Green innovation has become one of the mainstream concepts to address environmental issues. However, research on green innovation, especially at the firm level, is still evolving. Building upon the natural resource-based view (NRBV) and resource-based theory (RBT) lenses, this study proposes a research framework to explore determining factors of green innovation adoption (GIA) in the Brazilian cassava agribusiness sector. The research design from the semi-structured interviews method was employed in firms associated with ABAM (Brazilian Association of Starch and Cassava Producers) and SIMP (Union of Cassava Producers in Paraná). The findings suggest that behavioral factors for GIA, such as collaborative behaviors, productivity, safety behaviors, and green behaviors, are directly associated with other determining factors, such as knowledge, operating costs, stakeholder pressure, economic benefits, information access, customer assessment, organizational compatibility, and business support. Furthermore, GIA can lead to the effective implementation of sustainable practices to enhance economic performance and effective environmental management. The originality of this work stems from including behavioral factors for managers’ decision-making regarding resource allocation for GIA. It also includes a guideline to increase competitiveness in active green markets. It also contributes to a vision of GIA to evolve NRBV and RBT theories.

Collaborative innovation become one of the most strategy decision across firms and a well-defined phenomenon that became popular among practitioners and researchers (A. S. Cui O’Connor, 2012; Liu et al., 2017). Many theories were considered to explain collaboration phenomena such as resources-based view, organization theory, strategy, information processing theory, the economic theory of complementarities among others (Barney, 1991; Cassiman Veugelers, 2006; Daft Lengel, 1986; Milgrom Roberts, 1995; Tushman Nadler, 1978). However, technology advances provide new variations in collaboration to innovativeness. For example, collaborative activities with suppliers and customers (Karhade Dong, 2021), community source projects (Liu et al., 2017) or collaboration with distant partners (T. Cui et al., 2020), corporate engagement with startups (Shankar Shepherd, 2019), innovation networks (Aarikka-Stenroos et al., 2017), and innovation ecosystems (Granstrand Holgersson, 2020).Collaborative innovation takes over the existence of an inter-organizational activities executed by people that together perform with high level of interdependence something innovative (T. Cui et al., 2020; Davis Eisenhardt, 2011). Some authors (Adner Kapoor, 2010; T. Cui et al., 2020; Rico et al., 2008) highlight that this interdependence is characterized along two dimensions: technological and behavioral. Technological interdependence is linked to knowledge and the exchange of resources for research and development, and behavioral interdependence is associated with the field of communication, social interaction between collaborative actors and the coordination of these relationships to innovate.Other perspectives in the literature explain and theorize about collaborative innovation as knowledge-sharing trajectories (Majchrzak Malhotra, 2016; Trkman Desouza, 2012), or multi-actor collaboration (Torfing, 2019), or building collaborative capabilities (Swink, 2006) among other approaches. In this editorial, we bring some thoughts and idea about collaborative innovation under a technological perspective to incentive researchers to go beyond in innovative technologies research embedded in collaboration.Collaboration efforts also became a common way of firms to enhance innovations and its technological development with clear determinants about their beneficial effects, and therefore, the literature is well stablished in this subject (Pereira et al., 2018). However, collaboration only succeeds when technological resources and capabilities are combined, and parties define jointly how to enhance and use them accordingly (Snow, 2015).Collaborative innovation as a new technological paradigm refers to a network innovation model supported by interactions of multiple parties such as enterprises, universities and research institutions as core elements and government, financial institutions, nonprofit organizations, intermediaries as auxiliary elements (W. Zhang et al., 2021). Notwithstanding, collaboration networks operating in different organizational levels are present in various patterns and characteristics of evolution, they require different actors and capabilities in the network composition to become a remarkable asset in developing technologies to be patented afterwards in some cases (Gomes et al., 2017).In facing of risks of failures during innovative trajectories, firms invest in collaborative initiatives as an attempt to mitigate cost impacts, share responsibilities and greater technical performance in the process of technology lifecycle development. Thus, technological alliances are useful means to attend these goals (Kim Song, 2007). Technological alliances are critical to enable digital transformation and innovation. Briefly, Zhang et al. (2021) highlight technological alliance as a voluntary interfirm cooperation involving codeveloping technologies through sharing and exchanging of these technologies to meet business needs (W. Zhang et al., 2021).The collaborations in various technological domains help to bring heterogenous knowledge, complementary resources, and capabilities for a better innovation performance (Swink, 2006; W. Zhang et al., 2021). Under the perspective that innovation is essentially knowledge creation (Nonaka, 1994), collaborative innovation through a technological perspective may be configured by different activities, processes, or routines of generation, sharing, integration, and utilization of knowledge produced during the innovation process lifecycle (Nonaka, 1994; W. Zhang et al., 2021). Further, this configuration of activities, processes, or routines support the development of evolutionary technological capabilities (Sampson, 2007).In the field of technological innovations, the evolution now is more collaborative in nature (J. Zhang et al., 2019). Collaboration is a trend for technological prosperity. Analyzing collaborative innovation in the literature is a great challenge even if the focus on technologies is defined because various aspects and applications of collaboration to innovate invade the academic literature in many forms. For instance, Zhou and Ren (2021) analyzed low-carbon technology collaborative innovation in industrial cluster; Shen et al. (2021) studied collaborative innovation in supply chain systems; Wan et al. (2022) highlight that blockchain application intensify collaborative innovation through distributed computing, cryptography and game theory; Li and Zhou (2022) researched on the mechanism of Government–Industry–University–Institute collaborative innovation in green technology; and Fan et al. (2022) pointed out that collaborative innovation also may act as a driver to mobilize and coordinate scientific and technological resources within a city, further promoting innovative development among cities.On the other hand, technological collaborative innovations has its own dark side for firms: it has been costly, it demands money, efforts, and time...

The e-mail allegedly attributed to Satoshi Nakamoto (supposedly a pseudonym) was transmitted 14 years ago, describing the development of an electronic currency (Nakamoto, 2008). The design of this electronic currency represented the solution of the general Byzantine problem, a well-known problem in computing, which, in general terms, defines that one of the parts of a system can intentionally fail, and with that, make the entire network unavailable. Therefore, the premise is that part of the system is corrupt (Dolev et al., 1982). In the few lines of the email, Satoshi Nakamoto described such a solution and published an article with the details made available on the same date. The article describes how to transmit information within a chain of blocks that are: synchronized with date and time (time stamp); combined with code that depends on a previous block (hash code); can be validated with public and private key cryptography framework anonymously and decentrally; but highly resilient to any tampering attempt and with public record. The concept of digital currency, in this case Bitcoin, consisted at that time of a code or token resulting from encryption and that could be included in these blocks. Blocks registered definitively in the ledgers distributed along the blockchain network that could be traced. The digital framework developed by Satoshi Nakamoto, although it emerged to make Bitcoin viable as a digital currency, has been separated over the last 14 years. Blockchain can be understood as a decentralized communication technology that gave rise to a family of other technological structures of encrypted communication such as ecosystems, public blockchain, private blockchain and blockchain networks, mainly (Mazumdar Ruj, 2022). Digital currencies, on the other hand, have also developed in variety and quantity, so much so that as we write this editorial there are over 10,000 digital currencies in operation. The total capitalization value of digital currencies rose from USD 18 billion at the beginning of 2017, surpassing USD 1.4 trillion by mid-2021 (Su et al., 2022). Currently, there is no technological impediment for companies to create their own digital currencies using a Bitcoin network or an Etherium network, for example, as well as many other networks available.Obviously, even today, there are technical challenges related, mainly, to the scalability of these networks and currencies. Bitcoin, when created, had a capacity of 7 transactions per second, currently, as we write this editorial, the transaction capacity of the Bitcoin network (BTS) is 14 transactions per second. The Etherium (ETH) network was born with a capacity of 20 transactions per second and currently has a capacity of 35 transactions per second. For comparison purposes, the VISA network has a capacity of 1700 transactions per second, which shows that there is still some way to make blockchain networks the new communication backbone, scalable for more mass uses (Chauhan Patel, 2022). There are implementations of the Solana network, for example, which promises to reach 50,000 transactions per second, still in the confirmation phase from a practical point of view, which could allow running Internet of Things (IoT) applications on this blockchain network (Duffy et al., 2021).At the same time, since 2013, the reorganization of the TCP IP structure from IPv4 (4.2 billion IP addresses) to IPv6 (79 octillion IP addresses or 7.9 x ) more than the total number of IPv4 addresses) has been implemented. Such implementation made it possible to expand connectivity to a level sufficient for the world demand, which is 56 octillion (56 x ) addresses per human being on earth. In terms of addressing, the possibilities of connecting new and future elements on the internet/blockchain communication network are guaranteed, making the IoT (Internet of Things) a real possibility.In addition to the traditional applications dedicated to making digital currency viable, especially in the last 5 years, certain works resulting from the combination of information technology and human creativity (also known as creative economy) brought NFT (Non-Fungible Token) to the management field. NFT are tokens (produced through encrypted code, subscribed in some blockchain network) that express the ownership of their author. Whoever acquires an NFT, has his/her record recorded in a ledger and, therefore, can exercise the rights or benefits related to the possession of that NFT. There are two main origins of an NFT, digital games and works of art or graphic expressions (Vasan et al., 2022). In the case of digital games, NFT can be used to record permanently and nominally the “achievements achieved” within a given game. Its owner now takes possession of a certain item that, previously, would only exist within the game itself, a virtual (digital) environment. In the case of graphic, artistic expressions, and other works of art, it is possible to make your possession digital. Works from the natural environment (physical), the result of expressions of human creativity, are now registered in an NFT-type token, coming to exist in the virtual world (digital). In this way, the works, and the data of their authorship and ownership, are permanently registered in the ledger of a blockchain network specialized in transacting NFT. As in the game, the possession of an NFT of a work of art allows the author to trade or use the benefits related to the possession of this NFT.From the convergence of connectivity technologies such as cloud computing, the advent of IPV6 and technologies based on tokens (blockchain, crypto assets and NFT not exhaustively) the concept of Web 3.0 becomes viable. Web 3.0 can be understood as a network of people and physical objects, making the integration between the natural world and the virtual world more intense (augmented, virtual and mixed reality). The idea of a Metaverse (Web 3.0 Application) depends on the technological...

Relational capabilities (RC) draw upon the relational view incorporated into different approaches in competing ways. To provide a clarification of concepts to identify trends, perspectives, and future research opportunities, we conducted a literature review through a bibliometric analysis from 1979 to 2021 publications. Additionally, we highlight the most influential papers that extensively discuss RC and its influences and variations to manage innovation. Findings identify some descriptive insights about publications and the turning point article in the literature that influenced the evolution of RC under the innovation management perspective. RC intertwines into various aspects of innovation management, such as knowledge-based co-creation, learning value, collaborative strategy, innovative ecosystems, strategic management, managing partners, and organizational growth. Therefore, the stream of innovation management leads us to conceptualize RC, highlighting opportunities for further research to solidify RC’s significance. By reviewing and identifying the most influential papers and their authors and systematizing existing knowledge on RC, this research produces theoretical contributions for dynamic capabilities and innovation theory. From a practitioner standpoint, managers likely look at relational resources and strategies towards innovativeness from a new perspective understanding that relational rents exist.

Objetivo: Apresentar a análise de conteúdo baseada em classificação hierárquica descendente e a análise fatorial de correspondência como técnicas complementares e sequenciais, com possível aplicação na área de gestão da inovaçãoMétodo: Análise de conteúdo baseada em técnicas de Computer-Aided Text Analisys (CATA) por meio do software IRAMUTEQ.Originalidade/Relevância: O paradigma de pesquisa, normalmente influencia as próprias bases de conhecimento e metodologias de domínio do pesquisador. A análise de textos manual pode eventualmente ser atribuída ao paradigma interpretativista e as técnicas CATA podem ser eventualmente atribuídas ao paradigma pós-positivista, no entanto, não parece haver razão para fazer essa distinção.Resultados: Apresentação de framework que demonstra as escolhas tecnológicas das empresas mais inovadoras do mundo (Google, Apple e Amazon), as escolhas comuns e as distintas, entre elas.Contribuições teóricas/metodológicas: Desenvolvimento de método de análise de escolhas tecnológicas das empresas mais inovadoras do mundo, aplicando a análise de conteúdo com base na classificação hierárquica descendente e a análise fatorial de correspondência de forma sequencial e complementar.Contribuições sociais / para a gestão: As tomadas de decisões para a gestão da inovação podem ser revistas de acordo com as escolhas tecnológicas apresentadas. A vantagem competitiva tem por natureza a distintividade. Demonstramos que não é um problema dominar as mesmas tecnologias, ou seja, empresas podem ter domínios tecnológicos similares e ainda assim terem abordagens mercadológicas diferentes.

In this study, we explore how institutional theory and its many subareas contributes, are utilized and applied to the area of higher education management’s research by their scholars. For this purpose, we performed a bibliometric analysis on 659 papers extracted from Web of Science database. As results we indicate five main clusters as foundation to the field: institutional theory; economic impact of entrepreneurship and universities; competitiveness of universities as businesses; service quality and; measurement and development of models for higher education. And 7 main clusters as subfields of research: Institutional Multiplicity; Institutional pressures on Higher Education; Higher Education Efficiency; Leadership in Higher Education; Entrepreneurial Higher Education; Academy & Professional relations and; Quality and Satisfaction in Higher Education.