Цель: получение лучшего понимания того, как цифровая компетентность пользователя влияет на восприятие измерений качества на российском рынке смартфонов.

Задачи (сформулированы как исследовательские вопросы):
– Как индивидуальный уровень цифровой компетенции влияет на оценку измерений воспринимаемого качества смартфона?
– Как индивидуальный уровень цифровой компетенции влияет на важность измерений воспринимаемого качества смартфона?

Результаты:
– Составлена модель цифровой компетентности российских пользователей смартфонов, включающая три элемента – цифровой инструментарий, цифровая эффективность и цифровая безопасность;
– Цифровая компетентность пользователя повышает оценку простоты использования, оценку производительности, важность производительности и важность разнообразия функций смартфона;
– Разработаны рекомендации для производителей смартфонов – например, для достижения лучшего конкурентного положения они могут адаптировать маркетинговые активности на российском рынке к разным уровням цифровой грамотности потребителей,
а также повышать цифровую компетентность пользователей.

Introduction …………………………………………………………………………………………………………………..7 Chapter 1. Digital competence phenomenon ……………………………………………………………………9
1.1 1.2
Definition of digital competence………………………………………………………………………..9
Models of digital competence ………………………………………………………………………….13 1.2.1 Conceptual descriptive models…………………………………………………………………….13 1.2.2 DigComp-based models ……………………………………………………………………………..17 1.2.3 Models by Russian researchers ……………………………………………………………………19 1.2.4 Other models …………………………………………………………………………………………….23
Summary and conclusions…………………………………………………………………………………………25
Chapter 2. Development of research model ……………………………………………………………………28
2.1 Development of the theoretical framework and research propositions ……………………….28 2.1.1 Dimensions of perceived smartphone quality ………………………………………………..28 2.1.2 Additional factors influencing perceived smartphone quality ………………………….35
2.2 Research design development ………………………………………………………………………………41 2.2.1 Choice of digital competence assessment technique……………………………………….41 2.2.2 Questionnaire development…………………………………………………………………………44 2.2.3 Data collection and analysis ………………………………………………………………………..49
Summary and conclusions…………………………………………………………………………………………53
Chapter 3. Data analysis and practical implications……………………………………………………….55
3.1 Data analysis………………………………………………………………………………………………………55 3.1.1 Obtained sample ………………………………………………………………………………………..55 3.1.2 Exploratory factor analysis………………………………………………………………………….57 3.1.3 Research model and hypotheses testing ………………………………………………………..61
3.2. Discussion of the results……………………………………………………………………………………..64 3.2.1 Data-based models and their interpretation……………………………………………………64 3.2.2 Further practical implications………………………………………………………………………67 3.2.3 Limitations and further research…………………………………………………………………..72
CONCLUSIONS …………………………………………………………………………………………………………..73 References…………………………………………………………………………………………………………………….75 Appendices …………………………………………………………………………………………………………………..84
Appendix 1. Questionnaire………………………………………………………………………………………..84 Appendix 2. Exploratory factor analysis ……………………………………………………………………..96 Digital competence…………………………………………………………………………………………….96 Evaluation of quality dimensions ……………………………………………………………………….102 Importance of quality dimensions ………………………………………………………………………108 Appendix 3. Data-based models……………………………………………………………………………….114 Evaluation of quality dimensions ……………………………………………………………………….114 Importance of quality dimensions ………………………………………………………………………118

Research gap
Digital competence is construct that describes a ‘a set of knowledge, skills, and attitudes
associated with the use of digital technology in individual’s goals fulfillment.’ It is crucial to navigate in the current everchanging digital environment, as well as to choose and use technological solutions appropriately. Various researchers view ICT skills ‘as a basic skill needed to function in society’, ‘as an essential requirement for life’, or even as a ‘survival skill’ (Ferrari, 2012).
At the same time, only 27% of Russian citizens have developed a high level of digital competence (NAFI, 2020). Due to the insufficient level of knowledge and skills in the field of digital technologies, many people and organizations were not ready to work in a remote format in current conditions of self-isolation (NAFI, 2020). Contrary to popular opinion, when it comes to safety and security, as well as the ethical use of the gadgets, even the so-called ‘digital natives’ often lack important knowledge, attitudes, and skills (Promethean, 2016).
At the moment, there is a lack of clear understanding on how the level of individual digital competence influences consumer perception. Moreover, the concept of consumer digital competence is still not defined in the academic literature, and ‘there is still no consensus regarding what constitutes consumer digital competences’ (Golovacheva, Smirnova, 2019).
Regarding the concept of digital competence, there is academic research available on the influence of personal innovativeness, digital self-efficacy, or digital savviness (Jin, 2013; Sell et al., 2014; McDonald, Uncles, 2007). However, no research has focused on the relationship between user’s digital competence, in all its integrity and complexity, and consumer perception. The lack of knowledge on relationship between digital competence and consumer perception represents the wide definition if this master’s thesis research gap.
Research problem
User’s level of digital competence is expected to affect consumer perception of highly technological goods especially significantly. One of the most appealing product categories for further research are smartphones. The number of smartphone users has been increasing significantly because of the growth of the smartphone industry, which develops new operating systems and a proliferation of applications (Martins et al., 2018). The number of Russian active smartphone users is growing and is expected to exceed 93 million in 2022 (Statista, 2020). Russian smartphone market is highly dynamic and has welcomed several new entrants in the last decade, with concentration of top-3 players decreasing from over 80% in 2010 to around 40% in 2019
7
(Passport GMID, 2020). Smartphones have been influencing the way people communicate with each other, becoming a near necessity in both private and professional lives (Derks et al, 2016). The unprecedented growth of smartphones has attracted academic attention, hoping to determine the motivations that explain smartphone use (Yeh et al., 2016).
The characteristic that can be used to track the effect of individual’s digital competence on smartphone perception is perceived quality. Quality is a formative concept that plays a particularly important role in the smartphone market, influencing customer satisfaction and customer loyalty (Yeh et al., 2016). At the same time, quality is a multi-dimensional construct and, in its broader definition, can cover almost all characteristics of the product (Molina‐Castillo, 2013). The example of such approach is the classical Garvin’s eight dimensions of quality that describe various features, including aesthetics of the product (Garvin, 1987). Consequently, the research problem of this master’s thesis is gaining understanding on how user’s digital competence influences perception of quality dimensions in the Russian smartphone market.
Research questions
For quality, it is important to assess not only perceived quality itself, but also assess the importance of its dimensions. Consumers perceive some dimensions of quality as more important than others, and it influences their behaviour and decision-making (Brucks et al., 2000). The importance of quality dimensions has been assessed repeatedly during various SERVQUAL model applications (Jones, Shandiz, 2015). According to marketing experts, ‘sometimes organisations make assumptions about what is important to the customer. Once they probe, they may discover that what the customer values is quite different’ (Wisniewski, 1996). Therefore, it is important to not only understand the consumers’ evaluation of different quality components, but also understand, which of them are important. As a result of such logic, the research questions of the master’s thesis are:
RQ1: How does individual digital competence level affect smartphone perceived quality dimensions evaluation by the consumer?
RQ2: How does individual digital competence level affect smartphone perceived quality dimensions importance for the consumer?
As little research is available on the topic, this master’s thesis is of exploratory type, with research conducted in order to initially explore the phenomena of interest. For the same reason, the investigation operates with research propositions and not research hypotheses.

For the aims of research, digital competence concept evolution was tracked, and eleven digital competence frameworks were reviewed. On their basis, a research digital competence model was developed. A model of quality dimensions was chosen for application in the Russian smartphone market, and additional factors influencing the effect of digital competence on smartphone perceived quality were identified. A questionnaire for digital competence level assessment and smartphone quality assessment was comprised and practically tested.
The research proposes several theoretical findings. After statistical analysis of the obtained data, smartphone quality dimensions applied to Russian market were proposed – ease of use, versatility, longevity, endurance, serviceability, performance, and prestige. This presents a difference from the initial quality dimensions model applied in the research design: the original component of ‘durability’ has split into two – ‘longevity’ (characterizing the total length of product’s life cycle) and ‘endurance’ (characterizing the ability of the device to work in unfavorable circumstances).
Another, both theoretical and practical contribution, is the result of digital competence factor analysis. The resulting three-component digital competence framework for Russian smartphone users was formed. A separate component of digital efficiency was discovered, which is not explicitly covered by current digital competence models. The other two, more conventional components of data-based digital competence framework, are ‘digital toolbox’ and ‘digital safety’.
The research propositions that were substantiated imply that user’s digital competence in the Russian smartphone market has positive effect on ease of use evaluation, performance evaluation, performance importance, and versatility importance. Therefore, user digital competence, directly affects smartphone perceived quality in the Russian market through these four relationships. These relationships describe the answer to the research questions stated in the beginning of the research. Moreover, perceived network quality moderates the effect of digital competence on smartphone’s ease of use, decreasing the effect of digital competence on perceived ease of use.
Master’s thesis also draws several practical recommendations for market players based on the analyzed data. Two models have been built, describing relationships between digital competence and smartphone quality dimensions, as well as between some of those quality dimensions. These patterns can be used by smartphone manufacturers to modify consumers’ perception of their devices. For example, more digitally competent consumers will demand higher performance and higher versatility from their smartphones, so these characteristics must be up to par with their requirements. When prestige of the smartphone is of high importance for the user,
73
the expectations of performance and versatility will also grow, as well as expectations to receive quality service. Digitally competent consumers tend to assess smartphone’s ease of use and performance higher, likely because they are able to benefit from more functions and interface solutions provided by the device. The increase of evaluation of these two characteristics (ease of use and performance) will lead to increase of versatility, longevity, and prestige evaluation. Consequently, users with higher digital competence are able to evaluate almost all smartphone quality dimensions higher, even though sometimes through mediating constructs.
Perceived network quality moderates the effect of digital competence on smartphone’s ease of use. This means that smartphone manufacturers can develop initiatives on development of knowledge among consumers, that will help distinguish between product-related incidents and network-related incidents.
Additional managerial implications are also developed. Firstly, it is important to target consumers based on their digital competence level. With this approach, marketers should differentiate the product characteristics emphasized in marketing communications, with performance, ease of use and versatility components of smartphone quality taking central place for digitally competent audience. Secondly, smartphone producers should pursue consumer education with the aim of creating more positive perception of products and brands. The increase in digital competence will lead to higher evaluation and importance of product characteristics. This, in turn, may also increase brand loyalty.

REFERENCES
1. Aaker, D. A. (1992), The Value of Brand Equity. Journal of Business Strategy, 13(4), 27-32.
2. Abigail, Ng. Smartphone users are waiting longer before upgrading — here’s why. CNBC, May 16, 2019, https://www.cnbc.com/2019/05/17/smartphone-users-are-waiting-longer-
before-upgrading-heres-why.html (accessed May 20, 2020).
3. Ala-Mutka, K., Punie, Y., & Redecker, C. (2008). Digital competence for lifelong learning.
Institute for Prospective Technological Studies (IPTS), European Commission, Joint Research
Centre.
4. Alekseev, V. Вопреки трендам. На рынке смартфонов в России сменились лидеры и
привычки покупателей. [In spite of trends. Leaders and consumer habits have changed on the Russian smartphone market]. Delovoy Peterburg, February 20, 2020, https://www.dp.ru/a/2020/02/20/Vopreki_trendam__Na_rinke (accessed May 20, 2020).
5. Alhabeeb, M. J. (2007). On consumer trust and product loyalty. International Journal of Consumer Studies, 31(6), 609–612.
6. Aviram, A., & Eshet-Alkalai, Y. (2006). Towards a theory of digital literacy: three scenarios for the next steps. European Journal of Open, Distance and E-Learning, 9(1).
7. Bayu, R., Noor, Y. L., & Diah, K. (2019). Analysis of The Effect of Brand Image, Product Quality and After-Sales Service on Repurchase Decision of Samsung Smartphones. Russian Journal of Agricultural and Socio-Economic Sciences, 92(8).
8. Berman, N.D. (2017). To the question of digital literacy [К вопросу о цифровой грамотности]. Contemporary research on social problems [Современные исследования социальных проблем], 8(6-2).
9. Blackwell, R. J., Miniard, P. W., & Engel, J. F. (2006). Consumer Behaviour, 10th international edition. Cincinnati OH: Thomson, South-Western.
10. Boakye, K. G., McGinnis, T., & Prybutok, V. R. (2014). Q-TAM: a quality technology acceptance model for technology operations managers. Operations Management Research, 7(1-2), 13-23.
11. Bock, T., & Sergeant, J. (2002). Small sample market research. International Journal of Market Research, 44(2), 1-7.
12. Boronenko T.A., Kaisina, A.B., Fedotova, V.S. (2019). Development of schoolers’ digital literacy in the creation of digital educational environment [Развитие цифровой грамотности школьников в условиях создания цифровой образовательной среды]. Perspectives of Science and Education [Перспективы науки и образования], (2 (38)).
75
13. Brečko, B., & Ferrari, A. (2016). The digital competence framework for consumers. European Commission, Joint Research Center (JRC).
14. Brucks, M., Zeithaml, V. A., & Naylor, G. (2000). Price and brand name as indicators of quality dimensions for consumer durables. Journal of the academy of marketing science, 28(3), 359-374.
15. Butje, M. (2012). Product marketing for technology companies. Routledge.
16. Calvani, A., Fini, A., & Ranieri, M. (2009). Assessing digital competence in secondary education. Issues, models and instruments. Issues in information and media literacy:
education, practice and pedagogy, 153-172.
17. Carretero, S., Vuorikari, R., & Punie, Y. (2017). The Digital Competence Framework for
Citizens. Publications Office of the European Union.
18. Chell, E. (1998), Critical Incident Technique. Qualitative Methods and Analysis in
Organizational Research: A Practical Guide. Gillian Symon and Catherine Cassell, eds.
Thousand Oaks, CA: Sage, 51-72.
19. Chen, C. M., & Ann, B. Y. (2016). Efficiencies vs. importance-performance analysis for the
leading smartphone brands of Apple, Samsung and HTC. Total Quality Management &
Business Excellence, 27(3-4), 227-249.
20. Chen, C. M., & Ann, B. Y. (2016). Efficiencies vs. importance-performance analysis for the
leading smartphone brands of Apple, Samsung and HTC. Total Quality Management &
Business Excellence, 27(3-4), 227-249.
21. Chen, M. M., Murphy, H. C., & Knecht, S. (2016). An importance performance analysis of
smartphone applications for hotel chains. Journal of Hospitality and Tourism Management,
29, 69-79.
22. Cherkashin, D. «Билайн» составил портрет среднестатистического россиянина с iPhone.
[Beeline has made a portrait of an average Russian with an iPhone]. iGuides, September 25, 2018,https://www.iguides.ru/main/gadgets/bilayn_sostavil_portret_srednestatisticheskogo_ rossiyanina_s_iphone/ (accessed May 20, 2020).
23. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
24. Chin, W. W. (2010). How to write up and report PLS analyses. In Handbook of partial least squares, 655-690. Springer, Berlin, Heidelberg.
25. Chow, M. M., Chen, L. H., Yeow, J. A., & Wong, P. W. (2012). Conceptual paper: Factors affecting the demand of smartphone among young adult. International Journal on social science economics & Art, 2(2), 44-49.
76

26. Chowdhury, S. R. (2017). Measuring the relationship between product quality dimensions & repurchase intention of smart phone: A case study on Chittagong city. International Journal of Scientific & Engineering Research, 8(2), 1031-1040.
27. Clemenz, J., Brettel, M., & Moeller, T. (2012). How the personality of a brand impacts the perception of different dimensions of quality. Journal of Brand Management, 20(1), 52-64.
28. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum.
29. Derks, D., Bakker, A., Peters, P., & van Wingerden, P. (2016). Work-related smartphone use, work–family conflict and family role performance: The role of segmentation preference. Human Relations; Studies Towards the Integration of the Social Sciences, 69(5), 1045–1068.
30. Dormann, W. It’s Time to Retire Your Unsupported Things. Carnegie Mellon University, October 23, 2019, https://insights.sei.cmu.edu/cert/2019/10/its-time-to-retire-your- unsupported-things.html (accessed May 20, 2020).
31. Eshet, Y. (2004). Digital literacy: A conceptual framework for survival skills in the digital era. Journal of educational multimedia and hypermedia, 13(1), 93-106.
32. Farjam, S., & Hongyi, X. (2015). Reviewing the concept of brand equity and evaluating consumer-based brand equity (CBBE) models. International Journal of Management Science and Business Administration, 1(8), 14-29.
33. Farquhar, P.H. (1989). Managing brand equity. Marketing Research, Vol. 1, September, 24- 33.
34. Ferrari, A. (2012). Digital competence in practice: An analysis of frameworks. Institute for Prospective Technological Studies (IPTS), European Commission, Joint Research Centre.
35. Fielder, A., Vuorikari R., Rodríguez P., Punie, Y. (2016). Background Review for Developing the Digital Competence Framework for Consumers. Institute for Prospective Technological Studies (IPTS), European Commission, Joint Research Centre.
36. Filieri, R., & Lin, Z. (2017). The role of aesthetic, cultural, utilitarian and branding factors in young Chinese consumers’ repurchase intention of smartphone brands. Computers in Human Behavior, 67, 139-150.
37. Fleaca, E., & Stanciu, R. D. (2019). Digital-age learning and business engineering education– a pilot study on students’ E-skills. Procedia Manufacturing, 32, 1051-1057.
38. Fraillon, J., Ainley, J., Schulz, W., Friedman, T., & Duckworth, D. (2018). Preparing for Life in a Digital World. IEA International Computer and Information Literacy Study.
39. Garvin, D. A. (1987). Competing on the eight dimensions of quality.
77

40. Goodhue, D. L., Lewis, W., & Thompson, R. (2012). Does PLS have advantages for small sample size or non-normal data?. Mis Quarterly, 981-1001.
41. Grewal, D., Bart, Y., Spann, M., & Zubcsek, P. (2016). Mobile advertising: A framework and research agenda. Journal of Interactive Marketing, 34, 3–14.
42. Hamka, F., Bouwman, H., De Reuver, M., & Kroesen, M. (2014). Mobile customer segmentation based on smartphone measurement. Telematics and Informatics, 31(2), 220-227.
43. Heriyati, P., & Siek, T. P. (2011). Effects of word of mouth communication and perceived quality on decision making moderated by gender: Jakarta blackberry smartphone consumer’s
perspective. Contemporary Management Research, 7(4).
44. Hew, J. J., Badaruddin, M. N. B. A., & Moorthy, M. K. (2017). Crafting a smartphone
repurchase decision making process: Do brand attachment and gender matter?. Telematics and
Informatics, 34(4), 34-56.
45. Horrigan, J. B. (2017, February 6). Information Overload. https://www.pewresearch.org/
internet/2016/12/07/information-overload/ (accessed May 20, 2020).
46. Huang, Y. T., & Shih, K. H. (2017). Customer-based brand equity of smartphone in the
emerging market. International Journal of Mobile Communications, 15(5), 467-490.
47. Ickin, S. (2015). Quality of experience on smartphones: Network, application, and energy
perspectives (Doctoral dissertation, Blekinge Institute of Technology).
48. Ilomäki, L., Kantosalo, A., & Lakkala, M. (2011). What is digital competence? Linked portal.
European Schoolnet (EUN), Brussels, 1-12.
49. Informatics Europe and Association for Computing Machinery Europe (IE and ACM). (2013).
Report of the joint Informatics Europe and ACM Europe Working Group on Informatic Education. April 2013. Retrieved June 15, 2013, from http://europe.acm.org/iereport/index.html
50. Ipsos, Russia 2019: The time for adjustments. Ipsos, https://www.ipsos.com/sites/ default/files/ct/publication/documents/2018-10/flair-russia-2019.pdf (accessed May 20, 2020).
51. Jones, J. L., & Shandiz, M. (2015). Service quality expectations: Exploring the importance of SERVQUAL dimensions from different nonprofit constituent groups. Journal of Nonprofit & Public Sector Marketing, 27(1), 48-69.
52. Khan, F., & Vuopala, E. (2019). Digital Competence Assessment Across Generations: A Finnish Sample Using the Digcomp Framework. International Journal of Digital Literacy and Digital Competence (IJDLDC), 10(2), 15-28.
78

53. Kim M., Chang Y., Park M.C., Lee J. (2015) The effects of service interactivity on the satisfaction and the loyalty of smartphone users. Telemat Inform 32(4), 949–960.
54. King, C. and Grace, D. (2009). Employee based brand equity: A third perspective. Services Marketing Quarterly, 30(2), 122-147.
55. Kinyakina, E. В России было продано 30 млн смартфонов за год. [30 million smartphones
were sold in Russia last year]. Vedomosti, January 12, 2020, https://www.vedomosti.ru/technology/articles/2020/01/12/820396-prodano-30-smartfonov (accessed May 20, 2020).
56. Kluzer S., Pujol Priego L. (2018). DigComp into Action – Get inspired, make it happen. S. Carretero, Y. Punie, R. Vuorikari, M. Cabrera, and O’Keefe, W. (Eds.). JRC Science for Policy Report, EUR 29115 EN, Publications Office of the European Union, Luxembourg, 2018.
57. Knapp, J. P. (1991). The Benefits of Consumer Education. A Survey Report.
58. Kock, N. (2020). WarpPLS User Manual: Version 7.0. The official manual for using WarpPLS
software. http://www.scriptwarp.com/warppls/ (accessed May 20, 2020).
59. Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS‐SEM: The inverse
square root and gamma‐exponential methods. Information Systems Journal, 28(1), 227-261.
60. Kong, S. C., Wang, Y. Q., & Lai, M. (2019). Development and validation of an instrument for measuring digital empowerment of primary school students. In Proceedings of the ACM
Conference on Global Computing Education (172-177).
61. Law, N. W. Y., Woo, D. J., de la Torre, J., & Wong, K. W. G. (2018). A global framework of
reference on digital literacy skills for indicator 4.4.2. UNESCO Institute for Statistics.
62. Lin, T.C., Huang, S.-L., Hsu, C.J., (2015). A dual-factor model of loyalty to IT product – The
case of smartphones, International Journal of Information Management, 35, 215–228.
63. Lobao, M. Android versus iOS software updates revisited: Two years later and not much has changed. Android Police, November 2, 2017, https://www.androidpolice.com/ 2017/11/02/android-versus-ios-software-updates-revisited-two-years-later/ (accessed May 20,
2020).
64. Malhotra, N., & Birks, D., Wills, P. (2012). Marketing Research: An applied approach: 4th
European Edition. Pearson education.
65. Martilla, J. A., & James, J. C. (1977). Importance-performance analysis. Journal of marketing,
41(1), 77-79.
66. Martins, J., Costa, C., Oliveira, T., Gonçalves, R., & Branco, F. (2019). How smartphone
advertising influences consumers’ purchase intention. Journal of Business Research, 94, 378– 387.
79

67. Mediascope, Аудитория медиа в России. [Audience of media in Russia]. Mediascope, 2019, mediascope.net/upload/iblock/4c8/Adindex%202019_аудитория%20медиа.pdf (accessed May 20, 2020).
68. Molina‐Castillo, F. J., Calantone, R. J., Stanko, M. A., & Munuera‐Aleman, J. L. (2013). Product quality as a formative index: Evaluating an alternative measurement approach. Journal of Product Innovation Management, 30(2), 380-398.
69. Moore, G. A. (2014). Crossing the Chasm: Marketing and Selling Disruptive Products to Mainsteam Competitors. New York: Harper Business.
70. Morellato, M. (2014). Digital Competence in Tourism Education: Cooperative-experiential Learning. Journal of Teaching in Travel & Tourism, 14(2), 184.
71. Muthupoltotage, U. P., & Gardner, L. (2018). Analysing the Relationships Between Digital Literacy and Self-Regulated Learning of Undergraduates—A Preliminary Investigation. In Advances in Information Systems Development (1-16). Springer, Cham.
72. Ng, W. (2012). Can we teach digital natives digital literacy?. Computers & education, 59(3), 1065-1078.
73. Noh, M. J., & Lee, K. T. (2016). An analysis of the relationship between quality and user acceptance in smartphone apps. Information Systems and e-Business Management, 14(2), 273-291.
74. Nordén, L. Å., Mannila, L., & Pears, A. (2017, October). Development of a self-efficacy scale for digital competences in schools. IEEE Frontiers in Education Conference (FIE) (1-7). IEEE.
75. Oh, Y., & Oh, J. (2017). A Critical Incident Approach to Consumer Response in the Smartphone Market: Product, Service and Contents. Information Systems and E-Business
Management, 15(3), 577–597.
76. Park, J., & Han, S. H. (2013). Defining user value: A case study of a smartphone. International
Journal of Industrial Ergonomics, 43(4), 274-282.
77. Passport GMID. Mobile Phones in Russia, Country Report (accessed May 20, 2020).
78. Promethean. (2019, November 11). Digital literacy in the classroom. How important is it?
Retrieved December 5, 2019, from https://resourced.prometheanworld.com/digital-literacy-
classroom-important/ (accessed May 20, 2020).
79. PwC Russia, Цифровая революция определяет привычки потребителей. [The digital
revolution determines consumer habits]. PwC, https://www.pwc.ru/ru/retail-
consumer/publications/retail-rus/gcis-consumer-ru-final.pdf (accessed May 20, 2020).
80. Rhee, K., Yang, S., Cheon, K., Kim, S. & Kwon, H. (2007). Consumer competence index
development. Research Paper submitted to Korea Fair Trade Commission.
80

81. Sanusi, A., & Herlina, H. (2018). Quality of products and countries of origin at interest in buying Samsung smartphone with perceived quality as intervening. DLSU Business & Economics Review 28 (Special Edition).
82. Schoon, B. Samsung says Galaxy users are waiting longer to upgrade their phones. 9to5Google, February 12, 2020, https://9to5google.com/2020/02/12/samsung-galaxy-update- cycle-longer/ (accessed May 20, 2020).
83. Sell, A., Mezei, J., & Walden, P. (2014). An attitude-based latent class segmentation analysis of mobile phone users. Telematics and Informatics, 31(2), 209-219.
84. Semiz, B. B. (2016). Comparison of Stratified Sampling and Quota Sampling in Terms of Population Mean. Proceedings of The 7th MAC 2016, 97-103.
85. Seufert, S., Guggemos, J., & Tarantini, E. (2019, April). Design for System Change: Developing Digital Competences of Vocational Teachers. In International Workshop on Learning Technology for Education in Cloud (393-407). Springer, Cham.
86. Sharikov, A. (2016). Digital literacy: a Four-component model. The Journal of Social Policy Studies [Журнал исследований социальной политики], 14(1), 87.
87. Shcherbakov, A. Смартфоны и морозы — все, что вам нужно знать. [Smartphones and cold weather — everything you need to know]. Hi-Tech Mail.Ru, January 7, 2017, https://hi- tech.mail.ru/news/frozen-smartphone/ (accessed May 20, 2020).
88. Shi, X., Lin, Z., Liu, J., & Hui, Y. K. (2018). Consumer loyalty toward smartphone brands: The determining roles of deliberate inertia and cognitive lock-in. Information & Management, 55(7), 866–876.
89. Shin, D. H. (2014). Measuring the quality of smartphones: development of a customer satisfaction index for smart services. International Journal of Mobile Communications, 12(4), 311-327.
90. Shin, D. H. (2015). Effect of the customer experience on satisfaction with smartphones: Assessing smart satisfaction index with partial least squares. Telecommunications Policy, 39(8), 627-641.
91. Shintaputri, I., & Wuisan, A. J. (2017). The impact of perceived price towards perceived value through the mediation of perceived quality: a case of brand X Smartphone in Indonesian middle-class customers. iBuss Management, 5(1).
92. Simon, C. J., and Sullivan, M. W. (1993). The measurement and determinants of brand equity: a financial approach. Marketing science, 12(1), 28-52.
93. Skov, A. (2019). The Digital Competency Wheel. https://digcompp.digital-competence.eu/ (accessed May 20, 2020).
81

94. Soldatova, G.U. Nestik, T.A., Rasskazova E.I., Zotova, E.U. (2013) Digital competence of Russian adolescents and their parents: the results of a national-scale study [Цифровая компетентность российских подростков и родителей: результаты всероссийского исследования]. Moscow, Internet Development Fund [Фонд Развития Интернет].
95. Sotnikov, A. Apple не хочет, чтобы вы часто покупали iPhone. Рассказываем, почему уже не нужно менять смартфоны каждый год. [Apple doesn’t want you to buy iPhone too often. Why it is no longer needed to change smartphones every year?]. iGuides, September 18, 2018, https://www.iguides.ru/main/gadgets/apple_ne_khochet_chtoby_ vy_chasto_pokupali_iphone/ (accessed May 20, 2020).
96. Starov, S. A. (2015). Brand Management [Управление брендами], St. Petersburg: Graduate School of Management Publishing Centre.
97. Statcounter. Mobile Operating System Market Share Russian Federation, Apr 2019 – Apr 2020. https://gs.statcounter.com/os-market-share/mobile/russian-federation (accessed May 20, 2020).
98. Statcounter. Mobile Vendor Market Share Russian Federation, Apr 2019 – Apr 2020. Accessed May 20, 2020. https://gs.statcounter.com/vendor-market-share/mobile/russian- federation (accessed May 20, 2020).
99. Statista. Market share held by mobile operating systems in Russia from January 2012 to May
2019. https://www.statista.com/statistics/262174/market-share-held-by-mobile-operating- systems-in-russia/ (accessed May 20, 2020).
100. Statistics Solutions. Structural Equation Modeling. https://www.statisticssolutions.com/ structural-equation-modeling/ (accessed May 20, 2020).
101. Terry, J., Davies, A., Williams, C., Tait, S., & Condon, L. (2019). Improving the digital literacy competence of nursing and midwifery students: a qualitative study of the experiences of NICE student champions. Nurse education in practice, 34, 192-198.
102. Tröger, N., Wieser, H., & Hübner, R. (2017). Smartphones are replaced more frequently than T-shirts. Patterns of consumer use and reasons for replacing durable goods. Vienna: Chamber of Labour.
103. Tseng, F. M., & Lo, H. Y. (2011). Antecedents of consumers’ intentions to upgrade their mobile phones. Telecommunications Policy, 35(1), 74-86.
104. Uvarova, G. Влияние цифровых технологий на модель поведения покупателей как повод задуматься над онлайн-стратегией. [The impact of digital technologies on consumer behavior as a chance to rethink the online strategy]. Your Partner-Consultant, 13, no. 9579 (2015), https://www.eg-online.ru/article/277427/ (accessed May 20, 2020).
82

105. Vallespín, M., Molinillo, S., & Muñoz-Leiva, F. (2017). Segmentation and explanation of smartphone use for travel planning based on socio-demographic and behavioral variables. Industrial Management & Data Systems.
106. Van Deursen, A. J. A. M., Helsper, E. J., & Eynon, R. (2014). Measuring digital skills. From digital skills to tangible outcomes. Project Report.
107. Van Deursen, A. J., Helsper, E. J., & Eynon, R. (2016). Development and validation of the Internet Skills Scale (ISS). Information, Communication & Society, 19(6), 804-823.
108. Walker, A. (2015, August 27). Digital literacy or digital competence? Retrieved December 5, 2019, from http://www.aishawalker.com/2015/03/12/digital-literacy-or-digital-competence/ (accessed May 20, 2020).
109. Walker, A., & White, G. (2013). Technology Enhanced Language Learning: Connecting theory and practice. Oxford Handbooks for Language Teachers. Oxford University Press.
110. Wisniewski, M. (1996). Measuring service quality in the public sector: the potential for SERVQUAL. Total Quality Management, 7(4), 357-366.
111. Wollenberg, A., & Thuong, T. T. (2014). Consumer behaviour in the Smartphone market in Vietnam. International Journal of Innovation, Management and Technology, 5(6), 412.
112. Yeh, C., Wang, Y., & Yieh, K. (2016). Predicting smartphone brand loyalty: Consumer value and consumer-brand identification perspectives. International Journal of Information Management, 36(3), 245–257.
113. Zvezdina, N. V., & Sorokin, A. S. (2017). Research of consumer preferences in the Moscow smartphone market [Исследование потребительских предпочтений на московском рынке смартфонов]. Voprosy Statistiki, (7), 41–51.
114. Zvezdina, N. V., & Sorokin, A. S. (2018). Modeling Consumer Preferences on the Moscow Smartphone Market Using the Method of Conjoint Analysis [Моделирование потребительских предпочтений на московском рынке смартфонов методом совместного анализа]. Voprosy Statistiki, 25(12), 28–39.

Заказать новую

Лучшие эксперты сервиса ждут твоего задания

от 5 000 ₽

Не подошла эта работа?

Закажи новую работу, сделанную по твоим требованиям

Последние выполненные заказы

Хочешь уникальную работу?

Больше 3 000 экспертов уже готовы начать работу над твоим проектом!

Окончила магистратуру Воронежского государственного университета в 2009 г. В 2014 г. защитила кандидатскую диссертацию. С 2010 г. преподаю в Воронежском государственно... Читать все

Окончила магистратуру Воронежского государственного университета в 2009 г. В 2014 г. защитила кандидатскую диссертацию. С 2010 г. преподаю в Воронежском государственном университете инженерных технологий.

#Кандидатские #Магистерские

66 Выполненных работ

Здравствуйте) Имею сертификат специалиста (врач-лечебник). На данный момент являюсь ординатором(терапия, кардио), одновременно работаю диагностом. Занимаюсь диссертац... Читать все

#Кандидатские #Магистерские

13 Выполненных работ

Мне нравится изучать все новое, постоянно развиваюсь. Могу написать и диссертацию и кандидатскую. Есть опыт в различных сфера деятельности (туризм, экономика, бухучет... Читать все

Мне нравится изучать все новое, постоянно развиваюсь. Могу написать и диссертацию и кандидатскую. Есть опыт в различных сфера деятельности (туризм, экономика, бухучет, реклама, журналистика, педагогика, право)

#Кандидатские #Магистерские

39 Выполненных работ

Привет! Меня зовут Даша, я окончила журфак МГУ с красным дипломом, защитила магистерскую диссертацию на филфаке. Работала журналистом, PR-менеджером в международных ко... Читать все

Привет! Меня зовут Даша, я окончила журфак МГУ с красным дипломом, защитила магистерскую диссертацию на филфаке. Работала журналистом, PR-менеджером в международных компаниях, сейчас работаю редактором. Готова помогать вам с учёбой!

#Кандидатские #Магистерские

50 Выполненных работ

Имею 3 высших образования в сфере Экологии и техносферной безопасности (бакалавриат, магистратура, аспирантура), работаю на кафедре экологии одного из опорных ВУЗов РФ... Читать все

Имею 3 высших образования в сфере Экологии и техносферной безопасности (бакалавриат, магистратура, аспирантура), работаю на кафедре экологии одного из опорных ВУЗов РФ. Большой опыт в написании курсовых, дипломов, диссертаций.

#Кандидатские #Магистерские

27 Выполненных работ

Окончила специалитет по направлению "Прикладная информатика в экономике", магистратуру по направлению "Торговое дело". Защитила кандидатскую диссертацию по специальнос... Читать все

#Кандидатские #Магистерские

37 Выполненных работ

Пишу качественные выпускные квалификационные работы и магистерские диссертации. Опыт написания работ - более восьми лет. Всегда на связи.

#Кандидатские #Магистерские

28 Выполненных работ

Помогаю с выполнением курсовых проектов и контрольных работ по электроснабжению, электроосвещению, электрическим машинам, электротехнике. Занимался наукой, писал стать... Читать все

#Кандидатские #Магистерские

19 Выполненных работ