Hasil untuk "Marketing. Distribution of products"

P. Kotler, Nancy R. Lee

Yeon-Koo Che

Classic market design theory is rooted in static models where all participants trade simultaneously. In contrast, modern platform-mediated digital markets are fundamentally dynamic, defined by the asynchronous and stochastic arrival of supply and demand. This chapter surveys recent work that brings market design to this dynamic setting. We focus on a methodological framework that transforms complex dynamic problems into tractable static programs by analyzing the long-run stationary distribution of the system. The survey explores how priority rules and information policy can be designed to clear markets and screen agents when monetary transfers are unavailable, and, when they are available, how queues of participants and goods can be managed to balance intertemporal mismatches of demand and supply and to spread competitive pressures across time.

Socrates Deza-De-Souza-Ferreyra, Maria Jeanett Ramos-Cavero, Franklin Cordova-Buiza

This study examined the relationship between organic positioning strategies and the behavior of digital consumers in real estate companies in Peru, a topic of growing importance given the expanding role of digital marketing in the real estate sector. The primary objective was to determine the effectiveness of SEO strategies in influencing consumer behavior. A quantitative methodology was adopted, employing a non-experimental, cross-sectional, and correlational design. 100 real estate SEO experts in Peru, who were recruited from LinkedIn, were surveyed. Data were collected through surveys, and the analysis was conducted using the SPSS statistical software. The findings revealed that brand awareness, keyword analysis, and marketing strategy are pivotal components in the development of successful SEO approaches. Simultaneously, factors such as brand awareness, marketing performance, and brand interaction emerged as critical influencers of digital consumer behavior. The statistical analysis yielded a Pearson correlation coefficient of 0.707, indicating a strong positive relationship between organic positioning strategies and digital consumer behavior. These results underscore the practical value of implementing effective SEO strategies in enhancing consumer engagement and behavior in the digital space. In conclusion, the study demonstrates that well-executed organic positioning strategies can significantly improve digital consumer behavior, offering valuable insights for real estate companies seeking to optimize their digital marketing efforts. This highlights the importance of incorporating targeted SEO techniques to strengthen brand presence and drive consumer engagement in an increasingly competitive market.

Omar El Housni, Qing Feng, Huseyin Topaloglu

Assortment optimization is a critical tool for online retailers aiming to maximize revenue. However, optimizing purely for revenue can lead to unbalanced sales across products, potentially causing a long tail of low-selling products and products with excessively large market shares, both of which could be harmful to the seller. To address these issues, we introduce a market share balancing constraint that limits the disparity in expected sales between any two offered products to a factor of a given parameter $α$. We study both static and dynamic assortment optimization under the multinomial logit (MNL) model with this fairness constraint. In the static setting, the seller selects a distribution over assortments that satisfies the market share balancing constraint while maximizing expected revenue. We show that this problem can be solved in polynomial time, and we characterize the structure of the optimal solution: a product is included if and only if its revenue and preference weight exceed certain thresholds. We further extend our analysis to settings with additional feasibility constraints on the assortment and demonstrate that, given a $β$-approximation oracle for the constrained problem, we can construct a $β$-approximation algorithm under the fairness constraint. In the dynamic setting, each product has a finite initial inventory, and the seller implements a dynamic policy to maximize total expected revenue while respecting both inventory limits and the market share balancing constraint in expectation. We design a policy that is asymptotically optimal, with its approximation ratio converging to one as inventories grow large.

Liudmyla Potrashkova, Viktor Zaruba, Diana Raiko et al.

To justify the production of green products, it is necessary to anticipate the choice of consumers toward products with different environmental friendliness. Therefore, it is necessary to understand the factors that determine this choice, particularly value factors. The study is based on the idea that a consumer is stimulated to eco-consumption by a set of values, not excluding individualist values; and the influence of values is mediated by motives. The purpose of the study is to develop the theoretical foundations of constructing a three-level system of value factors of green consumption on the example of office paper consumption. As a result, the study formed a system of factors containing preferences, motives, and values of office paper consumers. According to the proposed approach, for each respondent, quantitative characteristics of the elements of the system of factors were determined through a survey, which made it possible to identify correlation relationships between the elements. A pilot study was used to test the proposed approach to constructing a value factors system. The results of the pilot survey showed a positive connection between eco-friendliness of consumer preferences – through motives – with such values as “Nature,” “Self-development,” “Country success,” and “Social power.” This finding provides additional justification for the assumption that individuals are driven to green consumption not only by socially oriented values but also by individualistic values. Identifying the value factors of green consumption will allow predicting consumer behavior and influencing it through targeted marketing offers.

Hong Sun, Biyu Liu, Peng Jiang et al.

The increase in e-commerce and online shopping has resulted in a significant amount of packaging waste from express delivery, posing a considerable burden on the environment. To address this issue, reusable express packaging has emerged as one of potential solutions to reduce packaging waste in express delivery. This study analyzes the evolutionary stability strategy of local governments and express delivery enterprises by constructing an evolutionary game model. The model considers the limited rationality and group behavior of decision makers, as well as the economies of scale and diseconomies of scale in operating cost of reusable express packaging. Results indicate that the variability in the cost of reusable express packaging may lead to the simultaneous emergence of two evolutionary stability strategies, contrasting traditional evolutionary game studies. Due to the present low uptake of reusable express packaging among express companies, coupled with the lack of subsidies support from local governments, it is difficult to attain the optimal situation in which businesses actively utilize reusable express packaging. To accomplish this objective, it is crucial to establish subsidy amounts that are balanced and reasonable, rather than merely elevating them to the highest possible levels. The study proposes an optimal range for government subsidy levels and gives corresponding policy suggestions.

Riyan Sisiawan Putra, Tri Siwi Agustina

The outbreak of the COVID-19 pandemic in all corners of the world has made all activities from various sectors difficult and even experience complete paralysis. As a result of the COVID-19 pandemic, a crisis emerged in various organizations engaged in the medical and non-medical fields. With the crisis due to the COVID-19 pandemic, a transformational leadership role is needed as a form to overcome feelings of worry, fear, and anxiety that arise in healthcare workers. The purpose of this review is to examine the resilience of healthcare workers amid the outbreak of the COVID-19 pandemic. Through well-established adopted questionnaires, data were collected from healthcare workers (N=134) treating COVID-19 patients in the Islamic Hospital in Surabaya, Indonesia. This type of research uses a quantitative approach, a sampling method with census technicalities, and the Partial Least Square (PLS) analysis method. The results showed that transformational Leadership had a positive effect on health workers. Then, there was no significant influence of transformational Leadership on negative effects on health workers. At the same time, from positive effects, it was found to have a significant influence on the resilience of health workers of Islamic Hospital during the COVID-19 crisis.

Ludovit Nastisin, Richard Fedorko, Beata Gavurova et al.

Delving into the intricate world of social media engagement, this comprehensive study analyses the dynamics of user interaction with posts from 5-star hotels on Facebook across the Visegrad Group countries. It meticulously aims to shed light on the variances among engagement metrics—shares, comments, and reactions—across different types of posted content. Furthermore, it explores the complex interrelations among these metrics to provide a holistic understanding of user engagement patterns. In pursuit of this goal, we scrutinized an extensive dataset comprising 10,820 Facebook posts shared by selected 5-star hotels throughout 2019. The data were meticulously collected from the social network utilizing the accessible API, ensuring a robust and reliable foundation for analysis. The investigation employed advanced statistical tools, namely the Kruskal‒Wallis test and Spearman's rho test, to thoroughly examine and interpret the complex data. The insights gleaned from this research are invaluable, painting a detailed picture of brand management strategies on social platforms. A significant finding of this study is the variation in user engagement levels in relation to the type of content disseminated. It highlights that visual content—specifically videos and photos—tends to dominate in terms of eliciting user responses, as compared to text statuses and links. This underlines the importance of leveraging visual media to captivate and engage the audience effectively. The study also reveals that engagement metrics are intricately linked, suggesting a synergistic effect rather than isolated impacts. This indicates that an integrated approach, considering these metrics as a cohesive unit, could be more beneficial in strategizing content for social media. Understanding these relationships and the dominant role of visual content can greatly inform and transform the way brands, especially in the hospitality industry, navigate their presence on social networks. These findings serve as a guiding framework for optimizing social media content strategies, aiming to maximize engagement and enhance the effectiveness of online brand management.

T.F. Alhassan, Sh. Niyazbekova, T.K. Blokhina

The study considers that the countries of the region are trying to take advantage of the opportunity of the Fourth Industrial Revolution (4IR) to industrialize and diversify their economies due to the rapid spread and widespread use of the Internet in the region. The modified methodology was used to assess the level of innovation potential (hereinafter referred to as IP), using elements such as the level of recep-tivity and readiness for innovative development, potential opportunities and others.Taking into account the role of financial opportunities in the development of innovations, a regres-sion analysis was carried out, which indicates a direct link between IP and investment in R&D in these countries, on the basis of which the potential for innovative development is predicted for 5 years. The article assessed the possibility of financing African startups and SMEs through crowdfunding platforms and venture investments. The results show that the current Internet penetration contributes to the de-velopment of venture capital and crowdfunding, which will increase by 50% and 93%, respectively, by 2025. To achieve these results, the authors have developed a recommendation that can increase the financial capacity of sub-Saharan Africa for their innovation sector.

Sahar Soltanieh, Javad Hashemi, Ali Etemad

This paper presents a systematic investigation into the effectiveness of Self-Supervised Learning (SSL) methods for Electrocardiogram (ECG) arrhythmia detection. We begin by conducting a novel analysis of the data distributions on three popular ECG-based arrhythmia datasets: PTB-XL, Chapman, and Ribeiro. To the best of our knowledge, our study is the first to quantitatively explore and characterize these distributions in the area. We then perform a comprehensive set of experiments using different augmentations and parameters to evaluate the effectiveness of various SSL methods, namely SimCRL, BYOL, and SwAV, for ECG representation learning, where we observe the best performance achieved by SwAV. Furthermore, our analysis shows that SSL methods achieve highly competitive results to those achieved by supervised state-of-the-art methods. To further assess the performance of these methods on both In-Distribution (ID) and Out-of-Distribution (OOD) ECG data, we conduct cross-dataset training and testing experiments. Our comprehensive experiments show almost identical results when comparing ID and OOD schemes, indicating that SSL techniques can learn highly effective representations that generalize well across different OOD datasets. This finding can have major implications for ECG-based arrhythmia detection. Lastly, to further analyze our results, we perform detailed per-disease studies on the performance of the SSL methods on the three datasets.

Zineb Hamdene, Azzeddine Nezai, Noureddine Abdellah

تعتبر الحبوب الغذاء الأساسي للسكان ومحصول إستراتيجي هام، والركيزة الأساسية للأمن الغذائي في الجزائر، وتعتبر ولاية سعيدة رائدة في إنتاج الحبوب، لكن كفاءتها تبقى دون المطلوب. هدفت هذه الدراسة إلى قياس تأثير العوامل التفسيرية المتمثلة في العوامل المناخية ومقدار التمويل وتوفير السكن الريفي على عدم الكفاءة الفنية لإنتاج القمح لبلديات محافظة سعيدة باستخدام منهج التحليل الحدودي العشوائي خلال الفترة 2015/2020. بينت النتائج الدراسة أن تقييم دالة الإنتاج الحدودي حسب طريقه الإمكان الأعظم للتقدير قد تمت وفقا للنموذج العشوائي، وأن مرونة كل من مساحة الأرض المزروعة والأرض المسقية والأرض المسمدة والمكننة قد بلغت (0.62، 0.28، 0.98، 0.5) على التوالي ويشير ذلك الى العلاقة الايجابية بين هذه المدخلات وإنتاج الجبوب، ووجود تأثير عكسي لكمية المبيدات على انتاج الحبوب. كما بينت النتائج أن عدم الكفاءة الفنية كان لها تأثير على تباين إنتاج الحبوب بمقاطعة سعيدة، وأن ظاهرة عدم الكفاءة تبقى مهمة في زراعة الحبوب في مقاطعة سعيدة ويجب إعتمادها في نماذج الإنتاج.

Mohsen Benslim

تهدف هذه الدراسة إلى مناقشة مدى فعالية نموذج KMV في المساعدة على تقييم والتنبؤ بمخاطر التعثر المالي. ولتحقيق هذه الغاية تم تسليط الضوء على النماذج الهيكلية وشروط تحديدها، كما تم التركيز على مختلف الأطر النظرية لنموذج KMV ومنهجية قياسه لمخاطر التعثر المالي، وكذا خطوات تطبيقه. حيث تم دراسة عينة من الشركات المدرجة في سوق أبو ظبي للأوراق المالية. ولتحقيق هدف الدراسة تم الاعتماد على المنهج الوصفي للإلمام بمختلف جوانب البحث. وقد توصلت الدراسة إلى أن نموذج KMV يعد من أهم النماذج المتاحة لتقييم مخاطر التعثر المالي، كما أن سهولة هذا النموذج تمكن المؤسسات والبنوك من توحيد مخاطر الائتمان ومساعدتها على أتخاد التدابير اللازمة والمناسبة في حالة التعثر.

Christian Raniero, Giuseppe Modarelli

This research work opens an interpretative view on corporate social responsibility (CSR) during an unexpected emergency reality and latent environmental collapse as a strategy to survive. The investigation approach follows the lines of a field analysis survey based on 288 consumers before (n=80) and during the spread of Covid-19 (n=208). The study aims to provide paradigms and interpretations of evidence-based CSR as a balanced reciprocity relationship in coping emergencies; this necessarily moved the authors to investigate the relationship transversally, examining the role of budgeting and its repercussions on well-being by hierarchical leadership. Specifically, the authors investigate the existence of possible niches of actions based on cooperative and responsible operations during emergencies.

Johannes Rude Jensen, Mohsen Pourpouneh, Kurt Nielsen et al.

Automated market makers (AMM) have grown to obtain significant market share within the cryptocurrency ecosystem, resulting in a proliferation of new products pursuing exotic strategies for horizontal differentiation. Yet, their theoretical properties are curiously homogeneous when a set of basic assumptions are met. In this paper, we start by presenting a universal approach to deriving a formula for liquidity provisioning for AMMs. Next, we show that the constant function market maker and token swap market maker models are theoretically equivalent when liquidity reserves are uniform. Proceeding with an examination of AMM market microstructure, we show how non-linear price effect translates into slippage for traders and impermanent losses for liquidity providers. We proceed by showing how impermanent losses are a function of both volatility and market depth and discuss the implications of these findings within the context of the literature.

Alexander Barzykin, Philippe Bergault, Olivier Guéant

In dealer markets, dealers provide prices at which they agree to buy and sell the assets and securities they have in their scope. With ever increasing trading volume, this quoting task has to be done algorithmically in most markets such as foreign exchange markets or corporate bond markets. Over the last ten years, many mathematical models have been designed that can be the basis of quoting algorithms in dealer markets. Nevertheless, in most (if not all) models, the dealer is a pure internalizer, setting quotes and waiting for clients. However, on many dealer markets, dealers also have access to an inter-dealer market or even public trading venues where they can hedge part of their inventory. In this paper, we propose a model taking this possibility into account, therefore allowing dealers to externalize part of their risk. The model displays an important feature well known to practitioners that within a certain inventory range the dealer internalizes the flow by appropriately adjusting the quotes and starts externalizing outside of that range. The larger the franchise, the wider is the inventory range suitable for pure internalization. The model is illustrated numerically with realistic parameters for USDCNH spot market.

Xuanying Chen, Zhining Liu, Li Yu et al.

Many payment platforms hold large-scale marketing campaigns, which allocate incentives to encourage users to pay through their applications. To maximize the return on investment, incentive allocations are commonly solved in a two-stage procedure. After training a response estimation model to estimate the users' mobile payment probabilities (MPP), a linear programming process is applied to obtain the optimal incentive allocation. However, the large amount of biased data in the training set, generated by the previous biased allocation policy, causes a biased estimation. This bias deteriorates the performance of the response model and misleads the linear programming process, dramatically degrading the performance of the resulting allocation policy. To overcome this obstacle, we propose a bias correction adversarial network. Our method leverages the small set of unbiased data obtained under a full-randomized allocation policy to train an unbiased model and then uses it to reduce the bias with adversarial learning. Offline and online experimental results demonstrate that our method outperforms state-of-the-art approaches and significantly improves the performance of the resulting allocation policy in a real-world marketing campaign.

Hao Feng, Jaime Llorca, Antonia M. Tulino et al.

Distributed cloud networking builds on network functions virtualization (NFV) and software defined networking (SDN) to enable the deployment of network services in the form of elastic virtual network functions (VNFs) instantiated over general purpose servers at distributed cloud locations. We address the design of fast approximation algorithms for the NFV service distribution problem (NSDP), whose goal is to determine the placement of VNFs, the routing of service flows, and the associated allocation of cloud and network resources that satisfy client demands with minimum cost. We show that in the case of load-proportional costs, the resulting fractional NSDP can be formulated as a multi-commodity-chain flow problem on a cloud augmented graph, and design a queue-length based algorithm, named QNSD, that provides an O(ε) approximation in time O(1/ε). We then address the case in which resource costs are a function of the integer number of allocated resources and design a variation of QNSD that effectively pushes for flow consolidation into a limited number of active resources to minimize overall cloud network cost.

M. Lemasson, L. Wood, Rickard Berzelius et al.

Supply chains describe the network of activities involved in producing and getting a product or service to consumers. This includes design, production, marketing, distribution, and support to the final consumer. The supply chain is a system of organizations, people, activities, information, and resources involved in moving the product from supplier to the end customer. Value chains are “global” when the activities are carried out on a global scale, both within the firm (through FDI) and through contracts with foreign firms (through offshore outsourcing). Global supply chains are also referred to as ‘global value chains’ or ‘global production networks’.

Hafiz Anwar Ullah Khan, Jip Kim, Yury Dvorkin

Power producers can exhibit strategic behavior in electricity markets to maximize their profits. This behavior is more pronounced with the deregulation of distribution markets, which offers an opportunity for profit arbitrage between transmission and distribution (T&D) markets. However, the temporally distinct nature of these two markets introduces a significant risk in profit for such producers. This paper derives its motivation from the perspective of a strategic producer and develops a Single Leader Multi-Follower (SLMF) game for deriving its participation strategies in T&D markets, while accounting for different T&D coordination schemes based on the individual market Gate Closure Times (GCT). We compare and contrast joint and sequential market clearing models with regulated and deregulated distribution environments and evaluate the risk of producer by leveraging consistent and coherent risk measures. SLMF game is reformulated as a Mathematical Program with Equilibrium Constraints (MPEC) and is solved using the seminal Scholtes's relaxation scheme. We validate the efficacy of our model and solution approach via the case study carried out on the 11-zone New York ISO, and 7-bus Manhattan power networks, used as transmission and distribution markets, respectively.

Richard Weinhold, Robert Mieth

The proposed open-source Power Market Tool (POMATO) aims to enable research on interconnected modern and future electricity markets in the context of the physical transmission system and its secure operation. POMATO has been designed to study capacity allocation and congestion management (CACM) policies of European zonal electricity markets, especially flow-based market coupling (FBMC). For this purpose, POMATO implements methods for the analysis of simultaneous zonal market clearing, nodal (N-k secure) power flow computation for capacity allocation, and multi-stage market clearing with adaptive grid representation and redispatch. The computationally demanding N-k secure power flow is enabled via an efficient constraint reduction algorithm. POMATO provides an integrated environment for data read-in, pre- and post-processing and interactive result visualization. Comprehensive data sets of European electricity systems compiled from Open Power System Data and Matpower Cases are part of the distribution. POMATO is implemented in Python and Julia, leveraging Python's easily maintainable data processing and user interaction features and Julia's well readable algebraic modeling language, superior computational performance and interfaces to open-source and commercial solvers.