Introduction

Background of the Study

The growth of mobile devices in terms of their role in the global marketplace is unstoppable. For example, by 2020, 99.3% of all internet users in China were considered to use mobile devices to exchange information online (source: Statista). In China, 58% of the population owns a mobile phone, and only 3% does not use a smartphone. Another striking example of this is that 70% of all media consumption time is spent on smartphones (source: e- Marketer). The explosion of high-speed mobile network services in China and the entry of an abundance of providers into the market have already enhanced fintech in other online product markets, and the state of smartphone usage in China makes it a valuable sector for the future of the global market.

The smartphone is no longer just a means of communication but also a hub for payment methods, a medium for taking photos and videos to support personal lifestyles, an archive for storing materials and an indispensable gadget that is ‘always within 30 centimetres of your body’ (Nakamura 2015). We are living in an age in which it is no longer sufficient to consider the smartphone only as a means of mobile communication. For example, we should also use the behavioural patterns of smartphone users to examine their purchasing intentions and behaviour.

In the face of the unprecedented COVID-19 crisis, China must take the lead in accelerating the development of the market for smartphones, a technology-driven commodity with a strong future, and in developing marketing strategies that meet consumer needs.

Research Rationale and Aim of the Study

As people have been restricted from interacting face to face and physically moving around the world due to the COVID-19 pandemic, smartphones have been used to frequently communicate with family and friends virtually, to communicate via Social Networking Services (SNS) and to send out information via Instagram and other social media platforms, including videos and photos.

At the same time, Generation Y (Gen-Y), the powerhouse born in the 1980s and 1990s driving China’s consumption, pursues personalised experiences, especially through product purchases, and has begun to exhibit unique behavioural patterns based on antecedent factors that differ from the behavioural principles of traditional management studies emphasising brand loyalty (Kim et al., 2019).

In addition, it is argued that people are currently more likely to share material products and enjoy their time using them than to become obsessed with owning them. In other words, they are less likely to be attached or obsessed with the products themselves, and their interests are more likely to be short-lived and transferable. This new pattern of consumption has been discussed as liquid consumption and is one of the issues that the marketing strategy sector needs to be aware of in the future (Atanasova, 2021; Bardhi & Eckhardt, 2017; Bardhi et al., 2012).

However, up to now, almost no research on the factors that determine smartphone use in China has focused on the joyfulness that comes from having a smartphone, an issue that cannot be overlooked. In this study, we develop findings on this topic through quantitative data verification.

Literature Review

Smartphones and Lifestyle

Understanding consumers’ tendencies and preferences for products and services is highly necessary and important for competition. In the current disruptive market environment, it is imperative to measure consumer attitudes and awareness among the growing smartphone market to understand the key factors that motivate them to make purchases. One of the most recent research conducted, Cambra-Fierro et al., (2021) discussed it is critical for businesses to understand how to handle adaptability in customer experience which is a key factor for customer retention.

Based on more than 300 interviews with university students, Park (2019) evaluated smartphones as familiar gadgets that can be used anytime and anywhere. The smartphone users perceive which smartphones are not just communication tools but a communication hub for making powerful decisions about the trends and fashion and also as a tool to interact with others which are embedded in their lifestyles (Lee et al., 2019).

From a broader perspective, communication and relationships can be discussed in a social context. Putnam (2000) argues that there is a shift towards individualism in society and that forms of mass media, such as television, are having an impact on this. At the same time, some researchers have reported on the various impacts the Internet and new technologies are having on social cohesion. When discussing the impact of mobile phones and its relation to users’ lifestyles, their impact on social interaction should not be overlooked. (Rotondi et al., 2017). Moreover, as Baraković et al., (2020) discussed connectedness via ICT measure can be of impact on successful ageing and well-being of population. Siepmann & Kowalczuk (2021) discussed the role of emotional factor for continuous usage of smartphone with potential contributions for health and fitness for elderly users.

China’s New Powerhouse of Mobile Gadgets: Customised and Personalised Smartphone Use

Although smartphones are no longer a luxury but an everyday item, especially for young people, they have undergone a series of technological innovations, and their advanced features and design have stimulated consumers to purchase new ones. This suggests that smartphone purchase behaviour may provide a useful test bed for examining the purchasing behaviour of young people towards technology-intensive products to determine which attributes are most likely to stimulate consumer purchase.

In their analysis of luxury goods purchasing in China, Kim et al., (2019) found that the post-80s (born in the 1980s) and post-90s (born in the 1990s) generations were the most likely to purchase luxury goods. In their analysis of luxury goods purchasing in China, Kim et al., (2019) also found that the post-80s and post-90s generations accounted for 43% and 28% of luxury goods buyers, respectively, and their contributions to total luxury goods consumption in China reached 56% and 23%, respectively.

Whether smartphones are a luxury product or a commodity is a matter of debate, but compared to the feature phones of the past, they have an extremely high degree of technology integration, design, operability and affinity for information processing, as well as a relatively high price. As for the use of highly functional and personalised experiences with gadgets, Chinese consumers born after the 80s and 90s emphasise the importance of ‘enjoying a unique atmosphere, expressing one's own personality and being different from ordinary people’, and they no longer expect only a single fundamental function (in the case of smartphones, communication) from a gadget, instead perceiving the gadget as part of a lifestyle (Kim et al., 2019; Nakamura 2015).

Analytical Model with Measurements

Innovativeness: Smartphones as an Aggregated Technology

Research by Holak & Lehmann (1990) shows that the use of innovative products is based on usage and images of previous products, which can lead to higher acceptance of and more willingness to own the innovated product. Sultan (1999) suggest that compatibility is another important factor, including the present operating system environment, changes in the software interface and the degree of previous experience, among other factors. For potential consumers comparing a smartphone and previous feature phone, if the degree of compatibility in operation method, extension device, hardware and operating system is higher, they will be more likely to adopt it.

Convergent products have recently been receiving increasing amounts of attention (Oe & Yamaoka, 2020; Lee, Lee & Yoo, 2000). In the consumer electronics industry, smartphones and other convergent technological devices are significant drivers of industry growth (Park & Kim, 2020), and this trend must have had an influence on consumer attitudes towards the related products.

In fact, there are many different combinations of functions and features in each smartphone product. Many companies have aimed to find a way to provide diverse functionality in a single product (Kim et al., 2019). Functionality is also one of factors that affect customer’s decisions in the market. Hence, its impact should be analysed as a theme in related research. As Holak & Lehmann (1990) predicted over 30 years ago, it is not only that innovative products increase the convenience of users; in addition, through the provision of various functions, users develop diverse customised methods of use, creating unique usage patterns that match individual lifestyles (Kim et al., 2019).

In this way, the functional sophistication of the products we buy is not limited to the evaluation of their usability; because they are innovative, they also support the diversification of individual experiences and the creation of personal stories. In other words, innovation goes beyond the realm of usability support and creates avenues for consumer customisation that influence their purchasing behaviour.

Personalised Experiences with Service

As noted above, innovative products not only enhance user convenience but also increase the attractiveness of consumer goods through the provision of a range of features that allow users to develop diverse and customised methods of use and create unique usage patterns that match their individual lifestyles.

During the economic recession over the last few years, the major manufacturers of everyday consumer goods have managed to ensure sustainability by introducing luxury versions or premier versions of commodities to the market. In other words, premiumisation has been used as a strategy to secure revenue growth (Murmura et al., 2021). For the consumer goods industry, this means making even the most mundane products look attractive, capturing the imaginations of consumers and creating invisible value in the form of products that are tailored to individual lifestyles. In line with the discussion, the concept of customer experience should be sought more carefully in the consumer study: Anshu et al., (2022) discussed the impact of customer experience on attitude and repurchase intention from a scope of value co-creation aspects of business and consumers interactions.

At a time when the COVID-19 pandemic has cut off options for variety of choices for consumers, it has also been pointed out that there is increased demand for luxury products within reach, such as expensive goods that bring pleasure to life (MacDonald & Dildar, 2020). There have been several studies on the so-called ‘lipstick effect’, which refers to the stimulated consumption of petit luxury goods during the economic crisis, and the factors that stimulate consumption have been examined. However, purchasing behaviour regarding smartphones, which have sophisticated and innovative features and are more expensive than previous feature phones, has not been discussed in terms of the lipstick effect in this context.

In addition to the current behaviour of Chinese consumers born after the 80s and 90s, which emphasises personalised experiences based on individual lifestyles, the economic and social stagnation brought about by the COVID-19 disaster may also have had an impact on smartphone purchasing behaviour through the psychological route described by the lipstick effect. In addition to the current focus on personalised experiences based on individual lifestyles that characterises the consumer behaviour of the post-80s and post-90s generations in China, the lipstick effect may also influence smartphone purchasing behaviour, as consumers aim to surround themselves with glamorous, fun and fashionable products in a climate of stagnation and uncertainty.

An analysis through the lens of the desire to feel radiant through fashionable products close at hand may be useful for examining smartphone purchasing behaviour in an era of symbiosis with COVID-19. In addition, it is likely that this argument could be confirmed in empirical research by substituting in fashionableness, the third factor generated by the previous factor analysis.

Fashionableness of Gadgets

Ramirez-Correa et al., (2020) discussed that young people are more attracted to gadgets for their fashionableness than for their basic functions in everyday life: They also pointed out that the success of mobile gadgets reflect the lifestyles of young, single, independent people and analyse the impact of the urbanisation process on innovation and fashion in the use of mobile phones, also analyse preferences for smartphones in the context of flaunting. Generally, it is understood that there is a positive relationship between customer satisfaction and product fashionableness through the channel of product ownership.

It should then be asked: What happens when we apply this concept to the Chinese smartphone market? As already mentioned, China is developing rapidly, both domestically and internationally, and has seen the rise of a middle class, with post-80s- and post-90s-generation buyers expanding their purchasing power and accelerating consumption behaviour on digital platforms (Kim et al., 2019).

Today, the smartphone industry is in a constant state of progress, and its development is accelerating. Compared to feature phones (traditional mobile phones), smartphones appear simpler and more fashionable. They are also available in different colours, are thinner and are more innovative. In order to gain consumer acceptance at the launch of a new product, suppliers include as many features as possible in a mobile phone and give it a sleek look.

This third factor is also easier to understand in light of the behavioural pattern of liquid consumption exhibited by Gen-Y, who have short-term interests and are less attached to things. In other words, they are not attached to possession but to the pleasure of having, and they prefer the pleasure of time gained rather than that of material happiness. In light of the behavioural pattern of liquid consumption exhibited by younger generations, which is associated with enjoyment of time, short-term interests and less attachment to things (Atanasova, 2021; McCoy et al., 2021), it can be assumed that the fashionableness of accessory-like products, which can be worn to feel good or a little bit happy, influences purchase decisions rather than their function as tools for communication.

Hypothesis Construction

Based on the above literature review, we hypothesised that consumer behaviour in the smartphone market is influenced by joyfulness. We further set innovativeness, personalised experience and fashionableness as hypothetical factors contributing joyfulness, and in Study 1, we quantitatively confirmed whether these three factors contributed to joyfulness in smartphone use.

The purpose of this study was to understand the phase of cognition of smartphone use among consumers born in the 80s and 90s, who are the driving force of consumption in China. Bearing in mind that Information and Communications Technology (ICT), including smartphone devices and services, can have a significant impact on lifestyles and socioeconomic activities, we pay particular attention to the three mentioned factors. Then, in Study 2, we closely compare how the three factors related to the first three identified hypotheses affect consumers’ smartphone purchase intentions in a sample group depending on age group.

H1: Innovativeness contributes to joyfulness in smartphone use.

H2: Personalised experience contributes to joyfulness in smartphone use.

H3: Fashionableness contributes to joyfulness in smartphone use.

H4.1: Innovativeness has an impact on purchase intention.

H4.2: Personalised experience has an impact on purchase intention.

H4.3: Fashionableness has an impact on purchase intention.

These hypotheses were used to create the conceptual framework shown in Figure 1.

Methodology

Approach

This study uses a quantitative analysis method. In order to test the hypotheses developed from the literature review, a questionnaire was designed to collect the phase of awareness and evaluations regarding smartphone use among Chinese smartphone buyers born in the 80s and 90s. Responses were collected from the relevant consumers using an online survey.

In addition to demographic information, such as gender, year of birth and income, and a group of questions on intentions regarding smartphone purchase, the questionnaire collected answers to a total of nine questions on the three latent factors drawn to reflect the hypothesis testing (innovativeness, personalised experiences and fashionableness) according to a five-point Likert scale. The obtained data were subjected to cleaning, including the maintenance of missing values, and a sample size of 366 was finalised.

Analytical Strategy

The data collected were analysed using SPSS (version 28). Descriptive statistics, confirmatory factor analysis and reliability testing of the factors generated were conducted, followed by hypothesis testing based on the three generated and confirmed factors. Hypothesis testing was conducted using Structural Equation Modelling (SEM) to test the relationships among the three factors contributing to joyfulness in consumers’ smartphone use.

Findings and Analysis

Descriptive Analysis

To determine the profile of the data collected, a descriptive statistical treatment was first applied at the beginning of the study to ensure that the dataset used for the analysis was balanced among the attributes and in accordance with the aims of the study. The descriptive statistics on the dataset are shown in Table 1.

Table 1 Descriptive Statistics of the Dataset
Demographic profile		Frequency	Percent	Cumulative Percent
Age group
	80's	162	44.3	44.3
	90's	204	55.7	100.0
	Total	366	100.0
Gender
	Male	176	48.1	48.1
	Female	189	51.6	99.7
	Don't want to respond	1	0.3	100.0
	Total	366	100.0
Monthly income
	U500	51	13.9	13.9
	501-1000	78	21.3	35.2
	1001-2000	49	13.4	48.6
	2001-3000	48	13.1	61.7
	3001-4000	59	16.1	77.9
	4001-5000	41	11.2	89.1
	5001-6000	19	5.2	94.3
	6001-8000	15	4.1	98.4
	O8001	6	1.6	100.0
	Total	366	100.0

Confirmatory Factor Analysis

Next, to check the factors generated, we applied a principal component analysis to the response data using a five-point Likert scale regarding the phase of expectations and perceptions and purchase intentions towards smartphones (Table 2).

As a result, three factors corresponding to the three antecedent factors assumed in the hypothesis were identified: Factor 1 Innovativeness (functionality and innovative attributes); Factor 2 Personalised experience; Factor 3 Fashionableness; Factor 4 Purchase intention.

Table 2 Factor Analysis Results and Cronbach’s Alpha Values for the Generated Factors
	Component
	1	2	3	4	alpha	New Alpha
11-1 Product attributes and functionality	0.699	0.091	-0.136	0.301	0.808	0.808
11-2 Design and usability	0.694	0.089	0.241	0.078
11-3 Variety of peripherals	0.636	0.204	0.124	-0.053
11-7Iinnovative featurese	0.610	0.064	0.335	0.186
11-6 Enhancing personal characters	0.164	0.820	0.072	-0.084	0.819	0.819
11-5 Good experiences of use	0.080	0.819	0.067	0.135
11-4 Comfortable and easy to use	0.187	0.543	0.201	0.354
11-8 Happy to own fashionable gadgets	0.212	0.054	0.832	0.061	0.752	0.752
11-9 Attracted by fashionableness	0.104	0.172	0.746	0.124
9. I would choose the same smartphone next time	0.071	0.105	-0.012	0.737	0.725	0.725
8. Satisfied with the current gadget of smarphone	0.159	0.026	0.216	0.663
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 5 iterations.

It should be noted that the three generated factors were found to explain 58.5% of the total data. The three factors corresponding to the three antecedents assumed in the hypothesis also comprised four observed factors (for innovation), three observed factors (for fashion) and two observed factors (for service quality and experience), respectively. All three factors had a Cronbach’s alpha above 0.6, confirming their validity (Taber, 2018).

Structural Equation Modelling Analysis

Study 1: Constituent Factors for Joyfulness

First, in Study 1, we used SEM to examine the factors contributing to the joyfulness brought about by smartphone use for three groups: the entire sample, those born in the 80s and those born in the 90s. The results revealed that the GFI of each model was high (above 0.90) and that the model reasonably explained the relationship between the three factors and joyfulness. All other model fit indices also had satisfactory values (Bagozzi & Foxall 1996).

As mentioned in the literature review, Chinese consumers born in the 80s, the 90s and onwards are more concerned with personal experiences and customisation than brand name and purchase products based on lifestyle and self-expression of style. In light of this, we formed a hypothesis on the pleasure of owning a smartphone and tested the impacts of three factors through factor analysis. The results demonstrated that all three factors (innovativeness, personalised experiences and fashionableness) impact the joy felt in owning a smartphone and that each had sufficiently high explanatory power to be considered a major contributor to joyfulness (Figure 2).

Table 3 Path Coefficients of the Sem Analyses for the Three Models (Joyfulness)
ToFrom			All		90's		80's
			Std. coefficient	P	Std. coefficient	P	Std. coefficient	P
Innovativeness	<---	Joyfulness	0.933	***	0.773	***	1.177	***
Personalised Experience	<---	Joyfulness	0.603	***	0.714	***	0.46	***
Fashionableness	<---	Joyfulness	0.715	***	0.806	***	0.621	***
J1	<---	Joyfulness	0.408	***	0.389	***	0.411	***
J2	<---	Joyfulness	0.313	***	0.38	***	0.219	**
I1	<---	Innovativeness	0.516	***	0.518	***	0.523	***
I2	<---	Innovativeness	0.607	***	0.495	***	0.735	***
I3	<---	Innovativeness	0.634	***	0.607	***	0.674	***
I4	<---	Innovativeness	0.484	***	0.385	***	0.582	***
P1	<---	Personalised Experience	0.567	***	0.511	***	0.599	***
P2	<---	Personalised Experience	0.68	***	0.61	***	0.838	***
P3	<---	Personalised Experience	0.649	***	0.531	***	0.817	***
F1	<---	Fashionableness	0.702	***	0.632	***	0.731	***
F2	<---	Fashionableness	0.614	***	0.571	***	0.666	***
Fitness Indexes
Chi square			99.38		66.151		99.892
df			41		41		41
C/D			2.424		1.613		2.436
p			0.000		0.000		0.000
GFI			0.958		0.948		0.913
AGFI			0.932		0.917		0.86
CFI			0.911		0.901		0.879
RMSEA			0.062		0.055		0.094

Table 3 reveals that there were differences in trends between the different segments. For example, when comparing those born in the 80s and 90s, the impact of personalised experiences and fashionableness on joyfulness was greater for the younger generation. However, as discussed above, the three hypothetical contributors to joyfulness had sufficient explanatory power for the entire sample as well as for the 80s and post-90s models. Therefore Hypotheses 1-3 are all supported with statistical significance.

Study 2: Joyfulness and Purchase Intention

In Study 2, we used SEM to investigate the relationship between joyfulness and purchase intention brought about by smartphones using three groups: the entire sample, those born in the 80s and those born in the 90s. The GFIs for all three hypothetical models were high (above 0.90), indicating that the relationship between joyfulness and purchase intention is statistically significant, given the goodness of fit of the models. Other fit measures for the research model included a χ2/degrees of freedom ration of 2.254 (χ2=103.668, df=46); it met the recommended level of 5.0 (Hair et al., 2010). As other results of fitting tests for the all samples, GFI (0.959), AGFI (0.931), and CFI (0.919) are high above the recommended level of >0.90, whereas RMSEA (0.059) also met the recommended level <0.08 (Xia & Yang 2020; Hair et al., 2010).

As stated in the literature review, Chinese consumers born after the 80s and 90s are known to express their lifestyle and personal style through personalisation and customisation. Study 1 suggested that the pleasure of owning a smartphone can be explained by three factors: innovativeness, personalised experience and fashionableness. Still, we need to ask what impact these three factors have on consumers' smartphone purchase intentions. To test hypotheses H4.1 to H4.3, we conducted an SEM analysis.

The results shown in Figure 3 and Table 4 demonstrate that although the model itself was valid, with sufficiently high GFIs and other fitting values, only fashionableness was linked to purchase intention. This finding was common to all three models, for the entire sample and for those born in the 80s and 90s. Despite the finding that all three latent factors are significant components of joyfulness, as made in Study 1, they do not all necessarily have a strong relationship with purchase intention. To summarise, only fashionableness was found to have an impact on smartphone purchase intention among all the sample models. Therefore, only Hypothesis 4.3 is supported, whereas H4.1 and H4.2 are not supported.

Table 4 Path Coefficients of the Sem Analyses for the Three Models (Purchase Intention)
To From			All		90's		80's
			Std. coefficient	p	Std. coefficient	P	Std. coefficient	P
Innovation	<---	Joyfulness	0.875	***	0.831	***	1.031	***
Personalised Experience	<---	Joyfulness	0.604	***	0.827	**	0.408	**
Fashionableness	<---	Joyfulness	0.653	***	0.705	**	0.524	**
Purchase Intention	<---	Innovativeness	0.050	0.681	*	0.783	0.141	0.493
Purchase Intention	<---	Personalised Experience	0.057	0.499	0.081	0.591	0.037	0.744
Purchase Intention	<---	Fashionableness	0.475	***	0.422	*	0.559	**
J1	<---	Joyfulness	0.435	**	0.409	*	0.470	*
J2	<---	Joyfulness	0.331	**	0.364	*	0.249	*
I1	<---	Innovativeness	0.522	***	0.546	***	0.519	***
I2	<---	Innovativeness	0.607	***	0.495	***	0.736	***
I3	<---	Innovativeness	0.630	***	0.592	***	0.676	***
I4	<---	Innovativeness	0.485	***	0.371	***	0.582	***
P1	<---	Personalised Experience	0.573	***	0.532	***	0.599	***
P2	<---	Personalised Experience	0.681	***	0.609	***	0.838	***
P3	<---	Personalised Experience	0.640	***	0.498	***	0.817	***
F1	<---	Fashionableness	0.676	***	0.576	***	0.745	***
F2	<---	Fashionableness	0.636	***	0.626	***	0.654	***
Fitness Indexes
Chi square			103.668		75.885		101.723
df			46		46		45
C/D			2.254		1.650		2.211
p			0.000		0.004		0.000
GFI			0.959		0.945		0.918
AGFI			0.931		0.906		0.861
CFI			0.919		0.898		0.890
RMSEA			0.059		0.057		0.087

Discussion

The hypothesis testing by SEM yielded the following results. First, all three hypothetical factors (innovativeness, personalised experiences and fashionableness) were found to be sufficient explanatory factors of the joyfulness experienced by smartphone users. The first sub-hypothesis (H4.1 ‘innovativeness’) does not show a significant impact on consumers’ purchase intention of smartphone. Similarly, second sub-hypothesis (H4.2 ‘personalised experience’) does not have a significant impact on their purchase intention, either. Whereas the third sub-hypothesis (H4.3 ‘fashionableness’) only indicates it has a significant impact on their purchase intention of smartphone. This is a contradiction to the existing research findings that innovativeness positively influences Chinese consumers' loyalty regarding smartphones (Holak & Lehmann, 1990; Sultan, 1999).

It has been argued that personalised experiences contribute to joyfulness in smartphone use as a function of the various elements of the smartphone, such as product innovation and product fashionableness, together with favourable and high service quality (Komatsu, 2004). With respect to the third sub-hypothesis, fashionableness was a key factor which leads to Chinese consumers’ behaviour in the smartphone purchase, which implies a current snapshot of unique Chinese consumers’ perception and behaviour.

The extent to which the Chinese smartphone industry is able to focus on fashionableness of gadgets would be a key factor in strategic marketing plans in attracting Chinese consumers. Interestingly, Chinese consumers perceive fashionableness aspect of smartphone as the first and foremost important factor as the top construct of joyfulness, therefore, it is critical for the smartphone businesses to focus and monitor the powerful Chinese consumers’ behavioural change in the future to sustain their businesses.

Customer Experience (CX) has evolved into a top priority for business managers worldwide, being a key factor in the long-term success of companies. CX research is also commonplace among academics and marketers. As discussed by Imhof & Klaus (2020), despite the fact that CX research is popular, the lack of agreement on the meaning and foundations of CX and the failure to develop sufficient evidence and tools to show that CX plays an important role in company success is worrying. They also point out that the fact that many researchers use proxy variables with little relevance to consumer behaviour for CX observables, such as service quality, customer satisfaction and net promoter score, mean that research in this area has failed to rise to the level of presenting concrete suggestions.

As a result, there is a need to propose more comprehensive and feasible measurement models and scales to understand CX as an important factor in consumer behaviour. Imhof & Klaus (2020) have also empirically demonstrated that CX is a much better predictor of consumer behaviour than customer satisfaction. As their leading-edge research suggests, there will be an increasing need for research on CX in the future, and it is essential for the field of marketing management to closely identify and discuss consumers’ purchase intentions for specific products at the micro level, as indicated by the results of this pilot study.

Conclusion

Theoretical Contributions

This study quantitatively examines the factors that lead people to purchase smartphones, based on a dataset collected from 366 people born in the 1980s and 1990s in China. This survey population is expected to drive consumption in the Chinese market as a new powerhouse. Smartphones are not only a means of communication, but also a lifestyle tool that expands people's personalities and personalities and brings them to life. Using the concept of liquid consumption as a guide, the study focused on the enjoyment that smartphone use brings, and hypothesised three factors - innovativeness, personalised experience, and fashionableness - to examine how these factors influence smartphone purchasing behaviour.

While empirical studies using Western datasets have accumulated findings that the personalised experience factor is an effective antecedent of gadget purchase behaviour, the results of this study are contrary to this. In other words, the results suggest that Chinese consumers' behaviour places more importance on fashionableness than on personalised experience factor, nor innovativeness. This is not to deny the possibility that Chinese consumers' perceptions may undergo a Western-style transformation as the market matures, but it should be borne in mind that the structure of consumer attitudes and behaviour in a global marketplace should be closely examined and appropriate marketing strategies developed.

Practical Contributions

The results of this study indicate there is a need to continue to track the impact of joyfulness and to invest in effective marketing strategies as Chinese consumers' attitudes and behaviours mature and change. Given the potential market for smartphones and high-speed network services in China, it is essential for marketers to analyse and respond to antecedents in the development of business strategies.

Chinese consumers born in the 80s and 90s, on whom this study focused, will continue to be the dominant consumer group driving the market for consumer goods in general as well as that of luxury goods. This study suggests that, at this point in time, the behavioural patterns and perceptions of this new group of Chinese consumers are such that it is important to increase the interest of potential consumers and stimulate their purchase intentions for smartphones by promoting the joyfulness that smartphone ownership brings through use of hypothetical marketing communications based on the three investigated factors. Overall, the study indicates the importance of stimulating potential consumers’ interests and purchase intentions.

Limitations

As a pilot study, this research focusses on the purchase behaviour of smartphones. In view of the group driving purchases born in the 80s and 90s onwards, multiple attributes influence the purchase intention of smartphones beyond the fundamental function of smartphones as communication devices through consumer joyfulness. This discussion has been added through this work. However, even given the findings and implications, the authors recognise the study has several limitations.

First, the dataset used in this study was biased, as it was collected mainly from web monitors in large cities in China, and the model and measures need to be tested on a larger, more balanced dataset before the results are generalised. In addition, although joyfulness was hypothesised to be a driving factor in liquid consumption, and although three antecedent factors were analysed in this study, the behavioural patterns and antecedents of liquid consumption will require further research to refine the objectives and scales of the model.

Finally, the fact that the smartphone is an important tool for consumers in omnichannel purchasing behaviour, such as online shopping, is not included within the scope of this study. In this respect, the concept ‘phygital’ has recently been proposed. Phygital is a combination of the words physical and digital is used to describe the convergence of customer behaviour in the real and digital worlds. In other words, it is a new hybrid form of CX (Klaus, 2021). In a future consumer society driven by digital natives, the concept of phygitality will be useful in advancing marketing practices, and it represents the most complete form of omnichannel management for the delivery of positive customer experiences (Banik, 2021). However, as Banik (2021) and other researchers have pointed out, there is a need for deeper consideration and discussion of which attributes are responsible for the impact of phygital retail experiences on customers. It is important to note that beyond its fundamental function as a communication device, the smartphone also functions as a tool for consumer and economic behaviour through its phygital nature, as well as fostering social connection and being part of a lifestyle.

Further Research Opportunities

To refine the models and measures obtained here, we will aim to further test them with large-scale datasets and provide robust suggestions. In particular, the Chinese market is one of the largest potential frontiers for the industry, and it is possible that there are differences in the antecedents of consumer behaviour between large urban areas and the countryside. It may thus be worthwhile to conduct a regional analysis and attempt to suggest a number of regional implications.

Services are intangible, and consumers derive benefits from using and owning them by customising them to suit their lifestyles. Future research could further explore the impact of personalised experiences, which constituted one of the main themes of this study, and track their changing influence on consumer behaviour in the Chinese market and other emerging markets.

The interaction between service providers and service users and the impact of marketing communications is another important research question for the study of purchase behaviour in the luxury goods market, and the customer’s service experience may outweigh strong and enduring ties with a brand.

Finally, as discussed in the limitations section, given that smartphones are an essential tool in online shopping and other digital purchasing activity, how this hub for socio-economic activity is reflected in the evaluation of smartphone purchase intentions and use is an issue that cannot be overlooked. In addition to investigating this issue, we will continue to conduct in-depth research and further analysis on the relationship between CX and purchasing behaviour and on the impact of liquid consumptive behaviour patterns on consumer preferences.

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Received: 28-Apr-2022, Manuscript No. JMIDS-22-11734; Editor assigned: 30-Apr-2022, PreQC No. JMIDS-22-11734 (PQ); Reviewed: 14-May-2022, QC No. JMIDS-22-11734; Revised: 21-May-2022, Manuscript No. JMIDS-22-11734 (R); Published: 28-May-2022