This book aims to revisit the "traditional" interaction between channel strategies and the marketing mix in a connected world. In particular, it focuses on the following four dimensions in this context: Consumers, Products, Value Proposition and Sustainability. Keeping in mind the growing digitalization of business processes in the retail world and the move towards omni-channel retailing, the book introduces the state-of-the-art academic and practitioner studies along these dimensions that could enhance the understanding of the potential impact that new technologies and strategies can have on practice in the near future. When launching a new product/service to market, firms usually consider various components of the marketing mix to influence consumers' purchase behaviors, such as product design, convenience, value proposition, promotions, sustainability initiatives, etc. This mix varies depending on the specific channel and consumer niche that the firm is targeting. But this book shows how channel strategy also influences the effectiveness in utilizing the marketing mix to attract potential customers.

This shortform book presents key peer-reviewed research selected by expert series editors and contextualised by new analysis from each author on government intervention and unexpected consequences in industrial history. With contributions on organisational structure, the quality of corporate governance, protectionism, the shareholder value model, and economic nationalism, this volume provides an array of fascinating insights into industrial history. Of interest to business and economic historians, this shortform book also provides analysis and illustrative case studies that will be valuable reading across the social sciences.

The well-ordered, fully aligned view of organization and management practice, with its unfailingly positive results, bears little relationship to the world that managers and others experience every day. This straight-line, 'do this and you'll get that' idealization is far removed from the wiggly reality. Despite this, the former continues to dominate the ways in which management is spoken about and judged in formal organizational arenas and wider society. This creates unrealistic expectations of what managers (from CEO to the front line) can sensibly achieve independently of the actions of others. Crucially, too, it distorts the ways in which they and others account formally for their actions. And so, the fantasy continues. Against this background, the book offers a radically different way of thinking about, and engaging with, the irreducible complexity of organization and management practice. Using straightforward language throughout, it sets out to help managers and others to become consciously aware of what they already know deep down about how organization works and what they - and everyone else - are actually doing in practice. It then offers a practical approach to everyday practice that takes complexity seriously. Armed with these new insights, readers will be better placed to apply their innate understanding and practical judgement to the demands that they and others face day to day. Whether these arise from their roles as managers, other practitioners, policy makers, regulatory authorities, or participants more generally.

This book provides students with an in-depth understanding of the concepts, frameworks and processes used to analyze and present visual data for better decision-making. Expert contributors provide guidance in translating complex concepts from large data sets and how this translation drives management practice. The book's first part provides a descriptive consideration of state-of-the-art science in visual design. The second part complements the first with a rich set of cases and visual examples, illustrating development and best practice to provide students with real-world context. Through their presentation of modern scientific principles, the editors inspire structured discussions of audience and design, recognizing differences in need, bias and effective processes across contexts and stakeholders. This cutting-edge resource will be of value to students in business analytics, business communication and management science classes, who will learn to be capable managers through the effective and direct visual communication of data. Researchers and practitioners will also find this an engaging and informative book.

Certain consultants argue leaders can quickly, easily, and considerably alter their organization cultures to improve performance. Conversely, field researchers have described situations where leaders could do little to alter the existing organization culture. Between these extreme positions, a spectrum of varying degrees of leader influence exists, and organizations fall at various places along this spectrum. This book presents five field studies dealing with team, service, and sales cultures where both expected and unexpected outcomes arose. In multiple instances, leaders hoped showing some employee appreciation would compensate for offering below market average wages. Several leadership groups were prospering based on cost cuts or increased sales. Those below often had their work intensified and they were experiencing greater stress. Eight paradoxical situations were uncovered and the interpretations of the participants were based in part on their personal work histories and the history of their current organization. In each case, evidence of employee informal organization and managerial operating cultures were documented. Analyzing Organization Cultures uses detailed case studies of five work organizations to offer a comparative approach to analyzing organizational culture. It shows the latest state of knowledge on the topic and will be of interest to researchers, academics, and students in the fields of organizational studies, management history, human resource management, and organizational theory.

Sustainable Production and Logistics: Modeling and Analysis Subject Guide: Engineering - Industrial & Manufacturing This book presents issues faced by planners of production and distribution operations in terms of smart manufacturing and sustainability, using efficient quantitative techniques in a variety of decision-making situations. Addressing the state-of-the-art of the smart and sustainable sides of production and distribution planning operations, it highlights how a current issue can be effectively approached and what particular quantitative technique can be used. The book goes on to provide a foundation in the new and fast-growing digital journey, and includes logistics 4.0 inside Industry 4.0, along with case studies. The information in this book is useful worldwide, especially in the Americas, Europe, Turkey, and Japan. It is written for academicians, researchers, practitioners, and students.

This book is based on ethnographic research from 2001-2, during Bank of Scotland's first year of merger with Halifax to form HBOS. The research is revisited from the present perspective in the wake of the global banking and financial crisis that undermined HBOS in 2008. This historical perspective on the ethnographic data is used to explore: people's responses to the pressures of heightened competition and organisational change; mutual and sometimes antagonistic perceptions of Scottish and English identities across the two merged banks; conflicting evaluations of national and organisational cultures; and the challenges of integrating ethnographic and historical perspectives in a single study. As an historical ethnography it 'salvages' a disappearing culture of Scottish and UK banking, disintegrated by neoliberal processes. -- .

Closed loop supply chains and their management have become mandatory for firms to stay competitive and profitable. This book provides insights into designing supply chain networks by understanding and incorporating key return parameters into the network design, which will affect profitability. The book discusses how customer categories and their acceptance behavior are incorporated into the network design. It also shows how to analyze the interaction of parameters on supply chain network design and profitability, offers modeling framework for incorporating uncertainties in the return product parameters, and shows how to design a robust network. Invaluable for managers in designing a sustainable, robust, and profitable supply chain network and ideal for managers, practitioners, and researchers in the area of supply chain network design and optimization.

"Design Engineering for Industry 4.0 (DE4.0) represents the 'human-cyber-physical view of the systems realization ecosystem "that is necessary to accommodate the drivers of Industry 4.0 (IoX) and provide an open ecosystem for the realization of complex systems. Seamless integration of digital threads and digital twins throughout the product design, the development and fulfillment lifecycle; the ability to accommodate diverse and rapidly changing technologies; and the mechanisms to facilitate the creation of new opportunities for the design of products, processes, services, and systems are some of the desired characteristics of DE4.0." Jiao, R., Commuri, S. Panchal, J., Milisavljevic-Syed, J, Allen, J.K., Mistree, F. and Schaefer, D., "Design Engineering in the Age of Industry 4.0," ASME Journal of Mechanical Design, 143(7), 070801, 25 pages. In keeping with the Design Engineering 4.0 construct the authors describe architecting a computer platform to support human designers make decisions associated with the realization of complex engineered systems. The platform is designed to facilitate end-to-end digital integration, customization and personalization, agile collaboration networks, open innovation, co-creation and crowdsourcing, product servitization and anything-as-a-service. Recognizing that simulation models are abstractions of reality the authors opt for a satisficing strategy instead of an optimization strategy. They include fundamentals and then describe tools for architecting a knowledge-based platforms for decision support. Challenges associated with developing a computational platform for decision support for the realization of complex engineered systems in the context of Design Engineering 4.0 are identified. Constructs for formulating design decisions (e.g., selection, compromise, and coupled decisions), knowledge modelling schemes (e.g., ontologies and modular templates), diagrams for designing decision workflows (e.g., the PEI-X diagram), and some analytical methods for robust design under uncertainty are presented. The authors describe integrating the knowledge-based platform to architect a cloud-based platform for decision support promoting co-design and cloud-based design communication essential for mass collaboration and open innovation for Design Engineering 4.0. This book is a valuable resource for researchers, design engineers, and others working on pushing the boundary of digitized manufacturing to include Design Engineering 4.0 principles in designing products, processes, and services.

Causal analytics methods can revolutionize the use of data to make effective decisions by revealing how different choices affect probabilities of various outcomes. This book presents and illustrates models, algorithms, principles, and software for deriving causal models from data and for using them to optimize decisions with uncertain outcomes. It discusses how to describe and summarize situations; detect changes; evaluate effects of policies or interventions; learn what works best under different conditions; predict values of as-yet unobserved quantities from available data; and identify the most likely explanations for observed outcomes, including surprises and anomalies. The book resents practical techniques for causal modeling and analytics that practitioners can apply to improve understanding of how choices affect probabilities of consequences and, based on this understanding, to recommend choices that are more likely to accomplish their intended objectives.The book begins with a survey of modern analytics methods, focusing mainly on techniques useful for decision, risk, and policy analysis. Chapter 2 introduces free in-browser software, including the Causal Analytics Toolkit (CAT) software, to enable readers to perform the analyses described and to apply modern analytics methods easily to their own data sets. Chapters 3 through 11 show how to apply causal analytics and risk analytics to practical risk analysis challenges, mainly related to public and occupational health risks from pathogens in food or from pollutants in air. Chapters 12 through 15 turn to broader questions of how to improve risk management decision-making by individuals, groups, organizations, institutions, and multi-generation societies with different cultures and norms for cooperation. These chapters examine organizational learning, community resilience, societal risk management, and intergenerational collaboration and justice in managing risks.

This book offers an easy-to-use and practice-oriented reference guide to mathematical averages. It presents different ways of aggregating input values given on a numerical scale, and of choosing and/or constructing aggregating functions for specific applications. Building on a previous monograph by Beliakov et al. published by Springer in 2007, it outlines new aggregation methods developed in the interim, with a special focus on the topic of averaging aggregation functions. It examines recent advances in the field, such as aggregation on lattices, penalty-based aggregation and weakly monotone averaging, and extends many of the already existing methods, such as: ordered weighted averaging (OWA), fuzzy integrals and mixture functions. A substantial mathematical background is not called for, as all the relevant mathematical notions are explained here and reported on together with a wealth of graphical illustrations of distinct families of aggregation functions. The authors mainly focus on practical applications and give central importance to the conciseness of exposition, as well as the relevance and applicability of the reported methods, offering a valuable resource for computer scientists, IT specialists, mathematicians, system architects, knowledge engineers and programmers, as well as for anyone facing the issue of how to combine various inputs into a single output value.

This handbook aims to highlight fundamental, methodological and computational aspects of networks of queues to provide insights and to unify results that can be applied in a more general manner. The handbook is organized into five parts:

Part 1 considers exact analytical results such as of product form type. Topics include characterization of product forms by physical balance concepts and simple traffic flow equations, classes of service and queue disciplines that allow a product form, a unified description of product forms for discrete time queueing networks, insights for insensitivity, and aggregation and decomposition results that allow sub networks to be aggregated into single nodes to reduce computational burden.

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Part 2 looks at monotonicity and comparison results such as for computational simplification by either of two approaches: stochastic monotonicity and ordering results based on the ordering of the process generators, and comparison results and explicit error bounds based on an underlying Markov reward structure leading to ordering of expectations of performance measures.

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Part 3 presents diffusion and fluid results. It specifically looks at the fluid regime and the diffusion regime. Both of these are illustrated through fluid limits for the analysis of system stability, diffusion approximations for multi-server systems, and a system fed by Gaussian traffic.

Part 4 illustrates computational and approximate results through the classical MVA (mean value analysis) and QNA (queueing network analyzer) for computing mean and variance of performance measures such as queue lengths and sojourn times; numerical approximation of response time distributions; and approximate decomposition results for large open queueing networks.

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Part 5 enlightens selected applications as loss networks originating from circuit switched telecommunications applications, capacity sharing originating from packet switching in data networks, and a hospital application that is of growing present day interest.

The book shows that the intertwined progress of theory and practice will remain to be most intriguing and will continue to be the basis of further developments in queueing networks."

One current challenge of conducting research from the leadership-as-practice perspective is a practical one: how to capture and analyse the elusive practice of leadership within the web of mundane organising processes. Although a number of researchers have attempted to address the issue, there is not yet a definitive 'how to' guide to making sense of the empirical manifestations of leadership practices. The book responds directly to this challenge and offers a theoretical framework and practical guidance to capturing, identifying and analysing evidence of leadership practice emergence; and provides implications of this approach for leadership academics and practitioners. The developed framework enables a method for understanding these leadership instances as they are enacted by individuals within and against the evolving activities of their day-to-day work. The framework is underpinned by cultural-historical activity theory and critical realism and it conceptualises leadership practice by placing agents' actions and interactions within the context of their relationships, objectives, experiences, material and non-material artefacts and wider organising processes and organisational structures; work that has not yet been undertaken in the field. It offers a strong theoretical foundation for further development of our understanding of leadership-as-practice, providing a methodological guidance for undertaking leadership-as-practice research, and enables a discussion on the variety of underlying processes and elements as they emerge from empirical observations. It will be of value to researchers, academics, professionals, and students in the fields of business and management with a particular interest in management theory, organisational studies, and leadership research.

The goal of this book is to publish the latest mathematical techniques, research, and developments in engineering. This book includes a comprehensive range of mathematics applied in engineering areas for different tasks. Various mathematical tools, techniques, strategies, and methods in engineering applications are covered in each chapter. Mathematical techniques are the strength of engineering sciences and form the common foundation of all novel disciplines within the field. Advanced Mathematical Techniques in Engineering Sciences provides an ample range of mathematical tools and techniques applied across various fields of engineering sciences. Using this book, engineers will gain a greater understanding of the practical applications of mathematics in engineering sciences. Features Covers the mathematical techniques applied in engineering sciences Focuses on the latest research in the field of engineering applications Provides insights on an international and transnational scale Offers new studies and research in modeling and simulation

This book covers the issues related to optimization of engineering and management problems using soft computing techniques with an industrial outlook. It covers a broad area related to real life complex decision making problems using a heuristics approach. It also explores a wide perspective and future directions in industrial engineering research on a global platform/scenario. The book highlights the concept of optimization, presents various soft computing techniques, offers sample problems, and discusses related software programs complete with illustrations. Features Explains the concept of optimization and relevance to soft computing techniques towards optimal solution in engineering and management Presents various soft computing techniques Offers problems and their optimization using various soft computing techniques Discusses related software programs, with illustrations Provides a step-by-step tutorial on how to handle relevant software for obtaining the optimal solution to various engineering problems

Diverse kinds of knowledge are vital for each organization that would successfully compete today in an international scenario. The emergent relevance of knowledge and its management in an even more complex environment opens up the possibility to analyze, investigate and deepen our understanding on different aspects related to several functional areas in business management. Nowadays, firms that create new knowledge and apply it effectively and efficiently will be successful at creating competitive advantages. The choices of the firms in selecting and applying different knowledge process (such as knowledge sourcing, transferring and exploiting) as well as knowledge tools may be crucial. Thus, the role of knowledge as the key source of potential advantage for organizations and indeed whole economies is still a hot debate in the international landscape. This book develops insights for the management of knowledge in cross-functional business areas to originate an innovative approach to the classical Knowledge Management (KM) field. This book provides a fresh perspective on different knowledge related topics in an international landscape, highlighting the key role of knowledge and its management in business activities. Overall, the primary aim of this book is to extend our understandings on how KM can be helpful in several cross-functional management areas, such as strategic management, finance, HRM and innovation as well as in different business circumstances such as M&A, internationalization processes and risk management.

This book provides a detailed introduction to the theoretical and methodological foundations of production efficiency analysis using benchmarking. Two of the more popular methods of efficiency evaluation are Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA), both of which are based on the concept of a production possibility set and its frontier. Depending on the assumed objectives of the decision-making unit, a Production, Cost, or Profit Frontier is constructed from observed data on input and output quantities and prices. While SFA uses different maximum likelihood estimation techniques to estimate a parametric frontier, DEA relies on mathematical programming to create a nonparametric frontier. Yet another alternative is the Convex Nonparametric Frontier, which is based on the assumed convexity of the production possibility set and creates a piecewise linear frontier consisting of a number of tangent hyper planes. Three of the papers in this volume provide a detailed and relatively easy to follow exposition of the underlying theory from neoclassical production economics and offer step-by-step instructions on the appropriate model to apply in different contexts and how to implement them. Of particular appeal are the instructions on (i) how to write the codes for different SFA models on STATA, (ii) how to write a VBA Macro for repetitive solution of the DEA problem for each production unit on Excel Solver, and (iii) how to write the codes for the Nonparametric Convex Frontier estimation. The three other papers in the volume are primarily theoretical and will be of interest to PhD students and researchers hoping to make methodological and conceptual contributions to the field of nonparametric efficiency analysis.

Knowledge capital is at the core of the socio-economic global system. Profit and not-for profit firms, institutions, and organizations, in general, face unique opportunities and threats related to knowledge management. Digital technologies and digital transformation offer a wide array of opportunities for value creation. At the same time, organizations need to foster newer, faster, and more dynamic ways of mobilizing and managing knowledge. Emerging trends, such as artificial intelligence, collective intelligence, agile methodologies, open innovation, and co-creation enable new business models and managerial paradigms that need to be understood and conceptualized. This book offers an extensive overview of the most recent trends in knowledge management and the most advanced theoretical approaches, while, at the same time, providing a wide array of case studies and evidence-based knowledge management practices. It takes into account the interrelation between ICT and knowledge management challenges, in terms of human/non-human interactions, which requires extraordinary organizational change and renewal. Further, the book presents an up-to-date examination of and guidance for the implementation of knowledge management in an era of unprecedented human/non-human interaction. The book conveys the results of more than a decade of research and applied experience in the field of knowledge management carried out by the author. It is intended not only for students and academics but also for managers and practitioners who are interested in deepening their understanding of knowledge and learning.

This book begins by introducing the topic of knowledge in literature, including its scientific foundations. Due to the ever-increasing number of scientific publications, literature reviews are becoming more and more essential to stay updated. Literature Reviews describes an innovative system for creating systematic literature reviews, through reviewing, analyzing, and synthesizing scientific and technological literature. It then discusses systematic literature reviews, content analysis, and literature synthesis separately, before presenting the methodology to combine them in one process. It showcases computational tools to aid in this technique and offers examples of the method in action. Finally, the book takes a new of future developments in the subject. This book is of interest to graduate students, as well as researchers and academics, helping them to deepen insights and improve skills needed to conduct thorough literature reviews.

This book presents some twenty case studies, showing how companies in different industry sectors and of different sizes make advances in Product Lifecycle Management (PLM). Like the author's previous volumes, this book provides a valuable resource for those wishing to learn about PLM and how to implement and apply it in their companies. Helping readers to * learn about implementing and benefiting from PLM; * learn about good PLM solutions and best practice; * improve their planning and decision-making abilities; * benefit from the lessons learned by the companies featured in the case studies; * proceed faster and further with PLM the book presents effective PLM solutions and best practices. At the same time, the case studies included demonstrate how different companies implement and benefit from PLM. Each case study is addressed in a separate chapter and details a different situation, enabling readers to put themselves in the situation and think through different actions and decisions. A valuable resource for PLM team managers and employees in engineering and manufacturing companies, the book is also of interest to researchers and students in industrial engineering fields.

This book presents best practices involving applications of decision sciences, business tactics and behavioral sciences for COVID-19. Addressing concrete problems in these vital fields, it focuses on theoretical and methodological investigations of managerial decisions that drive production and service enterprises' productivity and success. Moreover, it presents optimization techniques and tools that can also be adopted for other applications in various research areas after a thorough analysis of the specific problem. The book is intended for researchers and practitioners seeking optimum solutions to real-life problems in various application areas concerning COVID-19, helping them make scientifically founded decisions.

This book presents a collection of essays written by leading researchers to honor Roman Slowinski's major scholarly interests and contributions. He is well-known for conducting extensive research on methodologies and techniques for intelligent decision support, where he combines operational research and artificial intelligence. The book reconstructs his main contributions, presents cutting-edge research and provides an outlook on the most promising and advanced domains of computer science and multiple criteria decision aiding. The respective chapters cover a wide range of related research areas, including decision sciences, ordinal data mining, preference learning and multiple criteria decision aiding, modeling of uncertainty and imprecision in decision problems, rough set theory, fuzzy set theory, multi-objective optimization, project scheduling and decision support applications. As such, the book will appeal to researchers and scholars in related fields.

This book provides a thorough review of tested qualitative methods often used in organization studies, and outlines the challenges and essential requirements of designing a qualitative research project. The methods examined include case studies, observation, interviewing and the repertory grid technique. By highlighting certain key 'rules' for carrying out qualitative research and describing issues that should be avoided, this second volume of Qualitative Methodologies in Organization Studies is essential reading for academics and researchers who wish to understand the current state of qualitative data gathering within organization studies. Those exploring organization studies will find this two-volume collection extremely valuable as it contains robust contributions from highly-skilled authors who are actively researching in this field.

Open internationalization is a concept that brings a new perspective on the process of firm internationalization. As theories of internationalization show, some companies expand abroad only on their own, known as closed internationalization, while others combine their resources with those of other firms or use their networks for facilitating foreign implantation, known as open internationalization. Parallel to the development of the well-known concept of open innovation, open internationalization can be conceived as a meta-model for understanding companies' expansion abroad. This book gathers a selection of contemporary research works dedicated to open internationalization, either seen as a way to analyze expansion in foreign countries, or as a way to investigate the management of geographically dispersed activities. All the authors of the chapters are researchers specialized in the internationalization field. Readers will benefit from this new lens for understanding, studying or practising international business, from the decision to go abroad to its implementation and its efficiency. Open Internationalization Strategy includes both academic empirical investigations and literature reviews on specific topics, making it valuable to researchers, academics, managers, and students in the fields of business and management history, international business, organizational studies, and economics.

This book combines two distinctive topics: data science/image analysis and materials science. The purpose of this book is to show what type of nano material problems can be better solved by which set of data science methods. The majority of material science research is thus far carried out by domain-specific experts in material engineering, chemistry/chemical engineering, and mechanical & aerospace engineering. The book could benefit materials scientists and manufacturing engineers who were not exposed to systematic data science training while in schools, or data scientists in computer science or statistics disciplines who want to work on material image problems or contribute to materials discovery and optimization. This book provides in-depth discussions of how data science and operations research methods can help and improve nano image analysis, automating the otherwise manual and time-consuming operations for material engineering and enhancing decision making for nano material exploration. A broad set of data science methods are covered, including the representations of images, shape analysis, image pattern analysis, and analysis of streaming images, change points detection, graphical methods, and real-time dynamic modeling and object tracking. The data science methods are described in the context of nano image applications, with specific material science case studies.