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The provision of fair and remunerative prices to farmers through government intervention is one of the key debates to address the farmers' distress in India. This article identifies how different marketing channels are responsible for higher price realization over the officially announced minimum support price (MSP).

The study uses the NSSO-SAS, 2012–13 and NSSO-SAS, 2018–19 for Aggregate level data and Unit Level Data on the Situation Assessment Survey of Farmers' households. It uses logit regression to determine the factors responsible for better price realization.

Our major findings indicate that two factors importantly determine better price realization than MSP. Firstly, government agencies provide better prices for crops covered by MSP, such as paddy, wheat and cotton. However, the probability of receiving higher prices increases for some crops if the farmers belong to the upper land size classes and upper social category. Secondly, jowar, bajra, maize and ragi, other important crops that don't benefit from government agencies, may require higher levels of procurement at the state level.

The present study only analyzes selected major crops. Distance is an important factor in choosing a marketing channel that is not incorporated due to unavailability in NSS Data.

The study is based on the latest original empirical evidence and sheds light on the variation in price realization in different agricultural marketing channels in India.

The current literature has not investigated the perceived value of energy efficiency by households, regardless of financial benefits. Furthermore, there is a severe lack of research that investigates the effectiveness of the current format of EPC-labels. Therefore, the purpose of this paper is twofold: to study how households value energy efficiency in the housing market, regardless of price effects.

This study uses multiple hedonic regression models to analyse 706,778 Flemish properties for sale or rent between 2019 and 2023. The data is provided by Immoweb – the largest online real estate platform in Belgium. Given that the selling market is driven by different mechanisms than the rental market, the data set was divided in sold (522,164 listings) and rented properties (184,614 listings).

The ambiguous results of the A-label in the selling market indicate that the “class evaluation effect” found in related markets which use labels (e.g. household appliances) is also present in the housing market. However, the results of the other (lower) labels clearly show that owners do value energy improvements within labels, and this effect becomes stronger as the EPC-label becomes better. The rental market shows the opposite results. Energy improvements are only valued if they translate into a financial benefit. Taking these findings into account, the second part of this research shows that rescaling the EPC-label creates an incentive for improvements within labels.

This paper provides novel insights by studying the perceived value of energy efficiency in the absence of financial benefits and critically studying the effectiveness of the EPC-labels in their current shape. By investigating both the sales and rental market, the authors are able to make a comparison which creates valuable insights for academia, governments and real estate professionals.

This paper aims to model the price of cellar tours using a hedonic pricing approach. The authors analyze the complex relationship between the price of an add-on (here, cellar tours) and the price of the reference product (here, wine).

Thanks to a large database containing information on about 1,000 winery experiences, the authors regress the price of cellar tours on wine prices and on a broad set of objective characteristics that are (1) tour specific and (2) common to all tours offered by the winery. These exogenous controls include the type and style of experience offered, amenities and winemaking characteristics.

The authors show that the price of cellar tours follows the price of the most expensive wine sold by the winery, which is a proxy for reputation. The authors find that one of the main determinants of cellar tour prices is visit length: wineries charge more for longer experiences. The number of wines tasted during the visit also increases the price. Prices are higher in places where there is a high level of wine tourism activity, which might be a sign of authenticity.

Wine producers in different countries need to gain insights on how to price cellar tours, which are composite goods. The results can help practitioners price their winery experience according to common practices in different wine regions. The results may also be of interest to professionals in the tourism sector who are in charge of the pricing of by-products (e.g. tee-shirts, books, etc.), or for luxury fashion labels extending their brand in the catering industry with cafes and restaurants.

To the best of the authors’ knowledge, this paper is the first empirical analysis that examines the complex relationship between the price of an add-on and the price of the reference product in the context of wine tourism.

This study aims to solve optimal pricing and power bidding strategy problem for integrated combined heat and power (CHP) system by using a modified heuristic optimization algorithm.

In electricity markets, generation companies compete according to their bidding parameters; therefore, optimal pricing and bidding strategy are solved. Recently, CHP units are significantly operated by generation companies to meet power and heat, simultaneously.

For validation, it is shown that profit is improved by 0.04%–48.02% for single and 0.02%–31.30% for double-sided auctions. As heat price curve is extracted, the simulation results show that when CHP system is integrated with other units results in profit increase and emission decrease by 3.04%–3.18% and 2.23%–4.13%, respectively. Also, CHP units significantly affect bidding parameters.

The novelties are pricing and bidding strategy of integrated CHP system is solved; local heat selling is considered in pricing and bidding strategy problem and heat price curve is extracted; the effects of CHP utilization on bidding parameters are investigated; a modified heuristic and deterministic optimization algorithm is presented.

The study aims to analyze the impact of market participation on small paddy farmers' income and consumption expenditure. The study also estimates various determinants affecting the market participation of smallholders. Further, the study computes the efficiency of different paddy marketing channels and identifies the determinants that impact the marketing channel selection of paddy growers in Eastern India.

The study used the propensity score matching (PSM) approach to measure the impact of market participation on farm income and per capita consumption. Further, the study employed Acharya and Aggarwal's composite index approach to estimate the marketing efficiency of various paddy marketing channels. Further, a multinomial logit model was used to determine the marketing channel selection constraints.

The outcomes indicate that market participation positively impacts farm income and consumption expenditure. Education, membership in farmers' organizations, price information and distance to the marketplace significantly affect farmers' market participation. The results show that the producer–retailer marketing channel is the most efficient compared to others. However, most paddy farmers sell paddy to farmgate collectors due to a lack of market information, vehicle ownership, storage system, and inability to take the risk of venturing out of the farmgate into markets.

The study uses primary data and captures only farmers' perspectives to measure the impact of market participation, marketing channel efficiency and determinants for market channel selection. The other stakeholder's perceptions can be included in future studies.

Rarely does any study identifies the efficiency of different marketing channels for paddy farmers in India and includes cognitive factors like risk perception and trust in buyers as constraints for market channel selection.

The purpose of this paper is to provide a theoretically rigorous and practically relevant summary of research findings that enables managers to drive sustainable profits improvements via pricing. It showcases multiple case studies that demonstrate how companies can achieve higher-than-average profitability by implementing intelligent pricing strategies and tactics.

Over the past 20 years, this writer has conducted dozens of academic surveys with managers exploring the antecedents, moderators and consequences of pricing practices for existing and new products. The writer has analyzed all pricing research published in leading academic journals over the past decades. Finally, as equity partner of Hinterhuber & Partners, a pricing consultancy (www.hinterhuber.com), this writer – through collaborations with companies and workshops conducted with practicing managers – has collected data and insights on best practices in managing pricing as a strategic activity.

Pricing is the most powerful driver of superior profits, yet managers view pricing as relevant only in the context of innovation. This narrow view prevents companies from realizing their full potential. Best practice examples of pricing as well as rigorous academic research suggest that pricing based on solid scientific principles helps average companies to achieve above-average results. This paper presents a review of recent research and summarizes the fundamental principles that managers must master so that pricing becomes an enabler of lasting superior performance.

Academic research in pricing surpasses managerial practice. Managers often rely on outdated concepts when it comes to pricing strategy and tactics.

The paper presents a framework that allows managers to implement pricing strategies that improve performance.

Effective pricing strategies benefit companies, customers and other stakeholders.

The paper provides a comprehensive overview of the latest research on pricing and thus documents that pricing based on solid, scientific principles is an enable of lasting, above-average profitability.

As an important form of the e-commerce industry, online group buying is under the spotlight from with two sides: cheaper price but longer waiting time. The purpose of this paper is to adequately investigate the interaction between saving and waiting time of group buying comprehensively.

To fill the research gap, the authors elaborate a dual-channel supply chain (SC) with regular retail (individual buying) and group-buying channel, and formulate the demand based on the consumer utility with the positive effect of saving money and the negative effect of wasting time.

The authors find that power structure only changes the optimal prices, instead of the waiting time. The selling price mainly influences consumer demands, instead of the price discount of group buying. The SC profits are only positive to the channel preference, and it is the decisive parameter of consumers' choice. The price sensitivity lays a more remarkable impact on the SC compared to the time sensitivity. Above all, the price is the main factor of group buying, instead of time.

These results underscore the improvement for the dual-channel SC of group buying, providing managerial insights for the group-buying industry.

Poor post-harvest handling practices by seaweed farmers are a key issue in seaweed value chains, contributing to low-quality seaweed being supplied to processors. To address this, a range of advanced drying technologies and methods have been developed, yet uptake by farmers remains low. This study examines factors affecting drying technology uptake by seaweed farmers to identify opportunities to incentivise improved drying practices.

This study draws on a quantitative survey of 273 seaweed farmers in two villages in South Sulawesi, 16 months of ethnographic fieldwork and 166 semi-structured interviews.

Farmers engage in limited adoption of improved drying technologies and practices as they don't receive higher prices for higher quality products, instead aiming to meet only the minimum acceptable standards to avoid a price discount or rejection of their product. Technologies and techniques that have been adopted are often used in ways that differ from their original purpose, such as to reduce drying times and labour input, rather than to produce products of low moisture and dirt contents. Similarly, local traders mix high- and low-quality seaweed in order to supply warehouses with seaweed which on average meets minimum quality standards.

This study reveals that improved drying practices are unlikely to be adopted unless incentivised by more targeted price-grade differentials.

This study examines the influence of stock liquidity on stock price crash risk and the moderating role of institutional blockholders in Vietnam’s stock market.

Crash risk is measured by the negative coefficient of skewness of firm-specific weekly returns (NCSKEW) and the down-to-up volatility of firm-specific weekly stock returns (DUVOL). Liquidity is measured by adjusted Amihud illiquidity. The two-stage least squares method is used to address endogeneity issues.

Using firm-level data from Vietnam, we find that crash risk increases with stock liquidity. The relationship is stronger in firms owned by institutional blockholders. Moreover, intensive selling by institutional blockholders in the future will positively moderate the relationship between liquidity and crash risk.

Since stock liquidity could exacerbate crash risk through institutional blockholder trading, firm managers should avoid bad news accumulation and practice timely information disclosures. Investors should be mindful of the risk associated with liquidity and blockholder trading.

We contribute to the literature by showing that the activities of blockholders could partly explain the relationship between liquidity and crash risk. High liquidity encourages blockholders to exit upon receiving private bad news.

In this study, the central objective is to foresee stock market signals with the use of a proper structure to achieve the highest accuracy possible. For this purpose, three hybrid models have been developed for the stock markets which are a combination of support vector machine (SVM) with meta-heuristic algorithms of particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).All the analyses are technical and are based on the Japanese candlestick model.

Further as per the results achieved, the most suitable algorithm is chosen to anticipate sell and buy signals. Moreover, the authors have compared the results of the designed model validations in this study with basic models in three articles conducted in the past years. Therefore, SVM is examined by PSO. It is used as a classification agent to search the problem-solving space precisely and at a faster pace. With regards to the second model, SVM and ICA are tested to stock market timing, in a way that ICA is used as an optimization agent for the SVM parameters. At last, in the third model, SVM and GA are studied, where GA acts as an optimizer and feature selection agent.

As per the results, it is observed that all new models can predict accurately for only 6 days; however, in comparison with the confusion matrix results, it is observed that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.

In this study, the data for stock market of the years 2013–2021 were analyzed; the long length of timeframe makes the input data analysis challenging as they must be moderated with respect to the conditions where they have been changed.

In this study, two methods have been developed in a candlestick model; they are raw-based and signal-based approaches in which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.