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IT governance describes the decision rights and accountability framework used to ensure the alignment of IT-related activities with the organization’s strategy and objectives. Conversely, IT consumerization refers to the process whereby the changing practices and expectations of consumers influence the IT-related activities of workers and managers in organizations. We propose that IT consumerization not only challenges the foundations of IT governance but ultimately also transforms it. To explore this research problem, we utilize the punctuated equilibrium theory and a case study of IT consumerization and the transformation of IT governance in a large global bank. Our findings suggest that the widespread adoption of digital technology in everyday life leads to “everyone’s IT,” which is a new set of shared beliefs among consumers that highlights democratized access and individualized use of IT. As everyone’s IT beliefs begin to alter the IT-related activities of workers, the result is IT governance misalignments that ultimately lead to a punctuated transformation of IT governance that dismantles functional IT governance. The establishment of platform-based governance marks a new equilibrium period. Our mid-range theory contributes to the IS domain with the novel concept of everyone’s IT and a grounded explanation of IT governance transformation in the context of IT consumerization. Our theory offers a set of significant research and practical implications.

PurposeThe purpose of this study is to discover the learning mechanisms and temporal dynamics of implementing systems (Six Sigma) as it unfolds over time.Design/methodology/approachThe data come from a European engineering company that was implementing a Six Sigma-based quality management system (QMS) over a seven-year period. The analysis is based on an event-sequence reconstruction of the implementation process as it unfolded over time and discovers four different learning mechanisms that emerged: programmatic, persistent, adaptive and dialectical learning mechanisms. The research follows a process design study, where the authors study how the process unfolds over time.FindingsMuch of the literature on implementing management systems suggests that implementation follows a prescribed sequence of “turn-key” steps. However, the findings show that only 40% of all events were driven by prescribed “turn-key” generic practices, while 56% of events required constructing new practices via adaptive and dialectical learning. Moreover, the implementation process did not proceed in a linear programmatic fashion, but instead followed a punctuated equilibrium pattern, which alternated between periods of incremental change and major organizational change. The study also found that implementation required changing many complementary organizational structures and practices that were interdependent with the management system (i.e. Six Sigma). By understanding the implementation process, managers can better assess the time and effort involved, better adapt the system to their situated context and predict critical junctures where implementation could break down.Originality/valueThis research complements the few studies that have examined the process of implementing management systems. Most studies examine factors or conditions that result in implementation success (the what of implementing systems), but few examine the process of implementation and the learning that takes place during implementation (the how of implementing systems), which is a complex nonlinear process that involves different modes of learning.

Significance Paleontologists have long argued about what the fossil record call tell us about how species evolve over long periods. Simple models such as stasis and random walks have been used to explore evolutionary patterns, but these have not always adequately captured the ways in which traits change over time in fossil species. Here we find that models with complex evolutionary dynamics are often favored, especially for fossil series that sample many populations, suggesting that the underlying evolutionary reality is likely more complex than represented by simplified—though still useful—models of trait change. Previous analyses of evolutionary patterns, or modes, in fossil lineages have focused overwhelmingly on three simple models: stasis, random walks, and directional evolution. Here we use likelihood methods to fit an expanded set of evolutionary models to a large compilation of ancestor–descendant series of populations from the fossil record. In addition to the standard three models, we assess more complex models with punctuations and shifts from one evolutionary mode to another. As in previous studies, we find that stasis is common in the fossil record, as is a strict version of stasis that entails no real evolutionary changes. Incidence of directional evolution is relatively low (13%), but higher than in previous studies because our analytical approach can more sensitively detect noisy trends. Complex evolutionary models are often favored, overwhelmingly so for sequences comprising many samples. This finding is consistent with evolutionary dynamics that are, in reality, more complex than any of the models we consider. Furthermore, the timing of shifts in evolutionary dynamics varies among traits measured from the same series. Finally, we use our empirical collection of evolutionary sequences and a long and highly resolved proxy for global climate to inform simulations in which traits adaptively track temperature changes over time. When realistically calibrated, we find that this simple model can reproduce important aspects of our paleontological results. We conclude that observed paleontological patterns, including the prevalence of stasis, need not be inconsistent with adaptive evolution, even in the face of unstable physical environments.

A mathematical analysis of the evolution of a large population under the weak-mutation limit shows that such a population would spend most of the time in stasis in the vicinity of saddle points on the fitness landscape. The periods of stasis are punctuated by fast transitions, in lnNₑ/s time (Nₑ, effective population size; s, selection coefficient of a mutation), when a new beneficial mutation is fixed in the evolving population, which accordingly moves to a different saddle, or on much rarer occasions from a saddle to a local peak. Phenomenologically, this mode of evolution of a large population resembles punctuated equilibrium (PE) whereby phenotypic changes occur in rapid bursts that are separated by much longer intervals of stasis during which mutations accumulate but the phenotype does not change substantially. Theoretically, PE has been linked to self-organized criticality (SOC), a model in which the size of “avalanches” in an evolving system is power-law-distributed, resulting in increasing rarity of major events. Here we show, however, that a PE-like evolutionary regime is the default for a very simple model of an evolving population that does not rely on SOC or any other special conditions.

A common perspective is that consistent R&D investment facilitates innovation, while volatile spending implies myopic decision making. However, the benefits to exploiting extant competencies eventually erode, so firms must disrupt their R&D function and explore for new competitive advantage. We suggest that high-performing firms recognize when extant competencies decline and increase exploratory R&D to develop new competencies at the appropriate time. We find that changes in R&D expenditure away from the firm's historic trend, in either direction, are indicative of transitions between exploitative and exploratory R&D and are associated with increased firm performance. Increases in R&D expenditure above the trend are associated with an increased likelihood of highly cited patents, suggesting that firms are making the leap between R&D-based exploitation and exploration.

In recent years, some U.S. school districts have shifted away from direct management of schools, toward systems in which some or all schools operate under enhanced autonomy, accountability, and parental choice. Yet dynamics driving these changes are understudied, and there are few comparative studies of system-level governance shifts. To address these gaps, we use extensive qualitative data to analyze change in Los Angeles, Denver, and New Orleans. Drawing on evolutionary theories, we find that external crises, state policy, and new actors triggered change, yet distinct contexts and change processes resulted in markedly different systems. Finally, in all three cities, concerns that emerging systems exacerbated long-standing inequities indicate that governance change is both an organizational and highly contentious political process.

This article focuses on geographic communities as fields in which human-made and natural events occasionally disrupt the lives of organizations. We develop an institutional perspective to unpack how and why major events within communities affect organizations in the context of corporate philanthropy. To test this framework, we examine how different types of megaevents (the Olympics, the Super Bowl, political conventions) and natural disasters (such as floods and hurricanes) affected the philanthropic spending of locally headquartered Fortune 1000 firms between 1980 and 2006. Results show that philanthropic spending fluctuated dramatically as mega-events generally led to a punctuated increase in otherwise relatively stable patterns of giving by local corporations. The impact of natural disasters depended on the severity of damage: while major disasters had a negative effect, smallerscale disasters had a positive impact. Firms' philanthropic history and communities' intercorporate network cohesion moderated some of these effects. This study extends the institutional and community literatures by illuminating the geographic distribution of punctuating events as a central mechanism for community influences on organizations, shedding new light on the temporal dynamics of both endogenous and exogenous punctuating events and providing a more nuanced understanding of corporate-community relations.

The study considers the policies and budgetary review of the Brazilian innovation policies to suggest two significant punctuations during the period from 1995 to 2023. Supported by Punctuated Equilibrium Theory (PET), the analysis reveals an expansion phase from 2007 to 2014, followed by a reduction period from 2015 to 2023. To assess the impact of these policy changes, the Synthetic Control Method (SCM) is applied to measure the quantity and quality of documents published by Brazilian authors in the Web of Science database. Overall, the results confirm the expected effects on scientometric indicators: positive impacts during the expansion phase and negative impacts during the reduction phase. Notably, policy expansion had a more pronounced effect on publication volume than on citation impact. During the reduction period, collaborations with international and industrial partners strengthened as an alternative to limited national public funding. Additionally, the study highlights heterogeneous effects over time and demonstrates the efficacy of combining PET with SCM for evaluating public policies using panel data.

Intelligent life has emerged late in Earth’s habitable lifetime, and required a preceding series of key evolutionary transitions. A simple model (the Carter model) explains the late arrival of intelligent life by positing these evolutionary transitions were exceptionally unlikely ‘critical steps’. An alternative model (the neocatastrophism hypothesis) proposes that intelligent life was delayed by frequent catastrophes that served to set back evolutionary innovation. Here, we generalize the Carter model and explore this hypothesis by including catastrophes that can ‘undo’ an evolutionary transition. Introducing catastrophes or evolutionary dead ends can create situations in which critical steps occur rapidly or in clusters, suggesting that past estimates of the number of critical steps could be underestimated. If catastrophes affect complex life more than simple life, the critical steps will also exhibit a pattern of acceleration towards the present, suggesting that the increase in biological complexity over the past 500 Myr could reflect previously overlooked evolutionary transitions. Furthermore, our results have implications for understanding the different explanations (critical steps versus neo-catastrophes) for the evolution of intelligent life and the so-called Fermi paradox—the observation that intelligent life appears rare in the observable Universe.

Punctuated Equilibrium Theory posits that policy-making is generally characterized by long periods of stability that are interrupted by short periods of fundamental policy change. The literature converged on the measure of kurtosis and L-kurtosis to assess these change patterns. In this letter, we critically discuss these measures and propose the Gini coefficient as a (1) comparable, but (2) more intuitive, and (3) more precise measure of “punctuated” change patterns.