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How does health consciousness influence attitudes of elderly people towards traceable agricultural products? Perspectives of the technology acceptance model

Published online by Cambridge University Press:  21 March 2019

Hung-Chou Lin  and
Su-Hui Kuo
Hung-Chou Lin*
Affiliation:
Department of Adult & Continuing Education, National Taiwan Normal University, Taipei, Taiwan
Su-Hui Kuo
Affiliation:
Department of Enterprise Consulting, Corporate Synergy Development Center, Taipei, Taiwan
*
*Corresponding author. Email: [email protected]
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Abstract

Recently, internet usage among elderly adults has been increasing and becoming more mainstream; with the ageing population in Taiwan, concerns over health are on the rise, and this is directly related to the products that people eat. The main objectives of this study were to develop an integrated extensibility model incorporating the technology acceptance model and to investigate the impact of health consciousness on elderly adults’ acceptance of technology in relation to traceability information websites in Taiwan. This study used structural equation modelling to analyse the data. The results revealed that elderly people with high health consciousness and high perceived usefulness had more positive attitudes towards products than those with low health consciousness and low perceived usefulness, and those with high health consciousness and high perceived ease of use had more positive attitudes than those with low health consciousness and low perceived ease of use in relation to the agricultural product traceability system.

Keywords

health consciousnesstraceable agricultural productTaiwan agricultural and food traceabilitytechnology acceptance model
Type
Article
Information
Ageing & Society , Volume 40 , Issue 8 , August 2020 , pp. 1808 - 1821
Copyright
Copyright © Cambridge University Press 2019

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References

Aboelmaged, GM (2010) Predicting e-procurement adoption in a developing country: an empirical integration of technology acceptance model and theory of planned behaviour. Industrial Management & Data Systems 110, 392–414.10.1108/02635571011030042CrossRefGoogle Scholar
Aiken, LS and West, SG (1991) Multiple Regression: Testing and Interpreting Interactions. Thousand Oaks, CA: Sage.Google Scholar
Becker, MH, Maiman, LA, Kirscht, JP, Haefner, DP and Drachman, RH (1977) The Health Belief Model and prediction of dietary compliance: a field experiment. Journal of Health and Social Behavior 18, 348–366.10.2307/2955344CrossRefGoogle ScholarPubMed
Bigné-Alcañiz, E, Ruiz-Mafé, C, Aldás-Manzano, J and Sanz-Blas, S (2008) Influence of online shopping information dependency and innovativeness on internet shopping adoption. Online Information Review 32, 648–667.10.1108/14684520810914025CrossRefGoogle Scholar
Chung, JE, Park, N, Wang, H, Fulk, J and McLaughlin, M (2010) Age differences in perceptions of online community participation among non-users: an extension of the Technology Acceptance Model. Computers in Human Behavior 26, 1674–1684.10.1016/j.chb.2010.06.016CrossRefGoogle Scholar
Council of Agriculture (2017) What is the Traceable Agriculture Product? Available at http://taft.coa.gov.tw/ct.asp?xItem=4&CtNode=206&role=C.Google Scholar
Davis, FD (1989) Perceived usefulness, perceived ease of use, and user acceptance. MIS Quarterly 13, 319–340.10.2307/249008CrossRefGoogle Scholar
Dawson, JF and Richter, AW (2006) Probing three-way interactions in moderated multiple regression: development and application of a slope difference test. Journal of Applied Psychology 91, 917–926.10.1037/0021-9010.91.4.917CrossRefGoogle ScholarPubMed
Gefen, D (2000) E-commerce: the role of familiarity and trust. Omega 28, 725–737.10.1016/S0305-0483(00)00021-9CrossRefGoogle Scholar
Gefen, D, Karahanna, E and Straub, DW (2003) Trust and TAM in online shopping: an integrated model. MIS Quarterly 27, 51–90.10.2307/30036519CrossRefGoogle Scholar
Gould, SJ (1988) Consumer attitudes toward health and health care: a differential perspective. Journal of Consumer Affairs 22, 96–118.10.1111/j.1745-6606.1988.tb00215.xCrossRefGoogle Scholar
Grankvist, G and Biel, A (2001) The importance of beliefs and purchase criteria in the choice of eco-labeled food products. Journal of Environmental Psychology 21, 405–410.10.1006/jevp.2001.0234CrossRefGoogle Scholar
Hair, J, Anderson, R, Tatum, R and Black, W (2006) Multivariate Data Analysis. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Huang, JH, Lin, YR and Chuang, ST (2007) Elucidating user behavior of mobile learning: a perspective of the extended technology acceptance model. The Electronic Library 25, 585–598.10.1108/02640470710829569CrossRefGoogle Scholar
Jarvenpaa, SL, Tractinsky, N and Saarinen, L (1999) Consumer trust in an internet store: a cross-cultural validation. Journal of Computer-mediated Communication 5, 1–35.Google Scholar
Jayanti, RK and Burns, AC (1998) The antecedents of preventive health care behavior: an empirical study. Journal of the Academy of Marketing Science 26, 6–15.10.1177/0092070398261002CrossRefGoogle Scholar
Jones, S and Fox, S (2009) Generations Online in 2009. New York, NY: Pew Internet & American Life Project.Google Scholar
Kim, HB, Kim, TT and Shin, SW (2009) Modeling roles of subjective norms and eTrust in customers’ acceptance of airline B2C eCommerce websites. Tourism Management 30, 266–277.10.1016/j.tourman.2008.07.001CrossRefGoogle Scholar
Kim, J and Park, J (2005) A consumer shopping channel extension model: attitude shift toward the online store. Journal of Fashion Marketing and Management 9, 106–121.10.1108/13612020510586433CrossRefGoogle Scholar
Kim, S and Garrison, G (2009) Investigating mobile wireless technology adoption: an extension of the technology acceptance model. Information Systems Frontiers 11, 323–333.10.1007/s10796-008-9073-8CrossRefGoogle Scholar
Kraft, FB and Goodell, PW (1993) Identifying the health conscious consumer. Marketing Health Services 13, 18–25.Google ScholarPubMed
Lanseng, EJ and Andreassen, TW (2007) Electronic healthcare: a study of people's readiness and attitude toward performing self-diagnosis. International Journal of Service Industry Management 18, 394–417.10.1108/09564230710778155CrossRefGoogle Scholar
Lockie, S, Lyons, K, Lawrence, G and Grice, J (2004) Choosing organics: a path analysis of factors underlying the selection of organic food among Australian consumers. Appetite 43, 135–146.10.1016/j.appet.2004.02.004CrossRefGoogle ScholarPubMed
Magnusson, MK, Arvola, A, Hursti, UKK, Åberg, L and Sjödén, PO (2003) Choice of organic foods is related to perceived consequences for human health and to environmentally friendly behaviour. Appetite 40, 109–117.10.1016/S0195-6663(03)00002-3CrossRefGoogle ScholarPubMed
Magnusson, MK, Arvola, A, Koivisto Hursti, UK, Åberg, L and Sjödén, PO (2001) Attitudes towards organic foods among Swedish consumers. British Food Journal 103, 209–227.10.1108/00070700110386755CrossRefGoogle Scholar
McKechnie, S, Winklhofer, H and Ennew, C (2006) Applying the technology acceptance model to the online retailing of financial services. International Journal of Retail & Distribution Management 34, 388–410.10.1108/09590550610660297CrossRefGoogle Scholar
Michaelidou, N and Hassan, LM (2008) The role of health consciousness, food safety concern and ethical identity on attitudes and intentions towards organic food. International Journal of Consumer Studies 32, 163–170.10.1111/j.1470-6431.2007.00619.xCrossRefGoogle Scholar
Newsom, JT, McFarland, BH, Kaplan, MS, Huguet, N and Zani, B (2005) The health consciousness myth: implications of the near independence of major health behaviors in the North American population. Social Science & Medicine 60, 433–437.10.1016/j.socscimed.2004.05.015CrossRefGoogle ScholarPubMed
Pavlou, PA (2003) Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce 7, 101–134.Google Scholar
Plank, RE and Gould, SJ (1990) Health consciousness, scientific orientation and wellness: an examination of the determinants of wellness attitudes and behaviors. Health Marketing Quarterly 7, 65–82.10.1300/J026v07n03_06CrossRefGoogle Scholar
Read, W, Robertson, N and McQuilken, L (2011) A novel romance: the technology acceptance model with emotional attachment. Australasian Marketing Journal 19, 223–229.10.1016/j.ausmj.2011.07.004CrossRefGoogle Scholar
Shin, DH (2010) Analysis of online social networks: a cross-national study. Online Information Review 34, 473–495.10.1108/14684521011054080CrossRefGoogle Scholar
Shin, DH and Kim, WY (2008) Applying the technology acceptance model and flow theory to cyworld user behavior: implication of the web2. 0 user acceptance. CyberPsychology & Behavior 11, 378–382.10.1089/cpb.2007.0117CrossRefGoogle ScholarPubMed
Sun, H and Zhang, P (2006) The role of moderating factors in user technology acceptance. International Journal of Human–Computer Studies 64, 53–78.10.1016/j.ijhcs.2005.04.013CrossRefGoogle Scholar
Tarkiainen, A and Sundqvist, S (2009) Product involvement in organic food consumption: does ideology meet practice? Psychology & Marketing 26, 844–863.10.1002/mar.20302CrossRefGoogle Scholar
Tong, X (2010) A cross-national investigation of an extended technology acceptance model in the online shopping context. International Journal of Retail & Distribution Management 38, 742–759.10.1108/09590551011076524CrossRefGoogle Scholar
Tsai, MT, Cheng, NC and Chen, KS (2011) Understanding online group buying intention: the roles of sense of virtual community and technology acceptance factors. Total Quality Management & Business Excellence 22, 1091–1104.10.1080/14783363.2011.614870CrossRefGoogle Scholar
Walls, HL, Peeters, A, Loff, B and Crammond, BR (2009) Why education and choice won't solve the obesity problem. American Journal of Public Health 99, 590–592.10.2105/AJPH.2008.156232CrossRefGoogle ScholarPubMed
Wang, EST and Chou, NPY (2014) Consumer characteristics, social influence, and system factors on online group-buying repurchasing intention. Journal of Electronic Commerce Research 15, 119–132.Google Scholar
Yousafzai, SY, Foxall, GR and Pallister, JG (2007 a) Technology acceptance: a meta-analysis of the TAM. Part 1. Journal of Modelling in Management 2, 251–280.10.1108/17465660710834453CrossRefGoogle Scholar
Yousafzai, SY, Foxall, GR and Pallister, JG (2007 b) Technology acceptance: a meta-analysis of the TAM. Part 2. Journal of Modelling in Management 2, 281–304.10.1108/17465660710834462CrossRefGoogle Scholar
Yousafzai, SY, Foxall, GR and Pallister, JG (2010) Explaining internet banking behavior: theory of reasoned action, theory of planned behavior, or technology acceptance model? Journal of Applied Social Psychology 40, 1172–1202.10.1111/j.1559-1816.2010.00615.xCrossRefGoogle Scholar