The conceptualisation and measurement of consumer authenticity online

Abstract

Electronic commerce has become a global phenomenon. “Online is now becoming an integral part of any country’s economy ……..it is important for businesses to understand where the future opportunities will be” (Interactive Media in Retail Group, 2012). By 2017 60% of all U.S. retail sales will involve the Internet in some way, either as a direct electronic commerce transaction or as part of a shopper’s research on a laptop or mobile device (internetRetailer.com, 2014). With worldwide electronic commerce increasing exponentially, there are significant opportunities available for businesses that are competent in the online environment (eMarketer.com, 2013).

However the inauthenticity of online; brands, services and communities hinders the potential efficacy of electronic commerce in New Zealand and probably the World. The research reveals that consumers that can appropriate authenticity in their online; brands, community, and service will be more likely to engage in positive consumption behaviour. Moreover, with online consumer purchases in 2014 involving 3.5 billion global consumers spending $1.5 trillion euro’s the online retail opportunities are significant (eMarketer.com., 2013).

Yet while there have been numerous studies focused on various aspects of electronic commerce, a review of academic research identifies a knowledge gap in the conceptualisation and measurement of consumer authenticity online.

In order to fill that deficit a literature review is conducted. The literature review reveals the following nine primary constructs of authenticity: Approximate (Iconic), Identification, Production, Situation, Social, Moral, and Pure (Indexical) Authenticity, Virtuous and Practical Self and Interpersonal Self-authentication.

The research uses these constructs (in addition to: consumption behaviour and its two constructs - rational and experiential thinking) to build a conceptual model and develop hypotheses to explain consumer authenticity online.

In order to test the theoretical model a survey instrument is constructed using measures selected from academic articles based on their ability to validly measure the constructs in the model. The survey is then used to collect data from five hundred randomly selected online consumers from the wider Auckland district of New Zealand. The data collections method is via surveys administered on a face-to-face basis.

After data collection and cleaning a two-stage data analysis procedure begins: The first stage comprises descriptive data analysis to identify the trends of the dataset. The second stage or model development stage uses a two-phase process of confirmatory factor analysis to develop the model and determine its validity, and structural equation model analyses to test the hypothetical relationships. This is achieved by measuring the hypotheses of the original model and then modifying the model to better represent the characteristics of the dataset as advised by the AMOS analysis output.

Finally, both the accepted and rejected hypothesised relationships conceptualised in the alternative SEM model are analysed from; theoretical, consumption modes and consumer interpretation perspectives and the managerial implications determined.