Blockchain adoption from the Shipping industry: An empirical study

Abelson, 1985, A variance explanation paradox: when a little is a lot, Psychol. Bull., 97, 129, 10.1037/0033-2909.97.1.129 Ajzen, 1991, The theory of planned behavior, Organ. Behav. Hum. Decis. Process., 50, 179, 10.1016/0749-5978(91)90020-T Alalwan, 2017, Factors influencing adoption of mobile banking by Jordanian bank customers: extending UTAUT2 with Trust, Int. J. Inf. Manage., 37, 99, 10.1016/j.ijinfomgt.2017.01.002 Awatsheh, 2010, The impact of supply chain structure on the use of supplier socially responsible practices, Int. J. Oper. Product. Manage., 30, 1246, 10.1108/01443571011094253 Bavassano, 2020, Blockchain: how shipping industry is dealing with the ultimate technological leap, Res. Transport. Bus. Manage., 34 Brown, 2010, Predicting collaboration technology use: integrating technology adoption and collaboration research, J. Manage. Inform. Syst., 27, 9, 10.2753/MIS0742-1222270201 Chin, 1998, 295 Cohen, 1988 Colman, 1997, Comparing rating scales of different lengths: equivalence of scores from 5-point and 7-point scales, Psychol. Rep., 355, 10.2466/pr0.1997.80.2.355 Compeau, 1995, Computer self-efficacy: development of a measure and initial test, MIS Q., 19, 189, 10.2307/249688 Davis, 1989, User acceptance of computer technology: a comparison of two theoretical models, Manage. Sci., 35, 982, 10.1287/mnsc.35.8.982 Davis, 1992, Extrinsic and intrinsic motivation to use computers in the workplace, J. Appl. Soc. Psychol., 22, 1111, 10.1111/j.1559-1816.1992.tb00945.x DeLone, 2003, The Delone and Mclean model of information systems success: a ten-year update, J. Manage. Inform. Syst., 19, 9, 10.1080/07421222.2003.11045748 Eisenhardt, 2000, Dynamic capabilities: what are they?, Strat. Manage. J., 21, 1105, 10.1002/1097-0266(200010/11)21:10/11<1105::AID-SMJ133>3.0.CO;2-E Fishbein, 1975 George, 2016 Gotz, 2010, Evaluation of structural equation models using the Partial Least Squares (PLS) approach, 47 Groenfeldt, 2017 Hackius, 2017, Blockchain in logistics and supply chain: trick or treat?, 3 Hair, 2011, PLS-SEM: indeed a silver bullet, J. Mark. Theory Pract., 19, 139, 10.2753/MTP1069-6679190202 Henseler, 2009, The use of partial least squares path modeling in international marketing, 277 2020 Jensen, 2019, How TradeLens delivers business value with blockchain technology, MIS Q. Execut., 18, 10.17705/2msqe.00018 Lam, 2018, Analysing business models of liner shipping companies, Int. J. Ship. Transp. Logist., 10, 237, 10.1504/IJSTL.2018.090078 Liébana-Cabanillas, 2017, Predictive and explanatory modeling regarding adoption of mobile payment systems, Technol. Forecast. Soc. Change, 120, 32, 10.1016/j.techfore.2017.04.002 Lieber, 2017 Lin, 2011, An empirical investigation of mobile banking adoption: the effect of innovation attributes and knowledge-based Trust, Int. J. Inf. Manage., 31, 252, 10.1016/j.ijinfomgt.2010.07.006 Maruping, 2017, Going beyond intention: integrating behavioral expectation into the unified theory of acceptance and use of Technology, J. Assoc. Inf. Sci. Technol., 68, 623, 10.1002/asi.23699 Mayer, 1995, An integrative model of organizational Trust, Acad. Manage. Rev., 20, 709, 10.2307/258792 Moore, 1991, Development of an instrument to measure the perceptions of adopting an information technology innovation, Inform. Syst. Res., 2, 192, 10.1287/isre.2.3.192 Morgan, 2018, Supplier transparency: scale development and validation, Int. J. Logist. Manage., 29, 10.1108/IJLM-01-2017-0018 Müßigmann, 2020, Blockchain technology in logistics and supply chain management – A bibliometric literature review from 2016 to January 2020, IEEE Trans. Eng. Manage., 67, 988, 10.1109/TEM.2020.2980733 Notteboom, 2022 Opensea, 2017 Panos, 2020, The Blockchain and DLTs in the maritime industry: potential and barriers, Eur. J. Electr. Eng. Comput. Sci., 4, 5 Papathanasiou, 2020, The (non-)application of blockchain technology in the Greek shipping industry, Eur. Manage. J., 38, 927, 10.1016/j.emj.2020.04.007 Petter, 2009, A meta-analytic assessment of the DeLone and McLean IS success model: an examination of IS success at the individual level, Inform. Manage., 46, 159, 10.1016/j.im.2008.12.006 Petter, 2008, Measuring information systems success: models, dimensions, measures, and interrelationships, Eur. J. Inform. Syst., 17, 236, 10.1057/ejis.2008.15 Pu, 2021, Blockchain adoptions in the maritime industry: a conceptual framework, Marit. Policy Manage., 48, 777, 10.1080/03088839.2020.1825855 Queiroz, 2019, Blockchain adoption challenges in supply chain: an empirical investigation of the main drivers in India and the USA, Int. J. Inform. Manage., 46, 70, 10.1016/j.ijinfomgt.2018.11.021 Riffai, 2012, Big TAM in Oman: exploring the promise of online banking, its adoption by customers and the challenges of banking in Oman, Int. J. Inf. Manage., 32, 239, 10.1016/j.ijinfomgt.2011.11.007 Sauro, 2016, An Introduction to Correlation, Regression, and ANOVA, 277 Scott, 2017, Exploring the rise of blockchain technology: towards distributed collaborative organizations, Strat. Chain, 26, 423, 10.1002/jsc.2142 Taylor, 1995, Assessing IT usage: the role of prior experience, MIS Q., 19, 561, 10.2307/249633 Teece, 1997, Dynamic capabilities and strategic management, Strat. Manage. J., 18, 509, 10.1002/(SICI)1097-0266(199708)18:7<509::AID-SMJ882>3.0.CO;2-Z Theotokas, 2018 Thompson, 1991, Personal computing: toward a conceptual model of utilization, MIS Q., 15, 125, 10.2307/249443 Tsiulin, 2020, Blockchain-based applications in shipping and port management: a literature review towards defining key conceptual frameworks, Rev. Int. Bus. Strat., 30, 201, 10.1108/RIBS-04-2019-0051 2019 Vaggelas, 2021, Is there gender (in)equality in shipping? Insights from Greece Venkatesh, 2008, Predicting different conceptualizations of system use: the competing roles of behavioral intention, facilitating conditions, and behavioral expectation, MIS Q., 32, 483, 10.2307/25148853 Venkatesh, 2003, User acceptance of information technology: toward a unified view, MIS Q., 27, 425, 10.2307/30036540 Venkatesh, 2012, Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology, MIS Q., 36, 157, 10.2307/41410412 Warshaw, 1985, Disentangling behavioral intention and behavioral expectation, J. Exp. Soc. Psychol., 21, 213, 10.1016/0022-1031(85)90017-4 World Bank, 2002 2017 Wu, 2011, A meta-analysis of the impact of Trust on technology acceptance model: investigation of moderating influence of subject and context type, Int. J. Inf. Manage., 31, 572, 10.1016/j.ijinfomgt.2011.03.004 Yang, 2019, Maritime shipping digitalization: blockchain-based technology applications, future improvements and intention to use, Transport. Res. Part E, 131, 108, 10.1016/j.tre.2019.09.020 Yi, 2006, Understanding information technology acceptance by individual professionals: toward an integrative view, Inform. Manage., 43, 350, 10.1016/j.im.2005.08.006 Zhong, 2021, A Stackelberg game based two-stage framework to make decisions of freight rate for container shipping lines in the emerging blockchain-based market, Transport. Res. Part E, 149 Zhou, 2020, Challenges and critical success factors of blockchain implementation: policy implications for Singapore's maritime industry, Mar. Policy, 122