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This study aims to take a holistic perspective to investigate how open innovation supports sustainability and the contribution to the Unite Nations (UN) Sustainable Development Goals (SDGs).

The study is based on an in-depth single case study of Andriani SpA, a leading Italian company in the food industry. The case is built by triangulating data from direct observations, documentary analysis and semi-structured interviews.

The findings show an organization that has developed its competitive advantage by adopting open innovation to embed sustainability in its strategy and business model. The case study complements the understanding of how open innovation can effectively drive strategic renewal and innovation activities to address sustainability objectives in the food industry.

This study contributes to theoretical development by offering new and insightful explanations of firms' strategic behaviour and coevolution toward sustainability via open innovation. It provides practitioners, policymakers, researchers and students with reflections and inspiration about how open innovation may be deployed to support a holistic strategic renewal aimed at sustainability objectives, such as the SDGs, in the food industry.

The purpose of this study is to deepen understanding of the effects of using social media technologies to acquire technological knowledge and organizational learning competences, of technological knowledge competences on organizational learning and finally of organizational learning on organizational performance.

The study was performed by analyzing data from a sample of 197 technology firms located in Spain. The hypotheses were tested using a structural equations model with the program LISREL 8.80.

This study’s conceptual framework is grounded in complexity theory – along with dynamic capabilities theory, which complements the resource-based view. The study contributes to the literature by proposing a model that reflects empirically how business ecosystems that use social media technologies enable the development of interorganizational and social collaboration networks that encourage learning and development of technological knowledge competences.

It would be interesting for future studies to consider other elements to conceptualize and measure social media technologies, including (among others) significance of the various tools used and strategic integration. The model might also analyze other sectors and another combination of variables.

The results of this study have several managerial implications: developing social media technologies and interorganizational social collaboration networks not only enables the organizational learning process but also encourages technological knowledge competences. Through innovation processes, use of social media technologies also contributes to strengthening companies’ strategic positioning, which ultimately helps to improve firms’ organizational performance.

Since social media technologies drive information systems in contemporary society (because they enable interaction with numerous agents), the authors highlight the use of complexity theory to develop a conceptual framework.

The study also deepens understanding of the connections by which new experiential learning contributes to the generation of coevolutionary adaptive business ecosystems and digital strategies that enable development of interorganizational and social collaborative networks through technological knowledge competences. Only after examining the impact of social media technologies on organizational performance in prior literature, did the authors underscore that both quantity and frequency of social media technology use are positively related to improvement in knowledge processes that lead to employees’ creation and acquisition of new metaknowledge.

With the help of basic physics, the application of computer algorithms in the form of recent advances such as machine learning and neural networking in textile Industry has been discussed in this review. Scientists have linked the underlying structural or chemical science of textile materials and discovered several strategies for completing some of the most time-consuming tasks with ease and precision. Since the 1980s, computer algorithms and machine learning have been used to aid the majority of the textile testing process. With the rise in demand for automation, deep learning, and neural networks, these two now handle the majority of testing and quality control operations in the form of image processing.

The state-of-the-art of artificial intelligence (AI) applications in the textile sector is reviewed in this paper. Based on several research problems and AI-based methods, the current literature is evaluated. The research issues are categorized into three categories based on the operation processes of the textile industry, including yarn manufacturing, fabric manufacture and coloration.

AI-assisted automation has improved not only machine efficiency but also overall industry operations. AI's fundamental concepts have been examined for real-world challenges. Several scientists conducted the majority of the case studies, and they confirmed that image analysis, backpropagation and neural networking may be specifically used as testing techniques in textile material testing. AI can be used to automate processes in various circumstances.

This research conducts a thorough analysis of artificial neural network applications in the textile sector.

This document presents BasES, which is a tool kit disseminated as an open educational resource. BasES is focused on the topic of buildings-as-energy services, promoting the knowledge integration to envisage buildings as components of future distributed renewable and interactive energy systems (DRIs). BasES will allow users of exploring and analysing DRIs' emergent properties at the local level, developing, and implementing the tool kit proposed. The specific objective concerns the use of the tool kit in the organisation of a technology support net (TSN) for buildings-as-a-service. TSN is composed of a multitude of actors, who often have different perspectives and scopes, but they are called to work collaboratively in order to establish work rules, requisite skills, work contents, standards and measures, culture and organisational patterns with regard to the emergent systems. Buildings-as-a-service is a completely new topic, and thus, an appropriate TSN is needed urgently. Our tool kit (i.e. Buildings-as-Energy-Services; BasES) will be a ground-breaking cognitive apparatus for involving stakeholders in knowledge transfer and integration processes. Thus, a new generation of product-service systems will be promoted. BasES is expected to configure a multi-stakeholder co-designed UK roadmap on socio-technical innovation in DRIs transition.

This study applies bibliometric analysis to explore the evolution of the research paradigm of agility related to management and organisations.

Authors prepared a quantitative study of the review of selected articles using co-citation analysis and bibliographic coupling. Based on the bibliometric analyses, the evolution of the agility field (past, present, and future of agility research) was prepared.

Emergent themes focus on the importance of agility in interpreting organisational responses in the context of issues as diverse as information systems and business intelligence systems, market orientation, strategic alignment and social computing. Future research needs to focus on digitisation in conjunction with informatisation, an important topic for creating a new organisational culture and knowledge management through increased collaboration between humans and machines.

As the authors are aware, this study is one of the first to choose to show the overall development and importance of agility through quantitative bibliometric methods used to assess the value and contribution of scientific productivity and its impact on development.