Journal of Knowledge Management

Wang, Yichuan; Byrd, Terry Anthony

2017 Journal of Knowledge Management

doi: 10.1108/JKM-08-2015-0301

PurposeDrawing on the resource-based theory and dynamic capability view, this paper aims to examine the mechanisms by which business analytics (BA) capabilities (i.e. the effective use of data aggregation, analytics and data interpretation tools) in healthcare units indirectly influence decision-making effectiveness through the mediating role of knowledge absorptive capacity.Design/methodology/approachUsing a survey method, this study collected data from the hospitals in Taiwan. Of the 155 responses received, three were incomplete, giving a 35.84 per cent response rate with 152 valid data points. Structural equation modeling was used to test the hypotheses.FindingsThis study conceptualizes, operationalizes and measures the BA capability as a multi-dimensional construct that is formed by capturing the functionalities of BA systems in health care, leading to the conclusion that healthcare units are likely to obtain valuable knowledge through using the data analysis and interpretation tools effectively. The effective use of data analysis and interpretation tools in healthcare units indirectly influence decision-making effectiveness, an impact that is mediated by absorptive capacity.Originality/valueThis study adds values to the literature by conceptualizing BA capabilities in healthcare and demonstrating how knowledge absorption matters when implementing BA to the decision-making process. The mediating role of absorptive capacity not only provides a mechanism by which BA can contribute to decision-making practices but also offers a new solution to the puzzle of the IT productivity paradox in healthcare settings.

Ferraris, Alberto; Santoro, Gabriele; Dezi, Luca

2017 Journal of Knowledge Management

doi: 10.1108/JKM-09-2016-0411

PurposeThis paper aims at exploring the effect of knowledge management (KM) practices on the relationship between external research and development (R&D) and innovative performance. The authors argue that the firms which develop and possess superior KM capabilities have the ability to better manage external knowledge and combine it with the internal one.Design/methodology/approachThe authors used a sample of 117 European MNC subsidiaries. An OLS regression analysis was carried out to evaluate the moderator effect of KM on the relationship between external R&D and innovative performance.FindingsThe authors found positive evidences in favor of a moderator effect of KM. This means that subsidiaries with superior KM capabilities are more effective in using external R&D, augmenting the magnitude of their external sources of knowledge and, consequently, improving their innovative performance.Practical implicationsManagerially speaking, both corporate and subsidiaries’ managers need to understand the relevance of managing knowledge effectively and efficiently at the subsidiary level. Corporate managers need to allocate more resources (both financial and managerial) to the subsidiaries that are active in knowledge transfer and sharing, while subsidiaries managers need to implement practically the KM tools and processes at the subsidiary organizational level to improve subsidiary’s innovative performance.Originality/valueThis paper contributes mainly to the KM field, highlighting the importance of KM at the subsidiary level, whereas most of previous studies focus on different units of analysis.

Martinez-Conesa, Isabel; Soto-Acosta, Pedro; Carayannis, Elias George

2017 Journal of Knowledge Management

doi: 10.1108/JKM-09-2016-0403

PurposeThis study aims to shed light on the internal and external antecedents of open innovation (OI) in the context of small- and medium-sized enterprises (SMEs), with a special focus on the role of knowledge management (KM) capability. The paper develops and tests an integrative research model which assesses the effect of internal factors on KM capability; the impact of organizational and external factors, namely, KM capability and environmental dynamism, on OI; and whether environmental dynamism moderates the relationship between KM capability and OI.Design/methodology/approachDrawing on the knowledge-based view and the social exchange and the contingency theories, this paper develops an integrative research model which analyzes several relations between organizational antecedents of KM capability and its effect on OI by using covariance-based structural equation modeling on a data set of Spanish SMEs.FindingsResults confirm that information technology-supported operations and commitment-based human resource practices have a positive and significant influence on KM capability. In contrast, results do not find support for the relationship between interdepartmental connectedness and KM capability, whereas both KM capability and environmental dynamism have a direct influence on OI.Originality/valueThis paper adds to existing research on OI, as it is the first study that addresses the critical role of KM capability for the implementation of OI.

Shin, Seungryul Ryan; Han, John; Marhold, Klaus; Kang, Jina

2017 Journal of Knowledge Management

doi: 10.1108/JKM-07-2016-0295

PurposeThe purpose of this study is to investigate the effects of open innovation, especially focusing on technological M&A, on subsequent innovation and changes to the firm’s core technological portfolio.Design/methodology/approachThe study suggests three types of core technological areas, based on prior focus and experience in technological categories. These are 1) the existing core area, in which the acquirer firm retains its knowledge and expertise, 2) the enhanced core area, where knowledge and expertise in the acquirer firm’s insufficient areas are strengthened, and 3) the new core area, i.e. new knowledge fields in which the acquirer firm ventures into. The study then analyzes the effects of two key knowledge characteristics of the target firm, similarity and complementarity, on post-M&A innovation outcomes in each of the three core technological areas.FindingsThe results confirm that while none of the investigated knowledge characteristics of the target firm is advantageous for post-M&A innovation outcomes in existing core areas, similarity of the target firm does facilitate post-M&A innovation outcomes in enhanced core areas. Moreover, the results confirm that complementarity of the target firm is beneficial for post-M&A innovation outcomes in new core areas.Originality/valueThe study explains the reconfiguration mechanism of a firm’s core technological portfolio. It also suggests an extended framework to analyze innovation outcomes in more detail. Moreover, the study helps to explain why most M&As result in failure.

Liu, Yong; Li, Kevin W.

2017 Journal of Knowledge Management

doi: 10.1108/JKM-05-2016-0183

PurposeThe purpose of this paper is to propose a novel prospect-based two-sided matching decision model for matching supply and demand of technological knowledge assisted by a broker. This model enables the analyst to account for the stakeholders’ psychological behaviours and their impact on the matching decision in an open innovation setting.Design/methodology/approachThe prospect theory and grey relational analysis are used to develop the proposed two-sided matching decision framework.FindingsBy properly calibrating model parameters, the case study demonstrates that the proposed approach can be applied to real-world technological knowledge trading in a market for technology (MFT) and yields matching results that are more consistent with the reality.Research limitations/implicationsThe proposed model does not differentiate the types of knowledge exchanged (established vs novel, tacit vs codified, general vs specialized) (Ardito et al., 2016, Nielsen and Nielsen, 2009). Moreover, the model focuses on incorporating psychological behaviour of the MFT participants and does not consider their other characteristics.Practical implicationsThe proposed model can be applied to achieve a better matching between technological knowledge suppliers and users in a broker-assisted MFT.Social implicationsA better matching between technological knowledge suppliers and users can enhance the success of open innovation, thereby contributing to the betterment of the society.Originality/valueThis paper furnishes a novel theoretical model for matching supply and demand in a broker-assisted MFT. Methodologically, the proposed model can effectively capture market participants’ psychological considerations.

Savino, Tommaso; Messeni Petruzzelli, Antonio; Albino, Vito

2017 Journal of Knowledge Management

doi: 10.1108/JKM-09-2016-0381

PurposeInto cultural and creative industries, the innovation is increasingly realized by a lead creator which is supported by a specific team. Hence, this paper aims to understand the composition of this particular team.Design/methodology/approachThe authors conducted an in-depth case study of “Dal Pescatore”. This is the Italian restaurant keeping the highest award previewed by Michelin Guide from the longer period. The main figures of the restaurant are the head chefs (Nadia and Giovanni Santini) who are continually supported by a dedicated teamFindingsThe analysis underlines the necessity to create a team which combines aged people linked to firms’ tradition with a low percentage of young foreign apprentices. If the old-timer member assures a deep understanding of the firm’s knowledge base, the young foreign apprentice can show an high learning attitude through which he/she more easily shares their different knowledge.Research limitations/implicationsThis study discussed organizational efforts to foster innovation capacities of the main individuals into a firm. However, the present research suffers from some limitations which limits the generalizability of the results beyond the company studied: a single case study on a small and family firm with consolidated organizational routines. In addition, this research does not solutions about the mechanisms of interaction among these different team members.Originality/valueRecent studies observed how a number of cultural and creative firms innovate through a particular team that develops the ideas of a lead creator. Nevertheless, despite the increasing importance of these teams, their composition remains unclear.

Zhang, Tingting; Wang, William Yu Chung; Pauleen, David J.

2017 Journal of Knowledge Management

doi: 10.1108/JKM-12-2016-0522

PurposeThis paper aims to investigate the value of big data investments by examining the market reaction to company announcements of big data investments and tests the effect for firms that are either knowledge intensive or not.Design/methodology/approachThis study is based on an event study using data from two stock markets in China.FindingsThe stock market sees an overall index increase in stock prices when announcements of big data investments are revealed by grouping all the listed firms included in the sample. Increased stock prices are also the case for non-knowledge intensive firms. However, the stock market does not seem to react to big data investment announcements by testing the knowledge intensive firms along.Research limitations/implicationsThis study contributes to the literature on assessing the economic value of big data investments from the perspective of big data information value chain by taking an unexpected change in stock price as the measure of the financial performance of the investment and by comparing market reactions between knowledge intensive firms and non-knowledge intensive firms. Findings of this study can be used to refine practitioners’ understanding of the economic value of big data investments to different firms and provide guidance to their future investments in knowledge management to maximize the benefits along the big data information value chain. However, findings of study should be interpreted carefully when applying them to companies that are not publicly traded on the stock market or listed on other financial markets.Originality/valueBased on the concept of big data information value chain, this study advances research on the economic value of big data investments. Taking the perspective of stock market investors, this study investigates how the stock market reacts to big data investments by comparing the reactions to knowledge-intensive firms and non-knowledge-intensive firms. The results may be particularly interesting to those publicly traded companies that have not previously invested in knowledge management systems. The findings imply that stock investors tend to believe that big data investment could possibly increase the future returns for non-knowledge-intensive firms.

Scuotto, Veronica; Del Giudice, Manlio; Bresciani, Stefano; Meissner, Dirk

2017 Journal of Knowledge Management

doi: 10.1108/JKM-10-2016-0465

PurposeThis paper aims to investigate three key factors (i.e. cognitive dimensions, the knowledge-driven approach and absorptive capacity) that are likely to determine the preference for informal inbound open innovation (OI) modes, through the lens of the OI model and knowledge-based view (KBV). The innovation literature has differentiated these collaborations into informal inbound OI entry modes and formal inbound OI modes, offering an advocative and conceptual view. However, empirical studies on these collaborations are still limited.Design/methodology/approachBuilding on the above-mentioned theoretical framework, the empirical research was performed in two stages. First, data were collected via a closed-ended questionnaire distributed to all the participants from the sample by e-mail. Second, to assess the hypotheses, structural equation modelling (SEM) via IBM® SPSS® Amos 20 was applied.FindingsThe empirical research was conducted on 175 small to medium enterprises in the United Kingdom, suggesting that the knowledge-driven approach is the strongest determinant, leading to a preference for informal inbound OI modes. The findings were obtained using SEM and are discussed in line with the theoretical framework.Research limitations/implicationsOwing to the chosen context and sector of the empirical analysis, the research results may lack generalisability. Hence, new studies are proposed.Practical implicationsThe paper includes implications for the development of informal inbound OI led by knowledge-driven approach.Originality/valueThis paper offers an empirical research to investigate knowledge-driven preferences in informal inbound OI modes.

Wang, Yueqi; Guo, Bin; Yin, Yanjie

2017 Journal of Knowledge Management

doi: 10.1108/JKM-09-2016-0368

PurposeThe purpose of this study is to explore organizational factors that act as antecedents of open innovation search. The authors aim to empirically examine whether the extent to which the organizational slack is absorbed determines its influence on firms’ openness in innovation search. In addition, the authors also examine the moderating effect of absorptive capacity on the relationship between slack and open innovation search.Design/methodology/approachThis study adopted secondary data from multiple sources (NBER, Compustat and US census) and then constructed a ten-year balanced panel dataset of 298 manufacturers. The generalized least square method was used to explore the determinants of open innovation search among manufacturing firms.FindingsThe results of this study reveal that the absorption level of organizational slack indeed determines the openness in innovation search. Specifically, absorbed slack negatively affects a firm’s openness in innovation search, whereas unabsorbed slack promotes open innovation search. Additionally, the relationship between absorbed slack and open innovation search will be less negative with the increase of absorptive capacity.Originality/valueDifferent from most previous studies that have examined the performance effect of open search among high-tech and large enterprises, this study focuses on the antecedents of open search strategy in both high- and low-tech, large and small firms. The findings reveal that different forms of organizational slack divergently influence a firm’s open search strategy, contributing to the understanding of the relationship between organizational slack and knowledge search behavior in a broader context, as well as the understanding of the moderating effect of absorptive capacity.

Serenko, Alexander; Bontis, Nick

2017 Journal of Knowledge Management

doi: 10.1108/JKM-11-2016-0490

PurposeThe purpose of this study is to update a global ranking of 27 knowledge management and intellectual capital (KM/IC) academic journals.Design/methodology/approachThe ranking was developed based on a combination of results from a survey of 482 active KM/IC researchers and journal citation impact indices.FindingsThe ranking list includes 27 currently active KM/IC journals. The A+ journals are the Journal of Knowledge Management and the Journal of Intellectual Capital. The A journals are the Learning Organization, Knowledge Management Research & Practice, Knowledge and Process Management, VINE: The Journal of Information and Knowledge Management Systems and International Journal of Knowledge Management. A majority of recently launched journals did not fare well in the ranking. Whereas a journal’s longevity is important, it is not the only factor affecting its ranking position. Expert survey and citation impact measures are relatively consistent, but expert survey ranking scores change faster.Practical implicationsKM/IC discipline stakeholders, including practitioners, editors, publishers, reviewers, researchers, students, administrators and librarians, may consult the developed ranking list for various purposes. Compared to 2008, more researchers indicated KM/IC as their primary area of concentration, which is a positive indicator of discipline development.Originality/valueThis is the most recent ranking list of KM/IC academic journals.