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Standard approaches to price decisions are normally illustrated as step‐by‐step developments that try to group pricing issues loosely into some format. These current approaches do not emphasize the interaction of consumer characteristics with the competitive environment of each market. Describes a modified version of the Tellis Price Strategy Matrix to enable coordinated market issues and company strategies by directing emphasis on pricing issues and techniques that are appropriate and effective, given the consumers′ (or segment′s) as well as the company′s objectives, as constrained by the competitive nature of the product′s market. By using this type of matrix as a guide, product managers can quickly evaluate the appropriate issues of concern for a given pricing decision and then progress toward a pricing decision with more confidence.

The purpose of this paper is to investigate and identify the price sensitivity of consumers of three- and five-star hotels and to determine the impact of bundling strategies on consumers’ price sensitivity.

To calculate price sensitivity, authors apply the van Westendorp’s price sensitivity meter (PSM). To understand the impact of bundling strategies, univariate and bivariate techniques are applied.

PSM results reveal the optimal prices and the range of acceptable prices for three- and five-star hotel. The bundling strategy results reveal that five-star customers are less sensitive to mixed-leader bundling. Regarding mixed-joint bundling, managers could improve sales through bundling strategies if they selected an attractive service (e.g. restaurants).

Findings assist hotel managers to understand the different price sensitivities, according to the hotel typology. Managers can manage prices without the risk of losing market share or revenue. The results help managers in deciding which bundling strategies they can create, as well as the services to be included to achieve highest profitability.

No research to date to the best of the authors’ knowledge has attempted to understand and compare the role of bundling strategies in three- and five-stars hotels. Moreover, no research has attempted to measure and compare customers’ price sensitivity of three- and five-stars hotels.

The social media revolution has brought tremendous change in business strategies for marketing and promoting the products and services. Online social networks have become prime choice to promote the products because of the large size of online communities. Identification of seed nodes or identifying the users who are able to maximize the spread of information over the network is the key challenge faced by organizations. It is proved as non-deterministic polynomial-time hard problem. The purpose of this paper is to design an efficient algorithm for optimal seed selection to cover the online social network as much as possible to maximize the influence. In this approach, agglomerative clustering is used to generate the initial population of seed nodes for GA.

In this paper agglomerative clustering based approach is proposed to generate the initial population of seed nodes for GA. This approach helps in creating the initial populations of Genetic algorithm from different parts of the network. Genetic algorithm evolves this population and aids in generating the best seed nodes in the network.

The performance of of proposed approach is assessed with respect to existing seed selection approaches like k-medoid, k-means, general greedy, random, discounted degree and high degree. The algorithms are compared over networks data sets with varying out-degree ratio. Experiments reveal that the proposed approach is able to improve the spread of influence by 35% as compared to contemporary techniques.

This paper is original contribution. The agglomerative clustering-based GA for optimal seed selection is developed to improve the spread of influence in online social networks. This paper is of immense importance for viral marketing and the organizations willing to promote product or services online via influential personalities.

The purpose of this paper is to generalize the one‐factor mortgage‐backed securities (MBS)‐pricing model proposed by Kariya and Kobayashi to a three‐factor model. The authors describe prepayment behavior due to refinancing and rising housing prices by discrete‐time, no‐arbitrage pricing theory, making an association between prepayment behavior and cash flow patterns.

The structure, rationality and potential for practical use of our model is demonstrated by valuing an MBS via Monte Carlo simulation and then conducting a comparative static analysis.

The proposed model is found to be effective for analysing MBS cash flow patterns, making a decision for bond investments and risk management due to prepayment.

While the one‐factor valuation model Kariya and Kobayashi treated is a basic framework, the generalized model presented in this paper is much more effective for analysing MBS cash flow patterns, making a decision for bond investments and risk management due to prepayment.

The purpose of this paper is to provide a framework to help marketers of services price their products by looking beyond costs and competitive forces. By analysing the value of information; consumers' price sensitivity; and transaction costs other than search costs, against the characteristics of their service they could make more profitable pricing decisions.

A critical review of the academic and professional literature reveals a rich array of possibilities for pricing services. A simple framework is developed in the form of a matrix crossing the three dimensions of heterogeneity of consumer demand with the four characteristics of services. Each cell represents a set of pricing options.

Services should be priced in a way to reflect the customers' price sensitivity, the nature of the transaction and its cost, and the value of information. The pricing should also reflect the four characteristics of services: intangibility, perishability, lack of standardization, and inseparability of production and consumption.

This paper fills a conceptual and practical gap for a structured review of the current state of knowledge about the pricing of services. It offers practical and solid advice and examples demonstrating the application of the different types of pricing strategies for service providers.

Summarizes three explanations put forward in previous research for the deviation of closed‐end fund (CEF) share prices from their net asset values and tests the theories based on market sentiment (noise trading) and market segmentation (market frictions). Analyses 1991‐1997 data on 18 UK CEFs (13 investing in the UK and 5 in the USA) to explore the pattern of cointegration and error corrected Granger causality between the fund discounts and indices which proxy for UK and US investor sentiment. Discusses the results, which support both theories for UK CEFs and show some evidence of cointegration and information transmission. Briefly considers consistency with other research and the implications of the findings.

The purpose of this paper is to review and analyze the perishable inventory models along various dimensions such as its evolution, scope, demand, shelf life, replenishment policy, modeling techniques and research gaps.

In total, 418 relevant and scholarly articles of various researchers and practitioners during 1990-2016 were reviewed. They were critically analyzed along author profile, nature of perishability, research contributions of different countries, publication along time, research methodologies adopted, etc. to draw fruitful conclusions. The future research for perishable inventory modeling was also discussed and suggested.

There are plethora of perishable inventory studies with divergent objectives and scope. Besides demand and perishable rate in perishable inventory models, other factors such as price discount, allow shortage or not, inflation, time value of money and so on were found to be combined to make it more realistic. The modeling of inventory systems with two or more perishable items is limited. The multi-echelon inventory with centralized decision and information sharing is acquiring lot of importance because of supply chain integration in the competitive market.

Only peer-reviewed journals and conference papers were analyzed, whereas the manuals, reports, white papers and blood-related articles were excluded. Clustering of literature revealed that future studies should focus on stochastic modeling.

Stress had been laid to identify future research gaps that will help in developing realistic models. The present work will form a guideline to choose the appropriate methodology(s) and mathematical technique(s) in different situations with perishable inventory.

The current review analyzed 419 research papers available in the literature on perishable inventory modeling to summarize its current status and identify its potential future directions. Also the future research gaps were uncovered. This systemic review is strongly felt to fill the gap in the perishable inventory literature and help in formulating effective strategies to design of an effective and efficient inventory management system for perishable items.

Consumers use a variety of information cues to select products; price, however, is the most important. It is possible that the market environment can influence how price is viewed by consumers. The purpose of this study is to: establish validity and reliability for multidimensional aspects of the price construct; to explore how US and Korean students are different or similar in their perception of price cues; and to use countries’ retail environments to explore the differences. Findings of this study show that US subjects have higher levels of prestige sensitivity, price mavenism and value consciousness, than did Korean students. However, Koreans exhibited higher levels of sale proneness and price consciousness. Theoretical and managerial implications were suggested based on these findings.