Wine Brand Category Choice and Confucianism: A Purchase Motivation Comparison of Caucasian, Chinese and Korean Consumers

Abstract

Immigrants are an important demographic group who are increasingly targeted as consumers by the wine industry in Australia and other Western markets. These markets are often not homogenous as intra-national diversity has created a complex market place in many Western key markets. In this study, wine brand category choice for Chinese and South Korean consumers living in Australia was probed and contrasted with the choices of Caucasian consumers. Three purchase scenarios, namely self/household-consumption, social entertainment-use and gift giving were presented to 511 consumers through a shopping mall intercept using a paper-based questionnaire. Separate models were developed to distinguish preferences for Australian and French wine. Backward deletion regression analysis was used to arrive at the most parsimonious models. A comparison of three research models, namely a marketing model, a Confucian Consumption Behaviour Component (CCBC) model and a Hybrid Model were tested. We found that the hybrid model (i.e. a combination of marketing variables and CCBC variables) has the highest explanatory power for consumers' wine brand category choice. Different ethnic groups have different wine brand category choice for different purchase scenarios. Our findings provide theoretical implications for ethic marketing research and brand category choice, and we also offer insights for wine makers to better position their products for all markets characterised by intra-national diversity.

Competitiveness and workforce performance: Asiavis-à-visthe “West”

“…workforce. The study found evidence of Confucian Heritage Cultures (Lee, 1996;Monkhouse et al, 2013;Yao et al, 2015) with China, Japan and Korea distinct from the non-Confucian Asian countries in the study (India and Indonesia). As such a new term: Confucian Orbit is introduced for Korea, China and Japan, countries where performance has dramatically improved and reached, if not superseded, the West.…”

Contributions from Literature for Understanding Wine Marketing

“…Government regulations implemented around the world are another area many stakeholders should take into account when designing any wine marketing plan [41]. Wine marketing provides a crucial contribution to the dynamics and performance of the sector around the world; however, its design is affected by several factors [42][43][44][45], where scientific research brings fundamental insights [46][47][48]. In any case, the social and cultural dimension of the wine should also be considered and explored within wine marketing plans [49,50].…”

“…December 2019 [105] A large portion of iGen (21)(22)(23)(24) and millennial (25)(26)(27)(28)(29) prefers sparkling wine fairly or a little sweet (54 and 46%, respectively). Millennial (30)(31)(32)(33)(34)(35)(36)(37)(38)(39), GenX (43)(44)(45)(46)(47)(48)(49)(50)(51)(52)(53)(54), and boomer (55-73) prefer sparkling wine somewhat or very dry (50, 66, and 76%, respectively).…”

“…February 2020 [107] Millennial (26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43), GenX (44)(45)(46)(47)(48)(49)(50)(51)(52)(53)(54)(55) and boomer (56)(57)(58)(59)(60)(61)(62)(63)(64)(65)(66)(67)(68)(69)(70)(71)(72)(73)(74) are the generations with higher frequency wine consumption.…”

“…Wineries Tourism Quality New Alcohol [51] 0.000 0.009 0.000 0.005 0.000 0.009 0.000 0.006 0.000 0.000 0.000 0.000 0.005 0.000 0.000 0.000 0.000 0.000 0.000 [38] 0.000 0.000 0.019 0.003 0.058 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.010 0.000 0.000 0.000 0.000 0.049 0.000 [26] 0.000 0.000 0.000 0.000 0.000 0.026 0.008 0.000 0.000 0.011 0.025 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.000 [45] 0.042 0.000 0.000 0.032 0.000 0.034 0.000 0.000 0.000 0.000 0.000 0.000 0.011 0.000 0.000 0.000 0.000 0.000 0.000 [28] 0.000 0.009 0.000 0.003 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002 0.000 0.000 0.000 0.000 0.000 0.000 [27] 0.000 0.018 0.000 0.003 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002 0.000 0.000 0.000 0.000 0.000 0.000 [40] 0.000 0.000 0.019 0.008 0.000 0.000 0.008 0.000 0.000 0.011 0.000 0.000 0.002 0.013 0.000 0.000 0.000 0.012 0.000 [50] 0.000 0.018 0.010 0.000 0.000 0.000 0.008 0.011 0.000 0.000 0.013 0.000 0.008 0.000 0.000 0.000 0.000 0.000 0.000 [32] 0.010 0.000 0.000 0.003 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.007 0.007 0.000 0.000 0.000 0.000 0.000 0.000 [29] 0.000 0.000 0.010 0.003 0.000 0.000 0.008 0.000 0.000 0.000 0.000 0.000 0.003 0.000 0.000 0.000 0.000 0.000 0.000 [35] 0.000 0.000 0.057 0.003 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002 0.013 0.000 0.000 0.000 0.000 0.000 [44] 0.000 0.009 0.010 0.008 0.000 0.017 0.000 0.000 0.000 0.000 0.013 0.000 0.005 0.000 0.000 0.000 0.000 0.000 0.000 [48] 0.000 0.000 0.000 0.003 0.000 0.026 0.025 0.011 0.000 0.000 0.000 0.015 0.004 0.000 0.000 0.000 0.000 0.000 0.000 [43] 0.000 0.000 0.000 0.013 0.008 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002 0.000 0.000 0.000 0.000 0.012 0.000 [31] 0.042 0.009 0.010 0.016 0.017 0.017 0.000 0.006 0.000 0.011 0.000 0.015 0.011 0.000 0.007 0.000 0.029 0.012 0.000 [49] 0.000 0.018 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.013 0.000 0.007 0.000 0.000 0.008 0.010 0.000 0.000 [37] 0.000 0.000 0.000 0.000 0.000 0.026 0.000 0.006 0.000 0.000 0.000 0.000 0.002 0.000 0.021 0.008 0.000 0.000 0.000 [24] 0.010 0.000 0.000 0.005 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002 0.000 0.000 0.000 0.010 0.000 0.000 [42] 0.000 0.018 0.000 0.011 0.000 0.000 0.008 0.000 0.000 0.000 0.000 0.000 0.005 0.000 0.000 0.000 0.000 0.000 0.000 [25] 0.000 0.000 0.000 0.024 0.000 0.009 0.000 0.000 0.000 0.000 0.013 0.000 0.003 0.000 0.000 0.000 0.000 0.012 0.000 [30] 0.000 0.053 0.000 0.003 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002 0.000 0.000 0.000 0.019 0.000 0.000…”