Keywords

Adaptation, Export Commitment, Export-Marketing Mix Strategy, Export Performance, Foreign Market Attractiveness, International Trade, Zimbabwe.

Introduction

Globalisation of trade has induced an ever-increasing number of firms to engage in international operations (Mühlbacher et al., 2006; Leonidou & Katsikeas, 2010; Chang & Fang, 2015; Chen et al., 2016). Exporting is strategic because for firms to internationalise and is frequently used by firms (Morgan & Katsikeas, 1997; Zhao & Zou, 2002; Katsikea et al., 2007; Sousa et al., 2008), as it gives firms high levels of flexibility and requires minimal financial, human, and resource commitments when compared to other international entry modes (Leonidou, 1995; Sousa, 2004). Furthermore, exporting allows firms to acquire market knowledge, as it often requires them to compete in diverse and less familiar environments. Knowledge acquired through exporting can be applied not only in foreign markets, but also in the domestic market, thereby rendering firms more competitive (and, thus, more successful) abroad and at home.

As a result of several benefits that exporting can bring to firms and nations, over the last six decades, a number of researchers have devoted their research efforts to the identification of the variables that affect the export performance of firms. However, and despite notable progress in the recognition of the drivers of export performance of firms, knowledge on this topic is still limited and literature on the export performance frequently yields inconsistent results (Sousa et al., 2008). In this context, researchers have investigated the impact of a large variety of factors on export performance, including industry antecedents (Ito & Pucik, 1993; Das, 1994), environmental factors (Cavusgil & Zou, 1994; Cadogan et al., 2012), and organisational antecedents (Cadogan et al., 2012; Morgan et al., 2012). Among the factors just outlined, organisational variables are the ones which have been more often examined by researchers. This is grounded on the fact that organisational predictors are more under the control of the firms. As such, organisational factors can potentially be used by firms to shape their levels of export success.

The literature on export performance generally lacks a comprehensive theory base and remains fragmented to this day. This fragmented and lack of a general theory originates in (i) numerous studies that adopt inconsistent methodological and analytical approaches (ii) substantial number of determinants of export performance, and (iii) contradicting and confusing findings on the implications of the different determinants of export performance (Sousa et al., 2008). Madsen (1987) and Chetty & Hamilton (1993) and Zou & Stan (1998) and Katsikeas et al. (2000) and Sousa et al. (2008) and Zou et al. (2009), have all contributed with noteworthy efforts to standardise the export performance literature through traditional literature reviews and hybrid approaches, which combine vote-counts with narrative reviews, to reveal discrepancies in the literature.

The performance and growth of exports, has throughout the world, been of great interest to among others, economists, entrepreneurs, managers, governments, financial institutions, and non-governmental organisations, (Baker, 1992). Globally, exports are being highly regarded for the pivotal role in promoting grassroots economic growth, and equitable sustainable development. Zimbabwean manufacturing companies have been facing and are still facing serious competition from foreign products. This cut-throat competition seems to be intensifying and fuelled by the enhanced globalisation agenda, with regional integration also proving to be the hallmark of the new global economic architecture.

A typical example is the COMESA bloc whose envisaged migration from being a Free Trade Area (FTA) to becoming a Customs Union (CU) results in duties being significantly lowered down, while other non-tariff barriers are also being abolished. Against this backdrop, the Zimbabwe manufacturing sector has struggled for quality and competitiveness. The ripple effect of this scenario has meant that the country’s exports have remained very depressed and a negative trade balance has been experienced for some time now (Reserve Bank of Zimbabwe, 2016a).

The Reserve Bank of Zimbabwe (2015) pointed out that the liquidity crunch that has been negatively affecting the Zimbabwe economy for the past decade, requires that exports be enhanced or improved, since exports remained the chief source of financial liquidity. The manufacturing sector is very critical to economic growth, prosperity and higher standard of living. Part of the reason for that is its multiplier effect. More than any other sector in the economy, manufacturing creates the most wealth (Reserve Bank of Zimbabwe, 2016a). Manufacturing pays higher wages and provides greater benefits, on average, than other industries. It performs almost two-thirds of private sector research and development, creates the highest number of jobs to support the industry while serving the surrounding communities, and contributes to around 8 percent of Zimbabwe’s total exports (Reserve Bank of Zimbabwe, 2017).

Statement of the Problem

Given the importance of exporting, an array of international research has focused on understanding the factors that determine successful performance in exports. In particular, recent years have seen increasing attention being given to the identification and assessment of international business competencies that underpin export performance of firms (Knight & Kim, 2009; Kaleka, 2012; Chang & Fang, 2015; Chen et al., 2019). However, previous studies have not comprehensively examined major factors that affect performance of exporting firms.

Moreover, the majority of prior studies in this direction have focused on Western and advanced economies, hence, an understanding of the relationship between such competencies and export performance in the developing economies’ context is still lacking (Boso et al., 2016). Considerable evidence from prior studies points to differences between advanced and developing economies in factors important for export. More importantly, exporting firms operating from developing economies have to manage multiple export market challenges, such as resource constraints (Tesfom & Lutz, 2006; Boso et al., 2016), little international experience (Gries & Naudé, 2010), lack of marketing knowledge and information (Tesfom & Lutz, 2006), complex regulatory system and underdeveloped institutions and structures supporting international operations (Bell et al., 2004; Boso et al., 2016), and significant tariff and non-tariff barriers applied to their manufactured exports (Korneliussen & Blasius, 2008). Given these differences, more studies and data are needed from the context of developing economies to broaden knowledge on the subject (Okpara, 2009; Boso et al., 2016). This study, therefore, generates a better understanding through step-by-step disentangling of the complex relationship between managerial characteristics, export marketing mix strategies and export performance in a developing economy context, such as Zimbabwe.

The manufacturing sector in Zimbabwe has over the last decade suffered from the economic downturn, which the country experienced. Its contribution to total exports has remained extremely low over the years, averaging about US$50 million per year (Reserve Bank of Zimbabwe, 2017). Despite numerous Government and Reserve Bank of Zimbabwe efforts to encourage more exports, through various export oriented policies, and export incentive schemes, the annual contribution of the manufacturing sector to total exports remained subdued at around 8%, compared to mining sector at 54%, agriculture 30%, hunting 2%, and services 6% (Reserve Bank of Zimbabwe, 2017).

Firms that export are typically more productive, more skilled labour intensive and more capital intensive (Bernard et al., 2007, 2010, 2011; Wagner, 2007, 2012) and within the set of exporters, the more productive firms export more products to more destinations and export larger volumes to each market (Bernard et al., 2010; Karedza & Govender, 2016). It follows that as these characteristics improve, exports will rise accordingly. Encouraging improvements in the productivity of Zimbabwean manufacturing firms (i.e., reductions in inefficiency or increases in technology), or the quality of inputs they use (i.e., skilled labour, services such as design sales or support, components etc.) will therefore have an effect on the overall Zimbabwe exports.

Research Objectives

1. To determine the key factors that influence the export performance of the manufacturing firms in Zimbabwe;

2. To examine interceding effects of export-marketing mix strategy on the relationship between management’s commitment to export, experience on the international markets, programmes that promote exports, and export performance;

3. To examine the regulating (moderating) effect of the attractiveness of a foreign market on the relationship between the 4Ps), and export performance; and

4. To develop and test a mediating and moderating export performance model.

In order to contextualise the research objectives, the following hypotheses were developed: -

H1: Adaptation of the 4Ps (place, product, promotion, and price) positively enhances export performance;

H2: Management’s commitment to export enhances the adaption of the 4Ps;

H3: Programmes that promote exporting enhances the adaptation of the 4Ps;

H4: Experience with international markets enhances the adaptation of the 4Ps;

H5: The 4Ps enhances the relationship between export commitment and export performance;

H6: The 4Ps) regulate the relationship between Programmes that promote exporting and export performance;

H7: The 4Ps regulate the relationship between Experience with international markets and export performance; and

H8: The more the attractiveness of the foreign market, the stronger the relationship between the 4Ps and export performance.

Literature Review

Researchers seem to agree that export performance is a multidimensional construct. In this context, two broad categories of export performance are export sales performance and export profit performance (Zou et al., 1998; Cadogan et al., 2009; Morgan et al., 2012). Assessments of export performance using profit take into account costs and range across differing outcomes. The importance of export sales performance and export profit performance as two critical categories of export performance corresponds to the notion that organisational success can be classified into outcomes that take account for costs versus outcomes that place emphasis on revenues and that do not reflect costs (Homburg et al., 2011).

Most issues associated with the literature boils down to the lack of a sound theoretical basis and disagreement across studies on the appropriate measure of export performance and determinants thereof (Leonidou, 2003; Sousa et al., 2008). The majority literature completely neglects a coherent theoretical basis and formulate hypotheses without reference to theoretical arguments, while different conceptual definitions, classifications and measures of factors that affect export performance hinder the comparability of studies. This lack of theoretical guidance and inconsistent use of determinants are among the main causes of the conflicting empirical findings that reflects the literature (Zou & Stan, 1998; Sousa et al., 2008). The first attempts to research on export performance dates back to (Madsen, 1987; Aaby & Slater, 1989; Chetty & Hamilton, 1993). Aaby & Slater (1989) developed the first framework of casual relationships in their strategic export model, where the export performance was evaluated against management influences such as firm characteristics, competences and strategy. Chetty & Hamilton (1993) extended the strategic export model in a meta-analysis in an attempt to validate the findings of Aaby & Slater, 1989), but most of the results remained inconclusive. The main point of criticism is related to the inclusion of studies that investigated conceptually broader dimensions of export performance.

Despite the fact that export performance has been at the centre of interest in the study of export-marketing, the evaluation of conceptual underpinnings of export performance and its measures has largely been ignored (Katsikeas et al., 2000; Sousa et al., 2008). Indeed, there is little agreement in the literature about a conceptual definition of export performance, as well as about its operational definition (Shoham, 1998). In fact, most of the papers on export performance in the past did not even provide a conceptual definition of export performance (Sousa, 2004) and empirical efforts to explore this area are even less developed (Lages & Montgomery, 2005; Sousa et al., 2008).

A wide range of literature has been published on measurement of export performance and such studies are summarised in Table 1.

Table 1: Export Performance Measurements
Export Performance Measure	Type	Researchers
Sales Growth and Intensity of exports	Objective (Unbiased)	Alvarez, 2004; Lages & Lages, 2004; Morgan et al., 2004; Lages et al., 2008b; Hultman et al., 2011; and Morgan et al., 2012.
Profitability or Increase in Market Share of exports	Objective (Unbiased)	Das, 1994; Moen, 1999; Lages & Lages, 2004; Morgan et al., 2004; Wong, 2004; Katsikeas et al., 2006; Hultman et al., 2011; and Morgan et al., 2012.
Strategic Goals Achievement	Subjective (Biased)	Cavusgil & Zou, 1994; Das, 1994; Styles, 1998; Zou et al., 1998; Francis & Collins-Dodd 2004 and Lages & Lages, 2004.
Management’s understanding of Export Success	Subjective (Biased)	Cavusgil & Zou, 1994; Evangelist, 1994; Katsikeas et al., 1996; and Wilkinson & Brouthers, 2006.
Export Performance Satisfaction	Subjective (Biased)	Jap, 2002; Lages et al., 2008a; and Lages & Montgomery, 2004
Combination of Measurements	Subjective (Biased)	Zou et al., 1998; Katsikeas et al., 2000; Shoham 2002; O’Cass & Julian 2003; Morgan et al., 2004 and Sousa & Bradley, 2008.

Conceptual Framework And Hypotheses Development

Figure 1 shows the independent, interceding, and regulating variables on the relationship with export performance (dependent variable). The controls variables are firm size, age and type of industry.

Table 2 shows expected outcomes of the hypotheses

Table 2: Hypotheses And Export Performance
Hypothesis	Explanatory Latent Variable	Expected Outcome
H1:	4Ps (place, product, promotion, and price)/export performance	(+)
H2:	Management’s commitment to export/adaption of the 4Ps	(+)
H3:	Programmes that promote exporting and adaptation of the 4Ps	(+)
H4:	Experience with international markets and the adaptation of the 4Ps	(+)
H5:	The 4Ps enhances the relationship between export commitment and export performance;	(+)
H6:	The 4Ps) regulate the relationship between Programmes that promote exporting and export performance;	(+)
H7:	The 4Ps regulate the relationship between Experience with international markets and export performance	(+)
H8:	The more the attractiveness of the foreign market, the stronger the relationship between the 4Ps and export performance.	(+)

Research Methodology

An explorative sequential mixed method was used in order to determine the socio-economic factors that enhance export performance of the food and beverage manufacturing firms. For this purpose, a semi-structured interview (qualitative method) and a questionnaire (quantitative method) were used to collect data. Data has been connected in that the results of the qualitative was used to develop a measurement instrument, namely a questionnaire (quantitative method). In this way, an attempt has also been made to ensure triangulation of data.

For this study, the researchers chose key informants based on their employment positions in the 100 food and beverage manufacturing and exporting firms in the year 2018. The Reserve Bank of Zimbabwe exporter’s database has been used because the Central Bank keeps an up-to-date database of all exporters in Zimbabwe. The population for the qualitative phase comprised of chief executive officers, managing directors, general managers and owners of the firms. The population of the qualitative research study consisted of a non-probability, purposive selection of 91 exporting firms in six major cities namely; Harare, Bulawayo, Mutare, Gweru, Kwekwe and Chitunwgiza. A total of 91% of the firms are concentrated in these six major cities.

Data Collection

In order to eliminate selection bias, a web-based ‘random number generator’ has been used to select 22 key informants from the 91 food and beverage manufacturing firms.

Table 3 shows distribution of target population and samples drawn for the qualitative interviews.

Table 3: Distribution Of Target Population Of The Key Informants
Location	Food Manufacturing Firms			Beverages Manufacturing Firms
	Target Population	Sample Drawn Randomly	No. of Qualitative Interviews Conducted	Target Population	Sample Drawn Randomly	No. of Qualitative Interviews Conducted
Harare	31	6	5	8	3	2
Bulawayo	19	3	2	4	1	1
Gweru	8	2	2	2	1	1
Mutare	7	1	1	2	1	1
Kwekwe	4	1	1	1	1	1
Chitungwiza	4	1	1	1	1	0
	73	14	12	18	8	6
Chinhoyi	2	0	0	0	0	0
Bindura	2	0	0	0	0	0
Chipinge	0	0	0	1	0	0
Beitbridge	1	0	0	1	0	0
Masvingo	1	0	0	1	0	0
Total	79	14	12	21	8	6

A combination of the ‘deliver and collect’ technique and the use of email services has been appropriate for primary data collection due to lack of up-to-date email directory and the spread of respondents across the major cities in Zimbabwe (Ibeh, 2004; Brock & Zhou, 2004; Crick et al., 2011).

After screening the completed questionnaires, 1 was declared unusable due to more than 15% missing values, leaving a total of 49 questionnaires for analysis (Hair et al., 2012). The study achieved a response rate of 81.7%. The sample size requirements to detect R² values of 0.10 to 0.50 based on the number of arrows pointing to the endogenous variable in PLS-SEM analysis, was met (Hair et al., 2014a).

Findings

Table 4 shows that a greater proportion of the respondents (94.8 %) indicated that they were agreeable that the listed factors have positive effect on export performance of the firms. Only about 1.3% disagreed and 3.9% were undecided.

Table 4: Responses On Factors That Affect The Export Performance Of The Food And Beverage Manufacturing Firms
Factors	Number of Respondents
	Strongly Disagree	Disagree	Undecided	Agree	Strongly Agree
Access to affordable working capital	0	0	0	8	41
Availability of efficient production technology	0	0	1	3	45
Availability of export incentives	0	0	0	2	47
Competitive pricing of goods	0	1	2	10	36
Depreciated exchange rate for the local currency	1	2	1	14	31
Ease of doing export business	0	0	0	34	15
Export committed management	0	0	1	22	26
Export marketing mix strategy	0	0	3	13	33
Foreign market attractiveness	0	0	0	5	44
Good distribution network	0	3	1	7	38
Good knowledge of the foreign market	0	0	1	19	29
High capacity utilisation	4	3	10	14	18
High demand for the products	0	0	0	20	29
High productivity	0	0	2	23	24
High quality inputs	0	0	0	24	25
High quality of goods produced	0	0	1	34	14
Large scale operation (firm size)	0	1	11	20	17
Low export market competition	0	0	5	19	25
Low production costs (competitiveness)	0	0	1	22	26
Low tariffs (by importing country)	0	0	3	25	21
Low tax regime	0	0	1	17	31
Low threats of substitutes	0	0	5	33	11
Management perception toward export	0	0	0	35	14
Mature firm (age)	0	0	3	32	14
No trade restrictions (e.g., permit requirements etc)	0	0	2	20	27
Profitable export sales	0	2	1	24	22
Reduced or no export barriers	0	0	2	22	25
Reliable supply of inputs	0	0	0	23	26
Reliable transportation system (road, air & Rail)	0	0	0	20	29
Skilled labour force	0	0	1	24	24
Stable political environment	0	2	1	22	24
Well established research and development	0	1	2	27	19
Total Number of Responses	5	15	61	637	850
Proportion (%)	0.3	1.0	3.9	40.6	54.2

Analysis

Unlike other structural equations modelling techniques such as LISREL, AMOS, and EQS, Partial Least Squares (PLS) does not need to satisfy assumptions like multivariate normality and independence of observations (Chin & Newsted, 1999; Chin, 2010). PLS combines regression, path analysis and principal components analysis, and avoids the problems of factor indeterminacy and inadmissible (Fornell et al., 1990; Buchan, 2005). Other structural equations modelling techniques such as LISREL, require a minimum sample of 150 (Anderson & Gerbing, 1998; Chin & Newsted, 1999), whereas PLS requires only a minimum number of 30 cases. In line with the reasons cites above, the researcher decided to use PLS for testing the model. The two stage procedure followed by MacMillan et al. (2005) has been adopted to carry out the analysis.

Reliability and Validity

Reliability has been assessed in two different ways. Firstly, the magnitudes of the factor loadings corresponding to each construct have been examined. Fornell & Larcker (1981), recommend a loading of 0.70 for each item on the constructed factor, but 0.50 is often used in factor analysis. The convergent validity has been assessed by examining the average variance extracted (AVE) for each of the factors. The AVE is the average shared between a construct and its measure, and Fornell & Larcker (1981) suggested a minimum of 0.50. For assessment of the discriminant validity, the AVE values were plotted on the diagonal and the squares of correlations as off-diagonal items. If the amounts shown in the off-diagonals are less than the diagonals, then the measures have discriminant validity.

Testing the Structural Model

At this stage of the analysis, the R² values were examined to assess the predictive ability of the model. For assessing the R² values, the guidelines provided by Hair et al. (2006) have been used. Subsequently, the path coefficients are examined and their structural significance has been assessed.

Model estimation and measurement

The measurement model and significance values are shown in Table 5.

Table 5: The Measurement Model And The Significance Values
Latent Variable(s)	Performance Indicators	F: Loadings	Standard Error	T Statistics
Performance (Export) α=0.93, Pc=0.94, AVE=0.75	Sales volume. Export market share. Export market profitability. Return on investment. Export sales intensity.	0.847 0.885 0.914 0.811 0.891	0.034 0.023 0.015 0.057 0.024	24.90*** 38.43*** 61.25*** 14.20*** 37.11***
Place α=0.83, Pc=0.89, AVE=0.68	Selection criteria Transport strategy. Distribution budget. Type of middlemen.	0.775 0.842 0.890 0.801	0.061 0.057 0.023 0.046	12.79*** 14.78*** 38.14*** 17.52***
Product α=0.88, Pc=0.91, AVE=0.68	Product design. Variety. Product quality. Features and characteristics. Packaging.	0.729 0.820 0.891 0.836 0.870	0.085 0.062 0.030 0.044 0.038	8.55*** 13.26*** 23.06*** 18.83*** 22.06***
Promotion α=0.82, Pc=0.88, AVE=0.63	Channels for adverts. Promotion objectives. Budget for promotion Direct marketing.	0.761 0.846 0.834 0.782	0.062 0.041 0.046 0.053	12.36*** 20.48*** 17.98*** 14.75***
Price α=0.70, Pc=0.79, AVE=0.57	Determination of price strategy. Price discount policy. Price margins.	0.586 0.813 0.843	0.228 0.186 0.160	2.70*** 4.30*** 5.30***
Commitment (Export) α=0.72, Pc=0.78, AVE=0.54	Frequent travels to foreign markets. Adequate funds set aside to develop export markets. Exporting is priority	0.750 0.755 0.701	0.071 0.061 0.138	10.62*** 12.46*** 5.13***
Programmes for Promoting Exports α=0.91, Pc=0.93, AVE=0.75	Attending Seminars. Conducting Training Providing export advice Export publications.	0.869 0.885 0.887 0.873 0.817	0.025 0.027 0.031 0.028 0.048	34.25*** 33.36*** 28.43*** 31.13*** 17.02***
Management’s Experience on international markets α=0.77, Pc=0.86, AVE=0.68	Professional experience. Attendance of formal courses Follow up on trade deals Many foreign markets	0.680 0.690 0.820 0.871	0.064 0.096 0.046 0.022	10.55*** 7.18*** 17.91*** 35.95***
Attractiveness of Foreign Market α=0.84, Pc=0.89, AVE=0.67	Potential demand Education of consumers Level of industrial development. Rules and Regulations	0.814 0.832 0.837 0.891	0.045 0.034 0.035 0.043	17.65*** 28.18*** 24.30*** 21.13***

Table 6: Discriminant Validity
Fornell-Larcker Criterion
	Age	EPP	ExpComt	ExPerf	FMA	Fsize	Industry	InExp	Place	Price	Product	Promotion
Age	1.000
EPP	0.039	0.866
ExpComt	0.298	0.410	0.736
ExPerf	0.089	0.284	0.419	0.870
FMA	0.194	0.377	0.488	0.600	0.824
Fsize	0.475	0.069	0.432	0.262	0.217	1.000
Industry	0.110	0.147	0.102	0.005	0.018	0.225	1.000
InExp	0.400	0.435	0.492	0.286	0.237	0.350	0.075	0.770
Place	0.036	0.335	0.322	0.393	0.351	0.183	0.029	0.140	0.828
Price	0.244	0.151	0.228	0.125	0.157	0.143	0.238	0.216	0.297	0.756
Product	0.194	0.251	0.383	0.249	0.383	0.184	0.173	0.170	0.201	0.404	0.831
Promotion	0.056	0.216	0.313	0.114	0.046	0.262	0.091	0.435	0.234	0.226	0.118	0.806

All item loadings are greater than 0.58 with most of them exceeding 0.708 with significance at the p<0.001 level (Haenlein & Andreas 2004; Hair et al., 2014a). There has been no collinearity issues with constructs in the structural model (Sarstedt et al., 2014). The measurement model has been confirmed to be used to assess the structural model and test path analysis in the research hypothesis (Hair et al., 2012).

Discriminant validity was assessed using the Fornell-Larker criterion which compares the squares root of the AVE values with the latent variable correlations (Martin & Méjean, 2011). The results exhibit no evidence of strong correlations between constructs.

Table 7: Results Of The Pls-Sem Analysis
Hypo.	Variables	Expected Result	Place	Product	Promotion	Price	Decision
H1	4Ps/EP	(+)	(+)***	(+)***	(-) ns	(-) ns	2 supported
H2	EC/4Ps	(+)	(+)***	(+)***	(+)***	(+)***	Supported
H3	EPP/4Ps	(+)	(+)***	(+) ns	(+) ns	(+) ns	1 supported
H4	IE/4Ps	(+)	(-) ns	(-) ns	(+)***	(-) ns	1 supported
	Interceding (Mediation)
H5	EC→4Ps→EP	(+)	(+)**	(+)**	(+) ns	(+) ns	2 supported
H6	EPP→4Ps→EP	(+)	(+)**	(-) ns	(-) ns	(-) ns	1 supported
H7	IE→4Ps→EP	(+)	(-) ns	(-) ns	(-) ns	(-) ns	Not supported
	Regulation (Moderation)
H8	FMA via 4Ps and EP	(+)	(+)***	(+)***	(+)**	(+) ns	3 supported

Tables 8 summarises the characteristics of exporting firms in Zimbabwe.

Structural Model 1 – Place as mediator

Figure 2 shows the results of the path analysis and significance level. The value of the mean average variance accounted (AVA) is 0.25 (R²) and R² is greater than 0.10 (Falk & Miller 1992). Place explained a total of 44% of variance of Export Performance. Commitment to Export explained a total of 20% of the variance of Place and Export Performance. Programmes for Promoting Exports (EPP) explained a total of 19% of Place and Export Performance. The Q2 values range from (EC=0.08; EPP=0.14; Place=0.09; EP=0.30) which are above acceptable levels (Hair et al., 2014a). The f² values range from 0.02 to 0.26. Place recorded an interceding effect of 0.29 on Export Performance. Place significantly affects Export Performance (EP) at (p= 0.009, t=2.60).

Structural Model 2 – Product as Mediator

Figure 3 shows the results of the path analysis and significance level. The value of the mean average variance accounted (AVA) is 0.25 (R²) and R² is greater than 0.10 (Falk & Miller, 1992). The Q² values range from (EC=0.08; EPP=0.14; EP=0.28) which are above acceptable levels (Hair et al., 2014a). The f² values range from 0.02 to 0.26. Product recorded an interceding effect of 0.26 on Export Performance. Product significantly affects Export Performance (EP) at (p= .009, t=2.60).

Structural Model 3 – Promotion as Mediator

Figure 4 shows the results of the path analysis and significance level. The value of the mean average variance accounted (AVA) is 0.26 (R²) and R² is greater than 0.10 (Falk & Miller 1992). The Q² values range from (EC=0.08; EPP=0.14; EP=0.140 which are above acceptable levels (Hair, Hult, Ringle & Sarstedt 2014a). The f² values range from 0.02 to 0.26. Product recorded an interceding effect of 0.26 on Export Performance. Promotion insignificantly affects Export Performance (EP) at (p=0.009, t=2.60).

Structural Model 4 – Price as Mediator

Figure 5 shows the results of the path analysis and significance level. The value of the mean average variance accounted (AVA) is 0.09 (R²) and R² is less than 0.10 (Falk & Miller 1992). The Q² values range from (EC=0.31; EPP=0.17; Price=0.012; EP=0.17). The f² values range from 0.02 to 0.26. Price recorded an interceding effect of 0.17 on Export Performance. Price insignificantly affects Export Performance (EP) at (p= 0.916, t=0.497).

Results of the PLS-SEM Analysis

As shown in Table 7 (the results of the PLS-SEM Analysis and decisions), place and product have positive and significant impact on export performance of the food and beverage manufacturing firms in Zimbabwe.

Table 8: Characteristics Of Zimbabwean Exporting Firms
Place Adaption	Product Adaption	Promotion Adaption	Price Adaption	People
• Poor transport infrastructure • Logistics barriers • Extensive use of Agents or middlemen as compared to direct distribution • Firms mostly located near major trunk road and rail	• Low product quality • Packaging needs to meet international standards • Less differentiated • Limited product modification, product design and style, and packaging	• Zimtrade (export promotion agency) lacks capacity • Trade shows and exhibitions not prioritised • No training and development programmes • Rely mostly on other forms of promotion such as export of samples	• Uncompetitive prices • Lack of access to affordable finance • Pricing policies not responsive to the fluctuation, price reductions. • Pricing mechanism based on cost of production	• Unsupportive business environment • High technical skills • Lack of international experience • Limited export commitment • Limited cultural adaptation • Limited export initiatives • Lack of financial resources, allocation of resources and export investment.

Discussion

Price and Export Performance recorded non-significant results which supports the theoretical evidence of a negative relationship existing between the two variables. Of the 4Ps, place (distribution) and product are the most adapted export-marketing mix strategies by the food and beverage manufacturing firms in Zimbabwe, and promotion and price are the least adapted. The qualitative interviews have produced the same results as those of the quantitative interviews.

With regards to other factors that affect export performance, the qualitative results show that functional, marketing, and logistical barriers and lack of funding are common problems associated with exporting in Zimbabwe. The fast track land reform programme, poor quality farm produce, unnecessary bureaucracy, lack of aligned workforce, and late delivery of export orders, have been linked to functional barriers.

Control variables, namely, firm size and age of the firm have produced positive results with export performance. Type of industry has shown results in which depict non-significant relationship with the export performance. Table 9 shows quantitative and qualitative results of the study.

Table 9: Quantitative & Qualitative Results Of The Studies
Theme	Quantitative	Qualitative
Export Performance Determinants
The 4 Ps
Place (Distribution)	Significant (+)	Supported
Product	Significant (+)	Supported
Promotion	Non-significant (-)	Not Supported
Price	Non-significant (-)	Not Supported
Export Commitment	Significant (+)	Supported
Programmes to Promote Exports	Non-significant (+)	Supported
International Experience	Non-significant (+)	Not Supported
Foreign Market Attractiveness	Significant (+)	Supported
Interceding (Mediation) Effect
EC→4Ps→EP	Place & Product significant (+)	not applicable
EPP→4Ps→EP	Place significant (+)	not applicable
IE→4Ps→EP	4Ps non-significant (-)	not applicable
Regulation (Moderation) Effect
FMA - 4Ps and EP	Place, Product & Promotion significant (+)	not applicable
Other Factors
Initiation of Exports	not applicable	Supported
Firm location	not applicable	Supported
Common challenges	not applicable	Supported
Measurement of EP
Subjective measures	Subjective	Supported
Objective measures	not applicable	Not supported

The role of Innovation and Technology on Enhancing Export Performance

The study revealed that innovation and technology play a critical role in export development, and contribute significantly to value addition of Zimbabwe exports. The results show that technology has a positive relationship with export performance. This corroborates with other studies (Sanyal, 2004; Montobbio & Rampa, 2005; Zengin, 2014) that were carried out in some developing countries.

Bi-lateral Trade Agreements and Export Performance

A limited and less significant number of respondents cited trade agreements as enhancers of exports in the manufacturing sectors. However, the respondents indicated that once technology has been improved so as to enhance product quality, trade agreements would be necessary for facilitation of trade. The study established that the share of manufactured products in total exports present a negative effect on total value of bi-lateral exports which implies that the demand for manufactured products is low due to competition or change in consumer preferences in the importing country.

The Effect of Credit and Export Performance

The results advocate that access to affordable bank financing has a positive and significant effect on the manufacturing firm’s export performance. The results suggest that access to affordable credit increases the firm’s export revenue. The capacity of the firm to increase production and increase the market reach is significantly enhanced.

Our results further provide evidence that access to finance by manufacturing firms have positive effect on the overall firm performance. An enhanced financial muscle most strongly support the entry of less well-endowed firms into foreign markets and substantially sustain exports into that market. Increased export performance by manufacturing firms has positive ripple effects on job creation, value added exports as well as productivity.

Conclusion

The study has identified a number of factors that affect the export performance of the food and beverage manufacturing firms such as firm characteristics factors (firm size, management perception toward export, firm export experience, firm strategy and commitment); firm competency factors (technology, marketing knowledge, foreign market knowledge and international performance; adequacy of infrastructure; labour cost and labour skill; economic factors (economic growth, economic policy, inflation, exchange rate); market factors (market attractiveness, market competitiveness and market structures); contextual environment factors (trade barriers, cultural differences - cultural distance); physical distance; export initiation; and location of the firm.

The commitment to export, place and product adaptation and foreign market attractiveness have emerged as key success factors for the Zimbabwean firms to enhance their exports. The research has shown that place (distribution) and products have been significantly adapted, which reiterates the relevance of adaptation strategies on enhancing export performance (Leonidou et al., 2002). Thus, research contributes to the literature by validating two of the adaptation forces (place and product) in a model focusing on emerging country context in Africa. This study reveals the reasons behind the mixed findings of the effect of the management experience of the international export markets on the export performance.

Recommendation

In order to enhance the export performance of the manufacturing firms in less economically developed countries, the following managerial and policy implications are apparent from the study:

1. Manufacturing firms should have access to affordable working capital for successful exporting endeavours;

2. The management of the manufacturing firms should have good knowledge of the foreign markets, not only in terms of the consumer preferences, but also in terms of the existing market regulations and requirements;

3. Manufacturing firms should invest in export skills development activities for their personnel, and in product research and development;

4. The Governments should actively create conducive business working environments for their nations, so as to ensure that the ease of doing export business is upgraded and sustained; and

5. The Governments should ensure that their nations have reliable transportation system (road, air, rail and/or water) so that the exporting firms become competitive and continue generating the much needed foreign exchange.

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