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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.

This paper aims to critically examine the accounting and information systems literature to understand the changes that are occurring in the management accounting profession. The changes the authors are interested in are linked to technology-driven innovations in managerial decision-making and in organizational structures. In addition, the paper highlights research gaps and opportunities for future research.

The authors adopted a grounded theory literature review method (Wolfswinkel et al., 2013) to achieve the study’s aims.

The authors identified four research themes that describe the changes in the management accounting profession due to technology-driven innovations: structured vs unstructured data, human vs algorithm-driven decision-making, delineated vs blurred functional boundaries and hierarchical vs platform-based organizations. The authors also identified tensions mentioned in the literature for each research theme.

Previous studies display a rather narrow focus on the role of digital technologies in accounting work and new competences that management accountants require in the digital era. By contrast, the authors focus on the broader technology-driven shifts in organizational processes and structures, which vastly change how accounting information is collected, processed and analyzed internally to support managerial decision-making. Hence, the paper focuses on how management accountants can adapt and evolve as their organizations transition toward a digital environment.

We develop a credit-risk model to study the informational role of investment in an economy susceptible to large liquidity shocks. Firms' investment decisions carry information about their asset quality, thereby mitigating informational frictions when firms enter bankruptcy. An increase in aggregate investment can reduce the informational value of investment, depressing firms' recovery values. Therefore, policies boosting investment can decrease debt and firm values by reducing the informational value of investment. The presence of debt overhang may enhance firm value by making firms' investment decisions more informative. We present suggestive empirical evidence consistent with model predictions on the relation between firms' investments and recovery rates.

The purpose of this systematic review is to critically analyze pharmaceutical industry case studies on the implementation of Lean 4.0 methodologies to synthesize key lessons, benefits and best practices. The goal is to inform decisions and guide investments in related technologies for enhancing quality, compliance, efficiency and responsiveness across production and supply chain processes.

The article utilized a systematic literature review (SLR) methodology following five phases: formulating research questions, locating relevant articles, selecting and evaluating articles, analyzing and synthesizing findings and reporting results. The SLR aimed to critically analyze pharmaceutical industry case studies on Lean 4.0 implementation to synthesize key lessons, benefits and best practices.

Key findings reveal recurrent efficiency gains, obstacles around legacy system integration and data governance as well as necessary operator training investments alongside technological upgrades. On average, quality assurance reliability improved by over 50%, while inventory waste declined by 57% based on quantified metrics across documented initiatives synthesizing robotics, sensors and analytics.

As a comprehensive literature review, findings depend on available documented implementations within the search period rather than direct case evaluations. Reporting bias may also skew toward more successful accounts.

Synthesized implementation patterns, performance outcomes and concealed pitfalls provide pharmaceutical leaders with an evidence-based reference guide aiding adoption strategy development, resource planning and workforce transitioning crucial for Lean 4.0 assimilation.

This systematic assessment of pharmaceutical Lean 4.0 adoption offers an unprecedented perspective into the real-world issues, dependencies and modifications necessary for successful integration, absent from conceptual projections or isolated case studies alone until now.

The purpose of this paper is to explore how process management (PM) can support small- and medium-sized enterprises (SMEs) in pursuing sustained competitive advantage. For this purpose, a dynamic capabilities (DC) lens was used.

A narrative literature review and a multiple case study with an action research approach at two road freight transport companies were used.

PM provides structure and system thinking to support the development of competitive advantage. Concerning PM, management of knowledge, management style and process orientation are key factors for the generation of competitive advantage for SMEs.

This study contributes to PM literature by studying its support for and implementation at SMEs. Furthermore, the study contributes to the literature on DC by providing concrete examples of activities linked to such capabilities.

This study contributes to practitioners by providing examples of implementing PM and identifying competitive advantage, connected with PM elements.

This study has social and environmental implications for the quality of life of the Swedish people.

This paper contributes to clarifying the connection between the research fields of quality management and DC to explore how PM can support SMEs in pursuing sustained competitive advantage.

To enrich the research on the economic consequences of enterprise digital development from the perspective of capacity utilization.

Using a sample of listed firms from 2010 to 2020, this paper exploits text analysis of annual reports to construct a proxy for enterprise digital development.

Results show that enterprise digital development not only improves their own capacity utilization but also generates a positive spillover effect on the capacity utilization of peer firms and firms in the supply chain. Next, based on the incomplete information about market demand and potential competitors when making capacity-building decisions, the mechanism tests show that improving the accuracy of market forecasts and reducing investment surges are potential channels behind the baseline results. Cross-sectional tests show the baseline result is more pronounced when industries are highly homogeneous and when firms have access to less information.

This paper contributes to the research related to the economic consequences of digital development. With the development of the digital economy, the real effects of enterprise digital development have also triggered extensive interest and exploration. Existing studies mainly examine the impact on physical operations, such as specialization division of labor, innovation activities, business performance or total factor productivity (Huang, Yu, & Zhang, 2019; Yuan, Xiao, Geng, & Sheng, 2021; Wang, Kuang, & Shao, 2017; Li, Liu, & Shao, 2021; Zhao, Wang, & Li, 2021). These studies measure the economic benefits from the perspective of the supply (output) side but neglect the importance of the supply system to adapt to the actual market demand. In contrast, this paper focuses on capacity utilization, aimed at estimating the net economic effect of digital development by considering the supply-demand fit scenario. Thus, our findings enrich the relevant studies on the potential consequences of digital development.

Currently, foresight studies have been adapted to incorporate new techniques based on big data and machine learning (BDML), which has led to new approaches and conceptual changes regarding uncertainty and how to prospect future. The purpose of this study is to explore the effects of BDML on foresight practice and on conceptual changes in uncertainty.

The methodology is twofold: a bibliometric analysis of BDML-supported foresight studies collected from Scopus up to 2021 and a survey analysis with 479 foresight experts to gather opinions and expectations from academics and practitioners related to BDML in foresight studies. These approaches provide a comprehensive understanding of the current landscape and future paths of BDML-supported foresight research, using quantitative analysis of literature and qualitative input from experts in the field, and discuss potential theoretical changes related to uncertainty.

It is still incipient but increasing the number of prospective studies that use BDML techniques, which are often integrated into traditional foresight methodologies. Although it is expected that BDML will boost data analysis, there are concerns regarding possible biased results. Data literacy will be required from the foresight team to leverage the potential and mitigate risks. The article also discusses the extent to which BDML is expected to affect uncertainty, both theoretically and in foresight practice.

This study contributes to the conceptual debate on decision-making under uncertainty and raises public understanding on the opportunities and challenges of using BDML for foresight and decision-making.

Literature on the board diversity of Islamic banks (IB) found limited knowledge of the “deep-level” attribute. This study aims to explain the impact of the board diversity attributes (education levels, educational backgrounds and the interactions between these two attributes of diversity) on profitability.

The research sample is 37 fully flagged IBs from five Southeast Asian countries, covering nine years (2010–2019). Data were analyzed using the two-step system generalized moment (2SYS-GMM) method.

We found that the cognitive conflict between the board of directors (BOD) and the Shariah Supervisory Board (SSB), which has heterogeneity in its education level and educational background, positively affects profitability. These results reinforce the resources dependence theory (RDT) approach that having boards with heterogeneous characteristics is beneficial for IB.

The findings of this study would offer useful information for Islamic banking authorities to revise or formulate rules and guidelines and make a greater effort to implement corporate governance (CG) reform measures by determining educational level and background as a requirement to become a member of a BOD or an SSB.

This paper contributes in three ways: (1) we use the “deep-level” diversity attributes of the BOD and the SSB, (2) it focuses on cognitive conflict in boards by presenting the expertise diversity of the BOD and SSB and (3) we interact with the level of education to evaluate the effect of a cognitive conflict.

This study aims to investigate the effects of board cultural diversity (BCD) and board gender diversity (BGD) of the board of directors on environmental, social and governance (ESG) performance in the European banking sector using resource-based view (RBV) theory. In addition, this study analyses the linkages between BCD and BGD and knowledge sharing on the board of directors to improve ESG performance.

This study selected a sample of European-listed banks covering the period 2021. ESG and diversity variables were collected from Refinitiv Eikon and analysed using the ordinary least squares model. This study was conducted in the European context regulated by Directive 95/2014/EU, which requires sustainability disclosure. The original population was represented by 250 banks; after missing data were excluded, the final sample comprised 96 European-listed banks.

The findings highlight the positive linkages between BGD, BCD and ESG scores in the European banking sector. In addition, the findings highlight that diversity contributes to knowledge sharing by improving ESG performance in a regulated sector. Nonetheless, the combined effect of BGD and BCD negatively impacts ESG performance.

To the best of the authors’ knowledge, this is the first study to measure and analyse a regulated sector, such as banking, and the relationship between cultural and gender diversity for sharing knowledge under the RBV theory lens in the ESG framework.

This study investigates the relationship between board gender diversity (BGD) and the time to Initial Public Offering (IPO), which stands as an entrepreneurially risky choice, particularly challenging in family firms. We also investigate the moderating role of family ownership dispersion (FOD).

We draw on an integrated theoretical framework bringing together the upper echelons theory and the socio-emotional wealth (SEW) perspective and on hand-collected data on a sample of Italian family IPOs that occurred in the period 2000–2020. We employ ordinary least squares (OLS) regression and alternative model estimations to test our hypotheses.

BGD positively affects the time to IPO, thus, it increases the time required to go public. FOD negatively moderates this relationship. Our findings remain robust with different measures for BGD, FOD, and family business definition as well as with different econometric models.

The article develops literature on family firms and IPO and it enriches the academic debate about gender and IPOs in family firms. It adds to studies addressing the determinants of the time to IPO by incorporating gender diversity and the FOD into the discussion. Finally, it contributes to research on women and outcomes in family firms.