Foreword

In today’s rapidly evolving global market, data is increasingly becoming the currency of decision-making, and artificial intelligence is reshaping the very contours of enterprise strategy. Businesses no longer survive by intuition alone; they require systematic insight, underpinned by robust analytical models and collaborative frameworks. Having devoted much of my work to agent-based simulations, system dynamics, and value co-creation among diverse stakeholders—from small-scale entrepreneurs to large-scale industrial sectors—I recognize the urgent need for business leaders to understand data science in a holistic manner. This book, Data Science for Commercial, arrives at the perfect juncture to illuminate that path.

My own journey has shown me the transformative power of systems thinking and service science methodologies. When organizations, governments, and communities co-create solutions, guided by data and powered by thoughtful analytics, we see sustainable gains that would be impossible through siloed, traditional approaches. Whether the focus is on MSME empowerment, digital platforms for stakeholder collaboration, or sustainability-driven supply chain management, the consistent theme is that strategic decisions require a well-designed fusion of data, models, and human insight. What makes this volume exceptional is its emphasis on exactly those dimensions: it provides a robust conceptual framework, walks readers through real-world case studies, and, crucially, highlights how data science can align multiple interests and priorities to achieve measurable outcomes.

I particularly applaud the practical orientation here. In my own research—ranging from agent-based modeling of public health crises to big data platforms for micro-entrepreneurs—I’ve encountered the perennial challenge of bridging the gap between theoretical potential and everyday business reality. Often, companies struggle to translate even sophisticated analytics into meaningful operational changes or sustained competitive advantages. By incorporating step-by-step assignments and scenario-based learning, Data Science for Commercial ensures that readers do not just amass knowledge; they learn how to deploy that knowledge within their own organizations. This applied perspective is the key to cultivating a generation of leaders who can navigate complexities, rather than being overwhelmed by them.

Just as crucial is the book’s recognition that we exist in an interconnected ecosystem. My research in sustainability, resource-based theory, and collective problem-solving has repeatedly demonstrated that no single actor can thrive in isolation. Data science, when wielded responsibly, becomes a unifying lens that harmonizes different stakeholders—producers, consumers, investors, regulators—for shared value creation. By presenting frameworks for analyzing multi-stakeholder environments, this work demonstrates how analytics can be a springboard to more inclusive and resilient business models. It ties seamlessly with the service-science perspective, reminding us that solutions become exponentially more powerful when they arise from synergy rather than top-down mandates.

Looking ahead, the demands on business leaders grow more complex by the day. AI-driven transformations, environmental challenges, social shifts—these are not mere buzzwords but genuine forces reshaping the commercial landscape. The promise of data science lies in helping us approach these forces with strategic clarity, scientific rigor, and a spirit of co-creation. Data Science for Commercial distills these principles into a coherent and actionable guide. I am confident that anyone reading this book—be they seasoned executives, budding entrepreneurs, policy-makers, or students—will emerge better equipped to tackle the uncertainties of modern commerce.

May you find in these pages the same inspiration I have found in my own journey: that armed with data, a strong methodological framework, and a willingness to collaborate, we can transform daunting, complex challenges into opportunities for sustainable growth and shared prosperity. This is the true essence of data science in the commercial realm, and I congratulate the authors for capturing it so effectively.