Marketing Scenarios Research Articles

A Review of Marketing Strategy in Internet Marketing

It is a company's entire strategy for attracting and converting potential customers into buyers ofits products or services. In addition to the company's value proposition and core brand message, amarketing plan includes information on the demographics of the target audience. This paper showintroduction of marketing, internet strategy, internet marketing scenario, market strategy in neweconomy firm.

Dynamic path for green product development: A game-theoretic analysis of product-process innovation with supply chain collaboration

Two contrasting paths are embraced within the practice of green product development: The first involves market entry with high-quality products in the initial phase, followed by a gradual release of mass-market products at reduced prices. The second entails entering the market with low-quality products, followed by step-by-step improvements in quality. The decision-making on path selection is divided into two stages: in the first stage, firms choose green product technologies, and in the second stage, they determine the path for green product development based on the selected technologies. Our research findings highlight the crucial role of efficiency-cost ratios in product-process innovation for green product development. Equilibriums are only achievable when efficiency-cost ratios are relatively low. Given the singular impact of component cost on profit, the path for process innovation consistently trends downward, whereas the path for product innovation can either descend or ascend. Collaboration positively impacts the conditions for equilibrium existence, making it more attainable. When the manufacturer’s efficiency-cost ratio for product innovation is low, collaboration can transition the path from a descending trend to an ascending one, and vice versa. The selection of appropriate technological parameters is important for achieving a win–win relationship between the environment and profitability. Additionally, we have expanded our models to include competition and marketing scenarios. We find that competition primarily influences green product development by altering the motivation for path selection. Marketing and product-process innovation demonstrate a complementary relationship.

An Examination of Farmers Engagement in Assam’s Rural Periodic Markets

The agricultural marketing scenario of Assam is having some distinct features due to its topographicalfactors. Several issues including intensity of flood etc., makes the agricultural marketing process achallenging task for the farmers as well as the other stakeholders. Often, it appears as a discouraging factorfor the farmers to produce certain crops because of issues related to storage and marketing. Primary marketsare the first connecting link between the producer and buyer of agricultural commodities. Thus theseavenues play a crucial role in providing remunerative return or a means of livelihood to the growers. Thereare mainly three major players in the agricultural marketing scenario of Assam. These are the periodicmarkets, daily markets and mobile markets. Rural periodic markets occupy a significant place for a state likeAssam, where 75 percent of the populations are dependent on agriculture for living directly as well asindirectly. More than 80 percent of the farmers are marginal or small in terms of land holding status. Due tosmall amount of disposable surplus, primary markets are the major avenues for disposal of their produces.Apart from livelihood creation, periodic markets also help in the process of value addition of agriculturecommodities by providing scope for forward and backward linkages for the farmers. In this paper attempt ismade to analyze farmer’s participation in the periodic market of Assam. The study is carried out in theSonitpur district of Assam. The work is primarily descriptive in nature. Primary and secondary data wereused for the study. Both qualitative and quantitative approaches were followed to collect the desiredinformation. It was observed that primary markets are the major avenues for disposal of agricultural surplus.The prevalent prices of primary market, distance to the nearest market, volume of marketable surplus etc.,influences the marketing decision of the growers. The study suggest for solving several issues for creating aconducive marketing platform for the benefits of the growers.

Managing the Dual Effect of Virtual Influencers: Examining Benefits to Brands and Drawbacks for Consumers

Today's marketing scenario is evolving, and brands use virtual influencers to promote their products and services. The following research paper talks about the dual role of virtual influencers. This study investigates the benefits the virtual influencers offer the brand and potential consumer drawbacks. In this paper, we have taken "Kyra", a domestic influencer, and "lil Mcquela", an international influencer. We have compared both influencers and found out the positive impact they create for the brands and the negative impact they create towards the consumers.

Digital Marketing in Bangladesh during the COVID-19

The COVID-19 pandemic has severely devitalized the wheels of the global economy. As a part of the global economy, Bangladesh has also faced the debilitating effects of a worldwide economic shutdown. Financial, trade and commerce, economic, banking, agricultural, and industrial – all the prolific sectors seem to be heavily affected by deadly clutches of the COVID-19 pandemic both locally and globally. However, a different scenario has been observed in the digital marketing sectors around the world. Since the novel coronavirus is highly contagious and deadly and spreads out mostly in physical contact, traditional marketing, sales, shopping, and business have started debilitating from its beginning in 2020. As a consequence, online sales and digital transformation have dramatically been accelerated in Bangladesh in recent times. Though the digital marketing sector of Bangladesh is still in its infancy, our country has experienced a revolutionary rise in digital marketing due to the COVID-19 pandemic. That is, this deadly virus has shown us that this sector has huge prospects and prosperity in flourishing our enterprises and businesses through digitalization and the assistance of the ICT industry. This study aims at presenting the current scenario of digital marketing of Bangladesh amidst the COVID-19 pandemic and pointing out the challenges and drawbacks in this sector. Findings suggest that immediate policy initiatives be taken to develop the digital marketing sector of Bangladesh.

Relationship between time pressure and consumers' impulsive buying—Role of perceived value and emotions

Live-streaming e-commerce has become one of the mainstream marketing scenarios, attracting the attention of consumers and the academic community. In live-streaming e-commerce, retailers often use limited-time sales to induce a sense of urgency, prompting consumers to make impromptu purchase decisions. However, existing studies show contradictory results regarding the effectiveness and underlying mechanism of this marketing method. This study empirically investigates the relationship between time pressure and impulsive buying, including affective and cognitive aspects, using the Stimulus-Organism-Response (SOR) and Schachter-Singer (SST) theories. The results suggest that time pressure has a positive relationship with impulsive buying, with an affective rather than cognitive focus. Moreover, the relationship between time pressure and affective (vs. cognitive) impulsive buying is mediated by perceived value. Positive emotions positively moderate, while negative emotions negatively moderate, the relationship between time pressure and affective impulsive buying. This study enhances the understanding of how consumers make purchase decisions under time pressure in live e-commerce scenarios.

The Influence of Service Quality and Brand Image on Mixue Purchase Decisions in Yogyakarta

In this study, it was found that service quality and brand image both exert a positive and significant influence on the purchasing decisions of Mixue products in Yogyakarta. Furthermore, when analyzed together, service quality and brand image collectively hold a significant sway over Mixue purchasing decisions within the city. The research results align with prior studies in the field, emphasizing the importance of service quality as a dynamic factor that can meet or exceed customer expectations. Moreover, brand image plays a crucial role in consumer decision-making, as it reflects the associations and perceptions consumers have about a particular brand. The consistency of these findings across various studies underscores their relevance and applicability in real-world marketing scenarios. These insights are valuable for businesses, especially those in the culinary industry, as they highlight the significance of offering high-quality service and building a strong brand image to attract and retain customers. Understanding the interplay between service quality, brand image, and purchasing decisions can aid businesses in developing effective marketing strategies to thrive in a competitive marketplace. In conclusion, this research contributes to the body of knowledge in marketing management and provides practical guidance for businesses aiming to navigate the ever-changing landscape of consumer behavior. By adapting to these insights, companies can position themselves strategically to succeed in the market and win the competition.

Modelling consumers' choice of novel food.

A variety of approaches to reducing the environmental impact of food production and consumption are being explored including technological solutions, such as food produced via biotechnological processes. However, the development of these technologies requires significant upfront investment and consumer acceptance is not guaranteed. The purpose of this research is to develop a system dynamics model to forecast demand, under multiple marketing and quality scenarios, for foods produced via novel technologies, using cellular agriculture as a case study. The model considers consumer heterogeneity, product awareness, word of mouth marketing (WOM), in-store marketing options, pricing options and product utility to estimate diffusion rates and market penetration. To our knowledge, there is no demand forecasting model available for food produced via novel technologies which relies on purchase intention data and incorporates all these factors. Therefore, this research closes a critical gap for that industry. Ultimately, the model shows that price and the consumers' utility for the product drives the final demand regardless of marketing scenario. Further, the rate of diffusion was highest when product samples are provided in store for all scenarios except when product utility is low and the product price is high. Model results suggest that market saturation was reached within the 32-week trial period when the price of the cellular agriculture product was the same as a traditional product but not when the price was double that of traditional meat. Given the lack of available trial data, the model scenarios should be considered a prior probability which should be refined as more data becomes available.

Implementation Path of Machine Learning in Intelligent Marketing Scenarios of Commercial Banks

This paper takes commercial banks' intelligent marketing scenario as the entry point and introduces machine learning into the intelligent marketing scenario. It introduces the range of application and implementation path of machine learning in commercial banks' intelligent marketing solutions, discusses the possible problems and methods in the process of model construction, and gives empirical analysis of simulating scenarios. Emphasis is placed on developing effective marketing strategies and adjusting marketing strategies based on the results of model deployment monitoring to establish a complete intelligent marketing system and closed-loop process. It provides reference for commercial banks to improve marketing response rate and realize digital operation.

A Systematic Review of the Influencing Factors of Sharing Economy Platform

With the rise of sharing economy in recent years in China, the study of value co-creation in the context of sharing economy has begun to develop. Although the number of literature is relatively limited, it is the hot spot and trend of research and development in China. Nowadays, the research in this field has gradually expanded from the related theoretical concept of value co-creation to practical marketing scenarios such as consumer service experience, service innovation, and sharing economy. At the same time, the application research gradually tends to customer experience, customer value, and other customer perspective research. Start from “value co-creation and service leading logic” to “Customer participation, satisfaction, and loyalty” and then to the direction of “service innovation and service quality” evolution. Nowadays, the research trend of value co-creation is based on the basic theory of value co-creation and service-oriented logic.

The influence of communication language on purchase intention in consumer contexts: the mediating effects of presence and arousal

AbstractPanoramic visual, tactile, and auditory interactions have been widely used to create scene-based immersive experiences to enhance consumer experience and stimulate emotional responses, thereby increasing purchase intentions. Guided by scene marketing theory and the archetypal theory of mind-flow experience, this article introduces the concepts of presence and emotional arousal to examine how communication language causes emotional fluctuations in potential consumers, leading to purchase intentions. Therefore, from the interaction experience of “external perception - scene language” and “internal sensing - communication language”, the dual chain of mediation of presence perception and emotional arousal is selected to construct a consumer. The results reveal that the pathway of consumers’ purchase intentions is not always the same in the context of consumer language perception. In addition, the results demonstrate that the vividness and richness of the presentation of scene language in a consumer language perception context have positively influenced the relationship between communication language and presence perception. Compared to the direct effect on purchase intention, communication language tends to have an indirect positive effect on consumers’ purchase intention through the single mediation of presence perception and the chain mediation of emotional arousal. The increasing prevalence of interactive linguistic experiences, where emotional arousal has become an essential trigger for consumers’ purchase intentions, is an important representation of the specificity and complexity of consumer language elements. Thus, this research provides crucial theoretical guidance for the design of immersive experiential marketing and linguistic scenarios.

Research on Commercial Banks’ Construction of New Marketing Scenarios under Financial Technology

Commercial banks’ financial services have ushered in new changes with the in-depth development of Internet technology and its close integration with financial services. Finance no longer exists independently in people’s lives but relies on Internet+ to address every need in users’ lives. The pain points of services are embedded in many life scenarios, providing scenario-based financial services seamlessly connected with customers’ production and life, and more easily meeting customers’ fragmented needs everywhere. Further from the macro and micro levels, analyze the construction of commercial banks’ marketing scenarios in Internet financial technology. On this basis, this paper puts forward strategic suggestions for commercial banks in the context of Internet finance. After clarifying the significant business value of Internet finance, scenario-based construction effectively promotes the core business of commercial banks’ strategic transformation.

Micro-Influencer Recommendation by Multi-Perspective Account Representation Learning

Influencer marketing is emerging as a new marketing method, changing the marketing strategies of brands profoundly. In order to help brands to find suitable micro-influencers as marketing partners, micro-influencer recommendation is regarded as an indispensable part of influencer marketing. However, previous works only focus on modeling the individual image of brands/micro-influencers, which is insufficient to represent the characteristics of brands/micro-influencers over the marketing scenarios. In this case, we propose a micro-influencer ranking joint learning framework which models brands/micro-influencers from the perspective of individual image, target audiences, and cooperation preferences. Specifically, to model accounts' individual image, we extract topics information and images semantic information from historical content information, and fuse them to learn the account content representation. We introduce target audiences as a new kind of marketing role into micro-influencer recommendation, in which audiences information of brand/micro-influencer is leveraged to learn the multi-modal account audiences representation. Afterwards, we build the attribute co-occurrence graph network to mine cooperation preferences from social media interaction information. Based on account attributes, the cooperation preferences between brands and micro-influencers are refined to attributes' co-occurrence information. The attribute node embeddings learned in the attribute co-occurrence graph network are further utilized to construct the account attribute representation. Finally, the global ranking function is designed to generate ranking scores for all brand-micro-influencer pairs from the three perspectives jointly. The extensive experiments on a publicly available dataset demonstrate the effectiveness of our proposed model over the state-of-the-art methods.

Artificial Intelligence: How it is Changing the Marketing Scenario?

Artificial Intelligence: How it is Changing the Marketing Scenario?

Innovation in Rural Marketing

Abstract: The aim of this research is to study the current scenario of Rural Marketing in India, the rural market presents with its various opportunities and challenges, given how diversely populated the rural consumers in India are. The rural market consists of 83.3 crore people and this is what attracts marketers to enter in this market. To market in the territory of rural marketing cqorporations must understand the rural consumer. There is a shift incoming from urban to the rural marketing as the development and levels of literacy and awareness among the rural consumers is rising and these consumers want value for their money. Marketers when catering to rural consumers need to connect with them and also undertake demonstrations for the better understanding of the rural people. Many innovations in the strategy to market into the rural markets have been undertaken in the past years. This paper aims to understand these innovations and strategies and to understand the rural consumer of India. The future of rural marketing and the development in rural areas is promising in development of rural economies and for the people living in these rural areas a better life.

9 Strategically Supplementing Yearling Cattle on Cool Season Pasture: Implications for Cattle Performance and Return to Management

Abstract The cattle industry and its associated markets are inherently volatile, leading producers to search for more economically sustainable production practices. Supplementation with high protein feed increases yearling gain. However, strategically supplementing in the latter half of the grazing season, as forage quality declines, could provide a more economical increase in gain and return to management. Therefore, a three-year experiment was conducted at the High Plains Agriculture Laboratory, in Sidney, NE. The effects of strategically supplementing dry distillers grains (DDG) on yearling cattle performance and return to management were compared among a variety of economic conditions. Yearlings (313±46 kg) were stocked at 4.3 ha/animal on crested wheatgrass pastures for an average of 112 days beginning in mid-May. They were supplemented either throughout the entire period (FULL), only during the latter part (STRAT), or not at all (CONT) (n = 4 reps/treatment in years 1 and 2, 3 reps/treatment in year 3). Supplemented yearlings received 1.59 kg of DDGs 6 days/week. On average, CP (%DM) of crested wheatgrass declined from 10.2 (May) to 6.8 (September), while IVDMD (%DM) declined from 51 (May) to 37 (September). There were no significant (P > 0.53) experimental year and treatment effects for cattle performance. However, there was an effect (P < 0.01) of treatment and year on ADG and final body weight. On average, non-supplemented yearlings had an average daily gain (ADG) of 0.68 kg/d. Providing supplement increased ADG by 0.23 kg/d (P < 0.01). Performance did not differ (P < 0.01) between STRAT and FULL, despite STRAT receiving nearly half (54%) the amount of supplement. Cattle and DDG prices from the previous decade (2012–2021) were applied to experimental data to create various potential marketing scenarios. Return to management was calculated as the return to labor costs for providing supplement. On average, FULL returned $14.96 more and STRAT returned $32.21 more per yearling than CONT. Within economic year, return of STRAT was greater (P ≤ 0.05) than CONT in all years except 2012, 2019 and 2021. Return of FULL was greater (P ≤ 0.05) than CONT in all years except 2012, 2018, 2019, and 2021. Numerically, STRAT was always greater than CONT and FULL. Higher DDG prices coupled with lower live cattle prices caused less return in those years. Breakeven DDG costs for STRAT averaged $530/909 kg and ranged from $268/909 kg to $822/909 kg. Applying a $0.30/yearling/day labor cost, the average breakeven for this strategy declines to $345/909 kg of DDG. These results suggest that strategically supplementing DDG as forage quality of crested wheatgrass declines in the summer will provide similar yearling performance to supplementing throughout the entire grazing season. Strategic supplementation also appears to have a high likelihood increasing return to management.

Enterprise Precision Marketing Effectiveness Model Based on Data Mining Technology

Due to the explosive growth of massive consumption data, the traditional marketing model of enterprises has become stretched. The rapid advancement of data mining technology has given new impetus to the innovation of the marketing strategies of enterprises, promoting the progressive transformation of enterprises from traditional passive marketing to precise and refined marketing. Data mining technology’s basic task is to analyze data, acquire insight into cause and effect, and then predict the future. As a result, the technology is coupled with the enterprises’ marketing activities, and a precise marketing model is built using big data consumption. This will aid in the comprehensive and three-dimensional description of customers, as well as the analysis of potential customers’ attributes, to give a scientific basis for the formulation and implementation of precise data-driven decision-making for enterprises. As a result, our study enhances and optimizes the K-means algorithm in combination with the artificial bee colony algorithm aiming at fixing the issue that the K-means algorithm is sensitive to cluster center initialization and improving the enterprise precision marketing model’s clustering performance. In the precise marketing scenario of the telecom business, the improved K-means clustering model is utilized to realize the analysis and prediction of telecom customers, as well as to carry out precise marketing based on the predicted findings. Finally, the optimized K-means clustering algorithm can objectively and comprehensively reflect the characteristics of telecom customer value segmentation, efficiently mining future clients and preventing blind marketing by enterprises, based on the model's actual verification results. Simultaneously, it provides substantial data support for telecom enterprises’ resource planning, as well as pointing out the next step in increasing market share.

Research Hotspot and Prospect of Artificial Intelligence in Marketing in China——Visual Analysis Based on CiteSpace

The artificial intelligence industry has developed rapidly and is now being used in a number of areas of integration, such as healthcare, education and agriculture. A comprehensive understanding of the research hotspots and prospect of artificial intelligence in marketing will be of great value to scholars and companies in their marketing work. Using the CNKI database as the data source, this study adopts a quantitative analysis research method and uses the visualization software CiteSpace 5.8 R3 to comb through the domestic AI marketing-related literature published during the decade 2001-2021, draw up a scientific knowledge map, and analyze it in terms of research hotspots, themes and evolutionary trends respectively. The results show that "big data", "precision marketing", "digital marketing", "advertising" and "smart marketing" are the hot keywords; The research focuses on five modules: "Smart Advertising", "Smart Media Marketing", "Precision Marketing", "New Retail" and "Short Video Marketing". Further analysis reveals that future research could start with AI marketing scenarios, data and carriers, with an eye towards deeper exploration of content scenarios, user profiling, new media marketing and other more segmented areas.

An Experimental Study on Anchoring Effect of Consumers' Price Judgment Based on Consumers' Experiencing Scenes.

Consumers are prone to cognitive biases in decision-making due to the impact of time restrictions, specific environment, and project inducements in the process of experience. Compared with traditional marketing scenarios, it is easy to bias decision makers due to the existence of anchor information. Research on anchoring effect focuses on psychology, economics, law, and medicine instead of the price judgment of consumers. This article uses experimental research to explore the existence and influencing factors of anchoring effect when consumers judge and estimate the price of a product in experiencing scenes. In this article, the hypothesis is that anchoring effect exists and is influenced by factors including anchor value, gender, emotion, personality, knowledge and skill, time pressure, early warning indication, cognitive need, and self-confidence level under external and internal anchor conditions. Subjects judged and estimated different prices after product experience through the design of different decision-making scenarios of external (high anchors and low anchors) and internal anchors, and finally, the anchoring index (AI) and the mean skew index were used to calculate the anchoring effect. The experimental results showed that consumers were affected by anchoring effect when making price judgment in experiencing scenes. In addition to the factors of time pressure and self-confidence level, gender, personality, knowledge, and skill all had a significant influence on anchoring effect under external anchor conditions. Finally, this article provides advice for enterprise marketing planners including setting reasonable anchor values, highlighting the design of experiencing scenes, and developing differentiation strategies.

A Progressive Approach for Neighboring Geosocial Communities Search Over Large Spatial Graphs

Searching for neighbors for a query node in a spatial network is a fundamental problem and has been extensively investigated. However, most existing works focus only on the node level when conducting such a query and rarely pay attention to the social relations among the neighbors. We argue that a user, in some cases, is more likely to engage in some activities collectively, i.e., going to the bar with friends rather than alone. For this reason, we consider the neighbor searching problem at a community level in this paper and examine a new problem: Neighboring Geosocial Communities Search (NGCS) over large spatial graphs. Specifically, given a parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> and query node <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula> , we aim to find the top- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> nearest communities for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula> . Moreover, in each returned community, nodes have cohesive relations with each other and are covered by a minimum covering circle (MCC) whose radius is less than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula> . It is obvious that the NGCS problem finds its standard applications in marketing and other scenarios but it is very challenging for large spatial graphs because it requires detecting all qualified cohesive user communities. Therefore, in this paper, we adopt a local search approach to reduce the difficulty. The introduced algorithm finds the top- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> neighboring geo-social communities through a progressive search in the graph without thoroughly examining the graph. Analyses show that the complexity of the algorithm is decreased by an order of magnitude. Extensive experiments on real social networks confirm the superiority and effectiveness of our solutions.