Digital Quality Dimensions

In order to recognize the critical role of service quality in digital contexts, many researchers have initially adopted SERVQUAL to measure service performance, but they face enormous challenges because of the reliability and validity of the generic SERVQUAL measures and lack of Information Technology (IT) artifact in the Information Systems (IS) context (Jiang et al. 2000; Kettinger and Lee 1994; Orlikowski and Iacono 2001). Critics in IS, for example, Van Dyke et al. (1997) highlight that the confusion of SERVQUAL’s expectation component and its difference score measurement approach make the model perform poorly in establishing discriminant validity for those five dimensions. Although such studies are important in explaining IT usage, they are relatively weak in capturing human–technology interactions and provide limited guidance for system designers (Nelson et al. 2005). Orlikowski and Iacono (2001) have highlighted that such IT research, which employs a “proxy view” of technology, has lost its connection to the field’s core subject matter — the IT artifact itself. Besides, some researchers found that when applying the SERVQUAL model to e-services’ collapse, most dimensions lose their reliability and validity (Gefen 2002). Overall, the extant literature on the SERVQUAL model in IS does not focus on human–technology interaction (system quality), interpersonal interaction and outcome (or information) benefits separately to measure overall IS service quality.

Service quality theories in a web-based electronic service strongly influence mobile service because in both cases, services are delivered over an electronic platform. Several powerful models have been developed to address the issues of service quality over this platform, such as SITEQUAL (Yoo and Donthu 2001), eQUAL (Barnes and Vidgen 2002), web quality (Aladwani and Palvia 2002), E-S-QUAL (Parasuraman et al. 2005). In order to overcome the pitfalls of the earlier models, Parasuraman et al. (2005) develop the E-S-QUAL or electronic service quality model to measure service quality of web-based electronic services. The uniqueness of the E-S-QUAL model lies in its capacity to capture perceptions on human–technology interaction for any web-based e-service platform (Sousa and Voss 2006). Similarly, (Fassnacht and Koese 2006) introduce quite a broad model by focusing on online electronic networks. They proposed to measure service quality through environment quality, delivery quality and information quality. However, this model does not address the unique characteristics of the mobile platform (e.g., network quality, interaction quality) and it is again restricted to measuring service quality of all web-related services.

Although service quality failures are frequently related to back office operations (i.e., information systems), most web-based electronic service quality studies are primarily based on front office (i.e., quality of interaction between the end-user and the virtual platform). Since overall customer satisfaction is strongly influenced by service quality at all moments of contact, few studies (e.g., Sousa and Voss 2006) integrate both front office and back office operations in evaluating service quality. In this case, Sousa and Voss (2006) proposed a powerful service quality model focusing on system quality, interpersonal quality and interaction quality to measure any service which contains both electronic (e.g., mobile channel) and physical components (service provided by persons). Therefore, they proposed the dimensions of the E-S-QUAL model (Parasuraman et al. 2005) to measure system quality and the SERVQUAL model (Parasuraman et al. 1985, 1988) to measure interpersonal interaction quality for any service over an electronic platform. However, Sousa and Voss (2006’s) conceptual model was not empirically tested and, again, it was proposed as a generic model for all electronic services ignoring the contextual influence of service quality settings. In the case of mobile services, Chae et al. (2002) develop a quality model focusing on the characteristics of a generic mobile platform. They identified four primary quality dimensions and these were connection quality, content quality, interaction quality and contextual quality.

In addition to web and mobile, Social Media (SM) or Social Networking Sites (SNS) are affecting the lives of individuals across the globe in numerous ways which include but not limited to the way people communicate, socialize, learn, entertain themselves, or even the way they conduct their information search, make decisions and do their shopping (Constantinides and Fountain 2008; Mangold and Faulds 2009; Vollmer and Precourt 2008). These changes forced almost all marketers (e.g. B2B, B2C) to adopt social media as a central element while marketing their products and services. For example, in a recent survey 88.2% of B2C and 93% of B2B firms indicated that they have started social media initiatives and almost half of them fully integrates social media into their business strategies (Holden-Bache 2011; Insites 2011). Kim and Nitecki (2014)‘s research on measuring the quality of social media services by adopting and modifying E-S-QUAL approach suggests four dimensions; namely, efficiency, system availability, privacy and fulfilment and two endogenous constructs; namely, perceived value and loyalty intentions. While defining the dimensions of online social value by utilizing Social Exchange Theory, Hu et al. (2015) suggests that utilitarian benefits (such as relational and informational), hedonic benefits (such as enjoyment and curiosity fulfilment), information risk and effort work as inputs in the assessment of online social value.

Organizations are increasingly linked to the proliferation of e-services, which are embedded in omnichannel environment, combining the web with physical facilities i.e. phone and other channels of service delivery. Evidence from different literature argue that companies which integrate their physical presence with internet based channels are more successful compared to companies operating in a single channel environment (Gulati and Garino 1999; Michael 2001; Vishwanath and Mulvin 2001). A seamless customer experience within and across physical and virtual channels reflects the integration quality of multichannel services.

Sousa and Voss (2006) develop a conceptual framework for multichannel service quality. They have illustrated the distinguishing factors of three service quality components; namely, virtual, physical and integration quality. Sousa and Voss (2006) argue that even though an organization offering good level of virtual and physical quality, they may lack in terms of the overall perception of multichannel service offering. Hence, they have proposed “Integration Quality”, a third component of quality in multichannel services. Sousa and Voss (2006, p. 359) define integration quality as “the quality of the overall service experienced by a customer, encompassing all the existing physical and virtual components”. The types of channels range from in-store (e.g., hotel reception desks, and retail stores), to digital (e.g., phone-based customer contact centres and airline self-check-in kiosks), and to virtual channels (e.g., the Internet and smart phone apps).

The first dimensions of integration quality proposed by Sousa and Voss (2006) is “Channel-Service Configuration”. This refers to the quality of service combination of the existing channels. The first sub-dimension of channel service configuration is breadth of channel choice that refers to the degree to which customers can chose and accomplish specific tasks through alternative channels. The second sub-dimension proposed by Sousa and Voss (2006) is transparency of the existing channel-service configuration which refers to the degree to which customers are aware of the existence of all available channels and of differences between service features across different channels.

The second dimension of integration quality proposed by Sousa and Voss (2006) is “Integrated Interactions” which refers to the consistency of service provided through all the channels. Integrated interactions quality dimension has two components. The first component is content consistency referring to the consistency of both outgoing and incoming information between the service provider and the customer. The second component is process consistency referring to the consistency between the relevant and comparable process aspects of the front offices linked with the different channels.

Extending the work of Sousa and Voss (2006), Banerjee (2014) reports several dimensions of integration quality using a qualitative, multimethod case research within a banking context. The study explores the misalignment between the organizational perception and the design of a multichannel system and customer expectations of a multichannel service experience in banking. The dimensions of integration quality proposed by Banerjee (2014) include channel service configuration quality (e.g., breadth of channel choice, transparency of channel-service configuration, appropriateness of channel-service configuration) and integrated interaction quality (e.g., content consistency, transaction data and interaction data integration, process consistency, within channel and across channel integration). Figure 1 illustrates a conceptual framework of integration quality dimensions proposed by Sousa and Voss (2006) and Banerjee (2014).

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