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The purpose of this paper is to contribute to the marketing literature and practice by examining the effect of product pricing on consumer behaviours with regard to the assertiveness and the sentiments expressed in their product reviews. In addition, the paper uses new data collection and machine learning tools that can also be extended for other research of online consumer reviewing behaviours.

Using web crawling techniques, a large data set was extracted from the Google Play Store. Following this, the authors created machine learning algorithms to identify topics from product reviews and to quantify assertiveness and sentiments from the review texts.

The results indicate that product pricing models affect consumer review sentiment, assertiveness and topics. Removing upfront payment obligations positively impacts the overall and pricing specific consumer sentiment and reduces assertiveness.

The results reveal new effects of pricing models on the nature of consumer reviews of products and form a basis for future research. The study was conducted in the gaming category of the Google Play Store and the generalisability of the findings for other app segments or marketplaces should be further tested.

The findings can help companies that create digital products in choosing a pricing strategy for their apps. The paper is the first to investigate how pricing modes affect the nature of online reviews written by consumers.

States that current pricing strategies used in the service industries are often too simplistic and ineffective in the face of complex environmental conditions. Introduces the Pricing Differentiation Premium Model, which includes in the firm′s pricing strategy its ability to differentiate itself from competitors. Discusses possible strategies for influencing differentiation premiums which can improve the pricing discretion of the service provider.

Examines the advantages and disadvantages of six service pricing approaches in the service literature including: traditional cost‐oriented approach; traditional competitive‐oriented approach; extended cost‐oriented approach; differentiation premium approach; client‐driven approach; and bundle pricing approach. Proposes a multi‐step synthetic pricing approach and a framework to deal with the complexity of service pricing. Compared with other pricing approaches, the multi‐step synthetic service pricing approach has the advantages of considering simultaneously the crucial aspects of service pricing: market competitiveness; internal cost‐profit structure; bundling and unbundling service pricing; service characteristics premium; price standard limits; client‐oriented price/demand sensitivity; and client‐oriented profit maximization. Provides an example to demonstrate the managerial application of the proposed approach.

This paper has used account-level data of corporate and retail borrowers, assessed their credit risk through the risk-neutral principle and examined its implication on loan pricing.

It derives the capital charge and credit risk-premium for expected and unexpected losses through a risk-neutral approach. It estimates the risk-adjusted return on capital as the pricing principle for loans. Using GMM regression, the article has assessed the determinants of risk-based pricing.

It has been found that risk-premium is not reflected in the current loan pricing policy as per Basel II norms. However, the GMM estimation on RAROC can price risk premium and probability of default, LGD, risk weight, bank beta and capital adequacy, which are the prime determinants of loan pricing. The average RAROC for retail loans is more than that of corporate loans despite the same level of risk capital requirement for both categories of loans. The robustness tests indicate that the RAROC method of loan pricing and its determinants are consistent against the time and type of borrowers.

The RAROC method of pricing effectively assesses the inherent risk associated with loans. Though the empirical findings are confined to the sample bank, the model can be used for any bank implementing the Basel principle of risk and capital assessments.

The article has developed and validated the model for estimating RAROC, as per Basel II guidelines, for loan pricing that any bank can use.

It has developed the risk-based loan pricing model for retail and corporate borrowers. It has significant practical utility for banks to manage their risk, reduce their losses and productively utilise the public deposits for societal developments.

The article empirically validated the risk-neutral pricing principle using a unique 1,520 retail and corporate borrowers dataset.

This paper extends the merger pricing model associated with Larson‐Gonedes to the general question: how well does the premium developed from the pricing model forecast the securities market reaction of the actual merger? Based on a sample of 91 common stock mergers, shareholders in participating firms incur wealth losses about half the time but the magnitude of the gains outweighs the losses such that statistically significant gains are reported for both buyers and sellers. Removal of market wide price movements further increases the gains to shareholders. However, the premium consistently overstates the gain obtained by acquired firms and bears no systematic relationship to the gains registered by shareholders of acquiring firms. Financial analyses of mergers have focused almost exclusively on mergers as “events” with resultant measurements in abnormal returns surrounding the merger announcement/consummation to shareholders, and occasionally bondholders, in both buying and selling firms. Recent reviews of these studies by Halpern (1983), Jensen and Ruback (1983), and especially Roll (1986) stress the tentativeness of the findings and the ambiguity of their interpretation. The common feature of all this analysis has been on the ex post valuation of the merger event by the securities market from an informational content perspective. Alternatively, these studies have evaluated indirectly whether the price premium paid in an acquisition exceeds, equals, or is less than the market's valuation of the net present value of the merger, and how the spoils/losses are distributed between acquirers and acquirees. But never is the bid premium itself determined and then compared to the market's reaction upon public announcement. As Roll argues, the merger process involves three steps: “First, the bidding firm identifies a potential target firm; second, a ‘valuation’ of the equity of the target is undertaken…; third, the ‘value’ is compared to current market price… If value exceeds price, a bid is made…” Roil (1986, p. 198). This paper links the price premium offered in mergers to the market's reaction to the news of the merger, or alternatively, it compares Roll's steps two and three. The merger pricing model used is the exchange ratio determination model developed by Larson and Gonedes (1969) and applied to mergers by Conn and Nielsen (1977). The pricing model, commonly cited in finance texts (eg. Copeland and Weston (1988, pp. 757–763), has the advantage of being deterministic and thus provides a direct measure of the bid premium subject to a pareto optimal wealth constraint for shareholders in both buying and selling firms. The principal question this paper asks is: Does the price premium provide a consistent, unbiased forecast of the market's reaction? This is an important question from both the bidding firms' and target firms' perspectives for several reasons. First, the terms of the negotiated merger may signal important information to the securities market regarding the degree of agency costs in the merging firms. For example, an excessively high negotiated price for the target may indicate either the bidder has inept management or management insulated from shareholder interests. Thus, the terms of a merger may reflect not only the participants' expectations regarding the merger itself, but also be influenced by existing — although previously unknown — agency costs. The signalling information contained in merger announcement may obviously mask the expectational information, creating ambiguity in interpretation of market reaction. Second, distribution of the market reaction for buyers and sellers is important not only to participating firms' shareholders, but also to the effectiveness of the market for corporate control. A perfectly competitive merger market assures that merger premiums equal the expected value of the increased market values of merging firms. Thus, divergences between premiums and subsequent market reactions may have important implications for assessing the degree of competitiveness in the merger market, and hence, the effectiveness of mergers as a disciplinary force in the market for corporate control. Finally, the adequacy of ex ante merger pricing models remains an unexplored issue. Using an improved methodology, the Larson and Gonedes (LG) model is expanded to adjust for market wide movements in PE ratios; thus, merger specific influences on wealth positions are more clearly focused upon in contrast to the earlier work by Conn and Nielsen (1977). The earlier finding by Conn and Nielsen that approximately one half of mergers sampled in the 1960s failed to meet the pareto wealth constraint for participating firms is therefore re‐examined with an improved methodology and more recent sample of mergers occurring through 1979. The paper is organised as follows. Section I reviews and critiques the Larson‐Gonedes merger pricing model. Section II describes the empirical methodology and sample. Section III presents the empirical results and Section IV concludes with a summary.

The purpose of this paper is to demonstrate how crop price insurance premium can be calculated using an option pricing model and how insurers can transfer underwriting risks in the futures market.

Based on data from spot and futures market in China, this paper develops an improved B-S model for the calculation of crop price insurance premium and tests the possibility of hedging underwriting risks by insurance firms in the futures market.

The authors find that spot price of crops in China can be estimated with agricultural commodity futures prices, and can be taken as the insured price for crop price insurance. The authors also find that improved B-S model yields better estimation of crop price insurance premium than traditional B-S model when spot price does not follow geometric Brownian motion. Finally, the authors find that hedging can be one good alternative for insurance firms to manage underwriting risks.

This paper develops an improved B-S model that is data-driven in nature. Insured price of the crop price insurance, or the exercise price used in the B-S model, is estimated from a co-integration model built on spot and futures market price series. Meanwhile, distributional patterns of spot price series, one important factor determining the applicability of B-S model, is factored into the improved B-S model so that the latter is more robust and friendly to data with varied distributions. This paper also verifies the possibility of hedging of underwriting risks by insurance firms in the futures market.

This article aims to address the relationship between price strategies and price‐setting practices. The first derive from a normative tradition in the pricing literature and the latter from a descriptive tradition. Price strategies are visible in the market, whereas price‐setting practices are hidden behind the boundaries of an organization.

The study deals with the relationship between price strategies and price‐setting practices that refer to the use of customer value, competition, and cost information. Hypotheses are tested on survey data on 95 small and medium‐sized manufacturing and service firms in The Netherlands.

The results show that price strategies and price‐setting practices are related because strategies are implemented through price‐setting practices. However, some firms do not pursue any of the strategies indicated by pricing theory, some firms engage in practices for no clear strategic reasons, and some firms insufficiently engage in appropriate practices to implement their strategic choices.

The results are limited to small companies. Researchers should examine why firms may not pursue any price strategy that is offered by pricing theory. They may also focus on organizational learning and pricing capabilities.

Managers need greater awareness about the price strategies they can use, should be cautious about a potential mismatch between price strategies and price‐setting practices, and should reassess whether their firms are capable of engaging in the appropriate practices.

Linking price strategies to price‐setting practices reduces conceptual confusion in the pricing literature and may help to specify the gap between pricing theory and practice.

This paper provides a review of the extensive contributions made to the audit pricing literature by researchers utilizing Australian data. Recent United States [hereafter US] regulatory requirements under the Sarbanes Oxley Act (Section 102) have mandated disclosure of audit fees. As such this is a useful occasion to review the existing Australian audit pricing research, since the audit fee disclosure advantage once enjoyed by Australian researchers has now effectively dissipated. Beginning with the origins and genesis of audit pricing research in Australia, this review then discusses the key contributions to the literature over time. It concludes with some brief discussion of potential research directions.

This paper aims to understand empirically how shares of standard and premium private label (PL) products affect a retailer’s marketing mix decisions toward national brands (NBs).

Using a comprehensive store-level data set covering 52 categories and 130 stores of two retailer chains during 2003-2009, this paper examines how shares of standard and premium PLs affect retailer marketing strategies for NB retail prices, promotions and product assortments. The empirical analysis uses a simultaneous equations model estimated by the generalized method of moments approach and controls for endogeneity between PL shares and NB decisions and potential confounding variables including consumer, manufacturer and retailer factors.

Standard PL shares are associated positively with NB retail prices and negatively with NB promotions and assortments. In contrast, premium PL shares are associated positively with NB retail prices, promotions and assortments.

The results indicate that retailers make strategic NB decisions through multitier PLs. Specifically, the evidence suggests that retailers use standard and premium PLs differently in promotion and assortment decisions toward NBs. NB manufacturers need to be cognizant of the increasing marketing power of retailers through their multitier PLs.

Prior research has mainly focused on the role of PLs as a strategic weapon to gain power in the channel and its impact on NB pricing decisions in a single PL context. After accounting for potential confounding factors (retailer, consumer and manufacturer) and endogeneity, the authors find empirical evidence that retailers appear to leverage standard and premium PLs differently in some marketing mix decisions toward NB. In particular, the results reveal PL performance to be a determinant of retailer NB assortment decisions.

As sales of store brands increase, retailers are shifting their store branding strategies by raising store brand prices, extending their store brand assortments to high‐risk categories, and marketing store brands in high retail image formats. The purpose of the research is to explore the effects of these changes on consumers’ judgments of store brands. The conceptual framework is derived from pricing, prospect, and information processing theories. It is tested in two experiments. The study finds that consumers’ use of price information varies by decision‐making context. In particular, price‐based effects for store brands are moderated by the contextual factors of category risk and retail image.