1,721,293 research outputs found
A bibliographic analysis of 20 years of research on innovation and new product development in technology and innovation management (TIM) journals
No full textIn this perspectives article, we analyze 20 years of research on the topics of “innovation management” and “new product development” in the technology and innovation management (TIM) domain. More specifically, we investigate the questions related to three issues: (i) Performance: Which authors, institutions, countries, journals, and papers have been most productive (number of papers) and most influential (number of citations)? (ii) Networks: What are the links between authors, between countries, between institutions, between journals and co-citation? (iii) Attention: What has been the shift in research attention (i.e., stated keywords) over time? To do this, we use the VOSViewer bibliographic method to assess the domain’s performance and its changes in research attention and present maps of the knowledge structure and networks. Our study adds to and improves upon previous bibliometric reviews in terms of extensivity (i.e., data from 7,612 papers), scope, and accuracy. In addition to the descriptive evaluations of the domain, we also suggest several implications from these results. For performance, we highlight a weak link between productive authors and influential authors, which could be explained by productive authors being part of extensive co-authorship networks, being selective and publishing less but in the highest quality journals, and working in countries with institutions that pioneer research on the topic (and conversely, less influential authors working in countries with an incentive structure that rewards quantity but not quality). Our network results help explain that collaborations are linked to research productivity rather than influential research. Further, our network results reveal collaborations based on country linkages that might create research echo chambers in which research attention is augmented or reinforced by a geographical network. From our results on research attention, we discuss how the dominant keywords are restricted to TIM topics and highly influenced by seminal papers and authors outside the TIM domain. Thus, the field is predominantly inward-looking, drawing from other cognate business and management fields, and hardly drawing from other academic fields. These findings elucidate and extend the concerns other innovation management scholars have raised, noting that the lack of varied and cooperative authorship within the TIM domain has led to stale, repeated methods and metrics in TIM papers, potentially reducing the field’s future influence. We conclude by outlining some adverse implications of our paper. We explain how its evaluations could further produce confirmation biases author and institution standing and motivate publication strategies and incentives that exacerbate research misconduct
What fails and when? A process view of innovation failure
Get PDFResearch on innovation failure has proliferated lately but with little theoretical attention given to the diversity of the concept. Using process theorizing, we present a model and propositions to understand how a firm's anticipation and value toward failure depends on the type of failure (task versus outcome) and the phase (divergent versus convergent) and point (early versus later) ‘within’ the process that the failure occurs. Using the anticipation-value stances, we then present a typology of four modes of innovation failure that can arise ‘from’ task and outcomes failure in the innovation process. The four modes (and associated learning response) are unsolicited failures (prevent-alert-eliminate); hazardous failures (predict-modify-mitigate); fortuitous failures (probe-expose-extrapolate); and excursive failures (facilitate-analyze-harness). To help explain the ideas in our process model and typology, we use the well-known IDEO shopping cart innovation project as an illustrative example. Together, these contributions provide contingency oriented insights on how failure varies and journeys within and from the innovation process, which helps researchers and managers to better understand the related causes, effects and learning responses
Editorial: Standardization in a Digital and Global World: State-of-the-Art and Future Perspectives
Get PDFLeveraging social capital in university-industry knowledge transfer strategies: a comparative positioning framework
Get PDFUniversity-industry partnerships emphasise the transformation of knowledge into products and processes which can be commercially exploited. This paper presents a framework for understanding how social capital in university-industry partnerships affect knowledge transfer strategies, which impacts on collaborative innovation developments. University-industry partnerships in three different countries, all from regions at varying stages of development, are compared using the proposed framework. These include a developed region (Canada), a transition region (Malta), and a developing region (South Africa). Structural, relational and cognitive social capital dimensions are mapped against the knowledge transfer strategy that the university-industry partnership employed: leveraging existing knowledge or appropriating new knowledge. Exploring the comparative presence of social capital in knowledge transfer strategies assists in better understanding how university-industry partnerships can position themselves to facilitate innovation. The paper proposes a link between social capital and knowledge transfer strategy by illustrating how it impacts the competitive positioning of the university-industry partners involved
Recommended from our members
Does getting along matter? Tourist-tourist rapport in guided group activities
Get PDFGuided group activities, where tourists consume with other tourists, are common and important. Although literature suggests customer-employee rapport impacts customer satisfaction, the composition and impact of tourist-tourist rapport in guided group activities have received minimal attention. We use a three-study mixed method approach to conceptualize and examine tourist-tourist rapport in guided group activities. Study 1 identifies two recognized dyadic dimensions of tourist-tourist rapport (enjoyable interaction and personal connection) and two new group-based dimensions (group attentiveness and service congruity). Study 2 (video experiment) and Study 3 (field experiment) find that enjoyable interaction and personal connection mediate the relationship between group attentiveness and service congruity with satisfaction. Thus, tourist-tourist rapport in a group context is more multidimensional and complex than previously conceptualized for customer-employee rapport and non-group contexts. Further, we find tourist-tourist rapport is a critical service factor such that high levels satisfy, while low levels dissatisfy
Making sense of text: artificial intelligence-enabled content analysis
Get PDFPurpose: The purpose of this paper is to introduce, apply and compare how artificial intelligence (AI), and specifically the IBM Watson system, can be used for content analysis in marketing research relative to manual and computer-aided (non-AI) approaches to content analysis.
Design/methodology/approach: To illustrate the use of AI-enabled content analysis, this paper examines the text of leadership speeches, content related to organizational brand. The process and results of using AI are compared to manual and computer-aided approaches by using three performance factors for content analysis: reliability, validity and efficiency.
Findings: Relative to manual and computer-aided approaches, AI-enabled content analysis provides clear advantages with high reliability, high validity and moderate efficiency.
Research limitations/implications: This paper offers three contributions. First, it highlights the continued importance of the content analysis research method, particularly with the explosive growth of natural language-based user-generated content. Second, it provides a road map of how to use AI-enabled content analysis. Third, it applies and compares AI-enabled content analysis to manual and computer-aided, using leadership speeches.
Practical implications: For each of the three approaches, nine steps are outlined and described to allow for replicability of this study. The advantages and disadvantages of using AI for content analysis are discussed. Together these are intended to motivate and guide researchers to apply and develop AI-enabled content analysis for research in marketing and other disciplines.
Originality/value: To the best of the authors' knowledge, this paper is among the first to introduce, apply and compare how AI can be used for content analysis
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Cultural similarity and impartiality on voting bias: The case of FIFA’s World’s Best Male Football Player Award
Get PDFPrevious studies on voting bias in competitive awards have not fully considered the role of cultural similarity. Using data for the Best FIFA Men’s Player Award, we evaluate the extent of voting bias in this Award using three cultural similarity factors (cultural distance, cultural clusters, and collectivism), six established in-group factors (nationality, club, league, geography, ethnicity, religion, and language) and the impartiality of the voter’s country. Using statistical and econometric methods, we find that voter-player cultural similarity is positively associated with voting bias and find no evidence of impartiality when it comes to cultural or national ties. We also find that media voters are less biased than captain voters and coach voters, and that coaches are less biased than captains
- …
