Resumo

Service providing companies that participate in tender processes deal daily with the decision to participate or not in the process (making a bid or not) (Li, Zhang, Chen, & Martek, 2020). Deciding whether or not to explore an opportunity is complex and involves multiple factors, such as project demands, organizational capacity, the tender itself etc (Biruk, Jaskowski, & Czarnigowska, 2017). Decision making in this process is crucial, directly impacting the success of an organization and may cause irreparable damage if not done properly (Lesniak et al., 2018; Li et al., 2020).

Given the multiple issues involved in tender decision making, MCDM is an appropriate methodology to help decision making in this context. However, no studies have been carried out using MCDM methods for decisions to participate in tenders from the standpoint of a company contracted. Studies using MCDM focus on the contracting company (Gonçalo & Morais, 2018) or problems related to the production chain (Mota, De Almeida, & Alencar, 2009). Thus, the aim of this study is to propose a multi-criteria model to support decisions to participate in tenders in the Brazilian oil and gas industry.

A tender involves inviting bids/proposals to participate in (or execute) a project. There are two possible viewpoints in this process: (i) that of the contracting party and; (ii) that of the contracted company (or service provider). In the second case, the object of the present study, the aim is to select the best project to bid on considering the objectives of the organization. Thus, efforts to win a tender include two main decisions: to make a bid or not, and in the event of a bid, submit an accurate proposal that meets the requirements without underbidding.

In order to construct the model, the present study used three phases suggested by De Almeida et al. (2015), where five criteria (conditions for participating in the tender; size of the project; project complexity; experience with similar projects; time to prepare the bid) were defined based on literature reports and the R-TOPSIS method was used to assess the tender documents. In order to establish the weight of each criterion, the Swing Weights Procedure using the SMARTER method was applied. For numerical application, a company located in Rio Grande do Norte state, Brazil was used.

With respect to the discussion presented, alternative A1 ranked first and A2 last. The experience factor proved to be important for companies in the context analyzed, since this criterion considers several factors, such as internal and external conditions and risks (Wang et al., 2007). In addition, large highly complex projects were unfavorable to decision makers, since they require longer bid preparation times and contain challenging contractual conditions.

The model proposed combined the SMARTER and R-TOPSIS methods to respectively establish weights and assess alternatives (tender documents), obtaining reliable results. Thus, the objective was achieved. The findings demonstrate the need to assess decisions to participate from the standpoint of the contracted company using methodologies that can encompass the multiple parameters involved in the area. It is important to note that the study does not suggest that this is the only correct model to use, but shows its clarity and reliability.

Biruk, S., Jaskowski, P., & Czarnigowska, A. (2017). Modeling Contractor’s Bidding Decisions. Procedia Engineering, 182, 91-98. Lesniak, A., Kubek, D., Plebankiewickz, E., Zima, K., & Belniak, S. (2018). Fuzzy AHP Application for Supporting Contractors Bidding Decision. Symmetry, 10(11), 642. Li, G., Zhang, G., Chen, C., & Martek, I. (2020). Empirical bid or no bid decision process in international construction projects: Structural equation modeling framework. Journal of Construction Engineering and Management, 146(6).