Gain a competitive edge with GlobalData’s custom intelligence solutions. Tailored insights into competitors, market trends, and strategic planning. Read More

In 2021, 44.5 percent of organizations worldwide revealed that they perceive customer experience (CX) as a primary competitive differentiator. During the survey, 45 percent of organizations stated that they thought artificial intelligence solutions will reshape their customer experience (CX) in the next five years.

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).

Discover how GlobalData’s competitive intelligence tracking solutions provide businesses with the data they need to stay ahead in a competitive landscape. Read More

Competition is an important biotic interaction that influences survival and reproduction. While competition on ecological timescales has received great attention, little is known about competition on evolutionary timescales. Do competitive abilities change over hundreds of thousands to millions of years? Can we predict competitive outcomes using phenotypic traits? How much do traits that confer competitive advantage and competitive outcomes change? Here we show, using communities of encrusting marine bryozoans spanning more than 2 million years, that size is a significant determinant of overgrowth outcomes: colonies with larger zooids tend to overgrow colonies with smaller zooids. We also detected temporally coordinated changes in average zooid sizes, suggesting that different species responded to a common external driver. Although species-specific average zooid sizes change over evolutionary timescales, species-specific competitive abilities seem relatively stable, suggesting that traits other than zooid size also control overgrowth outcomes and/or that evolutionary constraints are involved.

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

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.

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 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.

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.

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 competitive marketing software market 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 rising adoption of cloud-based solutions offers scalability and cost-effectiveness, attracting both SMEs seeking efficient marketing tools and large enterprises needing comprehensive competitive intelligence. Furthermore, the evolving digital marketing landscape, characterized by increasing competition and sophisticated customer behavior, necessitates sophisticated tools for market analysis, keyword research, competitor tracking, and performance monitoring. The market is segmented by application (SMEs and large enterprises) and type (cloud-based and on-premises), with cloud-based solutions dominating due to their flexibility and accessibility. Geographical distribution sees North America and Europe as leading regions, reflecting the higher adoption rates of advanced marketing technologies in these developed markets. However, rapid growth is expected in Asia-Pacific regions driven by increasing digitalization and expanding business activity. While the market presents significant opportunities, challenges remain. High initial investment costs for some enterprise-grade solutions, coupled with the need for specialized expertise to effectively utilize these tools, could hinder wider adoption, particularly among SMEs. Data security and privacy concerns also represent potential restraints, necessitating robust security measures from software providers. The competitive landscape is dynamic, with established players like SEMrush, Ahrefs, and Moz Pro facing competition from emerging players. Successful players will need to focus on innovation, continuous improvement of their analytical capabilities, seamless integration with existing marketing technology stacks, and competitive pricing to maintain market share and attract new customers. Ultimately, the market's future hinges on the continued digital transformation of businesses and the ongoing need for effective competitive intelligence gathering.

The competitive analysis of industry rivals reveals a dynamic landscape with established players holding significant market share. BuiltWith, WooRank, SEMrush, and Google dominate the market, offering comprehensive solutions for website analytics, SEO, and digital marketing. These companies have robust technological capabilities, established customer bases, and strong brand recognition. Emerging rivals, such as SpyFu, Owletter, SimilarWeb, Moz, SunTec Data, and TrendSource, are gaining traction by specializing in specific niches or offering innovative features. They are actively developing cutting-edge technologies, targeted analytics, and tailored solutions to meet evolving customer needs. The competitive landscape is expected to remain fluid, with ongoing innovations and strategic partnerships shaping market dynamics. As companies strive to differentiate themselves and gain market share, the battle for supremacy will continue to intensify.

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?

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.

1. Theory indicates that competing species coexist in a community when intraspecific competition is stronger than interspecific competition. When body size determines the outcome of competitive interactions between individuals, coexistence depends also on how resource use and the ability to compete for these resources change with body size. Testing coexistence theory in size-structured communities, therefore, requires disentangling the effects of size-dependent competitive abilities and niche shifts.

2. Here, we tested the hypothesis that the evolution of species and size-dependent competitive asymmetries increased the likelihood of coexistence between interacting species.

3. We experimentally estimated the effects of size-dependent competitive interactions on somatic growth rates of two interacting fish species, Trinidadian guppies (Poecilia reticulata) and killifish (Rivulus hartii). We controlled for the effects of size-dependent changes in the niche at two competitive settings representing the early (allopatric) and late (sympatric) evolutionary stages of a killifish-guppy community. We fitted the growth data to a model that incorporates species and size-dependent competitive asymmetries to test whether changes in the competitive interactions across sizes increased the likelihood of species coexistence from allopatry to sympatry.

4. We found that guppies are competitively superior to killifish but were less so in sympatric populations. The decrease in the effects of interspecific competition on the fitness of killifish and increase in the interspecific effect on guppies’ fitness increased the likelihood that sympatric guppies and killifish will coexist. However, while the competitive asymmetries between the species changed consistently between allopatry and sympatry between drainages, the magnitude of the size-dependent competitive asymmetries varied between drainages.

5. These results demonstrate the importance of integrating evolution and trait-based interactions into the research on how species coexist.

Methods These data were collected from two surface competition experiments in the laboratory.

Learn more about Market Research Intellect's Aminoglycosides Competitive Market Report, valued at USD 2.3 billion in 2024, and set to grow to USD 3.5 billion by 2033 with a CAGR of 5.2% (2026-2033).

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.

Austria scored 76.61 points out of 100 on the 2019 Global Competitiveness Report published by the World Economic Forum. This dataset provides the latest reported value for - Austria Competitiveness Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Background: House mice are commensal animals with a nearly global distribution, structured into well-differentiated local populations. Besides genetic differences between the populations, they have also diverged behaviorally over time, whereby it remains open how fast general behavioral characteristics can change. Here we study the competitive potential of two very recently separated populations of the Western house mouse (Mus musculus domesticus) by using two different approaches – one under controlled cage conditions, the other under more natural conditions in enclosures mimicking a secondary encounter condition.

Results: We observe a clear bias in the competitive ability towards one of the populations for both tests. The measured behavioral bias is also reflected in the number of hybrid offspring produced in the enclosures.

Conclusion: Our data suggest that key behavioral characteristics with a direct influence on relative fitness can quickly change during the evolution of populations. It seems possible that the colonization situation in Western Europe, with a rapid spread of the mice after their arrival, would have favored more competitive populations on the expansion front. The study shows the possible impact of behavioral changes on the evolution of populations.