Case Study of Successful Utilization of Digital Technology Innovations Determinants of Cooperative Institutions in Bali: The Impact of the Covid-19 Pandemic

Surya Dewi Rustariyuni

Abstract


The Covid-19 pandemic has caused serious problems for all sectors and financial institutions, including cooperatives. One solution for cooperative institutions is to innovate digital technology to overcome social distancing. Cooperatives that can maintain their performance during the Covid-19 pandemic are those that can innovate technology. In this study, a qualitative descriptive method was used to determine the factors that influence the successful use of digital technology innovations by cooperatives in Bali due to the Covid-19 pandemic. The key informants in this study were the chairman of the board and cooperative management who applied digital technology innovation during the Covid-19 pandemic and triangulation was used for data analysis purposes. We found that top management commitment and support, perceived costs, security concerns, compatible technology facilities, perceived benefits, performance expectations and business prospects were critical to the successful use of digital technology innovations by cooperatives in Bali during the Covid-19 pandemic.


Keywords


Top management commitment and support, technology facilities, digital technology innovation, cost perception, security issues, Covid-19 pandemic

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References


Abed, S. S. (2020). Social Commerce Adoption Using TOE Framework: An Empirical Investigation of Saudi Arabian SMEs. International Journal of Information Management, 53(March), 102118. https://doi.org/10.1016/j.ijinfomgt.2020.102118

Abushanab, E., Michael Pearson, J., & Setterstrom, A. J. (2010). Internet Banking and Customers’ Acceptance in Jordan: The Unified Model’s Perspective. Communications of the Association for Information Systems, 26(1), 493–524. https://doi.org/10.17705/1cais.02623

Addy, M., Adinyira, E., & Ayarkwa, J. (2018). Antecedents of Building Information Modelling Adoption Among Quantity Surveyors in Ghana: An Application of A Technology Acceptance Model. Journal of Engineering, Design and Technology, 16(2), 313–326. https://doi.org/10.1108/JEDT-06-2017-0056

Ahmadi, H., Nilashi, M., & Ibrahim, O. (2015). Organizational decision to adopt hospital information system: An empirical investigation in the case of Malaysian public hospitals. International Journal of Medical Informatics, 84(3), 166–188.

https://doi.org/10.1016/j.ijmedinf.2014.12.004

Ahmadi, H., Nilashi, M., Shahmoradi, L., & Ibrahim, O. (2017). Hospital Information System adoption: Expert perspectives on an adoption framework for Malaysian public hospitals. Computers in Human Behavior, 67, 161–189. https://doi.org/10.1016/j.chb.2016.10.023

Ahmadi, H., Nilashi, M., Shahmoradi, L., Ibrahim, O., Sadoughi, F., Alizadeh, M., & Alizadeh, A. (2018). The moderating effect of hospital size on inter and intra-organizational factors of Hospital Information System adoption. Technological Forecasting and Social Change, 134(May), 124–149. https://doi.org/10.1016/j.techfore.2018.05.021

Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Algharabat, R. (2018). Examining factors influencing Jordanian customers’ intentions and adoption of internet banking: Extending UTAUT2 with risk. Journal of Retailing and Consumer Services, 40(August 2017), 125–138. https://doi.org/10.1016/j.jretconser.2017.08.026

Alamanda, D. T., Wibowo, L. A., Munawar, S., & Nisa, A. K. (2021). The Interest of Technology Adoption in E-Commerce Mobile Apps Using Modified Unified Theory of Acceptance and Use of Technology 2 in Indonesia. International Journal of Applied Business and International Management, 6(3), 35–45. https://doi.org/10.32535/ijabim.v6i3.1327

Alharbi, I. M., Zyngier, S., & Hodkinson, C. (2013). Privacy by design and customers’ perceived privacy and security concerns in the success of e-commerce. Journal of Enterprise Information Management, 26(6), 702–718. https://doi.org/10.1108/JEIM-07-2013-0039

Ali, O., Shrestha, A., Osmanaj, V., & Muhammed, S. (2021). Cloud Computing Technology Adoption: An Evaluation of Key Factors in Local Governments. Information Technology and People, 34(2), 666–703. https://doi.org/10.1108/ITP-03-2019-0119

Alkhater, N., Walters, R., & Wills, G. (2018). An Empirical Study of Factors Influencing Cloud Adoption Among Private Sector Organisations. Telematics and Informatics, 35(1), 38–54. https://doi.org/10.1016/j.tele.2017.09.017

Alwahaishi, S., & Snášel, V. (2013). Consumers’ acceptance and use of information and communications technology: A UTAUT and flow based theoretical model. Journal of Technology Management and Innovation, 8(2), 61–73. https://doi.org/10.4067/s0718-27242013000200005

Ammar, A., & Ahmed, E. M. (2016). Factors influencing Sudanese microfinance intention to adopt mobile banking. Cogent Business & Management, 5(1), 1–20. https://doi.org/10.1080/23311975.2016.1154257

Aryani, N. K. Y., Sapta, I. K. S., & Sujana, I. W. (2021). The Influence of Organizational Culture and Competence on Employee Performance Mediated by Organizational Commitments in the Procurement of Goods and Services Secretariat Regency of Karangasem. Asia Pacific Journal of Management and Education, 4(3), 76–86. https://doi.org/10.32535/apjme.v4i3.1270

Asiaei, A., & Nor, N. Z. (2019). A Multifaceted Framework for Adoption of Cloud Computing in Malaysian SMEs. Journal of Science and Technology Policy Management, 10(3), 708–750. https://doi.org/10.1108/JSTPM-05-2018-0053

Awa, H. O., Ojiabo, O. U., & Orokor, L. E. (2017). Integrated Technology-Organization-Environment (T-O-E) Taxonomies for Technology Adoption. Journal of Enterprise Information Management, 30(6), 893–921. https://doi.org/10.1108/JEIM-03-2016-0079

Awa, H. O., Ukoha, O., & Igwe, S. R. (2017). Revisiting Technology-Organization-Environment (T-O-E) Theory for Enriched Applicability. Bottom Line, 30(1), 2–22. https://doi.org/10.1108/BL-12-2016-0044

Ayaz, A., & Yanartaş, M. (2020). An analysis on the unified theory of acceptance and use of technology theory (UTAUT): Acceptance of electronic document management system (EDMS). Computers in Human Behavior Reports, 2(September), 100032. https://doi.org/10.1016/j.chbr.2020.100032

Baabdullah, A. M., Alalwan, A. A., Rana, N. P., Kizgin, H., & Patil, P. (2019). Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model. International Journal of Information Management, 44(July 2018), 38–52. https://doi.org/10.1016/j.ijinfomgt.2018.09.002

Barrutia, J. M., & Echebarria, C. (2021). Effect of the COVID-19 pandemic on public managers’ attitudes toward digital transformation. Technology in Society, 67, 101776. https://doi.org/10.1016/j.techsoc.2021.101776

Beraha, I., & Đuričin, S. (2020). The impact of COVID-19 crisis on medium-sized enterprises in Serbia. Economic Analysis, 53(1), 14–27. https://doi.org/10.28934/ea.20.53.1.pp14-27

Bhatiasevi, V. (2016). An extended UTAUT model to explain the adoption of mobile banking. Information Development, 32(4), 799–814. https://doi.org/10.1177/0266666915570764

Bose, R., & Luo, X. (2011). Integrative Framework for Assessing Firms’ Potential to Undertake Green IT Initiatives Via Virtualization - A Theoretical Perspective. Journal of Strategic Information Systems, 20(1), 38–54. https://doi.org/10.1016/j.jsis.2011.01.003

Cao, Q., & Niu, X. (2019). Integrating context-awareness and UTAUT to explain Alipay user adoption. International Journal of Industrial Ergonomics, 69(October 2017), 9–13. https://doi.org/10.1016/j.ergon.2018.09.004

Carreiro, H., & Oliveira, T. (2019). Impact of transformational leadership on the diffusion of innovation in firms: Application to mobile cloud computing. Computers in Industry, 107, 104–113. https://doi.org/10.1016/j.compind.2019.02.006

Chan, F. T. S., Chong, A. Y., & Zhou, L. (2012). An Empirical Investigation of Factors Affecting e-collaboration Diffusion in SMEs. International Journal of Production Economics, 138(2), 329–344. https://doi.org/10.1016/j.ijpe.2012.04.004

Chong, A. Y. L. (2013). A two-staged SEM-neural network approach for understanding and predicting the determinants of m-commerce adoption. Expert Systems with Applications, 40(4), 1240–1247. https://doi.org/10.1016/j.eswa.2012.08.067

de Albuquerque, J. P., Diniz, E. H., & Cernev, A. K. (2014). Mobile payments: a scoping study of the literature and issues for future research. Information Development, 32(3), 527–553. https://doi.org/10.1177/0266666914557338

depkop.go.id. (2020). Menkopukm : Transformasi Digital Koperasi Harus Dipercepat. Humas Kementerian Koperasi Dan UKM. http://www.depkop.go.id/read/menkopukm-transformasi-digital-koperasi-harus-dipercepat

Dinas Koperasi Usaha Kecil dan Menengah Provinsi Bali. (2021). Rekapitulasi Data Koperasi Per Desember 2021. https://diskopukm.baliprov.go.id/data-dan-informasi/data-koperasi/

Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J. S., Gupta, B., Lal, B., Misra, S., Prashant, P., Raman, R., Rana, N. P., Sharma, S. K., & Upadhyay, N. (2020). Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life. International Journal of Information Management, 55(July), 102211. https://doi.org/10.1016/j.ijinfomgt.2020.102211

Farah, M. F., Hasni, M. J. S., & Abbas, A. K. (2018). Mobile-banking adoption: empirical evidence from the banking sector in Pakistan. International Journal of Bank Marketing, 36(7), 1386–1413. https://doi.org/10.1108/IJBM-10-2017-0215

Fernandez, J. (2020). Pandemi CoViD-19 dan Perubahan Sosial Ekonomi: Anggaran Bencana dan Pasca Bencana. Infoanggaran.Com. https://infoanggaran.com/detail/--pandemi-covid19-dan-perubahan-sosial-ekonomi-anggaran-bencana-dan-pasca-bencana

Ferri, L., Spanò, R., Ginesti, G., & Theodosopoulos, G. (2020). Ascertaining Auditors’ Intentions to Use Blockchain Technology: Evidence from The Big 4 Accountancy Firms in Italy. Meditari Accountancy Research. https://doi.org/10.1108/MEDAR-03-2020-0829

Ford, G. S. (2018). Is faster better? Quantifying the relationship between broadband speed and economic growth. Telecommunications Policy, 42(9), 766–777. https://doi.org/10.1016/j.telpol.2018.05.006

Fuentelsaz, L., Gómez, J., & Palomas, S. (2012). Production technologies and financial performance: The effect of uneven diffusion among competitors. Research Policy, 41(2), 401–413. https://doi.org/10.1016/j.respol.2011.09.006

Gangwar, H., Date, H., & Ramaswamy, R. (2015). Understanding Determinants of Cloud Computing Adoption Using an Integrated TAM-TOE Model. Journal of Enterprise Information Management, 28(1), 107–130. https://doi.org/10.1108/JEIM-08-2013-0065

Ghobakhloo, M., Arias-Aranda, D., & Benitez-Amado, J. (2011). Adoption of e-commerce applications in SMEs. In Industrial Management and Data Systems (Vol. 111, Issue 8). https://doi.org/10.1108/02635571111170785

Ghobakhloo, M., & Ching, N. T. (2019). Adoption of digital technologies of smart manufacturing in SMEs. Journal of Industrial Information Integration, 16(January), 100107. https://doi.org/10.1016/j.jii.2019.100107

Goodell, J. W. (2020). COVID-19 and Finance: Agendas for Future Research. Finance Research Letters, 35(April). https://doi.org/10.1016/j.frl.2020.101512

Gupta, K. P., Manrai, R., & Goel, U. (2019). Factors influencing adoption of payments banks by Indian customers: extending UTAUT with perceived credibility. Journal of Asia Business Studies, 13(2), 173–195. https://doi.org/10.1108/JABS-07-2017-0111

Gupta, P., Seetharaman, A., & Raj, J. R. (2013). The usage and adoption of cloud computing by small and medium businesses. International Journal of Information Management, 33(5), 861–874. https://doi.org/10.1016/j.ijinfomgt.2013.07.001

Gutierrez, A., Boukrami, E., & Lumsden, R. (2015). Technological, organisational and environmental factors influencing managers’ decision to adopt cloud computing in the UK. Journal of Enterprise Information Management, 28(6), 788–807. https://doi.org/10.1108/JEIM-01-2015-0001

Haneem, F., Kama, N., Taskin, N., Pauleen, D., & Abu Bakar, N. A. (2019). Determinants of master data management adoption by local government organizations: An empirical study. International Journal of Information Management, 45(November 2018), 25–43. https://doi.org/10.1016/j.ijinfomgt.2018.10.007

Hasbi, M. (2020). Impact of very high-speed broadband on company creation and entrepreneurship: Empirical Evidence. Telecommunications Policy, 44(3), 1–21. https://doi.org/10.1016/j.telpol.2019.101873

Hsiu-Fen Lin. (2014). Understanding The Determinants of Electronic Supply Chain Management System Adoption: Using The Technology-Organization-Environment Framework. Technological Forecasting and Social Change, 86, 80–92. https://doi.org/10.1016/j.techfore.2013.09.001

Hussain, Z. (2021). Paradigm of technological convergence and digital transformation: The challenges of CH sectors in the global COVID-19 pandemic and commencing resilience-based structure for the post-COVID-19 era. Digital Applications in Archaeology and Cultural Heritage, 21(March), e00182. https://doi.org/10.1016/j.daach.2021.e00182

Ilin, V., Ivetić, J., & Simić, D. (2017). Understanding the determinants of e-business adoption in ERP-enabled firms and non-ERP-enabled firms: A case study of the Western Balkan Peninsula. Technological Forecasting and Social Change, 125(August), 206–223. https://doi.org/10.1016/j.techfore.2017.07.025

Kamble, S. S., Gunasekaran, A., Kumar, V., Belhadi, A., & Foropon, C. (2021). A machine learning based approach for predicting blockchain adoption in supply Chain. Technological Forecasting and Social Change, 163(November 2020), 120465. https://doi.org/10.1016/j.techfore.2020.120465

KemenkopUKM. (2021). Perlu Peran Koperasi Atasi Aneka Permasalahan UMKM. Kemenkop.Go.Id.

Khalid, B., & Naumova, E. (2021). Digital transformation SCM in view of Covid-19 from Thailand SMEs perspective. In Global Challenges of Digital Transformation of Markets (pp. 49–66). Nova Science Publishers, Inc. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116780657&partnerID=40&md5=ba31fd0ae1e1f4171e6c6c7e95801880

Khayer, A., Jahan, N., Hossain, M. N., & Hossain, M. Y. (2021). The Adoption of Cloud Computing in Small and Medium Enterprises: A Developing Country Perspective. VINE Journal of Information and Knowledge Management Systems. https://doi.org/10.1108/VJIKMS-05-2019-0064

Kuciapski, M. (2017). A model of mobile technologies acceptance for knowledge transfer by employees. Journal of Knowledge Management, 21(5), 1053–1076. https://doi.org/10.1108/JKM-03-2016-0136

Kumar, D., Samalia, H. V., & Verma, P. (2017). Exploring suitability of cloud computing for small and medium-sized enterprises in India. Journal of Small Business and Enterprise Development, 24(4), 814–832. https://doi.org/10.1108/JSBED-01-2017-0002

Lancelot Miltgen, C., Popovič, A., & Oliveira, T. (2013). Determinants of end-user acceptance of biometrics: Integrating the “big 3” of technology acceptance with privacy context. Decision Support Systems, 56(1), 103–114. https://doi.org/10.1016/j.dss.2013.05.010

Larsson, S., & Gustavsson, S. (2020). Marketing Innovation for SMEs during COVID-19 Pandemic. Lulea University of Technology.

Le, A. T. P., Kunasekaran, P., Rasoolimanesh, S. M., AriRagavan, N., & Thomas, T. K. (2021). Investigating the determinants and process of destination management system (DMS) implementation. Journal of Organizational Change Management. https://doi.org/10.1108/JOCM-11-2020-0352

Lee, S. M., & Trimi, S. (2021). Convergence innovation in the digital age and in the COVID-19 pandemic crisis. Journal of Business Research, 123(September 2020), 14–22. https://doi.org/10.1016/j.jbusres.2020.09.041

Lian, J. W., Yen, D. C., & Wang, Y. T. (2014). An exploratory study to understand the critical factors affecting the decision to adopt cloud computing in Taiwan hospital. International Journal of Information Management, 34(1), 28–36. https://doi.org/10.1016/j.ijinfomgt.2013.09.004

Low, C., Chen, Y., & Wu, M. (2011). Understanding the determinants of cloud computing adoption. Industrial Management and Data Systems, 111(7), 1006–1023. https://doi.org/10.1108/02635571111161262

Ma, D., Tina Du, J., Cen, Y., & Wu, P. (2016). Exploring the adoption of mobile internet services by socioeconomically disadvantaged people: A qualitative user study. Aslib Journal of Information Management, 68(6), 670–693. https://doi.org/10.1108/AJIM-03-2016-0027

Maduku, D. K., Mpinganjira, M., & Duh, H. (2016). Understanding mobile marketing adoption intention by South African SMEs: A multi-perspective framework. International Journal of Information Management, 36(5), 711–723. https://doi.org/10.1016/j.ijinfomgt.2016.04.018

Malik, K., Ogden, T., Meki, M., Morduch, J., & Quinn, S. (2020). COVID-19 and the Future of Microfinance : Evidence and Insights from Pakistan. Oxford Review of Economic Policy 36.Supplement_1, 138–168.

Maroufkhani, P., Tseng, M., & Iranmanesh, M. (2020). Big data analytics adoption: Determinants and performances among small to medium-sized enterprises. International Journal of Information Management, 54(February), 102190. https://doi.org/10.1016/j.ijinfomgt.2020.102190

Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1–13. https://doi.org/10.1016/j.ijinfomgt.2013.06.002

Martins, R., Oliveira, T., & Thomas, M. A. (2016). An Empirical Analysis to Assess The Determinants of SaaS Diffusion in Firms. Computers in Human Behavior, 62, 19–33. https://doi.org/10.1016/j.chb.2016.03.049

Merhi, M., Hone, K., & Tarhini, A. (2019). A cross-cultural study of the intention to use mobile banking between Lebanese and British consumers: Extending UTAUT2 with security , privacy and trust. Technology in Society, 59(June), 101–151. https://doi.org/10.1016/j.techsoc.2019.101151

Oliveira, T., Faria, M., & Abraham, M. (2014). Extending the understanding of mobile banking adoption : When UTAUT meets TTF and ITM. International Journal of Information Management, 34, 689–703. https://doi.org/10.1016/j.ijinfomgt.2014.06.004

Oliveira, T., & Martins, M. F. (2010). Understanding e-business adoption across industries in European countries. Industrial Management and Data Systems, 110(9), 1337–1354. https://doi.org/10.1108/02635571011087428

Oliveira, T., Thomas, M., & Espadanal, M. (2014). Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information and Management, 51(5), 497–510. https://doi.org/10.1016/j.im.2014.03.006

Ooi, K. B., Lee, V. H., Tan, G. W. H., Hew, T. S., & Hew, J. J. (2018). Cloud computing in manufacturing: The next industrial revolution in Malaysia? Expert Systems with Applications, 93, 376–394. https://doi.org/10.1016/j.eswa.2017.10.009

Ooi, K., Lee, V., Tan, G. W., Hew, T., & Hew, J. (2018). Cloud Computing in Manufacturing : The Next Industrial Revolution in Malaysia ? Expert Systems With Applications, 93, 376–394. https://doi.org/10.1016/j.eswa.2017.10.009

Osakwe, C. N., Chovancová, M., & Agu, M. (2015). Can micro-enterprises leverage on the adoption of corporate websites to bolster their brand visibility? Examining salient adoption issues in Nigeria. Information Development, 32(4), 904–919. https://doi.org/10.1177/0266666915573551

Priyadarshinee, P., Raut, R. D., Jha, M. K., & Gardas, B. B. (2017). Understanding and predicting the determinants of cloud computing adoption: A two staged hybrid SEM - Neural networks approach. Computers in Human Behavior, 76, 341–362. https://doi.org/10.1016/j.chb.2017.07.027

Putri, A., Amran, A., Suparwo, A., Kurniawan, A., Rahayu, Y. S., & Suryana, S. (2021). The Importance of Perceived Organizational Support and Work From Home to increase Work-Life Balance During The Covid-19 Pandemic. Asia Pacific Journal of Management and Education, 4(3), 10–21. https://doi.org/10.32535/apjme.v4i3.1262

Rahi, S., & Abd.Ghani, M. (2019). Investigating the role of UTAUT and e-service quality in internet banking adoption setting. TQM Journal, 31(3), 491–506. https://doi.org/10.1108/TQM-02-2018-0018

Ramayah, T., Ling, N. S., Taghizadeh, S. K., & Rahman, S. A. (2016). Factors influencing SMEs website continuance intention in Malaysia. Telematics and Informatics, 33(1), 150–164. https://doi.org/10.1016/j.tele.2015.06.007

Ramdani, B., Chevers, D., & Williams, D. A. (2013). SMEs’ Adoption of Enterprise Applications: A Technology-Organisation-Environment Model. Journal of Small Business and Enterprise Development, 20(4), 735–753. https://doi.org/10.1108/JSBED-12-2011-0035

Reddick, C. G., Enriquez, R., Harris, R. J., & Sharma, B. (2020). Determinants of broadband access and affordability: An analysis of a community survey on the digital divide. Cities, 106(September), 102904. https://doi.org/10.1016/j.cities.2020.102904

Riffai, M. M. M. A., Grant, K., & Edgar, D. (2012). Big TAM in Oman: Exploring the promise of on-line banking, its adoption by customers and the challenges of banking in Oman. International Journal of Information Management, 32(3), 239–250. https://doi.org/10.1016/j.ijinfomgt.2011.11.007

Robinson, J., & Kengatharan, N. (2020). Exploring the effect of Covid-19 on Small and Medium Enterprises: Early Evidence from Sri Lanka. Journal of Applied Economics and Business Research, 10(2), 115–125. http://jafeb.org/journal/article.php?code=76216

Sabani, A. (2020). Investigating the influence of transparency on the adoption of e-Government in Indonesia. Journal of Science and Technology Policy Management. https://doi.org/10.1108/JSTPM-03-2020-0046

Safari, F., Safari, N., & Hasanzadeh, A. (2015). The Adoption of Software-as-a-Service (SaaS): Ranking The Determinants. Journal of Enterprise Information Management, 28(3), 400–422. https://doi.org/10.1108/JEIM-02-2014-0017

Satoto, S. H., & Putra, H. N. K. (2021). The Effect of Financial Literacy and other Determinants on the Intention to Use Electronic Money: Consumer Behavior as a Variable Mediation. International Journal of Applied Business and International Management, 6(3), 23–34. https://doi.org/10.32535/ijabim.v6i3.1326

Senyo, P. K., Effah, J., & Addae, E. (2016). Preliminary insight into cloud computing adoption in a developing country. Journal of Enterprise Information Management, 29(4), 505–524. https://doi.org/10.1108/JEIM-09-2014-0094

Singh, S., Sharma, M., & Dhir, S. (2021). Modeling the effects of digital transformation in Indian manufacturing industry. Technology in Society, 67(August), 101763. https://doi.org/10.1016/j.techsoc.2021.101763

Sivathanu, B. (2019). Adoption of industrial IoT (IIoT) in auto-component manufacturing SMEs in India. Information Resources Management Journal, 32(2), 52–75. https://doi.org/10.4018/IRMJ.2019040103

Soong, K. K., Ahmed, E. M., & Tan, K. S. (2020). Factors Influencing Malaysian Small and Medium Enterprises Adoption of Electronic Government Procurement. Journal of Public Procurement, 20(1), 38–61. https://doi.org/10.1108/JOPP-09-2019-0066

Sun, S., Hall, D. J., & Cegielski, C. G. (2020). Organizational Intention To Adopt Big Data In The B2B Context: An Integrated View. Industrial Marketing Management, 86(June 2018), 109–121. https://doi.org/10.1016/j.indmarman.2019.09.003

Supartika, I. P. (2020). Agar Tak Ditinggalkan , Diskop & UMKM Denpasar Minta Koperasi. Bali.Tribunnews.Com. https://bali.tribunnews.com/2020/10/28/agar-tak-ditinggalkan-diskop-umkm-denpasar-minta-koperasi-manfaatkan-teknologi-digital

Szutowski, D., Szulczewska-Remi, A., & Ratajczak, P. (2019). Managing innovation processes in industrial sector. Qualitative study. Economic Research-Ekonomska Istrazivanja , 32(1), 282–300. https://doi.org/10.1080/1331677X.2018.1553681

Ullah, F., Sepasgozar, S. M. E., Thaheem, M. J., & Al-Turjman, F. (2021). Barriers to the digitalisation and innovation of Australian Smart Real Estate: A managerial perspective on the technology non-adoption. Environmental Technology and Innovation, 22, 101527. https://doi.org/10.1016/j.eti.2021.101527

Van Looy, A. (2021). A quantitative and qualitative study of the link between business process management and digital innovation. Information and Management, 58(2), 103413. https://doi.org/10.1016/j.im.2020.103413

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. www.jstor.org/stable/30036540

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly: Management Information Systems, 36(1), 157–178. https://doi.org/10.2307/41410412

Viswanath Venkatesh, J. Y. L. T. and X. X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. Management Information Systems Research Center, JSTOR, 36(1), 157–178. https://doi.org/10.1109/MWSYM.2015.7167037

Wang, H. J., & Lo, J. (2016). Adoption of open government data among government agencies. Government Information Quarterly, 33(1), 80–88. https://doi.org/10.1016/j.giq.2015.11.004

Wei, J., Lowry, P. B., & Seedorf, S. (2015). The Assimilation of RFID Technology by Chinese Companies: A Technology Diffusion Perspective. Information and Management, 52(6), 628–642. https://doi.org/10.1016/j.im.2015.05.001

Wong, L. W., Leong, L. Y., Hew, J. J., Tan, G. W. H., & Ooi, K. B. (2020). Time to Seize The Digital Evolution: Adoption of Blockchain In Operations and Supply Chain Management Among Malaysian SMEs. International Journal of Information Management, 52(August 2019), 101997. https://doi.org/10.1016/j.ijinfomgt.2019.08.005

Yang, Z., Sun, J., Zhang, Y., & Wang, Y. (2015). Understanding SaaS adoption from the perspective of organizational users: A tripod readiness model. Computers in Human Behavior, 45, 254–264. https://doi.org/10.1016/j.chb.2014.12.022

Yeh, C. C., & Chen, Y. F. (2018). Critical success factors for adoption of 3D printing. Technological Forecasting and Social Change, 132(June 2017), 209–216. https://doi.org/10.1016/j.techfore.2018.02.003

Zaazou, Z. A., & Abdou, D. S. (2020). Egyptian Small and Medium Sized Enterprises ’ Battle Against COVID- 19 Pandemic : March – July 2020. Journal of Humanities and Applied Social Sciences, July. https://doi.org/10.1108/JHASS-09-2020-0161

Zetterli, P. (2020). Four Ways Microfinance Institutions Are Responding to COVID-19 (Issue August 2020). https://www.cgap.org/blog/four-ways-microfinance-institutions-are-responding-covid-19

Zheng, C., & Zhang, J. (2021). The impact of COVID-19 on the efficiency of microfinance institutions. International Review of Economics and Finance, 71, 407–423. https://doi.org/10.1016/j.iref.2020.09.016

Zhou, T. (2011). Understanding mobile internet continuance usage from the perspectives of UTAUT and flow. Information Development, 27(3), 207–218. https://doi.org/10.1177/0266666911414596

Zuiderwijk, A., Janssen, M., & Dwivedi, Y. K. (2015). Acceptance and use predictors of open data technologies: Drawing upon the unified theory of acceptance and use of technology. Government Information Quarterly, 32(4), 429–440. https://doi.org/10.1016/j.giq.2015.09.005




DOI: https://doi.org/10.32535/ijabim.v7i3.1789

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