Search Results (530)

This paper presents a two-stage explainable recommendation system for reciprocal affiliate–seller matching that uses machine learning and data science to handle voluminous data and generate personalized ranking lists for each user. In the first stage, a representation learning model was trained to create dense embeddings for affiliates and sellers, ensuring efficient identification of relevant pairs. In the second stage, a learning-to-rank approach was applied to refine the recommendation list based on user suitability and relevance. Diversity-enhancing reranking (maximal marginal relevance/explicit query aspect diversification) and popularity penalties were also implemented, and their effects on accuracy and provider-side diversity were quantified. Model interpretability techniques were used to identify which features affect a recommendation. The system was evaluated on a fully synthetic dataset that mimics the high-level statistics generated by affiliate platforms, and the results were compared against classical baselines (ALS, Bayesian personalized ranking) and ablated variants of the proposed model. While the reported ranking metrics (e.g., normalized discounted cumulative gain at 10 (NDCG@10)) are close to 1.0 under controlled conditions, potential overfitting, synthetic data limitations, and the need for further validation on real-world datasets are addressed. Attributions based on Shapley additive explanations were computed offline for the ranking model and excluded from the online latency budget, which was dominated by approximate nearest neighbors-based retrieval and listwise ranking. Our work demonstrates that high top-K accuracy, diversity-aware reranking, and post hoc explainability can be integrated within a single recommendation pipeline. While initially validated under synthetic evaluation, the pipeline was further assessed on a public real-world behavioral dataset, highlighting deployment challenges in affiliate–seller platforms and revealing practical constraints related to incomplete metadata. Full article

Background/Objectives: This study explored how attribute framing (lifestyle-focused vs. technology-focused product descriptions) and popularity cueing (presence or absence of a “best-seller” label) influenced purchase likelihood for a fictitious selection of hearing aids (HAs) among Canadian adults aged 40 years and above. The study further aimed to investigate whether the effects observed were unique to HAs or applicable to less-specialized consumer technology contexts. Method: A 2 × 2 × 2 mixed experimental design compared attribute framing and popularity cueing effects across HAs and notebook computers at three technology levels (entry-level, midrange, and premium). Participants (n = 122) provided ratings indicating their purchase likelihood for each product. Results: Attribute framing showed no significant influence on purchase decisions across technology levels. The presence of a popularity cue that the midrange HA was the best-seller negatively affected purchase likelihood for the entry-level HA, with higher purchase likelihood ratings observed when this cue was absent. Participants expressed stronger purchase likelihood for premium HAs compared to premium notebook computers. Notably, these two effects were not statistically significant following correction for multiple comparisons. Conclusions: Popularity cues for HAs may have inadvertent consequences for consumer perceptions of models with differing technology levels. Findings also suggest potentially greater willingness to invest in premium health-related technologies versus familiar consumer technology. Further research involving current HA users or candidates is needed to better understand these findings. Full article

Based on survey data from 320 Azerbaijani enterprises operating across the organic product value chain—including producers, sellers, and key supporting firms such as logistics, financial, and ICT service providers—this study investigates how digital platform capability influences firms’ innovation and performance outcomes and their perceived high-quality economic development within an emerging digital economy context. Four constructs—Digital Platform Capability, Enterprise Digital Transformation, Innovation and Performance Outcomes, and Perceived High-Quality Economic Development—are measured using multi-item Likert scales. Confirmatory factor analysis and Structural Equation Modeling (SEM) are employed to test the proposed relationships. The results show that Digital Platform Capability exerts a strong positive effect on Innovation and Performance Outcomes (β = 0.574) and on Perceived High-Quality Economic Development (β = 0.512). In addition, Innovation and Performance Outcomes have a direct positive impact on Perceived High-Quality Economic Development (β = 0.313). Mediation analysis further indicates that Enterprise Digital Transformation partially mediates this relationship, transmitting approximately 52% of the total effect of Innovation and Performance Outcomes on Perceived High-Quality Economic Development. These findings underscore digital transformation as a key structural mechanism through which firm-level innovation and performance contribute to broader perceptions of high-quality economic development. The study provides novel empirical evidence from Azerbaijan and offers practical implications for digital policy design and enterprise strategies aimed at promoting innovation-driven, inclusive, and sustainable growth. Full article

Origin warehouses, positioned at the critical “first mile” of the agri-food supply chain, profoundly influence supply chain power structures and profit allocation, as well as supply chain stability and sustainable development. To explore the role of origin warehouses in the agri-food supply chain, this study develops a three-level game model comprising a “planter–origin warehouse operator–seller” framework. Notably, this study conceptualizes the dual-functional “origin warehouse” as observed in practice, proposing two theoretical modes: the Logistics Center (LC) and the Supply Chain Center (SCC). By treating quality level, service level, and selling price decisions as endogenous variables, this study further reveals the interconnected decision-making mechanisms under different operational modes. Overall, the LC mode performs better in quality-driven markets, generating higher system profits and greater social welfare, whereas the SCC mode is superior when consumers are more price-sensitive or place greater value on service. Based on these findings, this study provides decision-making guidance for origin warehouse operators aiming to select the optimal mode under varying market conditions and proposes targeted coordination strategies to promote the high-quality development and economic sustainability of the agri-food supply chain. Full article

The rapid development of China’s high-speed railways (HSRs) and the implementation of revenue management policies have promoted the marketization of railway passenger transport, which is mainly reflected in the gradual transformation from a seller’s market dominated by operating companies to a buyer’s market dominated by passenger demand. Passenger travel needs are becoming increasingly diverse. In order to improve the quality of HSR services and attract more passengers, this paper starts from passenger satisfaction and considers the heterogeneity of travel preferences of passengers with different travel distances. Based on the passenger travel data of the Nanning-Guangzhou (NG) HSR line, the K-means clustering method is used to classify passengers into three categories: short-distance, medium-distance, and long-distance travel. A structural equation modeling–multinomial logit (SEM-MNL) model integrating both explicit and latent variables was constructed to analyze passenger travel origin-destination (OD) choices. Stata software was used to estimate passenger preferences for perceived satisfaction functions across different travel distances. Finally, considering constraints such as load factor, departure capacity, and spatiotemporal passenger flow demand, a line planning optimization model was constructed with the goal of minimizing train operating costs and maximizing passenger travel satisfaction. An improved subtraction optimizer algorithm was designed for the solution. Using the NG Line as a case study, the proposed method achieved a reduction in train operating costs while enhancing overall passenger satisfaction. Full article

In this paper, low-pass corrugated filters based on half-mode groove gap waveguide (HMGGW) technology are proposed for the first time. The design process starts from the equivalent classical low-pass implementation in corrugated rectangular waveguide. Then, the final response is achieved after a slight re-optimization of groove widths and lengths. As a proof of concept, two corrugated low-pass filters with upper cutoff frequencies at 27 and 29.5 GHz, and maximum attenuation rejection at 34.5 and 39 GHz, respectively, have been designed and manufactured. In spite of the frequency range of operation, the return losses are better than 19.5 dB for both tuning-less filter prototypes, while measured insertion losses are lower than 0.25 dB and 0.3 dB, respectively, in almost the entire passband. The very good agreement between simulations and measurements fully validates the use of this new emerging technology for the implementation of low-pass filters at high frequency bands. Full article

The pervasive misuse of Duty-Free Quota Abuse Smuggling has seriously undermined fiscal and market order. This study breaks through the traditional model’s assumption of complete rationality and establishes a Multi-Phase Dynamic Decision-Making Model for Duty-Free Quota Abuse Smuggling Chain System, incorporating the risk avoidance preference of illegal actors to analyze strategic interactions within the smuggling chain system. Through theoretical deduction and simulation experiments, the evolution of the system during the decision-making phases of Decentralized Profit-Seeking, Localized Collusive, and Collaborative Profit-Seeking was analyzed, and key intervention points were identified. The study results indicate that smuggling chains will continuously gravitate toward localized collusive; the risk avoidance of illegal actors suppresses local alliance benefits and shortens accumulation cycles; strengthening cost constraints reduces the overall level of smuggling in the system, with Quota Sellers being the most sensitive. Therefore, we propose hierarchical regulation, credit supervision, and differentiated law enforcement to precisely target smuggling chains. Full article

This paper applies quantum game theory to three ethical dilemmas that frequently arise in negotiation: cooperation versus competition, self-interest versus equity, and honesty versus deception. Using quantum extensions of selected games such as the Prisoner’s Dilemma, the Ultimatum Game, the Battle of the Sexes, and the Buyer–Seller Game, we examine whether quantization can generate equilibria that improve classical outcomes while also aligning more closely with ethical principles such as fairness, cooperation, and honesty. The analysis shows that quantum strategies, through entanglement and superposition, can sustain cooperative, fair, or honest behaviour as stable equilibria, outcomes that are typically unstable or unattainable in classical settings. The specific outcomes depend on the chosen quantization method, but across cases, the analysis consistently shows that quantum formulations expand the range of solutions in which efficiency and ethical principles co-exist. Full article

The App Store introduced a title-length limit for mobile apps in 2016, and similar policies were later adopted across the industry. This issue drew considerable attention from industry practitioners in the 2010s. Using both empirical and theoretical approaches, this paper examines the effectiveness of this policy and its welfare implications. Title length became an issue because some sellers assemble meaningful keywords in the app title to convey information to consumers, while others combine irrelevant yet popular keywords in an attempt to increase their app’s downloads. We hypothesize that when titles are short, title length is positively associated with an app’s performance because both honest and opportunistic sellers coexist in the market. However, due to the presence of opportunistic sellers, once titles become too long, this positive relationship disappears. We examine this hypothesis using a random sample of 1998 apps from the App Store in 2015. Our results show that for apps with titles longer than 30 characters, title length remains positively associated with app performance. However, for titles exceeding 50 characters, we do not have sufficient evidence to conclude that further increases in length continue to generate additional downloads. To interpret our empirical findings, we construct communication games between an app seller and a consumer, in which the equilibrium is characterized by a threshold. Based on our model and empirical observations, the 30-character limit might hurt consumers. Full article

This study explores the core competencies required for sales and marketing roles in the rapidly evolving NEV sector. Adopting an exploratory sequential mixed-methods design, it employs a big data-driven approach to construct a competency framework: web crawlers collected NEV-related recruitment data across over 20 major Chinese cities, the Latent Dirichlet Allocation (LDA) model identified core competency items, and a multi-dimensional consensus scoring process via the Nominal Group Technique (NGT) refined the framework. The resulting validated model comprises nine thematic clusters, reflecting a shift from internal combustion engine (ICE) vehicle sales’ traditional skill set. Beyond enriching conventional competencies (customer reception, sales service, CRM, sales support), it highlights emerging capabilities: live-streaming/short-video marketing, digital media operations, and ecosystem-oriented resource collaboration. Further, NGT-based multi-dimensional evaluations (frequency, importance, difficulty) generated a four-quadrant matrix, offering actionable guidance for vocational education and corporate training (VET) curriculum design. Theoretically, this study redefines digital-era automotive sales roles: not mere product sellers, but core actors in user experience co-creation and ecological value integration, which enriches discourse on sales role evolution. Full article

In the current digital competition environment, e-commerce platforms have increased their investment in targeted advertising, improving advertising efficiency while also influencing the choice of product sales modes. This study aims to deeply explore the investment made by platforms in targeted technology and the impact of the choice of sales modes under the asymmetry of power structures. Based on game theory and optimization theory, we develop a decision-making model for targeted technology investments and sales mode selection. Through equilibrium analysis and numerical simulation, the results show that (1) targeted advertising leads to price increases, a reduction in advertising investment, and a decline in demand. Additionally, targeted advertising boosts the seller’s profit while negatively affecting the profit of the other party. (2) When in platform-led sales mode, if the unit advertising cost is low, the platform favors the resale mode; otherwise, it opts for the agency mode. When in manufacturer-led sales mode, regardless of the advertising mode, if the unit advertising cost is low, the manufacturer prefers the agency mode; otherwise, it selects the resale mode. (3) Under different power structures, the conditions and scope for platform-targeted technology investments were provided, and for different advertising models, suggestions were provided for the sales mode selection of the platform and the manufacturer. Full article

This paper tested the use of the surplus efficient frontier (a minimum tracking error portfolio selection method) to select the optimal hedging portfolio that replicates the best Mexican #4 lemon price in a t + 1 and t + 4 week hedging scenario. Using data on the nine most traded agricultural futures in the US from January 2000 to February 2025, we tested hedging effectiveness across 502 futures portfolios in a weekly backtest. The results suggest that a corn and wheat portfolio increases the hedging effectiveness of the lemon price by 0.7033 or 70.33%. A result that, including the impact of trading fees and taxes, leads to a reduction in income risk to a lemon seller in a t + 1 week hedging horizon. The results suggest that a public or private financial institution could take a short position in such a portfolio to provide a hedge at a price that finances the spot/future price difference at minimum cost to Mexican taxpayers. Full article

Intermediaries are central to complex transactions. In housing markets, real estate brokers coordinate information flows, reduce search costs, and guide lay buyers and sellers through legal and financial steps. Despite this importance, scholarship on brokerage is dispersed across disciplines and methods. This paper presents a semi-systematic review of peer-reviewed articles published between 1970 and 2021. We map (i) study characteristics (country of origin and field), (ii) the distribution of units of analysis (individual, firm/organization, market), and (iii) the most frequently examined topics. Our synthesis indicates steadily rising academic interest but a fragmented knowledge base. We conclude by highlighting gaps—especially the scarcity of cross-country comparisons and the relative lack of qualitative and mixed-method studies on brokers’ practices and experiences. Full article

Background: The use of pesticides among smallholder farmers, agrochemical sellers, and agricultural officers involves a complex interplay of knowledge, economic factors, and regulatory frameworks. Therefore, this study explores the patterns, practices, and socio-environmental dynamics of pesticide use among smallholder farmers and agro-input sellers in Iringa and Njombe. Method: This study employed a qualitative, phenomenological design, guided by the socio-ecological model (SEM), to explore the lived experience of farmers, agro-dealers, and extension officers. It involved a total of 23 interviews performed in the Njombe and Iringa regions. Data were collected between October 2024 and March 2025, using a combination of in-depth phenomenological interviews, key informant interviews, and field observations, and were categorized into themes and subthemes analyzed using InVivo. Results: The study involved a total of 23 participants drawn from the Iringa and Njombe regions. The gender distribution was nearly balanced, with 52.1% male and 47.8% female respondents. The mean age of participants was 33 years (95% CI: 29.3–37.3). In terms of education, over half (52.17%) had completed primary school. The findings show that smallholders in Iringa and Njombe widely use mixed pesticides and fertilizers, rely on trusted brands, and adapt to climate impacts, but face challenges with regard to unsafe mixing, poor storage, fake products, and weak regulation, highlighting the need for better education, market oversight, and safer practices. Conclusion: Using the socio-ecological model, the findings indicate that pesticide use among smallholder horticultural farmers in Iringa and Njombe is influenced by a complex interaction of socio-economic constraints, market forces, climate variability, and institutional shortcomings. Although farmers have some awareness of safe practices, systemic barriers continue to limit the adoption of sustainable pesticide management. Full article

Cross-border e-commerce (CBEC) involves online transactions between sellers and consumers across national borders. Despite increasing volatility in international trade, the CBEC market continues to grow, making it critical to understand how firms manage logistics uncertainty. This study investigates how internal and external uncertainties differently influence logistics service flexibility (LSF) and logistics information system (LIS) utilization. Using survey data from 214 CBEC professionals primarily located in Korea, structural equation modeling (SEM) reveals divergent patterns: (1) external uncertainties enhance logistics flexibility, whereas internal uncertainties show no significant direct effect; (2) internal uncertainties negatively affect LIS utilization, while external uncertainties show a marginally positive relationship; and (3) LIS utilization mediates the negative pathway from internal uncertainty to flexibility. These findings indicate that firms respond asymmetrically to uncertainty sources, challenging the view that uncertainty universally promotes digital adaptation. Framing LSF (reconfiguration) and LIS use (sensing/seizing) as distinct dynamic capabilities, our results show source-contingent activation: external turbulence catalyzes reconfiguration, whereas internal frictions dampen sensing/seizing, indirectly suppressing flexibility. By identifying an indirect-only (negative) pathway from internal uncertainty via LIS, we refine dynamic capability theory in CBEC logistics and delineate boundary conditions under which uncertainty does not automatically induce digital adaptation. Full article