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The purpose of this study is to synthesize the literature on the topic of strategic renewal by identifying the key dimensions of extant research and the connections between fragmented research domains.

This study applies systematic literature review to identify the level of consistency and generalizability of research findings across existing studies in a comprehensive manner.

This study identifies six main themes of strategic renewal in the extant literature: (1) antecedents, (2) initiation, (3) logic, (4) structure, (5) process and (6) outcomes of strategic renewal.

By integrating the current streams of research, the review offers a conceptual model of strategic renewal that maps the current state of the research and provide insights into key themes for the future research.

This study, identifies connections between fragmented research domain and offers a conceptual framework of strategic renewal.

This paper aims at developing a behavioral agent-based model for interacting financial markets. Additionally, the effect of imposing Tobin taxes on market dynamics is explored.

The agent-based approach is followed to capture the highly complex, dynamic nature of financial markets. The model represents the interaction between two different financial markets located in two countries. The artificial markets are populated with heterogeneous, boundedly rational agents. There are two types of agents populating the markets; market makers and traders. Each time step, traders decide on which market to participate in and which trading strategy to follow. Traders can follow technical trading strategy, fundamental trading strategy or abstain from trading. The time-varying weight of each trading strategy depends on the current and past performance of this strategy. However, technical traders are loss-averse, where losses are perceived twice the equivalent gains. Market makers settle asset prices according to the net submitted orders.

The proposed framework can replicate important stylized facts observed empirically such as bubbles and crashes, excess volatility, clustered volatility, power-law tails, persistent autocorrelation in absolute returns and fractal structure.

Artificial models linking micro to macro behavior facilitate exploring the effect of different fiscal and monetary policies. The results of imposing Tobin taxes indicate that a small levy may raise government revenues without causing market distortion or instability.

This paper proposes a novel approach to explore the effect of loss aversion on the decision-making process in interacting financial markets framework.

In addressing the future trajectory of knowledge management systems, this paper uses the psycho-social notion of generativity which recently stimulated contributions in technology and innovation for a holistic systemic knowledge management (KM) review. The purpose of this study is to identify current shortcomings and fixations together with their ramifying affordances, all enveloped within a novel KM concept and prototype-system-under-development.

It follows up on prior publications using design science research (DSR) methodologies in compliance with theory effectiveness, a principle expecting system designs to be purposeful in terms of utility and communication. The KM perspective taken prioritizes a decentralizing agenda benefiting knowledge workers while also aiming to foster a fruitful co-evolution with traditional organizational KM approaches.

The notions of generative fit and capacities in their technical, informational and social interpretations prove able to accommodate diverse KM models and to cumulatively synthesize a wide range of related concepts and perspectives. In the process, Nonaka’s renowned socialize, externalize, combine, internalize and Ba model is repurposed and extended to suggest a corresponding complementing seize, imbed, collate, encompass, effectuate workflow embedded in distinct digital ecosystems fully aligned to the diversity of the generative attributes introduced.

Although the prototype development is still in progress, the study conforms to the DSR practice to report on early visions of technology impact on users, organizations and society and also refers to and reflects on aspects of feasibility, suitability, acceptability and the system’s prospect as a general-purpose technology or disruptive innovation.

The paper transdisciplinarily integrates the well-established psychological notions of generativity into its newer digital and systemic KM dimensions. The resulting new insights transparently inform the concept and prototype design, present a holistic framework for individuals and organizations and suggest avenues for new KM applications and KM research directions inspired by the adopted and adapted novel generativity contexts.

The aim of this article is to present a model for the orchestration of dynamic capabilities (ODCs) in cleantech companies that aim to obtain competitive advantage in the market.

The authors present herein descriptive research guided by a qualitative multiple case study approach carried out with 12 cleantech companies.

The results have showed that the ODC model is present in the product/process cycle, thus providing new capabilities and generating sustainable competitive advantage through the research categories presented.

This study contributes to the literature on the ODCs through microfoundations based on evidence of companies inserted in technological and intensively dynamic contexts.

This article demonstrates, through the ODC model, the main capabilities and characteristics of the assets of cleantech companies and how the process of renewing competencies to obtain competitive advantage occurs.

The ODC model utilizes technological resources in the product/process cycle. Asset specificity and the capacity for innovation allow cleantech companies to explore regulatory loopholes, making their sustainable model innovative and obtaining competitive advantage through the renewal of entrepreneurial capabilities and competencies.

This study aims to analyze what promotes the adoption of open innovation (OI) in the foodservice sector. Specifically, it seeks to shed light on the bottom-up mechanisms (the microfoundations) that allow a foodservice firm to organize for OI.

The research design is an in-depth exploratory case study with 18 semi-structured interviews. The findings have been triangulated with documentation available on the corporate website, the project reports and direct observation. Data were analyzed using an inductive approach, coding individual interview transcripts.

This study identifies three categories of capabilities that have to be spread to different organizational levels: the capability to sense organizational triggers to change, to develop external collaborations and knowledge exchanges with different parties and the management's ability to be aware of organizational imperatives and the need to proceed with process adjustment. Results highlight the importance of sensing organizational triggers, allowing a quick switch between new strategies in implementing an OI approach. It was crucial for the company to co-develop new products and services with a large audience of stakeholders, not only limited to customers. The case remarks on the required ability of the organization and management team to activate mechanisms aimed at reconfiguring the competencies within each business unit, keeping an alignment with the needs of the stakeholders.

The study emphasizes the multi-level characteristics of OI and provides a framework for microfoundations on how to organize for OI. Results contribute to the recent debate on the skills and routines an organization should design and promote within their employees.

Arts and cultural activities have been illustrated to be beneficial for mental health service users. The purpose of this paper is to explore the benefits of museum visits and engage in arts activities for mental health service users.

Semi-structured interviews were conducted with 17 mental health service users in Denmark. A thematic approach was used to analyse the data and theoretical lens of sociological theories of institutional logics was employed to explore the findings.

These benefits are perceived to include empowerment and meaning in life, which are two of the core principles of recovery; arts engagement can, therefore, be a useful tool in recovery. The findings also show that the experience of visiting a museum was not always positive and depended upon the interaction with the museum educators.

The service users identified arts engagement as creating meaning in life and empowerment, which are two element in the conceptual framework, CHIME (an acronym for: Connectedness, Hope and optimism, Identity, Meaning in life and Empowerment), that describes the human process of recovery. The findings also highlighted that if museums want to engage positively with people with mental health problems and contribute to their recovery then the training of staff and the improvement of institutional approaches to support working with vulnerable people are essential.

The purpose of this paper is to explore two distinct subsets of dynamic capabilities that need to be deployed when pursuing innovation through inter-organizational activities, respectively, in the contexts of broad networks and specific alliances. The authors draw distinctions and explore potential interdependencies between these two dynamic capability reservoirs, by integrating concepts from the theoretical perspectives they are derived from, but which have until now largely ignored each other – the social network perspective and the dynamic capabilities view.

The authors investigate nanotechnology-driven R&D activities in the 1995–2005 period for 76 publicly traded firms in the electronics and electrical equipment industry and in the chemicals and pharmaceuticals industry, that applied for 580 nanotechnology-related patents and engaged in 2,459 alliances during the observation period. The authors used zero-truncated Poisson regression as the estimation method.

The findings support conceptualizing dynamic capabilities as four distinct subsets, deployed for sensing or seizing purposes, and across the two different inter-organizational contexts. The findings also suggest potential synergies between these subsets of dynamic capabilities, with two subsets being more macro-oriented (i.e. sensing and seizing opportunities within networks) and the two other ones more micro-oriented (i.e. sensing and seizing opportunities within specific alliances).

The authors show that firms differ in their subsets of dynamic capabilities for pursuing different types of inter-organizational, boundary-spanning relationships (such as alliances vs broader network relationships), which ultimately affects their innovation performance.

The authors contribute to the growing body of work on dynamic capabilities and firm-specific advantages by unbundling the dynamic capability subsets, and investigating their complex interdependencies for managing different types of inter-organizational linkages. The main new insight is that the “linear model” of generating more innovations through higher inter-firm collaboration in an emerging field paints an erroneous picture of how high innovation performance is actually achieved.

The purpose of this paper is to have a review on the analysis of information diffusion based on evolutionary game theory. People now get used to interact over social networks, and one of the most important functions of social networks is information sharing. Understanding the mechanisms of the information diffusion over social networks is critical to various applications including online advertisement and rumor control.

It has been shown that the graphical evolutionary game theory (EGT) is a very efficient method to study this problem.

By applying EGT to information diffusion, the authors could predict every small change in the process, get the detailed dynamics and finally foretell the stable states.

In this paper, the authors provide a general review on the evolutionary game-theoretic framework for information diffusion over social network by summarizing the results and conclusions of works using graphical EGT.

With the recent development of science and technology, research on information diffusion has become increasingly important.

To analyze the process of information diffusion, researchers have proposed a framework with graphical evolutionary game theory (EGT) according to the theory of biological evolution.

Through this method, one can study and even predict information diffusion.

This paper summarizes three existing works using graphical EGT to discuss how to obtain the static state and the dynamics of information diffusion in social network.

Since the last few decades, Artificial Neural Networks have been the center of attraction of a large number of researchers for solving diversified problem domains. Due to its distinguishing features such as generalization ability, robustness and strong ability to tackle nonlinear problems, it appears to be more popular in financial time series modeling and prediction. In this paper, a Pi-Sigma Neural Network is designed for foretelling the future currency exchange rates in different prediction horizon. The unrevealed parameters of the network are interpreted by a hybrid learning algorithm termed as Shuffled Differential Evolution (SDE). The main motivation of this study is to integrate the partitioning and random shuffling scheme of Shuffled Frog Leaping algorithm with evolutionary steps of a Differential Evolution technique to obtain an optimal solution with an accelerated convergence rate. The efficiency of the proposed predictor model is actualized by predicting the exchange rate price of a US dollar against Swiss France (CHF) and Japanese Yen (JPY) accumulated within the same period of time.