Can You Be Too Well Connected?
Ethan R. Burris, , Dawn Klinghoffer, Elizabeth McCune, and Tannaz Sattari Tabrizi; Harvard Business Review Digital Articles, ()
The benefits and pitfalls of networking have never been quantified. A team of researchers examined the meeting schedules and emails of Microsoft employees to find the employees with the most and least amount of connectedness. Well-connected employees were more engaged and more likely to speak up about issues at work. But the researchers were surprised to also find several downsides of being well-connected. Well-connected employees are less likely to engage in actions that would upset their hard-earned relationships. Furthermore, they were 16% less likely to be satisfied with their work-life balance and 20% less likely to think that their workload allowed them to achieve an acceptable work-life balance. The authors suggest several steps companies can take to guard work-life balance and encourage even networked employees to blow the whistle on problems that they see in their company.
A Project-level Analysis of Value Creation in Firms
A Project-level Analysis of Value Creation in Firms. Financial Management 49(2), 423-446.
This paper analyzes value-creation in firms at the project level. We present evidence that managers facing short-termist incentives set a lower threshold for accepting projects. Using novel data on new client and product announcements in both the U.S. and international markets, we find that the market responds less positively to a new project announcement when the firm’s managers have incentives to focus on short-term stock price performance. Furthermore, textual analysis of project announcements show that firms with short-termist CEOs use more vague and generically positive language when introducing new projects to the marketplace.
aPRIDIT Unsupervised Classification with Asymmetric Valuation of Variable Discriminatory Worth
Linda L. Golden, Patrick L. Brockett, Montserrat Guillen, and Danae Manika; Multivariate Behavior Research, 55(5) 685-703
Sometimes one needs to classify individuals into groups, but there is no available grouping information due to social desirability bias in reporting behavior like unethical or dishonest intentions or unlawful actions. Assessing hard-to-detect behaviors is useful; however it is methodologically difficult because people are unlikely to self-disclose bad actions. This paper presents an unsupervised classification methodology utilizing ordinal categorical predictor variables. It allows for classification, individual respondent ranking, and grouping without access to a dependent group indicator variable. The methodology also measures predictor variable worth (for determining target behavior group membership) at a predictor variable category-by-category level, so different variable response categories can contain different amounts of information about classification. It is asymmetric in that a “0” on a binary predictor does not have a similar impact toward signaling “membership in the target group” as a “1” has for signaling “membership in the non-target group.” The methodology is illustrated by identifying Spanish consumers filing fraudulent insurance claims. A second illustration classifies Portuguese high school student’s propensity to alcohol abuse. Results show the methodology is useful when it is difficult to get dependent variable information, and is useful for deciding which predictor variables and categorical response options are most important.
Are Online Reviews of Physicians Reliable Indicators of Clinical Outcomes? A Focus on Chronic Disease Management
Danish H. Saifee, Zhiqiang (Eric) Zheng, Indranil R. Bardhan, and Atanu Lahiri; Information Systems Research, 31(4) 1282-1300
Current trends on patient empowerment indicate that patients who play an active role in managing their health also seek and use information obtained from online reviews of physicians. However, it is far from certain whether patient-generated online reviews accurately reflect the quality of care provided by physicians, especially in the context of chronic disease care. Because chronic diseases require continuous care, monitoring, and multiple treatments over extended time periods, it can be quite hard for patients to assess the effectiveness of a particular physician accurately. Given this credence nature of chronic disease care, the research question is the following: what is the information value associated with online reviews of physicians who treat chronic disease patients? We address this issue by examining the link between online reviews of physicians and their patients’ actual clinical outcomes based on a granular admission–discharge data set. Contrary to popular belief, our study finds that there is no clear relationship between online reviews of physicians and their patients’ clinical outcomes, such as readmission risk or emergency room visits. Our findings have two major implications: (a) online reviews may not be helpful in the context of healthcare services with credence aspects; (b) because treatments of chronic diseases have more credence good characteristics when compared with surgeries or other acute care services, one should not extrapolate research on surgeries and acute care services to chronic disease care. Rather, one should acquire a better understanding of the information conveyed in online reviews regarding a physician’s ability to deliver certain clinical outcomes before drawing inferences. Our findings have important ramifications for all stakeholders including hospitals, physicians, patients, payers, and policymakers.
Branching and Anchoring: Complementary Asset Configurations in Conditions of Knightian Uncertainty
Curba Morris Lampert, Minyoung Kim, and Francisco Polidoro; Academy of Management Review, 45(4) 847-868
The role of complementary assets across the different stages of a firm’s value chain in facilitating value creation and value appropriation from technological innovation remains a key area of interest in strategy and entrepreneurship research. However, current thinking on complementary assets operates with an unstated boundary condition—that relevant assets and asset configurations are relatively well known to the innovating firm. This assumption is applicable under conditions of “risk,” wherein decision-makers can know outcomes and probabilities. It is less clear, though, how current insights apply under conditions of “Knightian uncertainty,” in which neither outcomes nor probabilities are knowable. The purpose of this paper is to advance a complementary assets theory that accounts for conditions of Knightian uncertainty, thus aligning theory with the contemporary realities surrounding innovating firms. This article highlights an important intertemporal trade-off that existing literature ignores—without accounting for Knightian uncertainty, firms may unknowingly direct complementary assets in ways that favor current value appropriation at the expense of future value creation. We discuss theoretical implications for research on the microfoundations of dynamic capabilities and opportunities for future research on complementary asset configurations across geographic boundaries and across organizations in innovation ecosystems.