Optimal Effort Research Articles

Optimal drilling efforts and industry structure

Optimal drilling efforts and industry structure

Bifurcation and optimal harvesting analysis of a discrete-time predator–prey model with fear and prey refuge effects

<p>In this contribution, the complicated dynamical behaviors and optimal harvesting policy of a discrete-time predator–prey model with fear and refuge effects are formulated. Both the fear and prey refuge effects refer to an interaction between predator and prey. In the first place, the existence and local stability of three fixed points of proposed model are investigated by virtue of our methodology, that is, the eigenvalues of the Jacobian matrix. One step further, it is worth mentioning that the model undergoes flip bifurcation (i.e., period–doubling bifurcation) and Neimark–Sacker bifurcation at the interior fixed point by the utilization of bifurcation theory and center manifold theory. Also, optimal harvesting strategy is investigated, and the expressions of optimal harvesting efforts are determined. Two examples, in the end, are put forward to prove that they are consistent with the previous theoretical results.</p>

Trade credit contracting in a risk-averse supply chain under adverse selection and moral hazard

Trade credit, as an effective tool for integrating and coordinating material, information, and financial flows in supply chain management, is becoming increasingly widespread. We explore how a manufacturer can design optimal trade credit contracts when a risk-averse retailer hides its sales cost information (adverse selection) and selling effort level (moral hazard). We develop incentive models for a risk-averse supply chain when adverse selection and moral hazard coexist, which are then compared with the results under single information asymmetry (moral hazard). Moreover, we analyze the effects of private information and risk-aversion coefficient on contract parameters, selling effort level and the profit or utility of the supply chain. The study shows that when the degree of retailer’s risk aversion is within a certain range, reasonable trade credit contracts designed by the manufacturer can effectively induce the retailer to report its real sales cost and encourage it to exert appropriate effort. Furthermore, we find that the optimal trade credit period, optimal transfer payment, and retailer’s optimal sales effort level under dual information asymmetry are less than under single information asymmetry. Numerical analysis are conducted to demonstrate the effects of the parameters on decisions and profits.

Equilibrium Grading Policies With Implications for Female Interest in STEM Courses

We show that stricter grading policies in STEM courses reduce STEM enrollment, especially for women. We estimate a model of student demand for courses and optimal effort choices given professor grading policies. Grading policies are treated as equilibrium objects that in part depend on student demand for courses. Differences in demand for STEM and non‐STEM courses explain much of why STEM classes give lower grades. Restrictions on grading policies that equalize average grades across classes reduce the STEM gender gap and increase overall enrollment in STEM classes.

Genetic diversity and population structure of a rare and endangered freshwater macrophyte <i>Potamogeton rutilus</i> Wolfg.

Comprehending genetic variation and population structure is paramount for devising optimal management strategies and conservation efforts. In this study, we employed amplified fragment length polymorphism (AFLP) analysis to assess the distribution of genetic variation within and among populations of the rare macrophyte <i>Potamogeton rutilus</i> Wolfg. This species has experienced habitat alterations leading to its disappearance from numerous previously known European locations. Our analysis encompassed eight populations collected from Poland, Lithuania, and Estonia, situated within the central region of <i>P. rutilus</i> distribution. The results of our study indicate that the analyzed populations are characterized by relatively low levels of genetic diversity (the mean of Nei’s gene diversity was 0.031±0.003 and the Shannon’s information index 0.049± 0.004), and intermediate gene flow (Nm = 0.289). Analysis of molecular variance (AMOVA) revealed higher levels of variation among populations (63%) than within populations (37%); PhiPT = 0.634, <i>p</i> < 0.001, which might be attributed to the founder effect, frequent vegetative propagation, and limited seedling recruitment. The results of STRUCTURE, PCoA and NeighbourNet analyses suggest that the genetic structure of the studied populations falls into three main clusters not fully corresponding to geographical regions. The Mantel test did not show a significant correlation between genetic distance and geographical distance among populations. The most geographically isolated population sampled in Poland (ROT) is genetically close to the Estonian population VAL and VIT, although it is located far closer to the stations in Lithuania. Implications of acquired data for the genetic management of the species are discussed.

Optimal production and predictive maintenance decisions for deteriorated products under advance-cash-credit payments

In the 4th industrial revolution era, manufacturers tend to integrate predictive maintenance into production systems to maximize the lifespan of equipment and avoid costly disruptions. Using internet of things sensors and data analyses, predictive maintenance can significantly reduce the production downtime by detecting and predicting system problems before they become uncontrollable, resulting in a lower defective rate. Additionally, an advance-cash-credit (ACC) payment scheme is commonly applied in real-world business transactions to enhance cash flow flexibility among supply chain members. In this study, we developed a supplier–manufacturer chain, wherein a predictive-maintenance-adopting manufacturer received an ACC payment from a supplier, to demonstrate a supply chain management situation within the imperfect economic production quantity framework. The inventory system of the manufacturer was modeled as a cost minimization problem to determine the optimal replenishment cycle time and predictive maintenance effort for deteriorated products. The proposed model also adopted a discounted cash-flow analysis to consider the time value of the cost function, which was proven to be strictly convex in the replenishment time and predictive maintenance effort. Furthermore, a numerical and sensitivity analysis was conducted to illustrate the effectiveness of the proposed model and gain management insights.

Optimal multi-period pricing and sales effort decisions with a logit demand model in an integrated channel

PurposeThe purpose of this study is to provide an optimal joint strategy of multi-period pricing and sales effort for a retailer with a logit choice demand in an integrated channel.Design/methodology/approachCustomer demand is characterized by a logit choice model, it varies over time and is influenced by price and sales effort. The multi-period decision model for the retailer is constructed using a discrete-time dynamic programming method to determine the optimal price and sales effort in each period.FindingsWhen the inventory level does not exceed a certain threshold, decreasing price and increasing sales effort over time or as inventory level increases are the optimal strategies. However, once the inventory level exceeds the threshold, the optimal strategy is to maintain both price and sales effort constant as the inventory level changes or to increase price and decrease sales effort over time. Additionally, the greater the influence of sales effort on demand or the higher the arrival rate of customers, the higher the optimal price and the greater the optimal sales effort level.Originality/valueThis study contributes to the existing research on dynamic pricing and sales effort in integrated channels by incorporating a logit choice model. Furthermore, it provides valuable management insights for retailers operating in an integrated channel to make pricing and sales effort decisions based on inventory level and time period.

Cooperative optimal train operation algorithm for utilizing regenerative braking energy

The efficient use of regenerative braking energy between trains can significantly reduce the net traction energy consumption in urban rail transit systems, and has attracted considerable attention in recent years. An effective way of using regenerative braking energy is to adjust the train's coasting or cruising phase to an acceleration phase to match the braking phase of a nearby train within the same substation. This paper formulates the train driving phase adjustment problem as a cooperative optimal control problem, where a novel energy constraint is introduced to ensure efficient use of regenerative braking energy during the adjusted phase with optimal traction effort. By applying the control parameterisation method and elaborate handling of the energy constraint and the non-smooth control bound constraint, we transform the formulated problem into a nonlinear programming problem. We then use the sequential quadratic programming algorithm to solve the resulting problem, with the gradients of the cost and constraint functions computed using the sensitivity method. Numerical examples based on real-world data for a subway line show the effectiveness of the proposed method and its advantages over a genetic algorithm in terms of energy savings and computational efficiency.

VILLAGE COMMUNITY EMPOWERMENT IN IMPLEMENTING THE REVITALISATION OF LOCAL CULTURE "CLEAN VILLAGE"

This paper discusses community empowerment in supporting local cultural revitalisation. The purpose of this paper is to see what concrete efforts are made to empower the community of Jorong Balaigurah in implementing the revitalisation of local culture "clean village". This empowerment was carried out in Jorong Balaigurah, Agam Regency, West Sumatra Province. Empowerment time is determined for 3 months, from August to November 2023. To obtain empowerment data, observation, interview, and document- tation techniques were used. As an approach used in this Empowerment is a descriptive approach. The results of the Empowerment show the following. First, concrete efforts to empower village communities in implementing "Clean Village" in Jorong Balaigurah include: first, Community Empowerment Plan, identification of potential Jorong Balaigurah community groups, identification of local wealth, optimal community empowerment efforts, socialisation of empowerment; second Bersih (1) gotong royong (2) Local wisdom values, (3) Cookery, (4) Costs, (5) Revitalisation of Local Culture, concrete efforts to revitalise local culture in implementing "Clean Village" in Jorong Balaigurah is by conducting cultural coaching to young gene- rations with the label regeneration or regeneration of gotong royong culture;

Sustainable strategies for green supply chain within the platform economy consider subsidies and marketing efforts.

As consumers' green awareness continues to grow, the level of a product's eco-friendliness and the quality of its marketing have become significant factors in shaping consumers' purchasing decisions. The power structures within the supply chain, as well as corresponding government subsidy policies, are also key elements influencing sustainable strategies for the green supply chain. In a green supply chain comprising one manufacturer and one e-commerce platform, two sales models exist within the online e-commerce platforms: reselling and agency selling. This paper establishes and analyzes three distinct Stackelberg game models, namely: manufacturer-led model without subsidy (bm), manufacturer-led model with subsidy (sm), and platform-led model with subsidy (sp). The results are shown as follows, with the rise of consumers' environmental awareness, more consumers opt for green products, inspiring the manufacturer to increase its optimal greenness and platform to enhance its optimal marketing efforts level. Notably, government subsidies provide a significant stimulus. An increase in the green technology cost coefficient leads to a decline in the manufacturer's profits across all three modes. Intriguingly, the manufacturer's profits are always highest in the sp mode. As the marketing efforts cost coefficient increases, the platform's profits decrease in the bm and sm modes. In contrast, in the sp mode, the platform's profits increase rather than a decrease. The choice of mode primarily depends on the platform's marketing efforts cost coefficient. When this coefficient exceeds a threshold, the platform chooses the sp mode. However, due to the relatively low marketing efficiency in this scenario, the manufacturer prefers the sm mode. For the government, the sp mode involves agency selling, serves as an effective mechanism to redistribute subsidies, thereby yielding the maximum social welfare benefits. Management insights are provided for the manufacturer and platform managers to make decisions about the degree of greenness and marketing efforts level, along with insights for governments to optimize subsidy policies.

PENDUGAAN STATUS STOK DAN INDIKATOR BIOEKONOMI PERIKANAN KERAPU DI TELUK SALEH, NUSA TENGGARA BARAT

One of the challenges in managing small-scale fisheries with limited data is the need for indicators to estimate the stock status and the total allowable catch for sustainable utilization of fish resources. This study aims to estimate the stock status, catch, and optimal fishing effort of the grouper fishery in Saleh Bay, West Nusa Tenggara Province by using the Length-based Spawning Potential Ratio analysis, production surplus model, and bioeconomic approach. Based on the results of this study, it is known that Plectopomus leopardus and Epinephelus coioides are in overexploited condition, while Plectropomus maculatus is in fully exploited status. This study also shows that with a bioeconomic approach, optimal conditions for grouper fisheries in these waters are achieved when the catch is 3,862.1 tonnes per year. The results of this study underline the importance of maximum economic yield-based management as a framework for a fishing quota-based system as an additional instrument in implementing sustainable fishery management in the future. The success of applying the quota system and the total allowable effort is determined by the accuracy of the catch data of small vessels around Saleh Bay under regulatory provisions, supervision and effective law enforcement, the socio-cultural conditions of local communities and the level of compliance with regulations.Keywords: fishing effort, grouper, overfished, quota system.

Signaling green capability with wholesale price or certification

With the rise of environmentally conscious consumers in the digital age, e-commerce platforms have a significant potential to promote green products through marketing. However, these platforms may face information asymmetry regarding the green production and operational capabilities of their manufacturing suppliers, which could hinder optimal marketing efforts. This study explores how manufacturers with high green capabilities can signal their private information to platforms to receive more green marketing support. We first analyze the traditional signaling mechanism using wholesale prices and then examine how the addition of green certification can facilitate the signaling process. We derive the supply chain equilibria under both signaling mechanisms. Our results show that a single wholesale price signal can substantially distort the manufacturer's wholesale price upward, leading to a significant deviation of the retail platform's pricing and marketing decisions from the optimal levels in a symmetric information scenario. However, adding green certification signals can mitigate this undesirable distortion and reduce the efficiency lost due to information asymmetry. Both signaling mechanisms can exacerbate the double marginalization effect, which can be mitigated to a smaller extent by adding green certification in the signaling contract. Our study highlights the signaling role of green certification in the supply chain and sheds light on the practical value of adopting green certifications.

Allocating Mental Effort in Cognitive Tasks: A Model of Motivation in the ACT-R Cognitive Architecture.

Motivation is the driving force that influences people's behaviors and interacts with many cognitive functions. Computationally, motivation is represented as a cost-benefit analysis that weighs efforts and rewards in order to choose the optimal actions. Shenhav and colleagues proposed an elegant theory, the Expected Value of Control (EVC), which describes the relationship between cognitive efforts, costs, and rewards. In this paper, we propose a more fine-grained and detailed motivation framework that incorporates the principles of EVC into the ACT-R cognitive architecture. Specifically, motivation is represented as a specific slot in the Goal buffer with a corresponding scalar value, M, that is translated into the reward value Rt that is delivered when the goal is reached. This implementation is tested in two models. The first model is a high-level model that reproduces the EVC predictions with abstract actions. The second model is an augmented version of an existing ACT-R model of the Simon task. The motivation mechanism is shown to permit optimal effort allocation and reproduce known phenomena. Finally, the broader implications of our mechanism are discussed.

You should reject this paper: Dynamic agency, sequential evaluation, and learning in academic publishing

A variety of real-world situations take the form of repeated principal-agent problems with binary evaluation. I evaluate the principal's optimal evaluation effort and quality threshold for acceptance in the setting of dynamic agency with binary evaluation, focusing specifically on the evaluation by a top academic journal of papers submitted by economists. In the baseline model, the journal should statistically discriminate in favour of high-status economists, by setting an acceptance threshold that declines with their prior estimate of the economist's quality, while evaluation effort should likely increase with perceived author quality, as this provides incentives for authors to exert more effort, which is particularly valuable from the highest-quality authors. However, if a first good publication is more valuable than subsequent publications by the same economist, acceptance thresholds will tend to increase after publication success, relative to the threshold that would have followed a rejection.

Disseminating for impact: creating curriculum activities for translational dissemination for the clinical and translational research workforce.

There has been an increased focus on the practices associated with dissemination for the translation of research to clinical practice and ultimately, policy. Simultaneously, there has been attention placed on the role of the clinical research workforce in supporting optimal dissemination efforts for impact and societal benefit. Curriculums focused on education opportunities for dissemination for translational scientists have been under-reported. The Translational Science Benefits Model (TSBM) is a framework that has been developed to support assessment of clinical and translational research outcomes that measure impact (both in the clinical and community setting) beyond traditional citations in academic journals/bibliometric activities. The TSBM framework outlines more than 30 different facets of impact and can provide a basis for operationalizing broad impacts of research for translational and clinical scientists. Engagement science offers methods and modalities to work with individual stakeholders, and collaborators in a team science model, and engagement with external scholars and society. This article will describe the use of the TSBM framework and engagement science strategies to develop a translational dissemination framework with novel components for evaluation of dissemination and implementation activities. We propose using the translational dissemination framework to guide the development of an educational curriculum for the clinical research workforce. We outline the educational domains and proposed evaluation criteria essential in implementing this innovative translational dissemination educational content for the clinical and translational research workforce.

Developing tools for municipalities to meet carbon targets

Carbon emissions must be cut in half by 2030 to meet the Paris Agreement’s goals, and cities and municipalities are at the forefront of the fight against climate change. In 2017, the energy use of buildings directly accounted for 51% of emissions in the City of Victoria and offered the greatest opportunity for the municipal government to act. Unfortunately, at this point, many cities and municipalities lack the tools and locally relevant data to make effective policy decisions. This research aims to develop a practical framework for analyzing and comparing the carbon impact of policies enacted by municipal governments, and is specifically focused on the energy consumption, and operating and embodied carbon related to single-family dwellings (SFDs) in the City of Victoria, which contains a heterogeneous building stock with construction dates ranging between 1860 to present day. The underlying model has been developed based on statistical modeling and agent-based behavioral responses to different policy actions. The agent-based modelling approach models stock development in terms of new construction, retrofit, and replacement by simulating individual decisions at the building level. The results can be used to identify optimal efforts to minimizing barriers or bottlenecks in achieving low-carbon ambitions while understanding or addressing related aspects such as housing affordability. Municipalities can use the dashboard to identify and prioritize climate solutions that meet their stringent obligations.

Peran Pengawas dalam Meningkatkan Mutu Guru Madrasah di MTs. Negeri 2 Aceh Tamiang

One factor in the low quality of education is the need for more training for teachers in schools and madrasas. This is the task and role of supervisors in developing teachers to improve the quality of education. Therefore, the main focus of this research is to describe the role of supervisors in improving the quality of teachers in madrasas. This research is descriptive and qualitative, taking the location of MTs.Negeri 2 Aceh Tamiang is the research location. Data was collected using interviews and observations of supervisors and madrasa heads as key informants. "Data analysis is guided by Miles and Huberman's theory through data reduction and data presentation followed by conclusions or verification." The end of this paper concludes that supervisors improve teachers' quality at the MTs.Negeri 2 Aceh Tamiang madrasah has made optimal supervision efforts in the academic and managerial fields. It is proven that supervisors have assisted in improving teachers' abilities in preparing the administration of learning planning/guidance programs, implementing learning/guidance, and carrying out assessments of student learning outcomes. Meanwhile, the managerial sector has guided madrasa heads.

Research on digital transformation strategy of the energy industry based on differential game under the dual-carbon background in China

Digital transformation of the energy industry is at the vanguard of promoting green and low-carbon development of energy, and the transformation and upgrading of the energy industry is a critical path to achieve the goal of “dual carbon.” The study takes energy enterprises, digital technology providers, and local governments in China as the research objects, then by constructing a three-party dynamic differential game model, four scenarios are considered respectively. The optimal digitization effort, digitization level, carbon emission reduction expectations, and optimal benefits of each subject are studied. The results show that: (1) Government subsidies function as an effective regulating mechanism, helping regulate the profit distribution of energy enterprises. With government subsidies, cost-sharing contracts can improve the profits of energy enterprises and digital service providers and enhance industry digitization and carbon emission reduction to some extent. (2) When there are government subsidies, the optimal digitalization efforts of energy enterprises and the optimal subsidy coefficient of government under the three decisions are independent of time. The extent to which subsidies improve system members' income is correlated to its game structure and status. (3) In the centralized decision-making state, digitalization level, product emission reduction, and total system profit are higher than in the decentralized decision-making state, which can better help the overall revenue system composed of energy enterprises, digital service providers, and local governments to achieve economic and environmental optimization at the same time and reach the Pareto optimal state. (4) With government subsidies and after the introduction of contracts, when certain conditions are met, the followers' optimal digital effort level, product emission reduction, digitization level, demand and profits of each member are all improved except for the leader's optimal effort level, Pareto improvement of profits of all participating members in the system is realized.

Predictor-based model predictive control for maglev planar motor with a 2D Halbach array mover

Magnetic levitated planar motors are widely employed in flexible manufacturing and photolithography due to their characteristics of high precision, high acceleration, and low maintenance. In this paper, a novel predictor-based model predictive control is proposed to improve the tracking performance of a maglev planar motor which consists of a 2D Halbach array mover and stationary square coils. A Kalman filter and finite spectrum assignment based on an augmented system model are employed to forecast mover’s location by compensating for the system delay due to data transmission and processing. The predicted location is fed back to model predictive control for control optimization under the limit of coil currents. Hildreth’s quadratic algorithm is then applied to solve for the optimal control effort within the constraints. Comparative experiments demonstrate the effectiveness of the proposed control strategy, the total tracking error of which is much smaller than the result of a proportional–integral–derivative controller and standard model predictive control in all tests. Additionally, experimental results show that the proposed predictor-based model predictive control can tolerate higher speeds of the mover while retaining mover’s steadiness. The experimental results suggest the proposed predictor-based model predictive control is an effective path-tracking strategy for magnetic levitated planar motors subject to delays.

MONETARY AND FISCAL POLICY IN THE COVID 19 PANDEMIC ERA PRESENTATION AND ANALYSIS

The research was carried out in order to analyze Indonesian monetary policy and fiscal policy carried out by the Government and Bank Indonesia to anticipate all economic impacts arising from the Covid-19 pandemic which has had a major influence on the Indonesian economy. The method used in this research is descriptive qualitative, namely a research method that tries to understand various concepts found in research using content analysis techniques and library research. The research results show the efforts made by the Indonesian government in the form of monetary policy which is needed in order to stabilize the economic system together with fiscal policy. The Indonesian government together with the Central Bank have made optimal efforts to implement a combination and synergy of these policies to ensure that the country recovers quickly and emerges from a larger economic crisis.