A Common Currency: Early U.S. Monetary Policy and the Transition to the Dollar

The transition of the U.S. money supply from the mixture of paper bills of credit, certificates, and foreign coins that circulated at various exchange rates with the British pound sterling during the colonial period to the unified dollar standard of the early national period was rapid and had far-reaching consequences. This paper documents the transition and highlights the importance of this standardization in bringing order to the nation's finances and in facilitating the accumulation and intermediation of capital. It describes how the struggle of the colonies to maintain viable substitutes for hard money set the stage for the financial leaders of the Federalist period, led by Alexander Hamilton, to settle upon the dollar, attach it to a convertible metallic base, and create a national Bank that issued notes denominated in the new monetary unit. It also presents recently-constructed estimates of the U.S. money stock for 1790-1820 and relates them to measures of the nation's early modernization.

Do Budget Deficits Raise Interest Rates? A Survey of the Empirical Literature

Do government budget deficits raise interest rates and thus “crowd out” private investment? This question has been the topic of a multitude of empirical studies, which proposed to evaluate the impact of financing government activity. We survey the theory and some empirical results. Traditional theories either support deficits having a positive or a neutral effect on interest rates. Various tests of these propositions yield diverse results, and one can find all conclusions – that deficits raise, decrease or do not effect interest rates. Also, there is little attempt to ground their assumption that rising interest rates result in a crowding out of private borrowing and investment. The problem with many of the empirical studies begins with their narrow theoretical underpinnings which are driven by assumptions of resource constraints, exogenous money supply, or government budget constraints. Alternatively, models that derive their economics from the demand side determining supply, have a transmission mechanisms missing from traditional models that may explain econometric testing incongruities. Such models take account of multi-asset markets, investment accelerators and consider the alternative causality - interest rates to budget deficits. They emphasize financial market instruments, investor behavior, and the relationship between the treasury and the central bank in determining fiscal and monetary policy. As a result, such models provide a richer understanding to the interaction between deficits and interest rates in their institutional setting.

DATA MONETIZATION CHALLENGES IN ESTABLISHED ORGANIZATIONS: A SYSTEMATIC LITERATURE REVIEW

Over the last decades, researchers and practitioners have looked at data as a valuable asset for improving business processes in organizations. However, nowadays, they see data more as a tradable asset that can be monetized. Data monetization here refers to generating revenue from selling data and data-based products and services. Despite providing opportunities for generating new revenue streams, data monetization is not without challenges, especially in established organizations. Previous research shows that an organization’s data monetization capability is constrained by its existing business model, infrastructure, and organizational culture. Although Information Systems (IS) research and practice have shown an increasing interest in data monetization, we lack a thorough understanding of its challenges. As a first step in addressing this gap, we set out to identify challenges that established organizations face in monetizing their data. To that end, we conducted a systematic literature review and identified 21 challenges reported in the extant literature. Based on their nature, we divided these challenges into five categories, including business model, legal & regulatory, security & privacy, organizational, and data management challenges. Our study has several implications for IS research and practice

Groping in the dark? Exploring customer perception of hidden actions in smart service ecosystems through the lens of agency theory

DDue to new technologies, providers of digital goods and services collect an ever-increasing amount of personal data. Although the GDPR mandates that providers must inform their customers about the handling of their data, past privacy scandals have shown that customers lack information. In this study, we adopt a qualitative-exploratory approach to develop a rich understanding of the practices about which customers are not fully informed. We rely on agency theory to understand hidden actions as an informational advantage of providers. By conducting focus groups, we identify perceptions of three key hidden actions of smart product customers in B2C service ecosystems. Building on the hidden actions, we understand the relationship between customer and provider in smart service ecosystems characterized by information asymmetries. With our research, we provide the first steps towards understanding the nature and role of hidden actions in the context of smart service ecosystems. For practitioners, we provide guidance on how to effectively reduce information asymmetries

Network Rules

Crawford compares the debate between the telcos and the online companies over broadband access regimes often called the network neutrality debate to the ongoing tussle between intellectual property maximalists and free culture advocates which are strikingly parallel sets of arguments. The maximalists claim that creativity comes from lone genuises (the romantic author) who must be given legal incentives to works but intellectual property scholars have carefully examined the incentives of their arguments and have pointed out that granting overly strong property rights to copyright holders might not be socially appropriate. Moreover, the network providers claim that they (the romantic builders) must be allowed by law to price-discriminate vis-a-vis content sources in order to be encouraged to build the network

Exploring the Boundaries of Patent Commercialization Models via Litigation

This thesis explores direct patent commercialization via patent assertion, particularly patent infringement litigation, a complex nonmarket activity whose successful undertaking requires knowledge, creativity, and financial resources, as well as a colorable infringement case. Despite these complexities, firms have increasingly employed patents as competitive tools via patent assertions, particularly in the United States. This thesis explores the business models that have been created to facilitate the direct monetization of patents. Since secrecy underpins the patent assertion strategies studied, the thesis is based on rich and enhanced secondary data. In particular, a data chaining technique has been developed to assemble relevant but disparate data into a larger coherent data set that is amenable to combination and pairing with other forms of relevant public data. This research has discovered that one particularly successful business model that employs a leveraging strategy, known as the non-practicing entity (“NPE”), has itself spawned at least two other business models, the highly capitalized “patent mass aggregator” and the “patent privateer.” The patent privateer, newly discovered in this research, is particularly interesting because it provides a way for firms to employ patents to attack competitors by forming specialized NPEs in a manner that essentially expands the boundaries of the firm. This research has also examined plaintiff firm management processes during litigations brought under leveraging and proprietary strategies, the two patent litigation strategies in which firms affirmatively initiate infringement litigations. In particular, this research investigates the commercial contexts that drive patent assertion strategies to explore the effective limits of the patent right in a litigation context. The investigation concludes that a variety of robust business models and management processes may be quite successful in extracting value from patents in the US

Estimating the relation of big data on business model innovation: a qualitative research

Gaining interdisciplinary attention across academia, the concept of Big Data also finds application in the business world. Realizing the potential of the trend, this research considers the impact of Big Data with a strategic perspective and by focusing on the following research question: How can data and data-driven decisions lead to business model innovation?Challenging the assumption that Big Data even has the potential to impact business models, this research firstly elaborates on the construct of business modelsandbusiness model patterns. Subsequently, the Big Data concept is defined, by focusing on its unstructured and fast-moving nature. Considering the broad influence Big Data might have on business models, a qualitative research design is esteemed appropriate to answer the research question: The anal yses of semi-structured interviews with experts give insights about complex relations in the field of Big Data.For this research 13 participants contributedtheir opinions on Big Data, among others, they identifycurrent methodsand illustrate data visions for the future.One of the main findings of this research is that Big Data still imposes problems on managers, most of them are of analytical, technical or cultural nature. At the same time, the agents that suffer from insufficient data analytics,are invested to generate a data strategy that will facilitate data management.This research defines that data objects must be prioritized due to their utility,by means of data valuation. Associating a monetary value with data objects helps managersto commit totheirdecisions indata management. Furthermore, this research reveals that Big Data integration improves operations at various levels. In an incremental instance,businesses can reduce costs or differentiate their product and service portfolio through Big Data integration.Furthermore, Big Data finds applications on a strategic level:This research detects that Big Data possesses the proficiency to facilitate all business model dimensions and even to create innovation. Concluding, this master thesiscontributes to the research field of Strategy&Innovationas it increases the theoretical understanding of Big Data and its integration in strategic decision making. It considers several related topics to assess the capability of data,by including the notions of data monetization and experience data. Furthermore, this thesis discloses novel case studies, which give evidence of the status quo of data integration across industries. By deriving propositions, this study serves as a valuable guideline for further research on data management and business model innovation

MOTION HANDBOOK: From Overtourism to Innovating Sustainable Solutions in the EU

Erasmus + Programme of the European Union. Project with reference: 2020-1-FI01-KA203-066543