Journal of Hospitality Application and Research

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User Acceptance and Usage of Food App – A Moderating Influence of Work-family Conflict using Extended TAM


Affiliations
1 Assistant Professor, Rajagiri Business School, Kochi, Kerala, India
2 Florida Gulf Coast University, Florida, United States
     

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Purpose/Aim: The paper aims at the technology adoption of a food app. The study is conducted in India using the TAM Model and investigates how work-family conflict moderates the relationship between Behavioral Intention and independent variables like Perceived Value, Perceived Ease of Use and Perceived Usefulness. The study also investigates if there is a significant difference in behavioral intention controlling for socio-demographic factors. Design/Methodology/Approach: A survey was conducted among 273 respondents across India. A convenient and snowball sampling was used for this purpose and the respondents were working professionals. Confirmatory analysis was conducted to test the measurement model and structural equation modelling was done to test for moderation effects. The analysis was conducted in R Studio. Findings: The study found that Perceived Value has high significance in the adoption of food tech apps. The moderating effect of work-family conflict is very significant in the case of Value and Perceived Usefulness. However, work-family conflict does not have a moderating effect on Perceived Ease of Use. There is a significant difference in behavioral intention accounting for control variables like age and spouse working. Research Limitations: This study was conducted in India. Future research can use this model to study the phenomenon of food app adoption in other countrieswhile adding important constructs like personal innovativeness, network effects, and habit if required. Quota sampling can be done to pick a minimum number of respondents for each socio-demographic indicator for better explanatory power. Practical Implications: The study provides online aggregator companies, data on how work-family conflict affects the adoption of the app. Companies like Swiggy and Zomato could improve perceived value irrespective of absence of work-family conflict. Restaurants can use this study to understand how they can add further value to make sure their services are attractive to even customers with less workfamily conflict. Originality/Value : The findings allow the factors that can influence the adoption of food apps in India to be understood. Unlike existing studies based on Technology Acceptance Model (TAM), this study includes perceived value and how work-family conflict moderates the relationship between Perceived Usefulness, Perceived Value and Perceived Ease of Use with Behavioral Intention. The research also investigates the significant differences in behavioral intention controlling for factors like amily type, Age, Gender and Marital status. Most studies on adoption of apps are either generalized or more focused on sectors like banking and shopping. By focusing on India, this model can also be applied to other countries which are relatively new to food app adoption.

Keywords

Food App, Technology Adoption, Work-family Conflict, Perceived Value
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  • Ajzen, I. (1991). The theory of planned behavior. Organization Behavior and Human Decision Processes, 50(2), 179-211.

  • Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4).

  • Chau, P. Y. K., & Hu, P. J. (2002). Examining a model of information technology acceptance by individual professionals: An exploratory study. Journal of Management Information Systems, 18(4), 191-229.

  • Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Massachusetts, United States: Sloan School of Management, Massachusetts Institute of Technology.

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.

  • Davis, F. D., Bogozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35, 982-1003.

  • Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475-487.

  • Davis, F. D., & Venkatesh, V. (1996). A critical assessment of potential measurement biases in the technology acceptance model: Three experiments internet. International Journal of Human-Computer Studies, 45(1), 19-45.

  • Dapp, T., Stobbe, A., & Wruuck P. (2012, December 20). The future of (mobile) payments - New (online) players competing with banks, Deutsche Bank Research (pp. 1-31).

  • Dewan, S. G., & Chen, L. D. (2005). Mobile payment adoption in the US: A cross-industry, cross platform solution. Journal of Information Privacy and Security, 1(2), 4-25.

  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, Mass; Don Mills, Ontario: Addison-Wesley Pub. Co.

  • Goodhue, D. L., & Thompson, R. L. (1995). Task technology fit and individual performance. MIS Quarterly, 19, 213-236.

  • Venkatesh, V., Morris, M. G., Davis, F. D., & Davis, G. B. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27, 425-478.

  • Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Science, 39(2), 273312.

  • Yang, K. C. C. (2005). Exploring factors affecting the adoption of mobile commerce in Singapore. Telematics and Informatics, 22, 257-277.

  • Yi, M. Y., Jackson, J. D., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information & Management,43(3), 350-363.

  • Parasuraman, A., Valarie A., Z., & Leonard L., B. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-40.

  • Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). E-S-QUAL: A multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3), 213-233.

  • Parasuraman, A., Zeithaml, V., & Berry, L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(4), 41-50.

  • Cho, M., Bonn, M. A., & Li, J. (Justin). (2018). Differences in perceptions about food delivery apps between single-person and multi-person households. International Journal of Hospitality Management, 77, 108-116.

  • Huang, E. Y., Lin, S. W., & Fan, Y. C. (2015). MS-QUAL: Mobile service quality measurement. Electronic Commerce Research and Applications, 14(2), 126-142.

  • Tan, F. B., & Chou, J. P. (2008). The relationship between mobile service quality, perceived technology compatibility, and users’ perceived playfulness in the context of mobile information and entertainment services. Intl. Journal of Human-Computer Interaction, 24(7), 649-671.

  • Wu, J.-H., & Wang, S.-C. (2005). What drives mobile commerce? Information & Management, 42(5), 719-729.

  • Yeo, V. C. S., Goh, S.-K., & Rezaei, S. (2017). Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) service. J. Retail. Consum. Serv., 35, 150-162.

  • Yoon, C., & Kim, S. (2007). Convenience and TAM in a ubiquitous computing environment: The case of wireless LAN. Electron. Commer. Res. Appl., 6(1), 102-112.

  • Yusra, Y., & Agus, A. (2018). Online food delivery service quality: Does personal innovativeness matter? Asia Proc. Soc. Sci., 2(3), 251-255.

  • Ebbs, C. A. (1996). Qualitative research inquiry: Issues of power and ethics. Education, 117(2), 217-222.

  • Yauch, C. A., & Steudel, H. J. (2003). Organizational research methods.

  • Aguinis, H., & Henle, C. A. (2002). Ethics in research. In S. G. Rogelberg (Ed.), Blackwell Handbooks of Research Methods in Psychology, Handbook of Research Methods in Industrial and Organizational Psychology (pp. 34-56). Blackwell Publishing.


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  • User Acceptance and Usage of Food App – A Moderating Influence of Work-family Conflict using Extended TAM

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Authors

Kannan Sekar
Assistant Professor, Rajagiri Business School, Kochi, Kerala, India
Lakshman Mahadevan
Florida Gulf Coast University, Florida, United States

Abstract


Purpose/Aim: The paper aims at the technology adoption of a food app. The study is conducted in India using the TAM Model and investigates how work-family conflict moderates the relationship between Behavioral Intention and independent variables like Perceived Value, Perceived Ease of Use and Perceived Usefulness. The study also investigates if there is a significant difference in behavioral intention controlling for socio-demographic factors. Design/Methodology/Approach: A survey was conducted among 273 respondents across India. A convenient and snowball sampling was used for this purpose and the respondents were working professionals. Confirmatory analysis was conducted to test the measurement model and structural equation modelling was done to test for moderation effects. The analysis was conducted in R Studio. Findings: The study found that Perceived Value has high significance in the adoption of food tech apps. The moderating effect of work-family conflict is very significant in the case of Value and Perceived Usefulness. However, work-family conflict does not have a moderating effect on Perceived Ease of Use. There is a significant difference in behavioral intention accounting for control variables like age and spouse working. Research Limitations: This study was conducted in India. Future research can use this model to study the phenomenon of food app adoption in other countrieswhile adding important constructs like personal innovativeness, network effects, and habit if required. Quota sampling can be done to pick a minimum number of respondents for each socio-demographic indicator for better explanatory power. Practical Implications: The study provides online aggregator companies, data on how work-family conflict affects the adoption of the app. Companies like Swiggy and Zomato could improve perceived value irrespective of absence of work-family conflict. Restaurants can use this study to understand how they can add further value to make sure their services are attractive to even customers with less workfamily conflict. Originality/Value : The findings allow the factors that can influence the adoption of food apps in India to be understood. Unlike existing studies based on Technology Acceptance Model (TAM), this study includes perceived value and how work-family conflict moderates the relationship between Perceived Usefulness, Perceived Value and Perceived Ease of Use with Behavioral Intention. The research also investigates the significant differences in behavioral intention controlling for factors like amily type, Age, Gender and Marital status. Most studies on adoption of apps are either generalized or more focused on sectors like banking and shopping. By focusing on India, this model can also be applied to other countries which are relatively new to food app adoption.

Keywords


Food App, Technology Adoption, Work-family Conflict, Perceived Value

References