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Purpose: Innovation and sustainability are key in today's competitive world. It is no longer possible to conceive an organization that has not incorporated these two elements for it to become successful. The longitudinal bibliometric study seeks to examine the topography of innovation and sustainability to determine whether there is already a terminological integration that could be defined as innovation capability in a sustainable way. The objective of this work is to identify the growth trajectories of the literature, the countries considered as knowledge nodes, the most influential authors, the classification of journals, clusters and collaborative networks measured by co-citation, the analysis by keywords, countries and knowledge areas. Design/methodology/approach: The study is developed under the bibliometric approach, and the period 1990–2018 was considered. The steps taken were as follows: 16 keywords of each term were identified and selected in 3 methodological layers by a panel of experts; an algorithm was designed and applied to identify these selected keywords in the titles, abstracts and keywords using terms in the Web of Science (WoS) of Clarivate Analytics to contrast them; and a review in specialized journals was carried out in the first quartile (Q1) of the WoS until 2018. Findings: The most relevant finding of the study lies in the sustained growth of the convergence of the terms innovation and sustainability. In addition, the longitudinal review of the two concepts also shows that innovation is directly linked to sustainability, suggesting that the convergence of concepts and practices becomes part of the strategy of companies seeking to be competitive and sustainable. Practical implications: At the management level, this research seeks to present a definition of innovability based on the convergence of the concepts of innovation and sustainability. This new concept can be applied as a management strategy for companies seeking to be competitive and sustainable. Theoretical and practical evidences that reinforce this construct are presented. At the academic level, the manuscript shows a longitudinal review on innovation and sustainability, a relevant scientific mapping and, finally, a new theoretical and practical concept is proposed that seeks to create strategies for competitiveness in a sustainable way. At the level of society, the study contributes to the sustainable development goals. Originality/value: The results show that a field of studies on innovation is emerging that has a high potential to position itself as a new space for research. The concept of "innovability" is proposed. [ABSTRACT FROM AUTHOR]

Abstract Organizational innovation requires strong social collaboration and knowledge networks as well as focused partner selection strategies that complement employee strengths. Therefore, this paper proposes an effective, innovative partner selection method on the basis of collaboration network deconstruction optimization using collaboration and knowledge networks. To ensure collaborative network deconstruction optimization, the proposed method firstly improves the focal actor's management efficiency by eliminating network redundancy and identifying the key primary contacts. Then, to fully consider the knowledge benefits to be gained from joint collaboration, the knowledge fusion process is modeled using knowledge combinations from the knowledge networks. Further, social benefits and knowledge benefits maximization are jointly considered in the selection of suitable partners. And at last, a case study is given that demonstrates the proposed method is highly effective in selecting suitable partners for the focal actor that significantly improves both the social and knowledge benefits. [ABSTRACT FROM AUTHOR]

This paper introduces a novel method aimed at enhancing online-to-offline (O2O) services recommendations by utilizing two-layer knowledge networks. The primary objective of this method is to assist consumers in efficiently navigating the myriad of options available when choosing O2O services. Using co-occurrence relationships, we construct a two-layer knowledge network system, comprising a service knowledge network based on service usage information as the first layer and a consumer knowledge network, built on "co-used" behaviors as the second layer. The former is established upon service use data, while the latter is founded on "co-used" behaviors among consumers. The features and information of these two knowledge networks can complement each other to produce precise and effective recommendations. Empirical findings gained from our experiments demonstrate that: (1) the proposed recommendation method outperforms widely-used and state-of-the-art recommendation methods; (2) both the service knowledge network and consumer knowledge network play an equally significant role in O2O service recommendations; (3) the location of O2O services is an essential factor in consumers' choices for services. Notably, this research also identifies the optimal parameter settings for the proposed recommendation method. [ABSTRACT FROM AUTHOR]

• The R packages' network has one biggest connected component. • Most packages are in the connected component or are independent. • Superlinear preferential attachment in dependency and suggestion relationships. • Lognormal distribution of added connections per package. • Power law distributions in dependency and suggestion networks. We analyze the evolution of the main package library of the programming language R, a free and open-source software used in Statistics, Economics, Machine Learning, Geography, and many other fields. R-packages are self-contained pieces of the software that can relate to each other through dependency and suggestion relationships, giving rise to empirical collaborative networks that have grown significantly in the last twenty years. The dependency network connects two packages if one requires another, and the suggestion network connects packages if there are examples using them together. Each network's structure is composed by two main groups: the biggest connected component (BCC) and the set of independent packages, isolated from the rest. We characterize how new packages enter the network in terms of the number of connections they incorporate, and the packages they connect to. The number of incorporated connections follows a log-normal distribution, whose scale is linear on the fraction of packages in the BCC. We characterize to which packages the incomers connect to in terms of preferential attachment, finding super-linear preferential attachment in both networks. We provide a detailed characterization of the network's evolution, and point possible links to the history of the R community. The constructed dataset with the networks at different times is freely available through a public repository. [ABSTRACT FROM AUTHOR]

Community-based Natural Resource Management (CBNRM) focuses on the collective management of ecosystems to promote human well-being and aims to devolve authority for ecosystem management to the local (community) level. CBNRM therefore requires strong investments in capacity development of local institutions and governance structures. CBNRM has come under strong criticism for its failures to deliver real benefits to communities. In this paper we explore the reasons for the frequent failure of CBNRM. We postulate that good governance buffers CBNRM against unexpected change, notably conflicts, especially in the early stages when income generation, infrastructure development and capacity development have not yet taken place. We assess the key characteristics of CBNRM governance systems that could perform this buffering function, using case study examples from Macubeni, Nqabara, Makuleke and Richtersveld to support our propositions. In our case studies, 11 strategies have been used to increase the incidence of success of CBNRM: understand and describe the social-ecological system; establish and communicate a clear vision; build on local organizations: plan ahead: create rules for resource use and enforce them: communicate the vision, plan and rules; develop management capacity: finance the initial stages of the initiative: work within available legal frameworks: monitor and learn all the time: and create lasting incentives. Despite these strategies there are, however, a number of obstinate implementation challenges, related to governance shortcomings and external factors which management cannot control. We therefore propose seven additional strategies to promote good governance in CBNRM: 1. Develop knowledge networks that draw on the experience and wisdom of a wide range of key individuals. 2. Establish formulised decision-making structures (e.g. multi-level project steering committees) with clear constitutions and codes of conduct. 3. Clearly define and legitimise conflict resolution procedures. 4. Ensure acceptance of the governance structure by community members. 5. Obtain formal commitment to well-defined roles and responsibilities by key individuals. 6. Establish tangible incentives to key individuals for meeting their commitments. 7. Develop the capacity for facilitation to promote communication. Local communities, government and scientists have important roles to play in maintaining these knowledge and governance networks through adaptive co-management. [ABSTRACT FROM AUTHOR]