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Journal articles on the topic 'Market structure'

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Published: 4 June 2021
Last updated: 25 May 2024

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1

Lee, In Ho, and Robin Mason. "Market structure in congestible markets." European Economic Review 45, no. 4-6 (May 2001): 809–18. http://dx.doi.org/10.1016/s0014-2921(01)00130-1.

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2

Aissaoui, Rachida, and Robert R. Wiggins. "Market Structure and Market Growth in Restricted Demand Markets." Academy of Management Proceedings 2012, no. 1 (July 2012): 13997. http://dx.doi.org/10.5465/ambpp.2012.13997abstract.

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3

Schmidt, Stephen. "Market structure and market outcomes in deregulated rail freight markets." International Journal of Industrial Organization 19, no. 1-2 (January 2001): 99–131. http://dx.doi.org/10.1016/s0167-7187(99)00009-0.

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4

Russell, Gary J., and Ruth N. Bolton. "Implications of Market Structure for Elasticity Structure." Journal of Marketing Research 25, no. 3 (August 1988): 229–41. http://dx.doi.org/10.1177/002224378802500301.

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Though considerable attention has been given to market structure, little research has been done on the relationship between market structure and elasticity structure. The authors develop and partially test the aggregate constant ratio elasticity pattern (ACREP), a parsimonious marketing mix elasticity model that describes the elasticity structure of submarkets characterized by a proportional-draw market share mechanism. An analysis of the brand price elasticities in nine markets (covering six product categories) suggests that the ACREP model is a robust approach for predicting the elasticity structure of submarkets within a nondurable product class. The underlying ACREP parameters, measuring consumer propensity to switch within and between submarkets, show systematic relationships with structural characteristics of the product markets.
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5

LIUBKINA, Olena, and Vitalii IHNATIUK. "TRANSACTION COSTS OF TRADING IN ORGANIZED STOCK MARKETS: STRUCTURE AND IMPLICATIONS FOR MARKET EFFICIENCY." Herald of Khmelnytskyi National University. Economic sciences 320, no. 4 (June 29, 2023): 60–71. http://dx.doi.org/10.31891/2307-5740-2023-320-4-9.

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The article substantiates the origin of transaction costs of stock trading from the point of view of the microstructure of the stock market. The article is devoted to the problem of improving the efficiency of decision-making in the field of portfolio investment, in particular in terms of reducing the cost of conducting operations. The object is the microstructure of the stock market, which allows to study in detail the process of making transactions with securities. The origin of transaction costs of stock trading was determined from the point of view of the microstructure of the market: as an appropriate fee for urgency and certainty in the purchase and sale process; as the premium for participation in market trading and conducting the exchange to stimulate potential counterparties; as the result of potential discrepancy in terms of information that the participants of exchange operations have. The classification of transaction costs is systematized according to various criteria: clarity of identification and assessment (explicit – commissions of intermediaries and the stock exchange, taxes, etc.and implicit – costs of spread, timeliness, market impact, missed opportunities); according to the reason for the various transaction costs (taxes, commissions, transaction execution costs and costs of missed opportunities). It is established that implicit costs add a significant level of uncertainty to the investment decision-making process, and therefore their evaluation and control is a priority issue for the investment entity. The main approaches to quantification of implicit transaction costs – missed opportunity costs, spread costs, and market impact costs-are summarized. Prospects for improving the tools for estimating transaction costs of operations in organized stock markets are determined.
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6

Conroy, Robert M., and Robert L. Winkler. "Market structure." Journal of Banking & Finance 10, no. 1 (March 1986): 21–36. http://dx.doi.org/10.1016/0378-4266(86)90018-x.

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7

Hirschey, Mark. "Market Structure and Market Value." Journal of Business 58, no. 1 (January 1985): 89. http://dx.doi.org/10.1086/296284.

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8

Francois, Joseph, and Ian Wooton. "Market Structure and Market Access." World Economy 33, no. 7 (June 1, 2010): 873–93. http://dx.doi.org/10.1111/j.1467-9701.2010.01234.x.

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9

Martin, Stephen. "Market Structure and Market Performance." Review of Industrial Organization 40, no. 2 (February 3, 2012): 87–108. http://dx.doi.org/10.1007/s11151-012-9338-8.

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10

Jolly, Curtis M. "Market Structure of Food Markets in Haiti." Journal of Food Products Marketing 5, no. 1 (October 16, 1998): 67–82. http://dx.doi.org/10.1300/j038v05n01_07.

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11

Singh, Shikha, and Mandira Sarma. "Financial Structure and Stability: An Empirical Exploration." Journal of Central Banking Theory and Practice 9, s1 (July 1, 2020): 9–32. http://dx.doi.org/10.2478/jcbtp-2020-0021.

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AbstractThis paper attempts to investigate empirically whether financial and macroeconomic stability of economies are significantly affected by the structure of their financial systems, viz., bank-based and market-based structures. Using panel data estimations based on data from 82 countries for the period of 1996-2012, we find that in general, bank-based financial system contributes significantly to instability of the financial sectors and currency market. We also find some evidence that within the bank-based structure, higher presence of foreign banks is positively associated with currency market pressure. Additionally, the results show that the choice of bank-based versus market-based financial structure is important for low income countries. Banks in low income countries contribute to exchange market pressures whereas stock markets leads to reduction in such pressure. In high income countries, stock markets do not significantly affect banking and currency market instability.
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12

Bennett, Paul, and Li Wei. "Market structure, fragmentation, and market quality." Journal of Financial Markets 9, no. 1 (February 2006): 49–78. http://dx.doi.org/10.1016/j.finmar.2005.12.001.

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13

Bugamelli, Matteo, and Roberto Tedeschi. "Pricing-to-Market and Market Structure." Oxford Bulletin of Economics and Statistics 70, no. 2 (April 2008): 155–80. http://dx.doi.org/10.1111/j.1468-0084.2007.00493.x.

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14

Polk, Charles, and Evan Schulman. "Market Structure Matters." Journal of Trading 7, no. 1 (December 2011): 15–17. http://dx.doi.org/10.3905/jot.2011.7.1.015.

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15

Polk, Charles, and Evan Schulman. "Market Structure Matters." Journal of Trading 7, no. 1 (December 31, 2011): 15–17. http://dx.doi.org/10.3905/jot.2012.7.1.015.

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16

Kultti, K. "About market structure." Review of Economic Dynamics 6, no. 1 (January 2003): 240–51. http://dx.doi.org/10.1016/s1094-2025(02)00016-9.

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17

NORGAARD, JULIA R., HAROLD J. WALBERT, and R. AUGUST HARDY. "Shadow markets and hierarchies: comparing and modeling networks in the Dark Net." Journal of Institutional Economics 14, no. 5 (January 14, 2018): 877–99. http://dx.doi.org/10.1017/s1744137417000613.

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AbstractThis paper analyzes the determinants of network structure, as measured by hierarchy and monopolization, by examining various black market networks. We examine structures of networks on the Internet Dark Net (Virtual) and compare it to network structures of traditional black markets (Ground), using agent-based modeling. The purpose of modeling these two different types of illicit markets is to understand the network structure that emerges from the interactions of the agents in each environment. Traditional black markets are relatively hierarchical, with high degree and high betweenness. We compare the density and average length of the shortest path of the simulated Ground black market networks with our simulated Virtual network. We find that hierarchy and monopolization tendencies in networks are products of different transaction costs and information asymmetries. The Internet is an effective way to lower multiple aspects of network structure. We observe that the network structure surrounding the interactions in the Virtual black market is less hierarchical and slightly more monopolistic than the network structure of the Ground market.
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18

Young, David P. T. "Modeling Media Markets: How Important is Market Structure?" Journal of Media Economics 13, no. 1 (January 2000): 27–44. http://dx.doi.org/10.1207/s15327736me1301_3.

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19

Fang, Hanming, and Zenan Wu. "Multidimensional private information, market structure, and insurance markets." RAND Journal of Economics 49, no. 3 (August 24, 2018): 751–87. http://dx.doi.org/10.1111/1756-2171.12251.

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20

Alexandrova-Kabadjova, Biliana, Edward Tsang, and Andreas Krause. "Market structure and information in payment card markets." International Journal of Automation and Computing 8, no. 3 (August 2011): 364–70. http://dx.doi.org/10.1007/s11633-011-0593-1.

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21

Rasda, M., and M. Saleh S. Ali. "Mattirowalie Traditional Market Structure in Barru Regency." Advances in Environmental Biology 15, no. 2 (February 1, 2021): 1–5. http://dx.doi.org/10.22587/aeb.2021.15.2.1.

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Market structure is information about business behavior and market performance which is explained through market conditions. This study aims to determine the structure of traditional markets in Barru Regency, South Sulawesi Province by looking at the distribution channels of products that occur at the level of traders involved in trading activities in the traditional markets of Barru Regency. The results of research in the field show that in the traditional market Mattirowalie, Barru Regency, South Sulawesi Province has a market structure with a level of distribution network for agricultural products. Initially these goods were obtained partly from producer farmers (Barru seller farmers), partly from wholesalers (agents) who originating from other districts enter into collectors and retailers in the traditional market Mattirowalie, Barru Regency, especially wholesalers (agents) of rice and vegetables, then collectors after obtaining goods sell their merchandise to local retailers, then retailers sell or distribute their merchandise to local retailers. buyers / consumers in the traditional markets of Barru Regency.
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22

Kumar, Ronald Ravinesh, and Peter J. Stauvermann. "International Borrowing and Lending in the Presence of Oligopolistic Competition." Journal of Risk and Financial Management 16, no. 8 (July 28, 2023): 357. http://dx.doi.org/10.3390/jrfm16080357.

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This paper examines the implications of imperfect competition in a two-country framework where a single good is produced. Using an overlapping generation model, we analyze the effects of market structures. Specifically, one country is assumed to operate under a perfectly competitive market structure, while the other country operates under an oligopolistic market structure. Our analysis reveals that the differences in factor prices between the two countries when they are in autarky lead to intergenerational trade once their capital markets are integrated. A key finding is that the country with an oligopolistic market structure becomes a lending country, while the country with a competitive market structure becomes a borrowing country. Furthermore, we find that the country with an oligopolistic market structure, serving as a lender, experiences a current account surplus, while the country with a perfectly competitive market structure, acting as a debtor, incurs a current account deficit.
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23

Alfaihani, Sara, Oleg Badunenko, and Shabbar Jaffry. "Market size and market structure in banking." Journal of International Financial Markets, Institutions and Money 72 (May 2021): 101342. http://dx.doi.org/10.1016/j.intfin.2021.101342.

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24

Farrow, Scott. "Flexible Manufacturing: Market Structure and Market Failure." Journal of Policy Analysis and Management 4, no. 4 (1985): 583. http://dx.doi.org/10.2307/3323756.

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25

Elberfeld, Walter, and Georg Götz. "Market Size, Technology Choice, and Market Structure." German Economic Review 3, no. 1 (February 1, 2002): 25–41. http://dx.doi.org/10.1111/1468-0475.00050.

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Abstract We introduce technology choice into a model of monopolistic competition and analyze the structural effects of changes in market size. A larger market leads to the adoption of a large-scale technology. If a technology switch occurs, the number of firms decreases, and a rationalizing effect arises: individual and aggregate output increases; prices fall. This need not benefit consumers since a technology switch is associated with a decrease in product variety.
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26

Larue, Bruno, and Harvey E. Lapan. "Market Structure, Quality and World Wheat Market." Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie 40, no. 2 (July 1992): 311–28. http://dx.doi.org/10.1111/j.1744-7976.1992.tb03696.x.

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27

Sun, Baowen, Wenjun Jing, Xuankai Zhao, and Yi He. "Research on market power and market structure." International Journal of Crowd Science 1, no. 3 (September 4, 2017): 210–22. http://dx.doi.org/10.1108/ijcs-08-2017-0009.

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Purpose This paper aims to clear whether the monopoly structure of the internet industry has produced market power and discussed the welfare change of the internet industry monopoly. Design/methodology/approach By using new empirical industrial organization methods and taking the e-commerce market as an example, the authors measured market power and economies of scale of the internet platform companies. Findings Internet platform enterprises have formed scale economy, but it has not had market power, and the industry still maintains high levels of competition; also, the emergence of large enterprises may increase the welfare of consumers. Originality/value The conclusion of this paper clarified actual competition status of internet industry and provided a new foothold for regulation and ideas for the traditional industry to crack the Marshall Conflict.
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28

Chung, Kee H., Jangkoo Kang, and Joon-Seok Kim. "Tick size, market structure, and market quality." Review of Quantitative Finance and Accounting 36, no. 1 (March 17, 2010): 57–81. http://dx.doi.org/10.1007/s11156-010-0171-6.

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29

Markusen, James, and Frank Stähler. "Endogenous market structure and foreign market entry." Review of World Economics 147, no. 2 (December 19, 2010): 195–215. http://dx.doi.org/10.1007/s10290-010-0085-3.

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30

Tribó, Josep A. "Inventories, financial structure and market structure." International Journal of Production Economics 71, no. 1-3 (May 2001): 79–89. http://dx.doi.org/10.1016/s0925-5273(00)00107-9.

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31

Poyrazoglu, Gokturk. "Determination of Price Zones during Transition from Uniform to Zonal Electricity Market: A Case Study for Turkey." Energies 14, no. 4 (February 15, 2021): 1014. http://dx.doi.org/10.3390/en14041014.

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In the electricity market, different pricing models can be applied to increase market competitiveness. Different electricity systems use different market structures. Uniform marginal pricing, zonal marginal pricing, and nodal marginal pricing methods are commonly used market structures. For markets wishing to move from a uniform pricing structure to a more competitive zonal pricing structure, the determination of price zones is critical for achieving a competitive market that generates accurate price signals. Three different pricing zone detection algorithms are analyzed in this paper including the k-means clustering and queen/rook spatially constraint clustering. Finally, the results of a case study for the Turkish electricity system are shared to compare each method.
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32

Zhou, Ziqi. "Market Competition and Monopoly Power: Insights from Oligopoly Structure." Highlights in Business, Economics and Management 24 (January 22, 2024): 188–95. http://dx.doi.org/10.54097/vvg6pr04.

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In this context, the primary objective is to conduct a comprehensive investigation into the real-world implementation and impact of distinct economic models. Through the literature analysis, the paper sets out to examine product competition and corporate conduct within two contemporary markets. Through this meticulous approach, the aim is to unveil the nuanced distinctions and intriguing parallels that exist between Oligopoly and Oligopoly Competitive Markets. First, broad definitions and classifications of both oligopolistic and oligopolistically competitive markets are considered. Second, the subtle differences between the two markets will be shown through specific oligopoly examples (such as OPEC and mobile phone market). Third, detailed analysis of the features of the similarity between the two markets. Finally, the study found that, as two different market structures, the oligopoly market and the oligopoly competition market have completely different gaps in market control and price stability, but it is undeniable that the two markets have the same driving force in innovation.
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33

Fahrizal, Fahrizal, Mustafa Mustafa, and Romano Romano. "Analysis of Nutmeg Market Structure in South Aceh District." International Journal of Multicultural and Multireligious Understanding 6, no. 5 (November 29, 2019): 950. http://dx.doi.org/10.18415/ijmmu.v6i2.1165.

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Market structure can affect performance and behavior in a market. This research aim to analyze the nutmeg market structure in South Aceh District. Indonesia. By looking at the level of competition, market concentration and barriers to market entry. The results of a qualitative study of nutmeg market structure are classified as oligopoly markets while quantitatively by looking at market share, market concentration and market entry barriers from the results obtained by the market are highly concentrated so it is very difficult to enter to the nutmeg market by new traders.
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34

Smyrlakis, Nikolaos, Leopold Summerer, and Loretta Latronico. "Innovation Dynamics in a Monopsony Structure." International Journal of Space Technology Management and Innovation 1, no. 1 (January 2011): 24–43. http://dx.doi.org/10.4018/ijstmi.2011010102.

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Innovation is a widely recognised driver of markets for economic growth and technological progress. This paper investigates the innovation dynamics in a monopsony market with a governmental monopsonist. The research is based on an agent-based model published for a traditional, competitive oligopoly market structure and explains aspects of innovation dynamics, such as how innovation is created, how the strategies of imitation and innovation pay off, the diffusion of both strategies and factors that influence them. Following the Schumpeterian concept of emerging innovation as a relational good, the model includes a dynamical component of strategy changes for sellers, which depends on the success of the strategy of those with whom they are exchanging information. For the present work, the structure of this model has been adapted to represent the specific buyer-power situation of monopsony markets. By changing the connectivity of the network between buyers and sellers and by combining all buyers into one, the network is transformed into one that models a monopsony market. In simplified terms, part of the European space market has been described as such a monopsonistic market with a governmental quasi-monopsonist. The paper investigates how innovation dynamics change in such a market.
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35

Aspembitova, Ayana T., Ling Feng, and Lock Yue Chew. "Behavioral structure of users in cryptocurrency market." PLOS ONE 16, no. 1 (January 12, 2021): e0242600. http://dx.doi.org/10.1371/journal.pone.0242600.

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Human behavior as they engaged in financial activities is intimately connected to the observed market dynamics. Despite many existing theories and studies on the fundamental motivations of the behavior of humans in financial systems, there is still limited empirical deduction of the behavioral compositions of the financial agents from a detailed market analysis. Blockchain technology has provided an avenue for the latter investigation with its voluminous data and its transparency of financial transactions. It has enabled us to perform empirical inference on the behavioral patterns of users in the market, which we explore in the bitcoin and ethereum cryptocurrency markets. In our study, we first determine various properties of the bitcoin and ethereum users by a temporal complex network analysis. After which, we develop methodology by combining k-means clustering and Support Vector Machines to derive behavioral types of users in the two cryptocurrency markets. Interestingly, we found four distinct strategies that are common in both markets: optimists, pessimists, positive traders and negative traders. The composition of user behavior is remarkably different between the bitcoin and ethereum market during periods of local price fluctuations and large systemic events. We observe that bitcoin (ethereum) users tend to take a short-term (long-term) view of the market during the local events. For the large systemic events, ethereum (bitcoin) users are found to consistently display a greater sense of pessimism (optimism) towards the future of the market.
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36

Lagos, Ricardo, and Guillaume Rocheteau. "Search in Asset Markets: Market Structure, Liquidity, and Welfare." American Economic Review 97, no. 2 (April 1, 2007): 198–202. http://dx.doi.org/10.1257/aer.97.2.198.

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37

Beck, Jason, Frank Scott, and Aaron Yelowitz. "Concentration and Market Structure in Local Real Estate Markets." Real Estate Economics 40, no. 3 (January 11, 2012): 422–60. http://dx.doi.org/10.1111/j.1540-6229.2011.00322.x.

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38

Etro, Federico. "Endogenous market structures and the optimal financial structure." Canadian Journal of Economics/Revue canadienne d'économique 43, no. 4 (October 18, 2010): 1333–52. http://dx.doi.org/10.1111/j.1540-5982.2010.01616.x.

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39

Kim, Usic. "Duality Structure in Market." Society and Theory 10 (May 31, 2007): 263. http://dx.doi.org/10.17209/st.2007.05.10.263.

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40

Sung,Tae-Kyung. "Market Structure and Standardization." Management & Information Systems Review 33, no. 4 (November 2014): 63–75. http://dx.doi.org/10.29214/damis.2014.33.4.005.

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41

GROSSMAN, SANFORD J., and MERTON H. MILLER. "Liquidity and Market Structure." Journal of Finance 43, no. 3 (July 1988): 617–33. http://dx.doi.org/10.1111/j.1540-6261.1988.tb04594.x.

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42

Tribe, Keith. "Market Structure and Equilibrium." History of Political Economy 48, no. 3 (September 2016): 547–49. http://dx.doi.org/10.1215/00182702-3638767.

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43

Mazanec, Josef A. "Neural market structure analysis." European Journal of Marketing 35, no. 7/8 (August 2001): 894–916. http://dx.doi.org/10.1108/eum0000000005730.

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44

Kavajecz, Kenneth A., and Elizabeth R. Odders-White. "Volatility and market structure." Journal of Financial Markets 4, no. 4 (October 2001): 359–84. http://dx.doi.org/10.1016/s1386-4181(01)00013-1.

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45

Neary, J. Peter. "Globalization and Market Structure." Journal of the European Economic Association 1, no. 2-3 (May 1, 2003): 245–71. http://dx.doi.org/10.1162/154247603322390928.

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46

Sutton, John. "Technology and market structure." European Economic Review 40, no. 3-5 (April 1996): 511–30. http://dx.doi.org/10.1016/0014-2921(95)00065-8.

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47

Rosenau, Pauline Vaillancourt. "Market Structure and Performance." Journal of Health & Social Policy 13, no. 1 (April 2001): 41–72. http://dx.doi.org/10.1300/j045v13n01_03.

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48

Grimm, Veronika, Frank Riedel, and Elmar Wolfstetter. "Implementing efficient market structure." Review of Economic Design 7, no. 4 (February 1, 2003): 443–63. http://dx.doi.org/10.1007/s100580300087.

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49

Raider, Holly J. "Market Structure and Innovation." Social Science Research 27, no. 1 (March 1998): 1–21. http://dx.doi.org/10.1006/ssre.1997.0608.

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50

Blank, Steven C. "World dairy market structure." Agribusiness 2, no. 2 (1986): 183–98. http://dx.doi.org/10.1002/1520-6297(198622)2:2<183::aid-agr2720020204>3.0.co;2-#.

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