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To classify the food trends for the total population as inter- or pangenerational, we used disaggregated household-based consumption data on 60 food categories over the period from 1990 to 2020 in Switzerland. We followed six different cohorts with a range of 10 birth years each and estimated robust trends for each generation and each product. Our results show that especially for meat, different generations follow different trends and form ‘intergenerational’ trends for the total population, whereas beans and peas would be an example of products with an increasing consumption for every single generation and a ‘pangenerational’ trend. Our study is the first to suggest distinguishing inter- and pangenerational food trends and to cover the most disaggregated available food consumption data in Switzerland for the period from 1990 to 2020. Managers and policymakers should consider the mentioned differences in food consumption to mitigate errors in consumption projections, target consumers more effectively, and promote healthier food consumption.",{"EN":130},"Distinguishing inter- and pangenerational food trends",{"VOID":132},"[\"6934786993193634762\"]",{"VOID":134},"Adesogan AT, Dahl GE (2020) MILK Symposium Introduction: dairy production in developing countries. J Dairy Sci 103(11):9677–9680. https:\u002F\u002Fdoi.org\u002F10.3168\u002Fjds.2020-18313\nAepli M, Finger R (2013) Determinants of sheep and goat meat consumption in Switzerland. Agric Food Econ. https:\u002F\u002Fdoi.org\u002F10.1186\u002F2193-7532-1-11\nAristei D, Perali F, Pieroni L (2008) Cohort, age and time effects in alcohol consumption by Italian households: a double-hurdle approach. 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Front Nutr 9:870883. https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffnut.2022.870883\nTrondsen T, Braaten T, Lund E, Eggen AE (2004) Health and seafood consumption patterns among women aged 45–69 years. Food Qual Prefer 15(2):117–128. https:\u002F\u002Fdoi.org\u002F10.1016\u002FS0950-3293(03)00038-7\nVan Dijk M, Morley T, Rau ML, Saghai Y (2021) A meta-analysis of projected global food demand and population at risk of hunger for the period 2010–2050. Nat Food 2(7):494–501. https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs43016-021-00322-9\nVaterlaus MJ, Patten EV, Cesia R, Young JA (2015) The perceived influence of social media on young adult health behaviors. Comput Hum Behav 45:151–157. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.chb.2014.12.013\nVon Ow A, Waldvogel T, Nemecek T (2020) Environmental optimization of the Swiss population’s diet using domestic production resources. J Clean Prod 248:119241. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jclepro.2019.119241\nWilhelmina Q, Joost J, George E, Ruivenkamp G (2010) Globalization vs. localization: global food challenges and local solutions. Int J Consum 34(3):357–366. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fj.1470-6431.2010.00868.x\nWooldridge J (2013) Introductory econometrics: A modern approach, 5th edn. Cengage Learning, South-Western\nWu Y, Wang L, Zhu J, Gao L, Wang Y (2021) Growing fast food consumption and obesity in Asia: challenges and implications. Soc Sci Med 269:113601. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.socscimed.2020.113601\nYang SB (2020) A cohort analysis on sodium and sodium-calorie intake with the Korean National Health and Nutrition Examination Survey. Korean J Food Sci Technol 33(1):98–104. https:\u002F\u002Fdoi.org\u002F10.9799\u002Fksfan.2020.33.1.098\nYork R (2007) Demographic trends and energy consumption in European Union Nations, 1960–2025. Soc Sci Res 36(3):855–872. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ssresearch.2006.06.007\nZan HUA, Fan JX (2010) Cohort effects of household expenditures on food away from home. J Consum Aff 44(1):213–233\nZhang B, Srihari SN (2003) Properties of binary vector dissimilarity measures. CEDAR, State University of New York at Buffalo. https:\u002F\u002Fcedar.buffalo.edu\u002F~binzhang\u002FPapers\u002Fbin_CVPRIP03_propbina.pdf. Accessed 22 Dec 2022\nZeng L, Ruan M, Liu J, Wilde P, Naumova EN, Mozaffarian D, Zhang FF (2019) Trends in processed meat, unprocessed red meat, poultry, and fish consumption in the United States, 1999–2016. J Acad Nutr Diet. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jand.2019.04.004\nZhong F, Xiang J, Zhu J (2012) Impact of demographic dynamics on food consumption—a case study of energy intake in China. China Econ Rev 23(4):1011–1019. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.chieco.2012.05.005",{"VOID":136},"10.1186\u002Fs40100-023-00252-z","PUBLICATION","VERIFIED","2024-06-23T22:26:04.579+00:00","Auto Verify","https:\u002F\u002Fagrifoodecon.springeropen.com\u002Farticles\u002F10.1186\u002Fs40100-023-00252-z",[143,161],{"id":144,"sortIndex":19,"researcher":18,"roles":145,"affiliations":147,"properties":156,"displayName":158,"givenName":18,"familyName":18},"7030a4d7-91e7-4fc6-aae1-4b203071b6e3",[146],"AUTHOR",[148],{"id":149,"sortIndex":19,"affiliation":150,"properties":18},"438f6569-ec87-44b7-a16b-6547061d64dc",{"id":149,"createTime":18,"updateTime":18,"relativeEntities":151,"slug":18,"properties":152,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":155,"statistic":18},[],{"title":153},{"VI":154},"Socioeconomics, Agroscope, Ettenhausen, 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and food security after COVID-19: relocalizing food systems?",{"VOID":257},"[\"6564579862234771729\"]",{"EN":253},{"VOID":260},"Blog WFP. 2020 https:\u002F\u002Fwww.wfp.org\u002Fnews\u002Fcovid-19-will-double-number-people-facing-food-crises-unless-swift-action-taken. On calculations about the world undernourishment see https:\u002F\u002Fhungermap.wfp.org\u002F\nCEPAL. Informe Especial COVID-19 Enfrentar los efectos cada vez mayores del COVID-19 para una reactivación con igualdad: nuevas proyecciones. 2020 https:\u002F\u002Fwww.cepal.org\u002Fes\u002Fpublicaciones\u002F45782-enfrentar-efectos-cada-vez-mayores-covid-19-reactivacion-igualdad-nuevas\nFAO-FLAMA Newsletters (2020) Wholesale markets: action against COVID-19. http:\u002F\u002Fwww.fao.org\u002Famericas\u002Fpublicaciones-audiovideo\u002Fcovid19-y-sistemas-alimentarios\u002Fboletines-fao-flama\u002Fen\u002F\nILO Monitor (2020) COVID-19 and the world of work. Third edition. chrome-extension:\u002F\u002Fohfgljdgelakfkefopgklcohadegdpjf\u002Fhttps:\u002F\u002Fwww.ilo.org\u002Fwcmsp5\u002Fgroups\u002Fpublic\u002F---dgreports\u002F---dcomm\u002Fdocuments\u002Fbriefingnote\u002Fwcms_743146.pdf\nMahler DG, Lakner C, Castaneda RAA, Wu H (2020) Updated estimates of the impact of COVID-19 on global poverty. World Bank Blog. https:\u002F\u002Fblogs.worldbank.org\u002Fopendata\u002Fupdated-estimates-impact-covid-19-global-poverty\nWorld Economic Outlook (WEO) (2020) Forecast, World Bank. https:\u002F\u002Fwww.imf.org\u002Fen\u002FPublications\u002FWEO\u002FIssues\u002F2020\u002F06\u002F24\u002FWEOUpdateJune2020\nWorld Trade Organization information note 12 August 2020 (2020) “Trade costs in the time of global pandemic”. 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Belik",{"VOID":282},"[\"UqrZyKQAAAAJ\"]",{"url":18,"publisher":284,"properties":18},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":285,"slug":10,"properties":286,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":289,"manageAffiliations":302,"indexDatabases":313,"url":107,"thumbnailPath":18,"statistic":335,"gsStatistic":18,"type":115,"analyzePriority":18},[],{"issn":287,"title":288},{"VOID":13},{"EN":15},[290,294,298],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":291,"label":292,"description":293,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":295,"label":296,"description":297,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},{"id":34,"createTime":18,"updateTime":18,"relativeEntities":299,"label":300,"description":301,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":37},{},[303,308],{"id":41,"createTime":18,"updateTime":18,"relativeEntities":304,"slug":18,"properties":305,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":307,"statistic":18},[],{"title":306},{"EN":45},[47],{"id":49,"createTime":18,"updateTime":18,"relativeEntities":309,"slug":18,"properties":310,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":312,"statistic":18},[],{"title":311},{"EN":53},[],[314,321,328],{"id":57,"indexDatabase":315,"url":68,"indexYears":69,"academicFieldIds":320,"indexDatabaseRanking":74},{"id":59,"createTime":18,"updateTime":18,"relativeEntities":316,"label":317,"description":318,"key":65,"publicationTags":319,"standard":18},[],{"EN":62,"VI":62},{"EN":62,"VI":64},[67],[71,72,73],{"id":76,"indexDatabase":322,"url":89,"indexYears":18,"academicFieldIds":327,"indexDatabaseRanking":18},{"id":78,"createTime":18,"updateTime":18,"relativeEntities":323,"label":324,"description":325,"key":85,"publicationTags":326,"standard":18},[],{"EN":81,"VI":81},{"EN":83,"VI":84},[87,88],[91],{"id":93,"indexDatabase":329,"url":89,"indexYears":18,"academicFieldIds":334,"indexDatabaseRanking":18},{"id":95,"createTime":18,"updateTime":18,"relativeEntities":330,"label":331,"description":332,"key":102,"publicationTags":333,"standard":18},[],{"EN":98,"VI":98},{"EN":100,"VI":101},[104,88],[106],{"impactFactor":19,"impactFactorByYear":336,"i10Index":19,"i10IndexLast5Year":19,"totalPublication":110,"totalPublicationByYear":337,"totalCitation":19,"totalCitationByYear":338,"totalCitationPerPublication":19,"totalCitationPerPublicationByYear":339,"hindexLast5Year":19,"hindex":19},{},{"2021":112,"2022":112,"2023":112},{},{},"2020-09-17",2020,[87,104,74],{"id":344,"createTime":345,"updateTime":346,"relativeEntities":347,"slug":348,"properties":349,"entityType":137,"verifyStatus":138,"verifyTime":360,"verifyNote":140,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":361,"fullTextUrl":18,"authors":362,"publicationType":176,"publisherRelationship":415,"citationCount":19,"citationInfo":477,"publishDate":480,"publishYear":478,"citationAnalyzeStatus":17,"lastCitationAnalyze":481,"indexDatabases":482,"openAccess":18,"references":18,"isForceReanalyzing":244},"7466860e-f3b0-4ef1-80f6-7fb1cd406d50","2024-01-20T02:34:18.365+00:00","2026-07-14T04:05:27.316+00:00",[],"Examining-projection-bias-in-experimental-auctions-the-role-of-hunger-and-immediate-gratification",{"abstract":350,"title":352,"gsPaper":354,"references":356,"doi":358},{"EN":351},"The relevance of projection bias in decision making processes has been widely studied, but not specifically in experimental auctions. We study the role of projection bias in experimental auctions by examining the bidding behavior of hungry and non-hungry subjects on food products delivered either immediately after the auction or in 1 week’s time. Results indicate that the difference in bids between a hot state (hunger) and a cold state (satiation) almost doubles when subjects have to predict their future tastes versus when they bid for a product intended for immediate consumption. More specifically, when subjects have to predict their future willingness to pay from their current tastes, they tend to over-predict their hunger and under-predict satiation.",{"EN":353},"Examining projection bias in experimental auctions: the role of hunger and immediate gratification",{"VOID":355},"[\"9274848509081753053\"]",{"VOID":357},"Alfnes F (2007) Willingness to Pay Versus Expected Consumption Value in Vickrey Auctions for New Experience Goods. Am J Agric Econ 89(4):921–931\nBirch LL, Billman J, Richards SS (1984) Time of Day Influences Food Acceptability. Appetite 5(2):109–116\nBushong B, King LM, Camerer CF, Rangel A (2010) Pavlovian Processes in Consumer Choice: The Physical Presence of a Good Increases Willingness to Pay. Am Econ Rev 100(4):1556–1571\nBusse MR, Pope DG, Pope JC, Silva-Risso J (2012) Projection Bias in the Car and Housing Markets. Working Paper 18212. National Bureau of Economic Research, Cambridge, MA, http:\u002F\u002Fwww.nber.org\u002Fpapers\u002Fw18212\nConlin M, O’Donoghue T, Vogelsang TJ (2007) Projection Bias in Catolog Orders. Am Econ Rev 97(4):1217–1249\nCorrigan J, Drichoutis A, Lusk J, Nayga RM Jr, Rousu M (2012) Repeated Rounds with Price Feedback in Experimental Auction Valuation: An Adversarial Collaboration. Am J Agric Econ 94(1):97–115\nCorrigan JR, Rousu MC (2006a) The Effect of Initial Endowments in Experimental Auctions American Journal of Agricultural Economics 88 (2):448–457\nCorrigan JR, Rousu MC (2006b) Posted Prices and Bid Affiliation: Evidence from Experimental Auctions. American Journal of Agricultural Economics. 88(4)1078-1090\nDellaVigna S (2009) Psychology and Economics: Evidence from the Field. J Econ Lit 47(2):315–372\nDemont M, Rutsaert P, Ndour M, Verbeke W (2013a) Reversing Urban Bias in African Rice markets: Evidence from Senegal. World Development 45:63–74\nDemont M, Rutsaert P, Ndour M, Verbeke W, Seck PA, Tollens E (2013b) Experimental Auctions, Collective Induction and Choice Shift: Willingness-to-pay for Rice Quality in Senegal. European Review of Agricultural Economics 40(2):261–286\nDemont M, Zossou E, Rutsaert P, Ndour M, Van Mele P, Verbeke W (2012) Consumer valuation of improved rice parboiling technologies in Benin. 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Mark Sci 12(3):318–338\nJack FR, Piacentini MG, Schröder JA (1997) Perception of Fruit as a Snack: A Comparison with Manufactured Snack Foods. Food Qual Prefer 8(3):175–182\nKirchkamp O, Poen E, Reiß JP (2009) Outside options: Another reason to choose the first-price auction. Eur Econ Rev 53(2):153–169\nKramer FM, Rock K, Engell D (1992) Effects of Time of Day and Appropriateness on Food Intake and Hedonic Ratings at Morning and Midday. Appetite 18(1):1–13\nLoewenstein G (1996) Out of Control: Visceral Influences on Behavior. Organ Behav Hum Decis Process 65(3):272–292\nLoewenstein G (2005) Projection Bias in Medical Decision Making. Med Decis Making 25(1):96–104\nLoewenstein G, O’Donoghue R, Rabin M (2003) Projection Bias in Predicting Future Utility. Q J Econ 118(4):1209–1248\nLozano DI, Crites SL, Aikman SN (1999) Changes in Food Attitudes as a Function of Hunger. Appetite 32(2):207–218\nLusk J, Feldkamp T, Schroeder T (2004a) Experimental Auction Procedure: Impact on Valuation of Quality Differentiated Goods. American Journal of Agricultural Economics 86:389–405\nLusk JL, House LO, Valli C, Jaeger SR, Moore M, Morrow JL, Traill WB (2004b) Effect on information about benefits of biotechnology on consumer acceptance of genetically modified food: evidence from experimental auctions in the United States, England and France. European Review of Agricultural Economics 31(2):180–204\nMela DJ, Aaron JL, Gatenby SJ (1997) Relationships of Consumer Characteristics and Food Deprivation to Food Purchasing Behavior. Physiol Behav 60(5):1331–1335\nMenkhaus DJ, Borden GW, Whipple GD, Hoffman E, Field RA (1992) An Empirical Application of Laboratory Experimental Auctions in Marketing Research. J Agric Resour Econ 17(1):44–55\nMorawetz UB, De Groote H, Chege SK (2011) Improving the Use of Experimental Auctions in Africa: Theory and Evidence. J Agric Resour Econ 36(2):263–279\nNisbett RE, Kanouse DE (1968) Obesity, Hunger, and Supermarket Shopping Behavior. Proc Annu Convention Am Psycology Assoc 3:683–684\nRabin M (1998) Psychology and Economics. J Econ Lit 36(1):11–46\nRead D, Van Leeuwen B (1998) Predicting Hunger: The Effects of Appetite and Delay on Choice. Organ Behav Hum Decis Process 76(2):189–205\nScott TR (1990) Gustatory Control of Food Selection. In: Stricker EM (ed) Handbook of Behavioral Neurobiology, vol 10. Plenum Press, New York, pp 243–263\nShogren JF, Margolis M, Koo C, List JA (2001) A Random Nth-Price Auction. J Econ Behav Organ 46(4):409–421\nSoler F, Gil JM, Sánchez M (2002) Consumers’ acceptability of organic food in Spain. Results from an experimental auction market. Br Food J 104(8):670–687\nSymmonds M, Emmanuel JJ, Drew ME, Batterham RL, Dolan RJ (2010) Metabolic state alters economic decision making under risk in humans. PLoS One 5(6):e11090",{"VOID":359},"10.1186\u002Fs40100-015-0040-7","2024-05-15T03:02:21.050+00:00","https:\u002F\u002Fagrifoodecon.springeropen.com\u002Farticles\u002F10.1186\u002Fs40100-015-0040-7",[363,380,397],{"id":364,"sortIndex":19,"researcher":18,"roles":365,"affiliations":366,"properties":375,"displayName":377,"givenName":18,"familyName":18},"84db5296-9c67-48b1-8610-f917ed654432",[146],[367],{"id":368,"sortIndex":19,"affiliation":369,"properties":18},"78393456-1f8e-4da6-adba-cdcc13614978",{"id":368,"createTime":18,"updateTime":18,"relativeEntities":370,"slug":18,"properties":371,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":374,"statistic":18},[],{"title":372},{"VI":373},"Department of Agricultural Economics, E.T.S. Ingenieros Agrónomos Universidad Politécnica de Madrid, Madrid, Spain",[],{"title":376,"gsAuthor":378},{"VI":377},"Teresa Briz",{"VOID":379},"[\"-VLvOesAAAAJ\"]",{"id":381,"sortIndex":112,"researcher":18,"roles":382,"affiliations":383,"properties":392,"displayName":394,"givenName":18,"familyName":18},"0aba68fc-ffdb-49a1-9293-4ae19b67b473",[146],[384],{"id":385,"sortIndex":19,"affiliation":386,"properties":18},"1c0221cb-10ad-4bdd-8cc9-4a4b8ec628fc",{"id":385,"createTime":18,"updateTime":18,"relativeEntities":387,"slug":18,"properties":388,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":391,"statistic":18},[],{"title":389},{"VI":390},"Department of Agricultural Economics & Rural Development, Agricultural University of Athens, Athens, Greece",[],{"title":393,"gsAuthor":395},{"VI":394},"Andreas C. 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The purpose of this study is to contribute to the competitiveness of smallholder farmers in a more coordinated and sustainable way that promote their effective and efficient participation in high-value agro-food market chains. In particular, the study aims at determining the main role of households’ capitals, institutional, and access-related factors in conditioning the decision of smallholder farmers of African indigenous vegetables (AIVs) to access pillars of competitiveness in high-value market chains (HVMCs). For this purpose, a unique household-level data from a total of 1232 rural and peri-urban AIV-producing households were surveyed, and the data obtained were analysed by using a multivariate probit model. The results suggest that about two thirds of smallholder AIV farmers had access to at least one pillar of competitiveness in HVMCs. The model results show the presence of inter-dependency of household level decisions to access multiple pillars of competitiveness in HVMCs. Furthermore, the results also reveal that coping with shocks, coupled with access to information on market prices and warnings of unexpected events, contract farming, certification and modern irrigation technologies are the main conditioning factors to the access of the pillars of competitiveness by smallholder farmers. The promotion and implementation of a well-founded mobile phone-based information access platforms, as well as effective and efficient livelihood strategies that support smallholder farmers to access pillars of competitiveness, is of critical importance towards overcoming the major competitiveness constraints along high-value agro-food chains.","Các nông hộ nhỏ thường bị loại trừ khỏi sự tham gia hiệu quả và hiệu quả vào các chuỗi thị trường thực phẩm nông sản có giá trị cao do các rào cản cạnh tranh lớn và một số thất bại trên thị trường dọc theo các chuỗi này. Mục tiêu của nghiên cứu này là đóng góp vào khả năng cạnh tranh của các nông hộ nhỏ theo cách có sự phối hợp và bền vững hơn nhằm thúc đẩy sự tham gia hiệu quả và hiệu lực của họ vào các chuỗi thị trường thực phẩm nông sản có giá trị cao. Cụ thể, nghiên cứu nhằm xác định vai trò chính của các vốn của hộ gia đình, các yếu tố thể chế và liên quan đến quyền tiếp cận trong việc điều chỉnh quyết định của các nông hộ nhỏ trồng rau củ truyền thống châu Phi (AIVs) khi tiếp cận các trụ cột của khả năng cạnh tranh trong các chuỗi thị trường có giá trị cao (HVMCs). Để thực hiện điều này, một tập dữ liệu duy nhất ở cấp độ hộ gia đình từ tổng số 1232 hộ sản xuất AIVs ở vùng nông thôn và ngoại ô đã được khảo sát, và dữ liệu thu được đã được phân tích bằng mô hình hồi quy probit đa biến. Kết quả cho thấy khoảng hai phần ba các nông hộ AIV nhỏ có truy cập vào ít nhất một trụ cột của khả năng cạnh tranh trong HVMCs. Kết quả mô hình cho thấy sự tồn tại của sự phụ thuộc lẫn nhau của các quyết định ở cấp độ hộ gia đình trong việc tiếp cận nhiều trụ cột khả năng cạnh tranh trong HVMCs. Hơn nữa, kết quả cũng tiết lộ rằng việc đối phó với các cú sốc, kết hợp với quyền tiếp cận thông tin về giá thị trường và cảnh báo về các sự kiện bất ngờ, hợp đồng canh tác, chứng nhận và công nghệ tưới tiêu hiện đại là những yếu tố chính điều chỉnh việc tiếp cận các trụ cột khả năng cạnh tranh của các nông hộ nhỏ. Việc thúc đẩy và triển khai các nền tảng hỗ trợ thông tin dựa trên điện thoại di động được xây dựng hợp lý, cũng như các chiến lược sinh kế hiệu quả và đúng đắn hỗ trợ các nông hộ nhỏ tiếp cận các trụ cột khả năng cạnh tranh là điều cực kỳ quan trọng trong việc vượt qua những rào cản khả năng cạnh tranh lớn dọc theo các chuỗi thực phẩm nông sản có giá trị cao.",{"EN":494,"VI":495},"Determinants of the competitiveness of smallholder African indigenous vegetable farmers in high-value agro-food chains in Kenya: A multivariate probit regression analysis","Các yếu tố quyết định khả năng cạnh tranh của nông dân sản xuất rau củ truyền thống ở Kenya trong chuỗi thị trường thực phẩm nông sản có giá trị cao: Phân tích hồi quy probit đa biến",{"VOID":497},"[\"1351058791659347792\"]",{"VI":499},"nông hộ nhỏ, khả năng cạnh tranh, chuỗi thị trường thực phẩm nông sản có giá trị cao, rau củ truyền thống châu Phi, phân tích hồi quy probit đa biến",{"VOID":501},"10.1186\u002Fs40100-019-0122-z","2024-04-29T20:56:28.533+00:00",[504],"VI","https:\u002F\u002Fagrifoodecon.springeropen.com\u002Farticles\u002F10.1186\u002Fs40100-019-0122-z",[507,531,548,563,576],{"id":508,"sortIndex":19,"researcher":18,"roles":509,"affiliations":510,"properties":528,"displayName":530,"givenName":18,"familyName":18},"f52ef54e-fffc-49df-af13-eef066827fd8",[146],[511,519],{"id":512,"sortIndex":19,"affiliation":513,"properties":18},"a59f4b80-149a-42c9-8303-d5f752bacd11",{"id":512,"createTime":18,"updateTime":18,"relativeEntities":514,"slug":18,"properties":515,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":518,"statistic":18},[],{"title":516},{"VI":517},"Department of Agricultural Economics, Humboldt University of Berlin, Berlin, Germany",[],{"id":520,"sortIndex":112,"affiliation":521,"properties":527},"33bda68d-0224-4dc8-91af-bb8c54889862",{"id":520,"createTime":18,"updateTime":18,"relativeEntities":522,"slug":18,"properties":523,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":526,"statistic":18},[],{"title":524},{"VI":525},"Department of Agricultural Economics and Agribusiness Management, Egerton University, Egerton, Kenya",[],{},{"title":529},{"VI":530},"Evans Ngenoh",{"id":532,"sortIndex":112,"researcher":18,"roles":533,"affiliations":534,"properties":543,"displayName":545,"givenName":18,"familyName":18},"0aa29242-77d8-48e5-825e-d77c05a2a796",[146],[535],{"id":536,"sortIndex":19,"affiliation":537,"properties":18},"9622b8f7-4667-4987-90c2-1b6ab53fefff",{"id":536,"createTime":18,"updateTime":18,"relativeEntities":538,"slug":18,"properties":539,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":542,"statistic":18},[],{"title":540},{"VI":541},"Institute of Arid Lands Management, Laikipia University, Nyahururu, Kenya",[],{"title":544,"gsAuthor":546},{"VI":545},"Barnabas K. 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Singap Manag Rev 26(1):45–61",{},{"id":18,"text":663,"url":664,"identifiers":665},"Asfaw S, Mithöfer D, Waibel H (2010) What impact are EU supermarket standards having on developing countries' export of high-value horticultural products? Evidence from Kenya. J Int Food Agribusiness Mark 22(3–4):252–276","https:\u002F\u002Fdoi.org\u002F10.1080\u002F08974431003641398",{"openalex":666,"mag":667,"doi":668},"W2035486764","2035486764","10.1080\u002F08974431003641398",{"id":670,"text":671,"url":672,"identifiers":673},"0d5324db-f11d-470d-97b4-d1efc3c62d67","Bahta S, Malope P (2014) Measurement of competitiveness in smallholder livestock systems and emerging policy advocacy: an application to Botswana. Food Policy 49:408–417. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.foodpol.2014.10.006","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0306919214001481",{"doi":674},"10.1016\u002Fj.foodpol.2014.10.006",{"id":676,"text":677,"url":678,"identifiers":679},"4c68646b-0035-4279-8000-0006b275d4fa","Barrett CB (2008) Smallholder market participation: concepts and evidence from Eastern and Southern Africa. Food Policy 33(4):299–317","https:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs10440-022-00541-7",{"doi":680},"10.1007\u002Fs10440-022-00541-7",{"id":18,"text":682,"url":683,"identifiers":684},"Barrett CB, Bachke ME, Bellemare MF, Michelson HC, Narayanan S, Walker TF (2012) Smallholder participation in contract farming: comparative evidence from five countries. 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J Dev Agric Econ 7(7):254–261",{"doi":680},{"id":913,"createTime":914,"updateTime":915,"relativeEntities":916,"slug":917,"properties":918,"entityType":137,"verifyStatus":138,"verifyTime":930,"verifyNote":140,"languages":18,"translateLanguages":931,"viewCount":19,"primaryUrl":932,"fullTextUrl":18,"authors":933,"publicationType":176,"publisherRelationship":966,"citationCount":19,"citationInfo":1027,"publishDate":1029,"publishYear":653,"citationAnalyzeStatus":17,"lastCitationAnalyze":915,"indexDatabases":1030,"openAccess":18,"references":1031,"isForceReanalyzing":244},"10ad334b-09ef-4321-8007-1f37fa8a48bc","2024-02-13T00:37:41.496+00:00","2026-04-12T11:16:15.899+00:00",[],"Coping-with-food-and-nutrition-insecurity-in-Zimbabwe-does-household-head-gender-matter-",{"abstract":919,"title":922,"gsPaper":925,"keywords":927,"doi":928},{"EN":920,"VI":921},"On the basis of a large-scale nationally representative sample of household data from five pooled cross-section surveys conducted by the Zimbabwe Vulnerability Assessment Committee (ZimVAC), this study assesses the existence of gender differences in the vulnerability to food and nutrition insecurity, usage of consumption-based and livelihoods-based coping strategies, and the existence of gender heterogeneity in the correlation of usage of such coping strategies when confronted by food and nutrition insecurity. The study offers three main findings. Firstly, female-headed households are more susceptible to food and nutrition insecurity than those headed by males. Secondly, female-headed households are more likely to employ consumption-based coping strategies than their male counterparts, but there is no statistically significant difference in the usage of livelihoods-based coping strategies. Finally, whilst there is little evidence of gender heterogeneity in the correlation of the usage consumption-based coping strategies, there is overwhelming evidence that female-headed household heads are less likely to adopt livelihoods-based coping strategies when confronted with food and nutrition insecurity. The sum total of these findings is that whilst female-headed households are more prone to food insecurity than their male counterparts, they are less able to use livelihoods-based coping strategies to weather household food and nutrition insecurity than their male counterparts.","Dựa trên một mẫu dữ liệu hộ gia đình đại diện quy mô lớn từ năm cuộc khảo sát cắt ngang được tiến hành bởi Ủy ban Đánh giá Tổn thương Zimbabwe (ZimVAC), nghiên cứu này đánh giá sự tồn tại của sự khác biệt giới tính trong độ nhạy cảm với bất an thực phẩm và dinh dưỡng, việc sử dụng các chiến lược ứng phó dựa trên tiêu dùng và sinh kế, cũng như sự tồn tại của sự khác biệt giới tính trong mối tương quan của việc sử dụng các chiến lược ứng phó này khi đối mặt với bất an thực phẩm và dinh dưỡng. Nghiên cứu đưa ra ba phát hiện chính. Thứ nhất, các hộ gia đình do nữ giới đứng đầu có mức độ dễ bị tổn thương với bất an thực phẩm và dinh dưỡng cao hơn so với các hộ gia đình do nam giới đứng đầu. Thứ hai, các hộ gia đình do nữ giới đứng đầu có khả năng cao hơn trong việc áp dụng các chiến lược ứng phó dựa trên tiêu dùng so với các hộ gia đình do nam giới đứng đầu, nhưng không có sự khác biệt có ý nghĩa thống kê trong việc sử dụng các chiến lược ứng phó dựa trên sinh kế. Cuối cùng, trong khi có ít bằng chứng về sự khác biệt giới tính trong mối tương quan của việc sử dụng các chiến lược ứng phó dựa trên tiêu dùng, có bằng chứng rõ ràng rằng các đầu hộ gia đình nữ ít có khả năng áp dụng các chiến lược ứng phó dựa trên sinh kế khi phải đối mặt với bất an thực phẩm và dinh dưỡng. Tổng thể các phát hiện này cho thấy trong khi các hộ gia đình do nữ giới đứng đầu có mức độ nhạy cảm cao hơn với bất an thực phẩm thì họ lại kém hơn trong việc sử dụng các chiến lược ứng phó dựa trên sinh kế để vượt qua tình trạng bất an thực phẩm và dinh dưỡng trong hộ gia đình.",{"EN":923,"VI":924},"Coping with food and nutrition insecurity in Zimbabwe: does household head gender matter?","Đối phó với tình trạng bất an thực phẩm và dinh dưỡng tại Zimbabwe: Giới tính của người đứng đầu hộ gia đình có quan trọng không?",{"VOID":926},"[\"7624102259749556073\"]",{"VI":253},{"VOID":929},"10.1186\u002Fs40100-019-0144-6","2024-04-29T19:55:23.835+00:00",[504],"https:\u002F\u002Fagrifoodecon.springeropen.com\u002Farticles\u002F10.1186\u002Fs40100-019-0144-6",[934,951],{"id":935,"sortIndex":19,"researcher":18,"roles":936,"affiliations":937,"properties":946,"displayName":948,"givenName":18,"familyName":18},"0e7e0148-7de0-4822-831d-c98ec9d66f4f",[146],[938],{"id":939,"sortIndex":19,"affiliation":940,"properties":18},"45ceb6a4-2646-4326-ba29-63cf9da9d14d",{"id":939,"createTime":18,"updateTime":18,"relativeEntities":941,"slug":18,"properties":942,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":945,"statistic":18},[],{"title":943},{"VI":944},"Department of Economics, Bindura University of Science Education, Bindura, Zimbabwe",[],{"title":947,"gsAuthor":949},{"VI":948},"Terrence Kairiza",{"VOID":950},"[\"18kBwO8AAAAJ\"]",{"id":952,"sortIndex":112,"researcher":18,"roles":953,"affiliations":954,"properties":963,"displayName":965,"givenName":18,"familyName":18},"048a1ffa-3665-4203-b4b3-a281f08d4826",[146],[955],{"id":956,"sortIndex":19,"affiliation":957,"properties":18},"5194016d-3680-4733-b8fd-5c98ca7bdc5d",{"id":956,"createTime":18,"updateTime":18,"relativeEntities":958,"slug":18,"properties":959,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":962,"statistic":18},[],{"title":960},{"VI":961},"Food and Nutrition Council of Zimbabwe, Harare, Zimbabwe",[],{"title":964},{"VI":965},"George D. Kembo",{"url":932,"publisher":967,"properties":1023},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":968,"slug":10,"properties":969,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":972,"manageAffiliations":985,"indexDatabases":996,"url":107,"thumbnailPath":18,"statistic":1018,"gsStatistic":18,"type":115,"analyzePriority":18},[],{"issn":970,"title":971},{"VOID":13},{"EN":15},[973,977,981],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":974,"label":975,"description":976,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":978,"label":979,"description":980,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},{"id":34,"createTime":18,"updateTime":18,"relativeEntities":982,"label":983,"description":984,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":37},{},[986,991],{"id":41,"createTime":18,"updateTime":18,"relativeEntities":987,"slug":18,"properties":988,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":990,"statistic":18},[],{"title":989},{"EN":45},[47],{"id":49,"createTime":18,"updateTime":18,"relativeEntities":992,"slug":18,"properties":993,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":995,"statistic":18},[],{"title":994},{"EN":53},[],[997,1004,1011],{"id":57,"indexDatabase":998,"url":68,"indexYears":69,"academicFieldIds":1003,"indexDatabaseRanking":74},{"id":59,"createTime":18,"updateTime":18,"relativeEntities":999,"label":1000,"description":1001,"key":65,"publicationTags":1002,"standard":18},[],{"EN":62,"VI":62},{"EN":62,"VI":64},[67],[71,72,73],{"id":76,"indexDatabase":1005,"url":89,"indexYears":18,"academicFieldIds":1010,"indexDatabaseRanking":18},{"id":78,"createTime":18,"updateTime":18,"relativeEntities":1006,"label":1007,"description":1008,"key":85,"publicationTags":1009,"standard":18},[],{"EN":81,"VI":81},{"EN":83,"VI":84},[87,88],[91],{"id":93,"indexDatabase":1012,"url":89,"indexYears":18,"academicFieldIds":1017,"indexDatabaseRanking":18},{"id":95,"createTime":18,"updateTime":18,"relativeEntities":1013,"label":1014,"description":1015,"key":102,"publicationTags":1016,"standard":18},[],{"EN":98,"VI":98},{"EN":100,"VI":101},[104,88],[106],{"impactFactor":19,"impactFactorByYear":1019,"i10Index":19,"i10IndexLast5Year":19,"totalPublication":110,"totalPublicationByYear":1020,"totalCitation":19,"totalCitationByYear":1021,"totalCitationPerPublication":19,"totalCitationPerPublicationByYear":1022,"hindexLast5Year":19,"hindex":19},{},{"2021":112,"2022":112,"2023":112},{},{},{"pages":1024,"volume":1026},{"VOID":1025},"1-16",{"VOID":650},{"total":19,"publishYear":653,"statisticByYear":1028},{},"2019-12-28",[87,104,74],[1032,1035,1038,1041,1044,1047,1050,1054,1057,1060,1063,1069,1072,1075,1078,1081,1084,1087,1090,1096,1099,1102,1105,1111,1114,1120,1123,1126,1129,1136,1139,1144],{"id":676,"text":1033,"url":678,"identifiers":1034},"Christian P (2010) Impact of the economic crisis and increase in food prices on child mortality: exploring nutritional pathways. 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Elsevier 37(7):1222–1234",{"doi":680},{"id":676,"text":1079,"url":678,"identifiers":1080},"Gupta P, Singh K, Seth V, Agarwal S, Mathur P (2015) Coping strategies adopted by households to prevent food insecurity in urban slums of Delhi, India. Journal of Food Security 3:6–10",{"doi":680},{"id":676,"text":1082,"url":678,"identifiers":1083},"Horrell S, Krishnan P (2007) Poverty and productivity in female-headed households in Zimbabwe. Journal of Development Studies 43(8):1351–1380",{"doi":680},{"id":676,"text":1085,"url":678,"identifiers":1086},"Ivanic M, Will M (2008) Implications of higher global food prices for poverty in low-income countries-super-1. Agricultural Economics, International Association of Agricultural Economists 39(s1):405–416",{"doi":680},{"id":676,"text":1088,"url":678,"identifiers":1089},"Ivanic M, Will M, Zaman H (2012) Estimating the short-run poverty impacts of the 2010–11 surge in food prices. World Development 40(11):2302–2317",{"doi":680},{"id":1091,"text":1092,"url":1093,"identifiers":1094},"502ed3b4-a4f6-4869-919c-5a71a7f58f58","Kairiza T, Kiprono P, Magadzire V (2017) Gender differences in financial inclusion amongst entrepreneurs in Zimbabwe. Small Business Economics 48(1):259–272","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11187-016-9773-2",{"doi":1095},"10.1007\u002Fs11187-016-9773-2",{"id":18,"text":1097,"url":18,"identifiers":1098},"King-Dejardin A, Owens J (2009) Asia in the global economic crisis: Impacts and responses from a gender perspective. ILO Regional Office for Asia and the Pacific, Bangkok",{},{"id":18,"text":1100,"url":18,"identifiers":1101},"Klasen S, Lechtenfeld T, Povel F (2015) A feminization of vulnerability? Female headship, poverty, and vulnerability in Thailand and Vietnam. World Development 71(C):36–53",{},{"id":18,"text":1103,"url":18,"identifiers":1104},"Maxwell D, Caldwell R (2008) The coping strategies index field methods manual. Second Edition. Cooperative Assistance for Relief Everywhere (CARE). Atlanta, GA: CARE",{},{"id":1106,"text":1107,"url":1108,"identifiers":1109},"26ecf413-4bd2-457a-8982-bae7c86cb43d","Maxwell D, Ahiadeke C, Levin C, Armar-Klemesu M, Zakariah S, Lamptey GM (1999) Alternative food-security indicators: Revisiting the frequency and severity of coping strategies. Food Policy. https:\u002F\u002Fdoi.org\u002F10.1016\u002FS0306-9192(99)00051-2","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0306919299000512",{"doi":1110},"10.1016\u002Fs0306-9192(99)00051-2",{"id":676,"text":1112,"url":678,"identifiers":1113},"Peterman A, Behrman J, Quisumbing A (2010) A review of empirical evidence on gender differences in non-land agricultural inputs, technology, and services in developing countries. 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Washington, D.C.: IFPRI.",{"doi":680},{"id":676,"text":1127,"url":678,"identifiers":1128},"Quisumbing A, Meinzen-Dick R, Bassett L (2008) Helping women respond to the global food price crisis. Policy Brief 7. Washington, DC: IFRPI.",{"doi":680},{"id":18,"text":1130,"url":1131,"identifiers":1132},"Quisumbing A, Pandolfelli L (2009) Promising approaches to address the needs of poor female farmers: Resources, constraints, and interventions. World Development 38(4):581–592. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.worlddev.2009.10.006","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.worlddev.2009.10.006",{"mag":1133,"openalex":1134,"doi":1135},"2027752257","W2027752257","10.1016\u002Fj.worlddev.2009.10.006",{"id":18,"text":1137,"url":18,"identifiers":1138},"Reevy G, Maslach C (2001) People’s use of social support: gender and personality differences. Sex Roles 44:437–459",{},{"id":18,"text":1140,"url":1141,"identifiers":1142},"Skoufias E, Quisumbing A (2005) Eur J Dev Res 17:24. https:\u002F\u002Fdoi.org\u002F10.1080\u002F09578810500066498","https:\u002F\u002Fdoi.org\u002F10.1080\u002F09578810500066498",{"doi":1143},"10.1080\u002F09578810500066498",{"id":1145,"text":1146,"url":1147,"identifiers":1148},"5fb752ba-b0a6-41ba-96a0-4ac9d80564c6","Tirado M, Clarke R, Jaykus L-A, McQuatters-Gollop A, Frank J (2010) Climate change and food safety: a review. Food Research International 43:1745–1765","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0963996910002231",{"doi":1149},"10.1016\u002Fj.foodres.2010.07.003",{"id":1151,"createTime":1152,"updateTime":1153,"relativeEntities":1154,"slug":1155,"properties":1156,"entityType":137,"verifyStatus":138,"verifyTime":1169,"verifyNote":140,"languages":18,"translateLanguages":1170,"viewCount":19,"primaryUrl":1171,"fullTextUrl":18,"authors":1172,"publicationType":176,"publisherRelationship":1248,"citationCount":1310,"citationInfo":1311,"publishDate":1316,"publishYear":1312,"citationAnalyzeStatus":17,"lastCitationAnalyze":1317,"indexDatabases":1318,"openAccess":18,"references":1319,"isForceReanalyzing":244},"f521fe90-2b89-41e4-8029-18945480a411","2023-11-25T06:27:55.467+00:00","2026-02-02T17:46:36.521+00:00",[],"The-leading-role-of-perception-the-FACOPA-model-to-comprehend-innovation-adoption",{"abstract":1157,"title":1160,"gsPaper":1163,"keywords":1165,"doi":1167},{"EN":1158,"VI":1159},"In this work, we explore the link between the perception of complexity and the possibility of adopting precision agricultural tools (PATs). Many studies have analysed the role of perception, mostly considering it a determinant of adoption on the same level as other contextual factors. In contrast, this study contributes by assuming that farmers' perceived complexity is the main factor influencing their propensity to innovate and should be analysed on a different level. Starting from this assumption, a new theoretical model is proposed with the aim of studying the “factors–perception of complexity–adoption” (FACOPA) process. To test the validity of our hypothesis, a survey is conducted based on a purposive sample of 285 farmers. First, a linear regression model permits us to identify determinants of the perception of complexity. Then, a multinomial logistic model is used to determine which aspects of perceived complexity may affect the choice to adopt precision farming tools made by three different types of agricultural entrepreneurs: adopters, non-adopters, and planners. First, the linear regression results show that socio-structural variables have a logical relationship with perceived complexity, with age, farm size, the intensity of information and the intensity of work being significant. Then, the multinomial logistic model highlights that non-adopters perceive almost all aspects of complexity as barriers to adoption. Planners show a lower perception of complexity than non-adopters, with complexity being determined by financial and network aspects. The results provide interesting suggestions for policy-makers. Indeed, the FACOPA model offers insights into an intervention framework in which policy measures can be diversified to disseminate PATs based on farmer categories. Non-adopters require a broader set of policy instruments, while planners should be encouraged to become adopters through financial support and the activation of innovation networks.","Trong công trình này, chúng tôi khai thác mối liên hệ giữa nhận thức về độ phức tạp và khả năng áp dụng các công cụ nông nghiệp chính xác (PATs). Nhiều nghiên cứu đã phân tích vai trò của nhận thức, chủ yếu xem xét nó như một yếu tố quyết định việc thông qua tương đương với các yếu tố bối cảnh khác. Ngược lại, nghiên cứu này đóng góp bằng cách giả định rằng độ phức tạp mà nông dân nhận thức là yếu tố chính ảnh hưởng đến xu hướng đổi mới của họ và nên được phân tích ở một cấp độ khác. Bắt đầu từ giả định này, một mô hình lý thuyết mới được đề xuất với mục tiêu nghiên cứu quá trình “các yếu tố – nhận thức về độ phức tạp – việc thông qua” (FACOPA). Để kiểm tra tính hợp lệ của giả thuyết của chúng tôi, một cuộc khảo sát được thực hiện dựa trên mẫu định hướng gồm 285 nông dân. Trước tiên, một mô hình hồi quy tuyến tính cho phép chúng tôi xác định các yếu tố quyết định nhận thức về độ phức tạp. Sau đó, một mô hình logistic đa nhánh được sử dụng để xác định những khía cạnh của độ phức tạp nhận thức có thể ảnh hưởng đến sự lựa chọn áp dụng các công cụ nông nghiệp chính xác của ba loại doanh nhân nông nghiệp khác nhau: người áp dụng, người không áp dụng và người lập kế hoạch. Đầu tiên, kết quả hồi quy tuyến tính cho thấy rằng các biến xã hội - cấu trúc có mối quan hệ logic với độ phức tạp mà nông dân nhận thức, với tuổi tác, quy mô trang trại, mức độ thông tin và mức độ công việc đều có ý nghĩa. Sau đó, mô hình logistic đa nhánh nhấn mạnh rằng những người không áp dụng coi hầu hết các khía cạnh của độ phức tạp là rào cản đối với việc áp dụng. Những người lập kế hoạch cho thấy nhận thức về độ phức tạp thấp hơn so với những người không áp dụng, với độ phức tạp được xác định bởi các khía cạnh tài chính và mạng lưới. Kết quả cung cấp những gợi ý thú vị cho các nhà hoạch định chính sách. Thực tế, mô hình FACOPA cung cấp cái nhìn sâu sắc về một khung can thiệp trong đó các biện pháp chính sách có thể được đa dạng hóa để phổ biến các PATs dựa trên các loại nông dân. Những người không áp dụng cần một tập hợp rộng hơn các công cụ chính sách, trong khi những người lập kế hoạch nên được khuyến khích trở thành những người áp dụng thông qua hỗ trợ tài chính và kích hoạt các mạng lưới đổi mới.",{"EN":1161,"VI":1162},"The leading role of perception: the FACOPA model to comprehend innovation adoption","Vai trò dẫn dắt của nhận thức: mô hình FACOPA để hiểu rõ việc thông qua đổi mới",{"VOID":1164},"[\"7118333466872594017\"]",{"VI":1166},"đổi mới, nhận thức, nông nghiệp chính xác, mô hình FACOPA, áp dụng công cụ nông 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Document prepared for the European Parliament's Committee on Agriculture and Rural Development",{},{"id":1746,"createTime":1747,"updateTime":1748,"relativeEntities":1749,"slug":1750,"properties":1751,"entityType":137,"verifyStatus":138,"verifyTime":1748,"verifyNote":140,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":1760,"fullTextUrl":18,"authors":1761,"publicationType":176,"publisherRelationship":1777,"citationCount":18,"citationInfo":18,"publishDate":1839,"publishYear":1840,"citationAnalyzeStatus":17,"lastCitationAnalyze":18,"indexDatabases":1841,"openAccess":18,"references":18,"isForceReanalyzing":244},"0211c4bf-8784-4f5b-b532-3f004261b8ee","2024-01-11T02:18:48.324+00:00","2025-02-26T21:28:21.918+00:00",[],"Joint-ownership-by-farmers-and-investors-in-the-agri-food-industry-an-exploratory-study-of-the-limited-cooperative-association",{"abstract":1752,"title":1754,"references":1756,"doi":1758},{"EN":1753},"Since the 1990s, producers of farm commodities have been attempting to enter value-added agri-food sectors by means of joint ownership of hybrid cooperatives. New generation cooperatives, characterized by substantial supply and equity requirements, inspired much farm producer optimism before revealing weaknesses and limitations in the early 2000s. In response, recent innovations in US cooperative state law introduced the limited cooperative association (LCA), a new legal entity allowing joint ownership by member patrons and member investors to facilitate large-scale equity acquisition. However, business registration data indicate few such organizations have been formed in the agri-food industry. The LCA is adopted by several small-scale operations in niche markets such as lamb, elderberry, and non-GMO seed, but there is not much interest among business organizations in the commodity sector. This paper raises possible explanations for the limited adoption of the LCA, including the competing objectives of farmers and investors, the ambiguous legal interpretation of investor objectives, the superiority of other legal structures, and the lack of strategic advantages. The conclusion facilitates an invitation to further study the challenging future of farmer cooperatives in the agri-food industry.",{"EN":1755},"Joint ownership by farmers and investors in the agri-food industry: an exploratory study of the limited cooperative association",{"VOID":1757},"Baarda J (2006) Current issues in cooperative finance and governance. In: Cooperative programs, rural development. U.S. Department of Agriculture, Washington, D.C.\nBenos T, Kalogeras N, Verhees FJ, Sergaki P, Pennings JM (2016) Cooperatives’ organizational restructuring, strategic attributes, and performance: the case of agribusiness cooperatives in Greece. Agribusiness 32(1):127–150\nBeverland M (2007) Can cooperatives brand? Exploring the interplay between cooperative structure and sustained brand marketing success. Food Policy 32(4):480–495\nBrown L (2006) Innovations in co-operative marketing and communications. Centre for the Study of Co-operatives, University of Saskatchewan, Saskatoon\nBrown RB, Merrett CD (2000) The limited liability company versus the new generation cooperative: alternative business forms for rural economic development. In: ) (ed) Illinois Institute for Rural Affairs, Rural Research Report 11. Illinois Institute for Rural Affairs, Macomb\nBurress MJ, Cook ML, Klein PG (2008) The clustering of organizational innovation: developing governance models for vertical integration. Int Food Agribusiness Manage Rev 11(4):49–75\nChaddad FR, Cook ML (2004) Understanding New Cooperative Models: An Ownership-Control Rights Typology. Rev Agric Econ 26(3):348–360\nCook ML (1995) The future of US agricultural cooperatives: a neo-institutional approach. Am J Agric Econ 77(5):1153–1159\nCook ML, Iliopoulos C (1999) Beginning to inform the theory of the cooperative firm: emergence of the new generation cooperative. Finn J Bus Econ 4(99):525–535\nDean JB, Geu TE (2008) The uniform limited cooperative association act: an introduction. Drake J Agric Law 13:63–113\nDempsey JJ, Kumar AA, Loyd B, Merkel LS (2002) A value culture for agriculture: to become high-performing businesses, agricultural co-ops must move away from their traditional role as service providers. McKinsey Q(Summer):64–76. https:\u002F\u002Fgo.galegroup.com\u002Fps\u002Fi.do?p=AONE&sw=w&u=googlescholar&v=2.1&it=r&id=GALE%7CA90192563&sid=classroomWidget&asid=00032fdb\nDeng W, Hendrikse GW (2015) Managerial vision bias and cooperative governance. Eur Rev Agric Econ 42(5):797–828\nDrnevich PL, Croson DC (2013) Information technology and business-level strategy: toward an integrated theoretical perspective. MIS Q 37(2):483–509\nEversull E (2008) Co-ops ring up additional $14 billion in sales via other ownership structures. Rural Coop 75(6):18–19\nFerrell SL (2002) New generation cooperatives and the capper-Volstead act: playing a new game by the old rules. Okla City UL Rev 27:737–771\nFrederick DA (1998) The impact of LLCs on cooperatives: bane, boon, or non-event? J Coop 13:44–52\nGeu TE, Dean JB (2009a) The new uniform limited cooperative association act: a capital idea for principled self-help value added firms, community-based economic development, and low-profit joint ventures. Real Property Trust Estate Law J 44(1):55–205\nGeu TE, Dean JB (2009b) The uniform limited cooperative act: comparative leverage points and principles. Coop Account 62(1):3–12\nGrashuis J (2017) Branding by farmer cooperatives: an empirical study of trademark ownership. J Coop Organ Manag 5(2):57–64\nGrashuis J (2018) An exploratory study of cooperative survival: strategic adaptation to external developments. Sustainability 10(3):652\nGrashuis J, Cook M (2018) An examination of new generation cooperatives in the upper midwest: successes, failures, and limitations. Ann Public Coop Econ 89(4):623-644\nGrashuis J, Su Y (2018) A review of the empirical literature on farmer cooperatives: performance, ownership and governance, finance, and member attitude. Ann Public Coop Econ. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fapce.12205\nHanson M (2001) A new cooperative structure for the 21st century: the Wyoming processing cooperative law. Coop Account Fall 2001:3–9\nHardesty SD (2005) Cooperatives as marketers of branded products. J Food Distrib Res 36(1):237–242\nHarris A, Stefanson B, Fulton M (1996) New generation cooperatives and cooperative theory. J Coop 11(6):15–28\nHendrikse GW, Veerman CP (2001) Marketing co-operatives: an incomplete contracting perspective. J Agric Econ 52(1):53–64\nHöhler J, Kühl R (2017) Dimensions of member heterogeneity in cooperatives and their impact on organization - a literature review. In: Annals of public and cooperative economics. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fapce.12177\nHovelaque V, Duvaleix-Tréguer S, Cordier J (2009) Effects of constrained supply and price contracts on agricultural cooperatives. Eur J Oper Res 199(3):769–780\nKelley CR (2001) New generation farmer cooperatives: the problem of the just investing farmer. NDL Rev 77:185–246\nKenkel P, Park J (2007) Business models and producer-owned ventures: choices, challenges, and changes. J Agric Appl Econ 39(2):381–387\nKontogeorgos A (2012) Brands, quality badges and agricultural cooperatives: how can they co-exist? TQM J 24(1):72–82\nLiang Q, Hendrikse GW (2013) Cooperative CEO identity and efficient governance: member or outside CEO? Agribusiness 29(1):23–38\nLushin L (2010) A Trojan horse in our midst: ten faults of the limited cooperative association act. Coop Grocer 151:28–29\nMcCorriston S (2002) Why should imperfect competition matter to agricultural economists? Eur Rev Agric Econ 29(3):349–371\nMérel PR, Saitone TL, Sexton RJ (2009) Cooperatives and quality-differentiated markets: strengths, weaknesses, and modeling approaches. J Rural Coop 37(2):201–224\nMerlo C (2017) Crossing the merger finish line. In: Rural Cooperatives, September\u002FOctober 2017. U.S. Department of Agriculture, Washington, D.C.\nPasour EC, Rucker RR (2005) Plowshares and pork barrels: the political economy of agriculture. The Independent Institute, Oakland\nPatrie W (1998) Creating co-op fever: a rural developer’s guide to forming cooperatives. In: Rural Business-Cooperative Service, Service report 54. U.S. Department of Agriculture, Washington, D.C.\nPorter PK, Scully GW (1987) Economic efficiency in cooperatives. J Law Econ 30(2):489–512\nReynolds B (2012) Joint ventures and subsidiaries of agricultural cooperatives. In: Rural Business and Cooperative Programs, research report 226. U.S. Department of Agriculture, Washington, D.C.\nSaitone TL, Sexton RJ (2017) Concentration and consolidation in the U.S. food supply chain: the latest evidence and implications for consumers, farmers, and policymakers. Econ Rev 102:25–59 Federal Reserve Bank of Kansas City\nSenechal D (2007) Value-added business success factors—the role of investor attitudes and expectations. Ag Decision Maker 2007:5–6\nSexton RJ (1990) Imperfect competition in agricultural markets and the role of cooperatives: a spatial analysis. Am J Agric Econ 72(3):709–720\nSexton RJ (2013) Market power, misconceptions, and modern agricultural markets. Am J Agric Econ 95(2):209–219\nSoboh RAME, Lansink AO, Giesen G, van Dijk G (2009) Performance Measurement of the Agricultural Marketing Cooperatives: The Gap between Theory and Practice. Rev Agric Econ 31(3):446–469\nSpear R (2000) The co-operative advantage. Ann Public Coop Econ 71(4):507–523",{"VOID":1759},"10.1186\u002Fs40100-018-0118-0","https:\u002F\u002Fagrifoodecon.springeropen.com\u002Farticles\u002F10.1186\u002Fs40100-018-0118-0",[1762],{"id":1763,"sortIndex":19,"researcher":18,"roles":1764,"affiliations":1765,"properties":1774,"displayName":1776,"givenName":18,"familyName":18},"60dd918a-2258-4143-bf79-4c4976d889a5",[146],[1766],{"id":1767,"sortIndex":19,"affiliation":1768,"properties":18},"42121701-b9f5-4311-ace9-17c11e69ff66",{"id":1767,"createTime":18,"updateTime":18,"relativeEntities":1769,"slug":18,"properties":1770,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1773,"statistic":18},[],{"title":1771},{"VI":1772},"Department of Agricultural and Applied Economics, University of Missouri, Columbia, USA",[],{"title":1775},{"VI":1776},"Jasper 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study investigates the factors affecting the inter-organizational relationships and governance of firms in agri-food supply chains and assesses the influence that the current conditions of vertical coordination have on the economic performance of these firms. Research hypotheses describing the causal effects between the environment, product characteristics, inter-organizational relationships, relational governance, and firm economic performance are formulated and tested using a structural equation modeling approach. Data were gathered from a questionnaire administered via a direct survey to both farmers and processors in a traditional high-quality dairy sheep supply chain in the Italian region of Sardinia: the Pecorino Romano Protected Designation of Origin. Results point out the role of informal contractual arrangements in this local production system characterized by social cohesion, entailing higher product quality and better economic performance. Further, the study highlights the role of trust as a key variable for attaining collaborative paths along the agri-food supply chain, particularly between farmers and processors.",{"EN":1852},"A structural equation modeling analysis of relational governance and economic performance in agri-food supply chains: evidence from the dairy sheep industry in Sardinia (Italy)",{"VOID":1854},"Albisu LM, Frohberg K, Hartmann M (2010) Building sustainable relationships in agri-food chains: challenges from farm to retail. In: Fisher C, Hartmann M (eds) Agri-food chain relationships. CAB International, Wallingford, UK, p 25\nAramyan LH (2007) Measuring supply chain performance in the agri-food sector. PhD thesis Wageningen University, Wageningen\nAramyan LH, Kuiper M (2009) Analyzing price transmission in agri-food supply chains: an overview. Meas Bus Excell 13(3):3–12\nAramyan LH, Lansink A, van der Vorst J, van Kooten O (2007) Performance measurement in agri-food supply chains: a case study. Supply Chain Manage Int J 12(4):304–315\nArbuckle JL (2009) AMOS 18 user’s guide. Amos Development Corporation, Crawfordville\nBagozzi RP, Yi Y (1988) On the evaluation of structural equation models. J Acad Mark Sci 16(1):74–94\nBecattini G (1989) Modelli locali di sviluppo. Il Mulino, Bologna\nBernués A, Boutonnet JP, Casasús I, Chentouf M, Gabiña D, Joy M, López-Francos A, Morand-Fehr P, Pacheco F (2011) Economic, social and environmental sustainability in sheep and goat production systems. Zaragoza: CIHEAM \u002F FAO \u002F CITA-DGA, 2011. 379 p. (Options Méditerranéennes : Série A. Séminaires Méditerranéens; n. 100). 7. 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J Oper Manag 17(5):497–520\nChaddad F, Rodriquez-Alcala ME (2010) Inter-organizational relationships in agri-food systems: a transaction cost economics approach. In: Fischer C, Hartmann M (eds) Agri-food chain relationships, pp 45–60\nChin WW, Peterson RA, Brown SP (2008) Structural equation modeling in marketing: some practical reminders. J Mark Theory Pract 16(4):287–298\nClaro DP, Hagelaar G, Omta O (2003) The determinants of relational governance and performance: how to manage business relationships? Ind Mark Manag 32:703–716.\nde Marco G, Vrignaud P, Destrieux C, de Marco D, Testelin S, Devauchelle B, & Berquin P (2009). Principle of structural equation modeling for exploring functional interactivity within a putative network of interconnected brain areas. Magnetic Resonance Imaging, 27(1), 1–12. https:\u002F\u002Fdoi.org\u002F10.1016\u002FJ.MRI.2008.05.003.\nde Rancourt M, Carrère L (2011) Milk sheep production systems in Europe: diversity and main trends. 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Malorgio",{"url":1857,"publisher":1927,"properties":1983},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1928,"slug":10,"properties":1929,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":1932,"manageAffiliations":1945,"indexDatabases":1956,"url":107,"thumbnailPath":18,"statistic":1978,"gsStatistic":18,"type":115,"analyzePriority":18},[],{"issn":1930,"title":1931},{"VOID":13},{"EN":15},[1933,1937,1941],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":1934,"label":1935,"description":1936,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":1938,"label":1939,"description":1940,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},{"id":34,"createTime":18,"updateTime":18,"relativeEntities":1942,"label":1943,"description":1944,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":37},{},[1946,1951],{"id":41,"createTime":18,"updateTime":18,"relativeEntities":1947,"slug":18,"properties":1948,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1950,"statistic":18},[],{"title":1949},{"EN":45},[47],{"id":49,"createTime":18,"updateTime":18,"relativeEntities":1952,"slug":18,"properties":1953,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1955,"statistic":18},[],{"title":1954},{"EN":53},[],[1957,1964,1971],{"id":57,"indexDatabase":1958,"url":68,"indexYears":69,"academicFieldIds":1963,"indexDatabaseRanking":74},{"id":59,"createTime":18,"updateTime":18,"relativeEntities":1959,"label":1960,"description":1961,"key":65,"publicationTags":1962,"standard":18},[],{"EN":62,"VI":62},{"EN":62,"VI":64},[67],[71,72,73],{"id":76,"indexDatabase":1965,"url":89,"indexYears":18,"academicFieldIds":1970,"indexDatabaseRanking":18},{"id":78,"createTime":18,"updateTime":18,"relativeEntities":1966,"label":1967,"description":1968,"key":85,"publicationTags":1969,"standard":18},[],{"EN":81,"VI":81},{"EN":83,"VI":84},[87,88],[91],{"id":93,"indexDatabase":1972,"url":89,"indexYears":18,"academicFieldIds":1977,"indexDatabaseRanking":18},{"id":95,"createTime":18,"updateTime":18,"relativeEntities":1973,"label":1974,"description":1975,"key":102,"publicationTags":1976,"standard":18},[],{"EN":98,"VI":98},{"EN":100,"VI":101},[104,88],[106],{"impactFactor":19,"impactFactorByYear":1979,"i10Index":19,"i10IndexLast5Year":19,"totalPublication":110,"totalPublicationByYear":1980,"totalCitation":19,"totalCitationByYear":1981,"totalCitationPerPublication":19,"totalCitationPerPublicationByYear":1982,"hindexLast5Year":19,"hindex":19},{},{"2021":112,"2022":112,"2023":112},{},{},{"pages":1984,"volume":1986},{"VOID":1985},"1-21",{"VOID":1838},"2018-03-01",[87,104,74],{"id":1990,"createTime":1991,"updateTime":1992,"relativeEntities":1993,"slug":1994,"properties":1995,"entityType":137,"verifyStatus":138,"verifyTime":2004,"verifyNote":140,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":2005,"fullTextUrl":18,"authors":2006,"publicationType":176,"publisherRelationship":2059,"citationCount":18,"citationInfo":18,"publishDate":2120,"publishYear":1312,"citationAnalyzeStatus":17,"lastCitationAnalyze":18,"indexDatabases":2121,"openAccess":18,"references":18,"isForceReanalyzing":244},"87977a47-e26b-4bcc-b49b-821b2ec451d0","2024-02-08T18:31:34.450+00:00","2025-02-25T19:16:01.416+00:00",[],"Leveraging-farm-production-diversity-for-dietary-diversity-evidence-from-national-level-panel-data",{"abstract":1996,"title":1998,"references":2000,"doi":2002},{"EN":1997},"Dietary diversity is the key to improved health and nutrition. Farm production diversity has the potential of enhancing dietary diversity but this interrelationship varies and is ambiguous in many societies. To examine the effect of farm production diversity on household dietary diversity using nationally representative panel data of Bangladesh we have used Bangladesh Integrated Household Survey (BIHS) data collected by International Food Policy Research Institute (IFPRI) in 2011\u002F12, 2015 and 2018\u002F19. Total sample size is 11,720. For assessing dietary diversity we have used different indicators namely household dietary diversity score (HDDS) and food variety score (FVS). We have also used multiple methods for measuring farm production diversity including production diversity score, crop diversity score and Simpson diversification index. Poisson regression model has been used. Results revealed a strong positive association among farm production diversity, income and dietary diversity though the extent of the association is small. The variables such as market orientation, access to market, age and education are also found to influence on household dietary diversity. Our results propose that for increasing dietary diversity efforts should be taken to increase farm production diversity combined with diverse income and market access.\n",{"EN":1999},"Leveraging farm production diversity for dietary diversity: evidence from national level panel data",{"VOID":2001},"Ahmed T, Mahfuz M, Ireen S, Ahmed AS, Rahman S, Islam MM, Alam N, Hossain MI, Rahman SMM, Ali MM, Choudhury FP, Cravioto A (2012) Nutrition of children and women in Bangladesh: trends and directions for the future. J Health Pop Nutr 30(1):1\nAhmed AU, Ahmad K, Chou V, Hernandez R, Menon P, Naeem F, Naher F, Quabili W, Sraboni E, Yu B, Hassan Z (2013) The status of food security in the feed the future zone and other regions of Bangladesh: results from the 2011–2012. Bangladesh integrated household survey, Project report submitted to the US Agency\nAi C, Norton EC (2003) Interaction terms in logit and probit models. Econ Lett 80:123–129. https:\u002F\u002Fdoi.org\u002F10.1016\u002FS0165-1765(03)00032-6\nAllen S, de Brauw A (2018) Nutrition sensitive value chains: theory, progress, and open questions. Glob Food Secur 16:22–28. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.gfs.2017.07.002\nAnnim SK, Frempong RB (2018) Effects of access to credit and income on dietary diversity in Ghana. Food Secur 10(6):1649–1663. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12571-018-0862-8\nBabatunde RO, Qaim M (2010) Impact of off-farm income on food security and nutrition in Nigeria. Food Policy 35(4):303–311. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.foodpol.2010.01.006\nBellon MR, Ntandou-Bouzitou GD, Caracciolo F (2016) Onfarm diversity and market participation are positively associated with dietary diversity of rural mothers in southern Benin, West Africa. PLoS ONE 11(9):e0162535\nBelton B, van Asseldonk IJM, Thilsted SH (2014) Faltering fisheries and ascendant aquaculture: implications for food and nutrition security in Bangladesh. Food Policy 44:77–87\nBenfica R, Kilic T (2016) The effects of smallholder agricultural involvement on household food consumption and dietary diversity: evidence from Malawi. IFAD Research Series 4. International Fund for Agricultural Development (IFAD), Rome\nBrambor T, Clark WR, Golder M (2006) Understanding interaction models: improving empirical analyses, 1. Polit Anal 4:63–82. https:\u002F\u002Fdoi.org\u002F10.1093\u002Fpan\u002Fmpi014\nBurlingame B, Dernini S (eds) (2012) Sustainable diets and biodiversity: directions and solutions for policy, research and action. FAO and Bioversity International, Rome\nCarletto C, Corral P, Guelfi A (2017) Agricultural commercialization and nutrition revisited: empirical evidence from three African countries. Food Policy 67:106–118\nChegere MJ, Stage J (2020) Agricultural production diversity, dietary diversity and nutritional status: panel data evidence from Tanzania. World Dev 129:104856. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.worlddev.2019.104856\nChinnadurai M, Karunakaran KR, Chandrasekaran M, Balasubramanian R, Umanath M (2016) Examining linkage between dietary pattern and crop diversification: an [sic] evidence from Tamil Nadu. Agric Econ Res Rev 29:149–160\nDavis B, Di Giuseppe S, Zezza A (2014) Income diversification patterns in rural sub-Saharan Africa: reassessing the evidence. World Bank Policy Research Working Paper, 7108\nDavis B, Giuseppe DS, Zezza A (2017) Are African households (not) leaving agriculture? Patterns of households’ income sources in rural sub-Saharan Africa. Food Policy 67:153–174\nDeb U (2014) Dynamics of rural livelihoods in Bangladesh and India: insights. Paper presented at the Pre-conference Mini-symposium on “Rapid Transformation of Rural Economies in South Asia: Insights from Village Dynamics Studies”, organized as part of the 8th Conference of the Asian Society of Agricultural Economists (ASAE), held on 14 October 2014 at the BRAC Centre for Development Management (BRAC-CDM), Savar, Dhaka, Bangladesh\nDillon A, McGee K, Oseni G (2014) Agricultural production, dietary diversity, and climate variability. Policy Research Working Paper No. 7022. The World Bank, Washington, DC\nDoan D (2014) Does income improve diet diversity in China? Paper presented at 58th annual conference of the Australian agricultural and resource economics society, Port Macquarie, New South Wales, 4–7 Feb 2014\nDrescher LS, Thiele S, Roosen J, Mensink GB (2009) Consumer demand for healthy eating considering diversity—an economic approach for German individuals. Int J Consum Stud 33:684–696\nDrewnowski A, Henderson AS, Driscoll A, Rolls BJ (1997) The Dietary Variety Score: assessing diet quality in healthy young and older adults. J Am Diet Assoc 97:266–271\nFanzo J, Hunter D, Borelli T, Mattei F (eds) (2013) Diversifying food and diets: using agricultural diversity to improve nutrition and health. Routledge, London\nFAO (2011) Guidelines for measuring household and individual dietary diversity. FAO, Rome\nFAO (2013) The state of food and agriculture: food systems for better nutrition. FAO, Rome\nFAO (2014) The state of food and agriculture: innovation in family farming. Food and Agriculture Organization of the United Nations, Rome\nFongar A, Gödecke T, Aseta A, Qaim M (2019) How well do different dietary and nutrition assessment tools match? Insights from rural Kenya. Public Health Nutr 22(3):391–403\nGodecke T, Stein AJ, Qaim M (2012) The global burden of chronic and hidden hunger: trends and determinants. Glob Food Secur 17:21–29\nHerrero M, Thornton PK, Notenbaert AM, Wood S, Msangi S, Freeman HA (2010) Smart investments in sustainable food production: revisiting mixed crop–livestock systems. Science 327:822–825. https:\u002F\u002Fdoi.org\u002F10.1126\u002Fscience.1183725\nHirvonen K, Hoddinott J (2017) Agricultural production and children’s diets: evidence from rural Ethiopia. Agric Econ 48(4):469–480\nIFAD, UNEP (2013) Smallholders, food security and the environment. International Fund for Agricultural Development and United Nations Environment Programme, Rome and Nairobi\nJones AD (2017) Critical review of the emerging research evidence on agricultural biodiversity, diet diversity, and nutritional status in low- and middle-income countries. Nutr Rev 75(10):769–782. https:\u002F\u002Fdoi.org\u002F10.1093\u002Fnutrit\u002Fnux040\nJones AD, Shrinivas A, Bezner-Kerr R (2014) Farm production diversity is associated with greater household dietary diversity in Malawi: findings from nationally representative data. Food Policy 46:1–12. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.foodpol.2014.02.001\nKadiyala S, Harris J, Headey D, Yosef S, Gillespie S (2014) Agriculture and nutrition in India: mapping evidence to pathways. ANNALS 1331(1):43–56\nKanter R, Walls HL, Tak M, Roberts F, Waage J (2015) A conceptual framework for understanding the impacts of agriculture and food system policies on nutrition and health. Food Secur 7(4):767–777\nKeding GB, Msuya JM, Maass BL, Krawinkel MB (2012) Relating dietary diversity and food variety scores to vegetable production and socio-economic status of women in rural Tanzania. Food Secur 4(1):129–140\nKennedy G, Ballard TDM (2010) Guidelines for measuring household and individual dietary diversity. Food and Agriculture Organization of the United Nations, Rome\nKennedy G, Pedro MR, Seghieri C, Nantel G, Brouwer I (2007) Dietary diversity score is a useful indicator of micronutrient intake in non-breast-feeding Filipino children. J Nutr 137:1–6\nKennedy G, Ballard T, Dop MC (2011) Guidelines for measuring household and individual dietary diversity. Food and Agriculture Organization of the United Nations, Rome\nKoppmair S, Kassie M, Qaim M (2016) Farm production, market access and dietary diversity in Malawi. Public Health Nutr 20:325–335. https:\u002F\u002Fdoi.org\u002F10.1017\u002FS1368980016002135\nKoppmair S, Kassie M, Qaim M (2017) Farm production, market access and dietary diversity in Malawi. Public Health Nutr 20(2):325–335\nKumar N, Harris J, Rawat R (2015) If they grow it, will they eat and grow? Evidence from Zambia on agricultural diversity and child undernutrition. J Dev Stud 51(8):1060–1077\nLovo S, Veronesi M (2019) Crop diversification and child health: empirical evidence from Tanzania. Ecol Econ 158:168–179\nM’Kaibi FK, Steyn NP, Ochola SA, Du Plessis L (2017) The relationship between agricultural biodiversity, dietary diversity, household food security, and stunting of children in rural Kenya. Food Sci Nutr 5:243–254\nMalapit HJL, Kadiyala S, Quisumbing AR, Cunningham K, Tyagi P (2015) Women’s empowerment mitigates the negative effects of low production diversity on maternal and child nutrition in Nepal. J Dev Stud 51(8):1097–1123. https:\u002F\u002Fdoi.org\u002F10.1080\u002F00220388.2015.1018904\nMequanint B, Melesse M, Christophe BBI, Brouwer ADB (2019) Improving diets through food systems in low- and middle-income countries. IFPRI Discussion Paper 01858\nMuthini D, Nzuma J, Nyikal R (2020) Farm production diversity and its association with dietary diversity in Kenya. Food Secur. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12571-020-01030-1\nOsmani SR, Ahmed A, Ahmed T, Hossain N, Huq S, Shahan A (2016) Strategic review of food security and nutrition in Bangladesh. An independent review commissioned by the World Food Programme (WFP). WFP, Dhaka\nOyarzun PJ, Borja RM, Sherwood S, Parra V (2013) Making sense of agro-biodiversity, diet, and intensification of smallholder family farming in the highland Andes of Ecuador. Ecol Food Nutr 52(6):515–541\nPandey VL, Mahendra DS, Jayachandran U (2016) Impact of agricultural interventions on the nutritional status in South Asia: a review. 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Nutrition Programme, World Health Organization, Geneva\nWinters P, Essam T, Zezza A, Davis B, Carletto C (2010) Patterns of rural development: a cross-country comparison using microeconomic data. J Agric Econ 61:628–651\nWorld Bank (2007) From agriculture to nutrition: path- ways, synergies and outcomes. World Bank, Washington, DC",{"VOID":2003},"10.1186\u002Fs40100-022-00221-y","2025-02-25T19:16:01.415+00:00","https:\u002F\u002Fagrifoodecon.springeropen.com\u002Farticles\u002F10.1186\u002Fs40100-022-00221-y",[2007,2031,2044],{"id":2008,"sortIndex":19,"researcher":18,"roles":2009,"affiliations":2010,"properties":2028,"displayName":2030,"givenName":18,"familyName":18},"bf55a8fe-a6cb-4d80-8ac5-cc4386e04785",[146],[2011,2019],{"id":2012,"sortIndex":19,"affiliation":2013,"properties":18},"d76c87ed-0418-4ef9-ae40-b443efe35660",{"id":2012,"createTime":18,"updateTime":18,"relativeEntities":2014,"slug":18,"properties":2015,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2018,"statistic":18},[],{"title":2016},{"VI":2017},"Division of Agricultural Economics, ICAR-Indian Agricultural Research Institute (IARI), New Delhi, India",[],{"id":2020,"sortIndex":112,"affiliation":2021,"properties":2027},"e940ac8f-9103-4e8e-8776-94ab9c8d2157",{"id":2020,"createTime":18,"updateTime":18,"relativeEntities":2022,"slug":18,"properties":2023,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2026,"statistic":18},[],{"title":2024},{"VI":2025},"Agricultural Economics Division, Bangladesh Agricultural Research Institute (BARI), Gazipur, Bangladesh",[],{},{"title":2029},{"VI":2030},"Sayla 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this paper, we review published studies to assess the influence of time preferences on human health behaviour. Our review indicates that elicited discount rates for health have been found to be higher than those for money in both the social and private context. We discuss the importance of discount rates for public policy since high time discount rates can contribute to governmental emphasis on acute health care, rather than preventive health care. We then examine how time preferences interrelate with specific health concerns such as smoking or obesity. We find that even when time preferences are elicited in the monetary domain, they can be successful in predicting smoking cessation and likewise for obesity. We also discuss how time preferences relate with teen risk taking behavior. D91, I0",{"EN":2132},"Time preferences and health behaviour: a review",{"VOID":2134},"Adams J: The mediating role of time perspective in socio-economic inequalities in smoking and physical activity in older English adults. 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J Soc Issues 1997, 53(1):129–145. doi:10.1111\u002Fj.1540–4560.1997.tb02435.x\nWatts JJ, Segal L: Market failure, policy failure and other distortions in chronic disease markets. BMC Health Serv Res 2009, 9: 102–102. doi:10.1186\u002F1472–6963–9-102\nZhang L, Rashad I: Obesity and time preference: the health consequences of discounting the future. J Biosoc Sci 2008, 40(1):97–113. doi:10.1186\u002F1472–6963–9-102",{"VOID":2136},"10.1186\u002F2193-7532-1-17","https:\u002F\u002Fagrifoodecon.springeropen.com\u002Farticles\u002F10.1186\u002F2193-7532-1-17",[2139,2154,2169],{"id":2140,"sortIndex":19,"researcher":18,"roles":2141,"affiliations":2142,"properties":2151,"displayName":2153,"givenName":18,"familyName":18},"6cfb958e-a18a-492b-9b7f-42d177c7a4ff",[146],[2143],{"id":2144,"sortIndex":19,"affiliation":2145,"properties":18},"a8a078de-55d1-4e7f-92e5-64355bc6e4ec",{"id":2144,"createTime":18,"updateTime":18,"relativeEntities":2146,"slug":18,"properties":2147,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2150,"statistic":18},[],{"title":2148},{"VI":2149},"Sensory Spectrum, New Providence, USA",[],{"title":2152},{"VI":2153},"Lydia 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