Revista Espacios. Vol 34 (Nº 2) Año 2013

The purpose of this paper is to present the findings of a longitudinal study which explored Brazilian low income consumer attitudes regarding technology and acceptance of mobile phone innovation.

The main reasons for conducting this research are related to the importance of mobile phone as an instrument of both communication and socialization, the size of cell phone market in Brazil (it is world´s fifth market, 255 million cell phones in May 2012 and density of 129.3 phones per 100 inhabitants, Teleco, 2012) and the low-income segment (also referred as social pyramid base or socio-economic classes CD) which represents 78% of Brazilian population (Cetelem Bgm, Estado de S.Paulo, 2011). In Brazil, 82% of cell phones are prepaid (Teleco, 2012) which means that a campaign focusing on Internet access on mobile phones would not be advisable; on the other hand, Bluetooth marketing, which offers contents and software free of charge, may be an appropriate tool for this public.

Additionally a survey conducted by Gfk (2010) explains that mobile phone is the leader in intention of electronic devices exchange between Brazilians population, the research points that 40% of the interviewed intended to change of model in 2010. This rate tends to increase between the young (53%), interested in more distinguishing devices such as access to the Internet and high resolution camera.

Many studies lead to the conclusion that cell phones contribute to social and digital inclusion of low-income population, making social relations and communication easier as well as developing civic consciousness (Lex, 2008; Bacha; Vianna; Santos, 2009). Despite the range of this tool, it is noticed that there are few articles exploring this segment.

This work is aimed at contributing to a better understanding of low-income segment, regarding the analysis of appropriate tools and public target segmentation, which are essential to mobile cell phone marketing performance as well as the benefits companies may obtain.

2. Theoretical background

At first, a bibliographic survey was conducted in order to deepen understanding of emerging social classes and their role in society as well as introduce approach related to technology and mobile phone innovation.

When it comes to today mobile phone market it is an environment in which technology is evolving at high speed and consumers can be confused by the increasing amount of innovations at the device as well as the service level, turning the success of innovations highly unpredictable (Ferreira, Rocha, 2011).

There are many different models and theoretical perspectives for the understanding the determinants of acceptance and usage of new technologies: the Theory of Diffusion (Rogers, 2003); Theory of Reasoned Action (TRA), Technology Adoption Model (TAM), (Decomposed) Theory of Planned Behavior ((D)TPB) (Fishbein, Ajzen, 1975; Ajzen, 1985; Davis, 1989; Taylor, Todd, 1995); techonology readness and cognitive evaluation (Lin al.,2007), diffusion process and adopters personal characteristics (Gatignon, Robertson, 1991). Rogers (2003) considered five innovation attributes (relative advantage, compatibility, complexity, trialability and observability). Roach (2009) focus on three innovation attributes to exert significant influence over an individual’s adoption decision: relative advantage, compatibility and complexity. Relative advantage refers to the degree to which an innovation is perceived as being better than the innovation it replaces; compatibility refers to the degree that an innovation is considered compatible with the existing values, past experiences and needs of the potential adopter; and complexity refers to the level of complexity associated with understanding and using the innovation.

In Brazil, the following authors can be emphasized: Souza, 2002; Hernandez, Mazzon, 2008; Pires; Costa, 2008; Ferreira, Rocha, 2011 and Pádua Jr., Prado, 2005 for applying theoretical models on innovation, technology adoption theories and behavior predicting based on attitudes and intentions towards a behavior.According to Ferreira e Rocha (2011) the main focus of the diverse lines of research on technology acceptance was the implementation and use of new technologies in the workplace environment, leaving to a secondary place the final consumer.

Considering mobile phone, frequently products that have just been offered to consumers are substituted by others that promise more and better resources. The technological sophistication increases the variety of products and services but it increases also the consumer difficulty in understanding and dealing with these innovations, turning complex the decision on its insertion in daily life. Although the products of high technology play an important role in daily life, few studies have been carried in order to focus specifically in the field of consumer behavior and specifically of the low income consumer (Mick, Fournier, 1998; Souza, 2002; Ferreira, Rocha, 2011).

As for attitudes, the term derives from the Social Psychology and its most accepted definitions relate attitude to the favorable or not evaluation of some specific object. The attitude construct is composed of three dimensions cognitive, affective and behavioral. However, none of them can be taken as the only determinative behavior factor. In fact, the attitudes or intensions do not determine the purchase behavior, but in general they are useful to predict consumer behavior. Attitudes can help to evaluate marketing actions and can also be used to segment a market (Engel, Blackwell, Miniard, 2000).

Understanding the factors that have influence in consumers’ acceptance and adoption of new technologies is interesting both for companies and for the academic research. Consumer relation with high technology products and services can be subject to emotions such anxiety and fear, related to their previous experiences (Pereira, Rocha, 2011).

Pádua Jr., Prado (2005) consider that currently technological innovations occur in such a high speed that when finally a person become familiar to one definitive product, the same becomes obsolete for the launching of a more advanced version. In many cases, the speed of launching of new features higher than the speed of diffusion and learning. The consumer may find that the innovation is very complex, that it needs a great effort of learning or he may postpone the purchase seeking for more information or waiting till a friend buys the product to diminish the uncertainty on the same.

3. Methodological procedures

This work aims at answering the following question: how low-income population accepts technology and mobile phone innovation in São Paulo, Brazil. The main objective of this project is to evaluate the acceptance of technology and mobile phone innovation by low-income population in São Paulo, Brazil. Here are some specific objectives: to evaluate personal characteristics (demography and use of mobile phone); to evaluate attitude concerning technology; to evaluate attitudes related to the adoption of technological innovations in cellular, beyond generating a typology of consumers on the basis of the mentioned characteristics.

It is a longitudinal research, survey-type study, conducted with two samples of 449 individuals in 2006 and 420 individual in 2011, with low income population from CD socioeconomic class, inhabitants of the city of São Paulo, mobile phone owners and users. Taking socioeconomic classes into account, the samples were selected according to the Brazilian Economic Classification Scheme (ABEP, 2003), by whichaccording to the score obtained for owning specific material possessions as well as the education level of the head of the family, it is established a connection with the power to buy of a population.

The survey was conducted in neighborhoods where pedestrian flow was intense, such as Penha, Cangaíba, Arthur Alvin, Itaquera, Guaianazes, São Mateus, Mooca; Ipiranga, Sacomã, Jabaquara and Vila Maria, because they are considered typical low-class neighborhoods. Some studies reveal that a sample that comprises students only is more appropriate for a mobile marketing research because the number of young people who use cell phones and master mobile services and software is higher (Leppaniemi, Karjaluoto, 2005).

The questionnaire comprised closed questions in order to evaluate interviewees’ behavior as well as their biography, such as gender, age and mobile phone usage and Likert scale of agreement on attitudes.

Measurement instrument item scales were adapted from previous studies. Attitudes towards technology and mobile phone innovation acceptance were assessed using a 5-point Likert scale (I completely agree, I partly agree, indifferent, I partly disagree and I completely disagree), which were modified versions of those used in other empirical studies of technology driven innovation (Pádua Jr. and Prado, 2005; Roach, 2009; Rogers, 2003). The answers given to the questionnaires were typed into survey software SPSS.

Data obtained were analyzed through usual position and dispersion measurement as well as application of multivariate statistics technique, which make it possible to analyze sets of data consisting of two or more variants (quantitative). Among the existing techniques the factor analysis and cluster analysis were selected. Prior to the application of the techniques mentioned (factorial and cluster analysis), a careful data analysis was performed.

Factor analysis aims at finding a set of latent factors in a bigger set of variants, which may summarize the existing information with little loss; it also make it possible to select variants that represent the original set. In order to facilitate the interpretation, rotated factor loadings are used according to Varimax method (Hair Jr. et al, 2006).

The scales were evaluated regarding content validity that is "the extent which a specific set of items reflects a content domain” (DeVellis, 2003, p. 49).

The assumption that the construct set of items is unidimensional was considered. Hair Jr.et al (2006) argues that the factorial analysis plays a crucial role to evaluation if the construct is unidimensional. The factor load of all items was superior the 0,5. The tests on the adequacy of the factorial analysis had also been satisfactory. The Kaiser-Meyer-Olkin (KMO) is a measure of sample adequacy. KMO was equal 0,606 for scale of attitudes with regard to technology and 0,640 for scale of adoption of cellular innovations. They were considered satisfactory. The internal consistency was equated with Cronbach´s coefficients had been found superior to 0,5 for all constructs (Malhotra, 2001; Hair Jr, 2006).

According to Malhotra (2001), cluster analysis is an interdependency technique. The steps to perform cluster analysis followed the literature on the subject (Malhotra, 2001; Hair JR, 2006). Taking into account the variants studied, cluster analysis aims at gathering individuals in many groups in a way that there is homogeneity inside the groups and heterogeneity outside them. Hierarchical and optimization are among the most used clustering methods. Hierarchical method was used during the first phase, when interviewees were grouped through a process that is repeated until a dendogram is established.

In order to understand the consumer, it is necessary to understand the differences or heterogeneity of segments. One of the most traditional approaches uses the marketing research to identify a priori segments. In the a priori segmentation, database is divided in groups in order to perform compared analysis. Groups are defined in advance because heterogeneity is easy to identify, group separation is almost obvious. In the a posteriori segmentation, heterogeneity is not easy to identify, so techniques are applied in order to separate database in groups (clusters), such as cluster analysis.

The choice of variants was based on theoretical references in order to fill an existing gap in the literature, that is, the lack of studies focusing low income population.Cluster analysis dendogram has shown very agglomerations very distant for making a choice regarding measurement of conglomerates distance. Delimitations were visually established, taking into account points of considerable changes. Also researchers´ intuition played an important role when defining the number of conglomerates (Malhotra, 2001).

Clusters have been identified using non-hierarchical K-means cluster analysis through the use of SPSS software 15.0. Tests have been applied: t-test is used to compare average values in two groups (clusters); ANOVA is used to compare average values in more than two groups (clusters), and chi-square is used in many situations; in this study, to identify the existence of connections among category values

4. Results

Comparative study of sample profile

The following table (Table 1) presents the Sample Demographic Profile from the two samples by gender socioeconomic class, age and education. In short it can be observed that the samples are equitably distributed between men and women. It shows predominance of respondents of class C that currently represents more than the half of the Brazilian population. Some discrepancies between the two samples can be credited to the non probabilistic method of sampling. The ownership of the d high technology electronic device is the following: desktop (56%), notebook (21%), netbook (6%), high resolution TV (17%), digital camera (51%), Iphone (5%), Smartphone (7%), Ipad (2%) e Blue-Ray (2%).

Mobile phone ownership and usage

The following table (table 2) presents comparative results with regard to the mobile phone ownership and usage. Related to the daily use, one perceives that rates increased from 84% in 2006 to 91% in 2011. This can be credited to marketing efforts from mobile vendors and operators, what can also be associated to the decrease in average of expense from R$42.39 in 2006 to R$37.12 in 2011.

It should be emphasized also that the interviews rate that should recommend their mobile operator has increased from 64% in 2006 to 83% in 2011, possibly showing their satisfaction degree.

Table 2: Mobile phone ownership and usage

Mobile phone ownership and usage	2006 n=449	2011 n =420
Use frequency	%	%
Daily	84	91
Weekly	5	3
Monthly	8	4
Rarely	3	2
Ownership	%	%
Use of own mobile phone	96	95
Type of plan
Pre-paid	89	90
Mobile expenses	%	%
Up to R$10,00	7	10
From R$11,00 to R$30,00	41	55
From R$31,00 to R$50,00	25	18
From R$51,00 to R$70,00	20	6
From R$71,00 to R$100,00	3	4
From R$101,00 to R$150,00	3	3
From R$151,00 to R$200,00	2	2
From R$ 201,00 and		2
Average expenses	42,39	37,12
Mobile ownership	%	%
Less than 6 months	32	5
From 6 months till 1 year	20	8
From 1- 2 years	19	13
From 2 - 3 years	14	13
From 3 - 5 years	7	22
Up to 5 years	7	39
Device exchange	%	%
None	60	15
Once	15	11
Twice	8	15
3 Times	10	23
4 Times	3	15
5 Times	2	7
6 Times Or Over	2	15
Number of devices that have or use	%	%
None	5	5
1	88	71
2	7	19
3 or over	-	5
Number of devices in the household	%	%
1	42	6
2	27	31
3	23	31
From 4 or over	8	31
Operator indication	%	%
Yes	64	83
No	36	17

Mobile phone daily used functions

The following section describes the most daily used mobile functions. At first it is possible to consider the most important functions as “to make calls” (65% in 2006 and 90% in 2011), “to receive calls” (84% in 2006 and 88% in 2011), “clock” (84 in 2006 and 77% in 2011), “alarm” (69% in 2006 and 72% in 2011),“phone catalogue” (68% in 2006 and 71% in 2011), “call register” (78% in 2006 and 70% in 2011). The significant increase for “to make calls” can be credited to the operator’s promotions that do not charge for in between the same operator. In a second group it is possible to consider “SMS” (27% in 2006 and 64% in 2011), “Schedule” (65% in 2006 and 45% in 2011), “MP3” (13% in 2006 and 44% in 2011), “Ear phone” (13% in 2006 and 40% in 2011), “Calendar” (42% in 2006 and38% in 2011). It is possible to verify a great increase for “SMS” (The Brazilian operators make lots of promotions for SMS), “MP3” and “Ear phone” (probably because the age sample average is quite young). The following functions must be considered, although with the lowest percentages: “Calculator” (37% in 2006 and 26% in 2011), Bluetooth (5% in 2006 and 22% in 2011), “digital camera” (9% in 2006 and 22% in2011).

Pádua Jr., Prado (2005) classified the functions in three types: basic, intermediary and advanced. The basic functions comprise: to receive or to make a call, to receive or to send messages...The intermediary functions are: music download, games, alarm and the advanced functions are: digital camera, to send and to receive photos and images, video download, video recording and reproduction, internet, e-mail, game download. The most used functions can be classified as basic and intermediary.

Torres, Borges, Jambeiro (2006) classified functions as informative and communicative. Functions were considered informative when voices, sounds or images come from a database in a non synchronic manner. The function is communicative when information (voices, sounds or images) is generated the moment the device is used. So it can be verified that the most used functions are communicative.

Technology and mobile phone innovation attitudes

Besides the descriptive analysis, a Factor Analysis was also performed which results are presented as follow.

Attitudes regarding technology in general

The descriptive analysis showed that the highest accordance rates were obtained for “Computers came to help improve my” (54% in 2006 and 79% in 2011), “When I purchase an electronic gadget I take into consideration manufactures that provide good technical assistance” (60 % in 2006 and 73% in 2011), “When a new electronic gadget is relesead I wait until it becomes affordable for me” (71% in 2006 and 66% in 2011).

The lowest accordance rates refers to “In general, I have difficulties in dealing with technological advances around us” (42% in 2006 and 44% in 2011); “Computers are dangerous because the cause unemployment” (49% in 2006, 30% in 2011). “I fear that technological advances may control my live” (35% in 2006, 25% in 2011); “In general, I am one of the first to buy new electronic gadgets” (40% in 2006 and 20% in 2011).

The results show a reduction in rates of fear with regard to the technology, also an increase in rates of reliability, thus some beliefs on the threats of the technology have not been remained in time. Some studies show that perceived risk can include damages, accidents, psychological, monetary performance of the product and losses physical, of social status, time and future chances (Pádua Jr., Prado, 2005).

Due to these uncertainties, the consumers can postpone the purchase of new products because they consider it a risky decision and the complex devices may turn them sorry for the previous purchase.

A factor analysis was also performed and results show three different components, which explain 64% of total variance.

The fist component “caution” includes “When I purchase an electronic gadget I take into consideration manufactures that provide good technical assistance” (0,809), “When a new electronic gadget is released I wait until it becomes affordable for me” (0,709) and “In general, I have difficulties in dealing with technological advances around us” (0,581). The second component “fear” is related to “I fear that technological advances may control my live” (0,858), “Computers are dangerous because the cause unemployment” (0,853). The third component “optimism”, refers to “In general, I am one of the first to buy new electronic gadgets” (0,683), “Computers came to help improve my life” (0,599).

Attitudes regarding cellular innovation acceptance

The descriptive analysis shows that the statements with the highest rates are: “The new devices are better than the old ones” (78% in 2006, 73% in 2011), “I do not have any problems in understanding my mobile phone functioning” (88% in 2006, 71% in 2011), “The available functions in the new devices are more interesting than the old ones” (82% in 2006, 69% in 2011), “The new devices are incentives to buy a new one” (62% in 2006, 61% in 2011).

The lowest rates were obtained for the following statements: “The new generation cellular phone device are more difficult to be used than the old one”(40% in 2006, 59% in 2011); “It is difficult to use the cellular most advanced functions such as access to the Internet” (49% in 2006, 51% in 2011); “I love the challenge to learn to use everything the cellular offers me” (47% in 2006, 50% in 2011), “It is difficult to understand the recent cellular phone devices and services innovations (as for example: GPRS, EDGE, MMS, GSM, etc.)” (46% in 2006, 45% in 2011), “It is difficult to use the cellular most advanced functions such as digital camera” (35% in 2006, 35% in 2011), “It is possible to try a new device before buying it” (31% in 2006, 31% in 2011), “It is possible to try new available services before buying them” (27% in 2006, 30% in 2011). As shown in the table below, many controversial points were identified throughout the analysis, that is, there are significant differences between 2006 and 2011, regarding the difficulties and problems in understanding the new features and devices.

A factor analysis was performed and the results showed four components that explain 60% of the total variance. The fist one “difficulty” is related to “It is difficult to use the cellular most advanced functions such as access to the Internet” (0,765), “It is difficult to use the cellular most advanced functions such as digital camera “ (0,761), “The new generation cellular phone device are more difficult to be used than the old ones” (0,595), “It is difficult to understand the recent cellular phone devices and services innovations (as for example: GPRS, EDGE, MMS, GSM, etc.).” (0,575). The component “perceived advantages” is related to “The new devices are better than the old ones.” (0,808); “The available functions in the new devices are more interesting than the old ones” (0,711), “The new devices are incentives to buy a new one” (0,593). The component “trialability” refers to “It is possible to try new available services before buying them” (0,804); “It is possible to try a new device before buying it “(0,788); and finally the fourth component “daring” relates to “I love the challenge to learn to use everything the cellular offers me” (0,796), “I do not have any problems in understanding my mobile phone functioning” (0,644).

Segmentation: cluster analysis

Through both factor and cluster analyses, it was possible to identify three groups and demonstrate that they are heterogeneous groups when it comes to attitudes. Also the components obtained through factor analysis were examined along with demographic values, such as income, socioeconomic classification, age and gender. Those three identified clusters may indicate that the sample interviewed comprises different segments regarding technology and innovation acceptance.

The Cluster 1 (adopters) represents 22% of sample. They have the highest percentage of women, the highest percentage for weekly use of cellular phone, the highest percentage of income between 6 -10 minimum wages, the highest percentage of class C, the highest percentage of incomplete and complete higher education, the highest percentage of age between 25-39, the highest percentage of post-paid cellular phone, the highest percentage of notebook, high definition TV and digital camera ownership. As for attitudes, this cluster has high average for “daring” related to technology and for “perceived advantages” for innovation acceptance.

The Cluster 2 (fearful) represents 38% of the sample. They have the highest percentage of mobile daily use, the lowest education. They are the oldest group (most people are over 40 years old), they have the highest percentage with an income of 2-5 minimum wages, the highest percentage of married people, and the highest percentage of desktop ownership. As for attitudes, they have the highest average for “fear” for technology and “trialability” for innovation.

The Cluster 3 (spenders) represents 40% of the sample, it is the largest group. They have the lowest percentage of mobile daily use, the highest percentage of men, the highest percentage of age between 15-24 years old, the highest percentage of class D, the highest percentage of pre-paid, the lowest income, the highest percentage of medium education, the highest percentage of single people, the highest percentage of those that do not have desktop and notebook but they have the highest percentage of Smartphone. As for attitudes, they have the highest average for “caution”, “optimism” in dealing with technology and “difficulty” in dealing with innovation.

5. Final considerations

The purpose of this paper is to present the findings of a longitudinal study which explored Brazilian low income consumer attitudes regarding technology and acceptance of mobile phone innovation.

The mobile phone market environment is characterized by the diminishing product life cycles and rapid technological advancements. These are the principal reasons why consumers can be confused by the increasing amount of innovations at the device as well as the service level, turning the success of innovations unpredictable. A clear understanding of the factors affecting consumers’ adoption processes is very important to the development of an effective marketing

For this reason, this study has aimed at collecting data regarding on low income consumer attitude when interacting with cell phones. Another contribution refers to the possibilities for segmentation. Also, because it is a study based on attitudes and an attitude reflects the individual's feelings of favorableness or disfavor toward performing the behavior, it will possible to understand the formation of the behavioral intention of adopting mobile marketing and also verify if attitudes toward mobile marketing could be good predictors to behavioral intention.

The findings are limited to Brazilian consumers in Sao Paulo and cannot be generalized across the whole of Brazil or other international markets. This research was conducted based on a non-probabilistic sampling and only low income consumers were considered, so other cultural contexts and product categories could be investigated in the future. Also although the chosen sample has a similar to the universe profile, it cannot guarantee that the studied sample is the best representation of this class of consumers.

Although innovation is good for marketers, innovation also generates perceived risk among consumers often motivated to avoid mistakes. In summary, results indicate that consumer attitudes towards technology and innovations may influenced by fear, caution, optimism, difficulty, perceived advantages and trialability, so findings are partially supported by literature.

It has been observed, therefore, that the use of the cellular increases for the low income population, mainly because the pre-paid system and also as result of the operator and vendors aggressive communication and distribution.

So results may contribute to theory and practice in different ways. The principal contribution of the study is first, a Brazilian marketing segmentation for low income consumers and second, the possibility of integrating findings that could be used to develop further research in international marketing. Despite the importanceof the technological and innovation issue there is limited research on this subject, particularly focused on the income consumer behavior.

The research findings can be also used to formulate strategies either for academic studies and they reinforce the idea that the image portrayed by marketing experts does not correspond to reality once a homogeneous approach in dealing with the low income consumer is to be rejected.

By dealing with the low income consumer as a homogeneous group, companies and professionals may be losing many opportunities to offer products and services that both satisfy the desires and meet the needs of this diverse public. This segment is heterogeneous regarding their habits, attitudes and psychographic profile. This study determines the group of people who are more open to products and services as well as suggest the most relevant arguments to reach this public. In short, the clusters identified can also show that the term low income does not refer to a homogeneous group and for this reason one must be careful when using this generic term.

6. References

AE - Agência Estado. (2009); “Classe C tem mais de um quarto do poder de consumo”. Published in: http://www.estadao.com.br/economia/ not_eco148293,0.htm, accessed June 2011.

Ajzen, I. (1985); From intentions to actions: A theory of planned behavior. In J. Kuhl, J. Beckman (Eds.). Upper Saddle River, New Jersey: Prentice Hall.

Bacha, M. L., Vianna, N.; Santos, J. (2009);Celular e Inclusão social. São Paulo: Fapesp/Pleiade.

Cetelem Bgn (2011); Disponible en http://www.cetelem.com.br/portal/Sobre_Cetelem/Observador.shtml

Davis, F. D. 1989.“Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology”. MIS Quarterly, v. 13, n. 3, pp. 319-339.

DeVellis, R. (2003); Scale Development Theory and Applications.Califórnia: Ed. Sage.

Engel, J.; Blackwell, R.; Miniard, P. 2000. Comportamento do consumidor. Rio de Janeiro: LTC.

Ferreira, J. B.; Rocha, A. (2011); “Aceitação e Prontidão do Consumidor para Tecnologia: Proposta de um Novo Modelo e Teste Empírico”. Anais do Encontro Nacional da Associação Pós-graduação e Pesquisa em Administração, Rio de Janeiro, RJ, Brasil, 35.

Fishbein, M.; Ajzen, I. (1975); Belief, Attitude. Intention and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley Publishing.

Gatignon, H.; Robertson, T. S. (1991); Innovative decision processes. In: Robertson, T. S.; Kassarjian, H. H. Handbook of consumer behavior. NewJersey: Prentice-Hall,. p. 316-348

Hair Jr., P. et al. (2006);Análise Multivariada de dados. 5ª ed. Porto Alegre: Bookman.

Leppaniemi, M.,Karjaluoto, H. (2005);“Factors influencing consumers' willingness to accept mobile advertising: a conceptual model”. International Journal of Mobile Communication, vol.3 No. 3, pp. 197-213.

Lex, S. (2008); Inovação tecnológica e vantagens competitivas sustentáveis no Setor de Telefonia celular do Brasil: um estudo sobre a interveniência da convergência digital, Tese de Doutorado em Administração, Universidade Presbiteriana Mackenzie, SP, Brasil.

Lin, C. H.; Shih; H. Y.,Sher; P. J. (2007); “Integrating Technology Readiness into Technology Acceptance: The TRAM Model”. Psychology and Marketing, v. 24, n. 7, pp. 641-657.

Malhotra, N. K. (2001); Pesquisa de Marketing: uma orientação aplicada. 3ª ed. Porto Alegre: Bookman.

Mick, D. G.; Fournier, S. (1998);“Paradoxes of Technology: Consumer Cognizance, Emotions and Coping Strategies”. Journal of Consumer Research, v. 25, pp. 123-143.

Pádua Jr., F.; Prado, P. A (2005); “Adoção de Inovações em Produtos de Alta Tecnologia Por Jovens: O Caso do Telefone Celular”. Anais do Encontro Nacional da Associação Pós-graduação e Pesquisa em Administração. Brasilia, DF, 29.

Pires, J. P.; Costa, B. A. F. (2008);“Fatores do Índice de Prontidão à Tecnologia (TRI) como Elementos Diferenciadores entre Usuários e Não Usuários de Internet Banking e como Antecedentes”. RAC, Curitiba, v. 12, n. 2, p. 429-456, Abr./Jun. (2008); Published in: http://www.scielo.br/pdf/rac/v12n2/a07v12n2.pdf, accessed June 2012.

Rogers, E. M. (2003); Diffusion of Innovations. 5th ed., The Free Press, New York.

Roach, G. (2009); “Consumer Perceptions of Mobile Phone Marketing: A Direct Marketing Innovation”. Journal of Research in Interactive Marketing, vol. 3, no. 2.pp. 124-138.

Souza, R.V. (2002); “Prontidão para tecnologia do consumidor: aspectos emocionais da adoção de produtos e serviços baseados em tecnologia”. Anais do Encontro Nacional da Associação Pós-graduação e Pesquisa em Administração, Salvador, BA, Brasil, 26.

Taylor, S.; Todd, P.A. (1995); “Understanding Information Technology Usage: A Test of Competing Models”.Information Systems Research, v. 6, n. 2, p. 144-176.

Torres, S., Borges, J.; Jambeiro, O. (2006); “Serviços de Informação e Comunicação Via Telefone Celular: Qualificação, da Oferta e Indicações de Consumo por Adolescentes, em Salvador”. EpticRevista de Economía Política de las Tecnologías de La Información y Comunicación, vol. VIII, n. 3, sep. Published in: http://www.seer.ufs.br/index.php/eptic/article/viewFile/261/250, accessed June 2012.

Mobile Technological Innovation Acceptance: A Study Based On Low Income Brazilian Consumer Attitudes

Aceptación de innovaciones tecnológicas en celulares: un estudio basado en actitudes del consumidor de baja renta en Brasil

Contenido

1. Introduction

2. Theoretical background

3. Methodological procedures

4. Results

Comparative study of sample profile

Mobile phone ownership and usage

Mobile phone daily used functions

Technology and mobile phone innovation attitudes

Attitudes regarding technology in general

Attitudes regarding cellular innovation acceptance

Segmentation: cluster analysis

5. Final considerations

6. References