Unlock the Sharing Economy: The Case of the Parking Sector for Recurrent Commuting Trips

This study examines the pricing strategy of a parking sharing platform that rents the daytime-usage rights of private parking spaces from parking owners and sells them to parking users. In an urban area with both shared parking and curbside parking, a choice equilibrium model is proposed to predict the number of shared parking users under any given pricing strategy of the platform. We analytically analyze how the pricing strategy of the platform (price charged on users and rent paid to parking owners or sharers) would affect the parking choice equilibrium and several system efficiency metrics. It is shown that the platform is profitable when some parking owners have a relatively small inconvenience cost from sharing their spaces, but its profit is always negative at minimum social cost. Numerical studies are conducted to illustrate the analytical results and provide further understanding.

Pay-What-You-Want Pricing in the Digital Product Marketplace: A Feasible Alternative to Piracy Prevention?

In pay-what-you-want (PWYW) pricing, buyers are allowed to pay any amount they want, often including a price of zero. Standard theory predicts that buyers are driven solely by their own interest and will always choose to pay nothing, making PWYW pricing impractical to use. Nonetheless, PWYW pricing has been consistently occurring in the marketplace. We build and analyze a theoretical model to explain the presence of PWYW pricing in the marketplace and identify the situations under which businesses are better off adopting it over the traditional posted pricing. Because the digital product domain is a particularly good fit for PWYW pricing because of its constant exposure to piracy threats, we focus on digital product firms and examine PWYW pricing as an alternative to their piracy prevention efforts. We show that PWYW pricing becomes a superior pricing strategy when the pirate version is quite similar to the authentic product and it is costly for the firm to improve its product quality. Moreover, if network externalities are present, PWYW pricing can outperform posted pricing only when the network externalities are weak. The results explain why PWYW pricing is rare in the established digital product marketplace, which exhibits strong network externalities.

Trading and Pricing Sensor Data in Competing Edge Servers with Double Auction Markets

With the development of the IoT (Internet of Things), sensors networks can bring a large amount of valuable data. In addition to be utilized in the local IoT applications, the data can also be traded in the connected edge servers. As an efficient resource allocation mechanism, the double auction has been widely used in the stock and futures markets and can be also applied in the data resource allocation in sensor networks. Currently, there usually exist multiple edge servers running double auctions competing with each other to attract data users (buyers) and producers (sellers). Therefore, the double auction market run on each edge server needs efficient mechanism to improve the allocation efficiency. Specifically, the pricing strategy of the double auction plays an important role on affecting traders’ profit, and thus, will affect the traders’ market choices and bidding strategies, which in turn affect the competition result of double auction markets. In addition, the traders’ trading strategies will also affect the market’s pricing strategy. Therefore, we need to analyze the double auction markets’ pricing strategy and traders’ trading strategies. Specifically, we use a deep reinforcement learning algorithm combined with mean field theory to solve this problem with a huge state and action space. For trading strategies, we use the Independent Parametrized Deep Q-Network (I-PDQN) algorithm combined with mean field theory to compute the Nash equilibrium strategies. We then compare it with the fictitious play (FP) algorithm. The experimental results show that the computation speed of I-PDQN algorithm is significantly faster than that of FP algorithm. For pricing strategies, the double auction markets will dynamically adjust the pricing strategy according to traders’ trading strategies. This is a sequential decision-making process involving multiple agents. Therefore, we model it as a Markov game. We adopt Multiagent Deep Deterministic Policy Gradient (MADDPG) algorithm to analyze the Nash equilibrium pricing strategies. The experimental results show that the MADDPG algorithm solves the problem faster than the FP algorithm.

The influence of international offshore jurisdictions on the pricing strategy

The article analyzes the causes of offshore jurisdictions and identifies the effects of offshore on national economies. An analysis of the implementation of export-import operations carried out by offshore companies in order to influence the pricing process. The pricing mechanism with affiliates within offshore jurisdictions was presented. It was substantiated the role of offshore banks in the implementation of the pricing mechanism. It was presented the pricing mechanisms within offshore jurisdictions. It has been made an analysis of the impact of transfer pricing within offshore jurisdictions. It was substantiated the economic mechanism of pricing. The international experience of regulation of offshore jurisdictions and the system of controlling the operations of affiliates was analyzed. It was substantiated the mechanisms of functioning of offshore zones and companies operating in offshore jurisdictions. The relationship between agreements concluded within offshore jurisdictions in the following areas is established and substantiated: the agreement is concluded between two independent companies in case of underpricing; the agreement is concluded between the companies connected with the capital relations (affiliated companies) at understatement of the price; agreements between two independent companies in case of overpricing; agreements between affiliated companies in case of overpricing. It was justified the use of the transfer pricing mechanism within offshore jurisdictions. Transfer prices allow you to withdraw capital from the country, as well as hide the profits of companies from taxation. The following ways of minimizing taxation are systematized: registration of a company that concentrates profits in a jurisdiction with lower taxation; concentration of profits in companies that are unprofitable according to management accounting; the use of front companies as sales companies in which profits are concentrated; non-payment of taxes as a result of illegal liquidation of the enterprise - the taxpayer, where the profit is concentrated. The basis of tax minimization is the use in the transaction of a price that deviates from the market.

Strategic Provision of Trade Credit in a Dual-Channel Supply Chain

This study focuses on a a dual-channel supply chain that consists of a capital-constrained brick-and-mortar retailer and a manufacturer, where a manufacturer can simultaneously sell products through a traditional retail channel and a direct online channel. Supplementary pricing strategy and competitive pricing strategy are simulated in our model, and we find that the former one is the better choice for the manufacturer when the retailer suffers capital constraints. In our analysis, the capital constraint on retailer could mitigate the price competition between two channels, and it may be beneficial to the manufacturer under certain conditions. Our findings show that the manufacturer should strategically provide trade credit to retailers rather than unconditionally provide it. We present two trade-credit strategies (trade credit with positive interest rate and trade credit with zero interest rate) and suggest that the manufacturer should choose an appropriate trade-credit strategy according to the initial capital of the retailer. To guide the manufacturer when and how to provide trade credit, we conduct several numerical simulations based on our results and further plot out a graph to direct the manufacturer to an appropriate strategy of trade credit.

Dynamic Pricing and Inventory Control with Fixed Ordering Cost and Incomplete Demand Information

We consider the periodic review dynamic pricing and inventory control problem with fixed ordering cost. Demand is random and price dependent, and unsatisfied demand is backlogged. With complete demand information, the celebrated [Formula: see text] policy is proved to be optimal, where s and S are the reorder point and order-up-to level for ordering strategy, and [Formula: see text], a function of on-hand inventory level, characterizes the pricing strategy. In this paper, we consider incomplete demand information and develop online learning algorithms whose average profit approaches that of the optimal [Formula: see text] with a tight [Formula: see text] regret rate. A number of salient features differentiate our work from the existing online learning researches in the operations management (OM) literature. First, computing the optimal [Formula: see text] policy requires solving a dynamic programming (DP) over multiple periods involving unknown quantities, which is different from the majority of learning problems in OM that only require solving single-period optimization questions. It is hence challenging to establish stability results through DP recursions, which we accomplish by proving uniform convergence of the profit-to-go function. The necessity of analyzing action-dependent state transition over multiple periods resembles the reinforcement learning question, considerably more difficult than existing bandit learning algorithms. Second, the pricing function [Formula: see text] is of infinite dimension, and approaching it is much more challenging than approaching a finite number of parameters as seen in existing researches. The demand-price relationship is estimated based on upper confidence bound, but the confidence interval cannot be explicitly calculated due to the complexity of the DP recursion. Finally, because of the multiperiod nature of [Formula: see text] policies the actual distribution of the randomness in demand plays an important role in determining the optimal pricing strategy [Formula: see text], which is unknown to the learner a priori. In this paper, the demand randomness is approximated by an empirical distribution constructed using dependent samples, and a novel Wasserstein metric-based argument is employed to prove convergence of the empirical distribution. This paper was accepted by J. George Shanthikumar, big data analytics.

Pricing strategy and product substitution of bullwhip effect in dual parallel supply chain: aggravation or mitigation?

The bullwhip effect (BE) affects not only the revenue of the retailer but also the revenue of the manufacture. Thus, a lot of retailers and manufacturers aim to attenuate the negative impact of the BE. In this research, two parallel supply chains distributing two substitutable products with price-sensitive demands are considered, the order-up-to inventory policy, as well as the MMSE forecasting method, are employed by retailers in these chains. The retailer’s price-setting follows the first-order vector autoregressive process, suggesting that its pricing decision depends on its previous price as well as its rival’s price, owing to the BE. The analytical expression of the BE is calculated by the statistical method. Besides, the effects of pricing strategy and product substitution on the BE are studied through simulation. A conclusion can be drawn that the BE of the two parallel supply chains will be affected by lead time, product substitution rate, and pricing coefficient. Of particular interest is that the BE can be efficiently alleviated by adopting a price strategy with many correlations and a small coefficient of autocorrelation.

Pelatihan Pendidikan Entrepreneurship Bagi Siswa-Siswi SMAK Frateran: Penentuan Strategi Harga Jual

The purpose of this community service to Frateran Highschool is to increase their understanding towards Determining Pricing Strategy within their businesses. This training is on live discussion via zoom regarding the previous experiences in determining pricing strategy among lecturers, facilitators, and students as participants. These activities were conducted in an hour meeting session on 17th September 2021, as community service from Ciputra lecturers’ activity to SMAK. Frateran Surabaya. The class was attended by 12 out of 15 students registered, grade XII within Entrepreneurship Subject. The pricing strategies matrix consists of 3x3 quadrants, which then divided into 1. Fixed menu Pricing, and 2. Dynamic Pricing. Students also learned about value added within a product, thus lead them into positioning and differentiation for the businesses. The explanation also given by using examples for each method: Traveloka, Gofood, Grabfood (promotional posters & vouchers) to balance out peak and low order times, Ovo (program features in application) increasing customers convenience in adding values, Starbucks (personnel contribution service and behind the scenes operational video). The conclusion, the activity was able to increase students’ understanding of fixed and dynamic pricing strategy, value added within products/services, and finally positioning and differentiation within service industry.