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Hwang, Seongbeom, and Yuna Lee. "Identifying customer priority for new products in target marketing: Using RFM model and TextRank." Innovative Marketing 17, no. 2 (June 11, 2021): 125–36. http://dx.doi.org/10.21511/im.17(2).2021.12.
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Target marketing is a key strategy used to increase the revenue. Among many methods that identify prospective customers, the recency, frequency, monetary value (RFM) model is considered the most accurate. However, no RFM study has focused on prospects for new product launches. This study addresses this gap by using website access data to identify prospects for new products, thereby extending RFM models to include website-specific weights. An RF model, built using frequency and recency information from website access data of customers, and an RwF model, built by adding website weights to frequency of access, were developed. A TextRank algorithm was used to analyze weights for each website based on the access frequency, thus defining the weights in the RwF model. South Korean mobile users’ website access data between May 1 and July 31, 2020 were used to validate the models. Through a significant lift curve, the results indicate that the models are highly effective in prioritizing customers for target marketing of new products. In particular, the RwF model, reflecting website-specific weights, showed a customer response rate of more than 30% among the top 10% customers. The findings extend the RFM literature beyond purchase history and enable practitioners to find target customers without a purchase history.
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Bumbaca, Federico (Rico), Sanjog Misra, and Peter E. Rossi. "Scalable Target Marketing: Distributed Markov Chain Monte Carlo for Bayesian Hierarchical Models." Journal of Marketing Research 57, no. 6 (October 1, 2020): 999–1018. http://dx.doi.org/10.1177/0022243720952410.
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Many problems in marketing and economics require firms to make targeted consumer-specific decisions, but current estimation methods are not designed to scale to the size of modern data sets. In this article, the authors propose a new algorithm to close that gap. They develop a distributed Markov chain Monte Carlo (MCMC) algorithm for estimating Bayesian hierarchical models when the number of consumers is very large and the objects of interest are the consumer-level parameters. The two-stage and embarrassingly parallel algorithm is asymptotically unbiased in the number of consumers, retains the flexibility of a standard MCMC algorithm, and is easy to implement. The authors show that the distributed MCMC algorithm is faster and more efficient than a single-machine algorithm by at least an order of magnitude. They illustrate the approach with simulations with up to 100 million consumers, and with data on 1,088,310 donors to a charitable organization. The algorithm enables an increase of between $1.6 million and $4.6 million in additional donations when applied to a large modern-size data set compared with a typical-size data set.
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Šoltés, Erik, Janka Táborecká-Petrovičová, and Romana Šipoldová. "Targeting of Online Advertising Using Logistic Regression." E+M Ekonomie a Management 23, no. 4 (December 1, 2020): 197–214. http://dx.doi.org/10.15240/tul/001/2020-4-013.
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Recently, the internet became the dominant medium in marketing and comparing the development of expenditures into advertising indicates the dominance of online advertising will be inevitably stronger. Internet advertising compared to traditional media advertising has plenty of advantages hence online marketing exhibits a huge expansion in recent era. To fully utilize the potential of online marketing, it is necessary to effectively target activities of relevant internet users with the real presumption they will purchase promoted products or services. The paper is focused on demographic targeting by the mean of logistic regression models. Explanatory variables in presented application are arising from affinities of internet webpages visited by particular users and areas of their interests that are identified from their online behaviour. Our paper provides binomial logistic mode whose role is to predict the gender of internet user and multinomial logistic model constructed for the estimation of age category the user may be assigned to. The only variables exploited in the model by the mean of stepwise regression are variables with significant influence. The impact of particular factors is quantified via odds ratios that are used for the identification of areas of interests typical for women, men and for considered age categories. The paper demonstrates how it is possible to utilise estimated logistic models for the estimation of probabilities that the internet user is from a target group – in our case, women aged 25–44 years old. Prediction quality of models is assessed by the set of classification measures arising from confusion matrix that is generally acceptable in machine learning. Presented analyses are conducted in statistical software SAS Enterprise Guide on data provided from the real advertising campaign. More than 160,000 statistical units enabled the confirm results gained on training dataset of a relatively huge validation dataset.
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Azmi, Nor Jijidiana, Radzuwan Rashid, Bahtiar Mohamad, Mairas Abd Rahman, and Zulkarnian Ahmad. "Student Athletes’ Perception of Female Models in Sports Advertisements." Asian Social Science 13, no. 10 (September 27, 2017): 120. http://dx.doi.org/10.5539/ass.v13n10p120.
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Women in advertisements are no longer portrayed as having traditional roles. Instead, they are portrayed as dominant and powerful. This new marketing strategy is hoped to be more persuasive in reaching the target audience, especially the female buyers, thus increasing the sales in the market. This qualitative research aims to explore student-athletes’ views on the portrayal of female models in sports advertisements. A focus group interview involving three female student-athletes was conducted. A total of 20 advertisements, which portray female models, from five leading sports brands were used as stimuli for the focus group. The findings reveal that the participants have different perceptions towards the body image and athletic values of the advertisements, despite having the same background as a student athlete. Sexual appeal, the portrayal of healthy and positive body image, and strong athletic ability are among the functions of the female models in the advertisements, as perceived by the participants.
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Ascarza, Eva. "Retention Futility: Targeting High-Risk Customers Might be Ineffective." Journal of Marketing Research 55, no. 1 (February 2018): 80–98. http://dx.doi.org/10.1509/jmr.16.0163.
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Companies in a variety of sectors are increasingly managing customer churn proactively, generally by detecting customers at the highest risk of churning and targeting retention efforts towards them. While there is a vast literature on developing churn prediction models that identify customers at the highest risk of churning, no research has investigated whether it is indeed optimal to target those individuals. Combining two field experiments with machine learning techniques, the author demonstrates that customers identified as having the highest risk of churning are not necessarily the best targets for proactive churn programs. This finding is not only contrary to common wisdom but also suggests that retention programs are sometimes futile not because firms offer the wrong incentives but because they do not apply the right targeting rules. Accordingly, firms should focus their modeling efforts on identifying the observed heterogeneity in response to the intervention and to target customers on the basis of their sensitivity to the intervention, regardless of their risk of churning. This approach is empirically demonstrated to be significantly more effective than the standard practice of targeting customers with the highest risk of churning. More broadly, the author encourages firms and researchers using randomized trials (or A/B tests) to look beyond the average effect of interventions and leverage the observed heterogeneity in customers' response to select customer targets.
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Wittink, Dick R. "Econometric Models for Marketing Decisions." Journal of Marketing Research 42, no. 1 (February 2005): 1–3. http://dx.doi.org/10.1509/jmkr.42.1.1.56893.
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Pachali, Max J., Peter Kurz, and Thomas Otter. "How to generalize from a hierarchical model?" Quantitative Marketing and Economics 18, no. 4 (May 17, 2020): 343–80. http://dx.doi.org/10.1007/s11129-020-09226-7.
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Abstract Models of consumer heterogeneity play a pivotal role in marketing and economics, specifically in random coefficient or mixed logit models for aggregate or individual data and in hierarchical Bayesian models of heterogeneity. In applications, the inferential target often pertains to a population beyond the sample of consumers providing the data. For example, optimal prices inferred from the model are expected to be optimal in the population and not just optimal in the observed, finite sample. The population model, random coefficients distribution, or heterogeneity distribution is the natural and correct basis for generalizations from the observed sample to the market. However, in many if not most applications standard heterogeneity models such as the multivariate normal, or its finite mixture generalization lack economic rationality because they support regions of the parameter space that contradict basic economic arguments. For example, such population distributions support positive price coefficients or preferences against fuel-efficiency in cars. Likely as a consequence, it is common practice in applied research to rely on the collection of individual level mean estimates of consumers as a representation of population preferences that often substantially reduce the support for parameters in violation of economic expectations. To overcome the choice between relying on a mis-specified heterogeneity distribution and the collection of individual level means that fail to measure heterogeneity consistently, we develop an approach that facilitates the formulation of more economically faithful heterogeneity distributions based on prior constraints. In the common situation where the heterogeneity distribution comprises both constrained and unconstrained coefficients (e.g., brand and price coefficients), the choice of subjective prior parameters is an unresolved challenge. As a solution to this problem, we propose a marginal-conditional decomposition that avoids the conflict between wanting to be more informative about constrained parameters and only weakly informative about unconstrained parameters. We show how to efficiently sample from the implied posterior and illustrate the merits of our prior as well as the drawbacks of relying on means of individual level preferences for decision-making in two illustrative case studies.
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Ochoa, Carlos, and Josep Miquel Porcar. "Modeling the effect of quota sampling on online fieldwork efficiency: An analysis of the connection between uncertainty and sample usage." International Journal of Market Research 60, no. 5 (June 1, 2018): 484–501. http://dx.doi.org/10.1177/1470785318779545.
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Market, Opinion and Social Research is increasingly relying on non-probabilistic online panels as data sources and quota sampling as the default sampling method. Quota sampling applied to online panels requires discarding participants to ensure that the final sample match the target population distribution. This article analyzes how different features of a quota sample (such as the sample size, number, and types of quotas) impact the number of participants that must be discarded during the data collection (fieldwork efficiency). Both analytical models and simulation have been used for this purpose. Finally, we show how uncertainty about participants relates to fieldwork efficiency, providing practical recommendations in pursuing this goal.
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Ignatieva, E. V., I. V. Yartseva, Z. S. Shprakh, A. P. Kolpaksidi, M. V. Dmitrieva, A. V. Lantsova, L. L. Nikolaeva, and I. R. Prosalkova. "Quantitative determination of the N-glycoside derivative of substituted indolo[2,3a]carbazole in innovative dosage forms." Russian Journal of Biotherapy 21, no. 3 (October 31, 2022): 61–71. http://dx.doi.org/10.17650/1726-9784-2022-21-3-61-71.
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Background. A glycoside derivative of indolocarbazole LHS-1269, one of the new drugs selectively affecting tumors, which was first synthesized at the N.N. Blokhin National Medical-Research Center of Oncology of the Ministry of Health of Russia, is of particular scientific interest. Experimental studies demonstrated a multi-target mechanism of action of this compound. LHS-1269 interacts with several intracellular targets and induces various pathways of cell death. Several innovative models of the dosage forms were designed to achieve the highest antitumor activity of the compound and to perform further preclinical studies.Aim. To develop the methods for the quantitative determination of LHS-1269 in pharmaceutical compositions proposed as a result of the search for the optimal dosage form.Materials and methods. The study analyzed the spectrophotometric characteristics of LHS-1269 solutions in dimethylformamide, dimethylsulfoxide (DMSO) and in the mixture of solvents DMSO–ethyl alcohol, as well as electronic absorption spectra of the excipients in the mixture of solvents DMSO–ethyl alcohol. Spectrophotometric measurements were performed on a Cary 100 spectrophotometer (Varian, Inc., Australia) in the wavelength range from 200 to 500 nm. The standard sample is the substance LHS-1269 (N.N. Blokhin Oncology Research Center of the Ministry of Health of Russia).Results. The carried out studies showed that LHS-1269 solutions in dimethylformamide, DMSO and mixture of DMSO– ethyl alcohol are suitable for spectrophotometric measurements. Several variants of the methodology for the assay of LHS-1269 in various dosage form models that differ in the content of the active substance and the excipients composition have been developed: LHS-1269 concentrate for solution for injection and infusion; lyophilisate for solution for injection; liposomal lyophilisate for dispersion for injection.Conclusion. Techniques for the assay of LHS-1269 in dosage form models have been developed. It has been shown that the developed techniques are applicable for LHS-1269 quantitative determination in innovative dosage forms containing polymeric low molecular weightsolubilizers, lipids, cholesterol, mono- or oligosaccharides as excipients.
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Quaye, Emmanuel Silva, and Yvonne Saini. "Kaya FM: the challenge of an afropolitan positioning." Emerald Emerging Markets Case Studies 11, no. 2 (June 25, 2021): 1–35. http://dx.doi.org/10.1108/eemcs-06-2020-0182.
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Learning outcomes Amongst other things, at the end of this case discussion, the student should be able to: diagnose situational factors that contribute to a brand’s positioning; explore important issues in implementing brand positioning strategies; use relevant models for understanding a firm’s internal and external environments to inform strategic decisions about customers and competition; demonstrate an understanding of target audience; identify the unique attributes of the competition to inform a firm’s positioning and competitive strategy. Case overview/synopsis Kaya FM derives its name from the isiZulu word “ikhaya”, which means “home”. The name reflects the mission of the radio station to provide a home for black South Africans who were denied many opportunities during the apartheid era in South Africa. Kaya FM has been broadcasting since 1997, following the deregulation of the media landscape in South Africa. However, by 2018, the radio landscape has become very challenging. Mainstream advertisers still do not consider Kaya FM as a preferred channel to reach their target audience. Overall, radio listenership is dwindling and advertising sales growth is not encouraging. Greg Maloka, Kaya FM’s station manager is considering how to preserve the station’s unique positioning as it competes with both more dominant stations and new entrants so that Kaya FM can truly be a home for Afropolitans for many years to come. Complexity academic level Honour’s and master’s level, as well as executive education delegates. Supplementary materials Teaching Notes are available for educators only. Subject code CSS 8: Marketing.
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Monti, Alessandro. "Mozart und seine Subskription der drei Klavierkonzerte KV 413-415 von 1783." Jahrbuch für Wirtschaftsgeschichte / Economic History Yearbook 61, no. 2 (November 25, 2020): 297–318. http://dx.doi.org/10.1515/jbwg-2020-0013.
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AbstractThe research on the history of pricing strategies and decisions by companies and individuals has not received much attention up to now. This is surprising, as pricing is the most important profit driver, and thus an inquiry into the historic origins of price-related decisions by the early modern market operators can yield important insights for both historians and current practitioners on successful marketing strategies. The following article contributes to the research on business history by proposing, first of all, a framework for the conceptual definition between a revenue and a price model. Furthermore, it is shown that subscription-based revenue was generated as early as 1617. The revenue model of the subscription – an early antecedent of today’s crowdfunding scheme – will then be covered in detail by investigating the case of Wolfgang Amadeus Mozart’s piano concertos KV 413-415. The influential composer decided to appeal to a broader target group by using a subscription-based pricing scheme for these three piano concertos in 1783. The subscription however was unsuccessful, and the major reason for this failure as well as Mozart’s probable economic reasoning are elaborated. Finally, the rising modern market forc es, that steered the Viennese music market of the late 18th century towards modern*structures, made sure that market operators at that time tried to adapt to these forces by offering modern and innovative revenue and price models, such as highly differentiated, content-based and time-definite subscriptions.
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Mizrach, Bruce. "Target zone models with stochastic realignments: an econometric evaluation." Journal of International Money and Finance 14, no. 5 (October 1995): 641–57. http://dx.doi.org/10.1016/0261-5606(95)00027-c.
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Asafu-Adjaye, John, Edwin Kuh, John W. Neese, and Peter Hollinger. "Structural Sensitivity in Econometric Models." Journal of the Operational Research Society 37, no. 4 (April 1986): 440. http://dx.doi.org/10.2307/2582577.
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Asafu-Adjaye, John. "Structural Sensitivity in Econometric Models." Journal of the Operational Research Society 37, no. 4 (April 1986): 440. http://dx.doi.org/10.1057/jors.1986.77.
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Franses, Philip Hans. "On the Use of Econometric Models for Policy Simulation in Marketing." Journal of Marketing Research 42, no. 1 (February 2005): 4–14. http://dx.doi.org/10.1509/jmkr.42.1.4.56891.
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In this article, the author discusses the properties of useful econometric models for marketing phenomena, with particular attention on models for policy simulations. The author addresses model diagnostics, parameter stability, exogeneity, and the Lucas critique. He also presents the results of a search through the 1998–2003 issues of the Journal of Marketing Research. Finally, the author offers practical guidelines.
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Chintagunta, Pradeep, Philip Hans Franses, and Richard Paap. "Introduction to the special issue on new econometric models in marketing." Journal of Applied Econometrics 24, no. 3 (March 3, 2009): 375–76. http://dx.doi.org/10.1002/jae.1055.
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Wittink, Dick R., Dominique M. Hanssens, Leonard J. Parsons, and Randall L. Schultz. "Market Response Models: Econometric and Time Series Analysis." Journal of Marketing Research 28, no. 2 (May 1991): 246. http://dx.doi.org/10.2307/3172814.
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Prišenk, Jernej, and Jernej Turk. "Assessment of Concept between Rural Development Challenges and Local Food Systems: A Combination between Multi-Criteria Decision Analysis and Econometric Modelling Approach." Sustainability 14, no. 6 (March 16, 2022): 3477. http://dx.doi.org/10.3390/su14063477.
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This study investigates the influence of social, economic, and environmental impacts on the promotion and marketing systems of local food products from mountain areas in Slovenia. These impacts were assessed using an econometric modelling approach. Two econometric models were developed (one for production and one for marketing). The case studies of local food products were selected from Slovenian mountain regions, most of which were from less-favored areas (LFAs). A majority of the selected food commodities were of high quality, with or without protected designations. Data collection was carried out via interviews. Due to production limitation on mountain areas in Slovenia and other constraints in LFAs, the socio-economic and environmental impacts on success of production and marketing systems need to be clarified. These relations present a potential impact on the wider socio-economic development in the region. The empirical results, obtained using an econometric modelling approach, clearly show the importance of encouraging the socio-economic and environmental impacts in ensuring the marketing and production potentials of local food products. The result express good relationships, and cooperation between the actors in the food supply chains contributing to a successful marketing system and production system of local food products (small, average, large) is dependent on the available local labour in mountain rural areas.
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Baltas, George. "Econometric Models for Discrete Choice Analysis of Travel and Tourism Demand." Journal of Travel & Tourism Marketing 21, no. 4 (August 15, 2007): 25–40. http://dx.doi.org/10.1300/j073v21n04_04.
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Andrews, Rick L. "Book Review: Market Response Models: Econometric and Time Series Analysis." Journal of Marketing Research 39, no. 3 (August 2002): 387–88. http://dx.doi.org/10.1509/jmkr.39.3.387.19107.
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Thomas, Arthur M., and Neil Canter. "Financial Benefits of Florida Generic Orange Juice Marketing." Agricultural and Resource Economics Review 38, no. 3 (December 2009): 431–44. http://dx.doi.org/10.1017/s1068280500009679.
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The benefits to Florida orange growers of generic orange juice advertising are assessed using additive, nonlinear, regional econometric models, measuring the impact of category and brand marketing efforts on category demand while controlling for pricing and various other factors. The study shows that generic marketing efforts increased orange juice category demand by 8.3 percent, resulting in increased orange prices and a benefit-to-cost ratio to Florida growers of 3.5 to 1. Branded promotional activity was found to primarily fuel brand switching and pantry-loading, with only modest impacts on overall category demand.
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Fildes, Robert. "Quantitative Forecasting-The State of the Art: Econometric Models." Journal of the Operational Research Society 36, no. 7 (July 1985): 549. http://dx.doi.org/10.2307/2582473.
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Fildes, Robert. "Quantitative Forecasting—the State of the Art: Econometric Models." Journal of the Operational Research Society 36, no. 7 (July 1985): 549–80. http://dx.doi.org/10.1057/jors.1985.99.
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Amoussou, Amour Gbaguidi, and Aristide Medenou. "Application of ARIMA models on Export potential Indicator." African Journal of Applied Statistics 8, no. 2 (July 1, 2021): 1165–80. http://dx.doi.org/10.16929/ajas/2021.1165.263.
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The export potential indicator is designed for countries that aim to support established exports by increasing exports to new or existing target markets, and several studies are being managed using various mathematical model to predict the export values. Here, we propose an econometric model that could be useful to predict the export values. We performed the ARIMA model to evaluate the realized and unrealized export potentials of products. We therefore propose to carry out actions in favor of increasing the export potential.
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Donkers, Bas, Philip Hans Franses, and Peter C. Verhoef. "Selective Sampling for Binary Choice Models." Journal of Marketing Research 40, no. 4 (November 2003): 492–97. http://dx.doi.org/10.1509/jmkr.40.4.492.19395.
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Marketing problems sometimes pertain to the analysis of dichotomous dependent variables, such as “buy” and “not buy” or “respond” and “not respond.” One outcome can strongly outnumber the other, such as when many households do not respond (e.g., to a direct mailing). In such situations, an efficient data-collection strategy is to sample disproportionately more from the smaller group. However, subsequent statistical analysis must account for this sampling strategy. In this article, the authors put forward the econometric method that can correct for the sample selection bias, when this method does not lead to a loss in precision. The authors illustrate the method for synthetic and real-life data and document that reductions of more than 50% in sample sizes can be obtained.
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G.P., Ranjitha, Rai Siddhant Sinha, Augustin Paul, and R. Sai Shiva Jayanth. "How does pandemic force social enterprises to evolve? – A case study of ThankUFoods." Emerald Emerging Markets Case Studies 12, no. 3 (August 16, 2022): 1–21. http://dx.doi.org/10.1108/eemcs-08-2021-0244.
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Learning outcomes After completion of this case, students would be able to understand the challenges faced by social entrepreneurship in a time of pandemic, as well as gain a perspective of the background, history, evolution and the setup of such organizations; appreciate the role of marketing methods in tackling the challenges faced and how the management of such enterprises could use them on the ground; evaluate possible future options/pathways that could be taken in the backdrop of a pandemic and, more importantly, in a developing country context; and apply the elements of social entrepreneurship theory and suggest a way ahead for ThankUfoods (TUF). Case overview/synopsis TUF is a social enterprise that empowers visually and physically challenged people by using while profitably selling food products. Few years of existence, it was facing a major dilemma regarding strategies to continue its existing business and the way forward. Because of the pandemic, the traditional offline business models became redundant on which TUF was heavily dependent. At the same time, TUF had to balance providing support to its employees, staying financially afloat and upholding its parent organization’s core objectives, the India Association for Blind (IAB). IAB was founded to rescue and provide livelihood for specially abled people. TUF was formed as a sister concern that combined charitable work and profit earning to make visually challenged people self-sufficient. At this juncture, the protagonist of the case Mr Abdul Raheem, chief executive officer of TUF and vice president of IAB, approached consultants to chart the way forward. He was forced to explore novel options ranging from conceptual ones, such as setting the right objectives and revisiting mission and vision, to more operational ones, such as venturing into online space, increasing advertisements and achieving breakeven sales. This case study highlights the overall journey of TUF, the underlying constraints, the new challenges faced and the dilemma ahead. Further, it covers the context and challenges peculiar to an emerging market setting. More importantly, it provides a setting for the students to be in the protagonist’s position and ponder – how should a social enterprise functioning in an emerging market function in times of pandemic crises? If it decides to explore novel options, what should be those, how can it proceed, and what to be cautious about. Complexity academic level The target audience for the case study are students from MBA and BBA courses, management trainees who are interested to learn about the challenges social entrepreneurship face at the time of crisis. This case study could be used to explain concepts about social entrepreneurship, brand positioning, e-commerce marketing and decision-making in the time of pandemics/crises. The case is also suitable for senior management personnel who participate in executive education programs. Supplementary materials Teaching notes are available for educators only. Subject code CSS 3: Entrepreneurship
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Raya, Josep Maria. "Evaluating Different Housing Prices: Marketing and Financial Distortions." International Real Estate Review 24, no. 4 (December 31, 2021): 549–76. http://dx.doi.org/10.53383/100330.
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The aim of this paper is to evaluate the importance of housing price. We compare the evolution of three different types of housing prices (list, sale and appraisal prices). The objective is to see the marketing and financial consequences of using each type of housing price. To do this, a dataset of a real estate company and its financial intermediary with all of these types of housing prices is used. We estimate econometric models in which the dependent variables are: price (appraisal, selling or list), mark-up, loan to value and foreclosures. The results show evidence of the consequences of using a specific housing price in terms of inflation calculation, financial assets, and collateral valuation and mortgage default, among others.
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Bapna, S. L. "Using Crop Outlook Information for Timely Marketing Decisions in Government." Vikalpa: The Journal for Decision Makers 11, no. 2 (April 1986): 131–40. http://dx.doi.org/10.1177/0256090919860205.
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Reliable and timely information on crop prospects is not available in India. As a consequence, market planning of procurement, storage and distribution operations, and pricing of foodgrains and other crops is usually based on subjective judgements of the government officials about the crofj prospects; therefore decisions are ad hoc and sub-optimal. This paper outlines an approach which uses econometric models. It is shown that reliable and timely crop outlook information can be obtained much before harvest at a low cost. It is illustrated how use of such information by the agricultural institutions in the government can improve the management of crop supplies and demand more effectively.
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Jia, Fang, and Boli Yang. "Forecasting Volatility of Stock Index: Deep Learning Model with Likelihood-Based Loss Function." Complexity 2021 (February 25, 2021): 1–13. http://dx.doi.org/10.1155/2021/5511802.
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Volatility is widely used in different financial areas, and forecasting the volatility of financial assets can be valuable. In this paper, we use deep neural network (DNN) and long short-term memory (LSTM) model to forecast the volatility of stock index. Most related research studies use distance loss function to train the machine learning models, and they gain two disadvantages. The first one is that they introduce errors when using estimated volatility to be the forecasting target, and the second one is that their models cannot be compared to econometric models fairly. To solve these two problems, we further introduce a likelihood-based loss function to train the deep learning models and test all the models by the likelihood of the test sample. The results show that our deep learning models with likelihood-based loss function can forecast volatility more precisely than the econometric model and the deep learning models with distance loss function, and the LSTM model is the better one in the two deep learning models with likelihood-based loss function.
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Lautman, Martin R., and Koen Pauwels. "Identifying Metrics That Matter: What Are the Real Key Performance Indicators (KPIs) That Drive Consumer Behavior?" GfK Marketing Intelligence Review 5, no. 2 (November 1, 2013): 46–52. http://dx.doi.org/10.2478/gfkmir-2014-0017.
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Abstract Vector auto regression (VAR) is a form of econometric modeling that is receiving increased attention in marketing research applications. It is used to observe whether potentially relevant indicators have a real impact on sales or success factors. Compared with correlation, regression and conjoint techniques, VAR models are superior because they are able to show the impact of changes over time on the basis of real business data. The research shows how VAR models are applied in different marketing settings. VAR models can filter relevant metrics from a whole set of potentially relevant performance indicators and quantify the sales impact of each variable. They further observe lead and lag effects that cannot be tracked when measurement is conducted at a single point in time. Modeling can be performed on competitive brands as well. VAR models also make it possible to test whether the same success factors that drive a category also drive the sales of each of the brands in that category.
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Nakazi, Florence, Immaculate Babirye, Eliud Birachi, and Michael Adrogu Ugen. "Exploring retailer marketing strategies for value added bean products in Kenya." International Food and Agribusiness Management Review 22, no. 5 (September 11, 2019): 675–87. http://dx.doi.org/10.22434/ifamr2018.0073.
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Unlike many other Sub-Saharan African countries, for many years Kenya had comparative advantages in the manufacturing of processed bean products. However, for new competitors intending to join the bean processing industry, little is known about marketing strategies for value added bean products. Using data from 90 retailers in the Nairobi and Kiambu counties in Kenya, a two-step econometric procedure-multivariate probit and Poisson regression models were applied to analyse retailers’ marketing strategy decisions. Findings show that information sources, cost of marketing, supply modalities, price of products, and quantities handled significantly influenced retailers’ marketing strategy choice. Surveyed retailers applied varying marketing strategies to market value added bean products. There is need for prospective retailers to choose an appropriate mix of strategies to penetrate the dynamic market with a number of value added bean products, and promote local consumption of value added bean products.
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Müller, Sven, and Knut Haase. "Local revenue response to service quality: spatial effects in seasonal ticket revenue data." European Journal of Marketing 49, no. 9/10 (September 14, 2015): 1391–416. http://dx.doi.org/10.1108/ejm-10-2013-0531.
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Purpose – This paper aims to consider spatial effects in the analysis of the relationship of revenue and service quality. When firms’ customers are located in spatially dispersed areas, it can be difficult to manage service quality on a geographically small scale because the relative importance of service quality might vary spatially. Moreover, standard approaches discussed so far in the marketing science literature usually neglect spatial effects, such as spatial dependencies (e.g. spatial autocorrelation) and spatial drift (spatial non-stationarity). Design/methodology/approach – The authors propose a comprehensive but intelligible approach based on spatial econometric methods that cover spatial dependencies and spatial drift simultaneously. In particular, they incorporate the spatial expansion method (spatial drift) into spatial econometric models (e.g. spatial lag model). Findings – Using real company data on seasonal ticket revenue (dependent variable) and service quality (independent variables) of a regional public transport service provider, the authors find that the elasticity for the length of the public transport network is between 0.2 and 0.5, whereas the elasticity for the headway is between −0.2 and 0.6, for example. The authors control for several socio-economic, socio-demographic and land-use variables. Practical implications – Based on the empirical findings, the authors show that addressing spatial effects of service data can improve management’s ability to implement programs aimed at enhancing seasonal ticket revenue. Therefore, they derive a spatial revenue response function that enables managers to identify small-scale areas that are most efficient in terms of increasing revenue by service improvement. Originality/value – The paper addresses the need to account for spatial effects in revenue response functions of public transport companies.
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Staudt, Yves, and Joël Wagner. "What policyholder and contract features determine the evolution of non-life insurance customer relationships?" International Journal of Bank Marketing 36, no. 6 (September 3, 2018): 1098–124. http://dx.doi.org/10.1108/ijbm-11-2016-0175.
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Purpose Over the last decade, technological and social trends have significantly influenced the relationship between customers and insurers. New buying patterns, price comparison platforms and the usage of different interaction channels driving single-product purchases and impacting lapses have influenced insurers’ customer portfolios and development. The purpose of this paper is to study the features driving the customer relationship along three areas, namely, customer acquisition, development and retention. Design/methodology/approach After defining 14 related hypotheses, the authors use econometric analyses to quantitatively support these hypotheses in the three areas of interest. The authors build on a large-scale longitudinal data set from a Swiss insurance company covering the period from 2005 to 2014 and including 2,757,000 customer-years. The data comprise information on private customers, their contract history, including coverage and losses and the channels used for buying insurance. This analysis focuses on the two most common non-life insurance products, namely, household/liability and car insurance. Findings The authors provide descriptive statistics and results from econometric analyses to determine the significant features and patterns affecting customer development and retention. Among the main results, the authors underline the significant influence on cross-selling given by the customer’s age and the interaction channel. Customers from rural regions are more loyal and likely to conduct cross-buying when compared to their peers from urban regions. Car insurance holders are more likely to lapse than household/liability insurance clients. Finally, while newly acquired customers tend to buy only a single product, the authors show the importance of cross-selling for retaining customers. In fact, customer retention is positively influenced by the number of products hold. Research limitations/implications This work is relevant for academics and practitioners alike, adding a quantitative basis to the understanding of managing customer relationships and for the development of further prospective models. Further work could investigate or add products, extend the study to other companies and focus on customer development with time. Originality/value This study explores a large-scale longitudinal data set. The analyses of customer acquisition, development and retention can support insurers to construct their own models for customer relationship management.
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Koosha, Hamidreza, and Amir Albadvi. "Allocation of marketing budgets to customer acquisition and retention spending based on decision calculus." Journal of Modelling in Management 10, no. 2 (July 20, 2015): 179–97. http://dx.doi.org/10.1108/jm2-02-2013-0006.
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Purpose – The purpose of this paper is to allocate marketing budgets in complex environments, where data are scarce and management judgment is available. In this research, marketing budgets are allocated, to maximize customer equity as a long-term profitability measure. Design/methodology/approach – The researchers provide a model for allocation of marketing budgets based on both decision calculus and econometric models and combine it with the concept of Markov chain model to cope with data scarcity. Dynamic programming is used to find the optimal solution. Findings – The authors examine the model in telecommunication industry. Applicability of the model is supported by an illustrative example. To allocate marketing budgets, researchers consider three strategies for each period: do nothing, retention-focused strategy and acquisition-focused strategy. The results show the applicability and effectiveness of the model to find the best strategy. Research limitations/implications – As the suggested approach is based on management judgment, it is useful in situations, as the authors have experts or experienced managers to achieve reliable data. In situations which the authors do not have access to experienced managers, the results may be unreliable. Practical implications – The suggested approach is useful in situations of data scarcity, where experienced managers are accessible. The researchers have focused on telecommunication industry cases; however, the model is useful in other industries like the insurance industry. Originality/value – The main contribution of the research lies in the suggestion of a new approach to allocate marketing budgets in data scarcity situations in multi-period planning horizons. The researchers use both decision calculus and econometric tools to find the transition matrices of marketing plans.
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Tellis, Gerard J. "The Price Elasticity of Selective Demand: A Meta-Analysis of Econometric Models of Sales." Journal of Marketing Research 25, no. 4 (November 1988): 331–41. http://dx.doi.org/10.1177/002224378802500401.
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The author describes a meta-analysis of econometric studies that estimated the elasticity of selective sales or market share to price. The literature review yielded 367 suitable price elasticities from about 220 different brands/markets. The results indicate that the price elasticity is significantly negative and, in absolute value, eight times larger than the advertising elasticity obtained from a prior meta-analysis. The omission of distribution or quality, the use of only cross-sectional data, and temporal aggregation lead to severe biases in the estimates of price elasticity. The elasticity also differs significantly over the brand life cycle, product categories, estimation methods, and countries.
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Thomas, Jacquelyn S. "Econometric Analysis of Customer Retention in an Aviation Trade Organization." Transportation Research Record: Journal of the Transportation Research Board 1567, no. 1 (January 1997): 33–40. http://dx.doi.org/10.3141/1567-05.
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The proliferation of customer data bases is a direct consequence of firms’ drive toward efficient customer-firm interactions. With regard to customer-firm interactions, firms have focused on customer retention rates. Using a customer data base, firms try to identify the most valuable customers within that data base. After identifying these customers, firms attempt to develop strategies and tactics that increase the retention of the most valued customers and maximize the profitability of the entire base of customers. With this goal in mind, common firm practices that have arisen are the offering of rewards, free additional services, and add-on selling. The impact of rewards, additional services, and add-on selling on the customer equity of a trade association in the aviation industry is examined. In particular a model that examines the impact that these factors have on customer retention and firm profitability is developed. This model is tested on a membership data base from a service organization that offers membership rewards, additional free services, and fee-based products to aircraft owners and pilots. The findings from this research have implications for how trade associations should develop marketing programs and strategically manage and target their most valuable customers.
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BOJNEC, S., and G. PETER. "Vertical market integration and competition : the meat sector in Slovenia." Agricultural and Food Science 14, no. 3 (December 4, 2008): 236. http://dx.doi.org/10.2137/145960605775013182.
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This paper presents price transmission models explaining the farm-to-retail price spread and degree of competition in the meat marketing chains during the period of economic transition in Slovenia. The meat marketing chains in Slovenia are characterised by relatively large processing and marketing margins, which are expected to decline with market deregulation and integration into the international markets. As results of the economic restructuring and policy reforms, competitive market pressures in a marketing margin determination have increased, inducing pressures for efficiency improvements in the vertical market integration from the farm to the retail stage in the Slovenian meat sector. Co-integration models are applied to estimate vertical market integration and to assess the degree of price competition in the Slovenian beef and pork marketing chains. The tested econometric models confirmed the existence of the long run market integration in the meat chain and the speed of adjustment of price changes. Farm-gate meat prices are identified as weakly exogenous, indicating the crucial role of supply side processing and marketing factors in the retail meat price determination. The results of structural tests suggest a long-run mark-up price strategy in the beef, and a competitive price strategy in the pork, chain as the outcome of policy reforms. The increased competitive market pressures are very likely to increase efficiency in the beef markets. Efficiency improvements in the Slovenian food markets are needed in the increased competitive market pressures of the enlarged European Union markets.;
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Nikolaychuk, Sergiy, and Yurii Sholomytskyi. "Using Macroeconomic Models for Monetary Policy in Ukraine." Visnyk of the National Bank of Ukraine, no. 233 (September 29, 2015): 54–64. http://dx.doi.org/10.26531/vnbu2015.233.054.
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An important precondition for successful implementation of inflation targeting is the ability of the central bank to forecast inflation given the fact that the inflation forecast has become an intermediate target. Certainly, this means there should be clear understanding of the monetary policy transmission mechanism functioning within the bank, because it is precisely through transmission channels that a central bank has to ensure convergence of its inflation forecast to the target. And it is almost impossible to pursue inflation targeting without a set of macroeconomic models that describes the monetary policy transmission mechanism and helps to analyse the current state of the economy as well as forecast (simulate) short- and medium-term macroeconomic scenarios. This article provides a review of the current state of macroeconomic modelling at central banks and describes the history of development and actual stance of the National Bank of Ukraine’s system of macroeconomic models. The existing system provides quite reliable support for the current monetary policy decision-making process, but it has to be improved by implementing a more sophisticated model (such as a dynamic stochastic general equilibrium model) and enhancing the set of econometric models for shortterm forecast purposes in the future.
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Chandrashekaran, Murali, Beth A. Walker, James C. Ward, and Peter H. Reingen. "Modeling Individual Preference Evolution and Choice in a Dynamic Group Setting." Journal of Marketing Research 33, no. 2 (May 1996): 211–23. http://dx.doi.org/10.1177/002224379603300208.
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Organizational buying and strategic marketing decisions often emerge from a messy process of belief accommodation and compromise. In a longitudinal field study, the authors investigate how the beliefs and preferences of individual actors in a collective decision developed and changed. This provides a rare opportunity to relate beliefs and social influence to articulated preferences, as well as to evaluate the basic assumptions that underlie persuasive arguments theory, a prominent theory of group polarization. Econometric models are employed to test proposed relationships between group processes and outcomes. A model incorporating both cognitive and social process variables accurately predicts 95% of the actors’ top choices. The authors provide new insights for understanding the dynamics underlying group polarization and exploring group processes in marketing.
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Özsomer, Ayşegül, and Gregory E. Prussia. "Competing Perspectives in International Marketing Strategy: Contingency and Process Models." Journal of International Marketing 8, no. 1 (March 2000): 27–50. http://dx.doi.org/10.1509/jimk.8.1.27.19561.
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Empirical studies investigating the relationship between marketing standardization and performance have generated mixed results. This study investigates the causal ordering between marketing strategy and marketing structure as determinants of subsidiary performance. The authors propose a multiple contingencies approach that tests both the contingency (e.g., Chandler 1962 ) and the process (e.g., Bower 1970 ) frameworks in the subsidiary context. Findings based on a two-phase longitudinal study provide initial support for the framework that suggests that marketing structure follows marketing strategy. In response to increased target market similarity, companies in the study opted for more standardized marketing strategies. Furthermore, centralization of structure mediated the relationship between marketing strategy and subsidiary performance. The performance impact of centralization, however, was cross-lagged and negative. Results suggest adapting marketing strategies to local markets as a way of enhancing performance.
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Agieva, Movlatkhan T., Alexei V. Korolev, and Guennady A. Ougolnitsky. "Game theoretic models of sustainable management in marketing networks." Contributions to Game Theory and Management 13 (2020): 24–56. http://dx.doi.org/10.21638/11701/spbu31.2020.03.
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Difference and differential Stackelberg games of opinion control on marketing networks are considered. The principal allocates financial resources to the firms for marketing purposes. It is supposed that the structure of a target audience described by a weighted directed graph is already determined in the stage of network analysis, and marketing control actions are applied only to the members of strong subgroups (opinion leaders). Conditions of homeostasis (phase constraints) which reflect the requirements of sustainable management are introduced additionally. The Stackelberg equilibria are found analytically. It is shown that the interests of the principal and the firms are completely compatible.
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Habeeb Hashim, Luay, and Ahmad Naeem Flaih. "Modeling the Rainfall Count data Using Some Zero Type models with application." Journal of Al-Qadisiyah for computer science and mathematics 11, no. 2 (August 26, 2019): 14–27. http://dx.doi.org/10.29304/jqcm.2019.11.2.554.
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Count data, including zero counts arise in a wide variety of application, hence models for counts have become widely popular in many fields. In the statistics field, one may define the count data as that type of observation which takes only the non-negative integers value. Sometimes researchers may Counts more zeros than the expected. Excess zero can be defined as Zero-Inflation. Data with abundant zeros are especially popular in health, marketing, finance, econometric, ecology, statistics quality control, geographical, and environmental fields when counting the occurrence of certain behavioral and natural events, such as frequency of alcohol use, take drugs, number of cigarettes smoked, the occurrence of earthquakes, rainfall, and etc. Some models have been used to analyzing count data such as the zero-inflated Poisson (ZIP) model and the negative binomial model. In this paper, the models, Poisson, Negative Binomial, ZIP, and ZINB were been used to analyze rainfall data.
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Fayvishenko, Diana, Liudmyla Cherniavska, Iryna Bondarenko, Tetiana Sashchuk, Inna Sypchenko, and Nataliia Lebid. "THE IMPACT OF BRAND SOCIAL MEDIA MARKETING ON THE DYNAMICS OF THE COMPANY’S SHARE VALUE." Business: Theory and Practice 24, no. 1 (January 26, 2023): 24–32. http://dx.doi.org/10.3846/btp.2023.17117.
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The aim of the study was to determine the impact of brand social media marketing on the dynamics of the company’s share value. Methods of analysis and synthesis were used to determine the features of the implementation of the brand advertising campaign in social media. The economics and statistics analysis were used to analyse the costs of social media marketing (SMM) of the brands of global companies – leaders in market capitalization of shares, as well as to determine the capitalization level. The monographic method is used for a comprehensive and in-depth study of social media marketing, the causal links between the implementation of the advertising campaign and the overall performance of companies. The essence and importance of social media in the promotion of modern brands are studied considering the results of research and practice of global companies. The advantages of social media marketing activities of companies for brand promotion in the context of increasing the company’s value are identified, which include: increasing brand awareness; increasing the level of conversion and increasing the number of potential customers; direct communication with the target audience; coverage of the target audience which is not covered by traditional types of advertising. The dynamics of expenditures on social media marketing of global brands, as well as the dynamics of the cost of market capitalization of global companies were studied. An econometric regression model was developed to determine the quantitative impact of the costs of global brand social media marketing on the market value of shares of global companies. It was found that with an increase of $ 1 billion in spending on brand social media marketing, the cost of market capitalization of companies’ shares increases by an average of $ 1,445,947. Prospects for further research are to find new and increase the effectiveness of existing methods of brand social media marketing in order to maintain a stable competitive position and gain new competitive advantages.
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ZAVHORODNIA, TETIANA, OKSANA PROSKUROVYCH, and KATERYNA GORBATIUK. "DIAGNOSIS OF THE RESULT OF A SEWING ENTERPRISE PRODUCTION ACTIVITY." MODELING THE DEVELOPMENT OF THE ECONOMIC SYSTEMS 1, no. 1 (June 2021): 47–54. http://dx.doi.org/10.31891/mdes/2021-1-6.
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In the scientific article, the process of diagnosing the production activity result of a sewing enterprise is investigated. An assessment of the state of production and marketing activities of a sewing enterprise based on the dynamics of the volume of marketable and sold products. The factor analysis of the efficiency of resources using (number of human resources, cost of materials and fixed assets) on an enterprise of sewing branch is carried out. Econometric modeling and forecasting of the production activity results, concerning the change of the basic components of resource potential of a sewing enterprise, are applied. Several econometric and one trend models, which describe the change of the volume of marketable products on a sewing factory, have been built. In addition to linear dependences, the power and multiplicative production function of changing the production activity result is formed. All constructed models have a high value of the coefficient of determination, which indicates a significant share of the influence of selected factors on the performance indicator. At the same time, they are adequate, so they can be used for forecasting the volume of marketable products. The results of modeling and further forecasting proved that the best models are the three-factor model, power model, two-factor model built on the impact of staff and cost of material resources, and one-factor relationship between product volume and cost of materials. These models have a sufficiently high value of the coefficient of determination, the lowest value of the standard error, and the adequacy of these models according to Fisher's criterion and the reliability of their parameters according to Student's criterion.
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Kübler, Raoul, and Koen Pauwels. "Metrics Gone Wrong: What Managers Can Learn from the 2016 US Presidential Election." NIM Marketing Intelligence Review 13, no. 1 (May 1, 2021): 30–35. http://dx.doi.org/10.2478/nimmir-2021-0005.
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Abstract In the 2016 presidential election, the vast majority of available polls showed a comfortable lead for Hillary Clinton throughout the whole race, but in the end, she lost. Campaign managers could have known better, if they had had a closer look at other data sources and variables that – like polls – show voter engagement and preferences. In the political arena, donations, media coverage, social media followership, engagement and sentiment may similarly indicate how well a candidate is doing, and most of these variables are available for free. Validating the bigger picture with alternative data sources is not limited to politics. The latest marketing research shows that online-consumer-behavior metrics can enrich, and sometimes replace, traditional funnel metrics. Trusting a single ‘silver bullet’ metric does not just lead to surprises, it can also mislead managerial decision-making. Econometric models can help disentangle a complex web of dynamic interactions and show immediate and lagged effects of marketing or political events.
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Fierro, Alvaro, and Ibon Aranburu. "Airbnb Branding: Heritage as a Branding Element in the Sharing Economy." Sustainability 11, no. 1 (December 23, 2018): 74. http://dx.doi.org/10.3390/su11010074.
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The cultural heritage of cities has been proven to be a generator of economic activity and a singular place branding/marketing tool for territories. In addition, in recent times, there has been a boom in the collaborative economy in urban destinations, epitomized by accommodation companies, such as Airbnb. The main objective of this article was to analyze how cultural heritage adds value to the collaborative economy. To this end, a method was proposed that analyzed Airbnb host descriptions, detecting the cultural and heritage goods mentioned, therein, which are used as marketing elements. From these cultural assets, various econometric models were generated that aimed to assess the number of guest reviews, which were used as a proxy for the number of guests. To evaluate this method, a case study was developed in the city of Bilbao. In view of the results, it can be concluded that cultural heritage and spatial location positively influence the activity of the collaborative economy, increasing the number of guests and their economic value.
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Wang, Shaohua, Yanyan Chen, Jianling Huang, Ning Chen, and Yao Lu. "Macrolevel Traffic Crash Analysis: A Spatial Econometric Model Approach." Mathematical Problems in Engineering 2019 (May 6, 2019): 1–10. http://dx.doi.org/10.1155/2019/5306247.
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This study presents a spatial approach for the macrolevel traffic crashes analysis based on point-of-interest (POI) data and other related data from an open source. The spatial autoregression is explored by Moran’s I Index with three spatial weight features (i.e., (a) Rook, (b) Queen, and (c) Euclidean distance). The traditional Ordinary Least Square (OLS) model, the Spatial Lag Model (SLM), the Spatial Error Model (SEM), and the Spatial Durbin Model (SDM) were developed to describe the spatial correlations among 2,114 Traffic Analysis Zones (TAZs) of Tianjin, one of the four municipalities in China. Results of the models indicated that the SDM with the Rook spatial weight feature is found to be the optimal spatial model to characterize the relationship of various variables and crashes. The results show that population density, consumption density, intersection density, and road density have significantly positive influence on traffic crashes, whereas company density, hotel density, and residential density have significant but negative effects in the local TAZ. The spillover effects coefficient of population density and road density are positive, indicating that the increase of these variables in the surrounding TAZs will lead to the increase of crashes in the target zone. The impacts of company density and hotel density are just the opposite. In general, the research findings can help transportation planners and managers better understand the general characteristics of traffic crashes and improve the situation of traffic security.
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Dash, Mihir. "Web mining for e-commerce websites using repeat-purchase models." Journal of Management and Science 6, no. 1 (June 30, 2017): 6–10. http://dx.doi.org/10.26524/jms.2016.2.
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e-retailing and database marketing are two emerging industries that require strong support from the CRM system. It is important for a website to keep its customers interested and come back frequently to visit. As web data and direct marketing data are available in huge volumes, data mining is an important and popular tool for both industries to develop good CRM systems to target loyal customers. Since most of this data is primary purchasing data, one could even go one step further to develop models to describe and predict behaviour of customers.In this study two statistical models from the theory of repeat purchase behaviour were used to analyse customer loyalty. The models were able to predict the percentage of repeat-customers, and were able to identify marketing variables which affect the repeat-rate.
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VOLONTYR, Ludmila, Nadiya POTAPOVA, and Oksana ZELINSKA. "ECONOMETRIC MODELING IN FORMATION OF OPTIMAL PRICE FOR IMPLEMENTATION OF AGRICULTURAL PRODUCTS." "EСONOMY. FINANСES. MANAGEMENT: Topical issues of science and practical activity", no. 5 (45) (May 2019): 83–93. http://dx.doi.org/10.37128/2411-4413-2019-5-9.
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Ukraine is a predominantly agricultural country, and this branch has been recently demonstrating relatively high efficiency. Vegetable growing is a specific branch of crop production, which includes a large set of vegetables grown according to different technologies, with different shelf life of vegetable products, their different cost and production efficiency. The analysis of the situation on the vegetable market of Ukraine showed that there is a certain correlation between production volumes, sales and products sales prices. The price market environment on the vegetable market in recent years is largely determined by the ratio of supply and demand on the market. Thus, sales volumes increase when the supply on the market is the highest and the price level on the market is the lowest. The absence of permanent wholesale distribution channels also leads to an increase in the hidden market for vegetable products. According to experts of the Ukrainian Agrarian Confederation, the hidden market for fruit and vegetables is about $ 14 billion, or about 60% of the total turnover of vegetable products in Ukraine. Due to the moratorium on the sale of agricultural land, businesses are not able to buy land on their own and develop their business in the long-term prospects. Today, government support in the vegetable sector is limited to preferential lending and to individual funding programs, most often in collaboration with international donors. Much of the support for agro-industrial farms goes to grain and pulse plant producers, which significantly limits the opportunity for developing crop producers with higher marginality. The conditions in which the agrarian sector operates have a high degree of changeable uncertainty, and this circumstance requires agricultural producers to find ways to obtain reliable information about the state of the agricultural market, organizational and functional links between the subjects of the agricultural market, prices for agricultural products. etc. The purpose of this study is to: analyze the price of vegetable sales in Ukraine; substantiation of the use of the AGMEMOD partial equilibrium model for forecasting vegetable production in Ukraine; establish dependence of demand and supply of vegetable production on their sales price; determine the point of equilibrium of supply and demand and calculate of the optimal selling price of vegetables in Ukraine; justify the optimal costs for vegetable production; analyze of the price of selling vegetables in Ukraine and determine the optimal price according to supply and demand, as well as the optimal cost of vegetable production. Now, there are 12 key vegetable crops in Ukraine. These are potatoes, cucumbers, tomatoes, cabbage, beets, carrots, onions, garlic, peppers, zucchini, eggplants and pumpkin. Of these 12 cultures, 9 showed an increase in the period 2010-2016, even without taking into account the uncontrolled Crimea and Donbass. This increase has been driven by two crucial factors: - yield increase. This was made possible due to improving the quality of the seed and natural technological progress in the processing and the use of crop protecting agents. - increase in export demand for products. The demand, for example, for Ukrainian carrots and onions has increased, and therefore the opportunities for their cultivation have become greater. Price is a complex economic category, practically the only element of marketing that enables an enterprise to earn real income. Without proper economic justification of the price level, the normal functioning of economic entities and entire sectors of the economy is impossible, which in turn has a significant impact on the material well-being of the population. The level of market price depends on the value of other marketing elements, as well as on the level of competition on the market and the general state of the economy. As a rule, other marketing elements also change (for example, with increasing product differentiation in order to maximize price or at least the difference between price and cost). The price formation strategy allows determining the price level and marginal prices for individual product groups. The price formation should always be carried out taking into account the nomenclature and quality of products, their usefulness, importance and purchasing power of consumers and prices of the competitors. The strategy of price formation management is a set of measures to maintain conditional prices while actually regulating them in accordance with the variety and characteristics of demand, competition in the market. The AGMEMOD model is an example of the partial equilibrium (PE) models used in agriculture. The main advantages of partial equilibrium models are: the simplicity of the implemented algorithms, the operation of which is quite easily traced; relative availability of necessary data; the calculations are amenable to adequate economic interpretation, making it possible to quickly analyze the consequences of making a decision in the agricultural sector. However, partial equilibrium models are not without their disadvantages. In particular, they do not permit to assess macroeconomic effects such as changes in national income or employment levels, the effects that may be obtained from the redistribution of resources (labor, capital, etc.) into more efficient sectors. For national researchers, it is advisable to use these models, because they have a module of Ukraine, but it is necessary to supplement the program with statistics on vegetables. The demand is a function of price changes in the current period, and the supply is a function of price changes in previous periods. Econometric models of supply and demand dependence of vegetable production on the price of their sale are constructed. The equilibrium of the system is observed at the price of 6558 UAH. for 1 ton of vegetables under the given conditions of consumption, the demand is equal to supply and is 9321 thousand tons. Econometric models of price dependence on material costs, labor costs and depreciation have been constructed. By the first model, it can be determined that the content of unaccounted factors is estimated at 99.82 UAH. per hectare; with an increase in material costs by 1 hectare by 1 UAH, selling price increases by 0.9 UAH. per ton. Based on the Fisher's ratio test, the model is adequate, the relationship between the indicators is tight. The relationship between the indicators of the second model is weak, the calculated correlation coefficient can be trusted, but in general, the adequacy of the model conclusion cannot be made. The model shows that with an increase in labor costs by 1 UAH per hectare, the price increases by 10.03 UAH per ton. The third model based on the Fisher's ratio test is adequate, the relationship between the indicators is average. With the increase in depreciation costs per hectare by 1 UAH, the selling price will increase by 12.42 UAH per ton. The value of the linear correlation coefficient other than zero is statistically significant. Based on the calculated models, we will determine the optimal cost per hectare: material – 7144.2 UAH, labor costs – 689.4 UAH, depreciation costs – 543.4 UAH.
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Shevluga, Nastya, and Oleksandr Zozul’ov. "Research target as a tool of marketing communications." Marketing and Digital Technologies 6, no. 3 (September 20, 2022): 25–33. http://dx.doi.org/10.15276/mdt.6.3.2022.3.
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The aim of the article. The purpose of the article is the formation of a marketing research system taking into account the economic and technological features of this market. Taking into account the above, the following tasks were set and solved: determine the specifics of the video game release, taking into account the production and technical, consumer, economic features of this product; determine the necessary marketing research at each stage of game production and provide a systemic view. We consider the result of solving the tasks to be the construction of the author's scheme of application of analysis methods for each of the stages of the game's release. Analyses results. The first attempts to study the phenomenon of video games as a type of meaningful non-productive human activity were recorded in the early 1990s. Research approaches have undergone significant changes since then. Thus, the article discussed in detail three main approaches: narratological, processual and non-reductionist. The video game market has specific properties, so the authors analyzed the system of economic relations between counterparties. Understanding the way of interaction between such subjects made it possible to form an idea about the levels of interaction and the role of the company-developer in the chain of releasing a new product to the market. Monetization models of game products were also studied separately, as possible ways of financing projects. It was found that marketing research plays a significant role in increasing the efficiency of the use of available resources, in particular, determining the feasibility of investment contributions, adjusting the market and product strategy of the enterprise. Thanks to the analysis of the scientific literature, an own vision for marketing research of video games was formed. The result of the work was the author's scheme with the given methods of learning for each of the stages of production of a new game product for the market.Monitoring and analytics tools that are widely used, in particular at the post-production stage, are described. Conclusions and directions for further research. The release of a new game product is a valuable case both from the point of view of monetary resources and the labor of qualified personnel. The proposed scheme, which reflects the system of marketing research before and after the release of the game, allows you to create conditions and improve the conditions for bringing a new product to the market, covers all stages of the production process and allows you to monitor project success metrics. The goal of further research may be detailing the stages and improving methods of conducting research