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Special Issue "Knowledge Management, Innovation and Big Data: Implications for Sustainability, Policy Making and Competitiveness"

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: 31 December 2017

Special Issue Editors

Guest Editor
Prof. Patricia Ordóñez de Pablos

The University of Oviedo, Spain
Website | E-Mail
Interests: big data; knowledge management; human resource management; information technologies; intellectual capital
Guest Editor
Prof. Miltiadis D. Lytras

School of Business, Deree—The American College of Greece, 6 Gravias Street GR-153 42 Aghia Paraskevi Athens, Greece
Website | E-Mail
Phone: +30 210 600 9800
Interests: smart cities; innovation; big data research; data mining; analytics; emerging technologies; information systems; entrepreunership; technology enhanced learning; virtual reality; knowledge management

Special Issue Information

Dear Colleagues,

Strategy management involves understanding the forces and causes that explain performance differences between organizations and economies, a result of different stocks of knowledge-based resources and capabilities. These resources are key for achieving and sustaining and competitive advantage for companies, economies and societies.

The Big Data and Data Analytics is a new paradigm for the integration of Internet Technology in the human and machine contexts. Now, we are able to transform raw data that are massively produced by humans and machines in to knowledge and wisdom capable of supporting smart decision making, innovative services, new business models, innovation, and entrepreneurship.

Aims of the Special Issue:

The Special Issue will explore the role of knowledge management strategies and tools to enhance the power of big data and help decision makers in today’s competitive economy.

The Special Issue will analyze the relation of knowledge management, big data and information technology towards a deeper understanding of their impact on economies and societies today.

Topics of interest

  • Big data analytics
  • Challenges and trends in knowledge and creative economics
  • Competitive strategy, knowledge-based view of the firm
  • Data and e-commerce
  • Ethical issues of big data
  • Future skills of knowledge workers
  • Human resource management, intellectual capital reporting
  • Human/relational/social/organizational capital
  • Innovation networks
  • Innovation, knowledge management and leadership
  • Intangible resources, sustainability, big data
  • Knowledge economics and neuroeconomics
  • Organizational learning, networked learning
  • Product and process innovation, technology and innovation management
  • Semantic big data
  • Social networks, gamification
  • Sustainability and organizational competitiveness
Prof. Patricia Ordóñez de Pablos
Dr. Miltiades D. Lytras
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (8 papers)

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Research

Open AccessArticle Knowledge Creation Process and Sustainable Competitive Advantage: the Role of Technological Innovation Capabilities
Sustainability 2017, 9(12), 2280; doi:10.3390/su9122280
Received: 25 November 2017 / Revised: 7 December 2017 / Accepted: 7 December 2017 / Published: 11 December 2017
PDF Full-text (568 KB) | HTML Full-text | XML Full-text
Abstract
This study examines the relationship between the knowledge creation process and technological innovation capabilities, and analyzes their effect on a firm’s sustainable competitive advantage using a knowledge-based view theoretical framework. We conduct structural equation modeling analyses using survey data from 315 Chinese industrial
[...] Read more.
This study examines the relationship between the knowledge creation process and technological innovation capabilities, and analyzes their effect on a firm’s sustainable competitive advantage using a knowledge-based view theoretical framework. We conduct structural equation modeling analyses using survey data from 315 Chinese industrial firms to test the direct and indirect effects of the knowledge creation process on sustainable competitive advantage. Technological innovation capabilities—operationalized to reflect the dimensions of process innovation capability and product innovation capability—are used as the mediating variable for explaining the relationship between the knowledge creation process and sustainable competitive advantage. The results indicate that the knowledge creation process does not have a significant direct effect on sustainable competitive advantage. Rather, the knowledge creation process can only influence the sustainable competitive advantage through the mediating effect of technological innovation capabilities completely. Consequently, the knowledge creation process favors the development of technological innovation capabilities for processes and products, because processes and products can lead to a sustainable competitive advantage. Full article
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Open AccessArticle Top Management Teams’ Characteristics and Strategic Decision-Making: A Mediation of Risk Perceptions and Mental Models
Sustainability 2017, 9(12), 2265; doi:10.3390/su9122265
Received: 2 November 2017 / Revised: 5 December 2017 / Accepted: 5 December 2017 / Published: 7 December 2017
PDF Full-text (360 KB) | HTML Full-text | XML Full-text
Abstract
Strategic decision-making is a key factor of sustainability and development in enterprises. Moreover, the top management team (TMT) of an enterprise constitutes the base for decision-making. This study employed structural equation modeling to analyze questionnaires regarding TMTs’ characteristics and strategic decision-making, and tested
[...] Read more.
Strategic decision-making is a key factor of sustainability and development in enterprises. Moreover, the top management team (TMT) of an enterprise constitutes the base for decision-making. This study employed structural equation modeling to analyze questionnaires regarding TMTs’ characteristics and strategic decision-making, and tested the mediating effects of risk perceptions and mental models and the moderating effects of psychological ownership. We investigated 289 valid questionnaires on TMTs completed by representatives from enterprises in China and found risk perceptions and mental models that serve as a mediating factor and are affected by the TMTs’ characteristics and decision-making. We also found that psychological ownership exerts moderating effects between TMTs’ characteristics and decision-making. This paper concludes with a discussion of theoretical and managerial implications for enterprise owners. Full article
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Open AccessArticle Developing a Methodology of Structuring and Layering Technological Information in Patent Documents through Natural Language Processing
Sustainability 2017, 9(11), 2117; doi:10.3390/su9112117
Received: 15 September 2017 / Revised: 6 November 2017 / Accepted: 13 November 2017 / Published: 17 November 2017
PDF Full-text (1391 KB) | HTML Full-text | XML Full-text
Abstract
Since patents contain various types of objective technological information, they are used to identify the characteristics of technology fields. Text mining in patent analysis is employed in various fields such as trend analysis and technology classification, and knowledge flow among technologies. However, since
[...] Read more.
Since patents contain various types of objective technological information, they are used to identify the characteristics of technology fields. Text mining in patent analysis is employed in various fields such as trend analysis and technology classification, and knowledge flow among technologies. However, since keyword-based text mining has the limitation whereby, when screening useful keywords, it frequently omits meaningful keywords, analyzers therefore need to repeat the careful scrutiny of the derived keywords to clarify the meaning of keywords. In this research, we structure meaningful keyword sets related to technological information from patent documents; then we layer the keywords, depending on the level of information. This research involves two steps. First, the characteristics of technological information are analyzed by reviewing the patent law and investigating the description of patent documents. Second, the technological information is structured by considering the information types, and the keywords in each type are layered through natural language processing. Consequently, the structured and layered keyword set does not omit useful keywords and the analyzer can easily understand the meaning of each keyword. Full article
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Open AccessArticle Big Social Network Data and Sustainable Economic Development
Sustainability 2017, 9(11), 2027; doi:10.3390/su9112027
Received: 9 October 2017 / Revised: 3 November 2017 / Accepted: 4 November 2017 / Published: 7 November 2017
PDF Full-text (2857 KB) | HTML Full-text | XML Full-text
Abstract
New information technologies have led to the rapid and effective growth of social networks. The amount of data produced by social networks has increased the value of the big data concept, which is one of the popular current phenomena. The immediate or unpredictable
[...] Read more.
New information technologies have led to the rapid and effective growth of social networks. The amount of data produced by social networks has increased the value of the big data concept, which is one of the popular current phenomena. The immediate or unpredictable effects of a wide array of economic activities on large masses and the reactions to them can be measured by using social media platforms and big data methods. Thus, it would be extremely beneficial to analyze the harmful environmental and social impacts that are caused by unsustainable business applications. As social networks and big data are popular realms currently, their efficient use would be an important factor in sustainable economic development. Accurate analysis of people’s consumption habits and economic tendencies would provide significant advantages to companies. Moreover, unknown consumption factors that affect the economic preferences of individuals can be discovered and economic efficiency can be increased. This study shows that the numerous solution opportunities that are provided by social networks and big data have become significant tools in dynamic policy creation by companies and states, in solving problems related to women’s rights, the environment, and health. Full article
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Open AccessArticle Crowdsourcing Analysis of Twitter Data on Climate Change: Paid Workers vs. Volunteers
Sustainability 2017, 9(11), 2019; doi:10.3390/su9112019
Received: 25 September 2017 / Revised: 27 October 2017 / Accepted: 30 October 2017 / Published: 3 November 2017
PDF Full-text (1639 KB) | HTML Full-text | XML Full-text
Abstract
Web based crowdsourcing has become an important method of environmental data processing. Two alternatives are widely used today by researchers in various fields: paid data processing mediated by for-profit businesses such as Amazon’s Mechanical Turk, and volunteer data processing conducted by amateur citizen-scientists.
[...] Read more.
Web based crowdsourcing has become an important method of environmental data processing. Two alternatives are widely used today by researchers in various fields: paid data processing mediated by for-profit businesses such as Amazon’s Mechanical Turk, and volunteer data processing conducted by amateur citizen-scientists. While the first option delivers results much faster, it is not quite clear how it compares with volunteer processing in terms of quality. This study compares volunteer and paid processing of social media data originating from climate change discussions on Twitter. The same sample of Twitter messages discussing climate change was offered for processing to the volunteer workers through the Climate Tweet project, and to the paid workers through the Amazon MTurk platform. We found that paid crowdsourcing required the employment of a high redundancy data processing design to obtain quality that was comparable with volunteered processing. Among the methods applied to improve data processing accuracy, limiting the geographical locations of the paid workers appeared the most productive. Conversely, we did not find significant geographical differences in the accuracy of data processed by volunteer workers. We suggest that the main driver of the found pattern is the differences in familiarity of the paid workers with the research topic. Full article
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Open AccessArticle Impacts of Leadership on Project-Based Organizational Innovation Performance: The Mediator of Knowledge Sharing and Moderator of Social Capital
Sustainability 2017, 9(10), 1893; doi:10.3390/su9101893
Received: 21 September 2017 / Revised: 17 October 2017 / Accepted: 17 October 2017 / Published: 20 October 2017
PDF Full-text (820 KB) | HTML Full-text | XML Full-text
Abstract
With the increasing importance of leadership in project-based organizations, innovation is essential for the sustainable development of construction projects. Since few studies have explored the relationship between leadership and innovation in construction projects, this study fills this research gap and makes a significant
[...] Read more.
With the increasing importance of leadership in project-based organizations, innovation is essential for the sustainable development of construction projects. Since few studies have explored the relationship between leadership and innovation in construction projects, this study fills this research gap and makes a significant theoretical contribution to the existing body of literature. Based on a knowledge-rated and resource-based view, this study aims to investigate various effects of different types of leadership on innovation performance in a construction project-based organization. Therefore, a theoretical model was constructed to explore the mediation mechanism and boundary condition of different types of leadership to improve innovation. The theoretical model was validated with empirical data covering project managers and engineers from the project-based organization in China via regression analysis and path analysis. The results show that transformational leadership and transactional leadership have some positively significant effects on knowledge sharing and innovation performance. Meanwhile, knowledge sharing partially mediates the relationship between transformational leadership and/or transactional leadership and innovation performance. Additionally, by considering different levels of social capital, transformational leadership is likely to have a strong positive impact on innovation performance through knowledge sharing. Our findings ensure a better understanding of the role of leadership, knowledge management, and social capital in the innovation process of construction projects. Therefore, project managers should promote a higher stimulation of a leadership behavior, encouraging knowledge management, and establishing the social capital, thus improving the innovation performance in the project-based organizations in construction projects. Full article
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Open AccessArticle Role of Human Knowledge and Communication on Operational Benefits Gained from Six Sigma
Sustainability 2017, 9(10), 1721; doi:10.3390/su9101721
Received: 9 August 2017 / Revised: 15 September 2017 / Accepted: 21 September 2017 / Published: 26 September 2017
PDF Full-text (893 KB) | HTML Full-text | XML Full-text
Abstract
Six Sigma (SS) is a production philosophy focused on human experiences and knowledge, aimed to minimize defects of products and services. The appropriate implementation of SS requires an education process, reliable data analysis, efficient didactic material, statistical techniques and human knowledge to improve
[...] Read more.
Six Sigma (SS) is a production philosophy focused on human experiences and knowledge, aimed to minimize defects of products and services. The appropriate implementation of SS requires an education process, reliable data analysis, efficient didactic material, statistical techniques and human knowledge to improve communication and operational benefits. In this article, we present a structural equation model integrating those aspects as latent variables and relating them with ten hypotheses. Data for hypothesis validation were gathered among 301 manufacturing companies, and assessed using partial least squares (PLS) to estimate direct, indirect, and total effects. As results, we found that access to reliable information, trusted analysis and knowledgeable management are crucial for SS implementation at the problem definition stage. Likewise, to execute and control SS projects, it is important to be trained in statistical techniques through clear didactic materials. Full article
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Open AccessArticle What Makes Firms Innovative? The Role of Social Capital in Corporate Innovation
Sustainability 2017, 9(9), 1564; doi:10.3390/su9091564
Received: 7 August 2017 / Revised: 24 August 2017 / Accepted: 31 August 2017 / Published: 3 September 2017
PDF Full-text (768 KB) | HTML Full-text | XML Full-text
Abstract
This paper offers a social capital explanation for the purported relationship between human capital investment and an organization’s innovation capability. We argue that social capital plays a mediating role in the relationship between the level of individual knowledge of employees and organizations’ innovation
[...] Read more.
This paper offers a social capital explanation for the purported relationship between human capital investment and an organization’s innovation capability. We argue that social capital plays a mediating role in the relationship between the level of individual knowledge of employees and organizations’ innovation capabilities. The mediating mechanism is attributed to the role of social capital in knowledge exchange and combination that help enhance knowledge creation. Using survey data of 319 manufacturing firms in Korea, we conducted structural equation modeling (SEM) analysis to verify the mediating role of social capital in firms’ innovation performance. The results demonstrated that relational and cognitive dimensions of social capital are important mediators in realizing organizational innovation performance. Full article
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Knowledge creation process and sustainable competitive advantage: The role of technological innovation capabilities
Abstract: This study examines the relationship between knowledge creation process and technological innovation capabilities, and analyzes their effect on firms’ sustainable competitive advantage using a
knowledge-based view theoretical framework. We conduct hierarchical linear regression and structural equation modeling analyses using survey data from 315 Chinese industrial firms to test the direct and indirect effects of the knowledge creation process on sustainable competitive advantage. Technological innovation capabilities – operationalized to reflect the dimensions of process innovation capability and product innovation capability – are used as the mediating variables for explaining the relationship between knowledge creation process and sustainable competitive advantage. The results confirm that the significance of the direct effect of knowledge creation process on sustainable competitive advantage is reduced when the indirect effect of knowledge creation process through technological innovation capabilities is included in a total effect model. Consequently, knowledge creation process favors the development of technological innovation capabilities and that both knowledge creation process and technological innovation capabilities for products and processes can lead to sustainable competitive advantage.

 

Title: Top Management Team’s Characteristics, Risk Perceptions and Strategic Decision Behavior- The Role of Mental mode and Psychological Ownership
Abstract: Strategicdecision making is a key factor for enterprise to sustain and develop. Moreover, the TMT (Top ManagementTeam) of enterprise is one important core of decision making. This studyemploys Structural Equation Model toanalyzequestionnaires among TMT’s characteristicsand risk perceptionsof the decisions making while testing the mental mode and psychological ownership between the moderating effects. We investigated 289 valid questionnaires of TMT in the China’s enterprises, and found TMT’s characteristics plays as mediating factor and are affected by risk perception and decision making. We also found mental mode and psychological ownership have the moderating effect between risk perception and decision making. This research concludes with a discussion of the theoretical and managerial implications for enterprise owner.

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