The purpose of this rebuttal to Costanza and Finkelstein (2015) is (a) to examine the findings surrounding the new generations at work, (b) to suggest the risks of not responding to change in generations with new talent strategies, and (c) to propose a new theory about the development of a new millennial culture and how practitioners and researchers may capitalize on the promise of a more positive and joyful workplace culture. We propose to accomplish these points by (a) citing recent global findings showing that Millennials (born after 1980) are turning away from companies with cultures that were designed for 20th century workers, (b) presenting a theory on the development of an emerging millennial culture that is based on positive industrial and organizational psychology, and (c) recommending that the method of innovation design teams be used to render workplaces compatible with the emerging culture.

The focal article by Costanza and Finkelstein (2015) shed a light on the current status of generational research at work that often treats generation as an age grouping variable. Although the authors primarily focused on the applicability of research findings to the current workforce, I believe the benefits of studying and understanding generations should not be limited to this purpose. The goal of this commentary is twofold. First, I would like to revisit the concept of generation and the purposes of studying generations at work. Second, given the problems with generational research presented by Costanza and Finkelstein, I would like to propose potential actions that we can take.

Pulakos, Mueller Hanson, Arad, and Moye (2015) have stated that performance management (PM) best practices have resulted in the dissatisfaction of employees and managers with PM reviews and systems. The authors have suggested that the focus should be on driving critical PM behaviors that have been shown to increase engagement and performance. Corporate Leadership Council (2004) research demonstrated that increased engagement takes place when PM behaviors such as setting clear expectations, providing regular feedback, and helping employees develop and succeed occur. In addition, effective PM happens when employees are contributing to the process as well.

Few would dispute that the nature of work, and the workers who perform it, has evolved considerably in the 70 years since the founding of the Society for Industrial and Organizational Psychology (SIOP) as the American Psychological Association's (APA's) Division 14, focused on industrial, business, and organizational psychology. Yet, in many ways the populations sampled in industrial–organizational (I-O) psychology research have failed to keep pace with this evolution. Bergman and Jean (2016) highlight how I-O research samples underrepresent (relative to the labor market) low- or medium-skill workers, wage earners, and temporary workers, resulting in a body of science that is overly focused on salaried, professional managers and executives. Though these discrepancies in the nature of individuals’ work and employment are certainly present and problematic in organizational research, one issue that should not be overlooked is that of adequately representing nationality and culture in I-O research samples.

This response highlights the common themes across the commentaries that reflect both opportunities and barriers to the successful creation of lesbian, gay, bisexual, and transgendered supportive organizations. In addition, in the interest of comprehensiveness, we describe additional perspectives and points that were not offered in the dialogue. Finally, in line with the evidence presented in the focal paper, we urge readers to consider their own roles in advocating for equity.

Here, we expand on Landers and Behrend's (2015) discussion of the external validity of convenience samples. In particular, we note that their focal article failed to mention one important limitation of multi-organization convenience samples (e.g., MTurk samples, student samples): Multi-organization convenience samples tend to confound levels of analysis, which affects the external validity of these samples. Specifically, between-organizations phenomena (i.e., organization-level) and within-organizations phenomena (i.e., individual-level) are distinct and separable (Ostroff, 1993; Robinson, 1950). Unfortunately, multi-organization samples such as those found in MTurk or MBA student samples can confound these two sets of phenomena. The current commentary uses a levels-of-analysis framework to expand on Landers and Behrend's discussion of what external validity is, and then the commentary illustrates how the diversity of convenience samples can actually harm external validity under some common circumstances.

Adler et al. (2016) raise some controversial issues about whether performance rating systems should be eliminated or not. We strongly believe that the decision to do away with performance ratings is premature because more research needs to be done, as suggested by “the better questions” that Adler et al. listed at the end of the focal article. We propose that those questions can be extended further by testing them in other cultures and supplemented with these questions: When, how, and why do cultural values influence performance management? Given the nature of our increasingly diverse workforce in which employees with different cultural values work together within the same organization, it is crucial to identify and document the influence of culture on performance appraisal practices. In this commentary, we briefly summarize research to date on the influence of cultural values on performance management and identify some important future research directions.

For many, Penn State is synonymous with football and Coach Joe Paterno, an association that has been a source of pride for many alumni, staff, and students for years. As Alderfer's (2013) article summarizes, that overlap has now made the horrific behaviors of the former football coach Sandusky indelibly connected to Penn State. Alderfer argues that the scandal can be explained by the actions or inactions of nine Penn State groups “whose collective behavior first allowed the criminal acts to occur and then put an end to them” (p. 117).

The “big data” movement is forcing many fields to establish best practices for the collection, analysis, and application of big data, and the field of industrial–organizational (I-O) psychology is not exempt from this disruptive influence. Over the last several years, I-O scientists and practitioners have grappled with questions related to the definition, application, and interpretation of big data (e.g., Doverspike, 2013; Maurath, 2014; Morrison & Abraham, 2015; Poeppelman, Blacksmith, & Yang, 2013). The focal article by Guzzo, Fink, King, Tonidandel, and Landis (2015) continues this discussion and represents one of the first attempts to establish a formal set of recommendations for working with big data in ways that are consistent with I-O psychology's professional guidelines and ethics requirements.

The focal article (Grand et al., 2018) addresses one of the most important issues across virtually all areas of science (Goldstein, 2010): the trustworthiness and credibility of a scientific discipline. Once these attributes are lost, it is difficult to regain them within a reasonable time frame, if ever. In contrast to previous articles on this topic (e.g., Kepes & McDaniel, 2013), the authors of the focal article provide a detailed review of the stakeholders surrounding industrial and organizational (I-O) psychology, including their potential effect on the robustness and trustworthiness of our scientific discipline. In essence, the focal article describes I-O psychology's ecosystem responsible for fostering robust and credible science. The authors should be commended for their comprehensive undertaking, and we have no substantive disagreements. However, implicitly, as with most articles on this vital topic, the focal article tends to take a bottom-up approach to decision making and change. The bottom-up approach is an emergent process where the individuals involved in the day-to-day activities are primarily responsible for the decision-making process and resulting change (Kindler, 1979). Thus, changes resulting from this process are incremental and typically involve making minor adjustments to existing processes (Bartunek & Moch, 1987).