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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.

Different external supply scenarios faced by the retailers will affect their choice of strategy when supply is disrupted and becomes far less than demand, urgently. This study focuses on analyzing both demand and supply side response strategies to meet customer demand and reduce the impact of the shortage during supply disruptions.

According to the quantity of products that the external market can provide, the external supply scenarios were divided into sufficient-type external supply and learning-type external supply. A two-echelon perishable goods supply chain was analyzed, and three kinds of contingency strategy models for downstream retailers were investigated. First, in the sufficient external supply scenario, the optimal price and transshipment quantity to maximize retailer's profits is discussed. Second, in the scenario of learning-type external supply, this study analyzes the optimal decision in three mechanisms of the hybrid strategy and their application: price priority mechanism, quantity priority mechanism and price–quantity balance mechanism. Furthermore, the influence of penalty cost and supply on the priority orders of different mechanisms was studied.

Results show that comparing the two pure strategies (pricing strategy and transshipment strategy)it was noted that the hybrid strategy produces the best results in sufficient-type external supply scenario. In the learning-type external supply scenario, a numerical study has shown the existence of three areas in case of penalty cost and supplier's capacity, and each areas has different priority orders of the three mechanisms. Under the situation of learning external supply, the retailer's optimal strategy is affected by parameters such as penalty cost and supply volume.

The main innovation of the work lies in the following: First; the external supply situation was divided into sufficiency type and learning type, which improves the external situation faced by retailers after the outbreak of emergencies, helps retailers understand the external situation, conforms to the actual situation and has certain practical application value. Second; in the context of learning external supply, there are three coping strategies for retailers, including: Price priority mechanism, Quantity priority mechanism and Pricing and transshipment balance mechanism. This will help retailers make strategic choices, make more scientific management decisions and improve the supply chain emergency management theory. Third; the demand side response was managed through the change of external supply during supply side recovery period and supply disruption. The proposed model enables managing and analyzing supply disruption efficiently and effectively via handling uncertainty by considering all aspects of decision-making process. The proposed model can be applied in various fields such as vegetable and fruit, fresh food, etc.

Our result of this paper aims to indicate that the beta pricing formula could be applied in a long-term model setting as well.

In this paper, we show that the capital asset pricing model can be derived from a three-period general equilibrium model.

We show that our extended model yields a Pareto efficient outcome.

The capital asset pricing model (CAPM) model can be used for pricing long-lived assets.

Long-term modelling and sustainability can be modelled in our setting.

Our results were only known for two periods. The extension to 3 periods opens up a large scope of applicational possibilities in asset pricing, behavioural analysis and long-term efficiency.

The empirical studies of the options market efficiency have reported contradictory results, which sometimes confuse practitioners and academicians. The aim of this study was to clarify several aspects of options market efficiency by exploring the answers to two main questions: Under what conditions is the options market more efficient? Are the discrepancies in the estimated efficiency due to the reality of efficiency or mismeasurement?

Using a meta-analysis approach, 54 studies have been analyzed, which included 1,315 tests. The sum of the observations for all of the tests is 3.7 m observation sets. The effect size (type r) has been used to compare the different statistics in different studies. The cumulative effect size and its diversification have been calculated by the random effects model and Q statistic, respectively.

The most interesting finding of the study was that the options market, in all circumstances, is significantly inefficient. Another important finding was that the heterogeneity of options market efficiency is due to the complexity of pricing relations, test time, violation index and price type. To overcome this heterogeneity and accuracy, future studies should test the no-arbitrage options pricing relations at different times and by different price types, using complex and simple pricing relations and either mean violation or violation ratio efficiency measures.

Public disagreement about the options market efficiency in past studies means that this variable is heterogeneous in different conditions. As a significant contribution, this study develops the literature by proposing the causes of options market efficiency heterogeneity.

This paper aims to explore the relationship between market pricing and design quality within the development industry. Currently, there is a lack of research that examines real estate at the property level. Development quality is widely believed to have diminished over the past decades, while many investors seem uninterested in the design process. The study aims to address these issues through a pricing model that integrates design attributes. It is hoped that empirical findings will invite broader stakeholder interest in the design process.

The research establishes a framework for assessing spatial compliance across residential developments within London. Compliance is assessed across ten boroughs, with technical space guidelines used as a proxy for design quality. Transaction prices and spatial assessments are aligned within a hedonic pricing model. Empirical findings are used to establish whether undermining spatial standards presents a significant development risk.

Findings suggest a relationship between sale time and unit size, with “compliant” units typically transacting earlier than “non-compliant” units. Almost half of the 1,600 apartments surveyed appear to undermine technical guidelines.

It is suggested that an array of design attributes be explored that extend beyond unit size. Additionally, future studies may consider the long-term implications of design quality via secondary transaction prices.

Practical implications include the development of a more scientific approach to design valuation. This may enhance the position of product design management within the development industry and architectural services.

Social implications may include improvement in residential design.

An innovative approach combines a thorough understanding of both design and economic principles.

In most economies, there are rules from the market regulators or government to sell at an equal wholesale price (EWP). But when one upstream channel is facing a negative demand disruption and another positive, EWP can create extra pressure on the disadvantageous supply chain partner, which faces negative disruption. The purpose of this study is to analyse the impact of EWP and the scope of the discriminatory wholesale price (DWP) during disruptions.

For the study, the authors used a dual-channel supply chain consisting of a manufacturer, online retailer (OR) and traditional brick-and-mortar (BM) retailer. Stackelberg game is used to model the interaction between the upstream and downstream channel partners, and the horizontal Nash game to analyse the interaction within downstream channel partners. For modelling asymmetric disruption, the authors took instances from the lock-down and post-lock-down periods of the COVID-19 pandemic, where consumers flow from BM retailer to OR store.

By analysing the disruption period, the authors found that this asymmetric disruption is detrimental to the BM channel, favourable to OR and has no impact on the manufacturer. But with DWP, the authors found that the profit of the BM channel and manufacturer can be increased during disruption. Though the profit of the OR decreased, it was found to be higher than in the pre-disruption period. Under DWP, the consumer surplus increased during disruption, making it favourable for the customers also. Thus, DWP can aid in creating a win-win strategy for all the supply chain partners during asymmetric disruption. Later as an extension to the study, the authors analysed the impact of the consumer transfer factor and found that it plays a crucial role in the optimal decisions of the channel partner during DWP.

Very scant literature analyses the intersection of DWP and disruptions. To the best of the authors’ knowledge, this study, for the first time uses DWP as a tool to help the disadvantageous supply chain partner during asymmetric disruptions. The study findings will assist the government, market regulators and manufacturers in revamping the wholesale pricing policies and strategies to help the disadvantageous supply chain partner during asymmetric disruption.

This study aims to fill a gap in the literature by providing evidence for a “greenium” in the primary Sukuk market. The term “greenium” is defined in the study as the lower cost of capital or reduced yields that green Sukuk may offer compared to non-green Sukuk, reflecting investor willingness to accept lower returns for green investments. Therefore, the main aim of this study is to investigate the potential role of “greenium” as an incentive for issuers to fund eco-friendly projects, contributing to a sustainable environment.

This study uses propensity score matching techniques to provide an accurate comparison of pricing differences between green and non-green Sukuk issued in global primary markets during the period 2017–2022.

The results reveal that green Sukuk signify a “greenium” effect. This suggests that investors find green Sukuk attractive, willing to accept lower returns. Given the positive investor response to green initiatives in the market, issuers can capitalize on the growing demand for green Sukuk, leading to low-cost funding.

This study makes an important contribution to the literature at the interface of Islamic finance and environmental sustainability. In particular, it stands out by focusing on the pricing dynamics in the green Sukuk market and highlights the potential benefits of issuing green Sukuk to help achieve sustainability goals while providing access to lower cost of capital for the transition to a low-carbon economy.

Financial mathematics is one of the most rapidly evolving fields in today’s banking and cooperative industries. In the current study, a new fractional differentiation operator with a nonsingular kernel based on the Robotnov fractional exponential function (RFEF) is considered for the Black–Scholes model, which is the most important model in finance. For simulations, homotopy perturbation and the Laplace transform are used and the obtained solutions are expressed in terms of the generalized Mittag-Leffler function (MLF).

The homotopy perturbation method (HPM) with the help of the Laplace transform is presented here to check the behaviours of the solutions of the Black–Scholes model. HPM is well known for its accuracy and simplicity.

In this attempt, the exact solutions to a famous financial market problem, namely, the BS option pricing model, are obtained using homotopy perturbation and the LT method, where the fractional derivative is taken in a new YAC sense. We obtained solutions for each financial market problem in terms of the generalized Mittag-Leffler function.

The Black–Scholes model is presented using a new kind of operator, the Yang-Abdel-Aty-Cattani (YAC) operator. That is a new concept. The revised model is solved using a well-known semi-analytic technique, the homotopy perturbation method (HPM), with the help of the Laplace transform. Also, the obtained solutions are compared with the exact solutions to prove the effectiveness of the proposed work. The different characteristics of the solutions are investigated for different values of fractional-order derivatives.

Carbon leakage – where multinational enterprises (MNEs) transfer carbon-intensive production activities to countries with laxer emissions constraints for cost purposes – is one of the main mechanisms through which international business (IB) contributes to climate change. This chapter discusses a new policy initiative called the Carbon Border Adjustment Mechanism (CBAM) that the European Union (EU) introduced in May 2023 to fight carbon leakage. The authors analyze the logic of CBAM and discuss how it will likely influence IB both in industries that are directly targeted by CBAM and related industries that will face spillover effects.

This paper forms an e-commerce supply chain that include a manufacturer providing products and an online platform providing service. The reselling platform mode and the agent platform mode are considered through an exploration of the manufacturer Stackelberg (MS), vertical Nash (VN), platform Stackelberg (PS) power structures. The purpose of this paper is to explore the pricing and platform service decisions under different platform selling modes and channel power structures.

Based on the game theory models, this paper investigates the interaction between the manufacturer and the online platform under four different scenarios. The optimal solutions of four models are provided. Through comparison analyses, this paper evaluates the impacts of platform selling mode and channel power structure on the pricing and platform service decisions and the members’ profits.

The manufacturer prefers the MS power structure in any platform mode. The online platform prefers the PS (MS) power structure under a low (high) service cost efficiency in the reselling platform mode, while prefers the PS and VN power structures in the agent platform mode. Moreover, the manufacturer prefers the agent (reselling) platform mode under a low (high) service cost efficiency in any power structure. The online platform prefers the reselling platform mode in the MS and PS power structures, while prefers the reselling (agent) platform mode under a low (high) service cost efficiency in the VN power structures.

The analysis result provides important managerial implications that help the supply chain members develop a better understanding of the selection of the platform selling mode and the effect of the channel power structure in the presence of platform service.