scholarly journals An Agent-Based Computational Economics Approach To Technology Adoption Timing And The Emergence Of Dominant Designs

2011 ◽  
Vol 9 (2) ◽  
Author(s):  
Alfred G. Warner ◽  
Ozgun Caliskan-Demirag
Keyword(s):  
Environmental Factors ◽  
Computational Economics ◽  
Font Size ◽  
Agent Based ◽  
Compelling Reason ◽  
Dominant Designs ◽  
Dominant Design ◽  
Adoption Decisions ◽  
Key Resources ◽  
Broad Scale

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt; mso-pagination: none;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">Dominant technology designs emerge as the sum of adoption decisions across many firms. We take the position that if certain factors drive adoption by an individual firm, then in the aggregate, they may also illuminate the conditions under which a particular dominant design might emerge. In order to show this, we develop an agent-based computational model to explore linkages between firm specific, industry, and environmental factors, such as knowledge overlap, firm size, environmental uncertainty, and the scope of returns to adoption. We show that the significance of these factors varies with the stage of the technology contest. Early in the process, firms that have a compelling reason to adopt (such as to avoid obsolescence of key resources) choose to enter to create momentum for a particular approach. Other firms, due to indifference, inability or uncertainty, may defer until outcomes are clearer or choose not to adopt at all. More importantly, what constitutes a compelling reason for adoption varies with the nature of the firms that lead as innovators and the external environmental factors. On a broad scale, strong regularities in adoption timing and characteristics of technology winners emerge from the analysis.</span></span></p>

scholarly journals Agent-based computational economics

Scholarpedia ◽  
2007 ◽  
Vol 2 (2) ◽  
pp. 1970 ◽  
Author(s):  
Leigh Tesfatsion
Keyword(s):  
Computational Economics ◽  
Agent Based

Computational Economics in the Era of Natural Computationalism

2018 ◽  
Author(s):  
Shu-Heng Chen ◽  
Mak Kaboudan ◽  
Ye-Rong Du
Keyword(s):  
General Equilibrium ◽  
Rational Expectations ◽  
Computational Economics ◽  
Algorithmic Trading ◽  
Neural Computing ◽  
Computing Systems ◽  
Agent Based ◽  
Numerical Aspect ◽  
Nature Inspired Intelligence

After a brief review of natural computationalism, this introductory chapter presents a new skeleton of computational economics and finance (CEF) along with an overview of the handbook. It begins with a conventional pursuit focusing on the algorithmic or numerical aspect of CEF such as computational efforts devoted to rational expectations, (dynamic) general equilibrium, and volatility. It then moves toward an automata- or organism-based perspective of CEF, involving nature-inspired intelligence, algorithmic trading, automated markets, network- and agent-based computing, and neural computing. As an alternative way to introduce this novel skeleton, the chapter starts with a view of computation or computing, addressing what computational economics intends to compute and what kinds of economics make computation so hard, and then it turns to a view of computing systems in which the Walrasian kind of computational economics is replaced by the Wolframian kind due to computational irreducibility.

scholarly journals Spatiotemporal Variations in Mercury Bioaccumulation at Fine and Broad Scales for Two Freshwater Sport Fishes

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1625 ◽  
Author(s):  
Shyam Thomas ◽  
Stephanie Melles ◽  
Satyendra Bhavsar
Keyword(s):  
Climate Change ◽  
Environmental Factors ◽  
Northern Pike ◽  
Space Time ◽  
Fine Scale ◽  
Spatiotemporal Variations ◽  
Scale Models ◽  
Change Context ◽  
Mercury Bioaccumulation ◽  
Broad Scale

Bioaccumulation of mercury in sport fish is a complex process that varies in space and time. Both large-scale climatic as well as fine-scale environmental factors are drivers of these space-time variations. In this study, we avail a long-running monitoring program from Ontario, Canada to better understand spatiotemporal variations in fish mercury bioaccumulation at two distinct scales. Focusing on two common large-bodied sport fishes (Walleye and Northern Pike), the data were analyzed at fine- and broad-scales, where fine-scale implies variations in bioaccumulation at waterbody- and year-level and broad-scale captures variations across 3 latitudinal zones (~5° each) and eight time periods (~5-year each). A series of linear mixed-effects models (LMEMs) were employed to capture the spatial, temporal and spatiotemporal variations in mercury bioaccumulation. Fine-scale models were overall better fit than broad-scale models suggesting environmental factors operating at the waterbody-level and annual climatic conditions matter most. Moreover, for both scales, the space time interaction explained most of the variation. The random slopes from the best-fitting broad-scale model were used to define a bioaccumulation index that captures trends within a climate change context. The broad-scale trends suggests of multiple and potentially conflicting climate-driven mechanisms. Interestingly, broad-scale temporal trends showed contrasting bioaccumulation patterns—increasing in Northern Pike and decreasing in Walleye, thus suggesting species-specific ecological differences also matter. Overall, by taking a scale-specific approach, the study highlights the overwhelming influence of fine-scale variations and their interactions on mercury bioaccumulation; while at broad-scale the mercury bioaccumulation trends are summarized within a climate change context.

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