Hasil untuk "Marketing. Distribution of products"

T. McGuire, R. Staelin

Chris K. Anderson

Greg M. Allenby, Peter E. Rossi

James Brand, A. Israeli, Donald Ngwe

Large language models (LLMs) have quickly become popular as labor-augmenting tools for programming, writing, and many other processes that benefit from quick text generation. In this paper we explore the uses and benefits of LLMs for researchers and practitioners who aim to understand consumer preferences. We focus on the distributional nature of LLM responses, and query the Generative Pre-trained Transformer 3.5 (GPT-3.5) model to generate hundreds of survey responses to each prompt. We offer two sets of results to illustrate our approach and assess it. First, we show that GPT-3.5, a widely-used LLM, responds to sets of survey questions in ways that are consistent with economic theory and well-documented patterns of consumer behavior, including downward-sloping demand curves and state dependence. Second, we show that estimates of willingness-to-pay for products and features generated by GPT-3.5 are of realistic magnitudes and match estimates from a recent study that elicited preferences from human consumers. We also offer preliminary guidelines for how best to query information from GPT-3.5 for marketing purposes and discuss potential limitations. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4395751

Ziqing Yin, Xuanjing Chen, Xi Zhang

The rapid proliferation of AI-generated content (AIGC) has reshaped the dynamics of digital marketing and online consumer behavior. However, predicting the diffusion trajectory and market impact of such content remains challenging due to data heterogeneity, non linear propagation mechanisms, and evolving consumer interactions. This study proposes an AI driven Decision Support System (DSS) that integrates multi source data including social media streams, marketing expenditure records, consumer engagement logs, and sentiment dynamics using a hybrid Graph Neural Network (GNN) and Temporal Transformer framework. The model jointly learns the content diffusion structure and temporal influence evolution through a dual channel architecture, while causal inference modules disentangle the effects of marketing stimuli on return on investment (ROI) and market visibility. Experiments on large scale real-world datasets collected from multiple online platforms such as Twitter, TikTok, and YouTube advertising show that our system outperforms existing baselines in all six metrics. The proposed DSS enhances marketing decisions by providing interpretable real-time insights into AIGC driven content dissemination and market growth patterns.

Berk Yilmaz, Huthaifa I. Ashqar

The recent advances in large language models (LLMs) have revolutionized industries such as finance, marketing, and customer service by enabling sophisticated natural language processing tasks. However, the broad adoption of LLMs brings significant challenges, particularly in the form of social biases that can be embedded within their outputs. Biases related to gender, age, and other sensitive attributes can lead to unfair treatment, raising ethical concerns and risking both company reputation and customer trust. This study examined bias in finance-related marketing slogans generated by LLMs (i.e., ChatGPT) by prompting tailored ads targeting five demographic categories: gender, marital status, age, income level, and education level. A total of 1,700 slogans were generated for 17 unique demographic groups, and key terms were categorized into four thematic groups: empowerment, financial, benefits and features, and personalization. Bias was systematically assessed using relative bias calculations and statistically tested with the Kolmogorov-Smirnov (KS) test against general slogans generated for any individual. Results revealed that marketing slogans are not neutral; rather, they emphasize different themes based on demographic factors. Women, younger individuals, low-income earners, and those with lower education levels receive more distinct messaging compared to older, higher-income, and highly educated individuals. This underscores the need to consider demographic-based biases in AI-generated marketing strategies and their broader societal implications. The findings of this study provide a roadmap for developing more equitable AI systems, highlighting the need for ongoing bias detection and mitigation efforts in LLMs.

Maxwell C. Siegel

Let $p$ be an integer $\geq2$ and let $K$ be a global field. A foliated $p$-adic F-series is a function $X$ of a $p$-adic integer variable $\mathfrak{z}$ satisfying the functional equations $X\left(p\mathfrak{z}+j\right)=a_{j}X\left(\mathfrak{z}\right)+b_{j}$ for all $\mathfrak{z}\in\mathbb{Z}_{p}$ and all $j\in\left\{ 0,\ldots,p-1\right\} $, where the $a_{j}$s and $b_{j}$s are indeterminates. Treating $X$ as taking value in a certain ring of formal power series over $K$, this paper establishes a universal/functorial Fourier theory for F-series: we show that $X$ has a Fourier transform, and that, for nearly any ideal $I\subseteq R$, where of $R=\mathcal{O}_{K}\left[a_{0},\ldots,a_{p-1},b_{0},\ldots,b_{p-1}\right]$, this Fourier transform descends through the quotient mod $I$ which imposes on $X$ the relations encoded by $I$. Furthermore, we show that the pointwise product of $X$ with itself $n$ times also has a Fourier transform compatible with descent. These results generalize to products $X_{1}^{e_{1}}\cdots X_{d}^{e_{d}}$ of any $d$ distinct F-series $X_{1},\ldots,X_{d}$ with integer exponents $e_{1},\ldots,e_{d}\geq0$. Using these Fourier transforms, F-series and their products can be identified with distributions on $\mathbb{Z}_{p}$ in a manner compatible with descent mod $I$, forming algebras under pointwise multiplication. Also, to any given F-series or product thereof, one can associate an affine algebraic variety over $K$ which I call the breakdown variety. The distributions induced by a product of F-series under descent mod $I$ exhibit sensitivity to $I$'s containment of the ideal corresponding to the distributions' breakdown varieties. This yields a novel method of encoding given affine algebraic varieties through distributions in a way compatible with pointwise products, convolutions, and tensor products.

L. Lisa, M. Turunen, Maike Gossen

The second-hand clothing market is crucial for redirecting consumption away from new garments, promoting reused clothing, and preventing premature disposal. This article examines the business and marketing strategies, distribution channels, and communications of second-hand clothing companies to analyze how they attract consumers to extend the lifetime of garments. Empirical data consist of market ethnography, including physical visits to stores and observations of companies’ digital channels. Qualitative data were collected for six months, and a total of 20 companies operating in the Finnish second-hand market were included. The findings reveal that second-hand companies use different operating models with a variety of marketing practices to attract consumers and facilitate product circulation. Some marketing practices appear to unintentionally promote increased consumption: tactical pricing and constant discounts, novelty-driven merchandising, and call-to-action communication may attract customers to unconsidered purchases. Some second-hand companies also appeared to offer credit to sellers for the purchase of new items, which could lead to higher rather than lower consumption. Second-hand companies predominantly prioritize transactions, yet sufficiency-orienting marketing practices for intensifying use or extending product lifetime are less emphasized.

Muhammad Sufyan Ramish, Junaid Ansari, Ummi Naiemah Saraih et al.

Deceptive advertisement is a primary factor affecting customer loyalty because when people do not receive what they expect from advertisements, they tend to avoid using those brands. Although past researches have addressed the perceived deception in advertisements and its impact on customer loyalty, there is a lack of studies focusing on the mediating role of corporate trust, corporate image, and perceived deception in relation to customer loyalty. Household consumers were chosen as the target population due to their exposure to advertisements. A sample of 250 individuals participated in this study. Smart PLS was used for data analysis. This study confirms that perceived deception, corporate trust and corporate image play a significant mediating role in establishing customer loyalty. The findings of this study can assist marketers in developing new designs and strategies that do not mislead customers. It will also help marketers to identify the factors that should be considered when designing advertisements.

Hossein Tayebi Falehi, Reza Shajie, Shahram Alam et al.

Purpose: This research aims to analyze the success process of Iranian wrestling based on Bosscher's championship sports development model. Materials andMethods: it is qualitative-quantitative research which is applied in terms of purpose; it is mixed exploratory research and it uses Grounded Theory in terms of methodology. The statistical population of the research was 14 managers, specialists, and experts selected through purposive and snowball sampling method via in-depth and semi-structured interview. At the same time, data was analyzed using the Glaser method, including open, selective and theoretical coding by MAXQDA software.Results: Data analysis was done in the quantitative section using a researcher-made questionnaire. The final model was obtained after passing all steps. The findings showed that public sport, governance and structure, research and innovation, supporting athletes, talent identification, and national and international competition are the main categories of the ultimate model of the current research.Conclusion: It can be concluded that, in addition to the need to pay attention to all these things, financial factors, human resources and communication with other organizations, especially the government and the Ministry of Sports, can lead to very important practical considerations for the future of wrestling.

Kanza Armifa Angia Said, Adinda Rabiatuladawiyah, Wira Natalia et al.

Setiap anak bangsa, tak peduli latar belakang ekonomi, keluarga, serta tempat tinggal, layak untuk diberikan edukasi dan inspirasi terkait dengan bela negara. Hal ini membuat tim pengabdian UPN “Veteran” Jakarta berinisiatif melakukan kegiatan sosialisasi dan bakti sosial kepada anak-anak panti asuhan dalam rangka mewujudkan generasi penerus bangsa yang memiliki kesadaran dan semangat dalam membela negaranya. Sasaran dari kegiatan ini adalah 30 orang anak di Panti Asuhan Kafilul Yatim Nurul Falah. Kegiatan ini terbagi ke dalam tiga tahapan, yaitu tahap perencanaan, pelaksanaan, dan evaluasi. Dari kegiatan yang telah dilakukan, diperoleh hasil bahwa anak-anak dapat memahami apa itu bela negara dan bagaimana cara mengimplementasikannya dalam kehidupan sehari-hari. Selain itu, kegiatan ini menjadikan anak-anak menjadi lebih percaya diri dan membantu mereka dalam berbaur dan mengenal sesama. Ini menunjukkan bahwa kegiatan sosialisasi dan bakti sosial pada panti asuhan dapat membantu menumbuhkan kesadaran dan semangat bela negara melalui pemberian perhatian, kepedulian, dan inspirasi. Mereka juga dapat merasakan rasanya dihargai, memperoleh keterampilan dan peluang di masa depan, serta membangun lingkungan yang positif. Semoga dengan adanya kegiatan ini anak-anak dapat terus tumbuh dan berkembang dengan membawa sikap semangat bela negara di tengah masyarakat. Kata Kunci: bela negara; sosialisasi; bakti sosial; anak bangsa; panti asuhan

Tobias Bitterli, Fabian Schär

In this paper we analyze constant product market makers (CPMMs). We formalize the liquidity providers' profitability conditions and introduce a concept we call the profitability frontier in the xyk-space. We study the effect of mint and burn fees on the profitability frontier, consider various pool types, and compile a large data set from all Uniswap V2 transactions. We use this data to further study our theoretical framework and the profitability conditions. We show how the profitability of liquidity provision is severely affected by the costs of mint and burn events relative to the portfolio size and the characteristics of the trading pair.

Qifang Zhao, Tianyu Li, Meng Du et al.

When doing private domain marketing with cloud services, the merchants usually have to purchase different machine learning models for the multiple marketing purposes, leading to a very high cost. We present a unified user-item matching framework to simultaneously conduct item recommendation and user targeting with just one model. We empirically demonstrate that the above concurrent modeling is viable via modeling the user-item interaction matrix with the multinomial distribution, and propose a bidirectional bias-corrected NCE loss for the implementation. The proposed loss function guides the model to learn the user-item joint probability $p(u,i)$ instead of the conditional probability $p(i|u)$ or $p(u|i)$ through correcting both the users and items' biases caused by the in-batch negative sampling. In addition, our framework is model-agnostic enabling a flexible adaptation of different model architectures. Extensive experiments demonstrate that our framework results in significant performance gains in comparison with the state-of-the-art methods, with greatly reduced cost on computing resources and daily maintenance.

Nisan Güniz Serper, Elif Şen, Banu Çalış Uslu

Optimization models enable organizations to find the best solution and respond to the demand from an uncertain environment and stochastic process promptly and with less engineering effort. This study aims to optimize the number of seasonal agents and customer prioritization needed for a call center system using big data analytics and discrete event simulations to improve customer satisfaction. The study was carried out based on data from a leading heating and ventilation company’s call center. The K-means clustering technique was used to determine customer segmentation on 6-million-customer data. For prioritization, the making of a Recency-Frequency-Monetary (RFM) analysis was applied. The system was modeled using ARENA simulation software, and performance parameters were measured depending on the segments obtained. The results show that the simulation model performed with data analytics gives better results for a beneficial financial impact with numerical values in customer prioritization, reducing the average waiting time of the most prioritized customers by more than 90%, and for the least prioritized customers, it increased the average waiting time by approximately just 40%. However, with the company segments, the increase in the average waiting time of the least prioritized customers was approximately 300%.

Mikhael Laurente

Philippines is considered one of the fastest developing economies because of the growing service sector. This growth brought a significant change in the economic structure of the country which previously relied on the agricultural sector. This paper conducted a study about the significant impact of structural change on labor productivity growth and employment. The paper localized the decomposition analysis used in literatures to extract the share of “within” sector and “structural change” to total changes in labor productivity in the Philippines from 2004-2018, and Applied Pooled Least Square, to obtain the impact of structural change to labor productivity growth and employment. Based on Durbin-Watson test results, both Panel Regression Equation and Seemingly Unrelated Equation were utilized because there is no contemporaneous autocorrelation found in Pooled Least Square. Using Breusch-Pagan LM Test, Panel Regression is deemed more appropriate than Seemingly Unrelated Regression. Furthermore, the decomposition analysis showed that higher share of service sector in employment makes the contribution of “structural change” lesser to labor productivity growth due to labor market that becomes less flexible as service sector dominates the labor market because of higher skillsets needed by the sector. The regression analysis showed that structural change is a significant determinant of employment and labor productivity; structural change has a positive relationship to labor productivity due to the transfer of labor to high-productivity sector; and structural change has a negative relationship to employment because the employment brought by the structural change cannot be absorbed by the labor force because of skills mismatch.

BOUQLILA FATINE, DAHAB DOUNIA

The context of CORONAVIRUS 2019 epidemic and the policy of social distancing encouraged by the World Health Organization (WHO) have pushed consumers to turn to online shopping. Indeed, to avoid contracting the virus by using cash or by going to crowded places, consumers are starting to favor e-commerce. This craze for e-commerce has led to an acceleration electronic payments usage. In order to understand the reasons for the high use of this type of payment during the pandemic, this study tries to determine the factors that drove the adoption of electronic payments (E-payments) during this period. The study is based on the Technology Acceptance Model (TAM), which examines the intention to adopt e-payments by focusing on the role of important factors in the acceptance of new technologies and particularly online payments. Thus, this paper contributes to the literature by examining the influence of social distancing, perceived risk, perceived security, and trust on behavioral intention to adopt electronic payment in the context of COVID 19 epidemic in Morocco. The data was collected using an online survey administered to 265 individuals. The results revealed that perceived risk, social distancing, perceived security, and trust predicted perceived usefulness, while perceived usefulness in turn had positive effects on behavioral intention to use online payment. This research examined for the first time the influence of a new variable "social distancing", which is considered an important factor in the epidemic context, and showed its positive influence on perceived usefulness of mobile payment. It also revealed that, in this particular context, perceived risk positively influences perceived usefulness, contrary to the results of several previous studies, as the risk studied is related to the risk of contracting a dangerous virus. This paper also provides interesting empirical results that allow e-services providers improve their marketing plans by highlighting the main factors that promote the adoption of electronic payments, namely, trust, perceived security, avoidance of physical contact and handling of cash, which are the main sources of contamination by CORONAVIRUS. Nevertheless, it has some limitations, such as studying intention to use instead of actual behavior. This limitation may constitute a new perspective for future research.

Faiza Shah, Yumin Liu, Yasir Shah et al.

Recent advances in data analysis and processing methods can improve the ability of computational applications to perform complex steps of different tasks. With the progress of information and communication technologies (ICT), Blockchain-based complex data processing for transaction analysis and smart contract agreement has become a new research area in the fields of mathematics and computation. Stability of financial sector based on the ICT is a core component for growing the economics of medium and small enterprises. This stability brings the innovation to businesses productivity, while the management of information takes more prospective for improving the efficiency and more ways for innovating the business of products. In this study, we use the autoregressive distribution lag (ARDL) model with Blockchain-based complex data processing approach to emphasize the role of ICT in the field of trade credit maintainability. Actually, the ICT connects the industries in the entire world and makes business sectors that use its technologies be more advanced. Based on the ARDL model conducted on the records gathered from 2000 to 2019, the analysis concludes that the ICT-based complex data processing is a critical component of trade credit. The statistics of ICT are chosen based on the economy penetrations through the Internet and mobile phones. The causality exposed between the trade credit and ICT is bidirectional in nature. Also, it is found that the usage of mobile phones has a substantial influence on the business sectors, as a substantial amount of trading and business transactions are conducted over the phone. Therefore, the primary concern is the association between the Blockchain and trade credit, which is thoroughly discussed in this work. The trade credit improves the stability of financial sector and the Blockchain supports its maintainability by the role of ICT. The results of the study can help the business stakeholders and investors to estimate the marketing for future useful execution.

Arindam Dutta, Anirban Pathak

We present two new schemes for quantum key distribution (QKD) that neither require entanglement nor an ideal single-photon source, making them implementable with commercially available single-photon sources. These protocols are shown to be secure against multiple attacks, including intercept-resend and a class of collective attacks. We derive bounds on the key rate and demonstrate that a specific type of classical pre-processing can increase the tolerable error limit. A trade-off between quantum resources and information revealed to an eavesdropper (Eve) is observed, with higher efficiency achievable through the use of additional quantum resources. Specifically, our proposed protocols outperform the SARG04 protocol in terms of efficiency at the cost of more quantum resources.

X. Xu

With the progress of information technology and the change of business environment, the marketing strategy adopted by brands or companies is changed from traditional marketing to Internet marketing. In this process, marketing communication as the main means of implementing marketing strategy is the part that produces the biggest change. Therefore, this paper puts forward the concept of integrated marketing communication, and studies the differences between traditional marketing and Internet marketing in the implementation of marketing strategies (4Ps) from the perspective of marketing communication based on relevant literature, mainly in the choice of marketing channels. In addition, this paper also studies the reasons why the emerging Internet beverage brand Genki Forest has developed rapidly in just four to five years, and analyzes the application of integrated marketing communication in the current Internet era from the three aspects of product power and pricing, digital marketing communication and new retail offline distribution, so as to provide a reference for other brands and companies.