No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Application of multidimensional scaling for marketing-mix modification: A case study on mobile phone category
Abstract
This paper introduces an application of multidimensional scaling for marketing-mix modification of products at the maturity stage of product life cycle. The application is based upon the concept that marketers would benefit from mining the consumer behaviors to assist their marketing decisions. Using the preference map of multidimensional scaling method and influence-satisfaction matrix, the proposed methodology promotes marketers to analyze their current level of consumer satisfaction in the market and modify the marketing-mix based upon the current consumer preference and satisfaction.The proposed methodology adopts multidimensional preference (MDPREF) algorithm, which is designed to do multidimensional scaling of preference or evaluation data. While most applications with the multidimensional scaling have been to understand the position of a set of brands or products, the proposed methodology with MDPREF algorithm is to understand the similarities and dissimilarities among a set of marketing elements of a brand in consumer’s perception. A case example for the mobile phone category is provided.
... Today, due to dynamically changing customer desires as well as rapid technology evolution, mapping customer needs with optimal configuration of product features have become much more challenging than before ( Wang 2013). For instance, owing to market saturation in smart phones, Nokia and Motorola lost huge market shares and were merged by Microsoft and Google, respectively (Cha, Kim, and Lee 2009;Oküdan, Chiu, and Kim 2013). In contrast, Apple and Samsung have reported their brilliant revenues resulting from hot-selling smart phones, smart pads and other consumer electronic products. ...
... In order to achieve successful new product development in a crowded and fragmented market, product positioning and product recommendation are two critical techniques to help firms better understand the underlying relationships between product features, competing alternatives and diverse consumers (Lilien and Rangaswamy 2003;Petiot and Grognet 2006;Cha, Kim, and Lee 2009). Specifically, product positioning is not what you do to a product but it is what you do to the prospect of customers. ...
... Optimal product positioning corresponds to determining which attributes and associated levels should be configured in product varieties to satisfy customer requirements (Kwong, Luo, and Tang 2011). In practice, product positioning is implemented through a series of steps: (1) visualising competitive alternatives and product features in a low-dimensional space, (2) constructing a predictive model to forecast how potential buyers will react to marketing stimulus and (3) determining the optimal position of new product (s) and identifying the niche segment(s) to run a firm's business (Cha, Kim, and Lee 2009). ...
Diverse customer desires coupled with technological advances have forced companies to manufacture products with ultimate performance, low cost, high quality and much shorter time-to-market. Recently, the popularity of smart phones has given rise to seriously declined product sales of digital cameras. In this paper, a two-phase framework is presented to offer decision supports on developing next-generation cameras. In the phase of market segmentation, Kansei engineering is employed to capture customer perceptions of affective features. Then, rough set theory is conducted to generate decision rules for partitioning the whole market into the consumer segment and the professional segment, respectively. In the phase of product customisation, conjoint analysis is applied to extract customer preferences for functional features. Furthermore, Grey relational analysis is conducted to select the top three varieties with regard to two distinct segments. In particular, this paper is capable to help brand companies or camera manufacturers better capture customer perceptions and preferences for digital cameras, effectively perform market segmentation (based on affective features) and efficiently conduct product customisation (based on functional features).
... So the new product will replace the old product by product functions, and the new product will push customers to adapt them by price strategy (Fishman & Rob, 2002). Some research analyzed the position of brands/products for mobile phone market by the preference map of multidimensional scaling method and influence-satisfaction matrix (Cha, Kim, & Lee, 2009). In order to satisfy customers' heterogeneous needs and provide mass customization manufactures, some research made a lot of effort on the recommendation system of classification-based for personalization purchase of mobile phone (Lee & Kwon, 2008;Zhang & Jiao, 2007). ...
... Therefore, the phenomenon pushes enterprises need to understand customers' preferences in the diverse mobile phone market. A market position model of product/brand considered that the aspects (marketing mix) should include product, price, distribution, advertising and sales promotion (Cha et al., 2009). A selection model of value-added services for system operators suggest that the aspect of service function included entertainment, transaction, information, and communication (Kuo & Chen, 2006). ...
... These studies give us an important idea of customer preferences of product image. Product aspect should include tangible characteristics and intangible characteristics, and advertising aspect should include advertising contents, advertising media, and advertising copy/campaign (Cha et al., 2009). A research of product design for mobile phone considered product form features should include body (length, width, thickness, volume and type), function button (type, style), number button (shape, arrangement) and panel (detail treatment) and analyze the customer' needs of product designs for different styles users (plain, sports, female, simplicity and business) (Shieh & Yang, 2008). ...
This study aims to determine the services provided by TSPs for motivating the consumers to purchase new e-era mobile phones and find their corresponding functions of products, and to plan new e-era mobile phones based on customers’ attributes for satisfying the customer needs. This study uses four aspects (image of product, price of product, function of product and derived function of product) and 14 criteria to determine customer’s motivations of purchase and needs on new e-era mobile phones. We also combined AHP (Analytic hierarchy process) and FIM (Fuzzy integral method) with MCDM techniques to construct the value-created evaluation model for planning the new e-era mobile phones. This study selects 27 styles of 3G mobile phones already sold on the market, and uses the different customer’s attributes data to evaluate price’s satisfaction (product’s price) and value’s satisfaction (product’s image, product’s function and product’s derived function) for performance of these 3G mobile phones in a 2-axle evaluation map based on mass customization. This study shows three different customer’s attributes (male, female, both) to measure the satisfaction performance of 3G mobile phones in a 2-axle development strategy map using data from people that are surveyed randomly by 21–30 years old. The development strategy map will provide some new strategy view for developing new e-era mobile phone market based on value and price-satisfied portfolios.
... MDS was used to investigate the relationships in the corpora. Borg and Groenen (1997) argue that MDS is a statistical method developed to detect in a visual way the complex patterns in high-dimensional datasets. By arranging points in space according to similarities between different objects, MDS displays as two or three-dimensional geometrical pictures the structure of distance-type data (Cha et al., 2009). ...
... Borg and Groenen (1997) argue that MDS is a statistical method developed to detect in a visual way the complex patterns in high-dimensional datasets. By arranging points in space according to similarities between different objects, MDS displays as two or three-dimensional geometrical pictures the structure of distance-type data (Cha et al., 2009). Thus, similar sub-corpora are placed near each other on the map, while dissimilar sub-corpora are placed far away from each other. ...
... MDS was used to investigate the relationships in the corpora. Borg and Groenen (1997) argue that MDS is a statistical method developed to detect in a visual way the complex patterns in high-dimensional datasets. By arranging points in space according to similarities between different objects, MDS displays as two or three-dimensional geometrical pictures the structure of distance-type data (Cha et al., 2009). ...
... Borg and Groenen (1997) argue that MDS is a statistical method developed to detect in a visual way the complex patterns in high-dimensional datasets. By arranging points in space according to similarities between different objects, MDS displays as two or three-dimensional geometrical pictures the structure of distance-type data (Cha et al., 2009). Thus, similar sub-corpora are placed near each other on the map, while dissimilar sub-corpora are placed far away from each other. ...
... In order to achieve successful new product development in a crowded and fragmented market, product positioning and product recommendation are two critical techniques to help firms better understand the underlying relationships between product features, competing alternatives and diverse consumers (Lilien and Rangaswamy 2003; Petiot and Grognet 2006; Cha, Kim, and Lee 2009). Specifically, product positioning is not what you do to a product but it is what you do to the prospect of customers. ...
... Optimal product positioning corresponds to determining which attributes and associated levels should be configured in product varieties to satisfy customer requirements (Kwong, Luo, and Tang 2011). In practice, product positioning is implemented through a series of steps: (1) visualising competitive alternatives and product features in a low-dimensional space, (2) constructing a predictive model to forecast how potential buyers will react to marketing stimulus and (3) determining the optimal position of new product (s) and identifying the niche segment(s) to run a firm's business (Cha, Kim, and Lee 2009). Specifically, a perceptual map is a powerful tool to visualise the underlying relationships between the competing products (brands) and associated features (criteria) in a lower dimensional space. ...
Recently, several global companies start to develop wearable devices like smart watches or smart glasses to avoid market saturation in smart phones, especially when wireless technology was rapidly shifting from the third to the fourth generation. In order to better understand the relative strengths and weaknesses of smart alternatives, this paper presents a market-oriented framework to accomplish product positioning and product recommendation. Initially, correspondence analysis is applied to elicit expert perceptions for conducting product positioning. Then, based on customer preferences, product recommendation can be accomplished in either an unsupervised way (purchase profiles for new products are unavailable) or a supervised manner (for justifying the validity of the proposed recommender system). In particular, analytical hierarchy process is employed to elicit customers’ choices among smart alternatives (treated as prior information or decision labels). In summary, managerial insights are provided as follows: (1) smart phones are good at providing a platform for satisfying home entertainment, (2) smart watches are perceived as auxiliary carriers to accomplish health care and safety monitoring and (3) smart glasses are promising to fulfill industrial operation, logistics service and homeland security.
... We utilized the MDS method to reduce the dimensions of population flow vectors as other-wise it would be very challenging to visualize high-dimensional vectors. The MDS approach has been widely used to visualize similarities in multivariate data (Mead, 1992;Cha et al., 2009;He and Shang, 2018;Machado and Mehdipour, 2019). Given N objects that are represented as d-dimensional vectors and all the pairwise similarities or distances between them, the MDS finds a k-dimensional embedding for the N objects that preserve pairwise distances, where k < d (Chen, 2003). ...
Human migration between cities is one important aspect of spatial interaction that not only reflects urban attractiveness but also denotes interactions amongst agglomerations. We therefore implemented a web-based visualization system to analyze and interactively explore local and distant population flow patterns between cities on the Qinghai-Tibet Plateau (QTP). We utilized 2017 Tencent population flow data from which we initially constructed inbound and outbound vectors for cities on the QTP. We then used multidimensional scaling to examine and visualize migration patterns and similarities between cities. Results reveal the presence of six local and three distant human mobility patterns on the QTP as well as average summer monthly migrations more than twice the level of those in the winter.
... The products that have been marketed, the price will affect it. In this case, the provision of pricing for a product has a role that gives influence to customers to buy and become an eternal customer [21]. From the price provided, the customer must get satisfaction, and the company needs to get the profit set by the company rules. ...
... MDS shows the structure of distance-type data in a two-dimensional graph by arranging points in space based on similarities between different objects. Following Cha, Kim, and Lee (2009), we used MDS to map the relationships among sub-corpora through the construction of a low k-dimensional space based on perceived similarities or dissimilarities among the set of sub-corpora. The alternating least squares approach to scaling (ALSCAL) algorithm (Zsoka, Szerenyi, Szechy, & Kocsis, 2013) is used in this study since this algorithm has been shown to optimally compute the Euclidean distances between objects in the k-dimensional space. ...
Although the Generation of ’98 writers represents a group of renown Spanish novelists, philosophers, essayists and poets active during the 1898 Spanish-American war, no previous studies have attempted to analyze the diverse linguistic and stylistic features employed by such writers. This study aims to use computational stylometry to detect hidden stylistic and linguistic patterns employed by three Generation of ’98 writers, namely Pío Baroja, Vicente Blasco Ibáñez and Miguel de Unamuno. We employ a large corpus comprising 1,702,243 words representing nineteen works by the three writers. Several rigorous criteria were satisfied in designing the corpora such as authorship, genre, topic and register. Concordance, wordclouds, consensus trees, multidimensional and cluster analyses were performed to reveal the different stylistic and linguistic patterns used by the three writers. Although we focus solely on the use of the word “árabe”, we show that computational stylometry techniques can be used to help detect hidden stylistic and linguistic patterns employed by different writers. This result is significant since it can help the reader navigate across various possibilities of expressions and terminologies employed by different writers.
In this paper, the symmetrical Kullback–Leibler divergence is proposed to capture the dynamical features of various complex time series more accurately. The symmetrical Kullback–Leibler divergence is modified from the Kullback–Leibler divergence to make it possess the properties of a normal distance measure. A new multidimensional scaling (MDS) method with the proposed symmetrical Kullback–Leibler divergence is established, which is an efficient clustering and visualization technique. The proposed method also includes the probability distribution of the weighted-permutation patterns, which not only provides a modified time series quantification process with more possible patterns, but also facilitates the reduction of error when extracting the hidden information from time series. The upper and lower bounds of the proposed divergence are also presented. Through simulation and reality-based data experiments, it is affirmed that the MDS based on this novel dissimilarity measure is capable of presenting more distinctive and rational clustering results by comparing it with the MDS methods based on conventional dissimilarities.
This article uses multidimensional scaling and correspondence analysis to explore how international airline passengers position various air carriers. The analysis has produced perceptual maps of relative positions of airlines and their service attributes. Empirical data were collected from Taiwanese air passengers who had flown from Taipei to Tokyo and to Singapore. Factor analysis was performed to reduce a large number of airline service attributes into a small set of underlying factors. The results of multidimensional scaling analyses reveal that some air carriers are closely competitive; this can be seen by their close proximity in the perceptual map. However, certain airlines possess a unique service quality profile and are not strongly associated with other airlines; such unique firms appear as isolated points on the perceptual map. Interestingly, both multidimensional scaling and correspondence analysis produce similar perceptual maps of the airlines' relative positions and service attributes. However, the advantage of correspondence analysis over multidimensional scaling is that data collection is relatively quick and easy because the analyst is not required to obtain respondents' ratings for each attribute. This study provides specific suggestions about how air carriers on each route can use the results to improve their performance or to build a differential edge.
Market Segmentation has been a key area of implementation of soft computing techniques in E-commerce applications. Various techniques have been used to achieve maximum results in the classification of the ecommerce market. From stochastic techniques to neural networks, there is a plethora of techniques that have been applied. In this paper, we use self organising Maps (SOMs) an unsupervised learning technique to study the various factors which can be used to segment the market. On the other hand supervised learning techniques such as Nearest Neighbour (NN) and Support vector machine (SVM) are used to quantitatively classify the purchase behaviour based on various factors. The better classification technique is identified through appropriate measures. Further, evolutionary algorithms are used to augment the performance of these classification techniques. Analysis of the results and various factors affecting it is also performed.
Pricing is one of the most important decisions made by the management (Skouras, Avlonitis and Indounas 2005). It is an important management tool to achieve the objectives of the organization (Kasper, Helsdingen and Vries 2000, p.627). However, pricing decisions do not rely on any one discipline but follow a highly complex process encompassing many different theoretical aspects such as accounting, economics, and marketing (Hornby and MacLeod 1996). It is simultaneously affected by cost and demand conditions which are not parallel and are difficult to align as an efficient decision supporting the strategic objectives of the firm. If the price of a product is too low, it leads to a high quantity of (demand and) sales but, at the same time, to low markup and profit (profitability). If the price is too high, it gives a high markup on variable cost but may lead to losses due to fixed costs and low demand quantity when sales volume does not exceed the breakeven point. In order to reach a reasonable size (and growth) and profitability, the price must be within a certain range. This price range determines in practice the degrees of freedom existing in pricing decision making. In this range, the price should be set to best support the strategy of the firm.
This article uses multidimensional scaling and correspondence analysis to explore how international airline passengers position various air carriers. The analysis has produced perceptual maps of relative positions of airlines and their service attributes. Empirical data were collected from Taiwanese air passengers who had flown from Taipei to Tokyo and to Singapore. Factor analysis was performed to reduce a large number of airline service attributes into a small set of underlying factors. The results of multidimensional scaling analyses reveal that some air carriers are closely competitive; this can be seen by their close proximity in the perceptual map. However, certain airlines possess a unique service quality profile and are not strongly associated with other airlines; such unique firms appear as isolated points on the perceptual map. Interestingly, both multidimensional scaling and correspondence analysis produce similar perceptual maps of the airlines' relative positions and service attributes. However, the advantage of correspondence analysis over multidimensional scaling is that data collection is relatively quick and easy because the analyst is not required to obtain respondents' ratings for each attribute. This study provides specific suggestions about how air carriers on each route can use the results to improve their performance or to build a differential edge.
Many methods thus have been proposed to predict traffic conditions. However, it is difficult to accurately predict traffic jam, because it requires a wide range of knowledge such as statistics and informational technology. It is known that the probability of traffic jam can be evaluated by travel times of passing cars in a location of the motorway. In this paper, we restrict our attention to finding more efficient statistical methods through comparing models. For this reason, we used Multidimensional Scaling statistical methods to study the relationship between traffic conditions and travel time in different locations and times. This work aims at applying basic models to forecast traffic conditions.
The study presents a decision support system, called path marketing analysis, which can help managers to utilize their market knowledge and experience to develop more effective market share growth plans in mature business markets. Through treating marketing mix elements in a hierarchical fashion, the approach identifies key drivers of market share change and then uses this information to uncover, evaluate, and compare alternative opportunities for market share growth. Also included is a structure for estimating the prospective return on assets employed by alternative share growth strategies.
The MIL-STD-188-220C protocol, which is a standard of American Department of Defense, is designed for mobile ad-hoc networks that provide unicast and multicast routing capabilities in a military ad-hoc network environment. In this paper, we model an ad-hoc network consisting of 31 nodes hierarchically, each of which models a radio transceiver based on the MIL-STD-188-220C standard on a battle maneuver vechicle. We propose four possible scenarios to exchange the real-time location information of maneuver vehicles and evaluate the performance in the network, and determine the optimal strategy among them by OPNET simulations. Furthermore, we investigate the required values of system parameters, such as packet generation time interval and data rate to optimize the performance.
Despite its pedagogical predominance during the last four decades, marketing scholars increasingly doubt the value of the 4Ps schema. As a prelude to a precursory structural framework for marketing management, criticisms and previously proposed modifications of the 4Ps are reviewed. Next, the basic premise of Hunt's four explananda of marketing theory—that exchange is the core concept of marketing—is made uncertain by evidence culled from multiple sources. If true, then circumscribing the domain of marketing management from an exchange focus may be problematic. To address this concern and previous criticisms, an alternative structural framework, grounded in a set of basic questions important to marketing practitioners and scholars, is proposed. By outlining a unifying framework for marketing management practice, pedagogy, and theory development, this question set may spur efforts that help dissipate the continuing academician–practitioner miasma.
'Conceptual marketing' can only take managers so far.
ANY discussion of the fundamentals of market research obviously requires a consideration of the factors which go to make up the market itself. The first is the need or utility of the product itself. For example, a snowplow, no matter how well constructed, will not find a market on the equator, nor is there apt to be a need for an electric fan or air conditioning in the arctic regions. The second factor is the matter of timing; many products have failed, not because the product did not have a good utility value, but because it was put out too early or it overstayed the market. A third factor is pricing, and in this respect, for our purposes, we mean the general field within which those forces which determine the price and volume of a particular commodity operate. Putting it another way, the market is the price level at which consumers will absorb a given ...
This book considers marketing management within the overall corporate system of business policy-making, strategic planning and the implementation and control of effective plans. The information requirements of marketing management are highlighted and the marketing information system concept is developed within the framework of managerial information systems. In the chapters which deal with the elements of the marketing ‘mix’, the interrelated nature of these variables is emphasized. The book illustrates how the successful marketing manager can master each ‘weapon’ in the marketing ‘armoury’ and how (s)he can integrate those weapons to achieve the right mix for each product. The accent on integrated marketing continues in the final section where differentiated marketing is presented as an integrative framework and where the systematic control of marketing operations is described. This book is for students who will one day be managers: its emphasis is therefore on what is possible in marketing management and the most effective means by which marketing objectives can be attained.
The study researched the possibility of standardizing the marketing mix by investigating the cross-cultural responses from the United States, Brazil, France and India. The study tested the premise of standardization by determining if respondents perceived specific attributes of a common non-durable consumer product the same or differently. The results indicate the opportunity for dynamic marketing standardization remains limited but applicable within specific cultural country markets. Several attribute perceptions between US and foreign respondents are found to be more similar than dissimilar suggesting advantages may exist for a limited implementation of marketing mix standardization as part of a global marketing strategy.
We develop an empirical model for the adoption process of a new durable product that accounts for consumer heterogeneity as well as consumers forward-looking behavior. Accounting for heterogeneity is important for two reasons. As the mix of consumers with different preferences and price sensitivities could change over time, firms need to update their marketing strategies. Further, it allows for a variety of shapes for the aggregate adoption process over time. As prices for durable and technology products fall over time with firms continually introducing enhanced products, consumers may anticipate these prices and improvements and delay their purchases in the product category. Forward-looking consumers optimize purchase timing by trading off their utilities from buying the product and their expectations on future prices, quality levels, and brand availability. Such forward-looking behavior will result in price dynamics in the marketplace as price changes today influence future purchases. And it results in different shapes of the new product sales pattern over time by influencing the time to take-off. We show how the parameters of our model can be estimated using aggregate data on the sales, prices, and attributes of brands in a product category. We apply our model to market data from the digital camera category. Our data are consistent with the presence of both heterogeneity and forward looking behavior among consumers. At the product category level, we are able to decompose the effects of the entry of Sony into primary demand expansion and switching from other brands. At the brand level, we find that there exist several segments in the market with different preferences for the brands and different price sensitivities leading to differences in adoption timing and brand choice across segments. For a given brand, we show how the changing customer mix over time has implications for that brands pricing strategies. We characterize how price effects vary across brands and over time and how price changes in a given time period influence sales in subsequent periods. Model comparison and validation results are also provided.
Conjoint analysis is used to understand how consumers develop preferences for products or services, which encompass, as usual, multi-attributes and multi-attribute levels. Conjoint analysis has been one of the popular tools for multi-attribute decision-making problems on products and services for consumers over the last 30 years. It has also been used to market segmentation and optimal product positioning. In spite of its popularity and commercial success, a major weakness of conjoint analysis has been pointed such that respondents participating in conjoint experiment have to evaluate a number of hypothetical product profiles. To reduce the number of hypothetical products, this paper proposes a systematic method, called data fusion, and explores the usability of various data fusion techniques. The paper evaluates traditional data fusion (correlation-based), hierarchical Bayesian-based data fusion, and neural network-based data fusion.
This study mines customer behavior to assist managers in developing better promotion and other relevant policies for a firm. The association rules of the relational database design are implemented in the mining system which provides electronic catalog designs and promotional policies. It provides marketing managers with a useful tool to rapidly search for valuable information based on customer transaction information. Thus, it enables marketing managers to rapidly establish marketing strategies to enhance sales and profit. It results in better sales for the firm a retail store mall.
Multidimensional scaling (MDS) is a statistical tool for constructing a low-dimension configuration to represent the relationships among objects. In order to extend the conventional MDS analysis to consider the situation of uncertainty under group decision making, in this paper the interval-valued data is considered to represent the dissimilarity matrix in MDS and the rough sets concept is used for dealing with the problems of group decision making and uncertainty simultaneously. In addition, two numerical examples are used to demonstrate the proposed method in both the situation of individual differences scaling and the conventional MDS analysis with the interval-valued data, respectively. On the basis of the results, we can conclude that the proposed method is more suitable for the real-world problems. q 2005 Elsevier Ltd. All rights reserved.
Fundamentals of marketing research CA: Sage Publication, Inc. Song, I A micromodel of new product adoption with heterogeneous and forward-looking consumers: Application to the digital camera category
- S Smith
- G Albaum
- P K Chintagunta
Smith, S., & Albaum, G. (2005). Fundamentals of marketing research. CA: Sage Publication, Inc. Song, I., & Chintagunta, P. K. (2003). A micromodel of new product adoption with heterogeneous and forward-looking consumers: Application to the digital camera category. Quantitative Marketing and Economics, 1(4), 371–407.
Marketing engineering
- G L Lilien
- A Rangaswamy
Lilien, G. L., & Rangaswamy, A. (2002). Marketing engineering (2nd ed.). New Jersey:
Prentice Hall.
Formation of Brand Concept
- S Hong
Hong, S. (1999). Formation of Brand Concept. In Invisible roots. Seoul, Korea: Bakyoung-sa.