ACM Transactions on Economics and Computation

Scope & Guideline

Advancing Knowledge at the Nexus of Economics and Computation

Introduction

Explore the comprehensive scope of ACM Transactions on Economics and Computation through our detailed guidelines, including its aims and scope. Stay updated with trending and emerging topics, and delve into declining areas to understand shifts in academic interest. Our guidelines also showcase highly cited topics, featuring influential research making a significant impact. Additionally, discover the latest published papers and those with high citation counts, offering a snapshot of current scholarly conversations. Use these guidelines to explore ACM Transactions on Economics and Computation in depth and align your research initiatives with current academic trends.
LanguageEnglish
ISSN2167-8375
PublisherASSOC COMPUTING MACHINERY
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 2013 to 2024
AbbreviationACM T ECON COMPUT / ACM Trans. Econ. Comput.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address1601 Broadway, 10th Floor, NEW YORK, NY 10019-7434

Aims and Scopes

ACM Transactions on Economics and Computation focuses on the intersection of economics, computation, and game theory, emphasizing the design and analysis of algorithms that address economic problems. The journal seeks to publish innovative research that leverages computational techniques to solve complex economic and game-theoretic issues.
  1. Algorithmic Game Theory:
    Research related to the design and analysis of algorithms in strategic settings, including auction design, mechanism design, and equilibrium computation.
  2. Market Design and Mechanism Design:
    Studies focusing on the creation of efficient and fair mechanisms for various market scenarios, including auctions, matching markets, and public goods allocation.
  3. Computational Economics:
    Exploration of economic models through computational methods, addressing issues like resource allocation, pricing strategies, and the dynamics of economic systems.
  4. Fairness and Efficiency in Allocation Problems:
    Investigations into the balance between fairness and efficiency in resource allocation, including topics like envy-freeness, proportionality, and stability.
  5. Network Economics:
    Examination of economic behaviors and outcomes in networked environments, including congestion games, social networks, and decentralized systems.
Recent trends in publications within ACM Transactions on Economics and Computation reveal a shift towards more nuanced and computationally intensive themes. This section outlines the emerging topics that are gaining traction in the journal's focus.
  1. Blockchain and Decentralized Systems:
    Recent studies highlight the growing importance of blockchain technology and decentralized systems in economic contexts, particularly in areas like reward sharing and market dynamics.
  2. Online Algorithms and Dynamic Matching:
    The focus on online algorithms, especially in task assignment and market matching scenarios, indicates a trend towards addressing real-time decision-making in uncertain environments.
  3. Fairness in Algorithmic Design:
    An increasing emphasis on fairness in algorithmic processes reflects a broader societal concern for equitable outcomes, particularly in resource allocation and market mechanisms.
  4. Price of Anarchy and Efficiency Analysis:
    Research exploring the Price of Anarchy in various economic settings suggests a growing interest in the efficiency of decentralized systems and their implications for economic outcomes.
  5. Learning and Adaptive Mechanisms:
    Emerging themes related to learning frameworks in economic settings, including adaptive mechanisms and the use of learning algorithms to improve decision-making in dynamic environments.

Declining or Waning

While ACM Transactions on Economics and Computation has consistently focused on various aspects of economics and computation, certain themes appear to be declining in prominence based on recent publications. This section highlights the areas that are receiving less attention over time.
  1. Traditional Game Theory without Computational Insights:
    There seems to be a reduced focus on classical game theory concepts that do not incorporate computational methods or algorithmic perspectives, indicating a shift towards more applied computational approaches.
  2. Static Economic Models:
    Research involving static economic models, which do not consider dynamic or computational factors, appears to be waning as the journal emphasizes more dynamic and algorithm-driven analyses.
  3. Single-Agent Decision Problems:
    Topics centered solely on individual decision-making without considering strategic interactions or multi-agent frameworks are becoming less prominent, as the journal increasingly favors studies involving multiple agents and their interactions.

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