Doing Business in Europe pp 295-313 | Cite as
Sociotechnical Challenges of Transition Economy SMEs During EU Integration
Abstract
Small-to-medium-sized enterprises (SMEs) are the backbone of national economies, in particular, for transition and emerging nations. SMEs contribute significantly to employment generation and innovation in countries that are in transition. However, SMEs face several social and technical challenges as they focus on technological innovation. SMEs face several barriers in technological innovation because of their limited financial, human, and technological resources. The purpose of this study was to investigate the key sociotechnical challenges that the SMEs of a transition economy face during EU integration and then to highlight any critical success factors for overcoming those challenges. Albania was the case study because they recently achieved candidate country status and are progressing toward EU integration. The central research question which drove the study was: What are the key social and technical challenges that SMEs in transition countries, such as Albania, face in the process of EU integration? We extended existing quantitative research by using qualitative data collection. We used in-depth interviews with 20 managers working in 10 medium-sized enterprises in Albania. After analyzing the data we identified five critical success factors for these EU transition-country SMEs. The first factor was the degree of investment made by the SME to introduce information and communication technology and software into the work processes. The second factor was the degree of investment made by the SME to acquire adequate resources to train their employees to use technology. The third factor was the perceived usefulness of the new technology by employees. The fourth characteristic was the level of employee self-efficacy (confidence) in using new technology. The final attribute was the openness attitude of employees towards using new technology. These results should generalize to other SMEs in Albania and to future EU transition countries. This study should be of interest to SMEs executives and organizational researchers in transition or developing countries, as well as to socio-economic practitioners in any industry or discipline.
Keywords
SMEs Transition Innovation European IntegrationList of Abbreviations
- BI
Behavioral Intent
- CSF
Critical Success Factors
- EU
European Union
- GDP
Gross Domestic Product
- IDT
Innovation Diffusion Theory
- PEU
Perceived Ease of Use [sometimes EU in the context of TAM]
- PU
Perceived Usefulness [sometimes U in the context of TAM]
- SME
Small to Medium Size Enterprise
- TAM
Technology Acceptance Model (TAM2, TAM3 are revisions)
- TPB
Theory of Planned Behavior
- TRA
Theory of Reasoned Action
- TTF
Task Technology Fit
- UTAUT
Unified Theory of Acceptance and Use of Technology
References
- Abadi HRD, Ranjbarian B, Zade FK (2012) Investigate the customers’ behavioral intention to use mobile banking based on TPB, TAM and perceived risk (a case study in Meli bank). Int J Acad Res Bus Social Sci 2(10):312–322Google Scholar
- Ahmad SZ (2012) Micro, small and medium-sized enterprises development in the Kingdom of Saudi Arabia. World J Entrep Manag Sustain Dev 8(4):217–232Google Scholar
- Ajzen I (1991) The theory of planned behavior. Organ Behav Hum Decis Process 50:179–211CrossRefGoogle Scholar
- Al-Gahtani SS, Hubona GS, Wang J (2007) Information technology (it) in saudi arabia: culture and the acceptance and use of it. Inf Manag J 44(8):681–691CrossRefGoogle Scholar
- Arpaci I, Kilicer K, Bardakci S (2015) Effects of security and privacy concerns on educational use of cloud services. Comput Hum Behav 45(1):93–98CrossRefGoogle Scholar
- Attuquayefio S, Addo H (2014) Review of studies with utaut as conceptual framework. Eur Scientific J 10(8):249–258Google Scholar
- Bo Z, Quiyan T (2012) Research of SMEs’ technology innovation model from multiple perspectives. Chin Manag Stud 6(1):124–136. https://doi.org/10.1108/17506141211213825 CrossRefGoogle Scholar
- Chaczko Z, Alenazy W (2014) The extended technology acceptance model and the design of the 21st century classroom. Proceedings of the IEEE Asia-Pacific conference on computer aided system engineering, APCASE. doi: https://doi.org/10.1109/APCASE.2014.6924483
- Chen C-F, Xua X, Arpan L (2017) Between the technology acceptance model and sustainable energy technology acceptance model: investigating smart meter acceptance in the United States. Energy Res Social Sci 25(1):93–104CrossRefGoogle Scholar
- Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):319–340CrossRefGoogle Scholar
- Davis FD, Bagozzi RP, Warshaw PR (1989) User acceptance of computer technology: a comparison of two theoretical models. Manag Sci 35(8):982–1003CrossRefGoogle Scholar
- European Commission (2015) Annual report on European SMEs. http://ec.europa.eu/DocsRoom/documents/16341/attachments/2/translations
- European Commission (2016) Conditions for membership – European neighbourhood policy and enlargement negotiations. https://ec.europa.eu/neighbourhood-enlargement/policy/conditions-membership_en. Retrieved 10 Jan 2017
- European Neighbourhood Policy and Enlargement Negotiations (2016). http://ec.europa.eu/enlargement/countries/detailed-country-information/albania/index_en.htm. Retrieved 28 July 2016
- Ferneley E, Bell F (2006) Using bricolage to integrate business and information technology innovation in SMEs. Technovation 26(3):232–241. https://doi.org/10.1016/j.technovation.2005.03.005 CrossRefGoogle Scholar
- Fishbein M, Ajzen I (1975) Belief, attitude, intention, behavior: an introduction to theory and research. Addison-Wesley, Reading, MAGoogle Scholar
- Gangwar H, Date H, Raoot AD (2014) Review on it adoption: ınsights from recent technologies. J Enterp Inf Manag 27(4):488–502CrossRefGoogle Scholar
- Howard R, Restrepo L, Chang C-Y (2017) Addressing individual perceptions: an application of the unified theory of acceptance and use of technology to building information modelling. Int J Proj Manag 35(1):107–120CrossRefGoogle Scholar
- King WR, He J (2006) A meta-analysis of the technology acceptance model. Inf Manag 43(1):744–755Google Scholar
- Kurnia S, Karnali RJ, Rahim MM (2015) A qualitative study of business-to-business electronic commerce adoption within the Indonesian grocery industry: a multi-theory perspective. Inf Manag 52(1):518–536CrossRefGoogle Scholar
- Lee I, Choi B, Kim J, Hong S (2007) Culture-technology fit: effects of cultural characteristics on the post-adoption beliefs of mobile internet users. Int J Electron Commer 11(4):11–51CrossRefGoogle Scholar
- Lian JW (2015) Critical factors for cloud based e-invoice service adoption in Taiwan: an empirical study. Int J Inf Manag 35(1):98–109CrossRefGoogle Scholar
- Mortenson MJ, Vidgen R (2016) A computational literature review of the technology acceptance model. Int J Inf Manag 36(1):1248–1259CrossRefGoogle Scholar
- Nysveen H, Pedersen PE, Thorbjornsen H (2005) Intentions to use mobile services: antecedents and cross-service comparisons. J Acad Mark Sci 33(3):330–346CrossRefGoogle Scholar
- Onkvisit S, Shaw JJ (1994) Consumer behaviour: strategy and analysis. MacMillan College Publishing Company, New York, NYGoogle Scholar
- Parrilli MD, Elola A (2012) The strength of science and technology drivers for SME innovation. Small Bus Econ 39(4):897–907. https://doi.org/10.1007/s11187-011-9319-6. CrossRefGoogle Scholar
- Rizzuto TE, Reeves J (2007) A multidisciplinary meta-analysis of human barriers to technology implementation. Consulting Psychol J Pract Res 59(3):226–240CrossRefGoogle Scholar
- Rizzuto TE, Schwarz A, Schwarz C (2014) Toward a deeper understanding of IT adoption: a multilevel analysis. Inf Manag 51:479–487CrossRefGoogle Scholar
- Rogers EM, Shoemaker FF (1971) Communication of ınnovation. The Free Press, New York, NYGoogle Scholar
- Sağa S, Sezena B, Güzela M (2016) Factors that motivate or prevent adoption of open innovation by SMEs in developing countries and policy suggestions. Proc Social Behav Sci 235(1):756–763Google Scholar
- Schiffman LG, Kanuk LL (1994) Consumer behavior, 5th edn. Prentice Hall, LondonGoogle Scholar
- Strang KD (2012) Multicultural face of organizations. In: Sarlak MA (ed) The new faces of organizations in the 21st century, vol 5. North American Institute of Science and Information Technology (NAISIT), ON, pp 1–21. http://naisit.org/book/detail/id/6. Retrieved 28 July 2016
- Strang KD, Vajjhala NR (2017) Student resistance to a mandatory learning management system in online supply chain courses. J Organ End User Comput (JOEUC) 29(3):49–67CrossRefGoogle Scholar
- Subrahmanya MHB (2015) Innovation and growth of engineering SMEs in Bangalore: why do only some innovate and only some grow faster? J Eng Technol Manag 36(1):24–40. doi: https://doi.org/10.1016/j.jengtecman.2015.05.001
- Tang DP, Chen LJ (2011) A review of the evolution of research on information technology acceptance model. doi: https://doi.org/10.1109/ICBMEI.2011.5917980
- Vajjhala NR, Rojba G (2012) Role of knowledge sourcing in Albanian small and medium-sized enterprises. In: Proceedings of the management, knowledge and learning international conference, Celje, Slovenia, pp. 505–511Google Scholar
- Vajjhala NR, Strang KD (2014) Collaboration strategies for a transition economy: measuring culture in Albania. Int J Cross Cultur Manag 21(1):78–103CrossRefGoogle Scholar
- Vajjhala NR, Vucetic J (2016) Strategic knowledge management in small- and medium-sized enterprises in transition economies—case of Albania. Proceedings of management, knowledge, and learning & technology, innovation and industrial management joint international conference, Timisoara, Romania. ISSN 2232-3309. ISBN 978-961-6914-16-1Google Scholar
- Van der Schyff K, Krauss KE (2014) Higher education cloud computing in south africa: towards understanding trust and adoption issues. South Afr Comp J 55(1):40–55Google Scholar
- Venkatesh V, Bala H (2008) Technology acceptance model 3 and a research agenda on interventions. Decis Sci J 39(2):273–315CrossRefGoogle Scholar
- Venkatesh V, Davis FD (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci 46(2):186–204CrossRefGoogle Scholar
- Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Q 27(3):425–478CrossRefGoogle Scholar
- Venkatesh V, Thong JY, Xu X (2012) Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q 36(1):157–178Google Scholar
- Viswanath V, Davis FD (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci 46(2):186–204CrossRefGoogle Scholar
- Wonglimpiyarat J (2015) Challenges of SMEs innovation and entrepreneurial financing. World J Entrep Manag Sustain Dev 11(4):295–311. https://doi.org/10.1108/WJEMSD-04-2015-0019. Google Scholar
- Wu B, Chen X (2017) Continuance intention to use MOOCs: integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Comput Hum Behav 67(1):221–232. https://doi.org/10.1016/j.chb.2016.10.028 CrossRefGoogle Scholar
- Yu C-S, Tao Y-H (2009) Understanding business-level innovation technology adoption. Technovation 29(2):92–109. https://doi.org/10.1016/j.technovation.2008.07.007 CrossRefGoogle Scholar
- Zhao Y, Zhu Q (2010) Influence factors of technology acceptance model in mobile learning. Proceedings of the fourth ınternational conference on genetic and evolutionary computingGoogle Scholar