1. INTRODUCTION:

In the dynamic business environment, firms from developing countries have considered exporting as a tool for economic expansion, profitability and continued existence (Leonidas, 1995; Sousa and Alserhan, 2002). The reason is that exporting is regarded as a well accepted and faster means to enhance business operations in international market (Spyropoulou et al. 2007; Tesform and Lutz, 2006). However, export market orientation is the recent field in international marketing, as previous literatures on market orientation have been confined to domestic context (Olimpia, Chewit and Amonrant, 2007).

Shoe manufacturing industry in India is characterised as highly competitive and fragmented industry with large number of shoe firms. In such intensive competition, it becomes necessary that shoe manufacturers must be flexible enough to cater changing needs of their customers. International markets are characterised by large amount of uncertainty with regard to latest technology, potential customers and competitors. This uncertainty in business environment requires firms to obtain export related information and disseminate the same to work upon it (Bozic, 2006; Cadogan, Cui and Yeund, 2003; William, 2006; Krishna and Chekitan, 2003; Salavou, 2002). As a result, MO is regarded as an important strategy to improve Export Performance.

Previous studies on market orientation have claimed that the two types of MO, that is, Proactive Market Orientation and Responsive Market Orientation, are complementary in nature (Bak-Olesen, 2013). Various scholars in the past have also regarded external environmental factors as a key moderator in influencing MO- Performance relationship (Wang, Chen and Chen, 2012; Bak-Olesen, 2013). Bak-Olesen (2013) found positive impact of technological turbulent environment on MO and Performance relationship. Likewise, another study by Wang, Chen and Chen (2012) examined the impact of market & technological turbulent environment on MO and Performance relationship. On the other hand, various researchers argue that environmental factors, like technological turbulence and market turbulence, do not moderate the relationship between MO and performance (Aziz and Yassin, 2010; Subramanian and Gopalkrishna, 2001). Thus, there are diverse views about the impact of environmental factors on MO-Performance relationship.

In the view of the above discussion, this study aims to present a clear picture on the relationship between MO and Export Performance. Specifically, we examine this relationship from the context of shoe manufacturing firms and the impact of turbulent environmental factors on this relationship.

2. LITERATURE REVIEW:

2.1 Market Orientation-Export performance:

Export performance is defined as the result of firm’s activities in international markets (Muhammed and Saleem, 2008). Various authors have acknowledged the most widely accepted definition of export performance by considering growth in sales, level of export sales and the revenue generated from exporting activities (Aaby and Slater, 1989; Albaum, Strandskov and Duerr, 1998; Katsikeas, Leonidou and Morgan, 2000). Researchers have recognised the importance of market oriented behaviour as a pathway to improve export performance (Brendan and Graham, 2002; Cadogan, Cui and Li, 2003; Olimpia, Chawit and Amonrat, 2006). In this context, Narver, Slater and MacLachlan (2004) categorised market orientation in two types, that is, PMO (focus on latent needs of the customers) and RMO (focus on expressed needs of the customers).

The previous literature on the relationship between MO and Export Performance, researchers does not distinguish as to implementing which type of market orientation will lead to improve export performance. In context of exporting, MO has been described as a series of activities like market intelligence relevant to the operations of export firms, disseminating this information which helps firm to devise export oriented strategies (Usman et al., 2012). Lages and Sousa (2010) observed that recent researchers have argued that export managers are now both Proactive and Responsive in order to improve performance.

In previous studies, various researchers have acknowledged the importance of MO in improving firm’s Export Performance (Sousa, Martinez-Lopez and Coelho, 2008; Usman et al., 2012). This is because market orientation enables firms to have “market sensing” ability which leads to effective performance (Bak-Olesen, 2013). For instance, researchers like Akyol and Akehurst (2003) observed that firms which are engaged in creating export related marketing information are superior to other firms in international market which are not market oriented. As the primary purpose of marketing is to know how firms develop competitive edge and how these results lead to improved performance (Kira, Jayachandran and Bearden, 2005), other researchers signify the importance of these competitive strategies to exporters who are facing constantly changing external environment (Acquaah, Adjei and Mensa-Bonusu, 2008) and proactive motivation in terms of desire for growth (Ibeh, Ibrahim and Ezepue, 2007). Thus, it is hypothesized that:

H₁: Proactive Market Orientation is positively related to Export Performance.

H₂: Responsive Market Orientation is positively related to Export Performance.

2.2 Moderating Role of External Environmental Factors:

All organizations are influenced by external environmental factors to some extent. These external environmental factors are characterized as being dynamic in nature. The intricacy in environment poses challenge on firms to respond to these external pressures in order to survive in this competitive shoe market. Any business concern, ignoring or being insensitive to these factors, invites problems in sustaining this market.

The external environment of shoe manufacturing industries affects the MO and Export Performance relationship (Bak-Olesen, 2013). Competition is regarded as the basic feature of this external environment. Within this competitive environment, shoe exporters are expected to develop core competencies as the customers now days are becoming more demanding. Thus, various external environment factors have been identified in past studies which have a moderating effect on both the behaviours of Market Orientation, namely, PMO and RMO and Performance.

2.3 Technological Turbulence and Market Orientation:

Kohli and Jaworski (1990) defined technological turbulence as the changes in the “entire process of transforming inputs to outputs and the delivery of those outputs to the end customer” (as cited in Momrak, 2012; Zeng, Benedetto and Song, 2013). Further, they argued that, with the increase in technological turbulence, MO and performance relationship decreases thus having a curvilinear relationship between them (Lonial and Raju, 2001). Various authors argued that Responsive Market Orientation becomes negative when the firm operates in more turbulent technological environment. When technological environment becomes more turbulent, firms are expected to have alternative opportunities to achieve competitive edge through technological advancement (Tsai, Chou and Kuo, 2008; Zeng, Benedetto and Song, 2013). In contrast, Proactive Market Orientation is regarded as the behaviour which focus on exploring new knowledge (March, 1991) and is positively associated with advanced technology (Ahuja and Lampert, 2001).\

H3_a:

The relationship between Proactive Market Orientation and Export Performance is moderated through Technological turbulent environment.

H4_a:

The relationship between Responsive Market Orientation and Export Performance is moderated through Technological turbulent environment.

2.4 Market Turbulence and Market Orientation:

Jaworski and Kohli (1993) scrutinized the moderating role of market turbulence on market orientation-performance relationship. Market turbulence is defines as “the rate of change in the composition of customers and their preferences” (Jaworski and Kohli, 1993). Market turbulence results in many speedy changes in the environment which leads to changing needs of the customers (Qureshi, Mian and Oswego, 2010). Thus, management must be responsive to market changes to meet this uncertainty in customer’s preference (Gray et al., 1998). Researchers like Jaworski and Kohli (1993) argued that increase in market turbulence will make the market orientation-performance relationship stronger. Other authors argued that firms should increase the level of RMO in order to meet the increased uncertainty in customers’ information (Song et al., 2013). Adding to this, the authors further stated that in more market turbulence environment companies find difficulty in predicting customer demand accurately (Song et al., 2013).

H3_b:

The relationship between Proactive Market Orientation and Export Performance is moderated through Market turbulent environment.

H4_b:

The relationship between Responsive Market Orientation and Export Performance is moderated through Market turbulent environment.

In summary, based on literature review on MO, export performance and environmental factors; our conceptual framework is as depicted in Figure 1.

3. METHODOLOGY:

3.1 Sampling and Data Collection:

The sample population for the study consists of 80 export manager or the marketing manager of manufacturing industries in Agra city of India. A list of shoe manufacturing exporters was obtained from AFMEC (Agra Footwear Manufacturers & Exporters Chamber), an organization which works for whole footwear industry in Agra. The list contains the name of all exporting firm along with the address of the firm, email address, contact number and the name of the owner of the firm. To achieve the required sample size and to collect the data, initially the questionnaire along with the covering letter was administered to all the exporting firms randomly on their email address followed by the reminder mail. In the second instance, personal visit was made to the firms who did not respond on email. The response rate obtained was 91.9%.

3.2 Measures:

The scales used in the study were adopted from previous research. For Proactive and Responsive Market Orientation, the widely accepted scales developed by Narver, Slater and MacLachlan (2004) were used. To measure Export Performance, this study adopted the scale from the work of Gray (1997). Market turbulence and technological turbulence were measured using a scale developed by Jaworski and Kohli (1993).

4. DATA ANALYSIS:

4.1 Validity and Reliability of measurement scales:

Confirmatory factor analysis (CFA) using AMOS 22.0 was carried out to measure the validity of the measurement model having 5 constructs (PMO, RMO, EP, MT and TT). From each construct, few items having poor factor loading (below 0.05) were eliminated. Goodness of fit of the model was then assessed in terms of widely used measures (Kline, 1998) which includes Chi-square to degrees of freedom ratio (/df ratio), Bentler’s comparative fit index (CFI), Bollen’s incremental fit index (IFI), Joreskog and Sorbom ‘s goodness of fit index (GFI), and Browne and Cudeck’s root mean square error of approximation (RMSEA). As stated by Hair et al, 2009, the factor loadings for each item must be greater than 0.05 and that the threshold values of GFI, IFI and CFI must be above 0.90 and threshold value of RMSEA must be below 0.08 for the model that fits well with the collected data (Hair et. al, 2009). The results showed that for Proactive Market Orientation (PMO), /df ratio= 1.706, GFI= 0.918, CFI= 0.962, IFI= 0.964 and RMSEA= 0.011. For Responsive Market orientation (RMO), /df ratio = 1.348, GFI= 0.940, CFI= 0.978, IFI= 0.976 and RMSEA= 0.077. For Market Turbulence (MT), /df ratio = 1.188, GFI= 0.989, CFI= 0.963, IFI= 0.975 and RMSEA= 0.057. For Technological Turbulence (TT), /df ratio= 1.928, GFI= 0.958, CFI= 0.936, IFI= 0.933 and RMSEA= 0.026. For export performance (EP) /df ratio= 1.409, GFI= 0.967, CFI= 0.984, IFI= 0.976 and RMSEA= 0.065. Table I summaries the results of validity of scales.

Table I: Summarised results of scales validity

Model Indices	Threshold Values	Construct values
		PMO	RMO	MT	TT	EP
/df ratio	1-3	1.706	1.348	1.188	1.928	1.409
GFI	> 0.90	0.918	0.940	0.989	0.958	0.967
CFI	> 0.90	0.962	0.978	0.963	0.936	0.984
IFI	> 0.90	0.964	0.976	0.975	0.933	0.976
RMSEA	<0.08	0.011	0.077	0.057	0.026	0.065

Note: PMO-Proactive Market Orientation; RMO-Responsive Market Orientation; MT-Market Turbulence; TT- Technological Turbulence; EP- Export Performance

Further Cronbach alpha, Composite reliability and Average Variance Extracted (AVE) were calculated in order to check the internal reliability. Bagozzi and Yi (1998) suggested that the acceptable range for composite reliability should exceed 0.70 (as cited in Tsai, Chou and Kuo, 2007). Bagozzi, Yi and Phillips (1991) suggested that the threshold value for average variance extracted should exceed 0.05 (as cited in Tsai, Chou and Kuo, 2007)

Table 2 Above provides Factor Loadings, Cronbach Alpha, Composite Reliability and Average Variance Extracted for each construct

5. RESULTS:

Multiple regression was used for testing Hypothesis 1 and Hypothesis 2 relating to PMO, RMO and EP. Table 3 shows the results of multiple regression analysis.

Table 3: Multiple regression analysis results

	Standardised beta	t-value

PMO	0.168	2.003*
RMO	0.778	9.961**
R-square	0.825
Adjusted R- square	0.819
F-Model	121.34***
N	80

According to the results, the model that includes PMO and RMO accounted for 81% of the variance (Adjusted R-square of 0.819) in export performance with F-statistic for the overall significance of the model (121.34) as can be seen in Table 3. The coefficients of Proactive Market Orientation (0.168, p= 0.05) and Responsive Market Orientation (0.778, p= 0.020) are all positive and significant. These results confirm H₁ and H₂ that Proactive Market Orientation and Responsive Market Orientation is positively related to Export Performance with Responsive Market Orientation (t = 9.961, sig 0.020) having large impact on Export Performance.

5.1 Moderating Effect:

For testing the moderating effect, the sample of firms was divided into two parts- firms having high Market turbulence and high Technological turbulence, and firms having low Market turbulence and low Technological turbulence. Simple linear regression is carried out for both the groups. Export performance is considered as the dependent variable and Proactive Market Orientation and Responsive Market Orientation are considered as the independent variable in regression equation. The results of linear regression regarding PMO, RMO and EP under different environment are given in Table 4.

For moderating effect of Technological turbulence, the results confirm that, in high technological turbulent environment, the relationship between PMO and EP becomes stronger. Table 4 (a) shows the evidence that in high technological turbulent environment the coefficient is 0.436 and in low technological turbulent environment the coefficient is 0.417. Further, Proactive Market Orientation explains 21 per cent variation in Export Performance for high Technological turbulence and 18 per cent for low Technological turbulent environment. These results lead to confirmation of Hypothesis 3 (a). Further, in case of high technological turbulence, the relationship between RMO and EP is weaker with coefficient of 0.896 and stronger in low technological turbulence with coefficient of 0.884. Further, in low technological turbulent environment, 77 per cent variation is explained by responsive market orientation on export performance, and, in high technological turbulence environment, it is 75 per cent. This leads to rejection of Hypothesis 4 (a).

For Market turbulence, the result proves that, in case of high market turbulent environment, the relationship between proactive market orientation and export performance becomes weaker. Table 4 (b) shows the coefficients of 0.424 in case of low market turbulence and 0.419for high market turbulence. Further, Proactive Market Orientation explains 20 per cent variation in export performance for low market turbulence, and, 19 per cent variation for high market turbulence. This contradicts Hypothesis 3 (b). Moreover, the results indicate that the relationship between responsive market orientation and export performance is stronger in case of high market turbulence. Table 5 (b) depicts the coefficients in high and low market turbulence environment. In high market turbulence environment, the coefficient is 0.883, and, in low market turbulence environment, the coefficient is 0.894. 77 per cent variation is explained by responsive market orientation in high turbulence environment and 75 per cent variation is explained in low market turbulence. Thus, Hypothesis 4 (b) is not rejected.

As coefficients of independent variables (PMO and RMO) for two regression equations are different, we performed a hypothesis test to examine the significance of this difference. Thus, null hypothesis H₀:β₁= β₂versus alternative hypothesis H₁: β_1≠ β₂ was tested, where β₁and β₂ are regression coefficients in case of low and high technological turbulence and market turbulence respectively. The test was performed to check the homogeneity of groups using ANOVA approach with the following expressions (Goon, Gupta, Dasgupta, 2013).

Test Statistic = X , with degrees of freedom= (1, 76).

Table 4 Results of linear regression regarding effect of environmental factors

Table 4 (a) Results of linear regression regarding effect of Technological turbulence on Proactive Market Orientation and Export Performance

	Coefficient	R² value	p-value
Low technological turbulence	0.417	0.182	0.034
High technological turbulence	0.436	0.214	0.023

Table 4 (b) Results of linear regression regarding effect of Market Turbulence on Proactive Market Orientation and Export Performance

	Coefficient	R2 value	p-value
Low market turbulence	0.424	0.201	0.019
High market turbulence	0. 419	0.196	0.028

Table 5 Results of linear regression regarding effect of environmental factors

Table 5 (a) Results of linear regression regarding effect of technological turbulence on responsive market orientation and export performance

	Coefficient	R² value	p-value
Low technological turbulence	0.896	0.778	0
High technological turbulence	0.884	0.75	0

Table 5 (b) Results of linear regression regarding effect of market turbulence on responsive market orientation and export performance

	Coefficient	R2 value	p-value
Low market turbulence	0.883	0.758	0
High market turbulence	0.894	0.77	0

Based on empirical data, F_calculated for environmental factors (Technological turbulence=5.48, Market turbulence=4.76) on Proactive Market Orientation-Export Performance relationship is more than tabulated value at 5 per-cent significant level with 1, 76 degrees of freedom (F_1,76,.05=3.97). Thus, we reject null hypothesis that two regression coefficients are equal. This indicates that turbulent environment significantly moderates the Proactive Market Orientation-Export Performance relationship.

Likewise, F_calculated for environmental factors (Technological turbulence=4.16, Market Turbulence=5.06) on responsive market orientation-export performance relationship is more than tabulated value at 5 per-cent significant level with 1, 76 degrees of freedom (F_1,76,.05=3.97), which signifies the moderating role of turbulent environment between Responsive Market Orientation and Export Performance.

Table 6 Summary of research findings on the relationship between Proactive Market Orientation, Responsive Market Orientation and Turbulent Environment

Market Orientation Moderator	Technological Turbulence		Market Turbulence
	Low	High	Low	High
PMO	Weaker	Stronger	Stronger	Weaker
RMO	Stronger	Weaker	Weaker	Stronger

6. CONCLUSION:

Previous studies on MO and performance in relation to environmental factors have mostly focused on European countries. The present study carried out with reference to market orientation and export performance lead to three key conclusions with respect to shoe manufacturing industry in India. First, a clear picture of distinguishing both the forms of Market Orientation behaviour, namely, PMO (focus on latent needs) and RMO (focus on expressed needs) was made in relation to export performance. Results revealed that both proactive market orientation and responsive market orientation have a positive association with export performance irrespective of the degree of environmental factors like market turbulence and technological turbulence. Amongst both forms of market orientation responsive market orientation relates more strongly to export performance than proactive market orientation. Second, shoe manufacturing firms which operate in high technological turbulence, but low market turbulence have stronger relationship between PMO and EP. This is because when shoe manufacturing firms work in high market turbulence environment they are less able to foresee customer’s demand as it keeps changing regularly. Last, the relationship between RMO and EP is stronger for those shoe manufacturing firms which have high market turbulence but low technological turbulence. This is because when firms maintain large network ties with all the related actors in the industry they are able to get all relevant information about future demands of their customers thus responding proactively. During technological turbulence when the technology in the industry changes very rapidly, firms must adapt to these changes in order to gain competitive advantage. In particular, the findings of the study are in consistent with the previous research which has conducted in developed countries. The findings further disclose that environmental factors have an important moderator effect between market orientation behaviour adopted by shoe manufacturing firms and the export performance of these firms.

7. MANAGERIAL IMPLICATIONS:

The results of the study provide valuable insight into the role of environmental factors when it comes to examining the relationship between MO and EP. The knowledge of environmental factors is useful to exporters to align the level of Proactive Market Orientation and Responsive Market Orientation keeping in view the level of environmental turbulence (high and low). Therefore, shoe manufacturing firms which practice only responsive market orientation activities must move forward and look at the environmental changes and grab opportunities from the environment by behaving proactively. Failing to do so may lead firms in great trouble. Exporting firms in addition to satisfying expressed needs of the customers must focus on satisfying latent needs of their customers due to the fact that Agra district is considered as the major hub of shoe manufacturing with large number of players operating including both large firms and small firms.

8. DIRECTION FOR FUTURE RESEARCH:

The present study on market orientation, export performance and environmental factors was based on cross-sectional data. Further research in this area can be performed by researchers based on longitudinal data to have a better picture on the adoption of both the forms of market orientation by shoe manufacturers. Second, as most of the firms were small firms, the respondents were mostly the owner of the firm indicating the possibility of biasness in providing information. Therefore, in order to minimise biasness future studies could be conducted taking into consideration other informants of the firm. Third, future studies can also be undertaken by considering other external environmental determinants like competitive intensity and price competition.

Last, empirical studies on examining the relationship of PMO, RMO and EP have been very few. This study examines the export performance with reference to only shoe manufacturing industries in Agra district. Future research could be undertaken to study the export performance in relation to other export industries.

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Received on 16.09.2017 Modified on 24.09.2017

Int. J. Ad. Social Sciences. 2017; 5(3):183-190.

Construct	Indicator	Factor	Cronbach	Composite	Average Variance
		Loadings	Alpha	Reliability	Extracted (AVE)
PMO	PMO 1	0.63	0.83	0.81	0.62
	PMO 2	0.52
	PMO 4	0.52
	PMO 5	0.81
	PMO 6	0.89
	PMO 7	0.69
	PMO 8	0.64
RMO	RMO 1	0.72	0.84	0.8	0.61
	RMO 3	0.64
	RMO 4	0.64
	RMO 5	0.73
	RMO 6	0.51
	RMO 7	0.66
MT	MT 1	0.73	0.67	0.78	0.64
	MT 2	0.71
	MT 4	0.64
	MT 5	0.54
	MT 6	0.63
TT	TT 1	0.72	0.63	0.86	0.55
	TT 2	0.74
	TT 3	0.62
	TT 4	0.65
	TT 5	0.77
EP	EP 1	0.56	0.73	0.76	0.63
	EP 2	0.76
	EP 3	0.68
	EP 4	0.74

Impact of Market Orientation on Export Performance: Mediating Effect of External Turbulent Environment