Search Results (15)

This paper explores optimal strategies for manufacturers, streamers, and retailers in a dual-channel environment, focusing on three commission structures and two power structures. Our analysis identifies steady states where dynamic commissions converge, enhancing profitability and stability for all parties. We find that less dominant partners prefer commission structures that reinforce existing power structures. Profitability is influenced by dynamic commissions: under manufacturer dominance, dynamic wholesale price and commission rate increase profitability for manufacturers and retailers while decreasing streamers’ profits. In contrast, under streamer dominance, a dynamic commission rate enhances streamers’ profits but reduces those of manufacturers and retailers. This evaluation highlights the shared interests between manufacturers and retailers. Taking the spillover effect into account, commission strategies should consider hassle cost, initial commission rate, and spillover impact. Product selection strategies show consistent trends, with moderate hassle cost and a disutility factor ranging from moderate to high, regardless of the spillover effect. Full article

We study an online–merge–offline (OMO) system that integrates a retailer’s online and offline channels through an e-commerce platform and a wireless applet. The customers in the online channel are generated through paid advertising in an e-commerce platform, while the offline channel is a regional retail chain. The OMO system omnichannelizes sole-channel customers from either channel by converting them into omnichannel ones with the wireless applet and then providing them online and offline options at each touch point along the shopping journey. The prices in the OMO system across both channels are uniform. To validate the effectiveness of this new omnichannel system, we construct a legacy system that maintains separate online and offline channels with independent customer populations. Using the legacy system as a benchmark, we assume the OMO system has arbitrary omnichannelization rates of the customers flowing into the two channels. We analyse the perfect OMO system which has all the customers omnichannelized, and show its advantage over the legacy system. We then numerically find that if the omnichannelization rates in the OMO system are general then it is most efficient when products are either highly digital or highly nondigital. Full article

In the context of new retail, the development of omni-channels is flourishing. The entry threshold for the clothing industry is low, and the popularity of online shopping has, to some extent, reduced consumers’ perception of the authenticity of clothing. As a result, returns are a serious issue in the clothing industry. This article focuses on a clothing retailer while addressing retail and return issues in the clothing industry. It develops and analyzes models for an online single-channel strategy and two omni-channel showroom strategies: “Experience in Store and Buy Online (ESBO)” with an experience store and “Buy Online and Return in Store (BORS)” with a physical store. These models are used to examine the pricing and return decisions of the retailer in the three strategic scenarios. Additionally, this study considers the impact of fashion trends on demand. It explores pricing and return strategies in two showroom models under the influence of the fashion trend decay factor. Moreover, sensitivity analyses and numerical analyses of the important parameters are performed. This research demonstrates the following: (1) In the case of high return transportation costs and online return hassle costs, clothing retailers can attract consumers to increase profits through establishing offline channels; (2) extending the sales time of fashionable clothing has a positive effect on profits, but blindly prolonging the continuation of the sales time will lead to a decrease in profits; (3) the larger the initial fashion level or the smaller the fashion level decay factor, the greater the optimal retailer profits. The impacts of the initial fashion level and fashion level decay factor on profits are more significant in omni-channel operations. This article aims to identify optimal strategies for retailers utilizing omni-channel operations and offer managerial insights for the sale of fashionable apparel. Full article

Over the past decade, return freight insurance (RFI) and return pickup services (RPSs) have emerged as dominant return service strategies in e-commerce, particularly in China’s competitive online retail market. Despite their prominence, the strategic dynamics guiding e-sellers’ choice between these services remain underexplored. This study develops a game-theoretic model to analyze the equilibrium return strategies of two horizontally competing e-sellers with varying misfit probabilities. By examining four subgames, we identify the conditions under which e-sellers converge on either RFI or RPSs. Our findings revealed that highly similar or highly differentiated products typically favor RFI due to intense price competition or reduced need for service-based competition, while moderately differentiated products lead to RPS adoption as service quality becomes a key competitive lever. Additionally, competitive pressure often drives e-sellers to adopt homogenized return strategies, particularly RPSs, to maintain market position. The equilibrium outcomes are shaped by misfit probability differences, consumer hassle costs, and cost structures, offering actionable insights into optimizing return strategies in competitive e-commerce environments. These findings provide actionable insights into optimizing return service strategies in competitive e-commerce environments and contribute to the growing literature on return policies as a competitive lever in online retail markets. Full article

The pricing of ride-hailing platforms (e.g., Didi Rider and Uber) is heavily and simultaneously influenced by the cross-group network effect and congestion effect. To analyze the bilateral pricing of ride-hailing platforms under the influence of these two effects, in this paper we construct a game-theoretic model under four different scenarios and analyze the equilibrium outcomes. The results show that: (1) when both passengers and drivers are sensitive to hassle costs, if the cross-group network effect on the passenger side is higher than that on the driver side, then the platform’s pricing on both sides increases with the increase in the congestion effect, otherwise the prices on both sides of the platform decrease with the increase in the congestion effect; (2) when passengers are sensitive to hassle costs and drivers are sensitive to price, if the ratio for passengers’ and drivers’ different perceptions of price and hassle cost is greater than a certain threshold, then the platform’s pricing on the passenger side increases with the increase in the congestion effect and the platform’s pricing on the driver side decreases with the increase in the congestion effect, otherwise the platform’s pricing on the passenger side decreases with the increase in the congestion effect and the platform’s pricing on the drivers’ side increases with the increase in the congestion effect; (3) when passengers are sensitive to price and drivers are sensitive to hassle costs, if the ratio for passengers’ and drivers’ different perceptions of price and hassle costs is greater than a certain threshold, then the platform’s pricing on the passenger side decreases with the increase in the congestion effect and the platform’s pricing on the drivers’ side increases with the increase in the congestion effect, otherwise the platform’s pricing on the passenger side increases with the increase of the congestion effect and the platform’s pricing on the driver side decreases with the increase in the congestion effect; (4) when both passengers and drivers are price-sensitive, if the cross-group network effect on the passengers’ side is larger than that on the drivers’ side, then the platform should decrease its pricing on both sides with the increase in the congestion effect, otherwise, if the cross-group network effect on the passengers’ side is less than that on the drivers’ side, the platform should increase its pricing on both sides with the increase in the congestion effect; (5) the platform is able to generate the highest profit in each scenario, and the results of the profit comparison between the four scenarios depends on the cross-group network effects and the congestion effects on both the passengers’ and the drivers’ sides. Full article

The current traditional paper ballot voting schemes suffer from several limitations such as processing delays due to counting paper ballots, lack of transparency, and manipulation of the ballots. To solve these limitations, an electronic voting (e-voting) scheme has received massive interest from both governments and academia. In e-voting, individuals can cast their vote online using their smartphones without the need to wait in long lines. Additionally, handicapped voters who face limited wheelchair access in many polling centers could now participate in elections hassle-free. The existing e-voting schemes suffer from several limitations as they are either centralized, based on public blockchains, or utilize local private blockchains. This results in privacy issues (using public blockchains) or large financial costs (using local/private blockchains) due to the amount of computing power and technical knowledge needed to host blockchains locally. To address the aforementioned limitations, in this paper, we propose an online voting scheme using IBM cloud-based Hyperledger Fabric. Our scheme allows voters to cast their encrypted votes in a secure manner. Then any participant can obtain the ballot results in a decentralized and transparent manner, without sacrificing the privacy of individual voters. We implement the proposed scheme using IBM cloud-based Hyperledger Fabric. The experimental results identify the performance characteristics of our scheme and demonstrate that it is feasible to run an election consisting of thousands of participants using cloud-based Fabric. Full article

With the rapid development of information technology and communication technology, several online recovery platforms have introduced offline channels to encourage customers to participate in product acquisition and improve profits. Motivated by this reverse supply chain practice, we develop a game theory model under three scenarios (single offline channel, single online channel, and dual-channel structures) to assess the effect of a newly added offline channel for online recovery platforms and explore the factors that have significant impacts on the dual-channel strategy for recovery platforms. We conduct static analyses to solve the model and perform a numerical study to examine the robustness of the results. The results reveal that a recovery platform can always gain more profit and set lower recovery prices under the dual-channel structure. However, the relatively high shipping cost might cause the recovery platform to recover a smaller quantity under the dual-channel structure compared with the single offline channel structure. In addition, the recovery platform is more likely to adopt a dual-channel structure with low shipping cost, high average hassle cost or hassle cost uncertainty, and less uncertainty on the reservation value. Moreover, the recovery platform can use the price difference between online and offline channels as a tool to split product holders and induce them to choose the most appropriate channel. Our findings highlight the profit and recovery quantity benefits brought by the dual-channel structure, and provide management insights for recovery platforms. Full article

Electric vehicles (EVs) are gradually becoming an integral part of the drive to accomplish sustainable energy standards. Due to their limited onboard battery capacity, EVs’ expanding popularity creates a need for widespread charging stations. However, fast charging stations, particularly Extreme Fast Charging (EFC), may impose a hassle on the electrical system due to overload during peak hours, frequent power gaps, and voltage sag. To flatten the power supply, the photovoltaic (PV) Hybrid Energy Storage Systems (HESS) and the uncertain and variable nature of PV systems always include solar and hybrid energy storage systems (HESS) such as batteries and supercapacitors. This research suggests a multi-port DC-DC converter (MPC) with a bidirectional DC-DC converter for battery ESS-integrated PV systems. The MPC can regulate the majority of active power through PV to a battery, PV to an EV charging station, HESS to an EV charging station, and PV to AC grid. Additionally, a PI controller is used for the MPC, taking both the PV and battery voltage variations into account. Therefore, the presented configuration can achieve the key benefits of greater integration, more efficiency, and reduced cost. Simulation results show the advantages of this multiport EV charging circuit with PV-HESS and design in different modes. Full article

The continuous monitoring of respiratory rate (RR) and oxygen saturation (SpO2) is crucial for patients with cardiac, pulmonary, and surgical conditions. RR and SpO2 are used to assess the effectiveness of lung medications and ventilator support. In recent studies, the use of a photoplethysmogram (PPG) has been recommended for evaluating RR and SpO2. This research presents a novel method of estimating RR and SpO2 using machine learning models that incorporate PPG signal features. A number of established methods are used to extract meaningful features from PPG. A feature selection approach was used to reduce the computational complexity and the possibility of overfitting. There were 19 models trained for both RR and SpO2 separately, from which the most appropriate regression model was selected. The Gaussian process regression model outperformed all the other models for both RR and SpO2 estimation. The mean absolute error (MAE) for RR was 0.89, while the root-mean-squared error (RMSE) was 1.41. For SpO2, the model had an RMSE of 0.98 and an MAE of 0.57. The proposed system is a state-of-the-art approach for estimating RR and SpO2 reliably from PPG. If RR and SpO2 can be consistently and effectively derived from the PPG signal, patients can monitor their RR and SpO2 at a cheaper cost and with less hassle. Full article

The wide use of internet-enabled devices has not left the healthcare sector untouched. The health status of each individual is being monitored irrespective of his/her medical conditions. The advent of such medical devices is beneficial not only for patients but also for physicians, hospitals, and insurance companies. It makes healthcare fast, reliable, and hassle-free. People can keep an eye on their blood pressure, pulse rate, etc., and thus take preventive measures on their own. In hospitals, too, the Internet of Things (IoT) is being deployed for various tasks such as monitoring oxygen and blood sugar levels, electrocardiograms (ECGs), etc. The IoT in healthcare also reduces the cost of various ailments through fast and rigorous data analysis. The prediction of diseases through machine-learning techniques based on symptoms has become a promising concept. There may also be a situation where real-time analysis is required. In such a latency-sensitive situation, fog computing plays a vital role. Establishing communication every time with the cloud is not required with the introduction of fog and thus the latency is reduced. Healthcare is a latency-sensitive application area. So, the deployment of fog computing in this area is of vital importance. Our work focuses on improving the efficiency of the system for the precise diagnosis of and recommendations for heart disease. It evaluates the system using a machine-learning module. Full article

This paper investigates when an omnichannel brand should offer digital coupons in the online and buy-online-and-pick-up-in-store (BOPS) channels and, if so, the joint decision of coupon face value and store inventory. The impact of a digital coupon promotion on store inventory is also explored. Two scenarios are considered, one where consumers’ costs in the online and store channels are homogeneous and another in which they are heterogeneous, and two newsvendor models, with and without a coupon promotion, are constructed under each scenario. The results show that the issuance of coupons improves the omnichannel brand’s profit when the price is high and the coefficient of the difference in valuation between two types of consumers is low in the homogeneous scenario. In the heterogeneous scenario, the brand prefers the coupon promotion when the price is high or moderate and the coefficient of the difference in valuation between two types of consumers is high. In addition, offering a coupon promotion yields a higher store inventory in most cases. However, store inventory is decreased in some special cases in the homogeneous scenario. Moreover, an increased hassle cost in the BOPS channel significantly lowers the offline demand and profit increase from a digital coupon promotion. Furthermore, a coupon promotion is more likely to benefit both the brand and consumers as the cross-selling revenue increases. These results provide guidance for omnichannel brands to implement coupon promotions and adjust store inventory with stochastic demand. Full article

Based on consumers’ different preferences for hassle costs, we study two platform operation strategies: selected platforms and diversified platforms. Considering diverse charging systems of merchants on the platform, a two-sided user utility function and profit function are established to examine the influence of hassle costs, platform services and the strength of two-sided network effects on the scale of platform users, and platforms’ profits and price. The results show that: (1) The selected platform strategy adopting the transaction fee system is better than other strategies. (2) Under the selected platform strategy, the scale of bilateral users and platform profits will decrease with the increase in hassle costs, and increase with the strengthening of the bilateral network effects. However, the proportion of equilibrium pricing for merchants will increase with the increase in consumer hassle costs, and will decrease with the increase in the network effect on the consumer side. (3) The less value-added services that selected platforms provide to consumers, the more value-added services exist to merchants and the higher the equilibrium pricing is for merchants. However, as the network effect on the side of merchants is increasing, the equilibrium pricing ratio of the platform to merchants shows three trends However, the general trend is that the greater the network effect of the business side, the lower the fee ratio and the higher the platform profit. Full article

For safe autonomous driving, deep neural network (DNN)-based perception systems play essential roles, where a vast amount of driving images should be manually collected and labeled with ground truth (GT) for training and validation purposes. After observing the manual GT generation’s high cost and unavoidable human errors, this study presents an open-source automatic GT generation tool, CarFree, based on the Carla autonomous driving simulator. By that, we aim to democratize the daunting task of (in particular) object detection dataset generation, which was only possible by big companies or institutes due to its high cost. CarFree comprises (i) a data extraction client that automatically collects relevant information from the Carla simulator’s server and (ii) a post-processing software that produces precise 2D bounding boxes of vehicles and pedestrians on the gathered driving images. Our evaluation results show that CarFree can generate a considerable amount of realistic driving images along with their GTs in a reasonable time. Moreover, using the synthesized training images with artificially made unusual weather and lighting conditions, which are difficult to obtain in real-world driving scenarios, CarFree significantly improves the object detection accuracy in the real world, particularly in the case of harsh environments. With CarFree, we expect its users to generate a variety of object detection datasets in hassle-free ways. Full article

As an increasing number of firms move to omnichannel operation for business sustainability, it is also necessary for fresh produce firms to adopt an omnichannel model by integrating online and offline channels. We focus on a fresh produce supply chain consisting of a supplier who sells online directly and a physical store retailer. The purpose of this paper is to explore the optimal channel selection strategy considering the fresh-keeping efforts of supply chain members. Specifically, we examine the conditions under which the supply chain members should cooperate to adopt the deliver-from-store (DFS) model and further investigate the impact of consumers’ freshness sensitivity and offline hassle cost on supply chain members’ sales model options. Several important conclusions are shown as follows. First, the retailer’s profit increases with the increasing freshness sensitivity in the dual-channel model, while it decreases if consumers are sufficiently sensitive to freshness in the DFS model. Second, if adopting the DFS model, online demand and total market demand expand, and the performance of the supplier and the retailer heavily depends on the size of the commission rate. Third, there always exists a win–win situation with an appropriate range of commission rate when the consumer’s hassle cost is large. This paper contributes to the omnichannel strategy research of fresh produce supply chain management and the results provide management insights for the sustainable development of the fresh produce industry in the omnichannel retailing environment. Full article

This paper is motivated by the dilemma faced by firms who sell new and remanufactured products offline that need to consider whether to enter e-commerce platforms considering that more and more consumers are shopping online on e-commerce platforms rather than shopping offline. Our paper aims to help firms with new and remanufactured products make a channel choice and determine product pricing strategies in the contexts of e-commerce and carbon tax policy. Our paper uses optimization theory, game theory, utility functions and profit-maximization models to investigate the optimal channel choice of whether a firm should enter an e-commerce platform; it also investigates the optimal prices of new and remanufactured products and referral fees in two cases—the firm does not enter the platform (N) and the firm enters the platform (Y). Some insights are presented as follows: We found that the firm should enter the platform if the annual service fee is relatively low, otherwise, the firm should not enter the platform. Interestingly, in the case of a firm with an offline store with relatively large operational costs or hassle costs, the firm is more reluctant to enter the platform. In the extension, we considered some consumers who only purchase offline products, and found that the firm considering these consumers is more likely to choose not to enter the platform. Moreover, we argue that the carbon tax policy has a positive effect on product prices but a negative effect on referral fees charged by the platform, and the choice of Y hurts the environment due to a relatively high total carbon emission. Full article