Price Incentives Research Articles

Public transport pricing incentive schemes in a competitive market.

In many countries, public transport (PT) services are offered by multiple operators with different modes, such as trains, metros, and buses, which are interchangeable across a single journey. This paper presents a model with one origin (O)-destination(D) path operated by two operators, each of which is responsible for different parts of the OD journey. One operator competes with potential third-party transport companies by offering discount incentives. Such an abstract settings has not been discussed in the literature. We explore how prices, demand, profits, and social welfare change with discounts through a theoretical analysis and numerical simulations under five scenarios. The results indicate that in all the scenarios the operator offering a discount incentive can always attract more passengers and increase its profits. Moreover, reducing the service time of operators offering discounts contributes to an increase in social welfare. Notably, this paper deduces for the first time that the demand scenario aimed at maximizing social welfare is twice as high as that aimed at maximizing total profit. However, in the scenario of maximum social welfare, the profitability of operators becomes challenging.

Scale sensitivity of ethanol production via consolidated bioprocessing with consideration of feedstock cost

AbstractWe examine feedstock cost and minimum selling price for ethanol production from corn stover as a function of scale, stover yield, participation rate, and price incentives for two conversion technologies: a conventional base case featuring thermochemical pretreatment with added cellulase, and an advanced case featuring consolidated bioprocessing with cotreatment (C‐CBP). Delivered feedstock cost ranged from $85 Mg−1 at small (10 million gallons year−1 or ~38 million L year−1) scale with high yield and participation rates to $124 Mg−1 at large scale (60 million gallons year−1 or 227 million L year−1) and low yield and participation rates. The minimum ethanol selling price (MESP) was approximately twofold lower for the advanced case compared with the base case. The payback period was several times lower for the advanced case compared with the base case, with increasing disparity at smaller scales, and was highly sensitive to ethanol price supports. For both C‐CBP and the conventional processing paradigm, MESP decreased with increasing scale, indicating that the cost penalty due to higher feedstock transport distances was more than outweighed by lower capital costs. However, the cost penalty for operation at small scale, expressed in $ gallon−1 ethanol, is lower for C‐CBP than for the conventional paradigm by roughly twofold. Particularly for initial applications of C‐CBP, we speculate that this cost penalty will likely be modest compared with the anticipated benefits of small‐scale operation such as increased opportunity to use existing infrastructure, easier plant siting and supply chain establishment, and lower total investment required.

Mitigating power grid impact from proactive data center workload shifts: A coordinated scheduling strategy integrating synergistic traffic - data - power networks

The widespread adoption of cloud computing has markedly escalated the demand for Internet services, rendering Internet Data Centers (IDCs) a critical component in the consideration for demand response (DR) initiatives and grid energy management. This work proposes a flexible scheduling strategy integrating data, traffic, and power networks (DN-TN-PN) to mitigate the impact of proactive IDC workload transfers on power system balance. The spatial-temporal transfer characteristics of EV charging and discharging loads are utilized to track the proactive spatial-temporal transfer of IDC workloads. Considering the influence of weather factors and traffic congestion on EV travel time, an incentive pricing model for EV users is introduced to alleviate bus load fluctuation and line congestion in the distribution network. Numerical simulations demonstrate that the proposed EV pricing strategy, which accounts for the coupled DN-TN-PN, reduces IDC-induced load fluctuations by over 20 % and decreases transmission line occupancy by approximately 15 %, opening up more opportunities for the implementation of DR programs.

Electricity user behavior analysis and marketing strategy based on internet of things and big data

This paper examines power user behavior and the design of marketing strategies, using a case study of Smart Community A. We explore how advanced analytical models are used to enhance energy efficiency and user services. First, we apply spectral clustering to refine user segmentation and identify distinct electricity consumption patterns among different groups. Then, the Hidden Markov Model (HMM) analyzes user behavior, uncovering shifts in consumption habits and enabling personalized service offerings. Next, the ARIMA model predicts electricity consumption trends, guiding grid scheduling and resource allocation. Based on these analyses, we develop targeted marketing strategies, such as dynamic pricing and energy-saving incentives, which boost user engagement and reduce energy usage. Through an IoT and big data-driven interactive marketing platform, we enhance user experience and foster a culture of energy conservation. Finally, a feedback mechanism ensures continuous improvement and maximizes the effectiveness of the marketing strategies.

Hybrid Modeling Techniques for Municipal Solid Waste Forecasting: An Application to OECD Countries

Abstract Accurate forecasting of municipal solid waste (MSW) generation is critical for effective waste management, given the rising volumes of waste posing environmental and public health challenges. This study investigates the efficacy of hybrid forecasting models in predicting MSW generation trends across Organization for Economic Cooperation and Development (OECD) countries. The empirical analysis utilizes five distinct approaches – ARIMA, Theta model, neural networks, exponential smoothing state space (ETS), and TBATS models. MSW data spanning 1995–2021 for 29 OECD nations are analyzed using the hybrid models and benchmarked against individual ARIMA models. The results demonstrate superior predictive accuracy for the hybrid models across multiple error metrics, capturing complex data patterns and relationships missed by individual models. The forecasts project continued MSW generation growth in most countries but reveal nuanced country-level differences as well. The implications for waste management policies include implementing waste reduction and recycling programs, investing in infrastructure and technology, enhancing public education, implementing pricing incentives, rigorous monitoring and evaluation of practices, and multi-stakeholder collaboration. However, uncertainties related to model selection and data limitations warrant acknowledgment. Overall, this study affirms the value of hybrid forecasting models in providing robust insights to inform evidence-based waste management strategies and transition toward sustainability in the OECD region.

Collaborative optimization for energy hub and load aggregator considering the carbon intensity-driven and uncertainty-aware

To achieve optimization operation between the energy hub operator and the load aggregators, this paper proposes a collaborative model for the energy hub and load aggregator considering the carbon intensity-driven and uncertainty. Firstly, a time-coupled carbon emission flow model for energy storage is proposed to cope with the change in carbon intensity at the injection node. Meanwhile, a carbon intensity-based incentive price is developed for interruptible loads with diverse carbon intensity. Secondly, the Wasserstein metric-based distributionally robust optimization method is leveraged to height against the energy hub uncertainty, in which the infinite-dimensional distributionally robust optimization model is reformulated into a tractable linear programming. Thirdly, considering the multi-entity characteristics of energy hub and load aggregators, a collaborative optimization method based on the alternating direction method of multipliers algorithm is constructed. Finally, to meet the convergence requirements of the alternating direction method of multipliers algorithm, the iterative convexification algorithm is applied to transform the nonconvex bi-level energy hub-users model into an iterative convex model by avoiding binary variables and big-M parameters. Consequently, the energy hub and load aggregator can operate cooperatively and protect privacy in uncertain conditions. Simulation results verify the effectiveness of the proposed model and method. Simulation results demonstrate the effectiveness of the proposed model and method. Specifically, the iterative convexification algorithm achieved a profit of ¥1653.82 for the load aggregator, which is 24.4 % higher than the profit obtained by CONOPT (¥1329.73) and 20.3 % higher than that obtained by IPOPT (¥1374.69), thus providing substantial advantages over traditional nonlinear solvers.

Two-stage low-carbon economic dispatch of an integrated energy system considering flexible decoupling of electricity and heat on sides of source and load

Under the goal of "double carbon", in order to further enhance the level of new energy consumption and solve the problem of restricting the flexibility of the system by "ordering power by heat" of combined heat and power (CHP) units, a low-carbon economic planning strategy with flexible decoupling of electricity and heat is proposed, by introducing a new type of electric-thermal coupling equipment on both sides of the source and load. Firstly, Consideration of the low-carbon and environmentally friendly characteristics of green ammonia production and ammonia-doped combustion technologies, a wind power(WT) – power to ammonia(P2A) - CHP units - thermal power (TH) units joint operation strategy is proposed on the source side. This strategy realizes the conversion of abandoned wind to green ammonia to ammonia coal hybrid generation, the decoupled operation of CHP units and promotes the consumption of wind power and the low-carbon operation of the system. Secondly, A dynamic incentive demand response model is developed to meet the demand of high proportion distributed PV in situ consumption on the load side. The dynamic incentive price guides the distributed power-to-heat load to change the response capacity, tracks the abandonment of wind and light, realizes the flexible conversion of power and heat load, and cooperates with the source side to promote the coupling operation of electric pyrolysis. On this basis, consider the flexible decoupling capability of electric-heat coupling equipment on both sides of the source and load to establish a two-phase low-carbon scheduling model for the day-before and day-after phases. In the day-ahead phase, the source-side electric-thermal-ammonia joint operation strategy is considered, and the electric and thermal energy supply plans are adjusted centrally; In the intra-day phase, the flexible adjustment range of power-to-heat devices and the heat load inertia on the load side are taken into account, and the electricity and heat planning strategies are adjusted in a distributed-centralised manner in conjunction with the source side. Finally, through the simulation of different cases, the results show that compared with the traditional electric heating system, the total cost of the system considering the scheduling strategy proposed in this paper decreases by ￥826,900, the carbon emission decreases by 1.2t, and basically realises the consumption of wind power and distributed photovoltaic power output. The proposed scheme reduces carbon emissions, promotes the consumption of wind power and distributed photovoltaic output, and is able to reach the goal of low-carbon economic dispatch.

Electric Vehicle Integration in Coupled Power Distribution and Transportation Networks: A Review

Integrating electric vehicles (EVs) into the coupled power distribution network (PDN) and transportation network (TN) presents substantial challenges. This paper explores three key areas in EV integration: charging/discharging scheduling, charging navigation, and charging station planning. First, the paper discusses the features and importance of EV integrated traffic–power networks. Then, it examines key factors influencing EV strategy, such as user behavior, charging preferences, and battery performance. Next, the study establishes an EV charging and discharging model, with particular emphasis on the complexities introduced by factors such as pricing mechanisms and integration approaches. Furthermore, the charging navigation model and the role of real-time traffic information are discussed. Additionally, the paper highlights the importance of multi-type charging stations and the impact of uncertainty on charging station planning. The paper concludes by identifying significant challenges and potential opportunities for EV integration. Future research should focus on enhancing coupled network modeling, refining user behavior models, developing incentive pricing mechanisms, and advancing autonomous driving and automated charging technologies. Such efforts will be essential for achieving a sustainable and efficient EV ecosystem.

Cost of Cultivation is Rising or Profitability Rising for Major Pulse Crop? A Case from Rajasthan, India

Background: The basic challenge every farmer in India faces is to increase profitability level and minimize the cost. For this, it is essential to know how the cost of cultivation and profitability is changing of crops over a period of time. The present study attempted to estimate the cost of cultivation, cost of production and returns of major pulse crops in the Rajasthan state. For workout the economics of pulses crop, secondary data was collected from 2000-01 to 2021-22 which is compiled from various sources and publications for profitability analysis of pulse crop. Methods: The study was conducted in Rajasthan state and analysis done for 22 years used the “Cost of Cultivation of Principal Crops in Rajasthan” by DES, New Delhi uses different cost concepts for estimating costs and returns. In the present study, the cost C2 was considered for computing profitability. Cost C2 in CCPC data covers all the variables and fixed costs. Result: The actual cost of production of gram crop increased from Rs. 1772.32 per quintal in TE 2003 to Rs. 3650.5 per quintal in TE 2021. Return per rupee invested increased from 2.52 to 3.01 during TE 2003 to TE 2021. Cost of production of urad crop had increased from Rs. 2520.63 per quintal in TE 2003 to Rs. 7385.45 per quintal in TE 2021. The return per rupee invested in cost A2 had reduced from 2.14 in TE 2003 to 1.99 in TE 2021. Moong crop also showed increasing trend for cost of production from Rs. 2696.08 per quintal in TE 2003 to Rs. 7385.45 per quintal in TE 2021. Return for each rupee invested a increased from 2.10 in TE 2003 to 2.14 in TE 2021. Return per rupee invested was not profitable for the farmers for urad. Therefore, proper processing and procurement policy for these crops grown by the farmers should be implemented. Urad crop need more efficiently technological breakthrough to reduce cost of production and proper price incentive to pace with other pulses crops in the state.

Will e-consumers wait longer for a more sustainable on-demand food delivery? A choice experiment using green information

ABSTRACT The rapid growth of on-demand food delivery has sparked concerns about its societal and environmental impact. While alternative solutions like group ordering and electric bikes aim to address these issues, their adoption is hindered by inconveniences, mainly due to the longer delivery times, which are critical in food delivery. Price incentives such as discounts have traditionally been used as compensation, but questions about their long-term feasibility persist. This study assesses whether providing carbon footprint information can reduce the reliance on price incentives, especially when compensating for longer delivery times. Through a mixed-design experiment with 215 e-consumers in Greater Jakarta, we found that green information effectively encourages more sustainable delivery choices, similar to discounts. However, combining green information with discounts adds little value, suggesting that emphasizing green information alone could reduce financial costs and foster intrinsic motivation. Additionally, female and younger consumers are more responsive to green information, indicating the potential for targeted sustainability efforts in the on-demand food delivery sector.

Reducing meat consumption in restaurants: Exploring the default mechanism in a surprise menu, combined with effort and price incentives

Default options can be effective behavioural nudges in various contexts. Re-designing restaurant menus with vegetarian options as the default can be a promising route to reduce meat consumption. However, it is not yet clear whether the default also works when customers do not know what specific menu items they receive, as is the case in surprise menus. Furthermore, we question whether the effectiveness of a vegetarian default on an individual's choice for a vegetarian dish can be further strengthened when the default mechanism is deployed together with other strong intervention mechanisms: price incentives and imposed effort.In a real-life field experiment, we tested the effectiveness of the default for a Chef's Menu where consumers only know that the dish is vegetarian or that it contains meat or fish. Moreover, we tested the effect of the default together with either a supplemental price needed to be paid for the meat option, or an increase in the effort to switch to the alternative meat options (making them less easy to order compared to the vegetarian option). Analyses of the sales data show that significantly more vegetarian options were ordered in the weeks that the vegetarian dish was the default. However, neither the price incentive nor the increased effort seemed to strengthen the original default effects. The current study shows the strength of a default intervention, also in the case of a surprise menu, and provides insights for practitioners to maximize the effectiveness of a default.

Impact of a nudge-based food environment intervention in a hospital convenience store on staff’s food intake and Na/K

BackgroundA food environment intervention using nudge tactics was implemented at a hospital convenience store (CVS) in Tokyo to improve employees’ eating habits. The objective of this study was to evaluate its effects on the urinary sodium-to-potassium ratio (Na/K), food intake, eating attitude, and behavior.MethodsUsing a pre–post design; the intervention incorporated nudge tactics, healthier options, easy-to-pick food placement, and eye-catching information. We also used price incentives. The primary outcomes included changes in Na/K and sodium and potassium excretion assessed using spot urine samples at health checkups. Secondary outcomes were changes in staff food intake, eating attitude, and behavior which were assessed using questionnaire surveys. All outcomes were evaluated statistically. Furthermore, we investigated how the intervention led to outcomes using path analysis.ResultsA total of 140 participant (52men and 88women) were analyzed. Significant changes were observed in Na/K (3.16 to 2.98 in median, p = 0.02) and potassium excretion (43.4 to 45.2 mmol/day in mean, p = 0.03). However, sodium excretion did not change significantly. The intake of fruits and dairy products increased with improved self-efficacy. The most influential factor for lowering Na/K and increasing potassium excretion was information from the CVS; purchasing “balanced meals” to lower Na/K and salads to increase potassium excretion were second.ConclusionsFood environment intervention using nudge tactics can improve staff’s food intake and lower Na/K.Trial registrationRegistration number: UMIN000049444 (UMIN-CTR).Date of registration: November. 7. 2022.

Managers’ Stock Price Incentives and Earnings Management Using Tax Expense

ABSTRACT This study examines the association between stock price incentives (portfolio delta) and earnings management using tax expense, as well as whether this association varies with opportunities to manage earnings. Prior research suggests stock price incentives provide a positive “reward effect” and a negative “risk effect,” causing managers to trade off these countervailing effects when managing earnings. We posit that greater opportunities to manage earnings alter the risk-reward tradeoff related to portfolio delta, potentially changing the association between stock price incentives and earnings management. We do not find a significant association between stock price incentives and earnings management using tax expense on average. However, the association is positive and significant when tax-related earnings management opportunities are sufficiently high, consistent with opportunities mitigating the risk effect of delta. Collectively, our results suggest that managers respond to stock price incentives differently depending on their opportunity sets. Data Availability: Data are available from the public sources cited in the text.

Behavioral Efficiency and Residential Electricity Consumption: A Microdata Study

Sustainability requires that policy makers be able to use market signals to implement energy and environmental policy and that energy consumers respond rationally to these signals. Therefore, it is essential to understand how consumers’ responses to market signals are formed. We propose a new model to measure behavioral efficiency in residential electricity consumption derived from the individual householder indirect utility function. This leads to a pair of simultaneous stochastic demand frontiers for electricity consumption (kWh) and power demand (kVA). Each is a function of power demand (standing) charges and energy demand (running) charges together with the net income after demand charges, the stock of appliances and household characteristics. We estimate the model using two samples of household responses, each of which represents around one percent of the total national population available, and we also pool these samples using pseudo-panel data procedures. We demonstrate how the resulting elasticity and efficiency estimates are related to the theory of behavioral agents from recent developments in behavioral economics. These developments also use the individual indirect utility function to derive propositions based on internality and hyperbolic discounting. The econometric estimates permit the calibration of the individual welfare effects of policy initiatives using carbon tax and price incentives with behavioral agents.

Online budget-limited pricing incentives for remote mobile sensing

Online budget-limited pricing incentives for remote mobile sensing

Fossil Fuel Subsidy Inventories vs. Net Carbon Prices

Price incentives for reducing fossil fuel related carbon emissions are an important component of effective and efficient climate policy. Current incentives stem from a mixture of energy taxes and carbon pricing (incentivizing less emissions) and diverse support measures for fossil fuels (incentivizing more emissions). We develop a net carbon price indicator that complements existing subsidy and carbon pricing indicators. It can be calculated on different aggregation levels and compared across countries. We calculate the different components and our aggregate indicator for the year 2018 and for eight countries including the worlds’ six largest emitters. Our analysis reveals large differences in net carbon prices across countries and across sectors within countries. We argue that the sectoral differences can inform about adequate national policy reforms while the aggregate national indicator can be useful for international negotiations about comparable national efforts.

Pursuing circular economics through the integrated crop-livestock systems: An integrative review on practices, strategies and challenges post Green Revolution in Indonesia

The Green Revolution, driven by advanced technology, substantially increased food production in Asian developing countries, including Indonesia. Nevertheless, it also resulted in environmental consequences, notably soil fertility degradation, threatening future agricultural productivity. As an alternative approach, the Integrated Crops-Livestock System (ICLS) holds promise for simultaneously enhancing crop and livestock yields while upholding environmental sustainability. This article investigates the significance of ICLS as a sustainable agricultural solution in the context of circular economics post Green Revolution era in Indonesia. This study employs an integrative literature review, encompassing secondary data analysis, research findings, and publications, to underscore the potential of ICLS in Indonesia and beyond. Despite its potential, the limited adoption of ICLS among Indonesian farmers is attributed to factors such as inadequate knowledge and skills, insufficient policy support, and inadequate dissemination and promotion efforts. To promote widespread ICLS implementation, robust dissemination strategies are imperative, encompassing technical guidance, counseling, training, and on-farm demonstrations. In addition, policy support, including accessible credit and price incentives, is essential to incentivize farmers to embrace ICLS practices. This article underscores the relevance of circular economics within the context of integrated farming and provides insights for policymakers and stakeholders aiming to promote sustainable agriculture in Indonesia's post Green Revolution era.

Gum Arabic Producers' Opinions and Views towards Gum Arabic Marketing Policies-and Strategies, Sudan

The study aimed to conduct a comparative analysis of the opinions and views of gum Arabic producers towards Gum Arabic marketing policies in Sudan. Primary data were collected in 2016, using a structured questionnaire and 150 gum Arabic producers were interviewed, representing 20% of the targeted population in the study. Secondary data were collected from related official documents. Descriptive statistical analysis was used to investigate the opinions views and socio-economic characteristics of the stakeholders. The results indicated that about (97%) of the respondents preferred the free-trade policy to concession as it gives more price incentives to producers (98%), encouraging producers (98%). There are 98 % of the producers conserve and reforest instead of cutting Hashab trees. All the respondents confirmed the prices are higher post-free-trade than pre-free-trade period. 74% of the gum producers were economically active including the young; this indicated continuing to preserve indigenous knowledge techniques of gum Arabic production across generations. The study recommended continuing the free-trade policy in the production and marketing of gum Arabic, involving the private sector to provide credit to the gum Arabic producers to expand their gum production area. Improve infrastructure and basic services in the gum Arabic production areas.

Optimizing resource allocation for cluster D2D-assisted fog computing networks: A three-layer Stackelberg game approach

Resource management in fog computing is a highly challenging issue. Resource constraints of fog devices, the dynamic and diverse nature of workloads such as data-intensive, computationally intensive, and latency-sensitive applications, and the unpredictability of fog computing environments make it more challenging. How to collaboratively schedule edge, and end multi-layer ubiquitous computing resources to break through single node scale and resource bottlenecks to further improve computing performance also needs to be addressed. In this paper, we leverage idle resources on the user side, and study the resource allocation problems in the D2D-assisted fog computing networks. Firstly, we use an improved Louvain algorithm to cluster users and select the D2D device with the highest priority in each cluster as the cluster head to assist fog computing, where cluster heads can act as both servers and relays. Secondly, considering that fog nodes and D2D devices have limited resources and are not obligated to share their resources for free, we propose a price incentive method to construct a three-layer Stackelberg game model that maximizes the benefits of fog nodes and cluster heads while minimizing user costs. Then, we use the Lagrange multiplier method and the Karush–Kuhn–Tucker (KKT) conditions to solve the equilibrium point of the model to achieve our goal. Finally, the simulation results show that our proposed scheme markedly decreases the overall system cost in comparison to the four benchmark schemes. Moreover, in various scenarios the total cost of our scheme consistently remains lower than the other four schemes, affirming the efficiency of the scheme proposed in this paper.

The Influence of Marketing Stimulation and Situational Factors on Impulse Purchasing Behavior of Vietnamese Consumers

Today, with the increasingly improved standards of living, consumers’ demands are becoming more diverse. As daily purchasing activities are becoming less planned, impulse purchases are increasingly the norm. This paper focuses on factors influencing consumers’ impulse purchase behavior in three of Vietnam’s largest cities (Hanoi, Da Nang and Ho Chi Minh) based on a review of previous research as well as an analysis of effects of marketing stimuli and situational factors. Data were obtained from 264 Vietnamese consumers who have made impulse purchases using an online survey. Hypothesis testing and path modeling demonstrated that among four marketing stimuli factors, except for price incentives, all have a significant positive impact on impulsive purchase behavior. In addition, time pressure and ability to pay have a significant impact on impulsive purchase behaviors of urban Vietnamese consumers. These findings enrich the extant knowledge on the relationship between marketing stimulation, situational factors and impulse purchasing behavior. They also have important implications for firms that aim to stimulate changes in consumers' psychological desires, thereby stimulating consumers to engage in impulsive purchase behavior.