Innovation is defined as a process that is fraught with uncertainty. This article's aim is to diminish lack of knowledge of the factors that create uncertainty in innovation processes. The basic thrust of the present argument is that the potential value integral to innovation may or may not be materialized in the future. Given that the future entails uncertainty, it is reasonable to expect that uncertainty is inherent in every innovation process. Uncertainty results from the fact that, on the one hand, events in the future do not follow the course of past events, and, on the other, knowledge of the future is always incomplete. Using a systematic approach to reviewing the literature, eight factors which create uncertainty in processes of innovation were identified, namely: technological uncertainty, market uncertainty, regulatory/institutional uncertainty, social/political uncertainty, acceptance/legitimacy uncertainty, managerial uncertainty, timing uncertainty, and consequence uncertainty.

Abstract. New technologies are promising us many upsides like enhanced health, convenience, productivity, safety, and more useful data, information and knowledge for people and organizations. The potential downsides are challenges to personal privacy, over-hyped expectations, increasing technological complexity that boggles us. Our point is this change requires scientific discussion from the point of management, leadership and organizations -that is, it is time to discuss the meaning of these challenges seriously also in terms of existing traditions of management science. This review type article discusses the nature and role of the Internet of Things (IoT), Big Data and other key technological waves of ubiquitous revolution vis-á-vis the existing knowledge on management, organizations and knowledge management practices in organizations. Recent changes in the fields of robotics, artificial intelligence and automation technology indicate that all kinds of intelligence and smartness are increasing and organizational cultures are going to change indicating fast changes in the field of modern management and management sciences. Organizational processes form the base for the knowledge-based decision-making. Developing and utilizing smart solutions -like the utilization of Big Data -emphasize the importance of open system thinking. Digitalized services can for instance create new interfaces between service providers and users. Service users create social value while they are participating in co-producing activities. Hence, the IoT and Big Data undoubtedly strengthen the role of participation in service production, service economy, innovativeness in-between organizations (as a joint processes) and leadership models incorporated in service-dominant -logic. Moreover, IoT, Big Data, and especially digitalization bring about the renaissance of knowledge in decision-making.At organizational level, smart organizations do no rely on knowledge production, but focus on knowledge integration instead. Knowledge integration becomes a key part of management systems. This also means that seminal theories with regard to decision-making and knowledge management do not suffice anymore. At organizational level there is a growing need to develop abilities to act in changing, not easy to forecasted and non-linear situations due to the complexity related to utilization and developing digitalization. Authentic and clinical leadership involves components such as awareness, unbiased processing, action, and relations. IoT and Big Data certainly effect organizations. The connection between IoT, Big Data, management systems as well as

Companies have been facing the dark side of social media. Particularly, the odds of customer complaints and brand insults have increased tremendously. Social media has given a voice to disappointed consumers. They use the voice when they feel negative emotions, for example, due to product failures, service problems or unethical behavior. It seems reasonable to expect that the more ubiquitous social media becomes, the more it persuades people to share also their negative experiences. However, although social media raises new challenges for companies, it also gives them new opportunities. Social media enables companies to trace disappointed customers, evaluate their impressiveness and communicate with them. The conceptual paper aims to develop a model for the relationship between social media behavior, negative consumer emotions and brand disloyalty. The argument of this paper is that although social media gives consumers more power which is manifested in sharing negative emotions related to the company, the effect this has on brand disloyalty depends on the company's behavior.

Purpose -The purpose of this paper is to present a conceptual analysis of the theoretical and managerial bases and objectives of predictive business. Predictive business refers to operational decision-making and the development of business processes on the basis of business event analysis. It supports the early recognition of business opportunities and threats, better customer intimacy and agile reaction to changes in business environment. An underlying rationale for predictive business is the attainment of competitive advantage through better management of information and knowledge. Design/methodology/approach -The approach to this article is conceptual and theoretical. The literature-based discussion and analysis combines the perspectives of business performance management, business intelligence, and knowledge management to provide a new model of thinking and operation. Findings -For a company predictive business is simultaneously a practical challenge and an epistemic one. It is a practical challenge because predictive business presupposes a change in the company's modes of operation. It is also an epistemic challenge, since it concerns the company's ability to find appropriate balance between knowledge exploitation and knowledge exploration. Research limitations/implications -Further research should be carried out on the functionality of practical applications as well as the attitudinal and technical preparedness of companies to adopt a new mode of operation. As a subject of investigation, the world of business events offer interesting methodological possibilities, since the basis of the work is the gathering and analysis of large quantities of information on operational activities. Originality/value -There has been little research concerning business events in knowledge management context. This article presents a theoretically founded basis for predictive business, combining the concept of analysing business events with previous research in the field of knowledge management.

Social media increases the connectivity of people inside and outside an organisation. It is not just the implementation of communication technology, but the transformation of working and organisational cultures. The paper presumes that social media provides new opportunities to the organisational knowledge creation process by amplifying knowledge created by individuals as well as crystallising and connecting it to an organisation's knowledge system. The process depends fundamentally on the individual's tacit knowledge and its conversion into organisational explicit knowledge. Knowledge conversion is not a linear and sequential process, but a process which is affected by the individual's emotions. This paper explores the interplay between knowledge and emotions in the organisational knowledge creation process in the context of social media. The paper concludes that knowledge and emotion shared in social media contribute to the social identity, which increases the odds of altruistic behaviour towards others in a way that benefits the organisation.