Cross-functional Collaboration Research Articles

Adopting agile in government: a comparative case study

ABSTRACT This study examines the adoption of agile in public administrations through the lens of Scandinavian institutionalism and translation theory. By conducting interviews in 19 German public administrations, we investigate how agile is translated into public settings and how they address associated challenges. Our findings reveal three translation modes: agile stripped down to a cultural concept, agile as governance to foster cross-functional collaboration, and agile as methodology, adhering closely to its original values and principles. As such, our study contributes to a better understanding of and theoretical advancements surrounding agile in government.

The Role of Product Management and Market Research Analysis for Business Development in Selected Pharmaceutical Companies

This research paper delves into the pivotal role of product management and market research analysis in the context of pharmaceutical companies. It explores how these strategic tools contribute to business development amidst the intricate landscape of the pharmaceutical industry, characterized by rapid scientific advancements, evolving market dynamics, and stringent regulatory requirements. The paper emphasizes the evolution of product management within the pharmaceutical sector, highlighting its transition from a focus on research and development to encompassing comprehensive lifecycle management and commercialization strategies. Through a review of literature and data analysis, the paper examines various facets such as patient-centric innovation, regulatory compliance, digital transformation, competitive landscape analysis, and cross-functional collaboration. The study aims to shed light on the significance of integrating product management and market research analysis for driving sustainable business growth, enhancing competitiveness, and delivering impactful healthcare solutions in pharmaceutical companies.

Enhancing manufacturing productivity: A review of AI-Driven supply chain management optimization and ERP systems integration

This abstract delves into the realm of manufacturing productivity enhancement through the review of AI-driven supply chain management (SCM) optimization and Enterprise Resource Planning (ERP) systems integration. As industries strive for operational excellence, the convergence of artificial intelligence (AI) and supply chain management emerges as a transformative force in driving efficiency, agility, and competitiveness. Through a comprehensive analysis, this abstract examines the synergistic relationship between AI-driven SCM optimization and the integration of ERP systems, elucidating their collective impact on manufacturing productivity. AI-driven SCM optimization encompasses a spectrum of technologies and methodologies, including predictive analytics, machine learning, and autonomous decision-making systems, aimed at optimizing various facets of the supply chain, from demand forecasting and inventory management to production planning and logistics optimization. By harnessing the power of AI, manufacturers can enhance forecasting accuracy, reduce lead times, optimize inventory levels, and mitigate supply chain disruptions, thereby improving overall productivity and customer satisfaction. Integration of ERP systems plays a complementary role in manufacturing productivity enhancement by providing a centralized platform for data management, process automation, and cross-functional collaboration. Through seamless integration with AI-driven SCM optimization tools, ERP systems enable real-time data exchange, actionable insights, and end-to-end visibility across the supply chain, facilitating informed decision-making and agile response to dynamic market conditions. Drawing insights from case studies and industry examples, this abstract highlights best practices, challenges, and emerging trends in AI-driven SCM optimization and ERP systems integration. Strategies for successful implementation, including organizational readiness assessment, change management, and stakeholder engagement, are discussed to guide manufacturers in unlocking the full potential of these transformative technologies. In conclusion, the convergence of AI-driven SCM optimization and ERP systems integration offers a compelling pathway for enhancing manufacturing productivity, driving operational excellence, and sustaining competitive advantage in the digital era.. Keywords: Artificial Intelligence, Supply Chain Management, Enterprise Resource Planning, Manufacturing Productivity, AI Integration, Predictive Analytics.

Understanding the Nexus: Business Intelligence and its Impact on Customer Experience Across Diverse Work Sectors

In the 21st-century hyper-competitive business landscape, comprehending and improving customer experience (CX) is highly quintessential for sustainable success across diverse industry sectors. Customers today hold more options in pursuing a luxurious lifestyle compared to their predecessors, yet their expectations continue to be on a constant surge. To meet these rising expectations, today's organisations strongly emphasize incorporating the best industry practices to ensure a high-end customer experience [1]. One such practice that has been included in recent times is integrating business intelligence and analytics. By leveraging advanced analytics tools and techniques, businesses can extract valuable insights from vast datasets, enabling informed decision-making and proactive strategies [2]. Business intelligence and analytics play a vital role in this practice by providing real-time data analysis, predictive modelling, and actionable recommendations, empowering organizations to optimize operations, enhance customer experiences, and stay ahead in today's dynamic marketplace [3]. The following paper aims to explore the vital role Business Intelligence (BI) plays in enhancing customer experience across various sectors. By applying a comprehensive review and analysis methodology, the study will seek to investigate how BI tools, strategies, and analytics influence user experience metrics, organizational performance, and competitive advantage in disparate sectors. Moreover, it further aims to determine the significance of leveraging data-driven insights garnered through business intelligence processes to comprehend customer behaviours, preferences, and sentiments across diverse sectors, ranging from retail and hospitality to finance and healthcare. The paper will bolster the aforementioned analysis by synthesising empirical case analysis, diving into the multifaceted impacts of Business Intelligence and Analytics on Customer Experience. Furthermore, the paper aims to examine the role of BI in optimizing operational efficiencies, streamlining processes, and fostering innovation to meet evolving customer expectations and market demands. Alongside this, it will dive deeper into issues such as data privacy concerns, and underscore the importance of organizational culture, leadership support, and cross-functional collaboration in fostering a BI-driven CX-centric mindset within diverse work environments. Through empirical evidence and industry case studies, the paper will seek to demonstrate how Business Intelligence adoption correlates with improved customer satisfaction scores and profitability metrics across diverse sectors. Towards the end, the paper will present a concluding argument by highlighting key insights, implications, and the imperative of investing in robust data infrastructure, analytics capabilities, and talent development initiatives to unlock the full transformative power of Business Intelligence in driving superior customer experiences. It will eventually underscore the need for continuous evaluation, adaptation, and innovation in Business Intelligence strategies to stay abreast of evolving customer preferences, technological advancements, and competitive dynamics. By illuminating the transformative impact of Business Intelligence on Customer Experience metrics, organizational performance, and competitive advantage, the study aims to provide valuable insights and guidelines for leveraging data-driven strategies to drive customer-centric innovation and sustainable growth in an increasingly dynamic business landscape.

LEVERAGING WORKFORCE ANALYTICS FOR SUPPLY CHAIN EFFICIENCY: A REVIEW OF HR DATA-DRIVEN PRACTICES

This study explores the pivotal role of HR analytics in enhancing supply chain management (SCM) efficiency, marking a significant shift from traditional HR practices to data-driven decision-making. The main objective was to bridge the gap between HR analytics and SCM performance, highlighting the transformative potential of integrating advanced data analysis in workforce management to optimize supply chain operations. Employing a systematic literature review and content analysis methodology, this research meticulously analyzed peer-reviewed articles, conference papers, and scholarly books from prominent databases. The search strategy was comprehensive, incorporating a broad spectrum of relevant keywords to ensure the inclusion of significant studies that address the integration of HR analytics into SCM. Key findings underscore the transformative power of HR analytics in SCM, revealing that data-driven HR practices significantly contribute to operational efficiency, strategic decision-making, and enhanced competitive advantage. Advanced analytical tools, such as AI, machine learning, and predictive analytics, have been identified as critical in optimizing workforce performance and aligning human capital with supply chain objectives. The study concludes with actionable recommendations for practitioners, leaders, and policymakers, emphasizing the importance of robust data governance, cross-functional collaboration, and the development of analytics competencies. It also outlines emerging challenges and opportunities in leveraging workforce analytics, suggesting directions for future research, particularly in exploring the strategic impacts of HR analytics on supply chain resilience and sustainability. This research contributes to the growing body of knowledge on the strategic integration of HR analytics in supply chain management, offering a roadmap for organizations seeking to enhance supply chain efficiency through data-driven HR practices. Keywords: HR Analytics, Supply Chain Management, Data-Driven Decision-Making, Workforce Optimization.

Using Soft System Methodology to Align Digitalization Strategies with Processes/Business Strategies: Towards A Qualitative Approach

This qualitative study investigated the alignment between digital strategy and business and process strategies, focusing on its impact on competitive advantage and operational effectiveness. Through interviews, case studies, focus group, and document analysis, the research highlighted the significance of strategic alignment in the digital era, identifying key themes such as leadership commitment, cross-functional collaboration, innovation culture, continuous learning, and data-driven decision-making. Key Findings: - Leadership Commitment: Effective digital strategy alignment is strongly influenced by the active support and vision of senior leadership; - Cross-Functional Collaboration. This study contributes valuable insights into the practices and challenges of strategic alignment, offering guidance for organizations navigating the complexities of digital transformation.

Improving Care Continuity in Oncology Settings: A Lean Management Approach to Minimize Discharges Without Follow-Up Appointments.

This study aimed to reduce the number of patients discharged without scheduled follow-up appointments by implementing lean management principles. Conducted at the Sultan Qaboos Comprehensive Cancer Center in Muscat, Oman, the research utilized a one-group pretest-posttest quasi-experimental design to evaluate the impact of lean management interventions on the rate of patient discharges without follow-up appointments. Strategies such as the Kaizen principle, Gemba Walks, cross-functional collaboration, standard work procedures, and waste reduction were employed to enhance operational efficiency. Spanning from Quarter 3 of 2022 to Quarter 2 of 2023, the study demonstrated a significant decrease in the percentage of patients discharged without planned follow-up appointments. The rate dropped from 9% in September 2022 to 0% in March 2023, with statistically significant differences observed (X2= 65.05, p value=<.0001). By effectively implementing lean management principles, this research successfully enhanced care continuity for oncology patients after being discharged.

Creative principles for managing innovation projects in BANI environment

In the dynamic landscape of innovation, where environments are increasingly characterized as Brittle, Accelerating, Nonlinear, and Incomprehensible (BANI), traditional project management approaches fall short of addressing the complexities and uncertainties that arise. This abstract explores a set of creative principles tailored for the effective management of innovation projects within BANI environments. Drawing inspiration from agile frameworks, design thinking, and open innovation, these principles aim to navigate the brittleness, acceleration, nonlinearity, and incomprehensibility inherent in such contexts. Adaptive leadership, rapid prototyping, and scenario planning emerge as key components, fostering a culture of continuous learning and cross-functional collaboration. Emphasizing innovation metrics beyond traditional KPIs, the abstract advocates for an ecosystem thinking approach to holistically comprehend the intricate interplay of factors within BANI environments. By integrating these creative principles, organizations can position themselves to not only adapt to the challenges presented by BANI but to thrive amid uncertainty, turning it into a catalyst for innovative growth. The world of innovation is facing unprecedented challenges. The acronym BANI – Brittle, Anxious, Nonlinear, and Incomprehensible – aptly captures the current environment characterized by fragile systems and interconnectedness. A single event can trigger cascading disruptions across industries and continents. Heightened uncertainty and anxiety. Rapid change and unforeseen events create constant pressure and require agility in decisionmaking. Non-linear trajectories and emergent phenomena. Traditional planning becomes obsolete in a world where cause and effect are blurry and unexpected outcomes arise. An incomprehensible information landscape. The sheer volume and complexity of data make it difficult to discern truth and make informed decisions. By embracing these creative principles, we can transform innovation projects from rigid endeavours into dynamic journeys of exploration and discovery. In the face of the BANI environment, embracing creativity, learning from failures, and pivoting quickly are the keys to unlocking ground breaking ideas and shaping a better future.

Syncretic project management in the era of artificial intelligence explosion

As the technological landscape rapidly evolves, the convergence of innovation and artificial intelligence (AI) presents unprecedented opportunities and challenges for project management. This paper introduces a comprehensive mathematical model for the syncretic management of innovative projects in the age of the AI explosion. Syncretism in this context refers to the seamless integration of diverse elements, including interdisciplinary collaboration, AI technologies, and adaptive methodologies, to optimize project outcomes. The proposed model encompasses various facets of project management, innovation, and AI integration. It delineates stages of project lifecycle management, emphasizing resource allocation, risk assessment, and adaptive strategies. In the innovation management domain, the model incorporates methodologies for idea generation, technology scouting, and open innovation, recognizing AI's role in shaping the innovative landscape. A crucial aspect of the model lies in the integration of AI technologies throughout the project. This includes identifying relevant use cases, managing data effectively, selecting appropriate AI models, and establishing decision support systems. The syncretic approach emphasizes cross-functional collaboration, fostering an environment where different disciplines seamlessly contribute to project success. Resource optimization is a key focus, leveraging AI to allocate resources efficiently, predict maintenance needs, and enhance overall project performance. Ethical and legal considerations are embedded within the model to ensure responsible AI usage, and the paper outlines mechanisms for ongoing training and development to equip teams with the necessary skills. The model's effectiveness is evaluated through the lens of monitoring and evaluation, with defined key performance indicators, continuous monitoring, and feedback loops for iterative improvements. Communication and collaboration are underscored, utilizing modern tools to facilitate stakeholder engagement and effective teamwork. This paper contributes to the evolving discourse on project management by providing a robust framework that adapts to the dynamic nature of AI and innovation. It serves as a guide for project managers, interdisciplinary teams, and decision-makers navigating the challenges and opportunities presented by the syncretic management of innovative projects in the era of the AI explosion.

Syncretic management of innovative projects in the age of ai explosion

As the technological landscape rapidly evolves, the convergence of innovation and artificial intelligence (AI) presents unprecedented opportunities and challenges for project management. This paper introduces a comprehensive mathematical model for the syncretic management of innovative projects in the age of the AI explosion. Syncretism in this context refers to the seamless integration of diverse elements, including interdisciplinary collaboration, AI technologies, and adaptive methodologies, to optimize project outcomes. The proposed model encompasses various facets of project management, innovation, and AI integration. It delineates stages of project lifecycle management, emphasizing resource allocation, risk assessment, and adaptive strategies. In the innovation management domain, the model incorporates methodologies for idea generation, technology scouting, and open innovation, recognizing AI's role in shaping the innovative landscape. A crucial aspect of the model lies in the integration of AI technologies throughout the project. This includes identifying relevant use cases, managing data effectively, selecting appropriate AI models, and establishing decision support systems. The syncretic approach emphasizes cross-functional collaboration, fostering an environment where different disciplines seamlessly contribute to project success. Resource optimization is a key focus, leveraging AI to allocate resources efficiently, predict maintenance needs, and enhance overall project performance. Ethical and legal considerations are embedded within the model to ensure responsible AI usage, and the paper outlines mechanisms for ongoing training and development to equip teams with the necessary skills. The model's effectiveness is evaluated through the lens of monitoring and evaluation, with defined key performance indicators, continuous monitoring, and feedback loops for iterative improvements. Communication and collaboration are underscored, utilizing modern tools to facilitate stakeholder engagement and effective teamwork. This paper contributes to the evolving discourse on project management by providing a robust framework that adapts to the dynamic nature of AI and innovation. It serves as a guide for project managers, interdisciplinary teams, and decision-makers navigating the challenges and opportunities presented by the syncretic management of innovative projects in the era of the AI explosion.

IMPLEMENTING AI IN BUSINESS MODELS: STRATEGIES FOR EFFICIENCY AND INNOVATION

This review delves into the profound impact of artificial intelligence (AI) integration on contemporary business paradigms. The paper meticulously explores diverse AI applications, including machine learning, natural language processing, and predictive analytics, illustrating how these technologies can revolutionize operational processes, augment decision-making capabilities, and foster unparalleled innovation within organizations. Drawing from case studies and industry examples across various sectors such as finance, healthcare, retail, and manufacturing, the study elucidates successful AI implementation strategies. It examines the importance of robust data governance frameworks to ensure quality and integrity, the acquisition of AI talent, and the imperative of fostering a culture of innovation and adaptability within organizations undergoing AI transformation. Furthermore, the paper addresses the nuanced challenges and risks inherent in AI adoption, spanning ethical considerations surrounding data privacy and bias mitigation, cybersecurity vulnerabilities, and the potential impact on the workforce. By providing a comprehensive overview of the opportunities and challenges associated with AI integration in business models, the study equips organizational leaders, policymakers, and stakeholders with invaluable insights to navigate the evolving landscape of AI-driven innovation. It underscores the significance of strategic foresight, cross-functional collaboration, and continuous learning in harnessing the full potential of AI technologies to drive sustainable growth and competitive advantage in the digital era.&#x0D; Keywords: AI, Business, Models, Strategies, Efficiency, Innovation.

Requirements for Cultivating Customer Focus

In today's fiercely competitive global marketplace, companies face a plethora of opportunities, as well as threats and challenges. As products become increasingly homogeneous, companies must develop concepts and strategies for fostering relationships with their customers. This necessitates a comprehensive approach, with a shift from transactional marketing to relationship marketing already underway, placing emphasis on the customer. Customer Relationship Management (CRM) holds promise for navigating competitive markets, yet high failure rates in CRM implementation persist. One critical success factor for CRM implementation is a steadfast orientation towards the customer. Achieving customer orientation entails various measures including change management, cross-functional collaboration, process optimization, employee engagement, and support from company stakeholders. Internal marketing is crucial for persuading employees to transition from functional to cross-functional thinking. Customer orientation is not merely a strategy, but a journey and long-term commitment, requiring continual assessment and enhancement. This paper offers an in-depth exploration of the essential factors for cultivating customer orientation.

THE ROLE OF AGILE PROJECT MANAGEMENT IN DRIVING INNOVATION IN ENERGY-EFFICIENT HVAC SOLUTIONS

This review delves into the significance of Agile Project Management (APM) in fostering innovation within the realm of energy-efficient Heating, Ventilation, and Air Conditioning (HVAC) solutions. As the global focus intensifies on sustainability and energy conservation, the HVAC industry stands at the forefront of addressing environmental challenges through innovative technologies. Agile methodologies, originally developed for software development, have transcended their conventional domains to revolutionize project management across various industries. This review explores how the application of Agile principles can catalyze innovation in energy-efficient HVAC solutions. Firstly, it delineates the core tenets of Agile Project Management, emphasizing iterative development, adaptive planning, and customer collaboration. By prioritizing flexibility and responsiveness to change, Agile methodologies empower HVAC project teams to swiftly adapt to evolving customer needs and technological advancements. This agility is particularly crucial in the HVAC sector, where rapid technological innovations necessitate quick iterations and constant feedback loops to refine energy-efficient solutions. Furthermore, the review elucidates how Agile frameworks such as Scrum and Kanban facilitate cross-functional collaboration and enhance communication within HVAC project teams. By fostering a collaborative environment that encourages transparency and knowledge sharing, Agile methodologies cultivate a culture of innovation wherein team members can experiment with novel ideas and swiftly pivot based on market feedback. Moreover, this review underscores the role of Agile Project Management in mitigating risks associated with innovation in energy-efficient HVAC solutions. Through frequent iterations and incremental delivery, Agile methodologies enable HVAC project teams to identify potential bottlenecks and address them proactively, thereby reducing project risks and enhancing overall project success rates. This review highlights the transformative potential of Agile Project Management in driving innovation within the energy-efficient HVAC industry. By embracing Agile methodologies, HVAC project teams can navigate the complexities of innovation more effectively, accelerate time-to-market for energy-efficient solutions, and ultimately contribute to the sustainable transformation of the HVAC sector.&#x0D; Keywords: Agile, Project Management, Innovation, Energy-Efficient, HVAC, Review.

Driving Organizational Effectiveness: Implementing Safe Agile Framework for Team Alignment in Large Organisations

Implementing the Scaled Agile Framework (SAFe) in large organizations is crucial for achieving organizational effectiveness, especially as they expand globally. The SAFe framework, initially designed for software development, has evolved to cater to diverse industries like health, manufacturing, engineering, and financial services. The study elaborates the significance of implementing SAFe agile framework for team alignment in large organisations. SAFe operates at four levels: Team, Program, Large Solution, and Portfolio. Efficient collaboration, communication, and coordination, the three Cs of SAFe Agile, are essential for synergy across these levels. To practically implement SAFe and achieve team alignment, organizations should follow ten SAFe principles. These principles include taking an economic view, applying systems thinking, assuming variability, building incrementally with fast learning cycles, basing milestones on objective evaluation, ensuring uninterrupted value flow, applying cadence, unlocking intrinsic motivation, embracing decentralized decision-making, and organizing around value. Balancing bottom-up and top-down approaches through a middle-out method ensures effective SAFe implementation. This approach combines the strengths of methods, fostering cross-functional collaboration and effective communication channels from teams to the portfolio level. In conclusion, large-scale businesses may enhance organizational success through the transformational process of applying the SAFe framework for team alignment, which improves alignment, cooperation, efficiency, flexibility, and continuous improvement.

Driving sustainable growth in SME manufacturing: The role of digital transformation, project, and capture management

In the landscape of Small and Medium-sized Enterprises (SMEs) within the manufacturing sector, achieving sustainable growth amidst increasing competition and evolving market demands presents a significant challenge. This abstract delves into the pivotal role of digital transformation, project management, and capture management in fostering sustainable growth for SME manufacturers. Digital transformation has emerged as a transformative force, offering SME manufacturers unprecedented opportunities to optimize processes, enhance efficiency, and expand their market reach. Through the adoption of advanced technologies such as Internet of Things (IoT), Artificial Intelligence (AI), and cloud computing, SMEs can streamline operations, improve product quality, and swiftly adapt to changing consumer preferences. Moreover, effective project management plays a crucial role in driving sustainable growth by ensuring timely delivery of products, cost optimization, and resource utilization. By implementing robust project management methodologies such as Agile or Lean, SME manufacturers can mitigate risks, enhance collaboration, and accelerate innovation, thereby gaining a competitive edge in the market. Furthermore, capture management, encompassing the identification, qualification, and pursuit of business opportunities, is instrumental in securing long-term growth for SME manufacturers. By strategically identifying target markets, understanding customer needs, and developing tailored solutions, SMEs can effectively capitalize on emerging opportunities and strengthen their market position. However, harnessing the synergies between digital transformation, project management, and capture management requires a comprehensive strategic approach. SME manufacturers must invest in cultivating a culture of innovation, fostering cross-functional collaboration, and nurturing talent equipped with the requisite digital and managerial skills. Driving sustainable growth in SME manufacturing necessitates a holistic approach that integrates digital transformation, project management, and capture management strategies. By embracing technological advancements, optimizing operational processes, and seizing market opportunities, SME manufacturers can embark on a trajectory of sustained success in the ever-evolving landscape of manufacturing.

Entrepreneurial leadership in high-tech industries: A review of key traits and success strategies

Entrepreneurial leadership plays a pivotal role in navigating the dynamic landscape of high-tech industries, where innovation, agility, and strategic vision are imperative for success. This paper provides a comprehensive review of key traits and success strategies associated with entrepreneurial leadership in the context of high-tech sectors. In high-tech industries, characterized by rapid technological advancements and fierce competition, the traditional leadership paradigm often falls short. Entrepreneurial leaders in this domain are distinguished by a set of traits that enable them to thrive in uncertainty and foster innovation. Proactivity, risk-taking propensity, and a keen sense of opportunity recognition emerge as fundamental traits that differentiate successful entrepreneurial leaders from their counterparts. This review explores how these traits contribute to creating an environment conducive to innovation and adaptation. Strategies employed by entrepreneurial leaders in high-tech industries are multifaceted, encompassing both organizational and individual levels. At the organizational level, fostering a culture of experimentation, encouraging cross-functional collaboration, and establishing flexible structures emerge as critical success factors. These strategies not only enhance the organization's adaptive capacity but also stimulate a culture of continuous learning and knowledge sharing. On an individual level, entrepreneurial leaders in high-tech industries often display a high degree of emotional intelligence, enabling them to navigate complex interpersonal relationships and foster a collaborative work environment. Additionally, effective communication and the ability to inspire and motivate diverse teams become crucial tools for leaders to drive innovation and ensure sustained success. Furthermore, the review delves into the role of strategic vision and adaptability in entrepreneurial leadership. Successful leaders in high-tech industries possess the foresight to anticipate market trends, coupled with the flexibility to adjust strategies swiftly in response to evolving technological landscapes. This paper encapsulates the essence of entrepreneurial leadership in high-tech industries by exploring key traits and success strategies. By understanding and incorporating these elements, leaders can cultivate an environment that fosters innovation, resilience, and sustainable growth in the ever-evolving high-tech landscape.

Managing large-scale projects: Unpacking the role of project memory

Drawing on ethnographic fieldwork conducted in a US-based firm engaged in a large-scale information system implementation project, this study presents an inductively developed framework of project memory incorporating three mnemonic co-orchestration practices: situated focusing, synchronizing discourse, and converging boundaries. Project memory is proposed to help manage challenges posed by large-scale projects as we observed in this study. This study offers insights into the role and practices of project memory and provides recommendations for managerial practice related to developing narrative and storytelling skills, strategically using meetings, and fostering a culture of cross-functional collaboration in large-scale projects.

Integrating Environmental, Social, and Governance Considerations into Company Operations

This manuscript comprehensively analyzes integrating environmental, social, and governance (ESG) considerations into company operations. Through an extensive literature review and case studies of industry leaders like Patagonia, Google, IKEA, Microsoft, and HSBC, the study explores the strategies adopted by corporate managers to align business practices with broader societal and environmental goals. The critique and recommendations address the effectiveness of ESG initiatives, challenges in implementation, cross-functional collaboration, balancing short-term and long-term goals, stakeholder engagement, continuous education, and risk management. The paper concludes by emphasizing the paradigm shift towards responsible and sustainable business practices, with recommendations for ongoing refinement.

Managerial agility and digital transformation of hydraulic basins: A case study of the Guir Hydraulic Basin Agency

This study aims to examine the impact of managerial agility on decision-making and water resources management within the Guir Hydraulic Basin Agency, focusing on digital approaches. Using a primarily quantitative approach, a questionnaire was administered to assess the perception of digital transformation success and the role of managerial agility among staff within the agency. The results underscore the pivotal role of managerial agility in optimizing water resources within the Hydraulic Basin Agency. The perceived success of digital transformation efforts, alongside the emphasis on collaborative decision-making and agile leadership, highlights the significance of this managerial approach. Furthermore, the recognition of digital training and cross-functional collaboration underscores the multifaceted impact of managerial agility on fostering sustainable water management practices. Agile communication emerges as crucial for aligning stakeholders with digital transformation objectives, thereby reinforcing the integral role of managerial agility in driving efficiency and sustainability in water resources management.

Brand Accounting- a Hard Rock to Drill

This paper delves into brand accounting, emphasizing its distinctiveness from Goodwill and advocating for a separate accounting system. Using the 'Lion Marka' case illustrates how brand valuation, centred on visual elements like logos and names, differs from the broader spectrum of Goodwill. The paper's objectives include: Developing precise methods for brand quantification. Integrating brand value into accounting systems. Providing insights for strategic decision-making. It highlights the advantages of brand accounting, such as enhanced financial reporting transparency and informed decision-making, while acknowledging challenges like subjectivity and the dynamic nature of brands. The literature review explores ongoing debates on measuring brand value, its impact on financial reporting, and the role of disclosure. The future of brand accounting anticipates standardization, integration into ESG reporting, and the use of advanced technologies like AI. The significance of brand accounting lies in its ability to enhance transparency, inform decision-making, and contribute to strategic resource allocation. Practical implications encompass risk management, investor relations, brand management strategies, and cross-functional collaboration. The paper concludes by emphasizing the evolving landscape of brand accounting, its pivotal role in financial reporting, and its integration into contemporary business practices. As stakeholders integrate these insights, brand accounting is poised to be crucial to financial management and decision-making in the dynamic business environment.