Technology Integration and Attitude Towards New Food as Predictors of Self-Efficacy in Cooking

Marivic R. Lugnasin *

Santo Tomas College of Agriculture, Sciences and Technology, Davao del Norte, Philippines.

Jolina P. Villaruz

Santo Tomas College of Agriculture, Sciences and Technology, Davao del Norte, Philippines.

Mary Cristine P. Imperial

Santo Tomas College of Agriculture, Sciences and Technology, Davao del Norte, Philippines.

John Mark B. Lazaro

Santo Tomas College of Agriculture, Sciences and Technology, Davao del Norte, Philippines.

*Author to whom correspondence should be addressed.


Abstract

This descriptive-predictive study aims to provide a comprehensive overview of the current landscape of technology use in cooking and individuals' attitudes toward experimenting with new ingredients. Through predictive analysis, the study seeks to identify potential relationships and predictive patterns between technology integration, attitude toward new food, and self-efficacy in cooking. There were 7 different restaurant and 110 employees in Santo Tomas and Davao del Norte were chosen through the quota sampling technique. This study used three adapted questionnaires. Mean, Pearson r, standard deviation, and regression analysis were used as statistical tools. The study's findings showed that technology integration in terms of self-efficacy, performance outcome expectations, self-evaluative outcome expectations, social outcome expectations, and interest was observed. Attitude towards new food in terms of skepticism, innovativeness, and traditionalism is observed. Predictors of self-efficacy in cooking are often observed. Also, there was a significant relationship between technology integration, attitude toward new food, and self-efficacy in cooking among restaurant employees with a (P<0.001 & R=0.757) and (P<0 & R=734). Further analysis eventually showed a significant influence of technology integration, attitude towards new food, and self-efficacy in cooking among restaurant employees with a (β = 0.492 & p < 0.001) and (β = 0.299 & p < 0.025). Therefore, this emphasizes that restaurant employees are encouraged to take part in specialized training courses or workshops designed to increase their digital literacy and comfort level and increase their self-efficacy in using technology for culinary reasons. Restaurant employees who are less hesitant about trying new foods are strongly encouraged to participate fully in tasting events or cooking classes that introduce them to various products and culinary styles. Promoting teamwork and collaboration among colleagues fosters mutual learning and growth, enhancing morale and self-efficacy. Recognizing and reinforcing progress can shift employees' perspectives, fostering a positive cooking mindset.

Keywords: Technology integration, attitude towards new food, predictors of self-efficacy in cooking, descriptive and predictive design, regression analysis, Davao del Norte, Philippines


How to Cite

Lugnasin , M. R., Villaruz , J. P., Imperial , M. C. P., & Lazaro , J. M. B. (2024). Technology Integration and Attitude Towards New Food as Predictors of Self-Efficacy in Cooking. Asian Journal of Food Research and Nutrition, 3(3), 471–484. Retrieved from https://journalajfrn.com/index.php/AJFRN/article/view/149

Downloads

Download data is not yet available.

References

Oleschuk M, Choi HY, Ellison B, Prescott MP. Associations between cooking self-efficacy, attitude, and behaviors among people living alone: A cross-sectional survey analysis. Appetite. 2023; 189:106999. Available:https://doi.org/10.1016/j.appet.2023.106999

Üngüren E, Tekin ÖA. The effect of openness to experience personality trait of kitchen staff on creativity potential: The mediating effect of food neophobia and the moderating effect of occupational self-efficacy. International Journal of Gastronomy and Food Science. 2022; 28:100530.Available:https://doi.org/10.1016/j.ijgfs.2022.100530

Torres MG. Teaching nutrition education and cooking self-efficacy through TikTok videos: A pilot study (Doctoral dissertation, California State University, Northridge); 2021.

Keskin E. Relationships among self-efficacy, job resourcefulness and job performance of hotel cooks in Cappadocia. Journal of multidisciplinary academic tourism. 2020;5(1):17-27.

Lee Y, Yoon H, Kim T, Jung H. Food Insecurity during the Pandemic in South Korea: The Effects of University Students’ Perceived Food Insecurity on Psychological Well-Being, Self-Efficacy, and Life Satisfaction. Foods. 2023;12 (18):3429. Available:https://doi.org/10.3390/foods12183429

De Borba TP, Da Silva MV, Jomori MM, Bernardo GL, Fernandes AC, Da Costa Proença RP, Rockenbach G, Uggioni PL. Self-efficacy in cooking and consuming fruigts and veetables among Brazilian university students: the relationship with sociodemographic characteristics. British Food Journal. 2021;123(6):2049–2065. Available: https://doi.org/10.1108/bfj-04-2020-0311

Abun D. Employees’ self-efficacy and work performance of employees as mediated by work environment. Social Science Research Network; 2021. Available:https://doi.org/10.2139/ssrn.3958247

Jacinto MAT, Samonte FA. Anxiety and efficacy in computer technology integration among secondary school teachers of Angadanan, Isabela, Philippines. Journal of BIMP-EAGA Regional Development. 2021;7(1):57-65.

Almagro R, Flores L. teacher’s work values in public schools: The influence of web-based professional development to self efficacy and resilience in Davao Region; 2023.DOI:10.20944/preprints202312.1349.v1

Basarmak U, Hamutoglu NB. Developing and Validating a Comprehensive Scale to Measure Perceived Barriers to Technology Integration. International Journal of Technology in Education and Science. 2020;4(1):53-71.

Gomez FC, Trespalacios J, Hsu YC, Yang D. Exploring teachers’ technology integration self-efficacy through the 2017 ISTE Standards. TechTrends. 2022:1-13.

Cattaneo C, Lavelli V, Proserpio C, Laureati M, Pagliarini E. Consumers’ attitude towards food by‐products: the influence of food technology neophobia, education and information. International Journal of Food Science & Technology. 2019;54(3);679-687.

Santisi G, Magnano P, Di Marco G. Psychological sustainability and attitudes of new food consumption. A research on food disgust and neophobia. Quality-Access to Success. 2019;20.

Lo BK, Loui C, Folta SC, Flickinger A, Connor LM, Liu Pinder B. Attitude and Etiquette, Is it destroying or making your Teams; 2018. Available:https://www.linkedin.com/pulse/attitude-etiquette-destroying-making-your-teams-bryan-pinder

Knol LL, Robb CA, McKinley EM, Wood M. Very low food security status is related to lower cooking self-efficacy and less frequent food preparation behaviors among college students. Journal of nutrition education and behavior. 2019; 51(3):357-363.

Davis FD. User acceptance of information systems: the technology acceptance model (TAM); 1987.

Bandura A. Social foundations of thought and aedo»: A social cognitive theory; 1986.

Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: Toward a unified view. MIS quarterly. 2003:425-478.

Smith PR, Zook Z. Marketing communications: Integrating online and offline, customer engagement and digital technologies. Kogan Page Publishers; 2019.

Ajzen I. The theory of planned behavior. Organizational behavior and human decision processes. 1991;50(2):179-211.

Rosenstock IM. The health belief model and Preventive health behavior. Health Education Monographs. 1974;2(4):354–386.Available:https://doi.org/10.1177/109019817400200405

Johnson RB, Christensen L. Educational research: Quantitative, qualitative, and mixed approaches. Sage publications; 2019.

Henson RK, Stewart G, Bedford L. Key challenges and some guidance on using strong quantitative methodology in education research. Journal of Urban Mathematics Education. 2020;13(2). Available:https://doi.org/10.21423/jume-v13i2a382

Moraga JA, Quezada LE, Palominos P, Oddershede AM, Silva HA. A quantitative methodology to enhance a strategy map. International Journal of Production Economics. 2020;219:43–53. Available:https://doi.org/10.1016/j.ijpe.2019.05.020

Mohajan HK. Quantitative research: A successful investigation in natural and social sciences. Journal of Economic Development, Environment and People. 2020;9(4):50-79.

Wollman LF. Research paradigms; 2018.

McLeod S. Questionnaire: Definition, examples, design and types. Simply psychology. 2018;78:350-365.

Niederhauser DS, Perkmen S. Validation of the Intrapersonal Technology Integration Scale: Assessing the Influence of Intrapersonal Factors that Influence Technology Integration. Computers in the Schools. 2008c;25(1–2):98–111. Available:https://doi.org/10.1080/07380560802157956

Ozgen L. Academicians’ attitude towards “new foods”. Food and Public Health. 2014;4(6):259-265.

Condrasky MD, Williams JE, Catalano PM, Griffin SF. Development of psychosocial scales for evaluating the impact of a culinary nutrition education program on cooking and healthful eating. Journal of Nutrition Education and Behavior. 2011;43(6):511–516. Available:https://doi.org/10.1016/j.jneb.2010.09.013

Qadri SS. Impact of Advertising on Sales Performance (Doctoral dissertation, Greenwich University Pakistan); 2020.

Bhandari P. Data Collection | Definition, Methods & Examples. Scribbr; 2023.Available:https://www.scribbr.com/methodology/data-collection/?fbclid=IwAR3kkXdCpvvnn7n8w4VMKiPGEeZqQQ9mYH9924otmQ8ds9r5yBhAoLW4g1U

Zoran A. Cooking with Computers: The Vision of Digital Gastronomy [Point of View]. Proceedings of the IEEE. 2019; 107(8):1467–1473.Available:https://doi.org/10.1109/jproc.2019.2925262

Jin Y. Integrated cooker for kitchen. SciSpace – Paper; 2019. Available:https://typeset.io/papers/integrated-cooker-for-kitchen-2099dq6pph

Głuchowski A, Czarniecka-Skubina E, Kostyra E, Wasiak‐Zys G, Bylinka K. Sensory Features, Liking and Emotions of Consumers towards Classical, Molecular and Note by Note Foods. Foods. 2021;10(1):33. Available:https://doi.org/10.3390/foods10010133

Kudo K. Role of Food Neophobia, Food Attitudes and Written Information on the Acceptance of Novel Fish Products: A Cross-Cultural Study; 2022.Available:https://doi.org/10.15760/etd.7842

Jeong S, Kim O. A study on the effect of hotel chef’s coaching leadership on Self-Efficacy and Organizational Citizenship behavior. Dong-asia Siksaenghwal Hakoeji/Dong’asia Sigsaenghwal Haghoeji. 2022;32(5):273–283. Available:https://doi.org/10.17495/easdl.2022.10.32.5.273

Mahfud T, Nugraheni M, Pardjono P, Lastariwati B. Measuring Occupational Self-Efficacy: A Culinary Students’ Cooking Performance perspective. Jurnal Pendidikan Teknologi Dan Kejuruan/Jurnal Pendidikan Teknologi Dan Kejuruan. 2021;27(2):138–145. Available:https://doi.org/10.21831/jptk.v27i2.39530

Lestari NS, Rosman D, Chan S, Nawangsari LC, Natalina HD, Triono F. Impact of robots, artificial intelligence, service Automation (RAISA) acceptance, self-efficacy, and relationship quality on job performance. 2022 4th International Conference on Cybernetics and Intelligent System (ICORIS); 2022.Available:https://doi.org/10.1109/icoris56080.2022.10031336

Agwa Y. A study of food allergy knowledge, attitudes, and practices of restaurant employees. International Journal of Tourism and Hospitality Management. 2023; 6(1):229–244. Available:https://doi.org/10.21608/ijthm.2023.300885

Cattaneo C, Lavelli V, Proserpio C, Laureati M, Pagliarini E. Consumers’ attitude towards food by‐products: the influence of food technology neophobia, education and information. International Journal of Food Science & Technology. 2018;54(3):679–687.

Yogesh S. Self-cooking devices. SciSpace – Paper; 2020b. Available:https://typeset.io/papers/self-cooking-devices-25ter1wbu2

Kudo K. Role of Food Neophobia, Food Attitudes and Written Information on the Acceptance of Novel Fish Products: A Cross-Cultural Study; 2022b. Available:https://doi.org/10.15760/etd.7842