Scenarios for the Brazilian road freight transport industry

Author:

Penteado Pinto Martins Pérsio,Maurício Gama Boaventura João,Americo Fischmann Adalberto,Kramer Costa Benny,Giovinazzo Spers Renata

Abstract

PurposeThis article aims to describe a qualitative, exploratory study with the objective of developing scenarios for the road freight transport industry in Brazil and evaluating the effectiveness of the method applied, which used the stakeholders of said industry as a means to identify the variables of the scenarios.Design/approach/methodologyAccording to the classification scheme developed by Huss and Honton, the authors' method fits into the intuitive logics approach to scenarios, employing concepts of stakeholder analysis as proposed by Freeman. Primary data collection was conducted through key informant interviews, as outlined by Fetterman. The use of the method of intuitive logics combined with the stakeholder analysis evaluates the consistency of experts' opinions on the characteristics of stakeholders. Four environmental scenarios, distinct but equally plausible, were generated for the road freight transport industry as it was felt that more than four scenarios tends to be too complex.FindingsThe method applied produced scenarios distinctive enough to classify them as contrasting, accounting for macroenvironmental variables and variables determined by influential stakeholders in the analyzed industry. Organized and connected, these variables produced precise end states that warrant consideration in the policies and strategies of industry players. The characteristics of the scenarios produced reveal that the method was effective. The authors found the most influential stakeholders in the industry to be the government, shipping clients, end consumers, logistics service providers, and trade associations. The industry's main uncertainties are tied to how the actions of government, shippers, and logistics service providers will unfold.Research limitations/implicationsSome limitations could be identified in the method. One refers to the absence of procedures to govern the chronology of events at the time of preparation of scenario plots. Another shortcoming is the third and final stage of the research; the authors observed some weakness in the method when defining a variable that is independent because it can be independent of the variables selected for the last step but dependent on others considered but not selected.Practical implicationsThe results of the study can stimulate reflection of stakeholders on factors that will affect their decision making, stimulate understanding of the conditions for sustainability of the industry, and identify business opportunities and necessary strategic resources for the success of organizations in the future.Social implicationsThe transport industry plays a vital role in factors that are paramount for the economical development of a country, such as exploration of resources and mass production, and, in Brazil, road freight transport is of particular importance. The research can guide public policy in regulating and investing in industry, since the plots facilitate the understanding of the consequences of causal relationships as well as the final states resulting from these. The scenarios reveal causal relationships strongly influenced by the stakeholder “government”, especially regarding investment in infrastructure, regulation and supervision of the industry.Originality/valueApplication of the method proposed by Boaventura and Fischmann to the road freight transport industry generated distinct, but equally plausible scenarios. The method considered the key uncertainties as dichotomous variables. The scenarios were different since combinations of final states of the key uncertainties led to a different logic or rationale. The authors may state that this particular application contributed towards improvement of the method, as it tested the method's logic when applied to a complex environment influenced by many stakeholders.

Publisher

Emerald

Subject

Business and International Management,Management of Technology and Innovation

Reference32 articles.

1. Ayres, R.U. (1984), “Limits and possibilities of large‐scale long‐range societal models”, Technological Forecasting and Social Change, Vol. 25, pp. 297‐308.

2. Ayres, R.U. and Axtell, R. (1996), “Foresight as a survival characteristic: when (if ever) does the long view pay?”, Technological Forecasting and Social Change, Vol. 51, pp. 209‐35.

3. Banister, D., Dreborg, K., Hedberg, L., Hunhammar, S., Steen, P. and Åkerman, J.A. (2000), “Transport policy scenarios for the EU: 2020 images of the future”, Innovation: The European Journal of Social Sciences, Vol. 13 No. 1, pp. 27‐45.

4. Blois, H.D., Finamore, E.B., Mallmann, V.M. and Biazi, R. (2007), Cenários Prospectivos no Transporte Rodoviário de Cargas: um Estudo no Core de Produção do Estado do Rio Grande do Sul, XXXI Encontro da ANPAD, Rio de Janeiro.

5. Boaventura, J.M.G. and Fischmann, A.A. (2007), “Um método para cenários empregando stakeholder analysis: um estudo no setor de automação comercial”, RA/USP – Revista de Administração, Vol. 42 No. 2, pp. 141‐54.

Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3