Strong Complementarity Research Articles

Strategic complements: Poverty-targeted subsidy programs show additive benefits on household toilet purchases in rural Cambodia when coupled with sanitation marketing.

While poverty-targeted subsidies have shown promise as a means of reducing financial constraints on low-income populations to invest in new latrines, concerns have been raised about whether they may reduce demand for new latrines among non-eligible, non-poor populations, especially in geographically limited or closed markets. Using quasi experimental methods, we investigate the interaction effects of the “CHOBA” subsidy, a partial poverty-targeted monetary incentive to build a toilet, and a sanitation marketing program (SanMark) on new latrine uptake among households from different income segments in 110 rural villages across six Cambodian provinces. These programs were implemented either jointly with or independently. Overall, we find strong complementarity of the CHOBA subsidy with SanMark where the coupled implementation of the programs increased latrine uptake across all households as compared to exclusive deployment of the programs independently. Additionally, the CHOBA subsidy alone resulted in higher gains among the poor compared to SanMark suggesting that financial constraint is indeed a significant demand barrier for new latrines. The presence of the poverty-targeted subsidies did not reduce demand for new latrine purchases among ineligible households. Instead, we find some evidence for a positive spillover effect of subsidies on uptake of latrines among ineligible households in villages where both programs were implemented indicating that the presence of sanitation subsidies and the decision to purchase latrines among non-beneficiaries can be viewed as complements. We employ multivariate logistic regressions as well as further robustness checks to estimate the effects of the different interventions, with qualitatively consistent results.

Abstract 6398: Functional characterization of Androgen Receptor splice variants in breast cancer invasion and metastasis

Abstract Introduction: A growing body of evidence suggests the prognostic and therapeutic value of Androgen Receptors (AR) in Breast Cancer (BrCa), particularly Triple Negative BrCa (TNBC). The splice variants of AR (ARVs); notably full-length AR (AR-fl) of ~110 kDa and a C-terminally Ligand Binding Domain (LBD) truncated AR isoform (AR-V7) of ~67 kDa are present in a variety of tissues. The ligand-independent AR-V7 is constitutively expressed and confers castration resistance in prostate cancer. With the irrefutable role of ARVs in BrCa, we evaluated their expression profile in cell lines with their prevalence and clinicopathological correlation in BrCa patients from India. Methods: Breast Cancer cell lines MDA-MB-231, MCF7, and MDA-MB-453 were procured from American Type Culture Collection. Thirty-eight de novo cases of Breast Cancer undergoing surgical intervention at a tertiary healthcare center in India were recruited. Tumor and adjacent benign tissue were collected after informed consent. The ARVs expression at transcriptomic and proteomic levels was evaluated by qRT-PCR and western blotting & Immunohistochemistry (IHC) respectively. For functional annotation, ARVs were knocked down in vitro using differently targeting siRNAs facilitated by Lipofectamine 3000 based transfection. There was a strong complementarity observed in western blotting and IHC. Results: All the ARVs were significantly higher in MDA-MB-453 followed by MCF7 and MDA-MB-231 cells. The expression ratio of AR-V7 versus AR-fl is, however, elevated in highly aggressive TNBC cell line MDA-MB-231. 67% of patients recruited were immunostained positive for AR (n=38). A majority of patients were of Luminal phenotype (37%) expressing both the prominent ARVs. One-third of the TNBC fraction were AR positive. Following the TNBC cell line, a subset of patients' samples also exhibited a substantial upregulation of AR-V7 compared to AR-fl. These patients had poor prognoses and aggressive features. The siRNA knockdown of all the ARVs resulted in decreased invasion and Epithelial-mesenchymal transition (EMT). Interestingly knocking down of ARVs barring AR-V7, restored invasiveness suggesting the compensatory behavior of AR-V7. Conclusion: Our work demonstrates the presence of ARVs in BrCa with a particular focus on the AR-V7. The LBD truncated AR-V7 potentiates the growth in BrCa cell lines and patients. This study further encourages the ARVs expression screening with AR positive BrCa for a prognostic biomarker of aggressive phenotype and therapeutic resistance. Citation Format: Tryambak Pratap Srivastava, Ruby Dhar, Anurag Srivastava, SVS Deo, Rajinder Parshad, Subhradip Karmakar. Functional characterization of Androgen Receptor splice variants in breast cancer invasion and metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6398.

Load-driven interactions between energy efficiency and demand response on regional grid scales

• We simulate bottom-up energy efficiency load impacts at building and grid scales. • Efficiency can interact differently with demand response on different scales. • We see no fixed relationship between efficiency and demand response; details matter. • Most often, there is competition between efficiency and demand response. • Strong complementarity is also possible, especially with controls-based efficiency. Energy efficiency (EE) has long been recognized as a source of value to the electricity grid. Especially with increasing penetration of variable renewable generation, demand response (DR) can also provide system value and support the evolving needs of the grid. Yet there has been little study to date of interactions between EE and DR that may complicate their grid impacts. In this study we perform bottom-up modelling of the interactive effects between EE and DR in buildings for three representative regions of the United States electricity grid. Leveraging new simulation tools that enable detailed modelling of the building stock, we synthesize system-level demand profiles for several scenarios representing different portfolios of EE measures. In each scenario, we couple the underlying building models with a database of DR-enabling technologies to estimate building-level DR capabilities and compute a system-level supply curve for DR. We assess the resulting EE and DR interactive effects based on an existing conceptual framework. The results show a complex relationship between EE and DR, with interactive effects whose size and direction can vary widely depending on the grid system, type of DR, and the framework level being considered. Most often, the overall effect is competition between EE and DR, but significant complementarity can also occur, especially when the EE portfolio includes controls measures. Our results suggest that EE and DR programs developed without considering interactive effects may erode the benefits of both resources, whereas a more integrated approach may yield increased benefits.

Spatial-temporal interaction learning based two-stream network for action recognition

Two-stream convolutional neural networks have been widely applied to action recognition. However, two-stream networks are usually adopted to capture spatial information and temporal information separately, which normally ignore the strong complementarity and correlation between spatial and temporal information in videos. To solve this problem, we propose a Spatial-Temporal Interaction Learning Two-stream network (STILT) for action recognition. Our proposed two-stream (i.e., a spatial stream and a temporal stream) network has a spatial–temporal interaction learning module, which uses an alternating co-attention mechanism between two streams to learn the correlation between spatial features and temporal features. The spatial–temporal interaction learning module allows the two streams to guide each other and then generates optimized spatial attention features and temporal attention features. Thus, the proposed network can establish the interactive connection between two streams, which efficiently exploits the attended spatial and temporal features to improve recognition accuracy. Experiments on three widely used datasets (i.e., UCF101, HMDB51 and Kinetics) show that the proposed network outperforms the state-of-the-art models in action recognition.

Experimental and numerical studies of separation intensification in segmented flow microreactors

Process intensification studies have already been well-established in continuous operations, particularly achieved by using microreactors. Separation intensification benefits from the application of process intensification and shows great potential, yet it is still not sufficiently studied. In this work, liquid-liquid two-phase segmented flow capillary microreactors and simulation models based on finite element method were used to perform experimental and numerical studies on the extractive separation intensification of the Zn-Cd-Mn system, respectively. The influence of hydrodynamics including metal ion concentration, plug velocity, and initial pH of the aqueous phase on the separation factor was explored. By regulating the hydrodynamic conditions, higher separation factors are obtained in shorter times to achieve separation intensification. The Damkhler number (Da) was introduced to clarify the rate-determining step and elaborate the separation mechanism. During the simulations, the results obtained from the model based on the finite element method agree well with the experimental ones. Taking advantage of the strong complementarity between numerical and experimental studies, separation intensification can be more deeply understood.

Genomic Instability in Somatic Hybridization between Poncirus and Citrus Species Aiming to Create New Rootstocks

Rootstocks are an important component for citrus adaptation to increasing biotic and abiotic stresses resulting from global climate change. There is a strong complementarity between Citrus species, which adapt to abiotic stresses, and Poncirus trifoliata and its intergeneric hybrids, which exhibit resistances or tolerances to major diseases and pests. Thus, symmetrical somatic hybridization between complementary diploid rootstocks of these two genera appears to be an efficient way to develop new tetraploid rootstocks in order to address the new challenges of the citrus industry. New intergeneric somatic hybrids were obtained by electrofusion between protoplasts of Citrus and P. trifoliata hybrids. Extensive characterization of the nuclear and cytoplasmic genomes was performed by genotyping-by-sequencing (GBS) analysis. This revealed diploid cybrids and nuclear somatic hybrids. Mitochondrial genomes were mostly inherited from the callus parent, but homologous recombination events were observed for one parental combination. Chloroplasts exhibited random uniparental inheritance. GBS revealed local chromosomal instabilities for all nuclear somatic hybrids and whole chromosome eliminations for two hybrids. However, at the whole genome level, symmetrical addition of the nuclear genomes of both parents was predominant and all somatic hybrids displayed at least one trifoliate orange haplotype throughout the genome.

A complementary and precise vehicle detection approach in RGB-T images via semi-supervised transfer learning and decision-level fusion

ABSTRACT Owing to the strong complementarity between visible and infra-red thermal (RGB-T) images, the two types of images receive the increased application of vehicle detection in traffic monitoring. Now, how to take full advantage of the two kinds of images for vehicle fusion detection has drawn wide publicity. Nevertheless, due to the requirement of high quality and high precision on vehicle fusion detection, and insufficiency of the infra-red thermal dataset, it is extremely hard to realize the vehicle fusion detection in RGB-T images. In our work, a complementary and precise vehicle fusion detection approach in RGB-T images is put forward, which combines the detection results of both visible and infra-red thermal images based on a decision-level fusion strategy. For vehicle detection in visible images, an effective and shallow network is constructed. For vehicle detection in infra-red thermal images, we do not directly train an effective network because of the insufficiency of the infra-red thermal vehicle samples. Instead, semi-supervised transfer learning is applied to combine the trained visible network for vehicle detection in infra-red thermal images. Next, for the decision-level fusion, we propose a novel fusion algorithm. It not only retains the vehicle results detected only in the visible images or only the infra-red thermal images but also fuses the detection results of the same vehicle in both visible and infra-red thermal images. Finally, VOT2019 and RGBT234 data sets are introduced to evaluate the proposed vehicle fusion detection approach. Compared with the main trend of current, it is indicated that the proposed approach can obtain competitive and superior vehicle fusion detection results in RGB-T images.

EPNet++: Cascade Bi-Directional Fusion for Multi-Modal 3D Object Detection.

Recently, fusing the LiDAR point cloud and camera image to improve the performance and robustness of 3D object detection has received more and more attention, as these two modalities naturally possess strong complementarity. In this paper, we propose EPNet++ for multi-modal 3D object detection by introducing a novel Cascade Bi-directional Fusion (CB-Fusion) module and a Multi-Modal Consistency (MC) loss. More concretely, the proposed CB-Fusion module enhances point features with plentiful semantic information absorbed from the image features in a cascade bi-directional interaction fusion manner, leading to more powerful and discriminative feature representations. The MC loss explicitly guarantees the consistency between predicted scores from two modalities to obtain more comprehensive and reliable confidence scores. The experimental results on the KITTI, JRDB and SUN-RGBD datasets demonstrate the superiority of EPNet++ over the state-of-the-art methods. Besides, we emphasize a critical but easily overlooked problem, which is to explore the performance and robustness of a 3D detector in a sparser scene. Extensive experiments present that EPNet++ outperforms the existing SOTA methods with remarkable margins in highly sparse point cloud cases, which might be an available direction to reduce the expensive cost of LiDAR sensors.

Systematic shifts in scaling behavior based on organizational strategy in universities.

To build better theories of cities, companies, and other social institutions such as universities, requires that we understand the tradeoffs and complementarities that exist between their core functions, and that we understand bounds to their growth. Scaling theory has been a powerful tool for addressing such questions in diverse physical, biological and urban systems, revealing systematic quantitative regularities between size and function. Here we apply scaling theory to the social sciences, taking a synoptic view of an entire class of institutions. The United States higher education system serves as an ideal case study, since it includes over 5,800 institutions with shared broad objectives, but ranges in strategy from vocational training to the production of novel research, contains public, nonprofit and for-profit models, and spans sizes from 10 to roughly 100,000 enrolled students. We show that, like organisms, ecosystems and cities, universities and colleges scale in a surprisingly systematic fashion following simple power-law behavior. Comparing seven commonly accepted sectors of higher education organizations, we find distinct regimes of scaling between a school’s total enrollment and its expenditures, revenues, graduation rates and economic added value. Our results quantify how each sector leverages specific economies of scale to address distinct priorities. Taken together, the scaling of features within a sector along with the shifts in scaling across sectors implies that there are generic mechanisms and constraints shared by all sectors, which lead to tradeoffs between their different societal functions and roles. We highlight the strong complementarity between public and private research universities, and community and state colleges, that all display superlinear returns to scale. In contrast to the scaling of biological systems, our results highlight that much of the observed scaling behavior is modulated by the particular strategies of organizations rather than an immutable set of constraints.

WaterMap and Molecular Dynamic Simulation-Guided Discovery of Potential PAK1 Inhibitors Using Repurposing Approaches.

p21-Activated kinase 1 (PAK1) is positioned at the nexus of several oncogenic signaling pathways. Currently, there are no approved inhibitors for disabling the transfer of phosphate in the active site directly, as they are limited by lower affinity, and poor kinase selectivity. In this work, a repurposing study utilizing FDA-approved drugs from the DrugBank database was pursued with an initial selection of 27 molecules out of ∼2162 drug molecules, based on their docking energies and molecular interaction patterns. From the molecules that were considered for WaterMap analysis, seven molecules, namely, Mitoxantrone, Labetalol, Acalabrutinib, Sacubitril, Flubendazole, Trazodone, and Niraparib, ascertained the ability to overlap with high-energy hydration sites. Considering many other displaced unfavorable water molecules, only Acalabrutinib, Flubendazole, and Trazodone molecules highlighted their prominence in terms of binding affinity gains through ΔΔG that ranges between 6.44 and 2.59 kcal/mol. Even if Mitoxantrone exhibited the highest docking score and greater interaction strength, it did not comply with the WaterMap and molecular dynamics simulation results. Moreover, detailed MD simulation trajectory analyses suggested that the drug molecules Flubendazole, Niraparib, and Acalabrutinib were highly stable, observed from their RMSD values and consistent interaction pattern with Glu315, Glu345, Leu347, and Asp407 including the hydrophobic interactions maintained in the three replicates. However, the drug molecule Trazodone displayed a loss of crucial interaction with Leu347, which was essential to inhibit the kinase activity of PAK1. The molecular orbital and electrostatic potential analyses elucidated the reactivity and strong complementarity potentials of the drug molecules in the binding pocket of PAK1. Therefore, the CADD-based reposition efforts, reported in this work, helped in the successful identification of new PAK1 inhibitors that requires further investigation by in vitro analysis.

Economic impact of public R&D: an international perspective

AbstractDespite the fact that research and development (R&D) activities are carried out in most countries in public research institutes such as universities and public research organizations, there have been few studies that attempted to estimate the economic impact of such public investment in R&D. In this paper, we analyze the relations between total factor productivity (TFP) and public and private R&D as well as gross domestic product for a set of 17 Organisation for Economic Cooperation and Development (OECD) countries using a vector-error-correction model. We find that for the period 1975–2014, investment in public R&D has had a clearly positive effect on TFP growth in the majority of countries analyzed. In simulations allowing for a permanent positive shock to public R&D, we observe a strong dynamic complementarity between the public and private (domestic) stocks of R&D for several countries. In countries where this complementarity is strong, the TFP effect of extra public R&D investments is also strong. A discriminant analysis shows that in countries with high complementarity between private and public R&D, the share of foreign funding of R&D performed in the business sector combined with a high business R&D intensity tends to be low. At the same time, the share of basic R&D in business R&D combined with a higher public R&D intensity tends to be higher in countries with strong complementarity.

Gated Fusion of Infrared and Visible Light Images Based on CNN

As a new research direction, fusion image technology has attracted more and more attention in many fields. Among them, infrared image and visible image, the two kinds of multimodal data have strong complementarity, the fusion image of the two modes contains not only the radiation information of infrared image, but also the texture detail information of visible image. In this paper, a convolutional neural network-based encoding-fusing-decoding network model structure is used. In the encoding stage, Dense Block, which has the advantage of feature extraction, was adapted to extract the image features. In the fusion stage, four fusion methods were compared and analyzed, and the gated fusion was selected as the main method of fusion layer. In the decoding stage, RDB (Residual Dense Blocks) was used to restore the fused features to the fused image. The fusion image based on this method is sensitive to temperature characteristics and has a better performance in image quality. The fused image has a high contrast, a relatively smooth fusion effect, and the overall visual effect is more natural.

When does complementarity support pluralism about schools of economic thought?

ABSTRACT An intuitively appealing argument for pluralism in economics can be made on the grounds that schools of economic thought complement one another. Let us call this the complementarity-based argument for pluralism (CAP). The concepts of complementarity, pluralism, and school of thought are scrutinized in this paper to evaluate this argument. I argue that the complementarity of schools is relative to scientific goals, which implies that discussing complementarity of schools of economic thought requires discussing the goals of economic research. I also distinguish weak from strong complementarity and show that some alleged complementarity relations between schools are weak and thus provide little support for CAP. However, if strong complementarity relations, relative to a valuable goal, can be demonstrated to exist between specific schools, this is a strong reason for pluralism about those schools. Finally, I provide suggestions on how to distinguish strong from weak complementarity.

Five years of citizen science and standardised field surveys in an informal urban green space reveal a threatened Eden for wild bees in Brussels, Belgium

Abstract Urbanisation is often put forward as an important driver of biodiversity loss, including for pollinators such as wild bees. However, recent evidence shows that the mosaics of urban green spaces, and in particular certain categories of informal urban green spaces (IGS), can play an important role to help native wild bees thrive in cities. Here, we describe the results of 5 years of citizen science and standardised field surveys of wild bees conducted at the Friche Josaphat, a 24‐ha urban wasteland in the Brussels‐Capital Region (Belgium). These field surveys were initiated following the planned restructuring and partial destruction of this site by the regional authorities. We recorded a total of 2507 specimens belonging to 127 species of wild bees, i.e. 60.5% of the 210 species recorded regionally, including nine that are threatened with extinction at national or European scales. The Friche Josaphat encompasses a significant share of the functional and phylogenetic diversity of wild bees known from the Brussels‐Capital Region and is one of the most species‐rich localities known to date for wild bees in Belgium. Collectively, our results highlight the strong complementarity of citizen science and academic approaches in biodiversity surveys, and they reaffirm that wastelands are essential components of urban biodiversity. Our study stresses the need to provide biodiverse IGS with a formal status within the mosaic of urban green spaces but also to acknowledge and safeguard their natural capital and the multiple ecosystem services they provide.

An evolutionary perspective on economic catch-up by latecomers

AbstractThis paper proposes an evolutionary view of economic catch-up by latecomers, considered as a long-run process of closing the gap in capabilities by promoting learning and innovation in interaction with innovation systems (national, sectoral or regional). According to this perspective, catch-up is viewed as a dynamic evolutionary process which is not deterministic and cannot be planned in details because it faces uncertainty and continuous change; is associated with a variety of exogenous events (windows of opportunity) and is the result of the idiosyncratic behavior of heterogeneous actors characterized by different understanding, views and experiences. This process leads to a variety of responses and strategies by latecomer firms and countries, even in the presence of similar external technological or market conditions. One major point that emerges from this perspective is that there is a strong complementarity between learning and capabilities by domestic firms and the national, sectoral, and regional systems in which firms operate. The paper also discusses various strategies, such as detours and leapfrogging, along the stages and the different paths and trajectories that this long-term evolutionary process of countries and sectors follows.

Negative interest rates, excess liquidity and retail deposits: Banks’ reaction to unconventional monetary policy in the euro area

Negative interest rate policy (NIRP) is associated with a particular friction. The remuneration of banks´ retail deposits tends to be floored at zero, which limits the transmission of policy rate cuts to bank funding costs. We investigate whether this friction affects banks’ reactions under NIRP compared to a standard rate cut in the euro area. We argue that reliance on retail deposit funding and the level of excess liquidity holdings may increase banks’ responsiveness to NIRP. We find evidence that banks highly exposed to NIRP tend to grant more loans, i.e. NIRP is indeed expansionary for the levels of interest rates seen in the euro area so far. This confirms studies pointing to higher risk taking by banks under NIRP and sheds some new light on results that associate NIRP with a contraction in bank loans, albeit in specific market segments. We are the first to document the importance of banks’ excess liquidity holdings for the effectiveness of NIRP, pointing to a strong complementarity of NIRP with central bank liquidity injections, e.g. via asset purchases.

Regional Policy Spillovers and Complementarity in the Great Lockdown

Nonpharmaceutical interventions (NPIs) are the primary measures to control pandemics. Should regional governments coordinate in implementing NPIs? If so, how? The answers depend on spatial spillovers and complementarity or substitutability of regional NPIs. This paper estimates the spillover effects of stay-at-home (SAH) orders on the COVID-19 infection growth across adjacent counties on the state borders in the United States. We find that the spillover effects critically depend on the local implementation of SAH orders. With local SAH orders, the spillover effects reduce the daily case growth rate by 5.1 percentage points in the first three weeks of treatment, with an accumulative case reduction of 66.6 percent; otherwise, the spillover effects slightly increase the growth rate though statistically insignificant. Such strong complementarity in reducing infections is in contrast to previous findings of substitutability in changing mobility. Our results suggest that NPIs are best implemented jointly, and there may be coordination failures among decentralized regional governments.

Joint exploitation of space-borne and ground-based multitemporal InSAR measurements for volcano monitoring: The Stromboli volcano case study

We present a joint exploitation of space-borne and ground-based Synthetic Aperture Radar Interferometry (InSAR) and Multi Temporal (MT) InSAR measurements for investigating the Stromboli volcano (Italy) deformation phenomena. In particular, we focus our analysis on three periods: a) the time interval following the 2014 flank eruption, b) the July–August 2019 eruption and c) the following post-eruptive phase. To do this, we take advantage from an unprecedented set of space-borne and ground-based SAR data collected from April 2015 up to November 2019 along two (one ascending and one descending) Sentinel-1 (S-1) tracks, as well as, in the same period, by two ground-based systems installed along the Sciara del Fuoco northern rim. Such data availability permitted us to first characterize the volcano long-term 3D deformation behavior of the pre-eruptive period (April 2015–June 2019), by jointly inverting the space-borne and ground-based InSAR measurements. Then, the GB-SAR measurements allowed us to investigate the sin-eruptive time span (3rd July 2019 – 30th August 2019) which revealed rapid deformation episodes (e.g. more than 30 mm/h just 2 min before the 3rd July 2019 explosion) associated with the eruptive activity, that cannot be detected with the weekly S-1 temporal sampling. Finally, the S-1 measurements permitted to better constrain the post 2019 eruption deformations (31st August 2019 – 5th November 2019), which are mainly located outside the GB-SAR sensed area. The presented results demonstrate the effectiveness of the joint exploitation of the InSAR measurements obtained through satellite and terrestrial SAR systems, highlighting their strong complementarity to map and interpret the deformation phenomena affecting volcanic areas.

The Elusive Peace Dividend of Development Policy: From War Traps to Macro Complementarities

This article reviews the literature on civil conflict and development with a focus on the socioeconomic consequences of violence and on promising policies for fostering peace. We make four main points. First, one of the reasons conflict is still often overlooked as key factor for development is that conflict costs are typically underestimated, in particular the shadow costs of deterrence. Second, there are several types of war traps that hold countries back, both economically and politically. Third, to break these traps, policies must be calibrated to address jointly both poverty and social tensions, as there is a strong macro complementarity between peace and development objectives. We document how single-minded policies that ignore this dual challenge can spectacularly fail, and we discuss in depth a series of particularly promising policies. Fourth, we highlight the increasing potential of novel data collection methodologies and the need for policy evaluation tools in violent contexts.

The Evolution of Resource-Based Inquiry: A Review and Meta-Analytic Integration of the Strategic Resources–Actions–Performance Pathway

Understanding why some firms outperform others is central to strategy research. The resource-based view (RBV) suggests that competitive advantages arise due to possessing strategic resources (i.e., assets that are valuable, rare, nonsubstitutable, and inimitable), and researchers have extended this logic to explain performance differences. However, RBV is relatively silent about the actions managers could use to create or capitalize on a resource-based advantage. Enriching RBV, the resource orchestration framework describes specific managerial actions that use such resources to realize performance gains. After reviewing the conceptual evolution of these two literature streams as well as related streams, we use meta-analytic structural equation modeling to aggregate evidence from 255 samples involving 111,120 observations to answer outstanding research questions regarding the strategic resources–actions–performance pathway. The results show strong complementarity and interdependence between their logics. Additional inquiry drawing on their complementarity is a clear path toward enhancing scholars’ understanding of how and why some firms outperform others. We build on our findings to lay a foundation for such inquiry, including a call for theorizing centered on the interdependence of resources and actions, as well as new theoretical terrain that can help resource-based inquiry continue to evolve.