Main Article Content



This research article investigates the switching intentions and attitudes towards switching intentions among high-tech electronic products, including smartphones, smartwatches, and smart appliances, in Pakistan. Unlike previous studies in Pakistan, this research employs the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TBP) to gain a more comprehensive understanding of customer behavior in this context. The study collected data through online questionnaires distributed to customers across the Khyber Pakhtunkhwa Province of Pakistan, resulting in 261 responses, with 255 being used for analysis. The findings reveal significant relationships between various factors. Firstly, a positive attitude towards switching intention, a greater perceived control over resources, and positive feedback from internal groups were found to increase the likelihood of customers switching among high-tech electronic products. Secondly, the study found that customers' attitudes towards switching intention are positively influenced by perceived ease of use, perceived usefulness, and personal innovativeness. When customers perceive a product as easy to learn and use, providing better utility, and possessing innovative features, their attitudes toward switching intentions become more favorable. In summary, this research provides valuable insights into the factors influencing switching intentions and attitudes among customers of high-tech electronic products in Pakistan, extending the scope beyond smartphones. The use of both TAM and TBP models enhances the comprehensiveness of the study, offering valuable implications for businesses and policymakers in the region's high-tech electronic product market. This research article is based on the purpose of using TBP to knowing switching intention while CAT model to know attitude towards switching intention among high-tech electronic products which includes of smartphones, smart watch and smart appliances etc. in a developing country Pakistan. Most studies of Pakistan in Pakistan has not used the TBP to know switching intention and CAT model to know attitudes towards switching intention among high-tech electronic product, in addition neither they have included other high-tech electronic products besides from smartphone. However, extending the high-tech electronic products category by included such products such as smart watches, smart appliances and laptops etc. while using the technological aspect such as looking to attitudes towards switching intention from extended TAM model (CAT) and TBP to among high-tech electronic products, would provide more comprehensive results.

Article Details

Author Biography



1MS Scholar at the Institute of Business Studies and Leadership

Abdul Wali Khan University, Mardan

2Senior HR Officer LRH MTI Peshawar

3Ph.D. Research Scholar

4Assistant Professor at Shaheed Benazir Bhutto Women University Peshawar

5Assistant Professor at National University of Modern Languages Islamabad


Steenhuis, & Bruijn. (2006). High technology revisited: definition and position. IEEE International Conference on Management of Innovation and Technology (pp. 1080-1084). Spokane: IEEE.

Abbasi, Elyas, & Tarhini. (2015). Impact of Individualism and Collectivism over the Individual’s Technology Acceptance Behaviour: A Multi-Group Analysis between Pakistan and Turkey. Journal of Enterprise Information Management System, 1-6.

Akhter, Saleem, Qamar, Iqbal, & Mahmood. (2014). MOBILE PHONE FEATURE PREFERENCES AND CONSUMPTION PATTERN OF STUDENTS IN UNIVERSITY OF SARGODHA. International Journal of Asian Social Science, 383-391.


Arteaga. (2023, 3 27). testsiteforme. Retrieved from Data Collection and Analysis: https://www.testsiteforme.com/en/what-is-exploratory-factor-analysis/

Ashfaq. (2015). Factors leading to brand switching in cellular phones: A Case of Pakistan . Journal of Marketing and Consumer Research, 32-41.

Awan, Nadeem, & Faisal. (2016). Anaysis of customers preferences regarding brandswitching in cellular sector of Pakistan. Global Journal of Management and Social Sciences, 58-88.

Bansal, & Taylor. (1999). The Service Provider Switching Model (SPSM): A Model of Consumer Switching Behavior in the Services Industry. Journal of Service Research, 200-218.

Bobbitt. (2021, 11 16). The Five Assumptions of Multiple Linear Regression. Retrieved from Statology.org: https://www.statology.org/multiple-linear-regression-assumptions/

Brown. (2011). Likert items and scales of measurement? : JALT Testing & Evaluation SIG Newsletter, 10-14.

Camacho, Vázquez, & Cossío-Silva. (2017). Exploring the Customer's Intention to Switch Firms: The Role of Customer-related Antecedents. Wiley Psychology Marketing, 1039-1049.

Chen, & Chao. (2011). Habitual or reasoned? Using the theory of planned behavior,technology acceptance model, and habit to examine switching intentions toward public transit. Elseiver, 128-137.

Collins. (2022, 11 1). Climate Consulting by selectra. Retrieved from Selectra Climate: https://climate.selectra.com

Cornell. (2023, 8 11). Advantages And Disadvantages of Online Surveys. Retrieved from proprofssurvey.com: https://www.proprofssurvey.com/blog/advantages-disadvantages-of-online-surveys/

Datalab, A. (2021, 8 4). Understanding Durbin-Watson Test. Retrieved from Medium: https://medium.com/@analyttica/durbin-watson-test-fde429f79203

Dr.Heidel. (2023). Statistica. Retrieved from scalestatistics: https://www.scalestatistics.com/skewness-and-kurtosis.html

Dwivedi, Papzafeiropoulou, Brinkman, & Lal. (2010). Examining the influence of service quality and secondary influence on the behavioural intention to change internet service provider. Information Systems Frontiers, 208-217.

Eaton, Frank, Jhonson, & Willoughby. (2019). Comparing exploratory factor models of the Brief Electricity and Magnetism Assessment and the Conceptual Survey of Electricity and Magnetism. The American Physical Society, 1-11.

Figueiredo, & Gomes. (2013). The skew-normal distribution in SPC. Revstat - Statistical Journal, 1-19.

Frost. (2023). Cronbach’s Alpha: Definition, Calculations & Example. Retrieved from statisticsbyjim.com: https://statisticsbyjim.com/basics/cronbachs-alpha/

Garcia, Saura, Orejuela, & Junior. (2020). Purchase intention and purchase behavior online: A cross-cultural approach. Heliyon, 1-11.

Guler, & Uyanık. (2013). A study on multiple linear regression analysis. Procedia- Social and Behavoiral Sciences, 234-240.

Ha, Kim, & Hyun. (2011). Switching Intention Model Development: Role of Service Performances, Customer Satisfaction, and Switching Barriers in the Hotel Industry. International journal of Hospitality Managment, 620-629.

Hair, Black, Babin, & Anderson. (2019). Multivariate Data Analysis. North Way Andover: Cengage Learning EMEA.

Haute. (2021). Sampling Techniques Sample types and sample. Oxford University Press.

Ibrahim, & Arshad. (2017). Examining the Impact of Product Involvement,Subjective Norm and Perceived Behavioral Control on Investment Intentions of Individual Investors in Pakistan. Investment Management and Financial Innovations, 181-193.

Jawaid. (2020, 10 29). How a lack of innovation is crippling Pakistan’s economy. Retrieved from tribune.com.pk: https://tribune.com.pk/article/97206/how-a-lack-of-innovation-is-crippling-pakistans-economy

Junjie, & Yingxin. (2022). The Discussions of Positivism and Interpretivism. Global Academic Journal of Humanities and Social Sciences, 10-14.

Kabir. (2016). METHODS OF DATA COLLECTION. In Kabir, Basic Guidelines for Research: An Introductory Approach for All Disciplines (pp. 201-275). Chittagong: Book Zone Publication, Chittagong-4203, Bangladesh.

Kivunja, & Kuyini. (2017). Understanding and Applying Research Paradigms in Educational Contexts. International Journal of Higher Education, 26-41.

Kolossovski. (2019, 8 22). What Makes a Great High-Tech Product? Retrieved from uxdesign.cc: https://uxdesign.cc/what-makes-a-great-high-tech-product-9f7197e5bda3

Liu, & Lee. (2020). Factors Analysis Influencing the Switching Intention of Chinese Mobile Games based on Push-Pull-Mooring Mod. JOURNAL OF INFORMATION TECHNOLOGY APPLICATIONS & MANAGEMENT, 49-68.

Mackenzie, & Knipe. (2006). Research dilemmas: Paradigms, methods and methodology. Issues in Educational Research, 193-205.

Mahmood. (2022, 3 9). Assumptions of Multiple Linear Regression. Retrieved from towardsdatascience: https://towardsdatascience.com/assumptions-of-multiple-linear-regression-d16f2eb8a2e7

Martins, Meyll, & Ferreira. (2013). Factors Affecting Mobile Users’ Switching Intentions: A Comparative Study between the Brazilian and German Markets. Anpad, 239-262.

Mohsin, Nawaz, Khan, Shaukat, & Aslam. (2011). Impact of customer satisfaction on customer loyalty and intentions to switch: Evidence from banking sector of Pakistan. International Journal of Business and Social Science , 263-270.

Montelpare, Read, McComber, Mahar, & Ritchie. (2020, 9 1). University of Prince Edward Island| Robertson Library. Retrieved from Data Screening and Cleaning: https://pressbooks.library.upei.ca/montelpare/chapter/data-screening-cleaning/

Mouloudj, Bouarar, & Stojczew. (2021). Analyzing the Students' Intention to Use Online Learning System in the Context of COVID-19 Pandemic: A Theory of Planned Behavior Approach. Advances in Global Eduaction and Research, 1-17.

Msaed, C., Al-kwifi, S., & Ahmed, Z. (2017). Building a comprehensive model to investigate factors behind switching intention of high-technology products. Journal of Product & Brand Management, 102-119.

Munir, Javed, & Bhutto. (2022). YOUNG ADULTS' SWITCHING BEHAVIOUR IN THE CELLULAR SERVICE INDUSTRY OF PAKISTAN. Global Journal for Management and Administrative Sciences , 1-16.

Oppong, & Agbedra. (2016). Assessing Univariate and Multivariate Normality, A Guide For Non-Statisticians. International Institute for Science, Technology and Education (IISTE): E-Journals, 26-33.

Osborne , & Waters. (2002). Four assumptions of multiple regression that researchers should aways text. A peer-reviewed electronic journal, 1-5.

Pologeorgis, J Boyle, & Schmitt. (2022, May 3). How Globalization Affects Developed Countries. Retrieved from www.investopedia.com: https://www.investopedia.com/articles/economics/10/globalization-developed-countries.asp

Pourabedin, Foon, Chatterjee, & Ho. (2016). Customers’ online channel switching behavior: The moderating role of switching cost. Information - An International Interdisciplinary Journal in English, Japanese and Chinese, 2961-2970.

Rahman. (2022, 9 28). For high-tech exports. Retrieved from www.thenews.com.pk: https://www.thenews.com.pk/print/995225-for-high-tech-exports

Rehman, & Alharthi. (2016). An Introduction to Research Paradigms. International Journal of Educational Investigations, 51-59.

Rizwan, Sadaf, Hafeez, & Naz. (2013). An Examination of the Switching Behavior of the Customers in Cellular Industry of Pakistan. Journal of Public Administration and Governance, 335-354.

Rouse. (2016, 11 9). TechnoPedia. Retrieved from www.technopedia.com: https://www.techopedia.com/definition/7576/high-tech

Roy. (2017). APP ADOPTION AND SWITCHING BEHAVIOR: APPLYING THE EXTENDED TAM IN SMARTPHONE APP USAGE. Journal of Information Systems and Technology Management, 239-261.

Saeed, Hussain, & Riaz. (2011). Factors affecting consumers’ switching intentions . European Journal of Social Sciences, 54-61.

Saleem, Bibi, Lakho, & Hussain. (2022). DETERMINANTS OF CUSTOMER SWITCHING INTENTION IN PAKISTAN:A CASE OF CELLULAR SERVICES. Bulletin of Business and Economics, 27-36.

Samuels, P. (2017). Advice on Exploratory Factor Analysis. Birmingham: Birmingham City University.

Sequitin. (2021, 10 5). What Is an Outlier? Retrieved from careerfoundry.com: https://careerfoundry.com/en/blog/data-analytics/what-is-an-outlier/

Shun, & Carroll. (2017). A Comprehensive Definition of Technology from an Ethological Perspective. MDPI, 1-20.

Soomro, & Ghumro. (2013). AN ANALYSIS OF CONSUMER BEHAVIOR IN MOBILE PHONE MARKET IN SINDH. European Scientific Journal, 205-513.

Suhr. (2006). Exploratory or Confirmatory Factor Analysis? Proceedings of the 31st Annual SAS? Users Group International Conference (pp. 200-231). Cary, NC: SAS Institute Cary.

Surucu, Yikilmaz, & Masiakci. (2022). Exploratory Factor Analysis (EFA) in Quantitative Researches and Practical Considerations. OSFPREPRINTS, 1-31.

Tanveer, Kaur, Thomas, Mahmood, Paruthi, & Yu. (2021). Mobile Phone Buying Decisions among Young Adults: An Empirical Study of Influencing Factors. Sustainability , 1-18.

Taylor. (2023, 5 11). Multiple Linear Regression. Retrieved from corporatefinanceinstitute: https://corporatefinanceinstitute.com/resources/data-science/multiple-linear-regression/

Tu, & Yang. (2019). Key Factors Influencing Consumers’ Purchase of Electric Vehicles. Sustainability, 1-22.

Verma, Gautam, Pandey, Mishra, & Shukla. (2017). Sampling Typology and Techniques. International Journal for Scientific Research & Development, 298-301.

Watkins. (2018). Exploratory Factor Analysis: A Guide to Best Practice. Journal of Black Psychology, 1-28.

Watson. (2018, 8 14). MRC Cognition and Brain Sciences Unit. Retrieved from imaging.mrc-cbu.cam.ac.uk: https://imaging.mrc-cbu.cam.ac.uk/statswiki/FAQ/Simon

Wirtz, Xiao, Chiang, & Malhotra. (2014). Contrasting the drivers of switching intent and switching behavior in contractual service settings. Journal of Retailing, 463-480.

Xi Aw, & Chong. (2019). Understanding non-private label consumers’ switching intention in emerging market. Marketing Intelligence & Planning , 689-705.

Yadav, Swami, & Pal. (2006). High technology marketing: Conceptualization and case study. High Technology Marketing, 57-74.

Yang, Lee, & Zo. (2017). User acceptance of smart home services: An extension of the theory of planned behavior. Industrial Management and Data Systems, 68-89.

Yong, Husin, & Kamarudin. (2021). Understanding Research Paradigms: A Scientific Guide. Journal of Contemporary Issues in Business and Government, 5857-5865.

Youn, Lee, & Brookshire. (2021). Fashion consumers' channel switching behavoir during the COVID-19: Protection motivation theory in the extended planned behavoir framework. Clothing and Textiles Research Journal, 139-156.

Yu, & Richardson. (2014). An Exploratory Factor Analysis and Reliability Analysis of the Student Online Learning Readiness (SOLR) Instrument. Purdue University ProQuest Dissertations Publishing, 120- 141.

Zach. (2021, 1 21). The Durbin-Watson Test: Definition & Example. Retrieved from Statology: https://www.statology.org/durbin-watson-test/

Zahid, Jawaid, & Zahid. (2015). Factors Behind Brand Switching: Evidences from Pakistan. INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY SCIENCES AND ENGINEERING, 14-20.