Cloud-computing strategies for sustainable ICT utilization : a decision-making framework for non-expert Smart Building managers

Virtualization of processing power, storage, and networking applications via cloud-computing allows Smart Buildings to operate heavy demand computing resources off-premises. While this approach reduces in-house costs and energy use, recent case-studies have highlighted complexities in decision-making processes associated with implementing the concept of cloud-computing. This complexity is due to the rapid evolution of these technologies without standardization of approach by those organizations offering cloud-computing provision as a commercial concern. This study defines the term Smart Building as an ICT environment where a degree of system integration is accomplished. Non-expert managers are highlighted as key users of the outcomes from this project given the diverse nature of Smart Buildings’ operational objectives. This research evaluates different ICT management methods to effectively support decisions made by non-expert clients to deploy different models of cloud-computing services in their Smart Buildings ICT environments. The objective of this study is to reduce the need for costly 3rd party ICT consultancy providers, so non-experts can focus more on their Smart Buildings’ core competencies rather than the complex, expensive, and energy consuming processes of ICT management. The gap identified by this research represents vulnerability for non-expert managers to make effective decisions regarding cloud-computing cost estimation, deployment assessment, associated power consumption, and management flexibility in their Smart Buildings ICT environments. The project analyses cloud-computing decision-making concepts with reference to different Smart Building ICT attributes. In particular, it focuses on a structured programme of data collection which is achieved through semi-structured interviews, cost simulations and risk-analysis surveys. The main output is a theoretical management framework for non-expert decision-makers across variously-operated Smart Buildings. Furthermore, a decision-support tool is designed to enable non-expert managers to identify the extent of virtualization potential by evaluating different implementation options. This is presented to correlate with contract limitations, security challenges, system integration levels, sustainability, and long-term costs. These requirements are explored in contrast to cloud demand changes observed across specified periods. Dependencies were identified to greatly vary depending on numerous organizational aspects such as performance, size, and workload. The study argues that constructing long-term, sustainable, and cost-efficient strategies for any cloud deployment, depends on the thorough identification of required services off and on-premises. It points out that most of today’s heavy-burdened Smart Buildings are outsourcing these services to costly independent suppliers, which causes unnecessary management complexities, additional cost, and system incompatibility. The main conclusions argue that cloud-computing cost can differ depending on the Smart Building attributes and ICT requirements, and although in most cases cloud services are more convenient and cost effective at the early stages of the deployment and migration process, it can become costly in the future if not planned carefully using cost estimation service patterns. The results of the study can be exploited to enhance core competencies within Smart Buildings in order to maximize growth and attract new business opportunities

Innovative public governance through cloud computing: Information privacy, business models and performance measurement challenges

Purpose: The purpose of this paper is to identify and analyze challenges and to discuss proposed solutions for innovative public governance through cloud computing. Innovative technologies, such as federation of services and cloud computing, can greatly contribute to the provision of e-government services, through scaleable and flexible systems. Furthermore, they can facilitate in reducing costs and overcoming public information segmentation. Nonetheless, when public agencies use these technologies, they encounter several associated organizational and technical changes, as well as significant challenges. Design/methodology/approach: We followed a multidisciplinary perspective (social, behavioral, business and technical) and conducted a conceptual analysis for analyzing the associated challenges. We conducted focus group interviews in two countries for evaluating the performance models that resulted from the conceptual analysis. Findings: This study identifies and analyzes several challenges that may emerge while adopting innovative technologies for public governance and e-government services. Furthermore, it presents suggested solutions deriving from the experience of designing a related platform for public governance, including issues of privacy requirements, proposed business models and key performance indicators for public services on cloud computing. Research limitations/implications: The challenges and solutions discussed are based on the experience gained by designing one platform. However, we rely on issues and challenges collected from four countries. Practical implications: The identification of challenges for innovative design of e-government services through a central portal in Europe and using service federation is expected to inform practitioners in different roles about significant changes across multiple levels that are implied and may accelerate the challenges' resolution. Originality/value: This is the first study that discusses from multiple perspectives and through empirical investigation the challenges to realize public governance through innovative technologies. The results emerge from an actual portal that will function at a European level. © Emerald Group Publishing Limited

Harnessing Artificial Intelligence Capabilities Through Cloud Services: a Case Study of Inhibitors and Success Factors

Industry and research have recognized the need to adopt and utilize artificial intelligence (AI) to automate and streamline business processes to gain competitive edges. However, developing and running AI algorithms requires a complex IT infrastructure, significant computing power, and sufficient IT expertise, making it unattainable for many organizations. Organizations attempting to build AI solutions in-house often opt to establish an AI center of excellence, accumulating huge costs and extremely long time to value. Fortunately, this deterrence is eliminated by the availability of AI delivered through cloud computing services. The cloud deployment models, Infrastructure as a Service, Platform as a Service, and Software as a Service provide various AI services. IaaS delivers virtualized computing resources over the internet and enables the raw computational power and specialized hardware for building and training AI algorithms. PaaS provides development tools and running environments that assist data scientists and developers in implementing code to bring out AI capabilities. Finally, SaaS offers off-the-shelf AI tools and pre-trained models provided to customers on a commercial basis. Due to the lack of customizability and control of pre-built AI solutions, this empirical investigation focuses merely on IaaS and PaaS-related AI services. The rationale is associated with the complexity of developing, managing and maintaining customized cloud infrastructures and AI solutions that meet a business's actual needs. By applying the Diffusion of Innovation (DOI) theory and the Critical Success Factor (CSF) method, this research explores and identifies the drivers and inhibitors for AI services adoption and critical success factors for harnessing AI capabilities through cloud services.Based on a comprehensive review of the existing literature and a series of nine systematic interviews, this study reveals ten factors that drive- and 17 factors that inhibit the adoption of AI developer tools and infrastructure services. To further aid practitioners and researchers in mitigating the challenges of harnessing AI capabilities, this study identifies four affinity groups of success factors: 1) organizational factors, 2) cloud management factors, 3) technical factors, and 4) the technology commercialization process. Within these categories, nine sub-affinity groups and 20 sets of CSFs are presented

Determinants influencing adoption of cloud computing by small medium enterprises in South Africa

Submitted in partial fulfillment of the requirements for the degree of Master of Commerce in Information Systems (Coursework) at the School of Economic and Business Sciences, University of the Witwatersrand, June 2017Small Medium Enterprises (SMEs) are now recognized as the driving force behind most thriving economies. This is mainly attributed to the role they play in most economies in reducing unemployment and their contribution towards Gross Domestic Product. This means that SMEs should have the right resources to enable them to enhance performance. Choosing the right technology to support their businesses is one of the important decisions that SMEs should make. Understanding the benefits and challenges of different technologies is often a problem for most SMEs. One of the new technologies that has gained prominence in recent years is cloud computing. Even though the value associated with this technology has been widely researched especially for large enterprises, the rate at which SMEs adopt cloud computing still remains low. The purpose of this research sought to explore and describe the determinants influencing the adoption of cloud computing by SMEs in South Africa. The study used Technology Organization Environment (TOE) framework as the theoretical lens in understanding the adoption of Could Computing phenomenon. Further, this qualitative exploratory and descriptive study used semi-structured interviews to collect data from five SMEs based in Johannesburg, Gauteng Province, operating in different industries and belonging to the National Small Business Chamber. The main factors that were identified as playing an important role in the adoption of cloud computing by SMEs are, relative advantage, complexity, compatibility, awareness, trialability, culture, top management support, size, regulation and trade partner relationship. It is worth noting that there was not enough evidence that competitive pressure played a significant role in SME cloud adoption.XL201

Cloud Adoption Factors in a Specific Business Area: Challenging the Findings of Organisation-Wide Cloud Computing Research

Existing literature investigates cloud adoption factors and their impact on the decision to adopt cloud services in organizations. These studies consider the decision to adopt cloud services as a horizontal organization-wide decision. In this paper we argue that most of cloud decisions in practice do not regard cloud adoption horizontally across the organization. Rather, they consider cloud adoption with respect to the particular business area in which the cloud service will be introduced. These are the types of decisions we investigate in this paper. Drawing on the cloud adoption literature and Diffusion of Innovation and Organizational Capability theories, we formulate our research model involving factors related to cloud’s relative advantage and to organizational innovativeness. Our findings show that cloud’s cost-reduction and remote access benefits tradeoff security concerns as the context of cloud adoption becomes specific and demonstrate the relevance of personnel innovativeness in cloud adoption decisions

Payments for Environmental Services in Watersheds: Insights From a Comparative Study of three Cases in Central America

We have compared three cases of payments for water-related environmental services (PES) in Central America, in terms of socioeconomic background, opportunity costs of forest conservation and stakeholders’ perceptions on the conditions of water resources and other issues. We found that, in general, the foregone benefits from land uses alternative to forest cover are larger than the amount paid, which apparently contradicts the economic foundation of PES schemes. A number of possible explanations are explored. The results also suggest that trade-offs between different environmental and social goals are likely to emerge in PES schemes, posing some doubts on their ability to be multipurpose instruments for environmental improvement and rural development. We also found that PES schemes may work as a conflictresolution instrument, facilitating downstream -upstream problem solving, though at the same time they might introduce changes in social perceptions of property rights.environmental services, watershed management, rural development, property rights, Honduras, Costa Rica, Nicaragua.

Self organising cloud cells: a resource efficient network densification strategy

Network densification is envisioned as the key enabler for 2020 vision that requires cellular systems to grow in capacity by hundreds of times to cope with unprecedented traffic growth trends being witnessed since advent of broadband on the move. However, increased energy consumption and complex mobility management associated with network densifications remain as the two main challenges to be addressed before further network densification can be exploited on a wide scale. In the wake of these challenges, this paper proposes and evaluates a novel dense network deployment strategy for increasing the capacity of future cellular systems without sacrificing energy efficiency and compromising mobility performance. Our deployment architecture consists of smart small cells, called cloud nodes, which provide data coverage to individual users on a demand bases while taking into account the spatial and temporal dynamics of user mobility and traffic. The decision to activate the cloud nodes, such that certain performance objectives at system level are targeted, is carried out by the overlaying macrocell based on a fuzzy-logic framework. We also compare the proposed architecture with conventional macrocell only deployment and pure microcell-based dense deployment in terms of blocking probability, handover probability and energy efficiency and discuss and quantify the trade-offs therein

A Literature Review on Cloud Computing Adoption Issues in Enterprises

Part 3: Creating Value through ApplicationsInternational audienceCloud computing has received increasing interest from enterprises since its inception. With its innovative information technology (IT) services delivery model, cloud computing could add technical and strategic business value to enterprises. However, cloud computing poses highly concerning internal (e.g., Top management and experience) and external issues (e.g., regulations and standards). This paper presents a systematic literature review to explore the current key issues related to cloud computing adoption. This is achieved by reviewing 51 articles published about cloud computing adoption. Using the grounded theory approach, articles are classified into eight main categories: internal, external, evaluation, proof of concept, adoption decision, implementation and integration, IT governance, and confirmation. Then, the eight categories are divided into two abstract categories: cloud computing adoption factors and processes, where the former affects the latter. The results of this review indicate that enterprises face serious issues before they decide to adopt cloud computing. Based on the findings, the paper provides a future information systems (IS) research agenda to explore the previously under-investigated areas regarding cloud computing adoption factors and processes. This paper calls for further theoretical, methodological, and empirical contributions to the research area of cloud computing adoption by enterprises