projects needed for its long term sustainability. The company has developed strong capabilities to identify market opportunities and to configure products to address them; however, BS Grupo has experienced major problems in the areas of people management and organizational structure. This thesis analyzes the current organizational design of BS Grupo using three lenses: strategic, political and cultural. Recommendations are made to develop a new organizational design that supports the growth plans of the venture. / by Juan Carlos Martinez Delgado. / S.M.

Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1997. / Includes bibliographical references (leaves 188-189). / by Edgardo Carlos and Alejandro Laiño. / M.S.

Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1996. / Includes bibliographical references (p. 132-133). / by Christopher D. McDaniel. / M.S.

Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1986. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND DEWEY / Bibliography: leaves 96-98. / by Rafael del Pino. / M.S.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 2008. / Includes bibliographical references (p. 288-290). / As companies compete to gain market share, increase profits and affect growth they often turn to concurrent engineering in an effort to bring new products to the market more quickly. Despite many anecdotal success stories, implementation of concurrent engineering can often prove difficult. As the pressure to bring new products to market increases, companies often compress their design iteration cycle times in an effort to develop products more quickly. In many cases, design cycles may overlap creating situations where learning opportunities (e.g. through testing) are missed and/or ignored. More perversely, compressing design iteration cycles can cause the creation of "phantom errors" and unnecessary rework as concurrent design activities iterate at different speeds. In this research, I use a system dynamics approach to develop a stylized simulation model of the design-build-test iteration cycle to explore the effects of cycle timing on learning. Specifically, I look at the frequency and timing of integration (build) test events and their effect on new product delivery time, quality, and development cost. This research adds to the existing literature in new product development, concurrent engineering, and system dynamics. Ultimately, the results serve to inform new product development project managers of the implications of design iteration timing on project performance and assist in the scheduling of integration events. / by Daniel J. McCarthy. / Ph.D.

Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. [49]-[57]). / This paper begins with the assumption that stock market development has a positive and causal relationship with long run economic growth. It thus takes the view that developing the equity market is an important policy objective for the Russian government. Through a series of interviews, data collection and a review of the literature, it is found that the Russian equity market is rather underdeveloped as measured by its liquidity, free float capitalization and industry concentration. In order to stimulate the development of the market, the paper focuses on the attraction of long term capital to sustainably increase the size and liquidity of the market and reduce volatility. A set of viable reforms are suggested to achieve this goal including: 1) the upgrade of market infrastructure primarily through the creation of a Central Settlement Depository and relaxation of prefunding requirements, 2) corporate governance improvements through a reduced government participation, increased board independence and the introduction of a minimum free float requirement and 3) Incentives for the pooling of long term domestic capital, in particular through the diversification of risk using cross-country swaps. / by Catherine F. Harwood. / S.M.

Thesis (S.M. in Management of Technology)--Massachusetts Institute of Technology, Sloan School of Management, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 122-126). / This work reviews the evolution and current state of the "Big Data" industry, and to understand the key components, challenges and opportunities of Big Data and analytics face in today business environment, this is analyzed in seven dimensions: Historical Background. The historical evolution and milestones in data management that eventually led to what we know today as Big Data. What is Big Data? Reviews the key concepts around big data, including Volume, Variety, and Velocity, and the key components of successful Big Data initiatives. Data Collection. The most important issue to consider before any big data initiative is to identify the "Business Case" or "Question" we want to answer, no "big data" initiative should be launched without clearly identify the business problem we want to tackle. Data collection strategy has to be closely defined taking in consideration the business case in question. Data Analysis. This section explores the techniques available to create value by aggregate, manipulate, analyze and visualize big data. Including predictive modeling, data mining, and statistical inference models. Data Visualization. Visualization of data is one of the most powerful and appealing techniques for data exploration. This section explores the main techniques for data visualization so that the characteristics of the data and the relationships among data items can be reported and analyzed. Impact. This section explores the potential impact and implications of big data in value creation in five domains: Insurance, Healthcare, Politics, Education and Marketing. Human Capital. This chapter explores the way big data will influence business processes and human capital, explore the role of the "Data Scientist" and analyze a potential shortage of data experts in coming years. Infrastructure and Solutions. This chapter explores the current professional services and infrastructure offering and how this industry and makes a review of vendors available in different specialties around big data. / by Alejandro Zarate Santovena. / S.M.in Management of Technology

Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, 2015. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 54-58). / "Freemium" has become a popular business model for digital and internet startups to acquire customers quickly and monetize with limited marketing resources. In this model, basic functionalities and features of the product are offered free of cost and advanced features are monetized. Typically firms rely on the size of the free user network since the conversion rate in these models is very low (2%-7%). This thesis analyzes successful business models and uses predictive analytics on a dataset from a freemium product to determine critical success factors. Empirical study is conducted on 79,033 total users and 4,217 premium subscribers of Last.fm, a Musica as a service (MaaS) product which employs the freemium pricing model, to predict the probability of a user being a subscriber. Classification and regression trees (CART) with k-fold cross validation is used to model on the training data and is validated on the test dataset to understand the influence of demographic, engagement, retention and social factors on subscribers. Five successful premium companies Linkedln, Zynga, Evernote, Spotify and DropBox are studied to understand the company background, value proposition and freemium model. The analyses was based on secondary case studies and information. The CART model designed yielded an accuracy of 74.84%, sensitivity of 67.6%, false negative rate (FNR) of 32.4% and Area under the curve (AUC) of 0.7474937. On fine-tuning the penalty matrix, FNR is reduced to 22% and sensitivity increased to 78% with an accuracy of 65.8%. The empirical study showed that age (demographic factor), playcount (engagement factor) and registration unixtime (retention) were the most significant variables in predicting outcome. Study of successful firms showed that freemium is not a one-size-fits-all strategy for internet startups. The strategy needs to be crafted specifically for each firm. Many factors go into formulating this plan including a strong product catalogue, focused customer acquisition engine, referrals, social and community features, continuous testing, data driven approach and commitment to continuous innovation. / by Pronitha Mysore Shankarananda. / S.M. in Management Research

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management, 2007. / Includes bibliographical references. / This thesis seeks to determine the critical factors that influence the adoption and effective use of technologies within the nonprofit sector. The analysis places a particular emphasis on the role of funders who finance technology adoption and intermediaries who play the role of catalysts, enablers, and educators in the implementation of and subsequent innovation with technology. Through reviewing the limited academic literature, surveying industry leaders, and performing cross-organizational and cross-regional comparisons, the thesis details policy recommendations for building ecosystems that can help create tech-savvy nonprofits. These critical success factors include a supportive community of foundations, significant diversity of nonprofit and for profit intermediaries, and involvement of senior leadership of nonprofit organizations. While intermediaries play the linchpin role in the networked system, policy recommendations are provided that specify how all actors can contribute to the construction of ecosystems that facilitate adoption, shared learning and effective use of technology in the nonprofit sector. / by Stephen P. Rockwell. / M.B.A.

Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 20-22). / After product adoption, consumers make decisions about continued use. These choices can be influenced by peer decisions in networks, but identifying causal peer influence effects is challenging. Correlations in peer behavior may be driven by correlated effects, exogenous consumer and peer characteristics, or endogenous peer effects of behavior (Manski 1993). Extending the work of Bramoullé et al. (2009), we apply proofs of peer effect identification in networks under a set of exogeneity assumptions to the panel data case. With engagement data for Yahoo Go, a mobile application, we use the network topology of application users in an instrumental variables setup to estimate usage peer effects, comparing the performance of a variety of regression models. We find analyses of this type may be especially useful for ruling out endogenous peer effects as a driver of behavior. Omitted variables (especially ones related to network homophily) and violation of the exogeneity assumptions can bias regression coefficients toward finding statistically significant peer effects. / by Daniel Ian Rock. / S.M. in Management Research