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Kim, Taehyun, and Hoon‐Young Lee. "External validity of market segmentation methods." European Journal of Marketing 45, no. 1/2 (February 15, 2011): 153–69. http://dx.doi.org/10.1108/03090561111095630.
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Prygara, Olga, and Viktoria Zhurylo. "THE PROCEDURE OF DEVELOPMENT OF INTERNATIONAL MARKET SEGMENTATION STRATEGY." Economic Analysis, no. 30(1, Part 1) (2020): 166–82. http://dx.doi.org/10.35774/econa2020.01.01.166.
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Introduction. Increase of intensity of international economic activity under the process of internationalization of commodity markets lead to the necessity of search of attractive international markets and segments. Aim of the article is the development of procedure of international market segmentation strategy and determination of peculiarities of international market segmentation in comparison with segmentation of domestic markets, considering the necessity of evaluation of factors of choice of attractive markets, considering the influence of cultural environment on entrepreneurial activity. Method (Methodology). Application of methods of scientific generalization, analysis and synthesis gave an opportunity to distinguish elements, that characterize segmentation of international markets; to systemize the factors of international market environment, that influence international market segmentation process, define customers’ characteristics, that influence their purchasing decisions; to distinguish stages of international market segmentation; to describe features and marketing tasks of each stage. Results. Segmentation of international markets has to be viewed as the systematized process of division of international markets on the groups of countries and groups of individual customers on the basis of their cultural values and motivations concerning their decision making process, that gives an opportunity to satisfy their specific needs and strengthen international competitive positions. The factors that influence international segmentation process are macrofactors: geographic, structural-demographic, legal, economic, scientific, socio-cultural; and microfactors: common market factors (market demand, competitive factors, factors of quality characteristics of the product) and customer-based factors (psychological, behavioral, individual characteristics of customers). The stages of the procedure of developing of international segmentation strategy are: market attractiveness evaluation; competitive analysis; demand evaluation; cultural environment analysis; macrosegmentation of markets; microsegmentation of markets; implementation of strategy and control. The proposed strategy of international segmentation strategy requires forming of the detailed marketing plan to a certain market segment and constant monitoring of its realization in accordance with changes in market environment and motivations of customers.
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Hruschka, H. "Market definition and segmentation using fuzzy clustering methods." International Journal of Research in Marketing 3, no. 2 (January 1986): 117–34. http://dx.doi.org/10.1016/0167-8116(86)90015-7.
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Yoseph, Fahed, and Mohammad AlMalaily. "NEW MARKET SEGMENTATION METHODS USING ENHANCED (RFM), CLV, MODIFIED REGRESSION AND CLUSTERING METHODS." International Journal of Computer Science and Information Technology 11, no. 01 (February 28, 2019): 43–60. http://dx.doi.org/10.5121/ijcsit.2019.11104.
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Thomas, Robert J. "Multistage market segmentation: an exploration of B2B segment alignment." Journal of Business & Industrial Marketing 31, no. 7 (August 1, 2016): 821–34. http://dx.doi.org/10.1108/jbim-12-2015-0245.
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Purpose The purpose of this paper is to explore the possibility of identifying market segments in multistage markets and assessing whether their alignment could provide a useful managerial approach to find competitive advantage and better understand market opportunities. Design/methodology/approach Using data from a pilot project, need-based market segments from different market stages were identified and their potential alignment evaluated. The data were not designed to test hypotheses, nor were they originally intended to be used to align segments. Nevertheless, they provided a unique opportunity to explore multistage segmentation and segment alignment in a business-to-business (B2B) setting. Findings Overall, the findings of this exploratory study should encourage both academics and practitioners to continue to explore the possibility of studying and aligning multistage market segments. The possibility of aligning segments was demonstrated using visual alignment based on managerial judgment of data and alignment based on a combined cluster analysis of customers across the multistage markets. Research limitations/implications First, the market research was not specifically designed to formulate and test hypotheses about the feasibility of aligning segments in multistage markets – it is an exploratory study. The research was based on a pilot project, and the survey-derived databases were conveniently available for analysis. While sample sizes were small, they are typical of many B2B markets. Second, to more effectively study complex relationships in multistage markets, it would have been desirable to include a more comprehensive set of needs. Each market stage has not only a set of their own perceived needs but also a set of perceptions of the needs of other stages. Third, as in many B2B studies, the data used in this pilot project were based on single informants. Practical implications A common complaint among firms is that B2B market segmentation does not really work that well for them. An unexplored reason for this may be that true market segmentation does not stop with one’s direct customer, but should also include the customer’s customer and so on, in a multistage market segmentation structure. One implication of the research presented here suggests that better understanding the segmentation structure in a multistage market can enlighten the opportunities and risks of implementing such a strategy. Multistage market segmentation alignment may lead to innovative positioning and message levers for the sales force to use as an argument to gain advantage according to common and unique aligned segment needs. Social implications The process may be applied to social institutions in addition to commercial organizations. Originality/value While it is obvious that market segmentation can be applied to any single market of customers, the question of applying it to complex multistage markets needs additional exploration. The original idea in this paper is that the potential for strategically aligning multistage markets and segments can have both conceptual and managerial implications for establishing competitive advantage and more efficient and effective resource allocation. The paper shows that that such alignment is possible; however, research and research methods in this area are nascent and will require continued step-by-step learning about these complex market structures to build up to a more definitive understanding of the processes involved to guide future research and managerial thinking.
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Sari, Hasrini, and Diningtyas Aulia Nurhadi. "Designing Marketing Strategy Based on Value from Clothing-producing Companies Using the AHP and Delphi methods." Jurnal Teknik Industri 20, no. 2 (August 31, 2019): 191. http://dx.doi.org/10.22219/jtiumm.vol20.no2.191-203.
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Organizations design some strategies to win the competition. This paper discusses the design of market strategies to achieve harmony between value-based segmentation and marketing mix. The strategy's implementation starts with segmentation, targeting, and positioning. The clothing company ("M") was selected as a research object. Identification of market segments using cluster analysis while determine the target market using the AHP and Delphi method. Besides, Bull's eye research was used for product positioning. The results show that "M" customers are classified into two groups, referred Big Spenders and Discount Finders. Big Spender selected as the primary target market with a focus on size and durability. The marketing strategy focuses on Instagram and Facebook. As a result, the ads developed prototypes have proven to be better.
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Eiras-Franco, Carlos, Bertha Guijarro-Berdiñas, Amparo Alonso-Betanzos, and Antonio Bahamonde. "Interpretable Market Segmentation on High Dimension Data." Proceedings 2, no. 18 (September 17, 2018): 1171. http://dx.doi.org/10.3390/proceedings2181171.
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Obtaining relevant information from the vast amount of data generated by interactions in a market or, in general, from a dyadic dataset, is a broad problem of great interest both for industry and academia. Also, the interpretability of machine learning algorithms is becoming increasingly relevant and even becoming a legal requirement, all of which increases the demand for such algorithms. In this work we propose a quality measure that factors in the interpretability of results. Additionally, we present a grouping algorithm on dyadic data that returns results with a level of interpretability selected by the user and capable of handling large volumes of data. Experiments show the accuracy of the results, on par with traditional methods, as well as its scalability.
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Hong Dien, Le, Nguyen Phuc Son, Pham Hoang Uyen, and Le Van Hinh. "On a segmentation of Coopextra customers in Thu Duc district." Science & Technology Development Journal - Economics - Law and Management 3, no. 1 (May 20, 2019): 28–36. http://dx.doi.org/10.32508/stdjelm.v3i1.537.
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Customer segmentation is the process of grouping customers based on similar characteristics such as behavior, shopping habits…so that businesses can do marketing to each customer group effectively and appropriately. Customer segmentation helps businesses determine different strategies and different marketing approaches to different groups. Customer segmentation helps marketers better understand customers as well as provide goals, strategies and marketing methods for different target groups. This paper aims to examine the customer segmentation using clustering method in statistics and unsupervised machine learning. The algorithms used are K-means and Elbow which are famous algorithms that have been successfully applied in many areas such as marketing, biology, library, insurance, finance... The purpose of clustering is to find meaningful market segments. However, the adoption and adjustment of parameters in the algorithms so as to find significant customer segmentations remain a challenge at present. In this paper, we used data of customers of Thu Duc CoopExtra and found significant customer segmentations which can be useful for more effective marketing and customer care by the supermarket.
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Félix, Rosa, Filipe Moura, and Kelly J. Clifton. "Typologies of Urban Cyclists: Review of Market Segmentation Methods for Planning Practice." Transportation Research Record: Journal of the Transportation Research Board 2662, no. 1 (January 2017): 125–33. http://dx.doi.org/10.3141/2662-14.
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Following global guidelines, several cities are investing in urban cycling. Cities are in different stages of cycling development and have adopted different approaches and packages of policies that are likely to be most effective at each stage. Urban cycling plans include investment in infrastructure, promotion, and education supporting the adoption of active modes for urban mobility. Some investments aim to meet current cyclists’ needs and others those of potential bicycle adopters. With respect to urban cyclists, several studies propose typologies, usually related to frequency, trip purpose, or motivation. This paper compares a set of cyclist typologies and the corresponding categorization methods and reviews 20 studies that considered different cyclists’ profiles. Most studies relied on expert judgment approaches or rule-based decisions; five considered multivariate analysis techniques for clustering groups, on the basis of data from surveys. Despite the variety of group categorizations, commonalities were found in most cases and divided cyclists into three main types: current cyclists (typically more proficient riders), potential cyclists (willing but not convinced), and noncyclists (unaware of or unwilling to shift to cycling). Dividing the population of potential cyclists into different typologies can better inform the different stages of planning for cycling infrastructure development by targeting more accurately the needs and requirements of different types of users. This is a key element in the management of a cycling network and cycling infrastructure, which are intended to be built on the basis of effective solutions and decisions to achieve desirable bicycle modal shares of regular trips.
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Grau, Maria M. Abad, Maria Tajtakova, and Daniel Arias Aranda. "Machine learning methods for the market segmentation of the performing arts audiences." International Journal of Business Environment 2, no. 3 (2009): 356. http://dx.doi.org/10.1504/ijbe.2009.023796.
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Bigné, Enrique, Joaquin Aldas-Manzano, Inés Küster, and Natalia Vila. "Mature market segmentation: a comparison of artificial neural networks and traditional methods." Neural Computing and Applications 19, no. 1 (December 19, 2008): 1–11. http://dx.doi.org/10.1007/s00521-008-0226-y.
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Zatsarynin, Serhii. "Market Segmentation of Innovative Products Using Genetic Algoritms." Marketing and Digital Technologies 5, no. 2 (June 29, 2021): 67–74. http://dx.doi.org/10.15276/mdt.5.2.2021.6.
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One way to increase the company's competitiveness is to find new market niches. The market niche is the result of innovations that stimulate hidden, potential demand, as a result of which the company, developing a new market, avoids intense competition and receives a higher rate of return. It is proved that the growing number and complexity of tasks in the field of marketing research, working with a large amount of information, leads to the need to group data. The aim of the study is to develop a universal approach to solving the problem of market segmentation of innovative products based on a combination of genetic algorithm with traditional clustering methods. An ideal market niche can be defined as a compact and isolated series of points, which in some space of characteristics are objects or data elements. The selection of a market niche in the medical equipment market is carried out using a top-down approach. This approach implies the traditional segmentation of customers, which is carried out in the following order: segmentation, segment selection, positioning. It is believed that segmentation is the starting point for the formation of a market niche. To segment the medical equipment market, it is proposed to use cluster analysis methods. According to the results of the analysis, it can be seen that the market segments of potential consumers of medical equipment and consumables of Siemens in Ukraine are characterized by a fairly dense grouping of images of consumers around the center of its cluster in the space of features. The presented genetic clustering algorithm is flexible in relation to the decision-making process, as it allows to perform clustering based on various criteria, such as maximum mutual removal of clusters, proximity of geometric images of objects to the center of the cluster, other criteria. This is achieved by changing the calculation formula of the fitness function, which takes into account the necessary combination of clustering criteria without changing the structure of the algorithm. The algorithm is insensitive to initialization, as in the process of evolution of chromosomes through the use of genetic operators, the algorithm completely covers the whole set of acceptable solutions, which, in turn, provides high quality market segmentation.
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Gomez, Anabel, Rebecca Loar, and Andrea England Kramer. "The impact of market segmentation and social marketing on uptake of preventive programmes: the example of voluntary medical male circumcision. A literature review." Gates Open Research 2 (December 11, 2018): 68. http://dx.doi.org/10.12688/gatesopenres.12888.1.
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Background: The business world has long recognized the power of defining discrete audiences within a target population. However, market segmentation’s full potential has not been applied to the public health context. While some broad elements of market segmentation (e.g., age, geography) are considered, a nuanced look at behavioural and psychographic segmentation, which could greatly enhance the possibility of lasting behaviour change, is often missing. Segmentation, and the associated mindset which acknowledges the multi-dimensional differences between people, allows service providers, implementers, policymakers, and government officials to target initiatives and lead to a greater likelihood of lasting behavioural change. This paper investigates what segmentation is, how it has been applied to voluntary medical male circumcision (VMMC), how it can be applied in development, and the challenges in both measuring and adopting segmentation as part of program design. Methods: We performed a detailed search of peer-reviewed literature using PubMed, ProQuest, ScienceDirect, Google Scholar, and the abstract directories of the International AIDS Society (IAS) published between January 2015 and September 2018. We also accessed articles from business databases such as the Harvard Business Review. Results: Results from a VMMC-focused intervention that successfully designed and delivered segmentation-based programs in two countries demonstrated that it is possible to adapt private sector approaches. However, within the sector of global development that is most familiar with segmentation, these efforts rarely go beyond basic demographic segments. Conclusions: Existing published material tends not to measure the impact of segmentation itself, but the impact of the intervention to which segmentation was applied, which makes it challenging for the development sector to invest in the approach without evidence that it works. Nonetheless, the experiences of segmentation and demand creation for VMMC do highlight the opportunity for better integrating this approach in HIV prevention and in global development and measurement initiatives.
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Brandt, Caroline, Charles Pahud De Mortanges, Christian Bluemelhuber, and Allard C. R. Van Riel. "Associative Networks: A New Approach to Market Segmentation." International Journal of Market Research 53, no. 2 (March 2011): 187–207. http://dx.doi.org/10.2501/ijmr-53-2-187-208.
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This paper aims to expand the domain of brand image perception measurement by providing a method for eliciting brand associative networks and comparing it with traditional brand image measurement methods. This paper then argues that these networks may differ from one individual to another, depending on the cultural background and/or the experience with the brand. Accordingly, the authors introduce a methodology of clustering consumers with similar perceptions into distinct segments, which can be targeted differently. Using picture analysis and metaphor-based elicitation techniques, Lipton's Ice Tea brand associations are extracted and utilised as an input for the creation of 160 individual associative networks. These networks are first aggregated to measure the brand reputation and subsequently clustered into six segments. This paper provides clear arguments for using associative networks as the preferred method to capture the complete brand image. The paper discusses implications of perceptual segmentation for image management, brand positioning, perceptual competition analysis and brand communication.
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Zheng, Shi-yong, Mao-hong Liu, and Jin-de Huang. "The Influence of Community Structure on the Diffusion of Knowledge—A View Based on Market Segmentation." International Journal of Emerging Technologies in Learning (iJET) 14, no. 08 (April 30, 2019): 97. http://dx.doi.org/10.3991/ijet.v14i08.10397.
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To analyze the effects of different seeding selection strategies on knowledge diffusion in education field, this study builds an ABMS spreading model and performs several simulation experiments. Besides, market segmentation is proposed as the methods of community recognition as, the effects of the mechanism of market segmentation on seeding user choosing strategies are in-vestigated, and knowledge diffusion efficiency is analyzed. Given the existing education community structure in social network of knowledge, and the forma-tion mechanism of network, and even if the multiple seeds locate in the same education community, they cannot effectively exert the knowledge diffusion function of each seeding node. Several studies have showed that random selec-tion strategy is more effective than the sensitive strategy without any market segmentation. The seeding strategy integrated with market segmentation is ca-pable of improving the efficiency of knowledge diffusion significantly. In the meantime, the sensitive seeding strategy under the education community recog-nition can achieve better knowledge diffusion efficiency.
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Bassi, Francesca. "Forecasting Financial Products Acquisition via Dynamic Segmentation: An Application to the Italian Market." International Journal of Market Research 57, no. 6 (November 2015): 909–30. http://dx.doi.org/10.2501/ijmr-2015-071.
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The topic of market segmentation is still one of the most pervasive in marketing. Among clustering techniques, finite mixture models have gained recognition as a method of segmentation with several advantages over traditional methods; one variant of finite mixture models – the latent class (LC) model – is probably the most popular. The LC approach is innovative and flexible, and can provide suitable solutions to several problems regarding the definition and development of marketing strategies, because it takes into account specific features of the collected data, such as their scale of measure (often ordinal or categorical, rather than continuous), their hierarchical structure and their longitudinal component. Dynamic segmentation is of key importance in many markets where it is unrealistic to assume stationary segments due to the dynamics in consumers' needs and product choices. In this paper, a mixture latent class Markov model is proposed to dynamically segment Italian households with reference to financial products ownership. The mixture approach is compared with the standard one in terms of its ability to forecast customers' behaviour in the reference market.
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Deng, Jinyang, and Rogelio Andrada. "Visitors' Spatial Movement Patterns and Market Segmentation in Washington, DC." Tourism Analysis 25, no. 1 (March 3, 2020): 1–20. http://dx.doi.org/10.3727/108354220x15758301241576.
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Visitors' movement patterns can provide important information on popular sites visited and the timing of visits. Such information can be used for transportation planning, appropriate use and management of tourism resources/facilities, and market segmentation. Traditional market segmentation methods typically use one or more nonspatial variables, which cannot reflect the spatial consumption of a destination if the spatial movement patterns are not considered. While studies on visitors' spatial movements in an urban area have recently gained popularity, few, if any, have investigated visitors' spatial movements in relation to urban forests (i. e., parks, gardens, and green spaces in an urban area). In view of this, this study segments visitor markets in Washington, DC based on dominant movement patterns of 1,090 visitors. General log-linear models are used to identify dominant movement patterns and poLCA in R Studio is used for segmentation analysis. Ten significant movement patterns are identified, including seven two-ward patterns and three three-ward patterns, with the National Mall as the most visited area in the city. Findings of this study are useful for the maintenance of urban forests, the design of visitor itineraries, and the effective marketing and management of attractions and facilities in the city.
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Maeda, Iwao, David deGraw, Michiharu Kitano, Hiroyasu Matsushima, Kiyoshi Izumi, Hiroki Sakaji, and Atsuo Kato. "Latent Segmentation of Stock Trading Strategies Using Multi-Modal Imitation Learning." Journal of Risk and Financial Management 13, no. 11 (October 23, 2020): 250. http://dx.doi.org/10.3390/jrfm13110250.
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While exchanges and regulators are able to observe and analyze the individual behavior of financial market participants through access to labeled data, this information is not accessible by other market participants nor by the general public. A key question, then, is whether it is possible to model individual market participants’ behaviors through observation of publicly available unlabeled market data alone. Several methods have been suggested in the literature using classification methods based on summary trading statistics, as well as using inverse reinforcement learning methods to infer the reward function underlying trader behavior. Our primary contribution is to propose an alternative neural network based multi-modal imitation learning model which performs latent segmentation of stock trading strategies. As a result that the segmentation in the latent space is optimized according to individual reward functions underlying the order submission behaviors across each segment, our results provide interpretable classifications and accurate predictions that outperform other methods in major classification indicators as verified on historical orderbook data from January 2018 to August 2019 obtained from the Tokyo Stock Exchange. By further analyzing the behavior of various trader segments, we confirmed that our proposed segments behaves in line with real-market investor sentiments.
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Zhao, Xuan. "Marketing Segmentation in Consumer Product Industry." E3S Web of Conferences 218 (2020): 01027. http://dx.doi.org/10.1051/e3sconf/202021801027.
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Marketing segmentation is widely used for targeting a smaller group of market in consumer product industry, and is useful for decision makers to effectively focus on their consumers’ purchasing behavior based on one marketing mix. In order to have a better understanding of the relationship between marketing segmentation in conventional business field and data science field, marketing segmentation is introduced from the perspectives of business and data science in this paper. In addition, on the basis of the introduction of both methods, conclusion can be drawn that data science methods are used in marketing segmentation as an assistance to present more precise output, based on the theory generated in business practice.
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Ivashkovskaya, Irina Vasilevna, and Ivan Kuznetsov. "An Empirical Study of Country Risk Adjustments to Market Multiples Valuation in Emerging Markets: the Case for Russia." Journal of Corporate Finance Research / Корпоративные Финансы | ISSN: 2073-0438 1, no. 3 (December 31, 2010): 26–52. http://dx.doi.org/10.17323/j.jcfr.2073-0438.1.3.2007.26-52.
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Valuation in emerging markets is always a challenge. The existence of sovereign risk and capital market segmentation as well as small trading volumes and narrow domestic capital market make it difficult to identify peer companies for market multiples valuation without cross- border comparables. This paper investigates the practical implementation of market multiples valuation in emerging markets when the analyst should involve peer companies from developed markets. Companies with comparable operational parameters bear different values on different financial markets. The problem of unavoidable difference among national stock markets exists, that is why methods of cross-border multiples’ corrections are called for. We address cross-border corrections procedures for adjusting multiples to a sovereign risk to find out the role and the extent of these type of adjustments in valuation. We are using the samples of Russian and US companies to test three different adjustments’ techniques: the sovereign spread, the relative market coefficients and the regression approach.
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Wu, C. H., G. T. S. Ho, C. H. Y. Lam, W. H. Ip, K. L. Choy, and Y. K. Tse. "An online niche-market tour identification system for the travel and tourism industry." Internet Research 26, no. 1 (February 1, 2016): 167–85. http://dx.doi.org/10.1108/intr-08-2014-0204.
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Purpose – The purpose of this paper is to present a novel approach for niche-market tour identification, with the objective to obtain a better segmentation of target tourists and support the design of tourism products. A proposed system, namely the Niche Tourism Identification System (NTIS) was implemented based on the proposed scheme and its functionality was showcased in a case study undertaken with a local travel agency. Design/methodology/approach – The proposed system implements automated customer market segmentation, based on similar characteristics that can be collected from potential customers. After that, special-interest tourism-based market strategies and products can be designed for the potential customers. The market segmentation is conducted using a GA-based k-means clustering engine (GACE), while the parameter setting is controlled by the travel agents. Findings – The proposed NTIS was deployed in a real-world case study which helps a local travel agency to determine the various types of niche tourism found in the existing market in Hong Kong. Its output was reviewed by experience tour planners. It was found that with the niche characteristics can be successfully revealed by summarizing the possible factors within the potential clusters in the existing database. The system performed consistently compared to human planners. Originality/value – To the best of the authors’ knowledge, although some alternative methods for segmenting travel markets have been proposed, few have provided any effective approaches for identifying existing niche markets to support online inquiry. Also, GACE has been proposed to compensate for the limitations that challenge k-means clustering in binding to a local optimum and for its weakness in dealing with multi-dimensional space.
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Usman, Hamza, Mohd Lizam, and Muhammad Usman Adekunle. "Property Price Modelling, Market Segmentation and Submarket Classifications: A Review." Real Estate Management and Valuation 28, no. 3 (September 1, 2020): 24–35. http://dx.doi.org/10.1515/remav-2020-0021.
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AbstractAccurate pricing of the property market is necessary to ensure effective and efficient decision making. Property price is typically modelled using the hedonic price model (HPM). This approach was found to exhibit aggregation bias due to its assumption that the coefficient estimate is constant and fails to consider variation in location. The aggregation bias is minimized by segmenting the property market into submarkets that are distinctly homogeneous within their submarket and heterogeneous across other submarkets. Although such segmentation was found to improve the prediction accuracy of HPM, there appear to be conflicting findings regarding what constitutes a submarket and how the submarkets are to be driven. This paper therefore reviews relevant literature on the subject matter. It was found that, initially, submarkets were delineated based on a priori classification of the property market into predefined boundaries. The method was challenged to be arbitrary and an empirically statistical data-driven property submarket classification was advocated. Based on the review, there is no consensus on the superiority of either of the methods over the another; a combination of the two methods can serve as a means of validating the effectiveness of property segmentation procedures for more accurate property price prediction.
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Démurger, Sylvie, Martin Fournier, Li Shi, and Wei Zhong. "Economic Liberalization with Rising Segmentation in China's Urban Labor Market." Asian Economic Papers 5, no. 3 (June 2006): 58–101. http://dx.doi.org/10.1162/asep.2006.5.3.58.
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The massive downsizing of the state-owned sector and the concomitant impressive growth of the private sector at the end of the 1990s have altered the nature of the Chinese labor market. The introduction of market mechanisms has contributed to increasing labor turnover and competitiveness in market wages. Using two urban household surveys for 1995 and 2002, this paper analyzes the evolution of labor market segmentation in urban China by applying an extended version of Oaxaca-Blinder decomposition methods. During the seven-year period, the sharp increase in real earnings for all workers shows substantial differences across ownership, economic sectors, and regions. We find strong evidence of a multitiered labor market along these three major lines and highlight increasing segmentation within each of the three dimensions, with the gap between the privileged segments of the labor market and the most competitive segments widening over time.
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Larina, Y. S. "MARKETING STRATEGIES IN INTERNATIONAL BUSINESS: ROLE, CONDITIONS AND METHODS OF CHOICE." Economic innovations 19, no. 2(64) (July 7, 2017): 183–89. http://dx.doi.org/10.31520/ei.2017.19.2(64).183-189.
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The objective necessity of business strategy development in international business is proved. We define the strategy as a generalized model of marketing actions, which includes a thorough study of the needs and requirements of consumers, segmentation, choice of target markets, identification of competitive advantages, differentiation, positioning, and clear identification of elements of marketing mix. The hierarchy of marketing strategies of the enterprise in the international business is defined. We proved that in the process of forming the marketing strategy of the agroindustrial complex in the foreign markets, it is necessary to adapt the main elements of this methodology to the world market of agricultural products and food by taking into account its features as a market with a high level of competition, high dynamics of development, peculiarities of consumer behavior on it, product specificity regarding quality, conditions of storage, etc. We determined the growth strategies as a most dynamic strategies in international business. Options of strategies of growth on foreign markets are considered. The features of realization of marketing strategies in the international business and the main factors influencing their success are determined. In particular we reviewed that the main problems of enterprises of domestic agroindustrial complex while entering the external markets are largely due to the defects of the proposed commodity policy, in particular the inconsistency between sellers and buyers regarding quality standards of products and packaging, non-compliance with global standards and certification principles. In addition, the problem may be insufficient level of service, ineffective pricing policy, inconsistency of actions of market participants. The tools and stages of building strategies for penetration into international business are substantiated.
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Marković, Dejan, Biljana Grgurović, and Slavica Štrbac. "THE USE OF SPATIAL DATA FOR SEGMENTATION OF THE POSTAL SERVICE MARKET." Technological and Economic Development of Economy 17, no. 1 (March 17, 2011): 87–100. http://dx.doi.org/10.3846/13928619.2011.554016.
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Modern trends in the field of postal traffic imply the existence of a large number of providers who distribute these services. A trend of this kind sets highly rigorous requirements regarding structure and quality of the services. On the other hand, the users are a heterogenous group with specific characteristics, which significantly complicates the process of segmentation, choice of a target market and formulating of an adequate marketing strategy. Application of some standard methods of demographic and psychographic segmentation, in the opinion of the authors of this paper, results in very general grouping most often based on assumptions. The aim is to point out the significance of spatial data and how the results obtained by application of a geographic information system (GIS) can be used in the case of segmentation of the postal service market.
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Benbrahim Ansari, Oussama. "Geo-Marketing Segmentation with Deep Learning." Businesses 1, no. 1 (June 16, 2021): 51–71. http://dx.doi.org/10.3390/businesses1010005.
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Spatial clustering is a fundamental instrument in modern geo-marketing. The complexity of handling of high-dimensional and geo-referenced data in the context of distribution networks imposes important challenges for marketers to catch the right customer segments with useful pattern similarities. The increasing availability of the geo-referenced data also places more pressure on the existing geo-marketing methods and makes it more difficult to detect hidden or non-linear relationships between the variables. In recent years, artificial neural networks have been established in different disciplines such as engineering, medical diagnosis, or finance, to solve complex problems due to their high performance and accuracy. The purpose of this paper is to perform a market segmentation by using unsupervised deep learning with self-organizing maps in the B2B industrial automation market across the United States. The results of this study demonstrate a high clustering performance (4 × 4 neurons) as well as a significant dimensionality reduction by using self-organizing maps. The high level of visualization of the maps out of the initially unorganized data set allows a comprehensive interpretation of the different clusters and patterns across space. The centroids of the clusters have been identified as footprints for assigning new marketing channels to ensure a better market coverage.
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Salamaga, Marcin. "International Market Segmentation with the Use of CMS Method and Cluster Analysis." Przegląd Statystyczny 65, no. 4 (January 30, 2019): 492–506. http://dx.doi.org/10.5604/01.3001.0014.0609.
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The segmentation of foreign markets is currently treated as an important element of the strategy of operations of enterprises that participate in international exchange of goods and services. This paper fits squarely into a current trend in research on the matter. The article presents the possibility of combining the model of Constant Market Share developed by Leamer, Stern (1970) with cluster analysis. The CMS method allows for a detailed assessment of the sources of changes occurring in the export of compared countries, and in particular its results allow for answering the following question: To what extent may changes in export be explained by the economic situation in the world trade of individual clusters of commodities and to what extent do they result from the competitiveness of these countries? The application of the multivariate statistical methods for the designated effects will allow for the identification of the clusters of countries of the most similar position in the spatial and commodity arrangement, including countries of similar competitiveness of trade. This approach has been applied to the segmentation of EU countries’ markets.
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Bruwer, Johan, Brigitte Roediger, and Frikkie Herbst. "Domain-specific market segmentation: a wine-related lifestyle (WRL) approach." Asia Pacific Journal of Marketing and Logistics 29, no. 1 (January 9, 2017): 4–26. http://dx.doi.org/10.1108/apjml-10-2015-0161.
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Purpose The purpose of this paper is to illustrate the use of a domain-specific research instrument (the wine-related lifestyle (WRL)) to determine the different lifestyle-related wine market segments in a country and compare the findings cross-culturally. Design/methodology/approach The research instrument included 48 psychographic activities, interests and opinions (AIO) statements, plus socio-demographic, product consumption and purchasing questions. A final sample of 376 South African wine consumers was utilised, whereon exploratory and confirmatory factor analysis, combined with Hough’s Euclidean test, were applied to determine the existence of clusters (segments), assign descriptions to them, and link these to product consumption data. Findings Five wine segments recurred when comparing wine market segmentation studies cross-culturally. This means that cross-culturally, similar types of people drink wine with similar AIOs towards wine. In the South African market, four of these segments were identified. Research limitations/implications This study achieved a robust lifestyle-based market segmentation algorithm which can be used by researchers in different country environments for wine as a domain-specific product. Originality/value The contribution of this research is threefold in that it tested the WRL instrument in a cross-cultural context which is the first time this has been done; in the process it interpreted the wine consumer segments in South Africa for the first time; using a WRL-based (AIO) approach. The study demonstrated that market segmentation based on psychographic (lifestyle) behaviour is strengthened when supported by two additional segmentation methods, namely, socio-demographics and product involvement (purchasing and consumption).
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Lu, Hong, Yan Chen, and Zhe Zheng. "Research on Chinese Fashion Luxury Goods Markets and Consumer Groups." Advanced Materials Research 796 (September 2013): 488–91. http://dx.doi.org/10.4028/www.scientific.net/amr.796.488.
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With the upward climbing of the Chinese fashion luxury goods market for about 30 years, China have become one of the world's biggest markets. This situation makes the research on the Chinese fashion luxury goods markets and consumer groups instructive. In this paper, the formation and development of Chinese luxury goods market were represented and analyzed. By using the methods of internet questionnaires and depth interview the consumer groups segmentation of Chinese fashion luxury goods were researched, 10 groups were got and their respective expectation elements of fashion luxury goods were researched and obtained. Some suggestions were given as reference to the design and marketing promotion of fashion luxury goods in China.
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Chen, Nai-Hua, Stephen Chi-Tsun Huang, Shih-Tung Shu, and Tung-Sheng Wang. "Market segmentation, service quality, and overall satisfaction: self-organizing map and structural equation modeling methods." Quality & Quantity 47, no. 2 (August 31, 2011): 969–87. http://dx.doi.org/10.1007/s11135-011-9577-z.
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Al Marzooqi, Mashael, and Syed Zamberi Ahmad. "Cylinders to pipelines: Abu Dhabi’s city gas project." Emerald Emerging Markets Case Studies 10, no. 3 (August 7, 2020): 1–19. http://dx.doi.org/10.1108/eemcs-02-2020-0051.
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Learning outcomes This case study focuses on the problems that a company have in segmenting a local market of a gas distribution company and some strategies that they can use for developing a viable market segmentation to target the right segment that will provide a good economics, revenue base customers who also have the mindset to change to a new product. At the end of this exercise, students should have a clear understanding of the following: the essentials concepts of market segmentation, targeting and positioning and how they can be leveraged so that businesses increase their returns; the main elements/steps that drive market segmentation and business positioning; the appropriate methods for market segmentation when targeting local markets for a city gas project; and the challenges companies might face when changing a product. Case overview/synopsis In 2018, commercial customers began asking Abu Dhabi National Oil Company (ADNOC) Distribution to provide a sustainable solution to ensure a continuous supply of safe gas and avoid the interruptions and hazards associated with the supply of liquefied petroleum gas (LPG) to their premises. The request was discussed with the ADNOC marketing, supply and trading (MST) Division to investigate the possibility of growing the natural gas business in the Emirate of Abu Dhabi, thus contributing to the Emirate’s security, economy, environment and community, and ultimately to ADNOC Strategy 2030. Khaled Salmeen, Director of the ADNOC MST Division, believed that industrial customers accounted for higher business volume and profitability. Nevertheless, he advised Shuhab Al Shehhi, the City Gas Project Manager, to study the potential benefits in targeting both residential and commercial customers as part of ADNOC’s responsibility towards community engagement and investments. Al Shehhi had to address several questions: How could the City Gas Project be strategized and positioned so as to target all market segments? What were the potential outcomes? Would targeting all market segments strengthen ADNOC’s brand position? Complexity academic level This case study was written for Marketing and Strategic Management courses in Bachelor of Business Administration programs. Supplementary materials Teaching Notes are available for educators only. Subject code CSS: 8 Marketing
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Saha, Nilotpal, and Brajesh Kumar. "Psychographic Market segmentation of Junior College Students in Silchar, Assam." IRA-International Journal of Management & Social Sciences (ISSN 2455-2267) 4, no. 2 (September 10, 2016): 455. http://dx.doi.org/10.21013/jmss.v4.n2.p15.
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<div><p><em>This paper discusses about characteristics of most enthusiastic buyers of a non-metro city. The paper adopts the analytical and exploratory research style based on primary data. It uses questionnaire based survey methods with a sample size of 250 junior college students (JCS) of Silchar, Assam, India. The paper tries to identify the segments depending upon the choices and purchasing decision made by these students on the basis of their psychographic profile. </em></p><p><em> </em></p><p><em>The research is unique for academic and professional relevance. As the research on psychographic market segmentation in small city especially the city from North-Eastern Region called Silchar, Assam is very rare. Hence, this study may be regarded as masterpiece as it provides in-depth analysis on psychographic market segmentation, which is found to differ in several important aspects.</em></p></div>
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Ni, Min Na, Li Wang, and Yan Li. "Study On the Design Methods of Fast Moving Consumer Goods." Advanced Materials Research 605-607 (December 2012): 276–82. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.276.
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The fast moving consumer goods included a wide range of items. The basic characteristics of the fast moving consumer goods result in that the consumers’ buying habit is: simple, rapid, impulsive, emotional. In the trend of market segmentation, enterprises have to make the products respond quickly to design and manufacture under the premise of meeting functions. In the design process, designers find out design point by axiomatic design method, and then through a modular design, rapidly assemble the various elements thereby to design series of products with distinctive features in batch, so as to help enterprises to extend the product life cycle.
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Fathu Nisha, M., P. Vasuki, and S. Mohamed Mansoor Roomi. "Fabric Defect Detection Using the Sensitive Plant Segmentation Algorithm." Fibres and Textiles in Eastern Europe 28, no. 3(141) (June 30, 2020): 84–87. http://dx.doi.org/10.5604/01.3001.0013.9025.
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Fabric quality control and defect detection are playing a crucial role in the textile industry with the development of high customer demand in the fashion market. This work presents fabric defect detection using a sensitive plant segmentation algorithm (SPSA) which, is developed with the sensitive behaviour of the sensitive plant biologically named “mimosa pudica”. This method consists of two stages: The first stage enhances the contrast of the defective fabric image and the second stage segments the fabric defects with the aid of the SPSA. The SPSA proposed was developed for defective pixel identification in non-uniform patterns of fabrics. In this paper, the SPSA was built through checking with devised conditions, correlation and error probability. Every pixel was checked with the algorithm developed to be marked either a defective or non-defective pixel. The SPSA proposed was tested on different types of fabric defect databases, showing a much improved performance over existing methods.
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Hayda, Yuriy, and Lyudmila Tsvyetkova. "SEGMENTATION OF DENTAL SERVICES MARKET ACCORDING TO A GEOGRAPHICAL PRINCIPLE IN UKRAINE." Economic Analysis, no. 27(1) (2017): 18–27. http://dx.doi.org/10.35774/econa2017.01.018.
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Introduction. The role and importance of market segmentation as a methodology and tools for market research is emphasized. The importance of practical and theoretical studies of dental services market in Ukraine is highlighted. The limitation of scientific studies that focus on segmenting the market is indicated. Purpose. The research aims is conduct the segmentation of dental services market of Ukraine according to the geographical breakdown of administrative units (regions, Crimea, Kyiv and Sevastopol). Method. The multivariate analysis methods have been applied in this study. Those are cluster analysis (k-means clustering) and multidimensional scaling. Results. As a result of the geographical segmentation of the dental market of Ukraine 9 clusters are allocated. They combine administrative units with similar indicators of dental personnel security infrastructure (the number of dentists in the public and private clinics and offices, staffing agencies dental specialists). The best dental staffing agencies are in the cluster that integrates Ivano-Frankivsk and Kharkiv region. The lowest number of experts in dental public establishments can be observed in Zaporizhzhya region. As for the private dental establishments the lowest number of professionals can be observed in Volyn, Donetsk, Odessa and Chernihiv regions. With the help of similar methods 7 groups of regions and cities of Ukraine according to the level of current and deferred demand have been defined. It has been determined on the basis of the specific rate of dental visits of adults to dental institutions, the number of their repeated visits, the need for dental sanation of adults and children. The highest percentage of the population that needs sanation (i.e. a number of consumers of dental services with postpond demand) is typical for the Transcarpathian region and for Kyiv. The smallest number of consumers of dental services with pent-up demand is in their geographical segment, which includes Zaporizhzhya, Kherson, Luhansk region and Sevastopol. Mykolaiv region is characterized by a very significant postpond demand for dental services, while the current demand is minor and mainly ensured by repeated visits to dental institutions by one and the same patient.
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Berghoff, Hartmut. "Marketing Diversity: The Making of a Global Consumer Product—Hohner's Harmonicas, 1857–1930." Enterprise & Society 2, no. 2 (June 2001): 338–72. http://dx.doi.org/10.1093/es/2.2.338.
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Unlike most nineteenth-century makers of traditional musical instruments, who did not aim at mass markets, German harmonica manufacturers were able to develop a large and worldwide market for their product. Located in regions outside Germany's industrial core districts, they epitomized successful specialty production. From the beginning, they relied on exports, especially to North America, a trade that was initially assisted by transatlantic emigrants who helped test market potential and tap into commercial networks. Hohner, the most successful harmonica manufacturer, created a well-known brand and extensively applied strategies of market segmentation and product differentiation from the 1890s onward, in part to satisfy customers' demand for myriad product variations. Sales channels and marketing methods also were far from homogeneous, being most effective when adapted to local conditions and cultures. For harmonica makers, diversity rather than uniformity was the key to global marketing success.
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Ramaswamy, Venkatram, Rabikar Chatterjee, and Steven H. Cohen. "Joint Segmentation on Distinct Interdependent Bases with Categorical Data." Journal of Marketing Research 33, no. 3 (August 1996): 337–50. http://dx.doi.org/10.1177/002224379603300308.
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The authors discuss a latent class framework for market segmentation with categorical data on two conceptually distinct but possibly interdependent bases for segmentation (e.g., benefits sought and usage of products and services). The joint latent segmentation model explicitly considers potential interdependence between the bases at the segment level by specifying the joint distribution of latent classes over the two bases, while simultaneously extracting segments on each distinct basis. An EM algorithm is used to estimate the model parameters. The authors present an empirical application, using pick-any data collected by a regional bank on two popular, conceptually appealing, and interdependent bases for segmenting customers of financial services—benefits (i.e., desired financial goals) and product usage (of an array of banking services). A comparative evaluation of the approach on synthetic data demonstrates the ability of the modeling framework to detect and estimate the interdependence structure underlying the two segmentation bases and thereby provide more accurate segmentation than “traditional” (single-basis) latent segmentation methods.
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Horner, Susan. "The Future of Market Segmentation and Relationship Marketing in the Tourism and Hospitality Sectors." Atna - Journal of Tourism Studies 1, no. 1 (January 1, 2006): 1–14. http://dx.doi.org/10.12727/ajts.1.1.
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There has been much written about the different methods of market segmentation in relation to the tourism and hospitality industry. Tourism and hospitality organisations have increasingly tried to devise ways of categorising consumers into discrete groups, understanding their behaviour in a variety of ways, and reflecting these findings in appropriate marketing strategies. This paper uses illustrative examples that have been researched to show that the new approach to market segmentation should be based on psychographic and behavioural characteristics, and considers the relevance of relationship marketing in the context of the post-modernist era and growing ethical debate. The paper concludes with a review of the future for branded tourism and hospitality organisations and suggests that an understanding of consumer behaviour should become the central focus for future commercial success
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Bach, Mirjana Pejić, Sandro Juković, Ksenija Dumičić, and Nataša Šarlija. "Business Client Segmentation in Banking Using Self-Organizing Maps." South East European Journal of Economics and Business 8, no. 2 (November 1, 2014): 32–41. http://dx.doi.org/10.2478/jeb-2013-0007.
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Abstract Segmentation in banking for the business client market is traditionally based on size measured in terms of income and the number of employees, and on statistical clustering methods (e.g. hierarchical clustering, k-means). The goal of the paper is to demonstrate that self-organizing maps (SOM) effectively extend the pool of possible criteria for segmentation of the business client market with more relevant criteria, including behavioral, demographic, personal, operational, situational, and cross-selling products. In order to attain the goal of the paper, the dataset on business clients of several banks in Croatia, which, besides size, incorporates a number of different criteria, is analyzed using the SOM-Ward clustering algorithm of Viscovery SOMine software. The SOM-Ward algorithm extracted three segments that differ with respect to the attributes of foreign trade operations (import/export), annual income, origin of capital, important bank selection criteria, views on the loan selection and the industry. The analyzed segments can be used by banks for deciding on the direction of further marketing activities.
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Sokolova, M. I. "THE MARKET CONCEPT OF THE XXI CENTURY: A NEW APPROACH TO CONSUMER SEGMENTATION." MGIMO Review of International Relations, no. 3(48) (June 28, 2016): 205–13. http://dx.doi.org/10.24833/2071-8160-2016-3-48-205-213.
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World economic development in the 21st century keeps tendencies and contradictions of the previous century. Economic growth in a number of the countries and, as a result, growth of consumption adjoins to an aggravation of global problems of the present. It not only ecology and climatic changes that undoubtedly worth the attention of world community, but also the aggravation of social problems. Among the last the question of poverty takes the central place. Poverty is a universal problem, in solution of which take part local authorities, the international organizations, commercial and noncommercial structures. It is intolerable to ignore a catastrophic situation in fight against this problem. It is necessary to look for ways of resolving it not only by using the existing methods, but also developing new approaches. One of the most significant tendencies in the sphere of fight against poverty is the development of the commercial enterprises working in the population segment with a low income level which by means of the activity help millions of people worldwide to get out of poverty. In other words, attraction of the commercial capital by an economic justification of profitability and prospects of investments into the companies working in the population segment with a low income level can be one of the methods allowing to solve effectively a poverty problem. This approach includes this population in economic activity, makes them by full-fledged participants of the market, which benefits to the creation of potential for economic growth and is a key step to getting out of poverty.
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Saayman, M., and T. Dieske. "Segmentation by motivation of tourists to the Kgalagadi Transfrontier Park." South African Journal of Business Management 46, no. 2 (June 30, 2015): 77–87. http://dx.doi.org/10.4102/sajbm.v46i2.93.
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The Kgalagadi Transfrontier Park is one of South Africa’s unique attractions for national and international tourists. However, little research has been done on visitors to transfrontier parks. In addition marketers highlight the importance of understanding the reasons why people travel and who these tourists are. Therefore the aim of this article is to segment the market of the Kgalagadi Transfrontier Park by means of visitors’ travel motives. This was achieved by means of a survey. In the statistical analysis, 414 questionnaires were used and the survey was conducted from 2010 to 2012. The statistical analysis included a factor analysis and ANOVA. Four factors were identified through the factor analysis namely escape, education and recreation, park attributes and exploration. The latter was unique to this research since it has not been found in other studies. The ANOVA confirmed that a wide variety of variables influence the decision-making process and that the marketing strategy should focus on different methods and events to attract a greater market.
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Pyzhikova, Natalya, Kristina Shvalov, and Pavel Shvalov. "The model of the distribution of oilseed processing products to foreign markets." E3S Web of Conferences 176 (2020): 05009. http://dx.doi.org/10.1051/e3sconf/202017605009.
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The article presents the results of a study of the world market of oilseeds and products of their processing, regional features of the agro- industrial complex (AIC) of the Krasnoyarsk Territory, as well as the rationale for the development of the region’s export activities in this direction. The purpose of the study is the formation of the model of the distribution of oilseed processing products to foreign markets. Research methods - an analytical and research arsenal of methods and methodological techniques: logical and situational analysis, diagnostics and monitoring, tabular and graphical techniques for interpreting factual information. Among general scientific methods, analysis, synthesis, deduction and induction, analogy have found application. The results of the Research: segmentation of consumers of vegetable oils, marketing complex of products, model of distribution of products to the market of vegetable oils of China. The formed distribution model is based on the goals of the enterprises of the agro-industrial complex of the Krasnoyarsk Territory: to introduce a new product (vegetable oils: rapeseed, cameline, mustard) and expand its presence to the markets. The formed distribution model will expand the possibilities of diversifying the activities of agricultural enterprises in the region when entering the foreign markets and will serve as a serious methodological basis for the design of innovative business models.
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Pham, Trung Kien, Thang Duc Nguyen, Chien Van Le, and Thuong Van Nguyen. "Analyzing customer sentiments using K-means algorithm." Journal of Mining and Earth Sciences 61, no. 5 (October 31, 2020): 145–50. http://dx.doi.org/10.46326/jmes.ktqtkd2020.19.
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Customer segmentation is the process of dividing customers based on common characteristics such as their behavior, buying habits and service usage,... so that companies can market for each group customers more effectively and appropriately. The paper analyzes customer cluster segmentation via the K-Means clustering methods of a business sector. The research was conducted on 272 customers with characteristics of age, income and expense score. The research results are divided into 2 target customer clusters, promising to help care and marketing customers more effectively; Help business units to have appropriate marketing strategies to reduce costs and increase efficiency.
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Behe, Bridget K., Benjamin L. Campbell, Charles R. Hall, Hayk Khachatryan, Jennifer H. Dennis, and Chengyan Yue. "Consumer Preferences for Local and Sustainable Plant Production Characteristics." HortScience 48, no. 2 (February 2013): 200–208. http://dx.doi.org/10.21273/hortsci.48.2.200.
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Some consumers are becoming more interested in and purchasing products that are locally grown and/or ecologically friendly. Market segmentation and product targeting are efficient methods to allocate a firm’s scarce marketing resources to supply heterogeneous markets. This study’s objective was to identify consumer segments, focusing on their gardening purchases, to determine whether there were differences in consumer preferences for provenance and environmental attributes for transplant purchases. Using a consumer survey of U.S. and Canadian consumers, we found that participants who purchased different plant types had distinct preferences for varying environmental attributes and provenances. We profiled nine consumer segments, identifying their plant purchases and preferences for local and sustainably grown products and plant containers. Results provide plant producers and retailers with market segments that can be identified and targeted and provide a basis for customizable marketing communications to enhance profits.
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Inoue, Ryo, Rihoko Ishiyama, and Ayako Sugiura. "Identifying local differences with fused-MCP: an apartment rental market case study on geographical segmentation detection." Japanese Journal of Statistics and Data Science 3, no. 1 (January 17, 2020): 183–214. http://dx.doi.org/10.1007/s42081-019-00070-y.
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AbstractAs the variety and quality of spatial data increase in recent times, the potential to analyze local characteristics based on spatial data is getting stronger. Previous spatial analysis methods structuralize the spatial autocorrelation of data by the distances between data observation points and the contiguity of the data-observed regions. It is significant for the estimation of global characteristics of spatial data. However, these approaches are not suitable for identifying local differences from the data since they assume a smooth spatial autocorrelation structure. Generalized fused lasso, which can detect local differences in spatial data, has been proposed in machine learning studies. Its limitation is that the estimated parameters are biased toward zero; however, methods that overcome the limitation have also been proposed. Fused-MCP is one of those methods and is expected to be useful in spatial analyses. This study applies fused-MCP to spatial analyses. As an example of spatial analyses based on fused-MCP, this study analyzes the structure of geographical segmentation of the real estate market in central Tokyo. Fused-MCP is utilized to extract areas where the valuation standard is the same. The results reveal that the geographical segmentation displays hierarchal patterns. Specifically, the market is divided by municipalities, railway lines and stations, and neighborhoods. The case study confirmed the applicability of fused-MCP to spatial analyses.
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Chan, Kit Yan, C. K. Kwong, and B. Q. Hu. "Market segmentation and ideal point identification for new product design using fuzzy data compression and fuzzy clustering methods." Applied Soft Computing 12, no. 4 (April 2012): 1371–78. http://dx.doi.org/10.1016/j.asoc.2011.11.026.
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Arnould, Eric J., and Melanie Wallendorf. "Market-Oriented Ethnography: Interpretation Building and Marketing Strategy Formulation." Journal of Marketing Research 31, no. 4 (November 1994): 484–504. http://dx.doi.org/10.1177/002224379403100404.
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The authors show how ethnography can provide multiple strategically important perspectives on behaviors of interest to marketing researchers. They first discuss the goals and four essential characteristics of ethnographic interpretation. Then they review the particular contributions to interpretation of several kinds of ethnographic observation and interview data. Next they discuss how interpretations are built from ethnographic data. They show how multilayered interpretations of market phenomena emerge through systematic analysis of complementary and discrepant data. Finally, the authors articulate three representational strategies that are used to link multilayered interpretations to marketing strategy formulation. They suggest that ethnographic methods are appropriate for apprehending a wide variety of consumption and use situations with implications for market segmentation and targeting; product and service positioning; and product, service, and brand management.
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Liu, Hui, Yinghui Huang, Zichao Wang, Kai Liu, Xiangen Hu, and Weijun Wang. "Personality or Value: A Comparative Study of Psychographic Segmentation Based on an Online Review Enhanced Recommender System." Applied Sciences 9, no. 10 (May 15, 2019): 1992. http://dx.doi.org/10.3390/app9101992.
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Big consumer data promises to be a game changer in applied and empirical marketing research. However, investigations of how big data helps inform consumers’ psychological aspects have, thus far, only received scant attention. Psychographics has been shown to be a valuable market segmentation path in understanding consumer preferences. Although in the context of e-commerce, as a component of psychographic segmentation, personality has been proven to be effective for prediction of e-commerce user preferences, it still remains unclear whether psychographic segmentation is practically influential in understanding user preferences across different product categories. To the best of our knowledge, we provide the first quantitative demonstration of the promising effect and relative importance of psychographic segmentation in predicting users’ online purchasing preferences across different product categories in e-commerce by using a data-driven approach. We first construct two online psychographic lexicons that include the Big Five Factor (BFF) personality traits and Schwartz Value Survey (SVS) using natural language processing (NLP) methods that are based on behavior measurements of users’ word use. We then incorporate the lexicons in a deep neural network (DNN)-based recommender system to predict users’ online purchasing preferences considering the new progress in segmentation-based user preference prediction methods. Overall, segmenting consumers into heterogeneous groups surprisingly does not demonstrate a significant improvement in understanding consumer preferences. Psychographic variables (both BFF and SVS) significantly improve the explanatory power of e-consumer preferences, whereas the improvement in prediction power is not significant. The SVS tends to outperform BFF segmentation, except for some product categories. Additionally, the DNN significantly outperforms previous methods. An e-commerce-oriented SVS measurement and segmentation approach that integrates both BFF and the SVS is recommended. The strong empirical evidence provides both practical guidance for e-commerce product development, marketing and recommendations, and a methodological reference for big data-driven marketing research.
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Saputra, Johan. "Analisa kepuasan pelanggan Original Equipment Manufacturing ban motor dengan metode IPA-QFD: Studi kasus di PT. GTB." Operations Excellence: Journal of Applied Industrial Engineering 12, no. 1 (March 26, 2020): 40. http://dx.doi.org/10.22441/oe.2020.v12.i1.004.
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PT. GTB is a manufacturing company that manufactures tyres for motor vehicles, one of them motorcycle tires. The market segmentation of PT. GTB is an Original Equipment Manufacturing (OEM) market. Based on OEM market segmentation, PT. GTB has two large customer groups that include OEM customers. The complaint level of the customer for the use of motor tires in 2017 as much as 622 times and year 2018 as much as 352 times. In an effort to maintain the sustainability of product sales, customer complaints are critical to the company's improvement focus. The purpose of this research is analyzing the types of customers complain the use of motor tires. In the early stages, interviews as a reference for conducting customer satisfaction surveys are further analyzed by the Importance Performance Analysis (IPA) and Quality Function Deployment (QFD) methods. Based on the results of this research, known customer satisfaction rate of the use of GTB motor tires on average is 3.56 which is lower than the customer's expectation of 4.40. The research has successfully identified seven priority attributes that are considered very important to the customer, which is the input for the company to do the improvement.
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Nămolosu, Simona Mihaela, and Iuliana Cetină. "Identifying The Optimal Product Strategy By Applying Portfolio Segmentation Methods – Case Of Smes In Banking Sector." Balkan Region Conference on Engineering and Business Education 1, no. 1 (August 15, 2014): 121–26. http://dx.doi.org/10.2478/cplbu-2014-0026.
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AbstractSmall and Medium Enterprises (SMEs) are a high potential target for banks to attack, but also a risky segment; high potential because the need for financing is increasing, but risky because the crisis affected a lot the solvability and profitability of these companies. On the other hand, loan facilities are some of the most complex banking products (if we analyse diverse financing needs of small companies, but rather due to the analysis and approval processes in banks). In defining strategic alternatives for financing products for SMEs, the following steps are essential: evaluating potential market segments and/or sub segments, always focusing on the general and particular commercial objectives of the bank, analysing the strategies used by the major competitors and last, but not least: developing motivational systems for the employees of the branches - the main distribution channel for a banking product.