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Social innovation is a recent theme, and the practices related to this area are characterized by punctual actions and projects restricted by time and space that make it difficult to develop strategies that can be sustained in this field. Therefore, one point that deserves to be highlighted in studies on social innovation is a matter of scalability. This paper aims to deal with a bibliometry whose objective was to map the existing studies about scalability of social innovation carried out in the Capes and EBSCOHost portals.

This paper deals with a bibliometry. The topic researched in this bibliometry is scalability of social innovation. The databases chosen for this research were Portal Periódico Capes and EBSCOHost because they are the leading providers of search databases.

A total of 42 papers were considered, distributed between 2002 and 2017. The analysis criteria for the study were origin (composed by year, author, country of origin, periodical and impact factor), focus of the investigations, justification, method and main techniques of research, contributions and theoretical advances and challenges and paths.

Among the main results found, one of them is that scalability is a topic that began to be researched recently, so that the USA and Brazil lead the research. Most of the studies focused on the scalability process and justified the importance of studies on the subject as a way to explore the potential of expanding the social impacts of a social innovation. Several studies have emphasized the role of networks as being quite positive for the scalability process and have been concerned with identifying factors that contribute to the scalability process. The challenge that most stood out among the papers was the financial sustainability of a social innovation. At the end, a research agenda was proposed.

The study aimsto analyze the main elements associated with the evolution of Brazilian agtechs from the initial conception of the business model to becoming companies in the scale-up stage.

The exploratory research was conducted based on data collected through in-depth interviews. The answers were analyzed quantitatively using descending hierarchical classification (DHC) and correspondence factor analysis (CFA) and qualitatively using content analysis.

Five main elements were identified as responsible for the evolution of the companies up to their entering the scale-up phase: (1) governance, (2) decisions inherent to resource allocation, (3) monitoring of strategic, tactical and operational activities, (4) fostering human capital development and (5) business model validation. Each element presents a set of performance indicators that show the scalability of these companies.

The model developed can help companies that have not yet advanced from the conception of the business model to the scalability of different sectors, in addition to agribusiness.

Proposal of a model that presents the main elements that impact on scalability and respective indicators that contributed to the scalability process of Brazilian agtechs.

This study contributed to advancing the knowledge on the organizational life cycle (OLC) of agricultural startups, particularly regarding the factors responsible for their scalability.

Technological developments and new customer expectations of immediacy have driven businesses to adopt on-demand service models. The purpose of this paper is to study the characteristics of a range of on-demand services in order to better understand the meaning of “on-demand” and its implications for service management. This enables the on-demand service logic to be applied to other service contexts, where it may add value for customers.

The study starts with a focused literature review and continues with a multiple case study methodology, as the on-demand service concept is in the early stages of theory development. Seven cases were studied, based on a maximum variation sampling strategy.

The results show that on-demand services are characterized by three interrelated characteristics: being highly available, responsive and scalable. Analysis further reveals that on-demand services display differences within the conceptual boundaries of these characteristics, i.e. they vary in terms of their availability, responsiveness and scalability.

Drawing on these findings, the study contributes to the service literature by being the first to specifically conceptualize and define the on-demand services concept and reveal three key characteristics that clarify the distinctive nature of this service type. Accordingly, on-demand services are clearly differentiated from other services. Additionally, the paper discusses the variety within on-demand services and develops an on-demand service continuum that gives detailed insights into the conceptual variations within such services.

This study aims to determine how the applications of blockchain technology (BT) can play a crucial role in managing financial flows in the humanitarian supply chain (HSC) and what benefits and challenges are associated with BT in a humanitarian setting.

The present study used a qualitative research approach, incorporating a systematic literature review and conducting semi-structured interviews with 12 experts in the fields of humanitarian operations, supply chain management, fintech and information technology.

The findings show that the humanitarian sector has the potential to reap significant benefits from BT, including secure data exchange, efficient SCM, streamlined donor financing, cost-effective financial transactions, smooth digital cash flow management and the facilitation of cash programs and crowdfunding. Despite the promising prospects, this study also illuminated various challenges associated with the application of BT in the HSC. Key challenges identified include scalability issues, high cost and resource requirements, lack of network reliability, data privacy, supply chain integration, knowledge and training gaps, regulatory frameworks and ethical considerations. Moreover, the study highlighted the importance of implementing mitigation strategies to address the challenges effectively.

The present study is confined to exploring the benefits, challenges and corresponding mitigation strategies. The research uses a semi-structured interview method as the primary research approach.

This study adds to the existing body of knowledge concerning BT and HSC by explaining the pivotal role of BT in improving the financial flow within HSC. Moreover, it addresses a notable research gap, as there is a scarcity of studies that holistically cover the expert perspectives on benefits, challenges and strategies related to blockchain applications for effective financial flows within humanitarian settings. Consequently, this study seeks to bridge this knowledge gap and provide valuable insights into this critical area.

Major public cloud providers, such as AWS, Azure or Google, offer seamless experiences for infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS). With the emergence of the public cloud's vast usage, administrators must be able to have a reliable method to provide the seamless experience that a public cloud offers on a smaller scale, such as a private cloud. When a smaller deployment or a private cloud is needed, OpenStack can meet the goals without increasing cost or sacrificing data control.

To demonstrate these enablement goals of resiliency and elasticity in IaaS and PaaS, the authors design a private distributed system cloud platform using OpenStack and its core services of Nova, Swift, Cinder, Neutron, Keystone, Horizon and Glance on a five-node deployment.

Through the demonstration of dynamically adding an IaaS node, pushing the deployment to its physical and logical limits, and eventually crashing the deployment, this paper shows how the PackStack utility facilitates the provisioning of an elastic and resilient OpenStack-based IaaS platform that can be used in production if the deployment is kept within designated boundaries.

The authors adopt the multinode-capable PackStack utility in favor of an all-in-one OpenStack build for a true demonstration of resiliency, elasticity and scalability in a small-scale IaaS. An all-in-one deployment is generally used for proof-of-concept deployments and is not easily scaled in production across multiple nodes. The authors demonstrate that combining PackStack with the multi-node design is suitable for smaller-scale production IaaS and PaaS deployments.

The present study seeks to outline the role of marketing automation (MA) in measuring the return on marketing activities and the challenges associated with reaching accountability in marketing.

To investigate the objective of the study, the authors adopted a qualitative approach, conducting an exploratory study among ten key informants located in Portugal.

Based on the results of the qualitative analysis, a conceptual framework is proposed, which includes both strategic- and operational-level factors with the goal of creating a value-based agenda. In this agenda, executives such as the Chief Marketing Officer emerge as value creators, fostering business scalability, and further arguments are provided to justify budget allocation to MA activities.

Through careful research of the elements that characterize the phenomenon under study, the present paper ultimately contributes to a better understanding of MA and accountability within the current business paradigm.

The scalability of similarity joins is threatened by the unexpected data characteristic of data skewness. This is a pervasive problem in scientific data. Due to skewness, the uneven distribution of attributes occurs, and it can cause a severe load imbalance problem. When database join operations are applied to these datasets, skewness occurs exponentially. All the algorithms developed to date for the implementation of database joins are highly skew sensitive. This paper presents a new approach for handling data-skewness in a character- based string similarity join using the MapReduce framework. In the literature, no such work exists to handle data skewness in character-based string similarity join, although work for set based string similarity joins exists. Proposed work has been divided into three stages, and every stage is further divided into mapper and reducer phases, which are dedicated to a specific task. The first stage is dedicated to finding the length of strings from a dataset. For valid candidate pair generation, MR-Pass Join framework has been suggested in the second stage. MRFA concepts are incorporated for string similarity join, which is named as “MRFA-SSJ” (MapReduce Frequency Adaptive – String Similarity Join) in the third stage which is further divided into four MapReduce phases. Hence, MRFA-SSJ has been proposed to handle skewness in the string similarity join. The experiments have been implemented on three different datasets namely: DBLP, Query log and a real dataset of IP addresses & Cookies by deploying Hadoop framework. The proposed algorithm has been compared with three known algorithms and it has been noticed that all these algorithms fail when data is highly skewed, whereas our proposed method handles highly skewed data without any problem. A set-up of the 15-node cluster has been used in this experiment, and we are following the Zipf distribution law for the analysis of skewness factor. Also, a comparison among existing and proposed techniques has been shown. Existing techniques survived till Zipf factor 0.5 whereas the proposed algorithm survives up to Zipf factor 1. Hence the proposed algorithm is skew insensitive and ensures scalability with a reasonable query processing time for string similarity database join. It also ensures the even distribution of attributes.

This research aims to explore leadership approaches that foster deeper learning and facilitate the transition from traditional schooling to a model aligned with the demands of the post-industrial digital knowledge society.

Employing a mixed-methods approach, the authors conducted surveys among school principals within a network of schools embracing deeper learning based on ten distinct but interlocking criteria that define this particular model of deeper learning. Through in-depth follow-up interviews with school leaders, the authors investigated the factors and obstacles that support sustainable implementation and scalability of deeper learning, with a specific focus on the role of transformational leadership.

During the implementation of transformative practices like deeper learning, school leaders demonstrate diverse perspectives on the necessary changes for their successful integration. Leaders inclined toward a “transactional” leadership style concentrate on changes within individual classrooms. Conversely, leaders exemplifying “transformational leadership” possess a broader vision and address systemic factors such as teacher collaboration, assessment regulations and the effective utilization of time and space within schools. To achieve widespread adoption of deeper learning across schools and the education system, it is essential to recruit more transformational leaders for formal leadership positions and reorient leadership training toward transformational approaches.

The deeper learning model developed for this intervention encompasses a four-stage process: Teachers initially collaborate in small teams to co-design interdisciplinary, deeper learning units. The actual units consist of three sequences: knowledge acquisition, where students gain knowledge through direct instruction supplemented by personalized learning on digital platforms; team-based co-creative and co-constructive tasks facilitated by teachers once students have acquired a solid knowledge base and the completion of authentic tasks, products or performances in sequence III. While small groups of intrinsically motivated teachers have successfully implemented the model, achieving broader scalability and dissemination across schools requires significant “transformational leadership” to challenge traditional norms regarding teacher collaboration, assessment practices and the efficient use of time and space in schools.

This paper presents a structured model of deeper learning based on ten distinct but interlocking quality criteria tested within a network of 26 schools. The model has demonstrated transformative effects on participating schools, albeit primarily observed in smaller substructures of large secondary schools. Teachers who previously worked independently have begun to collaboratively design learning experiences, resulting in “hybrid” classrooms where physical and digital spaces merge and extend to include maker spaces and out-of-school learning environments. Traditional summative assessments have been replaced by various forms of embedded formative assessment. However, these innovations are currently driven by small groups of intrinsically motivated teachers. The research provides insights into the type of school leadership necessary for comprehensive scaling and system-wide dissemination of deeper learning.

Block chain technology (BCT) has apparent capability of handling information in digital format, which has dragged attention of the practitioners for its utility in industrial and manufacturing practices. Conversely, the managerial adoption of BCT is relatively limited, which motivated the authors to identify crucial dimensions that can persuade the acceptance of BCT from an executive perspective. Thus, the present study is aimed to conduct to understand crucial barriers under BCT for managerial implementation in supply chain management (SCM) of small and medium enterprises (SMEs).

The present study investigated evident barriers to understand implementation of BCT. A questionnaire based survey is performed to collect primary data from service and manufacturing based companies in India. Survey responses are received online and the data is analyzed in a scorecard. The scorecard embedded the scribed entries of Likert scale to determine the relative score.

In present study, sixteen barriers from three categories named as technological, organizational and environmental are evaluated, where, five sub-barriers from technological domain, seven sub-barriers from organizational domain and four sub-barriers from environmental domain are evaluated. The findings of the study determined that the three factors, i.e. “complexity in setup/use”, “Security and privacy concern” and “Technological awareness” mostly affect the adaptation of BCT in SCM. Conversely, “Market dynamics”, “Scalability” and “Cost” do not influence the intention to adopt the technology.

Only few studies have endeavored to ascertain the BCT adoption in SCM of SMEs in developing country like India. Thus, the study is filling a momentous gap of mapping BCT dimensions in the scholastic literature. The findings are expected to enable SMEs to understand important factors to be considered for adopting BCT in their curriculum. Furthermore, the study may benefit the BCT developers and suppliers to endure customized solutions based on the findings.

Blockchain technology is one of the emerging innovative technologies making waves globally, and it has been adjudged to have the capability to transform businesses. With the different capabilities of the technology, such as immutability of information and decentralisation of authority attributes, the built environment is slow in its adoption. This study aims to explore the barriers to the implementation of blockchain technology in the construction using a principal component analysis (PCA) approach.

This research took a post-positivist philosophical stance, which informed a quantitative research approach through a questionnaire survey. From the South African built environment and information technology sector, 79 respondents were drawn through a snowballing sampling technique. The built environment professionals include architect, construction project manager, construction manager, quantity surveyor and engineer. Retrieved data were screened and analysed by adopting the descriptive analysis and PCA while Cronbach alpha evaluated the reliability. Also, Kruskal–Wallis H non-parametric test was used to determine the differences in the opinion of the respondent groups.

The analysis revealed that all the identified barriers ranked above the average mean with lack of clarity, scalability risks and lack of skills or knowledge ranking top three. PCA clustered the identified barriers into three components: organisational barriers, social barriers and technological barriers.

This study was carried out in the Gauteng province of South Africa, leaving out other provinces due to accessibility, cost and time constraints.

Built environment organisations need to be kept abreast of the capabilities of blockchain technology as the major barrier observed was the lack of clarity of blockchain technology. Also, the technological barriers identified from this study need to be addressed by information technology experts to give consumers the desired value for money in implementing blockchain technology for the built environment.

The blockchain technology capabilities are incomparable to any other invention thus far. Therefore, it is very important that the numerous stakeholders in the built environment be made aware of the blockchain technology capabilities while formulating a solution to the identified barriers. This will aid its implementation in the built environment and help the industry measure up with its counterparts.