Diversification in peri-urban agriculture: a case study in the Ruhr metropolitan region

References

• Assefa, T.T., Meuwissen, M.P.M., & Oude Lansink, A.G.J.M. (2016). Price risk perceptions and management strategies in selected European food supply chains: An exploratory approach. NJAS-Wageningen Journal of Life Sciences, 15–26. doi:10.1016/j.njas.2016.11.002
   Web of Science ®Google Scholar
• Aubry, C., & Kebir, L. (2013). Shortening food supply chains: A means for maintaining agriculture close to urban areas? The case of the French metropolitan area of Paris. Food Policy, 41, 85–93.
   Web of Science ®Google Scholar
• Barbieri, C., & Mahoney, E. (2009). Why is diversification an attractive farm adjustment strategy? insights from texas farmers and ranchers. Journal of Rural Studies, 25, 58–66.
   Web of Science ®Google Scholar
• Bodenschätzungsgesetz -BodSchätzG. (2007). Gesetz zur Schätzung des landwirtschaftlichen Kulturbodens. l. I S. 3150, 3176. Ed., Berlin, Germany: Bundestag der Bundesrepublik Deutschland.
   Google Scholar
• Carter, S. (1998). Portfolio entrepreneurship in the farm sector: Indigenous growth in rural areas? Entrepreneurship & Regional Development, 10(1), 17–32.
   Google Scholar
• Charness, G, Gneezy, U, & Imas, A. (2013). Experimental methods: eliciting risk preferences. Journal Of Economic Behavior & Organization, 87, 43-51. doi:
   Web of Science ®Google Scholar
• Clark, J.K., Munroe, D.K., & Mansfield, B. (2010). What counts as farming: How classification limits regionalization of the food system. Cambridge Journal of Regions, Economy and Society, 3(2), 245–259.
   Web of Science ®Google Scholar
• Core Team, R. 2016. “R: A language and environment for statistical computing.” Retrieved from http://www.R-project.org/.
   Google Scholar
• Cragg, J.G. (1971). Some statistical models for limited dependent variables with application to the demand for durable goods. Econometrica: Journal of the Econometric Society, 39(5), 829–844.
   Web of Science ®Google Scholar
• Ding, Y., Schoengold, K., & Tadesse, T. (2009). The impact of weather extremes on agricultural production methods: Does drought increase adoption of conservation tillage practices? Journal of Agricultural and Resource Economics, 34(3):395–411.
   Web of Science ®Google Scholar
• Dohmen, T., Falk, A., Huffman, D., Sunde, U., Schupp, J., & Wagner, G.G. (2011). Individual risk attitudes: Measurement, determinants, and behavioral consequences. Journal of the European Economic Association, 9(3), 522–550.
   Web of Science ®Google Scholar
• Dries, L., Pascucci, S., & Gardebroek, C. (2012). Diversification in Italian farm systems: Are farmers using interlinked strategies? New Medit, 11(4), 7–15.
   Web of Science ®Google Scholar
• El Benni, N., Finger, R., & Meuwissen, M. (2016). Potential effects of the Income Stabilization Tool (IST) in swiss agriculture. European Review of Agricultural Economics, 43, 475–502.
   Web of Science ®Google Scholar
• Ernwein, M. (2014). Framing urban gardening and agriculture: On space, scale and the public. Geoforum, 56, 77–86.
   Web of Science ®Google Scholar
• European Parliamentary Research Service. (2016). Farm diversification in the EU. In European Parliament: Briefing. Brussels, Belgium.
   Google Scholar
• Finger, R. (2016). Assessment of uncertain returns from investment in short rotation coppice using risk adjusted discount rates. Biomass and Bioenergy, 85, 320–326.
   Web of Science ®Google Scholar
• Gardner, B.L. (1994). Commercial agriculture in metropolitan areas: Economics and regulatory issues. Agricultural and Resource Economics Review, 23(1), 100–109.
   Google Scholar
• Greene, W.H. (2002). Econometric analysis. (5 ed). Upper Saddle River USA: Pearson Education, Inc.
   Google Scholar
• Haugen, M.S., & Vik, J. (2008). Farmers as entrepreneurs: The case of farm-based tourism. International Journal of Entrepreneurship and Small Business, 6(3), 321–336.
   Google Scholar
• Heimlich, R.E., & Barnard, C.H. (1992). Agricultural adaptation to urbanization: Farm types in northeast metropolitan areas. Northeastern Journal of Agricultural and Resource Economics, 21(1), 50–60.
   Google Scholar
• Huber, R., Flury, C., & Finger, R. (2015). Factors affecting farm growth intentions of family farms in mountain regions: Empirical evidence for Central Switzerland. Land Use Policy, 47, 188–197.
   Web of Science ®Google Scholar
• Ilbery, B.W. (1991). Farm diversification as an adjustment strategy on the urban fringe of the West Midlands. Journal of Rural Studies, 7(3), 207–218.
   Web of Science ®Google Scholar
• IT.NRW. 2011. “Agricultural Census Data 2010.” Landesbetrieb Information und Technik Nordrhein-Westfalen Retrieved January 31, 2016, from. https://www.landesdatenbank.nrw.de/ldbnrw/online.
   Google Scholar
• Jarosz, L. (2008). The city in the country: Growing alternative food networks in Metropolitan areas. Journal of Rural Studies, 24(3), 231–244.
   Web of Science ®Google Scholar
• Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica: Journal of the Econometric Society, 263–291. doi:10.2307/1914185
   Web of Science ®Google Scholar
• Kneafsey, M. (2010). The region in food—Important or irrelevant? Cambridge Journal of Regions, Economy and Society, 3(2), 177–190.
   Web of Science ®Google Scholar
• Knickel, K., Brunori, G., Rand, S., & Proost, J. (2009). Towards a better conceptual framework for innovation processes in agriculture and rural development: From linear models to systemic approaches. Journal of Agricultural Education and Extension, 15(2), 131–146.
   Google Scholar
• Knight, J., Weir, S., & Woldehanna, T. (2010). The role of education in facilitating risk-taking and innovation in agriculture. The Journal of Development Studies, 39(6), 1–22.
   Google Scholar
• Lange, A., Piorr, A., Siebert, R., & Zasada, I. (2013). Spatial differentiation of farm diversification: How rural attractiveness and vicinity to cities determine farm households’ response to the CAP. Land Use Policy, 31, 136–144.
   Web of Science ®Google Scholar
• Long, S.J. (1997). Regression models for categorical and limited dependent variables. Vol. 7, Advanced quantitative techniques in the social sciences. Thousand Oaks, USA: SAGE Publications Inc.
   Google Scholar
• Lovell, S.T. (2010). Multifunctional urban agriculture for sustainable land use planning in the United States. Sustainability, 2(8), 2499–2522.
   Google Scholar
• McClintock, N. (2010). Why farm the city? Theorizing urban agriculture through a lens of metabolic rift. Cambridge Journal of Regions, Economy and Society, 3(2), 191–207.
   Web of Science ®Google Scholar
• McNally, S. (2001). Farm diversification in England and Wales — What can we learn from the farm business survey? Journal of Rural Studies, 17(2), 247–257.
   Web of Science ®Google Scholar
• McNamara, K.T., & Weiss, C. (2005). Farm household income and On-and Off-farm Diversification. Journal of Agricultural and Applied Economics, 37(1), 37–48.
   Google Scholar
• Menapace, L., Colson, G., & Raffaelli, R. (2013). Risk aversion, subjective beliefs, and farmer risk management strategies. American Journal of Agricultural Economics, 95(2), 384–389.
   Web of Science ®Google Scholar
• Meraner, M., & Finger, R. (2017a). Risk perceptions, preferences and management strategies: Evidence from a case study using German livestock farmers. Journal of Risk Research, 1–26. doi:10.1080/13669877.2017.1351476
   PubMedGoogle Scholar
• Meraner, M., & Finger, R. (2017b). Data on German Farmers Risk Preference, Risk Perception and Risk Management Strategies Data in Brief, 15, 102–105.
   Google Scholar
• Meraner, M., Heijman, W., Kuhlman, T., & Finger, R. (2015). Determinants of farm diversification in the Netherlands. Land Use Policy, 42, 767–780.
   Web of Science ®Google Scholar
• Meraner, M., Pölling, B., & Finger, R. (2018). Data on farm diversification decisions and farmers’ risk preferences in the Ruhr Metropolitan region (Germany). Data in Brief, 18, 9–12.
   PubMedGoogle Scholar
• Meuwissen, M.P.M., Huirne, R.B.M., & Hardaker, B.J. (2001). Risk and risk management: An empirical analysis of Dutch livestock farmers. Livestock Production Science, 69(1), 43–53.
   Google Scholar
• Meyer, J. (2002). Expected utility as a paradigm for decision making in agriculture. In R.E. Just & R.D. Pope (Eds.), AComprehensive assessment of the role of risk in U.S. agriculture (pp. 3–19). Boston USA: Springer US.
   Google Scholar
• Mishra, A.K., El‐Osta, H.S., & Sandretto, C.L. (2004). Factors affecting farm enterprise diversification. Agricultural Finance Review, 64(2), 151–166.
   Google Scholar
• Mishra, A.K., Fannin, M.J., & Joo, H. (2014). Off-farm work, intensity of government payments, and farm exits: Evidence from a National Survey in the United States. Canadian Journal of Agricultural Economics/Revue Canadienne D’agroeconomie, 62(2), 283–306.
   Web of Science ®Google Scholar
• Monaco, F., Zasada, I., Wascher, D., Glavan, M., Pintar, M., Schmutz, U., … Sali, G. (2017). Food production and consumption: City regions between localism, agricultural land displacement, and economic competitiveness. Sustainability, 9(1), 96.
   Web of Science ®Google Scholar
• Mougeot, L.J.A. 2000. Urban agriculture: definition, presence, potentials and risks, and policy challenges. Cities Feeding People Series Report 31. International Development Research Centre (IDCR). Retrieved from https://idl-bnc.idrc.ca/dspace/bitstream/10625/26429/12/117785.pdf.
   Google Scholar
• Pfeifer, C., Jongeneel, R.A., Sonneveld, M.P.W., & Stoorvogel, J.J. (2009). Landscape properties as drivers for farm diversification: A Dutch case study. Land Use Policy, 26(4), 1106–1115.
   Web of Science ®Google Scholar
• Pölling, B., & Mergenthaler, M. (2017). The location matters: Determinants for “Deepening” and “Broadening” diversification strategies in ruhr metropolis’ urban farming. Sustainability, 9(7), 1168.
   Web of Science ®Google Scholar
• Pölling, B., Mergenthaler, M., & Lorleberg, W. (2016). Professional urban agriculture and its characteristic business models in Metropolis Ruhr, Germany. Land Use Policy, 58, 366–379.
   Web of Science ®Google Scholar
• Pölling, B., Sroka, W., & Mergenthaler, M. (2017). Success of urban farming’s city-adjustments and business models – Findings from a survey among farmers in Ruhr Metropolis, Germany. Land Use Policy, 69, 372–385.
   Web of Science ®Google Scholar
• Potter, C., & Lobley, M. (1996). The farm family life cycle, succession paths and environmental change in Britain’s countryside. Journal of Agricultural Economics, 47(1–4), 172–190.
   Google Scholar
• Ricker-Gilbert, J., Jayne, T.S., & Chirwa, E. (2011). Subsidies and crowding out: A double-hurdle model of fertilizer demand in Malawi. American Journal of Agricultural Economics, 93(1), 26–42.
   Web of Science ®Google Scholar
• Slovic, P., Fischhoff, B., & Lichtenstein, S. (1982). Why study risk perception? Risk Analysis, 2(2), 83–93.
   Google Scholar
• Thebo, A.L., Drechsel, P., & Lambin, E. (2014). Global assessment of urban and peri-urban agriculture: Irrigated and rainfed croplands. Environmental Research Letters, 9(11), 1–9.
   Web of Science ®Google Scholar
• van Raaij, F.W. (1981). Economic psychology. Journal of Economic Psychology, 1(1), 1–24.
   Web of Science ®Google Scholar
• van Veenhuizen, R., & Danso, G. 2007. Profitability and sustainability of urban and peri-urban agriculture.FAO, Agricultural Management, Marketing and Finance Occasional Paper 19. Rome.
   Google Scholar
• van Winsen, F., de Mey, Y., Lauwers, L., van Passel, S., Vancauteren, M., & Wauters, E. (2014). Determinants of risk behaviour: Effects of perceived risks and risk attitude on farmer’s adoption of risk management strategies. Journal of Risk Research, 19(1), 56–78.
   Web of Science ®Google Scholar
• Vuong, Q.H. (1989). Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica: Journal of the Econometric Society 57(2), 307–333.
   Google Scholar
• Weltin, M., Zasada, I., Franke, C., Piorr, A., Raggi, M., & Viaggi, D. (2017). Analysingbehavioural differences of farm households: An example of income diversification strategies based on European farm survey data.”. Land Use Policy, 62, 172–184.
   Web of Science ®Google Scholar
• Wilson, G.A. (2008). From ‘weak’ to ‘strong’ multifunctionality: Conceptualising farm-level multifunctional transitional pathways. Journal of Rural Studies, 3, 367–383.
   Google Scholar
• Zasada, I. (2011). Multifunctional peri-urban agriculture - A review of societal demands and the provision of goods and services by farming. Land Use Policy, 28(4), 639–648.
   Web of Science ®Google Scholar
• Zasada, I., Berges, R., Hilgendorf, J., & Piorr, A. (2013). Horsekeeping and the peri-urban development in the Berlin Metropolitan Region. Journal of Land Use Science, 8(2), 199–214.
   Google Scholar
• Zasada, I., Fertner, C., Piorr, A., & Nielsen, T.S. (2011). Peri-urbanisation and multifunctional adaptation of agriculture around Copenhagen. Geografisk Tidsskrift-Danish Journal of Geography, 111(1), 59–72.
   Web of Science ®Google Scholar
• Zeileis, A., Kleiber, C., & Jackman, S. (2008). Regression models for count data in R. Journal of Statistical Software, 27(8), 1–25.
   Web of Science ®Google Scholar