How does recency influence the timing of purchasing smartphones? The moderating role of context

Figures & data

Figure 1. Research framework

Table 1. The frequency distribution table of the samples

		Frequency	Percentage
Marital status	Single	273	58.1%
	Married without children	25	5.3%
	Married with children	162	34.5%
	Divorced	6	1.3%
	Widowed	4	0.9%
Age	≤20	15	3.2%
	21–30	264	56.2%
	31–40	46	9.8%
	41–50	88	18.7%
	≥51	57	12.1%
Highest education level	Junior high school or below	5	1.1%
	High school/Technical secondary school	37	7.9%
	Junior college	57	12.1%
	Bachelor	178	37.9%
	Master	171	36.4%
	Doctor degree or above	22	4.7%
Current occupation	Students	183	38.9%
	Office workers	221	47.0%
	Self-employed entrepreneurs	10	2.1%
	Freelance work	26	5.5%
	Retirees	19	4.0%
	Others	11	2.3%
Monthly income	≤2000 RMB	127	27.0%
	2000–4999 RMB	151	32.1%
	5000–7999 RMB	105	22.3%
	8000–9999 RMB	36	7.7%
	10000–14999 RMB	30	6.4%
	15000–19999 RMB	5	1.1%
	20000–29999 RMB	8	1.7%
	30000–49999 RMB	3	0.6%
	≥50000 RMB	5	1.1%

Table 2. Reliability and validity results

Construct		Item number	Cronbach’s alpha	CR	AVE	Square root of AVE
Need for uniqueness	Creative choice counter-conformity	11	0.957	0.987	0.729	0.854
	Unpopular choice counter-conformity	7	0.851
	Avoidance of similarity	10	0.954
Anticipated regret	Rational anticipated regret	10	0.950	0.981	0.767	0.876
	Perceptual anticipated regret	6	0.940

Table 3. Pearson’s correlation matrix

Variable	Coefficients of Pearson correlations
	Recency	Need for uniqueness	Education level	Anticipated regret	Purchase timing
Recency	1.000
Need for uniqueness	.012	1.000
Education level	−.004	−.124**	1.000
Anticipated regret	.057	.482**	−.148**	1.000
Purchase timing	−.172**	−.032	.001	.018	1.000

*p < .1; **p < .05; ***p < .01

Table 4. Results of moderated regression analysis

Dependent variable	Purchase timing
	Model 1	Model 2	Model 3
Control variable
Satisfaction with current brand (SCB)	.116**	.111**	.107**
Independent variable (Main effect)
Recency (R)		−.165***	−.151***
Moderator variables (Main effects)
Need of uniqueness (NU)		−.067	−.075
Education level (EL)		−.004	−.004
Anticipated regret (AR)		.073	.074
Moderating effects
R × NU			.098*
R × EL			−.062
R × AR			−.087*
R^2	.014	.045	.057
Δ R^2		.031	.013
F-value	6.420**	4.330***	3.498***
Δ F		3.769***	2.063

*Significant at p < .10; **Significant at p < .05; ***Significant at p < .01

Figure 2. Interaction plot of moderators

Table A1. Research questionnaire design

Part	Amounts of items	Construct	Reference	Measurement scale
Part 1	11 items	Smartphone purchase and use experience	N/A	Nominal scale, ratio scale, and five-scale Likert scale.
Part 2	28 items	Need for uniqueness	Knight and Kim (2007); Tian et al. (2001).	Five-scale Likert scale.
Part 3	16 items	Anticipated regret	Janis and Mann (1977).	Five-scale Likert scale.
Part 4	5 items	Demographic characteristics	N/A	Nominal scale and interval scale.

Knight, D. K., & Kim, E. Y. (2007). Japanese consumers’ need for uniqueness effects on brand perceptions and purchase intention. Journal of Fashion Marketing & Management, 11(2), 270–280. https://doi.org/10.1108/13612020710751428

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Tian, K. T., Bearden, W. O., & Hunter, G. L. (2001). Consumers’ need for uniqueness: Scale development and validation. Journal of Consumer Research, 28(1), 50–66. https://doi.org/10.1086/321947

 Web of Science ®Google Scholar

Janis, I. L., & Mann, L. (1977). Decision making: A psychological analysis of conflict, choice, and commitment. Free press.

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