Long-run Profit Research Articles

Quality driven maintenance policies for a deteriorating system subject to non-self-announcing failures

. In this study, we develop condition-based maintenance policies for a multi-state system subject to continuous-time Markovian deterioration that can result in non-self-announcing degradation including failure. Periodic inspections reveal the true state of the system; “good”, “medium”, “poor”, or “failed”. Upon receiving this piece of information, one of “do-nothing”, “minor repair”, “major repair”, “fix repair”, or “replace” maintenance actions is taken. On one hand, the system brings monetary rewards commensurate with system state–different rewards are earned per unit time spent in different states. On the other hand, quality loss that results from degraded system state is converted into monetary units–inspection and maintenance costs. Therefore, our objective is to determine the optimum inspection period and the corresponding maintenance policy that maximizes the expected long-run profit rate. We provide numerical examples to conduct sensitivity of the optimum inspection period and policy to system parameters, and to present the practical utility of our results.

Incumbent Incentives in Response to Entry

How should an incumbent respond to the arrival of an entrant? A long-standing literature documents a host of potential responses, but little work explores when each strategy will be more or less effective. This paper develops a model of incumbent-entrant competition between vertically and horizontally differentiated firms and applies that model to understand the incentives that shape an incumbent’s response to entry and ultimately, long-run profits. Analysis reveals the conditions under which an incumbent facing the full strategy space of possible exogenous entrants has incentive to attack an entrant and conditions where the incumbent has incentive to retreat. By viewing the incumbent and entrant in terms of their level of vertical and horizontal differentiation, this paper offers a unified view of prior work that generates insights about incumbent responses to entry that have been underappreciated. Further, this unified view offers insight on the effectiveness of a particular incumbent response. Supplemental Material: The online appendix is available at https://doi.org/10.1287/stsc.2022.0060 .

Real Competition and Profit Rate Equalisation: Theory and Evidence from the Norwegian Economy

The existence of long-run profitability differentials in market economies is a fundamental question that all traditions of economic thought since the times of the classical economists have dealt with in some form or another. In consideration of the modern synthesis of the classical views on competition into what has come to be known as the Theory of Real Competition, this article presents both a consistent theoretical basis from which to argue in favour of the tendential elimination of profitability premia across industries, as well as empirical evidence pointing to such conclusion from the Norwegian economy. The data, which covers 26 industries across nearly five decades (1971–2017), is used to estimate average and incremental total long-run profit rate differentials following two distinct methodologies. The first method has been commonly used in the prior literature, and the second has been newly systematised by this study’s author. Both methods are critically scrutinised, and their results compared to allow for a more robust conclusion. The findings suggest that average profit rates exhibit a weak tendency towards equalisation in Norway, and that such tendency is much stronger for incremental profit rates.

A simulation-based approximate dynamic programming approach to dynamic and stochastic resource-constrained multi-project scheduling problem

We consider the dynamic and stochastic resource-constrained multi-project scheduling problem which allows for the random arrival of projects and stochastic task durations. Completing projects generates rewards, which are reduced by a tardiness cost in the case of late completion. Multiple types of resource are available, and projects consume different amounts of these resources when under processing. The problem is modelled as an infinite-horizon discrete-time Markov decision process and seeks to maximise the expected discounted long-run profit. We use an approximate dynamic programming algorithm (ADP) with a linear approximation model which can be used for online decision making. Our approximation model uses project elements that are easily accessible by a decision-maker, with the model coefficients obtained offline via a combination of Monte Carlo simulation and least squares estimation. Our numerical study shows that ADP often statistically significantly outperforms the optimal reactive baseline algorithm (ORBA). In experiments on smaller problems however, both typically perform suboptimally compared to the optimal scheduler obtained by stochastic dynamic programming. ADP has an advantage over ORBA and dynamic programming in that ADP can be applied to larger problems. We also show that ADP generally produces statistically significantly higher profits than common algorithms used in practice, such as a rule-based algorithm and a reactive genetic algorithm.

Optimal Base-Stock Inventory-Management Policies of Cement Retailers under Supply-Side Disruptions

The current study aims to identify some optimal base-stock inventory-management policies that maximize the expected long-run profitability of cement retailers under potential supply-side disruptions. Unlike existing articles, the proposed economic order-quantity model considers periodically varying random demand rates of deteriorating items together with partially back-ordered shortages in the face of those random disruptions. This study computes the global concavity to execute the exemplary aspect for the optimal base-stock level under a slew of cost components and a fixed cycle length. Regarding the optimal pricing-related policies, this study proposes that cement retailers should stock from nearby supplier points. Unlike existing articles, we find that changes to either the unit-holding cost or the unit-lost sales cost have hardly any determining effect on the long-run profitability of retailers. When supply-side disruptions are more likely to occur during peak seasons, this study advocates for a planned capacity addition and higher base-stock levels of cement bags.

Who are the Best Adopters? User Selection Model for Free Trial Item Promotion

With the increasingly fierce market competition, the free trial has been widely applied as an effective incentive strategy to attract users and promote products. By providing opportunities to experience goods without charge, a free trial offers adopters more direct contact with the products and thus raises their willingness to buy. However, as the key point in the promotion process, how to select proper adopters is rarely explored. Empirically winnowing users by their static demographic attributes is feasible but less effective due to the lack of consideration of personalized demands. In this work, we propose SMILE – a tailored free trial user selection model for finding the best adopters promptly. Based on the reinforcement learning (RL) technique, SMILE can consider long-run profits and rely on user-item interactions to suggest actions. Besides, since selecting adopters from the large user candidates set is time-consuming, we design a balanced tree structure that reformulates the user action space. The experimental analysis on three datasets demonstrates the proposed model's superiority and elucidates why reinforcement learning and tree structure can improve performance. Our study shows technical feasibility of constructing a more robust and intelligent user selection model and guides for investigating more marketing promotion strategies.

Short-Run Returns around the Trades of Corporate Insiders on the London Stock Exchange

Previous work examined the long-run profitability of strategies mimicking the trades company directors in the shares of their own company, as a way of testing for market efficiency. The current paper examines patterns in abnormal returns in the days around these trades on the London Stock Exchange. We find movements in returns that are consistent with directors engaging in short-term market timing. We also report that some types of trades have superior predictive content over future returns. In particular, medium-sized trades are more informative for short-term returns than large ones, consistent with Barclay and Warner's (1993) stealth hypothesis whereby informed traders avoid trading in blocks. Another contribution of this study is to properly adjust the abnormal return estimates for microstructure (spread) transactions costs using daily bid-ask spread data. On a net basis, we find that abnormal returns all but disappear.

Productivity Improvement through Work Study Techniques: A Case of a Modern Rice Mill in Ikwo, Ebonyi State

Aim: To explore the use of the work-study techniques in the efficiency improvement in the productivity of a firm or industry. A firm's profit can be increased through productivity improvement by reducing non-value-added operations and adopting a new process for a particular activity. 
 Study Design: Currently, productivity improvement is a crucial factor in industries. Therefore, one of the primary goals of this firm is to improve productivity which enhances its long-run profit. The most critical tool for enhancing the firm's productivity is work study. Hence, this study noted the bottleneck and provided an appropriate technique for productivity improvement.
 Place and Duration of Study: A modern rice mill in Ikwo Ebonyi State Nigeria, between March 2021 and October 2022.
 Methodology: A method study was carried out using well-designed questionnaire techniques with interconnected critical analysis of a particular production line. A reasonable work content reduction was obtained when the proposed improvement method was applied. A stopwatch was used to obtain the time study with much emphasis on the standard time for the operation sequences. As a result, each workstation capacity per day was calculated.
 Results: The result shows that the firm productivity index improved by 14.29% when method study and work measurement were applied in the production line. Implementation of the proposed production line improved productivity from the old production line by 14.29%. Previously, the work content per ton was 4892 mins. Considering the line balancing and critical analysis of the proposed technique, the proposed work content took 3649 mins to be completed, this leads to a reduction of work content by 1243 mins after the line balancing and analysis. The proposed method helps to increase productivity to 14.29% with 25.41% reduction of work content and line balancing.
 Conclusion: In the Ikwo modern rice mill, productivity improvement is considered a critical factor for increasing the profit margin. Therefore, an increase in the profitable index of the firm is the function of productivity improvement, as a result of proper planning and control of the available input variables.

Inventory control policy for perishable products under a buyback contract and Brownian demands

In this study, we analyse the inventory management strategy for perishables, where customer demands are assumed to arrive continuously and modelled by a drifted Brownian motion. We apply the well-known (s, S) continuous review inventory policy; in this policy, an order is placed to increase the inventory level to S as soon as it falls below s. Benefitted from highly developed transportation and logistics industries, it is reasonable to employ the zero-leadtime assumption in our model. In addition, a buyback contract is granted for the retailer to recover the loss from perishing. We illustrate the sales cycle through Markov renewal approach and derive closed-form formulas for long-run profit rates. To evaluate the optimal ordering policy which maximises the profit rate of the retailer, we first analyse the condition for accepting backorder and derive the optimal backorder level s as a function of S, and then solve for the global optimal (s, S) policy through numerical studies. Moreover, we develop a heuristic approach to approximate the optimal policy. Sensitivity analyses are conducted to reveal the effect of different parameters on system behaviour. The conclusions provide managerial insights for formulating inventory policies for perishables under Brownian demand.

The Gamblification of Investing: How a New Generation of Investors Is Being Born to Lose.

Investing and gambling share key features, in that both involve risk, the coming together of two or more people, and both are voluntary activities. However, investing is generally a much better way than gambling for the average person to make long-run profits. This paper reviews evidence on two types of “gamblified” investment products where this advantage does not hold for investing: high-frequency stock trading and high-risk derivatives. This review defines a gamblified investment product as one that leads most investors to lose, that attracts people at risk of experiencing gambling-related harm, and that utilizes product design principles from gambling (either by encouraging a high frequency of use or by providing the allure of big lottery-like wins). The gamblification of investing produces novel challenges for the regulation of both financial markets and gambling.

Does Long-Run Profitability Characterize Small Wind Turbine Investments in the Higher Education Institutions? A GIS Approach to Improve Financial Analysis

Does Long-Run Profitability Characterize Small Wind Turbine Investments in the Higher Education Institutions? A GIS Approach to Improve Financial Analysis

Profitability vs. Stability: The Choice of Trading Strategies in a Capacity Sharing Supply Chain

Supported by a third-party capacity sharing platform, manufacturers can share capacities with others to match the rapidly changing demand. Both the capacity requestor and the capacity provider can choose to seek or wait for matches, forming different trading strategies (capacity- and demand-driven strategies). Based on the game and chaos theories, this paper analyzes the preference of the capacity provider, the capacity requestor, and the capacity platform operator on different trading strategies from the aspects of profitability and stability. It finds that the platform operator values stability much more than profitability, although the latter may reach higher optimal expected profits. The preference of each supply chain member is influenced by the production cost, potential market size, and the limited capacity of the capacity requestor. A stable system can result in higher long-run profits than a profitable system. We further propose the all-win situation for the capacity provider, capacity requestor, and platform operator.

Firms’ response to macroeconomic estimation errors

Initial Gross Domestic Product (GDP) announcements are important economic signals that convey information on the state of the economy but contain substantial estimation error. We investigate how GDP estimation errors affect firms' real decisions and profitability. We find that GDP estimation errors are positively associated with one-quarter-ahead changes in firms’ capital investments, production, inventory, and profitability. However, we observe long-run profitability reversals, which is consistent with initial over (under) production eventually being met with declines (increases) in future profitability. Furthermore, managerial responses to the estimation errors mimic the response to the true component of the GDP signal, suggesting that managers do not filter estimation errors and overreact to both GDP signal components. Our firm-level findings translate to the macroeconomic level, where we find that a long-run reversal follows a positive short-run aggregate investment response to GDP signal components.

Measuring Bias in Consumer Lending

AbstractThis article tests for bias in consumer lending using administrative data from a high-cost lender in the U.K. We motivate our analysis using a new principal-agent model of bias where loan examiners are incentivized to maximize a short-term outcome, not long-term profits, leading to bias against illiquid applicants at the margin of loan decisions. We identify the profitability of marginal applicants using the quasi-random assignment of loan examiners, finding significant bias against immigrant and older applicants when using the firm’s preferred measure of long-run profits but not when using the short-run measure used to evaluate examiner performance. In this case, market incentives based on characteristics that vary across groups lead to inefficient group-based bias.

Analysis of Credit Access, U.S. Agricultural Productivity, and Residual Returns to Resources

AbstractWe examine the relationship credit access has had with the U.S. agricultural productivity and residual returns to resources. Our theoretical analysis suggests that limited credit access can be sufficient to prevent a representative farmer from maximizing both short- and long-run profits. Empirical results show that increased credit access is positively associated with both productivity and residual returns to resources. Our findings imply that one way to stimulate the U.S. agricultural productivity growth is to increase credit access. They also provide strong empirical support for the productivity-stimulating value of programs such as the Farm Service Agency’s Farm Loan Program.

Motives behind the return anomaly around bonus issue announcements: the case of emerging markets

PurposeThis paper aims to examine the stock return behaviour around the bonus issue announcements in eight emerging markets for 2010–2019 by addressing the signalling, cash substitution and liquidity hypotheses.Design/methodology/approachBesides using the standard event study technique to test the presence of an anomaly, country-based regression analyses are performed. Firm-specific factors are used to understand the motive behind the anomaly observed pre- and post-announcement periods. Also, the Amihud illiquidity measure examines the liquidity hypothesis, while standardized profitability and investment ratios compare the long-run operational performance of bonus issuers to test the validity of signalling.FindingsThe findings provide evidence that abnormal returns can be detected ten days before the announcement in some countries, which is a sign of information leakage. The presence of the effect continues only in two countries after the announcement is released. The size of the bonus issue is found strongly significant in most countries, while a weak relation between abnormal return and other factors is detected. Moreover, the signalling hypothesis does not hold in the sense of long-run profitability increase, while liquidity assertion is partially presented.Research limitations/implicationsDue to an inadequate number of announcements in other emerging markets, the number of sample countries is limited by eight.Originality/valueThe research is novel regarding analyzing a wide range of emerging countries with various variables. Also, the paper is distinguished from other studies by applying multiple set of regressions under nine different event windows.

Inventory decision in a periodic review inventory model with two complementary products

Interaction effect across complementary products plays an important role in characterizing the optimal inventory policy. The inventory levels of complementary products are interrelated due to interaction between demand streams. In this paper, we consider a periodic review base-stock policy in the presence of two complementary products with interrelated demands and joint replenishment. Demands are modeled by a Poisson process and any unmet demand is lost. Demands can be in sets of one unit of each or jointly. If an arrival demand requests two products jointly and one of the products is not in stock, then the whole demand is lost. We aim to investigate how this interrelated demand phenomenon influences the optimal base-stock levels and the period length of a periodic review policy. We utilize the renewal reward theorem to derive the explicit expression of the expected profit rate in the system. The goal is to determine the optimal period length and the base-stock levels such that the expected profit rate is maximized. Enumeration and approximation algorithms are employed to find the optimal and near-optimal solutions, respectively. The approximation algorithm is based on a scenario with independent demand processes which results in an explicit expression for the long-run profit per time unit and leads to analytical solutions for optimal policies. Our numerical results reveal that the solutions obtained by the approximation algorithm are close to optimal solutions. Numerical experiences show that the maximum profit in the system is achieved if the proportion of customers with jointly demand increases. Moreover, the interaction effect between demand processes has a significant impact on the control policy performance when the units lost sales and unit holding costs are high, and the demand rare is low.

Double-tolerance design for manufacturing systems

Most production environments are stochastic in nature, due to the randomness inherent in the production processes. One important engineering problem commonly faced by practitioners is to determine optimal engineering tolerances to be used in production. This article develops optimization models for determining tolerance sets to maximize the long-run average net profit on a production line with processing and rework stations, as well as instantaneous inspection and scrap operations. We assume that only one server works at the rework station, and the service times at the processing and rework stations are uncertain, thus, a stochastic queueing system is embedded into the manufacturing process. We also consider the trade-off between the overall production cost and the cost associated with a quality loss in the final product. Our work is the first to introduce the concept of double-tolerance sets to the tolerance design optimization literature. By comparing the proposed double-tolerance model with a single-tolerance model, we investigate the impact of different parameter settings and modeling assumptions on the optimal tolerances through numerical examples and a sensitivity analysis.

Capital (Mis)allocation and Incentive Misalignment

This paper studies how the allocation of capital within firms is shaped by short-termist incentives. We first present empirical evidence on the existence of a within-firm capital (mis)allocation channel caused by distortions of managerial incentives. Using the reform of the FAS 123 accounting statement in the U.S. as a quasi-natural experiment and within-firm variation across investments with different durabilities, we find that firms systematically shifted expenditures towards less durable investments in response to a shift towards more short-term incentives. This reform-induced alteration of the firm-specific capital mix effectively shortened the durability of firms' capital stock. By calibrating a dynamic model of firm investments in which managers determine investment policies, we then seek to quantify the economic impact of such incentive distortions on output, investment and capital (mis)allocation. In our model, bonus-equity incentive contracts induce managers to make quasi-hyperbolic investment decisions and raise differences in the marginal products of capital goods. Relatively small deviations in incentives induced by the accounting reform caused substantial distortions within and across firms. Overall, the reform-induced shift in capital structures away from the social optimum lowered long-run profits by about 0.54% on average.

Evolution Dynamics of Agricultural Internet of Things Technology Promotion and Adoption in China

Internet of Things is the core technology of smart agriculture and can reform and upgrade traditional agriculture for reducing cost, reducing pollution, and increasing productivity and quality in China. From government-led and market economy perspectives, promotion mechanisms and sustainable adoption of agricultural Internet of Things technology are analyzed. In the initial application phase, the promotion of Internet of Things requires government support. For investigating the relationship between the government and farmers, this study builds an evolutionary game model and finds that increases of cost subsidy, farmers’ negative feedback, government’s positive feedback, and chemical agriculture cost can make the model evolve toward the strategy set: farmer adoption and government support. For long-term development, a sustainable model in competitive market is built by competition game and exponential replication equation. This paper analyzes the equilibrium of adoption ratio, long-run profit, and the conversion between equilibrium points under capacity sharing strategy in competitive market. It is also found that the market will eventually evolve to the technology selection strategy whose long-run average profit dominates the market. The innovations are that evolutionary game is used for analyzing the initial stage and competitive game and asynchronous update mechanism are used for analyzing the sustainable development adoption. At last, references are provided for agricultural Internet of Things development policy from the perspectives of initial promotion and long-run sustainability.