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Heightened environmental concerns have prompted businesses to align with regulatory demands, fostering a need for internal accounting tools aiding managerial decision‐making. While environmental management accounting (EMA) has become pivotal in supporting eco‐efficiency decisions within organizations, a gap persists in comprehending its genuine, proactive implementation for sustainable development in the existing literature. This study investigates why and how EMA is used for strategic decision‐making. A systematic literature review of 89 studies was conducted, and factors influencing EMA usage for strategic decision‐making were identified using the drivers–enablers–outcomes–barriers framework. Three reasons for EMA use in strategic decision‐making were identified: legitimacy, organizational efficiency, and strategic sustainable development. This study highlights the evolving use of EMA within organizations, moving from short‐term applications to recognizing its long‐term potential for strategic sustainable development. It explains the changing motives behind EMA adoption, driven by factors that encourage the use of advanced EMA tools for proactive, long‐term decision‐making in sustainable development. The integration of these tools depends on internal organizational factors like management's environmental responsibility, and proactive leadership commitment to sustainability. By exploring theoretical underpinnings and motivations of enhanced EMA usage, this research contributes to pragmatic approaches in sustainability accounting, illustrating how organizations, initially adopting EMA for legitimacy, recognize its benefits in guiding proactive, solution‐oriented managerial decisions toward strategic sustainable development. [ABSTRACT FROM AUTHOR]

Research Summary: External representations, particularly visuals, are important in strategic decision‐making. However, their pervasiveness and impact are not well understood in the strategy literature. Based on cognitive science research, we identify four cognitive functions crucial to strategic decision‐making that benefit from using external representations. We also propose a conceptual model and propositions that explain how the quality of strategic decision‐making depends on the interactions among task environment, external representations, and managers. We show that external representations influence in predictable ways the boundedly rational process of searching for new strategies. Key determinants include the manager's representational capability and the usability and malleability of the external representation. We discuss implications for users, designers, and teachers of external representations in strategy, as well as suggest avenues for future research. Managerial Summary: This research points to the pivotal role of external representations, especially visuals, in strategic decision‐making. Drawing from cognitive science, this study identifies four critical cognitive functions that benefit from these external representations—working memory, long‐term memory, pattern recognition, and knowledge transfer. Further, the study highlights that external representations significantly influence the process of strategic decision‐making in predictable ways. Finally, we show that not all external representations are alike in their ease of use and a managers' ability to operate on an external representation, referred to as representational capability, greatly affects the decision‐making quality. The implications extend to users, designers, and educators of external representations, urging attention to the design and use of external representations for improved decision outcomes. [ABSTRACT FROM AUTHOR]

This article re-estimates equations that have shown elite basketball players do better as leaders when they turn into coaches. Using comprehensive data from the NBA during the last three decades, we show that player-turned-coaches do not win statistically more matches in regular seasons while they do better in playoffs. The relatively better performance is driven by former guard players who lead to more defensive rebounds, free throws made, and points in the last moment of close matches during playoffs. In further analyses of direct channels, we show that guard-turned-coaches as a good example of expert leaders perform relatively better in strategic decision-making. For indirect channel analysis, we also provide statistical evidence that guard-turned-coaches are more creditable to both the insiders and outsiders of organizations. [ABSTRACT FROM AUTHOR]

This review explores the incorporation of complex systems theory into predictive analytics in the e-commerce sector, particularly emphasizing recent advancements in business management. By analyzing the intersection of these two domains, the review emphasizes the potential of complex systems models—including agent-based modeling and network theory—to improve the precision and efficacy of predictive analytics. It will provide a comprehensive overview of the applications of emergent predictive analytics techniques and tools, including real-time data analysis and machine learning, in inventory optimization, dynamic pricing, and personalization of customer experiences. In addition, this review will suggest future research directions to advance the discipline and address the technical, ethical, and practical challenges encountered during this integration phase. [ABSTRACT FROM AUTHOR]

Research Summary: We develop new theory on incumbent firms' strategic decision‐making and the associated emotional dynamics at platform transitions. Based on in‐depth interviews with Nokia's senior leaders about their decision to adopt the Windows platform in 2011, we suggest that highly capable platform companies' entry into the established phone industry invalidated senior leaders' long‐held core assumptions about the industry, triggering existential anxiety and stunting self‐regulation. Distinct mechanisms then influenced senior leaders' emotions toward external platform options—myopic appraisals of firm competitiveness inside a platform (vs. platform competitiveness against other platforms), appraisals of changing firm boundaries, and emotional resonance of potential partners. These emotions contributed to emotional drift, with top managers ultimately favoring the emotionally attractive option. Our theorizing extends theory on platforms, strategy, and emotion. Managerial Summary: This research provides fresh insights into how emotions play a crucial role in incumbent firms' strategic choices, especially in the context of evolving technology platforms and major industry shifts. Our research focused on Nokia's 2011 decision to adopt the Windows platform. We discovered that when new players, like platform companies, enter a market, they can unsettle longstanding beliefs, causing anxiety and decision‐making challenges among top management. Specifically, we found that executives often focus too narrowly on their firm's ability to compete within a new platform rather than the platform's overall competitiveness. Additionally, changes in company boundaries and the emotional appeal of potential partners significantly influence these decisions. Executives' analyses emotionally drift such that they start favoring the emotionally attractive options. [ABSTRACT FROM AUTHOR]

Universities play a crucial role in social, economic, and technological development. Over the last decades, higher education systems have experimented with multiple transformations due to social demands, socioeconomic paradigms, and external shakeouts. Even though teaching and research are still the core functions of universities, other activities are emerging within/beyond the universities' scope and boundaries to configure the "third mission." Despite the increasing importance of universities' third mission, little is known about the role of dynamic capabilities underpinning the configuration of the third mission across higher education systems. Using a unique longitudinal dataset that captures the German higher education landscape from 2000 to 2016, we investigate the effect of dynamic teaching/research capabilities for achieving the third university mission (knowledge transfer and technology commercialization). Our results reveal tensions between complementary and substitution effects when pursuing universities' three missions (teaching, research, and knowledge transfer and technology commercialization), requiring university managers' and policymakers' strategic decisions. We provide implications for university managers and the university community as well as policymakers during the re-configuration process of becoming more entrepreneurial and innovative, highlighting the relevance of effectively managing universities' dynamic capabilities. Plain English Summary: Universities have undergone significant transformations in recent decades, responding to societal demands, economic shifts, and external pressures. The third mission of universities thereby serves as a driving force and encompasses endeavors that go beyond traditional academic functions, such as knowledge transfer and technology commercialization. Despite its increasing importance, little is known about the underlying mechanisms that lead to third mission outcomes. To shed light on this crucial topic, this paper delves into the impact of dynamic teaching and research capabilities on achieving the third mission's goals. Our findings reveal goal conflicts that universities face in balancing their three missions, requiring university managers and policymakers to make strategic decisions to navigate these tensions effectively. As universities aim to become more entrepreneurial and innovative, effectively managing dynamic capabilities and making strategic decisions becomes paramount during reconfiguration processes, enabling universities to unlock their full potential for economic, technological, and societal impacts. [ABSTRACT FROM AUTHOR]

Competitive advantage is one of the essential components of customer satisfaction and business growth, but the COVID-19 pandemic has had a substantial influence on consumer behavior, while also giving rise to intense competition within the business environment in Africa, making competitive advantage and customer experience a challenge. Consequently, firms have been compelled to make strategic choices such as differentiation capability to navigate these challenges. The study therefore examines the effect of differentiation capability on the customer experience of selected consumer goods companies listed in Nigeria the biggest economy in Africa. The research adopted a cross-sectional survey method, and a total of 20 consumer products firms were identified and evaluated based on their capitalization criteria and continuous dividend payments. From this group, seven companies were chosen for further analysis. The sample size of 378 was determined using the Research Advisor Table, with a confidence level of 95% and a margin error of 5%. To address the issue of non-response, appropriate measures were taken, leading to the inclusion of an additional 113 respondents, representing 30% of the original sample. This adjustment resulted in a final sample size of 491. A total of 491 questionnaires were sent to the respondents, resulting in a response rate of 97.76%. The hypothesis was examined by regression analysis. The results of the study indicate that differentiation capability is an effective tool that is statistically significant and positive to customer experience (ß =0.842, t = 29.782, p<0.05); The research findings indicate that applying differentiation capability in a firm helps attain a stronger competitive position and has a favorable impact on customer experience. This research, therefore recommends that there is a need for technology adoption to cut production costs and establish a durable competitive advantage. [ABSTRACT FROM AUTHOR]

Local authorities have a strategic role in mitigating the environmental impacts of the transport sector. However, they struggle to integrate environmental issues into their decision-making processes, especially planning. In the European context of the Sustainable Urban Mobility Plan approach and Strategic Environmental Assessments (SEAs), this paper scrutinises three French localities to determine the current best practices and limitations for designing mobility plans and integrating environmental issues. Several limitations are identified: (1) limited expertise in defining and characterising actions and objectives, which complexifies plans' design, understanding, and monitoring; (2) a lack of a framework to conduct long-term quantitative environmental assessments and to use the results to influence decision effectively; and (3) monitoring processes are barely described in the documents, and the planning horizon where objectives are defined is not in sync with the indicators' mandatory evaluation period. This French case study thus reveals that European planning practices must be further analysed and improved to deal with the rising environmental concerns, e.g. through an operational framework to design mobility plans with effective integration of environmental issues. • Planning supports local authorities in moving towards a more sustainable mobility. • There is no robust approach to defining and characterising actions and objectives. • Robust long-term quantitative assessments are lacking to support planning. • Monitoring modalities are scarcely described in plans and SEAs. • Improving planning frameworks would help the integration of environmental issues. [ABSTRACT FROM AUTHOR]

This article aims to comprehensively analyze the crucial role played by data analytics and business intelligence (BI) strategies in propelling digital transformation within diverse industries. Through an extensive literature review and examination of real-world case studies, the study employs a systematic analysis of scholarly works and industry reports. This approach provides a panoramic view of how organizations utilize data-driven insights for competitive advantages, improved customer experiences, and fostering innovation. The findings underscore the pivotal significance of data analytics and BI strategies in influencing strategic decision-making, enhancing operational efficiency, and ensuring long-term sustainability across various industries. The study stands out in its originality by offering a unique synthesis of insights derived from scholarly works and real-world case studies, contributing to a holistic understanding of the transformative impact of data analytics and BI on contemporary business practices. While the study provides valuable insights, limitations include the scope of available literature and case studies. The implications call for further research to explore emerging trends and evolving challenges in the dynamic landscape of data analytics and BI. The practical implications highlight the tangible benefits organizations can derive from integrating data analytics and BI strategies, emphasizing their role in shaping strategic decisions and fostering operational efficiency. In a broader context, the study delves into the social implications of the symbiotic relationship between data analytics, BI, and digital transformation. It explores how these strategies impact broader societal and economic aspects, influencing innovation and sustainability. [ABSTRACT FROM AUTHOR]

How can strategic decision-making be reinforced through reliable forecasts of technological change? Observations of strategic forecasts have shown that they mainly rely upon expert opinions. To turn these opinions into consistent knowledge about the future, we need to manage cognitive biases using provable models. Observed forecasting methods provide useful tools for exploiting expert knowledge and data, but management of cognitive bias remains underdeveloped. To improve the situation with cognitive biases in technology forecasting, the Researching Future method (RFm) offers a mixed methods approach. This article introduces RFm, a method that combines a problem-based approach and a logistic function, unified by an applied resources paradigm. A practical case study is described to illustrate and validate RFm, and the results, limitations, and perspectives of RFm are then examined. The article contributes to the technology forecasting methodology and is of interest to copper mining technology R&D specialists, among others. [ABSTRACT FROM AUTHOR]

This study explores the intricate relationships between bank value, tax avoidance, and profitability, which significantly affect the stability and strategies of financial institutions worldwide. Understanding these connections is vital for comprehending the financial dynamics of banks, key players in economic growth and stability. The study focuses on these three factors due to their intertwined roles in shaping fiscal policy effectiveness, shareholder satisfaction, and overall financial health. The aim of this study is to explore the relationships between the bank value, tax avoidance and profitability aiming to clarify their interactions and their impact on the Jrdanian banks. Ordinary Least Squares regression analysis is employed using a mixed-methods approach, including quantitative regression analysis and qualitative assessments. The study results reveal a significant direct link between bank tax avoidance and profitability. The increase in Return on Assets is associated with a substantial increase in tax avoidance. In the expanded model, bank value and size did not exhibit statistically significant incremental information over profitability in explaining tax avoidance. Profitability emerges as a dominant factor, overshadowing the potential impact of size and value. The results underscore profitability as a key driver in bank tax strategies, highlighting a potential area for regulatory scrutiny and strategic realignment. In conclusion, the study underscores the pivotal influence of bank profitability on tax avoidance strategies. Policymakers, practitioners, and researchers are encouraged to recognize the prominence of profitability in formulating tax strategies.

Research Summary: To thrive in an unpredictable world, managers must adapt their decision‐making to changing events. However, a major impediment to adaptation is strategic persistence, that is, the tendency to stick with previously successful strategies. We examined whether multiple scenario analysis can help to overcome the dysfunctional effects of strategic persistence. In a laboratory study using a multi‐round strategy simulation that required players to change strategies to succeed, we found that multiple scenario analysis alleviated the effects of strategic persistence by stimulating strategic reorientation, that is, adaptive shifts in patterns of strategic choice. Multiple scenario analysis influenced strategic reorientation indirectly, by fostering belief in a new strategy, and its effectiveness depended on prior performance. We discuss implications for research on the cognitive microfoundations of strategic adaptation. Managerial Summary: What can managers do when their previously successful strategy stops working? We found that using multiple scenario analysis, a common strategic planning technique can help decision makers switch to a new strategy. In our study, using a business simulation game that required players to change strategies to succeed, we found that those players who imagined different industry futures as part of a multiple scenario analysis exercise were more likely to believe in new strategies and as a result more likely to switch to the winning strategy. However, this intervention was less effective for players who had high levels of success with the old strategy. We discuss how scenario‐based intervention techniques can be used to assist managers with reorientating to a new strategy. [ABSTRACT FROM AUTHOR]

The advent of Artificial Intelligence (AI) and Machine Learning (ML) has significantly transformed strategic decision-making processes within business operations. This paper explores the profound impact of these technologies on optimizing operational efficiency, enhancing decision accuracy, and fostering innovation. AI and ML enable organizations to process vast amounts of data, derive actionable insights, and predict trends with unparalleled precision. These capabilities have redefined traditional business models by offering data-driven strategies that are adaptive and responsive to dynamic market demands. The paper delves into various applications of AI and ML in strategic operations, including predictive analytics, automated processes, and intelligent decision support systems. Key advancements, such as natural language processing, deep learning, and reinforcement learning, have contributed to refining decision-making frameworks, ensuring scalability, and mitigating human biases. By integrating AI and ML, businesses can achieve enhanced agility, improved customer experiences, and a competitive edge in a rapidly evolving global economy. Furthermore, this paper critically examines the challenges associated with adopting AI and ML, such as data privacy concerns, algorithmic biases, and the ethical implications of autonomous decision-making systems. It also highlights the importance of fostering a culture of continuous learning and collaboration to leverage these technologies effectively. The study underscores the need for robust governance frameworks and regulatory standards to address the ethical and operational risks posed by AI and ML. By synthesizing insights from recent research and industry practices, this paper provides a comprehensive understanding of how AI and ML are shaping the future of strategic business operations, paving the way for sustainable and informed decision-making practices. [ABSTRACT FROM AUTHOR]

This study explores sensitivity analysis within the realm of decision-making in Operations Research, focusing on integrated mathematical models. The investigation centers on a critical variable--supplier lead time--using a case study to comprehend its impact on both operational efficiency and the overall costs of a manufacturing company. To optimize inventory levels, production costs, and total operational costs, an integrated mathematical model is devised, taking into account variations in supplier lead times. Sensitivity experiments are performed by manipulating supplier lead times, and the ensuing outcomes are scrutinized to offer comprehensive insights. The findings reveal that substantial alterations in supplier lead time can significantly affect operational performance and strategic decision-making. In response to lead time changes, adaptive strategies, such as implementing tighter contracts and exploring alternative suppliers, are suggested. This research enhances our understanding of how sensitivity analysis serves as a valuable tool for enhancing operational resilience and making informed decisions amidst uncertainties in supply chains. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this article is to understand the basics of strategic decisionmaking methodology based on the methodological implications of the Holy Quran and with the example of Surah Anfal. Method: This article is based on the combined mechanism of two methods of denotation research as well as the logic of denotation in the literature of fundamental science. In this regard,, theme analysis and content analysis were used in Atlas for data analysis. ti software, and some implications based on the fundamentals of strategic decision-making methodology were understood and explained. Findings: The result of this methodical process was the extraction of 120 primary codes,16 basic themes 120 primary codes,16 basic themes, and four organizing themes, which were formed under the Qur'an-based strategic decision-making methodology. Conclusion: Finally, the methodological implications of strategic decision-making are organized under the four general headings of strategic decision-making methodology system, effective components in the processing of strategic decisionmaking methods, location of evidence for strategic decision-making processing, quality and goodness of explanation. [ABSTRACT FROM AUTHOR]

Healthcare call centers serve an important role in the healthcare system to support patients' access to care and satisfaction and optimize medical resource allocation. Limited research has provided sufficient evidence on how to increase healthcare call center's efficiency from managerial aspects. In this study, a simulation model is built based on real-life healthcare call center settings and call information, to identify the opportunities for improvement. This call center processes approximately 2638 calls for 25 clinic sites every day. The call abandon rate was at 16.7%, which was far from the organization's goal of 5%. Some improvement opportunities based on managerial interests such as cross-coverage, non-scheduling call transition, staff availability and staff allocation without increasing staff numbers, are identified and their operational impacts are evaluated by the simulation model. Moreover, a genetic algorithm is used to find the optimal shift for staff allocation. The simulation results demonstrate the validity of the proposed model, provide valuable insights for decision-making before the implementation and provide other healthcare call centers' alternatives to improve performance. The recommendations were communicated to call center staff and consentaneous opportunities were implemented. The results showed a significant reduction of 39.5% in the call abandon rate. [ABSTRACT FROM AUTHOR]

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This systematic review examines the influence of emotions on strategic decision-making in business context, from the perspective of behavioral strategy. We examined 1,227 articles from two databases (Web of Science and PsycInfo), and after applying the inclusion and exclusion criteria, the final sample resulted in 43 articles. Our systematic review focuses on the role of emotions in strategic decision-making as well as the decision-making process itself. This systematic review explores research using a variety of approaches and a combination of theoretical and empirical perspectives brought by the literature. It aims to address three main questions: how board members’ emotions influence their decision-making; what insights behavioral strategy provides on the emotional aspect of strategic decision-making; and what are the main theories linking emotions to strategic decision-making in the business context. The results demonstrate how emotions can affect the quality of decisions and imply that conflict resolution and emotional intelligence are relevant skills for making strategic decisions. This analysis supports the need for incorporating emotional insights into strategic planning methods by considering agreeable and divergent points of view.

This article explores the different forms of intelligence in relation to expanding organizational design and enhancing development, and how it entertains the notions of growth and success. Furthermore, it embraces how the amalgamation of the different forms of intelligence contributes to the relevancy and longevity of the organization. Thereafter, leadership is discussed as crucial for organizational success that reflects engagement of decision intelligence, business intelligence, and competitive intelligence as key pillars of strategic decision-making. These concepts are taken to enable leaders in understanding complex problems that lead to developing innovative and creative solutions. The proposition here is transformative intelligence that is taken to combine these three concepts of intelligence that potentially would revolutionize organizational leadership and consequent decision-making. Simultaneously, the five pillars of leadership, or the 5Qs (Cognitive Intelligence, Digital Emotional Intelligence, Moral Intelligence, Innovation Intelligence, and Spiritual Intelligence), also contribute to strategic decision-making, enabling organizations to achieve desired transformation. This spectrum of reviewing intelligence as a combination concept benefits organization through streamlined decision-making, customer-centricity, anticipating disruptive forces, improved innovation, and better organizational culture. This article examines the scopes and potential drawbacks of each type of intelligence and showcases how adopting a business model which utilizes and combines the aforementioned types of intelligence ultimately creates a stronger and more resilient organization. [ABSTRACT FROM AUTHOR]

Upon the implementation of the European Union Carbon Border Adjustment Mechanism (CBAM), substantial challenges are anticipated to impact the international trade of Chinese steel products. To safeguard the competitiveness of Chinese steel products on the global stage, this paper establishes a tripartite evolutionary game model, involving large steel enterprises, small- and medium-sized steel enterprises, and the government. The model integrates collaborative emission reduction and free-riding benefits among enterprises, along with the government's dynamic subsidies and penalties. First, we calculate the replicator dynamic equations and conduct stability analysis to obtain the evolutionary trends and system equilibrium points in different phases of the CBAM. Then, we validate the evolutionary theoretical analysis of the model through example simulation analysis. Finally, we explore the impact of different parameters on the agents through a sensitivity analysis of parameters. The findings indicate that (1) large enterprises demonstrate greater sensitivity to CBAM, making their production structures more susceptible to changes in CBAM policies; (2) small- and medium-sized enterprises are more prone to free-riding behavior influence; (3) government intervention should be kept within appropriate boundaries, as excessive intervention may lead to strategic oscillation, with passive management being chosen by the government during the strengthening phase of CBAM; (4) elevating the price in the Chinese carbon market would slow down the structural changes in the production of Chinese steel enterprises, serving as an effective measure to counteract the impacts of CBAM. This paper provides theoretical support for how steel enterprises and the government can respond to CBAM, aiding stakeholders in selecting optimal strategies during different implementation stages and mitigating the impacts of the CBAM to the maximum extent possible. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) and machine learning (ML) are rapidly evolving and have already had major impacts on military capabilities in the battlefield, making new kinds of tools and tactics available. A less examined area of application for AI in a military context, however, is its impact on human strategic decision making. This article focuses on the more subtle cognitive influences of AI and how they can be strategically deployed to aid decision making around the state-level resort to force, in particular. I will argue that AI-driven technologies can be used to improve certain critical cognitive resources (e.g. memory, planning, mind-modelling, etc.) of decision makers, thereby providing valuable strategic advantages to those actors who use them successfully. At the same time, I will also caution against the risks of human decision makers becoming overly reliant on AI-support systems. Both the potential advantages and risks are areas that demand further study and consideration. [ABSTRACT FROM AUTHOR]

Although digitalization has become a prospect that is counted on for many problems in the construction industry, there have been limited attempts at exploring decision-making processes in construction firms concerning the integration of digital technologies and impacts beyond the projects. In this research, the system dynamics (SD) approach was proposed to investigate digitalization as a strategic decision considering the inherent relationships between project company and business levels. The SD model was conceptualized, formulated, and tested by conducting a demonstrative case study within a modular construction company. Conforming to the strategic priorities of the case company, business process engineering principles were adopted to model the existing practices and assess the impacts of implementing digital technologies such as building information modeling (BIM), enterprise resource planning (ERP), and radio frequency identification (RFID) at different maturity levels. The simulation tests revealed that the impacts of technologies are influenced by the internal dynamics of projects and company competencies as well as external uncertainties. The SD model has the potential to improve strategic decision-making by anticipating the causalities and feedback between the decisions and consequences of technology integration. The findings and model development steps proposed in this paper can be used by other companies that aim to make process improvements with digital technologies as well as researchers exploring the implications of digitalization in construction considering competencies and uncertainties. [ABSTRACT FROM AUTHOR]

This empirical qualitative study explores the role of gaming simulations in catalyzing changes to organization-wide management's perspectives on a novel strategy for aircraft orders and retirements. A large US airline developed the new strategy to tackle the pervasive problem of profit cyclicality, driving poor average profit performance across the cycle. Based on the dynamic model used to develop the strategy with senior management, a gaming simulation workshop was designed and delivered in groups of 20 to over 200 organization-wide managers. They tested various strategies for aircraft orders and retirements, under scenarios for market demand and conduct for competitors and regulators. A qualitative methodology was used to capture the workshop participants' perspectives on the efficacy of various capacity strategies, before, during and after the workshop. The findings are that managers experiment risk-free with innovations in strategies for capacity orders and retirements and they do indeed discover for themselves that there are counterintuitive alternatives that can achieve large and stable profitable growth. These strategies depend on competitors (role-played by workshops participants in the simulation) cooperating to create a win-win equilibrium. Performance far exceeds the industry benchmark profit cycle. The contribution is the empirical evidence of the effectiveness of gaming simulations to catalyze managers' shared beliefs and buy-in to a new strategy or business model. There are implications for practitioners in airlines and other sectors on the use of a gaming simulation workshop toolset, to help create such buy-in for an emerging strategy or business model. Protocols for best practice gaming simulation workshop design are discussed. [ABSTRACT FROM AUTHOR]

As the types of application services available for mobile smart devices increase, the variability and irregularity of their battery run time also increases. It is difficult to expect good prediction accuracy when general regression methods exploiting the regularity of past battery run time data are applied to predict the battery run time. Therefore, various prediction strategies are needed according to the dynamic execution situations of mobile smart devices. A novel decision-making process is also required to learn and select a strategy suitable for the dynamic situation. In this paper, we propose a reinforcement learning based prediction framework that maximizes the reward for the action of selecting a prediction strategy appropriate for the situation while valuing all strategies with their rewards and carrying out the prediction strategy with the highest value for the next prediction action. The numerical results obtained by experimenting the proposed framework confirmed that it generated good performance of estimating battery run time. [ABSTRACT FROM AUTHOR]

This paper introduces an automated decision-making framework for providing controlled agent behavior in systems dealing with human behavior-change. Controlled behavior in such settings is important in order to reduce unexpected side-effects of a system’s actions. The general structure of the framework is based on a psychological theory, the Theory of Planned Behavior (TPB), capturing causes to human motivational states, which enables reasoning about dynamics of human motivation. The framework consists of two main components: 1) an ontological knowledge-base that models an individual’s behavioral challenges to infer motivation states and 2) a transition system that, in a given motivation state, decides on motivational support, resulting in transitions between motivational states. The system generates plans (sequences of actions) for an agent to facilitate behavior change. A particular use-case is modeled regarding children with Autism Spectrum Conditions (ASC) who commonly experience difficulties in everyday social situations. An evaluation of a proof-of-concept prototype is performed that presents consistencies between ASC experts’ suggestions and plans generated by the system. [ABSTRACT FROM AUTHOR]

The long-term prosperity of a business depends heavily on innovation. Although many businesses have in-house R&D departments, the contribution of non-executive technical directors to innovation is often disregarded. The purpose of this study is to understand better the contribution of non-executive technical directors to corporate innovation. Semi-structured interviews with non-executive technical directors of different organizations were employed as a qualitative study strategy to collect data. The data was analyzed using a thematic approach to isolate common threads. According to the report, non-executive technical directors encourage creativity and new business ideas. The insights and technical knowledge they bring to the boardroom support the company's innovation strategy. Non-executive technical directors also serve as a link between the company's technical personnel and the board, ensuring that innovation projects are in line with the company's overall strategy. A company's innovation ecosystem must include non-executive technical directors. Their capacity to bridge the gap between the technical and business sides of the organization, as well as their technical experience and strategic thinking, make them invaluable to the company's innovation initiatives. Businesses that place a high priority on the position of non-executive technical directors in their strategic plan are more likely to have long-term success and development. [ABSTRACT FROM AUTHOR]

Research has so far made a rather limited advancement in identifying the contribution of the aspects of the working environment that matter to teachers' overall job satisfaction (TJS), as well as in providing evidence-based guidelines for improving their working experience. Addressing these deficiencies, the current work uses data related to school working environment facets, i.e., opportunities for self-fulfillment, work intensity/load, salary/income, leadership and collegial relations, and overall TJS, from a sample of 438 public primary school teachers in Greece and applies a multi-criteria decision analysis method (the multi-criteria satisfaction analysis (MUSA)) to identify the contribution of these facets to overall TJS, underline the strong and weak points of TJS based on their importance for teachers and the school's performance on them, and provide direct action implications for improving primary TJS. The results reveal that all the examined facets are crucial for TJS. Yet, self-fulfillment is the most important contributor to overall TJS and work intensity/load the least significant one. Also, self-fulfillment is the strongest point of TJS that school leaders and policymakers should continue investing on, whilst salary/income is a risk factor that could easily turn into a threat for TJS into the future. [ABSTRACT FROM AUTHOR]

This qualitative study explores the decision-making processes of deans in teacher education in the Philippines and investigates the challenges they encounter. The research employs a descriptive qualitative approach grounded in the interpretive paradigm, focusing on the experiences and perspectives of current and former deans. Data were collected through interviews, focus group discussions, and reflective essays, with thematic analysis used for data interpretation. Findings reveal key issues necessitating strategic decisions, including performance in licensure exams, introduction of new programs, accreditation demands, inherent functions, and faculty development programs. The identified key issues impact institutional quality, accreditation, and faculty competence. This study underscores the significance of strategic decision-making in teacher education leadership and administration, offering insights for educational policymakers, administrators, and stakeholders. By shedding light on these aspects, this study contributes to continuous improvement in teacher education and the broader educational landscape, aligning with evolving societal needs.

Abstract Partner choice promotes competition among individuals to be selected as a cooperative partner, a phenomenon referred to as competitive altruism. We explored whether chimpanzees engage in competitive altruism in a triadic Ultimatum Game where two proposers can send offers simultaneously or consecutively to a responder who can only accept one of the two competing offers. In a dyadic control condition only one proposer at a time could send an offer to the responder. Chimpanzees increased their offers across trials in the competitive triadic, but not in the dyadic control condition. Chimpanzees also increased their offers after being rejected in previous triadic trials. Furthermore, we found that chimpanzees, under specific conditions, outcompete first proposers in triadic consecutive trials before the responder could choose which offer to accept by offering more than what is expected if they acted randomly or simply offered the smallest possible amount. These results suggest that competitive altruism in chimpanzees did not emerge just as a by-product of them trying to increase over previous losses. Chimpanzees might consider how others’ interactions affect their outcomes and engage in strategies to maximize their chances of being selected as cooperative partners.

This article addresses the problem of interrelations between economic factors and military conflicts, examining the role of econometric forecasting in the context of academic management during periods of uncertainty surrounding hostilities. It delves into the two principal theories of classical macroeconomics – neutrality and dichotomy – and explores their applicability to the complex interplay between economic forces and military dynamics. In doing so, it challenges the conventional binary view of conflicts as either war or peace, emphasizing the nuanced gradations that emerge over time. The study highlights the significance of economic advantages in shaping decisions related to military conflicts and underscores the role of econometric forecasting as a critical factor in academic institutions navigating the indirect repercussions of hostilities. The article also presents a comprehensive examination of strategic interactions, introducing distinctions between moves, rounds, and plays in conflict scenarios. Drawing on recent research and publications, the article underscores the importance of understanding the economic principles governing the preservation of peace and forecasting the consequences of such decisions. It references seminal work by economists P. Romer, R. Lucas, R. Barro, I. Salla y Martin, and R. Levine, who laid the foundation for the study of endogenous economic development. The theories of trade and military conflict are two distinct branches in economic analysis and prediction. Trade theory is founded on contractual agreements and mutual benefits, while the military conflict theory centers on competition for dominance. It's important to recognize that various analytical methods exist for modeling equilibrium in such situations, whether they involve active hostilities or the coexistence of armed forces during economic stagnation due to anticipated conflicts. It becomes evident that the decision to initiate or de-escalate a military conflict is primarily driven by economic advantages, even in the domain of academic management. In this context, econometric forecasting techniques play a role in the economic activities of academic institutions, which may experience direct or indirect consequences of hostilities. This is because various sectors must compete for their survival amidst these dynamics. Purpose. The study's objectives include assessing the impact of military budgeting productivity on economic growth using economic and mathematical modeling techniques, with a focus on countries facing uncertainties related to hostilities, evolving budget and tax regulations, and inflation. The article adapts the models of J. Battis and T. Koeli to facilitate this analysis. Methods Macroeconomic Analyses, Economentric Analyses, Trend Analyses Results. Determining the optimal level of taxation to obtain the necessary income for the budgets of academic institutions in conditions of uncertainty in the conduct of hostilities. In conclusion, the study challenges classical economic doctrines by establishing a strong connection between military budget allocation and the real sectors of the economy. It underscores that a nation's economic growth is contingent upon the productivity and effectiveness of its military budgeting, even in a globalized world economic system. This study opens the door to further research in this interdisciplinary field. Keywords: Econometric forecasting, Academic management, Uncertainty, Hostilities, Economic modeling, Endogenous economic development, Academic institutions, Budgeting, Military conflicts, Financial impact, Economic growth, Strategic decision-making, Budget optimization, Risk assessment, Financial efficiency. Methods Macroeconomic Analyses, Economentric Analyses, Trend Analyses fig .: ; tab .: ; bibl .: 9.

This review explores the incorporation of complex systems theory into predictive analytics in the e-commerce sector, particularly emphasizing recent advancements in business management. By analyzing the intersection of these two domains, the review emphasizes the potential of complex systems models—including agent-based modeling and network theory—to improve the precision and efficacy of predictive analytics. It will provide a comprehensive overview of the applications of emergent predictive analytics techniques and tools, including real-time data analysis and machine learning, in inventory optimization, dynamic pricing, and personalization of customer experiences. In addition, this review will suggest future research directions to advance the discipline and address the technical, ethical, and practical challenges encountered during this integration phase.

Partner choice promotes competition among individuals to be selected as a cooperative partner, a phenomenon referred to as competitive altruism. We explored whether chimpanzees engage in competitive altruism in a triadic Ultimatum Game where two proposers can send offers simultaneously or consecutively to a responder who can only accept one of the two competing offers. In a dyadic control condition only one proposer at a time could send an offer to the responder. Chimpanzees increased their offers across trials in the competitive triadic, but not in the dyadic control condition. Chimpanzees also increased their offers after being rejected in previous triadic trials. Furthermore, we found that chimpanzees, under specific conditions, outcompete first proposers in triadic consecutive trials before the responder could choose which offer to accept by offering more than what is expected if they acted randomly or simply offered the smallest possible amount. These results suggest that competitive altruism in chimpanzees did not emerge just as a by-product of them trying to increase over previous losses. Chimpanzees might consider how others' interactions affect their outcomes and engage in strategies to maximize their chances of being selected as cooperative partners. [ABSTRACT FROM AUTHOR]

This study investigates the relation among leadership style adoption; strategic decision-making and business performance from the generational ownership perspective of family business. Prior studies have attempted to establish the relation of leadership style adoption through firm's working environment, with sparse literature on generational ownership. How does the generational shift impact performance? Is there a transition in leadership style? These need to be collated through strategic decision-making to understand their impact on business performance. The research employs a survey-based technique with data from owners of 100 large and medium family business firms. PLS-SEM is applied to analyse the relation of leadership style (considering organizational and attitudinal factors) through strategic decision-making on business performance. Two models were created, one from data collected from first generation owners and second from second generational owners. The results highlight that there is a shift in leadership style i.e., from Autocratic to Transformational style with the change in management control in the first and second generation. The outcomes indicate that autocratic leadership style and strategic decision-making explained 58.7 percent of business performance in the first generation and transformational leadership style predominated in second generation and this model explained 75.7 percent of variation in business performance. Since results imply that transformational leadership style dominated in second generation, a shift towards this style is preferable.The findings will act as a guideline for the new generations to accept how adopting a transformational leadership style through strategic decision-making may help improve family businesses performance. [ABSTRACT FROM AUTHOR]

This study formulates a mathematical dynamic Computable General Equilibrium (CGE) model within a rational expectations framework, adhering to neo-classical principles. It emphasizes the significant role of agents' expectations in determining the broader economic trajectory over time. The model combines microeconomic and macroeconomic perspectives by merging the concept of intertemporal choice with savings behavior. Its mathematical foundations are derived and calibrated using data from a social accounting matrix to enhance its simulation capabilities. The paper presents a practical simulation investigating the economic implications of a strategic investment impact within an specific European region, Madrid as the case of study. Such demand shock affects sectors such as electronics, food, pharmaceuticals, and education. The study models the long-term effects of heightened investment and persistent demand-side shocks. The research demonstrates the CGE model's ability to forecast economic shifts toward a new equilibrium after an investment shock, proving its utility for assessing the impacts of extensive environmental policies within a European context. The work's originality lies in its detailed mathematical formulation, contributing to theoretical discourse and practical application in business analytics. [ABSTRACT FROM AUTHOR]

This review article examines artificial intelligence (AI)’s role in strategic marketing decision-making. The researchers interviewed experts with experience in decision-making and used Carrefour Iraq as a case study to identify themes on how humans use AI for better strategic marketing decision-making. The key themes in this review were factors such as big data, efficiency, quality, trust, and limitations for prediction. The study has also looked into the marketing aspect of these themes within the scope of this research. The findings indicate that AI is recognized as a tool that may support humans in making strategic decisions in marketing. However, AI can technically make such decisions without human intervention; people do not want to give AI-complete autonomy in decision-making. Furthermore, the result implies that rather than making decisions independently, AI is more frequently applied to enhance strategic decision-making. It suggests that Al aims to improve decision-making rather than supplant people in daily life. In addition, the study makes the case that Al can assist humans in making better decisions by forecasting future scenarios that consider a particular action consequence. [ABSTRACT FROM AUTHOR]

Strategic problem‐solving enables organizations to pursue opportunities and address emerging threats proactively. However, traditional problem‐solving methods often rely on business processes and organizational procedures, which may not be available at the strategic level. This article investigates potential gaps in strategic problem‐solving methods through a Systematic Literature Review. The study analyses the existing literature on the potential of current problem‐solving methods to identify and resolve root causes of strategic problems when formal business processes and procedures are unavailable. A rigorous literature search process guided by focused research questions examines Problem Structuring Methods, Lean Thinking, Six Sigma, Theory of Constraints, Balanced Scorecard, SWOT Analysis, and other techniques. The synthesis of findings reveals limitations in strategic root cause analysis. In addition, the study introduces a supplementary decision‐making frame of reference to aid the selection of appropriate methods across problem‐solving, decision‐making, and solution implementation stages. This framework addresses the common challenges decision‐makers face in navigating organizational complexity and choosing suitable approaches, as well as visually maps methods to stages based on Content, Organizational, and Analytical complexity dimensions. The framework builds on the study's findings that using a single methodology may be insufficient for a complete decision process. The proposed decision‐making framework also offers valuable guidance for integrating diverse methods aligned to decision situations. [ABSTRACT FROM AUTHOR]