Partial least squares (PLS) path modeling is increasingly being promoted as a technique of choice for various analysis scenarios, despite the serious shortcomings of the method. The current lack of methodological justification for PLS prompted the editors of this journal to declare that research using this technique is likely to be deck-rejected (Guide and Ketokivi, 2015).
Emerging artificial intelligence (AI) capabilities are ushering in significant changes in how enterprises operate – and raising a host of questions for organizations. In this Kenan Insight, we explore how changing the organizational mindset to treat AI as an “employee” may pave the way to fully reaping the benefits of AI systems.
Join the Kenan Institute on Nov. 30 as we partner with Infinia ML to host the Machine Learning Symposium at UNC-Chapel Hill’s campus. This event will bring together academic, policy and business leaders to connect the possibilities of cutting-edge research with the realities of practical implementation in enterprise.
Join us to hear Dr. Daniel J. Egger present his findings from his work in the Quantum Technologies group at IBM Research in Zurich. His research focusses on the control of quantum computers and on the practical applications of quantum algorithms in finance.
We consider the allocation of inventory to stores in a “merchandise test,” whereby a fashion retailer deploys a new product to stores in limited quantities in order to learn about demand prior to the main selling season. Our problem formulation includes practical considerations like fixed costs and multiperiod inventory considerations but is challenging to analyze directly. Instead, we take a bounding approach that isolates the novel aspect of our problem: the impact of test inventory allocation on demand learning.
In this interactive virtual workshop, learn how news gets made and how you can evaluate the credibility of news you find on the web. These practical skills will help you become news literate in your professional and personal lives.
Purpose is the corporate buzzword of today, with politicians, the public and even shareholders calling on businesses to serve wider society. But purpose is also controversial, because companies have a responsibility to deliver returns to investors. Is there a trade-off between purpose and profit, or is it possible for companies to achieve both? The Kenan Institute of Private Enterprise hosted a virtual talk featuring London Business School Finance Professor Alex Edmans, who critically examined the case for purposeful business using rigorous evidence and real-life examples to show what works – and, importantly, what doesn’t. He discussed practical ways for businesses of all sizes to put purpose into practice, how investors and citizens can play their part, and how we can distinguish businesses that are truly purposeful from those that are greenwashing.
This study examines the antecedents and consequences of knowledge sharing and monitoring based governance strategies on emissions reduction. We theorize, and empirically test, the impact of supply base diversity in industry and geographic locations on the governance strategy choices. We find that sector and regional diversity both have a significant impact on emissions reduction strategies, yet their direct and interactive impacts are different. Regarding consequences, we find that engaging suppliers is associated with GHG emissions reduction for both buyers and suppliers.
Many providers of defined-contribution investment plans, such as 401(k) plans, have advocated for broader access to private investments. In this Kenan Insight, we examine the operating, regulatory and legal constraints involved in allowing that access, and explore what, if anything, retail investors are likely to gain from investing in private funds.
In the U.S. automobile industry, manufacturers distribute products through dealers and rental agencies. To mediate direct competition between the two intermediaries, manufacturers adopted buyback programs to repurchase used rental cars from rental agencies and redistribute them through dealers.
Much is known about the importance of learning and some of the distinct learning processes that organizations use (e.g., trial-and-error learning, vicarious learning, experimental learning, and improvisational learning). Yet surprisingly little is known about whether these processes combine over time in ordered ways, because most research on learning explores one particular process. Using theory elaboration and theory-building methods and data on the accumulated country entries of entrepreneurial firms, we address this gap. Our core contribution is an emergent theoretical framework that develops the concept of learning sequences. We find that learning sequences exist and are influenced by initial conditions.
The Strategic Management Journal encourages studies using qualitative empirical methods that investigate important research questions and phenomena in order to generate new insights. We believe that qualitative research often provides a means of identifying generalizable patterns concerning important questions in the field of strategic management.
The Hawthorne Effect is a prevalent observer effect that causes behavioral changes among participants of epidemiological studies or infection control interventions. The purpose of the review is to describe the origins of the Hawthorne Effect, to understand the term in relation to current scientific literature, to describe characteristics of the Hawthorne effect, and to discuss methods to quantify and overcome limitations associated with the Hawthorne Effect.
This study provides general methods to measure and characterize the welfare costs of long-run consumption uncertainty with Epstein and Zin (1989) preferences. I find that long-run uncertainty can create significant welfare costs even when risk aversion is moderate and the short-run consumption volatility low.
Negotiation role-playing simulations are among the most effective and widely used methods for teaching and conducting research on negotiations. Teachers and researchers can either license a published, “off-the-shelf” simulation or write their own custom “bespoke” simulation.
We introduce easy to implement regression-based methods for predicting quarterly real economic activity that use daily financial data. Our analysis is designed to elucidate the value of daily information and provide real-time forecast updates of the current (nowcasting) and future quarters.
How long do nascent industries take to become commercially viable? This paper applies historical methods to the two contemporaneous cases of emergence of the airlines and insulin industry in the early 1900s.
UNC Kenan-Flagler Business School Professor Camelia Kuhnen is an expert in corporate finance, behavioral finance and neuroeconomics, the application of neuroscience tools and methods to economic research. As many question whether a recession is on the way, she answers some questions about how the most notable consumer confidence surveys differ and whether Americans are prone to economic gloominess.
This paper surveys the recent advances in machine learning method for economic forecasting. The survey covers the following topics: nowcasting, textual data, panel and tensor data, high-dimensional Granger causality tests, time series cross-validation, classification with economic losses.
The efficiency of price discovery in the REIT market is an issue of enduring interest. Unfortunately, existing studies focus on REIT index data, and the general equity efficiency literature that uses individual assets typically excludes this sector.