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Novel and emerging technologies such as cognitive analytics attract a lot of hype among academic researchers and practitioners. However, returns on investments in these technologies are often poor. So, identifying mechanisms through which cognitive analytics can add value to firms is a critical research gap. The purpose of this paper is to theorize how cognitive analytics technologies can enable the dynamic capabilities of sensing, seizing and reconfiguring for an organization.

This conceptual paper draws on the extant academic literature on cognitive analytics and related technologies, the business value of analytics and artificial intelligence and the dynamic capabilities perspective, to establish the role of cognitive analytics technologies in enabling the sensing, seizing and reconfiguring capabilities of an organization.

Through arguments grounded in existing conceptual and empirical academic literature, this paper develops propositions and a theoretical framework linking cognitive analytics technologies with organizations’ dynamic capabilities (sensing, seizing and reconfiguring).

This paper has critical implications for both academic research and managerial practice. First, the authors develop a framework using the dynamic capabilities theoretical perspective to establish a novel pathway for the business value of cognitive analytics technology. Second, cognitive analytics is proposed as a novel antecedent of the dynamic organizational capabilities of sensing, seizing and reconfiguring.

To the best of the authors’ knowledge, this is the first paper to theorize how cognitive analytics technologies can enable dynamic organizational capabilities, and thus add business value to an organization.

Interactive mobile technologies (IMT) offered to hotel guests during their stay represent an interesting development in consumer technologies in the hotel industry. Such technologies are designed to facilitate transactions and enhance the quality of guest experience. This research explains how hotel guests develop attitudes and intentions to use IMT in hotels. The paper aims to discuss these issues.

Using data from students enrolled in a large hospitality program located in the Southwestern USA, the study validates a variant of the technology acceptance model, extended with constructs such as cognitive absorption and security that capture better the context of IMT in hotels.

The conceptual model explained a large part of variability in intentions to use IMT. Among several predictors, cognitive absorption was the stronger predictor of attitudes. The analysis also revealed the dimensions of cognitive absorption as a second-order factor in the context of mobile commerce in the hotel industry.

This research offers a number of notable theoretical contributions. First, it provides an unique perspective on adoption of immersive technologies that enhance the experiential value of the hotel stay. Second, it revisits and validates the multidimensional construct of cognitive absorption. Finally, it ascertains the roles of cognitive absorption, playfulness, and security in the adoption of IMT.

This research provides specific suggestions to integrate IMT in hotels based on system characteristics and users’ perceptions.

To date, the research examining the immersive aspects of technology is scant. This research provides a novel platform for the systematic examination of the adoption of immersive technologies as they mediate the experiences in hotel service settings.

The evolving digital transformations of organizational processes involve vast complexities. Factors such as labor resources at the individual and team levels that integrate and utilize information resources and evolving technologies to achieve collective intelligence are essential to this process. In order to better understand evolving demands of labor resources, existing research regarding worker/technology interactions for firm performance must be implemented and adapted to the changing market. This paper provides a conceptual research model enabling organizations to better understand the integration of worker/team attributes with collaboration modes, information resources and augmented technologies that yield effective collective intelligence for decision-making.

This manuscript includes a literature review on worker/team attributes interfacing with various technology platforms and the creation of collective intelligence. It then reviews complementary research including leadership elements for organizational outcomes and introduces more current work involving a digital transformation. The literature review provides the underpinnings for a conceptual model that incorporates essential elements for the creation of collective intelligence for decision-making and adds factors that are relevant for digital transformations. These elements include augmented technologies including cognitive technologies, collaborative platforms and worker attributes (skills, social sensitivity, leadership) all of which illustrate components of intellectual capital.

The paper summarizes key findings of existing research in worker/team interactions with technology platforms on organizational performance and provides an applied, conceptual research model incorporating these findings, along with new elements in the digital era for better identifying new worker requirements.

The value of this work is the introduction of an applied conceptual model based on established literature findings that includes new technologies (e.g. cognitive technologies), collaboration modes and worker/team attributes to address the requirements of the evolving knowledge worker in the digital era. It provides a framework to better understand more optimal resource allocations for the creation of collective intelligence and integrates the model components within an intellectual capital framework.

The authors address how a combination of artificial intelligence (AI) and cognitive computing --- adaptive data management systems that monitor, analyze, make decisions and learn -- will transform businesses, work and customer offerings.

A survey of 6,050 C-suite executives worldwide identified a small group of cognitive innovators and revealed what they are doing differently.

Cognitive innovators identify customer satisfaction, retention, acquisition and revenue growth as the primary rationale for embracing cognitive technologies.

Cognitive computing systems are already helping make sense of the deluge of data spawned by ordinary commerce because they are able to adapt and learn.

The authors offer a four-step approach to cognitive computing innovation based on their research findings.

The purpose of this paper is to elucidate the emerging landscape of procurement analytics. This paper focuses on the following questions: what are the current and future state of procurement analytics?; what changes in the procurement process will be required to enable integration of analytical solutions?; and what future areas of research arise when considering the future state of procurement analytics?

This paper employs a qualitative approach that relies on three sources of information: executive interviews, a review of current and emerging technology platforms and a small survey of subject matter experts in the field.

The procurement analytics landscape developed in this research suggests that the authors will continue to see major shifts in the sourcing and supply chain technology environment in the next five years. However, there currently exists a low usage of advanced procurement analytics, and data integrity and quality issues are preventing significant advances in analytics. This study identifies the need for organizations to establish a coherent approach to collection and storage of trusted organizational data that build on internal sources of spend analysis and contract databases. In addition, current ad hoc approaches to capturing unstructured data must be replaced by a systematic data governance strategy. An important element for organizations in this evolution is managing change and the need to nourish an analytic culture.

While the majority of forward-looking research and reports merely project broad technological impact of cognitive analytics and big data, much of it does not provide specific insights into functional impacts such as the impact on procurement. The analysis of this study provides us with a clear view of the potential for business analytics and cognitive analytics to be employed in procurement processes, and contributes to development of related research topics for future study. In addition, this study suggests detailed implementation strategies of emerging procurement technologies, contributing to the existing body of the literature and industry reports.

This paper aims to focus on distributed technologies with the aim of highlighting their economic-organizational dimensions. In particular, the contribution first presents a deeper understanding of the nature and the dynamics of the economies and diseconomies that arise from the adoption and diffusion of distributed technologies. Second, it aims to shed light on the increasing tension between the hierarchy-based model of production and peer-to-peer (p2p) production, which involves the pervasive diffusion of distributed technologies.

Adopting an economic-organizational perspective, which is deeply rooted in the related extant literature, an analytically consistent model is developed to simultaneously take into account the following variables: adoption density independent variable) and economies of knowledge integration and organizational diseconomies (the costs of a loss of control and the costs of organizational decoupling and recoupling) as dependent variables.

Distributed technologies allow access to a large quantity and a wide variety of cognitive slacks that have not been possible until now. In doing so, they are leading the transition towards p2p. This is an emerging production paradigm that is characterized – with respect to mass production – by a shift in the relative importance of cognitive slack in comparison with tangible slack. Nevertheless, the unrestrainable diffusion of distributed technologies is not neutral for organizations. On the one hand, these technologies allow for the integration of economies of knowledge, and on the other hand, they involve organizational diseconomies that should not be ignored by managers and researchers.

This paper fills a gap in the literature by developing a consistent analytical framework that simultaneously takes into account the economies of knowledge integration and potential organizational diseconomies (the costs of coordination and the loss of control) that arise from the adoption and diffusion of distributed technologies.

This article attempts to match the future needs of older people with the possibilities arising from applications based on new technology.

This article examines the implications of novel applications for active ageing policy. These applications are forecast to arise from the convergence of two or more previously separated science disciplines and technologies, including information and communication technologies, nanotechnologies, biotechnology and cognitive sciences.

Research on converging applications (CA) is largely driven by health applications, and is likely to spill over into the older generation's specific needs. Today, older people's most urgent needs require little CA. In the future, however, the role of CA will become more important as technology develops and is more widely used.

Owing to demographic change and its expected social and economic implications, there is a need to investigate how upcoming applications could contribute to the future specific needs of the older population.

The purpose of this paper is to examine peer production (P2P) conceived as an ecosystem for value co-creation. First, this paper provides information on the specific P2P method for value co-creation, which is based on distributed technologies, cognitive slack and search for quality, to provide outputs that are open to continuous improvement. Second, aiming to fill the extant literature gap, this paper discusses the efficient dimension of P2P, providing a framework for the net benefit analysis of the economies and diseconomies that affect the value co-creation processes.

The paper identifies three main literature clusters that are focused on P2P, namely, economical, sociological and organizational clusters, and integrates them with the economics of organizational perspective to elicit information on the efficient dimension of P2P. This efficient dimension is expressed by a net benefit analysis of the economies and diseconomies that affect the P2P value co-creation processes.

The P2P ecosystem is characterized by the intensive interaction among cognitive slack and distributed technologies. This complex interaction presents interesting implications in terms of efficiency that, until now, have not been analyzed in the literature. Aiming to fill the extant literature gap, this paper provides a consistent analytical framework that simultaneously takes into account the economies of knowledge integration and potential diseconomies, that is, the costs of coordination and loss of control that arise from the adoption and diffusion of distributed technologies.

This paper provides an original explanation of P2P as an emergent ecosystem that serves as a service logics amplifier of value co-creation. In this regard, analysis of the key features of P2P not only sheds new light on P2P, but also allows for the reflection on the ecosystem’s framework, which promotes a virtuous interaction between the conceptual speculation and understanding of reality. Moreover, the proposed framework for the net benefit analysis of the P2P value co-creation model draws the attention of managers and decision makers as they consider the following issue: value co-creation jointly considers not only its benefits, but also its associated costs.

This paper aims to build on the latest advances in cognitive computing techniques to systematically illustrate how unstructured data from users can offer significant value for co-innovation.

The paper adopts a general overview approach to understand how unstructured data from users can be analyzed with cognitive computing techniques for innovation. The paper links the computerized techniques with marketing innovation problems with an integrated framework using dynamic capabilities and complexity theory.

The paper identifies a suite of methodologies for facilitating company co-innovation via engaging with customers and external data with cognitive computing technologies. It helps to expand marketing researchers and practitioners’ understanding of using unstructured data.

This paper provides a conceptual framework that divides co-innovation process into three stages, ideas generation, ideas integration and ideas evaluation, and maps cognitive computing methodologies and technologies to each stage. This paper makes the theoretical contributions by developing propositions from both customer and firm perspectives.

This paper can be used for companies to engage consumers and external data for co-innovation activities by strategically select appropriate cognitive computing techniques to analyze unstructured data for better insights.

Given the lack of systematic discussion regarding what is possible from using cognitive computing to analyze unstructured data for co-innovation. This paper makes first attempt to summarize how unstructured data can be analyzed with cognitive computing techniques. This paper also integrates complexity theory to the framework from a novel perspective.

The purpose of this paper is to introduce and conceptualize the topic of Cognitive Centres. It emphasizes the importance of complexity management and cognitive technologies in management practice.

It elaborates the relevance of different types of models for management: Stafford Beer's operations room, viable system model, subject‐object and subject‐subject management models, expert‐based mathematical modelling and computational experiment, organizational‐activity games theory and cybernetic (Viplan) methodology.

The paper suggests models and approaches for strategic management. It shows the inadequacy of a subject‐object management model for industrial or regional governance. It integrates a communicative management approach, complexity management methods, the USSR's Gosplan experience of long‐term planning, the Keldysh Institute of Applied Mathematics experience of modelling extremely complex systems and modern cognitive and information technologies into the concept of a Cognitive Centre.

Cognitive Centres can enhance the adaptation and viability of a large network of small organizations: public enterprises, business and not‐for‐profit regional industries. The paper describes two cases of practical implementation.

The paper contributes to research on management models that integrates cybernetics, cognitive technologies and computational experiments.