Research on consumers’ intended usage of cold chain logistics service through fresh-food apps based on the structural equations model
Abstract
By expanding the theory of planned behavior with Structural Equation Modeling, the objective of the study is to investigate consumer behaviors in the purchasing of fresh food through fresh-food apps and cold chain logistics services usage in Shanghai and Beijing, China. The results showed that the usefulness of the fresh-food apps has a positive impact on consumers’ attitudes to enjoying apps’ cold chain logistics services. However, the ease of use of apps has never had a positive impact on consumers’ attitudes towards enjoying cold chain logistics services. Furthermore, consumers’ attitudes, perceived behavioral control and subjective norm have a positive impact on their intention to use cold chain logistics services via fresh food apps. Findings confirmed that attitude plays a part of mediating role in usefulness and behavioral intention.
Keyword : cold chain logistics, fresh-food apps, structural equation
How to Cite
Zhang, M., Fabus, M., & Zhang, Y. (2024). Research on consumers’ intended usage of cold chain logistics service through fresh-food apps based on the structural equations model. Business: Theory and Practice, 25(1), 61–72. https://doi.org/10.3846/btp.2024.15774
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Prentice-Hall.
Ajzen, I. (1985). From Intentions to actions: A theory of planned behavior. Springer. https://doi.org/10.1007/978-3-642-69746-3_2
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32(4), 665–683. https://doi.org/10.1111/j.1559-1816.2002.tb00236.x
Akdur, G., Aydin, M. N., & Akdur, G. (2020). Adoption of mobile health apps in dietetic practice: Case study of Diyetkolik. JMIR Mhealth Uhealth, 8(10), Article e16911. https://doi.org/10.2196/16911
Bhullar, A., & Gill, P. S. (2019). Mobile shopping application usability: An empirical study on factors affecting continued intention to use and mobile application loyalty. IUP Journal of Marketing Management, 18(4), 33–50.
Chakraborty, D. (2020). Indian shoppers’ attitude towards grocery shopping apps: A survey conducted on smartphone users. Metamorphosis: A Journal of Management Research, 18(2). https://doi.org/10.1177/0972622519885502
Chang, S. C., & Tung, F. C. (2008). An empirical investigation of students’ behavioural intentions to use the online learning course websites. British Journal of Educational Technology, 39(1), 71–83. https://doi.org/10.1111/j.1467-8535.2007.00742.x
Chan, R. Y., & Lau, L. B. (2002). Explaining green purchasing behavior: A cross-cultural study on American and Chinese Consumers. Journal of International Consumer Marketing, 14(2–3), 9–40. https://doi.org/10.1300/J046v14n02_02
Chen, Y.-h. (2020). Intelligent algorithms for cold chain logistics distribution optimization based on big data cloud computing analysis. Journal of Cloud Computing: Advances, Systems and Applications, 9(37). https://doi.org/10.1186/s13677-020-00174-x
Chen, H.-K., Chou, H.-W., & Hung, S.-Ch. (2018). Interrelationships between behaviour intention and its influential factors for consumers of motorcycle express cargo delivery service. Transportmetrica A: Transport Science, 15(2). https://doi.org/10.1080/23249935.2018.1509401
China Internet Network Information Center. (2021). The 47th China statistical report on internet development. CNNIC.
Choi, J.-Ch. (2020). User familiarity and satisfaction with food delivery mobile apps. SAGE Open, 10(4). https://doi.org/10.1177/2158244020970563
Chopdar, P. K., & Sivakumar, V. J. (2019). Understanding continuance usage of mobile shopping applications in India: the role of espoused cultural values and perceived risk. Behaviour & Information Technology, 38(1), 42–64. https://doi.org/10.1080/0144929X.2018.1513563
Collis, J., & Hussey, R. (2013). Business research: A practical guide for undergraduate and postgraduate students. Palgrave Macmillan.
Dai, J., Che, W., Lim, J. J., & Shou, Y. (2020). Service innovation of cold chain logistics service providers: A multiple-case study in China. Industrial Marketing Management, 89, 143–156. https://doi.org/10.1016/j.indmarman.2019.08.002
Dai, G., & Chen, L. (2020). Research on influencing factors of customer satisfaction on the e-commerce of fresh food. Logistical Engineering and Management, 42(10), 120–122.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
Diefenbach, M. A., Weinstein, N. D., & O’Reilly, J. (1993). Scales for assessing perceptions of health hazard susceptibility. Health Education Research, 8(2), 181–192. https://doi.org/10.1093/her/8.2.181
Diop, E. B., Zhao, S., Song, Sh., & Duy, T. V. (2020). Modelling travellers’ route switching behaviour in response to variable message signs using the technology acceptance model. Transport, 35(5), 533–547. https://doi.org/10.3846/transport.2020.12498
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(February), 39–50. https://doi.org/10.1177/002224378101800104
Fu, H. (2018). Factors influencing user usage intention on intelligent logistics information platform. Journal of Intelligent & Fuzzy Systems, 35(3), 2711–2720. https://doi.org/10.3233/JIFS-169623
Ghaderi, Z., Hatamifar, P., & Ghahramani, L. (2019). How smartphones enhance local tourism experiences? Asia Pacific Journal of Tourism Research, 24(8), 778–788. https://doi.org/10.1080/10941665.2019.1630456
Greaves, M., Zibarras, L. D., & Stride, C. (2013). Using the theory of planned behavior to explore environmental behavioral intentions in the workplace. Journal of Environmental Psychology, 34, 109–120. https://doi.org/10.1016/j.jenvp.2013.02.003
Green, P. E., Johnson, R. M., & Neal, W. D. (2003). The “Journal of Marketing Research”: Its initiation, growth, and knowledge dissemination. Journal of Marketing Research, 40(1), 1–9. https://doi.org/10.1509/jmkr.40.1.1.19125
Groß, M. (2015). Mobile shopping: A classification framework and literature review. International Journal of Retail & Distribution Management, 43(3), 221–241. https://doi.org/10.1108/IJRDM-06-2013-0119
Hair, J. F., Anderson, J., Tatham, R. E., & Black, W. C. (1995). Multivariate data analysis (4th ed.). Prentice-Hall, Inc.
Hair, J. T., Anderson R. E., Tatham, R. L., & Black, W. C. (1997). Multivariate data analysis with readings (3d ed.). Macmillan.
Haldar, P., & Goel, P. (2019). Willingness to use carsharing apps: An integrated TPB and TAM. International Journal of Indian Culture and Business Management, 19(2). https://doi.org/10.1504/IJICBM.2019.101743
Han, J.-W., Zuo, M., Zhu, W.-Y., Zuo, J.-H., Lü, E.-L., Yang, X. T. (2021). A comprehensive review of cold chain logistics for fresh agricultural products: Current status, challenges, and future trends. Trends in Food Science & Technology, 109, 536–551. https://doi.org/10.1016/j.tifs.2021.01.066
Hao, Ch., & Hai-Tao, Ch. (2020). Gift giving via social network services: The case of a WeChat mini-program used in China. Data Technologies and Applications, 54(4), 481–502. https://doi.org/10.1108/DTA-08-2019-0144
Hur, H. J., Lee, H. K., & Choo, H. J. (2017). Understanding usage intention in innovative mobile app service: Comparison between millennial and mature consumers. Computers in Human Behavior, 73, 353–361. https://doi.org/10.1016/j.chb.2017.03.051
Ilieva, J., Baron, S., & Healey, N. M. (2002). Online surveys in marketing research: Pros and cons. International Journal of Market Research, 44(3), 361–376. https://doi.org/10.1177/147078530204400303
Islam, M. Z., Low, P. K. C., & Hasan, I. (2013). Intention to use advanced mobile phone services (AMPS). Management Decision, 51(4), 824–838. https://doi.org/10.1108/00251741311326590
Khor, K. S., & Hazen, B. T. (2017). Remanufactured products purchase intentions and behaviour: Evidence from Malaysia. International Journal of Production Research, 55(8), 2149–2162. https://doi.org/10.1080/00207543.2016.1194534
Kim, M., Kim, J., Choi, J., & Trivedi, M. (2017). Mobile shopping through applications: Understanding application possession and mobile purchase. Journal of Interactive Marketing, 39(1), 55–68. https://doi.org/10.1016/j.intmar.2017.02.001
Kline, R. B. (2015). Principles and practice of structural equation modelling (4th ed.). Guilford Press.
Lee, E.-Y., Lee, S.-B., & Jeon, Y. J. J. (2017). Factors influencing the behavioral intention to use food delivery apps. Social Behavior and Personality: An International Journal, 45(9), 1461–1474. https://doi.org/10.2224/sbp.6185
Li, G. (2021). Development of cold chain logistics transportation system based on 5G network and Internet of things system. Microprocessors and Microsystems, 80, Article 103565. https://doi.org/10.1016/j.micpro.2020.103565
Liang, A. R.-D., & Lim, W. M. (2011). Exploring the online buying behavior of specialty food shoppers. International Journal of Hospitality Management, 30(4), 855–865. https://doi.org/10.1016/j.ijhm.2011.01.006
Lim, K.-B., Yeo, S.-F., & Wong, J.-Ch. (2020). Factors affecting purchasing intention by using mobile shopping applications in Malaysia. International Journal of Business and Society, 21(3), 1058–1067. https://doi.org/10.33736/ijbs.3311.2020
Mercier, S., Villeneuve, S., Mondor, M., & Uysal, I. (2017). Time-temperature management along the food cold chain: A review of recent developments. Comprehensive Reviews in Food Science and Food Safety, 16(4), 647–667. https://doi.org/10.1111/1541-4337.12269
Ndraha, N., Hsiao, H. I., Vlajic, J., Yang, M. F., & Lin, H. T. V. (2018). Time-temperature abuse in the food cold chain: Review of issues, challenges, and recommendations. Food Control, 89, 12–21. https://doi.org/10.1016/j.foodcont.2018.01.027
Narajan, Th., Balasubramanian, S. A., & Kasilingam, D. L. (2018). The moderating role of device type and age of users on the intention to use mobile shopping applications. Technology in Society, 53, 79–90. https://doi.org/10.1016/j.techsoc.2018.01.003
Patel, V. (2016). Use of mobile wallet service by the youth: A study based in Ahmedabad. ASBM Journal of Management, 9(2), 50–61.
Qi, L., Jung, G.-Y., Kim, & H.-H. (2020). Analysis on influencing factors of development of agricultural product cold chain logistics in Jilin Province, China. Journal of the Korea Convergence Society, 11(2), 9–15.
Rong, F., Zhang, Y., Wang, Z., & Li, Y. (2019). Influencing factors of consumer willingness to pay for cold chain logistics: An empirical analysis in China. Journal of Ambient Intelligence and Humanized Computing, 10, 3279–3285. https://doi.org/10.1007/s12652-018-1056-0
Schmidt, K. (2019). Predicting the consumption of expired food by an extended Theory of Planned Behavior. Food Quality and Preference, 78, Article 103746. https://doi.org/10.1016/j.foodqual.2019.103746
Shaharudin, M. R., Pani, J. J., Mansor, S. W., & Elias, S. J. (2010). Factors affecting purchase intention of organic food in Malaysia’s Kedah State. Cross-Cultural Communication, 6(2), 105–116.
Silver, L. (2019). Smartphone ownership is growing rapidly around the world, but not always equally. Pew Research Center’s Global Attitudes Project. https://www.pewresearch.org/global/2019/02/05/smartphone-ownership-is-growing-rapidly-around-the-world-but-not-always-equally/
Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation model. Sociological Methodology, 13, 290–312. https://doi.org/10.2307/270723
Son, J., Jin, B., & George, B. (2013). Consumers’ purchase intention toward foreign brand goods. Management Decision, 51(2), 434–450. https://doi.org/10.1108/00251741311301902
Sparks, P., & Shepherd, R. (1992). Self-identity and the theory of planned behavior: Assesing the role of identification with “green consumerism”. Social Psychology Quaterly, 55(4), 388–399. https://doi.org/10.2307/2786955
Teng, Ch.-Ch., & Lu, Ch.-H. (2016). Organic food consumption in Taiwan: Motives, involvement, and purchase intention under the moderating role of uncertainty. Appetite, 105, 95–105. https://doi.org/10.1016/j.appet.2016.05.006
Tonglet, M., Phillips, P. S., & Read, A. D. (2004). Using the theory of planned behaviour to investigate the determinants of recycling behaviour: A case study from Brixworth, UK. Resources, Conservation and Recycling, 41(3), 191–214. https://doi.org/10.1016/j.resconrec.2003.11.001
Valencia-Arias, A., Bermúdez-Hernández, J., & Bran-Piedrahita, L. (2021). Factors that encourage cigarette consumption among college students: A theory of planned behavior perspective. Journal of Pharmacy & Pharmacognosy Research, 9(3), 272–283. https://doi.org/10.56499/jppres20.925_9.3.272
Wai, I. Sh. H., Ng, S. S. Y., Chiu, D. K. W., Ho, K. K. W., & Lo, P. (2018). Exploring undergraduate students’ usage pattern of mobile apps for education. Journal of Librarianship and Information Science, 50(1), 34–47. https://doi.org/10.1177/0961000616662699
Wang, Q., Zhang, W., Tseng, M.-L., Sun, Y., & Zhang, Y. (2021). Intention in use recyclable express packaging in consumers’ behavior: An empirical study. Resources, Conservation and Recycling, 164, Article 105115. https://doi.org/10.1016/j.resconrec.2020.105115
Weigel, F. K., Hazen, B. T., Cegielski, C., & Hall, D. J. (2014). Diffusion of innovations and theory of planned behavior in information systems research: A meta-analysis. Communications of the Association for Information Systems, 34(1), 619–636. https://doi.org/10.17705/1CAIS.03431
Zhao, Z., Li, X. & Zhou, X. (2020). Distribution route optimization for electric vechicles in urban cold chain logistics for fresh products under time-varying traffic conditions. Mathematical Problems in Engineering, 2020. https://doi.org/10.1155/2020/9864935
Ajzen, I. (1985). From Intentions to actions: A theory of planned behavior. Springer. https://doi.org/10.1007/978-3-642-69746-3_2
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32(4), 665–683. https://doi.org/10.1111/j.1559-1816.2002.tb00236.x
Akdur, G., Aydin, M. N., & Akdur, G. (2020). Adoption of mobile health apps in dietetic practice: Case study of Diyetkolik. JMIR Mhealth Uhealth, 8(10), Article e16911. https://doi.org/10.2196/16911
Bhullar, A., & Gill, P. S. (2019). Mobile shopping application usability: An empirical study on factors affecting continued intention to use and mobile application loyalty. IUP Journal of Marketing Management, 18(4), 33–50.
Chakraborty, D. (2020). Indian shoppers’ attitude towards grocery shopping apps: A survey conducted on smartphone users. Metamorphosis: A Journal of Management Research, 18(2). https://doi.org/10.1177/0972622519885502
Chang, S. C., & Tung, F. C. (2008). An empirical investigation of students’ behavioural intentions to use the online learning course websites. British Journal of Educational Technology, 39(1), 71–83. https://doi.org/10.1111/j.1467-8535.2007.00742.x
Chan, R. Y., & Lau, L. B. (2002). Explaining green purchasing behavior: A cross-cultural study on American and Chinese Consumers. Journal of International Consumer Marketing, 14(2–3), 9–40. https://doi.org/10.1300/J046v14n02_02
Chen, Y.-h. (2020). Intelligent algorithms for cold chain logistics distribution optimization based on big data cloud computing analysis. Journal of Cloud Computing: Advances, Systems and Applications, 9(37). https://doi.org/10.1186/s13677-020-00174-x
Chen, H.-K., Chou, H.-W., & Hung, S.-Ch. (2018). Interrelationships between behaviour intention and its influential factors for consumers of motorcycle express cargo delivery service. Transportmetrica A: Transport Science, 15(2). https://doi.org/10.1080/23249935.2018.1509401
China Internet Network Information Center. (2021). The 47th China statistical report on internet development. CNNIC.
Choi, J.-Ch. (2020). User familiarity and satisfaction with food delivery mobile apps. SAGE Open, 10(4). https://doi.org/10.1177/2158244020970563
Chopdar, P. K., & Sivakumar, V. J. (2019). Understanding continuance usage of mobile shopping applications in India: the role of espoused cultural values and perceived risk. Behaviour & Information Technology, 38(1), 42–64. https://doi.org/10.1080/0144929X.2018.1513563
Collis, J., & Hussey, R. (2013). Business research: A practical guide for undergraduate and postgraduate students. Palgrave Macmillan.
Dai, J., Che, W., Lim, J. J., & Shou, Y. (2020). Service innovation of cold chain logistics service providers: A multiple-case study in China. Industrial Marketing Management, 89, 143–156. https://doi.org/10.1016/j.indmarman.2019.08.002
Dai, G., & Chen, L. (2020). Research on influencing factors of customer satisfaction on the e-commerce of fresh food. Logistical Engineering and Management, 42(10), 120–122.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
Diefenbach, M. A., Weinstein, N. D., & O’Reilly, J. (1993). Scales for assessing perceptions of health hazard susceptibility. Health Education Research, 8(2), 181–192. https://doi.org/10.1093/her/8.2.181
Diop, E. B., Zhao, S., Song, Sh., & Duy, T. V. (2020). Modelling travellers’ route switching behaviour in response to variable message signs using the technology acceptance model. Transport, 35(5), 533–547. https://doi.org/10.3846/transport.2020.12498
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(February), 39–50. https://doi.org/10.1177/002224378101800104
Fu, H. (2018). Factors influencing user usage intention on intelligent logistics information platform. Journal of Intelligent & Fuzzy Systems, 35(3), 2711–2720. https://doi.org/10.3233/JIFS-169623
Ghaderi, Z., Hatamifar, P., & Ghahramani, L. (2019). How smartphones enhance local tourism experiences? Asia Pacific Journal of Tourism Research, 24(8), 778–788. https://doi.org/10.1080/10941665.2019.1630456
Greaves, M., Zibarras, L. D., & Stride, C. (2013). Using the theory of planned behavior to explore environmental behavioral intentions in the workplace. Journal of Environmental Psychology, 34, 109–120. https://doi.org/10.1016/j.jenvp.2013.02.003
Green, P. E., Johnson, R. M., & Neal, W. D. (2003). The “Journal of Marketing Research”: Its initiation, growth, and knowledge dissemination. Journal of Marketing Research, 40(1), 1–9. https://doi.org/10.1509/jmkr.40.1.1.19125
Groß, M. (2015). Mobile shopping: A classification framework and literature review. International Journal of Retail & Distribution Management, 43(3), 221–241. https://doi.org/10.1108/IJRDM-06-2013-0119
Hair, J. F., Anderson, J., Tatham, R. E., & Black, W. C. (1995). Multivariate data analysis (4th ed.). Prentice-Hall, Inc.
Hair, J. T., Anderson R. E., Tatham, R. L., & Black, W. C. (1997). Multivariate data analysis with readings (3d ed.). Macmillan.
Haldar, P., & Goel, P. (2019). Willingness to use carsharing apps: An integrated TPB and TAM. International Journal of Indian Culture and Business Management, 19(2). https://doi.org/10.1504/IJICBM.2019.101743
Han, J.-W., Zuo, M., Zhu, W.-Y., Zuo, J.-H., Lü, E.-L., Yang, X. T. (2021). A comprehensive review of cold chain logistics for fresh agricultural products: Current status, challenges, and future trends. Trends in Food Science & Technology, 109, 536–551. https://doi.org/10.1016/j.tifs.2021.01.066
Hao, Ch., & Hai-Tao, Ch. (2020). Gift giving via social network services: The case of a WeChat mini-program used in China. Data Technologies and Applications, 54(4), 481–502. https://doi.org/10.1108/DTA-08-2019-0144
Hur, H. J., Lee, H. K., & Choo, H. J. (2017). Understanding usage intention in innovative mobile app service: Comparison between millennial and mature consumers. Computers in Human Behavior, 73, 353–361. https://doi.org/10.1016/j.chb.2017.03.051
Ilieva, J., Baron, S., & Healey, N. M. (2002). Online surveys in marketing research: Pros and cons. International Journal of Market Research, 44(3), 361–376. https://doi.org/10.1177/147078530204400303
Islam, M. Z., Low, P. K. C., & Hasan, I. (2013). Intention to use advanced mobile phone services (AMPS). Management Decision, 51(4), 824–838. https://doi.org/10.1108/00251741311326590
Khor, K. S., & Hazen, B. T. (2017). Remanufactured products purchase intentions and behaviour: Evidence from Malaysia. International Journal of Production Research, 55(8), 2149–2162. https://doi.org/10.1080/00207543.2016.1194534
Kim, M., Kim, J., Choi, J., & Trivedi, M. (2017). Mobile shopping through applications: Understanding application possession and mobile purchase. Journal of Interactive Marketing, 39(1), 55–68. https://doi.org/10.1016/j.intmar.2017.02.001
Kline, R. B. (2015). Principles and practice of structural equation modelling (4th ed.). Guilford Press.
Lee, E.-Y., Lee, S.-B., & Jeon, Y. J. J. (2017). Factors influencing the behavioral intention to use food delivery apps. Social Behavior and Personality: An International Journal, 45(9), 1461–1474. https://doi.org/10.2224/sbp.6185
Li, G. (2021). Development of cold chain logistics transportation system based on 5G network and Internet of things system. Microprocessors and Microsystems, 80, Article 103565. https://doi.org/10.1016/j.micpro.2020.103565
Liang, A. R.-D., & Lim, W. M. (2011). Exploring the online buying behavior of specialty food shoppers. International Journal of Hospitality Management, 30(4), 855–865. https://doi.org/10.1016/j.ijhm.2011.01.006
Lim, K.-B., Yeo, S.-F., & Wong, J.-Ch. (2020). Factors affecting purchasing intention by using mobile shopping applications in Malaysia. International Journal of Business and Society, 21(3), 1058–1067. https://doi.org/10.33736/ijbs.3311.2020
Mercier, S., Villeneuve, S., Mondor, M., & Uysal, I. (2017). Time-temperature management along the food cold chain: A review of recent developments. Comprehensive Reviews in Food Science and Food Safety, 16(4), 647–667. https://doi.org/10.1111/1541-4337.12269
Ndraha, N., Hsiao, H. I., Vlajic, J., Yang, M. F., & Lin, H. T. V. (2018). Time-temperature abuse in the food cold chain: Review of issues, challenges, and recommendations. Food Control, 89, 12–21. https://doi.org/10.1016/j.foodcont.2018.01.027
Narajan, Th., Balasubramanian, S. A., & Kasilingam, D. L. (2018). The moderating role of device type and age of users on the intention to use mobile shopping applications. Technology in Society, 53, 79–90. https://doi.org/10.1016/j.techsoc.2018.01.003
Patel, V. (2016). Use of mobile wallet service by the youth: A study based in Ahmedabad. ASBM Journal of Management, 9(2), 50–61.
Qi, L., Jung, G.-Y., Kim, & H.-H. (2020). Analysis on influencing factors of development of agricultural product cold chain logistics in Jilin Province, China. Journal of the Korea Convergence Society, 11(2), 9–15.
Rong, F., Zhang, Y., Wang, Z., & Li, Y. (2019). Influencing factors of consumer willingness to pay for cold chain logistics: An empirical analysis in China. Journal of Ambient Intelligence and Humanized Computing, 10, 3279–3285. https://doi.org/10.1007/s12652-018-1056-0
Schmidt, K. (2019). Predicting the consumption of expired food by an extended Theory of Planned Behavior. Food Quality and Preference, 78, Article 103746. https://doi.org/10.1016/j.foodqual.2019.103746
Shaharudin, M. R., Pani, J. J., Mansor, S. W., & Elias, S. J. (2010). Factors affecting purchase intention of organic food in Malaysia’s Kedah State. Cross-Cultural Communication, 6(2), 105–116.
Silver, L. (2019). Smartphone ownership is growing rapidly around the world, but not always equally. Pew Research Center’s Global Attitudes Project. https://www.pewresearch.org/global/2019/02/05/smartphone-ownership-is-growing-rapidly-around-the-world-but-not-always-equally/
Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation model. Sociological Methodology, 13, 290–312. https://doi.org/10.2307/270723
Son, J., Jin, B., & George, B. (2013). Consumers’ purchase intention toward foreign brand goods. Management Decision, 51(2), 434–450. https://doi.org/10.1108/00251741311301902
Sparks, P., & Shepherd, R. (1992). Self-identity and the theory of planned behavior: Assesing the role of identification with “green consumerism”. Social Psychology Quaterly, 55(4), 388–399. https://doi.org/10.2307/2786955
Teng, Ch.-Ch., & Lu, Ch.-H. (2016). Organic food consumption in Taiwan: Motives, involvement, and purchase intention under the moderating role of uncertainty. Appetite, 105, 95–105. https://doi.org/10.1016/j.appet.2016.05.006
Tonglet, M., Phillips, P. S., & Read, A. D. (2004). Using the theory of planned behaviour to investigate the determinants of recycling behaviour: A case study from Brixworth, UK. Resources, Conservation and Recycling, 41(3), 191–214. https://doi.org/10.1016/j.resconrec.2003.11.001
Valencia-Arias, A., Bermúdez-Hernández, J., & Bran-Piedrahita, L. (2021). Factors that encourage cigarette consumption among college students: A theory of planned behavior perspective. Journal of Pharmacy & Pharmacognosy Research, 9(3), 272–283. https://doi.org/10.56499/jppres20.925_9.3.272
Wai, I. Sh. H., Ng, S. S. Y., Chiu, D. K. W., Ho, K. K. W., & Lo, P. (2018). Exploring undergraduate students’ usage pattern of mobile apps for education. Journal of Librarianship and Information Science, 50(1), 34–47. https://doi.org/10.1177/0961000616662699
Wang, Q., Zhang, W., Tseng, M.-L., Sun, Y., & Zhang, Y. (2021). Intention in use recyclable express packaging in consumers’ behavior: An empirical study. Resources, Conservation and Recycling, 164, Article 105115. https://doi.org/10.1016/j.resconrec.2020.105115
Weigel, F. K., Hazen, B. T., Cegielski, C., & Hall, D. J. (2014). Diffusion of innovations and theory of planned behavior in information systems research: A meta-analysis. Communications of the Association for Information Systems, 34(1), 619–636. https://doi.org/10.17705/1CAIS.03431
Zhao, Z., Li, X. & Zhou, X. (2020). Distribution route optimization for electric vechicles in urban cold chain logistics for fresh products under time-varying traffic conditions. Mathematical Problems in Engineering, 2020. https://doi.org/10.1155/2020/9864935