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The purpose of this paper is to present an oligopolistic version of the cobweb model that departs from the strict assumptions of perfect competition in the traditional cobweb model.

Introducing a model where n identical producers engage in Cournot competition, with output decisions influencing market prices. The paper retains the original assumptions of naive expectations and a linear model where price expectations of Cournot competitors are made simultaneously with production decisions. The investigation focuses on the model's behavior as the number of producers decreases or industry concentration increases. The authors also show empirical evidence when drawing the data from the pig sector in China and the USA.

The findings indicate that the cobweb model undergoes a transition from divergent to continuous and even convergent as the number of producers decreases or industry concentration increases. The incorporation of costs related to entry and exit from the market contributes to achieving a more stable equilibrium state.

The cobweb model has been primarily studied in an idealized market structure of perfect competition, and the assumptions that they share are not obviously appropriate to many agriculture markets. This study presents an alternative version of the cobweb model in an oligopolistic market that relaxes the strict assumptions of perfect competition. The authors show the dynamics of reduced competitor numbers or increased industry concentration on the convergence of the cobweb model based on subtle variations in parameters.

Over the last years, powerful advances in the area of dynamic games have enriched game theory and made it more applicable to the modeling of real-world competitive strategies. The study of strategic behaviors of firms in an oligopoly market has received little attention, even though real firms have been shown to compete in output and in price in a single industry. The purpose of this study is to propose a game-theoretic approach to studying strategic behaviors of firms in an oligopoly market structure.

This approach was developed to study market dynamics and pricing strategic behavior of firms that have the possibility of deciding to be one of the two types (price-maker or price-taker) and reconsider the choice overtime on the basis of their current insights and knowledge and their experience. Firms try to improve their performance in the competitive market in a strategic way, by considering their steady-state profits and choosing the best type given the other firms’ types, actions and interactions.

The results of the present study confirm the previous study that the Cournot market is a stable market, where each firm can be a price-maker and enjoy individual learning as well as social learning. On the contrary, the market with price-takers only is never stable, and, therefore, the Walrasian equilibrium may not be supported in some instances. The Cournot market loses its stability as the number of firms in the market increases due to the fact that it will be more profitable for a firm to switch to price-taking when the number of firms is high enough. In such a situation, when the number of price-takers increases, there are no stable markets and price dynamics are destabilized.

The study and modeling of real-world competitive strategies would enhance the understanding of oligopoly markets. The study of strategic behaviors of firms in an oligopoly market has received little attention, even though real firms have been shown to compete in output and in price in a single industry as price-takers and price-makers.

This study aims to assess volatility spillovers and directional connectedness between electricity (EPs) and natural gas prices (GPs) in the Canadian electricity market, based on a hydrothermal power generation market strongly dependent on exogenous variables such as fossil fuel prices and climatology factors.

The methodology is divided into two stages. First, a quantile vector autoregression model is used to evaluate the direction and magnitude of the influence between natural gas and electricity prices through different quantiles of their distributions. Second, a cross-quantilogram is estimated to measure the directional predictability between these prices. The data set consists of daily electricity and natural gas prices between January 2015 and December 2023.

The main finding shows that electricity prices are pure shock receivers of volatility from natural gas prices for the different quantiles. In this way, natural gas price fluctuations explain 0.20%, 0.98% and 22.72% of electricity price volatility for the 10th, 50th and 90th quantiles, respectively. On the other hand, a significant and positive correlation is observed in the high quantiles of the electricity prices for any natural gas price value.

The study described the risk to the electricity market caused by nonrenewable source price fluctuations and provided evidence for designing regulatory policies to reduce its exposure in Alberta, Canada. It also allows us to understand the importance of natural gas in the energy transition process and define it as the fundamental determinant of the electricity market dynamic.

This paper aims to examine how the rise of financial technology (Fintech) lending affects bank competition. Moreover, this study also identifies the structure of Indonesian commercial banking sector and the different behaviour of competition among bank groups (based on their size, type and ownership) and the joint impact of COVID-19 due to the rise of Fintech lending.

Using an unbalanced panel data set of 118 commercial banks in Indonesia over the period 2018–2022, both static panel and 2SLS/IV data analysis were used and found that random effect model is the best model.

The results show that the Indonesian commercial banking sector can be considered as monopolistic competition. Moreover, using the Lerner index reveals that the entry of the Fintech lenders increases bank competition. Furthermore, there were different responses to the impact of Fintech lending on bank competition among state-owned banks, private banks, regional development banks and foreign banks. Greater efficiency and stability lead to greater market power. In the meantime, higher level of asset growth, capitalisation and cost-to-income ratio increase the competition. Lastly, higher bank credit growth and lower inflation boost overall bank competitiveness.

This study highlights some policy recommendations for commercial banks to be aware of the coming of Fintech lenders because they have started to increase the market competition. The government should create a more collaborative ecosystem between banks and Fintech lending to anticipate unhealthy competition.

This study will contribute to the literature by expanding the determinants of bank competition by considering the rise of Fintech lending in the market.

This study examines the impact of competition and concentration on bank income smoothing in Central and Eastern European (CEE) countries.

The two-step system GMM method was used to analyse the impact of competition and concentration on bank income smoothing in 17 CEEs from 2004 to 2015.

Loan loss provisions (LLPs) are negatively related to bank competition and concentration. The authors find no evidence for income smoothing using LLPs in a high-competition or high-concentration environment.

A limitation of the study is that the analysis was restricted to commercial banks. The authors did not examine investment banks or microfinance banks in this study. Also, not having access to databases does not allow them to include recent years in the study.

CEE commercial banks will likely keep fewer provisions or engage in under-provisioning when they face intense competition, and this can expose them to credit risk, which may threaten their stability.

This study is the first to investigate the effect of concentration and competition on income smoothing among CEE banks.

This study aims to investigate the role of international price volatility and inventories on domestic market price dynamics in the case of agricultural commodities.

A structural model is employed to uncover relationships among commodity price, price volatility, inventories and convenience yield. Monthly producer price data along with annual data on trade, consumption, inventories and tariffs for 71 countries and 13 commodities covering 2010–2019 are assembled to estimate the model. With a first-stage Least Absolute Shrinkage and Selection Operator (LASSO) estimator to identify the best instrument set, a nonlinear approach is used to estimate the model.

Results show that international market information plays a critical role in domestic market price dynamics. International price volatility has a stronger effect on domestic prices than that of international inventories.

Current upheaval in commodity markets requires an understanding of how prices move together and inventories affect that movement. A country's internal price is not independent of the effects of global market events.

Although hypotheses exist that global market information (volatility and inventories) helps countries manage domestic commodity prices, there have been limited studies on this relationship, especially with a structured model and cross-country data.

Motivated by the wide application of procurement strategies in retailing, this paper aims to examine the effect of procurement strategies on decisions and profits and strategic inventory (SI) is considered.

The game-theoretic models are developed under a two-period fresh product supply chain (FSC), and consist of the mode of purchasing products only in the first period without SI (Scenario S), the mode of purchasing products in every period without SI (Scenario T) and the mode of purchasing products in every period with SI (Scenario TS).

Conducting the calculating and comparing, some major findings can be concluded. In general, two-period purchasing strategies (Scenarios T and TS) promote a higher freshness-keeping effort than the single buying strategy (Scenario S). Regarding the pricing strategy, SI and Scenario S can both contribute to obtaining a lower wholesale price, the retailer's pricing is relatively complicated and hinges on the consumer's sensitivity to freshness-keeping effort and the holding cost. Besides, comparing the sales quantity and the profit, the authors find that Scenario TS stimulates more demands and brings more profits for the manufacturer. However, Scenario TS is not the optimal selection for the reason that SI sometimes hurts the retailer and even the whole supply chain. Whereas, when the holding cost is in a certain range, Scenario TS will lead to a win-win situation.

The main findings of this study can give the enterprises some advice on the procurement strategies of fresh products and the decisions of pricing and the freshness-keeping effort.

The rapid development of the Internet has led to an increasingly significant role for E-commerce business. This study examines how the green supply chain (GSC) operates on the E-commerce online channel (resell mode and agency mode) and the traditional offline channel with information sharing under demand uncertainty.

This study builds a multistage game model that considers the manufacturer selling green products through different channels. On the traditional offline channel, the competing retailers decide whether to share demand signals. Regarding the resale mode of E-commerce online channel, just E-tailer 1 determines whether to share information and decides the retail price. In the agency mode, the manufacturer decides the retail price directly, and E-tailer 2 sets the platform rate.

This study reveals that information accuracy is conducive to information value and profits on both channels. Interestingly, the platform fee rate in agency mode will inhibit the effect of a positive demand signal. Information sharing will cause double marginal effects, and price competition behavior will mitigate such effects. Additionally, when the platform fee rate is low, the manufacturer will select the E-commerce online channel for operation, but the retailers' profit is the highest in the traditional channel.

This research explores the interplay between different channel structures and information sharing in a GSC, considering price competition and demand uncertainty. Besides, we also considered what behaviors and factors will amplify or transfer the effect of double marginalization.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

The network capacity deployed to manage the busy hour (or peak-hour) traffic remains underused during the nonbusy (off-peak) hours. Transferring some traffic from peak-hour to off-peak hours is likely to improve the utilization of network resources during the off-peak hours. This paper aims to examine whether diverting traffic from peak-hour to off-peak hours is possible by adopting the differential pricing policy.

The peak-load pricing theory suggests that the policy of differential pricing is socially optimal when there is peak demand for a particular duration and then there is off-peak demand. In this study, hourly traffic data from both peak and off-peak periods were collected from the Indian telecom service provider, “Aircel.” The paper analyzed the disparity in traffic between peak and off-peak hours using the nonparametric Tukey’s test. An experiment was also conducted to analyze whether a significant shift in telecom traffic occurs from the peak to the off-peak period when a price discount is applied during the off-peak period.

Statistically significant differences were observed in network traffic between peak-hour and off-peak hours. The network utilization of the telecom service provider Aircel was notably lower, particularly during the off-peak hours. The experiment demonstrated a high degree of price sensitivity among telecom service subscribers. Telecom Regulatory Authority of India (TRAI) has not considered network utilization of telecom service providers as a key performance indicator. Based on the outcomes of the study, this paper recommends that TRAI should adopt a more proactive approach by encouraging telecom service providers to follow the policy of differential pricing to enhance utilization of their network capacity.

To the best of the authors’ knowledge, this is the first paper to explore the issue of pricing as a tool for bringing about more uniform movement of telecom traffic, thereby enhancing network utilization within India’s telecommunications sector.