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Industrial sectors that operate in uncertain environments - with demand variability, product seasonality and different industrialisation structures - need studies that enable identification and forecast trends. Therefore, the development of competitiveness extends beyond a company’s individual performance. Collective action, whether toward consumer markets, supplier markets, competitors and substitutes, can reinforce or help reformulate the current practices of an organisation, besides providing better results in the development of strategies and competitive positioning. Thus, clothing, the sector addressed in this work, is characterised by a long, fragmented, heterogeneous production chain, the competitiveness of which is linked to product differentiation. Therefore, the use of systemic approaches to study this sector is effective. In this sense, this research aims at adapting Systems Thinking and Scenario Planning (STSP) so that it supports the development and planning process in a given sector. Thus, this research applies STSP adapted to an analysis of the clothing sector in the northern region of Rio Grande do Sul State, Brazil. As a result, in academic terms, this research proposed and validated a method for analysing industrial sectors of the clothing industry. In the sectoral context, this research identified elements that leverage the sector’s competitiveness, besides generating knowledge and learning aimed at strengthening the sectoral structure identified, and fostering the formation of a new clothing cluster.

The purpose of this article is to construct a systemic structure to explain the relations subjacent to the coopetitive behaviour observed in a Latin American technological park. The research method is qualitative modelling. The primary research technique is the in-depth interview with park experts. Systemic language organised the speeches. The systemic language uses symbols that represent the elements of a system, such as variables, relations, and feedback loops. Initially, we constructed two essential archetypes that describe how the need for coopetition emerged, triggered by failures in meeting customers´ demands and reduced sales. Then, we built an overall systemic structure relying on the essential archetypes, which explains how the coopetitive strategy emerged in the park. The main conclusion reached by the study is learning and public policies as desirable conditions; failure in meeting customers’ requirements as the trigger; and sustainability, knowledge and resource sharing, mitigation of risks and uncertainties, and increased sales by price reduction, as reinforcing feedback factors. The main contribution of the study is a systemic qualitative model that helps understanding how to implement or manage a coopetitive strategy in a network formed of companies mainly driven by technological factors.

Soccer (football) is identified as the most popular sport in the world with a high turnover of economic-financial resources. The different segments of the soccer (football) value chain exert mutual influence on the variables that rule the dynamics of this sector. In this sense it is necessary to identify the variables that represent the soccer (football) value chain systemically; to understand the interrelationships between these variables, the main difficulties derived from this interrelationship and to point out variables that require actions to increment the results of the soccer (football) value chain as a whole. Hence, this study applied a semi-structured questionnaire with open-ended questions about the problems and leveraging variables that exist in this sports modality. A causal linkage diagram was elaborated based on the answers to the interviews, showing the systemic structure of the soccer (football) value chain in Brazil, whose premise it is to identify the existing circularities and the possibly existing points of leverage. The systemic structure pointed to the economic participation of soccer (football) in the Gross Domestic Product as a central variable to be leveraged, which tends to synthetize the results of the joint action of the actors in this chain. Furthermore, the variables that may limit or amplify the growth were identified. The systemic structure showed that the soccer (football) commodity chain is complex because of the great number of variables and interrelationships needed to represent its dynamics. The relationship between the actors also proved to be a factor of impact on economic and social development.

Action research is one of the research methods that seeks to develop scientific knowledge while simultaneously acting to solve real problems. Design science and design science research are approaches that address problem-solving oriented researches, converging in this aspect with the objectives of action research. A significant part of the literature discusses action research and design science research separately. However, there are some early discussions regarding the similarities and the differences between these research methods. The objective of this study is to deepen an analysis that distinguishes action research, design science and design science research as research methods considering their convergences and divergences. This leads to the discussion of the need for a third method: action design research. This study was conducted based on a configurative systematic literature review. The analysis and the synthesis of literature took into account themes and content analyses. Some results could be observed. First, there is a significant number of similarities among these research methods; second, there are complementary and positive synergies in their use; and third, the concepts of artifact and classes of problems seem to contribute both to the proposition and to the evaluation of the results obtained by action research. Finally, it was possible to establish a set of possibilities for the use of action research and design science research in a combined manner. The limitations of this study have a theoretical nature. There is a need for a comparative analysis of the use of action research and design science research and the use of action research under the paradigm of design science.

The purpose of this article is to analyze systemically the Brazilian production chain of semiconductors. The specific objectives of this article are to represent the chain systemically and to identify key variables and leverage points that can increase the overall performance of the semiconductor industry. The research method is qualitative modelling. Eleven practitioners of the industry answered a questionnaire approaching various aspects of the semiconductor industry in Brazil. By a systemic approach, the complex behavior present in the industry was considered. By content analysis, we identified patterns in the speech of the respondents. Texts fragments allowed the identification of key themes and variables present in the system. The association among key variables and complex behavior helped to build a systemic structure, aimed at representing the main relationships in the system. From the systemic structure, eight leverage points were identified and discussed. The key implications of the findings are the damage that cheap imports make in the local market; the need of strong public policies that include more than tax reduction, but also local conditions, like clusters or technological parks, for the high-tech manufacture; and the promotion of conditions that stimulate private investment in the industry.

In competitive and complex markets such as the commodities one, having the ability of planning scenarios and envisioning the behavior of prices in each of them, constitutes a competitive advantage for organizations. Within this context, this research aims at developing a method for the understanding of the key factors that impact the pricing of commodities through a systemic approach, allowing the estimation/evaluation of future prices in different scenarios. Action research was used as research methodology, which is characterized by the principles of collaborative and continuous learning. In order to implement the objectives of this research, an adaptation of the Systems Thinking and Scenario Planning method was developed and implemented in an industry of the iron ore market. The first phase led to the understanding of the main variables associated to the price; in the second phase, this learning was materialized in a system dynamic computational model, which was used in the third and final stage for the estimation/evaluation of future prices in some alternative scenarios. Interviews were conducted in parallel with the quantitative evaluation, in order to obtain subsidies for acceptance and refinement of the proposed method. The results obtained, the learning reported and the possible applications identified for the use of the model indicate that the proposed method allows for the understanding of the pricing of commodities through the systems thinking and the planning by scenarios.