Unit Profit Research Articles

Unit profit margins along post-Keynesian lines: from Sraffa, Kalecki, Robinson to Eichner, Wood, Harcourt and Kenyon

This article offers a retrospective reading of the evolution of post-Keynesian authors on the determination of corporate unit profit margins. It shows that this theory was essentially structured into three stages. The first stage is based on the so called imperfect competition theory and/or the degree of monopoly in the 1920s and 1930s, which was based in turn on an indirect approach and profit maximisation. This was followed by a second period of distancing from and questioning of this work, before a third period of structuring and convergence towards a more direct and inclusive approach focussing on growth and self-financing of investment in the 1970s. This evolution raises issues in terms of analysis and economic policy.

Hybrid modeling-based digital twin for performance optimization with flexible operation in the direct air-cooling power unit

The thermal power sector, one of the major CO2 emissions sources, is urged quicker steps to come up with an action that enables coal savings and carbon emissions reduction in China. Flexible operation is a growing trend among thermal power plants owing to the ever-increasing installation of renewable energy power resources. However, flexible operation comes with performance degradation, energy consumption growing and CO2 emissions increment. This study proposes a digital twin system for a direct air-cooling unit to determine the optimal back-pressure and corresponding fan frequency modulation under various operating conditions to minimize the coal consumption and maximize the unit profit. Thus, a hybrid model of the digital twin system integrating an extreme gradient boosting algorithm tuned by a particle swarm optimization algorithm and a domain knowledge-based analytical formulation for the optimal back-pressure is proposed. The proposed digital twin system is applied to a 600 MW on-duty direct air-cooling power unit. In the industrial case study, the proposed system saved 535.526 tons of standard coal and decreased CO2 emissions by 1335.068 tons within two weeks, which is remarkable.

Trade-offs or synergies? Hybridity and sustainable performance of dairy cooperatives in India

• Analyses the effect of National Dairy Plan on Indian dairy cooperatives. • Conceptualizes dairy cooperatives as hybrid organizations. • Regression analysis using 2-stage augmented inverse probability weighted estimator based on potential outcomes framework. • The performance of dairy cooperatives is affected by their hybrid characteristics. • Indian dairy cooperatives are characterized by synergetic outcomes, not trade-offs. India has come a long way in achieving milk security since it attained independence in 1947. During the 1950s India had to import about 55,000 tons of milk powder. By the year 2018–19 it had become one of the largest producers of milk in the world. The credit for this goes to the successful promotion of dairy cooperatives (DCs) in India. However, milk productivity in the country has continued to lag behind global averages. To increase milk productivity in India, the National Dairy Plan (NDP) was launched in 2011–12. Limited research appears to have been conducted on the effect of NDP on DC performance. Therefore, this article analyzes the effect of NDP on DC performance by conceptualizing DCs as hybrid organizations. However, there is limited research on how the hybrid character of cooperatives affects their performance. Regression analysis using 2-stage doubly robust, augmented inverse probability weighted (AIPW) estimator based on the potential outcomes framework on DC data collected via surveys and secondary reveals that NDP is imbibing characteristics of hybrid organizations in Indian DCs. Hybridity is statistically significant after controlling for village-level and DC-level variables. Financial hybridity is significant for four dependent variables: unit profit, quality of milk, human capability-building and community support. Autonomy, the other measure of hybridity, is significant for two dependent variables: growth of sales and unit profit. In other words, Indian DCs with hybrid characteristics actually pursue three different kinds of objectives: a) maximization of market-based logics (pursuit of self-interest, economic efficiency and profit maximization); b) maximization of community-oriented logics (pursuit of values such democracy, solidarity and autonomy); and, c) maximization of public benefit (public-sector led local economic development). The above discussion shows that Indian DCs are characterized by synergetic outcomes and not by trade-offs which contrasts with theoretical literature.

Determination of factors affecting competitiveness through technical and economic analyses of dairy cattle enterprises in Balıkesir province

In this study, technical and economic analysis of dairy cattle enterprises in Balıkesir province were carried out. The factors which affect the competitiveness of enterprises and are important in terms of the continuity of production were determined. The stratified sampling method was used to determine the sample, and the study material was two-year (2017–2018) data obtained from 147 enterprises. In addition to the economic analysis of the data obtained, factors affecting unit profit in enterprises were estimated using the multiple linear regression model. The cost elements in total enterprises in Balıkesir province in 2017–2018 include feed expenses (47.90%-47.29%), livestock depreciation (16.64%-16.13%), labor expenses (13.84%-14.30%), veterinary health expenses (4.03%-4.50%), fuel transportation expenses (3.43%-4.15%), building equipment depreciation (3.37%-3.64%), and other expense items. A distinct difference was observed between scales in terms of profit and loss states of the enterprises in the study, with an increase in the profitability level from small toward large scale enterprise. The small-scale enterprises, in particular, are at a loss. The most important determinant of competitiveness in the study is the region’s development level, where the enterprises are established in the borders of Balıkesir province. Additionally, among the technical parameters, the calving interval and the reduction of the disease rate have a positive effect on the competitiveness of the enterprises. Therefore, improving the financial structure of the enterprises and boosting the rate of technology utilization while simultaneously increasing enterprise scales will contribute positively to competitiveness.

A One-Phase Tree-Structure Method to Mine High Temporal Fuzzy Utility Itemsets

Compared to fuzzy utility itemset mining (FUIM), temporal fuzzy utility itemset mining (TFUIM) has been proposed and paid attention to in recent years. It considers the characteristics of transaction time, sold quantities of items, unit profit, and transformed semantic terms as essential factors. In the past, a tree-structure method with two phases was previously presented to solve this problem. However, it spent much time because of the number of candidates generated. This paper thus proposes a one-phase tree-structure method to find the high temporal fuzzy utility itemsets in a temporal database. The tree was designed to maintain candidate 1-itemsets with their upper bound values meeting the defined threshold constraint. Besides, each node in this tree keeps the required data of a 1-itemset for mining. We also designed an algorithm to construct the tree and gave an example to illustrate the mining process in detail. Computational experiments were conducted to demonstrate the one-phase tree-structure method is better than the previous one regarding the execution time on three real datasets.

A sustainable circular economic supply chain system with waste minimization using 3D printing and emissions reduction in plastic reforming industry

A circular supply chain consists of emission and wastes minimization technologies with a remarkable gain in profit, which is the aim of any industry that is concerned about environmental conservation. One of the most critical hurdles to the transition to sustainability is waste management. This study proposes a circular sustainable integrated model in a plastic reforming industry with investment in 3D printing techniques to minimize waste, emission reduction, and ordering cost reduction and it led to optimal profit. The customer's demand and the unit profit depend on the circularity index of the item. This paper looked at three scenarios with partial backlogging: (a) linear demand versus linear unit profit; (b) linear demand versus exponential unit profit; and (c) linear demand versus logistic unit profit. An algorithm was used to optimize the profit of the plastic reforming industry with optimal values of ordering quantity, circularity index, and investment in waste minimization, emission reduction, and ordering cost under carbon cap policy. This model establishes that the plastic reforming industry will get more profit and an optimal level of circularity index when it works with high efficiency of emission and waste minimization technologies under low investment, a rise in the carbon tax, and less opportunity cost. Sensitivity analysis and managerial framework in the plastic reforming industry were given to realize the sensitivity of decision variables with variation in key parameters.

LEVEL OF ALLOCATIVE EFFICIENCY ESTIMATION OF IRRIGATED TOMATO PRODUCTION UNDER KANO RIVER IRRIGATION PROJECT (KRIP), NIGERIA

The focus of this study is to analyze the Level of Economic Efficiency of Irrigated Tomato Production under Kano River Irrigation Project (KRIP), Nigeria. A combination of purposive and random sampling techniques were used to select 213 irrigated tomato farmers. Primary data were collected through a well-structured questionnaire. Data collected were analyzed using descriptive statistics such as frequency, percentages and data. It was found that the medium and large scale farms emerged as farms with price-efficiency in terms of higher unit profit (0.43) respectively. It can be concluded irrigated tomato farmers in the study area were fairly allocative efficient, suggesting that opportunities for improvement in the allocative efficiency of the respondents. It is recommended that education should be encouraged by extension agents through effective and efficient dissemination of information.

The Effects of Demand and Interest Rates on Investments, Evidence of Overinvestment from Two Behavioral Experiments

This article analyzes the causes of overinvestment and thus investment cycles with two behavioral experiments. In the experimental simulations increases in demand and cuts in interest rates increased unit profits, which led to uncoordinated and thus collectively too high investments (collective error). This made it possible to demonstrate collective errors that led to overinvestment and investment cycles (boom and bust cycles). Central banks and companies should take this into account when making their decisions. The experiments show the fundamental problem of uncoordinated supply adjustment and a tendency on the part of market participants to neglect the behavior of other actors and to underestimate the influence of the market on their own investment decisions.

Analysis of economy, energy efficiency, environment: A case study of the CHP system with both civil and industrial heat users

Integrated energy supply via the high-capacity combined heat and power (CHP) system is an effective way to achieve “win-win cooperation” for regional carbon reduction. A case study of the CHP system with both civil and industrial heat users is conducted to analysis the mixed impact of integrated energy supply on CHP systems. The steam-water equations and the off-design calculation model are developed to analyze the heat-power coupling mechanism of the CHP system. The linear-calculating diagram is obtained, which provides operational guidance for CHP system with simultaneous power, civil heat and industrial loads. Further, the analysis of economy, energy efficiency and environment within the operation region is performed. The results show that for a constant main steam flow rate, the industrial heat load is more profitable than the civil heat load. Moreover, the energy efficiency of the CHP unit can be further improved by undertaking the industrial heat load, despite at the expense of part capacity to supply civil heat. The average value of CO2 emissions per unit profit is reduced by approximately 7.69% overall after the stable industrial heat load of 100 MW, which means about 1.64 tons of CO2 can be reduced per 1000 USD profit.

Mining High Utility Time Interval Sequences Using MapReduce Approach: Multiple Utility Framework

Mining high utility sequential patterns is observed to be a significant research in data mining. Several methods mine the sequential patterns while taking utility values into consideration. The patterns of this type can determine the order in which items were purchased, but not the time interval between them. The time interval among items is important for predicting the most useful real-world circumstances, including retail market basket data analysis, stock market fluctuations, DNA sequence analysis, and so on. There are a very few algorithms for mining sequential patterns those consider both the utility and time interval. However, they assume the same threshold for each item, maintaining the same unit profit. Moreover, with the rapid growth in data, the traditional algorithms cannot handle the big data and are not scalable. To handle this problem, we propose a distributed three phase MapReduce framework that considers multiple utilities and suitable for handling big data. The time constraints are pushed into the algorithm instead of pre-defined intervals. Also, the proposed upper bound minimizes the number of candidate patterns during the mining process. The approach has been tested and the experimental results show its efficiency in terms of efficiency, memory utilization, and scalability.

Optimal procurement decisions for food products in a retailing system with variety dependent demand

In the food industry, acquiring a lion's share of the market is a key factor in a company's success. Offering similar substitutes instead of the requested stocked-out products has been an alternative to keep customers. In this paper, an economic ordering model with substitutable food products is investigated. Each product has its own initial constant demand which will be increased when inventory of the other products would be depleted. Similarity measures and quality of the principal request and its substitutes depends on any typical customer with its own information. Time intervals are considered as decision variables and the conditions which in closed form expression of the optimal solution are achievable are derived. Furthermore, the impact of the models' parameters on the optimal solution was investigated. It was clarified that a marginal increase in the unit profit of each food product has a positive impact on the total profit and the order quantity.

A single‐phase algorithm for mining high utility itemsets using compressed tree structures

Mining high utility itemsets (HUIs) from transaction databases considers such factors as the unit profit and quantity of purchased items. Two-phase tree-based algorithms transform a database into compressed tree structures and generate candidate patterns through a recursive pattern-growth procedure. This procedure requires a lot of memory and time to construct conditional pattern trees. To address this issue, this study employs two compressed tree structures, namely, Utility Count Tree and String Utility Tree, to enumerate valid patterns and thus promote fast utility computation. Furthermore, the study presents an algorithm called single-phase utility computation (SPUC) that leverages these two tree structures to mine HUIs in a single phase by incorporating novel pruning strategies. Experiments conducted on both real and synthetic datasets demonstrate the superior performance of SPUC compared with IHUP, UP-Growth, and UP-Growth+ algorithms.

Evolutionary game analysis of low‐carbon effort decisions in the supply chain considering fairness concerns

As global environmental problems are becoming more severe, how to efficiently reduce carbon emissions has become an urgent problem to be solved. Manufacturers and retailers can effectively reduce carbon emissions through low‐carbon efforts, and doing so is important for the sustainable development of low‐carbon supply chains. This paper develops a general framework that considers how bounded rationality and fairness concerns affect the manufacturer's and retailer's low‐carbon effort decisions and discusses the evolutionary stable strategy (ESS) and the evolution process of the manufacturer's and retailer's low‐carbon efforts. The ESS shows that the manufacturer and the retailer will increase their low‐carbon efforts when the initial unit profit is higher. Otherwise, a smaller initial unit profit will reduce their low‐carbon efforts. This paper also analyzes different attributes of fairness concerns and finds that advantageous fairness concerns increase low‐carbon efforts, whereas disadvantageous fairness concerns reduce low‐carbon efforts. In addition, fairness concerns will speed up the manufacturer's and retailer's low‐carbon efforts to ESSs. When the manufacturer and retailer choose the “no effort” strategy, they will stop investing quickly, but when they choose the “effort” strategy, they will not invest quickly. This paper can provide decision support for using the low‐carbon effort investment strategy by supply chain members.

Efficient algorithms for mining closed high utility itemsets in dynamic profit databases

The problem of discovering high-utility itemsets (HUIs) in transaction databases, which is an extension of Frequent Itemset Mining, is a commonly encountered mining task. Researchers have proposed algorithms to efficiently mine highly profitable itemsets in customer transaction databases, in which the unit profits of items are fixed. However, this assumption does not reflect the true nature of the utility measure of items in real-life transaction databases, which might vary over time. Moreover, since this important characteristic is ignored by all the current HUI mining algorithms, they are either not applicable to this type of database, or they generate inaccurate results. In addition, the HUI mining algorithms’ traditional limitation is that they produce a huge number of HUIs for users. In this paper, we define the problem of mining a lossless, concise and compact representation of HUIs, called closed HUIs (CHUIs), in dynamic unit profit databases. Based on newly defined of utility measure, a novel algorithm, called iEFIM-Closed, is introduced. This relies on this new utility measure, a novel compact database format to reduce the cost of database scans and increase the efficiency of the mining process. Experimental evaluations show that iEFIM-Closed significantly outperforms state-of-the-art algorithms for mining CHUIs on sparse databases with dynamic profit, and has competitive performance in dense databases in terms of runtime, the cost of database scans and scalability.

A Survey of incremental high-utility pattern mining based on storage structure

Traditional association rule mining has been widely studied, but this is not applicable to practical applications that must consider factors such as the unit profit of the item and the purchase quantity. High-utility itemset mining (HUIM) aims to find high-utility patterns by considering the number of items purchased and the unit profit. However, most high-utility itemset mining algorithms are designed for static databases. In real-world applications (such as market analysis and business decisions), databases are usually updated by inserting new data dynamically. Some researchers have proposed algorithms for finding high-utility itemsets in dynamically updated databases. Different from the batch processing algorithms that always process the databases from scratch, the incremental HUIM algorithms update and output high-utility itemsets in an incremental manner, thereby reducing the cost of finding high-utility itemsets. This paper provides the latest research on incremental high-utility itemset mining algorithms, including methods of storing itemsets and utilities based on tree, list, array and hash set storage structures. It also points out several important derivative algorithms and research challenges for incremental high-utility itemset mining.

The loss-averse newsvendor problem with quantity-oriented reference point under CVaR criterion

<p style='text-indent:20px;'>This paper studies a single-period inventory problem with quantity-oriented reference point, where the newsvendor has loss-averse preferences and conditional value-at-risk (CVaR) measure is introduced to hedge against his risk. It is shown there exists a unique optimal order quantity maximizing the CVaR of utility. Moreover, it is decreasing in loss aversion level, confidence level and target unit profit, respectively. Then we establish the sufficient conditions under which the newsvendor's optimal order quantity may be larger than, equal to or less than the classical newsvendor solution. In particular, when the target unit profit is a convex combination of the maximum and minimum, the optimal order quantity is independent of price and cost parameters. Numerical experiments are conducted to illustrate our results and present some managerial insights.</p>

Profit Analysis of a Standby Repairable System with Priority to Preventive Maintenance and Rest of Server Between Repairs

The paper aims to bring out the profit analysis of a system with cold standby redundancy of two identical units. In the system, we keep one unit in working and the other is to back up the operation. The system requires preventive maintenance after a specific time. The server has the dual role to carry out repair activities in terms of preventive maintenance and repair of the failed unit. In addition to that, the server is allowed to take rest after each repair. There is no need of rest of the server after preventive maintenance. The provision of priority has been made for the preventive maintenance over repairs. The repairs are done to increase the efficiency and productivity level of the system. The failure rate follows exponential distribution while repair time, rest time of the server and preventive maintenance rate follow arbitrary distributions. The significant reliability characteristics including MTSF, long run availability, server busy time due to repair & preventive maintenance, expected number of repairs, expected number of preventive maintenances per unit time and profit function are obtained using the usual stochastic processes approach. For particular values of the parameters, the revenue per unit up-time and cost functions related to repair activities are considered to carry out the profit analysis of the system model. The results are shown graphically and numerically to highlight the effect of different parameters on some significant reliability characteristics

Decisions and coordination of retailer-led low-carbon supply chain under altruistic preference

A low-carbon supply chain formed by a dominant retailer and a small and medium-sized manufacturer (SMM) is considered. Because the SMM faces the high cost pressure of adopting carbon emission reduction (CER) technologies, the retailer may take an altruistic preference for the long-term sustainability of the chain. Three decision-making models, centralized, decentralized without altruistic preference, and decentralized with altruistic preference, are constructed to compare decisions and profits of both parties. Since neither decentrailized models can lead to a coordinated solution that is incentive compitable, a coordination contract, referred to as the cost sharing contract with altruistic preference, is proposed. Numerical study shows that the altruistic preference can help increase the SMM's profit and system efficiency but decrease the retailer's profit. The coordination contract requires the retailer to adjust the unit profit and share more than half of the CER cost. It is found that the wholesale price is the lowest in the coordination contract and the comparison of unit profit depends on the coefficient of CER cost.

ЦІНОУТВОРЕННЯ В СИСТЕМІ ЕКОНОМІЧНОГО УПРАВЛІННЯ РОЗВИТКОМ БІЗНЕСУ

The role of pricing in the system of economic management of business development is analyzed. The relationship between the pricing strategy of the company and the processes of cost management and the company's profitability is revealed. The purpose of the article is to compare cost, market and parametric methods of pricing and determine the feasibility of their use in economic management of business development. The relevance of a unified systematization of pricing methods in the system of economic management of business development is shown, which will allow enterprises to set prices for products to maximize their profits. A comparative analysis of cost, market and parametric pricing methods is given and the expediency of their application in the economic management of business development is determined. It has been determined that market-based pricing methods allow a company to set a more efficient level of prices for products due to a more complete consideration of the influence of demand and competition factors in the pricing process. Necessary data for determining the price of products according to the cost method of pricing are variable costs of production per unit of goods, average fixed costs, unit profit. To determine the price of products by the market method, data on the level of demand, competition, market conditions, consumer perception of the value of the product are needed. To apply the parametric method of pricing requires data on the design and technical parameters of products, the level of costs for the production of goods. The application of cost pricing methods does not take into account the state of competition, market conditions, consumer preferences. The disadvantage of using market-based pricing methods is the possible difficulties in gathering information. Parametric pricing methods have limited application because they require complex calculations. The application of modern methodological approaches to pricing in the system of economic management of business development allows to achieve the strategic goals of the company by mobilizing human, financial, marketing and production resources of the company.

Seller Incentives in Sponsored Product Listings on Online Marketplaces

Many online marketplaces offer sponsored product listings as third-party sellers’ ad slots that are blended in organic product listings. A seller’s potential benefit from sponsored listings is a non- trivial question, as a consumer may prefer or avoid advertised products and such preferences can be position-specific. This paper investigates a seller’s advertising incentives across positions in a large-scale field experiment. We provide the first evidence that consumers may avoid sponsored listings and prefer organic listings of same products in prime positions, whereas the negative ad effects can be attenuated in lower positions. To evaluate a seller’s financial benefits, we conduct a model-based ROI analysis with potential ad-induced position shifts. A seller is predicted to make positive net profits with ad-induced position elevation, depending on target ad placements and ratios between unit profit margin and ad cost per click. The results suggest that the value of sponsored listings for a seller mainly comes from position relocation, not from visual prominence at a given position.