The effect of entrepreneurial orientation on export performance: Evidence from manufacturing SMEs in Tanzania

Figures & data

Figure 1. The conceptual model

Source: Literature review

Table 1. Proportional sampling

Region	No of exporting SMEs	Proportion	Sample size
Arusha	153	153/958*250	40
Dar es Salaam	390	390/958*250	102
Dodoma	115	115/958*250	30
Mbeya	115	115/958*250	30
Mwanza	185	185/958*250	48
Total	958	958/958*250	250

Source(s): SPSS output

Table 2. Confirmatory factor analysis results

Construct and items	Code	Loadings	α	CR	AVE
Innovativeness (INV)			0.856	0.856	0.598
Creativity in methods of operations	INV 1	0.78
Seeks out new ways of doing things	INV 2	0.81
Encourages people to think in unique ways	INV 3	0.78
Constantly experimenting with new products	INV 4	0.71
Proactiveness (PR)			0.855	0.855	0.600
Seeks to exploit anticipated market changes	PR 1	0.77
Opportunistically shape export environment	PR 2	0.88
Positioning to meet export market demands	PR 3	0.74
Excel at identifying opportunities	PR 4	0.69
Risk-Taking attitude (RS)			0.891	0.896	0.686
Invests in higher risk projects	RS 1	0.84
Tolerance for high risk projects	RS 2	0.93
Taking chances is part of business strategy	RS 3	0.66
Takes calculated risks with new ideas	RS 4	0.86
Export Performance (EXPERF)			0.934	0.932	0.603
Export has been very profitable	EXP 1	0.77
Export has generated a high sales volume	EXP 2	0.73
Export has achieved rapid growth	EXP 3	0.87
Export improved our global competitiveness	EXP 4	0.84
Export has strengthened our strategic position	EXP 5	0.76
Export increased our global market share	EXP 6	0.80
The export performance has been satisfactory	EXP 7	0.79
Our firm export has been successful	EXP 8	0.70
Our firm export has fully met our expectation	EXP 9	0.72

Notes: α- Cronbach’s alpha; CR- Composite Reliability; AVE- Average Variance Extracted

Model fit indices: χ²/df = 1.743; GFI = 0.909; NFI = 0.913; RFI = 0.902; TLI = 0.954; IFI = 0.961; CFI = 0.961; RMSEA = 0.055; SRMR = 0.047; PClose = 0.218

Table 3. Descriptive statistics and correlations

Variables	Mean	Std. deviation	INV	PR	RS	EXPERF
INV	3.9108	0.6964	1
PR	3.7644	1.0753	−0.108*	1
RS	4.0240	0.7353	0.365**	0.312**	1
EXPERF	3.8811	0.6908	0.451**	−0.119*	0.416**	1

*P < 0.05

**P < 0.01

Table 4. Discriminant validity results

Variables	MSV	ASV	INV	PR	RS	EXPERF
INV	0.291	0.112	0.773
PR	0.198	0.072	−0.097	0.774
RS	0.198	0.105	0.186	0.445	0.828
EXPERF	0.291	0.128	0.540	−0.097	0.289	0.777

Note(s): The square roots of AVE are indicated in diagonals (bolded), with construct inter-correlations in lower half of the table. All construct inter-correlations are less than the corresponding square root of AVEs.

Figure 2. Slope plotting for the interaction effect (INV*RS).

Table 5. Regression results and interaction effects of INV, PR and RS on EXPERF

Variables	Coeff	Se	T	P	LLCI	ULCI
Model A; Main effects
INV	0.3854	0.0579	6.6538	****	0.2713	0.4995
RS	0.3308	0.0572	5.7848	****	0.2182	0.4435
INV*RS	0.2234	0.0665	3.3589	0.0009	0.0924	0.3544
R^2	0.3082
F(sig.)	36.5357			****
R^2 change	0.0317
F(sig.) change	11.2819			0.0009
Model B; Main effects
PR	−0.1748	0.0380	−4.6005	****	−0.2491	−0.1000
RS	0.5551	0.0661	8.3933	****	0.4249	0.6854
PR*RS	0.1041	0.0468	2.2229	0.0271	0.0119	0.1964
R^2	0.2447
F(sig.)	26.5684			****
R^2 change	0.0152
F(sig.) change	4.9413			0.0271

**** p < 0.001

Figure 3. Slope plotting for the interaction effect (PR*RS).