Cultural intelligence and sales performance in online insurance marketing: evidence from a Chinese insurance firm

The spread of the Internet has expanded marketing beyond local, culturally homogeneous markets to broad geographical areas with diverse cultures, heightening the prominence of cultural clashes in customer–salesperson interactions. In China, despite a Han majority, religious, ethnic, and regional cultural diversity is substantial and can influence marketing outcomes. With the surge in online insurance marketing, salespeople increasingly engage with consumers from diverse cultural backgrounds, creating cultural challenges that may hinder sales performance. Cultural intelligence (CQ), the capability to function effectively in culturally diverse contexts, is posited as critical for online salespeople. Unlike general or emotional intelligence, CQ focuses on cross-cultural interactions and adaptation. This study focuses on China’s online insurance sector, where Internet-based distribution has grown rapidly (e.g., Internet channel premium income reached 290 billion yuan in 2020, 6.4% of total premiums), and investigates how salespeople’s CQ affects sales performance. The research objectives are: (1) identify cultural challenges arising from Internet-enabled marketing, (2) determine the role of salespeople’s CQ in online marketing performance, and (3) propose managerial countermeasures for online businesses. The study claims novelty in examining CQ’s role in online insurance marketing within a fundamentally changed business model.

CQ and sales performance: CQ lacks a single agreed definition but is commonly defined as the capability to collect and process culture-relevant information and adapt effectively in new cultural contexts (Earley and Ang, 2003). CQ comprises metacognitive, cognitive, motivational, and behavioral dimensions. Prior research links CQ to cross-cultural work adaptation and performance. Hypothesis H1: CQ of online insurance salespeople positively impacts sales performance. Adaptive selling, CQ, and sales performance: Adaptive selling is adjusting sales behavior to the perceived sales situation (Weitz et al., 1986) and is generally positively associated with sales performance. CQ is positively correlated with adaptive selling; higher metacognitive, cognitive, motivational, and behavioral CQ may facilitate strategic adjustment, cultural understanding, motivation, and appropriate behaviors during sales. Hypotheses: H2: Adaptive selling positively impacts sales performance. H3: CQ positively moderates the relationship between adaptive selling and sales performance. Customer orientation, CQ, and sales performance: Customer-oriented behaviors (investing in understanding and meeting customer needs) correlate positively with sales performance and satisfaction, including in insurance contexts. Cultural differences can hinder effective customer orientation. CQ may enhance information acquisition, cultural understanding, motivation, and behaviors aligned with customer expectations, thereby strengthening the effect of customer orientation on performance. Hypotheses: H4: Customer orientation positively impacts sales performance. H5: CQ positively moderates the relationship between customer orientation and sales performance. Perceived organizational support (POS), CQ, and sales performance: POS supports employees’ socio-emotional needs, increasing commitment and performance. POS relates to better cultural adaptation and may foster CQ development. It may also enhance the positive effect of CQ on performance. Hypotheses: H6: POS positively impacts sales performance. H7: CQ mediates the relationship between POS and sales performance.

Conceptual model: Building on prior work that links adaptive selling, customer orientation, and organizational support to sales performance, the study incorporates CQ as both a direct predictor, moderator, and mediator within a conceptual model. Structural equation modeling: Given latent constructs, SEM is used with partial least squares (PLS-SEM) implemented in SmartPLS. PLS-SEM is chosen for maximizing explanatory power for endogenous variables, handling non-normal data, and compatibility with relatively small samples (<600). The SEM includes measurement and structural models. Control variables included: gender, age, education level, managerial position, industry experience, and number of professional certificates. Collinearity diagnostics show VIF values <3 across constructs. Data source and measures: An electronic questionnaire (Questionnaire Star) was distributed via WeChat to >980 online insurance marketers at a medium-sized Chinese digital insurance brokerage, April 21–25, 2021. 601 responses were collected; after quality screening, 572 valid samples remained. Respondent profile: 72% male; majority under 30; most non-managerial; education concentrated at junior college; 28% without work-related certifications. Scales (5-point Likert): - Adaptive selling: shortened ADAPTS (Robinson et al., 2002) - Customer orientation: adapted SOCO (Saxe & Weitz, 1982), 4 forward and 1 reverse items - Perceived organizational support: adapted from Riggle et al. (2009), 5 items - Cultural intelligence: adapted short-form CQ (Thomas et al., 2005), measuring knowledge, skill, and cultural metacognition - Job performance: adapted from Williams & Anderson (1991), 5 items Reliability and validity: Overall Cronbach’s alpha 0.948. Construct alphas: adaptive selling 0.91, customer orientation 0.85, POS 0.89, CQ 0.94, performance 0.92. KMO = 0.947; Bartlett’s test significant. Measurement model: all standardized loadings >0.7; composite reliability >0.7; AVE >0.5, indicating convergent validity. Discriminant validity satisfied by Fornell-Larcker criterion. ANOVA and t-tests examined differences across demographics and experience. Model evaluation: R² for sales performance = 0.535; predictive relevance Q² for performance = 0.422. For CQ (endogenous in H7): R² = 0.244; Q² = 0.161. Effect sizes (f²) indicate meaningful explanatory contributions for most paths except the moderating effect of CQ on adaptive selling → performance.

- PLS-SEM path coefficients (Std, t, 95% CI): - H1 CQ → Performance: 0.223, t=4.459, 95% CI [0.121, 0.318] (significant) - H2 Adaptive selling → Performance: 0.356, t=7.555, 95% CI [0.265, 0.453] (significant) - H3 CQ × Adaptive selling → Performance: −0.059, t=0.750, 95% CI [−0.145, 0.136] (not significant) - H4 Customer orientation → Performance: 0.153, t=3.142, 95% CI [0.039, 0.230] (significant) - H5 CQ × Customer orientation → Performance: 0.118, t=2.087, 95% CI [−0.034, 0.183] (reported as positive moderating effect) - H6 Organizational support → Performance: 0.196, t=5.297, 95% CI [0.125, 0.270] (significant) - H7 Organizational support → CQ: 0.494, t=13.301, 95% CI [0.424, 0.566] (significant) - Mediation: Indirect effect POS → CQ → Performance = 0.110 (0.494 × 0.223), t=4.168, 95% CI [0.059, 0.162], indicating CQ partially mediates the POS–performance relationship; total POS effect on performance ≈ 0.306 (direct 0.196 + indirect 0.110). - Model fit and prediction: R² for performance = 0.535; Q² for performance = 0.422, indicating strong explanatory and predictive capability. VIF values <3 suggest no serious multicollinearity. - ANOVA insights: No significant differences by gender, education, or managerial status across key constructs. Age differences: 18–22 group reports higher perceived organizational support. Experience differences: <1 year tenure shows lower adaptive selling but highest POS; 3–4 years tenure shows highest performance. Certifications: more certificates associate with higher customer orientation, CQ, and POS.

Findings support that CQ directly enhances online insurance sales performance and strengthens the effectiveness of customer orientation on performance. The significant positive effects of adaptive selling and customer orientation on performance align with established sales literature, confirming their relevance in online, culturally diverse contexts. CQ’s insignificant moderation of the adaptive selling–performance link suggests that while culturally intelligent salespeople are inclusive and adept in cross-cultural contexts, this may dilute rigid customer segmentation and specific adaptive tactics, attenuating moderation effects in this pathway. Conversely, CQ appears to convert customer-oriented efforts into better outcomes under cultural differences by enabling faster cultural adaptation (cognitive CQ), stronger intrinsic motivation to engage customers (motivational CQ), and context-consistent behaviors (behavioral CQ). Perceived organizational support not only improves performance directly but also fosters CQ, which partially mediates POS’s impact on performance. This highlights organizational levers—support, care, and integration—that cultivate CQ and, in turn, enhance sales outcomes in online markets where cultural differences are salient.

Using survey data from 572 online insurance marketers at a Chinese digital brokerage, the study concludes that customer orientation, adaptive selling, perceived organizational support, and cultural intelligence significantly and positively influence sales performance. CQ also enhances the effect of customer orientation on performance and partially mediates the relationship between perceived organizational support and performance. Practically, as online insurance expands and cultural differences remain a barrier, firms should recognize culture as a key factor, prioritize hiring and training to raise CQ, and strengthen organizational support to foster motivational and behavioral dimensions of CQ. These actions can improve salespeople’s capacity to understand diverse customer needs and deliver appropriate solutions, thereby boosting performance. The results offer guidance for online insurance management and broader online marketing contexts.

- CQ theory is relatively nascent and often developed in expatriate contexts; applying it to domestic online marketing may involve theoretical immaturity. - The study examines a limited set of determinants of insurance sales performance, constraining exploration of CQ mechanisms. - Data were collected via electronic questionnaires, which may differ from manual methods and may affect data quality. - The study assumes cultural gaps but does not measure the magnitude of cultural distance precisely. Future research should classify cultural types and measure cultural gaps more accurately, examine differential effects of CQ dimensions on performance, and explore relationships between CQ and other performance determinants.