A Participatory Systems Mapping (PSM) based approach towards analysis of business sustainability of rural Indian milk dairies

Kamath, Vasanth; Seena Biju; Kamath, Giridhar B. Article A Participatory Systems Mapping (PSM) based approach towards analysis of business sustainability of rural Indian milk dairies Cogent Economics & Finance Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Kamath, Vasanth; Seena Biju; Kamath, Giridhar B. (2019) : A Participatory Systems Mapping (PSM) based approach towards analysis of business sustainability of rural Indian milk dairies, Cogent Economics & Finance, ISSN 2332-2039, Taylor & Francis, Abingdon, Vol. 7, Iss. 1, pp. 1-16, https://doi.org/10.1080/23322039.2019.1622172 This Version is available at: https://hdl.handle.net/10419/245243 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oaef20 Cogent Economics & Finance ISSN: (Print) 2332-2039 (Online) Journal homepage: https://www.tandfonline.com/loi/oaef20 A Participatory Systems Mapping (PSM) based approach towards analysis of business sustainability of rural Indian milk dairies Vasanth Kamath, Seena Biju & Giridhar B Kamath | To cite this article: Vasanth Kamath, Seena Biju & Giridhar B Kamath | (2019) A Participatory Systems Mapping (PSM) based approach towards analysis of business sustainability of rural Indian milk dairies, Cogent Economics & Finance, 7:1, 1622172, DOI: 10.1080/23322039.2019.1622172 To link to this article: https://doi.org/10.1080/23322039.2019.1622172 © 2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Published online: 03 Jun 2019. Submit your article to this journal Article views: 812 View related articles View Crossmark data GENERAL & APPLIED ECONOMICS | RESEARCH ARTICLE A Participatory Systems Mapping (PSM) based approach towards analysis of business sustainability of rural Indian milk dairies Vasanth Kamath 1 *, Seena Biju 2 and Giridhar B Kamath 3 Abstract: Drawing from the theories of Participatory Systems Mapping (PSM) this study presents an approach to analysing the business sustainability of entrepreneurial dairy ventures in India. The article begins with a general introduction to the small and medium scale dairy ventures in rural India, highlighting the prominent issues and challenges faced by the stakeholders. The second part demonstrates the use of the PSM framework in developing the Stock and flow diagram (SFD). Further, data from a local milk dairy is collected, and simulations are carried out between 2017–2025 using Vensim®. The outputs are analysed, and inferences are made. This study is expected to enable the policy makers towards the development of sustainable strategies for dairy businesses in general and enable the entrepreneur to analyse the future trends of the potential strategies under his consideration. Subjects: Dynamical Systems; Industrial Engineering & Manufacturing; Entrepreneurship and Small Business Management Keywords: Participatory Systems Mapping; entrepreneurship; milk dairy; system dynamics; simulations 1. Introduction India is one of the largest producers of milk in the world. This sector has both organised and unorganised players; the latter being more abundant in numbers (Kale, Ponnusamy, Chakravarthy, Vasanth Kamath ABOUT THE AUTHOR Dr. Vasanth Kamath is an Associate Professor in Operations and Information Sciences Management, T A Pai Management Institute. He teaches courses on System Dynamics, Operations Research, Operations Management, and Project Management. He is a member of the System Dynamics Society, and International Association of Engineers, London, UK. His methodological research focusses on methods and techniques for dealing with dynamically complex and uncertain policy issues. PUBLIC INTEREST STATEMENT “The dairy sector is one of the top-ranked sectors in India. The sector has players in the formal and informal sector, with the latter in plenty. The study provides a holistic view of the issues faced by the stakeholders, primarily the small and medium scaled dairy farmers. Based on group discussions and field studies, high production costs due to increasing fuel prices, lack of information to start and run the ventures, and low availability of veterinary consultants were the major issues. Also, this study demonstrates the use of System Dynamics simulation in the context of the sustainability of a rural milk dairy. The research provides the reader, an understanding of the practical issues faced by the dairy farmers and develop sustainable strategies to boost the sector. Also, it enables the reader to appreciate the usage of model-based policy support in the entrepreneurial context in general”. Kamath et al., Cogent Economics & Finance (2019), 7: 1622172 https://doi.org/10.1080/23322039.2019.1622172 © 2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Received: 16 February 2019 Accepted: 11 May 2019 First Published: 22 May 2019 *Corresponding author: Vasanth Kamath, Operations and Information science management, T A Pai Management Institute, India E-mail: [email protected] Reviewing editor: Yogesh Pai P, Manipal Institute of Management, Manipal Academy of Higher Education, Manipal, India Additional information is available at the end of the article Page 1 of 16 Sendhil, & Mohammad, 2018). The unorganised sector of dairy farming consists of farmers who primarily rely on milch animals to provide an additional source of family income (Sharma, Singh, Staal, & Delgado, 2002). To enable the producers in both sectors, the Government of India has announced many schemes for encouraging dairy farming. 1 Despite all these provisions, the dairy industry is witnessing many closures as far as the new ventures are concerned, primarily in rural settings. Some of the hedges to this industry are its skyrocketing prices of fuel and supplies, unavailability of fodder, lack of good veterinary consultants, and a dire need for a sound supply chain management system. Further, the lack of semiskilled/unskilled labour, and associated issues in a labour-intensive industry such as this, has led to the abrupt closure of several ventures. These issues stress the need for a study to answer the following questions: (a) What are the pressing issues impacting the sustainability of the small and medium scale dairy ventures? (b) How can these dairy ventures ensure sustainability in the light of some of the strategic decisions taken? To answer these questions, a literature review for developing a thorough grounding of the status quo of the dairy sector (section 3) was conducted. This section followed the objectives of the study in section 2. The research methodology (section 4) attempts to specify the process deployed in data collection, development of the model and validation of the results. Further, through PSM techniques, stakeholders’views about the sector are presented in section 5. The second question is answered through the simulation of a real-life case. Section 6 presents a case study of “Fresh and Natural”(name changed), a dairy start-up venture and the dairy farmer’s dilemma. To test the strategy portfolio for the future scenarios the SFD is developed, the underlying assumptions are mentioned in section 7. Section 8 presents the results of the simulation. The discussions and concluding remarks are offered in 9 and 10 respectively. Figure 1presents the paper structure. 2. Objectives of the study Through this manuscript, an attempt is made to identify the various issues faced by dairy farmers and other stakeholders in rural India. Using PSM as a foundation, a simulation model encapsulating the significant problems faced by an entrepreneur is developed. Further, an attempt to Objectives and research questions Data input from experts’ write-ups and literature analysis Issues identification and Scenario development Outcomes: Result and inferences Recommendations Development of simulation model Formulation of assumptions and relations between variables A case study of a rural dairy venture Methods and models Scenario to Strategy method System Dynamics model Figure 1. Paper structure. (Source: Authors) Kamath et al., Cogent Economics & Finance (2019), 7: 1622172 https://doi.org/10.1080/23322039.2019.1622172 Page 2 of 16 demonstrate the capability of model-based policy support is conducted using a case study of a typical dairy venture. The study is held in the Dakshina Kannada (DK) and Udupi Districts of Karnataka State in South India to enable policymakers to design transformational pathways towards sustainable business opportunities to the dairy businesses in the region. 3. Literature background 3.1. The dairy sector in general Globally, the dairy sector is facing a lot of uncertainties and challenges. There have been dynamic changes in consumer trends owing to the modernisation of the industry and the integrating of technologies (McMahon, Pieters, Schnuck, & Kroef, 2017). In continuum, this has also provided a plethora of opportunities. Gerosa and Skoet (2012) revealed that over forty years for all countries, the dietary energy intake from dairy products increased from 3.4–4.4 per cent. With an ever increase in population, the consumption rates are growing exponentially. It is estimated that industry is expected to generate revenues worth USD 442.32 billion in 2019 with a Compound Annual Growth Rate (CAGR) of 5 per cent. 2 The North American dairy industry is dominated by the United States of America with a market revenue at USD 48,506.40 million in 2011, 3 followed by Canada and Mexico. Similarly, Brazil and Argentina were the leading milk procuring countries in the South American continent (Bankuti, Damasceno, Schiavi, Kuwaraha, & Prizon, 2018). In Asia, India has come a long way to become one of the leading milk producing countries in the world. In its quest for self-reliance, the Indian dairy industry undertook structural changes and milk production increased four-fold over the last four decades. 3.2. The dairy sector in India The Indian dairy industry has been on a steady path of progression. It has grown from producing 17 million tons of milk in 1951 to 165 million tons in 2016–17 4 with a provisionally recorded gross output of 176.35 million tons for the year 2017–18. 5 The per capita availability of milk has grown from 178 grams per day in 1991–92 to 355 grams per day in 2016–17 which is comparable with the world per capita availability of milk at 289.31 grams per day for 2012 (Ohlan, 2016). The sector has both organised, as well as unorganised players operating with a large share of milk being produced by smallholders (Kale et al., 2018). The smallholders accounted for 62% of the milk produced which attributed to about 27% to the household income. These are marginal and small farmers (Sharma et al., 2002), and landless laborers (Aneja, 1980) who maintain one to three milch animals (Shukla & Brahmankar, 1999) of low genetic potential, primarily fed on by-products such as crop residues (Saadullah, 1989), reared with the help of under-employed family members (Sharma et al., 2002)andan objective to supplement the farmer’s income as well as to generate employment in the rural sector (Krishna Raj, 1980). Studies on the farmer’s income have hinted at an increase from 41% to 112% (Kalra, Singh, & Kumar, 2000;Kumar,2005;Patel,2003). Besides, the by-products of dairying, such as manure, help to improve the fertility and productivity of landholdings Chantalakhana and Skunmun (2001). The literature on dairy ventures in India is quite divided. While one strand of the research highlights the factors that hinder the growth of the sector, another highlights the growth opportunities for the industry. The first strand of literature encourages dairy farming and highlights that the entry timing could not have been any better . 6 Researchers like Rajeshwaran, Naik, and Dhas (2014) have mentioned that India has been experiencing a steady growth in demand for dairy products estimated at 6% to 8% per annum due to increasing demographic projection. Mahmood and Kundu (2008) also studied the demand characteristics of the dairy product and concluded that the increase is attributed to the changing demographic trends. This increasing trend leads to a demand-supply gap as the growth in supply is only 3% to 4% per annum as per the study conducted by (Rajeshwaran et al., 2014). With a positive Kamath et al., Cogent Economics & Finance (2019), 7: 1622172 https://doi.org/10.1080/23322039.2019.1622172 Page 3 of 16 demand-supply gap projection for milk and its products, the opportunities become attractive (Bhattacharya, Rao, & Gupta, 2014;Gokarn,2010). Moreover, the demand for other types of highadded-value dairy products ranging from packaged cheese and yoghurt, baby food supplements, dairy whiteners, ice creams, and probiotic dairy products is growing. These opportunities have led to many youngsters leaving their lucrative corporate careers and taking up dairy farming as a profession. 7 Another strand of the literature focusses on the challenges of dairy farming. Some of the specific issues that the sector is confronting are such as the high cost of milk production due to the low yield of milk (Hegde, 2001), low return due to improper feed practices (Saadullah, 1989), lack of dairy management practices (Khin Mar Oo, 2005), increase in fuel prices (Rangasamy & Dhaka, 2007a) that leading to increase in transportation and logistics costs (Rangasamy & Dhaka, 2007b), cost of milk reception and procurement (Chauhan, Kalra, Singh, & Raina, 2005; Rangasamy & Dhaka, 2007b), processing and manufacturing cost of dairy products (Ray, 2008), and reduced marketing margins (Yogi, Chauhan, & Sharma, 2007). These aspects pose a profound challenge to the sustainability of the dairy industry in India. Hegde (2001) suggests that the challenges in the dairy sector can be overcome by working towards reducing the cost of milk handling, clean milk production, active animal husbandry extension. This can happen with even simple, informal collaboration amongst the dairy players. Bulk procurement of fodder, partnership with agriculture farmers for green fodder, pooling of the vehicles used for transportation etc. This, in turn, facilitates a close dialogue with the farmers and such associations should be established and strengthened to acquire new knowledge and technologies and understand milk marketing scenario. 3.3. System dynamics and the dairy industry System Dynamics (SD) is a methodology proposed by Forrester (1961). This can be generally applied to studythedynamiccomplexityofdifferentsystemsinavarietyofsettings(Sterman,2000). What distinguishes SD from other methods of simulation is its ability to deal with non-linear behaviour of complex dynamic systems (Morecroft, 1988) and to describe any given system mathematically using quantitative or qualitative modes and appreciate the response of a system due to the inherent feedback structures. Modelling in SD consists of the necessary steps viz-a-viz, Problem identification, System Conceptualization, Model formulation, Simulation & validation, and Policy analysis & improvement (Sushil, 1993). Stanislao, Ford, Tedeschi, and Cannas (2012,2013); Lie and Rich (2016); Lie, Rich, and Burkart (2017), McRoberts, Nicholson, Blake, Tucker, and Padilla (2010) have worked on the application of SD in dairy farming. The contexts have been varying from the impact of genetics on the effects of marketing on the milk supply chain. However, it is an exciting observation that no papers are discussing the application of SD in studying the different operational strategies for a dairy, especially in the Indian context. Considering the size of the Indian market, it becomes relevant to position an application-based model which may be used as a teaching case for basic SD. This work aims at developing a model to analyse a practical situation of the future of an unorganised dairy business and propose solutions for its sustenance. 4. Methodology Post literature review, it can be summarised that the significant works in the field of dairy farming ventures in India are divided into two major strands. The first strand highlights the sector as promising and with very high potential. Whereas, the second strand focuses on the negative aspects of dairying and hints to proceed with caution. Through this study, an attempt is made to investigate and depict the actual picture at the ground level. This is achieved by conducting qualitative interviews amongst the different stakeholders regarding the underlying issues that affected the day to day functions. These qualitative interviews enabled the identification of significant problems where immediate policy intervention was needed. Kamath et al., Cogent Economics & Finance (2019), 7: 1622172 https://doi.org/10.1080/23322039.2019.1622172 Page 4 of 16 Further, the participants were encouraged to provide their views towards the development of a reliable simulation model by which one was able to explore the effects of critical issues influencing Dairy farmers. PSM framework (Wang & Cheong, 2005) was deemed appropriate. This framework was practical (see Figure 2) for building SD models for complex problems as it had an inherent ability to enhance the model’s reliability by combining several group process techniques—such as workshops, group discussions, brainstorming, and fieldwork—with SD modelling. The PSM framework makes full use of group techniques (Andersen, Richardson, & Vennix, 1997; Berard, 2010; Richardson & Andersen, 1995; Vennix, 1996) so that the model can reasonably incorporate a wide variety of knowledge, which includes systems thinking, SD, domain knowledge, and expertise. SD modelling is a rigorous method by which to study and manage complex systems (Sterman, 2000). The PSM framework covers the stages of the model-building process propounded by Sterman (2000) and includes problem articulation, formulating a dynamic hypothesis, formulating a simulation model, testing, and policy design and evaluation. In the modelling stage, the framework was used to develop a mental representation, identifying a causal loop diagram (CLD) and a stock and flow diagram (SFD) through which a simulation model can be prepared for the venture under consideration. The CLD links variables that have a causal interpretation and the SFD represents the structure of a target system with denotations of rates and accumulations. During this stage, mental representations were formalised using mathematical, logical, and theoretical means. Expert opinions were solicited to justify the model. Further, specific values required for the various stocks, flows and auxiliary variables were collected from a dairy venture belonging to one of the respondents. This was done on a convenience basis as the objective of the study was to demonstrate the capability of model-based policy support for different scenarios instead of arriving at generalisations. Yes Yes Yes Methods Group discussion Workshops Field surve y Establish a research group Modelling Problem analysis Preliminary mental representation Tentative mental representation Initial CLD and SFD Tentative CLD and SFD Formalisation Calibration Test and validation Experiment design Findings report Accurate? Passed? Accurate? No No Figure 2. The PSM framework. Note: CLD = causal loop diagram; SFD = stock and flow diagram (Source: Wang & Cheong, 2005) Kamath et al., Cogent Economics & Finance (2019), 7: 1622172 https://doi.org/10.1080/23322039.2019.1622172 Page 5 of 16 The robustness of the model developed was then tested for its causality using an approach followed by Roy and Mohapatra (2000), and robustness as suggested by Barlas (1994) for variations in the input parameters. The simulated behaviour of the model was studied and analysed. In this process, every variable was tested for dimensional consistency. The model was tested for extreme conditions (i.e., those that would never be observed in the real world). 5. Issues with the dairy industry in DK and Udupi district To identify the major issues, the driving factors, and the associated challenges in the dairy sector, stakeholder interviews primarily through the participatory methods were conducted. Further, the outputs were triangulated with the available literature (both scientific and the company reports). The participants in the interviews included academicians, policy makers, entrepreneurs, employees, veterinary consultants, and customers (Table 1). The interviews aimed to identify the areas of concern which potentially impact the sustainability of the ventures. The stakeholders identified various issues which were broadly grouped under the four crucial areas viz-a-viz, Government policies and awareness, Entrepreneurial issues, Workers and employment issues and Veterinary consultant issues. The stakeholders were further interviewed for their views. 5.1. Issues put forward by the academicians/policy makers The policymakers were positive about the potential of the Government schemes to promote dairy ventures. 8 They also mentioned that adequate information is provided in the Krishi Vigyana Kendra (KVK) 9 (Centre for Agriculture and Horticulture set up by the Government for farmers and entrepreneurs in every district). However, they mentioned that people very rarely making use of the facilities provided. The views of the participants (A2) are discussed below. Translated from local language: At KVK, we have maintained around 50 acres of farmland at Brahmavara, we have developed models of dairy and other animal husbandry units with an intent to provide an insight into aspects of dairying like basic requirements, animal housing, calf rearing, dung and urine management and others. We also conduct special workshops (free of cost) on topics like the selection of cows, transport of animals, daily care, feeding, healthcare, diseases, reproductive management etc. However, we have observed that the response is low. We wish that the people of the region make use of the state-of-the-art facilities that are provided here. Similarly, the academician (A1) mentioned: Table 1. Interviewee profiles ID Profile of the participants Academicians/Experts A1 Professor in Entrepreneurship A2 Policymaker in dairy farming Entrepreneurs E1 Dairy farmer (1 st generation) from DK District E2 Dairy farmer (2 nd generation) from Udupi District E3 Technologist turned Dairy farmer (1 st generation) from Udupi District E4 A former Dairy farmer who closed his business unit Employees EM1 Daily wage worker based from Udupi District EM2 A migrant worker from a neighbouring state on a fixed salary Veterinary Consultants V1 Veterinary consultant V2 Private Veterinary pharmacist Kamath et al., Cogent Economics & Finance (2019), 7: 1622172 https://doi.org/10.1080/23322039.2019.1622172 Page 6 of 16 Many promoters of small-scale dairies do not conduct the feasibility study well. With limited knowledge about the pros and cons of the venture, the promoters avail loan from co-operative banks and money lenders at high-interest rates. The improper planning often leads to failure of the enterprise. 5.2. Issues related to the farmers The farmers highlighted the issues that impacted them on a routine basis. The foremost was the rise in the fuel prices leading to increased costs of transportation, maintenance, and procurements. They perceived that they are unable to get the right price for the milk due to reasons related to increased rates of the fodder. Also, the imbalance in the ratio between the veterinary consultants/institutions to the number of cows was a vexing issue. Regarding the presence of facilities at the KVK, the farmers quoted inaccessibility due to the location as a constraint. The following are the view of participants E1, E2, and E3 respectively. One participant (E4) spoke about his story but refused to allow us to publish it in our manuscript due to social stigma. Prima-facie, it appeared to be a case of mismanagement of the venture due to lack of information and domain expertise. Translated from local language: I started this venture with great hope. However, the last few years have been very turbulent. The prices of fuel have skyrocketed in the previous few years. This has, in turn, increased transportation costs leading to increased operational expenditure. Also, the fodder availability is another concern, we usually stockpile the dry fodder (paddy grass) during the season and use it throughout the year, but then we do not get the green feed for our cattle (E1). The veterinary consultants are very few. It is difficult to schedule an appointment with them as they must cater to many clients. We wish the Government takes proper steps to increase the ratio of veterinary consultants and the animals (E2). I did not get the opportunity to go to KVK and see the facilities. It is in Brahmavara—Hebri road, which is very far from the place where I live. A single visit would consume at least half of my day. I do not understand why it was set-up at such a distant location (E3). 5.3. Issues related to the workers The local worker availability has always been an issue to the dairy farms in DK and Udupi districts. The two regions boast of a high average per-capita income in comparison to the others in the state. 10 Hence the wages are highly competitive. As a result, it becomes challenging to hire local workers considering excess operational costs. Most of the dairy ventures are forced to employ migrant workers from neighbouring states. This is accomplished through a local agent, who coordinates the labour supply for such enterprises. This has its limitations as the employees tend to be loosely controlled. Translated from local language: The wage that I get by working in the dairy venture is very less. A construction worker earns more than what I get. I am old now to engage myself in construction labour, and my children are earning, we are financially stable now, that is why I am willing to continue here (EM1). I am a resident of Uttar Pradesh. My family lives there. I get a decent salary here which is good enough to sustain both myself and my family back home. However, I don’t like this place. The cultures are different. I am facing challenges in getting accustomed to the local culture. Someday, I would want to go back and set-up my venture back at my home town (EM2). 5.4. Issues related to veterinary consultants The veterinary consultants highlighted the need for a higher number of medical practitioners to ensure that adequate service is being provided to the clients. They mentioned that most of the small-scale ventures buy animals from other enterprises at lower costs. These are the cows which are typically beyond their prime. Further, excessive cross-breeding has resulted in a decline in the quality of the milk. They also mentioned that the conditions in which the cattle are kept need to be improved. Kamath et al., Cogent Economics & Finance (2019), 7: 1622172 https://doi.org/10.1080/23322039.2019.1622172 Page 7 of 16 Notes 1. https://www.nabard.org/content.aspx?id=591. 2. https://www.prnewswire.com/news-releases/glo bal-dairy-industry—the-milky-way-271782401. html [Retrieved on 4 December 2018] . 3. https://www.businesswire.com/news/home/ 20140808005463/en/Research-Markets-Global-Dairy -Industry-Report-2014-2019 [Retrieved on 4 December 2018] . 4. https://www.nddb.coop/information/stats/milkpro dindia [Retrieved on 5 October 2018]. 5. https://www.indiatoday.in/pti-feed/story/milkproduction-up-6-6-pc-at-176-35-million-tonne-in -2017-18-1297732-2018-07-27, [Retrieved on 5October2018]. 6. http://www.indiadairy.com/dairy_advantage.html [Retrieved on 5 October 2018]. 7. https://www.thehindu.com/news/cities/ Mangalore/once-a-software-engineer-now -a-farmer/article7804873.ece[Retrieved on 5 October 2018]; https://timesofindia.indiatimes. com/city/bengaluru/Techies-quit-job-to-milk-dairy /articleshow/8543920.cms [Retrieved on 5 October 2018]. 8. https://www.nabard.org/content.aspx?id=591. 9. http://kvkudupi.in/. 10. http://www.cmdr.ac.in/editor_v51/assets/mono60.pdf, page 08, retrieved on 7 October 2018. References Andersen, D. F., Richardson, G. P., & Vennix, J. A. M. (1997). Group model building: Adding more science to the craft. System Dynamics Review,13(2), 187–201. doi:10.1002/(SICI)1099-1727(199722)13:2<187::AIDSDR124>3.0.CO;2-O Aneja, R. P. (1980). Bread and butter potential of dairy sector (pp. 16–39). Kurukshetra magazine: A journal on rural development, Government of India, Bombay. Bankuti, F. I., Damasceno, J. C., Schiavi, S. M., Kuwaraha, K. C., & Prizon, R. C. (2018). Structural features, labour conditions, and family succession in dairy production systems in Parana state, Brazil. Cahiers Agricultures,27(4), 1–11. doi:10.1051/cagri/ 2018028 Barlas, Y. (1994). Model validation in system dynamics. Proceedings of the International System Dynamics Conference.Scotland, UK: University of Stirling. doi:10.3168/jds.S0022-0302(94)77044-2 Berard, C. (2010). Group model building using system dynamics: An analysis of methodological frameworks. Electronic Journal of Business Research Methods,8(1), 35–45. Bhattacharya, R., Rao, N., & Gupta, A. S. (2014). Understanding Food Inflation in India. ADB South Asia Working Paper Series. Manila, Asian Development Bank. Chantalakhana, C., & Skunmun, P. (2001). Dairy development in thailand and a case study on environmental impacts of Peri-urban dairy colonies—part I smallholder dairy development. In D. Rangnekar & W. Thorpe (Eds.), Smallholder dairy production and marketing—opportunities and constraints, Proceedings of a South-South workshop held at nddb. Anand, India. Chauhan, A. K., Kalra, K. K., Singh, R. V., & Raina, B. B. (2005). Economic analysis of manufacturing milk products in a dairy plant. Research Bulletin. New Delhi: NDRI Publication. DuPuis, E. M. (2000). Not in my body: BGH and the rise of organic milk. Agriculture and Human Values,17(3), 285–295. doi:10.1023/A:1007604704026 Forrester, J. W. (1961). Industrial dynamics. Cambridge, Massachusetts: The MIT Press. Gerosa, S., & Skoet, J. (2012). Milk availability: Trends in production and demand and medium-term outlook. ESA Working paper No. 12-01, Agricultural Development Economics Division Food and Agriculture Organization of the United Nations. doi:10.1094/PDIS11-11-0999-PDN Gokarn, S. (2010). The price of protein. Monthly bulletin november 2010. New Delhi: Reserve Bank of India. Hegde, N. G. (2001). WTO challenges for Indian dairy farmers. Yojana,45(1), 34–35. Kale, R. B., Ponnusamy, K., Chakravarthy, A. K., Sendhil, R., & Mohammad, A. (2018). Future aspirations and planning of dairy farmers in India: Horizon 2020. Indian Journal of Animal Sciences,88(4), 493–498. Kalra, K. K., Singh, R. V., & Kumar, A. (2000). Optimisation model for resource allocation in mixed farming system of Haryana, Research Project Report: National Dairy Research Institute, Karnal, India. Khin Mar Oo. (2005). Knowledge and adoption of improved dairy management practices by women dairy farmers in Dharwad district (M.Sc. Thesis). University of Agriculture Sciences Dharwad. Krishna Raj. (1980). Indian dairyman (Vol. 32, pp. 12–18). New Delhi: IDA house publishers. Kumar, S. (2005). Statesman. A two-day National Seminar on Value Added Dairy Products organised jointly by the Dairy Technology Society of India (DTSI) and the National Dairy Research Institute (NDRI). Karnal, India. Lane, D. C. (2000). Diagramming conventions in system dynamics. The Journal of the Operational Research Society,51(2), 241–245. doi:10.1057/palgrave. jors.2600864 Lie, H., & Rich, K. M. (2016). Modelling dynamic processes in smallholder dairy value chains in Nicaragua: A system dynamics approach. International Journal on Food System Dynamics,7(4), 328–340. Lie, H., Rich, K. M., & Burkart, S. (2017). Participatory system dynamics modelling for dairy value chain development in Nicaragua. Development in Practice, 27(6), 785–800. doi:10.1080/ 09614524.2017.1343800 Mahmood, A., & Kundu, A. (2008). Demographic projections for India 2006-2051: Regional variations in Strategic analyses of the national river linking project (NRLP) of India Series 1India's water future : Scenarios and issues (pp. 101–113), eds. Amarasinghe, U. A., Shah, T., & ik, R.P.S., IMWI, Colombo, Sri Lanka McMahon, M., Pieters, L., Schnuck, P., & Kroef, R. (2017). Global dairy sector –Trends and opportunities. Netherlands: Deloitte consulting. McRoberts, K., Nicholson, C., Blake, R., Tucker, T., & Padilla, G. D. (2010). Dynamic assessment of rural dairy cooperative feasibility to improve livelihoods in South-Central Mexico. Proceedings of the 28th International Conference of the System Dynamics Society, Seoul, Korea. Morecroft, J. D. (1988). System dynamics and microworlds for policymakers. European Journal of Operational Research,35(3), 301–320. doi:10.1016/03772217(88)90221-4 Ohlan, R. (2016). Dairy economy of India: Structural changes in consumption and production. South Asia Research,36(2), 241–260. doi:10.1177/ 0262728016638731 Patel, A. (2003). Inaugural address. International Workshop on Livestock and Livelihoods: Challenges and Opportunities for Asia in the Emerging Market Environment. Anand, India. Kamath et al., Cogent Economics & Finance (2019), 7: 1622172 https://doi.org/10.1080/23322039.2019.1622172 Page 14 of 16 Rajeshwaran, S., Naik, G., & Dhas, A. C. (2014). Rising milk price–a cause for concern on food security. IIM Bangalore Research Paper No. 472. [Online] Retrieved from https://ssrn.com/abstract=2532842 Rangasamy, N., & Dhaka, J. P. (2007a). Milk procurement cost for co-operative and private dairy plants in Tamil Nadu –a comparison. Indian Journal of Agricultural Economics,62(4), 37–46. Rangasamy, N., & Dhaka, J. P. (2007b). Constraints faced by Co-operative and private dairy plants in Tamil NaduA comparative analysis. Indian Journal of Dairy Science,60(4), 300–306. Ray, J. (2008). Economics of manufacturing domestic milk products in West Tripura district (Unpublished M.Sc. Thesis). NDRI (Deemed University), Karnal, Haryana. Richardson, G. P., & Andersen, D. F. (1995). Teamwork in group model building. System Dynamics Review,11 (2), 113–137. doi:10.1002/(ISSN)1099-1727 Roy, S., & Mohapatra, P. K. J. (2000). Causality and validation of system dynamics models incorporating soft variables: establishing an interface with structural equation modelling. Paper presented at the 18th International Conference of The System Dynamics Society, Bergen, Norway. Saadullah, M. (1989). Availability of shrubs and tree fodders for farm animals in Bangladesh. In C. Devendra (Ed.), Proceedings of a workshop on Shrubs and tree fodders for farm animals in East and South-East Asia (pp. 221236). Singapore: IDRC (International Development Research Centre). Sharma, V. P., Singh, R. V., Staal, S., & Delgado, C. L. (2002). Annex-I: Critical issues for poor people in the Indian Dairy sector on the threshold of a new era. [Online] Retrieved from http://www.fao.org/ WAIRDOCS/LEAD/X6115E/x6115e0b.htm Shukla, R. K., & Brahmankar, S. D. (1999). Impact evaluation of operation flood on the rural dairy sector (pp. 110–117). New Delhi: National Council of Applied Economic Research. Stanislao, A. A., Ford, D., Tedeschi, L., & Armenia, S. (2013). Dairy business: Farmer education enables precision farming. Proceedings of the 31st International Conference of the System Dynamics Society. Cambridge, Massachusetts, USA. Stanislao, A. A., Ford, D., Tedeschi, L., & Cannas, A. (2012). Policy modeling for greenhouses gas emissions on dairy cattle sector: The importance of the milk production improvement. 30th International Conference of the System Dynamics Society.St. Gallen, Switzerland. doi:10.1094/PDIS-11-11-0999-PDN Sterman, J. D. (2000). Business dynamics systems thinking and modeling for a complex world. New York, NY: Irwin McGraw Hill. Sushil. (1993). System dynamics: A practical approach for managerial problems. Pennsylvania State University, New Delhi: Wiley Eastern Publication. Vennix, J. (1996). Group model building. New York: Wiley. Wang, W., & Cheong, F. (2005). A framework for the system dynamics (SD) modeling of the mobile commerce market. International Congress on Modeling and Simulation. [Online] Retrieved from https:// mssanz.org.au/modsim05/papers/wang_w1.pdf Yogi, R. K., Chauhan, A. K., & Sharma, S. P. (2007). Economics of milk marketing in Jaipur district of Rajasthan. Indian Journal of Dairy Sciences,60(4), 307–312. Annexure 1. The stock and flow diagram Jersey cost Holestein cost Fixed cost of livestock Milk obtained <TIME STEP> Bulk rate of milk Sales through milk business Manpower required Employee Salaries Average Salary per person Total Expenses <Fixed cost of livestock> <Employee Salaries> Net Profits Basic infrastructure Cost per shed Total cost of infrastructure <Total cost of infrastructure> Milk used for suckling Other expenses Utilities Veterinary Taxes <Sales through milk business> <Other expenses> Cost of fodder Green feed cost Dry feed cost Unit cost of cattle feed Unit cost of dry grass Units fed per Yea r Units CF per year Total sales Sales through male bulls Cost of male calf Sales through manure Cost per kg of manure Quantity of manure Quanitity produced per cow Sales through vermicompost <Quantity of manure> Cost per kg of vermicompost Concentrate feed cost Unit cost of concentrate feed Units of CF fed per year Milch fraction Average production Total livestock New calves Milch animals Births Maturity delay Male calves Gender fraction Fraction birth rate <Male calves> <Total livestock> <Total livestock> Livestock post milch life Milch life end Milch life Death rate Death fraction <advertising spending> Geriatirc cow deaths G Death fraction New livestock New Jersey New Holstein <New livestock> Growth Inflation Rate of growth <Units of CF fed per year> Initial cost Cattle cost Infrastructure cost Dilution fraction <Total livestock> Kamath et al., Cogent Economics & Finance (2019), 7: 1622172 https://doi.org/10.1080/23322039.2019.1622172 Page 15 of 16 © 2019 The Author(s). Thisopen access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. You are free to: Share —copy and redistribute the material in any medium or format. Adapt —remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution —You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. Cogent Economics & Finance (ISSN: 2332-2039) is published by Cogent OA, part of Taylor & Francis Group. Publishing with Cogent OA ensures: •Immediate, universal access to your article on publication •High visibility and discoverability via the Cogent OA website as well as Taylor & Francis Online •Download and citation statistics for your article •Rapid online publication •Input from, and dialog with, expert editors and editorial boards •Retention of full copyright of your article •Guaranteed legacy preservation of your article •Discounts and waivers for authors in developing regions Submit your manuscript to a Cogent OA journal at www.CogentOA.com Potential customers Customers new customers rate leaving customers Market size Seed customers Sales Sales size would be word of mouth sales would be advertising sales advertising effectiveness advertising spending Fraction would be with real prospects Obsolescence time <Milk obtained> WOM effectiveness Average family size Kamath et al., Cogent Economics & Finance (2019), 7: 1622172 https://doi.org/10.1080/23322039.2019.1622172 Page 16 of 16