Search results

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 discursive paper considers the use of restrictive practices in mental health inpatient settings and how these are often prioritised over relational approaches, especially where the diagnostic label of personality disorder intersects with risk.

Key concepts from Orwell’s 1984 are studied for their pertinence to mental health inpatient settings, supporting our argument that restrictive practices arise from dichotomous thinking and externalised fears.

Drawing upon Orwellian themes of power, social control and digital surveillance from 1984, the authors highlight the role of fear in perpetuating restrictive practices under a guise of benevolent care in mental health inpatient settings, especially for those who are diagnosed with a personality disorder. A lack of preparedness to work with complexity in such environments, coupled with a deficit in self-reflexivity and critical thinking, can exacerbate challenges.

To transcend damaging dichotomies and reduce restrictive practices in inpatient settings, the authors make the argument for the adequate preparation and education of the mental health nurse and authentic, collaborative, user-involved care.

The authors use Orwell’s novel to support a critical discourse around those damaging dichotomies and inherent contradictions that contribute to restrictive practice in contemporary mental health settings and to question whose interests’ these restrictive practices serve.

This paper aims to explain the unwillingness to exchange export knowledge by members of exporters’ networks and provides potential solutions to this problem.

This study uses data from a survey of 301 members of a French exporter’s network to test a set of hypotheses with partial least squares structural equation modeling.

Network participants’ export experience and age have a negative influence on their willingness to exchange knowledge. However, positive attitudes toward the network (perception of network quality, commitment) can mitigate those negative links.

Network members’ unwillingness to exchange knowledge represents a major challenge that threatens the existence of knowledge networks. The findings suggest solutions to this issue for network managers.

This study views knowledge exchange in a network as a risky behavior. It explains why members do not participate in networks. The model shows how contrary forces work and interact to deter or foster knowledge exchange.

We examine how superstition shapes corporate tax avoidance and do so by taking a risk perspective and focusing on the zodiac-year belief prevalent in China.

We adopt a difference-in-differences research design to compare the degree of corporate tax avoidance in the CEOs’ zodiac year with that in the adjacent years. We do propensity-score matching to form a sample of Chinese listed firms for the regression analysis.

We find causal evidence that firms exhibit a greater magnitude of tax avoidance in the CEOs’ zodiac years, a result attributable to relatively weak tax enforcement in the Chinese context. We also find that the zodiac-year effect on corporate tax avoidance is more pronounced for firms with tight financial constraints, firms with high business risk, firms headquartered in regions with a high degree of superstition and non-state-owned firms.

This study is the first to show that superstition is a determinant factor of tax avoidance and contributes to the tax literature by shedding light on the behavioral risk factors that shape corporate tax avoidance. We take the perspective of CEOs’ risk appetite to analyze how tax avoidance is influenced by the CEOs’ trade-off between the costs and benefits of avoiding taxes. Our results suggest that, when CEOs are more risk-averse, they attach more importance to financial risk than the risk of reputational losses and litigation associated with corporate tax avoidance. The findings imply that tax avoidance can be curbed by increasing (or decreasing) the tax (financial) risk confronting the CEOs.

Corruption and manipulation of earnings remain a serious concern all over the globe. In addition, corporate disclosure of anticorruption information is still in its infancy in developing and emerging countries. Studies have also highlighted the importance of female directors in corporate disclosures and mitigating earnings management (EM). Therefore, the purpose of this study is to examine the moderating effect of board gender diversity on the relationship between anticorruption disclosure (ACD) on EM among listed firms in the East Africa Community (EAC) partners states.

The study used an ACD check list developed from recent studies and the Global Reporting Initiative (GRI) 205 on anticorruption reporting standards. The sample comprising of 58 firms listed across EAC partner states stock/securities exchanges over the period between 2013 and 2022. The hypotheses were tested using the fixed effect regression model.

This study found low disclosure of anticorruption practices among the selected firms. The regression results revealed that ACD and board gender diversity negatively affected EM. In addition, the study found that board gender diversity moderated the relationship between ACD and EM. The study used the system generalized method of moment (GMM) model to address endogeneity concerns.

The study will help policymakers and accounting standards setters in determining if mandatory ACD can reduce harmful EM practices. Furthermore, the findings can be helpful to corporate governance standards setters in deciding whether to implement gender quotas to enhance the effect of ACD on EM.

To the best of the author’s knowledge, this is the first paper that empirically examines the effect of ACD on EM in EAC. The study further adds to the empirical literature by assessing the moderating effect of board gender diversity, which has not been examined by earlier studies on ACD and EM.

This study aims to examine the impact of the decision makers’ risk preference on logistics routing problem, contributing to logistics behavior analysis and route integration optimization under uncertain environment. Due to the unexpected events and complex environment in modern logistics operations, the logistics process is full of uncertainty. Based on the chance function of satisfying the transportation time and cost requirements, this paper focuses on the fourth party logistics routing integrated optimization problem considering the chance preference of decision makers from the perspective of satisfaction.

This study used the quantitative method to investigate the relationship between route decision making and human behavior. The cumulative prospect theory is used to describe the loss, gain and utility function based on confidence levels. A mathematical model and an improved ant colony algorithm are employed to solve the problems. Numerical examples show the effectiveness of the proposed model and algorithm.

The study’s findings reveal that the dual-population improvement strategy enhances the algorithm’s global search capability and the improved algorithm can solve the risk model quickly, verifying the effectiveness of the improvement method. Moreover, the decision-maker is more sensitive to losses, and the utility obtained when considering decision-makers' risk attitudes is greater than that obtained when the decision-maker exhibits risk neutrality.

In an uncertain environment, the logistics decision maker’s risk preference directly affects decision making. Different parameter combinations in the proposed model could be set for decision-makers with different risk attitudes to fit their needs more accurately. This could help managers design effective transportation plans and improve service levels. In addition, the improved algorithm can solve the proposed problem quickly, stably and effectively, so as to help the decision maker to make the logistics path decision quickly according to the required confidence level.

Considering the uncertainty in logistics and the risk behavior of decision makers, this paper studies integrated routing problem from the perspective of opportunity preference. Based on the chance function of satisfying the transportation time and cost requirements, a fourth party logistics routing integrated optimization problem model considering the chance preference of decision makers is established. According to the characteristics of the problem, an improved dual-population ant colony algorithm is designed to solve the proposed model. Numerical examples show the effectiveness the proposed methods.

The Indian stock market can be tricky when there's trouble in the world, like wars or big conflicts. It's like trying to read a secret message. We want to figure out what makes investors nervous or happy, because their feelings often affect how they buy and sell stocks. We're building a tool to make prediction that uses both numbers and people's opinions.

Hybrid approach leverages Twitter sentiment, market data, volatility index (VIX) and momentum indicators like moving average convergence divergence (MACD) and relative strength index (RSI) to deliver accurate market insights for informed investment decisions during uncertainty.

Our study reveals that geopolitical tensions' impact on stock markets is fleeting and confined to the short term. Capitalizing on this insight, we built a ground-breaking predictive model with an impressive 98.47% accuracy in forecasting stock market values during such events.

To the best of the authors' knowledge, this model's originality lies in its focus on short-term impact, novel data fusion and high accuracy. Focus on short-term impact: Our model uniquely identifies and quantifies the fleeting effects of geopolitical tensions on market behavior, a previously under-researched area. Novel data fusion: Combining sentiment analysis with established market indicators like VIX and momentum offers a comprehensive and dynamic approach to predicting market movements during volatile periods. Advanced predictive accuracy: Achieving the prediction accuracy (98.47%) sets this model apart from existing solutions, making it a valuable tool for informed decision-making.

The literature mainly concentrates on the relationships between externally oriented digital transformation (ExtDT), big data analytics capability (BDAC) and business model innovation (BMI) from an intra-organizational perspective. However, it is acknowledged that the external environment shapes the firm's strategy and affects innovation outcomes. Embracing an external environment perspective, the authors aim to fill this gap. The authors develop and test a moderated mediation model linking ExtDT to BMI. Drawing on the dynamic capabilities view, the authors' model posits that the effect of ExtDT on BMI is mediated by BDAC, while environmental hostility (EH) moderates these relationships.

The authors adopt a quantitative approach based on bootstrapped partial least square-path modeling (PLS-PM) to analyze a sample of 200 Italian data-driven SMEs.

The results highlight that ExtDT and BDAC positively affect BMI. The findings also indicate that ExtDT is an antecedent of BMI that is less disruptive than BDAC. The authors also obtain that ExtDT solely does not lead to BDAC. Interestingly, the effect of BDAC on BMI increases when EH moderates the relationship.

Analyzing the relationships between ExtDT, BDAC and BMI from an external environment perspective is an underexplored area of research. The authors contribute to this topic by evaluating how EH interacts with ExtDT and BDAC toward BMI.

This study aims to analyze the effect of cognitive load and social value orientation on managers’ preferences when they face with two types of restructuring choices in financially distressed firms: the first belonging to the family of organizational restructuring (massive layoffs) and the second to the family of financial restructuring (debt increases).

The authors investigate experimentally the impact of managers’ cognitive load and social value orientation on the decision to restructure leveraged buyout (LBO) firms in financial distress by using either massive layoffs or debt increases.

By investigating the impact of managers’ cognitive load and social value orientation on the restructuring decision of an LBO firm in financial distress, the research reveals that, on average, cognitively loaded managers prefer massive layoffs over increased debt levels. The massive layoffs seemingly provide a relatively easier way to avoid conflict with influential, residual claimants. In contrast, social value–oriented managers actively avoid massive layoffs and prefer to increase debt.

These results imply that the performance mechanisms emphasized to improve agency relations, for example, in LBOs, have their own limitations during periods of financial distress. This study shows that one of these limits is related to cognitive distortions and personality traits.

In this research, the originality lies in understanding how managers’ internal factors affect their restructuring decision-making, in the case of LBO firms in financial distress.

This study aims to understand the dynamics of Australian boards by focusing on the influence of board gender diversity on firms' cash holdings, within the distinctive Australian “if not, why not” regulatory framework.

The study uses ordinary least squares (OLS), fixed effects, generalized method of moments (GMM) and quasi-experimental methods such as difference-in-differences and propensity score matching to analyze the data.

There is a significantly negative relationship between board gender diversity and corporate cash holdings. This relationship is more pronounced when two or more female directors are on the board, supporting the critical mass theory. The results also reveal that the observed pattern can be attributed to the heightened monitoring intensity of female independent directors. Our quasi-experimental methods and pre-post analysis reveal that the observed effects are genuinely attributable to the increase in board gender diversity following regulatory reforms in Australia.

The findings provide practical insights for companies and policymakers, emphasizing the tangible effects of gender diversity on a company's financial strategy and corporate cash holdings. This information is crucial for organizations aiming to make informed decisions regarding board compositions and governance structures.

This research offers fresh insights into an important relationship between gender diversity on boards and corporate financial strategies in the Australian context, enriching the global conversation on the significance of gender diversity in corporate leadership.