{"id":3185,"date":"2022-05-23T07:57:15","date_gmt":"2022-05-23T07:57:15","guid":{"rendered":"https:\/\/mgt.sjp.ac.lk\/vjm\/?post_type=journal_article&p=3185"},"modified":"2022-05-23T07:59:35","modified_gmt":"2022-05-23T07:59:35","slug":"customers-technology-know-how-and-error-correction-capability-in-using-self-service-technologies","status":"publish","type":"journal_article","link":"https:\/\/mgt.sjp.ac.lk\/vjm\/journal_article\/customers-technology-know-how-and-error-correction-capability-in-using-self-service-technologies\/","title":{"rendered":"Customers’ Technology Know-How and Error-Correction Capability in using Self-Service Technologies"},"content":{"rendered":"

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B.S.\u00a0 Galdolage <\/o:p><\/span><\/p>\n

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Abstract
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Customers' levels of technology knowledge vary significantly, affecting their performance in Self-Service Technologies (SSTs) and their ability to respond to errors in SSTs caused by service or process failures. Despite the fact that this is a highly practical scenario, scholarly research on the subject is rare. Thus, the purpose of this research is to look into customer technology know-how in SSTs, their corrective actions in the event of SST service\/process failures, and differences among customers in terms of service performance, technology know-how, and error corrective capabilities in SSTs. <\/span>A qualitative approach was used to achieve the research objectives, with semi-structured interviews conducted with 25 SST users from various demographic backgrounds. A non-probabilistic purposeful sampling strategy was used to recruit individuals for the study, with the goal of hiring information-rich cases. Thematic analysis was used to analyze the data. <\/span>The study identified four types of knowledge that SST users need to effectively complete service transactions: computer knowledge, SST device knowledge, Internet knowledge, and language ability. Furthermore, the study identified numerous mechanisms used by customers to correct errors in SSTs and classified them as\u00a0error preventing' or 'error recovering' mechanisms. Additionally, the study discovered customer performance disparities among SSTs based on their level of technological expertise and error-correcting capabilities. The study divided SST users into three performance categories: 'Full performer,' 'Fair performer,' and 'Poor performer.' <\/span>The study contributes new knowledge by elucidating the interaction between SST users' technological expertise and error correction capabilities, a phenomenon that is rare in the previous literature, and contributing to the marketing theory by developing a typology to group customers based on customers\u2019 <\/span>level of technological expertise and error-correcting capabilities. <\/span>In the practical ground,<\/span> it informs SST service providers on how to maximize users' level of expertise while improving the service quality.<\/span><\/o:p><\/span><\/p>\n

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Keywords: <\/o:p><\/span><\/b><\/p>\n<\/p>\n

Self-service technologies, Technology know-how, Errors in SSTs, SST acceptance<\/span><\/o:p><\/span><\/p>\n

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