Consumer Perception of Mobile Phone Attributes

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1 Consumer Perception of Mobile Phone Attributes Tao Zhang 1, Pei-Luen Patrick Rau 2, Jia Zhou 2 1 Department of Electrical Engineering and Computer Science Vanderbilt University, TN 37211, USA 2 Department of Industrial Engineering, Tsinghua University, Beijing, , China ABSTRACT This paper reported results from a questionnaire survey of consumer perception of product attributes of mobile phones and how they consider the importance of each product attribute. The questionnaire contained 35 items covering brand, physical attributes, functional attributes, and beneficial attributes. All the items were measured with 7-point Likert scale anchored from strongly disagree to strongly agree. The questionnaire was administrated online to a broad sample (N=215) in China. An exploratory factor analysis was conducted to find out the latent constructs of mobile phone product attributes, which also reflect consumers common idea of attribute category. Eight factors, accounting for 62.88% of the total variation, were identified: common functions, appearance, multimedia functions, connectivity, personal information management functions, body design, brand & country, and product image. These attribute factors can be used as a basis for understanding of product attributes and its influencing factors. Results from the factor analysis also provide information about what consumers are concerned about when they evaluate mobile phones or make purchase decisions. Keywords: Product Attributes, Perception, Mobile Phones INTRODUCTION The perception of various product attributes gives the first impression for consumers, particularly when they have limited time and bandwidth to do a thorough research on a new product. This perception of attributes also has strong relation with consumer judgment of whether the product will satisfy their needs. Studying the structure of product attributions based on consumer perceptions will help practitioners to understand consumers acceptance of products. This is

2 2 especially important for mobile phones as more and more technologies and functional designs have been integrated into new mobile phones. Consumer requirements of mobile phone are now not limited to the basic communication functions, but also on functions for other mobile applications, efficiency, ease of use and comfort. Unlike other interactive systems (e.g., desktop computing), consumer criteria of judging benefits expected from mobile phones include factors like function specification, aesthetics, brand image, self-feeling and user experience. These factors altogether add influence on the overall consumer perception. Therefore, the objective of this study was to provide a quantitative and structural assessment of consumer perceptions of product attributes of mobile phones. LITERATURE REVIEW PRODUCT ATTRIBUTES Earlier studies such as Lancaster (1966) held that attributes are the objective physical aspects of a product. He said that people do not acquire products for the sake of the products themselves, but for the utility that is produced by characteristics of the products attributes. However, many of the product characteristics that are important from the point of view of consumers as well as designers are neither physical nor objective. Therefore, according to Grunet (1989), product attribute is any aspect of the product itself or its use that can be used to compare product alternatives. Each alternative can (but need not) be characterized by all attributes, that is, using one attribute does not preclude using another (Nelson, 1970). Attributes may concern concrete product properties, practical consequences the product and its use and possession may cause, or consequences related to consumers personal values. Product Attributes are requirement factors placed on a product from a consumer. Every product item is viewed as a combination of correlative product attributes by the consumer. The designed functions of the product, together with the appearance, price, brand, package and after-sale service, are all parts of product attributes. Attribute is said to be important if a change in the individual s perception of that product attribute leads to a change in the attitude toward the product. (Jaccard, Brinberg, & Ackerman, 1986). Attribute importance is characterized by the salience and determinacy of an attribute. Salience refers to the accessibility of the attribute, and determinacy to the correlation between an attribute and overall preference. Lefkoff-Hagius and Mason (1990) created a synthesis from a number of earlier studies and divided product attributes into the three categories: characteristics attributes, beneficial attributes and image attributes. Characteristics attributes are related to the physical properties of a product; beneficial attributes refer to benefits or risks that the product may cause; and image attributes are properties of the product that have an ability to define the product owner s relation to other people or self.

3 Chapter title 3 INFLUENCE OF PRODUCT ATTRIBUTES Consumer perception of product attributes can influence the formation and change of attitude, thereby impose its influence on buying behavior. Kotler and Armstrong (2005) said that consumers regard product as the combination of product attributes which are capable to satisfy their interests or requirements. Consumers make evaluation and choice according to certain rules regarding the performance of product attributes, and the importance they put on every attribute. Payne (1976) suggested that consumers attach different importance on product attributes. In certain occasions, only one single product attribute can lead to the buying decision, while in some other occasions there is a complex process when they are making any decision based on product attributes. Bahn et al. (2007) studied how feel of material, elasticity, tactile oneness, shape, and color of the passenger car crash pad influences satisfaction. The results indicated that softness of material was the key affective response factor of satisfaction. Product attributes also influence affect. Seva et al. (2007) found strong relationship between attributes of mobile phone and prepurchase affect. For example, slimmer phones increase feeling of contentment and encouragement, larger display increase feelings of amazement and encouragement. Fishbein (1975) proposed the Multi-attribute Attitude Model, in which he stated that the attitude towards certain products will be reflected by the evaluation of important attributes, then attitude can be assessed by measuring the evaluation of these attributes: A o o n i 1 b e i i, where A = Attitude towards the product b = The strength of belief on product attribute i i e = The performance rating of product attribute i i n = Number of important product attributes METHODOLOGY ITEMS OF PRODUCT ATTRIBUTES GENERATION Based on examination of prior work on similar products and analysis of the characteristics of mobile phones, an initial pool of items was developed. Items about function specification were based on the official websites of major mobile phone manufacturers. More items were developed by the author to cover all the three classifications of product attributes (characteristics attributes, beneficial attributes and image attributes). All the items were measured with 7-point Likert scale anchored at strongly disagree and strongly agree. Two criteria were used to determine which product attribute information will be presented in the

4 4 questionnaire: the respondent should understand what the specified attribute is; and the attribute should be relatively important to consumers during their assessment of perceived usability. Initial items of product attributes were firstly examined by the authors according to the correlation between items, and then critiques of items were sought from a focus group discussion. Three Ph.D. students and two master students majoring in Human-Computer Interaction (HCI) took part in the focus group discussion. They were all familiar with the research topic and questionnaire design. The aim of focus group discussion was to check if there were ambiguities in the wording of items, if there were important missing items regarding mobile phone products, and if there were any inconsistencies in the arrangement of items and overall questionnaire design. Several items were adjusted and wording modifications were made from the critiques. Two master students majoring in Social Science and one master student majoring in Economics were then asked to examine the adjusted questionnaire. The focus of their work was to check if there was overlap between items, if there were suggestive wordings in the item descriptions, and if there were questions that may exceed respondents knowledge and proficiency. The author took their feedback and incorporated it in the final revision of the questionnaire. There were 35 items in the final version of the questionnaire. These items were categorized into: brand, physical attributes, functional attributes, and beneficial attributes, which were similar to categories in the study by Lefkoff-Hagius and Mason (1990). DATA COLLECTION The questionnaire was administrated online to a broad sample in China including undergraduate and graduate students in several universities in Beijing, employees working in telecommunication industry, manufacturing industry, consulting company, and the government. A total of 215 responses were collected. As shown in Table 1, although more than half of the respondents are college students, the sample represents a wide range of mobile phone consumers with different age, education level, and income. The majority of respondents are young people with high level of education and middle level of income in China. The questionnaire began with an introduction of the survey objectives, followed by a survey of demographic information, mobile phone usage and experience. Then the list of 35 items was given. Respondents were asked to choose the extent to which they agree with the descriptive items for the mobile phone product attributes. They were encouraged to put down their addresses to get a copy of the result analysis.

5 Chapter title 5 Table 1 Demographic profile of questionnaire respondents VARIABLE CATEGORY NUMBER OF RESPONSES PERCENTAGE Age <20 years 5 2.3% years % years % >30 years 3 1.4% Gender Female % Male % Education Level Occupation Monthly Income High school 3 1.4% Associate degree 6 2.8% 4 years undergraduate % Master student % Doctorial student % Government official /Company manager 7 3.3% Technician/Engineer % Business/Service employee % Student % Others % <1000 RMB % RMB % RMB % >10000 RMB 2 0.9% RESULTS Exploratory factor analysis is a method for reducing the dimensionality of multivariate data and understanding patterns of association among variables, with the underlying common factor model. The model assumes that the observed variance in each measure is attributable to a relatively small number of common factors and a single specific factor. The objective of exploratory factor analysis is to identify the common factors and explain their relationship to the observed data, and the factor solution is derived from the patterns of association in the observations (Lattin, Carroll, & Green, 2002). An exploratory factor analysis was conducted in SAS to determine the latent traits of the items of product attributes. Principal axis factoring approach and the varimax rotation method was used. After deleting one item causing almost equal loadings on two common factors, the result shows that the first eight common factors account for 62.88% of the total variation in data. Items were then assigned to the common factors, given the criteria that factor loadings of items should be higher than 0.5. The result of exploratory factor analysis is shown in Table 2.

6 6 Table 2 Internal consistencies, means, standard deviations and factor loadings of attribute items FACTORS ITEMS MEAN SD FACTOR LOADINGS Common functions (α = 0.89, for = 4.27) Appearance (α = 0.79, for = 3.46) Connectivity (α = 0.70, for = 2.44) Body design ( for =2.15) PIM Functions (α = 0.67, for =2.11) I believe input method is an important feature for me to judge whether the mobile phone is easy to use. I think the short message functions (storage and manipulation) are important for me. I think the phonebook functions (storage and manipulation) are important to me I think the battery time is important I will be attracted by the appearance design of certain mobile phone and then want to own it. If I like the appearance of certain mobile phone, I will be very interested in it I think the body color is important to me I like the mobile phone appearance with special material I think it is a great pleasure to show the special appearance design of mobile phone to others I think the GRRS connection is important I will consider the connectivity (USB/Infrared/Bluetooth/Wifi) when choosing mobile phone. I will consider the accessories available when choosing mobile phone I think one particular body design in more suitable for me I think the body design should not be considered to be important I will ask about the capability to deal with events like temporary note/number taking when buying a mobile phone. I think the date planning functions like notepad, to do list, memo are important to me.

7 Chapter title 7 Brand & Country (α = 0.69, for =1.92) Product image ( for =1.61) I think the voice recording function is important to me. I will only use certain brands of mobile phone. I will choose mobile phones from certain countries. I will exclude mobile phones from certain countries. I believe the mobile phone design partly represents my life style CONCLUSIONS There is no precise definition of product attributes for mobile phones, as consumers generally perceive product attributes in a conceptual way. The notion of product attributes is formed and existing during the perception process. Previous studies on mobile phones mainly considered individual attributes, without a systematic view of how all the attributes influence perception of mobile phones as a whole. This study fills this gap. The exploratory factor analysis was appropriate to find out the latent constructs of mobile phone product attributes, which also reflect consumers common idea of attribute categories. Eight factors were identified: common functions, appearance, multimedia functions, connectivity, personal information management functions, body design, brand & country, and product image, which for 62.88% of the total variation. Important factors such common functions and appearance are identified. Since people use mobile phones for daily communications, they stress the importance of phonebook and SMS functions. Ease of use of input methods also influences their perception of common functions. The quantitative approach used in the present study can be beneficial to similar studies of consumer digital products. Results of this study can be smoothly implemented into design and marketing practice as a perceptive model. Limited resources can be efficiently allocated to important attributes. REFERENCES Bahn, S., Lee, C., Lee, J. H., and Yun, M. H. (2007). A statistical model of relationship between affective responses and product design attributes for capturing user needs. Usability and Internationalization, Pt 2, Proceedings - Global And Local User Interfaces, 4560, Fishbein, M., and Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading. MA: Addison-Wesley.

8 8 Grunet, K. G. (1989). Attributes, Attribute Value and Their Characteristics: A Unifying Approach and An Example Involving A Complex Household Investment. Journal of Economic Psychology, 10, Jaccard, J., Brinberg, D., and Ackerman, L. J. (1986). Assessing Attribute Importance: A Comparison of Six Methods. Journal of Consumer Research, 12(4), Kotler, P., and Armstrong, G. (2005). Principles of Marketing (11 ed.). Prentice Hall. Lancaster, K. J. (1966). A New Approach to Consumer Theory. Journal of Political Economy, 74(2), Lefkoff-Hagius, R., and Mason, C. H. (1990). The Role of Tangible and Intangible Attributes in Similarity and Preference Judgments. In M. E. Goldberg (Ed.), Advances in Consumer Research (Vol. 17, pp ). Provo, UT: Association for Consumer Research. Nelson, P. (1970). Information and Consumer Behavior. Journal of Political Economy, 78(2), Payne, J. W. (1976). Task Complexity and Contingent Processing in Decision Making: An Information Search and Protocal Analysis. Organizational Behavior and Human Performance, 16, Seva, R. R., Duh, H. B. L., and Helander, M. G. (2007). The marketing implications of affective product design. Applied Ergonomics, 38(6),

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