Information technology adoption: a review of the literature and classification

  • Review Paper
  • Published: 30 March 2017
  • Volume 17 , pages 361–390, ( 2018 )

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  • Maryam Salahshour Rad 1 ,
  • Mehrbakhsh Nilashi 1 , 2 &
  • Halina Mohamed Dahlan 1  

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In the information systems (IS) domain, technology adoption has been one of the most extensively researched areas. Although in the last decade various models had been introduced to address the acceptance or rejection of information systems, there is still a lack of existing studies regarding a comprehensive review and classification of researches in this area. The main objective of this study is steered toward gaining a comprehensive understanding of the progresses made in the domain of IT adoption research, by highlighting the achievements, setbacks, and prospects recorded in this field so as to be able to identify existing research gaps and prospective areas for future research. This paper aims at providing a comprehensive review on the current state of IT adoption research. A total of 330 articles published in IS ranked journals between the years 2006 and 2015 in the domain of IT adoption were reviewed. The research scope was narrowed to six perspectives, namely year of publication, theories underlining the technology adoption, level of research, dependent variables, context of the technology adoption, and independent variables. In this research, information on trends in IT adoption is provided by examining related research works to provide insights and future direction on technology adoption for practitioners and researchers. This paper highlights future research paths that can be taken by researchers who wish to endeavor in technology adoption research. It also summarizes the key findings of previous research works including statistical findings of factors that had been introduced in IT adoption studies.

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Abdekhoda, M., Ahmadi, M., Gohari, M., Noruzi, A.: The effects of organizational contextual factors on physicians’ attitude toward adoption of Electronic Medical Records. J. Biomed. Inform. 53 , 174–179 (2015)

Google Scholar  

AbuShanab, E., Pearson, J.M.: Internet banking in Jordan the unified theory of acceptance and use of technology (UTAUT) perspective. J. Syst. Inf. Technol. 9 (1), 78–97 (2007)

Aggelidis, V.P., Chatzoglou, P.D.: Using a modified technology acceptance model in hospitals. Int. J. Med. Inform. 78 (2), 115–126 (2009)

Agrebi, S., Jallais, J.: Explain the intention to use smartphones for mobile shopping. J. Retail. Consum. Serv. 22 , 16–23 (2015)

Agudo-Peregrina, Á.F., Hernández-García, Á., Pascual-Miguel, F.J.: Behavioral intention, use behavior and the acceptance of electronic learning systems: differences between higher education and lifelong learning. Comput. Hum. Behav. 34 , 301–314 (2014)

Aharony, N.: An exploratory study on factors affecting the adoption of cloud computing by information professionals. Electron. Lib. 33 (2), 308–323 (2015)

Ahmad, M., Markkula, J., Oivo, M.: Factors affecting e-government adoption in Pakistan: a citizen’s perspective. Transform. Gov. People Process Policy 7 (2), 225–239 (2013)

Ahmad, N., Amer, N.T., Qutaifan, F., Alhilali, A.: Technology adoption model and a road map to successful implementation of ITIL. J. Enterp. Inf. Manag. 26 (5), 553–576 (2013)

Ajzen, I.: From intentions to actions: a theory of planned behavior. In: Kuhl, J., Beckmann, J. (eds.) Springer Series in Social Psychology, pp. 11–39. Springer, Berlin (1985)

Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50 (2), 179–211 (1991)

Ajzen, I., Fishbein, M.: Understanding attitudes and predicting social behaviour. Prentice-Hall, Englewood Cliffs, NJ (1980)

Ajzen, I., Fishbein, M.: Attitude–behavior relations: a theoretical analysis and review of empirical research. Psychol. Bull. 84 (5), 888–918 (1977)

Akhtar Shareef, M., Kumar, V., Kumar, U., Dwivedi, Y.: Factors affecting citizen adoption of transactional electronic government. J. Enterp. Inf. Manag. 27 (4), 385–401 (2014)

Al-Adwan, A., Al-Adwan, A., Smedley, J.: Exploring students acceptance of e-learning using Technology Acceptance Model in Jordanian universities. Int. J. Educ. Dev. Using Inf. Commun. Technol. 9 (2), 4 (2013)

Al-Ajam, A.S., Md Nor, K.: Challenges of adoption of internet banking service in Yemen. Int. J. Bank Market. 33 (2), 178–194 (2015)

Alarcón-del-Amo, M.-C., Lorenzo-Romero, C., Del Chiappa, G.: Adoption of social networking sites by Italian. Inf. Syst. e-Bus. Manag. 12 (2), 165–187 (2014)

Alavi, M., Carlson, P.: A review of MIS research and disciplinary development. J. Manag. Inf. Syst. 8 (4), 45–62 (1992)

Al-Busaidi, K.A.: An empirical investigation linking learners’ adoption of blended learning to their intention of full e-learning. Behav. Inf. Technol. 32 (11), 1168–1176 (2013)

Al-Debei, M.M., Al-Lozi, E.: Explaining and predicting the adoption intention of mobile data services: a value-based approach. Comput. Hum. Behav. 35 , 326–338 (2014)

Al-Ghaith, W.A., Sanzogni, L., Sandhu, K.: Factors influencing the adoption and usage of online services in Saudi Arabia. Electron. J. Inf. Syst. Dev. Ctry 40 (1), 1–32 (2010)

Al-hujran, O., Al-debei, M.M., Chatfield, A., Migdadi, M.: The imperative of influencing citizen attitude toward e-government adoption and use. Comput. Hum. Behav. 53 , 189–203 (2015)

Al-jabri, I.M., Roztocki, N.: Adoption of ERP systems : Does information transparency matter? Telematics Inform. 32 (2), 300–310 (2015)

Al-Jabri, I.M., Sohail, M.S., Ndubisi, N.O.: Understanding the usage of global social networking sites by Arabs through the lens of uses and gratifications theory. J. Serv. Manag. 26 (4), 662–680 (2015)

Alomari, M., Woods, P., Sandhu, K.: Predictors for e-government adoption in Jordan: deployment of an empirical evaluation based on a citizen-centric approach. Inf. Technol. People 25 (2), 207–234 (2012)

Al-Qirim, N.: The adoption of eCommerce communications and applications technologies in small businesses in New Zealand. Electron. Commer. Res. Appl. 6 (4), 462–473 (2007)

Alshamaila, Y., Papagiannidis, S., Li, F.: Cloud computing adoption by SMEs in the north east of England: A multi-perspective framework. J. Enterp. Inf. Manag. 26 (3), 250–275 (2013)

Althunibat, A.: Determining the factors influencing students’ intention to use m-learning in Jordan higher education. Comput. Hum. Behav. 52 , 65–71 (2015)

Aluri, A., Palakurthi, R.: The influence of demographic factors on consumer attitudes and intentions to use RFID technologies in the US hotel industry. J. Hosp. Tour. Technol. 2 (3), 188–203 (2011)

Amaro, S., Duarte, P.: An integrative model of consumers’ intentions to purchase travel online. Tour. Manag. 46 , 64–79 (2015)

Amin, H.: An analysis of mobile credit card usage intentions. Inf.Manag. Comput. Secur. 15 (4), 260–269 (2007)

Amoako-Gyampah, K.: Perceived usefulness, user involvement and behavioral intention: an empirical study of ERP implementation. Comput. Hum. Behav. 23 (3), 1232–1248 (2007)

Anderson, E., Weitz, B.: Determinants of continuity in conventional industrial channel dyads. Marketing science 8 (4), 310–323 (1989)

Asnira, I., Kamarulzaman, Y.: Social media adoption: The role of media needs and innovation characteristics. Comput. Hum. Behav. 43 , 189–209 (2015)

Bagozzi, R.P.: The legacy of the technology acceptance model and a proposal for a paradigm shift. J. Assoc. Inf. Syst. 8 (4), 244–254 (2007)

Bandura, A.: Social Learning Theory. Prentice Hall, Englewood Cliffs (1977)

Bankole, F.O., Bankole, O.O., Brown, I.: Mobile banking adoption in Nigeria. Electron. J. Inf. Syst. Dev. Ctry 47 (2), 1–23 (2011)

Baptista, G., Oliveira, T.: Understanding mobile banking: the unified theory of acceptance and use of technology combined with cultural moderators. Comput. Hum. Behav. 50 , 418–430 (2015)

Basaglia, S., Caporarello, L., Magni, M., Pennarola, F.: Environmental and organizational drivers influencing the adoption of VoIP. Inf. Syst. e-Bus. Manag. 7 (1), 103–118 (2009)

Bashir, I., Madhavaiah, C.: Consumer attitude and behavioural intention towards Internet banking adoption in India. J. Indian Bus. Res. 7 (1), 67–102 (2015)

Behrend, T.S., Wiebe, E.N., London, J.E., Johnson, E.C.: Cloud computing adoption and usage in community colleges. Behav. Inf. Technol. 30 (2), 231–240 (2011)

Bélanger, F., Carter, L.: Trust and risk in e-government adoption. J. Strateg. Inf. Syst. 17 (2), 165–176 (2008)

Benbasat, I., Barki, H.: Quo vadis TAM? J. Assoc. Inf. Syst. 8 (4), 7 (2007)

Bigné, J.E., Aldás, J., Andreu, L.: B2B services: IT adoption in travel agency supply chains. J. Serv. Mark. 22 (6), 454–464 (2008)

Blake, R.H., Kyper, E.S.: An investigation of the intention to share media files over peer-to-peer networks. Behav. Inf. Technol. 32 (4), 410–422 (2013)

Booker, L.D., Detlor, B., Serenko, A.: Factors affecting the adoption of online library resources by business students. J. Am. Soc. Inform. Sci. Technol. 63 (12), 2503–2520 (2012)

Bramble, J.D., Siracuse, M.V., Galt, K.A., Rule, A.M., Clark, B.E., Paschal, K.A.: Examining barriers to health information technology adoption. Adv. Health Care Manag. 7 , 191–209 (2008)

Brand, M.J., Huizingh, E.K.R.E.: Into the drivers of innovation adoption: What is the impact of the current level of adoption? Eur. J. Innov. Manag. 11 (1), 5–24 (2008)

Brown, I., Russell, J.: Radio frequency identification technology: an exploratory study on adoption in the South African retail sector. Int. J. Inf. Manag. 27 (4), 250–265 (2007)

MathSciNet   Google Scholar  

Buabeng-Andoh, C.: Factors influencing teachers’ adoption and integration of information and communication technology into teaching: a review of the literature. Int. J. Educ. Dev. Using Inf. Commun. Technol. 8 (1), 136 (2012)

Bukhari, S.M.F., Ghoneim, A., Dennis, C., Jamjoom, B.: The antecedents of travellers’ e-satisfaction and intention to buy airline tickets online: a conceptual model. J. Enterp. Inf. Manag. 26 (6), 624–641 (2013)

Cao, Q., Gan, Q., Thompson, M.A.: Organizational adoption of supply chain management system: a multi-theoretic investigation. Decis. Support Syst. 55 (3), 720–727 (2013)

Carter, L.: E-government diffusion: a comparison of adoption constructs. Transf. Gov. People Process Policy 2 (3), 147–161 (2008)

Carter, L., Weerakkody, V.: E-government adoption: A cultural comparison. Inf. Syst. Front. 10 (4), 473–482 (2008)

Casey, T., Wilson-Evered, E.: Predicting uptake of technology innovations in online family dispute resolution services: an application and extension of the UTAUT. Comput. Hum. Behav. 28 (6), 2034–2045 (2012)

Chang, C.-C., Lin, C.-Y., Chen, Y.-C., Chin, Y.-C.: Predicting information-seeking intention in academic digital libraries. Electron. Lib. 27 (3), 448–460 (2009)

Chang, M.K., Cheung, W.: Determinants of the intention to use Internet/WWW at work: a confirmatory study. Inf. Manag. 39 (1), 1–14 (2001)

Chang, Y.P., Zhu, D.H.: Understanding social networking sites adoption in China: a comparison of pre-adoption and post-adoption. Comput. Hum. Behav. 27 (5), 1840–1848 (2011)

Che, T., Peng, Z., Hin, K., Hua, Z.: Antecedents of consumers’ intention to revisit an online group-buying website: a transaction cost perspective. Inf. Manag. 52 (5), 588–598 (2015)

Chen, C.C., Wu, J., Su, Y.S., Yang, S.C.: Key drivers for the continued use of RFID technology in the emergency room. Manag. Res. News 31 (4), 273–288 (2008)

Chen, C.Der, Fan, Y.W., Farn, C.K.: Predicting electronic toll collection service adoption: An integration of the technology acceptance model and the theory of planned behavior. Transp. Res. C Emerg. Technol. 15 (5), 300–311 (2007)

Chen, C.-F., Chen, P.-C.: Applying the TAM to travelers’ usage intentions of GPS devices. Expert Syst. Appl. 38 (5), 6217–6221 (2011)

Chen, C.-W.D., Cheng, C.-Y.J.: Understanding consumer intention in online shopping: a respecification and validation of the DeLone and McLean model. Behav. Inf. Technol. 28 (4), 335–345 (2009)

Chen, M.-Y., Teng, C.-I.: A comprehensive model of the effects of online store image on purchase intention in an e-commerce environment. Electron. Commer. Res. 13 (1), 1–23 (2013)

Chen, R.: Member use of social networking sites—an empirical examination. Decis. Support Syst. 54 (3), 1219–1227 (2013)

Chen, Y.C., Shang, R.A., Li, M.J.: The effects of perceived relevance of travel blogs’ content on the behavioral intention to visit a tourist destination. Comput. Hum. Behav. 30 , 787–799 (2014)

Cheng, S., Chen, S., Yen, D.C.: Continuance intention of E-portfolio system: a confirmatory and multigroup invariance analysis of technology acceptance model. Comput. Stand. Interfaces 42 , 17–23 (2015)

Cheng, S.-Y., Tsai, M.-T., Cheng, N.-C., Chen, K.-S.: Predicting intention to purchase on group buying website in Taiwan: virtual community, critical mass and risk. Online Inf. Rev. 36 (5), 698–712 (2012)

Cheng, T.E., Lam, D.Y., Yeung, A.C.: Adoption of internet banking: an empirical study in Hong Kong. Decis. Support Syst. 42 (3), 1558–1572 (2006)

Cheng, Y.: Towards an understanding of the factors affecting m-learning acceptance: roles of technological characteristics and compatibility. Asia Pac. Manag. Rev. 20 (3), 109–119 (2015)

Cheng, Y.-M.: Extending the expectation- confirmation model with quality and flow to explore nurses’ continued blended e-learning intention. Inf. Technol. People 27 (3), 230–258 (2014)

Chiou, J.-S., Shen, C.-C.: The antecedents of online financial service adoption: the impact of physical banking services on Internet banking acceptance. Behav. Inf. Technol. 31 (9), 859–871 (2012)

Chiu, C.-M., Wang, E.T.G.: Understanding Web-based learning continuance intention: the role of subjective task value. Inf. Manag. 45 (3), 194–201 (2008)

Chong, A.Y.L., Chan, F.T.: Structural equation modeling for multi-stage analysis on radio frequency identification (RFID) diffusion in the health care industry. Expert Syst. Appl. 39 (10), 8645–8654 (2012)

Chong, A.Y., Liu, M.J., Luo, J., Keng-boon, O.: Production economics predicting RFID adoption in healthcare supply chain from the perspectives of users. Int. J. Prod. Econ. 159 , 66–75 (2015)

Chong, A.Y.-L.: A two-staged SEM-neural network approach for understanding and predicting the determinants of m-commerce adoption. Expert Syst. Appl. 40 (4), 1240–1247 (2013)

Chong, A.Y.-L., Bai, R.: Predicting open IOS adoption in SMEs: an integrated SEM-neural network approach. Expert Syst. Appl. 41 (1), 221–229 (2014)

Chong, A.Y.-L., Ooi, K.-B., Lin, B., Bao, H.: An empirical analysis of the determinants of 3G adoption in China. Comput. Hum. Behav. 28 (2), 360–369 (2012)

Chong, A., Ooi, K., Lin, B., Raman, M.: Factors affecting the adoption level of c-commerce: an empirical study. J. Comput. Inf. Syst. 50 (2), 13–22 (2009)

Choudrie, J., Dwivedi, Y.K. Investigating the research approaches for examining technology adoption issues. J. Res. Pract. 1 (1):Article-D1 (2005)

Chu, C.-W., Lu, H.-P.: Factors influencing online music purchase intention in Taiwan: an empirical study based on the value-intention framework. Internet Res. 17 (2), 139–155 (2007)

Chukwunonso, F., Ibrahim, R., Selamat, A.: Exploring the research methods employed for investigating current challenges in e-learning adoption in universities: a short literature review. Front. Artif. Intell. Appl. 265 , 906–920 (2014)

Chuttur, M. Overview of the technology acceptance model: origins, developments and future directions. Sprouts: Working Pap. Inf. Syst. 9 :1–23 (2009)

Clark, B.R.: Interorganizational patterns in education. Adm. Sci. Q. 10 , 224–237 (1965)

Colemen, J.S.: Social capital in the creation of human capital. Am. J. Sociol. 94 , S95–S120 (1988)

Compeau, D., Higgins, C.A., Huff, S.: Social cognitive theory and individual reactions to computing technology: a longitudinal study. MIS Q. 23(2), 145–158 (1999)

Constantiou, I.D., Papazafeiropoulou, A., Vendelø, M.T.: Does culture affect the adoption of advanced mobile services? A comparative study of young adults’ perceptions in Denmark and the UK. ACM SIGMIS Database 40 (4), 132–147 (2009)

Crespo, A.H., del Bosque, I.R.: The influence of the commercial features of the Internet on the adoption of e-commerce by consumers. Electron. Commer. Res. Appl. 9 (6), 562–575 (2010)

Csikszentmihalyi, M.: Beyond Boredom and Anxiety: Experiencing Flow in Work and Play, p. 36. Jossey-Bass Publishers, San Francisco (1975)

Csikszentmihalyi, M.: Flow: The Psychology of Optimal Experience. Harper & Row, New York (1990)

Dai, H., Palvi, P.: Mobile commerce adoption in China and the United States: a cross-cultural study. ACM SIGMIS Database 40 (4), 43–61 (2009)

Datta, P.: A preliminary study of ecommerce adoption in developing countries. Inf. Syst. J. 21 (1), 3–32 (2011)

Davis, F.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13 (3), 319–340 (1989)

De Grove, F., Bourgonjon, J., Van Looy, J.: Digital games in the classroom? A contextual approach to teachers’ adoption intention of digital games in formal education. Comput. Hum. Behav. 28 (6), 2023–2033 (2012)

DeLone, W.H., McLean, E.R.: Information systems success: the quest for the dependent variable. Inf. Syst. Res. 3 (1), 60–95 (1992)

Deng, Z., Liu, S., Hinz, O.: The health information seeking and usage behavior intention of Chinese consumers through mobile phones. Inf. Technol. People 28 (2), 405–423 (2015)

Dickinger, A., Kleijnen, M.: Coupons going wireless: determinants of consumer intentions to redeem mobile coupons. J. Interact. Mark. 22 (3), 23–39 (2008)

Dwivedi, Y.K., Choudrie, J., Brinkman, W.-P.: Development of a survey instrument to examine consumer adoption of broadband. Ind. Manag. Data Syst. 106 (5), 700–718 (2006)

Elkhani, N., Soltani, S., Nazir Ahmad, M.: The effects of transformational leadership and ERP system self-efficacy on ERP system usage. J. Enterp. Inf. Manag. 27 (6), 759–785 (2014)

Eriksson, K., Kerem, K., Nilsson, D.: The adoption of commercial innovations in the former Central and Eastern European markets. Int. J. Bank Market. 26 (3), 154–169 (2008)

Fagan, M., Kilmon, C., Pandey, V.: Exploring the adoption of a virtual reality simulation: the role of perceived ease of use, perceived usefulness and personal innovativeness. Campus-Wide Inf. Syst. 29 (2), 117–127 (2012)

Featherman, M.S., Pavlou, P.A.: Predicting e-services adoption: a perceived risk facets perspective. Int. J. Hum Comput Stud. 59 (4), 451–474 (2003)

Fishbein, M., Ajzen, I.: Belief, attitude, intention and behavior: an introduction to theory and research. Addison-Wesley, Reading, MA (1977)

Gallego, M.D., Bueno, S., Racero, F.J., Noyes, J.: Open Source Software: the effects of training on acceptance. Comput. Hum. Behav. 49 , 390–399 (2015)

Gan, Q.: Is the adoption of electronic health record system “contagious”? Health Policy Technol. 4 (2), 107–112 (2015)

Gangwar, H., Date, H., Ramaswamy, R.: Understanding determinants of cloud computing adoption using an integrated TAM-TOE model. J. Enterp. Inf. Manag. 28 (1), 107–130 (2015)

Gangwar, H., Date, H., Raoot, A.D.: Review on IT adoption: insights from recent technologies. J. Enterp. Inf. Manag. 27 (4), 488–502 (2014)

Gao, L., Waechter, K.A., Bai, X.: Understanding consumers’ continuance intention towards mobile purchase: a theoretical framework and empirical study—a case of China. Comput. Hum. Behav. 53 , 249–262 (2015)

Gao, Y.: The influences of cognitive factors and trust on E-government acceptance: evidence from a two-stage model. Rev. Bus. Inf. Syst. (RBIS) 17 (4), 153–158 (2013)

Goode, S., Kartas, A.: Exploring software piracy as a factor of video game console adoption. Behav. Inf. Technol. 31 (6), 547–563 (2012)

Goodhue, D.L.: Understanding user evaluations of information systems. Manag. Sci. 41 (12), 1827–1844 (1995)

Goodhue, D.L., Thompson, R.L.: Task-technology fit and individual performance. MIS Q. 19 (2), 213–236 (1995)

Gu, J.-C., Lee, S.-C., Suh, Y.-H.: Determinants of behavioral intention to mobile banking. Expert Syst. Appl. 36 (9), 11605–11616 (2009)

Gu, V.C., Cao, Q., Duan, W.: Unified modeling language (UML) IT adoption—a holistic model of organizational capabilities perspective. Decis. Support Syst. 54 (1), 257–269 (2012)

Gunawan, D.D., Huarng, K.H.: Viral effects of social network and media on consumers’ purchase intention. J. Bus. Res. 68 (11), 2237–2241 (2015)

Gupta, B., Dasgupta, S., Gupta, A.: Adoption of ICT in a government organization in a developing country: an empirical study. J. Strateg. Inf. Syst. 17 (2), 140–154 (2008)

Gupta, R., Jain, K.: Adoption behavior of rural India for mobile telephony: a multigroup study. Telecommun. Policy 39 (8), 691–704 (2015)

Guriting, P., Ndubisi, N.O.: Borneo online banking: evaluating customer perceptions and behavioural intention. Manag. Res. News 29 (1/2), 6–15 (2006)

Gwebu, K.L., Wang, J.: Adoption of Open Source Software: the role of social identification. Decis. Support Syst. 51 (1), 220–229 (2011)

Hajli, M.: A research framework for social commerce adoption. Inf.Manag. Comput. Secur. 21 (3), 144–154 (2013)

Hanafizadeh, P., Khedmatgozar, H.R.: The mediating role of the dimensions of the perceived risk in the effect of customers’ awareness on the adoption of Internet banking in Iran. Electron. Commer. Res. 12 (2), 151–175 (2012)

Hanafizadeh, P., Keating, B.W., Khedmatgozar, H.R.: A systematic review of Internet banking adoption. Telemat. Inform. 31 (3), 492–510 (2014)

Heart, T.: Who is out there? Exploring the effects of trust and perceived risk on saas adoption intentions. ACM SIGMIS Database 41 (3), 49–68 (2010)

Hernandez, J.M.C.J.M.C., Mazzon, J.A., José, A.M., Jazzon, J.A.: Adoption of internet banking: proposition and implementation of an integrated methodology approach. Int. J. Bank Mark. 25 (2), 72–88 (2007)

Hong, T., Kim, E.: Segmenting customers in online stores based on factors that affect the customer’s intention to purchase. Expert Syst. Appl. 39 (2), 2127–2131 (2012)

Hoof, B., Groot, J., Jonge, S.D.: Situational influence on the use of communication technologies: a meta-analysis. J. Bus. Commun. 42 (1), 4–27 (2005)

Hopp, T., Gangadharbatla, H.: Examination of the factors that influence the technological adoption intentions of tomorrow’s new media producers: a longitudinal exploration. Comput. Hum. Behav. 55 , 1117–1124 (2014)

Hossain, M.A., Quaddus, M.: Radio frequency identification (RFID) adoption: A cross-sectional comparison of voluntary and mandatory contexts. Inf. Syst. Front. 17 (5), 1057–1076 (2015)

Hsiao, C.H., Yang, C.: The intellectual development of the technology acceptance model: a co-citation analysis. Int. J. Inf. Manag. 31 (2), 128–136 (2011)

Hsieh, P.: Healthcare professionals’ use of health clouds: integrating technology acceptance and status quo bias perspectives. Int. J. Med. Inform. 84 (7), 512–523 (2015)

Hsin Chang, H., Wen Chen, S.: The impact of online store environment cues on purchase intention: trust and perceived risk as a mediator. Online Inf. Rev. 32 (6), 818–841 (2008)

Hsu, M.K., Wang, S.W., Chiu, K.K.: Computer attitude, statistics anxiety and self-efficacy on statistical software adoption behavior: an empirical study of online MBA learners. Comput. Hum. Behav. 25 (2), 412–420 (2009)

Hsu, P.-F., Ray, S., Li-Hsieh, Y.-Y.: Examining cloud computing adoption intention, pricing mechanism, and deployment model. Int. J. Inf. Manag. 34 (4), 474–488 (2014)

Hua, G., Haughton, D.: Virtual worlds adoption: a research framework and empirical study. Online Inf. Rev. 33 (5), 889–900 (2009)

Huang, D.-L., Patrick Rau, P.-L., Salvendy, G., Gao, F., Zhou, J.: Factors affecting perception of information security and their impacts on IT adoption and security practices. Int. J. Hum Comput Stud. 69 (12), 870–883 (2011)

Huang, J.-C.: Remote health monitoring adoption model based on artificial neural networks. Expert Syst. Appl. 37 (1), 307–314 (2010)

Huang, T.C.-K., Liu, C.-C., Chang, D.-C.: An empirical investigation of factors influencing the adoption of data mining tools. Int. J. Inf. Manag. 32 (3), 257–270 (2012)

Hung, S.-Y., Hung, W.-H., Tsai, C.-A., Jiang, S.-C.: Critical factors of hospital adoption on CRM system: organizational and information system perspectives. Decis. Support Syst. 48 (4), 592–603 (2010)

Hung, S.-Y., Tsai, J.C.-A., Chuang, C.-C.: Investigating primary health care nurses’ intention to use information technology: an empirical study in Taiwan. Decis. Support Syst. 57 , 331–342 (2014)

Hung, W.-C., Jeng, I.: Factors influencing future educational technologists’ intentions to participate in online teaching. Br. J. Educ. Technol. 44 (2), 255–272 (2013)

Hussain Chandio, F., Irani, Z., Abbasi, M.S., Nizamani, H.A.: Acceptance of online banking information systems: an empirical case in a developing economy. Behav. Inf. Technol. 32 (7), 668–680 (2013)

Hussein, R., Mohamed, N., Ahlan, A.R., Mahmud, M.: E-government application: an integrated model on G2C adoption of online tax. Transform. Gov. People Process Policy 5 (3), 225–248 (2011)

Hwang, Y.: The moderating effects of gender on e-commerce systems adoption factors: An empirical investigation. Comput. Hum. Behav. 26 (6), 1753–1760 (2010)

Im, I., Hong, S., Kang, M.S.: An international comparison of technology adoption. Inf. Manag. 48 (1), 1–8 (2011)

Jehn, K.A., Mannix, E.A.: The dynamic nature of conflict: A longitudinal study of intragroup conflict and group performance. Acad. Manag. J. 44 (2), 238–251 (2001)

Jeyaraj, A., Rottman, J.W., Lacity, M.C.: A review of the predictors, linkages, and biases in IT innovation adoption research. Journal of Information Technology 21 (1), 1–23 (2006)

Jin, C.: Computers in Human Behavior Adoption of e-book among college students: The perspective of an integrated TAM. Comput. Hum. Behav. 41 , 471–477 (2014)

Johnston, K., Begg, S., Tanner, M.: Exploring the factors influencing the adoption of Open Source Software in Western Cape schools. Int. J. Educ. Dev. Using Inf. Commun. Technol. 9 (2), 64–84 (2013)

Jung, Y., Perez-Mira, B., Wiley-Patton, S.: Consumer adoption of mobile TV: Examining psychological flow and media content. Comput. Hum. Behav. 25 (1), 123–129 (2009)

Kamarulzaman, Y.: Adoption of travel e-shopping in the UK. Int. J. Retail Distrib. Manag. 35 (9), 703–719 (2007)

Kanat, I.E., Özkan, S.: Exploring citizens’ perception of government to citizen services: a model based on theory of planned behaviour (TBP). Transform. Gov. People Process Policy 3 (4), 406–419 (2009)

Kapoor, K.K., Dwivedi, Y.K., Williams, M.D.: Examining the role of three sets of innovation attributes for determining adoption of the interbank mobile payment service. Inf. Syst. Front. 17 (5), 1039–1056 (2015)

Kapoor, K., Dwivedi, Y.C., Piercy, N., Lal, B., Weerakkody, V.: RFID integrated systems in libraries: extending TAM model for empirically examining the use. J. Enterp. Inf. Manag. 27 (6), 731–758 (2014)

Karaali, D., Gumussoy, C.A., Calisir, F.: Factors affecting the intention to use a web-based learning system among blue-collar workers in the automotive industry. Comput. Hum. Behav. 27 (1), 343–354 (2011)

Karaiskos, D.C., Drossos, D.A., Tsiaousis, A.S., Giaglis, G.M., Fouskas, K.G.: Affective and social determinants of mobile data services adoption. Behav. Inf. Technol. 31 (3), 209–219 (2012)

Karjaluoto, H., Leppaniemi, M.: Social identity for teenagers: Understanding behavioral intention to participate in virtual world environment. J. Theor. Appl. Electron. Commer. Res. 8 (1), 1–16 (2013)

Khalifa, M., Cheng, S., Shen, K.: Adoption of mobile commerce: a confidence model. J. Comput. Inf. Syst. 53 (1), 14–22 (2012)

Khasawneh, A.M.: Concepts and measurements of innovativeness: The case of information and communication technologies. Int. J. Arab Cult. Manag. Sustain. Dev. 1 (1), 23–33 (2008)

Kijsanayotin, B., Pannarunothai, S., Speedie, S.M.: Factors influencing health information technology adoption in Thailand’s community health centers: applying the UTAUT model. Int. J. Med. Informatics 78 (6), 404–416 (2009)

Kim, C., Galliers, R.D., Shin, N., Ryoo, J.-H., Kim, J.: Factors influencing Internet shopping value and customer repurchase intention. Electron. Commer. Res. Appl. 11 (4), 374–387 (2012)

Kim, C., Mirusmonov, M., Lee, I.: An empirical examination of factors influencing the intention to use mobile payment. Comput. Hum. Behav. 26 (3), 310–322 (2010)

Kim, D., Ammeter, T.: Predicting personal information system adoption using an integrated diffusion model. Inf. Manag. 51 (4), 451–464 (2014)

Kim, H.-W., Chan, H.C., Gupta, S.: Value-based adoption of mobile Internet: an empirical investigation. Decis. Support Syst. 43 (1), 111–126 (2007)

Kim, J., Bernhard, B.: Factors influencing hotel customers’ intention to use a fingerprint system. J. Hosp. Tour. Technol. 5 (2), 98–125 (2014)

Kim, J., Forsythe, S.: Adoption of virtual try-on technology for online apparel shopping. J. Interact. Mark. 22 (2), 45–59 (2008)

Kim, S.: Factors affecting the use of social software: TAM perspectives. Electron. Lib. 30 (5), 690–706 (2012)

Kim, S.H.: Moderating effects of Job Relevance and Experience on mobile wireless technology acceptance: adoption of a smartphone by individuals. Inf. Manag. 45 (6), 387–393 (2008)

Kim, W.G., Ma, X., Kim, D.J.: Determinants of Chinese hotel customers’ e-satisfaction and purchase intentions. Tour. Manag. 27 (5), 890–900 (2006)

King, W.R., He, J.: A meta-analysis of the technology acceptance model. Inf. Manag. 43 (6), 740–755 (2006)

Kipnis, D.: Trust and technology. In: Kramer, R.M., Tyler, T.R. (eds.) Trust in Organizations: Frontiers of Theory and Research, pp. 39–50. Sage, Thousand Oaks (1996)

Kramer, R.M., Tyler, T.R.: Trust in Organizations: Frontiers of Theory and Research. Sage, Thousand Oaks (1995)

Kuo, R.-Z., Lee, G.-G.: Knowledge management system adoption: exploring the effects of empowering leadership, task-technology fit and compatibility. Behav. Inf. Technol. 30 (1), 113–129 (2011)

Kuo, Y.-F., Yen, S.-N.: Towards an understanding of the behavioral intention to use 3G mobile value-added services. Comput. Hum. Behav. 25 (1), 103–110 (2009)

Kurnia, S., Choudrie, J., Mahbubur, R., Alzougool, B.: E-commerce technology adoption: a Malaysian grocery SME retail sector study. J. Bus. Res. 68 (9), 1906–1918 (2015)

Lai, I.K.W., Tong, V.W.L., Lai, D.C.F.: Trust factors influencing the adoption of internet-based interorganizational systems. Electron. Commer. Res. Appl. 10 (1), 85–93 (2011)

Lallmahomed, M.Z., Rahim, N.Z.A., Ibrahim, R., Rahman, A.A.: Predicting different conceptualizations of system use: acceptance in hedonic volitional context (Facebook). Comput. Hum. Behav. 29 (6), 2776–2787 (2013)

Lam, T., Cho, V., Qu, H.: A study of hotel employee behavioral intentions towards adoption of information technology. Hosp. Manag. 26 , 49–65 (2007)

Laux, D., Luse, A., Mennecke, B., Townsend, A.M.: Adoption of biometric authentication systems: implications for research and practice in the deployment of end-user security systems. J. Organ.l Comput. Electron. Commer. 21 (3), 221–245 (2011)

Lean, O.K., Zailani, S., Ramayah, T., Fernando, Y.: Factors influencing intention to use e-government services among citizens in Malaysia. Int. J. Inf. Manag. 29 (6), 458–475 (2009)

Lee, C., Wan, G.: Including subjective norm and technology trust in the technology acceptance model: a case of e-ticketing in China. ACM SIGMIS Database 41 (4), 40–51 (2010)

Lee, C.-C.: Assessment of websites user behavior: a case study of housing agency firms. J. Inf. Optim. Sci. 33 (4–5), 553–574 (2012)

Lee, D., Chung, J.Y., Kim, H.: Text me when it becomes dangerous: exploring the determinants of college students’ adoption of mobile-based text alerts short message service. Comput. Hum. Behav. 29 (3), 563–569 (2013)

Lee, E., Han, S.: Determinants of adoption of mobile health services. Online Inf. Rev. 39 (4), 556–573 (2015)

Lee, J., Park, M.-C.: Factors affecting the smartphone users to use the mobile portal services: focusing on Korean mobile portals. Inf. Syst. e-Bus. Manag. 11 (2), 235–252 (2013)

Lee, M.-C.: Predicting and explaining the adoption of online trading: an empirical study in Taiwan. Decis. Support Syst. 47 (2), 133–142 (2009)

Lee, M.-C.: Factors influencing the adoption of internet banking: an integration of TAM and TPB with perceived risk and perceived benefit. Electron. Commer. Res. Appl. 8 (3), 130–141 (2009)

Lee, S.: An integrated adoption model for e-books in a mobile environment: evidence from South Korea. Telemat. Inform. 30 (2), 165–176 (2013)

Lee, W., Tyrrell, T., Erdem, M.: Exploring the behavioral aspects of adopting technology: meeting planners’ use of social network media and the impact of perceived critical mass. J. Hosp. Tour. Technol. 4 (1), 6–22 (2013)

Lee, Y.: Understanding anti-plagiarism software adoption: an extended protection motivation theory perspective. Decis. Support Syst. 50 (2), 361–369 (2011)

Lee, Y.C.: An empirical investigation into factors influencing the adoption of an e-learning system. Online Inf. Rev. 30 (5), 517–541 (2006)

Lee, Y.C.: The role of perceived resources in online learning adoption. Comput. Educ. 50 (4), 1423–1438 (2008)

Lee, Y., Kozar, K.A., Larsen, K.R.: The technology acceptance model: past, present, and future. Commun. Assoc. Inf. Syst. 12 (1), 50 (2003)

Lee, Y.-H., Hsieh, Y.-C., Chen, Y.-H.: An investigation of employees’ use of e-learning systems: applying the technology acceptance model. Behav. Inf. Technol. 32 (2), 173–189 (2013)

Legris, P., Ingham, J., Collerette, P.: Why do people use information technology? A critical review of the technology acceptance model. Inf. Manag. 40 (3), 191–204 (2003)

Leong, L.-Y., Ooi, K.-B., Chong, A.Y.-L., Lin, B.: Modeling the stimulators of the behavioral intention to use mobile entertainment: does gender really matter? Comput. Hum. Behav. 29 (5), 2109–2121 (2013)

Li, Y., Duan, Y., Fu, Z., Alford, P.: An empirical study on behavioural intention to reuse e-learning systems in rural China. Br. J. Educ. Technol. 43 (6), 933–948 (2012)

Lian, J.W.: Critical factors for cloud based e-invoice service adoption in Taiwan: an empirical study. Int. J. Inf. Manag. 35 (1), 98–109 (2015)

Liang, S., Lu, H.: Adoption of e-government services: an empirical study of the online tax filing system in Taiwan. Online Inf. Rev. 37 (3), 424–442 (2013)

Liao, H.L., Lu, H.P.: The role of experience and innovation characteristics in the adoption and continued use of e-learning websites. Comput. Educ. 51 (4), 1405–1416 (2008)

Liao, S., Chou, E.: Intention to adopt knowledge through virtual communities: posters vs lurkers. Online Inf. Rev. 36 (3), 442–461 (2011)

Liébana-Cabanillas, F., Sánchez-Fernández, J., Muñoz-Leiva, F.: The moderating effect of experience in the adoption of mobile payment tools in Virtual Social Networks: The m-Payment Acceptance Model in Virtual Social Networks (MPAM-VSN). Int. J. Inf. Manag. 34 (2), 151–166 (2014)

Liébana-Cabanillas, F., Sánchez-Fernández, J., Muñoz-Leiva, F.: Antecedents of the adoption of the new mobile payment systems: The moderating effect of age. Comput. Hum. Behav. 35 , 464–478 (2014)

Lin, C.H., Shih, H.Y., Sher, P.J.: Integrating technology readiness into technology acceptance: the TRAM model. Psychol. Mark. 24 (7), 641–657 (2007)

Lin, H.-F.: Examination of cognitive absorption influencing the intention to use a virtual community. Behav. Inf. Technol. 28 (5), 421–431 (2009)

Lin, H.-F.: An empirical investigation of mobile banking adoption: the effect of innovation attributes and knowledge-based trust. Int. J. Inf. Manag. 31 (3), 252–260 (2011)

Lin, T.T.C., Younbo, J., Sim, C.: Towards an understanding of intention to use mobile videos: Impression management, perceived facilitation, and social norms. Mob. Media Commun. 3 (1), 106–124 (2015)

Lin, Z., Filieri, R.: Airline passengers’ continuance intention towards online check- in services: the role of personal innovativeness and subjective knowledge. Transp. Res. Part E 81 , 158–168 (2015)

Liu, S.: The impact of forced use on customer adoption of self-service technologies. Comput. Hum. Behav. 28 (4), 1194–1201 (2012)

Liu, Y., Li, H.: Exploring the impact of use context on mobile hedonic services adoption: an empirical study on mobile gaming in China. Comput. Hum. Behav. 27 (2), 890–898 (2011)

Loureiro, S.M.C., Kaufmann, H.R., Rabino, S.: Intentions to use and recommend to others: an empirical study of online banking practices in Portugal and Austria. Online Inf. Rev. 38 (2), 186–208 (2014)

Lu, H.-P., Hsiao, K.-L.: The influence of extro/introversion on the intention to pay for social networking sites. Inf. Manag. 47 (3), 150–157 (2010)

Lu, H.-P., Yang, Y.-W.: Toward an understanding of the behavioral intention to use a social networking site: an extension of task-technology fit to social-technology fit. Comput. Hum. Behav. 34 , 323–332 (2014)

Luo, X., Gurung, A., Shim, J.P.: Understanding the determinants of user acceptance of enterprise instant messaging: an empirical study. J. Organ. Comput. Electron. Commer. 20 (2), 155–181 (2010)

Lwoga, E.: Critical success factors for adoption of web-based learning management systems in Tanzania. Int. J. Educ. Dev. Using Inf. Commun. Technol. (IJEDICT) 10 (1), 4–21 (2014)

Lwoga, E.T., Komba, M.: Antecedents of continued usage intentions of web-based learning management system in Tanzania. Educ. + Train. 57 (7), 738–756 (2015)

Mac Callum, K., Jeffrey, L.: Comparing the role of ICT literacy and anxiety in the adoption of mobile learning. Comput. Hum. Behav. 39 , 8–19 (2014)

MacLennan, E., Belle, J.-P.: Factors affecting the organizational adoption of service-oriented architecture (SOA). Inf. Syst. e-Bus. Manag. 12 (1), 71–100 (2014)

Maditinos, D., Chatzoudes, D., Sarigiannidis, L.: An examination of the critical factors affecting consumer acceptance of online banking: a focus on the dimensions of risk. J. Syst. Inf. Technol. 15 (1), 97–116 (2013)

Magsamen-conrad, K., Upadhyaya, S., Youngnyo, C., Dowd, J.: Bridging the divide: using UTAUT to predict multigenerational tablet adoption practices. Comput. Hum. Behav. 50 , 186–196 (2015)

Mallat, N.: Exploring consumer adoption of mobile payments—a qualitative study. J. Strateg. Inf. Syst. 16 (4), 413–432 (2007)

Martins, C., Oliveira, T., Popovič, A.: Understanding the Internet banking adoption: a unified theory of acceptance and use of technology and perceived risk application. Int. J. Inf. Manag. 34 (1), 1–13 (2014)

McKenna, B., Tuunanen, T., Gardner, L.: Consumers’ adoption of information services. Inf. Manag. 50 (5), 248–257 (2013)

Metzger, M.J.: Privacy, trust, and disclosure: exploring barriers to electronic commerce. J. Comput.-Media. Commun. 9 (4), 114–121 (2004)

Miller, J., Khera, O.: Digital Library adoption and the technology acceptance model: a cross-country analysis. Electron. J. Inf. Syst. Dev. Ctry. 40 , 1–19 (2010)

Moghavvemi, S., Akma Mohd Salleh, N.: Effect of precipitating events on information system adoption and use behaviour. J. Enterp. Inf. Manag. 27 (5), 599–622 (2014)

Mohammadi, H.: Social and individual antecedents of m-learning adoption in Iran. Comput. Hum. Behav. 49 , 191–207 (2015)

Molla, A., Licker, P.S.: E-Commerce systems success: an attempt to extend and respecify the DeLone and McLean model of IS success. J Electron Commer Res 2 (4), 131–141 (2001)

Montazemi, A.R., Qahri-Saremi, H.: Factors affecting adoption of online banking: a meta-analytic structural equation modeling study. Inf. Manag. 52 (2), 210–226 (2015)

Moore, G.C., Benbasat, I.: Development of an instrument to measure the perceptions of adopting an information technology innovation. Inf. Syst. Res. 2 (3), 192–222 (1991)

Moreno Cegarra, J.L., Cegarra Navarro, J.G., Córdoba Pachón, J.R.: Applying the technology acceptance model to a Spanish City Hall. Int. J. Inf. Manag. 34 (4), 437–445 (2014)

Mortimer, G., Neale, L., Hasan, S.F.E., Dunphy, B.: Investigating the factors influencing the adoption of m-banking: a cross cultural study. Int. J. Bank Mark. 33 (4), 545–570 (2015)

Mouakket, S., Bettayeb, A.M.: Investigating the factors influencing continuance usage intention of learning management systems by university instructors The Blackboard system case. Int. J. Web Inf. Syst. 11 (4), 491–509 (2015)

Mount, M.P., Fernandes, K.: Adoption of free and open source software within high-velocity firms. Behav. Inf. Technol. 32 (3), 231–246 (2013)

Mun, H.J., Yun, H., Kim, E.A., Hong, J.Y., Lee, C.C.: Research on factors influencing intention to use DMB using extended IS success model. Inf. Technol. Manag. 11 (3), 143–155 (2010)

Nahapiet, J., Ghoshal, S.: Social capital, intellectual capital and the organizational advantage. Acad. Manag. Rev. 23 (2), 242–266 (1998)

Nam, C.S., Bahn, S., Lee, R.: Acceptance of assistive technology by special education teachers: a structural equation model approach. Int. J. Hum.-Comput. Interact. 29 (5), 365–377 (2013)

Nasco, S.A., Toledo, E.G., Mykytyn, P.P.: Predicting electronic commerce adoption in Chilean SMEs. J. Bus. Res. 61 (6), 697–705 (2008)

Ndubisi, N.O., Sinti, Q.: Consumer attitudes, system’s characteristics and internet banking adoption in Malaysia. Manag. Res. News 29 (1/2), 16–27 (2006)

Negahban, A., Chung, C.H.: Discovering determinants of users perception of mobile device functionality fit. Comput. Hum. Behav. 35 , 75–84 (2014)

Neupane, A., Soar, J., Vaidya, K., Yong, J.: Willingness to adopt e-procurement to reduce corruption. Transform. Gov. People Process Policy 8 (4), 500–520 (2014)

Nguyen, T.D., Barrett, N.J.: The adoption of the internet by export firms in transitional markets. Asia Pac. J. Mark. Logist. 18 (1), 29–42 (2006)

Nikou, S., Bouwman, H.: Ubiquitous use of mobile social network services. Telemat. Inform. 31 (3), 422–433 (2014)

Nistor, N., Lerche, T., Weinberger, A., Ceobanu, C., Heymann, O.: Towards the integration of culture into the unified theory of acceptance and use of technology. Br. J. Educ. Technol. 45 (1), 36–55 (2014)

Oh, J., Yoon, S.-J.: Validation of haptic enabling technology acceptance model (HE-TAM): integration of IDT and TAM. Telemat. Inform. 31 (4), 585–596 (2014)

Okumus, B., Bilgihan, A.: Proposing a model to test smartphone users’ intention to use smart applications when ordering food in restaurants. J. Hosp. Tour. Technol. 5 (1), 31–49 (2014)

Oliveira, T., Faria, M., Thomas, M.A., Popovič, A.: Extending the understanding of mobile banking adoption: when UTAUT meets TTF and ITM. Int. J. Inf. Manag. 34 (5), 689–703 (2014)

Oliveira, T., Thomas, M., Espadanal, M.: Assessing the determinants of cloud computing adoption: an analysis of the manufacturing and services sectors. Inf. Manag. 51 (5), 497–510 (2014)

Oliver, R.L.: Effect of expectation and disconfirmation on postexposure product evaluations: an alternative interpretation. J. Appl. Psychol. 62 (4), 480 (1977)

Oliver, R.L.: A cognitive model of the antecedents and consequences of satisfaction decisions. J. Mark. Res. 62 , 460–469 (1980)

Ooi, K.-B., Sim, J.-J., Yew, K.-T., Lin, B.: Exploring factors influencing consumers’ behavioral intention to adopt broadband in Malaysia. Comput. Hum. Behav. 27 (3), 1168–1178 (2011)

Oostrom, J.K., van der Linden, D., Born, M.P., van der Molen, H.T.: New technology in personnel selection: how recruiter characteristics affect the adoption of new selection technology. Comput. Hum. Behav. 29 (6), 2404–2415 (2013)

Oum, S., Han, D.: An empirical study of the determinants of the intention to participate in user-created contents (UCC) services. Expert Syst. Appl. 38 (12), 15110–15121 (2011)

Oyedele, A., Simpson, P.M.: An empirical investigation of consumer control factors on intention to use selected self-service technologies. Int. J. Serv. Ind. Manag. 18 (3), 287–306 (2007)

Ozkan, S., Kanat, I.E.: E-government adoption model based on theory of planned behavior: empirical validation. Gov. Inf. Q. 28 (4), 503–513 (2011)

Özkan, S., Bindusara, G., Hackney, R.: Facilitating the adoption of e-payment systems: theoretical constructs and empirical analysis. J. Enterp. Inf. Manag. 23 (3), 305–325 (2010)

Pagani, M.: Determinants of adoption of High Speed Data Services in the business market: evidence for a combined technology acceptance model with task technology fit model. Inf. Manag. 43 (7), 847–860 (2006)

Pai, P., Arnott, D.C.: User adoption of social networking sites: Eliciting uses and gratifications through a means-end approach. Comput. Hum. Behav. 29 (3), 1039–1053 (2013)

Pan, S., Jordan-Marsh, M.: Internet use intention and adoption among Chinese older adults: from the expanded technology acceptance model perspective. Comput. Hum. Behav. 26 (5), 1111–1119 (2010)

Park, E., Kim, K.J.: An integrated adoption model of mobile cloud services: exploration of key determinants and extension of technology acceptance model. Telemat. Inform. 31 (3), 376–385 (2014)

Park, E., Ohm, J.: Factors influencing users’ employment of mobile map services. Telemat. Inform. 31 (2), 253–265 (2014)

Park, E., Baek, S., Ohm, J., Chang, H.J.: Determinants of player acceptance of mobile social network games: an application of extended technology acceptance model. Telemat. Inform. 31 (1), 3–15 (2014)

Park, N., Yang, A.: Online environmental community members’ intention to participate in environmental activities: an application of the theory of planned behavior in the Chinese context. Comput. Hum. Behav. 28 (4), 1298–1306 (2012)

Park, N., Jung, Y., Lee, K.M.: Intention to upload video content on the internet: the role of social norms and ego-involvement. Comput. Hum. Behav. 27 (5), 1996–2004 (2011)

Park, N., Lee, K.M., Cheong, P.H.: University instructors’ acceptance of electronic courseware: an application of the technology acceptance model. J. Comput.-Mediat. Commun. 13 (1), 163–186 (2007)

Park, Y., Chen, J.V.: Acceptance and adoption of the innovative use of smartphone. Ind. Manag. Data Syst. 107 (9), 1349–1365 (2007)

Peres, R., Correia, A., Moital, M.: The indicators of intention to adopt mobile electronic tourist guides. J. Hosp. Tour. Technol. 2 (2), 120–138 (2011)

Petter, S., McLean, E.R.: A meta-analytic assessment of the DeLone and McLean IS success model: an examination of IS success at the individual level. Inf. Manag. 46 (3), 159–166 (2009)

Pietro, L.Di, Virgilio, F.Di, Pantano, E.: Social network for the choice of tourist destination: attitude and behavioural intention. J. Hosp. Tour. Technol. 3 (1), 60–76 (2012)

Premkumar, G., Ramamurthy, K., Nilakanta, S.: Implementation of electronic data interchange: an innovation diffusion perspective. J. Manag. Inf. Syst. 11 (2), 157–186 (1994)

Prompattanapakdee, S.: The adoption and use of personal Internet banking services in Thailand. Electron. J. Inf. Syst. Dev. Ctry. 2009 , 1–30 (2009)

Pynoo, B., van Braak, J.: Predicting teachers’ generative and receptive use of an educational portal by intention, attitude and self-reported use. Comput. Hum. Behav. 34 , 315–322 (2014)

Qin, L., Kim, Y., Hsu, J., Tan, X.: The effects of social influence on user acceptance of online social networks. Int. J. Hum.-Comput. Interact. 27 (9), 885–899 (2011)

Ram, J., Corkindale, D., Wu, M.: Enterprise resource planning adoption: structural equation modeling analysis of antecedents. J. Comput. Inf. Syst. 54 (January), 53–65 (2013)

Ramanathan, L., Krishnan, S.: An empirical investigation into the adoption of Open Source Software in Information Technology outsourcing organizations. J. Syst. Inf. Technol. 17 (2), 167–192 (2015)

Ramanathan, R., Ramanathan, U., Ko, L.W.L.: Adoption of RFID technologies in UK logistics: moderating roles of size, barcode experience and government support. Expert Syst. Appl. 41 (1), 230–236 (2014)

Ramayah, T., Rouibah, K., Gopi, M., Rangel, G.J.: A decomposed theory of reasoned action to explain intention to use Internet stock trading among Malaysian investors. Comput. Hum. Behav. 25 (6), 1222–1230 (2009)

Ramdani, B., Kawalek, P., Lorenzo, O.: Predicting SMEs’ adoption of enterprise systems. J. Enterp. Inf. Manag. 22 (1/2), 10–24 (2009)

Rana, N.P., Dwivedi, Y.K.: Citizen’s adoption of an e-government system: Validating extended social cognitive theory (SCT). Gov. Inf. Q. 32 (2), 172–181 (2015)

Ratten, V.: Factors influencing consumer purchase intention of cloud computing in the United States and Turkey the role of performance expectancy. EuroMed J. Bus. 10 (1), 80–97 (2015)

Rauniar, R., Rawski, G., Yang, J., Johnson, B.: Technology acceptance model (TAM) and social media usage: an empirical study on Facebook. J. Enterp. Inf. Manag. 27 (1), 6–30 (2014)

Rawashdeh, A.: Factors affecting adoption of internet banking in Jordan. Int. J. Bank Mark. 33 (4), 510–529 (2015)

Rehman, M., Esichaikul, V., Kamal, M.: Factors influencing e-government adoption in Pakistan. Transform. Gov. People Process Policy 6 (3), 258–282 (2012)

Reunis, M.R.B., Santema, S.C., Harink, J.H.A.: Increasing e-ordering adoption: a case study. J. Purch. Supply Manag. 12 (2006), 322–331 (2006)

Reychav, I., Aguirre-Urreta, M.: Adoption of the Internet for knowledge acquisition in R&D processes. Behav. Inf. Technol. 33 (5), 452–469 (2013)

Richardson, J.: Diffusion of technology adoption in Cambodia: the test of a theory. Int. J. Educ. Dev. Using Inf. Commun. Technol. (IJEDICT) 5 (3), 157–171 (2009)

Riffai, M.M.M.A., Grant, K., Edgar, D.: Big TAM in Oman: Exploring the promise of on-line banking, its adoption by customers and the challenges of banking in Oman. Int. J. Inf. Manag. 32 (3), 239–250 (2012)

Rivera, M., Gregory, A., Cobos, L., Rivera, M., Gregory, A., Cobos, L.: Mobile application for the timeshare industry the influence of technology experience, intentions. J. Hosp. Tour. Technol. 6 (3), 242–257 (2015)

Roca, J.C., Gagné, M.: Understanding e-learning continuance intention in the workplace: A self-determination theory perspective. Comput. Hum. Behav. 24 (4), 1585–1604 (2008)

Rodríguez-Ardura, I., Meseguer-Artola, A.: Toward a longitudinal model of e-commerce: environmental, technological, and organizational drivers of B2C adoption. Inf. Soc. 26 (3), 209–227 (2010)

Rogers, E.: Diffusion of Innovations (4th ed.). New York, 12 (1995)

Rouibah, K., Abbas, H., Rouibah, S.: Factors affecting camera mobile phone adoption before e-shopping in the Arab world. Technol. Soc. 33 (3–4), 271–283 (2011)

Ruggiero, T.E.: Uses and gratifications theory in the 21st century. Mass Commun. Soc. 3 (1), 3–37 (2000)

Saldanha, T.J.V., Krishnan, M.S.: Organizational adoption of Web 2.0 technologies: an empirical analysis. J. Organ. l Comput. Electron. Commer. 22 (4), 301–333 (2012)

Sang, S., Lee, J.-D., Lee, J.: E-government adoption in Cambodia: a partial least squares approach. Transform. Gov. People Process Policy 4 (2), 138–157 (2010)

Schaupp, L.C., Carter, L., McBride, M.E.: E-file adoption: a study of U.S. taxpayers’ intentions. Comput. Hum. Behav. 26 (4), 636–644 (2010)

Schepers, J., Wetzels, M.: A meta-analysis of the technology acceptance model: investigating subjective norm and moderation effects. Inf. Manag. 44 (1), 90–103 (2007)

Schrier, T., Erdem, M., Brewer, P.: Merging task-technology fit and technology acceptance models to assess guest empowerment technology usage in hotels. J. Hosp. Tour. Technol. 1 (3), 201–217 (2010)

Setterstrom, A.J., Pearson, J.M., Orwig, R.A.: Web-enabled wireless technology: an exploratory study of adoption and continued use intentions. Behav. Inf. Technol. 32 (11), 1139–1154 (2013)

Shareef, M.A., Kumar, V., Kumar, U., Dwivedi, Y.K.: E-government adoption model (GAM): differing service maturity levels. Gov. Inf. Q. 28 (1), 17–35 (2011)

Sharp, J.H.: Development, extension, and application: a review of the technology acceptance model. Inf. Syst. Educ. J. 5 (9), 1–11 (2007)

Shen, X.-L., Cheung, C.M.K., Lee, M.K.O.: What leads students to adopt information from Wikipedia? An empirical investigation into the role of trust and information usefulness. Br. J. Educ. Technol. 44 (3), 502–517 (2013)

Shen, Y.-C., Huang, C.-Y., Chu, C.-H., Hsu, C.-T.: A benefit–cost perspective of the consumer adoption of the mobile banking system. Behav. Inf. Technol. 29 (5), 497–511 (2010)

Sheu, D.-F., Kao, Y.-P.: A study on consumers’ behavior model to use electronic purse—applied to TAM model. J. Inf. Optim. Sci. 31 (3), 587–602 (2010)

Shiau, W.-L., Luo, M.M.: Factors affecting online group buying intention and satisfaction: a social exchange theory perspective. Comput. Hum. Behav. 28 (6), 2431–2444 (2012)

Shin, D.H.: Understanding user acceptance of DMB in South Korea using the modified technology acceptance model. Int. J. Hum.-Comput. Interact. 25 (3), 173–198 (2009)

Shin, D.-H.: The effects of trust, security and privacy in social networking: a security-based approach to understand the pattern of adoption. Interact. Comput. 22 (5), 428–438 (2010)

Shropshire, J., Warkentin, M., Sharma, S.: Personality, attitudes, and intentions: predicting initial adoption of information security behavior. Comput. Secur. 49 , 177–191 (2015)

Siamagka, N., Christodoulides, G., Michaelidou, N., Valvi, A.: Determinants of social media adoption by B2B organizations. Ind. Mark. Manag. 51 , 89–99 (2015)

Sila, I.: Factors affecting the adoption of B2B e-commerce technologies. Electron. Commer. Res. 13 (2), 199–236 (2013)

Sintonen, S., Immonen, M.: Telecare services for aging people: assessment of critical factors influencing the adoption intention. Comput. Hum. Behav. 29 (4), 1307–1317 (2013)

Slade, E.L., Dwivedi, Y.K., Piercy, N.C., Williams, M.D.: Modeling consumers’ adoption intentions of remote mobile payments in the United Kingdom: extending UTAUT with innovativeness, risk, and trust. Psychol. Mark. 32 (8), 860–873 (2015)

Sun, Y., Jeyaraj, A.: Information technology adoption and continuance: a longitudinal study of individuals’ behavioral intentions. Inf. Manag. 50 (7), 457–465 (2013)

Svendsen, G.B., Johnsen, J.-A.K., Almås-Sørensen, L., Vittersø, J.: Personality and technology acceptance: the influence of personality factors on the core constructs of the Technology Acceptance Model. Behav. Inf. Technol. 32 (4), 323–334 (2013)

Tajfel, H. E. (1978). Differentiation between social groups: Studies in the social psychology of intergroup relations. Academic Press

Talukder, M., Quazi, A.: The impact of social influence on individuals’ adoption of innovation. J. Organ.l Comput. Electron. Commer. 21 (2), 111–135 (2011)

Tan, G.W.-H., Ooi, K.-B., Leong, L.-Y., Lin, B.: Predicting the drivers of behavioral intention to use mobile learning: a hybrid SEM-neural networks approach. Comput. Hum. Behav. 36 , 198–213 (2014)

Tan, X., Kim, Y.: User acceptance of SaaS-based collaboration tools: a case of Google Docs. J. Enterp. Inf. Manag. 28 (3), 423–442 (2015)

Tan, X., Qin, L., Kim, Y., Hsu, J.: Impact of privacy concern in social networking web sites. Internet Res. 22 (2), 211–233 (2012)

Tarhini, A., Hone, K., Liu, X.: The effects of individual differences on e-learning users’ behaviour in developing countries: a structural equation model. Comput. Hum. Behav. 41 , 153–163 (2014)

Tashkandi, A.N., Al-Jabri, I.M.: Cloud computing adoption by higher education institutions in Saudi Arabia: an exploratory study. Clust. Comput. 18 (4), 1527–1537 (2015)

Teo, T.: An empirical study to validate the technology acceptance model (TAM) in explaining the intention to use technology among educational users. Int. J. Inf. Commun. Technol. Educ. 6 (4), 1–12 (2010)

Teo, T.: Influences of contextual variables on the intention to use technology in education: a latent variable modeling approach. Camp.-Wide Inf. Syst. 30 (2), 95–105 (2013)

Teo, T., Lee, C.B.: Explaining the intention to use technology among student teachers: an application of the Theory of Planned Behavior (TPB). Camp.-Wide Inf. Syst. 27 (2), 60–67 (2010)

Thomas, T., Singh, L., Gaffar, K.: The utility of the UTAUT model in explaining mobile learning adoption in higher education in Guyana. Int. J. Educ. Dev. Using ICT 9 (3), 71–85 (2013)

To, M.L., Ngai, E.W.T.: Predicting the organisational adoption of B2C e-commerce: an empirical study. Ind. Manag. Data Syst. 106 (8), 1133–1147 (2006)

Tornatzky, L., Fleischer, M.: The processes of technological innovation. Lexington Books, D.C. Heath & Company, Lexington (1990)

Tsai, H.S., Larose, R.: Internet adoption and utilization in the inner city: a comparison of competing theories. Comput. Hum. Behav. 51 , 344–355 (2015)

Tsai, H., Chien, J., Tsai, M.: The influences of system usability and user satisfaction on continued Internet banking services usage intention: empirical evidence from Taiwan. Electron. Commer. Res. 16 , 137–169 (2014)

Tsai, M.-C., Lee, W., Wu, H.-C.: Determinants of RFID adoption intention: evidence from Taiwanese retail chains. Inf. Manag. 47 (5–6), 255–261 (2010)

Tsai, W., Ghoshal, S.: Social capital and value creation: the role of intrafirm networks. Acad. Manag. J. 41 (4), 464–476 (1998)

Tseng, S.: Exploring the intention to continue using web-based self-service. J. Retail. Consum. Serv. 24 , 85–93 (2015)

Tung, F.C., Chang, S.C., Chou, C.M.: An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry. Int. J. Med. Inform. 77 (5), 324–335 (2008)

Tung, F.-C., Chang, S.-C.: Nursing students’ behavioral intention to use online courses: a questionnaire survey. Int. J. Nurs. Stud. 45 (9), 1299–1309 (2008)

Tupes, E.C., Christal, R.E.: Recurrent personality factors based on trait ratings. J. Pers. 60 (2), 225–251 (1992)

Turner, M., Kitchenham, B., Brereton, P., Charters, S., Budgen, D.: Does the technology acceptance model predict actual use? A systematic literature review. Inf. Softw. Technol. 52 (5), 463–479 (2010)

Udo, G.J., Bagchi, K.K., Kirs, P.J.: An assessment of customers’ e-service quality perception, satisfaction and intention. Int. J. Inf. Manag. 30 (6), 481–492 (2010)

Udo, G.J., Bagchi, K.K., Kirs, P.J.: Exploring the role of espoused values on e-service adoption: a comparative analysis of the US and Nigerian users. Comput. Hum. Behav. 28 (5), 1768–1781 (2012)

Urbach, N., Müller, B.: The updated DeLone and McLean model of information systems success. In: Information Systems Theory (pp. 1–18). Springer, New York (2012)

Vatanasombut, B., Igbaria, M., Stylianou, A.C., Rodgers, W.: Information systems continuance intention of web-based applications customers: the case of online banking. Inf. Manag. 45 , 419–428 (2008)

Venkatesh, V.: Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Inf. Syst. Res. 11 (4), 342–365 (2000)

Venkatesh, V., Bala, H.: Technology acceptance model 3 and a research agenda on interventions. Decis. Sci. 39 (2), 273–315 (2008)

Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46 (2), 186–204 (2000)

Venkatesh, V., Morris, M., Davis, G., Davis, F.: User acceptance of information technology: toward a unified view. MIS Q. 27 (3), 425–478 (2003)

Venkatesh, V., Thong, J.Y., Xu, X.: Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q. 36 (1), 157–178 (2012)

Wang, H.-Y., Wu, S.-Y.: Factors influencing behavioural intention to patronise restaurants using iPad as a menu card. Behav. Inf. Technol. 33 (4), 395–409 (2014)

Wang, Y., Qualls, W.: Towards a theoretical model of technology adoption in hospitality organizations. Int. J. Hosp. Manag. 26 (3), 560–573 (2007)

Wang, Y.-S., Lin, H.-H., Luarn, P.: Predicting consumer intention to use mobile service. Inf. Syst. J. 2 , 157–179 (2006)

Wang, Y.-S., Wu, M.-C., Wang, H.-Y.: Investigating the determinants and age and gender differences in the acceptance of mobile learning. Br. J. Educ. Technol. 40 (1), 92–118 (2009)

Watjatrakul, B.: Intention to use a free voluntary service: the effects of social influence, knowledge and perceptions. J. Syst. Inf. Technol. 15 (2), 202–220 (2013)

Weerakkody, V., El-Haddadeh, R., Al-Sobhi, F., Shareef, M.A., Dwivedi, Y.K.: Examining the influence of intermediaries in facilitating e-government adoption: an empirical investigation. Int. J. Inf. Manag. 33 (5), 716–725 (2013)

Wei, H., Lin, K., Lu, H., Chuang, I., Lin, K., Lu, H., Chuang, I.: Understanding the intentions of users to “stick” to social networking sites: a case study in Taiwan. Behav. Inf. Technol. 34 (2), 151–162 (2015)

Wei, L., Zhang, M.: The adoption and use of mobile phone in rural China: a case study of Hubei, China. Telemat. Inform. 25 (3), 169–186 (2008)

White, A., Daniel, E., Ward, J., Wilson, H.: The adoption of consortium B2B e-marketplaces: an exploratory study. J. Strateg. Inf. Syst. 16 (1), 71–103 (2007)

Wong, C.H., Tan, G.W.H., Loke, S.P., Ooi, K.B.: Adoption of mobile social networking sites for learning? Online Inf. Rev. 39 (6), 762–778 (2015)

Wu, C.: Facebook users’ intentions in risk communication and food-safety issues. J. Bus. Res. 68 (11), 2242–2247 (2015)

Wu, I.-L., Li, J.-Y., Fu, C.-Y.: The adoption of mobile healthcare by hospital’s professionals: an integrative perspective. Decis. Support Syst. 51 (3), 587–596 (2011)

Wu, J.H., Cheng, C.M., Cheng, P.J.: Behavioral intention toward urban eco-land performance assessment models using TPB tests. J. Bus. Res. 68(4), 771–776 (2014)

Wu, W.-W.: Mining significant factors affecting the adoption of SaaS using the rough set approach. J. Syst. Softw. 84 (3), 435–441 (2011)

Wu, W.-W.: Developing an explorative model for SaaS adoption. Expert Syst. Appl. 38 (12), 15057–15064 (2011)

Wu, X., Subramaniam, C.: Understanding and predicting radio frequency identification (RFID) adoption in supply chains. J. Organ.l Comput. Electron. Commer. 21 (4), 348–367 (2011)

Xu, C., Ryan, S., Prybutok, V., Wen, C.: It is not for fun: an examination of social network site usage. Inf. Manag. 49 (5), 210–217 (2012)

Yadav, R., Chauhan, V., Pathak, G.S.: Intention to adopt internet banking in an emerging economy: a perspective of Indian youth. Int. J. Bank Mark. 33 (4), 530–544 (2015)

Yang, C., Hsu, Y.-C.: Impact of ergonomic and social psychological perspective: a case study of fashion technology adoption in Taiwan. Int. J. Hum.-Comput. Interact. 27 (7), 583–605 (2011)

Yang, H.L., Lin, S.L.: User continuance intention to use cloud storage service. Comput. Hum. Behav. 52 , 219–232 (2015)

Yang, H., Moon, Y., Rowley, C.: Social influence on knowledge worker’s adoption of innovative information technology. J. Comput. Inf. Syst. 50 (1), 25–36 (2009)

Yang, H.-L., Lai, C.-Y.: Understanding knowledge-sharing behaviour in Wikipedia. Behav. Inf. Technol. 30 (1), 131–142 (2011)

Yang, S., Lu, Y., Gupta, S., Cao, Y.: Does context matter? The impact of use context on mobile Internet adoption. Int. J. Hum.-Comput. Interact. 28 (8), 530–541 (2012)

Yang, S., Lu, Y., Gupta, S., Cao, Y., Zhang, R.: Mobile payment services adoption across time: an empirical study of the effects of behavioral beliefs, social influences, and personal traits. Comput. Hum. Behav. 28 (1), 129–142 (2012)

Yang, Z., Sun, J., Zhang, Y., Wang, Y.: Understanding SaaS adoption from the perspective of organizational users: a tripod readiness model. Comput. Hum. Behav. 45 , 254–264 (2015)

Yen, C.-H., Lu, H.-P.: Factors influencing online auction repurchase intention. Internet Res. 18 (1), 7–25 (2008)

Yen, D.C., Wu, C.-S., Cheng, F.-F., Huang, Y.-W.: Determinants of users’ intention to adopt wireless technology: an empirical study by integrating TTF with TAM. Comput. Hum. Behav. 26 (5), 906–915 (2010)

Yigitbasioglu, O.M.: The role of institutional pressures and top management support in the intention to adopt cloud computing solutions. J. Enterp. Inf. Manag. 28 (4), 579–594 (2015)

Yin, F., Liu, M., Lin, C.: Forecasting the continuance intention of social networking sites: assessing privacy risk and usefulness of technology. Technol. Forecast. Soc. Chang. 99 , 267–272 (2015)

Yiu, C.S., Grant, K., Edgar, D.: Factors affecting the adoption of Internet Banking in Hong Kong-implications for the banking sector. Int. J. Inf. Manag. 27 (5), 336–351 (2007)

Yu, J., Lee, H., Ha, I., Zo, H.: User acceptance of media tablets: an empirical examination of perceived value. Telem. Informa. 34 (4), 206–223 (2015)

Yu, J., Zo, H., Choi, M.K., Ciganek, A.P.: User acceptance of location-based social networking services: an extended perspective of perceived value. Online Inf. Rev. 37 (5), 711–730 (2013)

Zand, D.E.: Trust and managerial problem solving. Adm. Sci. Q. 17 (2), 229–239 (1972)

Zarmpou, T., Saprikis, V., Markos, A., Vlachopoulou, M.: Modeling users’ acceptance of mobile services. Electron. Commer. Res. 12 (2), 225–248 (2012)

Zeithaml, V.A.: Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. J. Mark. 52 (3), 2–22 (1988)

Zhang, L., Zhu, J., Liu, Q.: A meta-analysis of mobile commerce adoption and the moderating effect of culture. Comput. Hum. Behav. 28 (5), 1902–1911 (2012)

Zheng, D., Chen, J., Huang, L., Zhang, C.: E-government adoption in public administration organizations: integrating institutional theory perspective and resource-based view. Eur. J. Inf. Syst. 22 (2), 221–234 (2012)

Zhou, T., Lu, Y.: The effects of personality traits on user acceptance of mobile commerce. Int. J. Hum.-Comput. Interact. 27 (6), 545–561 (2011)

Zhou, T., Lu, Y., Wang, B.: Integrating TTF and UTAUT to explain mobile banking user adoption. Comput. Hum. Behav. 26 (4), 760–767 (2010)

Zhu, D.H., Chang, Y.P.: Investigating consumer attitude and intention toward free trials of technology-based services. Comput. Hum. Behav. 30 , 328–334 (2014)

Zhu, D.H., Chang, Y.P., Luo, J.J., Li, X.: Understanding the adoption of location-based recommendation agents among active users of social networking sites. Inf. Process. Manag. 50 (5), 675–682 (2014)

Zhu, W.W., Morosan, C.: An empirical examination of guests’ adoption of interactive mobile technologies in hotels: revisiting cognitive absorption, playfulness, and security. J. Hosp. Tour. Technol. 5 (1), 78–94 (2014)

Zuiderwijk, A., Janssen, M., Dwivedi, Y.K.: Acceptance and use predictors of open data technologies: drawing upon the unified theory of acceptance and use of technology. Govt. Inf. Q. 32 (4), 429–440 (2015)

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Salahshour Rad, M., Nilashi, M. & Mohamed Dahlan, H. Information technology adoption: a review of the literature and classification. Univ Access Inf Soc 17 , 361–390 (2018).

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Literature Review on the Impact of Digital Technology on Learning and Teaching

This literature review was commissioned by the Scottish Government to explore how the use of digital technology for learning and teaching can support teachers, parents, children and young people in improving outcomes and achieving our ambitions for education in Scotland

Digital learning and raising attainment

Key findings

There is conclusive evidence that digital equipment, tools and resources can, where effectively used, raise the speed and depth of learning in science and mathematics for primary and secondary age learners. There is indicative evidence that the same can be said for some aspects of literacy, especially writing and comprehension. Digital technologies appear to be appropriate means to improve basic literacy and numeracy skills, especially in primary settings.

The effect sizes are generally similar to other educational interventions that are effective in raising attainment, though the use of digital learning has other benefits. Also, the extent of the effect may be dampened by the level of capability of teachers to use digital learning tools and resources effectively to achieve learning outcomes. More effective use of digital teaching to raise attainment includes the ability of teachers to identify how digital tools and resources can be used to achieve learning outcomes and adapting their approach, as well as having knowledge and understanding of the technology. This applies in all schools.

Where learners use digital learning at home as well as school for formal and non-formal learning activities these have positive effects on their attainment, because they have extended their learning time. This is particularly important for secondary age learners.

The assessment framework, set out in Annex 2 , identifies a number of educational benefits that digital learning and teaching has the potential to help learners aged 5 to 18 to realise, through the opportunity to learn in different ways, access more sources of information, and be tested and get feedback differently. In terms of raising attainment, these benefits include short term outcomes, such as having a greater feeling of control over learning and more confidence to practise a skill, through to medium term outcomes such as faster acquisition of knowledge and skills, and improved impacts in terms of learners achieving higher exam or test results where digital technology has been used.

In this section, the impact of digital technology on children's attainment in a range of areas is discussed, followed by the impact on aspects of numeracy, literacy and science learning.

Raising children's attainment

There is a substantial body of research that has examined the impact of digital tools and resources on children's attainment in a range of areas.

Higgins et al (2012) provide a summary of research findings from studies with experimental and quasi-experimental designs, which have been combined in meta-analyses to assess the impact of digital learning in schools. Their search identified 48 studies which synthesised empirical research of the impact of digital tools and resources on the attainment of school age learners (5-18 year olds).

They found consistent but small positive associations between digital learning and educational outcomes. For example, Harrison et al (2004) identified statistically significant findings, positively associating higher levels of ICT use with school achievement at each Key Stage in England, and in English, maths, science, modern foreign languages and design technology. Somekh et al (2007) identified a link between high levels of ICT use and improved school performance. They found that the rate of improvement in tests in English at the end of primary education was faster in ICT Test Bed education authorities in England than in equivalent comparator areas. However, Higgins et al note that while these associations show, on average, schools with higher than average levels of ICT provision also have learners who perform slightly higher than average, it may be the case that high performing schools are more likely to be better equipped or more prepared to invest in technology or more motivated to bring about improvement.

Higgins et al report that in general analyses of the impact of digital technology on learning, the typical overall effect size is between 0.3 and 0.4 - just slightly below the overall average for researched interventions in education (Sipe & Curlette, 1997; Hattie, 2008) and no greater than other researched changes to teaching to raise attainment, such as peer tutoring or more focused feedback to learners. The range of effect sizes is also very wide (-0.03 to 1.05),which suggests that it is essential to take into account the differences between technologies and how they are used.

Table 4: Summary of meta-analyses published between 2000 and 2012 (in Higgins et al 2012)

In an earlier meta-analysis, Liao et al (2007), considered the effects of digital tools and resources on elementary school learners' achievement in Taiwan. Synthesizing research comparing the effects of digital learning (equipment, tools and resources) with traditional instruction on elementary school learners' achievement, they considered quantitative and qualitative information from 48 studies including over 5,000 learners. Of the 48 studies, 44 (92%) showed positive effects in favour of a computer assisted intervention, while four (8%) were negative and favoured a traditional instruction method. Nearly 60% of the studies examined the effects of computer aided instruction for teaching mathematics or science. Another 11% of the studies concentrated on the teaching of reading and language. They found an overall positive effect size across all the studies of 0.45 (study-weighted grand mean), which is considered to be a moderate effect, with a wide range of effect sizes (from 0.25 to 2.67).

No significant differences were found between subject areas, and the authors suggest that digital learning has the potential to be implemented in many different subject areas. They found that the two subjects that showed the highest effects were reading and languages, which had a high positive effect size of 0.7. Studies using computer simulations also had higher effects. The authors suggest this may be because simulations can provide learners with the opportunity to engage in a learning activity which could not be replicated in a classroom.

More qualitative studies have identified how improvements in attainment are achieved. From a wide study of primary and secondary schools in England that were early adopters in using digital learning and teaching, Jewitt et al (2011) concluded that:

  • Using digital resources provided learners with more time for active learning in the classroom;
  • Digital tools and resources provided more opportunity for active learning outside the classroom, as well as providing self-directed spaces, such as blogs and forums, and access to games with a learning benefit;
  • Digital resources provided learners with opportunities to choose the learning resources;
  • The resources provided safer spaces for formative assessment and feedback.

The sections below focus on specific key areas of attainment: literacy, numeracy, and science learning.

There is a large body of research that has examined the impact of digital equipment, tools and resources on children's literacy. The effects are generally positive, though not as large as the effects found where digital learning is used to improve numeracy, and consistent in finding that ICT helps improve reading and writing skills, as well as developing speaking and listening skills.

Effect of context

Archer and Savage (2014) undertook a meta-analysis to reassess the outcomes presented in three previous meta-analyses considering the impact of digital learning on language and literacy learning: Slavin et al (2008 and 2009) and Torgenson and Zhu (2003). Overall they found a relatively small average positive effect size of 0.18, with a few of the studies having a negative effect and three studies showing moderate to large effect sizes. The authors found that programmes with a small number of participants tended to show larger effect sizes than larger programmes but that not all were statistically significant.

Archer and Savage sought to understand whether the context within which the digital tool or resource was used has an impact on outcomes. In particular, they examined whether training and support given to the teachers or other staff delivering the programme had an impact. The authors found that training and support could be identified in around half of the studies and that it did appear to have a positive impact on the effectiveness of the literacy intervention, with the average effect size rising to 0.57. The authors conclude that this indicates the importance of including implementation factors, such as training and support, when considering the relative effectiveness of digital learning and teaching.

Effect on specific literacy skills

In their meta-analysis, Higgins et al (2012) found that digital learning has a greater impact on writing than on reading or spelling. For example, Torgenson and Zhu (2003) reviewed the impact of using digital technology on the literacy competences of 5-16 year-olds in English and found effect sizes on spelling (0.2) and reading (0.28) much lower than the high effect size for writing (0.89).

In their meta-analysis of studies investigating the effects of digital technology on primary schools in Taiwan, Laio et al (2007) considered studies over a range of curriculum areas; 11 of which addressed the effects of using digital learning in one or more literacy competence. They found no significant differences in effect size between the different subject areas, suggesting the potential for digital technology to raise outcomes is equal across different subjects. However, they did note that the two areas that showed the highest effect sizes (over 0.7) were reading and comprehension.

Effect of specific digital tools and resources

Somekh et al (2007) evaluated the Primary School Whiteboard Expansion ( PSWB ) project in England. They found that the length of time learners were taught with interactive whiteboards ( IWB s) was a major factor in learner attainment at the end of primary schooling, and that there were positive impacts on literacy (and numeracy) once teachers had experienced sustained use and the technology had become embedded in pedagogical practice. This equated to improvements at Key Stage 2 writing (age 11), where boys with low prior attainment made 2.5 months of additional progress.

Hess (2014) investigated the impact of using e-readers and e-books in the classroom, among 9-10 year olds in the USA . The e-books were used in daily teacher-led guided reading groups, replacing traditional print books in these sessions. Teachers also regularly used the e-readers in sessions where the class read aloud, and e-readers were available to learners during the school day for silent reading. The study found a significant difference in reading assessment scores for the group using the e-readers. Scores improved for both male and female learners and the gap between males and females decreased.

The use of digital tools and resources also appears to affect levels of literacy. Lysenko and Abrami (2014) investigated the use of two digital tools on reading comprehension for elementary school children (aged 6-8) in Quebec, Canada. The first was a multimedia tool which linked learning activities to interactive digital stories. The tool included games to engage learners in reading and writing activities, and instructions were provided orally to promote listening comprehension. The second tool was a web-based electronic portfolio in which learners could create a personalised portfolio of their reading and share work with peers, teachers and parents to get feedback. The authors found that in classes where both tools were used together during the whole school year learners performed significantly better both in vocabulary and reading comprehension (with medium-level effect sizes) than learners in classes where the tools were not part of English language instruction.

Rosen and Beck-Hill (2012) reported on a study programme that incorporated an interactive core curriculum and a digital teaching platform. At the time of their report it was available for 9-11 year old learners in English language, arts and mathematics classes in Dallas, Texas. The online platform contained teaching and learning tools. Learners were assessed using standardised tests administered before the programme and after a year's participation. The results of increased achievement scores demonstrated that in each of the two school year groups covered, the experimental learners significantly outperformed the control learners in reading and maths scores. In observations in classrooms that used the programme, the researchers observed higher teacher-learner interaction, a greater number and type of teaching methods per class, more frequent and complex examples of differentiation processes and skills, more frequent opportunities for learner collaboration, and significantly higher learner engagement. The authors report that the teaching pedagogy observed in the classrooms differed significantly from that observed in more traditional classrooms. The teachers following the programme commented that the digital resources made planning and implementing 'differentiation' more feasible. This is differentiation of teaching in terms of content, process, and product, to reflect learners' readiness, interests, and learning profile, through varied instructional and management strategies.

Effect of the amount and quality of digital technology use

The uses of digital technology and access to it appear to be critical factors. Lee et al (2009) analysed how in the US 15-16 year-old learners' school behaviour and standardised test scores in literacy are related to computer use. Learners were asked how many hours a day they typically used a computer for school work and for other activities. The results indicated that the learners who used the computer for one hour a day for both school work and other activities had significantly better reading test scores and more positive teacher evaluations for their classroom behaviours than any other groups [5] . This was found while controlling for socio-economic status, which has been shown to be a predictor of test scores in other research. The analysis used data from a national 2002 longitudinal study, and it is likely that learners' usage of computers has increased and changed since that time.

Biagi and Loi (2013), using data from the 2009 Programme for International Student Assessment ( PISA ) and information on how learners used digital technology at school and at home (both for school work and for entertainment), assessed the relationship between the intensity with which learners used digital tools and resources and literacy scores. They examined uses for: gaming activities (playing individual or collective online games), collaboration and communication activities (such as linking with others in on-line chat or discussion forums), information management and technical operations (such as searching for and downloading information) and creating content, knowledge and problem solving activities (such as using computers to do homework or running simulations at school). These were then compared to country specific test scores in reading. The authors found a positive and significant relationship between gaming activity and language attainment in 11 of the 23 countries studied. For the other measures, where relationships existed and were significant, they tended to be negative.

The more recent PISA data study ( OECD , 2015, using 2012 results) also found a positive relationship between the use of computers and better results in literacy where it is evident that digital technology is being used by learners to increase study time and practice [6] . In addition, it found that the effective use of digital tools is related to proficiency in reading.

There is a large body of research which has examined the impact of digital equipment, tools and resources on children's numeracy skills and mathematical competences throughout schooling. Higgins et al (2012) found from their meta-analysis that effect sizes of tested gains in knowledge and understanding tend to be greater in mathematics and science than in literacy. The key benefits found relate to problem solving skills, practising number skills and exploring patterns and relationships (Condie and Monroe, 2007), in addition to increased learner motivation and interest in mathematics.

Effect on specific numeracy skills

Li and Ma's (2010) meta-analysis of the impact of digital learning on school learners' mathematics learning found a generally positive effect. The authors considered 46 primary studies involving a total of over 36,000 learners in primary and secondary schools. About half of the mathematics achievement outcomes were measured by locally-developed or teacher-made instruments, and the other half by standardized tests. Almost all studies were well controlled, employing random assignment of learners to experimental or control conditions.

Overall, the authors found that, on average, there was a high, significantly positive effect of digital technology on mathematics achievement (mean effect size of 0.71), indicating that, in general, learners learning mathematics with the use of digital technology had higher mathematics achievement than those learning without digital technology. The authors found that:

  • Although the difference was small, younger school learners (under 13 years old) had higher attainment gains than older secondary school learners;
  • Gains were more positive where teaching was more learner-centred than teacher-centred. In this regard, the authors differentiate between traditional models, where the teacher tends to teach to the whole class, and a learner-centred teaching model which is discovery-based (inquiry-oriented) or problem-based (application-oriented) learning;
  • Shorter interventions (six months or less) were found to be more effective in promoting mathematics achievement than longer interventions (between six and 12 months). It is suggested that such gains in mathematics achievement are a result of the novelty effects of technology, as suggested in other research, and as learners get familiar with the technology the novelty effects tend to decrease;
  • The authors found no significant effects from different types of computer technology on mathematics achievement. Whether it was used as communication media, a tutorial device, or exploratory environment, learners displayed similar results in their mathematics achievement;
  • Equally, the authors found no significant relationship between the effect of using digital technology and the characteristics of learners included in the samples for studies, such as gender, ethnicity, or socio-economic characteristics.

The studies by Lee et al (2009) and Biagi and Loi (2013) found similar results for mathematics as they did for reading and literacy in relation to the use of digital equipment. Learners who used a computer at least one hour a day for both school work and other activities had significantly better mathematics test scores and more positive teacher evaluations for their classroom behaviour in mathematics classes than those who did not use the computer. Biagi and Loi (2013) found a significant positive relationship between intensity of gaming activity and maths test scores in 15 countries out of the 23 studied. As with language, the authors found that learners' total use of digital technologies was positively and significantly associated with PISA test scores for maths in 18 of the 23 countries studied.

Studies have found that using digital equipment for formal learning is also associated with increases in learners' motivation for learning mathematics. House and Telese (2011 and 2012) found that:

  • For learners aged 13 and 14 in South Korea, for example, those who expressed high levels of enjoyment at learning mathematics, more frequently used computers in their mathematics homework. However, learners who more frequently played computer games and used the internet outside of school tended to report that they did not enjoy learning mathematics;
  • Learners in the USA and Japan aged 13 and 14 who showed higher levels of algebra achievement also used computers more at home and at school for school work. Those who used computers most for other activities had lower test scores. In each of the USA and Japan they found that overall computer usage which included use for school work was significantly related to improvements in test scores.

Somekh et al (2007) found that, once the use of IWB s was embedded, in Key Stage 1 mathematics (age 7) in England, high attaining girls made gains of 4.75 months, enabling them to catch up with high attaining boys. In Key Stage 2 mathematics (age 11), average and high attaining boys and girls who had been taught extensively with the IWB made the equivalent of an extra 2.5 to 5 months' progress over the course of two years.

Digital tools and resources can also increase some learners' confidence in mathematics as well as their engagement in new approaches to learning and their mathematical competences. Overcoming learners' anxieties about mathematics and their competence in specific aspects of the subject are common concerns in teaching mathematics which hampers their ability to learn (reported in Huang et al 2014).

Huang et al (2014) researched the outcomes, in Taiwan, from a computer game simulating the purchase of commodities, from which 7 and 8 year-old primary school learners can learn addition and subtraction, and apply mathematical concepts. The model combined games-based learning with a diagnosis system. When the learner made a mistake, the system could detect the type of mistake and present corresponding instructions to help the learner improve their mathematical comprehension and application. The authors compared two learning groups: both used the game-based model but one without the diagnostic, feedback element. They found that the learning achievement post-test showed a significant difference and also that the mathematics anxiety level of the two learner groups was decreased by about 3.5%.

Passey (2011) found that among over 300 schools in England using Espresso digital resources, those that had been using them over a longer period made significantly greater increases in end of primary school numeracy test results than schools which were recent users.

Science learning

Effects on science knowledge and skills

In their meta-analysis, Laio et al (2007) considered 11 studies looking at the impact of digital technology on science learning. These had a moderate average effect size of 0.38 and generally had positive effects. Condie and Monroe (2007) identified that digital learning made science more interesting, authentic and relevant for learners and provided more time for post-experiment analysis and discussion.

In their study of the PISA data, Biagi and Loi (2013) found a significant positive relationship between learners' total use of digital equipment and science test scores in 21 of the 23 countries they studied. They also found evidence of a significant positive relationship between the intensity of using gaming activity and science scores in 13 of the 23 countries they studied. Somekh et al (2007) found that in primary school science all learners, except high attaining girls, made greater progress when given more exposure to IWB s, with low attaining boys making as much as 7.5 months' additional progress.

Effects of specific digital tools and resources

Digital tools and resources generally have a positive effect on learners' science learning. This can be seen from a number of studies assessing outcomes for learners in different stages of education.

Hung et al (2012) explored the effect of using multi-media tools in science learning in an elementary school's science course in Taiwan. Learners were asked to complete a digital storytelling project by taking pictures with digital cameras, developing the story based on the pictures taken, producing a film based on the pictures by adding subtitles and a background, and presenting the story. From the experimental results, the authors found that this approach improved the learners' motivation to learn science, their attitude, problem-solving capability and learning achievements. In addition, interviews found that the learners in the experimental group enjoyed the project-based learning activity and thought it helpful because of the digital storytelling aspect.

Hsu et al (2012) investigated the effects of incorporating self-explanation principles into a digital tool facilitating learners' conceptual learning about light and shadow with 8-9 year old learners in Taiwan. While they found no difference in the overall test scores of the experimental and control groups, they found a statistically significant difference in retention test scores. Those learners who had paid more attention to the self-explanation prompts tended to outperform those in the control group.

Anderson and Barnett's (2013) study, in the US , examined how a digital game used by learners aged 12-13 increased their understanding of electromagnetic concepts, compared to learners who conducted a more traditional inquiry-based investigation of the same concepts. There was a significant difference between the control and experimental groups in gains in knowledge and understanding of physics concepts. Additionally, learners in the experimental group were able to give more nuanced responses about the descriptions of electric fields and the influence of distance on the forces that change experience because of what they learnt during the game.

Güven and Sülün (2012) considered the effects of computer-enhanced teaching in science and technology courses on the structure and properties of matter, such as the periodical table, chemical bonding, and chemical reactions, for 13-14 year olds in Turkey. Their proposition was that computer-enhanced teaching can instil a greater sense of interest in scientific and technological developments, make abstract concepts concrete through simulation and modelling, and help to carry out some dangerous experiments in the classroom setting. They found a significant difference in achievement tests between the mean scores of the group of learners who were taught with the computer-enhanced teaching method and the control group who were taught with traditional teaching methods.

Belland (2009) investigated the extent to which a digital tool improved US middle school children's ability to form scientific arguments. Taking the premise that being able to construct and test an evidence-based argument is critical to learning science, he studied the impact of using a digital problem based learning tool on 12-14 year olds. Learners worked in small groups and were asked to develop and present proposals for spending a grant to investigate an issue relating to the human genome project. Those in the experimental group used an online system which structured the project into stages of scientific enquiry. The system prompted the learners to structure and organise their thinking in particular ways: by prompting the learners individually, sharing group members' ideas, tasking the group to form a consensus view, and prompting the group to assign specific tasks among themselves.

Using pre- and post- test scores to assess the impact on learners' abilities to evaluate arguments, Belland found a high positive effect size of 0.62 for average-achieving learners compared to their peers in the control group. No significant impacts were found for higher or lower-achieving learners. Belland suggests that for high-achieving learners, this may be because they already have good argument making skills and are already able to successfully structure how they approach an issue and gather evidence. The study also used qualitative information to consider how the learners used the digital tool and compared this to how learners in the control group worked. The author found that in the experimental group they made more progress and were more able to divide tasks up between them, which saved time. They also used the tool more and the teacher less to provide support.

Kucukozer et al (2009) examined the impact of digital tools on teaching basic concepts of astronomy to 11-13 year old school children in Turkey. Learners were asked to make predictions about an astronomical phenomenon such as what causes the seasons or the phases of the moon. A digital tool was used to model the predictions and display their results. The learners were then asked to explain the differences and the similarities between their predictions and their observations. In the prediction and explanation phase the learners worked in groups to discuss their ideas and come to a conclusion. In the observation phase they watched the 3D models presented by their teacher. Thereafter, they were asked to discuss and make conclusions about what they had watched. The authors found that instruction supported by observations and the computer modelling was significantly effective in bringing about better conceptual understanding and learning on the subject.

Ingredients of success

Where studies examine the process that brings about positive results from digital learning and teaching compared to traditional approaches, it is evident that these are more likely to be achieved where digital equipment, tools and resources are used for specific learning outcomes and built into a teaching model from the outset. This broadly supports Higgins et al's (2012) conclusions that:

  • Digital technology is best used as a supplement to normal teaching rather than as a replacement for it;
  • It is not whether technology is used (or not) which makes the difference, but how well the technology is applied to support teaching and learning by teachers;
  • More effective schools and teachers are more likely to use digital technologies effectively than other schools.

Differences in effect sizes and the extent that learners achieve positive gains in attainment are ascribed by most authors of the studies above to:

  • The quality of teaching and the ability of teachers to use the digital equipment and tools effectively for lessons;
  • The preparation and training teachers are given to use equipment and tools;
  • The opportunities teachers have to see how digital resources can be used and pedagogies adapted (Rosen and Beck-Hill, 2012; Belland, 2009).

Teachers have to adapt to learner-centred approaches to learning if they are to use digital tools and resources (Li and Ma, 2010).

As well as ensuring digital tools and resources are supporting learning goals, success appears to also be linked to some other factors:

  • The availability of equipment and tools within schools (and at home);
  • How learners use digital equipment. Higgins et al (2012) found that collaborative use of technology (in pairs or small groups) is usually more effective than individual use, though some learners - especially younger children - may need guidance in how to collaborate effectively and responsibly;
  • The extent that teaching continues to innovate using digital tools and resources (Higgins et al, 2012).

Fullan (2013) suggested four criteria that schools should meet if their use of digital technology to support increased attainment is to be successful. These were that systems should be engaging for learners and teachers; easy to adapt and use; ubiquitous - with access to the technology 24/7; and steeped in real life problem solving.

Fullan and Donnelly (2013) developed these themes further, proposing an evaluation tool to enable educators to systematically evaluate new companies, products and school models, using the context of what they have seen as necessary for success. Questions focus on the three key criteria of pedagogy (clarity and quality of intended outcome, quality of pedagogy and the relationship between teacher and learner, and quality of assessment platform and functioning); system change (implementation support, value for money, and whole system change potential) and technology (quality of user experience/model design, ease of adaptation, and comprehensiveness and integration).

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  • Open access
  • Published: 15 April 2024

Correction: Role of AI chatbots in education: systematic literature review

  • Lasha Labadze 1 ,
  • Maya Grigolia 2 &
  • Lela Machaidze 3  

International Journal of Educational Technology in Higher Education volume  21 , Article number:  28 ( 2024 ) Cite this article

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The Original Article was published on 31 October 2023

Correction: Int J Educ Technol High Educ 20, 56 (2023)

After publication of the original article (Labadze et al., 2023 ), the authors became aware that the use of a Large Language Model (LLM) has not been sufficiently documented in accordance with our editorial policy.

In view of this, the authors would like to add the following sentence to the Methodology section of the article:

“To improve the clarity of the discussion section, we employed Large Language Model (LLM) for stylistic suggestions.”

The original article has been updated.

Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI chatbots in education: Systematic literature review. Int J Educ Technol High Educ , 20 , 56. .

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Please note you do not have access to teaching notes, technology acceptance model in halal industries: a systematic literature review and research agenda.

Journal of Islamic Marketing

ISSN : 1759-0833

Article publication date: 16 April 2024

The continued relevance of technologies in halal industries requires managers to understand the factors contributing to such technologies’ acceptance. The technology acceptance model (TAM) is dominant in the literature that predicts user acceptance and behaviour towards technology. Despite the model’s significance, there has yet to be a systematic review of studies featuring halal sectors that use TAM. The purpose of this study is to systematically review the existing literature on TAM in halal industries to understand the research trends as well as TAM modifications and research opportunities in halal industries.


Guided by the preferred reporting items for systematic review and meta-analysis protocol, a framework-based review using the theories, contexts, characteristics and methods (TCCM) framework was conducted. The Scopus and Web of Science databases were used to retrieve English journal articles that investigated TAM in the context of halal markets. In total, 44 eligible articles were reviewed in terms of the developments and extensions of TAM in their studies across the halal industries.

The first study related to the use of TAM in the context of halal industries was published in 2014. The most prominent halal industry in the review, which used TAM, was Islamic finance. Indonesia was the leading economy in halal studies using TAM. Perceived usefulness was found to be a more significant factor than perceived ease of use for technology acceptance in TAM studies on halal industries. The significance of religiosity on TAM was inconsistent. Most research was done using quantitative surveys with consumers as the target sample.

Research limitations/implications

The studies in this review are based on the Scopus and Web of Science databases, which may be perceived as a study limitation. This study also only considered English journal articles and research in which the focus was on the use of TAM in halal industries rather than general industries with Muslim consumers.

Practical implications

Halal industries will continue to rely on technology for the provision of goods and services. With the rise of emerging technological innovations, this review will provide managers with an appreciation of technology acceptance across different contexts. Researchers can use the results of this review to guide future studies and contribute toward the development of this research area.


This review contributes to the Islamic marketing literature by being the first to comprehensively review the TAM model in the context of halal industries using the TCCM framework-based review approach. A research agenda is proposed to advance research on technology acceptance and TAM in halal industries.

  • Technology acceptance model
  • Technology adoption
  • Systematic literature review

Noor, N. (2024), "Technology acceptance model in halal industries: a systematic literature review and research agenda", Journal of Islamic Marketing , Vol. ahead-of-print No. ahead-of-print.

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Copyright © 2024, Emerald Publishing Limited

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Multi-dimensional challenges in the Indonesian social science information technology-based learning: A systematic literature review


  • 1 Magister Pendidikan Guru Madrasah Ibtidaiyah, Pascasarjana, Universitas Islam Negeri Salatiga, Indonesia.
  • 2 Teknologi Informasi, Fakultas Dakwah, Universitas Islam Negeri Salatiga, Indonesia.
  • 3 Doktoral Pendidikan Agama Islam, Pascasarjana, Universitas Islam Negeri Salatiga, Indonesia.
  • 4 Komunikasi dan Penyiaran Islam, Fakultas Dakwah, Universitas Islam Negeri Salatiga, Indonesia.
  • 5 Ilmu Hadis, Fakultas Ushuluddin Adab dan Humaniora, Universitas Islam Negeri Salatiga, Indonesia.
  • PMID: 38601659
  • PMCID: PMC11004741
  • DOI: 10.1016/j.heliyon.2024.e28706

The development of information technology (IT) has an essential role in education today. Most teachers in Indonesia utilize the traditional method rather than the advancement of IT. Through digital media, the social science learning process becomes fascinating, improves students' skills, and is more engaging. However, implementing Information Technology-based Learning (ITBL) takes a lot of work. It comes with tremendous challenges that should be addressed carefully. Many previous studies explain the feasibility of the media, its effectiveness, and the advantages of using IT-based learning media. However, they still need to present the challenges in IT-based social science learning, even more so in the Indonesian context. Given the vast landscape of ITBL in Indonesia, a case study approach could entail extensive fieldwork, data collection, and data analysis. Therefore, A literature review can be carried out with less resource investment, making it a pragmatic choice for researchers with limited time and resources. This research aims to discover the challenges of students, teachers, and educational institutions in IT-based social science learning in the Indonesian context. The search protocol is based on the P.R.I.S.M.A. (Preferred Reporting Items for Systematic Reviews and Meta-analysis). This systematic literature review results were obtained from 315 articles discussing the challenges of IT-based social science learning published from 2018 until 2022. This research reveals that most challenges students face are internal/self-challenges. For instance, there needs to be more self-regulation and necessary digital literation. On the other hand, teachers' most significant challenge is their lack of skills and experience in implementing IT-based learning media and their inability to operate complex software, even if they have poor digital literacy. The need for facilities and technological training presents challenges for institutions. The need to procure IT infrastructure is due to the difficulty of reaching certain areas (the terrain) in Indonesia. The challenges encountered by students, teachers, and educational institutions are not exclusive to any particular group and extend beyond their respective domains. Addressing the multi-dimensional challenges would be more efficient. The poor digital literacy challenges occurred in other nations, too. This particular challenge can be solved through instructional training. Moreover, the Indonesian government offers numerous free digital training programs for individuals or institutions called "Digitalent."

Keywords: Digital education; E-Learning; Information technology; Learning challenges; Social science.

© 2024 The Authors.

  • Open access
  • Published: 13 December 2023

Arts and creativity interventions for improving health and wellbeing in older adults: a systematic literature review of economic evaluation studies

  • Grainne Crealey 1 ,
  • Laura McQuade 2 ,
  • Roger O’Sullivan 2 &
  • Ciaran O’Neill 3  

BMC Public Health volume  23 , Article number:  2496 ( 2023 ) Cite this article

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As the population ages, older people account for a larger proportion of the health and social care budget. A significant body of evidence suggests that arts and creativity interventions can improve the physical, mental and social wellbeing of older adults, however the value and/or cost-effectiveness of such interventions remains unclear.

We systematically reviewed the economic evidence relating to such interventions, reporting our findings according to PRISMA guidelines. We searched bibliographic databases (MEDLINE, EMBASE, Econlit and Web of Science and NHSEED), trial registries and grey literature. No language or temporal restrictions were applied. Two screening rounds were conducted independently by health economists experienced in systematic literature review. Methodological quality was assessed, and key information extracted and tabulated to provide an overview of the published literature. A narrative synthesis without meta-analysis was conducted.

Only six studies were identified which provided evidence relating to the value or cost-effectiveness of arts and creativity interventions to improve health and wellbeing in older adults. The evidence which was identified was encouraging, with five out of the six studies reporting an acceptable probability of cost-effectiveness or positive return on investment (ranging from £1.20 to over £8 for every £1 of expenditure). However, considerable heterogeneity was observed with respect to study participants, design, and outcomes assessed. Of particular concern were potential biases inherent in social value analyses.


Despite many studies reporting positive health and wellbeing benefits of arts and creativity interventions in this population, we found meagre evidence on their value or cost-effectiveness. Such evidence is costly and time-consuming to generate, but essential if innovative non-pharmacological interventions are to be introduced to minimise the burden of illness in this population and ensure efficient use of public funds. The findings from this review suggests that capturing data on the value and/or cost-effectiveness of such interventions should be prioritised; furthermore, research effort should be directed to developing evaluative methods which move beyond the confines of current health technology assessment frameworks, to capture a broader picture of ‘value’ more applicable to arts and creativity interventions and public health interventions more generally.

PROSPERO registration

CRD42021267944 (14/07/2021).

Peer Review reports

The number and proportion of older adults in the population has increased in virtually every country in the world over past decades [ 1 ]. In 2015, there were around 901 million people aged 60 years and over worldwide, by 2030, this will have increased to 1.4 billion [ 2 ]. An ageing population is one of the greatest successes of public health but it has implications for economies in numerous ways: slower labour force growth; working-age people will have to make greater provisions in welfare payments for older people who are no longer economically active; provisions for increased long-term care; and, society must adjust to the changing needs, expectations and capabilities of an expanding group of its citizens.

The Covid-19 pandemic shone an uncompromising light on the health and social care sector, highlighting the seriousness of gaps in policies, systems and services. It also focused attention on the physical and mental health consequences of loneliness and social isolation. To foster healthy ageing and improve the lives of older people, their families and communities, sustained and equitable investment in health and wellbeing is required [ 3 ]. The prevailing model of health and social care which is based ostensibly on formal care provision is unlikely to be sustainable over the longer term. New models, which promote healthy ageing and recognise the need for increasing reliance on self-care are required, as will be evidence of their effectiveness, cost-effectiveness and scalability.

Arts and creativity interventions (ACIs) can have positive effects on health and well-being, as several reviews have shown [ 4 , 5 ]. For older people, ACI’s can enhance wellbeing [ 6 , 7 , 8 , 9 ], quality of life [ 10 , 11 ] and cognitive function [ 12 , 13 , 14 , 15 , 16 ]. They can also foster social cohesion [ 17 , 18 , 19 ] and reduce social disparities and injustices [ 20 ]; promote healthy behaviour; prevent ill health (including enhancing well-being and mental health) [ 21 , 22 , 23 , 24 , 25 ], reducing cognitive decline [ 26 , 27 ], frailty [ 28 , 29 , 30 , 31 , 32 , 33 ] and premature mortality [ 34 , 35 , 36 , 37 , 38 ]); support people with stroke [ 39 , 40 , 41 , 42 ]; degenerative neurological disorders and dementias and support end of life care [ 43 , 44 ]. Moreover, ACIs can benefit not only individuals, but also others, such as supporting the well-being of formal and informal carers, enriching our knowledge of health, and improving clinical skills [ 4 , 5 ].

The benefits of ACIs have also been acknowledged at a governmental level by those responsible for delivering health and care services: The UK All-Party Parliamentary Special Interest group on Arts, Health and Wellbeing produced a comprehensive review of creative intervention for health and wellbeing [ 45 ]. This report contained three key messages: that the arts can keep us well, aid recovery and support longer better lived lives; they can help meet major challenges facing health and social care; and that the arts can save money for the health service and social care.

Despite robust scientific evidence and governmental support, no systematic literature review has collated the evidence with respect to the value, cost or cost-effectiveness of such interventions. Our objective was to assess the economic impact of ACIs aimed at improving the health and wellbeing of older adults; to determine the range and quality of available studies; identify gaps in the evidence-base; and guide future research, practice and policy.

A protocol for this review was registered at PROSPERO, an international prospective register of systematic reviews (Registration ID CRD42021267944). We used pre-determined criteria for considering studies to include in the review, in terms of types of studies, participant and intervention characteristics.

The review followed the five-step approach on how to prepare a Systematic Review of Economic Evaluations (SR-EE) for informing evidence-based healthcare decisions [ 46 , 47 , 48 ]. Subsequent to developing and registering the protocol, the International Society for Pharmacoeconomic Outcomes and Research (ISPOR) published a good practice task force report for the critical appraisal of systematic reviews with costs and cost-effectiveness outcomes (SR-CCEOs) [ 49 ]. This was also used to inform the conduct of this review.

Eligibility criteria

Full economic evaluations are regarded as the optimal type of evidence for inclusion in a SR-EE [ 46 ], hence cost-minimisation analyses (CMA), cost-effectiveness analyses (CEA), cost-utility analyses (CUA) and cost–benefit analyses (CBA) were included. Social value analyses were also included as they are frequently used to inform decision-making and commissioning of services within local government. Additionally, they represent an important intermediate stage in our understanding of the costs and consequences of public health interventions, where significant challenges exist with regard to performing full evaluations [ 50 , 51 , 52 , 53 ].

Development of search strategies

The population (P), intervention (I), comparator (C) and outcomes (O) (PICO) tool provided a framework for development of the search strategy. Studies were included if participants were aged 50 years or older (or if the average age of the study population was 50 years or over). Interventions could relate to performance art (dance, singing, theatre, drama etc.), creative and visual arts (painting, sculpture, art making and design), or creative writing (writing narratives, poetry, storytelling). The intervention had to be active (for example, creating art as opposed to viewing art; playing an instrument as opposed to listening to music). The objective of the intervention had to be to improve health and wellbeing; it had to be delivered under the guidance of a professional; delivered in a group setting and delivered on more than one occasion. No restrictions were placed on the type of comparator(s) or the type of outcomes captured in the study. We deliberately limited the study to professionally led activities to provide a sharper distinction between social events where arts and creativity may occur and arts and creativity interventions per se. We set no language restriction nor a restriction on the date from which studies were reported.

Search methods

PRESS (peer-review electronic search strategies) guidelines informed the design our search strategy [ 54 , 55 ] and an information specialist adapted the search terms (outlined in Table S 1 ) for the following electronic bibliographic databases: MEDLINE, PubMed, EMBASE, Econlit and Web of Science and NHSEED. We also inspected references of all relevant studies; and searched trials registers ( Search terms used included cost, return on investment, economic, arts, music, storytelling, dancing, writing and older adult as well as social return on investment (SROI). The last search was performed on 09/11/2022. As many economic evaluations of ACIs (especially SROIs) are commissioned by government bodies or charitable organisations, a search of the grey literature was undertaken.

Handling searches

A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow chart was used to document study selection, illustrating the numbers of records retrieved and selection flow through the screening rounds [ 56 , 57 , 58 ]; all excluded records (with rationale for exclusion) were documented.

Selection of studies

Two screening rounds were conducted independently by two health economists experienced in undertaking reviews (GC, CO’N). The first round screened the title and abstract of articles based on the eligibility criteria; those selected at this stage entered a second round of full text screening with eligibility based on the inclusion and exclusion criteria. Any disagreements were discussed among the two reviewers, with access to a third reviewer available to resolve disagreements, though this proved unnecessary.

Data extraction and management

Two reviewers extracted relevant information independently using an proforma developed specifically for the purposes of this study, which included all 35 items suggested by Wijnen et al. (2016) [ 48 ]. Information was extracted in relation to the following factors: (1) general information including study title, author, year, funding source, country, setting and study design; (2) recruitment details, sample size, demographic characteristics (age, gender) and baseline health data (diagnosis, comorbidities); (3) interventions, effectiveness and cost data; (4) type of economic evaluation, perspective, payer, beneficiary, time horizon, measure of benefit and scale of intervention; (5) quality assessment, strength of evidence, any other important information; (6) results; (7) analysis of uncertainty and (8) conclusions. The quality assessment/risk of bias checklists were included in the data extraction proforma, and picklists were used to enhance uniformity of responses. The data extraction form was piloted by two reviewers (GC and CON) on one paper and discussion used to ensure consistent application thereafter.

Assessment of study quality

Two reviewers (GC & CON) independently assessed study quality, with recourse to a third reviewer for resolution of differences though this proved unnecessary. Quality assessment was based on the type of economic evaluation undertaken. Full and partial trial-based economic evaluations were assessed using the CHEC-extended checklist [ 59 ]. SROI analyses were assessed using a SROI-specific quality framework developed for the purpose of systematic review [ 60 ].

Data analysis methods

Due to the small number of evaluations detected, possible sources of heterogeneity and a lack of consensus on appropriate methods for pooling cost-effectiveness estimates [ 61 ] a narrative synthesis analysis was undertaken.

Database searches returned 11,619 records; from this, 402 duplicates were removed leaving 11,214 reports. From these 113 reports were assessment against the inclusion and exclusion criteria resulting in 4 studies for inclusion in the review. Over 40 websites were searched for relevant content returning 2 further studies for inclusion. The PRISMA 2020 diagram is presented in Fig.  1 . A high sensitivity search strategy was adopted to ensure all relevant studies were identified, resulting in a large number of studies being excluded at the first stage of screening.

figure 1

PRISMA 2020 flow diagram for new systematic reviews which include searches of databases, registers and other sources

A total of six studies were identified; key characteristics are presented in Table 1 . Identified studies were published between 2011 and 2020. Two studies used a health technology assessment (HTA) framework alongside clinical trials [ 62 , 63 ] to assess the cost-effectiveness of community singing interventions. Both evaluations scored highly on the CHEC-extended checklist (Table 2 ), with findings reported in line with the CHEERS (Consolidated Health Economic Estimation Reporting Standards) checklist 2022 [ 64 ].

Four further studies employed an SROI framework to assess art and/or craft interventions: two studies were published in the peer-reviewed literature [ 65 , 66 ] and a further two in the grey literature [ 67 , 68 ]. All four adhered closely to the suggested steps for performing an SROI and consequently secured high scores (Table 3 ). No quality differential was discerned between those studies published in the academic literature when compared with those from the grey literature.

Five of the studies were undertaken in the UK [ 63 , 66 , 67 , 68 , 69 ] and one in the US [ 63 ]. Four of the studies were designed for older adults with no cognitive impairment [ 62 , 63 , 67 , 68 ]; one was designed for participants with or without dementia [ 65 ], and another was specifically for older adults with dementia and their caregivers [ 66 ]. Three of the studies were delivered in a community setting [ 62 , 63 , 67 ], two in care homes [ 65 , 68 ] and one across a range of settings (hospital, community and residential) [ 66 ]. The length and duration of the ACIs varied; some lasted 1–2 h (with multiple classes available to participants) [ 65 ], whereas others were structured programmes with sessions lasting 90 min over a 14-week period [ 62 ]. The number of participants included in studies varied; the largest study contained data from 390 participants [ 63 ], whereas other studies measured engagement using numbers of care homes or housing associations included [ 67 , 68 ].

Costs were captured from a narrower perspective (i.e., the payer—health service) for those economic evaluations which followed a health technology assessment (HTA) framework [ 62 , 63 ]. Costs associated with providing the programme and health and social care utilisation costs were captured using cost diaries. Valuation of resource usage was in line with the reference case specified for each jurisdiction.

Social value analyses included in the review [ 65 , 66 , 67 , 68 ] captured a broader picture of cost; programme provision costs included were similar in nature to those identified using an HTA framework, however, the benefits captured went beyond the individual to capture costs to a wide range of stakeholders such as family members, activity co-ordinations and care home personnel. Costs were apportioned using financial proxies from a range of sources including HACT Social Value Bank [ 69 ] and market-based valuation methods.

The range of outcomes captured and valued across HTAs and SROIs was extensive: including, but not limited to, wellbeing, quality of life, physical health, cognitive functioning, communication, control over daily life choices, engagement and empowerment, social isolation, mobility, community inclusion, depressive symptoms, sadness, anxiety, loneliness, positive affect and interest in daily life. In the programmes assessed using an HTA framework, outcomes were captured using standardised and validated instruments, for both control and intervention groups across multiple time points. Statistical methods were used to assess changes in outcomes over time. Programmes assessed using SROI relied primarily on qualitative methods (such as reflective diaries and in-depth interviews) combined with routinely collected administrative data.

The evidence from the singing interventions was encouraging but not conclusive. The ‘Silver Song Club’ programme [ 62 ] reported a 64% probability of being cost-effective at a willingness-to-pay threshold of £30,000. This study was also included in the Public Health England (PHE) decision tool to support local commissioners in designing and implementing services to support older people’s healthy ageing, reporting a positive societal return on investment [ 70 ]. Evidence from the ‘Community of Voices’ trial [ 63 ] suggested that although intervention group members experienced statistically significant improvements in loneliness and interest in life compared to control participants, no significant group differences were observed for cognitive or physical outcomes or for healthcare costs.

A positive return on investment was reported by all social value analyses undertaken. The ‘Imagine Arts’ programme, reported a positive SROI of £1.20 for every £1 of expenditure [ 65 ]. A higher yield of between £3.20-£6.62 for each £1 invested was reported in the ‘Dementia and Imagination’ programme [ 66 ]. The ‘Craft Café’ programme, reported an SROI of £8.27 per £1 invested [ 68 ], and the ‘Creative Caring’ programme predicted a SROI of between £3 to £4 for every £1 spent [ 67 ]. The time period over which return on investment was calculated differed for each evaluation from less than one year to 4 years.

The primary finding from our review concerns the paucity of evidence relating to the value, cost and/or cost-effectiveness of ACIs aimed at improving health and wellbeing in this population. Despite few restrictions being applied to our search, only six studies were found which met our inclusion criteria. This is not indicative of research into ACIs in this population, as evidenced by the identification of ninety-three studies where arts and creativity interventions were found to support better health and wellbeing outcomes in another recent review [ 5 ]. An alternative explanation is that funders do not see the added value of undertaking such evaluations in this area. That is, for funders, the cost of evaluating an ACIs is likely to be deemed unjustified given the relatively small welfare loss a misallocation of resources to them might produce. While at first glance this may seem reasonable, it disadvantages ACIs in competing with other interventions for funding and arguably exposes an implicit prejudice in the treatment of interventions from which it may be difficult to extract profit in general. That is, the paucity of evidence, may reflect inherent biases within our political economy that favour the generation of marketable solutions to health issues from which value can be appropriated as profit. Pharmaceuticals are an obvious example of such solutions, where the literature is replete with examples of evaluations sponsored by pharmaceutical companies or where public funds are used to test the claims made by pharmaceutical companies in respect of the value of their products. If the potential of ACIs to improve health and well-being is to be robustly established, ACIs must effectively compete for funding with other interventions including those from pharma. This requires a larger, more robust evidence base than is currently available and investment in the creation of such an evidence base. As there is currently no ‘for-profit’ industry to generate such an evidence base, public funding of evaluations will be central to its creation.

Our second finding concerns the values reported in the meagre evidence we did find. In five of the six studies we identified, evidence indicated that ACIs targeted at older people offered value for money [ 62 , 65 , 66 , 67 , 68 ]. One study provided mixed evidence [ 63 ], however, in this study a ‘payer’ perspective was adopted when applying an HTA framework which, by virtue of the perspective adopted, excluded a range of benefits attributable to ACIs and public health interventions more generally. Among the four studies that adopted a SROI approach, estimated returns per £1 invested ranged from £1.20 to £8.27. Given the evident heterogeneity among studies in terms of context and methods, care is warranted in comparing estimates with each other or with other SROIs. Care is also required in accepting at face value the estimates reported given methodological issues that pertain to the current state of the art with respect to SROI. With these caveats in mind noted, the values reported for ACIs using the SROI approach are comparable with those from other SROI studies in other contexts including those as diverse as a first aid intervention [ 71 ], investment in urban greenways [ 72 ] and the provision of refuge services to those experiencing domestic violence [ 73 ] (a return on investment of £3.50-£4, £2.88-£5.81 and £4.94 respectively). Similarly, with respect to the study that adopted a cost-effectiveness approach, Coulton and colleagues (2015) reported a 64% probability of the intervention being cost-effective at a threshold of £30,000 [ 62 ]. Again, it is difficult to compare studies directly, but this is similar to that reported for interventions as diverse as a falls prevention initiative [ 74 ] and the treatment of depression using a collaborative approach [ 75 ] both in the UK. That the evidence base is meagre notwithstanding, there is, in other words, a prima facie case that ACIs are capable of offering value for money when targeted at older persons.

Our third finding relates to the state of the art with respect to SROIs in this area. Over the past 40 years, considerable time, effort and resources have been expended in the development of cost-effectiveness techniques in health and social care. While considerable heterogeneity can exist around their conduct, national guidance exists in many jurisdictions on the conduct of cost-effectiveness analyses (CEA) – such as the NICE reference case in the UK [ 76 ]– as well as in the reporting of these as set out in the CHEERS 2022 guidance [ 64 ]. This has helped raise the quality of published evaluations and the consistency with which they are reported. Despite the existence of a step-by-step guidance document on how to perform SROIs [ 77 ] which outlines how displacement effects, double counting, effect attribution and drop-off should be addressed, a significant body of work still remains to ensure that the methodology addresses a range of known biases in a robust manner. Where there is no comparator to the intervention being evaluated (as was the case in the SROIs reported here) it may be difficult to convince funders that the implicit incremental costs and benefits reported are indeed incremental and attributable to the intervention. Equally, where a comparator is present, greater consensus and standardisation is required regarding the identification, generation and application of, for example, financial proxies. Currently, SROI ratios combine value across a wide range of stakeholders, which is understandable if the objective is to capture all aspects of social benefit generated. This ratio, however, may not reflect the priorities and statutory responsibilities of healthcare funders. Whist all of the aforementioned issues can be addressed, investment is required to develop the SROI methodology further to more closely meet the needs of commissioning bodies.

Notwithstanding these challenges, social value analyses play a pivotal role within the procurement processes employed by government, local authorities and other non-departmental public bodies and should not be dismissed simply because the ‘burden of proof’ falls short of that required to secure remuneration within the health sector. As most SROIs are published in the grey literature, this means they often avoid peer scrutiny prior to publication and the potential quality assurance this can offer. It is noteworthy however that two of the SROIs included in this review [ 65 , 66 ] were published in the academic literature, suggesting that the academic community are engaging with this method which is to be applauded.

Moving forward, it is unlikely we will be able to meet all of the health and wellbeing needs of our ageing population solely in a primary or secondary care setting. New models of care are required, as are new models of funding to support interventions which can be delivered in non-healthcare settings. New hybrid models of evaluation will be required to provide robust economic evidence to assist in the allocation of scarce resources across health and non-healthcare settings; such evaluative frameworks must have robust theoretical underpinnings and be capable of delivering evidence from a non-clinical setting in a timely and cost-effective manner.

In the absence of a definitive evaluation framework for ACIs being currently available, we have a number of recommendations. First, and most importantly, all impact assessments should have a control group or credible counterfactual. This is currently not required when performing an SROI making it difficult to determine if all of the benefits ascribed to an intervention are in fact attributable. This recommendation is in line with the conclusion of a report by the London School of Economics [ 78 ] for the National Audit Office (NAO) which concluded that ‘any impact evaluation (and subsequent value for money calculation) requires construction of a counterfactual’. Second, a detailed technical appendix should accompany all impact assessments to allow independent review by a subject specialist. While this would assist peer review, it would allow providing greater transparency where peer review was not undertaken prior to publication. Furthermore, it would enable recalculation of SROI ratios to exclude ‘value’ attributable to stakeholders which are not relevant to a particular funder. Third, equity considerations should be addressed explicitly in all evaluations (this is currently not required in HTAs). Fourth, both costs and outcomes should be captured from a ‘broad’ perspective (adopting a ‘narrow’ healthcare perspective may underestimate the full economic impact), with non-healthcare sector costs being detailed as part of the analysis. Finally, data should be collected post-implementation to ensure that resources continue to be allocated efficiently.

As with any review, there are limitations which should be noted. A search of the grey literature was included as evaluations of applied public health interventions are not always reported in the academic literature. Systematically identifying grey literature and grey data can be problematic [ 79 , 80 , 81 , 82 , 83 ] as it is not collected, organised or stored in a consistent manner. Hence it is possible that we have not identified all relevant studies. Furthermore, as applied public health interventions can be performed in a non-healthcare setting we included SROIs in our review of economic evaluations. Current guidance on the systematic review of economic evaluations has been developed primarily for review of HTA as opposed to public health interventions and hence SROIs would be excluded, or if included would score poorly due to the inherent biases arising from no comparator or counterfactual being included.

This systematic review found that participation in group-based arts and creativity programmes was generally cost-effective and/or produced a positive return on investment whilst having a positive impact on older people’s physical, psychological, and social health and wellbeing outcomes. Unfortunately, the small number of studies identified, coupled with differences in methods used to assess economic impact hinders our ability to conclusively determine which types of art and creativity-based activities are more cost-effective or represent best value for money.

As well as the need for a greater focus on prevention of poor health as we age, new hybrid models of healthcare delivery are necessary to meet the needs of our ageing population. These models will integrate traditional medical care with other services such as home health aides (some of which may include artificial intelligence), telemedicine and social support networks. Alongside these, ACIs have the potential to provide a low cost, scalable, easily implementable and cost-effective solution to reduce the burden of illness in this age group and support healthy ageing.

Evidence on the cost-effectiveness of a range of ACIs is of utmost importance for policy and decision makers as it can both inform the development of policies that support the provision of ACIs in the context of ageing, but also identify the most cost-effective approaches for delivering such interventions. The development of hybrid models of evaluation, capable of capturing cost-effectiveness and social value, is becoming increasingly necessary as healthcare delivery for this age group moves beyond the realms of primary and secondary care and into the community. The development and refinement of such models will ensure a more comprehensive assessment of the impact of a diverse range of interventions providing a more nuanced understanding of the impact of an intervention. This will help inform decision making and ensure interventions are implemented in a cost-effective and socially beneficial manner.

Availability of data and materials

All data generated or analysed during this study are included in the published article and its supplementary information files.

United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects: The 2015 Revision, Key Findings and Advance Tables. Working Paper No. ESA/P/WP.241. 2015.

Office for National Statistics. Living longer: how our population is changing and why it matters. . 2018. Accessed 07/12/2022

Dyakova M, Hamelmann C, Bellis MA, Besnier E, Grey CNB, Ashton K, Schwappach A, Clar C. Investment for health and well-being: a review of the social return on investment from public health policies to support implementing the Sustainable Development Goals by building on Health 2020 [Internet]. Copenhagen: WHO Regional Office for Europe; 2017.

Google Scholar  

Fancourt D, Finn S. What is the evidence on the role of the arts in improving health and well-being? A scoping review. Copenhagen: WHO Regional Office for Europe; 2019.

McQuade L, O’Sullivan R. Examining arts and creativity in later life and its impact on older people’s health and wellbeing: a systematic review of the evidence. Perspect Publ Health. 2023;0(0).

Skingley A, De’Ath S, Napleton L. Evaluation of Edna: arts and dance for older people. Work Older People. 2016;20(1):46–56.

Article   Google Scholar  

Brustio PR, Liubicich ME, Chiabrero M, et al. Dancing in the golden age: a study on physical function, quality of life, and social engagement. Geriatr Nurs. 2018;39(6):635–9.

Article   PubMed   Google Scholar  

Beauchet O, Bastien T, Mittelman M, et al. Participatory art-based activity, community-dwelling older adults and changes in health condition: results from a pre-post intervention, single-arm, prospective and longitudinal study. Maturitas. 2020;134:8–14.

Article   CAS   PubMed   Google Scholar  

Roswiyani R, Hiew CH, Witteman CLM, et al. Art activities and qigong exercise for the well-being of older adults in nursing homes in Indonesia: a randomized controlled trial. Aging Ment Health. 2020;24(10):1569–78.

Shanahan J, Bhriain ON, Morris ME, et al. Irish set dancing classes for people with Parkinson’s disease: the needs of participants and dance teachers. Complement Ther Med. 2016;27:12–7.

Garcia Gouvêa JA, Antunes MD, Bortolozzi F, et al. Impact of senior dance on emotional and motor parameters and quality of life of the elderly. Rev Rene. 2017;18(1):51–8.

Sun J, Zhang N, Buys N, et al. The role of Tai Chi, cultural dancing, playing a musical instrument and singing in the prevention of chronic disease in Chinese older adults: a mind–body meditative approach. Int J Ment Health Pr. 2013;15:227–39.

Fu MC, Belza B, Nguyen H, et al. Impact of group-singing on older adult health in senior living communities: a pilot study. Arch Gerontol Geriatr. 2018;76:138–46.

Feng L, Romero-Garcia R, Suckling J, et al. Effects of choral singing versus health education on cognitive decline and aging: a randomized controlled trial. Aging-us. 2020;12(24):24798–816.

Seinfeld S, Figueroa H, Ortiz-Gil J, et al. Effects of music learning and piano practice on cognitive function, mood and quality of life in older adults. Front Psychol. 2013;4:810.

Article   PubMed   PubMed Central   Google Scholar  

MacRitchie J, Breaden M, Milne AJ, et al. Cognitive, motor and social factors of music instrument training programs for older adults’ improved wellbeing. Front Psychol. 2020;10:2868.

Freeman WJI. A neurobiological role of music in social bonding. In: Wallin N, Merkur B, Brown S, editors. The origins of music. Cambridge: MIT Press; 2000. .

Huron D. Is music an evolutionary adaptation? Ann N Y Acad Sci. 2001;930(1):43–61. .

Tarr B, Launay J, Dunbar RIM. Music and social bonding: “self–other” merging and neurohormonal mechanisms. Front Psychol. 2014;5:1096. .

Cain M, Lakhani A, Istvandity L. Short and long term outcomes for culturally and linguistically diverse (cald) and at-risk communities in participatory music programs: a systematic review. Arts Health. 2016;8(2):105–24. .

Martin L, Oepen R, Bauer K, Nottensteiner A, Mergheim K, Gruber H, et al. Creative arts interventions for stress management and prevention – a systematic review. Behav Sci (Basel). 2018;8(2):pii:E28. .

Linnemann A, Wenzel M, Grammes J, Kubiak T, Nater UM. Music listening and stress in daily life: a matter of timing. Int J Behav Med. 2018;25(2):223–30. .

Linnemann A, Strahler J, Nater UM. The stress-reducing effect of music listening varies depending on the social context. Psychoneuroendocrinology. 2016;72:97–105. .

Panteleeva Y, Ceschi G, Glowinski D, Courvoisier DS, Grandjean DM. Music for anxiety? meta-analysis of anxiety reduction in non-clinical samples. Psychol Music. 2017;46(4):473–87. .

Fancourt D, Tymoszuk U. Cultural engagement and incident depression in older adults: evidence from the English longitudinal study of ageing. Br J Psychiatry. 2018;214(4):225–9. .

Balbag MA, Pedersen NL, Gatz M. Playing a musical instrument as a protective factor against dementia and cognitive impairment: a population-based twin study. Int J Alzheimer’s Dis. 2014;2014:836748. .

Porat S, Goukasian N, Hwang KS, Zanto T, Do T, Pierce J, et al. Dance experience and associations with cortical gray matter thickness in the aging population. Dement Geriatr Cogn Dis Extra. 2016;6(3):508–17. .

Federici A, Bellagamba S, Rocchi MBL. Does dance-based training improve balance in adult and young old subjects? a pilot randomized controlled trial. Aging Clin Exp Res. 2005;17(5):385–9 PMID: 16392413.

Alpert PT, Miller SK, Wallmann H, Havey R, Cross C, Chevalia T, et al. The effect of modified jazz dance on balance, cognition, and mood in older adults. J Am Acad Nurse Pract. 2009;21(2):108–15. .

Jeon MY, Bark ES, Lee EG, Im JS, Jeong BS, Choe ES. The effects of a Korean traditional dance movement program in elderly women. Taehan Kanho Hakhoe Chi. 2005;35(7):126876 (in Korean). PMID: 16418553.

Eyigor S, Karapolat H, Durmaz B, Ibisoglu U, Cakir S. A randomized controlled trial of Turkish folklore dance on the physical performance, balance, depression and quality of life in older women. Arch Gerontol Geriatr. 2009;48(1):84–8. .

Noopud P, Suputtitada A, Khongprasert S, Kanungsukkasem V. Effects of Thai traditional dance on balance performance in daily life among older women. Aging Clin Exp Res. 2018;31(7):961–7. .

Trombetti A, Hars M, Herrmann FR, Kressig RW, Ferrari S, Rizzoli R. Effect of musicbased multitask training on gait, balance, and fall risk in elderly people: a randomized controlled trial. Arch Intern Med. 2011;171(6):525–33. .

Hyyppä MT, Mäki J, Impivaara O, Aromaa A. Individual-level measures of social capital as predictors of all-cause and cardiovascular mortality: a population-based prospective study of men and women in Finland. Eur J Epidemiol. 2007;22(9):589–97. .

Hyyppä MT, Mäki J, Impivaara O, Aromaa A. Leisure participation predicts survival: a population-based study in Finland. Health Promot Int. 2006;21(1):5–12. .

Lennartsson C, Silverstein M. Does engagement with life enhance survival of elderly people in Sweden? the role of social and leisure activities. J Gerontol B Psychol Sci Soc Sci. 2001;56(6):S335–42. .

Sundquist K, Lindström M, Malmström M, Johansson SE, Sundquist J. Social participation and coronary heart disease: a follow-up study of 6900 women and men in Sweden. Soc Sci Med. 1982;58(3):615–22. .

Väänänen A, Murray M, Koskinen A, Vahtera J, Kouvonen A, Kivimäki M. Engagement in cultural activities and cause-specific mortality: prospective cohort study. Prev Med. 2009;49(2–3):142–7. .

Särkämö T, Soto D. Music listening after stroke: beneficial effects and potential neural mechanisms. Ann N Y Acad Sci. 2012;1252(1):266–81. .

Särkämö T, Pihko E, Laitinen S, Forsblom A, Soinila S, Mikkonen M, et al. Music and speech listening enhance the recovery of early sensory processing after stroke. J Cogn Neurosci. 2010;22(12):2716–27. .

Särkämö T, Ripollés P, Vepsäläinen H, Autti T, Silvenno HM, Salli E, et al. Structural changes induced by daily music listening in the recovering brain after middle cerebral artery stroke: a voxel-based morphometry study. Front Hum Neurosci. 2014;8:245. .

Särkämö T, Tervaniemi M, Laitinen S, Forsblom A, Soinila S, Mikkonen M, et al. Music listening enhances cognitive recovery and mood after middle cerebral artery stroke. Brain. 2008;131(3):866–76. .

Fancourt D, Steptoe A, Cadar D. Cultural engagement and cognitive reserve: museum attendance and dementia incidence over a 10-year period. Br J Psychiatry. 2018;213(5):661–3. .

Fancourt D, Steptoe A, Cadar D. Cultural engagement predicts changes in cognitive function in older adults over a 10 year period: findings from the English longitudinal study of ageing. Sci Rep. 2018;8(1):10226. .

All Party Parliamentary group on arts, health and wellbeing. Creative health: the arts for health and wellbeing. 2017.

van Mastrigt GA, Hiligsmann M, Arts JJ, Broos PH, Kleijnen J, Evers SM, Majoie MH. How to prepare a systematic review of economic evaluations for informing evidence-based healthcare decisions: a five-step approach (part 1/3). Expert Rev Pharmacoecon Outcomes Res. 2016;16(6):689–704. . Epub 2016 Nov 2 PMID: 27805469.

Thielen FW, Van Mastrigt G, Burgers LT, Bramer WM, Majoie H, Evers S, Kleijnen J. How to prepare a systematic review of economic evaluations for clinical practice guidelines: database selection and search strategy development (part 2/3). Expert Rev Pharmacoecon Outcomes Res. 2016;16(6):705–21. . Epub 2016 Nov 2 PMID: 27805466.

Wijnen B, Van Mastrigt G, Redekop WK, Majoie H, De Kinderen R, Evers S. How to prepare a systematic review of economic evaluations for informing evidence-based healthcare decisions: data extraction, risk of bias, and transferability (part 3/3). Expert Rev Pharmacoecon Outcomes Res. 2016;16(6):723–32. . Epub 2016 Oct 21 PMID: 27762640.

Mandrik OL, Severens JLH, Bardach A, Ghabri S, Hamel C, Mathes T, Vale L, Wisløff T, Goldhaber-Fiebert JD. Critical appraisal of systematic reviews with costs and cost-effectiveness outcomes: an ISPOR good practices task force report. Value Health. 2021;24(4):463–72. . PMID: 33840423.

Kelly MP, McDaid D, Ludbrook A, Powell J: Economic appraisal of public health interventions.

Weatherly H, Drummond M, Claxton K, Cookson R, Ferguson B, Godfrey C, Rice N, Sculpher M, Sowden A. Methods for assessing the cost-effectiveness of public health interventions: key challenges and recommendations. Health Policy. 2009;93(2–3):85–92. . Epub 2009 Aug 25 PMID: 19709773.

Payne K, McAllister M, Davies LM. Valuing the economic benefits of complex interventions: when maximising health is not sufficient. Health Econ. 2012. .

Edwards RT, Charles JM, Lloyd-Williams H. Public health economics: a systematic review of guidance for the economic evaluation of public health interventions and discussion of key methodological issues. BMC Public Health. 2013;24(13):1001.;PMCID:PMC4015185 .

Rethlefsen ML, Farrell AM, Osterhaus Trzasko LC, Brigham TJ. Librarian co-authors correlated with higher quality reported search strategies in general internal medicine systematic reviews. J Clin Epidemiol. 2015;68(6):617–26. . Epub 2015 Feb 7 PMID: 25766056.

McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS peer review of electronic search strategies: 2015 guideline statement. J Clin Epidemiol. 2016;75:40–6. . Epub 2016 Mar 19 PMID: 27005575.

Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA Statement. PLoS Med. 2008;6:e1000097. .

Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, Clarke M, Devereaux PJ, Kleijnen J, Moher D. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009;21(339):b2700.;PMCID:PMC2714672 .

Moher D, Liberati A, Tetzlaff J, Altman DG. PRISMA Group. PLoS Med. 2009;6(7):e1000097 Evers S, Goossens M, De Vet H, et al. Criteria list for assessment of methodological quality of economic evaluations: consensus on health economic criteria. Int J Technol Assess Health Care. 2005;21(02):240–245.

Evers S, Goossens M, de Vet H, van Tulder M, Ament A. Criteria list for assessment of methodological quality of economic evaluations: Consensus on Health Economic Criteria. Int J Technol Assess Health Care. 2005;21(2):240–5 PMID: 15921065.

Hutchinson CL, Berndt A, Gilbert-Hunt S, George S, Ratcliffe J. Valuing the impact of health and social care programmes using social return on investment analysis: how have academics advanced the methodology? A protocol for a systematic review of peer-reviewed literature. BMJ Open. 2018;8(12):e022534. . PMID:30530579;PMCID:PMC6303612.

Higgins J, Green S. Cochrane handbook for systematic reviews of interventions version 5.1. 0. Chichester: The Cochrane Collaboration; 2013.

Coulton S, Clift S, Skingley A, Rodriguez J. Effectiveness and cost-effectiveness of community singing on mental health-related quality of life of older people: randomised controlled trial. Br J Psychiatry. 2015;207(3):250–5. . Epub 2015 Jun 18 PMID: 26089304.

Johnson JK, Stewart AL, Acree M, Nápoles AM, Flatt JD, Max WB, Gregorich SE. A community choir intervention to promote well-being among diverse older adults: results from the community of voices trial. J Gerontol B Psychol Sci Soc Sci. 2020;75(3):549–59. . PMID:30412233;PMCID:PMC7328053.

Husereau D, Drummond M, Augustovski F, de Bekker-Grob E, Briggs AH, Carswell C, Caulley L, Chaiyakunapruk N, Greenberg D, Loder E, Mauskopf J, Mullins CD, Petrou S, Pwu RF, Staniszewska S, CHEERS 2022 ISPOR Good Research Practices Task Force. Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations. Value Health. 2022;25(1):3–9. . PMID: 35031096.

Bosco A, Schneider J, Broome E. The social value of the arts for care home residents in England: a social return on investment (SROI) analysis of the imagine arts programme. Maturitas. 2019;124:15–24. . Epub 2019 Mar 13 PMID: 31097173.

Jones C, Windle G, Edwards RT. Dementia and imagination: a social return on investment analysis framework for art activities for people living with dementia. Gerontologist. 2020;60(1):112–23. . PMID: 30476114.

Social Value Lab and Impact Arts Craft Café: creative solutions to isolation and loneliness; Social return on investment. 2011.

MB associates. Make my day: the impact of Creative Caring in older people’s care homes. 2013.

HACT. n.d. UK Social Value Bank. Retrieved December 11, 2023. from .

The Older Adults’ NHS and social care return on investment tool. Project report. Public health England. December 2019. Last accessed 27/03/2023.

British Red Cross – Valuing First Aid Education. 2018. . Accessed 17/02/2023

Hunter R, Dallat M, Tully M, O’Neill C, Heron L, Kee F. Social return on investment analysis of an urban greenway. Cities and Health. 2020. .

NEF Consulting. Refuge: A social return on investment evaluation. 2016. Accessed 17/02/2022

Corbacho B, Cockayne S, Fairhurst C, Hewitt CE, Hicks K, Kenan AM, Lamb SE, MacIntosh C, Menz HB, Redmond AC, Rodgers S, Scantlebury A, Watson J, Torgerson DJ, on behalf of the REFORM study. Cost-Effectiveness of a Multifaceted Podiatry Intervention for the Prevention of Falls in Older People: The REducing Falls with Orthoses and a Multifaceted Podiatry Intervention Trial Findings. Gerontology. 2018;64(5):503–12. . Epub 2018 Jun 26 PMID: 29945150.

Green C, Richards DA, Hill JJ, Gask L, Lovell K, Chew-Graham C, Bower P, Cape J, Pilling S, Araya R, Kessler D, Bland JM, Gilbody S, Lewis G, Manning C, Hughes-Morley A, Barkham M. Cost-effectiveness of collaborative care for depression in UK primary care: economic evaluation of a randomised controlled trial (CADET). PLoS ONE. 2014;9(8):e104225.;PMCID:PMC4133193 .

National Institute for Health and Care Excellence (NICE). NICE health technology evaluations: the manual. 2022. Retrieved 27 March, 2023 from

NEF Consulting. SSE – Beatrice SROI framework – guidance document. . Accessed 17/02/2022

Gibbons S, McNally S, Overman H. Review of Government Evaluations: A report for the NAO. London: National Audit Office; 2013.

Turner AM, Liddy ED, Bradley J, Wheatley JA. Modeling public health interventions for improved access to the gray literature. J Med Libr Assoc. 2005;93(4):487–94 PMID: 16239945; PMCID: PMC1250325.

PubMed   PubMed Central   Google Scholar  

Benzies KM, Premji S, Hayden KA, Serrett K. State-of-the-evidence reviews: advantages and challenges of including grey literature. Worldviews Evid Based Nurs. 2006;3(2):55–61. . PMID: 17040510.

Franks H, Hardiker NR, McGrath M, McQuarrie C. Public health interventions and behaviour change: reviewing the grey literature. Public Health. 2012;126(1):12–7. . Epub 2011 Nov 29 PMID: 22130477.

Mahood Q, Van Eerd D, Irvin E. Searching for grey literature for systematic reviews: challenges and benefits. Res Synth Methods. 2014;5(3):221–34. . Epub 2013 Dec 6 PMID: 26052848.

Godin K, Stapleton J, Kirkpatrick SI, Hanning RM, Leatherdale ST. Applying systematic review search methods to the grey literature: a case study examining guidelines for school-based breakfast programs in Canada. Syst Rev. 2015;22(4):138. . PMID:26494010;PMCID:PMC4619264.

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We would like to thank Ms. Louise Bradley (Information Resource Officer, Institute of Public Health) for her assistance in refining search strategies and literature search.

This study was supported by the Institute of Public Health (IPH), 200 South Circular Road, Dublin 8, Ireland, D08 NH90. This study was a collaboration between two health economists (GC, CO’N) and two members of staff from the funding organisation (LM, RO’S). Input from IPH staff was fundamental in defining the scope of work and research question, refining search terms and review and editing of the manuscript. Staff from IPH were not involved in quality assurance or review of papers included in the manuscript.

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Grainne Crealey

Institute of Public Health, 200 South Circular Road, Dublin 8, D08 NH90, Ireland

Laura McQuade & Roger O’Sullivan

Centre for Public Health, Institute of Clinical Sciences, Royal Victoria Hospital, Belfast, BT12 6BA, UK

Ciaran O’Neill

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LMcQ and ROS were involved in defining the scope of work, refining the research question, provision of subject specific (public health) context, review of search strategy, review & editing of manuscript. CON and GC were involved in refining the research question and search strategy, provision of health economics and systematic reviewing expertise, review of returned reports, original draft preparation, review, editing and submission of manuscript. All authors read and approved the final manuscript.

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Additional file 1.

: Table S1. Search strategy for electronic databases and grey literature.

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Crealey, G., McQuade, L., O’Sullivan, R. et al. Arts and creativity interventions for improving health and wellbeing in older adults: a systematic literature review of economic evaluation studies. BMC Public Health 23 , 2496 (2023).

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BMC Public Health

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literature review on information technology


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