Flexible Distribution Strategies in Network Marketing Companies

Abstract

This chapter focuses on rarely explored areas in research, i.e. flexible distribution strategies in Network marketing (NM) companies. The purpose of this chapter is to compare the customer’s perception on flexible distribution strategies across the two companies i.e. Amway India Enterprises (AIE) and Hindustan Unilever Network (HUN) and formulate ‘Distribution Flexibility’ models for flexible distribution strategies. Empirical models are developed to test the predictors of ‘Distribution Flexibility’ in NM companies (HUN and AIE). This objective is attained through gathering information using ‘Snowball’ sampling technique from 300 Hindustan Unilever Network and 300 Amway India customers through structured questionnaire in Greater Hyderabad (Telangana State). The data was analyzed through descriptive and inferential statistics. The findings of this chapter reveal that the majority of HUN respondents are business people, whereas housewives are more prevalent in AIE. ‘Word of Mouth’ (WOM) through ‘Reference group’ plays a leading role. ‘Distribution Flexibility’ is mostly by Network management support and acquaintances . ‘Support’ is low in Amway when compared to HUN. ‘International quality’ is comparatively high in AIE than HUN. Prices are perceived to be higher in Amway India than Hindustan Unilever Network customers. The study highlights the importance of taking appropriate corrective measures to attend major classes like demographics, customer loyalty and satisfaction by increasing the distribution flexibility in network marketing. Even though precautions are taken to include all sections to represent the Telangana state, it is more effective to conduct such studies geographically segment-wise to be more accurate. It is intended that the information from this study will help customers, distributors, and companies’ executives to respond to the ever changing needs of end users in Indian marketing through increasing flexibility via Network marketing. The studies which focus on comparison of ‘Distribution Flexibility’ through network marketing (NM) in Indian context are very few and hence add more value in understanding customer’s buying behaviour in these areas.

1 Introduction

Network marketing has been transforming the distribution system through creating flexibility in distribution and is gaining momentum. Many organizations across the globe have professed the potential of NM in reaching prospective customers through flexible distribution strategies in every corner of the contemporary world. The long-established distribution chain in most of the companies relied on a physical distribution system of “Manufacturer—Wholesaler—Retailer—Consumer” concept. Berry (1997) articulates that in essence, Network Marketing [NM] is a way of organizing sales operations of a direct selling organization. It is a non-store approach relating to distribution of goods and services, directly to the customers. Network Marketing integrates the crux of free enterprise by providing an opportunity for the interested individuals or independent contractors to run a home based business. The network marketing thrives as a sales force catering to the recruitment of other members down the line in the market—making and hierarchy of multiple levels of compensation. It is like lessening the scale of networking of sales persons in selling products to the end users through ‘Referral’ and WOM marketing. The globalization coupled with rising incomes, increased customer exposure to different media, modern retail formats and digital marketing lead to customer centric revolution.

According to AC Nielsen study report (2002), consumers are seeking a flexible shopping experience across various channels, and expect marketers to deliver this. These shifts towards flexible shopping experience of customers have important implications for distribution systems that are competing in increasingly competitive environments. Added to this consumers are seeking more customized products or services than ever before. These shifts have fueled the growth of flexible distribution systems to increase reach and satisfy customers in a better way. But there is a huge gap in what customers say and how they exactly behave. Hence there exists a strong need to understand flexible distribution strategies, as it enables the distributors and marketers to serve customers better.

1.1 Context of the Study

According to the World Federation of Direct Selling Association (WFDSA) , globally NM is operating in 100 plus countries. The market size of the direct selling industry was INR 63,851 million for 2011–2012 and is expected to reach INR 108,436 millions by 2014–2016. As per the Indian Direct Selling Association (IDSA) estimates direct selling (DS) industry is expected to reach INR 340,000 million in 2011–2012 while the distributor base is expected to reach 80 Lakhs by 2014–2015. In India ‘Direct Selling’ is in nascent stage, i.e. two decades due to various reasons like lack of awareness and negative image etc. AIE and HUN are currently facing dip in sales revenues and hence the market share is coming down due to the high customer churn. According to AC Nielsen study report (2002) there is a significant shift in consumer buying behaviour. The study reports a sharp decline in average number of customers visit to store. Therefore, these swings in customers buying behaviour have an important bearing on Non-store retailers who are competing with store retailers in competitive environments through Network marketing.

This chapter progresses with providing the literature review relevant to distribution flexibility , identification of research gaps, approach of the study, design which includes sampling design, framed research question s, formulated hypotheses, data analysis and findings. The study concludes with providing the managerial implications, suggestions to distributors/customers, retailers for redesigning flexible distribution strategies, to attract and retain prospective consumers.

2 Literature Review

Flexibility is concerned with firm’s ability to adapt itself to a wide range of possible environments, uncertainties that it may encounter (Nour et al. 2015, p. 88). ‘Distribution Flexibility’ is firm’s ability to alter distribution processes in an efficient manner in order to adapt and meet the requirements of direct and indirect customers (Yu et al. 2012). Cova and Cova (2002, p. 2), stated that shoppers’ within horizontal consumer-to-consumer networks can exhibit ethnic behaviour. As an adaptation to the current revolution in retail scenario and ambiguity in current business scenario, flexibility became a core issue in management research in the 1980s and 1990s (Slack 1987; Sethi and Sethi 1990; Gerwin 1993; Upton 1994; Koste and Malhotra 1999). As an extension to the above (Sezen and Yilmaz 2007) further stated that many distribution firms altered their channel relationships to sustain in this contemporary and vibrant scenario of the volatile business environment forces.

Distribution flexibility in general may be defined as the capability to alter distribution strategies by satisfying the distributors/network members in an efficient way to meet the requirements of customers’. Distribution flexibility strategies in this study refer to the firms’ capability to swiftly adapt and react to the shifting customer needs through integrative capacities. Distribution flexibility plays a vital role in gaining and sustaining a strategic competitive advantage through customer satisfaction, loyalty and thereby converting loyal customers into customers plus distributors for spreading positive WOM and thereby expanding the distribution network of the firm. Research on the recipient side of ‘Word-of-mouth’ by Duhan et al. (1997) has shown that consumers have been found to seek more ‘word-of-mouth’ information when they are faced with a decision that is more difficult. Hence, there is need to address the true drivers of creating distribution flexibility in the Indian context.

Sparks and Schenk (2006, p. 3) stated that, multilevel marketing organizations (MLMs) are emerging speedily but regularly counter marketing organizational type boasting nearly 10 million members and over US $20 billion in annual sales. In terms of regional figures of overall direct selling industry, South India remains a central hub for direct selling companies closely followed by North India. Flexibility along with market orientation within chronological sequencing also seems to be a major theme for future research (Levinthal and Fichman 1988).

Berry (1997) stated that, in lieu of a supply organization building a large administrative and sales force comprising of employees, self-employed independent contractors can be encouraged to build a sales organization of persons, by deploying a unique training system called ‘sponsoring’. In this system of sponsoring the distributor (sometimes referred to as an ‘independent contractor’ or ‘a direct salesperson’) the knowledge and expertise gets shared with the new entrants. In turn, for this commitment, the sponsor earns commission based on a percentage of the sales from those recruited, subject to the structure of the organization plan. As per the Debroy, FICCI (April 2013), NM companies’ sales revenues are rapidly increasing year by year with compounded annual growth rate (CAGR) of 20 %. Additional source of income and employment is motivating more people to join this new sales channel (Sreekumar 2007). On contrary note, they are several myths associated with NM and many who join NM get disillusion very quickly, they lose interest and give up as a result the NM companies have large number of customers on paper but find very few active distributors (Bloch 1996). Msweli-Mbanga (2001) opined that distributors generate more sales and recruit more distributors in their network, only if they are committed to their organizations and have positive perceptions towards the organization’s marketing mix. Distributor’s social contacts have a higher propensity to purchase and this would result in increased performance. On the flip side, these organizations seem to attract critics which have complained that the average Network Marketing (NM) distributor earns very little. In light of the above mentioned facts, there is a need to take up research study on NM practices in Indian context focusing on the impact of demographic and behavioural aspects of the distributors of NM companies.

Hence we considered the demographic variables which were adapted and developed from Richard (1992), customer orientations and distributor attributes from the research conducted done by Reinartz et al. (2004) and Macintosh (2007), in order to understand the impact of demographic variables and the behavioural aspects like customer orientations and distributor attributes impact on consumer buying behaviour in network marketing firms.

3 Gaps Addressed and Evolved Research Questions

Based on the literature review this study identified research gaps, developed research questions, formulated objectives and framed hypotheses which form the base for this chapter. Earlier studies have not covered a major area of distribution flexibility in NM firms. Hence, this study is focused on understanding customer buying behaviour, maintaining relationships and retaining them by attracting through ‘royalties’ and ‘empowering them to recruit’ prospective customers. Past studies have not covered Multilevel Marketing (MLM) in Non-store retail formats. Hence there is a strong need to explore various aspects of customers buying behaviour and membership of customers/distributors belonging to AIE and HUN for the following reasons:

• (1) The problems and prospects of Network marketing in India have not been researched in depth to date.

• (2) Earlier studies have not mentioned the key factors for increasing flexibility through NM.

• (3) Amway India and Hindustan Unilever Network is currently facing dip in sales revenues and market share is coming down due to high customer churn.

In order to fill these gaps, this chapter focused on comprehending NM practices in Indian context covering the demographic and behavioural aspects of the distributors belonging to NM companies like AIE and HUN. From the above gaps in literature the research questions which evolved are:

• RQ1: What are the ‘Sources of Information’ for customers to improve distribution flexibility?

• RQ2: What is the ‘Demographic profile’ of customers associated with network marketing firms?

• RQ3: What are the factors that motivate customers to buy/join network marketing companies?

• RQ4: What are the factors influencing distribution flexibility in network marketing firms?

4 Distribution Flexibility In Network Marketing-Objectives and Design

Network marketing organizations [NMOs] like Amway , Mary Kay , Nu Skin , Shaklee etc., have been growing their importance over the last few decades. Today two per cent of direct sales reference is generated by network marketing organization and business units (Coughlan and Grayson 1998). It is observed that ‘Attrition’ percentage has been distressingly high among Network Marketing distributors especially in India (differs from company to company and time to time). Misuse or abuse of practices by a few fly-by-night operators, lack of distributor motivation, high pricing, etc., necessitated further in understanding the network marketing practices in true spirit as an alternative distributor mechanism focusing on its dimensions and the perception of existing network marketing distributors. Further researchers (Xueming and Homburg 2007) opined that customer satisfaction generates free word of mouth and thereby leads to a positive impact on a company’s excellence in human capital (employee talent and manager superiority). In order to review the distribution strategies in NM companies, we formuated the objectives of this study as following

• 1. To ascertain flexible distribution strategies in network marketing companies.

• 2. To compare the customer perceptions on distribution flexibility of AIE and HUN.

• 3. To formulate models for flexible distribution strategies in AIE and HUN.

In order to fulfil the above objectives and comprehend the concept of NM we developed a framework based on the review of past studies in NM (see Fig. 4.1). Dash et al. (1976) in their study, found that the level of pre-purchase information regarding the brand effects consumer buying behaviour. Schiffman (2001) opined that consumers purchase involvement is indicated by the extent of information search and their past experience. Shim and Kotsiopoulos (1992) identified four information sources: fashion advertising, fashion publications, media and personal sources and concluded that these factors to be insignificant on re-patronage loyalty behaviour. Zeithaml et al. (1996) further found evidence that loyal customers spread positive word of mouth and exhibit repeat purchase behaviour and are also willing to pay higher price. Sreekumar (2007) further extended that the network is built by the distributors themselves as the loyal customer whom they recruit or sign up becomes a wholesale customer who in turn can sponsor others as sub-distributors known as ‘Down lines’, which is also termed as ‘Referral Marketing’ and the subsequent layers thus formed is termed as ‘ Multilevel Marketing’. The introducer is known as ‘Up Line’ distributors. On contrary, research studies (Wotruba et al. 1991; Bloch 1996; Berry 1997) found that if the customer is dissatisfied they not only the spread of negative word of mouth, but also switch from one product supplier to another. They further found evidence that, the direct selling industry suffers very low rates of distributor retention. The low retention rate in the industry results in high costs associated with engaging new salespeople, and significant costs arising from broken relationships with customers.

Fig. 4.1

Framework for multilevel marketing

5 Hypotheses Development

Thomas et al. (2005) found that there are significant differences in demographic variables between multilevel (ML) and single level (SL) forms of direct selling organizations, but none of these differences correspond to differences in quitting intentions. They are also found evidence that significant difference exist between ML and SL salespeople on the behavioural and attitudinal variables like job satisfaction , organizational commitment , perceived image of direct selling in the marketplace, the importance of the job characteristics of work rewards and career growth. Analysis revealed that the relationship between some of these variables and quitting intentions differed substantially between ML and SL salespeople. Hence the hypotheses formulated are

• H_o1.0: There is a significant relationship between demographic variables (Ho1.1 Age, Ho1.2 Sex, Ho1.3 Marital Status, Ho1.4 Education, Ho1.5 Occupation and Ho1.6 Monthly Income) of customers belonging to HUN and and AIE.

• Ho2.0: There is no significant association between ‘Consumer attributes’ and their Satisfaction of HUN and AIE.

6 Research Methodology

The data was collected using a structured questionnaire and distributed to customers of HUN and AIE from Hyderabad and Secunderabad, Telangana State. Reliability of the questionnaire is measured by using Cronbach’s alpha. For all the variables, in the research instrument, descriptive statistics are presented using mean, standard deviations and variances, etc. To test the hypotheses on relationships of model variable, Chi-square, ANOVA, multiple linear regression Analysis are used. These statistical tools are used with the help of Predictive Analytics Software (PASW) 21.0 Version.

6.1 Research Design

Greater Hyderabad, Telangana State consists of sixteen revenue mandal offices. The respondents were selected from fifteen revenue blocks only (as there is no proper response from the 16th Mandal). A structured questionnaire was distributed to 1032 Amway India and Hindustan Unilever Network  distributors of various levels, out of which only 602 were returned and only 600 respondents were considered for the study as their responses are complete in nature. The response rate is 58 %. A time period of about nine months from May 2011 to January 2012 was spent to collect the data. Finally the responses are analyzed using ‘descriptive’ and ‘inferential’ statistics. IBM-PASW version 21 was used for data analysis . Cross sectional descriptive research design was used. The data were collected through a structured questionnaire and distributed to customers who belong to HUN and AIE from Hyderabad and Secunderabad, Telangana State.

6.2 Sampling Design

• I Population The total regular AIE customers in Hyderabad and Secunderabad are 1750 and HUN are 1250 (N = 3000).

• II Sample Size The total sample size is 600, which is 20 % of the population. The study was conducted on 300 AIE and 300 HUN customers.

• III Determination of sample size For determination of the sample size, categorical sample size formula is being used. Set of alpha level a priori at 0.05 assumed by the

  $$\frac{{(1.65^{2} \times 1.167^{2} )}}{{(4 \times 0.03)^{2} }}$$

  author/researcher. The acceptable error was set at 3 % and an estimated standard deviation of Likerts’ 5 point scale. The following sample size formula of Cochran’s for continuous data are used

  $$n_{o} = \frac{{\left( {t^{2} \times \sigma^{2} } \right)}}{{d^{2} }}|||\,n_{o} = \frac{{\left( {1.65^{2} \times \sigma^{2} } \right)}}{{d^{2} }}||\,n_{o} = \frac{{\left( {1.65^{2} \times x^{2} } \right)}}{{\left( {z \times 0.03} \right)^{2} }} = n\,\,||\,n_{o} = \frac{{\left( {1.65^{2} \times 1.167^{2} } \right)}}{{\left( {4 \times 0.03} \right)^{2} }}||\,n_{o} = \frac{{\left( {1.65^{2} \times x^{2} } \right)}}{{y^{2} }} = 527$$

  The sample for the present study is 600 > 527 hence it is a valid sample.

• IV Sample Unit The regular customers of AIE and HUN belong to Greater Hyderabad and Secunderabad, Telangana State.

• V Sample Frame As AIE and HUN are private companies the details of distributors and customers were not disclosed, but permitted the researcher to interact with active distributors and regular customers at product distribution point and business building seminar/meetings at different location.

• VI Sampling Technique The sample had been drawn using Snowball sampling technique from 600 AIE and HUN customers through structured questionnaire in Hyderabad, Telangana State.

6.3 Data Collection Procedure

The data were collected through the field survey using structured questionnaires. The data were collected from 600 AIE and HUN customers randomly selected from point of sale (product delivery points) and at different ventures of business building seminars located at Khairatabad, Begumpet, Bharkatpura, etc., in Hyderabad and Secunderabad. The secondary data such as corporate CDs, literature and price list, etc., were collected from Head office, New Delhi and other regional offices Gurgoan, Chennai, Bangalore and Mumbai, etc., from various AIE and HUN officers.

Dependent Variable

The dependent variable is ‘Distribution Flexibility’ . Likert’s five-point scale was used to measured why customers purchase, become loyal and promote products through ‘positive’ and ‘referral’ marketing of products in HUN and AIE.

Independent Variables

The three independent variables taken in the study are: Network Management Support, Acquaintances and Obedience .

Reliability and Validity Analysis

The reliability of the scale was measured using Cronbach’s alpha. The list of item used in the questionnaire for independent and dependent variables and their reliabilities are summarized in Appendix 1.

7 Data Analysis and Findings

The major findings of the study are as follows: The mean age of overall 600 respondents was 33 years, for AIE Customers 34 and 32 years for HUN customers (see Table 4.1).

Table 4.1 Sample characteristics

7.1 Sample Description

Nearly half of the respondents (46 %) belong to 18 to 30 years age group, 30 % of respondents belong to 31–40 and 24 % of respondents belong to above 41 years age group. Two-third of the sample (66 %) is woman and only one-third of them (34 %) were men. Half of the sampled respondents are Graduates (50 %), one-fourths (26 %) of consumers are Professional students and have just done schooling (24 %). Two-third of the sampled respondents (66 %) were married and one-thirds of them (34 %) are single. Housewives (41 %) occupy a major share, 25 % of consumers are Govt. Employees, 20 % of consumers are Business people, 6 % of consumers are Agriculturists, 6 % of consumers are Professionals and 3 % of consumers are from ‘Other’ category. More than one-thirds of the sample (37 %), earn Rs. 20,001 and above, 34 % of consumers earn less than Rs. 10,000 and 29 % of consumers earn between Rs. 10,001 and Rs. 20,000 (see Table 4.1).

7.2 Demographic Variables of Amway India and Hindustan Unilever Network Respondents

To test the significant relationship between demographic variables of AIE and HUN customers ANOVA was used.

H_o1.0: There is a significant relationship between demographic variables (H_o1.1 Age, H_o1.2 Sex, H_o1.3 Marital Status, H_o1.4 Education, H_o1.5 Occupation and H_o1.6 Monthly Income) of customers belongs to AIE and HUN.

The ANOVA test results shows that the variables age does not differ significantly with, F(28, 571) = 0.757, p = 0.814 and all the other variables differ significantly like Gender with F(28, 571) = 1.539, p = 0.039; Marital Status with F(28, 571) = 1.762, p = 0.010; Occupation with F(28, 571) = 1.339, p = 0.116; Education with F(28, 571) = 2.167, p = 0.001; Monthly income with F(28, 571) = 1.586, p = 0.030 among AIE and HUN distributors from Table 4.2.

Table 4.2 ANOVA for demographics of AIE and HUN

Findings Majority of the HUN respondents are business people, whereas house wives are majority in AIE. Majority of the HUN respondents earn above Rs. 20,000 whereas majority of AIE consumers earn less than Rs. 20,000.

7.3 Consumer Attributes and Satisfaction

To test the significant association between consumer attributes of AIE and HUN, ANOVO was used. Consumer attributes like quality, advertisements, utility, biodegradable, advantages, concentrated, beliefs and reputation, status symbol and prices are high in AIE whereas personal volume, business volume, satisfaction, highly concentrated and beliefs and reputation are high in HUN. Service remains to be the same across two firms from Table 4.3.

Table 4.3 ANOVA for ‘consumer attributes’ and satisfaction of AIE and HUN

Ho2.0: There is no significant association between ‘Consumer attributes’ and their satisfaction of AIE and HUN.

7.4 Distribution Flexibility Strategies of AIE and HUN

Multiple regression models were developed for ‘Distribution Flexibility’ of AIE and HUN. The R square value explains 0.509, 50 % of the variation in ‘Distribution flexibility’ of HUN is explained by network management support, Acquaintances and Obedience . The R value of 0.509 is close to 1 Distributor of HUN has a high positive relationship with Network Management Support, Acquaintances and Obedience (see Table 4.4).

Table 4.4 Model summary of distribution flexibility for HUN ^b

The regression equation line for the above data is,

Distribution Flexibility of HUN = −0.632 + 0.998 (Network Management Support) + 0.0019 (Acquaintances) + 0.0169 (Obedience)

The above equation is the calculated as contribution for the tested elements to achieve Distribution Flexibility of HUN effectively. From the regression equation line one can notice that network management support, Acquaintances and Obedience all the factors have a positive impact on distribution flexibility for Hindustan Unilever Network.

Results Adjusted R Square 0.509, F-Statistic 104.367, p-value 0.000^a which means the hypothesis is not true. Further detailed analysis shows that there is a positive variation as given below. ‘NM Support’ , ‘Acquaintances’ and ‘Obedience ’ all are supporting with positive direction with 0.998, 0.0019 and 0.0169 respectively with negative constant, i.e. −0.632 for HUN from Table 4.5.

Table 4.5 Distribution flexibility model for HUN

The regression model for distribution flexibility of AIE indicates R value of 0.653 is close to 1, indicates a high positive relationship with network management support, Acquaintances and Obedience . The R square value explains 0.653, 65 % of the variation in distribution flexibility for AIE Enterprises is explained by Network Management Support, Acquaintances and Obedience from Table 4.6.

Table 4.6 Model summary of distribution flexibility for Amway^b

The regression equation line for the above data is

Distribution Flexibility for AIE = −1.282 + 0.326(Network Management Support) + 1.184(Acquaintances) + 0.029(Obedience).

From the regression equation line one can notice that network management support, acquaintances and obedience all the factors have a positive impact on distribution flexibility for Amway India Enterprises.

Results For ‘Distribution Flexibility’ of AIE, the most influencing elements are ‘Support’, ‘ acquaintances’ and ‘Obedience’ all these factors are supporting with positive direction with 0.326, 1.184 and 0.029, respectively, with negative constant, i.e. −1.282 from Table 4.7.

Table 4.7 Distribution flexibility model for Amway India

Findings In case of Amway the ‘distribution flexibility’ is contributed more by acquaintances followed by network management Support . The contribution of obedience is negligible. In case of HUN ‘Distribution Flexibility’ is contributed more by network management support followed by acquaintances. The contribution of obedience is negligible.

7.5 Sources of Information

Henry Garret Rank Scores have been calculated for eight possible ‘sources for information’ using: Percentage Position = $\frac{{100\,\left( {Rij\, - 0.5} \right)}}{Nj}$, Where R _ij  = Rank given for ith factor by jth individual, N _j  = Number of factors ranked by jth individual.

‘Word of mouth’ through friends and relatives are the major sources of information to customers and independent sales consultants and public events were found to be least preferred sources of information. The results of ‘Sources of Information’ for AIE and HUN are shown in Fig. 4.2.

Fig. 4.2

Sources of information

Findings distributor support is low in AIE when compared to HUN.

7.6 Factors Influencing Purchase Behaviour of consumers from network marketing

Henry Garret Rank Scores have been calculated for ten possible ‘Factors influencing customer buying behavior’ and found that ‘International Quality’, ‘Benefits’ and ‘Service’ are the key factors in customer buying behaviour from AIE and HUN (see Fig. 4.3).

Fig. 4.3

Factors influencing customer buying behaviour

Findings ‘International quality’ is comparatively high in AIE than HUN ‘Prices’ are perceived to be higher in HUN than AIE by customers.

8 Limitations and Managerial Implications

The study is limited to 16 mandals of Greater Hyderabad, Telangana State. Only specific products categories and attributes which are similar in both companies are taken for this study. The study is limited only to two specific companies, i.e. HUN and AIE, hence cannot be generalized.

It is suggested that the results of this study may help marketers, i.e. companies/distributors/customers respond to the ever changing needs of end users in an Indian Network marketing scenario. This study helps the retailers and mangers in redesigning customer retention through distribution flexibility strategies and taking appropriate measures to attend all classes of task definitions like purchase loyalty, purchase frequency and tenure by increasing the marketing efficiency. This study has shown how definitions and risk factors affect method of selling selection processes and underline the need to put concerted efforts to understand risk sensitive customer and distributor clusters and risk relieving strategies.

9 Conclusion

With the heightened level of competition in Indian network marketing scenario, an increasing number of network marketing entities are currently facing difficulties in operating profitability, as it is evident from the high churn rate. So, it is proposed that the findings from this study may enable producers to alter their responsibilities and redesign their flexible distribution strategies and marketing communication to retain the existing customers and also to attract prospective distributors. ‘Friends and relatives’ are identified to be as important sources of information through powerful ‘word of mouth’ which has found to be more credible than other commercial sources in re-patronage behaviour. Customer re-patronage behaviour is found to be high if the marketer offers an exemplary product mix at competitive prices, quality, flexible distribution service and point of sales, physical facilities to offer a better atmosphere across all segments of customers and distributors. HUN should match AIE in terms of product range. Thus, findings of this study addressed critical issues of distributor behaviour by developing an integrative theory supporting the sequential structure of the constructs in Network marketing. Given the absence of published academic literature relating to network marketing this study will add value to the existing ‘body of knowledge’ on this subject.

As budgetary expenses on independent sales consultants and public events are yielding low returns, it is advocated that it is better to spend less and invest in giving more incentives to customers and network marketers as they improve distribution flexibility and play an vital role in spread of positive WOM through ‘friends and relatives’. ‘International quality’, ‘advantage and benefits’ are dominant factors in consumer purchase decision. HUN should be on par with AIE in terms of quality. Though the study has indicated prices as least significant, others feel that product prices are exorbitant in price sensitive market especially in AIE than HUN. So, AIE must emphasize more on redesigning distribution strategies to suit the price sensitive Indian market. Overall it can be concluded that the factors ‘Network Management Support’ and ‘Acquaintances’ are more important for increasing ‘Distribution Flexibility’ than ‘Obedience ’ in ‘ Network Marketing’ companies. Therefore, attempt should be made to use social Network Media such as Facebook , Twitter , etc., between the customers and customer contacts with the company. Frequent customer meet should be arranged by the companies to facilitate ‘Network Management Support’ to the distributors.

Therefore this study emphasizes the importance of ‘Method of Selling’, driven by determinant ‘Network Marketing Organization’ which is decisive in determining repeat purchase and recruitment of new members. It is more pertinent to mention exemplary product mix, quality distributor service and facilities at product delivery points and facilities to offer a better atmosphere and environment that enhance customer plus distributor satisfaction.

Appendix 1

1.1 List of Dependent, Independent Variables and Their Reliabilities

Support (α = 0.826)

• I guide my down line in product-selling activities.

• I orient my down line into our practices and procedures.

• I recruit new members into the sales organization.

• I keep in touch with my down line.

Obedience (α = 0.853)

• I use my NMO products regularly participate in training and meetings organized by my NMO or my up line.

• I keep in touch with the personnel in the my NMO office.

• In my activities, I follow the model given by my sponsor (or up line) with extreme care.

• I follow the distributor contact with extreme care.

Acquaintances (α = 0.871)

• I aim at contributing to issues concerning direct selling and network outside the NW organization.

• I keep in touch with distributors in other direct selling and NM organizations.

• I aim at contributing to the development of direct selling and networking activity, e.g. through associations.

• I make recommendations to NMO concerning issues that affect the distributor network.

Distribution Flexibility (α = 0.71)

• I refer NW products to acquaintances to expand distribution.

• I recommend NW products to other people besides acquaintances.

• I keep in touch with my distributors regularly.

• I recommend NW membership to acquaintances to improve flexibility in distribution.