A study on consumer adoption of technology facilitated services. Issue 6 (19th August 2014)

• Record Type: Journal Article
• Authors: RoyChowdhury, Indranil; Patro, Sanjay; Venugopal, Pingali; Israel, D
• Editors: Martin, Charles
• Is Part Of: Journal of services marketing. Volume 28:Issue 6(2014)
• Publication Date: 2014-08-19
• Subjects: Service industries -- Periodicals; Customer services -- Periodicals; 658.802
• DOI: 10.1108/JSM-04-2013-0095
• Languages: English
• ISSNs: 0887-6045

Abstract

Abstract : Purpose: Interactions between customer and service provider during delivery of a service is termed as "service-encounter". The technology that enables service delivery without customer having a face-to-face service-encounter is known as "self-service technology" (SST). Froehle & Roth described five different ways in which technology can be used in service-encounter. One of the ways, known as Technology-Facilitated Service (TFS), requires the simultaneous existence of three entities - customer, technology and service provider - during a service-encounter. Unlike SST, in TFS customer, technology and service provider must co-exist for the completion of the service. While most previous researches have focused on the study of SST, this research studies the factors affecting the customer's 'Intention to Adopt TFS' (I-TFS) and a conceptual model has been proposed. Design/methodology/approach: The factors affecting I-TFS can be divided in two categories: (a) Human-Technology Interaction (H-T I) & (b) Human-Human Interaction (H-H I). Although, existing literature has dealt with factors related to H-T I, ex: 'ease-of-use' and 'perceived-usefulness', the author tries to draw attention to H-H I variables, ex: 'facilitating-conditions', which are potentially significant but have remained fairly untouched. For the study participants were drawn from a target market where a TFS was operational. A scientifically developed survey was used to collect data from 222 participants. Structural Equation modelling (SEM) was used to analyze the conceptual model. Findings: The results strongly suggest that while H-T I factors are important, H-H I factors are equally critical during service delivery. H-H I factors become especially more relevant than H-T I in developing countries. Research limitations/implications: The study strongly suggests that attitude towards the human element i.e. service provider/front line employee is an important factor that impacts the customer's intention to use technology facilitated service. In the context of emerging economies where organizations provide innovative technology services to suit the needs of the respective populations human representatives are a must to support the service. We conducted this research within one TFS context. Additional studies with more diverse TFS with other consumer groups should be conducted to provide additional support and increase the generalization of both the research framework and findings. Practical implications: The findings of the study are useful to all those firms who are considering the implementation of other TFSs such as tele-medicine or distance education programs. By investigating the main causal variables that have an impact of adoption of TFS, we provide an actionable set of factors to help firms understand and influence TFS adoption behaviour. Originality/value: Research on factors affecting adoption of services has traditionally focused either on interpersonal interactions between customers and service providers (H-HI) or non-interpersonal interactions of customer with technology (H-TI). However, very few have studied dimensions of H-HI and H-TI together to understand their impact on customer's adoption of a service. Considering the need for more research, this study examines the relationships between H-HI, H-TI and their simultaneous impact on consumer adoption of services.