This study demonstrates how artificial intelligence (AI) shapes the strategic planning process in volatile, uncertain, complex and ambiguous (VUCA) business environments. Having adopted various domains of the Cynefin framework, the research explores AI's transformative potential and provide insights regarding how organisations can harness AI-driven solutions for strategic planning.
This conceptual paper theorises the role of AI in strategic planning process in a VUCA world by integrating extant knowledge across multiple literature streams. The “model paper” approach was adopted to provide a theoretical framework predicting relationships among considered concepts.
The paper highlights potential application of the Cynefin framework to manage complexities in strategic decision-making process, the transformative impact of AI at different stages of strategic planning, the required strategic planning characteristics within VUCA to be supported by AI and the attendant challenges posed by AI integration in the uncertain business landscape.
This study pioneers a theoretical exploration of AI's role in strategic planning within the VUCA business landscape, guided by the Cynefin framework. Thus, it enriches scholarly discourse and expands knowledge frontiers.
Scholars have underscored the importance of organizational authenticity, but it is unclear how it influences the links among market strategy, and nonmarket strategy (NMS) and firm performance. This study addresses this gap in the literature.
A survey of 294 managers in firms based in the United States investigates configurations among competitive strategy (e.g. cost leadership or differentiation), political and social nonmarket strategy (NMS), authenticity, and firm performance.
Cost leaders tend to engage in political nonmarket strategy (PNMS), but the interaction does not necessarily improve firm performance. Differentiators are more likely to pursue social nonmarket strategy (SNMS) and perform better, but neither market-nonmarket strategy configuration is inherently optimal.
The results support market-nonmarket strategy configurations but do not prescribe optimal combinations. However, the sample is cross-sector and employs self-reports for firm performance.
Political and social authenticity can enhance firm performance, but nonmarket activity can compromise a firm’s ability to be politically and socially authentic. Authenticity can drive performance, but a firm’s nonmarket activity can compromise its ability to be politically and socially authentic. Firms should view a prospective loss in authenticity as a potential cost of nonmarket activity.
This paper investigates how a firm’s emphasis on market (competitive) strategies, political and social nonmarket strategies, and political and social authenticity impact financial and non-financial performance. It also tests the veracity of two market-nonmarket configurations, cost leadership with political NMS and differentiation with social NMS.
Despite considerable evidence of the benefits of organizational transparency, policies to enhance transparency often fail or are met with resistance and unexpected results. In part, this is due to a lack of knowledge about the drivers of organizational transparency and their interrelationships. This study examines the interplay among the forces that influence organizational transparency, and thus answers numerous calls for developing a deeper theoretical understanding of the determinants of organizational transparency. We propose three forces that influence organizational transparency and theorize how they combine in nonlinear ways to form five archetypical transparency regimes that organizations operate within. We then discuss contingencies to organizational transparency within each regime.
We employ configurational theorizing to capture the complexity of transparency and the nonlinear relationships among the forces of transparency.
We propose three forces that influence organizational transparency: institutional, societal, and leadership. We identify configurations of the three forces that yield five archetypical transparency regimes. We then discuss contingencies for cultivating organizational transparency within each regime. Vanguard transparency and pioneering transparency represent the desired regimes for fostering organizational transparency. In contrast, hollow transparency and deceptive transparency reveal a combination of determinants that cultivate less desirable forms of organizational transparency. Paradoxical transparency represents a regime in which socially desirable outcomes are associated with undesirable consequences for an organization.
This paper is among the first to theorize the drivers of organizational transparency and to discuss the limits and boundaries of organizational responses to transparency determinants.
Despite the many benefits of transparency, we explain why efforts to enhance organizational transparency often fail or are met with mixed results. By considering the three forces, managers and policymakers can avoid unexpected and undesired organizational responses to transparency regimes.
We propose five transparency regimes that place a spotlight on social contingencies to enhance transparency.
This study offers an integrative theory of organizational responses to transparency determinants and develops its theoretical foundations. The model integrates the fragmented empirical findings from previous studies on the determinants of transparency and draws attention to overlooked institutional, societal, and leadership forces
This study investigates the relationships between environmental, social, and governance (ESG) controversies and insolvency risk in the insurance sector. Drawing from legitimacy and stakeholder theories, the authors explore the impact of ESG controversies on insurers’ insolvency risk and the moderating effect of ESG practices on this relationship.
This study utilises a dataset comprising 120 stock insurance firms spanning from 2011 to 2022. The authors employed system-GMM estimations to control for potential endogeneity and conducted several robustness checks.
ESG controversy positively influences insurers’ insolvency risk, with ESG practices mitigating these positive effects. The Governance (G) component of ESG practices plays a key role in counteracting the effects of ESG controversies on insurance companies’ insolvency risk.
This is the first study to investigate the direct relationship between ESG controversies and insolvency risk in the insurance industry. It underscores the critical influence of stakeholders’ perceptions of the company’s legitimacy, which is determined by the number of ESG controversies undertaken by the insurer company, on its insolvency risk. Additionally, by examining the three components of ESG practices individually, the authors offer insights into how managers can gain a competitive edge, particularly by utilising governance practices as safeguards against the adverse effects of ESG controversies on their financial risk.
Although many countries are focusing on the management of construction and demolition waste (CDW) resource utilization, the effect of risk aversion of the green innovation-led enterprise on the performance of the CDW resource utilization supply chain is unclear when considering different green innovation contexts (green innovation led by the building materials remanufacturer or by the construction waste recycler). This study aims to investigate how the level of risk aversion of the green innovation-led enterprise affects CDW resource utilization under different green innovation contexts based on contingency theory.
Using Stackelberg game theory, this study establishes a decision model consisting of a building materials remanufacturer, construction waste recycler and CDW production unit and investigates how the level of risk aversion of the green innovation-led enterprise under different green innovation contexts influences the performance level of the supply chain.
The conclusions are as follows. (1) For the green innovation-led enterprise, the risk-averse behaviour is always detrimental to his own profits. (2) For the follower, the profits of the construction waste recycler are negatively correlated with the level of risk aversion of the green innovation-led enterprise in the case of a small green innovation investment coefficient. If the green innovation investment coefficient is high, the opposite result is obtained. (3) When the green innovation investment coefficient is low, the total supply chain profits decrease as the level of risk aversion of the green innovation-led enterprise increases. When the green innovation investment coefficient is high, total supply chain profit shows an inverted U-shaped trend with respect to the degree of risk aversion of the green innovation-led enterprise.
(1) This study is the first to construct a green innovation context led by different enterprises in the CDW resource utilization supply chain, which provides a new perspective on green management and operation. (2) This study is the first to explore the operation mechanism of the CDW resource utilization supply chain based on contingency theory, which provides new evidence from the CDW resource utilization supply chain to prove contingency theory. At the same time, this study examines the interactive effects of the green innovation cost coefficient and the degree of risk aversion of green innovation-led enterprises on the performance of supply chain members, expanding the contingency theory research on contingencies affecting enterprise performance. (3) This study will guide members of the CDW resource utilization supply chain to rationally face risks and achieve optimal supply chain performance.
Artificial intelligence (AI) can help in defining preventive strategies in taking decisions in complex situations. This paper aims to research how workers might deal with intervening AI tools, with the goal of improving their daily working decisions and movements. We contribute to deepening how workers might deal with intervening AI tools aiming at improving their daily working decisions and movements. We investigate these aspects within a field, which is growing in importance due to environmental sustainability issues, i.e. waste management (WM).
This manuscript intends to (1) investigate if AI allows better performance in WM by reducing social security costs and by guaranteeing a better continuity of service and (2) examine which structural change is required to operationalize this predictive risk model in the real working context. To achieve these goals, this study developed a qualitative inquiry based on face-to-face interviews with highly qualified experts.
There is a positive impact of AI schemes in helping to detect critical operating issues. Specifically, AI potentially represents a tool for an alignment of operational behaviours to business strategic goals. Properly elaborated information, obtained through wearable digital infrastructures, allows to take decisions to streamline the work organization, reducing potential loss due to waste of time and/or physical resources.
Being a qualitative study, and the limited extension of data, it is not possible to guarantee its replication and generalizability. Nevertheless, the prestige of the interviewees makes this research an interesting pilot, on such an emerging theme as AI, thus eliciting stimulating insights from a deepening of information coming from respondents’ knowledge, skills and experience for implementing valuable AI schemes able to an align operational behaviours to business strategic goals.
The most critical issue is represented by the “quality” of the feedback provided to employees within the business environment, specifically when there is a transfer of knowledge within the organization.
The study focuses on a less investigated context, the role of AI in internal decision-making, particularly, for what regards the interaction between managers and workers as well as the one among workers. Algorithmically managed workers can be seen as the players of summarized results of complex algorithmic analyses offered through simpleminded interfaces, which they can easily use to take good decisions.
This article aims to assess risks related to the supply chain 5.0 digitalization. It aims to analyze interdependencies and causal relationships between critical digital supply chain 5.0 risks, emphasizing the need for proactive management to address emerging challenges.
Through an extensive literature review and expert judgment, risks related to supply chain 5.0 digitalization are identified. An integrated approach for risk assessment is employed, where the Analytic Hierarchy Process (AHP) is utilized to prioritize these risks. Subsequently, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is employed to investigate cause-and-effect relationships among the identified top 10 risks. This comprehensive analysis forms the basis for informed strategic management decision-making.
The analysis identifies significant influences of “Dependence on technology,” “Complexity”, “Potential system failures”, and “Cyber security” while “Environmental impact” and “Socio-economic disparities” emerge as prominent risks in supply chain 5.0 digitalization. These findings offer actionable insights for management decision-making, guiding the formulation of strategies to address and mitigate critical risks.
The proposed integrated approach (AHP-DEMATEL) provides valuable insights for managers to effectively mitigate digital supply chain 5.0 risks and strategically respond to disruptions. By prioritizing risks, organizations can allocate resources efficiently and address the most critical challenges first, minimizing long-term damage to resilience. Embracing this approach enables practitioners to enhance overall supply chain resilience, guiding key management decisions for the development of sustainable and adaptive strategies.
This paper marks the first comprehensive attempt to assess supply chain 5.0 digitalization risks using decision-making methods like AHP and DEMATEL. The integrated approach contributes novel insights to the field of supply chain risk management, specifically aiding management decision-making in the face of digitalization challenges.
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