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INSTRUMENTO PARA CAPTURA DE VALOR DE OFERTAS PSS SUSTENTÁVEL PARA A SECAGEM E ARMAZENAGEM DE GRÃOS

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Lermen, Fernando Henrique; Ribeiro, José Luis Duarte; Márcia Elisa Soares, ; Martins, Vera Lúcia Milani; , ;

Article:

A teoria do valor capturado postula que o lucro potencial na entrega de uma oferta de produtos e serviços é avaliado por meio da relação preço e desempenho, características do produto e do serviço e das competências da empresa. Este estudo trata da captura do valor em ofertas Sustainable Product-Service System (S-PSS). O objetivo deste estudo é desenvolver um instrumento de coleta de dados para capturar valor de ofertas S-PSS para a secagem e armazenagem de grãos desenvolvido para agricultores. O instrumento foi concebido visando o emprego de análises de cenários por meio de técnica de modelagem de dados de preferência como Conjoint Analysis (Choice-based Conjoint e Menu-based Choice), associadas e modelos econométricos com abordagem (Willingness-to-pay) para mensurar o quanto o consumidor está disposto a pagar por determinada oferta. O instrumento foi planejado para associar as respostas à dados socioeconômicos e de propensão à sustentabilidade do agricultor. Os cenários dos produtos foram planejados para ofertas da secagem e armazenagem de grãos, serviços de gestão de dados, opção de compra ou aluguel e a disposição a pagar do agricultor pela aquisição e demais serviços adicionais. Este artigo apresenta a validação por conteúdo do instrumento.

Article:

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Palavras-chave: Valor capturado; Conjoint; Willingness-to-pay; Agricultura; Pós-colheita,

Palavras-chave: -,

DOI: 10.5151/cbgdp2019-75

Referências bibliográficas
  • [1] ANAND, A., BANSAL, G., AGGRAWAL, D. Choice based diffusion model for predicting sales of mobile phones using conjoint analysis. The Journal of High Technology Management Research. v.22, p.216-226, 2018.
  • [2] BABALIS, S.J., BELESSIOTIS, V.G. Influence of the drying conditions on the drying constants and moisture diffusivity during the thin-layer drying of figs. Journal of Food Engineering. v.65, p.449–458, 2004.
  • [3] BEN AMOR, M., LINDAHL, M., FRANKELIUS, P., BEN, H. Revisiting industrial organization: Product service systems insight. Journal of Cleaner Production. v.196, p.1459–1477, 2018.
  • [4] BREIDERT, C., HAHSLER, M., REUTTERER, T. A review of Methods for Measuring willingness-to-pay. Innovation Marketing. p.1–32, 2006.
  • [5] CAFFREY, K.R., VEAL, M.W., CHINN, M.S. The farm to bio refinery continuum: A techno-economic and LCA analysis of ethanol production from sweet sorghum juice. Agricultural Systems. v.130, p.55–66, 2014.
  • [6] CALABRESE, A., CASTALDI, C., FORTE, G., GHIRON, N. Sustainability-oriented service innovation: An emerging research field. Journal of Cleaner Production. p.193, v.533–548, 2018.
  • [7] CALEGARI, L.P., BARBOSA, J., MARODIN, G.A., FETTERMANN, D.C. A conjoint analysis to consumer choice in Brazil: Defining device attributes for recognizing customized foods characteristics. Food Research International. v.109, p.1–13., 2018.
  • [8] CONAB - National Supply Company. Follow-up of the Brazilian crop, 201
  • [9] CRUZ, F.P.B., JOHANN, G., OLIVEIRA, K., PALÚ, F., ANTONIO, E., GUIRARDELLO, R., CURVELO, N. Crambe grain drying: Evaluation of a linear and double resistance driving force model and energetic performance. Renewable and Sustainable Energy Reviews. v.80, p.1–8, 2017.
  • [10] DIÓGENES, A.F., BASTO, A., ESTEVÃO-RODRIGUES, T.T., MOUTINHO, S., AIRES, T., OLIVA-TELES, A., PERES, H. Soybean meal replacement by corn distillers dried grains with solubles (DDGS) and exogenous non-starch polysaccharidases supplementation in diets for gilthead seabream (Sparus aurata) juveniles. Aquaculture, v.500, p.435–442, 2019.
  • [11] EMBRAPA, B. Agricultural research C. Characteristics of agricultural establishments - Total area groups, 2017.
  • [12] EUSTICE, C., MCCOLE, D., RUTTY, M. The impact of different product messages on wine tourists’ willingness to pay: A non-hypothetical experiment. Tourism Management. v.72, p.242–248, 2019.
  • [13] FARGNOLI, M., COSTANTINO, F., GRAVIO, G. DI, TRONCI, M. Product service-systems implementation: A customized framework to enhance sustainability and customer satisfaction. Journal of Cleaner Production. v.188, p.387–401, 2018.
  • [14] FOLEY, J.A., RAMANKUTTY, N., BRAUMAN, K.A., CASSIDY, E.S., GERBER, J.S., JOHNSTON, M., MUELLER, N.D., CONNELL, C.O., RAY, D.K., WEST, P.C., BALZER, C., BENNETT, E.M., SHEEHAN, J., SIEBERT, S., CARPENTER, S.R., HILL, J., MONFREDA, C., POLASKY, S., ROCKSTRO, J., TILMAN, D., ZAKS, D.P.M. Solutions for a cultivated planet. Nature, v.428, p.337–478, 2011.
  • [15] LIMA, D., GOMES, R., RUARO, C., BARRIONUEVO, S., LOURENÇO, L., WILSON, F., JÚNIOR, R. PAHs in corn grains submitted to drying with firewood. Food Chemistry. v.215, p.165–170, 2017.
  • [16] GATTA, V., MARCUCCI, E., SCACCIA, L. Willingness to pay confidence interval estimation methods: a comparison. Transportation Research. Part A, v.82, p.162–192, 2015.
  • [17] GREEN, P.E., RAO, V.R. Conjoint Measurement for Data Quantifying Judgmental. Journal of Marketing Research. v.8, p.355–363, 1971.
  • [18] GREEN, P.E., SRINIVASAN, V. Conjoint Analysis in Consumer Research: Issues and Outlook. Journal of Consumer Research. v.5, p.103–123, 1978.
  • [19] GREEN, P.E., SRINIVASAN, V. Conjoint Analysis in Marketing: New with Developments for and Practice. Journal of Marketing. v.54, p.3–19, 1990.
  • [20] HOHMEIER, K.C., ASSISTANT, P., LOOMIS, B., MANAGER, P.P., LEAD, M.T.M., GATWOOD, J. Consumer perceptions of and willingness-to-pay for point-of-care testing services in the community pharmacy. Research in Social and Administrative Pharmacy. v.14, p.360–366, 2018.
  • [21] HUERTAS-GARCÍA, R., NU, A., MIRAVITLLES, P. Statistical and cognitive optimization of experimental designs in conjoint analysis. European Journal of Management and Business Economics. v.25, p.142–149, 2016.
  • [22] INGVORDSEN, C.H., LYNGKJÆR, M.F., PELTONEN-SAINIO, P., MIKKELSEN, T.N., STOCKMARR, A., JØRGENSEN, R.B. How a 10-day heatwave impacts barley grain yield when superimposed onto future levels of temperature and CO2 as single and combined factors. Agriculture, Ecosystems and Environment. v.259, p.45–52, 2018.
  • [23] KAMAKURA, W.A., KWAK, K. Menu-choice modeling, 2010.
  • [24] KLARMAN, H.E. The Road to Cost-Effectiveness Analysis. The Milbank Memorial Fund Quarterly. v.60, p.585–603, 1982.
  • [25] LOUVIERE, J., HENSHER, D.A., SWAIT, J. Stated choice methods: analysis and application, Cambridge University Press, 2000.
  • [26] MAHAJAN, V., GREEN, P.E., GOLDBERG, S.M. A Conjoint Model for Measuring Self- and Cross-Price/Demand Relationships. Journal of Marketing Research. v.19, p.334–342, 1982.
  • [27] MEYERDING, S.G.H., GENTZ, M., ALTMANN, B., MEIER-DINKEL, L. Beef quality labels: A combination of sensory acceptance test, stated willingness to pay, and choice-based conjoint analysis. Appetite. v.127, p.324–333, 2018.
  • [28] MONT, O.K. Clarifying the concept of product – service system. Journal of Cleaner Production. v.10, p.237–245, 2002.
  • [29] NETZER, O., SRINIVASAN, V. Adaptive Self-Explication of Multi-Attribute Preferences. Journal of Marketing Research, v.48, p.140-156, 2011.
  • [30] NKOMOKI, W., BAVOROVÁ, M., BANOUT, J. Adoption of sustainable agricultural practices and food security threats: Effects of land tenure in Zambia. Land Use Policy, v.78, p.532–538, 2018.
  • [31] ORME, B.K. Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research, 2010.
  • [32] PAETZ, F., STEINER, W.J. Utility independence versus IIA property in independent probit models. Journal of Choice Modelling. v.26, p.41–47, 2018.
  • [33] PARK, C.S. The robustness of hierarchical Bayes conjoint analysis under alternative measurement scales. Journal of Business Research. v.57, p.1092–1097, 2004.
  • [34] PIERONI, M.D.P., BLOMSMA, F., MCALOONE, T.C., PIGOSSO, D.C.A., STIEF, P., DANTAN, J., ETIENNE, A., SIADAT, A. Enabling circular strategies with different types of product/service-systems. Procedia CIRP, v.73, p.179–184., 2018.
  • [35] PITTELKOW, C.M., LIANG, X., LINQUIST, B.A., GROENIGEN, K.J. VAN, LEE, J., LUNDY, M.E., GESTEL, N. VAN, SIX, J., VENTEREA, R.T., KESSEL, C. VAN. Productivity limits and potentials of the principles of conservation agriculture. Nature, v.517, p.365–368, 2014.
  • [36] QUINTERO-ANGEL, M., GONZÁLEZ-ACEVEDO, A. Tendencies and challenges for the assessment of agricultural sustainability. Agriculture Ecosystem Environmental. v.254, p.273–281, 2018.
  • [37] REYKDAL, Ó. Drying and storing of harvested grain A Review of Methods, Skýrsla Matís, 2018.
  • [38] ROSE-ANDERSSEN, C., ALLEN, P.M., TSINOPOULOS, C., MCCARTHY, I. Innovation in manufacturing as an evolutionary complex system. Technovation, v.25, p.1093–1105, 2005.
  • [39] SOHN, S.Y., LEE, W.S., JU, Y.H., 2013. Valuing academic patents and intellectual properties: Different perspectives of willingness to pay and sell. Technovation 33, 13–24.
  • [40] SONG, J., JANG, T., SOHN, S.Y. Conjoint analysis for IPTV service. Expert Systems with Applications. v.36, p.7860–7864., 2009.
  • [41] TEECE, D.J. Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy. Research Policy. v.15, p.285-305, 1986.
  • [42] TEECE, D.J. Capturing Value from Knowledge Assets: The New Economy, Markets for Know-How, and Intangible Assets. California Management Review, v.40, p.55–79, 1998.
  • [43] TELLES, T.S., REYDON, B.P., MAIA, A.G. Effects of no-tillage on agricultural land values in Brazil. Land Use Policy, v.76, p.124–129, 2018.
  • [44] USDA - United States Department of Agriculture. Ag and Food Sectors and the Economy, 2018a.
  • [45] USDA - United States Department of Agriculture. Grain: World Markets and Trade Table of Contents, 2018b.
  • [46] USDA - United States Department of Agriculture. Grain and Feed - Annual China’s Iron Rice Bowl Transforms into Government Checks, 2018c.
  • [47] VOLETI, S., SRINIVASAN, V., GHOSH, P. An approach to improve the predictive power of choice-based conjoint analysis. International Journal of Research in Marketing. v.34, p.325–335, 2017.
  • [48] XIE, X.K., ANDERSON, C.K., VERMA, R. Customer Preferences and Opaque Intermediaries. Cornell Hospital Quaterly. v.58, p.342–353, 2017.
  • [49] YANG, M., EVANS, S., VLADIMIROVA, D., RANA, P. Value uncaptured perspective for sustainable business model innovation. Journal of Cleaner Production. v.140, p.1794–1804, 2017.
  • [50] ZHU, H., GAO, J., CAI, Q., ZHU, H., GAO, J., CAI, Q., CHENG, G., WANG, S., AGARWAL, N.K. A product-service system using requirement analysis and knowledge management technologies. Kybernetes, 44, 823–842, 2015.
Como citar:

Lermen, Fernando Henrique; Ribeiro, José Luis Duarte; Márcia Elisa Soares, ; Martins, Vera Lúcia Milani; , ; "INSTRUMENTO PARA CAPTURA DE VALOR DE OFERTAS PSS SUSTENTÁVEL PARA A SECAGEM E ARMAZENAGEM DE GRÃOS", p. 1036-1046 . In: Anais do 12º Congresso Brasileiro de Inovação e Gestão de Desenvolvimento de Produto. São Paulo: Blucher, 2019.
ISSN 2357-7592, DOI 10.5151/cbgdp2019-75

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