Qualitative Structural Model for Capabilities in Open Data Organizations

Open data is increasingly becoming an essential asset for many organizations. However, large numbers of organizations fall short when it comes to utilizing open data effectively to fully leverage the potential of it. There are ample evidences that this shortcoming is attributable to the poor understanding of what types of capabilities are required to successfully conduct data related activities. At the same time, research on open data capabilities and how they relate to one another remains sparse. Based on the theoretical foundation constructed from the integration of Capability-based Theory and Dynamic Capability Theory and, extant literature and interviews of leadership of open data organizations, we attempt to address this knowledge gap by investigating open data capabilities and relationships between them. Findings help validate the two theories in the open data organizations and reveal unknown knowledge about open data capability areas and how they affect one another

Absorptive capacity and relationship learning mechanisms as complementary drivers of green innovation performance

This paper aims to explore in depth how internal and external knowledge-based drivers actually affect the firms\u2019 green innovation performance. Subsequently, this study analyzes the relationships between absorptive capacity (internal knowledge-based driver), relationship learning (external knowledge-based driver) and green innovation performance. This study relies on a sample of 112 firms belonging to the Spanish automotive components manufacturing sector (ACMS) and uses partial least squares path modeling to test the hypotheses proposed. The empirical results show that both absorptive capacity and relationship learning exert a significant positive effect on the dependent variable and that relationship learning moderates the link between absorptive capacity and green innovation performance. This paper presents some limitations with respect to the particular sector (i.e. the ACMS) and geographical context (Spain). For this reason, researchers must be thoughtful while generalizing these results to distinct scenarios. Managers should devote more time and resources to reinforce their absorptive capacity as an important strategic tool to generate new knowledge and hence foster green innovation performance in manufacturing industries. The paper shows the importance of encouraging decision-makers to cultivate and rely on relationship learning mechanisms with their main stakeholders and to acquire the necessary information and knowledge that might be valuable in the maturity of green innovations. This study proposes that relationship learning plays a moderating role in the relationship between absorptive capacity and green innovation performance

Rethinking bank business models: the role of intangibles

<p>Purpose: This paper provides a new way of rethinking banking models by using qualitative research on intangibles. This is required because the banking sector has been transformed significantly by the changing environment over the past two decades. The 2007-2009 financial crisis also added to concerns about existing bank business models.</p> <p>Design/Methodology approach: Using qualitative data collected from interviews with bank managers and analysts in the UK, this paper develops a grounded theory of bank intangibles.</p> <p>Findings: The model reveals how intangibles and tangible/financial resources interact in the bank value creation process, how they actively respond to environmental changes, how bank intangibles are understood by external observers such as analysts, and how bankers and analysts differ in their views.</p> <p>Research implications: Grounded theory provides the means to further develop bank models as business models and theoretical models. This provides the means to think beyond conventional finance constructs and to relate bank models to a wider theoretical literature concerning intellectual capital, organisational and social systems theory, and ‘performativity’.</p> <p>Practical implications: Such development of bank models and of a systems perspective is critical to the understanding of banks by bankers, by observers and for their ‘critical and reflexive performativity’. It also has implications for systemic risk and bank regulation.</p> <p>Social implications: Improvement in bank models and their use in open and transparent processes are key means to improve public accountability of banks.</p> <p>Originality: The paper reveals the core role of intellectual capital (IC) in banks, in markets, and in developing theory and research at firm and system levels. </p&gt

A Primer on Intellectual Capital

{Excerpt} Born of the information revolution, knowledge management has arisen in response to the belated understanding that intellectual capital is a core asset of organizations and that it should be circumscribed better. From this perspective, it is the growing body of tools, methods, and approaches, inevitably underpinned by values, by means of which organizations can bring about and maximize a return on knowledge assets, aka intellectual capital. That, Thomas Stewart explained pithily (yet broadly) is organized knowledge that can be used to generate wealth. (Conversely, it also helps to think of what intellectual capital is not, that is, monetary or physical resources.) More specifically, aggregated intellectual capital comprises • Human capital—the cumulative capabilities and engagement of an organization\u27s personnel, rooted in tacit and explicit knowledge, that can be invested to serve the joint purpose. • Relational (or customer) capital—the formal and informal external relationships, counting the information flows across and knowledge partnerships in them, that an organization devises with clients, audiences, and partners to co-create products and services, expressed in terms of width (coverage), channels (distribution), depth (penetration), and attachment (loyalty). • Structural (or organizational) capital—the collective capabilities of an organization—any of them codified, packaged, and systematized, including its governance, values, culture, management philosophy, business processes, practices, research and development, intellectual property, performance metrics, and information systems, as well as the systems for leveraging them

Towards technological rules for designing innovation networks: a dynamic capabilities view.

Inter-organizational innovation networks provide opportunities to exploit complementary resources that reside beyond the boundary of the firm. The shifting locus of innovation and value creation away from the “sole firm as innovator” poses important questions about the nature of these resources and the capabilities needed to leverage them for competitive advantage. The purpose of this paper is to describe research into producing design-oriented knowledge, for configuring inter-organizational networks as a means of accessing such resources for innovation

Investigating the impact of networking capability on firm innovation performance:using the resource-action-performance framework

The author's final peer reviewed version can be found by following the URI link. The Publisher's final version can be found by following the DOI link.Purpose The experience of successful firms has proven that one of the most important ways to promote co-learning and create successful networked innovations is the proper application of inter-organizational knowledge mechanisms. This study aims to use a resource-action-performance framework to open the black box on the relationship between networking capability and innovation performance. The research population embraces companies in the Iranian automotive industry. Design/methodology/approach Due to the latent nature of the variables studied, the required data are collected through a web-based cross-sectional survey. First, the content validity of the measurement tool is evaluated by experts. Then, a pre-test is conducted to assess the reliability of the measurement tool. All data are gathered by the Iranian Vehicle Manufacturers Association (IVMA) and Iranian Auto Parts Manufacturers Association (IAPMA) samples. The power analysis method and G*Power software are used to determine the sample size. Moreover, SmartPLS 3 and IBM SPSS 25 software are used for data analysis of the conceptual model and relating hypotheses. Findings The results of this study indicated that the relationships between networking capability, inter-organizational knowledge mechanisms and inter-organizational learning result in a self-reinforcing loop, with a marked impact on firm innovation performance. Originality/value Since there is little understanding of the interdependencies of networking capability, inter-organizational knowledge mechanisms, co-learning and their effect on firm innovation performance, most previous research studies have focused on only one or two of the above-mentioned variables. Thus, their cumulative effect has not examined yet. Looking at inter-organizational relationships from a network perspective and knowledge-based view (KBV), and to consider the simultaneous effect of knowledge mechanisms and learning as intermediary actions alongside, to consider the performance effect of the capability-building process, are the main advantages of this research

"We are always after that balance":managing innovation in the new digital media industry

The pressure to innovate is growing as technology cycles change more rapidly. Organisations need to balance exploration and exploitation effectively if they are to heed the innovation imperative. Organisational ambidexterity is proposed as a means to achieve such balance with structural or contextual ambidexterity as possible choices. Yet how organisations become ambidextrous is an as yet underresearched area, and different industry sectors may pose different innovation challenges. Using the case study method, this paper examines how a computer games company responds to an industry-specific innovation challenge and how it endeavours to balance exploration and exploitation. The findings suggest that ambidexterity is difficult to achieve, and is fraught with organisational tensions which might eventually jeopardise the innovation potential of a company. The paper suggests that more qualitative research is needed to further our understanding of innovation challenges, innovation management and organisational ambidexterity