As described in Chernyak-Hai and Rabenu's (2018) focal article, the workplace has changed tremendously over the past few decades. These changes, undoubtedly, have affected how individuals interact and build relationships in the workplace. We live in a “networked society,” where the advances in technology and subsequent spread of communication and information have reorganized the way individuals are connected to one another (Castells, 2004; Wellman, 1999). In other words, we exist in complex networks, where underlying interconnections and interdependencies are the keys to scientific understanding. In their focal article, Chernyak-Hai and Rabenu highlight the need to adapt social exchange theories and research to incorporate the change in workplace relationships resulting from advances in technology and changes in the global market and workforce (e.g., freelancers, contract workers).

Jones and Stout (2015) have recommended that industrial and organizational (I-O) researchers and practitioners take a more nuanced perspective with respect to nepotism and cronyism—recast as social connection preference (SCP)—when relevant I-O decisions (e.g., hiring) are made on the basis of kin or affiliation considerations. Jones and Stout's (2015) arguments have challenged the reflexive view that SCP is always negative and thus the prudent approach is to restrict and, if possible, prohibit it. They call for further research to flesh out our understanding of SCP in organizations, and we suggest that one way to do that is to explicitly incorporate trust theory, that is, the components of trustworthiness, which represent antecedents of trust.

Rotolo et al. (2018) identify a number of reasons why the field of industrial and organizational (I-O) psychology is losing relevancy, including a lack of focus on frontier topics, which may be most relevant to talent management practitioners. As someone who subscribes to the benefits of the scientist–practitioner approach to talent management, there is nothing I hold more precious than a healthy partnership between the I-O psychology academic community and talent management practitioners.

We read the focal article by Britt, Shen, Sinclair, Grossman, and Klieger (2016) with special interest. About 10 years ago, we were asked to write a chapter on hardiness (Beehr & Bowling, 2005), and in doing so we had many observations about hardiness that were similar to Britt et al.’s observations about resilience. Our chapter was most closely aligned with the “capacity” concept of resilience, but we think that both the “capacity” approach and the “demonstration” approach to resilience have merit.

Aguinis et al.’s (2017) analysis of the “most frequently cited sources, articles, and authors in industrial-organizational psychology textbooks” is a commendable piece of scholarship. Certainly, they have applied themselves to an important question and articulated a meaningful set of answers. We have no doubt too that for many readers the insights and answers they provide will be informative, compelling, and even reassuring—if only because they reinforce a view of the world with which they are familiar and by which they are comforted, even if that familiarity and comfort are framed in terms of a set of knotty professional concerns (Morton, Haslam, Postmes, & Ryan, 2006).

In their debate about whether companies should keep traditional, numerical ratings of employee performance in an ever-changing world of work, Colquitt and colleagues argued that performance ratings are too hard to do correctly, while Adler and colleagues (Adler et al., 2016) countered that “‘too hard’ is no excuse for I-O psychology.” I would like to build on this by suggesting that “too hard” is not only no excuse but also a complete dismissal of the central aspect of what our science seeks to achieve.

In their comprehensive apologetic treatment of synthetic validity, Johnson et al. (2010) echo Hough (2001), advocating development of a central synthetic validation database, which would serve as a repository of validity information to support future synthetic validation efforts. They offer two potential approaches for developing such a database. The first entails the conduct of “a large-scale study in which tests are administered to and performance ratings gathered on incumbents in a large number of jobs in a variety of organizations.” The authors consider this approach to be “ideal but impractical,” largely because of the scope and cost of the data collection required and the resulting investment required by any sponsoring organization. The second entails the conduct of multiple local studies to generate empirical estimates of relationships between measures of various predictor constructs and a standardized set of job components. Johnson et al. consider this approach more practical, citing Meyer, Dalal, and Bonaccio (2009) as a benchmark example.

We are gratified by the large number of commentaries to our focal article (Dalal, Bonaccio, et al., 2010) that advocated greater integration of industrial–organizational psychology and organizational behavior (IOOB) with the field of judgment and decision making (JDM). The commentaries were uniformly constructive and civil. Our disagreements with the commentaries are mild and are limited primarily to the roles of external validity, internal validity, and laboratory experiments in IOOB. For the majority of our response, we attempt to build on the views expressed in the commentaries and to articulate some thoughts regarding the future. We structure our response according to the following themes: barriers to cross-fertilization between IOOB and JDM, areas of existing and potential JDM-to-IOOB cross-fertilization, areas of potential IOOB-to-JDM cross-fertilization, and ways to increase (and ideally institutionalize) cross-fertilization. We hope our focal article and our response to the commentaries will help to ignite exciting basic research and important practical applications associated with decision making in the workplace.