scholarly journals Can differences in publisher size account for the relatively low prices of the journals available to master’s universities through commercial publishers’ databases? The importance of price discrimination and substitution effects

2022 ◽  
Author(s):  
William H. Walters
Keyword(s):  
Price Discrimination ◽  
Substitution Effects ◽  
Collection Development ◽  
Major Research ◽  
Explanatory Variables ◽  
Master's Institutions ◽  
For Profit ◽  
Size Number ◽  
Direct Association ◽  
Price Quotes

AbstractUsing price quotes and invoices for thousands of full-text databases and single-journal subscriptions, this study confirms that for a typical master’s university, the journals acquired through commercial publishers’ databases cost substantially less than those acquired through the databases of scholarly societies, universities, and other nonprofits. Moreover, the lower prices of commercial publishers’ journals cannot be readily attributed to publisher size (number of journals published) or to any of several other explanatory variables. There is a weak, direct association between publisher size and price among the for-profit journals but a stronger, inverse relationship between publisher size and price among the nonprofit journals. These findings, along with the results of previous research, suggest that resource providers may have incentives to keep prices low due to the collection development strategies adopted by many teaching-oriented colleges and universities. If the library’s goal is to hold a sufficient number of high-quality journals rather than to provide immediate access to every wanted journal, particular journals and databases may be regarded as substitutes even when each product provides unique content. Many U.S. bachelor’s and master’s institutions have goals different from those of the major research universities, and commercial publishers (along with some of the larger nonprofits) seem to recognize this when setting and negotiating prices.

Measuring the effects of tourists’ relative willingness to spend and third-degree price discrimination on inbound tourism expenditure differentials

2021 ◽  
pp. 135481662110300
Author(s):  
Usamah F Alfarhan ◽  
Khaldoon Nusair ◽  
Hamed Al-Azri ◽  
Saeed Al-Muharrami ◽  
Nan Hua
Keyword(s):  
Price Discrimination ◽  
Profit Maximization ◽  
Tourism Industry ◽  
Theoretical Argument ◽  
Total Expenditure ◽  
Conditional Quantile ◽  
For Profit ◽  
Inbound Tourism ◽  
Tourism Expenditure ◽  
Quantile Estimates

Tourism expenditures are determined by a set of antecedents that reflect tourists’ willingness and ability to spend, and de facto incremental monetary outlays at which willingness and ability is transformed into total expenditures. Based on the neoclassical theoretical argument of utility-constrained expenditure minimization, we extend the current literature by applying a sustainability-based segmentation criterion, namely, the Legatum Prosperity IndexTM to the decomposition of a total expenditure differential into tourists’ relative willingness to spend and an upper bound of third-degree price discrimination, using mean-level and conditional quantile estimates. Our results indicate that understanding the price–quantity composition of international inbound tourism expenditure differentials assists agents in the tourism industry in their quest for profit maximization.

The drivers of corporate governance disclosure: the case of Nifty 500 Index

2018 ◽  
Vol 60 (2) ◽  
pp. 681-700 ◽  
Author(s):  
Androniki Katarachia ◽  
Electra Pitoska ◽  
Grigoris Giannarakis ◽  
Elpida Poutoglidou
Keyword(s):  
Corporate Governance ◽  
Financial Leverage ◽  
Policy Makers ◽  
Content Type ◽  
Explanatory Variables ◽  
Size Number ◽  
Governance Practices ◽  
Board Director ◽  
First Time ◽  
Governance Disclosure

Purpose Based on agency theory, the purpose of this paper is to investigate the determinants on the dissemination level of corporate governance disclosure (CGD). Design/methodology/approach The sample of the study incorporates listed companies in Nifty 500 Index for the period 2009-2014. The Governance Disclosure Score calculated by Bloomberg is used as a proxy for the dissemination level of corporate governance information. In total, eight explanatory variables are uses, namely, board’s size, number of board meetings, CEO duality, presence of women on the board, company’s size, financial performance, Tobin’s Q ratio and financial leverage. Findings The results of study suggest a need for improvement in CGDs by Indian companies, as they fail to comply the majority of the proposed disclosure items. Furthermore, it is revealed that the number of board director, the value of company, the financial leverage and the presence of women affect negatively the dissemination level of corporate governance information. While, the size of company is the only determinant that positively affects the extent of CGD. Practical implications The results are valuable because they reveal the attributes that determines which companies needs less or extra monitoring by shareholders and investors regarding the applied corporate governance practices. In addition, the study can be valuable to policy makers responsible for the regulation of company’s accountability in relation to corporate governance practices. Originality/value The study extents previous studies by incorporating for the first time Bloomberg’s rating approach regarding the dissemination level of CGD in Indian context.

Profit efficiency analysis of rice production in Taiwan

2017 ◽  
Vol 9 (1) ◽  
pp. 32-47 ◽  
Author(s):  
Tsaiyu Chang ◽  
Daisuke Takahashi ◽  
Chih-Kuan Yang
Keyword(s):  
Farming System ◽  
Rice Production ◽  
Profit Efficiency ◽  
Content Type ◽  
Explanatory Variables ◽  
For Profit ◽  
Farm Survey ◽  
One Step ◽  
The Cost ◽  
Regression Adjustment

Purpose The purpose of this paper is to analyze and compare the profit efficiency of custom and self-farming methods of rice production in Taiwan. Design/methodology/approach This study examines the nature and extent of the profitability and profit efficiency of custom and self-farming based on a farm survey in Taiwan. Furthermore, it estimates the stochastic profit frontier to measure the degree of inefficiency and analyze the determinants of these inefficiencies. Findings The profitability and profit efficiency of custom farming are lower than for self-farming, and the differences in profitability are more significant for large rice farmers. The estimation results show that the custom farming area and the farmer’s age decrease efficiency and, regardless of the farming style used, larger farms have higher profit efficiency. Research limitations/implications This study’s findings show that self-farming is more favorable than custom farming for profit efficiency. This study examined this problem by conducting a regression adjustment for explanatory variables, but did not remove all self-selection bias, which may occur between profit efficiency and the choice of farming system. Originality/value Previous studies that measured the efficiency of rice farming often considered cost efficiency by the cost function, and ignored the increased profit from producing high-quality rice. This study used a one-step estimation of the profit frontier function to measure the degree of inefficiency and analyze the determinants of this inefficiency.

AI and Procurement

2021 ◽  
Author(s):  
Ruomeng Cui ◽  
Meng Li ◽  
Shichen Zhang
Keyword(s):  
Price Discrimination ◽  
Recommendation System ◽  
Wholesale Price ◽  
Problem Definition ◽  
Practical Relevance ◽  
Trading Company ◽  
Smart Control ◽  
Managerial Implications ◽  
The Impact ◽  
Price Quotes

Problem definition: In this research, we study how buyers’ use of artificial intelligence (AI) affects suppliers’ price quoting strategies. Specifically, we study the impact of automation—that is, the buyer uses a chatbot to automatically inquire about prices instead of asking in person—and the impact of smartness—that is, the buyer signals the use of a smart AI algorithm in selecting the supplier. Academic/practical relevance: In a world advancing toward AI, we explore how AI creates and delivers value in procurement. AI has two unique abilities: automation and smartness, which are associated with physical machines or software that enable us to operate more efficiently and effectively. Methodology: We collaborate with a trading company to run a field experiment on an online platform in which we compare suppliers’ wholesale price quotes across female, male, and chatbot buyer types under AI and no recommendation conditions. Results: We find that, when not equipped with a smart control, there is price discrimination against chatbot buyers who receive a higher wholesale price quote than human buyers. In fact, without smartness, automation alone receives the highest quoted wholesale price. However, signaling the use of a smart recommendation system can effectively reduce suppliers’ price quote for chatbot buyers. We also show that AI delivers the most value when buyers adopt automation and smartness simultaneously in procurement. Managerial implications: Our results imply that automation is not very valuable when implemented without smartness, which in turn suggests that building smartness is necessary before considering high levels of autonomy. Our study unlocks the optimal steps that buyers could adopt to develop AI in procurement processes.

scholarly journals EXPLAINING THE PRICE OF VOLUNTARY CARBON OFFSETS

2010 ◽  
Vol 01 (02) ◽  
pp. 93-111 ◽  
Author(s):  
MARC N. CONTE ◽  
MATTHEW J. KOTCHEN
Keyword(s):  
Carbon Offsets ◽  
Third Party ◽  
Hedonic Price ◽  
Large Variability ◽  
Explanatory Variables ◽  
For Profit ◽  
Not For Profit ◽  
Price Functions ◽  
Developed Nations ◽  
Project Level

This paper identifies factors that explain the large variability in the price of voluntary carbon offsets. We estimate hedonic price functions using a variety of provider- and project-level characteristics as explanatory variables. We find that providers located in Europe sell offsets at prices that are approximately 30% higher than providers located in either North America or Australasia. Contrary to what one might expect, offset prices are generally higher, by roughly 20%, when projects are located in developing or least-developed nations. But this result does not hold for forestry-based projects. We find evidence that forestry-based offsets sell at lower prices, and the result is particularly strong when projects are located in developing or least-developed nations. Offsets that are certified under the Clean Development Mechanism or the Gold Standard, and therefore qualify for emission reductions under the Kyoto Protocol, sell at a premium of more than 30%; however, third-party certification from the Voluntary Carbon Standard, one of the popular certifiers, is associated with a price discount. Variables that have no effect on offset prices are the number of projects that a provider manages and a provider's status as for-profit or not-for-profit.

scholarly journals Statistical Analysis of Maximally Similar Sets in Ecological Research

Mathematics ◽  
2018 ◽  
Vol 6 (12) ◽  
pp. 317
Author(s):  
David Roberts
Keyword(s):  
Statistical Power ◽  
Rank Order ◽  
Dimensional Space ◽  
Random Sets ◽  
Forest Composition ◽  
Triangular Distribution ◽  
Large Set ◽  
Spring Temperature ◽  
Explanatory Variables ◽  
Size Number

Maximally similar sets (MSSs) are sets of elements that share a neighborhood in a high-dimensional space defined by a symmetric, reflexive similarity relation. Each element of the universe is employed as the kernel of a neighborhood of a given size (number of members), and elements are added to the neighborhood in order of similarity to the current members of the set until the desired neighborhood size is achieved. The set of neighborhoods is then reduced to the set of unique, maximally similar sets by eliminating all sets that are permutations of an existing set. Subsequently, the within-MSS variability of candidate explanatory variables associated with the elements is compared to random sets of the same size to estimate the probability of obtaining variability as low as was observed. Explanatory variables can be compared for effect size by the rank order of within-MSS variability and random set variability, correcting for statistical power as necessary. The analyses performed identify constraints, as opposed to determinants, in the triangular distribution of pair-wise element similarity. In the example given here, the variability in spring temperature, summer temperature, and the growing degree days of forest vegetation sample units shows the greatest constraint on forest composition of a large set of candidate environmental variables.

Taxes, bankruptcy costs, and capital structure in for-profit and not-for-profit hospitals

2017 ◽  
Vol 31 (1) ◽  
pp. 21-32 ◽  
Author(s):  
Sean S Huang ◽  
Jie Yang ◽  
Nathan Carroll
Keyword(s):  
Capital Structure ◽  
Income Tax ◽  
Income Taxes ◽  
Personal Income ◽  
Explanatory Variables ◽  
For Profit ◽  
Bankruptcy Costs ◽  
Not For Profit ◽  
Acute Hospitals ◽  
The Capital Structure

About 60% of the US hospitals are not-for-profit and it is not clear how traditional theories of capital structure should be adapted to understand the borrowing behavior of not-for-profit hospitals. This paper identifies important determinants of capital structure taken from theories describing for-profit firms as well as prior literature on not-for-profit hospitals. We examine the differential effects these factors have on the capital structure of for-profit and not-for-profit hospitals. Specifically, we use a difference-in-differences regression framework to study how differences in leverage between for-profit and not-for-profit hospitals change in response to key explanatory variables (i.e. tax rates and bankruptcy costs). The sample in this study includes most US short-term general acute hospitals from 2000 to 2012. We find that personal and corporate income taxes and bankruptcy costs have significant and distinct effects on the capital structure of for-profit and not-for-profit hospitals. Specifically, relative to not-for-profit hospitals: (1) higher corporate income tax encourages for-profit hospitals to increase their debt usage; (2) higher personal income tax discourages for-profit hospitals to use debt; and (3) higher expected bankruptcy costs lead for-profit hospitals to use less debt. Over the past decade, the capital structure of for-profit hospitals has been more flexible as compared to that of not-for-profit hospitals. This may suggest that not-for-profit hospitals are more constrained by external financing resources. Particularly, our analysis suggests that not-for-profit hospitals operating in states with high corporate taxes but low personal income taxes may face particular challenges of borrowing funds relative to their for-profit competitors.

scholarly journals نمذجة أثر تغيُّر سعر الصرف على أسعار الأسمنت في السودان (2000- 2016)

2021 ◽  
Vol 9 (3) ◽  
pp. 1-10
Author(s):  
Mogahid Bilal Taha ◽  
Mudathir Suliman M.Ali
Keyword(s):  
Exchange Rate ◽  
Construction Materials ◽  
Feasibility Studies ◽  
Continuous Change ◽  
Explanatory Variables ◽  
Construction Contracts ◽  
For Profit ◽  
The Exchange Rate ◽  
Market Variables ◽  
The Impact

Feasibility studies, planning, pricing and contract management in the construction industry depend mainly on the stability of the economic process where most infrastructure projects require relatively long periods of time to implement them. In a highly inflationary economy where foreign exchange rates constantly change compared to the local currency for long periods that may extend for years. In such an economy, the prices of construction materials vary according to market variables. The methods of pricing items in bids are not feasible for profit and loss accounts and for competition purposes, which leads to significant complications in the management of construction contracts associated with these projects and generates a new case of continuous change unprecedented and has not been resolved even in the global construction contracts of FIDIC. The researcher monitored and collected the inflation values and the exchange rate of Sudanese pound against US dollar as the main currency for a large number of years against the prices of cement for the same years and then statistically studied through a number of statistical analysis programs. Information has been studied over time and then the change in the price of cement versus inflation and the exchange rate and a try to devise a function has been carried out in order to describe that change and express it in a mathematical formula that facilitates reading, analyzing and forecasting. It was found that the change of cement prices is related in a logarithmic function with both inflation and the exchange rate. The independent explanatory variables (exchange rate and inflation rate) were found to be responsible for at least 80% of the changes in the dependent variables (cement prices). The remaining 20% is the impact of other (random) variables not included in the model, and this is an indication of the quality of the documentation of the model. That the variables included in the model is the most influential in the dependent variable of non-included variables. The mathematical models have passed derived economic and standard criterion and have been acceptable statistically and can therefore be relied upon to test any hypotheses are developed.  

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