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In this paper, we review the literature on pay variation (e.g., pay dispersion, pay compression, pay range) in organizations. Pay variation research has increased markedly in the past two decades and much progress has been made in terms of understanding its consequences for individual, team, and organizational outcomes. Our review of this research exposes several levels-related assumptions that have limited theoretical and empirical progress. We isolate the issues that deserve attention, develop an illustrative multilevel model, and offer a number of testable propositions to guide future research on pay structures.

The world consists of diverse and distinctive economic systems. Due to the unique historical, cultural and location-specific contexts embedded in each economy, a comparison of strategic behaviors across economies is unlikely to provide a causal estimate of the influence of these contextual factors on strategy–performance relationships. In this paper, I outline three approaches to researching multinational firms that address this dilemma. They include the multilevel, historical and variance-centered perspectives, all of which can help international-business (IB) researchers develop stronger theoretical foundations from which to explain why country-specific contexts matter in designing IB action and research.

Using a routine dynamics perspective, the authors address a central question in a practice-driven institutional theory: where does change come from? In particular, the authors focus on the possibility that small variations in routines can accumulate into big changes in institutions. The analysis is limited strictly to endogenous change. The authors use narrative networks to formalize and operationalize key concepts, such as variation and change. The authors reinterpret results from a published simulation model (Pentland, Liu, Kremser, & Hærem, 2020) that examined endogenous change in organizational routines. The simulation suggests that over a wide range of conditions, minor variations can lead to irreversible structural changes in routines. In the absence of exogenous shocks and institutional entrepreneurs, patterns of action that were previously possible can become impossible. The mechanism underlying these changes requires both accumulation and forgetting. Without forgetting, small variations may pile up (like dirty laundry), but they will not result in big changes.

The purpose of this paper is to identify the sources of variation in firm performance. This is one of the cornerstones of strategy research, i.e. the relative importance of industry and firm-level effects on firm performance. Multilevel analysis is well suited to analyze variance in performance when the data are hierarchically structured (industry segments consist of firms, firms operate within the context of industry segments). The Belgian industry studied is a service industry that consists of about 25 electrical wholesalers. Data were collected from 20 firms during the period 1998–2003 from responses to a questionnaire sent to all the firms in the market. The sample in the data set covers more than 95 percent of the market (in sales), as the missing firms were just fringe competitors. The results show that firm effects explain most of the variance in four performance variables. That bears out the importance of each firm having its own specific, idiosyncratic resources and competences. The explanatory power of firm effects varies by about 30–40 percent while the intra-industry effect explains around 10 percent of the variance. Even though firm effects are dominant, intra-industry effects explain a significant portion of the variance in firm-level performance. The firm effect is smaller than in previous studies. The firm effect varies across the performance measures: firm effects are higher for returns on assets than for profit margins. The industry segment effect (or intra-industry effect) is more independent of the dependent variable. The industry segment effect is in line with previous studies on the strategic group effect. Top managers should carefully choose and monitor the intra-industry domain they are in.

For work organizations and their members, establishing and maintaining mutually satisfying employment relationships is a fundamental concern. The importance that scholars attach to employment relationships is reflected in research streams that explore the optimal design of strategic human resource management systems, the nature of psychological contract fulfillment and violation, and the factors associated with achieving person-environment fit, among others. Generally missing from theory and research pertaining to employment relationships is the perspective of individuals who reside at the employee-employer interface – managerial leaders. We argue that, for managerial leaders, a pervasive concern involves the tangible and intangible resource requirements of specific employees. We then provide the groundwork for study of the leader’s perspective on employment relationships by proposing a model that identifies how employees come to be perceived as low versus high maintenance and how these perceptions, in turn, influence leader cognition, affect, and behavior.

Utility strikes have spawned companies specializing in providing a priori analyses of the underground. Geophysical techniques such as Ground Penetrating Radar (GPR) are harnessed for this purpose. However, analyzing GPR data is labour-intensive and repetitive. It may therefore be worthwhile to amplify this process by means of Machine Learning (ML). In this work, harnessing the ADR design science methodology, an Intelligence Amplification (IA) system is designed that uses ML for decision-making with respect to utility material type. It is driven by three novel classes of Convolutional Neural Networks (CNNs) trained for this purpose, which yield accuracies of 81.5% with outliers of 86%. The tool is grounded in the available literature on IA, ML and GPR and is embedded into a generic analysis process. Early validation activities confirm its business value.

This research examines how the cost performance of defense contracts varies among the Air Force, Army, Navy, and the Department of Defense (DoD) and among five major defense contractors: Boeing, Lockheed Martin, Northrop Grumman, Raytheon, and General Dynamics. Data for these analyses was extracted from the recently established Defense Acquisition Management Information Retrieval (DAMIR) web-based interface for management information on Major Defense Acquisition Programs (MDAP). Note that, in addition to the three military services, MDAP data is also reported for DoD itself.

Data analysis indicates that the Navy ranks last among the military services and DoD in cost performance for MDAP contracts, while the Air Force ranks best. Of the defense contractors, Raytheon ranks last in cost performance and General Dynamics is next to last. Furthermore, the Navy contracts more frequently with Raytheon and General Dynamics than do the other services or DoD. Explanatory factors for poor cost performance may be due to factors such as the Navy's lack of oversight, the quality of the acquisition workforce, the defense contractors’ cost inefficiency, ethical lapses, or weak corporate governance, or combinations of these factors.

In addition, the schedule performance data was also identified. Tests of statistical significance on the schedule performance difference generally yield no results except for one relationship which indicates that the Navy is more likely to have Acquisition Program Baseline (APB) schedule breaches than its counterparts. Finally, cost performance data is examined for statistically significant differences between the two major categories of defense contracts: fixed-price contracts and cost-plus contracts. However, no significant findings were discovered.

Data from samples of managers from eight countries, Thailand, Nigeria, Philippines, Peru, Uruguay, Argentina, Spain, and the United States, are used to explore cross-national differences in how individuals make judgments about an individual's pay. A policy-capturing instrument is used to elicit judgments about the ways that variations in individual employee job performance, business unit performance, seniority, schooling, and need affect judgments about pay fairness. Significant between-country differences are found in the sensitivities of pay fairness judgments. However, these differences are not well explained by differences in individualism/collectivism reflected either by a priori categorizations of national culture or direct measures of horizontal/vertical collectivism. Implications for the explanation of cross-national differences are explored.

Purpose – Integrating insights from the literatures on internationalization and knowledge externalities, we posit that the reservoirs of scientific knowledge residing in different locations around the world have significant power in explaining interfirm performance variations. We assert that the ability to access and exploit such intangible resources differs considerably across multinationals, according to both firm-specific and exogenously determined factors.

Methodology – Unlike previous research that typically focuses on knowledge flows within one nation or between two countries, our statistical analysis combines firm-level data with industry-level information on 18 countries and 15 manufacturing sectors.

Findings and implications – The empirical findings indicate that the performance-enhancing effect of global knowledge reservoirs is positive and often higher than that of a firm's own knowledge. Whereas some multinationals excel at exploiting such intangible resources, others fail to do so successfully. In this respect, the results indicate that a firm's ability to benefit from global knowledge reservoirs is positively associated with its degree of international diversification, the intensity of its own research efforts, and exogenously determined opportunities pertaining to different technological domains.