Preface 1. Decision-Theoretic Foundations 1.1 Game Theory, Rationality, and Intelligence 1.2 Basic Concepts of Decision Theory 1.3 Axioms 1.4 The Expected-Utility Maximization Theorem 1.5 Equivalent Representations 1.6 Bayesian Conditional-Probability Systems 1.7 Limitations of the Bayesian Model 1.8 Domination 1.9 Proofs of the Domination Theorems Exercises 2. Basic Models 2.1 Games in Extensive Form 2.2 Strategic Form and the Normal Representation 2.3 Equivalence of Strategic-Form Games 2.4 Reduced Normal Representations 2.5 Elimination of Dominated Strategies 2.6 Multiagent Representations 2.7 Common Knowledge 2.8 Bayesian Games 2.9 Modeling Games with Incomplete Information Exercises 3. Equilibria of Strategic-Form Games 3.1 Domination and Ratonalizability 3.2 Nash Equilibrium 3.3 Computing Nash Equilibria 3.4 Significance of Nash Equilibria 3.5 The Focal-Point Effect 3.6 The Decision-Analytic Approach to Games 3.7 Evolution. Resistance. and Risk Dominance 3.8 Two-Person Zero-Sum Games 3.9 Bayesian Equilibria 3.10 Purification of Randomized Strategies in Equilibria 3.11 Auctions 3.12 Proof of Existence of Equilibrium 3.13 Infinite Strategy Sets Exercises 4. Sequential Equilibria of Extensive-Form Games 4.1 Mixed Strategies and Behavioral Strategies 4.2 Equilibria in Behavioral Strategies 4.3 Sequential Rationality at Information States with Positive Probability 4.4 Consistent Beliefs and Sequential Rationality at All Information States 4.5 Computing Sequential Equilibria 4.6 Subgame-Perfect Equilibria 4.7 Games with Perfect Information 4.8 Adding Chance Events with Small Probability 4.9 Forward Induction 4.10 Voting and Binary Agendas 4.11 Technical Proofs Exercises 5. Refinements of Equilibrium in Strategic Form 5.1 Introduction 5.2 Perfect Equilibria 5.3 Existence of Perfect and Sequential Equilibria 5.4 Proper Equilibria 5.5 Persistent Equilibria 5.6 Stable Sets 01 Equilibria 5.7 Generic Properties 5.8 Conclusions Exercises 6. Games with Communication 6.1 Contracts and Correlated Strategies 6.2 Correlated Equilibria 6.3 Bayesian Games with Communication 6.4 Bayesian Collective-Choice Problems and Bayesian Bargaining Problems 6.5 Trading Problems with Linear Utility 6.6 General Participation Constraints for Bayesian Games with Contracts 6.7 Sender-Receiver Games 6.8 Acceptable and Predominant Correlated Equilibria 6.9 Communication in Extensive-Form and Multistage Games Exercises Bibliographic Note 7. Repeated Games 7.1 The Repeated Prisoners Dilemma 7.2 A General Model of Repeated Garnet 7.3 Stationary Equilibria of Repeated Games with Complete State Information and Discounting 7.4 Repeated Games with Standard Information: Examples 7.5 General Feasibility Theorems for Standard Repeated Games 7.6 Finitely Repeated Games and the Role of Initial Doubt 7.7 Imperfect Observability of Moves 7.8 Repeated Wines in Large Decentralized Groups 7.9 Repeated Games with Incomplete Information 7.10 Continuous Time 7.11 Evolutionary Simulation of Repeated Games Exercises 8. Bargaining and Cooperation in Two-Person Games 8.1 Noncooperative Foundations of Cooperative Game Theory 8.2 Two-Person Bargaining Problems and the Nash Bargaining Solution 8.3 Interpersonal Comparisons of Weighted Utility 8.4 Transferable Utility 8.5 Rational Threats 8.6 Other Bargaining Solutions 8.7 An Alternating-Offer Bargaining Game 8.8 An Alternating-Offer Game with Incomplete Information 8.9 A Discrete Alternating-Offer Game 8.10 Renegotiation Exercises 9. Coalitions in Cooperative Games 9.1 Introduction to Coalitional Analysis 9.2 Characteristic Functions with Transferable Utility 9.3 The Core 9.4 The Shapkey Value 9.5 Values with Cooperation Structures 9.6 Other Solution Concepts 9.7 Colational Games with Nontransferable Utility 9.8 Cores without Transferable Utility 9.9 Values without Transferable Utility Exercises Bibliographic Note 10. Cooperation under Uncertainty 10.1 Introduction 10.2 Concepts of Efficiency 10.3 An Example 10.4 Ex Post Inefficiency and Subsequent Oilers 10.5 Computing Incentive-Efficient Mechanisms 10.6 Inscrutability and Durability 10.7 Mechanism Selection by an Informed Principal 10.8 Neutral Bargaining Solutions 10.9 Dynamic Matching Processes with Incomplete Information Exercises Bibliography Index

博弈论 : 矛盾冲突分析 = Game theory : analysis of conflict

Qualitative Interviewing: The Art of Hearing Data

Sorting Things Out: Classification and Its Consequences.

Eric Ries was born in September 1978. He graduated from Yale University and moved to silicon Valley in the beginning of the millennium. He pioneered the philosophy of Lean Startup, based on his experience with multiple startups, primary being IMVU which he co-founded along with Will Harvey in 2004. Eric Ries originated his Lean Startup philosophy after getting inspired from the Japanese Philosophy of Lean Manufacturing.

The Lean Startup:How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses

Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life

Normalising the "new normal": Changing tech-driven work practices under pandemic time pressure.

On the basis of 13 agile transformation cases over 15 years, we identify nine challenges associated with implementing Scaled Agile Framework, Scrum at Scale, Spotify, Large-Scale Scrum, Nexus, and other mixed or customized large-scale agile frameworks. These challenges should be considered by organizations aspiring to pursue a large-scale agile strategy. We also provide recommendations for practitioners and agile researchers.

Implementing Large-Scale Agile Frameworks: Challenges and Recommendations

In recent years, there has been significant growth in software companies across the healthcare sector developing new technologies to improve healthcare delivery and services. This has given rise to the emergence of Connected Health -- a new model for healthcare management. This also places considerable emphasis on the process of software development in supporting Connected Health. In addition, it highlights the growing reliance and trust we place on software to support healthcare decisions. However, unlike many other sectors, such as business and education, failure to align healthcare needs with software requirements can have devastating consequences on people's health and potentially cause death. Our research and experience with healthcare companies confirms the need to establish a Connected Health Innovation Framework using Design Thinking principles to a) support software developers in clearly identifying healthcare requirements and b) extend and enrich traditional software requirements gathering techniques. This paper presents an e-pharmacy case study and describes the impact this approach has within a Connected Health context.

/pdf/aligning-healthcare-innovation-and-software-requirements-1l3zs4vduy.pdf

Aligning healthcare innovation and software requirements through design thinking

Purpose – Open innovation is an emerging paradigm which exposes organisations to networked capabilities and competencies though collaboration relationships. The traditional view of the organisational environment raises concerns regarding the mismatch in the methods used to assess business value and understanding service process maturity. The purpose of this paper is to address this gap. Design/methodology/approach – This paper employs a systematic literature review to present a state-of-the-art literature review with particular focus on the applicability of capability maturity models (CMM) within an open innovation context. Findings – The authors present a conceptual account of our research developments and build on the state-of-the-art which bridges open innovation and CMM. The authors provide a comprehensive discussion on the literature and challenge the applicability of individual organisations evolving through maturity stages. The authors identify a significant gap in the emergence of open innovation ...

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Service capabilities within open innovation: Revisiting the applicability of capability maturity models

Healthcare delivery is being transformed by technology that personalizes, tracks, and manages patient information across devices. Smart and connected health will develop safer and more effective, efficient, equitable, and user-centered services through pervasive computing innovations.

Noel Carroll

Papers

Normalising the "new normal": Changing tech-driven work practices under pandemic time pressure.

Implementing Large-Scale Agile Frameworks: Challenges and Recommendations

Aligning healthcare innovation and software requirements through design thinking

Service capabilities within open innovation: Revisiting the applicability of capability maturity models

Key Success Factors for Smart and Connected Health Software Solutions