Hasil untuk "Marketing. Distribution of products"

Ruixing Ren, Junhui Zhao, Xiaoke Sun et al.

Vehicular Ad-hoc Networks (VANETs) serve as a critical enabler for intelligent transportation systems. However, their practical deployment faces a core governance dilemma: the network topology requires a dynamic trade-off between robustness against targeted attacks and ensuring low-latency information transmission. Most existing models generate fixed degree distributions, lacking the ability to adapt autonomously to the demands of diverse traffic scenarios. To address this challenge, this paper innovatively proposes a schedulable degree distribution model for localized VANETs. The core of this model lies in introducing a hybrid connection mechanism. When establishing connections, newly joining nodes do not follow a single rule but instead collaboratively perform random attachment and preferential attachment. Through theoretical derivation and simulation validation, this study demonstrates that by adjusting the cooperative weighting between these two mechanisms, the overall network degree distribution can achieve a continuous and controllable transition between a uniform distribution and a power-law distribution. The former effectively disperses attack risks and enhances robustness, while the latter facilitates the formation of hub nodes, shortening transmission paths to reduce latency. Experimental results based on the real-world road network of Beijing indicate that this model can precisely regulate node connection heterogeneity, attack resistance, and average transmission path length through the reshaping of the underlying topology. This provides a forward-looking and practical governance paradigm for constructing next-generation VANETs capable of dynamically adapting to complex environments.

Arkadiusz Kawa, Davor Dujak

Biomass wood plays a key role in renewable energy production. Using biomass for energy production reduces dependence on fossil fuels such as coal and oil, which are major sources of carbon dioxide emissions into the atmosphere. However, there are many challenges associated with biomass wood. One of them is logistics, especially storage and transportation requirements. Companies are investing in optimizing logistics processes to reduce operating costs and minimize environmental impact. The aim of this study is to develop and test the operationalization of logistics process requirements and the adaptation of logistics, and to empirically verify the impact of them on the performance of wood biomass companies. A survey of 300 wood biomass company respondents and structural equation modelling were conducted for the purpose of the article. Our research confirms a positive significant impact of logistics requirements enhanced by logistics adjustments on the firm’s performance in wood biomass supply chain.This study fills a gap in biomass logistics research by providing the first empirical model that tests how firms adapt their logistics to meet supply chain challenges. By focusing on firm performance, this work offers novel managerial insights into the strategic role of logistics adjustments within sustainable wood biomass supply chains.Our results highlight the importance of adopting logistics practices to improve efficiency and provide valuable information to help managers and policymakers develop low-emission supply chain strategies.

Akinori Ono

Haoyang Gui, Thales Bertaglia, Catalina Goanta et al.

Influencer marketing has become a crucial feature of digital marketing strategies. Despite its rapid growth and algorithmic relevance, the field of computational studies in influencer marketing remains fragmented, especially with limited systematic reviews covering the computational methodologies employed. This makes overarching scientific measurements in the influencer economy very scarce, to the detriment of interested stakeholders outside of platforms themselves, such as regulators, but also researchers from other fields. This paper aims to provide an overview of the state of the art of computational studies in influencer marketing by conducting a systematic literature review (SLR) based on the PRISMA model. The paper analyses 69 studies to identify key research themes, methodologies, and future directions in this research field. The review identifies four major research themes: Influencer identification and characterisation, Advertising strategies and engagement, Sponsored content analysis and discovery, and Fairness. Methodologically, the studies are categorised into machine learning-based techniques (e.g., classification, clustering) and non-machine-learning-based techniques (e.g., statistical analysis, network analysis). Key findings reveal a strong focus on optimising commercial outcomes, with limited attention to regulatory compliance and ethical considerations. The review highlights the need for more nuanced computational research that incorporates contextual factors such as language, platform, and industry type, as well as improved model explainability and dataset reproducibility. The paper concludes by proposing a multidisciplinary research agenda that emphasises the need for further links to regulation and compliance technology, finer granularity in analysis, and the development of standardised datasets.

Grant Johnson, Ammar Hakim, James Juno

Kinetic simulations of relativistic gases and plasmas are critical for understanding diverse astrophysical and terrestrial systems, but the accurate construction of the relativistic Maxwellian, the Maxwell-Jüttner (MJ) distribution, on a discrete simulation grid is challenging. Difficulties arise from the finite velocity bounds of the domain, which may not capture the entire distribution function, as well as errors introduced by projecting the function onto a discrete grid. Here we present a novel scheme for iteratively correcting the moments of the projected distribution applicable to all grid-based discretizations of the relativistic kinetic equation. In addition, we describe how to compute the needed nonlinear quantities, such as Lorentz boost factors, in a discontinuous Galerkin (DG) scheme through a combination of numerical quadrature and weak operations. The resulting method accurately captures the distribution function and ensures that the moments match the desired values to machine precision.

Julien Siems, Timur Carstensen, Arber Zela et al.

Linear Recurrent Neural Networks (linear RNNs) have emerged as competitive alternatives to Transformers for sequence modeling, offering efficient training and linear-time inference. However, existing architectures face a fundamental trade-off between expressivity and efficiency, dictated by the structure of their state-transition matrices. Diagonal matrices, used in models such as Mamba, GLA, or mLSTM, yield fast runtime but have limited expressivity. To address this, recent architectures such as DeltaNet and RWKV-7 adopted a diagonal plus rank--1 structure, which allows simultaneous token and channel mixing, improving associative recall and, as recently shown, state-tracking when allowing state-transition matrices to have negative eigenvalues. Building on the interpretation of DeltaNet's recurrence as performing one step of online gradient descent per token on an associative recall loss, we introduce DeltaProduct, which instead takes multiple ($n_h$) steps per token. This naturally leads to diagonal plus rank--$n_h$ state-transition matrices, formed as products of $n_h$ generalized Householder transformations, providing a tunable mechanism to balance expressivity and efficiency. We provide a detailed theoretical characterization of the state-tracking capability of DeltaProduct in finite precision, showing how it improves by increasing $n_h$. Our extensive experiments demonstrate that DeltaProduct outperforms DeltaNet in both state-tracking and language modeling, while also showing significantly improved length extrapolation capabilities.

Raha Aghaei, Ali A. Kiaei, Mahnaz Boush et al.

Large Language Models (LLMs) have revolutionized the process of customer engagement, campaign optimization, and content generation, in marketing management. In this paper, we explore the transformative potential of LLMs along with the current applications, future directions, and strategic recommendations for marketers. In particular, we focus on LLMs major business drivers such as personalization, real-time-interactive customer insights, and content automation, and how they enable customers and business outcomes. For instance, the ethical aspects of AI with respect to data privacy, transparency, and mitigation of bias are also covered, with the goal of promoting responsible use of the technology through best practices and the use of new technologies businesses can tap into the LLM potential, which help growth and stay one step ahead in the turmoil of digital marketing. This article is designed to give marketers the necessary guidance by using best industry practices to integrate these powerful LLMs into their marketing strategy and innovation without compromising on the ethos of their brand.

This article examines consumer behaviour’s impact on marketing campaigns' effectiveness using a recommender system and statistical analysis methods. Understanding consumer behaviour is essential in today's fiercely competitive and constantly evolving market. Our study aims to highlight the significant impact of consumer behaviour on marketing data through the innovative application of recommender systems supported by state-of-the-art machine learning and data analysis techniques. This approach addresses the formidable challenges of accurately predicting consumer behaviour. We provide a detailed introduction to recommendation systems, emphasizing their vital role in the modern marketing landscape. We then outline our theories, laying the groundwork for a deeper understanding of the relationship between marketing data and consumer behaviour. Additionally, we present a rigorous data analysis process that begins with data cleaning and progresses through univariate and bivariate analysis, culminating in advanced techniques such as the Apriori algorithm to discover association rules and thoroughly explore this symbiotic relationship. Our findings demonstrate the applicability and effectiveness of our methodology for interpreting the complex interplay between consumer behaviour and marketing data. Our conclusions highlight essential trends and offer practical recommendations for enhancing marketing strategies significantly. By elucidating the dynamic relationships between consumer behaviour and marketing outcomes, our study contributes to a more sophisticated understanding of consumer dynamics in the contemporary business environment. Furthermore, this paper underscores the importance of understanding consumer behaviour and the benefits of employing innovative data analysis methods. By decoding consumption trends, businesses can optimize their marketing strategies and improve customer satisfaction, strengthening their competitive edge in a constantly shifting market. Finally, incorporating recommender systems with artificial intelligence and machine learning tools for collaborative filtering can further refine these strategies, substantially boosting marketing efficacy.

Sungjoo Chung, Ying Zhang, Zhaoyu Wang et al.

Traditional power flow methods often adopt certain assumptions designed for passive balanced distribution systems, thus lacking practicality for unbalanced operation. Moreover, their computation accuracy and efficiency are heavily subject to unknown errors and bad data in measurements or prediction data of distributed energy resources (DERs). To address these issues, this paper proposes a hybrid data-aided robust power flow algorithm in unbalanced distribution systems, which combines Taylor series expansion knowledge with a data-driven regression technique. The proposed method initiates a linearization power flow model to derive an explicitly analytical solution by modified Taylor expansion. To mitigate the approximation loss that surges due to the DER integration and bad data, we further develop a data-aided robust support vector regression approach to estimate the errors efficiently. Comparative analysis in the 13-bus and 123-bus IEEE unbalanced feeders shows that the proposed algorithm achieves superior computational efficiency, with guaranteed accuracy and robustness against outliers.

Khadija Khatun, Chen Shen, Jun Tanimoto et al.

Understanding how cooperation emerges in public goods games is crucial for addressing societal challenges. While optional participation can establish cooperation without identifying cooperators, it relies on specific assumptions -- that individuals abstain and receive a non-negative payoff, or that non-participants cause damage to public goods -- which limits our understanding of its broader role. We generalize this mechanism by considering non-participants' payoffs and their potential direct influence on public goods, allowing us to examine how various strategic motives for non-participation affect cooperation. Using replicator dynamics, we find that cooperation thrives only when non-participants are motivated by individualistic or prosocial values, with individualistic motivations yielding optimal cooperation. These findings are robust to mutation, which slightly enlarges the region where cooperation can be maintained through cyclic dominance among strategies. Our results suggest that while optional participation can benefit cooperation, its effectiveness is limited and highlights the limitations of bottom-up schemes in supporting public goods.

Youcef Abdellaoui

This research paper aims at taking knowledge of the role of the university incubators in framing and accompaying competencies in order to create startups furthermore,to shade light on services offered for the incubated students through m'sila incubators,in its capacity as the most dynamic incubator at the national level ,some of the most important of its activites and the different patents and label certaficates have been highlighted . Among the most important results of the studies, the experience of the m'sila incubator was obviously very successful, the fact that its director was nomineted at the top of the national coordination commitee to follow UP inovation and university incubators where this commitee was founded in sptember 27th, 2022and which ensures the implentation of the ministeriel decesion12/75.

Ari Nissinen, Jyri Seppälä, Tero Heinonen

The carbon footprint (CF) should finally have a role in the decision-making of manufacturing companies, retailers, public procurers and consumers. We consider that more systematic approaches are urgently needed for collecting, storing and presenting carbon footprint information. The key issue from the standpoint of reliability and comparability is to recognise how each CF was determined and how it has been verified. Global Trade Item Number (GTIN) and the connected barcode symbol can be used to identify products. We propose that the presented framework can help to build databases which are easy to use for the manufacturers, retailers and various service providers and which can increase the production and usability of CF information.

Rosa Virginia Kartikarini, Carolina Dindy Dwi Miranti, Rini Budi Setyowati et al.

Tujuan dari kegiatan ini adalah memberikan produk pedoman membuat bahan mengajar online sebagai upaya untuk membantu pembuatan bahan ajar yang menarik bagi siswa/i ABK. Sasaran partisipan adalah guru SLB yang menangani anak berkebutuhan khusus (ABK) dengan berbagai diagnosis dan kondisi. Partisipan menghadapi kendala yang cukup berarti dalam menjalankan kegiatan belajar mengajar melalui platform online sejak tanggal 15 Maret 2020 sebagai akibat kebijakan penerapan Pembatasan Sosial Berskala Besar (PSBB) karena merebaknya pandemi COVID-19. Berdasarkan hasil asesmen menggunakan metode analisis SWOT (strengths, weaknesses, opportunities, dan threats) didapatkan hasil bahwa guru merasa belum memiliki keterampilan menggunakan software yang dapat dimanfaatkan untuk pembuatan produk belajar. Untuk membantu para guru dalam menyampaikan materi pembelajaran, penting untuk membuat panduan tentang penggunaan software Microsoft PowerPoint. Alat bantu berupa Panduan Membuat Karakter dan Video Animasi Sederhana Menggunakan Microsoft PowerPoint telah membantu para guru untuk lebih siap dan meningkat pengetahuannya dalam membuat materi ajar secara online.

Sebastian Krahmer, Stefan Ecklebe, Peter Schegner et al.

As the amount of volatile, renewable energy sources in power distribution grids is increasing, the stability of the latter is a vital aspect for grid operators. Within the STABEEL project, the authors develop rules on how to parametrize the reactive power control of distributed energy resources to increase the performance while guaranteeing stability. The work focuses on distribution grids with a high penetration of distributed energy resources equipped with Q(U)-characteristic. This contribution is based on the stability assessment of previous work and introduces a new approach utilizing the circle criterion. With the aim of extending existing technical guidelines, stability assessment methods are applied to various distribution grids - including those from the SimBench project. Herein, distributed energy resources can be modelled as detailed control loops or as approximations, derived from technical guidelines.

Ricardo Lopez-Dawn, Anastasios Giovanidis

Influencer marketing has become a thriving industry with a global market value expected to reach 15 billion dollars by 2022. The advertising problem that such agencies face is the following: given a monetary budget find a set of appropriate influencers that can create and publish posts of various types (e.g. text, image, video) for the promotion of a target product. The campaign's objective is to maximize across one or multiple online social platforms some impact metric of interest, e.g. number of impressions, sales (ROI), or audience reach. In this work, we present an original continuous formulation of the budgeted influencer marketing problem as a convex program. We further propose an efficient iterative algorithm based on the Frank-Wolfe method, that converges to the global optimum and has low computational complexity. We also suggest a simpler near-optimal rule of thumb, which can perform well in many practical scenarios. We test our algorithm and the heuristic against several alternatives from the optimization literature as well as standard seed selection methods and validate the superior performance of Frank-Wolfe in execution time and memory, as well as its capability to scale well for problems with very large number (millions) of social users.

M. I. A. Jalil, Suddin Lada, M. Bakri et al.

This research aims to study the effects of social media marketing strategies on the repurchase intention among suppliers of halal cosmetics in the context of Malaysia. The study, based on the theory of social media marketing, identifies these ties, and considers the mediating functions of word-of-mouth brand recognition and electronic word-of-mouth communication (e-WOM). The work takes a holistic view of brand recognition and e-WOM with reference to the two main relations, social media marketing strategy and repurchasing intention. The partial least squares structural equation modelling (PLS-SEM) method was employed and data collected from 300 respondents (followers) via an online questionnaire. The results indicate that there is a significant influence of social media marketing (SMM) on repurchase intention, brand awareness, and e-WOM; the impact is higher on brand awareness, followed by repurchase intention and eWOM. These results demonstrate that efficient brand management of the use of social media platforms will help increase brand awareness among halal cosmetics buyers. When used correctly, SMM may assist the distribution and communication of the most up-to-date information on cosmetic products and brands, resulting in increased awareness and repurchase intent. At the same time, eWOM is a useful tool for their respective followers to disseminate information. The research has important implications for the halal cosmetics sector, as it contributes to the theoretical and management literature on social media marketing strategy.

Eleonora Di Maria, M. Simoni, Giuseppe Pedeliento et al.

The Covid-19 pandemic has dramatically impacted firms and consumers (Donthu & Gustafsson, 2020). On one hand, firms had the opportunity to establish and manage relationships with key market actors by redefining established business processes of production, distribution, and even product development. On the other one, consumers were forced to temporarily or permanently change their habits and the way they buy, shop, consume, and travel (Sheth, 2020). This new scenario, sparked by the Covid-19 pandemic, caused important implications for firms. In fact, it required them to rapidly reorganize their processes and activities to continue running their businesses (Seetharaman, 2020) and prompted new forms of product (Ebersberger & Kuckertz, 2021) and service (Sharma et al., 2021) innovations to keep up with a new demand. Furthermore, it brought profound changes in the way firms manage relationships and communicate with their customers (Mangiò et al., 2021), and, above all, led to severe changes in consumers’ behaviours (Zwanka & Buff, 2021). Yet, while Covid-19 is undoubtedly one of the most traumatic events humanities have faced since the end of World War II, it also determined the emergence of novel social, economic, and business challenges that attracted the attention and interest of many marketing scholars. An attention that, we note, did not run out once the hardest times of the pandemic had been overcome but, on the contrary, one which is still

Francisco Cortezzi

Originating from the palm Euterpe oleracea, the açaí is an endemic fruit of the Amazon rainforest, the consumption of which has grown strongly in Brazil since the 1990s and is emerging in other regions of the world. Consumed mainly in the form of pulp and erected as a "superfruit" by marketing players for its antioxidant and nutritional potential, the açaí berry goes through a dynamic process encompassing both its space production and international distribution circuit as well as its composition derivative products. With more than 85% of its territory inserted in the Amazon rainforest, French Guiana has all the environmental requirements necessary for the development and production of açaí berries. Currently in this territory, the highest concentration of extractive production of Euterpe oleracea is found in the region of Lower Oyapock, on the border with Brazil. Despite the little government interest behind the fruit, a little over six years ago, agricultural producers in the metropolitan region of Cayenne have closely analyzed the dynamics and consumption of açaí by-products in Europe and on d 'other continents. From the favorable results of the international market analysis, these farmers created the company Yana Wassaï whose main objective is to develop the local production process targeting the foreign market. One of the objectives of this group is to transform the açaí berry into a “European” product. With a large part of the project already underway, the group plans to increase the cultivated area by around 300 hectares in the next three years to reach a total of more than 1,000 hectares of crops in the next eight years. During our stay in French Guiana, it was possible to discuss more closely with the main actors of this project, in addition to visiting and knowing the first irrigated plantations of the palm Euterpe oleracea belonging to the group.

Maja Konecnik Ruzzier, Katja Terglav, Robert Kaše

Purpose – This paper highlights the importance of employees and the internal branding process in building and sustaining powerful brands. Specifically, we explore the impact of internal brand communication on employee brand commitment. By including employee brand knowledge and employee-brand fit as mediators, organizations develop a more comprehensive understanding of how to enhance the affective brand commitment of their employees. Design/Methodology/Approach – A total of 226 employees of an international hotel chain participated in the study. Employee data were collected with a questionnaire and analyzed by applying structural equation modeling. Findings and implications – The results imply that what matters is not only the direct influence on employee commitment. Rather, by continuously enriching employee cognition and enhancing employee brand value congruence, organizations can achieve higher levels of affective brand commitment and, in turn, better customer service. The paper provides several practical implications for managers regarding how to manage communication and other internal branding efforts in their organizations, thus empowering employees and transforming them into brand champions. Limitations – Data on internal brand communication could also be collected from top management and direct supervisors to complement employee perspectives on internal branding. Originality/value – The inclusion of internal brand communication and employee brand knowledge in the internal branding process has led to more comprehensive understanding of how to enhance affective brand commitment of employees.

Julia Ganner, Lukas Kerschbaumer, Christina Tanzer

Purpose: The insurmountable tensions and turmoil caused by the COVID-19 pandemic in welfare systems worldwide demand governmental as well as non-governmental support, especially from the volunteer sector, which can be a powerful resource for mitigating the pandemic’s impacts. To identify ways of mobilising the enormous human resources of the baby boomer generation in particular, whose members are currently on the brink of entering retirement, the factors that have enabled and restricted volunteer management during the pandemic in Tyrol, Austria are examined. Design/method/approach: Following a qualitative approach, the authors performed 27 problem-centred interviews with representative senior citizens, retirees and individuals about to retire and companies in Tyrol. The authors evaluated the data in qualitative content analysis. Findings: Self-determination, time flexibility, acceptance of volunteer work in one’s social network and previous personal experience with volunteering are key determinants of sustainable volunteer work amongst retirees. Companies and a well-established acquisition management strategy also play a significant role in promoting volunteer work. Practical implications and originality/value: The study involves a holistic analysis of volunteer work at the individual and organisational levels. By capturing the potential of e-volunteering and how it improves the capacities of classic face-to-face volunteer work, it can support the development of more resilient infrastructures for supporting volunteer work. Research limitations/future research: The interpretation of visual and non-verbal signals was difficult due to the use of phone and online interviews, and the results should not be generalised. Even so, our findings pave the way for future studies on mechanisms determining virtual volunteering and volunteer management. Paper type: Empirical