Enterprise Transformation

This paper uses work system theory (WST) and two of its extensions to provide an integrated perspective on engineering enterprises for emergent change. This paper starts by explaining six basic assumptions and distinctions related to emergent change. It introduces four frameworks or models related to WST including the work system framework, work system life cycle model, a theory of workarounds, and a work system metamodel. It shows how each framework or model can help in identifying different aspects of engineering for emergent change and also can be the basis of guidelines for that purpose. Overall, this paper provides a unique way to think about the engineering of enterprises. In addition, it explains a combination of concepts and frameworks that provide a path toward engineering for emergent change.

This paper explores how work system theory (WST) and related core ideas in various versions of the work system method (WSM) overlap with enterprise engineering and with the DEMO methodology. Based on the definition of work system, an enterprise can be viewed as a set of interacting work systems. A work system can be summarized at various levels of detail. The simplest level is basically a verb phrase. The next level is a "work system snapshot." More detailed descriptions are based on a work system metamodel. This paper's contribution is in two areas, 1) establishing links between WST/WSM and enterprise engineering in general and 2) comparing aspects of WST/WSM and DEMO and demonstrating similarities, thereby implying the possibility of converting DEMO models into work system models that can be developed further using other methods and tools designed around WST. Those synergies might support combining theoretical underpinnings of DEMO with the intuitive simplicity of the work system perspective, which has been applied by many hundreds of employed MBA and Executive MBA students who produced management briefings recommending improvements in work systems in their own organizations. The overlap between WST/WSM and DEMO is demonstrated using a DEMO representation of the OMG's EU Rent example [1], which illustrated OMG's Semantics of Business Vocabulary and Business Rules (SBVR) [2] and Business Motivation Model (BMM) [3]. A tabular summary called a work system snapshot captures much of a DEMO essential model of the EU Rent example. A more extensive summary based on a work system metamodel adds information for going from construction to implementation. The example illustrates how a work system perspective on a sociotechnical system fits with 7 postulates of an enterprise engineering manifesto [4] and with 7 enterprise engineering fundamentals [5], thereby suggesting the potential value of deeper exploration of those relationships.

This conceptual contribution responds to the invitation to the DIGIT 2015 Call for Papers "to reflect on and move forward from the dominant stream of research work on technology acceptance." The dominant stream of research is basically about antecedents and correlates of adoption and continuation of use for hardware/software artifacts. This paper uses work system theory and several of its extensions to identify directions for adoption research that have been realized partially, but not nearly to the extent possible. It focuses on three general issues: 1) what adoption means in the context of work systems, 2) how adoption occurs, and 3) how adoption entities change after adoption, including decisions by work system participants about whether and how to comply or not comply with prescribed practices that are often taken-for-granted as the result of adoption processes.

The integration of Artificial Intelligence (AI) in accounting and commerce is transforming traditional processes by enabling real-time analytics and data-driven decision-making. Techniques like machine learning, natural language processing, and robotic process automation are employed across a range of tasks, including data entry, financial reporting, fraud detection, and customer service. These technological advancements significantly improve operational efficiency and cost-effectiveness. However, they also raise important concerns regarding ethics, data privacy, workforce displacement, and regulatory compliance. This study critically examines the multifaceted impact of AI on accounting and commerce by evaluating the associated opportunities, challenges, and emerging trends. Drawing upon interdisciplinary literature and current organizational practices, the study offers valuable insights for scholars, business leaders, and policymakers navigating this evolving landscape.

The promise of IoT technology to provide a ‘neural network for the physical world’ that opens new vistas for value creation has long been touted in information systems research. However, in many domains, this promise in large parts is still untapped due to clash between linear business models bound to singular organisations and distributed IoT infrastructures. In this paper, we propose a framework for conceptualising and quantifying value flows in IoT ecosystems and illustrate its potential usefulness for modelling the dynamics of IoT business models. We do so by presenting an illustrative system dynamics model of value flows in case of the Smart Office IoT ecosystem. Our research proposes venues of further research to model IoT value flows and thereby move closer to identifying specific IoT ecosystem value flows and their related business models.

Human Resources (HR) function. HR re-engineering -involving the redesign of HR processes, structures, and strategies -is crucial for aligning human capital with organizational goals. However, successful HR transformation requires more than just structural change; it demands strong leadership capable of inspiring, guiding, and sustaining the change process. This paper explores the impact of transformational leadership on the success of HR re-engineering efforts. Using a mixed-methods approach, including theoretical analysis and case study evaluations, this research demonstrates that transformational leadership significantly enhances the effectiveness, sustainability, and employee acceptance of HR transformations. Practical recommendations and future research avenues are also discussed.

Artificial intelligence-powered data analytics functions as an indispensable transformational force that helps organizations obtain immediately useful information from large databases while responding rapidly to shifting market conditions across different business sectors. This research analyzes how artificial intelligence, when connected to data analytics, drives transformational development through analyses of real-time applications along with advantages and obstacles that exist in addition to future analytical patterns. Through their union, data analytics and artificial intelligence systems enable businesses to derive actionable decisions from large database analysis, which leads to changed strategic decisions in multiple enterprise domains. Organizations now recognize that processing large amounts of data in real time has become a strategic necessity to achieve operational excellence while maximizing customer satisfaction. Artificial intelligence and data analytics harmonization created a fundamental change in the real-time decision framework that allows organizations to use data power for agile strategic moves in dynamic business environments. AI algorithms working together with data analytics methods allow organizations to obtain important insights so they can predict future business trends while automating operational choices to enhance overall productivity along with business opportunities. AI, together with data analytics, produces maximum effects during mission-critical decision-making situations involving finance risk control and medical diagnosis and supply chain continuity and cybersecurity protection events. AI algorithms empower the automated analysis of complex datasets by using machine learning together with deep learning as well as natural language processing to detect hidden patterns, anomalies, and correlations that traditional methods would struggle to reveal.

The integration of Artificial Intelligence (AI) into enterprise operations offers significant opportunities for efficiency, innovation, and competitive advantage. However, organizations often encounter multiple barriers that hinder AI adoption, including technological complexities, high implementation costs, workforce resistance, and ethical concerns. This research examines key challenges faced by enterprises in AI transformation and proposes scalable strategies to overcome these barriers. Through a systematic review of contemporary AI implementation cases and expert insights, we identify best practices such as phased deployment, workforce upskilling, robust governance frameworks, and agile methodologies. Additionally, we highlight the role of explainable AI (XAI) and ethical AI frameworks in enhancing trust and regulatory compliance. The findings suggest that a combination of organizational readiness, strategic investment, and continuous adaptation is crucial for the successful and scalable adoption of AI. This study provides a roadmap for enterprises to navigate AI transformation, ensuring both operational efficiency and long-term sustainability.

The increasing recognition of environmental and social challenges has prompted a significant shift towards integrating sustainability in project management, especially in the context of infrastructure development. This paper explores the various approaches for incorporating sustainability into project management frameworks, focusing on the triple bottom line (TBL) concept, sustainability assessment tools, and the role of organizational culture and leadership. It examines key success factors, such as resource availability, project manager competence, and stakeholder engagement, alongside barriers including perceived conflicts with traditional project goals, complexity, and organizational resistance. Theoretical underpinnings, including systems theory, stakeholder theory, and adaptive management principles, provide a foundation for understanding how sustainability can be systematically integrated into project management practices. The study highlights the importance of a holistic approach that balances environmental, social, and economic considerations to achieve sustainable infrastructure development. By applying these frameworks and theories, project managers can enhance the sustainability of infrastructure projects, ensuring long-term benefits for society and the environment.

Business process management is increasingly present in organisations, and process improvement is one of its focuses. Patterns for process redesign provide solutions for recurring problems in business process improvement initiatives. However, choosing which patterns to apply in a process is not an easy task, especially in large and complex processes scenarios. This paper proposes heuristics to automate the process redesign pattern selection. The heuristics indicates specific process parts to apply improvement patterns, considering the business process model elements. A case study was performed to evaluate the proposal. The results highlight the applicability and reliability of heuristics to identify improvement opportunities in business processes models.

Leadership, plays a very important role in moulding human capital development to align workforce capabilities with organizational objectives when the need for change arises. This paper seeks to explore how effective change leadership impacts employee skills acquisition, adaptability, and productivity. We use some real examples and theoretical insights to explore the interaction among leadership styles, strategies of change management, and the human capital lifecycle.

Abstract

Companies in the United States and other countries have one thing in common. They all experience good times and more difficult times. This book looks at how actual companies  managed their affairs when times are not good. Some companies handle matters well and they emerge successfully to continue as profitable entities and good places to work. Other companies flounder. The question is which managerial strategies and methods actually work best in real-world situations, and which do not.

This book describes16 businesses that experienced very difficult financial difficulties in several periods of our nation's industrial history. Nine of these companies emerged successfully and  seven were unsuccessful. The strategies employed, the managerial skills, and character traits among leaders are compared and contrasted to identify which of these characteristics and most important to achieving success.

All of the companies examined were real companies drawn from actual occurrences in the automobile and agricultural equipment industries, in part because more was written about the character and methods of the people involved in these trying events. Each case was studied over a 20 year period so more could be learned about what led up to the trouble, what steps were taken, and what results were achieved. Both engineering and managerial practices were examined.

Companies in the United States and other countries have one thing in common. They all experience good times and more difficult times. This book attempts to look at how companies manage their affairs when times are not so good. Some companies handle matters well. They emerge successfully from difficult times to continue as profitable entities and good places to work. Other companies flounder. The questions examined in this book are which managerial strategies and methods work best, and which do not. It recounts a longitudinal study of 16 businesses that experienced very difficult financial difficulties in several periods of our nation's industrial history. Nine of these companies were ultimately successful and  seven were unsuccessful. The strategies employed in successful turnarounds and the managerial skills and character traits present among successful turnaround agents are compared and contrasted with those of unsuccessful turnaround efforts.
All of the companies examined were real companies drawn from actual occurrences in the automobile and agricultural equipment industries, in part because more was written about the character and methods of the people involved in these trying events. Specific criteria and measurement procedures were used to select the cases for study and to classify the cases as successful or unsuccessful. Quantitative and narrative information, business histories, and interviews were used to examine strategies and key functional operations, including marketing, manufacturing, product development, and finance. Multiple data sets covering many years, usually 20 years, were examined for each case and published narratives were  examined to supplement the statistical data.

The global healthcare spending has constantly increased in the last decades, and there is data showing inefficiency in resource consumption that is not reflected in healthcare improvement. The need to introduce new ways to do the same at a lower cost is rational. To address this, we propose a method based on Enterprise Ontology to find non value-added transactions that must be redesigned to improve the healthcare management. This methodology was chosen as a basis for our solution because it provides a better understanding of the dynamics of an organization, and allows a good alignment between the enterprise design and operation. Demonstrations were accomplished within National Health System, making it possible to find transactions that can be refined or improved. Evaluation was carried out by means of interviews, the Four Principles from Österle et al., the Moody and Shanks Quality Framework, the framework from Pries-Heje et al., and the feedback from the scientific community. Results prove that the method yields an adequate and clear process view and is reliable when it comes to improving healthcare operational processes.

In the complex space of the healthcare system, we need tools that help decision makers to interactively and inexpensively eliminate infeasible approaches prior to executing expensive changes, and focus on only the most promising strategies. A data-rich agent-based decision support model in the context of hospital consolidation is introduced to address a variety of scenarios. By "rich, "we mean extensive rule sets and information sources: these include agents' financial statements, operational performance, as well as a detailed set of strategic objectives. An application of this model is to analyze hospitals' merger and acquisition activities in New York City based on overarching characteristics for the 5,000+ hospitals nationwide. The model is accompanied by a large-scale interactive visualization, where an array of seven 8 × 20 , 180 degree touch-screen monitors are installed. This unique approach enables non-technically oriented stakeholders an immersive experience that enables asking many "what if" questions and greatly increases their comfort levels through evidence-based decision making. The purpose of this research is to integrate various information sources to facilitate strategic decision-making processes and understand path dependencies.

The Massachusetts Institute of Technology (MIT) through its Lean Advancement Initiative (LAI) research team has been conducting research and facilitating enterprise-level transformations in large complex sociotechnical enterprises for over fifteen years. These enterprises have spanned a broad base of industries and governmental organizations including aerospace, automotive, electronics, health care, transportation, construction, defense acquisition and logistics, research labs and many others. What has emerged from both the action research in the field and its application in case studies in graduate courses is the concept of "overarching" enterprise principles and transformation methodologies that are independent of the industry or organization. A framework for transformation that consists of a set of interdependent methodologies, tools and enterprise principles that support holistic enterprise transformation is described and includes the following five elements: 1) Key Principles of Enterprise Thinking, 2) Enterprise Transformation Roadmap, 3) Lean Enterprise Self Assessment Tool (LESAT), 4) Enterprise Strategic Analysis for Transformation (ESAT) and 5) Enterprise Architecting Framework. The application of this framework to the enterprise systems analysis and design of various industry and governmental organizations is discussed.

The aim of this study was to investigate the manufacturing performance at sewing section through lean manufacturing principle in garment industry. The fundamental idea behind the concept of lean manufacturing consists to eliminate waste, which does not add value to the end product. Lean manufacturing is considered as one of the most influential activities that focus on cost reduction by eliminating non-value added activities. This paper addresses the relevance of lean manufacturing philosophy for the higher productivity in sewing section of the garments industry and pull out the frequent scenario of garments sector of Bangladesh by mentioning the existing pictures of sewing section. In this work, the existing layouts were studied and then lean manufacturing ideas are proposed to enhance the production system and some cellular manufacturing philosophies to find out the improved level of performance and productivity particularly in the garments section of that factory. All the operations related to different garments styles standard allowed minute or SAM were calculated. The resultant value of SMV for each style including and excluding non productive time were; Evelyn College-6.20 and 5.23 min; Rodeo Long Sleeve-7.53 and 6.43 min; Ramona MC01-7.05 and 5.87 min; Ramona MC03-6.95 and 5.74 min respectively. From this research work, various types of problems related to waste and various weaknesses of sewing section have been evaluated by using specific lean manufacturing tools as well as sewing performance has been measured in terms of effectiveness, time and quality. Waste related non productive activities and productivity are the two major issues in garments sector of Bangladesh. In this connection, this research was conducted. However, this research work proposes some recommendations for the future improvement of performance of the sewing section in garments industry.

This research paper examines the critical role of Business Process Management (BPM) in streamlining business operations, with a focus on reducing costs, minimizing waste, and boosting efficiency. The study explores the fundamental principles of BPM, including stakeholder interviews, process mapping techniques, and the documentation of current and future states. Through a comprehensive analysis of existing literature and case studies, this paper investigates the best practices, current challenges, lessons learned, and future directions in BPM implementation. The research highlights the importance of BPM as an essential discipline within enterprise architecture, emphasizing its capacity to capture critical details, identify gaps, and uncover improvement opportunities. By examining the end-to-end process steps, including both system and manual components, this study demonstrates how BPM can effectively streamline operations and drive organizational success. The findings of this research provide valuable insights for businesses seeking to optimize their processes, reduce operational costs, and enhance overall efficiency in an increasingly competitive global marketplace.

O objetivo desta pesquisa é verificar se a materialidade pode ser uma considerada uma competência de transformação organizacional na concepção sustentável. Uma intenção secundária é listar e ranquear outras possíveis competências que possibilitem alterar o cenário corporativo por meio das premissas do Triple Bottom Line. A abordagem empregada para resolver esta lacuna é o estudo Delphi. O método é responsável pela extração de um consenso entre especialistas no assunto. Para a ordenação das competências, uma ferramenta do Qualtrics e o Método Mudge foram selecionados. Este último tem como objetivo minimizar fatores subjetivos que estão inerentes ao cotidiano do ser humano, proporcionando uma tomada de decisão mais eficaz. Como um dos principais achados, esta pesquisa retornou 9 competências necessárias para realizar transformação organizacional na vertente citada. Além disso, confirmou que a materialidade pode ser considerada uma destas competências, e que ela pode contribuir para a seleção e, consequentemente, ajudar as empresas a alcançarem os Objetivos de Desenvolvimento Sustentável. A limitação deste trabalho está na ausência de orientações detalhes de como implementar tais competências no cotidiano organizacional. Como originalidade, este paper destaca-se ao ser o primeiro ao abordar as competências necessárias para transformação com os pilares sustentáveis e também ao dar aplicabilidade ao conceito recém-desenvolvido de materialidade.

This research investigates how the Unified Architecture Framework (UAF) can be leveraged to transform enterprise strategic planning, focusing on the application of UAF frameworks and best practices to drive organizational success. It provides an overview of UAF's comprehensive methodology, detailing its various viewpoints and models that facilitate alignment between business objectives and IT infrastructure. The paper examines how UAF supports effective decision-making, enhances organizational agility, and improves risk management through a structured approach. Through case studies and practical examples, the paper illustrates successful implementations of UAF, highlighting the benefits and challenges encountered. It offers actionable insights into best practices for integrating UAF into existing strategic planning processes, including strategies for overcoming common obstacles and maximizing the framework's potential. The discussion extends to future perspectives, addressing emerging trends and technological advancements that could influence UAF's evolution and application. Overall, the paper underscores the transformative impact of UAF on enterprise strategic planning, providing a roadmap for organizations seeking to leverage the framework to achieve strategic alignment, innovation, and long-term success. The paper also delves into the practical aspects of adopting UAF, including the steps required for successful implementation. It covers critical considerations such as the need for comprehensive training and stakeholder engagement, the importance of tailoring UAF to fit specific organizational contexts, and the integration of UAF with existing tools and methodologies. Through detailed analysis, the paper identifies key success factors and common pitfalls, offering guidance on how to navigate these challenges effectively. Furthermore, the paper explores the future trajectory of UAF, emphasizing the potential for further refinement and adaptation in response to evolving business and technological landscapes. It highlights how emerging technologies, such as artificial intelligence and advanced data analytics, can be integrated into the UAF framework to enhance its capabilities. By addressing these future perspectives, the paper aims to provide a forwardlooking view of how UAF can continue to drive enterprise transformation and innovation in an increasingly complex and dynamic environment.

Physician certification boards are an intrinsic part of medical professionalism, and the public is their key stakeholder. A decade ago, the 24 boards of the American Board of Medical Specialties committed to moving beyond the summative evaluation of physicians to a process of continuously evaluating and improving the care they deliver. The American Board of Family Medicine (ABFM) has been a leader in this change and is making strategic investments in the next major evolution of continuous certification. Physicians are frustrated with the pace of change, inability to reliably assess and change their practices, and the perceived risk to both income and professional autonomy. Certifying boards are natural targets for that frustration. Certifying boards have an opportunity to support physicians in improving the quality and safety of healthcare and appeal to physicians' intrinsic motivation for doing so. The ABFM is not retreating from that challenge but is instead listening carefully to family physicians and making strategic investments to evolve. The ABFM is the first certifying board to launch a registry that is designed to support physician capacity for quality assessment, improvement, data-reporting requirements, and population management. It also supports more effective measure development and research. The ABFM aims to help physicians maintain the privilege of self-governance by helping them continuously earn it.

Idealized system design produces requirements reflecting management intentions and "best practices." This paper proposes a workaround design system (WDS) for anticipating, designing, and/or preventing workarounds that bypass systems as designed. A WDS includes a process and an interactive "workaround design tool" (WDT) for identifying and evaluating foreseeable workarounds based on work system theory and a theory of workarounds. This paper summarizes the conceptual background and explains the form, use, and implications of the proposed WDS and WDT. The idea of WDS addresses significant gaps in practice and research. Designers should have methods for identifying likely obstacles and anticipating and evaluating a non-trivial percentage of plausible workarounds. Methods for identifying workarounds might help in training work system participants. Researchers might use WDS to explore why specific responses to obstacles did or did not occur. The lack of methods related to anticipating, designing or preventing workarounds implies that WDS may prove fruitful even though it is impossible to anticipate all possible workarounds.

The global healthcare spending has constantly increased in the last decades, and there is data showing inefficiency in resource consumption that is not reflected in healthcare improvement. The need to introduce new ways to do the same thing at a lower cost is rational. To address this, we propose a method based on Design Engineering Methodology for Organizations (DEMO) to find non value-added transactions that must be redesigned to simplify processes. This methodology was chosen as a basis for our solution because it provides a better understanding of the dynamics of an organization, and allows a good alignment between the enterprise design and operation. A demonstration was accomplished within an Emergency Medical Service and a Pharmacy, making it possible to find transactions that can be improved or automated. Evaluation was carried out by means of interviews, the Four Principles from Österle et al., and the Moody and Shanks Quality Framework. Results prove that the method yields an adequate and clear process view and is reliable when it comes to improving healthcare operational processes.

Australian government enterprises have shown a significant interest in the cloud technology-enabled enterprise transformation. Australian government suggests the whole-of-a-government strategy to cloud adoption. The challenge is how best to realise this cloud adoption strategy for the cloud technologyenabled enterprise transformation? The cloud adoption strategy realisation requires concrete guidelines and a comprehensive practical framework. This paper proposes the use of an agile enterprise architecture framework to developing and implementing the adaptive cloud technology-enabled enterprise architecture in the Australian government context. The results of this paper indicate that a holistic strategic agile enterprise architecture approach seems appropriate to support the strategic whole-of-a-government approach to cloud technology-enabled government enterprise transformation.

The global healthcare spending has constantly increased in the last decades, and there is data showing inefficiency in resource consumption that is not reflected in healthcare improvement. The need to introduce new ways to do the same thing at a lower cost is rational. To address this, we propose a method based on Design Engineering Methodology for Organizations (DEMO) to find non value-added transactions that must be redesigned to simplify processes. This methodology was chosen as a basis for our solution because it provides a better understanding of the dynamics of an organization, and allows a good alignment between the enterprise design and operation. A demonstration was accomplished within an Emergency Medical Service and a Pharmacy, making it possible to find transactions that can be improved or automated. Evaluation was carried out by means of interviews, the Four Principles from Österle et al., and the Moody and Shanks Quality Framework. Results prove that the method yields an adequate and clear process view and is reliable when it comes to improving healthcare operational processes.

This paper explores the support for more comprehensive modeling of service systems than that possible through modeling methods developed through partial perspectives, with uncertainties about their wider suitability and need for integration with other methods in this domain. It responds to a Dual Call for Papers from INFORMS Service Science and IEEE Transactions on Service Computing requesting contributions that address the barely explored challenge of establishing links between business views of service systems and more technical views from service computing. Competing definitions of service reveal that most business views of service emphasize acts or outcomes produced for others, whereas a service computing view emphasizes encapsulated functionalities that can be discovered and launched by service consumers. This paper uses work system theory (WST) and a related work system metamodel to represent a business view of service systems. It uses the Unified Service Description Language ...

Although mentioned frequently in the organization, management, public administration, and technology literatures, workarounds are understudied and undertheorized. This article provides an integrated theory of workarounds that describes how and why workarounds are created. The theory covers most types of workarounds and most situations in which workarounds occur in operational systems. This theory is based on a broad but useful definition of workaround that clarifies the preconditions for the occurrence of a workaround. The literature review is organized around a diagram that combines the five "voices" in the literature of workarounds. That diagram is modeled after the diagram summarizing Orton and Weick's [1990] loose coupling theory, which identified and combined five similar voices in the literature about loose coupling. Building on that basis, the theory of workarounds is a process theory driven by the interaction of key factors that determine whether possible workarounds are considered and how they are executed. This theory is useful for classifying workarounds and analyzing how they occur, for understanding compliance and noncompliance to methods and management mandates, for incorporating consideration of possible workarounds into systems analysis and design, and for studying how workarounds and other adaptations sometimes lead to larger planned changes in systems.

Current research related to the subject matter of business informatics reflects divergent orientations that are fundamentally about representing, analyzing, and designing services or processes or work systems or enterprises. After summarizing those four orientations and citing typical exemplars, this paper identifies a variety of paths toward greater integration between different orientations within business informatics. It identifies central topics for each orientation along with areas in which each orientation provides ideas that complement other orientations and reveal possible synergies. Both the approach for identifying potential synergies and the proposed synergies themselves could encourage greater integration within business informatics.

The main goal of the Enterprise Systems and Business Process Capability Workshop at ECIS 2011 is to discuss ways to achieve greater business value from ERP. This paper explains how various aspects of work system theory (WST) can be applied to achieve that goal by assuming that the underlying "design spaces" encompass much more than the features, configuration, and limitations of ERP software. It uses WST concepts to identify directions for achieving business value that might not be considered thoroughly in ERP implementations that focus primarily on converting from legacy software to ERP software. This paper starts by summarizing basic premises concerning the relationship between work systems and ERP. Focusing on the context of ERP usage, it explains the elements of the two central frameworks in WST, the work system framework and work system life cycle model. Instead of viewing the context as ERP usage or ERP projects, viewing the context as ERP-enabled work system improvement focuses attention on a number of paths toward greater business value that may not be used effectively in current practice. The paper discusses five relevant design spaces that are mentioned rarely, if at all, in current practice. Part of the paper's contribution is in making those ideas more explicit through framing the discussion around aspects of WST. Another part of its contribution is in providing a new way to discuss topics such as workarounds, add-ins, and exceptions that are sometimes controversial issues when ERP is used.

This paper presents a metamodel designed to help in understanding, analyzing, and designing sociotechnical systems. The metamodel extends and clarifies the work system framework and related concepts at the core of work system approach for understanding IT-reliant work systems in organizations [Alter, 2003, 2006a, 2008a]. Development of the metamodel supports a larger goal of creating an enhanced work system approach that is understandable to business professionals but that is somewhat more rigorous than most current applications of work system concepts and can be linked more directly to precise, highly detailed analysis and design approaches for IT professionals. The 32 elements in the metamodel include work system, the 9 elements of the work system framework (with information replaced by informational entity), and 22 other elements that clarify a number of questions and confusions observed in past applications of the work system approach. Specification of the metamodel clarifies ambiguities in the work system framework and forms a clearer conceptual basis for tools and methods that could improve communication and collaboration between business and IT professionals. It can also be used to organize much of the know-how and many of the system-related research results in the IS field.

Innovation and technological change have been at the center of our society for most of the past 50 years. During that time, academics have tried with varying success to study the processes that drive growth in innovation and technology. This paper provides a historical perspective on the trajectory of research on innovation and technological change. Based on our review, we offer three positions that run counter to the status-quo. First, that a model of innovation should explain the dynamics of market competition rather than to simply define the source of economic rents. Second, that the manner in which we should study innovation and technological change is much more behavioral in nature. Third, we need to unpack the organization to make progress in understanding innovation. With this in mind, we develop a taxonomy of the relevant literature in strategy, economics, product development, and technology management. We then propose some principles for modeling innovation and technological change in a manner that brings together these fields of study.

Business Process technology has long been discussed in various business process methodologies with diverse perspectives. Among them, the discussions on were mainly limited only in effectively fulfilling functional, informational and organizational aspects. For enriching the discussion scope, from DEMO (Design and Engineering Method for Organizations) perspective, this research extends to capture both human interactions and human capabilities aspects in the business process and the relating modeling methodology is also provided. For contextualizing our proposal, RPA (Robotic Process Automation), as one of the typical new application in freeing human workers from tedious and repetitive tasks, is adopted as an illustration example of our artifact development. Also, our proposed modeling methodology is evaluated in a deep-dive field study with a Chinese Bank X to testify the utility in analyzing and identifying applicable tasks for RPA adoptions and eventually delivering the business process model.

✷ To reduce costs and increase effectiveness, a new theory is being sought to transform teams, enterprises, and systems with computational approaches of complex social behavior that create "smart" systems. A new theory is necessary because, unlike the physical sciences, the economic, organizational, and, in general, social sciences have no overarching theory of fundamental principles that build from individuals to collectives. Instead, social science is mostly a-theoretical, derived primarily from ad hoc studies of individuals. Many of the "rational" results emerging from methodological individualism models at the collective level are misleading, such as collaboration, supposedly associated with increased trust and social well-being; instead, we have found that the more collaboration is isolated from competition, the more knowledge generation is reduced, illusions increased, and social welfare made dysfunctional. With our theory, still crude at this stage of development, using bi-stability, a simplified form of interdependence, we have constructed a theory of the dynamics of collectives that naturally arise from illusions along with natural measures for the metrics of organizational performance based on relative (entropy) darkness. However, at the unit level, unlike building a bridge or robot, while predictions about social behavior are possible, our theory of interdependent uncertainty indicates that traditional explanations of social behavior are both unavoidable and irreducibly incomplete. We discuss the implications for enterprise transformation. Our theory will be applied in a future companion article.

This paper analyses the key factors for the adoption of the new automobile modular platforms through an eclectic perspective linking the product architecture with the manufacturing network approach. An exploratory analysis of the European production networks of seven automobile manufacturers shows that the benefits of the modular platforms' adoption depend on two factors: the degree of platform modularity and the manufacturing issues of each carmaker-product portfolio, production volumes and network size. The results indicate that the degree of modularity of the platform chosen should be aligned with the manufacturing issues; otherwise, benefits might not reach expectations.

Business Process technology has long been discussed in various business process methodologies with diverse perspectives. Among them, the discussions on were mainly limited only in effectively fulfilling functional, informational and organizational aspects. For enriching the discussion scope, from DEMO (Design and Engineering Method for Organizations) perspective, this research extends to capture both human interactions and human capabilities aspects in the business process and the relating modeling methodology is also provided. For contextualizing our proposal, RPA (Robotic Process Automation), as one of the typical new application in freeing human workers from tedious and repetitive tasks, is adopted as an illustration example of our artifact development. Also, our proposed modeling methodology is evaluated in a deep-dive field study with a Chinese Bank X to testify the utility in analyzing and identifying applicable tasks for RPA adoptions and eventually delivering the business process model.

Enterprises increasingly execute complex transformations, such as mergers and splits, chain redesign, sharing and sourcing, and the rationalization of products, processes and applications. Its consequences are seldom sufficiently timely and completely discerned, while this is essential for governing such a transformation. Already in a small example we can see why Enterprise Ontology, as defined in DEMO (Design & Engineering Methodology for Organizations) delivers a clear and valuable instrument for transformation governance. Especially DEMO's Construction Model, which is the most abstract ontological aspect model, combines high expressiveness with a high Return On Modeling Effort (ROME).

The digital transformation is forcing organizations to change towards more data-driven business models. In this paper, we propose a conceptual framework that explains the role of innovation capabilities as a mediator between big data and business model. Using the design science research method approach, we built the framework based on the existing literature. We then applied the framework to the real-world context with three firms and refined it based on the feedback. This study contributes to big data research by pointing out the role of human and data-driven innovation capabilities in the big data value creation process. The developed framework is practitioner oriented, offering a systematic approach towards the development of big data capabilities.

Big data is an emerging research area where common terminology is still evolving. Different perspectives to the research area and terminology exist, but a common definition for big data does not exist. We have performed a systematic mapping study in order to identify different big data definitions and their perspectives. As a result, we present a state-of-the-art review of the current status in big data definitions, discuss the shortcomings of the current definitions, and propose possible solutions for the shortcomings. The paper contributes to the emerging big data research by analyzing current definitions of big data from different perspectives, suggesting enhancement to the terminology as well as pointing out new research avenues. In addition, the article helps new researchers and practitioners to understand what big data is, and bridges the knowledge between theory and practice.

This research stems from the disruptive phenomenon known as digital transformation, i.e. the pervasive use of digital technologies in order to add value in business. As a side effect of digital transformation, vast amounts of various types of data are generated at a fast pace. This data is known as big data. The data is the root source of added value that businesses look for. Big data represents first and foremost a major paradigm shift, a new way to view businesses, enabled by related technology. However, the paradigm shift towards data-oriented business models and processes is challenging to incumbent enterprises. The aim of this research is to help incumbents to move towards datadriven business models and processes. This dissertation is based on articles published in scientific journals. The articles are presented in the Publications section of this dissertation. Each of the articles applied different research methods, which is justified by the fact that big data is an emerging concept. The approaches included a literature review, a survey and a case study, as well as algorithmic approaches. Together the articles explore the big data landscape from several angles, both from the theoretical and practical viewpoints. The results can be viewed as a high-level framework that addresses the primary research question-understanding and utilising big data in the transformation process towards big data driven business-by explaining the phenomenon as well as the value creation processes and connecting theoretical aspects to practice. The theoretical foundations of this dissertation combine strategic management, data-driven innovations and big data in a way that helps to understand the digital transformation process. This dissertation explains, how big data value creation mechanisms work. It helps to understand the nature of the big data phenomenon and provides building blocks and guidance for practitioners. The results suggest that big data must be seen as a business initiative instead of technological matter and strengthen the perception that big data in general and data-driven innovation in particular are potential sources of added value.

Elegance is a term frequently associated with aesthetics in design. It typically connotes simplicity, beauty, and grace. When it comes to complex systems, it also connotes predictable behavior, power, and creative functionality. Elegance is what separates the merely functional from the engaging. An elegant design usually has a thematic vision that drives its creation. It engages both designers and users and supports creative exploration on their part. The process of elegant design is an iterative, creative process that exploits systems thinking, probing questioning, and appropriate analogies and metaphors to gain insights that can be transformed novel solutions. This paper provides key insights into elegant systems design and characteristics of elegant systems designers. It offers a heuristics‐driven elegant systems design process along with metrics for assessing elegance. © 2012 Wiley Periodicals, Inc. Syst Eng 15

This article reviews the histories of 15 turnaround cases in the agricultural equipment and automotive industries and identifies certain consistencies that will be useful to practicing managers and directors, and to students of turnarounds. Successful Unsuccessful Firms Firms Sample Size (Years) 55 60 Mean (IV) 6.74%-2.94% Standard Deviation '(SD) 6.52% 9.98% T Ratio (T) 3.97 Significance P< 0.001 i 'After tax profit as a per cent of revenue successful and unsuccessful cases during the period of recovery.

Prompted by difficulties inherent to causal analysis in problem formulation, and by a need for more formal and robust strategy and transformation design tools and frameworks, this article introduces a procedure for modeling strategic problems in the Systems Modeling Language (SysML). As a test bed for the procedure, we used the widely available Robin Hood strategic management case study. The modeling process fostered an enhanced understanding of the nature of the problem, and the resulting model proved rich and complex. The difficulties stemming from causal analysis were absent altogether, thus showing that SysML provides a good basis upon which to build a non-causal, systemic strategy and transformation design framework.

Physician certification boards are an intrinsic part of medical professionalism, and the public is their key stakeholder. A decade ago, the 24 boards of the American Board of Medical Specialties committed to moving beyond the summative evaluation of physicians to a process of continuously evaluating and improving the care they deliver. The American Board of Family Medicine (ABFM) has been a leader in this change and is making strategic investments in the next major evolution of continuous certification. Physicians are frustrated with the pace of change, inability to reliably assess and change their practices, and the perceived risk to both income and professional autonomy. Certifying boards are natural targets for that frustration. Certifying boards have an opportunity to support physicians in improving the quality and safety of healthcare and appeal to physicians' intrinsic motivation for doing so. The ABFM is not retreating from that challenge but is instead listening carefully to family physicians and making strategic investments to evolve. The ABFM is the first certifying board to launch a registry that is designed to support physician capacity for quality assessment, improvement, data-reporting requirements, and population management. It also supports more effective measure development and research. The ABFM aims to help physicians maintain the privilege of self-governance by helping them continuously earn it.

Traditional business process-based discrete event simulation is not sufficiently powerful to support change-related business process reengineering (BPR). The simulation methods are inadequate for describing large, complex systems and are difficult to change so as to simulate new BPR designs. The limitations are caused by (1) focusing on workflow; (2) low-abstraction conceptual models; (3) and a lack of separate opinions on design and implementation. Our research is based on enterprise engineering, a construction-based approach, rather than workflow. By clarifying the differences between and dependencies of the ontological and implementation models, this research proposes a generic framework for generating a modularized and component-based simulation model with increased reusability as well as with the capacity to make controllable changes in enterprise simulation. The method is assumed to assist BPR by reducing complexity and through its focus on enterprise engineering-based design thinking and human-centered interactions.

The paper examines how the upward and downward strategic influences of the head of the BI unit in the case organization have evolved over time and the BI perspective became legitimate in the organization. The analysis covers a decade long period of time. We engaged in an Action Research (AR) inquiry where the change process was explored through the first-hand experiences of one of the co-authors. The model of the strategic agency of middle managers was applied in the analysis. We analyse the evolution as well as the enablers and constraints of the strategic agency of the head of the BI unit in the case organisation and identify the type of strategic agency exhibited in the case.