Green Information System (GIS) Model in the Conference Sector: Exploring Attendees’ Adoption Behaviors for Conference Apps

References

• Qi H, Smith KA, Yeoman IS. An exploratory study of volunteer motivation at conferences: a case study of the First World Conference on Tourism for Development. Asia Pac J Tour Res. 2019;24:574–583. doi:10.1080/10941665.2019.1610000
   Web of Science ®Google Scholar
• Technology in Offsite Meetings and Incentive Events Research. The incentive research foundation. Available from: https://theirf.org/research/technology-in-offsite-meetings-and-incentive-events/265/. Accessed June 23, 2022.
   Google Scholar
• Mair J, Lockstone-Binney L, Whitelaw PA. The motives and barriers of association conference attendance: evidence from an Australasian tourism and hospitality academic conference. J Hosp Tour Manag. 2018;34:58–65. doi:10.1016/j.jhtm.2017.11.004
   Web of Science ®Google Scholar
• Getz D, Page SJ. Progress and prospects for event tourism research. Tour Manag. 2016;52:593–631.
   Web of Science ®Google Scholar
• Kim WH, Malek KM, Roberts KR. The effectiveness of green advertising in the convention industry: an application of a dual coding approach and the norm activation model. J Hosp Tour Manag. 2019;39:185–192. doi:10.1016/j.jhtm.2019.04.007
   Web of Science ®Google Scholar
• Wang SP, Chen MS, Li M. Taiwan’s marketing strategies for green conferences and exhibitions. Sustainability. 2019;11(5):1220.
   Web of Science ®Google Scholar
• Admin E. Global economic significance of business events. EIC Insights; 2018. Available from: https://insights.eventscouncil.org/Full-Article/2018-global-economic-significance-of-business-events. Accessed June 23, 2022.
   Google Scholar
• Meeting, Convention, and Event Planners. Occupational outlook handbook. U.S. Bureau of Labor Statistics. Available from: https://www.bls.gov/ooh/business-and-financial/meeting-convention-and-event-planners.htm. Accessed June 23, 2022.
   Google Scholar
• Case R. Events and the Environment. Routledge; 2013.
   Google Scholar
• Sena M. Green industry analysis 2020 - cost & trends. Franchisee Resource Center; 2020. Available from: https://www.franchisehelp.com/industry-reports/green-industry-analysis-2020-cost-trends/. Accessed June 23, 2022.
   Google Scholar
• Chi X, Han H. Exploring slow city attributes in Mainland China: tourist perceptions and behavioral intentions toward Chinese Cittaslow. J Travel Tour Mark. 2020;37:361–379. doi:10.1080/10548408.2020.1758286
   Web of Science ®Google Scholar
• Hu J, Xiong L, Lv X, Pu B. Sustainable rural tourism: linking residents’ environmentally responsible behaviour to tourists’ green consumption. Asia Pac J Tour Res. 2021;26:879–893. doi:10.1080/10941665.2021.1925316
   Web of Science ®Google Scholar
• Trudel R. Sustainable consumer behavior. Consum Psychol Rev. 2018. doi:10.1002/arcp.1045
   Google Scholar
• Tiseo I. Paper industry worldwide-statistics and facts. Statista. Available from: https://www.statista.com/topics/1701/paper-industry/. Accessed June 23, 2022.
   Google Scholar
• Bolander B, Fine JC. Digital conferencing in times of crisis. Int J Sociol Lang. 2021;2021:55–68. doi:10.1515/ijsl-2020-0088
   Google Scholar
• Ewijk van S, Hoekman P, Schaffartzik A. Emission reduction potentials for academic conference travel. J Ind Ecol. 2020;25(778–788):511–522. doi:10.1111/jiec.13076
   Web of Science ®Google Scholar
• Hiltner K. A nearly carbon-neutral conference model. Available from: https://hiltner.english.ucsb.edu/index.php/ncnc-guide/. Accessed June 23, 2022.
   Google Scholar
• Burtscher L, Barret D, Borkar A, et al. The carbon footprint of large astronomy meetings. Nat Astron. 2020;4(9):823–825. doi:10.1038/s41550-020-1207-z
   Web of Science ®Google Scholar
• Cohen S, Hanna P, Higham JES, Hopkins D, Orchiston C. Gender discourses in academic mobility. Gend Work Organ. 2019;27(2):149–65.
   Web of Science ®Google Scholar
• Sharma D. The world of virtual conferencing: is the pandemic paving the path? J Neurosurg Anesthesiol. 2020;33(1):7–9.
   Web of Science ®Google Scholar
• Arsenault J, Talbot J, Boustani L, Gonzales R, Manaugh K. The environmental footprint of academic and student mobility in a large research-oriented university. Environ Res Lett. 2019;14(9):095001. doi:10.1088/1748-9326/ab33e6
   Web of Science ®Google Scholar
• Spinellis DD, Louridas P. The carbon footprint of conference papers. PLoS One. 2013;8:e66508.
   PubMed Web of Science ®Google Scholar
• Guldbrandsson F, Malmodin J. Life cycle assessment of virtual meeting solutions. 9th Int’l Conference on EcoBalance; 2010.
   Google Scholar
• Quack D, Oley M. Environmental Advantages of Video Conferencing Systems-Results from a Simplified LCA. EnviroInfo; 2002.
   Google Scholar
• Ong D, Moors T, Sivaraman V. Comparison of the energy, carbon and time costs of videoconferencing and in-person meetings. Comput Commun. 2014;50:86–94. doi:10.1016/j.comcom.2014.02.009
   Web of Science ®Google Scholar
• Blenkinsop S, Foley A, Schneider N, Willis J, Fowler HJ, Sisodiya SM. Carbon emission savings and short‐term health care impacts from telemedicine: an evaluation in epilepsy. Epilepsia. 2021;62(11):2732–2740. doi:10.1111/epi.17046
   Web of Science ®Google Scholar
• Su N. The proportion of central energy consumption in the global total energy consumption is increasing year by year; 2018.
   Google Scholar
• Whitehead B, Andrews D, Shah A, Maidment G. Assessing the environmental impact of data centres part 1: background, energy use and metrics. Build Environ. 2014;82:151–159. doi:10.1016/j.buildenv.2014.08.021
   Web of Science ®Google Scholar
• Van Heddeghem W, Lambert S, Lannoo B, Colle D, Pickavet M, Demeester P. Trends in worldwide ICT electricity consumption from 2007 to 2012. Comput Commun. 2014;50:64–76. doi:10.1016/j.comcom.2014.02.008
   Web of Science ®Google Scholar
• Liu Y, Wei X, Xiao J, Liu Z, Xu Y, Tian Y. Energy consumption and emission mitigation prediction based on data center traffic and PUE for global data centers. Glob Energy Interconnect. 2020;3(3):272–282. doi:10.1016/j.gloei.2020.07.008
   Google Scholar
• Fraser H, Soanes K, Jones SA, Jones C, Malishev M. The value of virtual conferencing for ecology and conservation. Conserv Biol. 2017;31:540–546.
   PubMed Web of Science ®Google Scholar
• Reay DS. Virtual solution to carbon cost of conferences. Nature. 2003;424(6946):251. doi:10.1038/424251a
   Web of Science ®Google Scholar
• Sarabipour S. Virtual conferences raise standards for accessibility and interactions. eLife. 2020;9:e62668. doi:10.7554/eLife.62668
   PubMed Web of Science ®Google Scholar
• Vervoort D, Dearani JA, Starnes VA, Thourani VH, Nguyen TC. Brave New World: virtual conferencing and surgical education in the Coronavirus Disease 2019 era. J Thorac Cardiovasc Surg. 2020;161:748–752. doi:10.1016/j.jtcvs.2020.07.094
   Web of Science ®Google Scholar
• Kalmus P. No fly climate science. Earth scientists flying less. Available from: https://noflyclimatesci.org/. Accessed June 23, 2022.
   Google Scholar
• Hamm S, Frew E, Lade C. Hybrid and virtual conferencing modes versus traditional face-to-face conference delivery: a conference industry perspective. Event Manag. 2018;22(5):717–733. doi:10.3727/152599518X15299559637635
   Google Scholar
• United Nations Environment Programme. United Nations environment sets the tone for green meetings through UNEA-2. UNEP - UN Environment Programme. Available from: http://www.unep.org/events/unea/unea-2. Accessed June 23, 2022.
   Google Scholar
• Xu R, Frey RM, Fleisch E, Ilic A. Understanding the impact of personality traits on mobile app adoption - Insights from a large-scale field study. Comput Hum Behav. 2016;62:244–256. doi:10.1016/j.chb.2016.04.011
   Web of Science ®Google Scholar
• Lee KE. An Examination of the Decision-Making Process for Utilization of Mobile Applications in the MICE Industry. Iowa State University; 2016.
   Google Scholar
• Sopha BM. Sustainable paper consumption: exploring behavioral factors. Soc Sci. 2013;2(4):270–283. doi:10.3390/socsci2040270
   Google Scholar
• Sopha BM, Klöckner CA. Psychological factors in the diffusion of sustainable technology: a study of Norwegian households’ adoption of wood pellet heating. Renew Sustain Energy Rev. 2011;15(6):2756–2765. doi:10.1016/j.rser.2011.03.027
   Web of Science ®Google Scholar
• Maréchal K. Not irrational but habitual: the importance of “behavioural lock-in” in energy consumption. Ecol Econ. 2010;69(5):1104–1114. doi:10.1016/j.ecolecon.2009.12.004
   Web of Science ®Google Scholar
• Darby S. The effectiveness of feedback on energy consumption. DEFRA. 2006;486:26.
   Google Scholar
• Singh N. Investigating Conference Attendee’s Mobile Application Adoption Behavior: An Ecological Perspective. Iowa State University; 2018.
   Google Scholar
• Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: toward a unified view. Inst Transit Econ Microecon Issues E J. 2003;1:425–78.
   Google Scholar
• Venkatesh V, Thong JY, Xu X. Consumer acceptance and use of information technology. Manag Inf Syst Q. 2012;1:157–78.
   Google Scholar
• Limayem M, Hirt SG, Cheung CMK. How habit limits the predictive power of intention: the case of information systems continuance. MIS Q. 2007;31:705–737. doi:10.2307/25148817
   Web of Science ®Google Scholar
• Vallerand RJ. Toward A hierarchical model of intrinsic and extrinsic motivation. Adv Exp Soc Psychol. 1997;29:271–360.
   Web of Science ®Google Scholar
• Dodds WB, Monroe KB, Grewal D. Effects of price, brand, and store information on buyers’ product evaluations. J Mark Res. 1991;28:307–319.
   Web of Science ®Google Scholar
• Davis FD, Bagozzi RP, Warshaw PR. User acceptance of computer technology: a comparison of two theoretical models. Manag Sci. 1989;35(8):982–1003. doi:10.1287/mnsc.35.8.982
   Web of Science ®Google Scholar
• Fishbein M, Ajzen I, Ajzen I. Belief, attitude, intention, and behavior: an introduction to theory and research. Contemp Sociol. 1977;6(2):244. doi:10.2307/2065853
   Web of Science ®Google Scholar
• Swanson EB. Measuring user attitudes in MIS research: a review. Omega Int J Manag Sci. 1982;10(2):157–165. doi:10.1016/0305-0483(82)90050-0
   Web of Science ®Google Scholar
• Warshaw PR. Predicting purchase and other behaviors from general and contextually specific intentions. J Mark Res. 1980;17(1):26–33. doi:10.1177/002224378001700103
   Web of Science ®Google Scholar
• Ajzen I, Fishbein M. The influence of attitudes on behavior. Erlbaum. 2005;10:197–255.
   Google Scholar
• Kim SS, Malhotra NK. A longitudinal model of continued is use: an integrative view of four mechanisms underlying postadoption phenomena. Manag Sci. 2005;51(5):741–755. doi:10.1287/mnsc.1040.0326
   Web of Science ®Google Scholar
• Mehran J, Olya H, Han H, Kapuściński G. Determinants of canal boat tour participant behaviours: an explanatory mixed-method approach. J Travel Tour Mark. 2020;37:112–127. doi:10.1080/10548408.2020.1720890
   Web of Science ®Google Scholar
• Brown SA, Venkatesh V. Model of adoption and technology in households: a baseline model test and extension incorporating household life cycle. MIS Q. 2005;29:399–436. doi:10.2307/25148690
   Web of Science ®Google Scholar
• van der Heijden H. User acceptance of hedonic information systems. MIS Q. 2004;28:695–704.
   Web of Science ®Google Scholar
• Ajzen I, Fishbein M. Understanding Attitudes and Predicting Social Behavior. Prentice Hall; 1980.
   Google Scholar
• Faugeron C, Rokeach M. Beliefs, attitudes and values. a theory of organization and change. Rev Francaise Sociol. 1968;11:434. doi:10.2307/3320623
   Web of Science ®Google Scholar
• Stern PC. New environmental theories: toward a coherent theory of environmentally significant behavior. J Soc Issues. 2000;56(3):407–424. doi:10.1111/0022-4537.00175
   Web of Science ®Google Scholar
• Klöckner CA. A comprehensive model of the psychology of environmental behaviour—A meta-analysis. Glob Environ Change Hum Policy Dimens. 2013;23:1028–1038. doi:10.1016/j.gloenvcha.2013.05.014
   Web of Science ®Google Scholar
• Han H. Travelers’ pro-environmental behavior in a green lodging context: converging value-belief-norm theory and the theory of planned behavior. Tour Manag. 2015;47:164–177. doi:10.1016/j.tourman.2014.09.014
   Web of Science ®Google Scholar
• Su DN, Johnson LW, O’Mahony B. Will foodies travel for food? Incorporating food travel motivation and destination foodscape into the theory of planned behavior. Asia Pac J Tour Res. 2020;25:1012–1028. doi:10.1080/10941665.2020.1805475
   Web of Science ®Google Scholar
• Schwartz SH. Normative Influences on Altruism. Adv Exp Soc Psychol. 1977;10:221–279.
   Google Scholar
• Bagozzi RP, Gopinath M, Nyer PU. The role of emotions in marketing. J Acad Mark Sci. 1999;27(2):184–206. doi:10.1177/0092070399272005
   Web of Science ®Google Scholar
• Aluri A, Palakurthi RR. The influence of demographic factors on consumer attitudes and intentions to use RFID technologies in the US hotel industry. J Hosp Tour Technol. 2011;2:188–203.
   Google Scholar
• Kallaya J, Prasong P, Kittima M. An Acceptance of Mobile Learning for Higher Education Students in Thailand. Sripatum University, Bangkok; 2009.
   Google Scholar
• Nassuora AB. Students acceptance of mobile learning for higher education in Saudi Arabia. Am Acad Sch Res J. 2012;4:24–30.
   Google Scholar
• Thomas TD, 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 Inf Commun Technol. 2013;9:71–87.
   Google Scholar
• Jansson J, Marell A, Nordlund A. Exploring consumer adoption of a high involvement eco-innovation using value-belief-norm theory. J Consum Behav. 2011;10(1):51–60. doi:10.1002/cb.346
   Web of Science ®Google Scholar
• Wang G, Dou W, Zhou N. Consumption attitudes and adoption of new consumer products: a contingency approach. Eur J Mark. 2008;42(1/2):238–254. doi:10.1108/03090560810840998
   Web of Science ®Google Scholar
• Yoon YS, Uysal M. An examination of the effects of motivation and satisfaction on destination loyalty: a structural model. Tour Manag. 2005;26(45–56):45–56. doi:10.1016/j.tourman.2003.08.016
   Web of Science ®Google Scholar
• Kline RB. Principles and Practice of Structural Equation Modeling. 4th ed. Guilford Press; 2016.
   Google Scholar
• Hurley AE, Scandura TA, Schriesheim CA, et al. Exploratory and confirmatory factor analysis: guidelines, issues, and alternatives. J Organ Behav. 1997;18(6):667–683. doi:10.1002/(SICI)1099-1379(199711)18:6<667::AID-JOB874>3.0.CO;2-T
   Web of Science ®Google Scholar
• Nunnally JC, Bernstein IH. Psychometric Theory: Nunnally and Bernstein. 3rd ed. McGraw-Hill; 2007.
   Google Scholar
• Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18(1):39–50. doi:10.1177/002224378101800104
   Web of Science ®Google Scholar
• Hair JF. Multivariate Data Analysis: A Global Perspective. Pearson; 2010.
   Google Scholar
• Brooke PP, Russell DW, Price JL. Discriminant validation of measures of job satisfaction, job involvement, and organizational commitment. J Appl Psychol. 1988;73:139–145. doi:10.1037/0021-9010.73.2.139
   Web of Science ®Google Scholar
• MacCallum RC, Austin JT. Applications of structural equation modeling in psychological research. Annu Rev Psychol. 2000;51(1):201–226. doi:10.1146/annurev.psych.51.1.201
   PubMed Web of Science ®Google Scholar
• Shah R, Goldstein SM. Use of structural equation modeling in operations management research: looking back and forward ☆. J Oper Manag. 2006;24(2):148–169. doi:10.1016/j.jom.2005.05.001
   Web of Science ®Google Scholar
• Lee S, Hershberger SL, Simple A. Rule for generating equivalent models in covariance structure modeling. Multivar Behav Res. 1990;25(3):313–334. doi:10.1207/s15327906mbr2503_4
   PubMed Web of Science ®Google Scholar
• Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci. 2000;46(2):186–204. doi:10.1287/mnsc.46.2.186.11926
   Web of Science ®Google Scholar
• Karahanna E, Straub DW, Chervany NL. Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Q. 1999;23(2):183–213. doi:10.2307/249751
   Web of Science ®Google Scholar
• Thong JYL, Venkatesh V, Xu X, Hong SJ, Tam KY. Consumer acceptance of personal information and communication technology services. IEEE Trans Eng Manag. 2011;58:613–625. doi:10.1109/TEM.2010.2058851
   Web of Science ®Google Scholar
• Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989;13:319–340. doi:10.2307/249008
   Web of Science ®Google Scholar
• Bagozzi RP. A field investigation of causal relations among cognitions, affect, intentions, and behavior. J Mark Res. 1982;19(4):562–584. doi:10.1177/002224378201900415
   Web of Science ®Google Scholar
• Vos L. What is green marketing? 5 sustainable examples to know. Available from: https://learn.g2.com/green-marketing. Accessed June 23, 2022.
   Google Scholar
• Todd S. Who are the 100 most sustainable companies of 2020? Forbes. Available from: https://www.forbes.com/sites/samanthatodd/2020/01/21/who-are-the-100-most-sustainable-companies-of-2020/. Accessed June 23, 2022.
   Google Scholar
• Benbasat I, Barki H. Quo vadis TAM? J Assoc Inf Syst. 2007;8:16.
   Web of Science ®Google Scholar
• Lindenberg S, Steg L. Normative, gain and hedonic goal frames guiding environmental behavior. J Soc Issues. 2007;63:117–137. doi:10.1111/j.1540-4560.2007.00499.x
   Web of Science ®Google Scholar
• Chang TZ, Kong WH, Chen SJ. The moderating role of environmental concerns in travel behavior: an exploratory study. J China Tour Res. 2017;13:193–210. doi:10.1080/19388160.2017.1353471
   Web of Science ®Google Scholar
• Perkins HW, Berkowitz A. Perceiving the community norms of alcohol use among students: some research implications for campus alcohol education programming. Int J Addict. 1986;21(9–10):961–976. doi:10.3109/10826088609077249
   PubMed Web of Science ®Google Scholar