Australasian Marketing Journal

The main objectives of this study are twofold: (1) to gauge the expressions of loyalty toward a service provider, (2) to identify possible transformations of loyalty in the contractual service settings. Using an integrative theoretical perspective, the study presents a more holistic understanding of the dynamics of loyalty transformation taking a processual view. Following an interpretive research approach, we conducted twenty-eight semi-structured interviews with customers and managers of major mobile telephony service providers. The findings confirm that customer loyalty can transform into various states: (1) fanaticism, (2) stage of transition, (3) point of disinterest, and (4) state of betrayal. Moreover, it is determined that customers could express their loyalty to the service provider in several ways signifying their concern, advocacy, rituals, identification, beliefs, and nostalgic feelings.

This study aims to examine why online consumers watch Mukbang, a type of South Korean online entertainment show, by exploring the antecedents of consumers’ attitude toward Mukbang from a cross-cultural perspective. Data was collected from 114 Asians and 129 Caucasian participants using a self-administered questionnaire online. Data was then analysed using structural equation modelling. Similarities and differences were noted for both the samples. The findings show that Asians tend to watch Mukbang due to host attractiveness and social normative influence, while Caucasians watch such shows due to host attractiveness, perceived novelty and social normative influence. Practical implications are provided for traditional and digital marketers, advertisers and broadcast jockeys so they are better equipped with insights on online consumer behaviour, marketing strategies and conceptualisation of videos.

This paper seeks to empirically examine diffusion models and Google Trends’ ability to explain and nowcast the new product growth phenomenon. In addition to the selected diffusion models and Google Trends, this study proposes a new model that incorporates the two. The empirical analysis is based on the cases of the iPhone and the iPad. The results show that the new model exhibits a better curve fit among all the studied ones. In terms of nowcasting, although the performance of the new model differs from that of Google Trends in the two cases, they both produce more accurate results than the selected diffusion models.

Business and consumer buying behaviour has changed dramatically in recent time; a fact that is not lost on selling organisations when considering how best to recalibrate salesperson performance measures in response. However, a contemporary, systematic review of the academic literature concerning those most effective salesperson performance factors is markedly absent. This study joins a long line of investigatory efforts regarding the characteristics and habits of successful salesperson performance by adopting meta-analysis techniques to investigate the salesperson performance literature, content-analysing over 250 published articles from 1986 to 2017 and synthesising the findings into a new salesperson performance typology. The study finds that personal, organisational, co-worker, buyer and situational dimensions are responsible for increasing salespersons’ performance. Additionally, this work offers a parsimonious overview of current key salesperson performance research as well as a clear agenda for future salesperson performance research.

Consumers automatically associate animals and experiences with certain brands and products. The capability of surfacing the “automaticity of being” (Bargh & Chartrand, 2000) using metaphoric research tools provides a paradox—consumers tell researchers deeply held beliefs about the consequences of associating brands and products with scant editing of their thoughts; consumers may tell more about themselves through metaphors than they would otherwise be willing to share. The study here is a primer on this indirect approach for collecting consumers’ conscious and nonconscious thoughts about countries, brands, and industries. Using zoomorphic forced metaphor-elicitation, long interviews of eight Indian consumers uncover insights about their feelings about products from China, New Zealand, the United Kingdom, and the United States. The findings demonstrate collecting rich data using metaphors offers new perspectives on how consumers view foreign products. Findings show mental processes in which consumers trust brands even if they are manufactured abroad. When brands are not identified, well-known industries associated with individual countries influence product choices. These findings suggest gestalt brand and country images explain aspects of consumer attitudes about foreign products.

Kim et al. (2018) raised four issues along with possible remedies that could affect statistical conclusions from mediation analysis. The issues addressed were: omitted mediators, reverse mediation, multi-item measures, and experimental methods. This prompted an insightful response from Thoemmes and Lemmer (2019), who largely agreed upon and further developed three of the issues. But there was disagreement concerning the appropriateness of conducting reverse mediation, their argument being the likelihood of returning equivalent models. Here, it is acknowledged that mediation analysis should be theory-driven and not conducted just to see which model is better. Further, in some contexts such as mediation analysis based on survey data the benefits of conducting reverse mediation are likely to be minimal. However, it is not uncommon to measure the mediator after having measured dependent variables, particularly in experimental settings. Hence, it is argued here to check for artificial mediation by reversing the arrows. A simulation is conducted to support this argument.

This research note provides technical aspects of qualitative comparative analysis (QCA) for scholars seeking to better understanding the potentiality of the method. The note answers a few frequently asked questions about contrarian case analysis and data calibration and show how to implement these two relevant steps technically and appropriately. This study provides useful details and technical explanations on why and how to turn case data by using contrarian case analysis and how to calibrate data into fuzzy sets.