Search results

This research aims to determine the ideal fare for various aircraft itineraries by modeling prices using a neural network method. Dynamic pricing has been studied from the airline’s point of view, with a focus on demand forecasting and price differentiation. Early demand forecasting on a specific route can assist an airline in strategically planning flights and determining optimal pricing strategies.

A feedforward neural network was employed in the current study. Two hidden layers, consisting of 18 and 12 neurons, were incorporated to enhance the network’s capabilities. The activation function employed for these layers was tanh. Additionally, it was considered that the output layer’s functions were linear. The neural network inputs considered in this study were flight path, month of flight, flight date (week/day), flight time, aircraft type (Boeing, Airbus, other), and flight class (economy, business). The neural network output, on the other hand, was the ticket price. The dataset comprises 16,585 records, specifically flight data for Iranian airlines for 2022.

The findings indicate that the model achieved a high level of accuracy in approximating the actual data. Additionally, it demonstrated the ability to predict the optimal ticket price for various flight routes with minimal error.

Based on the significant alignment observed between the actual data and the tested data utilizing the algorithmic model, airlines can proactively anticipate ticket prices across all routes, optimizing the revenue generated by each flight. The neural network algorithm utilized in this study offers a valuable opportunity for companies to enhance their decision-making processes. By leveraging the algorithm’s features, companies can analyze past data effectively and predict future prices. This enables them to make informed and timely decisions based on reliable information.

The present study represents a pioneering research endeavor that investigates using a neural network algorithm to predict the most suitable pricing for various flight routes. This study aims to provide valuable insights into dynamic pricing for marketing researchers and practitioners.

The purpose of this paper is to examine the life and work, both fiction and nonfiction, of the American author Upton Sinclair, for the purposes of better understanding his impact on management theory and practice.

Critical biography is a historiographical approach that analyzes aspects of an individual’s life events and the context that surrounds those events to better understand the contributions of an individual. In this case, this paper analyzes Sinclair’s biography, his work-related fiction and nonfiction and his interactions with business leaders and management thinkers of the day, including scientific management founder Frederick Winslow Taylor, auto industry leader Henry Ford and safety razor magnate King Gillette.

This paper identified four themes which are related to management and workplace history that pervade his fiction and nonfiction writing and link these events to the events of his life as well as the context of the times.

Although others have cited certain aspects of Sinclair’s work for specific purposes, this paper presents a systematic review of Sinclair’s broad oeuvre and its relevance to management and workplace history using a critical biography approach.

This research investigates how subsidy programs in Vietnam's residential electricity market affect consumers' well-being.

Two perspectives are employed: cash transfer and quantity-based subsidy. The effectiveness of cash transfer is measured in three ways: benefit incidence, beneficiary incidence and materiality. The quantity-based subsidy is established under the increasing block rate pricing, with the first two block rates being lower than the marginal cost. To improve the quantity-based subsidy, the research examines the consumer surplus under four proposals.

The results show that both types of subsidies are ineffective in supporting the poor.

In order to achieve a more equal distribution among households, the subsidy program should remove all subsidized blocks and reflect the full marginal cost. Changes should be made to the price structure regarding both marginal price and intervals.

To mitigate the impact of the quantity-based subsidy, the government should improve the cash transfer by reducing extortion and improving targeting efficiency, especially for poor households living in rented houses.

This paper is the first to discuss the welfare effect of the electricity subsidy in Vietnam. First, it comprehensively evaluates the cash transfer subsidy in Vietnam. Second, it suggests a modification in the residential electricity tariff.

For an entrant platform in the on-demand service market, choosing an appropriate employment model is critical. This study explores how the entrant optimally chooses the employment model to achieve better performance and investigates the optimal pricing strategies and wage schemes for both incumbent and entrant platforms.

Based on the Hotelling model, the authors develop a game-theoretic framework to study the incumbent's and entrant's optimal service prices and wage schemes. Moreover, the authors determine the entrant's optimal employment model by comparing the entrant's optimal profits under different market configurations and analytically analyze the impacts of some critical factors on the platforms' decision-making.

This study reveals that the impacts of the unit misfit cost of suppliers or consumers on the pricing strategies and wage schemes vary with different operational efficiencies of platforms. Only when both the service efficiency of contractors and the basic employee benefits are low, entrants should adopt the employee model. Moreover, a lower unit misfit cost of suppliers or consumers makes entrants more likely to choose the contractor model. However, the service efficiency of contractors has nonmonotonic effects on the entrant's decision.

This study focuses on an entrant's decision on the optimal employment model in an on-demand service market, considering the competition between entrants and incumbents on both the supplier and consumer sides, which has not been investigated in the prior literature.

This paper aims to analyze the potentials of dynamic, commitment and revenue-sharing contracts; that a nonrebate offering manufacturer can use to safeguard his profit while his competitor offers customer rebates in a supply chain consisting of two manufacturers and a common retailer.

We consider a two-period supply chain model to explore optimal decisions under eight possible scenarios based on the contract and rebate offering decisions. Because the manufacturers are selling substitutable products, therefore, a customer rebate on one of the products negatively impacts the selling quantity of other. Optimal price, rebate, and quantities are examined and compared to explore the strategic choice for both the rebate offering and non-rebate offering manufacturer. Comparative evaluation is conducted to pinpoint how the parameters such as contract parameters and its nature affect the members.

The results demonstrate that all these contracts instigate the rebate offering manufacturer to provide a higher rebate, but do not ensure a higher profit. If the revenue sharing contract is offered to the common retailer, the effectiveness of the rebate program might reduce significantly, and the rebate offering manufacturer might receives lower profits. A non-rebate offering manufacturer might use a commitment contract to ensure higher profits for all the members and make sure the common retailer continues the product.

The effect of customer rebate vs. supply chain contract under competition has not yet been explored comprehensively. Therefore, the study contributes to the literature regarding interplay among pricing decision, contract choice and rebate promotion in a two-period setting. The conceptual and managerial insights contribute to a better understanding of strategic decision-making for both competing manufacturers under consumer rebates.

This paper aims to compare the efficiency of spatial and nonspatial hedonic price models in capturing housing submarkets dynamics for cities in developing countries. This study expects to contribute to a better understanding of the housing price determinants from both nonspatial and spatial perspectives. In addition, this paper fills a gap in the literature on the study of housing prices from a spatial perspective in Latin American cities.

This study uses a comparative analysis between an ordinary least squares regression and a geographical weighted regression, GWR. The study also assesses the performance of two distinct data sources: the city’s cadastral records and a real estate sales web portal.

The results suggest that compared to the traditional regression model, the spatial regression models are more effective at capturing housing market variations on a fine scale. Moreover, they reveal interesting findings on the spatial varying, sometimes contradictory effects of some housing attributes on housing prices in different areas of the city, suggesting the potential impact from segregation.

The availability of data on housing prices and characteristics in Latin American cities is fragmented and complex. The level of detail, granularity and coverage is not consistent over time. For this reason, this study combines and compares data sets from official and unofficial sources in an effort to close this gap. Likewise, the socioeconomic variables that come from the census must be carefully analyzed, knowing the historical context in which they were constructed, what they represent and their interpretation.

This paper suggests that despite the improvement on the spatial models, the selection of a specific one should always be based on the diagnosis of it as it highly depends on the data used and the objectives of the study.

This study enriches the limited body of literature on spatial hedonic price models of housing in Latin American cities. It also shed light on the importance of spatial approaches to identify complex housing submarkets.

Consumer culture is promoting immediate gratification, and the rise of digital financial services is increasing the risk of indebtedness while debt reduces well-being and affects mental health. The authors assess the effects of consumer information provision, debt literacy, chronic debt and attitudes toward debt on the intent to purchase on credit.

An online survey including an experiment with a credit offer vignette was conducted in a representative sample of Estonia (n = 1204). Treatment conditions depicted either the total cost and duration of the credit agreement or the annual percentage rate.

Receiving modified information resulted in a 26 to 30 percentage points decrease in propensity to purchase on credit. Purchasing on credit was associated with attitudes towards credit and chronic debt, but not with debt literacy.

The findings reveal large effects of information provision and highlight the limited effects of debt literacy on credit decisions. Limitations may emerge from differences in financial regulation across countries.

The authors' results highlight the importance of applying behavioural insights in consumer credit information provision, both in the financial sector and policy. Testing the messages allows having evidence-based solutions that promote responsible purchasing on credit.

The findings call for changes in credit information provision requirements. Their effect is significantly larger compared to the literature, emphasizing the role of credit information provision in less regulated online markets.

This study examines the importance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand. To this end, the authors construct a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model. The model encompasses several essential characteristics, including incomplete financial markets, incomplete exchange rate pass-through, deviations from the law of one price and a banking sector. The authors consider generalized Taylor rules, in which policymakers adjust policy rates in response to output, inflation, credit growth and exchange rate fluctuations. The marginal likelihoods are then employed to investigate whether the central bank responds to fluctuations in the exchange rate and credit growth.

This study constructs a small open economy DSGE model and then estimates the model using Bayesian methods.

The authors demonstrate that the monetary authority does target exchange rates, whereas there is no evidence in favor of incorporating credit growth into the policy rules. These findings survive various robustness checks. Furthermore, the authors demonstrate that domestic shocks contribute significantly to domestic business cycles. Although the terms of trade shock plays a minor role in business cycles, it explains the most significant proportion of exchange rate fluctuations, followed by the country risk premium shock.

This study is the first attempt at exploring the relevance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand.

The study aims to explore the discrepancy between the subjective and objective debt burdens across various household socio-demographic and debt characteristics. Additionally, it seeks to establish an optimal debt service-to-income ratio (DSTI) threshold for identifying over-indebtedness.

This study utilized a sample of 1,004 respondents from a nationwide survey conducted among Polish indebted households. A discrepancy ratio (DR) measure was proposed to evaluate the divergence between subjective and objective over-indebtedness. Binary logistic regression was employed to estimate the probability of being subjectively and objectively over-indebted, as well as the discrepancy between the two measures of over-indebtedness. The study also employed numerical simulations to determine the optimal DSTI threshold for identifying over-indebted households in general and based on their socio-economic characteristics.

The study established a debt service-to-income ratio (DSTI) threshold of 20% to minimize the discrepancy between subjective and objective debt burden, which is lower than thresholds found in other studies aimed at identifying over-indebted households. Age, number of loans, self-perceived needs satisfaction and type of debt were identified as significant socio-economic and debt-related determinants of over-indebtedness. Household socio-economic and debt-related characteristics significantly influence the threshold for identifying over-indebtedness using DSTI. It can vary widely, ranging from as low as 11% for well-educated women with multiple loan commitments to 43.7% for young males with vocational education, high incomes and originating from households with four or more members.

The paper proposes a more comprehensive approach to debt burden analysis by introducing a new methodology for determining a debt service-to-income (DSTI) threshold that could serve as a measure of over-indebtedness based on the discrepancy between subjective and objective over-indebtedness. It also emphasizes the significance of socio-economic and debt-related factors in evaluating subjective and objective over-indebtedness.

This paper analyzes real and welfare effects of a permanent change in inflation rate, focusing on macroprudential policy’ role and its interaction with monetary policy.

While investigating disinflation costs, the authors simulate a medium-scale dynamic general equilibrium model with borrowing constraints, credit frictions and macroprudential authority.

Providing discussions on different policy scenarios in a context where still it is expected high inflation, there are three key contributions. First, when macroprudential authority actively operates to improve financial stability, losses caused by disinflation are limited. Second, a Taylor rule directly responding to financial variables might entail a trade-off between price and financial stability objectives, by increasing disinflation costs. Third, disinflation is welfare improving for savers, while costly for borrowers and banks. Indeed, while savers benefit from policies reducing price stickiness distortion, borrowers are worried about credit frictions, coming from collateral constraint.

The paper suggests threefold policy implications: the macroprudential authority should actively intervene during a disinflation process to minimize costs and financial instability deriving from it; policymakers should implement a disinflationary policy stabilizing also output; the central bank and the macroprudential regulator should pursue financial and price stability goals, separately.

This paper is the first attempt to study effects of a permanent inflation target reduction in focusing on the macroprudential policy’ role.