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This article considers a two-stage supply chain consisting of a supplier and two competing multichannel retailers and examines their channel and pricing strategies. The supplier wholesales a product to the retailers who resell the product to consumers with different channel preferences. The retailers can either operate their online and offline channels separately and apply differential pricing strategy, or choose to integrate the channels and adopt unified pricing strategy. We establish a game-theoretical model to derive the optimal wholesale price of the supplier and equilibrium retailing prices of the two retailers, and investigate the impact of consumer structure and channel integration ability on the prices, demands, and profits. We then analyze the effect of channel integration and discuss the equilibrium strategy. We find no adoption, asymmetric adoption, and symmetric adoption of channel integration strategy are all possible equilibria. However, one or the both retailers can be worse off in the competition, while the supplier can be always better off if any retailer integrates the channels. Our results suggest that retailers should be very cautious when deciding whether to integrate channels under competition, and the supplier could design other mechanisms to encourage the retailers to integrate their channels.

The “buy online and pick up in store” (BOPS) mode is gaining tremendous popularity among retailers since it is convenient for consumers and brings additional store sales to retailers. However, operating the BOPS channel requires additional investment, which is a challenge for retailers. This article considers the pricing strategies of competing dual-channel retailers, focuses on whether and when they should adopt the BOPS strategy, and explores the impacts of market factors on the equilibrium outcomes. Since retailers’ decisions are usually made sequentially in reality, we use the Stackelberg game model to analyze retailers’ optimal strategies. First, we show that the follower's price is not always lower than the leader's price. Specifically, when the unit additional profit from cross-selling of the follower is low enough, the follower will set a higher price than the leader. Second, we find that retailers prefer the BOPS strategy when the fixed costs for offering BOPS channels are low enough, or when the difference between the additional profits from cross-selling of two retailers is sufficiently large. Third, we present an interesting insight: an increase in product return probability or retailer cost of handling a returned product can be beneficial to retailers.

With the rapid development of information and communications technology and high penetration of renewable energy, the role of an aggregator in a smart grid has emerged to better coordinate power and cash flows between energy producers and consumers through the adjustment of pricing signals. This study proposes variation indices about the statistics of renewables and a control law for an energy storage system. A deep reinforcement learning based pricing strategy of an aggregator for profit maximization in consideration of the energy balance is developed accordingly. The proposed approach can consider opponents’ behaviors, variability of renewables, and varying bounds of charging and discharging events in a nonstationary environment, which can be hardly addressed by pricing strategies based on conventional learning algorithms such as Q-learning and deep Q-network. Numerical analysis using real-world data shows that the proposed approach can outperform existing pricing strategies in terms of the learning speed and profit of aggregators.

The energy consumption disparity is an important factor affecting product pricing. The risk and the cost of new energy products are generally higher than those of traditional energy products, which results in conflicting pricing strategies between manufacturers and retailers. Applying the concepts from dynamic cooperative game theory, such as improved Shapley value, in this paper, we have studied the optimal pricing strategies of manufacturers and retailers in a cooperative and a noncooperative game. Based on policies and market conditions in China, we have used a logistic regression model to determine the impact of product sales, devised pricing strategies affected by the relevant government tax, and subsidy policy. The results show that, first, under the basic condition in which the manufacturer obtains profit, the optimal pricing of the retailer in a noncooperative game is more than that in a cooperative game. Second, the differential coefficient of the energy consumption of the two products in the cooperative game is greater than that in the noncooperative game. Third, the cooperative game not only plays an incentivizing role for retailers in setting reasonable prices of new energy products but also encourages manufacturers, producing a greater difference of energy consumption between traditional energy products and new energy products, which further reduces the consumption of new energy products. Finally, the strategies of sharing the green marketing costs by manufacturers and retailers can improve the total profits of the supply chain in addition to their own.

We investigate a firm’s information acquisition and voluntary disclosure decisions regarding demand forecast information. We study the interaction among the firm, its supplier, and the external capital market investors who assess the firm’s interim equity price. We first analyze when it is beneficial for the firm to acquire demand forecast information, and if such information is acquired, when the firm should disclose it to the supplier and investors. Then, we investigate how the firm’s information acquisition and disclosure decisions influence the investors’ and the supplier’s pricing strategies. We show that the optimal information disclosure policy for the firm is highly dependent on the corporate myopia level (CML): when the CML is low, the firm discloses low demand information only; when the CML is medium, the firm always withholds demand information; and when the CML is high, the firm discloses high demand information only. Our findings provide a novel plausible explanation to firms’ non-disclosure behaviors commonly observed in practice and highlight the importance of considering the interaction between the supply chain and the capital market.

As competition among CPG brands intensifies in both emerging and developed markets, brand managers increasingly focus on price as the weapon-of-choice. This calls for an assessment of not only their own price response, but also of their competitive pricing power, and its antecedents. The authors propose a set of universally applicable ('etic') and country-specific ('emic') drivers of brand price elasticity, clout, and vulnerability, for the world’s largest emerging market (viz., China). Leveraging a unique and large-scale data set from this market, they find that high price response is not necessarily indicative of high clout, nor does it signal high vulnerability. Hence, all three price response metrics matter. They also uncover marked differences in the impact of brand- and category-level drivers on these three metrics. Established etic factors such as line length, distribution intensity, and stockpilability have a substantial effect on one or more price response metrics. Among the emic factors, Chinese embeddedness, and especially social demonstrance play an important role: it strongly drives down brands’ price elasticity, but also reduces the intensity of price competition in the category and makes brands less vulnerable to rival actions. Foreign brands, in contrast, exhibit higher price response, and do not enjoy higher clout nor lower vulnerability than their domestic counterparts. Hence, they neither benefit from the aura, nor suffer from the liability, of foreignness. Overall, the study adds to empirical generalizations on the impact of price, and helps managers improve the effectiveness of their pricing strategies.

In the Big Data environment, when green manufacturers invest in the green production technology, to satisfy consumer demand timely and accurately, they may begin to gain consumer performance information (hereafter, CBDI) to design and produce product. However, these will go up their extra costs. Meanwhile, for a green manufacturer who sells the green product through the online channel and the offline channel, the expression of its market demand needs to rethink in the new environment. In these conditions, for a dual-channel green supply chain (hereafter, DGSC), chain members pay more attention on the pricing problems considering the inputs of CBDI and greening R&D. Hence, to resolve this question, a DGSC a green manufacturer selling by the online channel and with one retailer selling by the offline channel was chosen. Afterwards, the demand function of the DGSC was revised, and we analyzed the profits models and its pricing rules in the proposed four common cost-sharing models. Results indicate that whether the retailer bears the CBDI costs or the greening R&D costs, the retailer will not change its retail price. If the retailer can bear some CBDI costs, the alteration tendencies of the best wholesale price are related to the cost-sharing parameter.

The increasing use of intermittent renewable resources relies on the development of energy storage. In this paper, a two-stage credit-based sharing model between the coordinator who manages the energy storage system and the prosumers who borrow the capacity and energy from the coordinator is presented. The credit-based sharing model has been proposed to combine capacity sharing and energy sharing. As for the energy sharing, two forms of energy are considered: electricity and hydrogen. In addition, both cost-based and demand-based pricing strategies are introduced to facilitate the coordinator to capture considerable quantity of net profits and help the prosumers to reduce their energy purchase costs. Three cases have been compared to prove the effectiveness of the credit-based sharing model, i.e., the base case without the sharing process, the conventional model with sharing, and the proposed model. According to the simulation results, the proposed model is beneficial for both the coordinator and the prosumers. For the coordinator, the net profits can be enhanced, and the storage usage efficiency has been increased from an average of 39% to 62% compared with the conventional model.

This paper analyzes consumers' privacy choice concerning their data and firms' ensuing pricing strategies. Consumers decide whether to reveal private information in form of cookies. We study this endogenous decision in a duopoly model with behavior-based pricing and conduct an experiment to test our theoretical predictions. Contrasting two data environments, we derive a unique pure-strategy pooling equilibrium for each environment. We find that all consumers share their data in an open data environment while no consumers share data in an exclusive environment. In the experiment, however, some subjects readily share their data in the exclusive treatment. In the open data treatment subjects predominantly act as predicted by our theory. A mandated data sharing policy among firms leads consumers to share more data and increases consumer welfare. This helps policy makers to make an informed decision about data protection policies.

Multi-channel sales strategies have become common due to the usage of advanced information technologies. Yet, how one trading mechanism can influence the outcome of another, especially in the B2B market, is largely underexplored. This paper investigates the effect of price and quantity information from a pre-sales posted price channel on the performance of the century-old sequential Dutch auctions system. The pre-sales channel is conducted online preceding the auctions. Sellers can control the price and make a proportion of their stock available in the pre-sales. Anything left after the pre-sales is sold via the auctions. Our analysis of nearly 1.5 million flower lots reveals a positive effect where there are higher auction prices and total revenue for lots listed in the pre-sales than for lots that are not. The result holds even for lots with no actual sales in the pre-sales, indicating that buyers pay close attention to the additional information from the pre-sales posted price channel. By teasing out the information effect of pre-sales prices and pre-sales quantity on the auction prices, we evaluate a number of pricing strategies. The results suggest that selling at a high price in the pre-sales is still more beneficial than selling more by discounting prices.

PurposeThe purpose of this paper is to solve new pricing issues faced by low-carbon companies in the Yellow River Basin, which is caused by the change of key pricing factors in the mixed appliance background of Big Data and blockchain, such as product quality and carbon-emission reduction CER level (hereafter, CER level).Design/methodology/approachWe choose a low-carbon supply chain with a low-carbon manufacturer and a retailer as our research object. Then, we propose that using the ineffective effect of the CER level and the quality and safety level to reflect the relationships among the CER level, the quality and safety level and the market demand is more suitable in the new environment. Based on these, we revise the demand equation. Afterwards, by using Stackelberg game, four cost-sharing situations and their pricing rules are analyzed.FindingsResults indicated that in the four cost-sharing situations, the change trends and the magnitudes of the best retail prices were not affected by the changes of the inputs of the demand information and the traceability services costs (hereafter, DITS costs), the proportion about retailer's DITS costs undertaken by the manufacturer, the ineffective effect coefficient of the CER level and the quality and safety level and the cost optimization coefficient. However, the cost-sharing situations could affect the change magnitudes of the best revenues.Originality/valueThis paper has two main contributions. First, this paper proposes a demand function that is more suitable for the mixed appliance background of Big Data and blockchain. Secondly, this paper improves the cost-sharing model and finds that demand information sharing and traceability service sharing have different impacts on key pricing factors of low-carbon product. In addition, this research provides a theoretical reference for low-carbon supply chain members to formulate pricing strategies in the new background.

It is expected that commercial use of drones in the near future will involve delivery service operations by e-commerce companies. We consider relevant strategic and tactical decisions that these retailers will face in drone-based delivery operations, and derive policies on when to offer drone delivery, what delivery capacity to maintain, and what amount to charge for such deliveries. To this end, we develop a Markov decision process (MDP) framework, and introduce two heuristic procedures, through which near-optimal closed-form solutions can be obtained. The results are aimed at helping online retailers to determine in real time whether and to what extent to offer drone-based delivery for given product categories in different service zones. In addition, we study delivery fee structures and identify drone-based delivery pricing strategies under two widely used delivery pricing schemes. For capacity planning decisions, we describe an algorithm to identify the fleet size to utilize to fulfill uncertain demand in a given service region. We also identify structural characteristics on how these decisions and the expected profit are affected by changes in various problem parameters, which can generate generic insights on drone-based delivery operations for e-commerce companies. We find that retailers should prioritize more profitable items when allocating drone delivery capacity, and invest in adding more drones when per order opportunity costs are higher and promised delivery time thresholds are shorter. Retailers can potentially boost their net profits by increasing the effective promised delivery time threshold and/or decreasing the effective delivery delay costs and per order opportunity costs.

The aim of this article is to contribute to the understanding of the possibilities of application of selected pricing strategies in the conditions of the creative industries in Slovakia. A creative product has interesting economic aspects, which are conditioned by its specific parameters. The economic potential of a creative product is a way of returning the investment in its creation, as well as a way of generating profit. In this case, the economic potential is the set of economic utility – uniqueness, intellect, knowledge, talent and skills added by each participant in the process of product creation. These characteristics make the products of the creative industries fundamentally different from those of traditional manufacturing. The added value of a creative industry product is not determined by the amount of work invested in its creation, but by the subjective perception of consumers, insofar as its consumption satisfies their personal needs. Pricing in creative industry enterprises results from a number of factors that determine the strategic direction of the enterprise and its output. This fact in turn influences the strategy of conceiving and creating individual prices. These play an important role in the strategic marketing of creative industry enterprises, despite their specificities (zero price or free entry, voluntary, list-based). It should be noted that prices are set differently in the non-profit sector and in the for-profit sectors producing in the creative industries. This means that in terms of the marketing mix of each tool, the pricing functions need to be taken into account.

In this paper, we study how an oligopolist influences the coalition structure in federated cloud markets. Specifically, we use cooperative game theory to model the circumstances under which a cloud provider prefers to join a cloud federation vis-a-vis consider taking a price offer made by an oligopolist. We consider two price offering strategies for an oligopolist: non-adaptive and adaptive. In non-adaptive strategy, an oligopolist makes a price offer to all the cloud providers simultaneously. It can be noted that the oligopolist can buy-out all the cloud providers by making a price offer which is equal to a core allocation and the total price offer made by the oligopolist is equal to the value of the grand coalition. In adaptive strategy, the oligopolist approaches the cloud providers one after another in a sequential manner. We show that by using the adaptive strategy, the oligopolist can buy-out all the cloud providers at a total price offer which is less than that of the non-adaptive strategy.

PurposeThis paper aims to propose a two-period model in which an original equipment manufacturer (OEM) decides the remanufacturability level of products in product design and unit patent licensing fee at the first period, and a third-party remanufacturer (3PR) that has been licensed by the OEM enters the remanufacturing market to compete with the OEM at the second period.Design/methodology/approachThis paper analyzes the OEM's optimal decisions of remanufacturability level in the product design and unit patent licensing fee at the first period, as well as the OEM's and the 3PR's optimal decisions of selling prices at the second period, under two scenarios that the remanufacturing is constrained or unconstrained by the collected quantity available at the end of the first period, by making use of game theory.FindingsThe study finds that the OEM will choose high remanufacturability in product design only when the unit cost saving of remanufacturing or unit production cost of new products exceed certain thresholds.Originality/valueThe study is the first attempt to simultaneously integrate product design and patent licensing in remanufacturing. It provides useful insights for OEM managers who face competition from 3PRs and may use their product design strategies to deter 3PRs and may protect patent of products by levying patent licensing fees from 3PRs.

A crowdfunding platform is a typical two-sided market, as it acts as an intermediary that matches supply and demand sides of the platform, i.e., fundraisers and investors. Making the right pricing decision relies on a good understanding of dynamic behaviors of market players, which has not been fully understood in the research literature. This research studies investment decisions of crowdfunding investors and pricing choices of crowdfunding fundraisers, in both symmetric and asymmetric crowdfunding markets. For the symmetric crowdfunding market, a Hotelling model is used to analyze investors’ investment strategies and the minimum investment amount of financiers’ pricing strategies. For the asymmetric crowdfunding market, a Stackelberg model is used to analyze the decision-making behavior of the dominant and nondominant players competing for the same subset of potential investors on the platform. This research contributes to the existing research literature by considering, for the first time, the two unique variables, funding progress and the lucky draw probability of crowdfunding products, as well as their interaction. Our research finding suggests that investors should invest in crowdfunding products with relatively high minimum investment, even if it may lead to the failure of a crowdfunding project. Another interesting finding is that for crowdfunding fundraisers, asymmetric markets can be more profitable than symmetric markets. Our research results may contribute to crowdfunding product pricing theory and can be applied to real-world crowdfunding campaigns.

Companies adopt pricing strategies to maximize their profits. However, in light of an ongoing pandemic, these strategies have been put under the scanner across industries. Companies need to modify their pricing strategies to adapt to these unprecedented times. The study focuses on these pricing strategies, their necessity during the pandemic, and how they can be effectively implemented without any long-term implications for various companies and businesses. The study focuses on various aspects of pricing and the suitability of pricing strategies during the pandemic. The study suggests pricing strategies which companies may follow. Pricing strategies of several industries which are in crisis are also discussed. The study will help companies to understand the economic situation and formulate pricing strategies accordingly. Such pricing strategies will allow companies to satisfy their customers, sustain in the competition, and achieve business excellence.

As live streaming of events gains traction, pay-what-you-want (PWYW) pricing strategies are emerging as critical monetization tools. We assess the viability of PWYW by examining the relationship between popularity (i.e., audience size) of a live streaming event and the revenue it generates under a PWYW scheme. On the one hand, increasing audience size may enhance voluntary payment/tips if social image concerns are important, because larger audiences amplify the utility pertaining to social image. On the other hand, increasing audience size may reduce tips if gaining the broadcaster’s reciprocal acts motivates tipping because larger audiences are associated with fiercer competition for reciprocity. To examine these trade-offs in the relationship between audience size and revenue under PWYW, we manipulate audience size by exogenously adding synthetic viewers in live streaming shows on a platform in China. The results reveal a mostly positive relationship between audience size and average tip per viewer, which suggests that social image concerns dominate seeking reciprocity. In support of herding, adding synthetic viewers also increases the number of real viewers. Social image concerns and herding together explain the finding that adding one additional viewer improves the tipping revenue per minute by approximately .01 Yuan (1% of the mean level). Further, famous female broadcasters who use recognition-related words frequently during the event benefit the most from an increase in audience size. Overall, the results indicate that revenues under PWYW do not scale linearly and support the relevance of social image concerns in driving individual payment decisions under PWYW.

In the present worldwide highly competitive markets, competition occurs among the supply chain members on behalf of organizations. In this way, partners of the supply chain try to apply effective coordination to increase market shares. Because of the significance and utilization of inventory decisions and pricing strategies on accepting a product in the current business scenario, in this study, decentralized channel coordination is generalized to increase the profitability of a two-echelon supply chain. Here, a one-manufacturer–one-retailer supply chain mechanism for the deteriorating product with a leader–follower relationship under price-dependent demand is developed. Up-stream member-manufacturer sells the on-hand item to the downstream member-retailer in which the retailer faces off the customer. This model considers the effect of the deterioration of the product, selling price of both the channel members, cycle duration, idle time, ordering lot size in a decentralized supply chain system. The Stackelberg game method has been used considering the retailer as a leader and manufacturer as a follower to optimize the sales price of channel members and time–length up to zero manufacturer inventory for maximum profit. Finally, a numerical example and sensitivity analysis are given to demonstrate the model. The result shows that manufacturer profit is far better than the retailer profit though the retailer’s selling price is higher than that of the manufacturer’s selling price. Also, a little change in the manufacturing cost is highly sensitive for the profit of the channel members, which encourages the manufacturer to reduce the manufacturing cost and increases supply chain profit as well as channel members profit.

The importance of reasonable pricing strategy for electric vehicle batteries under the background of government subsidies has been recognized. However, variable government subsidy policy may highly impact the pricing strategy of electric vehicle batteries recycling market in its infancy. There is an urgent need to discover the hidden electric vehicle batteries relation, give the pricing strategy, and suggest the effective policy design. The paper studies the optimal pricing strategies for electric vehicle batteries in three different Chinese recycling channels in the government subsidies situation by using Stackelberg game. And then, the model is simulated in decentralized decision-making and centralized decision-making, respectively, to explain the relationship among parameters using MATLAB. Finally, a numerical experiment derived from the market data of electric vehicles in China and existing literature is used to show the effectiveness of Stackelberg model, proving that our approach can contribute to closed-loop supply chain pricing strategy for electric vehicle batteries recycling under government subsidies. Results show that the government should increase the subsidy of electric vehicle batteries recycling and urge the electric vehicle enterprises to take responsibility of batteries recycling. The total profit of the closed-loop supply chain with centralized decision-making is higher than the decentralized decision-making, so the upstream and downstream of the supply chain should strengthen communication to achieve profit growth. It significantly provides a theoretical basis for the enterprises in the electric vehicle batteries recycling closed-loop supply chain to formulate pricing strategies under three recycling models and provides suggestion for the government in the designing power battery recycling subsidy policy.

With the popularity of the Internet of Things (IoT) and large-scale deployment of sensors, data have exploded. Big data is utilized to extract useful knowledge and information and served as data services to consumers. While most of the current researches in the field of big data services focus on developing and improving algorithms for data mining and information extraction, and rarely studies “big data” from an economic perspective. This article thus studies the pricing and profit maximization problems in big data markets from an economic perspective. First, a method of quantifying the value of data is proposed to study the utility of raw data. Then, we build an economic model of the data market, which consists of three parties: 1) data vendor; 2) service provider; and 3) service users. The data vendor gathers various raw data and sells them to the service provider. The raw data are further processed into data services by a service provider, who provides service subscriptions to users to obtain profits. The interactions among them are formulated as a Stackelberg game to maximize the profits of all participators. The existence and uniqueness of equilibria pricing strategies are proved. Finally, numerical results show that the participators of the data market can achieve the maximum profit through the proposed pricing mechanism and economic model.

ObjectiveTo explore what is known about the tobacco industry’s (TI) price-based responses to tobacco excise tax policies and whether these vary by country income group using a systematic review.Data sourcesStudies assessing TI pricing tactics were identified via searches of five online databases using a combination of search keywords.Study selectionInclusion criteria were applied by two reviewers independently who screened all search results (titles and abstracts) for possible inclusion. They identified 37 publications that reported TI pricing tactics.Data extractionStudy details were tabulated, and information was extracted on the country income group, population characteristics, excise tax structure, and pricing strategies.Data synthesisOf the 37 publications identified, 22 were conducted in high-income countries, while 15 covered low-income and middle-income countries (LMICs). Major pricing strategies employed were: differentially shifting taxes between products (35 studies); launching new brands/products as pathways for downtrading (six studies), product promotions and different prices for the same products for different customers (six studies); price smoothing (two studies); and changing product attributes such as length/size of cigarettes or production processes (three studies).ConclusionsWhile there is limited evidence to fully ascertain industry responses to tax increases, this review suggests that the TI widely uses a multitude of sophisticated pricing strategies across different settings around the world with the intention of undermining tax policies, thereby increasing tobacco consumption and maximising their profits. There is a need for further research in this area especially in LMICs so that effective policy responses can be developed.

The e-waste from high-technology products is at the forefront of many studies that focus on remanufacturing and selling end-of-use electronics. For the market of high-technology products, new commodities belonging to the early generation depreciate faster due to the rapid technology development and the challenge faced from remanufactured products belonging to the latest generation. The aim of this research is to develop pricing strategies for these items and understand how customer’s acceptance towards remanufactured products and the technology obsolescence of new products influence the pricing decisions. This study considers a pricing model in a system with a manufacturer, a remanufacturer, and a retailer. The manufacturer sells the new products belonging to the early generation to the retailer, while the remanufacturer sells the remanufactured product belonging to the latest generation. The customers, categorized into quality-conscious and technology-savvies, select one of the items based on the price and perceived value. The results of five game theory models (viz., Nash Equilibrium, Retailer-Stackelberg balancing power, Retailer-Stackelberg manufacturer lead, Manufacturer-Stackelberg balancing power, and Manufacturer-Stackelberg manufacturer lead) are compared. The impact of different value perceptions between quality-conscious customers and technology-savvies and each customer segment’s relative size are discussed in the five game theory models. The result shows that acting as a follower is a wise decision and suggests that the retailer, manufacturer, and remanufacturer coordinate by balancing their power.

Purpose Managerialization – i.e. the institutional and organizational transformation of cultural institutions acknowledging the need for a managerial action to address their value propositions – is radically reshaping the way museums interact with relevant stakeholders and arrange their service offering. The paper aims at making sense out of the manifold implications of managerialization on museum activities. Design/methodology/approach Secondary data were collected from a sample of 4,073 Italian museums and art institutions. A logit regression model was designed to investigate the implications of museums’ managerialization on pricing strategies, service offering, organizational and marketing policies, inter-organizational relationships and digitalization. Findings Managerialization triggered an evolution in museums’ service offering and organizational practices. Institutions that underwent a managerial development were more likely to innovate their policies and strategies. However, managerialization may undermine the way museums focus on disadvantaged people, nurturing inequalities in the access to their service offering. Practical implications The managerialization of museums should be handled as a double-edged sword. Although it contributes in enriching the museums’ service offering and in differentiating their activities, it may generate drawbacks on the art institutions’ ability to address the demands of underprivileged groups. Tailored correctives are needed to avoid the side effects of managerialization. Originality/value This is one of the first attempts to investigate the implications of managerialization on museums’ practices and inter-organizational relationships. The research findings provide some insights into the challenges that are related to the managerialization of museums and art institutions.

Suppliers of tourist services continuously generate big data on ask prices. We suggest using this information, in the form of a price index, to forecast the occupation rates for virtually any time-space frame, provided that there are a sufficient number of decision makers “sharing” their pricing strategies on the web. Our approach guarantees great transparency and replicability, as big data from OTAs do not depend on search interfaces and can facilitate intelligent interactions between the territory and its inhabitants, thus providing a starting point for a smart decision-making process. We show that it is possible to obtain a noticeable increase in the forecasting performance by including the proposed leading indicator (price index) into the set of explanatory variables, even with very simple model specifications. Our findings offer a new research direction in the field of tourism demand forecasting leveraging on big data from the supply side.

Resilience and flexibility in manufacturing and supply chains are widely discussed at times of the present crises situation due to COVID-19 pandemic. It is a question of ongoing debate among practitioners about the role of flexibility and complexity in building resilience for firms and their supply chains. In this research, we examine the flexible business strategies at the demand, supply, and process side of supply chains contributing to resilience. Five of the major flexible business strategies were acknowledged in this research and the single items for constructing them were posited. In this study, we observe the correlations among the constructs based on survey-based research in electronics manufacturing firms, followed by a dimensionality reduction of constructs using factor analysis. The data collected were subject to several initial tests for ensuring validity, reliability, and adequacy using relevant statistical indicators. The measurement model was converted into a structural model and path coefficients were determined. From the path analysis, the latent variables contributing to flexibility in supply chains were found to be independent estimators of resilience. Adding to it, we observe that the single items for measuring the flexibility of supply, process, product, and pricing strategies were evidenced to be strongly correlated. The results are useful to managers for taking decisions related to flexibility implementation, towards enhancing resilience in supply chains.

PurposeThe purpose of this paper is to explore the operation strategies of a manufacturer who produces brown and green product simultaneously.Design/methodology/approachThe authors establish three models to examine the joint decisions of pricing and advertising. Three advertising strategies are: non-advertising investment (NA), advertising investment for brown product (BA) and advertising investment for green product (GA).FindingsThe theoretical analysis shows that advertising investment can substantially increase the product greening level and manufacturer's profit. More importantly, we find that the GA strategy is more likely to be the best strategy as the advertising investment efficiency increases. The BA strategy is more likely to be preferred as the R&D cost increases. Finally, the modeling results are verified by numerical experiments, and more insights are obtained.Research limitations/implicationsThis paper considers the case in which a single manufacturer produces the brown and green product simultaneously. In fact, many manufacturers in the market produce brown and green product at the same time. Furthermore, in addition to advertising investment for brown product and green product, manufacturers can also invest in advertising for brands.Originality/valueThe paper contributes to the investigations on green production and advertising decisions of a manufacturer who produces brown and green products simultaneously.

Purpose Responding to the store brand (SB) introduction by the retailer, the manufacturer may adopt the strategic choice of incorporating the fairness concern behavior of the retailer. This paper aims to examine how the manufacturer can counteract the retailer’s SB introduction by strategically choosing to or not to incorporating the retailer’s fairness concern. Design/methodology/approach This paper considers the SB introduction problem in a two-echelon supply chain consisting of one manufacturer and one retailer with fairness concern behavior. This paper resolves the pricing strategies under four strategic scenarios regarding fairness concern incorporation and SB introduction and examine the influences from the fairness concern on pricing strategies and profits. This paper further investigates the strategic choice equilibrium of the manufacturer and retailer on fairness concern and SB introduction decision. Findings The results show that the retailer can be better off by the introduction of the SB only when the acceptance degree of the SB is high enough. And whether the manufacturer should incorporate the retailer's fairness concern depends on the consumer's acceptance of the SB: Only when the consumer's acceptance is moderate, the manufacturer is able to counteract the SB by strategically not incorporating the retailer’s fairness concern behavior. Otherwise, the manufacturer cannot prevent the retailer from introducing the SB and can be better off by incorporating the retailer’s fairness concern behavior. Originality/value This paper contributes to the literature by examining whether the manufacturer can adopt the strategic incorporation of the retailer's fairness concern to counteract the retailer's SB introduction.

This study aims to find out the level of traditional retail competition and strategies developed by traditional retail to remain resilient in modern business competition in an Islamic perspective. This study uses qualitative approach with phenomenological research type. The data is obtained from secondary data, namely data on the number of traditional retail and some modern retail in Wiradesa Subdistrict, Pekalongan Regency, Central Java. Research data obtained by interview techniques to business owners and consumers, observations and documentation. The population in this study was 8 modern retail (3 Alfamart, 5 Indomart), and 428 traditional retail (grocery stores and grocery stores) in Wiradesa Sub-district. Samples taken were 1 Alfamart in Gumawang Village, 1 Indomart in Gumawang Village, Adam's Shop in Gumawang Village, and Blue Shop in Kemplong Village, Pekalongan Regency. Data triangulation is used to maintain the validity of data. The study found that: (1) strategies developed by traditional retail are a) communication strategies as well as social relations with consumers as the implementation of Islamic values in the field of business services, b) cheaper pricing strategies, (2) modern retail applies a variety of promotions to attract consumers, (3) the business development system of both types of retail conducted does not deviate from Islamic business ethics.Keywords: traditional retail, modern retail, competitive strategy, Islamic business ethics.

Are tourists sensitive to price? A field experiment was conducted to draw conclusions regarding the effect of three different price strategies on the revenues of a small business selling to tourists. Price elasticity determinations during each phase of the pricing experiment were also computed. This research was conducted in a tourist-based monopolistic competition market structure. Results from the pricing strategies examined indicated little to no difference in sales revenues regardless of pricing strategy employed. This finding is relevant for small businesses operating in a tourist market who often compete on price.

Purpose This paper aims to examine developments in tourism during the COVID-19 pandemic using the hotel sector in the North-East of England as the area of study. The country has attracted a lot of attention not only because of its importance as a tourism destination but also due to its rather controversial management of the pandemic at least in its early stages. Design/methodology/approach Fifteen semi-structured interviews based on ten open-ended questions were conducted with North East of England-based hotel managers of international brands on the level of their hotels’ preparedness to effectively deal with pandemic cases. The interviews took place in August and September 2020 with participants kept anonymous. Findings Meeting new operational and bureaucratic requirements added to the cost structure and proved a major challenge for managers who saw their hotel occupancy rates and revenue collapsing within a short period of time. Innovative and aggressive pricing strategies were introduced to lure especially younger travelers in the absence of business clientele. Staff were made redundant and/or asked to work overtime making effective human resource management very difficult. Originality/value This is one of the first research attempts to highlight the importance of the COVID-19 pandemic for the hotel sector in a major region of the UK. The paper also attempts some generalization by discussing managerial implications and suggesting a possible way forward for the hotel sector. Developing resilience by building on previously used successful business practices proves of essence.

In this study, the direct impact of knowledge about the electricity pricing policies on residents’ electricity saving behaviour and the indirect impact of these pricing strategies on residential co...

In recent years, with the rapid development of Internet technology, the integration of platform economy and e-commerce has become a popular business model. Two-sided platforms have a specific impact on sales, customer experience and transaction efficiency of both sides. In the current severe situation caused by the coronavirus pandemic, both the traditional unilateral market platform and the emerging two-sided market platform are in urgent need of a change in operation mode to reduce the marketing cost. Inspired by the cooperation between Meituan, a two-sided platform, and WeChat, a social media platform, this paper investigates the two-sided platform's scalable decisions on when to cooperate and how to optimize the pricing and investment decisions. We analyze how the two-sided platform makes decisions by considering the changes of network externalities from the cooperation with the social network platform. Compared with the scenario of non-cooperation, we derive the conditions under which platform cooperation can increase demands and increase platforms' profits, and analyze how cooperation affects the optimal pricing strategies. We find that the cooperation leads to a larger demand and a higher total profit, but might lead to higher registration prices for the platform users. Furthermore, we adopt the Nash bargaining framework and introduce platform bargaining power parameters to obtain the optimal cooperation and sharing strategy. Finally, we show how to adjust the investment strategy of the two-sided platform under platform cooperation.

(1) Background: A binding recommended retail price has been used in several markets in a variety of forms, and the book market is a typical example. Publishers sell books to online retailers at a unit wholesale discount computed on the cover price. Retailers are then allowed to set the retail price. Therefore, if consumers regard the cover prices as reference points, then they may be more likely to purchase books if retail prices are lower than the cover prices. (2) Methods: We develop a Stackelberg game model for a book supply chain to investigates how reference price effects affect retailers and publisher’s pricing strategies. (3) Results: The results show that retailers will sell printed books at a discount only when the publisher’s wholesale discount rate is not high. Further, as the intensity of the reference price effects increases, (a) the lower boundary of the wholesale discount rate rises, (b) publishers’ profits increase and (c) retailers’ profits increase relative to the level of consumers’ e-books acceptance. (4) Conclusions: This result is related to the fact that the online retailer, such as Amazon and JD.com, like to invoke reference price effects in consumers’ minds by highlighting the printed book’s discount rate.

Jenang Karomah is a business brand that has been established for 24 years to experience the dynamics of sales ups and downs. It is estimated that there is a link between variables of marketing strategy and service quality, especially for women buyers. This variable encourages researchers to research more about marketing strategies which include product, price, place, promotion. This study aims to analyze the marketing strategy of Jenang Karomah in Kudus and their impact on women's buying interest. The research method used in this study is a qualitative method, namely observation and interviews as data collection techniques. The results found four strategies developed by Jenang Karomah. First, the product strategy; packing with a good color, shape and brand, although still found packaging that is less tidy or defective. Second, place strategy; Jenang Karomah is located near the Kudus City Center where the majority of the community are also jenang sellers which results in competition to attract women buyers. Third, pricing strategies; Jenang Karomah fluctuates prices, especially during the moments of the big day before Lebaran or celebration which results in women's buying interest becoming very selective. Fourth, promotion strategies; Jenang Karomah has done offline promotions, but lacks promotion based on internet technology, namely social media such as YouTube, Instagram, Facebook, and Twitter which are widely used by young women as potential buyers. Four strategies developed by Jenang Karomah have influenced women's buying interest in Kudus City. The research method used in this study is qualitative with a descriptive analytical approach.

In recent years, online reviews are increasingly getting more concerns by firms and consumers because they can help mitigate consumers’ uncertainty on product quality and experienced attributes and significantly affect firms’ operational decisions. We in this study attempt to examine the remanufacturing entry and pricing strategies of manufacturers in the presence of online reviews. We consider an original equipment manufacturer (OEM) selling a new product over two periods in online retailing and determine whether and when to adopt a remanufacturing entry strategy in the market. We uncover online reviews’ quality-dimensional effect and experienced dimensional effect that jointly determine the OEM’s pricing and remanufacturing strategies. We show that in the presence of online reviews, the OEM will cautiously determine whether to adopt the first-period remanufacturing entry strategy and may also adopt the second-period remanufacturing entry strategy under certain conditions. Interestingly, the OEM will adopt the penetration pricing strategy for the new product and the remanufactured product (if available) when the actual product quality is sufficiently high, but the skimming pricing strategy otherwise, which is different from the uniform pricing strategy in the absence of online reviews. Our results also show that online reviews significantly affect the OEM’s profit and consumer surplus. In particular, when the actual product quality is high enough, the OEM and consumers will attain the “win–win” situation.

Participative pricing strategies may influence consumer purchase decisions; this research proposes specifically that firms’ delegation of pricing decisions to consumers can create a control–effort trade-off. Consumers favor greater pricing control but are deterred by the effort involved in deciding what to pay. Strategies such as pay what you want in turn might reduce purchase intentions due to the effort involved. In contrast, strategies that increase feelings of control but not perceived effort, such as pick your price options that let consumers choose from a limited set of prices, could enhance pricing outcomes. A field study and four laboratory experiments confirm these propositions. The findings demonstrate the mixed effects of participative pricing, identify mediating mechanisms that explain these effects, and specify common moderating conditions that shape the outcomes of participative pricing. These results have notable implications for pricing theory and practice.

This paper examines the influence of information forecast accuracy on the profits of the supply chain under the circumstance of a multichannel apparel supply chain. Due to the emergence of multichannel, customer showrooming behavior is becoming increasingly prevalent. For example, consumers usually buy garments online after experiencing the service in the traditional bricks and mortar in the clothing industry. Meanwhile, there are often information barriers between the manufacturer and the retailer, which will affect enterprise decision-making. To solve these problems, this paper mainly investigates the information sharing and customer showrooming phenomenon, which includes four models: no information sharing without showrooming model (NN), information sharing without showrooming model (SN), no information sharing with showrooming model (NS), and information sharing with showrooming model (SS). The numerical analysis shows that under the impact of the forecast error, information sharing between channel members is more favorable than no information sharing when parameters satisfy certain conditions. From the perspectives of the retailer, the manufacturer, and the whole supply chain, customer showrooming behavior will bring them less profit. These conclusions mean that the retailer should share information with the manufacturer and adjust their service level and sales price to alleviate the effect of showrooming.

Recommender systems enable firms to target customers with products and services that better match their needs, as well as cross-sell products and services. Considering these factors in markets with...

Urban air mobility (UAM) is an emerging concept proposed in recent years that uses electric vertical take-off and landing vehicles (eVTOLs). UAM is expected to offer an alternative way of transporting passengers and goods in urban areas with significantly improved mobility by making use of low-altitude airspace. In addition to other essential elements, ground infrastructure of vertiports is needed to transition UAM from concept to operation. This study examines the network design of UAM on-demand service, with a particular focus on the use of integer programming and a solution algorithm to determine the optimal locations of vertiports, user allocation to vertiports, and vertiport access- and egress-mode choices while considering the interactions between vertiport locations and potential UAM travel demand. A case study based on simulated disaggregate travel demand data of the Tampa Bay area in Florida, USA was conducted to demonstrate the effectiveness of the proposed model. Candidate vertiport locations were obtained by analyzing a three-dimensional (3D) geographic information system (GIS) map developed from lidar data of Florida and physical and regulation constraints of eVTOL operations at vertiports. Optimal locations of vertiports were determined to achieve the minimal total generalized cost; however, the modeling structure allows each user to select a better mode between ground transportation and UAM in terms of generalized cost. The outcomes of the case study reveal that although the percentage of trips that switched from ground mode to multimodal UAM was small, users choosing the UAM service benefited from significant time saving. In addition, the impact of different parameter settings on the demand for UAM service was explored from the supply side, and different pricing strategies were tested that might influence potential demand and revenue generation for UAM operators. The combined effects of the number of vertiports and pricing strategies were also analyzed. The findings from this study offer in-depth planning and managerial insights for municipal decision-makers and UAM operators. The conclusion of this paper discusses caveats to the study, ongoing efforts by the authors, and future directions in UAM research.

We study how the manufacturer and the supplier collaborate under various pricing and contracting scenarios. We characterize two downstream pricing strategies: (a) where the manufacturer announces the market price before the quality is determined, and (b) where the manufacturer decides the market price after the quality is determined. We also study three different contracting structures: (a) effort levels are both contractible and verifiable, (b) revenue sharing agreement between manufacturer and supplier, and (c) effort dependent contract when effort levels are verifiable but not contractible. We determine under which conditions the manufacturer should implement each of the scenarios.

BACKGROUND: Nudging and salient pricing are promising strategies to promote healthy food purchases, but it is possible their effects differ across food groups.OBJECTIVE: To investigate in which food groups nudging and/or pricing strategies most effectively changed product purchases and resulted in within-food groups substitutions or spillover effects.METHODS: In total, 318 participants successfully completed a web-based virtual supermarket experiment in the Netherlands. We conducted a secondary analysis of a mixed randomized experiment consisting of 5 conditions (within subject) and 3 arms (between subject) to investigate the single and combined effects of nudging (e.g., making healthy products salient), taxes (25% price increase), and/or subsidies (25% price decrease) across food groups (fruit and vegetables, grains, dairy, protein products, fats, beverages, snacks, and other foods). Generalized linear mixed models were used to estimate the incidence rate ratios and 95% CIs for changes in the number of products purchased.RESULTS: Compared with the control condition, the combination of subsidies on healthy products and taxes on unhealthy products in the nudging and price salience condition was overall the most effective, as the number of healthy purchases from fruit and vegetables increased by 9% [incidence rate ratio (IRR) = 1.09; 95% CI: 1.02, 1.18], grains by 16% (IRR = 1.16; 95% CI: 1.05, 1.28), and dairy by 58% (IRR = 1.58; 95% CI: 1.31, 1.89), whereas the protein and beverage purchases did not significantly change. Regarding unhealthy purchases, grains decreased by 39% (IRR = 0.72; 95% CI: 0.63, 0.82) and dairy by 30% (IRR = 0.77; 95% CI: 0.68, 0.87), whereas beverage and snack purchases did not significantly change. The groups of grains and dairy showed within-food group substitution patterns toward healthier products. Beneficial spillover effects to minimally targeted food groups were seen for unhealthy proteins (IRR = 0.81; 95% CI: 0.73, 0.91).CONCLUSIONS: Nudging and salient pricing strategies have a differential effect on purchases of a variety of food groups. The largest effects were found for dairy and grains, which may therefore be the most promising food groups to target in order to achieve healthier purchases. The randomized trial on which the current secondary analyses were based is registered in the Dutch trial registry (NTR7293; www.trialregister.nl).