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A list of competitive grant projects funded through the State Library of Oregon's Library Services and Technology Act (LSTA) Competitive Grants program since 2010. LSTA funds are from a federal allotment through the Institute of Museum and Library Services (IMLS).

The Competitive Intelligence Data Collection market is experiencing robust growth, driven by the increasing need for businesses to understand their competitive landscape and make data-driven decisions. The market, estimated at $15 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 15% throughout the forecast period (2025-2033), reaching an estimated $50 billion by 2033. This expansion is fueled by several key factors. Firstly, the proliferation of readily available data sources, combined with advancements in data analytics, enables businesses to glean deeper insights into their competitors' strategies, market positions, and financial performance. Secondly, heightened competition across various industries necessitates proactive intelligence gathering to maintain a competitive edge. Finally, the growing adoption of cloud-based solutions and sophisticated software platforms simplifies data collection and analysis, making competitive intelligence accessible to a broader range of businesses. The market segmentation reveals a significant share held by the "Business & Corporate" application segment, followed by the "Financial & Investment" sector, which benefits greatly from detailed competitive analyses. Within data types, "Public Information" sources currently dominate, but "Non-Public Information" collection is witnessing a rapid rise, propelled by the increasing demand for exclusive, in-depth insights. Leading players like SafeGraph, Moody's, and PitchBook are capitalizing on this growth by offering comprehensive solutions that encompass data collection, analysis, and visualization. Geographical analysis indicates North America holds the largest market share due to its highly competitive business environment and technological advancements, followed by Europe and Asia-Pacific. However, developing economies in Asia-Pacific are poised for significant growth, presenting promising future opportunities. While the market faces challenges such as data privacy concerns and the complexities of managing diverse data sources, the overall outlook for competitive intelligence data collection remains highly positive, driven by the escalating demand for robust and actionable competitive intelligence.

Primary competition and most important competitive strength when exporting or selling business' or organization's goods or services to Europe, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2023.

Discover how GlobalData’s competitive analysis helped a solar company gain valuable insights into market trends and outpace competition in a rapidly growing sector. Read More

On 1/11/18, Walmart announced that they would be closing 63 Sam’s Club locations. This list analyzes instances of overlap between the 63 closures and the following competitors:

  Costco Wholesale Club

  BJ’s Wholesale Club

  Target

  Walmart*

  Other Sam’s Club locations*



*Self-Inflicted Competition 

1. Competition can be fully hierarchical or intransitive, and this degree of hierarchy is driven by multiple factors, including environmental conditions, the functional traits of the species involved or the topology of competition networks. Studies simultaneously analyzing these drivers of competition hierarchy are rare. Additionally, organisms compete either directly or via interference competition for resources or space, within a local neighbourhood or across the habitat. Therefore, the drivers of competition could change accordingly and depend on the taxa studied.
2. We performed the first multi-taxon study on pairwise competition across major taxonomic groups, including experiments with vascular plants, mosses, saprobic fungi, aquatic protists and soil bacteria. We evaluated how general is competition intransitivity from the pairwise competition matrix including all species and also for each possible three-species combination (triplets). We then examined which species were likely to engage in competitive loops and the effects of environmental conditions, competitive rank, and functional traits on intransitive competition.
3. We found some degree of competition intransitivity in all taxa studied, with 38% to 5% of triplets being intransitive. Variance in competitive rank between species and more fertile conditions strongly reduced intransitivity, with triplets composed of species differing widely in their competitive ranks much less likely to be intransitive.
4. Including functional traits of the species involved more than doubled the variation explained compared to models including competitive rank only. Both trait means and variance within triplets affected the odds of them being intransitive. However the traits responsible and the direction of trait effects varied widely between taxa, suggesting that traits can have a wide variety of effects on competition.
5. Synthesis: We evaluated the drivers of competition across multiple taxa and showed that productivity and competitive rank are fundamental drivers of intransitivity. We also showed that not only the functional traits of each species, but also those of the accompanying species, determine competition intransitivity. Intransitive competition is common across multiple taxa but can dampen under fertile conditions or for those species with large variance in their competitive abilities. This provides a first step towards predicting the prevalence of intransitive competition in natural communities.

Competitive intelligence monitoring goes beyond your sales team. Our CI solutions also bring powerful insights to your production, logistics, operation & marketing departments.

Why should you use our Competitive intelligence data? 1. Increase visibility: Our geolocation approach allows us to “get inside” any facility in the US, providing visibility in places where other solutions do not reach. 2. In-depth 360º analysis: Perform a unique and in-depth analysis of competitors, suppliers and customers. 3. Powerful Insights: We use alternative data and big data methodologies to peel back the layers of any private or public company. 4. Uncover your blind spots against leading competitors: Understand the complete business environment of your competitors, from third-tier suppliers to main investors. 5. Identify business opportunities: Analyze your competitor's strategic shifts and identify unnoticed business opportunities and possible threats or disruptions. 6. Keep track of your competitor´s influence around any specific area: Maintain constant monitoring of your competitors' actions and their impact on specific market areas.

How other companies are using our CI Solution? 1. Enriched Data Intelligence: Our Market Intelligence data bring you key insights from different angles. 2. Due Diligence: Our data provide the required panorama to evaluate a company’s cross-company relations to decide whether or not to proceed with an acquisition. 3. Risk Assessment: Our CI approach allows you to anticipate potential disruptions by understanding behavior in all the supply chain tiers. 4. Supply Chain Analysis: Our advanced Geolocation approach allows you to visualize and map an entire supply chain network. 5. Insights Discovery: Our relationship identifiers algorithms generate data matrix networks that uncover new and unnoticed insights within a specific market, consumer segment, competitors' influence, logistics shifts, and more.

From "digital" to the real field: Most competitive intelligence companies focus their solutions analysis on social shares, review sites, and sales calls. Our competitive intelligence strategy consists on tracking the real behavior of your market on the field, so that you can answer questions like: -What uncovered need does my market have? -How much of a threat is my competition? -How is the market responding to my competitor´s offer? -How my competitors are changing? -Am I losing or winning market?

Identifying competitive exclusion at the macroevolutionary scale has typically relied on demonstrating a reciprocal, contradictory response by two co-occurring, functionally similar clades. Finding definitive examples of such a response in fossil time-series has proven challenging however, as has controlling for the effects of a changing physical environment. We take a novel approach to this issue by quantifying variation in trait values that capture almost the entirety of function for steam locomotives (SL), a known example of competitive exclusion from material culture, with the goal of identifying patterns suitable for assessing clade replacement in the fossil record. Our analyses find evidence of an immediate, directional response to the first appearance of a direct competitor, with subsequent competitors further reducing the realized niche of SLs, until extinction was the inevitable outcome. These results demonstrate when interspecific competition should lead to extinction and suggest that clade replacement may only occur when niche overlap between an incumbent and its competitors is near absolute and where the incumbent is incapable of transitioning to a new adaptive zone. Our findings provide the basis for a new approach to analyze putative examples of competitive exclusion that is largely free of a priori assumptions.

The Competitive Intelligence (CI) Tools Software market, valued at $1409.4 million in 2025, is experiencing robust growth. While a precise Compound Annual Growth Rate (CAGR) isn't provided, considering the rapid digital transformation across industries and the increasing need for data-driven decision-making, a conservative estimate of 15% CAGR for the forecast period (2025-2033) is reasonable. This growth is fueled by several key drivers: the rising adoption of cloud-based solutions offering scalability and accessibility, the expanding use of CI tools by both large enterprises and SMEs to gain a competitive edge, and the increasing complexity of market dynamics requiring sophisticated analytical capabilities. Trends indicate a shift towards AI-powered CI platforms that provide automated insights and predictive analytics, enhancing efficiency and accuracy. However, challenges such as the high cost of advanced CI solutions, the need for skilled professionals to interpret data effectively, and data privacy concerns act as market restraints. Segmentation reveals a significant preference for cloud-based deployments due to their flexibility and cost-effectiveness, while large enterprises constitute the major revenue segment due to their higher budgets and complex analytical needs. This segment is expected to grow at a slightly faster rate than the SME segment over the forecast period. The competitive landscape is characterized by a mix of established players and emerging startups. Companies like Crayon, Brandwatch, and SimilarWeb hold significant market share, leveraging their extensive data networks and established customer bases. However, the market also witnesses the entry of numerous agile startups offering innovative features and competitive pricing. Geographical distribution shows North America and Europe currently dominate the market, owing to higher technology adoption and a well-established business ecosystem. However, the Asia-Pacific region is projected to experience the fastest growth due to increasing digitalization and expanding business operations in emerging economies like India and China. The continued focus on innovation, particularly in AI and machine learning integration, will further shape the market's evolution over the next decade, opening opportunities for both established players and new entrants to capture market share.

Primary competition and most important competitive strength when exporting or selling business' or organization's goods or services to China, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2023.

The competitive multiplayer games market is a dynamic and rapidly expanding sector of the entertainment industry, projected to experience significant growth over the next decade. Driven by increasing internet penetration, the rise of esports, and the continuous development of sophisticated game engines and immersive graphics, this market is attracting substantial investment and generating considerable revenue. The key segments driving growth are free-to-play games, leveraging microtransactions and in-game purchases, and games targeting professional players, who participate in lucrative esports tournaments and leagues. While mobile gaming contributes significantly, the PC and console markets remain dominant, showcasing diverse platforms catering to various player preferences. Major players like Tencent, Activision Blizzard, and Electronic Arts dominate market share, investing heavily in game development, marketing, and esports initiatives. However, smaller, independent studios are also contributing significantly through innovative gameplay and niche market targeting. The market faces challenges, including increasing development costs, intense competition, and concerns about game addiction and player health. Nevertheless, the continued evolution of technology and the enduring appeal of competitive gaming suggest strong growth potential, particularly in regions like Asia-Pacific and North America, with burgeoning esports scenes fueling market expansion. The future of the competitive multiplayer games market hinges on several factors. Sustained investment in innovative game mechanics and compelling storylines is crucial to maintain player engagement. The expansion of esports infrastructure, including better streaming platforms and more professional leagues, will directly influence market growth. Furthermore, addressing concerns about game addiction and fostering responsible gaming practices are becoming increasingly important for long-term market sustainability. Finally, adapting to the evolving technological landscape, including advancements in virtual and augmented reality, will be essential for industry leaders to maintain a competitive edge and attract new players. Geographic expansion, particularly into emerging markets with rapidly growing internet access, presents significant opportunities for market penetration.

The global market for competitive analysis tools is experiencing robust growth, driven by the increasing need for businesses of all sizes to understand their competitive landscape and optimize their strategies. The market, estimated at $5 billion in 2025, is projected to exhibit a healthy Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $15 billion by 2033. This growth is fueled by several key factors. The rise of digital marketing and the increasing complexity of online competition necessitates sophisticated tools for analyzing competitor websites, strategies, and performance. Furthermore, the growing adoption of cloud-based solutions offers accessibility, scalability, and cost-effectiveness, contributing to market expansion. The segmentation reveals a significant portion of the market is held by large enterprises, reflecting their higher budgets and greater need for comprehensive competitive intelligence. However, the SME segment is also experiencing strong growth, indicating the increasing affordability and accessibility of these powerful tools. Key players such as SEMrush, Ahrefs, and SimilarWeb are driving innovation and market consolidation, while smaller, niche players cater to specialized needs. Geographic distribution shows North America and Europe currently dominating the market, but significant growth potential exists in rapidly developing economies across Asia-Pacific and other regions, fueled by digital transformation and the expansion of e-commerce. Market restraints include the high cost of some advanced competitive analysis tools, particularly for smaller businesses. Additionally, the complexity of certain tools can present a barrier to entry for users without substantial technical expertise. However, the trend towards user-friendly interfaces and subscription-based pricing models is mitigating this issue. The continuous evolution of search engine algorithms and online marketing tactics necessitates ongoing improvements and updates to the tools, posing challenges for vendors to maintain competitiveness. Nevertheless, the overall market outlook remains positive, indicating sustained growth and expansion fueled by the strategic importance of competitive intelligence in today's dynamic business environment.

The ARPA-E Grid Optimization (GO) Competition Challenge 1, from 2018 to 2019, focused on the basic Security Constrained AC Optimal Power Flow problem (SCOPF) for a single time period. The Challenge utilized sets of unique datasets generated by the ARPA-E GRID DATA program. Each dataset consisted of a collection of power system network models of different sizes with associated operating scenarios (snapshots in time defining instantaneous power demand, renewable generation, generator and line availability, etc.). The datasets were of two types: Real-Time, which included starting-point information, and Online, which did not. Week-Ahead data is also provided for some cases but was not used in the Competition. Although most datasets were synthetic and generated by GRIDDATA, a few came from industry and were only used in the Final Event. All synthetic Input Data and Team Results for the GO Competition Challenge 1 for the Sandbox, Trial Events 1 to 3, and the Final Event along with problem, format, scoring and rules descriptions are available here. Data for industry scenarios will not be made public.

Challenge 1, a minimization problem, required two computational steps. Solver 1 or Code 1 solved the base SCOPF problem under a strict wall clock time limit, as would be the case in industry, and reported the base case operating point as output, which was used to compute the Objective Function value that was used as the scenario score. The feasibility of the solution was provided by the Solver 2 or Code 2, which solves the power flow problem for all contingencies based on the results from Solver 1. This is not normally done in industry, so the time limits were relaxed. In fact, there were no time limits for Trial Event 1. This proved to be a mistake, with some codes running for more than 90 hours, and a time limit of 2 seconds per contingency was imposed for all other events. Entrants were free to use their own Solver 2 or use an open-source version provided by the Competition.

Containers, such as Docker, were considered to improve the portability of codes, but none that could reliably support a multi-node parallel computing environment, e.g., MPI, could be found.

For more information on the competition and challenge see the "GO Competition Challenge 1 Information" and "GO Competition Challenge 1 Additional Information" resources below.

The data set consists of a detailed training log from a Dutch high-level running team over a period of seven years (2012-2019). We included the middle and long distance runners of the team, that is, those competing on distances between the 800 meters and the marathon. This design decision is motivated by the fact that these groups have strong endurance based components in their training, making their training regimes comparable. The head coach of the team did not change during the years of data collection. The data set contains samples from 74 runners, of whom 27 are women and 47 are men. At the moment of data collection, they had been in the team for an average of 3.7 years. Most athletes competed on a national level, and some also on an international level. The study was conducted according to the requirements of the Declaration of Helsinki, and was approved by the ethics committee of the second author’s institution (research code: PSY-1920-S-0007).

Conduct competitive analysis for wind turbine cable companies, focusing on market positioning, innovation, and growth drivers. Read More

The body size competition model.

Russia Competitive Environment: OKVED2: Authorities Anticompetitive Actions Declined: PY: Mining & Quarrying data was reported at 5.000 % in Dec 2018. This records a decrease from the previous number of 6.000 % for Jun 2018. Russia Competitive Environment: OKVED2: Authorities Anticompetitive Actions Declined: PY: Mining & Quarrying data is updated semiannually, averaging 6.000 % from Jun 2017 (Median) to Dec 2018, with 4 observations. The data reached an all-time high of 6.000 % in Jun 2018 and a record low of 5.000 % in Dec 2018. Russia Competitive Environment: OKVED2: Authorities Anticompetitive Actions Declined: PY: Mining & Quarrying data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Business and Economic Survey – Table RU.SB010: Enterprises Survey: Competitive Environment.

Healthcare Antimicrobial Plastics Competitive Market size is valued at USD 44.15 Billion in 2024 and is projected to reach USD 80.89 Billion by 2032, growing at a CAGR of 7.9% during the forecast period 2026-2032.

Global Healthcare Antimicrobial Plastics Competitive Market Drivers

Regulatory and Industry Support: Governments and healthcare organizations worldwide emphasize the importance of infection control measures. Regulatory agencies have established standards and guidelines that promote the use of antimicrobial materials in healthcare. For example, the U.S. Environmental Protection Agency (EPA) and other global entities provide frameworks for the development and use of antimicrobial technologies, creating a favorable environment for market growth​

Growth in Aging Population and Chronic Diseases: An aging population and the increasing prevalence of chronic diseases are driving demand for advanced healthcare facilities and medical devices. Antimicrobial plastics are vital in producing durable, safe, and hygienic equipment, addressing the specific needs of elderly and immunocompromised patients​.