E-Customization Approaches, Their Differences from Traditional Mass Customization - Literature review Example

Chapter 2 E-customisation Approaches 2.1. Definition of e-customization In the age of technological innovation and creativity, marketing of consumer goods has shifted from mass production to mass customisation and more recently to e-customization. The term of mass customization was first introduced by Stan Davis in his book, The Future Perfect (1987). Davis saw mass customization as the next stage of evolution of the markets after mass production introduced during Industrial Revolution. In mass customisation, the market is not a homogenous one but composed of each customer who has individual tastes and preferences (Pine & Gilmore). E-customisation is the next level of mass customisation that reaps the benefit of information technology in order to make the strategy optimal. It refers to the design and development of products to suit the direct needs of the customers through the electronic media, notably the internet. Mass-customised products incorporate market information on customers’ preferences and tastes and hence are information-intensive products (Glazer, 1991, cited in Kaplan and Heinlein, 2006). Hence, information technology that enables mass customisation may be termed as e-customisation that is internet-supported mass customisation. Typically, sales tools based on web-enabled software are used to help customers in the decision-making process and begin the process of production only after the customer has decided on the product parameters. Through a computer-mediated environment (CME), the customer is able to decide to experiment with a creative assembly of the hordes of components available with the producer (Pine, 1994 cited in Jiang, 2000). Such mass customisation strategies have been followed by Dell and Gateway, that provide a number of configurations for the personal computer and laptops that the customer may choose from, Lutron Electronics that customize lighting solutions, and many other companies like Motorola’s Pager Division, Carlton Hotels, Progressive Insurance Company, etc. (Jiang, 2000). Kaplan and Heinlein, 2006 define e-customisation as “a strategy that creates value by some form of company – customer interaction at the fabrication/ assembly stage of the operations level to create customised products with production cost and monetary price similar to those of mass-produced products, where at least one of the three market dimensions – player, product and process – are digital”. 2.2. Differences from traditional mass customization The concept of traditional mass customisation or market segmentation arose from imperfect competition. In order to identify and study the market segments, researchers have used either traditional concepts of microeconomic behaviour or behavioural sciences (Frank et al, 1972, Wilkie and Cohen, 1977). Lancaster (1990, cited in Jiang 2000) lists the reasons for a company to undertake a mass customisation strategy: 1) each customer seeks variety in consumption, 2) different consumers have different tastes, 3) firms can increase profits by increasing variety and 4) firms can set up entry barriers for competitors differentiating products. Although such classification of the needs of mass customisation follows the basic tenets of microeconomic behaviour that drives a company’s strategy, it does not set out the optimal strategy that would also determine the range of variety that a consumer wants or the actual differences in tastes or the range of variety that would create entry barriers in a market. This is where e-customisation comes in to take traditional mass customisation one level up. Muniz and O’Guinn (1996) developed a communication theory that through e-customisation, customers can form groups or communities demanding a particular type of product that is a particular segment. By this, a “representational customer” can be imagined who chooses a particular product in a price range and also that every product has a representational customer. In such an idealised scenario, the company can undertake a segmenting-to-one strategy. Lancaster (1990) notes, “The fundamental structure of all variety problems, for the individual firm as well as society, is the interplay of two elements in the economy – the existence of a gain from variety and the existence of scale economies of some kind. If there are no economies of scale associated with individual product variants (in distribution as well as production) then it is clearly optimal to custom produce to everyone’s chosen specification, one-to-one segmenting. If there is no gain from variety and the scale economies, then it is clearly optimal to produce only a single variety if those economies are unlimited, or only such variety as uses scale economies to the limit (all products at minimum average cost output)” (quoted in Jiang, 2000). E-customisation, that is mass customisation through automation, has been enabled by flexible manufacturing techniques and information technology to collect data on customer preferences (Kotler, 1989, Pine, 1993). While the traditional mass customisation was considered a service provided by the producer (Davis, 1987, Lampen and Mintzberg, 1996, von Hippel, 1998), e-customisation integrates the customer in the value chain of the production process. The company then acquires information on the needs and requirements of the customers and translate it into the product specifications (Zipkin, 2001). This distinguishes e-customisation as a “synchronic and interactive” process as opposed to a “linear and transitive” process of mass customisation. E-customisation, therefore, results in a much wider variety of products than traditional mass customisation. Not only is there integration of the customer in the production process and in the choice of the product differentiation parameters, but also in user innovation that may be integrated with technology development or with interactive marketing by which customers are incorporated into the marketing and sales levels (Kaplan and Heinlein, 2006). Researchers found that mass customised products have price levels similar to those of mass produced products, particularly in markets that are highly volatile and mass customisation achieves economies of scale as a result of targeted production. In a perfectly competitive market, companies that produce mass-customised products would be able to gather all information regarding customers’ preferences and tastes and hence produce products perfectly tailor-made for customer segments. However, perfect information flow does not happen and an efficient customer relationship “will depend on the firm’s ability to learn about what the [customer’s] needs are in the first place – on how well it is able to collect and process information about its customers” (Glazer, 1999 quoted in Kaplan and Heinlein, 2006). Hence, e-customisation necessitates an integrated knowledge flow and interactivity through the Internet between the customer and the company, data collection and information processing (Pine, Peppers and Rogers, 1995, Kannan, 2001 and Zhuang and Lederer, 2003). Various Internet techniques like online registration, cookies, collaborative filtering and data mining are used to make the data collection and information processing possible (Pine, Peppers and Rogers, 1995). When used in combination with e-commerce, that is when buying and selling is organised electronically, mass customisation becomes all the more profitable. Choi, Stahl and Whinstone (1997) distinguish mass customisation from e-customisation on the basis of players, products and processes. In traditional mass customisation, all three elements are physical while in pure e-customisation, all three are purely digital. There may also be different combinations of physical and digital in the product, process and players as well. For example, a newspaper may be in the traditional form of a paper product, customised according to the customers’ needs physically by designing the process of arranging articles on specified pages physically using ink on paper and delivering to the customer’s doorsteps physically. Alternatively, the newspaper may be provided online, designing the web-pages according to customer’s choices and reaching the customer digitally. The newspaper may also be provided in paper form as well as in the online version. 2.3. Different approaches to e-customisation Bae and Plumlee noted that competition and cost consciousness have forced apparel retailers and manufacturers to focus on customers and a supply chain management process that aims to reduce time and cost. The Quick Response strategy that incorporates electronic and mechanical technologies as well as management practices that are based on trust between industry segments and customers reduces the time taken to convert fiber to fabric to garment for delivery to the customer. The basic principle of this strategy is to formulate the design process in accordance to customer preferences. This strategy not only reduces the risks of incorrect sales forecasts but also improves quality of service and hence customer satisfaction. But it requires a number of technologies like bar coding, CAD/CAM and electronic data interchange. Pine & Gilmore have classified mass customization strategies of firms based on changes in product (real customization) and representation (promotional communication): 1) adaptive strategy, 2) collaborative strategy, 3) transparent strategy and 4) cosmetic strategy. Adaptive strategy involves standardized products but customers themselves can do customization. Collaborative strategy involves designer’s identifying the customers’ needs and product being made accordingly. Transparent strategy refers to designing the required goods and services by observing the behavior of the customers. Cosmetic strategy is one where standard products are packed differently for different customers. The firm must realise that there is an optimum customisation strategy at which profits may be maximized. American Fit Corporation, a New YorkCity based clothing company uses its web pages to advertise and promote their customizable clothing, including men’s and women’s fashion clothing, such as khaki pants, jeans, shirts, skirts, etc. Their motto is “Don’t throw a fit, get your clothes custom fit.” The system known as “Virtual Taylor” enables a customer to “design and customize clothing made just for you”. The website offers 10 different styles of clothing, a choice of a myriad of fabrics and colors, and 3 options: by option #1, a customer can select a regular size and the retailer would alter the waist and inseam; by option #2, the customer can enter body measurements so that the company may fully customize the order and by option #3, the customer can choose the most desired pattern (with customized features) based on individual previous orders on the site. In other words, they offer the customer a choice of a standard product with some adjustments, i.e., an adaptive customization strategy (option #1), a fully customized product (option #2), and build a database of customer information, i.e., implement a customer integration strategy in the form of a customer option (option #3) (www.americanfit.com, 2001). LandsEnd, another popular clothes company located in Dodgeville, Wisconsin, has a web page that allows adaptive customization of its products on-line, which LandEnd calls “LandEnd’s Custom.” The web page makes it possible to custom design shirts and pants in almost any way, shape or form. It has a virtual on-line model (an image of a person), which the customer can change according to their preferences, enabling the customer to view the clothing they have chosen (www.landsend.com). Shirt Creations, a clothing company based in New York City, has developed a web page that allows customers to adaptively customize shirts online (www.ShirtCreations.com). Mass customization business model in the apparel industry is supported by a supply chain strategy, body scanning technology for fit customization and CAD/ CAM technologies for pattern making and digital fabric making. The Civil American and European Surface Anthropometry Resources (CAESAR) study in 2004 using a sample of 10,000 men and women from various cities of America to survey body sizes and shapes of people in the age group of 18-65. The results have been used by over 50 apparel companies including Victoriaas Secret, Jockey, Chicoas and J C Penny. Body scanners usually use white light technology, stimulating the triangulation of laser beams, at a low cost. These can be used to collect data on body sizes of specific target groups in order to develop size specifications so that there is consistency in fit. As a result of using body scanning technology, J C Penny has been able to evolve mass customized jeans like the Catherine fit (fitted slightly above the waist), the Audrey fit (more fitted at the waist) and the Marilyn fit (more fitted just below the waist). To derive these products, J C Penny surveyed 67 women between sizes 4 and 16. It found that 43% of its customers were unshaped, 33% was apple shaped and 19% was rectangle shaped. From this data, the retailer arrived at the targeted body specifications and slightly increased the bust, waist and hip measurements. Additionally, the psychographic data identified four lifestyle segments: 1) conservative (functional, not influenced by trend and brand loyal); 2) traditional (stylish but classic, expect performance, quality and value); 3) Modern (fashion aware, open to change, style driven); and 4) trendy (image conscious and want to be noticed). Through these sets of data arrived at with customer collaboration, J C Penny organised its merchandise in order to target at all segments of customers in accordance to lifestyles, age-groups and body sizes (just-style.com). Computer applications for designing of clothing use graphics as well as CAD technology through interactive design, simulation and visual features. While graphics are the first stage of design simulation, a large number of techniques have evolved over the recent past to enable virtual designing and collaboration between customers and garment producers. This involves the development of efficient mechanical simulation models that could replicate the characteristics of cloth that has deformable and non-linear characteristics. Also, since the cloth interacts with the body, the technology would need to determine the geometrical contacts that affect the behavior of the cloth. Hence, these require sophisticated computational methods that could make the designing process efficient and fast. For real-time garment manufacturing, cloth simulation is an important element of designing. Interactive models by using CAD tools like Lectra, Gerber, Investronica enable 2-D designing of patterns but the actual prototyping is still done manually (Volino, et al 2005).. The process of using information technology is essential in the modern day for any customisation strategy. However, use of technology also alters the dimensions of cost, production processes and capturing market information (Clemons, 1994). Flexible manufacturing processes are essential to support the e-customisation process (Sheth and Parvatiyar, 1995) while transaction costs incurred by the firm in shifting suppliers and service providers to manage inventories depends on a mutually beneficial relationship with customers (Gronroos, 1994). Hence, the marketing competencies within a company and the degree of one-to-one communication with the customer needs to be resolved for an effective e-customisation process. To begin with, a company may decide to offer mass-customized products only if it has been able to “develop interactive productive systems so that the consumer can identify his or her needs and then have the product… designed to meet these needs” (Blattberg & Glazer, 1994, quoted in Kaplan et al, 2007). Hence, the pre-requisites of effective e-customisation are a modern information system and a flexible manufacturing system. Many researchers have in fact found e-commerce to be complementary with e-customisation (Lee, Barua and Whinston, 2000; Gefen & Straub, 2003; Gefen, Karahanna and Straub, 2003, all cited in Kaplan et al, 2007). Some researchers have found that customers who are heavy users of a particular e-customised product are the early adopters of future innovations in technology (Dickerson & Gentry, 1983) while others postulate that use of a particular technology results in resistance to a new innovation (Shugun, 1980) and longer time to get accustomed to a new customisation process (Bardacki and Whitelock, 2003). Customer satisfaction is also seen to have a positive relationship with trust in the organisation to offer desired level of services (Johnson, 1999). Increase in trust is also association with decreasing risk and hence customers who are satisfied with an organisation’s product is more likely to adopt to mass customisation by the same company (Ram and Sheth, 1989). Since familiar attributes of a product increase the chances of adoption by customers, customisation as an add-on to the already achieved familiarity improves the evaluation of the mass-customised product (Rogers, 1995) Burns and Bryant noted that mass customization is essentially enabled by computer technology and a four-step supply chain. First, the representative measures are taken with the help of the customer; the measurements are entered into the computer and the garment specifications altered; the altered measurements sent to the fabric-cutting factory for altering the garment and lastly, the finished piece of garment bar coded, assembled and retailed. Anderson et al expanded the customization strategy for the apparel industry through four options: 1) expanded selection/ search, 2) design option, 3) co-design and 4) total custom. In the first stage, the customer is provided with various options to search different categories of apparel. In the design option, the customer can select various designs, colors, fabrics, etc. through computer aided technology. In the co-design option, the customer gets the option for personalised fit and in total custom, the customer can communicate with the retailer and the manufacturer. Burns and Bryant report that three types of mass customization are most commonly found in the apparel industry: 1) personalization of products such as modification of finished product. 2) fit-customization with the help of 3D body scanning system; and 3) design customization such as the use of CAD/CAM. Eun Lee and Chen (2000, p3-6) recommend a list of the technologies required in the apparel industry if mass customization has to be successful: 1) Body scanning system with all dimensions; 2) Single-ply cutting should be replaced with multi-ply cutting to reduce cutting costs; 3) Standardized CAD system should be made available so that there is compatibility between hardware and software across the industry; and 4) manufacturing system and organization structures have to design to suit mass customized production. Lee and Chen (2000) elaborates the e-customization process in the apparel industry through the use of computer technology in which the customer gets the advantage of body scanning through smart cards and intelligent search options as the retailers and manufacturers provide more design options. However, as Lee and Chen notes, e-customization can be successfully implemented only if every step in the supply chain is flexible and able to react quickly to changes in demand in designs. Since individual design specifications are unique, there has to be a clear understanding on the part of the manufacturers to undertake the specifications. The success factors of e-customisation are, of course, dependent on the extent of the company’s expertise to communicate with the customer, engaging the latter in an interactive process at the stage of designing and fabrication of the product, the collection of data and information of customer needs and desires, the sifting of the data in meaningful modules and organising the production process in accordance to the market segmentation thus arrived. The competitive environment supports such a segmentation and e-customisation strategy. Market volatility, instability and unpredictability of demand result in heterogeneity of customer segments. Hence, greater the market volatility, greater is the heterogeneity and hence greater the potential to e-customisation. The company that can garner the advantages of being the first mover is likely to be the most gainer. For example, Amazon was the first mover in transferring the physical bookstore to the digital arena hence has been the most successful (Jiang, 2000). The central issue in e-customisation is to get more customers than earning more margins, as opposed to the traditional mass customisation. Focussing on gaining market share through anonymous transactions with segmented customers is the key success as well as challenge for e-customisation. For this, collection of data should be more innovative than the traditional market research. Typically in e-customisation, transaction database derived from interactive communication with the customer is used. Ultimately, the rapid development of technology – computers, telecommunications, product development (CAD-CAM), flexible manufacturing processes, and distribution mechanisms (express delivery) – is the key to the success of e-customisation (Jiang, 2000). Works Cited Agarwal, R & Karahanna, E (2000). “Time Flies when you’re having fun: Cognitive absorption and beliefs about Information Technology Usage”. MIS Quarterly. 24(4) Bardacki, A and Whitelock, J (2003). “Mass-customisation in marketing: The Consumer Perspective”. Journal of Consumer Marketing. 20(5). Blattberg. R.C & Glazer, R (1994). Marketing in the Information Revolution. In The Marketing Information Revolution ed. R.C Blattberg, R Glazer and J.D.C. Little. Boston: Harvard Business School Choi, S, Stahl, D O and Whinstone, A.B (1997). The Economics of Electronic Commerce. Indianapolis: MacMillan Technical Publishing. Clemons, E K (1994). “Segmentation, differentiation and flexible pricing: experiences with information technology and segment-tailored strategies”. Journal of Management Information Systems. Vol 11 Davis, S M (1987). Future Perfect. Addison-Wesley, Reading. MA Dellart, B. G. C and Stremersch, S (2005). Marketing Mass-customised Products: Striking a Balance Between Utility and Complexity. Journal of Marketing Research. 42(2). Frank, R.E, Massey W.F and Wind, Y (1972). Market Segmentation. Prentice Hall Englewood Cliffs. NJ Gefen, D & Straub, S (2003) The Relative Importance of Perceived Ease in IS Adoption: A Study of E-Commerce Adoption. Journal of the Association for Information Systems 1(8). Gefen, D, Karahanna, E and Straub, S, (2003). Trust and TAM on Online Shopping: An Integrated Model. MIS Quarterly. 27(1) Gilmore, J.H and Pine, B.J (1997). “The Four Faces of mass Customisation”. Harvard Business Review.75 (1). Glazer, R. (1999). “Winning in Smart Markets”. Sloan Management Review. 40(4). Gronroos, C W L (1994).”From marketing mix to relationship marketing: towards a paradigm shift in marketing”. Management Decision. Vol 32 Hart, C.W.L (1995). “Mass Customisation: Theoretical Underpinnings, opportunities and limits”. International Journal of Service Industry management. Jiang, P (2000). Segment-based Mass Customisation: An Exploration of a new Conceptual Marketing Framework, Internet Research: Electronic Networking Applications and Policy, Volume 10. No 3 Just-style.com, SSSizing up garmet fit issue: Company Overview, August 9. 2007 Kaplan, A.M and Heinlein, M (2006). Towards a Parsimonious Definition of Traditional and mass Customisation. Journal of Product Innovation Management. 23 Kaplan, A.M, Schoder, D and Heinlein, M (2007). Factors Influencing the Adoption of Mass Customisation: The Impact of Base Category Consumption Frequency and Need Satisfaction. Journal of Product Innovation Management. 24 Kannan, P.K. (2001). “Introduction to the Special Issue: Marketing in the e-channel”. International Journal of Electronic Commerce. 5(3). Kotler, P (1989). “From Mass Market to Mass Customisation”. Planning Review. September-October. Lancaster, K (1990). “The economics of product variety: A Survey”. Marketing Science. Vol 9 Lampe, J and Mintzberg, H (1996). “Customising customisation”. Sloan Management Review. 38(1). Lee, C, Barua, A and Whinston, A.B (2000). The Complementarity of Mass-customisation and Electronic Commerce. Economics of Innovation & New Technology. 9(2). Munoz, Albert, Jr. and O’Guinn, T.C (1996). “Brand community and the sociology of brands”. In Corfman, L Lynch, J.G, Jr. (Ed). Advances in Consumer Research, Association for Consumer Research, Provo UT. Pine, B.J (1994). “Customers don’t want choices”. Managers Journal, Wall Street Journal, 18 April Pine, J.B. (1994). Mass customisation: The New Frontiers in Business Competition. Harvard Business School Press, Boston, MA. Pine, B J, Peppers, D and Rogers, M (1995). “Do you want to keep your customers forever?” Harvard Business Review. 73(2). Robinson, J (1938). The Economics of Imperfect Competition. Macmillan. London von Hippel, E (1998). Economics of Product Development by Users: The Impact of “Sticky” Local Information. Management Science. 44(5). Rogers, E.M. (1995). Diffusion and Innovation. 4th ed. New York: Free Press Shugan, S M (1980). The Cost of Thinking. Journal of Consumer Research. Sheth, J N and Parvatiyar, A (1995). “Relationship marketing in consumer markets: antecedents and consequences”. Journal of the Academy of Marketing Sciences. Vol 23 Volino, P, Cordier, F, Magnenat-Thalmann, N (2005). From early virtual garment simulation to interactive fashion design. Computer-Aided Design 37 Wilkie, W.L and Cohen. J.B (1977). “An overview of market segmentation: Behavioral Concepts and Research Approaches” Marketing Science Instritute Working Paper. Zipkin, P (2001). The Limits of Mass Customisation. Sloan Management Review. 42(3). Zhuang, Y and Lederer, A L (2003). An Instrument for Measuring Business Benefits of eCommerce retailing. International Journal of Electronic Commerce. 7(3). Read More