Hasil untuk "Marketing. Distribution of products"

Víctor Falguera, J. P. Quintero, A. Jiménez et al.

Bethany M. Kwan, R. Brownson, R. Glasgow et al.

Designing for dissemination and sustainability (D4DS) refers to principles and methods for enhancing the fit between a health program, policy, or practice and the context in which it is intended to be adopted. In this article we first summarize the historical context of D4DS and justify the need to shift traditional health research and dissemination practices. We present a diverse literature according to a D4DS organizing schema and describe a variety of dissemination products, design processes and outcomes, and approaches to messaging, packaging, and distribution. D4DS design processes include stakeholder engagement, participatory codesign, and context and situation analysis, and leverage methods and frameworks from dissemination and implementation science, marketing and business, communications and visual arts, and systems science. Finally, we present eight recommendations to adopt a D4DS paradigm, reflecting shifts in ways of thinking, skills and approaches, and infrastructure and systems for training and evaluation.

Varun Jewargi, Veerendrakumar M. Narasalagi, Amith Donald Menezes et al.

Type of the article: Research Article AbstractThe growing competitiveness of India’s FMCG personal care sector has increased the strategic importance of strengthening Consumer-Based Brand Equity (CBBE), particularly in categories with high product similarity and low switching costs. Under-standing the determinants of brand equity is therefore essential for guiding brand differentiation and long-term consumer loyalty. This study aims to identify and examine the determinants of consumer-based brand equity in the FMCG personal care sector using PLS-SEM. Primary data were collected from 1,137 consumers across five major Indian regions between October 2024 and March 2025 using purposive sampling and structured questionnaire. Eight constructs and sixteen hypotheses were tested using Partial Least Squares Structural Equation Modelling. The results show strong and statistically significant effects across all hypothesized paths (p < 0.001). Brand association demonstrated the strongest influence on brand preference (β = 0.400, t = 12.633), while brand awareness had its highest effect on brand trust (β = 0.333, t = 9.912). Perceived quality showed the strongest influence on brand experience (β = 0.261, t = 7.970). The mediating constructs — brand experience, preference, trust, and loyalty — significantly predicted overall brand equity, with brand trust exerting the greatest influence (β = 0.242, t = 6.034). The model demonstrated substantial explanatory power, with R² values ranging from 0.425 to 0.491, and acceptable model fit (SRMR = 0.054; NFI = 0.765). The results establish that cognitive and experiential brand drivers jointly shape CBBE, offering actionable insights for marketers aiming to strengthen loyalty and competitive positioning in the Indian FMCG personal care market.

Ke Yuan, Yaoxin Liu, Shriyesh Chandra et al.

This project focuses on analyzing retail market trends using historical sales data, search trends, and customer reviews. By identifying the patterns and trending products, the analysis provides actionable insights for retailers to optimize inventory management and marketing strategies, ultimately enhancing customer satisfaction and maximizing revenue.

Roy Ravid

Marketing mix modeling (MMM) is a widely used method to assess the effectiveness of marketing campaigns and optimize marketing strategies. Bayesian MMM is an advanced approach that allows for the incorporation of prior information, uncertainty quantification, and probabilistic predictions (1). In this paper, we describe the process of building a Bayesian MMM model for the online insurance company Lemonade. We first collected data on Lemonade's marketing activities, such as online advertising, social media, and brand marketing, as well as performance data. We then used a Bayesian framework to estimate the contribution of each marketing channel on total performance, while accounting for various factors such as seasonality, market trends, and macroeconomic indicators. To validate the model, we compared its predictions with the actual performance data from A/B-testing and sliding window holdout data (2). The results showed that the predicted contribution of each marketing channel is aligned with A/B test performance and is actionable. Furthermore, we conducted several scenario analyses using convex optimization to test the sensitivity of the model to different assumptions and to evaluate the impact of changes in the marketing mix on sales. The insights gained from the model allowed Lemonade to adjust their marketing strategy and allocate their budget more effectively. Our case study demonstrates the benefits of using Bayesian MMM for marketing attribution and optimization in a data-driven company like Lemonade. The approach is flexible, interpretable, and can provide valuable insights for decision-making.

Norman Müller, Peter Burggräf, Fabian Steinberg et al.

Predicting delivery delays is crucial for companies, especially in times of increasing global uncertainty and vulnerable supply chains. Machine learning (ML) offers significant potential to improve the forecast performance and quality of delivery delay prediction. Although various prediction approaches have been proposed in research, a structured and comprehensive overview is lacking. This paper addresses this gap by conducting a systematic literature review on the direct prediction of delivery delays. The objective is to identify applied prediction approaches and data sources, assess their readiness for real-world implementation, and derive a research agenda. The findings reveal that current research often focuses on marginal optimization of prediction performance while lacking practical applicability. Furthermore, most studies emphasize classifying deliveries as on time or delayed, rather than predicting the actual delay magnitude. Regarding the data used for prediction, combining enterprise resource planning (ERP) data with data from logistics improves prediction performance. However, environmental and location data, which could be easily integrated into ERP-based ML models, are rarely considered. This indicates a misalignment in current research, emphasizing the need for models combining practical applicability with predictive accuracy. Further research is required to address these identified deficits. Therefore, the present paper proposes a research agenda, to prioritize the most important deficits. These include, among others the industrial application, optimal prediction timing and ideal data combinations to achieve high prediction accuracy. It also highlights the need for integrated decision support systems that provide prediction-based recommendations, enhancing the practical value of predictive models in supply chain management.

Iman Mohammed Attia

The importance of continuously emerging new distribution is a mandate to understand the world and environment surrounding us. In this paper, the author will discuss a new distribution defined on the interval (0,1) as regards the methodology of deducing its PDF, some of its properties and related functions. A simulation and real data analysis will be highlighted.

Joon Suk Huh, Ellen Vitercik, Kirthevasan Kandasamy

We study a sequential profit-maximization problem, optimizing for both price and ancillary variables like marketing expenditures. Specifically, we aim to maximize profit over an arbitrary sequence of multiple demand curves, each dependent on a distinct ancillary variable, but sharing the same price. A prototypical example is targeted marketing, where a firm (seller) wishes to sell a product over multiple markets. The firm may invest different marketing expenditures for different markets to optimize customer acquisition, but must maintain the same price across all markets. Moreover, markets may have heterogeneous demand curves, each responding to prices and marketing expenditures differently. The firm's objective is to maximize its gross profit, the total revenue minus marketing costs. Our results are near-optimal algorithms for this class of problems in an adversarial bandit setting, where demand curves are arbitrary non-adaptive sequences, and the firm observes only noisy evaluations of chosen points on the demand curves. For $n$ demand curves (markets), we prove a regret upper bound of $\tilde{O}(nT^{3/4})$ and a lower bound of $Ω((nT)^{3/4})$ for monotonic demand curves, and a regret bound of $\tildeΘ(nT^{2/3})$ for demands curves that are monotonic in price and concave in the ancillary variables.

Mohammad Panahazari, Minoo Mohebbifar, Vahid Nazari Farsani et al.

Regarding the pervasive application of information and telecommunication technologies in the power distribution industry, responsive loads (RLs) have been widely employed in the operation of distribution and transmission systems. The utilization of these loads in the competitive environment of the power market has led to a decrease in costs and an increase in the flexibility of the distribution system and, consequently, the power system. This paper presents a framework for the competitive presence of RLs in local markets. The technical cooperation method of the Distribution System Operator (DSO) and Transmission System Operator (TSO), the persuasion mechanism of DSOs, and financial signals for getting and increasing the participation of consumers are represented based on local markets and market clearing mechanisms.

Saeed Nordin, Abolfazl Khodadadi, Priyanka Shinde et al.

With the increasing integration of power plants into the frequency-regulation markets, the importance of optimal trading has grown substantially. This paper conducts an in-depth analysis of their optimal trading behavior in sequential day-ahead, intraday, and frequency-regulation markets. We introduce a probabilistic multi-product optimization model, derived through a series of transformation techniques. Additionally, we present two reformulations that re-frame the problem as a mixed-integer linear programming problem with uncertain parameters. Various aspects of the model are thoroughly examined to observe the optimal multi-product trading behavior of hydro power plant assets, along with numerous case studies. Leveraging historical data from Nordic electricity markets, we construct realistic scenarios for the uncertain parameters. Furthermore, we then proposed an algorithm based on the No-U-Turn sampler to provide probability distribution functions of cleared prices in frequency-regulation and day-ahead markets. These distribution functions offer valuable statistical insights into temporal price risks for informed multi-product optimal-trading decisions.

Semra Ersöz

Brick-and-mortar pharmacies are facing strong competition from online pharmacies and are using digital techniques in their salesrooms as a counterstrategy. This study examines how digitalization affects purchase intentions among German customers. Perceived purchase risk, as a barrier to purchase, is compared for three types of pharmacies: non-digitalized pharmacies with conventional product displays (shelves) for products, digitalized pharmacies with digital signage displays for product presentation, and online pharmacies. Six risk types (performance, physical, psychological, financial, social, and privacy risks) and their effects on overall risk perception as well as purchase intentions are investigated in an online survey with a within-subject design. Results show that customers prefer non-digitalized pharmacies for shopping and rate their risk as the lowest. Digitalized brick-and-mortar pharmacies are ranked in the same league as online pharmacies in terms of risk assessment. The purchase intention in digitalized brick-and-mortar pharmacies is nevertheless higher than in online pharmacies.

Daniela Ioniță, Andreea Orîndaru, Marian Bratu

Customer relationship management (CRM) is a business approach which can provide a competitive advantage to small and medium sized enterprises (SMEs). To deploy a successful CRM strategy, SMEs need to invest in a CRM software but unfortunately, the adoption rate of such software is very low compared to large companies. This study is trying to identify the main reasons for not using CRM software and how adoption rate can be improved. In-depth interviews with marketing managers and business owners were conducted to investigate the types of relationships the organizations have with various stakeholders and find out the technical solutions used to implement CRM strategies. Several reasons were mentioned for not using, or using in a limited way, CRM software: they are not trusted, they do not work, they are too complicated or they are not needed because SMEs have a limited customer base and managing customer relationships is performed using simpler tools. The main problem is that respondents do not see the strategic importance of CRM software. As long as most respondents consider only the operational role of CRM software - which can be replaced with some success by other applications they already use - the adoption rate will continue to be limited.

Emad Rahmanian

Purpose – This paper aims to unify fragmented definitions of fake news and also present a comprehensive classification of the concept. Additionally, it provides an agenda for future marketing research based on the findings. Design/methodology/approach – A review of 36 articles investigating fake news from 1990 to 2020 was done. In total, 615 papers were found, and the article pool was refined manually in two steps; first, articles were skimmed and scanned for nonrelated articles; second, the pool was refined based on the scope of the research. Findings – The review resulted in a new definition and a collective classification of fake news. Also, the feature of each type of fake news, such as facticity, intention, harm and humor, is examined as well, and a definition for each type is presented. Originality/value – This extensive study, to the best of the author’s knowledge, for the first time, reviews major definitions and classification on fake news. Noticias falsas: una propuesta de clasificación y una agenda de investigación futura Objetivo – Este artículo pretende unificar las definiciones fragmentadas de las noticias falsas y también presentar una clasificación exhaustiva del concepto. Además, ofrece una agenda para futuras investigaciones de marketing basada en los resultados. Diseño – Se realizó una revisión de 36 artículos que investigaban las noticias falsas desde 1990 hasta 2020. Se encontraron 615 artículos, y el grupo de artículos se refinó manualmente en dos pasos, primero, se descremaron los artículos y se escanearon los artículos no relacionados, segundo, el grupo se refinó basado en el alcance de la investigación. Resultados – La revisión dio como resultado una nueva definición y una clasificación colectiva de las noticias falsas. Además, se examinan las características de cada tipo de noticias falsas, como la facticidad, la intención, el daño y el humor, y se presenta una definición para cada tipo. Originalidad – este amplio estudio revisa por primera vez las principales definiciones y la clasificación de las noticias falsas. 虚假新闻：分类建议和未来研究议程 目的 – 本文旨在统一假新闻的零散定义, 并对假新闻的概念进行全面的分类。此外, 它还根据本文的研究结果为未来的营销研究提供了一个议程。 设计/方法/途径 – 对1990年至2020年期间调查假新闻的36篇文章进行了回顾。一共发现了615篇论文, 并分为两步对此文章库进行了人工提炼：首先, 对文章进行略读和扫描以找出非相关文章, 其次, 根据研究范围对文章库进行了提炼。 研究结果 – 此次审查导致了对假新闻的新定义和集体分类。此外, 还分析了假新闻的真实性、意图、危害性、幽默性等各种类型的特征, 并给出了各种类型的定义。 原创性 – 此项涉及广泛假新闻内容的研究首次回顾了关于假新闻的主要定义和分类。

Widad BOUKALAA, Mosbah HARRAG

ارتبط الظهور الأول للجنات الضريبية بجذب الاستثمارات الأجنبية، إلا أنها أضحت من أهم آليات التهرب الضريبي الدولي في العصر الحالي، وذلك من خلال تمكين الممارسات السلبية للأفراد والشركات، مما يكلف النظام الضريبي العالمي خسارة 427 مليار دولار سنويا، 46,86% من إجمالي الخسائر مسؤولية جزر كايمان، بريطانيا، هولندا، لكسمبورغ، الو.م.أ. وتخسر الجزائر سنويا حوالي 429 مليون دولار(ما يعادل1,94% من إيراداتها الضريبية). لذلك فقد جاءت هذه الدراسة لتسلط الضوء على هذه الظاهرة التي شهدت اتساعا كبيرا في السنوات الأخيرة، والحث على تسطير استراتيجيات دولية للحد من اتساعها. The first appearance of tax havens is related to attracting foreign investment, But it has become one of the most important mechanisms of international tax evasion in the current era, costing the global tax system a loss of 427 billion annually, And 46,86% of the total losses are the responsibility of the Cayman Islands, Britain, the Netherlands, Luxemburg, USA. Algeria loses about $429 million a year, so this study came to highlight this phenomenon, urging the need to develop strategies to reduce its breadth.

Mohsen Afsharian

Sustainability in supply chain management addresses various challenges, from waste minimization to resource efficiency maximization. Two-dimensional cutting problems are common problems in most supply chains where small rectangular items need to be cut from large rectangular stock sheets to meet production needs or customer demands. The large stock sheets, produced from materials such as paper, steel, or wood, often contain defects. An optimal cutting solution is needed to avoid overlap with any defects and minimize waste in the cutting process. We propose a supply chain waste reduction optimization model using beam search algorithms for two-dimensional cutting problems with defects. Our proposed solution leverages the power of advanced analytics through a dynamic programming approach. Our algorithms feature variable beam widths and heuristic rules to reduce computation times while yielding high-quality solutions. A simulation model is used to assess the performance of the proposed algorithms.

Sachin Agarwal, Ravi Kant, Ravi Shankar

Performance measures are vital in assessing the disaster relief operations and mitigate the losses that occur during disaster. It is imperative to benchmark and monitor the growth of humanitarian organizations (HOs). The purpose of this research is to explore the performance measures for HOs based on a sustainability balanced scorecard (SBSC). This study identifies and finalizes 31 performance measures through literature and brainstorming session conducted with the experts. Finalized performance measures are classified into five humanitarian supply chain management (HSCM) performance perspectives using SBSC. The best worst method (BWM) is applied to prioritize the performance measures, and the additive ratio assessment (ARAS) is applied to evaluate the performance of HOs. The outcome of this research reveals that “beneficiaries’ and donors’ perspectives” is the most significant HSCM performance perspectives. The findings help to identify the relative importance of each performance measure for performance evaluation of HOs. The proposed framework can help HOs on the aspects of performance improvement relevant to both donors and beneficiaries group that facilitates stakeholders in the benchmarking and network design of HOs. This study explores the SBSC in HSCM to analyze the performance measures and evaluate the performance of HOs that enable an integrated performance measurement system. HOs monitored their logistics performance effectively, which further lead to process improvement for betterment.

Barbara Dańska-Borsiak

Along with an increase in the level of societies’ wealth, factors such as the state of health, the quality of education and negative output effects including environment quality are becoming increasingly important in assessing the standard of living and well‑being of the average person. A category that has long been used to measure the economic and social well‑being of societies is GDP per capita. However, in contemporary research, other attempts, more comprehensively describing important aspects of life, are being proposed. The main aim of this article is to examine the standard of living in NUTS–4 districts in Poland in 2020 in aggregate and in its particular dimensions. Spatial differentiation of the standard of living index and sub‑indices describing its individual dimensions was also examined. The standard of living was measured on the basis of a composite variable. This variable was constructed as Hellwig’s measure of economic development on the basis of values of partial indicators describing successive dimensions. Those indicators were determined as arithmetic means of normalised diagnostic variables. The highest standard of living is observed in cities with powiat status. Among them, there are both the largest agglomerations and smaller cities constituting local centres. In the spatial distribution of the standard of living measure, attention is drawn to the large concentration of districts with the lowest values in the north‑east of Poland, in the Kujawy Region and in the south‑east. Partial indicators describing the dimensions of the standard of living, constructed for the purposes of the study, reflect the situation with regard to the degree of implementation of detailed tasks of social policy. The analysis of the situation of districts in particular dimensions of the standard of living carried out in this paper makes it possible to indicate the districts that require the greatest attention of decision‑makers and to direct the greatest resources to them.

Safa El Kefi

This article presents a Benchmarking methodology to support decision-making for international market selection (IMS). In order to do so, we will be using an output-oriented Data Envelopment Analysis (DEA) model. This methodology considers multiple variables validated with a correlation analysis. The methodology is applied to all of the products directly exported from Spain, it takes into consideration different Inputs variables and returns us the efficient and regions generating higher benefits to access international markets with the lowest costs possible.

Fernanda Muniz, Guanyu Geng, Gopala “GG” Ganesh

## Purpose of the Study This paper describes the implementation of a semester-long rigorous drill exercise in an undergraduate Marketing Metrics class to better prepare the students in marketing math and metrics. ## Method/Design and Sample The drill assignment, implemented over eight semesters, used the website Management-by-the-numbers.com (MBTN). It consisted of a problem-based approach covering a large number of Marketing Metrics. In addition, the authors collected data on student performance during this time from a total of 902 students, about 80% of whom took the class face-to-face or F2F and 20% online or INET. ## Results These responses reveal that exercises like the MBTN assignment are a practical resource and learning opportunity for cultivating students' quantitative skills and analytical abilities. Marketing educators would benefit from such exercises to enhance students' experience and learning in their programs. ## Value to Marketing Educators This paper adds to existing pedagogical knowledge by exploring in detail one way to cultivate marketing students' quantitative analytical abilities. Businesses that hire marketing students increasingly expect them to be well-trained academically, including in good number skills. Therefore, developing these in undergraduate and graduate marketing students assumes greater importance for universities that offer these programs of study.

Madison Metsker-Galarza

Shonna Trinch and Edward Snajdr decipher signage in a way that will prevent you from looking at a sign in the same manner again. Their research is built on a series of site visits, observations, and ethnographic interviews and they posit that signage plays an important role in gentrification. As they explain it, signs effect public space; well designed and interesting signs are important attributes of placemaking, often part of a strategy for cities to reclaim their appeal.