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Abstract Paper aims This paper compares the economic valuation (Intrinsic Cost or IC) of carbon dioxide emissions (carbon price) of the externality taxes (Kyoto Protocol) of the Argentine Production Chain (APC). Originality The experimental IC index and this novel combination allow incorporating objective (incremental) and subjective (acceptance, hierarchy and uncertainty) evaluation of the APC. This method is extended in this paper (to other operators). Research method The ICs are applied to attribute graphs in two scenarios (APC and society), that are obtained from the combination of Fuzzy Decision Making (FMD), Analytic Hierarchy Process (AHP) and PSO with the Algebraic (AP), Generic Hamacher (GHP and PHP) and Einstein (EP) products. Main findings (i) The coherency of the new ICs is demonstrated by mathematical and graphical analysis; (ii) The most demanding operators are the EP and HP. Implications for theory and practice It contributes to establish mechanisms for regulation of the APC.

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Abstract Paper aims We investigate the drivers and barriers for the traceability digitalisation of the Australian construction supply chain. Originality There is a growing interest in the construction industry for embracing digital technologies. Nevertheless, the digital transition in construction industry is still slow, especially for addressing material traceability. Research method An exploratory-empirical study was conducted in which we performed the following steps: (i) definition of selection criteria; (ii) semi-structured interviews with 26 experts (academics, practitioners and stakeholders); and (iii) content analysis and propositions. Main findings Results allowed the identification of the most critical drivers and barriers for such traceability digitalisation, being consolidated in a conceptual framework that characterises the early and late adopters of digital technologies in the construction supply chain. Implications for theory and practice In theoretical terms, when considering the barriers/challenges, the degree to which the digital traceability's results are visible to the adopters seems to be an important issue, being able to impair the digitalisation of the construction supply chain. From a practical perspective, the more companies advance in the traceability digitalisation, the more aware they will become regarding its drivers/benefits and barriers/challenges. Nevertheless, some highly critical drivers/benefits and barriers/challenges were equally perceived by both early and late adopters.

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Abstract Paper aims Analyzes the use of process management and safety culture practices in Radiotherapy Services and impacts on quality of patient care and safety. Originality Radiotherapy processes require controls and must be developed in an environment with safety. However, despite necessary practices, there are few studies that analyze their implementation and impacts. Research method Was conducted a survey and the data were analyzed using descriptive statistics and SEM-PLS. Main findings Process management practices and safety culture have been used in response to competitive environment and regulatory guidelines. The study confirmed the positive impact of using safety culture and process management practices. Implications for theory and practice Managerial support promoting management and improvement practices and safety culture, along use of process maps, feedback in response to incident reports, patient satisfaction surveys and teamwork contributes to the quality of care and safety. These practices can be prioritized to be deployed by managers and in theoretical models.

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Abstract Paper aims This study demonstrates the complexity of the patient flow from admission to discharge of an adult Intensive Care Unit (ICU) through the application of the Functional Resonance Analysis Method (FRAM). Originality This paper shows the daily functioning of the patient flow, shedding light on the high levels of interdependence and variabilities in Complex Sociotechnical Systems. Research method The research was developed according to the four steps for FRAM analysis. Sources of evidence involved empirical data collection in a leading teaching public hospital in Brazil. Main findings There were identified 34 functions performed mainly by caregivers and support staff. Five instantiations were described to illustrate the functional resonance scenarios caused by the variability propagation across the functions. Implications for theory and practice Limitations of this study and suggestions for future research are pointed out. The resulting model is a basis for context understanding for ongoing and following studies.

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Abstract Paper aims The Industry 4.0 movement highlights the importance of information and communication technologies and the two main reasons for this are advances in digitalization and automation. However, organizations trying to implement technologies face several barriers in their systems. These barriers are intensified in legacy systems, tightly coupled to organizational processes. Thus, to overcome these barriers, an adequacy strategy was structured, and detailed in the context of interoperability. Originality This article proposes a digital transformation framework focused on interoperability in maintenance systems. Research method Aiming to make legacy systems work together with cyber-physical systems, the proposed framework suggests its suitability based on strategic decisions, using Multicriteria Decision Making (MCDM) methods. Main findings The framework outputs demonstrate that people are the main drivers of digital transformation and that the strategies proposed by it are coherent with the actual development of both cases, proven in a new interview one year apart from its application. Implications for theory and practice Real industrial cases demonstrate that the framework can guarantee interoperability while facilitating strategic decisions to implement technologies in legacy maintenance systems. In the end, the legacy system, which will interoperate with the new technologies, is called Smart Legacy System.

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Abstract Paper aims This study aims to empirically explore the mechanisms by which supply chain capabilities dedicated to risk management, robustness, and resilience contribute to improved agility performance in times of disruptions from unavoidable risks. Originality This is the first empirical research examining the direct and indirect effects of supply chain capabilities related to risk management, robustness, and resilience on improving agility performance in times of disruptions. Research method The study considers supply chain risk management as a dynamic capability and supply chain robustness and resilience as operational capabilities that have a mediating role in improving the agility performance of partner firms. Data collected through a survey was used for structural equation modeling and other tests to explore the respective effects of these supply chain capabilities in an environment marked by unavoidable risks, vulnerabilities, and disruptions. Main findings The development of a supply chain risk management capability supported by the generation and/or reconfiguration of the operational capabilities inherent in supply chain robustness and supply chain resilience results in improved agility performance for global supply chain partner firms in times of disruptions. Implications for theory and practice The results contribute to the theoretical development of issues related to the mechanisms by which supply chain capabilities, particularly risk management, robustness, and resilience work together to improve agility performance and achieve competitive advantage in times of disruptions.

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Abstract Paper aims We analyze in this study the management and governance structure of technology transfer in megaprojects under an emergency context. Originality We analyze an emergency health megaproject's management and governance structure. There is a dearth of studies that explore the management and governance structure of combination megaprojects in emergencies. We focus on analyzing the literature and the management and governance structure in the technology transfer, production, and supply of the Covid-19 vaccine. We then develop a reference model for building the management and governance structure of megaprojects in emergencies. Research method We conducted a case study in Bio-Manguinhos/Fiocruz. From the case study, we can analyze real situations that contribute to the development of theories. For this, we systematically reviewed the literature to identify how the megaproject management structure has been used. We interviewed stakeholders of the Oxford/AstraZeneca/Fiocruz vaccine megaproject against Covid-19 and triangulated these data by collecting corresponding documents. Main findings We conclude that the management and governance structure of the Oxford/AstraZeneca/Fiocruz vaccine technology transfer, production, and supply megaproject was appropriate. Since this structure should not be reproduced faithfully due to its specific characteristics, we developed a reference model for structure building in emergencies. This model can support institutions and governments in structuring management and governance in critical situations. Implications for theory and practice The knowledge obtained from this study will contribute to determining management and governance structures for future megaprojects, especially in emergencies.

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Abstract Paper aims The objective of this research is to propose a multicriteria negotiation model for selecting a sustainable packaging supplier in the food industry. The model aims to minimize the environmental, social and economic impacts of the production process of plastic while ensuring the operational criteria of packaging. Originality Despite the high number of scientific research using multicriteria decision-making suggested to select a supplier, the proposed negotiation model is innovative as it includes green manufacturing as a criterion for negotiation, alongside price and delivery time, to promote sustainable supply chain management. Research method The research method involves three stages: pre-negotiation, negotiation (based on FITradeoff), and post-agreement. The proposed model is illustrated using a case study of a Colombian slaughterhouse that needs to select a sustainable packaging supplier for the next two years. Main findings The main findings indicate that the proposed model that uses the FITradeoff for negotiation solves the problem of selecting sustainable packaging suppliers while promoting sustainable supply chain management in the agribusiness sector. Implications for theory and practice The model has implications for both theory and practice. It encourages interdependent companies to collaborate and enhances efficiency in greener terms for supply chains, buyer and seller firms. The proposition of an original integrative negotiation protocol for selecting sustainable suppliers in agribusiness can provide enterprises with a set of negotiation parameters to achieve successful sustainable supply chain management.

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Abstract Paper aims This article investigates the worldwide trend of growth in the number of recalls, as well as in the number of products involved in each campaign. Originality To investigate these facts, a study of the automotive recall was developed, comprising Brazil, the European Union, and the United States of America. Research method Due to the different availabilities between the locations, search tools and software were developed to obtain and group hidden data from 2010 to 2019. Main findings In this work, the impacts of the recall were analyzed using three categories of algorithms: clustering, classification, and regression. Analyzes were made about the results obtained and discussions were built about the importance of applying the machine learning technique. Implications for theory and practice The use of search tools and software to obtain and group hidden data in databases and opens the opportunity for new research in various areas.

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Abstract Paper aims This paper aims to discuss how Remote Collaboration Tools (RCT) can support and contribute to Action Research (AR) applications in operations management research. Originality Researchers shall capture the complexity of studied phenomena when conducting AR. Although, there is a lack of information regarding the use of RCT in AR. Hence, this paper provides original and comprehensive guidelines for the application of RCT in AR. Research method This paper provides an ex-post analysis of two face-to-face AR cases, based on the steps proposed by Coughlan and Coughlan (2002). Based on the ex-post analysis, it explains ex-ante and how RCT can impact and contribute to AR on operations management. Main findings The paper presents reflections, insights and guidance about the impacts of RCT in AR. RCT allow possibilities for continuity and efficient use of resources in AR. Although, when choosing RCT, special efforts should be put into team building and engagement. Implications for theory and practice The description of how the RCT can be used in the AR cycle can contribute to theory based on empirical results as guidance to increase value considering AR quality criteria. We intend to provide material for the advance of the field of Operations, Production and Management, theoretically and practically.

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Abstract Paper aims This paper aims the use of Social Network Analysis (SNA) as an assessment tool to answer the following research questions: (i) Who are the actors in Humanitarian Operations Networks (HON)?; and (ii) Which actors exert influence on HON? Originality This paper proposes the use of SNA in a different context, bringing new technics to the field of humanitarian logistics. Research method Multiple methodological tools are used such as UCINET, Cytoscape, and EXCEL® to apply SNA in the Brazilian context of sudden-onset natural disaster-response operations. Main findings This application validates the consistency of using SNA to assess HON, besides validating the stakeholder relationship model of the Public, Private, and People sectors in disaster-response operations. Implications for theory and practice Results show strong participation of the public sector in disaster-response operations in Brazil, indicating the need for greater engagement from civil society. Besides, the proposed method can be adopted in the context of any other country.

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Abstract Paper aims This study has the objective of mapping and empirically validating KPIs that can be used to assess healthcare supply chain risks. Originality We combined two methodological approaches: i) we conducted a systematic literature review to identify the healthcare supply chain risk assessment KPIs and ii) We grouped these KPIs into five constructs and validated their relations using PLS-SEM. Research method This is the only study that presents a systematic literature review to identify KPIs that measure healthcare supply chain risks, groups the KPIs into a theoretical framework, and presents a PLS-SEM validation. This study used data from Brazil, from a variety of healthcare supply chain organizations (suppliers, OEMs, clinics, and hospitals), therefore we cannot guarantee that the study can be generalized. Main findings The systematic literature review identified 27 KPIs which were grouped into five constructs. The structural model supported by the PLS-SEM technique revealed that reliability, responsiveness, costs, and agility are antecedents to healthcare supply chain quality. Implications for theory and practice Managers may rely upon this study to understand that healthcare supply chain reliability and responsiveness are antecedents to healthcare supply chain costs and agility, which are antecedents to healthcare supply chain quality.

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Abstract Paper aims This paper addresses difficulties among the Brazilian scholarly community in industrial engineering (IE) when conducting case-based research. It also provides further recommendations to increase methodological rigour. Originality The paper contributes to the practice of case research by providing a historical perspective of research methodology in Brazil and offering guidance to improve case research adoption as well as the methodological rigour. Research method The main challenges when conducting case research were first identified through a literature review. Then, an exploratory survey with Brazilian scholars was conducted to identify challenges perceived by those. Recommendations are then provided, especially regarding the data analysis stage. The recommendations are discussed in the light of the existing literature and based on authors’ experience in conducting qualitative research. Main findings Difficulties when conducting case research identified by scholars can be classified in three ‘Aquila’s hells’: (i) weak theoretical background, (ii) careless case study design/planning; and (iii) fragile/uncertain data analysis. Suggestions to improve the data analysis process consist of building a narrative, data reduction, improving coding, etc. Improving validity is also necessary. Implications for theory and practice The recommendations are especially meaningful to early-stage researchers and provide guidance to improve robustness when conducting case research.

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Abstract Paper aims The research aims at identifying the main drivers that motivate companies to adopt PSS towards a framework considering strategic, tactical, and operational levels. Originality Paper´s relevance comes from the development of a research tool that can be used by other researchers in different PSS research whether related to strategic issues or driven by low environmental impact trends. In addition, PSS drivers construct analysis. Research method A survey-based method, with a questionnaire with 30 questions were developed based on previous literature and applied to 85 executives, qualified to answer questions specifically related to the driven forces towards PSS, from different industries in Brazil. The survey data was analyzed by structural equation modeling. Main findings The results identified six main drivers: competitive advantage, portfolio, co-creation, co-production, integrated solution, and environmental sustainability. Besides, a framework looking at the integration of these six drivers is discussed in a three-level perspective strategic, tactical, and operational. Implications for theory and practice The paper could support organizations that are aiming at being a PSS provider by providing a better understand of the main drivers for moving towards product-service system solutions and it provides empirical support for the effects of hybrid models in manufacturing companies.

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Abstract Paper aims Housing is pivotal in advancing the quality of life. This study investigates the impact of economic complexity on the housing deficit within the Brazilian states. Originality Several studies have investigated the significance of social policies and economic growth as explanatory factors for housing deficits. Our study sheds light on the importance of economic structure in facilitating improved housing conditions for individuals. Research method The Fixed Effects Driscoll Kraay (FE-DK) econometric model was employed, utilizing panel data encompassing 27 Brazilian federative units spanning 2009 to 2017. Main findings The primary finding of this research elucidates the role of economic complexity as a determining factor that significantly impacts the housing deficit within Brazilian states. In other words, an enhanced economic structure contributes to improved housing conditions for the population and fosters a higher quality of life. Implications for theory and practice Theoretically, this paper posits the existence of a novel determinant that elucidates the housing and housing deficit theory. Moreover, the study makes a substantive contribution by advocating for public policies to facilitate housing conditions and enhance social well-being within a developing country. It underscores the pivotal significance of the productive structure in driving the economic development of the nation.

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Abstract Paper aims This paper proposes Cost at Risk (CaR), a concept and a methodology that allows the computation of the risk of cost estimations within a costing system by means of the Monte Carlo Simulation, considering a predefined level of confidence and considering the worst expected result in terms of cost in a certain period. Originality Traditionally, researchers and practitioners have been focused on deterministic costing models without recognizing and managing cost uncertainty. The proposed methodology is based on five steps that go from the determination of the parameters that generate uncertainty to the estimation of the risk. Research method A Design Science Research (DSR) approach was followed based on mathematical modeling and computer simulation. Main findings The model was applied to the imaging area of a hospital allowing to identify and quantify the risk of the most relevant costs and therefore, supporting the design and implementation of both operational and strategic decisions. Implications for theory and practice The main contribution is the inclusion in costing systems of the uncertainty inherent in the estimation of costs, particularly in complex environments.

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Abstract Paper aims This paper addresses the influence of socioeconomic, quality, built environment, and safety variables on the demand for public transportation service. Originality This study covers a differentiated and little explored analysis in the literature on the frequency of use of public transport, using different exploratory variables and characteristics of the urban environment. Research method A sample of 274 bus users was obtained and the multinomial logistic regression method was performed to analyze how different variables impact frequency of use public transportation. Main findings The use of public transportation to work and study, transportation vouchers, distance traveled to central business and accessibility were strongly associated with more frequency of public transportation use. Owning a vehicle, and dissatisfaction with fare and bus schedules led to less frequent use. Implications for theory and practice This study corroborate with literature, where the public transportation is not the main mode of transportation due: private vehicle ownership; dissatisfaction with the public transportation; very low household income; no tariff subsidy; and difficulties in accessing bus stops. In practice, it can aid public transport providers to promote strategies to increase demand and improve service. It also advises government bodies on encouraging sustainable mobility, bringing benefits to society.

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Abstract Paper aims This paper proposes a new optimization problem named the dynamic electric boat charging problem (DEBCP). Originality The problem dynamically determines the speed and charging decisions of an electric boat (EB) to be performed in photovoltaic charging stations (PVCSs). Research method The objective function is to minimize the charging plus the battery degradation costs. Considering that the energy consumption of the EB and the solar irradiance for the PVCSs are uncertain due to factors external to the operation, the dynamic component of the DEBCP recalculates the solution to the problem as new information related to these variables is known. To solve the problem, we propose a rolling horizon genetic algorithm. This method constantly reevaluates the speed and charging decisions of the operation. Such decisions are made with a genetic algorithm. Main findings Our results show that the recalculations help either reducing the cost of the solution when possible or correcting the operation when needed. Implications for theory and practice To evaluate our solution method, we built some test instances based on a future fluvial transport operation with an EB that will be implemented in Colombia. We assess the impact of the dynamic recalculations by comparing the results of the DBECP problem to a scenario following a static solution.

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Abstract Paper aims This paper aims to compare the results of the THOR2 Method, in comparison to the original THOR method, and to analyse possible rank changes between the methods, to support decision-making in the evolutionary process of waste recycling in Brazil. Originality ; Proposes a revision of the model for analysis of Waste Recycling, highlighting the vision of three decision makers individually, and later the integrated vision. Research method State of the art of the THOR and THOR2 methods, through an investigation in four databases and comparison using THORWeb. Main findings As a result of the disposal of plastic waste, reuse, mechanical recycling, chemical and incineration remained in the positions with the consumer as a decision maker. With the other decision makers there was only one significant change, where the landfill went from last to first position. Implications for theory and practice There was only one significant change when comparing methods.

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Abstract Paper aims The objective of this paper is to investigate the effectiveness of a method, here denominated the due date promise by slack time rule (DDPSTR), to evaluate its feasibility and effectiveness for accepting urgent orders in make-to-order (MTO) environments managed by the Simplified Drum-Buffer-Rope (S-DBR) system. Originality Evaluating alternative methods for dealing with urgent orders in MTO environments managed and controlled by the S-DBR system is a subject that has received little attention from academia. This study contributes to the field of knowledge by identifying and comparing three alternatives. Research method To evaluate its feasibility and effectiveness, the DDPSTR was compared with variations of a method based on prior reserve capacity when dealing with regular and urgent orders. Computer simulation was used to model a theoretical production line that emulated the S-DBR system in different scenarios, using average delay and percentage of late orders as performance indicators. Main findings The DDPSTR method achieved optimal results for both indicators, enabling reliable delivery dates and, at the same time, flexibility in accepting urgent orders. Implications for theory and practice This work has verified the effectiveness of the DDPSTR method as a means of dealing with urgent orders without compromising the reliability of previously promised order deadlines. It has additionally proposed the means by which future research can evaluate adaptations, such as offering the shortest feasible delivery times to customers when those initially requested by them prove unworkable.

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Abstract Paper aims To develop an effective and novel decision making method to assess the strategic priority of the criteria for sustainable and agile global manufacturing outsourcing partner (GOP) selection Originality The PIPRECIA Simplified method using random number based stochastic and triangular fuzzy number is applied for setting priority of the GOP selection criteria Research method Sustainable and agile criteria were adopted for global manufacturing outsourcing partner selection from the literature review and discussion with industry experts. Criteria weight and strategic priority was determined using a novel stochastic fuzzy PIPRECIA Simplified method using triangular fuzzy number and random number based uniform distribution of each criterion minimum-maximum ratings. This method will overcome the impreciseness, uncertainty and randomness in subjective group rating. Main findings Customer driven innovation, worker's training and career development, multi-skilled and flexible workforce, delivery flexibility, collaboration with partners, green manufacturing process, and worker's occupational health and safety are found to be the most important criteria in GOP selection in footwear industry. Main criteria in decreasing order of strategic priority are agile, social, environmental and economic. Implications for theory and practice The proposed novel method was applied with a case study of footwear industry to determine the criteria weight and priority, which will enhance supply chain agility and sustainability. The managers in the footwear industry can use the agile and sustainable criteria and proposed method easily.

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Abstract Paper aims This study identified the main aspects related to deservitization in manufacturing firms, a process involving the dilution of services after their integration into companies’ business models. Originality The deservitization process has been identified as a movement among manufacturing companies, but so far, there is limited understanding of its characteristics. The paper contributes to the existing literature by identifying the main aspects related to the dilution of once-added services by manufacturing firms. Research method A literature review was conducted. A content analysis of the selected papers (89 publications) was carried out to identify the main challenges discussed in the servitization literature as issues leading to deservitization. Main findings The explanations for manufacturing firms failing in the transition to servitization and consequently taking the deservitization path discussed in the literature are related to changes in the organizational structure, new capabilities, modification of the business model and strategy, and difficulties in the interaction between supplier and customer. Implications for theory and practice Deservitization is a complex phenomenon, and little is known about it, especially when compared to the existing body of knowledge on servitization. The paper thus extends the knowledge on the conditions leading to deservitization in manufacturing firms.

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Abstract Paper aims To predict monthly corn, soybean, and sugar spot prices in Brazil using hybrid forecasting techniques. Originality This study combines the Singular Spectrum Analysis with different forecasting methods. Research method This paper presents a set of hybrid forecasting approaches combining Singular Spectrum Analysis (SSA) with different univariate time series methods, ranging from complex seasonality methods to machine learning and autoregressive models to predict monthly corn, soybean, and sugar spot prices in Brazil. We carry out a range of out-of-sample forecasting experiments and use a comprehensive set of forecast evaluation metrics. We contrast the performance of the proposed approaches with that of a range of benchmark models. Main findings The results show that the proposed hybrid models present better performances, with the hybrid SSA-neural network approach providing the most competitive results in our sample. Implications for theory and practice Forecasting agricultural prices is of paramount importance to assist producers, farmers, and the industry in decision-making processes.

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Abstract Paper aims Several concerns regarding the lack of interpretability of machine learning models obstruct the implementation of machine learning projects as part of the demand forecasting process. This paper presents a methodology to support the introduction of machine learning into the forecasting process of a traditional direct sales company by providing explanations for the otherwise obscure results. We also suggest incorporating human knowledge inside the machine learning pipeline as an essential part of capturing the business logic and integrating machine learning into the existing processes. Originality Using explainable machine learning methods on real-life company data demonstrates that machine learning techniques are functional beyond the academy and can be introduced to everyday companies' production. Research method The project used real-world data from a company and followed a traditional machine learning pipeline to collect, preprocess, select and train a machine learning model, to conclude with the explanation of the model results through the implementation of SHAP Main findings The results provided insights regarding the contribution of the features to the forecast. We analyzed individual predictions to understand the behavior of different variables, proving helpful when interpreting complex machine learning models. Implications for theory and practice This study contributes to a discussion about adopting new technology and implementing machine learning models for demand forecasting. The methodology presented in this paper can be used to implement similar projects on interested companies.

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Abstract Paper aims This paper presents the literature findings of the Covid-19 vaccines supply chain, its main challenges and best practices, which are compared and verified empirically. Originality The questionnaire developed in this study provides new empirical data about the Covid-19 vaccines supply chain, especially regarding the impacts of the Covid-19 pandemic in the chain, as these events are still recent. Research method A questionnaire was sent by e-mail to specialists working with the Covid-19 vaccine supply chain in South America. Each response was compared to the literature findings. Main findings Despite the challenges faced by vaccination programs, some countries have achieved good results due to strategies adopted at the beginning of their immunization campaigns. The empirical research confirmed that literature findings match business reality, although some empirical results vary depending on the scenario of the country regarding the impacts of the pandemic. Implications for theory and practice This paper summarizes the Covid-19 vaccine supply chain and its challenges, best practices of the most successful countries regarding the immunization process, providing a better understanding of the pandemic scenario. Some empirical data corroborate the literature, and some discrepancies allow the formulation of suppositions that may be tested in future studies.

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Abstract Paper aims The paper aims to analyze preparedness and response for epidemics and pandemics, taking as reference the COVID-19 pandemic, to provide a foundation for developing a preparedness and response protocol to guide Civil Defenses fighting against health threats. For this purpose, we present the results of interviews carried out with Brazilian Civil Defenses, evaluating the role and the type of responsibility (in charge or supportive) of 12 entities in four key areas: (i) awareness and training; (ii) surveillance; (iii) information and communication; (iv) logistics and supplies. Originality The role of Civil Defenses in health threats still needs to be explored in academia. We often see Civil Defenses working to reduce risks and damages suffered by the population in case of disasters such as floods, landslides, and fires. In this paper, we go deeper into Civil Defense’s role and show that its efforts can be headed to face biological disasters such as the COVID-19 pandemic. In this sense, the paper is original as it brings an innovative outlook on the role of Civil Defense, providing inputs for developing a preparedness and response protocol for epidemics and pandemics. Research method We analyze 12 Brazilian Civil Defenses from different States in Brazil. The results were gathered through 9 interviews via video call and three responses from a questionnaire that guided the interviews. We evaluated data from Civil Defenses individually, and then using content analysis, we categorized the data to structure the results and raise essential insights. Main findings Most of the actions taken by the Civil Defenses during the pandemic response included logistics-related activities such as storage, transportation, distribution of required supplies, and mobilization of supply operations. Implications for theory and practice The findings emphasize the capacity of Civil Defenses to act in a vast scope of disasters, including biological disasters. Also, this study helps practitioners to develop guidelines and protocols to support Civil Defense in preparedness and response activities to epidemics and pandemics.

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Abstract Paper aims The first aim is methodological, by developing a conceptual model to describe the internal relationship environment (IRE), the critical factors that impact this environment, the characterization of the parties involved, and their relationships. The second is practical and instrumentalizes the model to measure the effect of differences perceived by internal customers. Originality Distinct works focus on the formulation of management systems, successful implementation, or external and market environmental factors, although there is a lack of studies that relate organizational performance to differences in perceived quality between the parties. Research method The methodology followed a flow of collection/analysis, of the informational data of the company, sketch of the model and flow of information, exploratory focus group, thematic analysis of content, and confirmatory focus group. Then, the procedure of operationalization of the model. Main findings The conceptual model and its instrumentalization describe the apparent relationships between the support team and the operations teams, the underlying relationships of the ERI with the company's management model, and organizational performance. Implications for theory and practice In practice, the proposed measurement instrument allows evaluation of the effects of differences in the perceived quality of internal customers.

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Abstract Paper aims considering that the fourth industrial revolution can be a primary engine for process innovation, this research proposes a 4.0 Production System applicable to the auto parts industry. Originality the study’s relevance is observed from the assimilation of practical issues with the scientific process for constructing a 4.0 Production System for the sector in question. Research method this research is structured from a real case study, proposing an artifact from Design Science Research. Main findings the results obtained provided a competitive advantage to the company, with a reduction of 23% in lead time, 16% in HM/Fuel Tank, 55% in WIP, and 38% in the total distance traveled by operators, in addition to an ROI of 9.22%. Implications for theory and practice the practical application of the artifact showed that its use is viable; however, to extract the maximum potential, it is suggested to insert it into the company's culture.

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Abstract Paper aims To propose a framework to support online simulation studies considering facilitated modeling and concepts of modern industry context, such as agility and flexibility. Originality Since the frameworks in the literature deal with simulation projects focused on healthcare and face-to-face meetings, the present work innovates by offering an agile and flexible guide for simulation projects in production systems, which also supports online interventions. Research method Action Research method was used to develop the framework. After its development, the FaMoSim (Facilitated Modeling Simulation) framework was applied in a real case to evaluate its applicability. Main findings In the application of FaMoSim, we achieved the framework's objectives: carrying out a faster (up to 3 months) and more flexible online modeling process; creating a simple computer model that does not require a complex data collection structure nor a specialist team; generating a better understanding of the process and assisting the stakeholders in identifying improvements. Implications for theory and practice Considering some challenges that prevent the expansion of DES studies, the framework assists in expanding DES studies in environments where it is not widely used. The framework supports online interventions, making it an interesting tool that can be used mainly in times of social distancing.

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Abstract Paper aims This paper aims to evaluate the digitalization scenario of Brazilian industry, as well as to propose a practical approach to its digital transformation. Originality No comparison is available that aims to understand the differences and gaps between theoretical research and the reality of digital transformation in Brazilian industries. Research method Based on three steps, namely: review and bibliographic analysis to identify the main aspects of digital transformation; content analysis of national reports to define the state of practice; comparison between the results of theory and practice. Main findings The results demonstrate an alignment between the aspects found in the scientific literature and the reports analyzed. The pillars of digital transformation are widely discussed in industrial reality. However, implementation gaps (and related opportunities) difficult the digital transformation of the Brazilian industry. Implications for theory and practice This paper introduces a proposition that unites theoretical aspects in a model that may be applied to enable digital transformation in the industry.

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Abstract Paper aims This paper proposes a roadmap framework based on a literature review to choose the most proper indicators and targets for a given logistics process derived from the organization's strategic goals. Originality One of the many benefits from the introduction of technologies and the digitization of logistics processes is the acquisition of a great amount of data, which is a valuable asset for an efficient management. In order to transform this data into useful information, most companies rely on performance indicators. In this sense, this paper proposes a roadmap framework based on previous works to guide managers on how to choose a set of indicators that are linked to the company’s targets. To the best of our knowledge, no previous research has proposed a framework dealing with target definitions based on historical data and previous standards or benchmarking, as well as the logistics indicators choice based on the representation theory. Research method In order to elaborate the framework, a two-step structured literature review was carried out, combined with a case application. The literature review included steps based on the works of Govindan & Bouzon (2018) and Moher et al. (2009). The Scopus and the Web of Science databases were selected to gather material to base this study. The framework was applied in a Brazilian construction enterprise, located in Joinville city, Southern Brazil. Main findings The framework application showed that the methodology can facilitate the selection of indicators linked with the company’s strategic goals. Additionally, the indicators legitimation process with managers, a step from the framework, showed that managers' knowledge about the company’s processes is essential for a successful logistics performance system implementation. However, the managers can be resistant to changes for new indicators, and this situation should be avoided during the legitimation process. Future studies may expand the methodology application to other areas than logistics, and future applications of the framework in a Logistics 4.0 environment should provide more insights for the model. Implications for theory and practice From a theoretical perspective, a complete table of logistics performance indicators is provided, as well as the framework for indicators and target definition. From a practical panorama, the framework application shows that practitioners can use this study as a guide to develop more effective logistics performance measurement systems. Moreover, concluding remarks on the relationship between digital transformation and performance measurement systems are provided.

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Abstract Paper aims This paper aims to discuss Industry 4.0 (I4.0) impacts on the Brazilian Modular Consortium (BMC) assembly lines related to work - issues correlated with human resources; production - physical resources used in production process; knowledge - associated with creation and sharing of knowledge. Originality Findings explore I4.0 research opportunities related to work and human factors on assembly lines. In lieu of gaps in literature, this research further discusses management challenges to support digital transformation and impacts on workers and organizations. Research method A case study on Engine Value Chain (EVC) of BMC, which includes MWM, engine manufacturer; Powertrain, engine assembler at BMC; Volkswagen Truck & Bus, BMC responsible. Semi-structured interviews were conducted with four senior managers responsible for I4.0 implementation. Responses were treated via content analysis. Main findings The interviewees highlight work and human factors as important for I4.0 implementation, which include workers tasks, skills, nature of work, human resource development, hiring process and organizations strategies. It was also found that knowledge sharing poses a huge challenge. Implications for theory and practice The findings contribute with academic interest on work, production and knowledge impacts on assembly lines, and with practitioners on issues related to I4.0 implementation.

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Abstract Paper aims The objectives of this paper are: (i) to analyze the impacts of Inventory Record Inaccuracy (IRI) on picking productivity (PP), lost sales (LS), and warehouse capacity utilization (WCU) for different warehouses; (ii) verify if the Cycle Counting (CC) implementation is sufficient to reduce IRI and (iii) the number of CC operators to maintain warehouse performance. Originality A causal loop diagram in detail of the IRI and CC variable's effects in receiving and picking processes is developed. IRI is separated into ghost and hidden inventory to represent the actual effects in WCU, LS, and PP. Research method A dynamic system model is built. Simulations are performed for the five categories of warehouse performance with different numbers of CC operators. Main findings IRI impacts in all warehouses simulated, so managers should monitor IRI besides employee productivity. CC can reduce IRI in all types of warehouses. The number of CC operators to be implemented is different for each warehouse. Implications for theory and practice Several implications for theory and practice are discussed. For example, IRI impacts more ADV and BIC warehouses without CC implementation. In TYP, ADV, and BIC warehouses CC is sufficient to reduce IRI. In MO and DIS warehouses, other improvements are needed.

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Abstract Paper aims This paper analyzes the work quality and productivity of during the COVID-19 pandemic from five Brazilian regions with three work models: face-to-face, virtual and workshiting. Originality Despite the number of studies on COVID-19 since the pandemic’s beginning, the literature lacks research that demonstrates relationships between productivity and the emergence of problems, illnesses, and adverse situations that compromise worker performance in the routines of these three work models. Research method The study used an experimental, descriptive, and transversal research design, without identification data Southeast of the participant, as anonymous and exclusive research, with 801 participants from different regions of Brazil (North, Northeast, Midwest, Northeast, and South), with different age groups. The work consisted of work issues focusing on the quality of work pandemic, for issues of analysis of time and productivity problems. The questions were about health issues in 6 parts of the study: mental demographics and increased sleep quality, fear of SARS-CoV-2, exercise, stress, and productivity. Main findings There was a strong significant relationship between the three work models and five variables: area of activity, work equipment used during quarantine, diseases found during the pandemic, problems reported during quarantine pandemic like sleep, stress, workload performed, and future expectations regarding the work performed and the pandemic. Significant relationships were also found with diseases before the pandemic, those perceived and reported during the pandemic period studied, and the sleep profile before and during. The statistical significance relationship was also strong between the areas of work audience and new diseases during the pandemic. Implications for theory and practice The research practically validates several other theoretical studies, with guidelines for the scientific community on work behavior for the three work models. The results, together with the relationships found by the statistical analysis of the p-value of the variables, help the public and private authorities to understand and rethink preventive measures in the emergence of new diseases and the optimization of work operations without compromising their quality and productivity.