Learning orientation and response of micro and small food agro-processing enterprises to the customers' needs in Tanzania

Abstract

Response to customers' needs is considered a key to success of micro and small food agro-processing enterprises. However, these firms tend lose customers as a result of fast changing customers' tastes and preferences in the market. Arguments are directed on the learning culture of micro and small food processing enterprises to appropriately capture and provide for the requirements of customers. This paper assessed the learning orientation of micro and small food agro-processing enterprises by specifically determine the extent to which learning orientation influence the response of micro and small food agro-processing firms to the customers' needs. The study employed quantitative method approach and a cross sectional survey design. A stratified sampling technique was used in the study, whereby data were collected using structured questionnaire from 302 owner-managers in Arusha, Morogoro and Dar es Salaam regions in Tanzania. The collected data were analysed using descriptive statistics and multiple linear regression. The findings revealed statistically significant relationship between learning orientation and response of micro and small food agro-processing enterprises to customers' needs. More specifically, commitment to learning was found to be positive significant related to response to customers' needs. Again, open-mindedness was found to be positive and significant related to response to customers' needs. Furthermore, the relationship between shared vision and response to customers' needs was found to be positive and significant. The results provide an implication that, enterprises with strong learning orientation are in better position to respond to customers' needs than enterprises with low learning orientation. This shows that, to be able to appropriately respond to the needs of the customers, the entrepreneurs need to put commitment in learning, open-up for new ideas and information and have a shared-vision which provide a clear direction for learning. This study advocates for policy makers and trainers to establish relevant tools to support learning environment for the micro and small enterprises to improve response to the varying needs of customers in the market.

Keywords:

• Learning orientation
• food agro-processing
• MSEs
• response to customers' needs

REVIEWING EDITOR:

• Len Tiu Wright, De Montfort University Faculty of Business and Law, United kingdom

SUBJECTS:

• Business, Management and Accounting
• Industry & Industrial Studies
• Philosophy of Psychology

1. Introduction

The Micro and Small-sized Enterprises (MSEs) have recently attracted the interest of many researchers worldwide due to their significant socio-economic importance. The MSEs are considered the seedbed for entrepreneurial activities and a mechanism for improving income distribution, stimulating income growth and reshaping the economic structure which has been highly reliant on activities of large enterprises (Kosa et al., 2018; Lestari et al., 2020; Ndiaye et al., 2018; Tambunan, 2020). One of such MSEs are Micro and Small Food Agro-processing Enterprises. The 80% of the agro-processing sub-sector is approximately made of food agro-processing MSEs which are involved in processing, packaging, pricing, distributing, and selling of value-added agricultural outputs (Ekblom, 2016; Kipene et al., 2015; United Nations Development Programme (UNDP), 2017)

There are various factors which affect the performance of food agro-processing MSEs in order to continuously realise the aforementioned socio-economic importance. Specifically, the performance of food agro-processing MSEs are affected by availability of reliable market, financial empowerment, strategic entrepreneurship aspects and business experience (Bengesi, 2013; John, 2016; Kipene et al., 2015). Furthermore, the food agro-processing MSEs' performance is likewise affected by demographic characteristics of the owner-manager, technical capabilities, supplier chain management, mobile technology, business development services (BDs) and policy frameworks (Kapinga, 2020; Njiku, 2019; Nkwabi & Fallon, 2020).

Besides, the performance of food agro-processing MSEs' can be released through proper response to customer needs and be able to retain them in such a that, customers would like to repeat purchases, talk positively about company products and buy variety of products from the same enterprise (Asagba et al., 2020; Turnbull & Wilson, 1989). Hence, proper response customers' needs and retaining customers is especially important to micro and small enterprises with limited resources to engage in aggressive marketing campaigns to continuously look for new customers (Alshurideh, 2016).

Meeting customers' changing customers' needs and expectations require continuous learning of the market dynamics and the changing behaviour of the market stakeholders (Awan & Hashmi, 2014). In other words, a strong learning character is of paramount importance in a highly competitive and dynamic business environment like that of food agro-processing MSEs (Kiyabo & Isaga, 2019). The proactive and continuous learning helps the food agro-processing MSEs develop market-based business practices that match with the current and future needs of the customers (Krautz & Hoffmann, 2017). Besides, learning orientation is considered a strategic resource which cannot be easily imitated however, it really influences positively customer retention practices (Hussain et al., 2016). Farhikhteh et al. (2020) posit that, increased customer choices and competition affect negatively the food agro-processing MSEs since they lose customers to competing businesses resulting into low sales and stagnant overall performances. Therefore, learning orientation influences response to customers' needs (Awan & Hashmi, 2014; Farhikhteh et al., 2020; Hussain et al., 2016; Krautz & Hoffmann, 2017; Kiyabo & Isaga, 2019). This is built on organizational learning theory which provides a link between learning orientation and firms' performance in the market (Sinkula et al., 1997).

Previously, some studies are done on the influence of learning orientation on response to customers' needs. For instance, Hermawati (2020) reveal that, the food agro-processing MSEs' owner-managers with insufficient learning orientation (knowledge and skills) fail to compete in a highly competitive and dynamic markets ending up with closing up their businesses ventures. Furthermore, the dynamics in the market could be minimized if owner-manager possess relevant learning capabilities and business practices that enable them to capture market opportunities and deal with challenges (Ogunyemi, 2020). The knowledge of customer needs, awareness competitor programmes and strategies, appropriate behaviour of the employees in service provision and availability of internal systems influence support coordination and quick response to customers' needs (Heikka et al., 2018; Vanhala et al., 2016). Learning on the quality, quantity and timing of delivery of supplies may have direct or indirect effect on the way customers evaluate the food agro-processing MSEs and ultimately the decision to transact with the business (Dubey et al., 2019; La Rocca et al., 2019; Nkwabi & Fallon, 2020). The appropriate learning orientation of the firms members facilitate not only collection and dissemination of the market information, but also constantly examining the quality of the information available with the business and the logics that guide the entire business processes and practices (Herath & Karunaratne, 2017).

Despite the influence of learning orientation on response to customers' needs in SMEs, the food agro-processing MSEs tend to lose customers compared to large food processing firms in the market (Ekblom, 2016). In other words, the food agro-processing MSEs operate in a highly competitive business environment in which they compete with large firms that produce similar and substitute food products. As a result, the given increased competition has raised customer choices and product varieties in the market (Ekblom, 2016). This happens while the food consumption patterns for consumers has been unstable due to the changes in life style (Lang & Rodrigues, 2022). This has consequently resulted into high movement of customers from one producer to another for the search of products which meet their expectations (Asagba et al., 2020). The smallness nature and limited capital margins of the food agro-processing MSEs provide less advantage for them to study the market to respond to the changing customers' needs accordingly compared to larger well-established firms (Singh et al., 2019). The less advantage of the food agro-processing MSEs is observed in their failure to capture the attention of the target market which rely more on commitment to get a deeper understanding of both expressed and hidden needs of the customers (Domi et al., 2020). Additionally, despite the growing interest in studying the effect of business learning orientation in small business context (Domi et al., 2020; Herath & Karunaratne, 2017), the empirical evidence that explains the relationship between learning orientation and response to customer needs is scant. Therefore, this study assess the relationship between learning orientation and response of food agro-processing MSEs to the customers' needs in Tanzania. It specifically determines:

1. the relationship between learning commitment and response of food agro-processing MSEs to the customers' needs in Tanzania

2. the relationship between open-mindedness and response of food agro-processing MSEs to the customers' needs in Tanzania

3. the relationship between shared vision and response of food agro-processing MSEs to the customers' needs in Tanzania

2. Literature review

2.1. The agro-processing sub-sector in Tanzania

The agro-processing sub-sectors is among the sub-sectors in manufacturing sector forming about 32 percent, 36 percent and 52 precent of the value-added manufacturing products in upper-middle, middle and low income countries respectively (Mazungunye, 2020; Mazungunye & Punt, 2021). The agro-processing sub-sector is considered potential in facilitating the total performance of the manufacturing sector in the economy as it responsible of about 15–20% of value-added products that are traded in both local and foreign markets (UNDP, 2017). In Tanzania, it is estimated that about 70% of the population engage in agriculture activities making the agro-processing sub-sector to be of crucial importance to national development (Japan International Cooperation Agency (JICA), 2017). Basically, most of firms in the agro-processsing sub-sector in Tanzania are at micro and small levels forming linkages between agriculture and other sectors including transportation, food services and resellers (Daninga, 2020; Mazungunye & Punt, 2021).

2.2. The organizational learning theory

A number of theories have been developed to explain the determinants of firms to be able to respond to needs of the target market. Among these theories, include the organizational learning theory (Cangelo & Dill, 1965). The organizational learning theory is among the theories in business management which has received prominence in businesses studies associated with turbulence and ever-changing customer needs (Hussain et al., 2016).

According to the theory, organizations which are in position to learning both internal and external business environment are in better position to improve their performance than ones which do not do. Learning involves acquisition of information, interpret, share, and store for future decisions. Thus, with strong learning business enterprises can find new ways of operating in the market, devise strategies and practices that suits the prevailing market situation (Kaunda et al., 2023).

The organizational learning theory relates to the study at hand in the sense that, when the food agro-processing MSEs learn both internal and external business environment they become in better position of improving their performance particularly response to customers' needs, i.e. turbulence and ever-changing customers' needs. In other words, learning both internal and external business environment in this study implies 'learning orientation' while performance implies response to customers' needs by the food agro-processing MSEs. Specifically, the theory supports the stand that, there is a relationship between learning orientation and response to customers' needs in the food agro-processing MSEs. From the given theory of organizational learning, there is a need to define key variables such as learning orientation and response to customers' needs with reference to previous studies.

Sinkula et al. (1997) defines learning orientation by learning commitment, open-mindedness and sharing of the learning vision among the organization members of which results into organizational learning. Accordingly, enterprises need to put commitment to learn the fast changing environment and the customers, open up for new information, ideas and opinions on how to prove services and they also need to have a shared vision on what specific information needs to be learnt by the members of the organization. In other words, enterprises with learning orientation are proactive in their actions and they are able to adapt to changes in the business environment. Additionally, Calantone et al. (2002) explains learning orientation using commitment to learning, ope-mindedness, sharing of the learning vision and intra-organizational knowledge sharing. Calantone et al. (2002) has added an item of knowledge sharing within organization functional units and sections. The given elements of learning orientation have been widely used in business studies (Hussain et al., 2016; Herath & Karunaratne, 2017; Rostini et al., 2021; Yuan et al., 2018). Regarding the context of the food agro-processing MSEs in Tanzania, the study at hand is going to use three components of learning orientation, i.e. learning commitment, shared vision and open-mindedness.

On the other hand, response to customers' needs is defined as capability of the firms to fullfill the prio set customers expectations are fulfilled, and acting on the needs of customers in a differentiated manner than do competitors (Kapoor & Kumar, 2019). It refers to expected delightment of customers in terms of product quality and features, prices, communications strategy, delivery mechanisms and the overall relationship management strategy (Alghizzawi et al., 2020; Domi et al., 2020). Meeting of customer needs and expectations in highly competitive markets provides a business enterprise with an avenue to survive (Kaunda et al., 2023). This is because, customers would like to maintain relationships with firms that quickly and accurately solve their requirements. It is the process of meeting customers' preferences as they prefer differentiated products, pricing strategies, distribution and market coverage, marketing communications and effective ways of solving complaints and querries (Alghizzawi et al., 2020; Kim, 2017; Kapoor & Kumar, 2019). The given customer needs and expectations are shaped by market changes, competing products and services in the market and the overall product use pattern of the customers (Oh et al., 2022).

2.3. Learning orientation and response to customer needs

There is empirical evidence that there is relationship between learning orientation and response to customers' needs in small business context (Domi et al., 2020; Herath & Karunaratne, 2017). The success of the agro-processing firms depends on the relationship between learning oreintatation and response to customers' needs which higly increases the chance of the customers to continue use specific brands in the market (Shamsudin et al., 2011). Learning orientation maintain stable and continous customers' transactions, business enterprises need to effectively respond to the wants and needs of the customers (Kapoor & Kumar, 2019).

Literature affirms that, learning enriches organization with pertinent information that can be a source of its competitive advantage (Dukeov et al., 2020) Consistently, strong commitment to learning has positively been associated with the achievement of the organizational goals. The study by Olokundun et al. (2017) explains that, among the important pre-requisites for developing a successful business plan is to establish a well-crafted learning culture to enable capture different parameters that affect the operations of an enterprise.

On the other hand, firm's learning orientation helps determine the quality of information collected for different decision of the business enterprise (Hussain et al., 2016). Basically, successful learning process ensures creation of information tank for devising business practices and strategies (Herath & Karunaratne, 2017). As such, business enterprises with high level of learning are likely to sucessfully compete and remain stable in highy dynamic business environment (Bratianu et al., 2020).

The business firms which have capabilities to learn the changing customer needs, competitors' actions and behaviours, learning from other market stakeholders that are in a position to develop relevant practices and programmes for their targeted customers (Hosseini et al., 2018). Baker et al. (2022) established that, learning orientation motivates a business enterprise to find quality information in pursuant to a specific strategic orientation adopted by a firm. Besides, Mahmoud et al. (2016) indicated that, strong learning orientation presents quality decisions on the strategies, practices and operations of a business of which, when backed with innovation, results into positive performance of the firm. In addition, Calantone et al. (2002) identified learning orientation as a strategic resource that brings insights to the organization on how to deal with changes in the environment. The study indicated that, business firms that have high learning orientation are in a better position to craft market-based business practices that suit the needs of the customers. This suggests that, positive learning orientation is associated with the ability to collect information and appropriately transform the collected information into business practices that generate firm competitive advantage.

3. Methodology

The current study adopted positivism research philosophy. This study is built on the views that, there exists a relationship between learning orientation and response to customers' needs in food agro-processing MSEs. Therefore, the positivism philosophical paradigm in the current study allowed testing of the organizational learning theory in the context of empirical review in food agro-processing MSEs in Tanzania. The study employed quantitative method approach. The approach facilitated in collecting objective data to respond to the study objectives. Besides, the quantitative approach provides an opportunity for collecting large amount of data within a reasonable timeframe.

This study employed explanatory cross-sectional survey design. The design was used to explain the relationship between learning orientation and response to customers' needs food agro-processing MSEs in Tanzania. In that explanation, the explanation was achieved in which data were collected at one time of a period from the units of inquiry.

The current study was carried out in three regions of Tanzania including Dar es Salaam, Morogoro and Arusha. The selected regions were found to be relevant, ensured data availability, accessibility and sufficiency in the sense that; the three regions present high concentration and stiff competition of the food agro-processing MSEs in Tanzania (Mazungunye & Punt, 2021; National Bureau of Statistics (NBS) & Ministry of Industry Trade and Investment (MITI), 2018). In summary, the three regions present high concentration and stiff competition of the food agro-processing MSEs in Tanzania.

The study population was the owner-managers of the food agro-processing MSEs. The food agro-processing MSEs form large portion of the agro-processing firms than non-food agro-processing firms; the food agro-processing MSEs face high competition both from large food processing firms; and there is noted high change of consumers life styles including food consumption habits and presence of many food supplements in the market necessitate high need of learning in relation to response to customers' needs in the food agro-processing MSEs. Besides, the agro-processing is considered among the priority sub-sectors in Tanzania in achieving the national development goals (Ministry of Agriculture, Livestock and Fisheries, 2017; Ministry of Finance and Planning, 2016).

This study used the sample size of 323 owner-managers of the food agro-processing MSEs. The sample size was calculated using Yamane (1967)'s formula from population sampling frame of 1690 food agro-processing MSEs. The sample was obtained using proportionate stratified sampling technique. The technique ensured high statistical accuracy as the study population composed of many heterogeneous groups. The data of this study were collected through a questionnaire survey of food agro-processing MSEs. The study opted for the survey method because it involved the collection of data from a highly distributed population with different characteristics in three regions. The survey as well provided high chances for representation, allowed chances of collecting large amount of data while at the same time limiting subjectivity in data collection process. To ensure research ethics, the identity of respondents remained anonymous and all data sources were acknowledged in the study.

All questionnaire survey items were adapted from the published studies that were relevant to this study. Learning orientation variables and respective items were borrowed from Sinkula et al; Herath and Karunaratne (2017), Yuan et al. (2018), Martinez et al. (2020) and Rostini et al. (2021). On the other hand, response to customer needs was adopted from Narver et al. (2004); Shah and Ahmad (2019) and Domi et al. (2020). All the items of the study variables were place under 5-points (1-Strongly Disagree to 5-Strongly Agree) Likert scale and the respondents were required to agree or disagree with the measurement statements.

Testing of reliability presents model reliability and validity information. The study established that, the composite reliability (CR) values for both learning orientation and response to customer needs were above 0.7. Again, the Average Variance Extracted (AVE) and the Maximum Shared Squared Variance (MSV) were found to lie within the proposed ranges as shown in Creswell (2012) and Rönkkö and Cho (2022). More specifically, the composite reliability for learning orientation constructs of shared vision (0.709), commitment to learning (0.705) and 0.825 for open-mindedness; AVE values were found to be 0.629 (shared vision), 0.614 (commitment to learning) and 0.715 for open-mindedness. MSV for share-vision was found to be 0.161, commitment to learning (0.161) and 0.146 for open-mindedness. Regarding response to customer needs, the CR =0.733, AVE= 0.509 and MSV= 0.144. All values were found to be in the acceptable margins indicating model validity and reliability (Creswell, 2012). Besides, a significant level of 5% was used in the study with an understanding this of level of significance improves precision of the measurement and tend to reduce errors (Middleton, 2022).

The study data were analyzed using descriptive statistics and multiple linear regression. The descriptive statistics were used to analyse respondents' characteristics and clear preliminary assumptions of the multiple linear regression. On the other hand, the multiple linear regression was used to determine the relationship between learning orientation with more than two constructs (predictors) and response to customers' needs (outcome) in the food agro-processing MSEs.

4. Findings of the study

4.1. Respondents' background information

A total 302 out of 323 questionnaire were filled and returned. Table 1 provides descriptive statistics of the respondents. Female respondents were 164 (54.3%) while male respondents were 138 equalling to 45.7%. The high number of females in food agro-processing business can be associated with the nature of the activities whereas baking, flour processing and other food agro-processing activities are considered to be more of famine than masculine nature in African society. Moreover, a large proportion of owner-managers had age ranging between 31 to 40 years. The people of this age group are active, energetic, productive and have defined goals for their businesses (Fuertes et al., 2013).

Table 1. Descriptive statistics of respondents.

Variable	Frequency	Percent
Sex
Male	138	45.70
Female	164	54.30
Respondents' age
≤30	92	30.46
31–40	101	33.44
41–50	62	20.53
51+	47	15.56
Education level
Primary education	39	12.91
Secondary education	80	26.49
Certificate and diploma	66	21.86
Degree and above	117	38.74
Experience in business operation
3 to 6 years	164	54.30
6 to 9 years	84	27.81
9 years and above	54	17.88

On the other hand, statistics indicated that, majority of the respondents in the study had education level of bachelor degree (38.74%), 26.49% were secondary school levers, 21.86% had either certificate or diploma education and that 12. 91% had primary school education. The statistics on education levels of owners of micro and small businesses are contrary to statistics of some years back which indicated that the dominant level of education in this category of businesses was primary level (Ministry of Industry and Trade (MIT), 2012). The difference in these statistics could be facilitated by the fact that, currently the government of Tanzania is providing free education in public secondary schools whereby many are able to join. In addition, the extended support of the government to provide loan to students' higher learning institutions enables many Tanzanians to enrol in higher education levels. It is also worthy note that, a few formal employment opportunities available in the country forces a number of graduates to get into self-employment market where they operate and manage their own businesses (Mwakilema, 2021).

Moreover, descriptive analysis of the respondents indicated that most of them had sufficient experience in agro-processing business to explain their learning behaviour and the manner in which they react to the customer requirements. It was observed that, about 54.3% of respondents had been running business for at three years, 27.81% had experience of six to nine years in business, while 17.88% of them had been in agro-processing business for more than nine years. These statistics provide a mixture of respondents who have been involvement in the business for a number of years and that they had fully knowledge of their business ventures.

4.2. Relationship between learning orientation and response to customers' needs

This study used a Multiple Linear Regression (MLR) to determine the relationship between learning orientation (i.e. learning commitment, open-mindedness and shared vision) and response to customers 'needs. In using the MLR in this study, some groundwork analyses were done to guarantee no violation of the MLR assumptions. The assumptions performed included sample size, independence of relations, outliers, normality, linearity, multicollinearity and homoscedasticity. The Factor Analysis was similarly done to reduce the number of variable items for the purpose of making a summated scale in the study. The correlation and reliability of the variable items were tested and ensured when running Factor Analysis.

Generally, the study sample size assumption was ensured using the formula 'N > 50 + 8 m (where m = number of independent variables' by (Tabachnick & Fidel, 2001 p.117). After calculation, it was noted that this study did not violate the sample size assumption, i.e. N > 50 + 8 (3) = 74. This study had three predictors and 302 cases which is more than obtained 74 cases. Furthermore, multicollinearity assumption was examined in the Coefficients Table, whereby all the tolerance values were greater than 0.10 and all the variance inflation factor (VIF) values were less than 10.

The multicollinearity assumption was therefore not violated (Table 2). The predictors had the correlations not above r = 0.7. Moreover, the outliers' assumption was not violated as there were no cases shown more than 3.3 or less than –3.3. in the Scatterplot (Figure 1). The normality assumption is ensured in this study as there was no major deviations from normality in Normal Probability Plot and in the histogram produced (Figures 2 and 3). Besides, the linearity assumption was not violated as the computed F statistics was 6.271 with an observed significance level of 0.000 (Table 3, ANOVA). Additionally, the independence of residuals/independent relationships was tested using the Durbin-Watson test in which the rule of thumb values, i.e. 1.5 < d < 2.5 was not violated in this study (i.e. 1.760 as in Table 4). Finally, the assumption of Homoscedasticity was ensured using the scatterplot in which the trend of residuals/variances concentrated around zero and scattered uniformly and randomly (Figure 1).

Figure 1. Scatterplot.

Figure 2. Histogram.

Figure 3. Normal P-P plot.

Table 2. Coefficients.

Coefficients^a
Model		Unstandardized coefficients		Standardized coefficients	t	Sig	Collinearity statistics
		B	Std. Error	Beta			Tolerance	VIF
1	(Constant)	15.191	4.616		3.291	.001
	Total mean score of commitment to learning	.256	.104	.157	2.456	.015	.770	1.299
	Total mean score of open mindedness	.286	.101	.176	2.749	.013	.922	1.084
	Total mean score of shared vision	.294	.096	.197	2.967	.009	.720	1.388

^aDependent Variable: Total Mean Score of Response to Customers' Needs.

Table 3. ANOVA.

ANOVA^a
Model		Sum of squares	df	Mean square	F	Sig
1	Regression	303.030	3	101.010	6.271	.000^b
	Residual	4799.805	298	16.107
	Total	5102.834	301

^aDependent variable: total mean score of response to customers' needs.

^bPredictors: (constant), total mean score of shared-vision, total mean score of open mindedness, total mean score of commitment to learning.

Table 4. Model summary.

Model summary^b
Model	R	R square	Adjusted R square	Std. error of the estimate	Durbin-Watson
1	.677^a	.459	.45	4.01332	1.760

^a Predictors: (constant), total mean score of shared vision, total mean score of open mindedness, total mean score of commitment to learning.

^b Dependent variable: total mean score of response to customers' needs.

The Adjusted R Square in Table 4 indicates how much of the variance in the outcome (i.e. response to customers' needs) was contributed by the model with the predictors (shared vision, open mindedness and commitment to learning). The output value is 0.45 which means that, the model explained 45% of the variance in the response to customers' needs in the food agro-processing MSEs.

The study revealed that, shared vision, open mindedness and commitment to learning have positive significant relationship with response to customers' needs in the food agro-processing MSEs. The results in Table 2 indicate that, commitment to learning is statistically significant related to response to customers' needs in food agro-processing MSE (Beta = 0.256, t = 2.456, p = 0.015). Besides open mindedness was found to be statistically significant in relation to response to customers' needs in food agro-processing MSEs (Beta = 0.286, t = 2.749, p = 0.013). In addition, shared vision is statistically significant in relation to response to customers' needs in food agro-processing MSEs (Beta = 0.294, t = 2.967, p = 0.009). These results imply that, learning orientation is statistically significant related to response to customers' needs in micro and small food agro-processing enterprises in Tanzania. According to the main findings, improve in learning orientation results into improved response of micro and small food agro-processing enterprises to the needs of the customers. The findings are supported with the fact that, learning is a crucial element in providing the customers' need (Domi et al., 2020). Besides, the results are in line to what was previously found (e.g. Domi et al., 2020; Dukeov et al., 2020; Herath & Karunaratne, 2017; Kapoor & Kumar, 2019). The given studies previously found statistically significant and positive relationship between orientation learning including share vision and open mindedness with response to customers' needs although not in micro and small food agro-processing enterprises. The results provide an indication that, the more entrepreneurs are inclined to learning the higher they can respond to different needs of customers. Basically, the needs for food products and more specifically agro-processed food products changes from time to time, the behaviour which requires continuous learning process to be able to fulfil the required needs. On the other hand, the results show that, strong learning-oriented entrepreneurs are in better position to capture both expressed and hidden needs of the customers while at the same time responding to the needs in a better way than do less learning-oriented entrepreneurs.

5. Conclusions and study implications

5.1. Conclusions

This study generally aimed at determining the relationship between learning orientation and response to customers' needs in micro and small food agro-processing enterprises in Tanzania. Overall results of the study conclude that, learning orientation plays a crucial role in responding to the customers' needs. Summarily, the contribution capacity of learning orientation to response to customers' needs is significant in food agro-processing MSEs. It is worth noting that, a strong and positive learning orientation facilitates the development of appropriate products based on customer preferences, setting of prices in relation to customer requirements and the prevailing market situation, benchmarking of products to those of competitors, service provision in line to the customers' situations and ensuring management of customers 'complaints and improved satisfaction.

This draws conclusion that, response to the needs of customers varies across agro-processing MSEs based on their learning orientation. Therefore, these firms need to put sufficient efforts to develop strong learning culture to successfully provide for customer needs and expectations. Fulfilling customer needs in highly competitive business environment such as the agro-processed products market facilitates customer bonding to the firms' products and services which in turn results to increased number of customers and total sales of the business (Nnko, 2023).

5.2. Study implications

The study of learning orientation in relation to response to the needs of customers in the context of agro-processing MSEs provides a new knowledge in marketing and small business management literature. Small businesses owners can use this knowledge to develop their business practices and strategies as well as for creating their competitive advantage in the market place. The study captures important aspects of commitment to information acquisition, evaluation, sharing and appropriately integrate the information in the business decisions. Therefore, the owners and managers of food agro-processing MSEs need from time to time cultivate their learning behaviour, capture both internal and external changes that affect their response to the needs of the target markets. This can be done with the help of members' participation in different business forums, seminars and exhibitions where they can meet competing firms, learn and exchange business ideas.

Besides, the government and trainers need to establish enabling environment for the small entrepreneurs to learn on how to effectively act on the customer needs. This can be done through capacity building training and seminars that focus on developing skills to micro and small enterprises on learning of the changes in the market, changes in customer tastes and preferences and appropriate response to the needs of the customers. This will enable wide spread of the necessary behaviours and business practices that could positively affect the business relationship with its target market and finally improve satisfaction and long-term returns.

Ethical clearance

The ethical clearance for the study was provided by the ethical Committee of the University of Dodoma (UDOM) in Tanzania, in accordance to Postgraduate Regulations of UDOM.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work is supported by the Institute of Accountancy Arusha (the employer of the corresponding author) through funds allocated to long-term training programmes.

Notes on contributors

Eliakira Nnko

Eliakira Nnko is a PhD candidate at the University of Dodoma (UDOM) in Tanzania.

Ismail J. Ismail

Ismail J. Ismail works as a Senior Lecturer in the Department of Business Administration at UDOM in Tanzania.

Elia John

Elia John works as a Lecturer at the Department of Business Administration and Management at UDOM in Tanzania.