Multi-Level Issues in Social Systems: Volume 5

Francis J. Yammarino, Ph.D., is SUNY distinguished professor of Management and director and fellow of the Center for Leadership Studies at the State University of New York at Binghamton. He received his Ph.D. in Organizational Behavior (Management) from the State University of New York at Buffalo. Dr. Yammarino has extensive research experience in the areas of superior–subordinate relationships, leadership, self–other agreement processes, and multiple levels of analysis issues. He has served on the editorial review boards of seven scholarly journals, including the Academy of Management Journal, Journal of Applied Psychology, and the Leadership Quarterly. Dr. Yammarino is a fellow of the American Psychological Society and the Society for Industrial and Organizational Psychology. He is the author of 10 books and has published about 100 articles. Dr. Yammarino has served as a consultant to numerous organizations, including IBM, Textron, TRW, Lockheed Martin, Medtronic, United Way, Skills Net, and the US Army, Navy, Air Force, and Department of Education.

“Multi-Level Issues in Social Systems” is Volume 5 of Research in Multi-Level Issues, an annual series that provides an outlet for the discussion of multi-level problems and solutions across a variety of fields of study. Using a scientific debate format of a key scholarly essay followed by two commentaries and a rebuttal, we present, in this series, theoretical work, significant empirical studies, methodological developments, analytical techniques, and philosophical treatments to advance the field of multi-level studies, regardless of disciplinary perspective.

In recent years, theory and research have been increasingly devoted to understanding organizational behavior in cross-cultural and global contexts, with particular attention being paid to the appropriateness of various human resources management (HRM) practices because practices that may be effective within one cultural context may not be effective in other cultural contexts. This chapter argues that a multi-level perspective is needed to explain the interplay between HRM practices and employee responses across cultural contexts. Specifically, the multi-level framework developed in this chapter elucidates the importance of fit between HRM practices, individual values, organizational values, and societal values. Societal values play a key role in the adoption of HRM practices, and the effectiveness of these HRM practices will depend largely on “fit” or alignment with the values of the societal culture in which the organization is operating. HRM practices also shape the collective responses of employees through organizational climate at the organizational level and through psychological climate at the individual level. For positive employee attitudes and responses to emerge, the climate created by the HRM practices must be aligned with societal and individual values. Building on these notions, the strength of the societal culture in which the organization is operating serves as a mechanism that links relationships between climate, value fit, and attitudes across levels of analysis. The chapter concludes with some recommendations for future research and implications for practice.

Aumann and Ostroff proposed a very comprehensive framework that attempts to identify the antecedents, mediators, moderators, and consequences of human resource management (HRM) in cross-cultural contexts. It is an ambitious framework that spans three levels of analysis (society, organization, and individual) with mechanisms of fit occurring at both the macro- and microlevels, focuses on both structure and process, and identifies cross-level interactions. The authors considered organizational and psychological climate as the key integration between culture and employee responses, and in this process inadvertently dismissed the function of organizational culture. We propose an organizational perspective on multi-level cultural integration and discuss its implication for cross-cultural HRM, highlighting the role of organizational culture as the major focus for integration with a host country's societal culture and its local employees’ values. The analysis is enriched by considering the strength of both organizational and societal culture and the cultural distance between the home and host country of the multinational firm. We identify how our approach has both augmented and simplified Aumann and Ostroff's framework to facilitate future research.

This chapter discusses the strengths and challenges posed by the chapter by Aumann and Ostroff entitled, “Multi-Level Fit: An Integrative Framework for Understanding HRM Practices in Cross-Cultural Contexts.” In addition, this chapter proposes an alternative multi-level model of culture, which consists of structural and dynamic dimensions with culture's strength as a moderator of the top-down bottom-up dynamic processes. This model assumes that there is a fit between the value system and the HRM practices, as they represent two layers of culture – visible and less visible. Yet, the fit can be interrupted when HRM practices are transferred across cultures. The chapter further discusses when HRM practices are rejected and when they are accepted despite the misfit.

In this response, we address the thoughtful commentaries by Chen and Tsui, and Erez and highlight three overarching themes emerging from their contributions. First, we address the challenge of balancing complexity and parsimony in our model of values, HRM practices and fit in cross-cultural contexts. Second, we provide further explanations of the linkages between societal and organizational values. Third, we address the question of whether culture and climate should be treated as separate constructs in the model. In doing so, we hope to stimulate future progress in multi-level and cross-cultural perspectives of HRM and fit.

Students of organizations are beginning to recognize the importance of continuous learning in organizations, but to date the concept is not well understood, particularly in terms of how the learning of individuals is related to the learning that takes place in groups, which is related to the learning that occurs in organizations (and all other combinations). To further our understanding, we offer the idea of continuous learning in organizations from a living system's perspective. We view individuals, groups, and organizations as living systems nested in a hierarchy. We propose that living systems can learn in three ways: they can adapt, they can generate, and they can transform. Learning triggers from the environment spark learning, and this relationship is moderated by the system's readiness to learn. Readiness to learn is a function of the permeability of the system's boundaries, the system's stage of development, and the system's meta-systems perspective. Additional research questions are presented to explore learning flow between levels and to determine how the match between one system's pressure for change and another system's readiness to learn affects the emergence of adaptive, generative, and transformative learning. In addition, research questions are offered as a means to test these ideas and build grounded theory. Finally, using this model, the chapter presents three case studies and suggests diagnostic questions to analyze and facilitate continuous learning from a multi-level perspective.

There has been much discussion and exhortation regarding the need for continuous learning in organizations. We examine why this is still an unresolved issue in most organizations by identifying some of the most prevalent obstacles to continuous learning. General issues are discussed that are associated with the schematic nature of human information processing, as well as the fragile nature of the experiential learning cycle, especially as it pertains to action. We conclude with an emergent multi-level framework that is organized around personal, relational, and structural obstacles to continuous learning in organizations. Removing as many obstacles as possible to individual, team, and organization learning appears to be a promising way to begin to move organizations from the state of relative vulnerability with regard to continuous learning to one of resilience.

In this commentary, we will examine London and Sessa's (this volume) article on continuous learning in organizations from alternative researcher and practitioner perspectives. Specifically, we review its major points, examine the issues of entity selection and definitions, discuss the need for a “parts and wholes” approach, contrast alternative process models that stress the importance of time, and speculate about different user perspectives and their approaches. On balance, their article will stimulate much needed discussion and research in an important area.

In this response to Day and Tate (this volume) and Markham, Groesbeck, and Swan (this volume), we clarify the concept of continuous learning from a living system's perspective and address the evolution of adaptive, generative, and transformative learning. Further, we assert that a system's drive for homeostasis is actually a fluid, continuous learning process that may vary in the rate and direction of change. Environmental triggers, readiness for learning, and feedback provide leverage points for change and learning within and across individual, group, and organizational systems. Future research is needed to identify and study the effects of these leverage points on systems’ adaptive, generative, and transformative learning.

This study examines the effects of a family's and individual children's characteristics on the probability of having a divorce. Current research shows a clear indication of increased divorce risks if an individual's parents or siblings have experienced a divorce. Explanations include both shared family characteristics (including genetic effects) and common characteristics of the individual children involved. This study analyzes the effects of shared family background characteristics on the divorce risk of individuals. By analyzing siblings within families and including individual children's characteristics in the analysis, it is possible to separate individual-level and family-level effects.

In addition to employing a multi-level structure of individual siblings nested within families, the data cited here are censored. For all individuals, the length of the marriage and the divorce status are known, but the divorce status is interpreted differently for individuals who have or have not experienced divorce. For divorced individuals, the final divorce status is known; for individuals who have not experienced divorce, the final marriage status is unknown or censored. The proper analysis model for such data is event history (also called survival) analysis. This study therefore employs a multi-level event history model.

Our results show that there is a similarity in the divorce risks of siblings from the same family, which is not explained away by the available child and family characteristics. This finding suggests that shared genetic and social heritage play an important role in the intergenerational transmission of divorce risks.

This article highlights some of Dronkers and Hox's significant findings about family background and sibling effects on divorce. It proposes that in addition to siblings’ common family background and genetic heritage, their interaction over the life course may influence their attitudes toward marriage and divorce. The influence of sibling modeling and interaction over the life course may vary, depending on the gender and birth order of siblings.

The chapter by Dronkers and Hox presents an interesting multi-level event history analysis of divorce risks. The sibling design gives excellent opportunities for studying the similarity between brothers and sisters in the risks of divorce. Various discussion points are raised, all of which bear in some way upon the choice of predictor variables in the multi-level logistic regression. Questions are posed about the level of detail of modeling time trends; about the fact that sampling weights are a function of number of siblings; and about the inclusion in the fixed part of the model of the fraction of previously divorced siblings, which is correlated with the family-level random intercept.

In this article, we further discuss the substantive and statistical issues raised in the articles by Farrell and Snijders. We point out where we agree and disagree with the two commentators. In addition to responding to a variety of issues that were raised, we point out where we believe additional studies may be particularly fruitful. We conclude that we believe that combining multi-level analyses with event-history analysis is potentially a very useful approach for future research.

U.S. industry–university (I–U) relations around intellectual property (IP) have become increasingly contentious since the Bayh-Dole Act of 1980, while especially lucrative patents and licenses resulting from biomedical and pharmaceutical discoveries capture the headlines. Some assert that I–U relations around IP are in crisis, others suggest that no such problem exists, and still others bemoan the “increasing commercialization” of U.S. education. This chapter develops a multi-level model of I–U IP dynamics, drawing on pluralistic, multi-theory perspectives, field interviews, and secondary data. The model includes three levels: the institutional (economy) level, I–U (sector) level, and the organizational level. These levels jointly affect the immediate context of any deal. The chapter closes with a discussion of this model's implications for further research and some theoretical speculations.

Jelinek has developed a multi-level model for conceptualizing the contextual influences through which intellectual property (IP) is “understood, interpreted and made sense of” by key parties to IP “deals.” This commentary reflects upon that model through a historical examination of industry–university relationships in one case – specifically, IBM. Since the late 1920s, IBM has encouraged multifaceted relationships with universities. From the start, IBM sought relationships with academia not only because of the market potential represented by university campuses, but also because Thomas Watson Sr. viewed academic customers as potential research collaborators, a novel idea at the time that later proved instrumental in the development of the corporation's successful research enterprise. IBM's university relationships have continued to evolve over time, reflecting shifts in the corporation's business strategy, and changes in larger macroeconomic structures. The case of IBM reveals complex interactions among governmental, corporate, and academic actors and their policies at different points in time, providing support for Jelinek's multi-level approach to framing IP dynamics, and suggesting possible refinements of the model for the future.

Both Marianne Jelinek's chapter and this commentary examine the legal, economic, and policy environments for university–industry technology transfer and the management of intellectual property. To complement Jelinek's framework, this commentary offers an alternative conceptual framework that incorporates the role of individual scientists and also acknowledges repeat transactions that form relationships between university and industry partners.

This paper outlines a multi-level conceptual framework of industry–university (I–U) intellectual property (IP) relationships to understand efforts to commercialize university discoveries by considering how the parties to deals make sense of their interactions. Institutional, sectoral, and organizational levels frame interactions around any single deal, shaping participants’ sometimes divergent views. The complex dynamics of interactions between the parties and between and among levels mean that details and nuances will be vital. Commentaries by Maryann Feldman and Marietta Baba provide detailed insights on universities (Feldman) and industry (Baba) that enrich and corroborate the multi-level model. Directions for further research and policy implications in this important emerging area are suggested.

This chapter provides a new theory for organizational leadership in which an organization's leadership, authority, management, power, and environments (LAMPE) are made coherent and integrated. Organizations work best if their LAMPE is coherent, integrated, and operational. The chapter begins by introducing basic concepts, such as structures, processes, process frameworks, task–role matrices, interdependence uncertainty, and virtual-like organizational arrangements. The LAMPE theory is then built upon this base. Leadership is defined as the processes of initiating, enabling, implementing, and sustaining change in an organization. Authority is defined as the legal right to preempt the outcome of a decision or a process. Management is defined in term of its major processes. Power is the control of interdependence uncertainty. When 29 leadership practices are introduced, it is possible to link them to all five of LAMPE's constructs. A number of conclusions are derived, in the form of 36 propositions: 5 dealing with leadership, 5 focusing on leadership requirements matching, 4 relating to leadership effectiveness, 5 dealing with leadership capacity, 4 concerning the benefits of distributed leadership, and 13 linking LAMPE to the theory of the organizational hologram.

Mackenzie's LAMPE theory provides a new view of leadership that is multi-level, processual, and reflective of leadership as it actually occurs in practice. While we see this approach as representing a much needed frameshift for leadership research, we believe Mackenzie may be able to “break the frame” even farther by incorporating elements of complexity science into his thinking. We suggest how complexity science might help Mackenzie flesh out his ideas about distributed leadership, as well as consider leadership that is not only about alignment and control but also about enabling and releasing informal, interactive dynamics within the organization.

This article begins by examining the recommendations of Uhl-Bien and Marion that the LAMPE theory of organizational leadership could be enhanced and improved if it were to incorporate elements of complexity and complexity leadership theory. Their advice should be reversed: complexity leadership theory should incorporate the theory, methods, and models already tested in the construct of the LAMPE theory. The reasons for this conclusion are based on a general discussion of the conditions under which a processual theory can be tested and the testing procedure be made rigorous. According to this approach, complexity leadership theory cannot be most rigorous and the LAMPE organizational leadership theory might be.

Kerstin Aumann is a doctoral student in the social-organizational psychology program at Teachers College, Columbia University. She received her B.S. at Northwestern University, after which she spent three years working in the Change Communication Specialty Group at Burson-Marsteller, a global communications firm. Her research interests include international human resources management, cross-cultural organizational behavior, and cultural diversity.