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Journal articles on the topic 'Pricing'

Author: Grafiati

Published: 4 June 2021

Last updated: 14 September 2024

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1

Wang, Xiao-Yong. "Effect of Carbon Pricing on Optimal Mix Design of Sustainable High-Strength Concrete." Sustainability 11, no. 20 (October 21, 2019): 5827. http://dx.doi.org/10.3390/su11205827.

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Material cost and CO2 emissions are among the vital issues related to the sustainability of high-strength concrete. This research proposes a calculation procedure for the mix design of silica fume-blended high-strength concrete with an optimal total cost considering various carbon pricings. First, the material cost and CO2 emission cost are determined using concrete mixture and unit prices. Gene expression programming (GEP) is used to evaluate concrete mechanical and workability properties. Second, a genetic algorithm (GA) is used to search the optimal mixture, considering various constraints, such as design compressive strength constraint, design workability constraint, range constraints, ratio constraints, and concrete volume constraint. The optimization objective of the GA is the sum of the material cost and the cost of CO2 emissions. Third, illustrative examples are shown for designing various kinds of concrete. Five strength levels (from 95 to 115 MPa with steps of 5 MPa) and four carbon pricings (normal carbon pricing, zero carbon pricing, five-fold carbon pricings, and ten-fold carbon pricings) are considered. A total of 20 optimal mixtures are calculated. The optimal mixtures were found the same for the cases of normal CO2 pricing and zero CO2 pricing. Optimal mixtures with higher strengths are more sensitive to variation in carbon pricing. For five-fold CO2 pricing, the cement content of mixtures with higher strengths (105, 110, and 115 MPa) are lower than those of normal CO2 pricing. As the CO2 pricing increases from five-fold to ten-fold, for mixtures with a strength of 110 MPa, the cement content becomes lower. Summarily, the proposed method can be applied to the material design of sustainable high-strength concrete with low material cost and CO2 emissions.

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2

Saputra, Gani. "Pengaruh Pajak, Ukuran Perusahaan, Profitabilitas Terhadap Transfer Pricing Dengan Leverage Sebagai Variabel Moderasi (Stusi Empiris Perusahaan Manufaktur Sektor Makanan dan Minuman Tahun 2017-2021)." Jurnal Literasi Akuntansi 3, no. 1 (March 29, 2023): 10–21. http://dx.doi.org/10.55587/jla.v3i1.88.

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Purpose: This study aims to show the effect of tax, company size and profitability on transfer pricing with leverage as a moderating variable. The nature of this research is quantitative. Methot: The population in this study are food and beverage sub-sector manufacturing companies listed on the Indonesia Stock Exchange in 2017-2021 and there are 40 companies. The research sample used purposive sampling and obtained 15 companies. This research uses secondary data in the form of financial reports and company annual financial reports which are downloaded from www.idx.co.id and the website of each company that is the sample in this study. Data analysis using multiple linear analysis and moderate regression analysis. Finding: The results of this study indicate that taxes have a positive effect on transfer pricing. Company size has a positive effect on transfer pricing. Profitability has a positive effect on transfer pricing. Leverage can strengthen the positive effect of taxes on pricin transfers. Leverage can strengthen the positive influence of company size on transfer pricing. However, leverage cannot moderate the effect of profitability on transfer pricing.

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3

Murodova, Nargiza. "TOURISM PRICING STRATEGIES." European International Journal of Multidisciplinary Research and Management Studies 4, no. 4 (April 1, 2024): 216–22. http://dx.doi.org/10.55640/eijmrms-04-04-34.

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Tourism pricing strategies are vital for businesses in the travel and hospitality sector to maximize revenue, attract and retain customers, and stay competitive. These strategies range from value-based pricing, which relies on the perceived value to the customer, to dynamic pricing, adjusting costs in real-time based on market demand. Other approaches include discount pricing for off-peak periods, package deals offering combined services, psychological pricing to make costs seem more attractive, penetrationpricing to quickly gain market share, premium pricing for exclusive experiences, seasonal adjustments, cost-plus pricing to cover expenses and ensure profit, and geographical pricing to account for regional economic differences. Each strategy has its unique implications and is chosen based on the business’s goals, market conditions, and customer preferences.

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4

Zhang, Lihui, Huiyuan Liu, and Daniel (Jian) Sun. "COMPARISON AND OPTIMIZATION OF CORDON AND AREA PRICINGS FOR MANAGING TRAVEL DEMAND." TRANSPORT 29, no. 3 (May 28, 2014): 248–59. http://dx.doi.org/10.3846/16484142.2014.914970.

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This paper analyses both the cordon and area pricings from the perspective of travel demand management. Sensitivity analysis of various performance measures with respect to the toll rate and demand elastic parameter is performed on a virtual grid network. The analysis shows that cordon pricing mainly affects those trips with origins outside of the Central Business District and destinations inside, while area pricing imposes additional cost on the trips with either origins or destinations in the Central Business District. Though both pricing strategies are able to alleviate traffic congestion in the charging area, area pricing seems more effective, however, area pricing owns the risk to detour too much traffic and thus cause severe congestion to the network outside of the Central Business District. Following the sensitivity analysis, a unified framework is proposed to optimize the designs of the both pricing strategies, which is flexible to account for various practical concerns. The optimization models are formulated as mixed-integer nonlinear programs with complementarity constraints, and the solution procedure is composed of solving a series of nonlinear programs and mixed-integer linear programs. Results from the numerical examples are in line with the findings in the sensitivity analysis. Under the specific network settings, cordon pricing achieves the best system performance when the toll rate reaches the maximum allowed, while area pricing finds the optimal design scheme when the toll rate equals half of the maximum allowed.

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5

Lahiri, Atanu, Rajiv M. Dewan, and Marshall Freimer. "Pricing of Wireless Services: Service Pricing vs. Traffic Pricing." Information Systems Research 24, no. 2 (June 2013): 418–35. http://dx.doi.org/10.1287/isre.1120.0434.

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6

Clarabella, Angelina, and Edi Pranoto. "JURIDICIAL ANALYSIS OF TRANSFER PRICING DOCUMENTS IN RESPECT OF TAX AVOIDANCE FOR MULTINATIONAL COMPANIES." UNTAG Law Review 5, no. 2 (December 11, 2021): 49. http://dx.doi.org/10.56444/ulrev.v5i2.2657.

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<span class="fontstyle0">Essential principle within business world definitely would be maximizing profit and minimizing capital. Hence many companies would struggle<br />and develop their own ways to avoid taxes as much as they could. Tax avoidance which is taken illegally would disrupt government's revenue indeed. This paper discusses normative juridical approach to examine problems as 1. How does transfer pricing documents could help to diagnose tax avoidance practice within companies? 2. How to prevent the occurrence of transfer pricing's shortcomings? This would highlight the transfer pricing's existence to eliminate illegal practice of tax avoidance<br />within multinational companies and some methods to prevent the shortcomings of transfer pricing. The results shows that 1. transfer Pricing documents are useful for diagnosing tax avoidance practices in multinational companies through an analysis of fairness and business practice and 2. in order to prevent deficiencies in Transfer Pricing documents, the Government must establish a cooperative relationship<br />between companies and reliable tax administrations. such as through AEoI (Automatic Exchange of Information) between countries to encourage transfer pricing inspection processes in multinational companies. The government should conduct cooperative relationship between the companies and tax administration to encourage the process of transfer pricing examination within multinational companies in precise scheduled time frame. Fair and favorable assessment of business report is significant due to undermine unnecessary cost and improper result.<br />The competence and professional judgement from the Directorate General of Taxes are substantial.</span> <br /><br />

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7

Swart, Barbara. "Fair pricing, and pricing paradoxes." South African Journal of Economic and Management Sciences 19, no. 2 (May 13, 2016): 321–29. http://dx.doi.org/10.4102/sajems.v19i2.1136.

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The St Petersburg Paradox revolves round the determination of a fair price for playing the St Petersburg Game. According to the original formulation, the price for the game is infinite, and, therefore, paradoxical. Although the St Petersburg Paradox can be seen as concerning merely a game, Paul Samuelson (1977) calls it a “fascinating chapter in the history of ideas”, a chapter that gave rise to a considerable number of papers over more than 200 years involving fields such as probability theory and economics. In a paper in this journal, Vivian (2013) undertook a numerical investigation of the St Petersburg Game. In this paper, the central issue of the paradox is identified as that of fair (risk-neutral) pricing, which is fundamental in economics and finance and involves important concepts such as no arbitrage, discounting, and risk-neutral measures. The model for the St Petersburg Game as set out in this paper is new and analytical and resolves the so-called pricing paradox by applying a discounting procedure. In this framework, it is shown that there is in fact no infinite price paradox, and simple formulas for obtaining a finite price for the game are also provided.

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8

Wrede, Matthias. "Uniform Pricing Versus Mill Pricing." Journal of Regional Science 43, no. 1 (February 2003): 167–79. http://dx.doi.org/10.1111/1467-9787.00008.

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9

Johansson, Magnus, Niklas Hallberg, Andreas Hinterhuber, Mark Zbaracki, and Stephan Liozu. "Pricing strategies and pricing capabilities." Journal of Revenue and Pricing Management 11, no. 1 (December 28, 2011): 4–11. http://dx.doi.org/10.1057/rpm.2011.42.

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10

Rosenberg, Alan E. "Congestion Pricing or Monopoly Pricing?" Electricity Journal 13, no. 3 (April 2000): 33–41. http://dx.doi.org/10.1016/s1040-6190(00)00094-4.

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11

Chen, Zengjing, and Reg Kulperger. "Minimax pricing and Choquet pricing." Insurance: Mathematics and Economics 38, no. 3 (June 2006): 518–28. http://dx.doi.org/10.1016/j.insmatheco.2005.11.010.

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12

Sim, Kyoungbo. "Predatory Pricing with Personalized Pricing." International Telecommunications Policy Review 31, no. 2 (June 30, 2024): 87–109. http://dx.doi.org/10.37793/itpr.31.2.3.

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13

Jafri, Hasan Effendi, and Elia Mustikasari. "Pengaruh Perencaan Pajak, Tunnneling Incentive dan Aset Tidak Berwujud Terhadap Perilaku Transfer Pricing pada Perusahaan Manufaktur yang Memiliki Hubungan Istimewa yang Terdaftar di Bursa Efek Indonesia Periode 2014-2016." Berkala Akuntansi dan Keuangan Indonesia 3, no. 2 (December 31, 2018): 63. http://dx.doi.org/10.20473/baki.v3i2.9969.

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This aim of this research is testing effect of tax planning, incentive tunneling and intangible assets to transfer pricing behavior as measured by sales of related parties divided by sales of non-related parties. Tax planning is measured by Cash ETR, incentive tunneling measured by related party parties divided by total assets and intangible assets measured by total intangible assets divided by total sales. The population in this study is a manufacturing company listed on the Indnesia Stock Exchange 2014-2016. Determination of selected sample in research using purposive sampling method. Examination of influence of tax planning, incenntive tunnneling and intangible asset to behavior of transistor pricinng analyzed using softwareSPSS 20.0. The results showed that there were 134 companies meeting the sample criteria. Based on the results of multiple linear regression analysis with 5% significance, the results of this study concluded that: (1) tax planning affect the behavior of transfer pricing (2) incentive tunneling affect the transfer pricing behavior (3) intangible assets have no effect the transfer pricing behavior.

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14

(Buzzy) Basch, N. Bernard. "Pricing." Library Acquisitions: Practice & Theory 12, no. 2 (January 1988): 203–5. http://dx.doi.org/10.1016/0364-6408(88)90069-5.

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15

Yeoman, Dr Ian. "Pricing." Journal of Revenue and Pricing Management 6, no. 1 (March 2007): 1. http://dx.doi.org/10.1057/palgrave.rpm.5160062.

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16

Sinclair, Stuart. "Pricing." Journal of Business Strategy 14, no. 3 (March 1993): 16–19. http://dx.doi.org/10.1108/eb039554.

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17

Heenan, David A. "Pricing." Journal of Business Strategy 14, no. 6 (June 1993): 18–19. http://dx.doi.org/10.1108/eb039597.

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18

Sibbald, Barbara. "Fair pricing or pricing for profit?" Canadian Medical Association Journal 189, no. 20 (May 22, 2017): E733—E734. http://dx.doi.org/10.1503/cmaj.1095429.

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19

Shipley, David, and David Jobber. "Integrative Pricing via the Pricing Wheel." Industrial Marketing Management 30, no. 3 (April 2001): 301–14. http://dx.doi.org/10.1016/s0019-8501(99)00098-x.

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20

Miraldo, Marisa. "Reference pricing and firms’ pricing strategies." Journal of Health Economics 28, no. 1 (January 2009): 176–97. http://dx.doi.org/10.1016/j.jhealeco.2008.09.006.

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21

Liang, Ling, Lin Tian, Jiaping Xie, Jianhong Xu, and Weisi Zhang. "Optimal pricing model of car-sharing: market pricing or platform pricing." Industrial Management & Data Systems 121, no. 3 (February 1, 2021): 594–612. http://dx.doi.org/10.1108/imds-04-2020-0230.

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PurposeThe car-sharing market has entered the mature stage, and consumers' demand shows a diversified increasing trend. This paper considers two modes of operation and two pricing strategies, which are business-to-consumer and consumer-to-consumer modes, market pricing and platform pricing. Under these conditions, the platform's revenue-sharing ratio will be different. The purpose of this paper is to explore this research question, and seeks an optimal pricing mechanism that can achieve a win–win situation between platform and automobile manufacturer in the two market modes.Design/methodology/approachThe authors design different profit functions for platform under the two contexts. Of course, the platform's function is constrained to the manufacturer's function. By introducing a revenue-sharing contract a Stackelberg game model dominated by the platform is established and the equilibrium solutions under the two pricing models are derived.FindingsThe study found that even if only market pricing is executed, the scale of the car-sharing market will continue to expand. As the car-sharing market becomes more saturated, platform pricing is better for the automobile manufacturer; in most cases, the platform prefers platform pricing, but when the number of private cars is relatively small, if the cost of car operation and maintenance for the automobile manufacturer is lower or the revenue-sharing ratio of private cars is high, then market pricing will be more favorable to the platform.Practical implicationsWith the cross-border integration of car service platforms and the automobile manufacturing industry, the key to achieving win–win cooperation and sustainable development in the car-sharing market will converge on the question of how to design a suitable pricing mechanism and revenue-sharing method.Originality/valueAuthors have determined how a car-sharing platform achieves a win–win order pricing strategy with the manufacturer and private car owners, respectively. And authors combined the supply chain revenue-sharing contract with the car-sharing market to explore the application of the revenue-sharing contract in the sharing economy.

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22

Sastro, Wahyudi. "Analisis Lanjut Metode Beda Hingga Eksplisit Untuk Menentukan Harga Opsi." Unisda Journal of Mathematics and Computer Science (UJMC) 5, no. 01 (June 13, 2019): 41–46. http://dx.doi.org/10.52166/ujmc.v5i01.1302.

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Abstract. Explicit finite difference method is used to approximate a partial differential equation that is applied to determine the option pricing. The results of this study note that the calculation of option pricing using explicit finite difference method is negative when partition N ≥ 25 with a value of -2.21. Thus, the results of the calculation of option pricing are not convergent and away from the results of analyzing the option pricirng (Black-Scholes) solution. This is because one of the three probabilities Bj = 1- σ2j2Δt is negative, namely (-0.12) when j ≥ 12 with S ≥ 16.25 (in units). So this explicit finite difference method cannot be used to determine the option pricing. Keywords: Option Pricing, Explicit Finite Difference Method Abstrak. Metode beda hingga eksplisit digunakan untuk mengaproksimasi suatu persamaan diferensial pasial yang aplikasikan untuk menentukan harga opsi. Hasil penelitian ini diketahui bahwa perhitungan harga opsi dengan menggunakan metode beda hingga eksplisit bernilai negatif pada saat partisi N ≥ 25 dengan nilai -2,21. Dengan demikian, hasil perhitungan harga opsi tidak konvergen dan menjauhi hasil solusi analitik perhitungan harga opsi (Black-Scholes). Hal ini disebabkan karena salah satu ketiga probabilitas Bj = 1- σ2j2Δt yaitu bernilai negatif yaitu (-0.12) saat j ≥ 12 dengan S ≥ 16.25 (dalam satuan). Sehingga metode beda hingga eksplisit ini tidak dapat digunakan untuk menentukan harga opsi. Kata Kunci: Harga Opsi, Metode Beda Hingga Eksplisit.

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23

Balkish, Renata Violetta, Trijoko Prasetyo, and Basuki Wibowo. "ANALISIS HUBUNGAN MANAJEMEN PAJAK, SELISIH KURS DAN KEPEMILIKAN ASING DENGAN TRANSFER PRICING PERUSAHAAN." Jurnal Akuntansi dan Keuangan 25, no. 1 (January 20, 2020): 43–53. http://dx.doi.org/10.23960/jak.v25i1.194.

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Transfer pricing is the company's policy in determining the transfer price of related parties transaction. The purposed of this research is to get empirical evidence about the correlation of tax management, exchange rate, and foreign ownership with transfer pricing’s company. Independent variables used in this research are tax management, exchange rate and foreign ownership. Dependent variable of this research is transfer pricing. The population in this research are mining companies and miscellaneous industries listed on the Indonesia Stock Exchange (IDX) in 2014-2018. The method used for determining the sample is purposive sampling method.Sample consists of 67 observations. Data analysis using correlation pearson test with IBM SPSS Statistics 23 program as an analysis tool. The research results show that tax management has positive correlation with transfer pricing’s company.However, exchange rate and foreign ownership have no correlation with transfer pricing’s company.

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24

Mishina, S. V. "Pricing and pricing policy in the organization." CONTINUUM. MATHS. INFORMATICS. EDUCATION, no. 3 (2020): 109–16. http://dx.doi.org/10.24888/2500-1957-2020-3-109-116.

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25

LeBlanc, Greg. "Signalling Strength: Limit Pricing and Predatory Pricing." RAND Journal of Economics 23, no. 4 (1992): 493. http://dx.doi.org/10.2307/2555901.

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26

Chang, Shih-Kang, and Latha Shanker. "OPTION PRICING AND THE ARBITRAGE PRICING THEORY." Financial Review 21, no. 3 (August 1986): 17. http://dx.doi.org/10.1111/j.1540-6288.1986.tb00681.x.

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27

Hinterhuber, Andreas, and Stephan M. Liozu. "Pricing ROI, pricing capabilities and firm performance." Journal of Revenue and Pricing Management 14, no. 3 (April 24, 2015): 211–28. http://dx.doi.org/10.1057/rpm.2015.11.

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28

Kahn, Alfred E., Peter C. Cramton, Robert H. Porter, and Richard D. Tabors. "Uniform Pricing or Pay-as-Bid Pricing." Electricity Journal 14, no. 6 (July 2001): 70–79. http://dx.doi.org/10.1016/s1040-6190(01)00216-0.

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29

Chang, Jack S. K., and Latha Shanker. "OPTION PRICING AND THE ARBITRAGE PRICING THEORY." Journal of Financial Research 10, no. 1 (March 1987): 1–16. http://dx.doi.org/10.1111/j.1475-6803.1987.tb00470.x.

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30

Liozu, Stephan M., and Andreas Hinterhuber. "Pricing orientation, pricing capabilities, and firm performance." Management Decision 51, no. 3 (March 22, 2013): 594–614. http://dx.doi.org/10.1108/00251741311309670.

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31

Carassus, Laurence, and Miklós Rásonyi. "Risk-Neutral Pricing for Arbitrage Pricing Theory." Journal of Optimization Theory and Applications 186, no. 1 (June 23, 2020): 248–63. http://dx.doi.org/10.1007/s10957-020-01699-6.

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32

Shivani, Lilender. "AIRLINE PRICING: HOW AIRLINES USE PRICING STRATGEIES." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (April 26, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem31778.

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Airline pricing strategies play a pivotal role in the aviation industry's revenue management. This abstract explores the intricate mechanisms behind airline pricing, delving into the fundamental principles, factors, and techniques utilized by airlines to set fares. Drawing from a combination of academic research, industry reports, and real-world examples, this abstract provides a concise overview of the dynamic landscape of airline pricing. The abstract begins by elucidating the core objectives of airline pricing strategies, emphasizing the dual goals of maximizing revenue and optimizing capacity utilization. It then delineates the key determinants that shape pricing decisions, including demand forecasting, market segmentation, competition analysis, cost considerations, and consumer behavior. Furthermore, the abstract elucidates various pricing tactics employed by airlines, such as dynamic pricing, yield management, fare differentiation, and ancillary revenue generation. It examines how advanced analytics and revenue management systems enable airlines to dynamically adjust fares in response to fluctuating demand patterns, market conditions, and competitor actions. Moreover, the abstract explores the role of distribution channels in airline pricing, highlighting the importance of direct bookings, online travel agencies (OTAs), global distribution systems (GDS), and partnerships with intermediaries. It also discusses the emergence of personalized pricing strategies, leveraging big data analytics and machine learning algorithms to tailor fares based on individual preferences and purchasing behavior. Additionally, the abstract touches upon the regulatory frameworks and ethical considerations surrounding airline pricing practices, including transparency, fairness, and consumer protection. It underscores the need for airlines to strike a balance between revenue optimization and customer satisfaction, fostering trust and loyalty among passengers. In conclusion, this abstract offer valuable insights into the complex ecosystem of airline pricing strategies, shedding light on the multifaceted interplay between market dynamics, technological advancements, and business objectives. By understanding the underlying principles and tactics of airline pricing, stakeholders can navigate the competitive landscape more effectively, driving sustainable growth and profitability in the aviation industry.

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33

Mohan, M. Madhu, and C. S. Jayanthi rasad. "Pricing Strategies – In Retail Sector." International Journal of Scientific Research 1, no. 7 (June 1, 2012): 127–28. http://dx.doi.org/10.15373/22778179/dec2012/45.

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34

Nerudová, D., and V. Solilová. "Transfer pricing in agricultural enterprises." Agricultural Economics (Zemědělská ekonomika) 57, No. 7 (August 1, 2011): 311–21. http://dx.doi.org/10.17221/84/2010-agricecon.

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International tax issues already have not been problems of multinational enterprises. The effect of globalization and international business development causes that many small and medium size firms including agricultural entities are now engaged in the cross-border transactions and have to face the international tax issues. One of the important areas of international taxes is transfer pricing. The transactions between these persons should be assessed at their arm's length price according to the arm's length principle (internationally accepted standard) as the price which would have been agreed between the unrelated parties in free market conditions. The aim of the paper is to evaluate the impact of the selection of the form of the subsidiary on the total tax liability of the agricultural entity, including the determination of the transfer price, the application of the arm's length principle and decisions about the most suitable legal form of the subsidiary.

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35

Melnychenko, Ruslan, Kateryna Pugachevska, and Kyrylo Kasianok. "Tax control of transfer pricing." Investment Management and Financial Innovations 14, no. 4 (December 9, 2017): 40–49. http://dx.doi.org/10.21511/imfi.14(4).2017.05.

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The subject of the scientific work is analysis of the essence of the “transfer pricing” concept. It has been proven that transfer pricing is an economic and legal tool used by business entities for their tax burden optimization. It has been concluded that the concept “transfer price” means the price generated by multinational corporations in the process of commercial activity between the affiliated companies located in different countries and, correspondingly, different tax jurisdictions. In essence, transfer pricing means intra-company pricing of goods transferred between the enterprise subdivisions located in different countries. Base erosion by means of transfer pricing can be performed not only based on the price manipulating by the affiliated companies, but also as a result of manipulating incomes and expenditures. The latter is accompanied by the financial resource withdrawal outside the national economy and its concentration in the low taxation jurisdictions. Transfer pricing bears serious risks both for an individual country and for the world economy. Contractual freedom of transnational corporations and industrial and financial groups cannot be unlimited regardless of the principle of freedom of contracts in the private law relations. Economic activity of such business entities must subject to a strict control on the part of the country. In the process of transfer pricing tax control, the controlling state agencies are intended to prevent the decrease of tax liabilities by shifting the income to low tax jurisdictions by taxpayers.

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36

Adhika, Firdha Nanda, and Sartika Wulandari. "Pengaruh Beban Pajak, Mekanisme Bonus, Exchange Rate, dan Intangible Asset terhadap Keputusan Transfer Pricing." Ekonomis: Journal of Economics and Business 7, no. 1 (March 26, 2023): 246. http://dx.doi.org/10.33087/ekonomis.v7i1.900.

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Business development encourages companies to grow into multinational companies whose activities are not only centered on one country. In transactions carried out by multinational companies, it is possible for companies to manipulate transfer prices (transfer pricing). The practice of transfer pricing is carried out with the hope of reducing the tax burden and also minimizing the amount of tax that must be paid to the State. The purpose of this study is to determine the effect of the tax burden, bonus mechanism, exchange rate, and intangible assets on manufacturing companies listed on the Indonesia Stock Exchange during the 2018-2021 period. The sample selection method used was purposive sampling method and obtained a sample of 72 research data. The data analysis technique used is multiple regression analysis using SPSS 25 as a statistical tool for testing the hypothesis. The result of this studi indicate that the variable tax burden, bonus mechanism, and exchange rate have no effect on companies making transfer pricng decision. Meanwhile, the intangible assets variable has a significant influence on transfer pricing decisions.

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37

Ren, Gui, and Tao Meng. "Research on Pricing Methods of Convertible Bonds Based on Deep Learning GAN Models." International Journal of Financial Studies 11, no. 4 (December 11, 2023): 145. http://dx.doi.org/10.3390/ijfs11040145.

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This paper proposes two data-driven models (including LSTM pricing model, WGAN pricing model) and an improved model of LSM based on GAN to analyze the pricing of convertible bonds. In addition, the LSM model with higher precision in traditional pricing model is selected for comparative study with other pricing models. It is found that the traditional LSM pricing model has a large error in the first-day pricing, and the pricing function needs to be further improved. Among the four pricing models, LSTM pricing model and WGAN pricing model have the best pricing effect. The WGAN pricing model is better than the LSTM pricing model (0.21%), and the LSM improved model (1.17%) is better than the traditional LSM model (2.26%). Applying the generative deep learning model GAN to the pricing of convertible bonds can circumvent the harsh preconditions of assumptions, and significantly improve the pricing effect of the traditional model. The scope of application of each model is different. Therefore, this paper proves the feasibility of the GAN model applied to the pricing of convertible bonds, and enriches the pricing function of derivatives in the financial field.

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38

Li, Feng. "Option Pricing." Journal of Derivatives 7, no. 4 (May 31, 2000): 49–65. http://dx.doi.org/10.3905/jod.2000.319134.

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39

Barnett II, William, Michael Saliba, and Walter Block. "Predatory pricing." Corporate Ownership and Control 4, no. 4 (2007): 397–402. http://dx.doi.org/10.22495/cocv4i4c3p4.

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Predatory pricing is logically impossible, because it necessarily involves pricing below cost. However, cost, properly understood as opportunity cost is subjective and is incommensurable with money prices; more important, to price below cost implies rationally choosing an alternative (selling at price) that is suboptimal, since cost is the most highly valued alternative not chosen. When critics declare that predatory pricing is to price below cost, they mean to set a price below some measure of money expenses. But this entails all kinds of problems; which concept of expense – marginal is most obvious; but also the issue of the present value of alternatives, which means discounting expected revenues and expected expenses.

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Baldenius, T. "Internal Pricing." Foundations and Trends in Accounting 3, no. 4 (2008): 223–313. http://dx.doi.org/10.1561/1400000013.

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Wricke, Martin, Andreas Herrmann, and Frank Huber. "Behavioral Pricing." WiSt - Wirtschaftswissenschaftliches Studium 29, no. 12 (2000): 692–98. http://dx.doi.org/10.15358/0340-1650-2000-12-692.

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Yeoman, Ian. "Personalised Pricing." Journal of Revenue and Pricing Management 21, no. 2 (March 14, 2022): 127–28. http://dx.doi.org/10.1057/s41272-022-00376-9.

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Oren, Shmuel, Stephen Smith, and Robert Wilson. "Capacity Pricing." Econometrica 53, no. 3 (May 1985): 545. http://dx.doi.org/10.2307/1911654.

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Eaglesham, David J. "Value Pricing." MRS Bulletin 32, no. 11 (November 2007): 878. http://dx.doi.org/10.1557/mrs2007.173.

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Bokšová, Jiřina. "Transfer Pricing." Český finanční a účetní časopis 2007, no. 2 (June 1, 2007): 28–33. http://dx.doi.org/10.18267/j.cfuc.219.

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Rühle, Alexander. "Partitioned Pricing." WiSt - Wirtschaftswissenschaftliches Studium 43, no. 3 (2014): 124–29. http://dx.doi.org/10.15358/0340-1650_2014_3_124.

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Fox, Jeffrey L. "Drug Pricing." Nature Biotechnology 8, no. 6 (June 1990): 502. http://dx.doi.org/10.1038/nbt0690-502.

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Barbier, Edward B. "Pricing Nature." Annual Review of Resource Economics 3, no. 1 (October 2011): 337–53. http://dx.doi.org/10.1146/annurev-resource-083110-120115.

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Luenberger, D. G. "Projection Pricing." Journal of Optimization Theory and Applications 109, no. 1 (April 2001): 1–25. http://dx.doi.org/10.1023/a:1017596419383.

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Jiang, Lan, and Hani S. Mahmassani. "Toll Pricing." Transportation Research Record: Journal of the Transportation Research Board 2343, no. 1 (January 2013): 105–15. http://dx.doi.org/10.3141/2343-13.

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