Hasil untuk "Marketing. Distribution of products"

Zhentong Lu, Kenichi Shimizu

We propose a new approach to estimating the random coefficient logit demand model for differentiated products when the vector of market-product level shocks is sparse. Assuming sparsity, we establish nonparametric identification of the distribution of random coefficients and demand shocks under mild conditions. Then we develop a Bayesian procedure, which exploits the sparsity structure using shrinkage priors, to conduct inference about the model parameters and counterfactual quantities. Comparing to the standard BLP (Berry, Levinsohn, & Pakes, 1995) method, our approach does not require demand inversion or instrumental variables (IVs), thus provides a compelling alternative when IVs are not available or their validity is questionable. Monte Carlo simulations validate our theoretical findings and demonstrate the effectiveness of our approach, while empirical applications reveal evidence of sparse demand shocks in well-known datasets.

Evann Keith TABASA, Marvin CRUZ

The purpose of this research was to examine the preferences of consumers for subcompact sedan cars in General Santos City, Philippines. This research may provide the car industry significant information as to how consumers process their car buying decisions that will in turn help car manufacturers and car dealerships develop market-driven marketing and sales strategies and tactics. Conjoint experimental research design was used in this study. Primary data were gathered through the use of a survey essentially structured using the orthogonally designed subcompact sedan car profiles that were rated by a total of 455 valid respondents based on their level of preference. Conjoint analysis revealed that consumers in General Santos City most prefer a subcompact sedan car which Price is USD. 16,044.00 (β=0.037), which Engine is 1.5 Liter - 4 Cylinder - 106 HP (β=0.092), which Safety feature is 6-7 SRS Airbags+Speed Sensing Doorlocks (β=0.019), which Fuel Efficiency is More than 12 Kilometers/Liter - City Driving (β=0.145) and which Brand is Honda - City (β=0.400). In addition, consumers place Brand as the most important attribute of a subcompact sedan car with overall relative importance of 43.065%, followed by Engine (18.898%), Price (17.088%), Fuel Efficiency (15.603%) and Safety (5.345%). Overall, majority of the consumers in General Santos City may choose Toyota - Vios as their Subcompact Sedan Car. This study recommends for car manufacturers to further nurture their car brands through advertising and other forms of promotion as consumers have the propensity to choose and purchase a subcompact sedan car primarily because of its brand.

Layla Alsheikh

This study aimed to investigate the impact of guerilla marketing (i.e., guerilla ambient marketing and guerilla sensation marketing) on customer behavior (i.e., customer purchase intention and customer brand attitude). The survey was held in May 2023; the questionnaire was distributed to a convenience sample of 450 customers of three malls in Jeddah city in the Kingdom of Saudi Arabia. The analysis was conducted by IBM SPSS and AMOS using 344 retrieved responses. Exploring research factors, confirming goodness-of-fit, and testing the hypothesized effects, the results indicated that both dimensions of guerrilla marketing had significant effects on both dimensions of customer behavior. However, the effect of ambient marketing on customer purchase intention was greater than its effect on customer brand attitude. Conversely, the effect of sensation marketing on customer brand attitude was greater than its effect on customer purchase intention. The paper concludes that ambient marketing has more power to boost customer purchase intention in comparison with sensation marketing, which is suitable for elevating customer brand attitude. For that, enterprises are required to try nonconventional marketing practices such as guerilla marketing in order to change customer behaviors. Further studies should use other dimensions of guerilla marketing and target more customers from different locations.

Alexandre Borba da Silveira, Jefferson Marlon Monticelli, Fabrício Silva Barbosa

Our article aims to analyze the main influences, experience and affective involvement that impact the consumer behavior of regional wines in Brazil. We used a descriptive quantitative survey. Our findings contribute to a greater understanding of the behavior of choice related to local experiences and what points are essential to involve the consumer with a product, in this case, wine. The Brazilian wine industry has been dealing with tariff disputes between countries, increased number of producers, reduction in consumption per capita and demand for higher quality wines. Our results show that cultural, social, personal, and psychological factors are crucial in this process.

Gulfam Haider, Laiba Zubair, Aman Saleem

This study, rooted in dynamic capability theory and the developing era of Big Data Analytics, explores the transformative effect of BDA EDCs on marketing. Ambidexterity and firms market performance in the textile sector of Pakistans cities. Specifically, focusing on the firms who directly deal with customers, investigates the nuanced role of BDA EDCs in textile retail firms potential to navigate market dynamics. Emphasizing the exploitation component of marketing ambidexterity, the study investigated the mediating function of marketing ambidexterity and the moderating influence of competitive pressure. Using a survey questionnaire, the study targets key choice makers in textile firms of Faisalabad, Chiniot and Lahore, Pakistan. The PLS-SEM model was employed as an analytical technique, allows for a full examination of the complicated relations between BDA EDCs, marketing ambidexterity, rival pressure, and market performance. The study Predicting a positive impact of Big Data on marketing ambidexterity, with a specific emphasis on exploitation. The study expects this exploitation-orientated marketing ambidexterity to significantly enhance the firms market performance. This research contributes to the existing literature on dynamic capabilities-based frameworks from the perspective of the retail segment of textile industry. The study emphasizes the role of BDA-EDCs in the retail sector, imparting insights into the direct and indirect results of BDA EDCs on market performance inside the retail area. The study s novelty lies in its contextualization of BDA-EDCs in the textile zone of Faisalabad, Lahore and Chiniot, providing a unique perspective on the effect of BDA on marketing ambidexterity and market performance in firms. Methodologically, the study uses numerous samples of retail sectors to make sure broader universality, contributing realistic insights.

Eduardo C. Garrido-Merchán, Maria Coronado-Vaca, Álvaro López-López et al.

Traditional economic models often rely on fixed assumptions about market dynamics, limiting their ability to capture the complexities and stochastic nature of real-world scenarios. However, reality is more complex and includes noise, making traditional models assumptions not met in the market. In this paper, we explore the application of deep reinforcement learning (DRL) to obtain optimal production strategies in microeconomic market environments to overcome the limitations of traditional models. Concretely, we propose a DRL-based approach to obtain an effective policy in competitive markets with multiple producers, each optimizing their production decisions in response to fluctuating demand, supply, prices, subsidies, fixed costs, total production curve, elasticities and other effects contaminated by noise. Our framework enables agents to learn adaptive production policies to several simulations that consistently outperform static and random strategies. As the deep neural networks used by the agents are universal approximators of functions, DRL algorithms can represent in the network complex patterns of data learnt by trial and error that explain the market. Through extensive simulations, we demonstrate how DRL can capture the intricate interplay between production costs, market prices, and competitor behavior, providing insights into optimal decision-making in dynamic economic settings. The results show that agents trained with DRL can strategically adjust production levels to maximize long-term profitability, even in the face of volatile market conditions. We believe that the study bridges the gap between theoretical economic modeling and practical market simulation, illustrating the potential of DRL to revolutionize decision-making in market strategies.

Xiaoqing Zhang, Yuhan Liu, Jianzhou Wang et al.

Influencer marketing campaign success heavily depends on identifying key opinion leaders who can effectively leverage their credibility and reach to promote products or services. The selecting influencers process is vital for boosting brand visibility, fostering consumer trust, and driving sales. While traditional research often simplifies complex factors like user attitudes, interaction frequency, and advertising content, into simple numerical values. However, this reductionist approach fails to capture the dynamic nature of influencer marketing effectiveness. To bridge this gap, we present SAGraph, a novel comprehensive dataset from Weibo that captures multi-dimensional marketing campaign data across six product domains. The dataset encompasses 345,039 user profiles with their complete interaction histories, including 1.3M comments and 554K reposts across 44K posts, providing unprecedented granularity in influencer marketing dynamics. SAGraph uniquely integrates user profiles, content features, and temporal interaction patterns, enabling in-depth analysis of influencer marketing mechanisms. Experimental results using both traditional baselines and state-of-the-art large language models (LLMs) demonstrate the crucial role of content analysis in predicting advertising effectiveness. Our findings reveal that LLM-based approaches achieve superior performance in understanding and predicting campaign success, opening new avenues for data-driven influencer marketing strategies. We hope that this dataset will inspire further research https://github.com/xiaoqzhwhu/SAGraph/.

Itani Listen Ramuthivheli, Dr Kirsty-Lee Sharp, Prof. Bongazana Dondolo

This study aims to investigate factors influencing students’ loyalty to Technical and Vocational Education and Training (TVET) colleges. In this study, five TVET colleges located in Gauteng were selected using a nonprobability judgement sample. A self-administered questionnaire was handed out to 462 full-time undergraduate students at each of the five TVET colleges during class time. This study explored how factors such as brand communication, service quality and overall satisfaction affect brand loyalty. Structural equation modelling using partial least squares (PLS) was used to test the relationships. The analysis revealed that brand satisfaction and service quality significantly affect students’ perceptions of brand loyalty. The results of this study, however, did not show an association between brand communication and brand loyalty. This study adds to new knowledge as it appears to be the first to examine brand loyalty in the South African TVET context, providing new insights into the literature about brand loyalty in higher education. The findings of this study have the potential to benefit TVET colleges facing challenges with student retention.

Marc S. Klinger, Robert G. Leigh

Recent work has highlighted the importance of crossed products in correctly elucidating the operator algebraic approach to quantum field theories. In the gravitational context, the crossed product simultaneously promotes von Neumann algebras associated with subregions in diffeomorphism covariant quantum field theories from type III to type II, and provides the necessary ingredients to gravitationally dress operators, thereby enforcing the constraints of the theory. In this note we enhance the crossed product construction to the context of general gauge theories with arbitrary combinations of internal and spacetime local symmetries. This is done by leveraging the correspondence between the crossed product and the extended phase space. We then undertake a detailed study of constraint quantization from the perspective of a generic crossed product algebra. We study and compare four distinct approaches to constraint quantization from this point of view: refined algebraic quantization, BRST quantization, path integral quantization, and the commutation theorem for crossed products. Far from simply reproducing existing analyses, the operator algebraic viewpoint sheds new light on old problems by reformulating the dressing of operators in terms of conditional expectations and other closely related projection maps. We conclude by applying our approach to the constraint quantization of three distinct gauge theories including a discussion of gravity on null hypersurfaces.

Mohammad Mousavi, Meng Wu

In this paper, a framework is proposed to coordinate the operation of the independent system operator (ISO) and distribution system operator (DSO). The framework is compatible with current practice of the U.S. wholesale market to enable massive distributed energy resources (DERs) to participate in the wholesale market. The DSO builds a bid-in cost function to be submitted to the ISO market through parametric programming. Once the ISO clears the wholesale market, the dispatch and payment of the DSO are determined by ISO. Then, the DSO determines the dispatch and payment of the DER aggregators. To compare the proposed framework, an ideal case is defined in which DER aggregators can participate in the wholesale market directly and ISO overseas operation of both transmission and distribution systems. We proved 1) the dispatches of the proposed ISO-DSO coordination framework are identical to those of the ideal case; 2) the payments to each DER aggregator are identical in the proposed framework and in the ideal case. Case studies are performed on a small illustrative example as well as a large test system which includes IEEE 118 bus transmission system and two distribution systems - the IEEE 33 node and IEEE 240 node test systems.

Mousumi Bose

Extant research has discussed how consumers cope with numerous stressors and how coping can help with their well-being. Additionally, recent research has highlighted the importance of situated learning or learning that takes place in the same context in which it is applied, in the process of coping with stressful service encounters. This research relates to the effect consumer resilience can have on situated learning, active coping and well-being, especially when faced with stressful service situations. Results from an online survey of consumers demonstrated the positive effect of resilience on situated learning that affects active coping through partial mediation. Both situated learning and active coping also positively influences consumers’ subjective well-being. Additionally, psychological flexibility moderates some of the pathways. While partial mediation of situated learning was effective only with participants with high psychological flexibility, resilience played a role helping consumers with low psychological flexibility to learn and cope.

Fatma El Zohra ALLOUI, Mohand Ouamer ALI ZIAN

تهدف هذه الورقة البحثية لمعرفة دور المؤسسات المناولة الصناعية في التنمية المستدامة، ومدى سعيها لتبني مبادئ المسؤولية الاجتماعية. حيث تجد نفسها مجبرة على ذلك نتيجة ضغط السوق، كل أصحاب المصلحة، المجتمع و البيئة. فالمؤسسات المسؤولة اجتماعيا تساهم بشكل مهم في تحقيق التنمية المستدامة، حيث تسعى لتحقيق الأداء المالي، الاجتماعي والبيئي. غير أن صغر حجم المؤسسات المناولة وضعف امكانياتها قد يشكلان صعوبة في تحقيق ذلك. وبالرغم من أن الضغط الراهن على المؤسسات الكبيرة الا انّ المؤسسات المناولة معنية بذلك من أجل تحسين تنافسيتها وضمان استمراريتها.  This research aims to understand the role of subcontractors in sustainable development and their efforts to be socially responsible. They are forced to do so due to pressure from the market, all stakeholders, society and the environment. Socially responsible firms contribute to the sustainable development; they seek to achieve the financial, social and environmental performance. The current pressure on the big firms, but the subcontractors are concerned to improve their competitiveness and their sustainability.

Atabek Atayev

In many markets buyers are poorly informed about which firms sell the product (product availability) and prices, and therefore have to spend time to obtain this information. In contrast, sellers typically have a better idea about which rivals offer the product. Information asymmetry between buyers and sellers on product availability, rather than just prices, has not been scrutinized in the literature on consumer search. We propose a theoretical model that incorporates this kind of information asymmetry into a simultaneous search model. Our key finding is that greater product availability may harm buyers by mitigating their willingness to search and, thus, softening competition.

Vaisakh K. M., Sreedevi E. P., Sudheesh K. Kattumannil

In the present paper, we develop a new goodness fit test for gamma distribution using the fixed point characterization. U-Statistic theory is employed to derive the test statistic. We discuss how the right censored observations are incorporated in the test developed here. The asymptotic properties of the test statistic in both censored and uncensored cases are studied in detail. Extensive Monte Carlo simulation studies are carried out to validate the performance of the proposed tests. We also illustrate the test procedure using several real data sets.

Chunyi Huang, Chengmin Wang, Mingzhi Zhang et al.

The burgeoning integration of distributed energy resources (DER) poses new challenges for the economic and safe operation of the electricity system. The current distribution-side policy is largely based on mandatory regulations and incentives, rather than the design of a competitive market mechanism to arouse DERs to freely compete in the retail market. To address this issue, we proposed a transactive retail market mechanism to attract the active participation of profit-driven DER retailers in a deregulated way. Considering the limited competitive property of the retail market, a bi-level DSO-dominated framework is constructed to simulate the virtual game between distribution system operator (DSO) and DER retailers. Specifically, the flexible interval pricing of retailers is modeled as a series of binary revenue constraints to influence the DSO's centralized economic dispatch decisions, where the time-varying distribution locational marginal price is adopted to settle energy activities at different locations over the time horizon. Due to the uncertain power flow path during the coordinated decision-making process, we proposed a general undirected second-order cone-based AC radial power flow model and provided sufficient conditions to ensure its exactness. Also, we applied a series of approximation and relaxation techniques to transform the bi-level mixed-integer quadratic framework with highly discrete induced domains into a solvable mixed-integer semidefinite programming problem. It is demonstrated in the case study that the proposed mechanism can not only improve market efficiency but also eliminate market power and the resulting market failures.

Wiesław Tadeusz Wątroba

Artykuł stanowi próbę rewizji dotychczasowej percepcji kategorii pokolenia, sugerującej periodyzację i identyczność przedziałów czasowych przypisywanych kolejnym generacjom. Zawarta w nim analiza porównawcza została oparta na nowym ujęciu pokolenia, wyznaczanym przez procesy społeczne i psychologiczne determinowane wydarzeniami historycznymi i kontekstem ekonomicznym, stymulujące wspólną tożsamość i świadomość pokoleniową, nie zaś na podstawie zbliżonej daty urodzenia. Szczegółowym przedmiotem analizy są różnice, czy raczej transgresje, charakteryzujące najważniejsze wartości pokoleń rezydujących w obrębie tzw. późnego kapitalizmu, tj. jego obecnego ponowoczesnego etapu.

Olim T. Astanakulov, Natalia V. Kuchkovskaya, Patimat S. Bataeva et al.

One of the most important demonstrations of the modern economy is the growing importance of innovation. The innovative process, or the process of technological change is a complex concept encompassing the improvement of products, production processes, raw materials as well as management methods. Therefore, the central  aim of the research is to analyse the innovative processes that contribute to the development of the state economy. To accomplish the objectives, we carried out the calculations to examine the relations between the cost indicators, modelling, correlation and regression analyses. The particularities of business processes in innovative activities of organisations leads to uneven distribution, specific cost structure in the crisis and the traditional situation of an insignificant share of innovation in the financing process. The study presents mathematic model of innovation activities of an enterprise, based on economic indicators of current operations. The object of the research are industrial enterprises. Since an important segment of business processes in innovation is small innovative companies, our task is to develop a methodology for forecasting the number that would be suitable for them. From the findings of our research, we concluded that the models that had been previously developed were more effective at the micro level. Based on the analysis of the distribution of costs between technological, marketing, organisational innovations by types of innovation and economic activities by building an adequate set of statistical models, we have identified the following particularities: the basic internal (directly dependent) and external (indirectly affecting) factors that affect the selected performance characteristics.

Siwar Jendoubi, Arnaud Martin

The Viral Marketing is a relatively new form of marketing that exploits social networks to promote a brand, a product, etc. The idea behind it is to find a set of influencers on the network that can trigger a large cascade of propagation and adoptions. In this paper, we will introduce an evidential opinion-based influence maximization model for viral marketing. Besides, our approach tackles three opinions based scenarios for viral marketing in the real world. The first scenario concerns influencers who have a positive opinion about the product. The second scenario deals with influencers who have a positive opinion about the product and produce effects on users who also have a positive opinion. The third scenario involves influence users who have a positive opinion about the product and produce effects on the negative opinion of other users concerning the product in question. Next, we proposed six influence measures, two for each scenario. We also use an influence maximization model that the set of detected influencers for each scenario. Finally, we show the performance of the proposed model with each influence measure through some experiments conducted on a generated dataset and a real world dataset collected from Twitter.

Neleen Leslie-Piper, Petula Senior

This study explores generational differences in the antecedents of brand loyalty in the carbonated beverage category. Eight loyalty dimensions were examined across three generational cohorts: Millennials, Generation X and Baby Boomers. Results indicate partial support for the study hypothesis. Significant generational differences were only observed for some loyalty dimensions and in most of those cases, Baby Boomers recorded significantly higher scores than Millennials but were not significantly different than other groups. There were also very few differences between Millennials and Generation X.

Sayantari Ghosh, Saumik Bhattacharya, Kumar Gaurav et al.

By now, Internet word-of-mouth marketing has established its importance for almost every kind of products. When word-of-mouth spread of a marketing campaign goes viral, the success of its strategy has been proved to be path-breaking for the firms. The current study is designed to extend knowledge about customer response to these campaigns, and is focused on the motivations that lead them to different responses. Primary goal of this study is to investigate the reasons that drive this dynamics and to generate a justified theoretical framework of diffusion dynamics of viral marketing campaigns. A rigorous analysis of data obtained through a questionnaire-based survey helped us to understand how people, who are from different age group, sex and locations, define and evaluate the encounter with a referral campaign online, in similar and unique logical ways. The key finding was a conceptual framework of customer motivation which in turn dictates the dynamics of the campaign. We have identified important themes related to customer motives, like significance of: incentives and ease, inherent forgetting, reminders from peers compared to company's remarketing mails, trust and brand value etc. Drawing an analogy with differential equation-based models of infectious disease spread, this paper further provides some initial evidence that participation in viral marketing campaigns has several consumer related dynamical factors which can be incorporated in an epidemiological model for mathematical treatment, to indicate key operational factors in ensuring an effective spread of the marketing campaign.