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Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team interacts when making BMI decisions. The paper also investigates how group biases and board members’ risk willingness affect this process.

Empirical data were collected through 26 in-depth interviews with German managing directors from 13 companies in four industries (mobility, manufacturing, healthcare and energy) to explore three research questions: (1) What group effects are prevalent in BMI group decision-making? (2) What are the key characteristics of BMI group decisions? And (3) what are the potential relationships between BMI group decision-making and managers' risk willingness? A thematic analysis based on Gioia's guidelines was conducted to identify themes in the comprehensive dataset.

First, the results show four typical group biases in BMI group decisions: Groupthink, social influence, hidden profile and group polarization. Findings show that the hidden profile paradigm and groupthink theory are essential in the context of BMI decisions. Second, we developed a BMI decision matrix, including the following key characteristics of BMI group decision-making managerial cohesion, conflict readiness and information- and emotion-based decision behavior. Third, in contrast to previous literature, we found that individual risk aversion can improve the quality of BMI decisions.

This paper provides managers with an opportunity to become aware of group biases that may impede their strategic BMI decisions. Specifically, it points out that managers should consider the key cognitive constraints due to their interactions when making BMI decisions. This work also highlights the importance of risk-averse decision-makers on boards.

This qualitative study contributes to the literature on decision-making by revealing key cognitive group biases in strategic decision-making. This study also enriches the behavioral science research stream of the BMI literature by attributing a critical influence on the quality of BMI decisions to managers' group interactions. In addition, this article provides new perspectives on managers' risk aversion in strategic decision-making.

Considering the bounded confidence of decision-makers (DMs), a new grey multi-criteria group consensus decision-making (GMCGCDM) model is established by using interval grey number (IGN), cobweb model, social network analysis (SNA) and consensus reaching process (CPR).

Firstly, the model analyzes the social relationship of DM under social networks and proposes a calculation method for DMs’ weights based on SNA. Secondly, the model defines a cobweb model to consider the preferences of decision-making alternatives in the decision-making process. The consensus degree is calculated by the area surrounded by the connections between each index value of DMs and the group. Then, the model coordinates the different opinions of various DMs to reduce the degree of bias of each DM and designs a consensus feedback mechanism based on bounded confidence to guide DMs to reach consensus.

The advantage of the proposed method is to highlight the practical application, taking the selection of low-carbon suppliers in the context of dual carbon as an example. Comparison analysis is performed to reveal the interpretability and applicability of the method.

The main contribution of this paper is to propose a new GMCGCDM model, which can not only expand the calculation method of DM’s weight and consensus degree but also reduce the time and cost of decision-making.

As the scale of mega transportation infrastructure projects (MTIs) continues to expand, the complexity of engineering construction sharply increases and decision-making sustainability faces severe challenges. Decision-making for mega transportation infrastructure projects unveils the knowledge-intensive characteristic, requiring collaborative decisions by cross-domain decision-makers. However, the exploration of heterogeneous knowledge fusion-driven decision-making problems is limited. This study aims to improve the deficiencies of existing decision-making by constructing a knowledge fusion-driven multi-attribute group decision model under fuzzy context to improve the sustainability of MTIs decision-making.

This study utilizes intuitionistic fuzzy information to handle uncertain information; calculates decision-makers and indicators weights by hesitation, fuzziness and intuitionistic fuzzy entropy; applies the intuitionistic fuzzy weighted averaging (IFWA) operator to fuse knowledge and uses consensus to measure the level of knowledge fusion. Finally, a calculation example is given to verify the rationality and effectiveness of the model.

This research finally constructs a two-level decision model driven by knowledge fusion, which alleviates the uncertainty and fuzziness of decision knowledge, promotes knowledge fusion among cross-domain decision-makers and can be effectively applied in practical applications.

This study provides an effective decision-making model for mega transportation infrastructure projects and guides policymakers.

The inconsistent results shown in previous group faultline research have created a need for investigating the underlying mechanisms of the faultline's effects. This study focuses on clarifying the competing mediating roles of information diversity and team conflict in the nonlinear relationship between board faultlines (BF) and decision quality.

This study is empirically tested with the questionnaire data from 105 Chinese listed companies.

This study finds: (1) an inverted U-shaped curve relationship between BF and board decision quality and (2) that the joint mediating effect of team conflict and information diversity leads to the inverted U-shaped curve relationship between BF and decision quality. Specifically, BF shows a U-shaped curve relationship with team conflict and an inverted U-shaped curve relationship with information diversity. Either too weak or too strong faultlines will inhibit the positive effects of information diversity and amplify the negative effects of team conflicts, leading to low-quality decisions.

This study contributes to the research on: (1) board governance as it clarifies the effect of BF on the board decision-making process and its quality, which helps to open the black box of board decision-making and (2) group faultlines as it reveals how information diversity and team conflict can play a joint mediating role in the functioning of team faultlines.

This article aims to trace the historical development of the behavioral strategy (BS) field, which implements psychology in strategic management. Mainly, it provides a contextual understanding of how this stream of research has historically evolved and what relevant future trajectories are. This work is part of the “over half a century of Management Decision” celebrative and informal Journal section.

We consider BS literature produced in management decision (MD), the oldest and longest-running scholarly publication in management, as a proxy for the evolution of management thought. Through a Systematic Literature Review (SLR) process, we collected – via the MD website and Scopus – a sample of 97 BS articles published in MD from its foundation (1967) until today (2024). Regarding the analysis, we adopted a Reflexive Thematic Analysis approach to synthesize the main BS topics, then read from a historical perspective regarding three “eras” over which the literature developed. Selected international literature outside the Journal’s boundaries was considered to complement this historical analysis.

Historically, within the BS field, the interest passed from the rules to rationally govern strategic decision-making processes, to studying what causes cognitive errors, to understanding how to avoid biases and to being prepared for dramatic changes. The article also identifies six future research trajectories, namely “positive heuristics,” “context-embedded mental processes,” “non-conventional thinking,” “cognitive evolutionary triggers,” “debiasing strategies” and “behavioral theories for new strategic challenges” that future research could investigate.

The limitation of the study lies in its exclusive focus on MD for investigating the historical evolution of BS, thereby overlooking critical contributions from other journals. Therefore, MD’s editorial preferences have influenced results. A comprehensive SLR on the BS field is still needed, requiring broader journal coverage to mitigate selection biases and enhance field appraisal.

This contribution is the first to offer a historical evolutionary view of the BS field, complementing the few other reviews on this stream of research. This fills a gap in the study of the evolution of management thought.

This study aimed to identify the determinants of farmers' participation in agricultural information-sharing digital groups and their impacts on farm performance.

Primary data of the 2015/2016 crop year collected from 175 cattle farmers were analyzed using descriptive statistics and econometric models. Farmers who had smartphones and participated in social groups/applications, especially those created to exchange agricultural information, were considered adopters of the technology.

A Poisson hurdle model showed that farmers' decision to participate in agricultural information-sharing digital groups is determined by schooling, age (negative effect) and use of tools for planning production. The intensity of participation is affected by risk propensity, interaction with specialist advisors, use of tools for planning production and participation in cooperatives. The authors also found empirical evidence that farmers' participation in agricultural information-sharing digital groups positively affects farm income per hectare.

The results of this study are important for accelerating the diffusion of low-cost digital technologies, which are powerful tools for improving farmers' sharing and access to valuable information in real time and in locations far from urban areas.

To the best of the authors’ knowledge, this is the first empirical analysis of the adoption and impacts of agricultural information-sharing digital groups/applications by Brazilian cattle farmers. The diffusion of simple digital technologies is important for reducing heterogeneity and increasing the efficiency of cattle production.

This article aims to tackle the organization's problems with a new paradigm of organizational consciousness by developing a framework.

The Phenomenological and Framework Synthesis approach is used to develop the conceptual framework for organizational consciousness.

The research article highlights organizational consciousness's implications for long-term sustainable success. It emphasizes the positive impact of conscious organizations on stakeholder well-being and the resolution of environmental and social problems.

The organizational consciousness framework encompasses the collective awareness, values, and purpose that guide an organization's actions and decisions. The framework emphasizes aligning organizational values, needs, and goals with all stakeholders' social, environmental, and well-being. It highlights the interconnectedness of stakeholders and encourages a system-thinking perspective. Furthermore, it acknowledges the role of individual and group consciousness in driving organizational transformation. It discusses the pathway to organizational success through conscious practices, emphasizing value creation beyond monetary gain. It explores the role of conscious leadership, innovative and continuous learning, and adaptation in fostering conscious organizations.

The purpose of the study is to examine the relation between board structure and firm performance variability in an international setting. The authors further explore the effect of national culture in shaping such relations.

The authors’ international sample contains 4,911 firms across 49 countries over the 2002–2017 period. The authors use national culture values on individualism and power distance developed by Hofstede (1980, 2001, 2011). The authors focus on within-firm, over-time variability of firm performance and estimate multivariate linear regressions with fixed effects. The authors address the endogeneity concern using the instrumental variable approach, and the authors’ results are robust to alternative measures of variables and different subsamples.

The authors find that firms with larger board size, greater board independence and less powerful CEOs have less variable performance. Individualism has a magnifying effect while power distance has a mitigating effect in shaping such relations.

To the best of the authors’ knowledge, this study is among the first to answer the call of Adams, Hermalin and Weisbach (2010) for research on corporate boards in an international setting. It is also one of the few studies which examine the variability of firm performance, while the majority of existing literature focuses on the level of firm performance. Most importantly, to the best of the authors’ knowledge, this study is the first to explore the role of national culture in shaping boardroom interactions that affect the decision-making process of corporate boards, which, in turn, affects firm performance variability.

Traditional risk prioritization methods in Enterprise Risk Management (ERM) rely on precise data, which is often not available in real-world contexts. This study addresses the need for a robust model that can handle uncertain and imprecise information for more accurate risk assessment.

We propose a group decision-making approach using fuzzy numbers to represent risk attributes and preferences. These are converted into fuzzy risk scores through defuzzification, providing a reliable method for risk ranking.

The proposed fuzzy risk prioritization framework improves decision-making and risk awareness in businesses. It offers a more accurate and robust ranking of enterprise risks, enhancing control and performance in supply chain operations by effectively representing uncertainty and accommodating multiple decision-makers.

The adoption of this fuzzy risk prioritization framework can lead to significant improvements in enterprise risk management across various industries. By accommodating uncertainty and multiple decision-makers, organizations can achieve more reliable risk assessments, ultimately enhancing operational efficiency and strategic decision-making. This model serves as a guide for firms seeking to refine their risk management processes under conditions of imprecise information.

This study introduces a novel weighted fuzzy Risk Priority Number method validated in the risk management process of an integrated steel plant. It is the first to apply this fuzzy approach in the steel industry, demonstrating its practical effectiveness under imprecise information. The results contribute significantly to risk assessment literature and provide a benchmarking tool for improving ERM practices.

The purpose of this study is to analyze the impacts of the COVID-19 pandemic on the performance of companies using a hybrid Multi-Criteria Decision-Making (MCDM) approach. Specifically, the study examines Türkiye’s Top 500 Industrial Enterprises to analyze their performance before and during the pandemic, and to capture their performance in determining investment and production strategy.

To achieve the study’s objectives, the Fuzzy Best-Worst Method (F-BWM) was used to obtain importance levels of performance indicators, decreasing the vagueness in experts’ decision-making preferences. The Measurement Alternatives and Ranking According to Compromise Solution (MARCOS) method was used to rank enterprises based on their performance.

The COVID-19 pandemic has clearly had a substantial impact on the performance of Türkiye’s top 500 industrial enterprises. While some companies suffered decreased sales, others reported that their revenues increased or remained constant during the outbreak. The results reveal that the pandemic caused a shift in the initial ranking outcomes for the first two enterprises.

The study’s limitations include the sample size and the time period under consideration, which may have an impact on the generalizability of the findings.

Decision-makers’ investment, employment and operational decisions were influenced by the impact of the COVID-19 pandemic. The results provide insights for decision-makers on how to achieve higher growth and performance under the pressure of the pandemic.

The study’s practical consequences help decision-makers understand how to attain higher growth and performance in the face of the epidemic.

The originality of this study lies in using a hybrid MCDM approach to examine the impact of the COVID-19 pandemic on company performance. A hybrid MCDM approach is proposed to help decision-makers make the best possible investment and implementation decisions.