To Örebro University

The acknowledgement of a research tradition by other disciplines shows its contribution to the development of the broader body of scientific knowledge. This paper investigates the contribution of IMP (Industrial Marketing and Purchasing) research to broader research disciplines by analyzing how researchers within and beyond IMP have cited core IMP articles. First, through quantitative bibliometric analysis, the paper identifies the diffusion to other research disciplines. Thereafter, through qualitative analysis, the impact of the IMP perspective is captured to understand how strong these imprints are. The analyses show that IMP research has been noticed among a range of adjacent research disciplines. However, the use of IMP references has generally been rudimentary, and without a deeper understanding of the IMP ontology, meaning that IMP still has some “weak ties” to the other disciplines. Establishing IMP's contribution through enduring imprints would need further engagement with researchers from other research disciplines and publications in top journals. The paper contributes empirically with how the IMP perspective has spread beyond the IMP Group and theoretically by adding insight into how research ideas travel and transform to other disciplines. 

Social media and the data it produces lend itself to being visualised as a network. Individual Twitter users can be represented as nodes and retweeted by another Twitter user, thereby forming a relationship, an edge, between users. However, an unbounded network is a sprawling mass of nodes and edges. Boundary settings are typically applied, for example, a time period, a hashtag, a keyword search or a network substructure of a phenomenon of interest. Thus, the particular visualisation created is dependent upon the boundaries applied, enabling productive visual consumption, but concealing its social shaping. To explore this question of boundary setting and its associated issues, we draw on an example from the Twitter discussions about the UK Minister for Health, Jeremy Hunt, and the media debate surrounding the contractual hours of junior doctors during 2015–2016. We discuss the role and impact differing stakeholders have in setting these boundaries. We seek to provide a set of ‘questioning lenses’ in which we ask why these boundary settings were selected, what effect they have, and what are the potential implications of these boundary setting techniques on the visualisation consumer.

Purpose: Strong agreement in the extant business literature emphasizes that digital developments are key to economic growth internationally. This is in spite of the recorded high levels (up to 50 percent) of failure among digital companies and entrepreneurs. The purpose of this paper is to identify the digital debates in Italy, explore current policies and develop a typology that characterizes digital entrepreneurs (DEs) and their start-up companies in Italy.

Design/methodology/approach: The digital debates and policies are explored through an extensive telephone survey of the self-perceptions and identified supports required by 348 Italian active DEs. Quantitative statistical techniques were used including factor analysis, cluster analysis and ANOVA, to identify motivations, profiles and critical success factors relevant to the sample.

Findings: The study identifies three main clusters among the DEs: emerging very young; emerging business focused and experienced. These clusters vary with the entrepreneurs’ background and competence base, motivation and satisfaction factors. The different kinds of profiles require specific kinds of supporting policies identified by the sample that focus on financial, educational and/or networking provision.

Originality/value: The paper affirms the central role of digital entities in modern economies expressed in the current literature and increases knowledge of the perceived success factors identified by DEs. The identification and classification of self-reported characteristics of Italian DEs and to what extent these characterizations might be useful for tailored interventions to support their success are the main contributions of this study. Accordingly, an authentic, original and self-reported portrayal has been constructed of the self-perceptions of Italian DEs. Finally, the study explores the implications for actions and new policies considering self-perceived profiles, needs and expectations of DEs.

Passenger transport is becoming more and more connected and multimodal. Instead of just taking a series of vehicles to complete a journey, the passenger is actually interacting with a connected cyber-physical social (CPS) transport system. In this study, we present a case study where big data from various sources is combined and analyzed to support and enhance the transport system in the Tampere region. Different types of static and real-time data sources and transportation related APIs are investigated. The goal is to find ways in which big data and collaborative networks can be used to improve the CPS transport system itself and the passenger satisfaction related to it. The study shows that even though the exploitation of big data does not directly improve the state of the physical transport infrastructure, it helps in utilizing more of its capacity. Secondly, the use of big data makes it more attractive to passengers.

Scholars and practitioners of knowledge management have paid increasing attention to the adoption of social media in business-to-business (B2B) setting for knowledge sharing; however, both the theoretical and empirical research in this domain are quite fragmented. The aim of this research is to deepen the understanding about the B2B companies’ awareness of the potentials of social media in improving their absorptive capacity and, consequently, if and how such companies deploy knowledge strategies based on social media adoption. We carried out an empirical survey of Finnish technology companies operating purely in B2B markets. Results highlight that social media adoption is still in a preliminary stage of development. Companies show a lack of awareness of the potentials of social media as a means for external knowledge acquisition and internal dissemination. Results suggest a strong need of a structured approach to the adoption of social media to overcome cultural and organisational barriers.

IMP research is often treated as an empirical perspective describing complexities of repeated business-to-business exchanges and their embeddedness. While building on some common understandings and concepts, this paper asks: How homogeneous is the IMP research? This paper uses cluster analysis to capture the roots and various sub-groups of IMP research as means to depict the question of homogeneity (i.e. a core focus in the research) or heterogeneity (i.e. using references from other fields or specific to sub-fields) of the IMP thought. In this scientific work in progress paper we introduce how we design to use bibliographical methods in order to harvest data from an extensive amount of IMP-related articles written from the 1970’s onwards. In this first attempt to reveal IMP we used overall 294 articles yielded to 10,615 co-citation relationships. A threshold of minimum number of citations of a cited reference was set to five (5) to capture such references that have been cited in multiple publications. We introduce visual mapping of defined subject area clusters and as an example we describe shortly clusters. Perhaps not surprisingly our findings suggest that IMP research is not so homogenous, with at least four clear clusters of IMP-research each utilizing different key references.

This paper addresses the educational hackthon as innovation pedagogy method for teaching fuzzy front end of innovation (FFEI) in higher education institutions (HEIs). Specifically it focuses on the process design and execution. This study is based on the idea that educational hackathons are as pecific type of innovation contest aimed at teaching and learning, thus incorporating a set of design variables. Therefore, the paper reports a case study according to those variables in HEI teaching in university-industry collaboration.This paper presents both the process description along with students’ learning and feedback, i.e. the development suggestions for the method. Presenting conclusions for both academic use and practical design of hackathons in teaching, the paper clarifies the literature of educational hackathons as a type of innovation pedagogy method, for teaching FFEI in HEIs beyond IT-industry.

Increased focus in popular press has been directed at how individuals born at different times differ in their preferences and ways of acting. Generation Z (Gen Z) refers to individuals born in the 1990s that are often described to be self-centred but also entrepreneurial, potentially based on how the abilities to get at permanent position has changed during the last decades. The purpose of this study is to investigate: What does Gen Z consider important organizational innovation factors at a future workplace? Based on a questionnaire directed at individuals as part of Gen Z, we focus our analysis on innovation enablers, to thereby also see how Gen Z’s expectations fit with needs to continuously and increasingly rapidly renew operations. With this study we contribute to a greater academic understanding of a new and in Sweden relatively unexplored Gen Z. The practical implication of the study is to provide employers with guidelines on how to create successful innovation incubation environments at their workplace.

Customers are human beings who express their emotions openly on social media platforms. There is a wealth of social media data that companies can make use of to improve their business decision making and tailor their marketing strategies. In order to benefit from this, organizations need to apply computational methods, which can save time and effort rather than applying traditional consumer research approaches, such as surveys or interviews. The purpose of this study is to investigate existing computational studies on detecting consumer emotions from social media data. We conducted a systematic literature review on articles published in ScienceDirect, IEEE Explore, ACM Digital Library, and Emerald Insight from the period 2009-2017. The aim was to discover how social media data was extracted, how large datasets were used in detecting emotions, the type of computational methods used, and the accuracy of the results obtained from the existing studies. Most of the studies were focused on sentiment analysis and different machine learning algorithms. The computational methods were applied in business decision making and marketing functions. Practical scenarios included emotion detection in customer reviews and sentiment analysis of retail brands. Based on these studies, we have uncovered situations where the results of the analysis are either sufficiently accurate or supportive for decision making. We provide recommendations for organizations and managers on developing their resources to make use of different computational methods for emotion and sentiment detection. Finally, we present the limitations of these methods and provide recommendations for aligning future research studies toward big social data analytics on customer emotions.

The aim of the study is to identify the contribution of authors in the domain of Knowledge Management (KM). The underlying data is from two leading KM journals,namely, the Journal of Knowledge Management (JKM)and the Journal of Intellectual Capital (JIC). We downloaded articles from Thomson Reuters Web of Science (WoS), with JKM and JIC-specific searches resulting in 508 and 73 citing articles respectively. The timeframe of analysis was 2009-2016. This dataset was used to create co-citation network visualisations to provide insights into the clusters of authors and research topics. Measures such as Betweenness centrality and hubs-authorities (HITS) were used to identify significant authors and their key themes of interest. More specifically, network analysis identified six dominant research themes, it revealed a total of 14,422 authors being cited (depicted as nodes in the visualisation) with a total of 1,023,123 citations (edges). Based on the findings of this study, the paper will explore the specific themes and the intellectual turning points in KM research and its evolution. Our bibliometric analysis has practical significance for researchers since it recognises the dominant research areas, and by extension, it identifies those that are still in their infancy; the latter having the potential of representing an interesting research gap. The limitation of the study is that the underlying data is only from two journals (albeit, from the top two journals in KM), which may lead to partially biased results. In future, the aim is to also leverage the analysis to more KM journals, e.g., the top ten journals within the Serenko & Bontis (2013) most updated list.