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Some firms use a curious pricing mechanism called “pay as you wish” pricing (PAYW). When PAYW is used, a firm lets consumers decide what a product is worth to them and how much they want to pay to get the product. This practice has been observed in a number of industries. In this paper, we theoretically investigate why and where PAYW can be a profitable pricing strategy relative to the conventional “pay as asked” pricing (PAAP) strategy. We show that PAYW has a number of advantages over PAAP such that it is well suited for some industries but not for others. These advantages are as follows: (1) PAYW helps a firm to maximally penetrate a market; (2) it allows a firm to price discriminate among heterogenous consumers; (3) it helps to moderate price competition. We derive conditions under which PAYW dominates PAAP and discuss ways to improve the profitability of PAYW.

This paper examines firms’ product policies when they sell an add-on (e.g., Internet service) in addition to a base product (e.g., hotel rooms) under vertical differentiation (e.g., four- versus three-star hotels). I show that the role of an add-on differs; higher-quality firms prefer to sell it as optional to discriminate consumers, and lower-quality firms trade off discrimination and differentiation, trying to lure consumers from higher-quality rivals with a lower-price add-on. Equilibrium policies of lower-quality firms are more sensitive to the cost-to-value ratio of an add-on. If the ratio is sufficiently small, then they sell it to all consumers, potentially explaining why lower-end hotels are more likely than higher-end ones to offer free Internet service. Contrary to consensus in the literature, optional add-ons can intensify price competition over consumers who trade off a higher-quality base product versus a lower-quality base including an add-on. Hence, higher-quality firms are incentivized to commit to bundling, while lower-quality firms prefer to commit to not selling it. Add-ons can further reduce lower-quality firms’ profits if consumers cannot observe the prices, because holding up consumers ex post encourages them to switch to higher-quality rivals, which then become better off. Therefore, lower-quality firms are incentivized to advertise add-on prices, and higher-quality firms are not. The online appendix is available at https://doi.org/10.1287/mksc.2017.1028 .

Bid-rigging has long been a problem in the construction area. This research identified the existing problems in evaluating damages from bid-rigging in Design-Bid-Build (DBB) and lowest-bid construction projects. Traditional econometric assessment based on stochastics requires sufficient historical data to obtain reliable estimates. Thus, it is crucial to collect and analyze data from pertinent projects for its utilization. To ensure the accuracy of the estimation, a substantial amount of data on the outcomes of DBB bids should have been gathered. In many construction projects, that requirement could not be met. Furthermore, econometric analysis cannot reflect the differences caused by the details of individual projects. This study proposes an alternative approach based on detailed cost estimates, weights of major work groups and their historical bid rates when historical data from similar projects are scarce. This approach can reflect the distinct characteristics of individual projects. The proposed model was applied to 23 gas pipeline construction projects under DBB and the lowest bid. This study identified the impacts of the different compositions of major work groups. Bid rates of the main work groups could not only be used to evaluate the damages caused by bid-rigging, but could also be used to determine reliable bid prices and provide a bidding strategy to aid the bidder’s decision-making process in future bids for similar projects.

This study examines the roles of resource consumption accounting and competitive prices in attaining sustainable profitability. The objectives were (1) to determine whether the adoption of resource consumption accounting practices yields significant improvements in competitive strategies in a highly competitive situation where activity-based costing has proved to be insignificant, and (2) to ascertain if the positive relationship between competitive pricing and sustainable profitability is increased by the extent to which resource consumption accounting exerts pressure for sustainability profitability. A PLS-SEM procedure was applied in analysing 129 of the top 30 performing companies’ structured questionnaire responses drawn from five industries in Kurdistan from 2021. The empirical results demonstrated that competitive pricing models involving resource consumption accounting systems provide superior price forecasting, error reduction and profit maximisation capabilities than existing energy models. The study’s outcomes highlight that the extent to which resource consumption accounting exerts pressure on sustainability profitability significantly increases the positive relationship between competitive pricing and sustainable profitability. The results of this study advance construct and item development involving competitive pricing and resource consumption accounting while testing relationships to uncover the moderating role of resource consumption accounting in profit maximisation. Thus, energy and non-energy industrial companies must rely on resource consumption accounting to set competitive prices and enhance and sustain their profitability by considering the overlooked energy pricing stochastic parameters and errors amid rising energy shortages and costs.

Value chain–based approaches offer tremendous scope for market-based improvements in production, productivity, rural economy diversification, and household incomes, but are often covered by literature that is too conceptual or heavily focused on analysis. This has created a gap in the information available to planners, practitioners, and value chain participants. Furthermore, few references are available on how these approaches can be applied specifically to developing agriculture in Africa. 'Building Competitiveness in Africa's Agriculture: A Guide to Value Chain Concepts and Applications' describes practical implementation approaches and illustrates them with scores of real African agribusiness case studies. Using these examples, the 'Guide' presents a range of concepts, analytical tools, and methodologies centered on the value chain that can be used to design, implement, and evaluate agricultural and agribusiness development initiatives. It stresses principles of market focus, collaboration, information sharing, and innovation. The 'Guide' begins by examining core concepts and issues related to value chains. A brief literature review then focuses on five topics of particular relevance to African agricultural value chains. These topics address challenges faced by value chain participants and practitioners that resonate through the many cases described in the book. The core of the book presents methodological tools and approaches that blend important value chain concepts with the topics and with sound business principles. The tools and case studies have been selected for their usefulness in supporting market-driven, private-sector initiatives to improve value chains. The 'Guide' offers 13 implementation approaches, presented within the implementation cycle of a value chain program, followed by descriptions of actual cases. Roughly 60 percent of the examples are from Africa, while the rest come from Europe, Latin America, and Asia. The 'Guide' offers useful guidance to businesspeople, policy makers, representatives of farmer or trade organizations, and others who are engaged in agro-enterprise and agribusiness development. These readers will learn how to use value chain approaches in ways that can contribute to sound operational decisions, improved market linkage, and better results for enterprise and industry development.

This article presents an efficient home energy management system for residential household within a microgrid. The smart meter's database initially stores the consumer's solar generation, battery's state of charge, and appliance-level information. Both the appliance's consumption and its state of operation are gathered. The end-user's energy use habits are then investigated using this data. As a consequence, accurate data on the frequency of usage, preferred operation interval, and average power consumption of the appliances were gathered using a time-of-day schedule. The outcomes were integrated with a Competitive Price Tracking algorithm to produce a smart home energy management solution that is efficient and user-focused. In addition to providing the optimum energy management strategy for a smart home in a microgrid, the developed model planned the controllable loads by taking into account consumer comfort and a separate waiting factor for each Appliances. The suggested model is demonstrated via simulation in the Typhoon HIL Real-Time Simulator. The operating cost recorded from the simulation is 155.08 INR, 150.56 INR, and 130.54 INR for case 1, 2, and 3, respectively. However, the proposed method is compared to other method, where operating cost from NILM-based method is recorded as 155.08 INR,153.12 INR, and 142.98 INR for case 1,2, and 3, respectively, and 151.38 INR for all cases, recorded from traditional Method. Graphical abstract

Bid-riggings have persisted as an issue in the construction industry with its estimated damages being the most troublesome element. This study identifies the current limitations in estimating these damages and proposes an alternative approach to estimate the damages from bid-rigging in design-build (DB) construction projects. This study investigated a hypothetical competitive scenario that reflected the pricing model in DB contracts aimed at both winning the project and making profits. The alternative approach utilized a simulation model based on each bidder’s historical bidding data that could reproduce competitive bidding in DB-delivery. The feasibility of the proposed model was demonstrated with a case study conducted on a real railway construction project. This proposed model can also be used in determining an optimal bid price for DB construction projects.

Repurchase intention is included in post-purchase behavior, so it becomes an important topic to be investigated. This study aims to determine the effect of trust, competitive prices, and application quality on repurchase intention in Traveloka online travel agents. This study uses an explanatory research approach using multiple linear regression analysis methods. Data sources come from distributing questionnaires online. The sampling method uses purposive sampling with the criteria of respondents being at least 18 years old and having made a purchase of at least one time on the Traveloka mobile application. The sample used was 150 respondents. The results of this study indicate that the variables of trust, competitive prices, and application quality significantly influence the repurchase intention of Traveloka online travel agents.

Prior research suggests that partially comparative pricing—in which a retailer provides price comparisons for some, but not all, of its products—is a double-edged sword. On the one hand, such pricing improves beliefs about the retailer's competitive price advantage on comparatively priced products for which its prices are compared with a competitor. On the other hand, it has been shown to damage perceptions of the retailer's noncomparatively priced products relative to those charged by the competition. However, this latter outcome is based on evidence examining the influence of partially comparative pricing across different product categories. The authors propose and demonstrate in five studies that price comparisons may actually improve relative price beliefs about the noncomparatively priced brands within the same product category. They further show this improvement to be attenuated as the number of price comparisons increase or when the price comparison is attached to a brand perceived as less typical of the product category. The authors conclude by drawing managerial implications and offer suggestions for further research.

In this paper, I investigate the competitive and welfare effects of the improvements in information accuracy in markets where firms can price discriminate after observing a private and noisy signal about a consumer's brand preference. I show that when firms believe that consumers have a brand preference for them, then they charge more to these consumers, and this price has an inverse U-shaped relationship with the signal’s accuracy. In contrast, the price charged after a disloyal signal has been observed falls as the signal's accuracy rises. While industry profit and overall welfare fall monotonically when price discrimination is based on increasingly more accurate information, the reverse happens to consumer surplus.