scholarly journals Organizational cloud security and control: a proactive approach

2019 ◽  
Vol 32 (3) ◽  
pp. 516-537 ◽  
Author(s):  
Konstantina Spanaki ◽  
Zeynep Gürgüç ◽  
Catherine Mulligan ◽  
Emil Lupu
Keyword(s):  
Data Collection ◽  
Ethical Behavior ◽  
Large Scale ◽  
Influencing Factor ◽  
Cloud Security ◽  
Decision Makers ◽  
Cloud Infrastructure ◽  
Content Type ◽  
Cloud Environments ◽  
Sharing Responsibility

Purpose The purpose of this paper is to unfold the perceptions around additional security in cloud environments by highlighting the importance of controlling mechanisms as an approach to the ethical use of the systems. The study focuses on the effects of the controlling mechanisms in maintaining an overall secure position for the cloud and the mediating role of the ethical behavior in this relationship. Design/methodology/approach A case study was conducted, examining the adoption of managed cloud security services as a means of control, as well as a large-scale survey with the views of IT decision makers about the effects of such adoption to the overall cloud security. Findings The findings indicate that there is indeed a positive relationship between the adoption of controlling mechanisms and the maintenance of overall cloud security, which increases when the users follow an ethical behavior in the use of the cloud. A framework based on the findings is built suggesting a research agenda for the future and a conceptualization of the field. Research limitations/implications One of the major limitations of the study is the fact that the data collection was based on the perceptions of IT decision makers from a cross-section of industries; however the proposed framework should also be examined in industry-specific context. Although the firm size was indicated as a high influencing factor, it was not considered for this study, as the data collection targeted a range of organizations from various sizes. Originality/value This study extends the research of IS security behavior based on the notion that individuals (clients and providers of cloud infrastructure) are protecting something separate from themselves, in a cloud-based environment, sharing responsibility and trust with their peers. The organization in this context is focusing on managed security solutions as a proactive measurement to preserve cloud security in cloud environments.

How “The Three Rules” guide strategy and investment decisions at Deloitte Consulting LLP

2015 ◽  
Vol 43 (3) ◽  
pp. 7-14 ◽  
Author(s):  
Jim Moffatt
Keyword(s):  
Design Methodology ◽  
Large Scale ◽  
Investment Decisions ◽  
Decision Makers ◽  
Research Project ◽  
Content Type ◽  
First Case ◽  
Practical Implications ◽  
Thought Leadership

Purpose – This case example looks at how Deloitte Consulting applies the Three Rules synthesized by Michael Raynor and Mumtaz Ahmed based on their large-scale research project that identified patterns in the way exceptional companies think. Design/methodology/approach – The Three Rules concept is a key piece of Deloitte Consulting’s thought leadership program. So how are the three rules helping the organization perform? Now that research has shown how exceptional companies think, CEO Jim Moffatt could address the question, “Does Deloitte think like an exceptional company?” Findings – Deloitte has had success with an approach that promotes a bias towards non-price value over price and revenue over costs. Practical implications – It’s critical that all decision makers in an organization understand how decisions that are consistent with the three rules have contributed to past success as well as how they can apply the rules to difficult challenges they face today. Originality/value – This is the first case study written from a CEO’s perspective that looks at how the Three Rules approach of Michael Raynor and Mumtaz Ahmed can foster a firm’s growth and exceptional performance.

scholarly journals Technology of computing risks visualization for distributed production infrastructures

2018 ◽  
Vol 224 ◽  
pp. 02071
Author(s):  
Dmitrii Voronin ◽  
Victoria Shevchenko ◽  
Olga Chengar
Keyword(s):  
Large Scale ◽  
Multidimensional Data ◽  
Cloud Infrastructure ◽  
Visualization Technique ◽  
Multidimensional Data Visualization ◽  
Cloud Environments ◽  
Research Gap ◽  
Radar Chart ◽  
Distributed Production ◽  
Support Decision Making

Scientific problems related to the classification, assessment, visualization and management of risks in the cloud environments have been considered. The analysis of the state-of-the-art methods, offered for these problems solving, has been carried out taking into account the specificity of the cloud infrastructure oriented on large-scale tasks processing in distributed production infrastructures. Unfortunately, not much of scientific and objective researches had been focused on the developing of effective approaches for cloud risks visualization providing the necessary information to support decision-making in distributed production infrastructures. In order to fill this research gap, this study attempts to propose a risks visualization technique that is based on radar chart implementation for multidimensional data visualization.

An analysis of the Gezi Park social movement tweets

2017 ◽  
Vol 69 (4) ◽  
pp. 426-440 ◽  
Author(s):  
Selcen Ozturkcan ◽  
Nihat Kasap ◽  
Muge Cevik ◽  
Tauhid Zaman
Keyword(s):  
Data Collection ◽  
Media Coverage ◽  
Large Scale ◽  
Real Life ◽  
Shopping Mall ◽  
Small Scale ◽  
Social Media Analytics ◽  
Public Park ◽  
Content Type ◽  
The Arab Spring

Purpose Twitter usage during Gezi Park Protests, a significant large-scale connective action, is analyzed to reveal meaningful findings on individual and group tweeting characteristics. Subsequent to the Arab Spring in terms of its timing, the Gezi Park Protests began by the spread of news on construction plans to build a shopping mall at a public park in Taksim Square in Istanbul on May 26, 2013. Though started as a small-scale local protest, it emerged into a series of multi-regional social protests, also known as the Gezi Park demonstrations. The paper aims to discuss these issues. Design/methodology/approach The authors sought answers to three important research questions: whether Twitter usage is reflective of real life events, what Twitter is actually used for, and is Twitter usage contagious? The authors have collected streamed data from Twitter. As a research methodology, the authors followed social media analytics framework proposed by Fan and Gordon (2014), which included three consecutive processes; capturing, understanding, and presenting. An analysis of 54 million publicly available tweets and 3.5 million foursquare check-ins, which account to randomly selected 1 percent of all tweets and check-ins posted from Istanbul, Turkey between March and September 2013 are presented. Findings A perceived lack of sufficient media coverage on events taking place on the streets is believed to result in Turkish protestors’ use of Twitter as a medium to share and get information on ongoing and planned demonstrations, to learn the recent news, to participate in the debate, and to create local and global awareness. Research limitations/implications Data collection via streamed tweets comes with certain limitations. Twitter restricts data collection on publicly available tweets and only allows randomly selected 1 percent of all tweets posted from a specific region. Therefore, the authors’ data include only tweets of publicly available Twitter profiles. The generalizability of the findings should be regarded with concerning this limitation. Practical implications The authors conclude that Twitter was used mainly as a platform to exchange information to organize street demonstrations. Originality/value The authors conclude that Twitter usage reflected Street movements on a chronological level. Finally, the authors present that Twitter usage is contagious whereas tweeting is not necessarily.

Decision-making model for the evaluation of industrialized housing systems in Ethiopia

2019 ◽  
Vol 27 (1) ◽  
pp. 296-320 ◽  
Author(s):  
Yidnekachew Tesmamma Daget ◽  
Hong Zhang
Keyword(s):  
Decision Making ◽  
Construction Industry ◽  
Large Scale ◽  
Cost Effective ◽  
Housing Development ◽  
Decision Makers ◽  
Content Type ◽  
Housing Systems ◽  
Decision Factors ◽  
Important Decision

Purpose The industrialized housing system (IHS) is regarded as an effective building philosophy based on off-site construction techniques to achieve rapid and cost-effective housing development. The purpose of this paper is to develop a multi-criteria decision-making support system (DMSS) model for the evaluation of housing systems to select the relevant decision factors and to identify the types and characteristics of suitable IHSs for application in a mass housing development. Design/methodology/approach A multi-criteria DMSS model with the analytical hierarchy process was designed. Based on the literature review and also the response of the ten experts’ interviews, 30 decision factors were identified for evaluation. In addition, 5 IHSs were considered as a case study for testing the model. Then, 30 professionals participated in a questionnaire survey conducted to evaluate the priority vector importance level of the decision factors and housing systems. Findings The result of the decision-making process showed that the top three decision factors are customer needs, supply chain and the construction industry. In addition, both precast concrete beam and slab blocks, as well as agro stone panels are identified as suitable housing systems. The systems have the characteristics of being lightweight, easy to produce and erect, and cost-effective, and they use local input resources and semi-skilled labor. The findings also revealed the potential and practicality of the model among multiple alternatives across multiple decision factors. Research limitations/implications The study has faced the limitations of available professionals and experts who have rich experience in the application of IHSs. In addition, there were few types of alternative IHSs and limited practice of IHSs implementation in large-scale housing construction. These challenges caused limitations to the relevant data collection. In order to address these challenges, all the available experts from the different sectors of the construction industry with the experience of IHSs construction are invited to participate and the available alternative IHSs in the market are selected for evaluation. Practical implications The rational evaluation method used to determine the important decision factors and the general characteristics of the suitable housing systems can help housing developers and decision makers in developing countries to make informed and effective decisions. Social implications The findings of the study help to address the challenge of lack of sufficient housing supply to the overwhelming housing demand that exists and identify the most important decision factors and suitable housing systems that can be applied for the rapid and decent large-scale housing developments at an affordable price. Originality/value This paper bridges the knowledge gaps that exist regarding the identification and evaluation of IHSs in Ethiopia. This study can help practitioners, housing developers, and decision makers to make informed and effective decisions regarding the evaluation and selection of IHSs.

Impact of lean operations on the roles of finance functions and their application of lean

2020 ◽  
Vol 32 (4) ◽  
pp. 731-763
Author(s):  
Henrik Nielsen ◽  
Thomas Borup Kristensen
Keyword(s):  
Structural Equation ◽  
Large Scale ◽  
Decision Makers ◽  
Equation Modeling ◽  
Average Deviation ◽  
Content Type ◽  
Lean Principles ◽  
New Instrument ◽  
Lean Operations ◽  
Finance Function

Purpose This paper aims to study the relations between lean operations, lean principles in finance functions and the roles of finance functions. Design/methodology/approach The paper uses structural equation modeling to analyze data from 408 different firms in the Danish production and services sectors. A dyadic approach is applied, as a sub-sample of 107 chief operating officers in the responding firms is used to investigate the construct validity, reliability and average deviation index of the instrument measuring the roles of finance functions. Findings The paper finds that lean-operation firms emphasize four different yet interdependent roles of finance functions. The paper also finds that lean operation leads to firms’ finance functions adopting lean principles. Research limitations/implications This paper characterizes lean-operation firms as contextually ambidextrous to predict relations between lean operation and roles of finance functions. The paper expands prior case study findings on the roles of finance functions in lean-operation firms, and the findings of the paper underline that finance functions continue to play an important role in these firms. Practical implications Decision-makers in lean-operation firms should not be hesitant with respect to integrating finance function workers into the lean operation. Furthermore, decision-makers should understand that a balanced emphasis of the roles of finance functions is necessary to avoid overemphasizing exploitation at the expense of exploration, or vice versa. Originality/value To the best of the authors’ knowledge, this is the first paper to provide large-scale evidence of the roles of finance functions in lean-operation firms and to show that lean principles diffuse to finance functions. Furthermore, the paper introduces a new instrument for measuring finance function roles, based on the competing values framework.

Post-conflict reconstruction – a case study in Kosovo

2015 ◽  
Vol 4 (1) ◽  
pp. 103-128 ◽  
Author(s):  
James Earnest
Keyword(s):  
Project Management ◽  
Data Collection ◽  
Large Scale ◽  
Local Economy ◽  
Development Cooperation ◽  
Research Approach ◽  
Infrastructure Projects ◽  
Content Type ◽  
Post Conflict ◽  
Functional Components

Purpose – Rehabilitation and reconstruction of social and economic infrastructure in a post-conflict environment are complex, long-debated issues in development cooperation. In addition to war creating large-scale human suffering, generating refugees, displacing populations, engendering psychological distress, obliterating infrastructure and transforming the economy, in post-conflict situations, deepening chaos and disorder can be found at the highest social, economic and political levels; serious developmental challenges remain insufficiently addressed. Repairing war-damaged infrastructure in order to reactivate the local economy is a challenge for all post-conflict countries. The paper aims to discuss these issues. Design/methodology/approach – The study was designed to examine planning and execution of post-conflict reconstruction (PCR). The use of a mixed-method research approach combining both quantitative and qualitative data collection was used to explore planning and implementation of PCR infrastructure projects in Kosovo. The data collection in the field was undertaken for a period of eight weeks, from July to September 2008. A total of 420 respondents were involved in the study process, as follows: key informants (four), pilot test (12), semi-structured interviews (36), project manager/engineers survey (231), chief of mission/country director survey (117), and focus group (20). To meet the needs of the society and recognise the required functional components of project management, the overall contexts of managing projects in a post-conflict environment have been discussed in the study. Findings – Planning and implementing reconstruction projects in areas affected by conflict have proven to be far more challenging than expected and responses by practitioners, aid agencies, and government regarded as inadequate. The changing political, economic, and social factors in Kosovo after the war in 1999 have had a significant influence on the limited adoption of a project management methodology in development and reconstruction projects. The findings from the exploratory study were aimed at improving understanding of the planning, pre-designing, and implementation of infrastructure projects. The findings indicated a need to promote a better understanding of how projects are undertaken at all levels of the organisation, and to describe processes, procedures, and tools used for the actual application of projects. The findings of the study identified a poor quality of planning and implementation of reconstruction projects in an environment of complexity, change, and uncertainty. The study also raised some very significant findings for a broader approach to community involvement in project identification, planning, and implementation. Infrastructure projects implemented in Kosovo were used to develop a conceptual framework for designing projects and programmes more likely to yield positive outcomes for post-conflict society. Originality/value – The study was done by the researcher in Kosovo.

Key supply chain strategies for the post-COVID-19 era: implications for resilience and sustainability

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sanjoy Kumar Paul ◽  
Md. Abdul Moktadir ◽  
Kamrul Ahsan
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Manufacturing Sector ◽  
Dominant Role ◽  
Decision Makers ◽  
The Novel ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Sustainability Practices ◽  
Novel Coronavirus

PurposeThe impacts of the novel coronavirus (COVID-19) outbreak continue to devastate supply chain operations. To attain a competitive advantage in the post-COVID-19 era, decision-makers should explore key supply chain strategies to move forward and ready their policies to be implemented when the crisis sufficiently subsides. This is a significant and practical decision-making issue for any supply chain; hence, the purpose of this study is to explore and analyse key supply chain strategies to ensure robustness and resilience in the post-COVID-19 era.Design/methodology/approachThis study conducted an expert survey targeting practitioners and academics to explore key supply chain strategies as means of moving forward in the post-COVID-19 era. Further, the key strategies were quantitatively analysed by applying the best-worst method (BWM) to determine their priority importance in the context of the manufacturing sector.FindingsThe results revealed that supply chain resilience and sustainability practices could play a dominant role in this period. The findings of the study can assist supply chain decision-makers in their formulations of key strategies.Originality/valueThis is the first study to investigate key supply chain strategies for the post-COVID-19 era. This study will help practitioners paying attention to resilience and sustainability practices for managing the impacts of future large-scale disruptions.

Collecting and evaluating large volumes of bibliographic metadata aggregated in the WorldCat database: a proposed methodology to overcome challenges

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vyacheslav I. Zavalin ◽  
Shawne D. Miksa
Keyword(s):  
Data Collection ◽  
Large Scale ◽  
Large Data ◽  
Study Data ◽  
Lessons Learned ◽  
Future Research ◽  
Data Set ◽  
Content Type ◽  
Large Data Set ◽  
Smart Data

Purpose This paper aims to discuss the challenges encountered in collecting, cleaning and analyzing the large data set of bibliographic metadata records in machine-readable cataloging [MARC 21] format. Possible solutions are presented. Design/methodology/approach This mixed method study relied on content analysis and social network analysis. The study examined subject representation in MARC 21 metadata records created in 2020 in WorldCat – the largest international database of “big smart data.” The methodological challenges that were encountered and solutions are examined. Findings In this general review paper with a focus on methodological issues, the discussion of challenges is followed by a discussion of solutions developed and tested as part of this study. Data collection, processing, analysis and visualization are addressed separately. Lessons learned and conclusions related to challenges and solutions for the design of a large-scale study evaluating MARC 21 bibliographic metadata from WorldCat are given. Overall recommendations for the design and implementation of future research are suggested. Originality/value There are no previous publications that address the challenges and solutions of data collection and analysis of WorldCat’s “big smart data” in the form of MARC 21 data. This is the first study to use a large data set to systematically examine MARC 21 library metadata records created after the most recent addition of new fields and subfields to MARC 21 Bibliographic Format standard in 2019 based on resource description and access rules. It is also the first to focus its analyzes on the networks formed by subject terms shared by MARC 21 bibliographic records in a data set extracted from a heterogeneous centralized database WorldCat.

scholarly journals The V-model of service quality: an African case study

2017 ◽  
Vol 51 (5/6) ◽  
pp. 923-945
Author(s):  
Grafton Whyte ◽  
Andy Bytheway
Keyword(s):  
Data Collection ◽  
Service Quality ◽  
Large Scale ◽  
Service Management ◽  
Quality Measurement ◽  
Psychological Theory ◽  
National Study ◽  
Complex Data ◽  
Content Type ◽  
New Model

Purpose This paper aims to introduce and demonstrate a new model for service quality that separates out the measurement of service quality in ways grounded in psychological theory and methodological symmetry. Design/methodology/approach A review of experience in service quality management suggests that new approaches are needed. By seeking a way of managing service at different levels, with symmetry between data collection and data analysis, a model is presented that has more potential applicability and flexibility than is found in traditional models. Findings A national study in Namibia, Africa provided data that successfully demonstrate the method of working and illustrate the contextual, analytical and data management issues and the reporting potential out of complex service management data. Research limitations/implications This new approach to the design of service quality measurement and assessment extends the capability that is generally found in other existing approaches. It provides a new foundation for further research into complex patterns of service success and that will establish more clearly the inter-dependencies between service encounters, service attributes and service measures at the survey item level. Practical implications Studies of multiple service sectors and multiple service recipient groups can now gather and manage large complex data sets and analyse and report that data in ways appropriate to the needs of different stakeholders. Social implications In any context where service quality is a socio-economic or development issue, it is now possible to take a more careful and nuanced approach to the collection and aggregation of data, which will inform policy makers and other stakeholder groups at the national or regional level. Originality/value This new model addresses a range of problems that have been reported with historical approaches such as SERVQUAL and related methods of working. It also provides foundations for new designs for large-scale service management data collection, organisation and analysis.

Container Orchestration With Cost-Efficient Autoscaling in Cloud Computing Environments

2020 ◽  
pp. 190-213
Author(s):  
Maria Rodriguez ◽  
Rajkumar Buyya
Keyword(s):  
Cluster Size ◽  
Large Scale ◽  
Management Approach ◽  
Public Cloud ◽  
Cloud Infrastructure ◽  
Initial Placement ◽  
Cloud Environments ◽  
Computing Environments ◽  
Cost Efficient ◽  
Container Orchestration

Containers are widely used by organizations to deploy diverse workloads such as web services, big data, and IoT applications. Container orchestration platforms are designed to manage the deployment of containerized applications in large-scale clusters. The majority of these platforms optimize the scheduling of containers on a fixed-sized cluster and are not enabled to autoscale the size of the cluster nor to consider features specific to public cloud environments. This chapter presents a resource management approach with three objectives: 1) optimize the initial placement of containers by efficiently scheduling them on existing resources, 2) autoscale the number of resources at runtime based on the cluster's workload, and 3) consolidate applications into fewer VMs at runtime. The framework was implemented as a Kubernetes plugin and its efficiency was evaluated on an Australian cloud infrastructure. The experiments demonstrate that a reduction of 58% in cost can be achieved by dynamically managing the cluster size and placement of applications.

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