The US Brain Research through Advancing Innovative Neurotechnologies Grand Challenge and the EU Human Brain Project Future and Emerging Technologies Flagship, though seemingly similar in many dimensions, have distinct features that have been shaped by politics and institutional systems. This article documents the history of the two projects and compares their organization and funding mechanisms.
Many business-to-business (B2B) selling situations involve outside sales (OS) representatives (reps) interfacing with customers and inside sales (IS) rep largely supporting OS reps. Put differently, OS reps are linchpins, while IS reps generally have auxiliary roles. Perhaps for this reason, the economic value of IS reps for the B2B IS-OS selling process has received little systematic investigation. The authors propose an approach that quantifies the incremental value of IS using observational data that are commonly available in organizational customer relationship management systems.
Teams often need to adapt to planned discontinuous task change or fundamental alteration of tasks, tools, and work systems. Although team adaptation theories have made substantive progress in explaining how teams can respond to change, they have not adequately considered the unique impact that discontinuous task change can have on teams. Such change can render not only collective but also individual task capabilities obsolete and necessitate a multilevel task relearning process. Drawing on the team compilation model, we suggest that adaptation to discontinuous task change is akin to team (re)development.
Physicians spend more than 5 hours a day working on Electronic Health Record (EHR) systems and more than an hour doing EHR tasks after the end of the workday. In this paper, we investigate how physicians' workflow decisions on when to perform EHR tasks affect: (1) total time on EHR and (2) time spent after work.
Health care costs in the United States make up a larger proportion of gross domestic product (GDP) than in any other developed country and continue to rise. We examine whether the use of consistent metrics in costing information systems across hospitals provides one avenue to reduce these costs. We refer to such consistency as “costing information consistency” or CIC and empirically measure it by identifying whether hospitals in a multihospital system share the same costing system vendor. Using M&A activity among vendors as an instrument for exogenous changes in hospital CIC, we find that CIC is associated with a 13.3% reduction in operating expenses, suggesting that increased cost comparability from CIC helps hospitals identify ways to reduce operating expenses by identifying clinical and administrative best practices.
Effective policymakers must balance the demands of formulating a corporate tax system that spurs economic activity while promoting a “level playing field” across firms. However, tax systems have become more complex over time, increasing firms’ difficulty in understanding and complying with tax regulations. We explore the role of corporate tax system complexity in both objectives, using an international sample and measuring tax system complexity based on the average time firms spend to comply with the country’s tax regulations. Examining both capital and labor investment, we document two key findings. First, firm-level investment is less sensitive to changes in corporate income tax rates when tax system complexity is higher, suggesting that such complexity can undermine the ability of tax policy to stimulate investment. Second, the impact of complexity on the sensitivity of investment to the tax rate varies significantly across firms, with domestic-owned, smaller, and private firms being more negatively affected by tax system complexity.
We examine how tax-induced organizational complexity (“TIOC”), which we define as the organizational complexity that would not exist in a zero-tax world, is associated with executive performance measurement. While these structures can facilitate lower tax burdens, firms need to design their performance measurement systems to encourage executives to manage the associated complexity to avoid potential negative consequences. Using firms’ subsidiary structures in tax havens and other low tax countries to measure TIOC, we document several main findings.
As federal, state and local governments struggle to reopen the economy as the COVID-19 pandemic surges onward, efforts to ensure people’s health and safety are seemingly at odds with attempts to spur economic activity. In this Kenan Insight, we explore how a data-driven approach to reopening North Carolina (and the U.S. as a whole) can help preserve both lives and livelihoods.
This chapter investigates the pricing of key contract provisions of Puerto Rican debt. In doing so, the chapter contributes to a body of research that asks the questions: do investors price contract provisions? Does the pricing of contract provisions vary with credit risk? To our knowledge, this is the first study to address these questions for the case of Puerto Rico or any municipal issuer. Puerto Rico’s unique status as a U.S. territory implies that its subsidiaries, such as municipalities, cannot file for bankruptcy under Chapter 9 of the U.S. Bankruptcy Code.
Business incubators are taking on a greater role in the development of entrepreneurial ecosystems, but debate continues over whether, how and in what situations they work. In this Kenan Insight, we explore what makes incubators successful and how communities can determine if one is right for them.
Schemas are a central concept in strategy and organization theory. Yet, despite the importance of schemas, little is known about how they emerge. Our in-depth historical analysis of how groups in the life insurance industry developed their schema for the computer from 1945-1975 addresses this gap. We identify three key processes--assimilation, deconstruction, and unitization--that collectively explain and resolve an inherent tension related to schema emergence: how to make the unfamiliar familiar but conceptually distinct. We also find that each process relates to analogical transfer, but in a more pluralistic and dynamic way than the existing literature describes. Broadly, these findings have important implications for organizational change and managerial cognition.
As AI and related technologies – such as machine learning, deep learning, natural language processing and computer vision – rapidly evolve, it's necessary to examine their limitations and ethical complexities.
The rapid growth in the adoption of mobile payments has already begun to reshape bank payment practices. Utilizing a unique data set from a leading bank in Asia that records credit card transactions of its customers before and after the launch of Alipay mobile payment, the largest mobile payment platform in the world, this study aims to understand the impact of mobile payment adoption on bank customer credit card activities and the change of this impact after the mobile payment expansion.
This paper aims to advance the use of numerical experiments to investigate issues that surround the design of cost systems. As with laboratory and field experiments, researchers must decide on the independent variables and their levels, the experimental design, and the dependent variables. Options for dependent and independent variables are ample, as are the ways in which we can model the relations among these variables.
We present a novel source of disagreement grounded in decision theory: ambiguity aversion. We show that ambiguity aversion generates endogenous disagreement between a firm's insider and outside shareholders, creating a new rationale for corporate governance systems.
This lunchtime conversation will feature sales experts Lilly Ferrick and Chris Morrison, two entrepreneurs and Scale School instructors who have each helped hundreds of entrepreneurs re-define their sales processes and create sales systems that are repeatable and scalable.
Urban Investment Strategies Center Director Jim Johnson and UNC Professor Jeanne Milliken Bonds assess the link between childcare systems and U.S. economic and social health, highlighting the way the pandemic has underscored the critical connection – especially in rural and low-income communities.
Health systems have employed online and phone-based triage tools using automated algorithms to quickly determine which COVID-19 patients may need the most attention. Primary care can also be transformed through the broad application of automated algorithms, writes researchers including Bradley Staats, faculty director of the UNC Center for the Business of Health, but this requires building automated clinical processes that are safe and effective.