Determinants of Marketing Channel Choice Among Handloom Micro-entrepreneurs: Evidence From Rural Assam,India

Abstract

Using primary data collected from 230 handloom micro-entrepreneurs of rural Assam, present study made an attempt to understand the marketing efficiency across different marketing channels of handloom products, and identify the factors determining handloom micro-entrepreneurs’ decision to select a marketing channel. Marketing efficiency was examined using standardised indices. A multinomial logistic regression model was estimated for identifying the factors determining marketing channel choice decision of handloom micro-entrepreneurs. Analysis of data reveals that though the retailer channel was economically most efficient among the three identified marketing channels in the study area, majority of handloom micro-entrepreneurs have chosen the least efficient channel of travelling traders for selling their produce. Using travelling traders as reference category, the results of regression estimate suggest that education of the entrepreneurs, firm size, access to market information, collective action through weavers’ groups, access to credits, and transaction cost-related factors significantly influenced the decision of handloom micro-entrepreneurs in the choice of marketing channels.

Keywords

Informal sector supply chain rural non-farm decision-making multinomial logit model

Introduction

The success of small businesses relies considerably on marketing efficiency (Datta and Sarkar 2020). Schumpeter (1911) recognised the importance of marketing in a world of business characterised by high degrees of risk and uncertainty. The informal business income in a developing economy is directly influenced by the ability of producers in choosing efficient marketing channels while selling their produce (Zhang et al. 2017). Since every marketing channel is characterised by diverse costs and profitability, the choice of an effective channel has implications for the welfare of rural micro-entrepreneurs operating in the informal sector of a developing economy. However, with growing market competition under the wave of globalisation, micro-entrepreneurs operating in rural, non-farm, informal sector are finding it difficult to take advantage of emerging markets as compared to modern firms (Goswami et al. 2017). For fetching a better price and profit margin, an appropriate decision regarding the choice of a marketing channel is crucial on the part of rural micro-entrepreneurs. Hence, understanding the determinants of marketing channel choice decision of micro-entrepreneurs operating in rural, informal, non-farm sector becomes imperative.

The handloom industry, which is the largest source of rural employment next to agriculture, occupies a distinct place in Indian informal sector, engaging nearly 3.14 million of the country’s households as a livelihood activity (Fourth All India Handloom Census 2020). The industry makes a significant contribution to the export earnings of the country by supplying more than 90% of global hand-woven cloths from India (Fourth All India Handloom Census 2020). Nevertheless, handloom is considered a sunset industry confronted with several challenges in recent years, such as shortage of raw materials, inadequate working capital, lack of financial support, weak marketing link, and stiff competition from mill and power loom sectors (Goswami et al. 2017). Limited expertise and impoverished socio-economic background of rural handloom artisans, on the one hand, and interference of middlemen in different marketing channels, on the other hand, pose challenges in marketing handloom products through appropriate channels (Niranjana 2004). The presence of middlemen in value chain increases marketing costs and margins, thereby reducing the returns of handloom micro-entrepreneurs. Though several policies and interventions have been adopted by the Indian government to enhance the productive capacity of handloom micro-entrepreneurs, a serious concern remains for the existing marketing level of handloom products and its value chain linkages. Participation in a high-value market channel can lead to a higher business return by reducing the margin of middlemen, which may encourage more production and business activities among rural handloom micro-entrepreneurs.

The studies regarding the choices of marketing channel are voluminous, which have focused mostly on agricultural marketing (Cheelo and van der Merwe 2021; Mgale and Yunxian 2020; Panda and Kumar 2012; Pham et al. 2019; Thamthanakoon et al. 2022; Zhang et al. 2017). There are few studies that have paid attention on the marketing strategies of small enterprises operating in formal and organised sectors (Agrawal 1998; Bettiol et al. 2012; Deb 1992; Keshari 2020; Pine and Gilmore 2007; Schau et al. 2009). A glimpse on literature of small enterprises, one can draw diverse impressions about the marketing strategies that were followed for sustaining business. Bettiol et al. (2012) argued that a relationship marketing strategy helps in creating and maintaining relationships with relevant groups of customers in order to serve sophisticated and personalised demands. Establishing a relationship with relevant stakeholders is necessary for monitoring their choices in products and brands (Schau et al. 2009). According to Agrawal (1998) and Pine and Gilmore (2007), experimental marketing is an alternative avenue in small businesses for fetching a wide range of markets and business gain. However, recent studies confirmed that traditional marketing methods are still popularly followed in small-scale industries in India (Keshari 2020; Suganya and Shanthi 2014). The issue of marketing at decentralised, informal, rural industrial level has been addressed in the works of a few scholars (Charsley 1992; Datta and Sarkar 2020; Jakate and Ganguly 1980; Murgan and Raju 2011; Niranjana 2004; Prasad 1981; Raghavulu 1981). Most of these studies highlighted the importance of product quality, price standard, and social capital in marketing performance of rural industrial products. There are few attempts urging appropriate policy interventions towards the hurdles in marketing of rural industrial products in India, such as competition from larger firms and absence of mechanism for proper and timely market information (Niranjana 2004; Prasad 1981). Existing marketing literature on non-farm sector spheres on diverse issues, but empirical attempt towards the marketing channel choice decision in context of rural, non-farm, informal sector is hard to come by. Though the recent study by Datta and Sarkar (2020) found that participation in a high-value marketing channel leads to a wide range of sales and pursuance of marketing goals for Khadi products; however, the study fails to address the factors determining the selection of a highly remunerative marketing channel. Hence, this issue requires further investigation. Besides having an idea of efficient marketing channels, there is a need for understanding factors restricting and complementing the selection of a marketing channel by rural micro-entrepreneurs operating in the informal sector.

This study intends to bridge the identified knowledge gaps and in doing so makes several contributions. For operational convenience, the study concentrated on the marketing channel selection by micro-entrepreneurs in the handloom sector of Assam. Apart from contributing to the entrepreneurial marketing literature by extending the analysis of marketing channel choice decisions outside the context of agriculture, the novelty of the present study lies in three pillars: (a) examining marketing efficiency across different marketing channels of handloom products; (b) bringing in the contribution of socio-economic and institutional factors in the choice of economically efficient marketing channels by handloom micro-entrepreneurs; and (c) accounting for the role of transaction cost in marketing channel selection by handloom micro-entrepreneurs. Furthermore, the present study integrates the rational choice theory (RCT) with handloom micro-entrepreneurs’ marketing channel choice behaviour. In doing so, this research would make an important theoretical contribution by articulating the underlying factors that influence the selection of an efficient marketing channel by rural handloom micro-entrepreneurs. The rest of this article has been fragmented into various sections. Data sources and sampling design are explained in the next section of the article. The third section outlines the operational framework of the study. Results and discussion are incorporated in the fourth section. Conclusion and policy implication of the study are summarised in final section of the article.

Data Source and Sampling

This study was conducted in the North-East Indian state of Assam for its relative importance in handloom weaving activities. Assam has the largest number of handloom households, sharing 40.37% of India’s total handloom households (Fourth All India Handloom Census 2020). Since the targeted unit of data collection (i.e., handloom micro-entrepreneurs) in the study area was large and dispersed in population, a multistage sampling technique was used for collecting the data given its suitability. Initially, two districts of Assam, namely Nagaon and Karbi Anglong, were selected for their relative importance in contribution to the total handloom cloth production of the state and product diversity. During 2019, Nagaon district was the largest (8.38%) contributor to the total handloom cloth production among rest of the districts of Assam, while Karbi Anglong ranked third in the list by contributing 6.56% to the state’s aggregate handloom cloth production (Statistical Handbook of Assam 2020). Another reason of selecting the Karbi Anglong district is its product diversity. In Karbi Anglong district, Pini-Pekok and Poho are two major handloom products traditionally woven by Karbi tribal people, while Mekhela-Chador and Gamosa are two major products traditionally woven by handloom weavers in Nagaon district. In the second stage, total of six community development blocks (namely, Kathiatoli, Raha, Rupahihat, Longsomepi, Samelangso and Lumbajang) with a breakup of three blocks from each sampled district were selected based on the concentration of commercial handloom weaving entrepreneurs. In the third stage, a list of villages was prepared for each selected block where handloom weaving activities were carried on commercial basis. Present study excluded those villages where handloom weaving activities were carried on non-commercial basis (operated primarily for domestic use). Then 20% of total listed villages from each block were selected. Accordingly, six villages from Kathiatoli block, five villages from Roha block, four villages from Rupahihat block, five villages from Longsomepi block, four villages from Samelangso block, and six villages from Lumbajang block were selected. In this way, a total of 30 villages were selected from the two sampled districts. In the final stage, a list of handloom micro-entrepreneurs was prepared for each village in consultation with village panchayat (village council) head and various community groups. From the list so prepared, 20% of the total handloom micro-entrepreneurs were selected randomly from each sampled village for personal interview. In this way, a total of 230 handloom micro-entrepreneurs were selected from the two districts. Data were collected from September 2020–February 2021 from rural handloom micro-entrepreneurs using a semi-structured pre-tested interview schedule. Additionally, 28 market functionaries were interviewed purposively with a break up of 10 travelling traders, 10 retailers, and 8 wholesalers. Data related to average prices, marketing costs, and marketing margins were collected from the market functionaries to evaluate the marketing efficiency across different channels.

Profile of the Respondents

Respondents of this study were the owners of handloom micro-enterprises (handloom micro-entrepreneurs). For operational conveniences, following Goswami et al. (2017), a handloom micro-entrepreneur was defined as an individual who owns a handloom weaving enterprise with not more than 10 working looms or paid workers during the preceding financial year of the survey period. Out of 230 handloom micro-entrepreneurs, 50.43% marketed their hand-woven cloths through travelling traders. The shares of respondents who marketed their produce through retailers and wholesalers were 27.39 and 22.17%, respectively (Table 1). Most of the handloom enterprises (63%) were owned by female entrepreneurs. The mean year of schooling of the sampled handloom micro-entrepreneurs was less than seven years. Handloom enterprises were operated on a very small scale, despite having nearly two decades of entrepreneurial engagement in handloom weaving. More than 65% of entrepreneurs operated their enterprises with less than four looms, while 40% of the entrepreneurs operated their enterprises with a single loom.

Table 1.

Handloom Marketing Channels and Distribution of Respondents.

Channel Number	Market Channels	Number of Respondents (%)
I	Manufacturer↓retailer↓ultimate buyer	63 (27.39)
II	Manufacturer↓wholesaler↓retailer↓ultimate buyer	51 (22.17)
III	Manufacturer↓travelling trader↓wholesaler↓retailer↓ultimate buyer	116 (50.43)
Total		230

Description of Handloom Products

Every handloom product manufactured by the weavers of Assam is unique, with images of birds, animals, and flowers mostly embroidered on it. The handloom units operated by sampled micro-entrepreneurs of the study area produce different traditional attires. However, the products like Mekhela-Chador, Gamosa, Pini-Pekok, and Poho were seen to be produced commonly and commercially by the handloom enterprises in the study area for their traditional and cultural importance among Assamese and Tribal communities in the state. Mekhela-Chador is a hand-woven traditional attire (like Saree) popularly worn by Assamese women. Gamosa (like Towel) is generally a white rectangular piece of cloth with primarily a red/green border on three sides and red/green woven motifs on the fourth. Pini-Pekok is a hand-woven traditional attire worn by Karbi women. Poho (Karbi Muffler) is worn around the head or used as a muffler by Karbi people. Mekhela-Chador and Gamosa are the fabrics of significance and easily recognised cultural symbols for indigenous people of Assam, while Pini-Pekok and Poho are traditional attires culturally attached to the Karbi Tribal community of Assam. Therefore, the present study considered these four handloom products, given their relative importance and popularity among the buyers and sellers in the state. The compositions of different categories of these products are detailed in Table 2.

Table 2.

Composition of Different Categories of Handloom Products.

Product	Category	Description
Mekhela-Chador/Pini-Pekok	A	Made by using 80 and above counts of yarn 16–24 hours of labour engagement for a single set of cloth More hand embroidery work
Mekhela-Chador/Pini-Pekok	B	Made by using 60 counts and above but less than 80 counts of yarn 8–12 hours of labour engagement for a single set of cloth Moderate hand embroidery work
Gamosa	A	Made by using 60 and above counts of yarn 6–9 hours of labour engagement for a single piece of cloth More hand embroidery work
Gamosa	B	Made by using 40 and above but less than 60 counts of yarn 3–4 hours of labour engagement for a single piece of cloth moderate hand embroidery work
Poho	–	Made by using 40 and above but less than 60 counts of yarn 4–5 hours of labour engagement for a single piece of cloth Hand embroidery work

Source: Field survey.

Operational Framework

Theoretical Framework

The present study conceptualises handloom micro-entrepreneurs marketing channel choice decision through the use of three channels, namely retailers, wholesalers, and travelling traders (Table 1). The theoretical lens for the study is RCT that supports the explanation of proposed decision-making behaviour of handloom micro-entrepreneurs in marketing channel choices. RCT is suitable for developing an understanding of the role of various characteristics in shaping an individual’s choice behaviour. Although the RCT is well known in behavioural and organisational literature, it has never been applied in rural micro-entrepreneurial decision-making domain. The theory recognises that individuals select amongst the available alternatives for maximising their utility (Levin and Milgrom 2004; Moscati and Tubaro 2009). RCT assumes that a rational decision-maker chooses the most preferred alternative based on calculations, information, and opportunities, available to him/her (Moscati and Tubaro 2009). Hence, based on RCT, the study intends to ascertain the importance of socio-economic, institutional, and transaction cost-related factors in shaping the marketing channel choice behaviour of handloom micro-entrepreneurs. The study would contribute to the theoretical development by integrating RCT with rural micro-entrepreneurs marketing channel choice behaviour.

Driven by the RCT and the literature review, the present study considers different contextual factors that could affect the marketing channel choice decisions of handloom micro-entrepreneurs, which are classified into three categories, namely socio-economic, institutional, and market access/transaction cost factors. The descriptions of the variables of the study and their hypothesised relationship with the choices of marketing channels are listed in Table 3. Within the socio-economic factors, the present model includes gender, age, education, business experience, and firm size (Hazarika and Goswami 2018; Mgale and Yunxian 2020; Parker 2018; Zhang et al. 2017). Females are less likely to participate in urban markets for their pre-occupied household responsibilities. However, education tends to facilitate greater access to the market information, business knowledge, and a better understanding of the possible advantages of handloom weaving business (Hazarika and Goswami 2018). Business experience helps in developing skills and expanding business networks (Parker 2018). Experience earned over the years in handloom weaving business is likely to help in understanding the market requirements and the benefits associated with different marketing channels, thereby enabling intuitive decisions in choosing a profitable channel. Firm size may be a proxy for scale of production, and larger firms are likely to choose wholesale markets in urban areas for their larger volume of production.

Table 3.

Description of Variables of the Study and Their Hypothesised Relationship with the Choices of Marketing Channels.

Determinants	Description	Measurement Unit	Hypothesised Relation
Gender	Gender of handloom micro-entrepreneur	1 for male and 0 for female	+
Age	Age of handloom micro-entrepreneur	Years	–
Education	Years of schooling of the respondent	Years	+
Businessexperience	Number of years spent in business	Years	+
Firm size	Number of working looms in handloom enterprise	Numbers	+
Access to market information	Having access to market information	1 for yes and 0 for no	+
Access to credits	Having access to formal or informal credits	1 for yes and 0 for no	+
Access to training programme	Availed weaving business training from Govt./NGO	1 for yes and 0 for no	+
Membership in weavers’ group	Having membership in any weavers’ group	1 for yes and 0 for no	+
Access to advertising programme	Advertised woven products	1 for yes and 0 for no	+
Distance to handloom market	Distance to the nearest handloom market	Kilometre	–
Distance to pucca (paved) road	Distance to the nearest pucca road	Kilometre	–
Means of transport	Means of transport facility	1 for owns and 0 for hired	+

Within the institutional factors, the model includes access to market information, access to credit and training, membership in weavers’ groups, and access to advertising programmes (Goswami et al. 2017; Hazarika and Goswami 2018; Thamthanakoon et al. 2022). Knowledge and information associated with price, input supply, and market demand play a significant role in entrepreneurial decision-making and work as a crucial element of business networks (Hazarika and Goswami 2018). Credit unavailability emerged as one of the binding constraints in high-value market selection in the agriculture sector (Mgale and Yunxian 2020). Given the context of handloom sector, micro-enterprises in rural areas are more vulnerable to working capital/credit constraints (Goswami et al. 2017). In such a situation, access to credit may boost production, modernisation, better supply chain management, and market participation, which in turn may increase the probability of choosing a highly efficient marketing channel by handloom micro-entrepreneurs. Training is vital for craft-based enterprises in rural areas for satisfying the highly differentiated, uncertain, and fragmented demand condition (Soe et al. 2015). In general, trained handloom micro-entrepreneurs have the skill of producing high-grade handloom products, which may increase the possibility of selling their products through highly remunerative marketing channels. Collective actions in small business have the advantage of bulking in the input and output markets and thereby enjoying economies of scale (Pham et al. 2019). Information and financial constraints in high-value market selection can also be alleviated to some extent by collective marketing practices. Hence, membership in a weavers’ group may have a considerable influence on marketing channel choice behaviour of handloom micro-entrepreneurs.

Within the market access/transaction cost factors, distance to handloom market, distance to pucca (paved) road, and means of transport facility have been included in the model. Researchers have acknowledged the role of transaction costs in marketing decision of agricultural products (Pham et al. 2019; Thamthanakoon et al. 2022; Zhang et al. 2017). Favourable conditions in transaction costs may complement handloom micro-entrepreneurs towards product diversification, supply chain management, and market discovery, and thus increase the possibility of choosing a highly efficient marketing channel.

Analytical Model

A random utility function can be used to describe the preferences of a rational decision-maker, and their choices can be seen as the outcome of utility maximisation (Levin and Milgrom 2004; Moscati and Tubaro 2009). Let us assume that the micro-entrepreneur ‘i’ has a random utility function by selecting marketing channel ‘h’, then the utility function can be formulated as follows:

U_{i h} = V_{i h} + ε_{i h}

(1)

Equation (1) contains a deterministic component (V_ih) which accounts for systematic effects of observed characteristics that influence the choice decision, and a random component (ε_ih) that accounts for the effect of unobserved characteristics which are not included in the utility function but may influence the utility of decision-maker in the choice decision (McFadden 1973).

In general, the deterministic element (V_ih) is assumed to have an additively separable linear form V_ih =β′X_ih, where X_ih and β′ are the vectors of observed factors and constant parameters, respectively. Hence, Equation (1) can be expressed as follows:

U_{i h} = β' X_{i h} + ε_{i h}

(2)

Under the rule of utility maximisation, a micro-entrepreneur facing a sort of existing marketing channels (h = 1, 2,…, n) will choose a channel ‘h’ if U_h > U_k, where U_h is the expected utility of chosen marketing channel and U_k is the utility of alternative channels. Thus, the probability of choosing marketing channel ‘h’ for producer ‘i’ can be expressed as follows:

\begin{matrix} P (h) = P (β' X_{i h} + ε_{i h} > β' X_{i k} + ε_{i k}) \forall h = 1, \dots, H; k \neq h \\ = P (ε_{i k} - ε_{i h} < β' X_{i h} - β' X_{i k}) \forall h = 1, \dots, H; k \neq h \end{matrix}

= \int_{ε} \prod (ε_{i k} - ε_{i h} < β' X_{i h} - β' X_{i k}) f (ε_{h}) d e_{h} \forall h = 1, \dots, H; k \neq h

(3)

ε_{h} = ε_{1}, \dots, ε_{h}

Equation (3) indicates that the selection of a particular marketing channel depends upon the systematic utilities of available alternatives and on the principle of joint probability of random terms ε_h (Apind 2015). A micro-entrepreneur is thus expected to select a marketing channel that offers highest utility among the available alternatives. If the H disturbances are independently and identically distributed, we can specify the multinomial logit (MNL) model for describing the probability of choosing a particular marketing channel. The MNL model allows the analysis of choice possibilities among more than two choices (Green 2003). In the situation where the dependent variable is an unordered categorical response variable, the MNL is the most appropriate estimation technique, subject to the assumption of independence of irrelevant alternatives (IIA) not being violated. The IIA assumption requires that the relative possibilities of two alternatives being chosen are not affected by the inclusion or omission of other options (Hausman and McFadden 1984).

Since handloom micro-entrepreneurs in the study area are faced with three distinct, unordered alternatives (1 = Retailer, 2 = Wholesaler, and 3 = Travelling trader), the MNL model has been specified as follows (Soe et al. 2015; Zhanget al. 2017):

P r o b (y_{i} = h) = \frac{\exp (β_{h}^{'} X)}{1 + Σ_{h = 1}^{H} \exp (β_{h}^{'} X)} f o r_{h} = 1, 2, 3

(4)

where $P r o b (y_{i} = h)$ is the likelihood of selecting market channel ‘h’ by ith handloom micro-entrepreneur; X = (x₁,…,x_k) is the vector of socio-economic, institutional, and market access/transaction cost factors; and β_h is the coefficients vector associated with marketing channel choice ‘h’.

To obtain the magnitude of change on the marketing channel choice decision, marginal effects were estimated by differentiating the Equation (4) with respect to the explanatory variables as follows:

\frac{\partial P_{h}}{\partial x_{k}} = P_{h} (β_{h k} - Σ_{H = 1}^{H - 1} P_{h} β_{h k})

(5)

Estimation Technique of Marketing Efficiency

In view of the presence of various intermediate agents in marketing of handloom products, the present study used the standardised indices developed by Shephard (1965) and Acharya and Agarwal (1999) for examining marketing efficiency across different marketing channels. The advantage of using these indices is that they explicitly incorporate the costs incurred and margins retained by various intermediaries involved in different channels of marketing. The indices of marketing efficiency as proposed are outlined below:

S h e p h a r d^{'} s I n d e x (S I) = \frac{R P}{T M C + T M M}

A c h a r y a & A g a r w a l^{'} s I n d e x (A A I) = \frac{N P R}{T M C + T M M}

where RP is the retailer’s selling price, NPR is the net price received by manufacturers (micro-entrepreneurs), TMC is total marketing cost, and TMM is the total market margin. A higher value of the indices reflects a higher level of efficiency, and opposite for a lower value of the indices.

Marketing cost was calculated by summing up the costs incurred by manufacturers and marketing intermediaries (i.e., travelling trader, wholesaler, and retailer) involved in marketing activities. The cost of market intermediaries included storage charges, packaging, labelling, transporting, sales promotion, and other costs. The size of marketing costs differs from one marketing channel to another because of various characteristics such as the type of commodity, marketing location, nature of marketing organisation, and market functioning (Acharya and Agarwal 1999). Marketing margin was worked out by subtracting the cost price (sum of purchase price and marketing cost) from the sales price of handloom products by a marketing agent.

Results and Discussion

Marketing Costs, Marketing Margins and Net Returns

Table 4 presents the marketing costs, marketing margins, and net returns of manufacturers across the different marketing channels. The total marketing costs across handloom products were seen to be highest in channel-III, ranging from INR 36.74 in Gamosa ‘B’ category (G_B) to INR 102.26 in Pini-Pekok ‘A’ category (PP_A) while the lowest costs were observed in channel-I (ranging from INR 20.06 in G_B to INR 62.16 in PP_A). It can also be seen that channel-III has retained the largest margins across products (ranging from INR 109.18 in G_B to INR 843.23 in PP_A), while the lowest marketing margins were earned via channel-I (ranging from INR 65.83 in G_B to INR 525.45 in PP_A). The high marketing costs and margins in channel-III were due to the existence of a larger number of intermediaries such as travelling traders, wholesalers, and retailers. In this channel, travelling traders bought the handloom products locally from manufacturers and sold them to wholesalers in urban markets. The wholesalers spent on labelling, packaging, storage and sales promotion and again sold them to the retailers, which increased the operating cost. The low cost shares and margins in channel-I were because of the presence of a small number of intermediate agents. On the other hand, the manufacturers received the highest return in channel-I where they sell directly to retailers, and lowest in channel-III where a larger number of intermediaries were involved. To sum up, increased market intermediaries were associated with higher marketing costs and margins, thereby reducing the net return of manufacturers.

Table 4.

Marketing Costs, Marketing Margins and Net Returns (INR/Set or Piece).

Particulars	MC_A	MC_B	G_A	G_B	PP_A	PP_B	P
Channel-I(Retailer)
NPR	1204.37	613.12	516.97	153.89	1745.13	1055.17	239.84
TMC	57.47	43.70	36.86	20.06	62.16	44.46	28.54
TMM	455.65	275.83	175.28	65.83	525.45	320.25	88.45
RP	1717.49	932.65	729.11	239.78	2332.74	1419.88	356.83
Channel-II (Wholesaler)
NPR	1103.80	515.01	437.67	132.09	1641.30	986.13	212.00
TMC	88.39	68.14	55.11	30.93	94.93	68.11	40.67
TMM	612.38	395.92	245.50	83.73	716.13	465.77	129.17
RP	1804.57	979.07	738.28	246.75	2452.36	1520.01	381.84
Channel-III(Travelling Trader)
NPR	1016.40	453.28	401.56	118.41	1548.47	936.83	188.90
TMC	100.27	76.05	62.68	36.74	102.26	75.73	45.10
TMM	767.20	501.59	308.52	109.18	848.23	586.47	156.15
RP	1883.87	1030.92	772.76	264.33	2498.96	1599.03	390.15

Source: Author’s estimates based on field survey.

Notes: MC_A and MC_B stand for Mekhela-Chador ‘A’ and ‘B’ categories, respectively.

G_A and G_B stand for Gamosa ‘A’ and ‘B’ categories, respectively.

PP_A and PP_B stand for Pini-Pekok ‘A’ and ‘B’ categories, respectively.

P stands for Poho.

Marketing Efficiency Across Different Channels

The results of Shephard’s index (SI) and Acharya and Agarwal’s index (AAI) measuring the marketing efficiency of handloom products across different channels are reported in Table 5. Marketing efficiency was observed to be higher among the retailer and wholesaler channels (channel-I and channel-II), implying these channels were functioning more efficiently. Among the three channels, the retailer channel turned out to be the most efficient marketing channel (with the value of SI ranging from 2.79 to 3.97 and AAI ranging from 1.79 to 2.97 across products). The low marketing costs and margins of intermediaries and higher prices received by manufacturers might be the possible reasons for greater efficiency of channel-I (refer Table 4). The efficiency values were seen to be lowest in the case of travelling trader channel (channel-III), with the values of SI ranging from 1.78 to 2.63 and AAI ranging from 0.78 to 1.63 across products. The ineffectiveness of this channel may be because of the high marketing costs and margins of intermediaries and lower prices received by manufacturers (refer Table 4). Among the handloom products selected for this study, the marketing efficiency was higher in Pini-Pekok ‘A’ category (PP_A) followed by Pini-Pekok ‘B’ category (PP_B) and Mekhela-Chador ‘A’ category (MC_A).

Table 5.

Marketing Efficiency (ME) Across Different Channels.

Particulars	MC_A	MC_B	G_A	G_B	PP_A	PP_B	P
Channel-I (Retailer)
ME (SI)	3.35	2.92	3.44	2.79	3.97	3.89	3.05
ME (AAI)	2.35	1.92	2.44	1.79	2.97	2.89	2.05
Channel-II (Wholesaler)
ME (SI)	2.57	2.11	2.46	2.15	3.02	2.85	2.25
ME (AAI)	1.57	1.11	1.46	1.15	2.02	1.85	1.25
Channel-III (Travelling Trader)
ME (SI)	2.17	1.78	2.08	1.81	2.63	2.41	1.94
ME (AAI)	1.17	0.78	1.08	0.81	1.63	1.41	0.94

Source: Authors’ estimates based on field survey.

Descriptive Statistics

The descriptive statistics of factors determining marketing channel choice decisions of handloom micro-entrepreneurs are reported in Table 6. The result shows that most of the micro-entrepreneurs who preferred retailer and wholesaler channels for marketing their products were male, while the travelling trader channel was popular among females. Given the pre-occupied household responsibilities of female within four walls, thereby limiting their mobility, the female entrepreneurs opted travelling traders channel as most convenient, as such traders used to buy finished handloom products at the doorstep of the producers/entrepreneurs. Micro-entrepreneurs choosing retailer channel were relatively younger in age (with a mean age of 41.86 years) relative to those choosing other two channels. Young entrepreneurs were more enthusiastic in exploring profitable marketing channels with smarter use of social media or networking than elderly entrepreneurs. The years of formal schooling, business experience, and firm size were seen to be higher among the micro-entrepreneurs choosing retailer and wholesaler channels relative to those who opted channel-III. Educated and experienced entrepreneurs normally have better awareness about emerging market opportunities and can, therefore, explore the more profitable channel for selling their finished products. Larger firms desired to sell their products to retailers and wholesalers because of their involvement in bulk buying and selling in the study area. Turning to institutional and market access/transaction cost factors, it was observed that access to credits and training programmes, membership in weavers’ groups, and access to market information and advertising programmes were higher among the micro-entrepreneurs who sold their products to retailers and wholesalers relative to those who marketed their products through travelling traders. Inadequate access to institutional facilities constrained the scale of production and market discovery, thereby insisting majority of handloom entrepreneurs to sell their products through travelling traders. The micro-entrepreneurs who sold their products to retailers and wholesalers were seen to be located in the proximity of handloom markets and pucca (paved) roads than those who sold their products to travelling traders. The ownership of means of transport was higher among the micro-entrepreneurs who sold their products through retailers and wholesalers relative to those who had chosen travelling traders. Favourable conditions for such enabling factors aided in better supply chain management and business communication with retailers and wholesalers, whereas remotely located micro-entrepreneurs were compelled to sell their products through travelling traders.

Table 6.

Descriptive Statistics of Factors Determining Marketing Channel Choice Decision.

	Channel-I(Retailer)		Channel-II(Wholesaler)		Channel-III(Travelling Trader)
Non-categorical Variables	Mean	SD	Mean	SD	Mean	SD
Age	41.86	9.24	44.31	4.40	42.63	11.18
Education	7.97	1.59	9.75	2.05	4.72	1.98
Business experience	18.81	6.61	20.08	4.19	15.34	5.40
Firm size	3.22	2.00	6.92	1.62	1.32	0.47
Distance to handloom market	4.30	1.01	4.45	0.94	6.99	1.11
Distance to paved road	1.61	0.47	1.45	0.43	2.96	0.89
Dummy Variables	(%)		(%)		(%)
Gender (1 = Male)	51		80		11
Access to credits (1 = Yes)	24		57		3
Access to training programme (1 = Yes)	46		65		13
Membership in weavers’ group (1 = Yes)	70		71		9
Access to market information(1 = Yes)	87		96		13
Access to advertising programme (1 = Yes)	70		96		6
Means of transport (1 = Owns)	62		82		5
Observations (N)	63		51		116

Source: Authors’ estimates based on field survey.

Note: SD stands for standard deviation.

Factors Determining Marketing Channel Choice Decision

Table 7 presents the results of MNL regression analysis of handloom micro-entrepreneurs’ marketing channel choice decision through the three alternative channels. In the estimation process, the travelling trader (channel-III) was considered as the reference category for comparing with the other two marketing channels, namely retailer and wholesaler. The Hausman test conducted for the IIA assumptions failed to reject the null hypothesis of independence of choice behaviour as the p-value was 1.00 for all choices (refer Table 8). Such result suggests that IIA was not violated, and the MNL specification is appropriate to describe marketing channel choice decisions of sampled handloom micro-entrepreneurs in Assam. The highly significant χ² test statistic (p = 0.00) indicates the strong explanatory capacity of the model. The value of pseudo R² was 0.88, implying that independent variables in the model explained 88% of variations in marketing channel choice behaviour.

Table 7.

MNL Estimation Results for Factors Determining Marketing Channel Choice Decision.

Variables	Retailer		Wholesaler
	Coefficient	Marginal Effect	Coefficient	Marginal Effect
Gender	7.473* (4.261)	0.012 (0.046)	9.474** (4.412)	0.067* (0.035)
Age	–0.780** (0.395)	–0.005 (0.003)	–0.843** (0.406)	–0.002 (0.002)
Education	0.234 (0.905)	–0.013 (0.013)	0.793 (0.926)	0.016* (0.009)
Businessexperience	1.010* (0.531)	0.003 (0.005)	1.210** (0.5546)	0.007 (0.004)
Firm size	4.759 (3.314)	–0.008 (0.028)	6.621** (3.348)	0.060*** (0.123)
Access to market information	28.000* (16.829)	0.207 (0.140)	29.808* (16.978)	0.087 (0.074)
Access to credits	28.894* (17.336)	0.238* (0.133)	29.917* (17.367)	0.065 (0.046)
Access to training programme	–1.970 (2.331)	–0.046 (0.035)	–0.963 (2.488)	0.027 (0.028)
Membership in weavers’ group	15.703* (8.986)	0.225*** (0.072)	12.834 (9.042)	–0.064** (0.032)
Access to advertising programme	–12.905 (8.615)	–0.095 (0.082)	–13.741 (8.849)	–0.040 (0.055)
Distance to handloom market	–0.115 (0.997)	–0.085*** (0.018)	–2.874 (1.270)	–0.087*** (0.017)
Distance to paved road	–32.734* (18.782)	–0.223 (0.140)	–35.528* (18.797)	–0.122** (0.048)
Means of transport facility	21.052** (11.860)	0.261*** (0.090)	18.679 (11.956)	–0.043 (0.040)
Constant	39.156** (21.848)		15.286 (22.589)
Log likelihood = –29.408
Pseudo R² = 0.8763
Likelihood Ratio χ²[26] = 416.78 [p > χ² = 0.000]
Number of Observation [N] = 230

Source: Authors’ estimates based on field survey.

Notes: Travelling trader is used as reference category.

*p < .10; **p < .05; ***p < .01.

Figures in parentheses are standard errors.

Table 8.

Hausman Test for IIA Assumptions for MNL.

Omitted Channels	Chi square	P Value
Retailer	0.00	1.00
Wholesaler	–1.10	1.00
Travelling trader	–2.29	1.00

Source: Authors’ estimates based on field survey.

Among the socio-economic factors, the gender of the handloom micro-entrepreneurs was seen to have a positive and significant impact on marketing channel choice decision. The value of marginal effect reveals that, compared to the reference category, the probability of choosing a retailer and a wholesaler for selling handloom products increased by 1.2 and 6.7%, respectively, among the male-owned handloom micro-enterprises. Such result indicates that male-owned handloom micro-enterprises had greater willingness to sell handloom products directly to retailers and wholesalers rather than through travelling traders. The conventional wisdom avers, given the business responsibility, male micro-entrepreneurs put greater efforts in exploring better marketing channels, while with pre-occupied household responsibilities women in rural areas have limited scope for exploring alternative marketing channels. The age of handloom micro-entrepreneurs was negatively associated with the choices of marketing channels such as retailer and wholesaler; however, the marginal effect implies that the variable has less relevance in the model in terms of statistical significance. Education is an important factor that influences sales management and marketing decisions (Mariano et al. 2012). As anticipated, the decision to sell handloom products to a wholesaler in urban areas rather than to a travelling trader was positively associated with the educational level of handloom micro-entrepreneurs. Thus, an additional year of schooling among handloom micro-entrepreneurs increased the probability of selling handloom items through wholesalers by 1.6%. Educated rural micro-entrepreneurs have better communication and exposure to emerging market opportunities (Hazarika and Goswami 2018). Again, handloom micro-entrepreneurs having experience in weaving business for longer periods were more likely to select retailers and wholesalers in urban areas compared to the reference category. One possible explanation is that more experienced manufacturers have better judgmental capacity in selection of a marketing channel that fetches them better business margins. Pingali et al. (2019) mentioned that business experience enhances the ability to negotiate better marketing terms. The firm size was seen to have positive and significant impact on the decision to select a wholesaler rather than a travelling trader for selling handloom products. The probability of micro-entrepreneurs preferring to select a wholesaler instead of a travelling trader increased by 6% with a unit increased in firm size. Hence, handloom micro-entrepreneurs with larger firms were more likely to choose wholesalers for selling their products. Such result may be due to the fact that the micro-entrepreneurs with relatively larger firms desired to sell their products to wholesalers because of their involvement in bulk buying and selling in the study area.

As conjectured, marketing channel choice of micro-entrepreneurs was significantly associated with institutional factors. The estimated result shows that greater awareness about preliminary market conditions on the prices and quantities of various handloom products among handloom micro-entrepreneurs increased the probability of choosing a retailer and a wholesaler instead of a travelling trader by 20.7 and 8.7%, respectively. On the other hand, handloom micro-entrepreneurs lacking information about market prices and quantities were less likely to travel to urban markets for selling their products to retailers and wholesalers. Knowledge about market conditions made a handloom micro-entrepreneur confident in selling their products in urban markets. Access to credit was found to be associated with an increased probability of selling handloom products to retailers and wholesalers in urban areas compared to the travelling traders. The value of marginal effect indicates that access to formal or informal credit raised the probability of handloom micro-entrepreneurs selling their products to retailers and wholesalers by 23.8 and 6.5%, respectively. Credit constraints limit the scope of micro-entrepreneurs (Hazarika and Goswami 2018), while access to credit helps in producing quality products and searching remunerative markets (Goswami et al. 2017). Handloom weaving being a family-owned business, involvement in weavers’ societies appeared to be advantageous for marketing hand-woven products collectively through proper channels. The estimated result reveals that membership in weavers’ groups significantly increased the probability of selling via retailers rather than travelling traders among the handloom micro-entrepreneurs in the study area. There are several studies in agricultural sector that emphasised the importance of collective action (Fischer and Qaim 2012; Pham et al. 2019; Tadesse and Kassie 2017). Producers in weavers’ society have the advantage of bulk selling at remote markets and thereby enjoying economies of scale.

Market access/transaction cost factors played an important role in the decision-making about marketing channel choices. The handloom enterprises located far from the handloom markets were less likely to select retailers and wholesalers for selling their woven cloths. In the context of agricultural products, Mgale and Yunxian (2020) found that better market access was difficult for rice farmers located in remote areas. The distance to the paved road was another factor that significantly influenced the choice of marketing channel among the sampled handloom micro-entrepreneurs. Greater the distance to paved road, higher the probability of choosing travelling traders instead of retailers and wholesalers. While analysing the marketing channel choices of vegetable growers, Panda and Kumar (2012) argued that access to better road infrastructure minimises the producers’ effort in reaching their produce to the marketing centre. Better road connectivity in rural areas facilitates the marketing of products from remote areas to the places of commerce (Goswami et al. 2017). Ownership of transport facilities was significantly associated with 26.1% higher probability of choosing a retailer instead of a travelling trader. Transportation facilities allow producers to access marketing centres that are located far-off, at minimal expense and travel time (Bathla 2016; Mgale and Yunxian 2020). Therefore, policy initiatives towards the development of rural market infrastructure, road connectivity, and public transportation facilities, especially in rural areas where micro-entrepreneurial activities are carried out, can be helpful in reducing transaction costs and thereby easing access to remunerative markets.

Conclusion and Policy Implication

Marketing is considered as one of the major entrepreneurial activities next to production in the world of business. Since every marketing channel is characterised by diverse costs and profitability, the choice of an efficient channel has implications for the welfare of rural micro-entrepreneurs operating in the informal sector. Given this context, the present study attempts to bring a comprehensive analysis of marketing efficiency across different marketing channels of handloom products and factors determining handloom micro-entrepreneurs’ decision to select a more efficient marketing channel. This study finds that though the retailer channel was economically most efficient among the three identified marketing channels in the study area, majority of handloom micro-entrepreneurs have chosen the least efficient channel of travelling traders for selling their produce. Using travelling traders as reference category, the MNL regression results revealed that education of the entrepreneurs, firm size, access to market information, collective action through weavers’ groups, access to credits, and transaction cost-related factors significantly influenced the decision of handloom micro-entrepreneurs in the selection of a more efficient marketing channel.

Though there are some existing government policies for the marketing incentive of handloom products, but these are implemented only through cooperatives which are dominated by large-scale entrepreneurs, thus limiting the reach of those policies for rural handloom micro-entrepreneurs. Government-organised agencies (such as JAGARAN) running under Assam Apex Weavers and Artisans Cooperative Federation Ltd (ARTFED) are mostly agglomerated in cities, manifesting no interest in procuring products from rural handloom micro-entrepreneurs. Hence, policy initiative is necessary for widening the reach of organised agencies in procuring handloom items directly from rural micro-entrepreneurs who are operating outside the cooperative fold. Moreover, the benefits of existing financial support schemes for handloom weavers are mostly enjoyed by the handloom entrepreneurs who are operating under the cooperative system in Assam. Therefore, policies for better access to institutional credit among rural handloom micro-entrepreneurs operating outside the cooperative system may help in reducing their reliance on travelling traders and encouraging them to sell at distant high-value markets. Recent initiative of government towards the ban on power-loom products in the state is expected to give a boost to the handloom micro-entrepreneurs in avoiding stiff competition posed by machine-made products. The caveats of this study are its focus on traditional marketing channels and restricting geographically only in two contiguous districts of Assam.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iD

Saddam Faruque

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