Business Intelligence/Knowledge Management

Purpose: The research aims to characterize newest soultions, especially with the respect to cybersecurity aspects of Business Intelligence analytics based on the processing of large sets of information with the use of sentiment analysis and Big Data. Design/Methodology/Approach: The working hypothesis refers to assumption that current regulations and security solutions for Business Intelligence analytics based on the processing of large sets of information with the use of sentiment analysis and Big Data is under extreme preassure to meet evergrowing challenges. There are more and more dends form the legal regulators as well as from the market and that creates a lot of problems with data protection. The article uses legal and comparative analysis as well as structural and functional analysis. Additionally, the interpretation method is also present. Findings: Article indicates that the aforementioned issues with the respect to growing importance of internet including the Internet of Things and Internet of Everything are becoming of more and more importance and cannot go with appropriate level of cybersecurity since the data they collect is of the great importance. The trends immanent to Industry 4.0 require from business more effort and customer orientation. Growing population and access to Internet demands larger scales of business operations. Practical Implications: As a result of conducting the research, it is possible to identify threats and present some recommendations for cybersecurity of Business Intelligence. Originality/Value: This is a complete research for Cybersecurity of Business Intelligence analytics based on the processing of large sets of information with the use of sentiment analysis and Big Data.

Knowledge management is currently changing significantly. KM effectively uses the right information and communication technology (ICT) and social interaction. New ways that exist in the virtual world make it possible to support knowledge and the process of acquiring it because to create knowledge and the process of sharing knowledge in a virtual world environment takes into account the social aspects needed. With the use of web 2.0 technologies, the main communication media in Second Life in the form of text, voice, instant messaging (IM), email and blogs can be maximized. By conducting exploratory analysis on "second life" research that contributes to a general understanding of how technology can be used to support or activate KM in education. College Student and lecturer can participate in teaching and learning processes, while academic staff supports the University business processes. A result provides factors that effects increase and impairment on student score, framework of 4 Pillar Solution Model for Second Life Education is formed and evaluation knowledge sharing maturity using COBIT 4.1 Framework and Maturity Level Classification using CMMI Model.

The purpose of this paper is to search for the main characteristics of intelligent organizations. Intelligence is one of those concepts that everyone has in mind, but hardly few can define or explain it. Thus, it is even more difficult to extend this concept to organizations, and to talk about organizational intelligence. This paper tries to show the new dimensions

The importance of the acquisition and provision of information within knowledge work such as engineering is widely acknowledged. This article reports an extensive empirical study of such information behaviors in engineers, using a novel and effective work sampling method. Seventy-eight design engineers each carried a portable handheld computer (PDA) for 20 working days. Once every hour, they were prompted to enter data concerning the task they were currently performing, including the information behaviors in which they were engaging. The resultant data represent a comprehensive picture of engineers' information behaviors and the percentage of their working time for which each of these behaviors accounts (55.75% in total). Specific hypotheses concerning the time spent engaged in these behaviors were also tested. Accordingly, it was found that participants spent substantially more time receiving information they had not requested than information they had, and this pattern was also reflected when they provided others with information. Furthermore, although there was no difference found between the time participants spent searching for information from other people compared with nonhuman sources, in the former case they spent relatively less time locating the information source and information within that source, and relatively more time engaged in problem solving and decision making. The results are discussed in terms of their implications for theory and organizational practice.

Business Intelligence (BI) and Competitive Intelligence (CI) are two rarely understood methods relevant to pragmatic Strategic Foresight™. BI was methodologically influenced by the Central Intelligence Agency's (CIA) collections and analysis techniques, and ideologically shaped by the 1980s specter of Japan, Inc. BI has evolved into a collection of sophisticated techniques that merge insights from business strategy, risk analysis, cognitive psychology, organizational behavior and political science. Jan Herring's model of the CIA's intelligence cycle is outlined. The relationship of BI to Michael Porter's 5 Forces and Anticipatory Management are discussed. The requirements of an intelligence analyst, common problems and the difficulties in establishing a BI unit are explored. Finally, four key methods-Mergers & Acquisitions, Environmental Scanning, 'Shadow' Marketing and Patent Searches-are detailed with relevant case studies. Author Biography Alex Burns is the editor of the award-winning Disinformation® site, and an Australian Foresight Institute graduate student. He is affiliated with the USbased Integral Institute, the National Values Center and the International Paleopsychology Project. His research interests include global media vectors, counterterrorism and risk societies.

This research, conducted by the author when a Senior Researcher at Newcastle University, UK, was funded by a UK governance organisation to help them assess, integrate and improve their understanding of the governed population.

ABSTRACT: Governance organisations have been urged to develop more holistic evidence-based approaches with partners to better deal with issues affecting the governed population. This presupposes an understanding of the population, yet there has been little research work addressing how governance organisations come to understand their governed population, nor how this understanding can be improved upon within such organisations.

This case study examined in-depth how understanding of a governed population was developed within one UK local governance organisation and it explored how such understanding might be developed and improved through more holistic and evidence-based organisational learning within the organisation and its governance partnerships.

The research methodology involved placement within the governance organisation, participant observations on several projects and innovative initiatives, observations within, across, and outside the organisation, and also interviews with varied key stakeholders.

The study examined:

- stakeholder engagement and networks
- current and varied understandings of the population
- mechanisms actually used for developing understandings
- the influence of context on organisational learning

and analysed these to arrive at a recommendations to improve organisational understanding of the governed population.

In the case studied, significant strengths were found: including innovative past learning trials for development, extensive ongoing networking activities, and many varied and accumulating quantitative datasets available across partnerships.

However, entrenched organisational approaches and practices constrained the development of holistic evidence-based understanding, for instance: the absence of systematic maintained collective learning processes; weak recording and forgetting of understandings; methodological exclusion of stakeholders from the development of understanding; the relative neglect of qualitative data, explanations, investigations, interpretations, and reflexivity; and also implicit organisational acceptance of such limitations and low aspirations.

Nonetheless, untapped opportunities existed to enable change including: latent practitioner knowledge and innovative management champions, the desire for improvement and raised aspirations within learning networks, and the development potential of alterative learning approaches.

It was concluded that more holistic evidence-based understanding was possible, but required new learning approaches beyond those then in use in both local government or academia.   

Recommendations are made to utilise and develop improved organisational learning approaches trialed and reported in the case study.

It is argued that the case study findings, conclusions, and recommendations may be applicable to other similar local governance organisations and partnerships that seek to better understand local populations, services and interventions.

The work was also submitted for, and awarded, an MPhil (at Newcastle University, supervised by Prof. Patsy Healy)

Globally organisations (private and public alike) are being pressured by the public to be more efficient in the use of their resources, to be flexible in the face of changing local and global trends, and to be more accountable in the use of resources and assets. This includes not leaving important organisational aspects such as intellectual capital development, relationship management, stakeholder engagement and knowledge management to chance.

Both private and public organisations are therefore purposefully turning toward organisational learning and its modern format, knowledge management, for insight. Unfortunately, most of the books in this area focus on the theoretical aspects of learning and knowledge management.  Additionally, executives, managers and employees in public organisations are finding that most of the learning and knowledge management literature has been exclusively written for the private sector.

It is with the above in mind that we have researched and designed theory, insights and frameworks that would work for the public sector. This text was written to be practical and implementable – hence the focus on ‘praxis’ in the title. One of the questions we are often asked is, “Now that I know something about knowledge management, and believe that it can add value to my organisation, where do I start and what do I start doing?”

Knowledge Management Praxis not only provides the phased tools for “doing”, through practical questionnaires, surveys and framework, but if worked on simultaneously by multiple members of a department or division, creates the necessary shared language and understanding for generating rapid successes and effectiveness.  It has been written primarily for managers and employees (even though it could assist in strategic planning processes).

Although most of the book refers specifically to the public sector, managers and employees in the private sector will benefit from the insights, templates and frameworks, surveys and practicality of the book.

The text draws on best practice, and is borne out of the research and consulting experiences of the authors, it is therefore both relevant and known to be effective.

We believe that it presents an interesting collective of inquiry, that has been contextualised both in its implications for theory and practice of knowledge management.

Self-service Business Intelligence (SSBI) is an emerging topic for many companies. Casual users should be enabled to independently build their own analyses and reports. This accelerates and simplifies the decision-making processes. Although recent studies began to discuss parts of a self-service environment, none of these present a comprehensive architecture. Following a design science research approach, this study proposes a new self-service oriented BI architecture in order to address this gap. Starting from an in-depth literature review, an initial model was developed and improved by qualitative data analysis from interviews with 18 BI and IT specialists form companies across different industries. The proposed architecture model demonstrates the interaction between introduced self-service elements with each other and with traditional BI components. For example, we look at the integration of collaboration rooms and a self-learning knowledge database that aims to be a source for a report recommender.

This research paper discusses about people issues
that impact knowledge management practices and how
organizations address it. Issues such as lack of collaboration,
mistrust, missing leadership qualities and inadequate
knowledge sharing have been discussed and how they would
result in failure of knowledge management practices in an
organization. Finally different strategies were provided to
address these people issues.

Industry 5.0 is a collection of technology that businesses need to advance their innovation initiatives and respond quickly to changing markets. It is primarily focused on predictive analytics, interconnectivity, machine learning and digital technology with the goal of revolutionizing how businesses function and grow. Industry 5.0 will enable you, from providers to consumers, to gather and analyze and utilize information for the real-time purpose of enhancing and improving operation, designs and products via immediate feedback, thus increasing production efficiency. As a result, this note advocates for and encourages companies to adopt Industry 5.0. Examining the state of the art and current state of business intelligence (BI) technology, the ways in which it has benefited organizations at the economic and business level in terms of decision-making, and highlighting some success stories implemented in various business, governmental, social, and academic environments. Additionally, it discusses the future of Industry 5.0, namely in the area of business intelligence, and how businesses can prepare for this transformation. This note contributes information about the present status and benefits of Industry 5.0, rapid technological advancements, and the intelligent digital technologies and integration of manufacturing. The revision of current value chains and processes can also make industries more robust to external shocks, like the COVID-19 crisis.

This research was funded by, and implemented within, a UK national research organisation, while the author was the KE and Impact Evaluation Manager responsible for assessing impact on a £15m UK government-funded research programme.

This work was also submitted as the authors MBA dissertation which was accepted and awarded in 2009.

ABSTRACT: A methodology and methods ‘toolbox’ is proposed for conducting impact research and assessment from within research programmes. The emphasis is upon how to clarify and assess the wider impacts from the early stages onwards.

The approach explicitly acknowledges, and attempts to address, the known issues and challenges of impact assessment while drawing upon the resources and opportunities available to research managers and researchers within such programmes.

The study has two triangulating foundations. Firstly, it examines the academic literature to help identify and design the pilot methodology and methods. Secondly it trials these in a real programme to both test and improve them.

The study was conducted over one year within one leading UK research organisation, where two research programmes (and around 60 research projects of £15m total value) were being assessed for their impacts. The study draws upon actual impact management experience and reflection, prospective (ex ante) and retrospective (ex post) assessments, participatory contributions from leading researchers undergoing assessment, and consultation with external users. The findings of this study outline the pilot and its first iteration. Recommendations are made for improvement to the methodology and methods.

A subsequent follow-on bid to UK government incorporating the impacts identified from implementing this methodology, successfully led to a further £15m of government funding.

It is expected the pilot methodology and methods will be applicable to other organisations, conducting and funding such research programmes, required to research and assess the wider research impacts.

Although primary focus of implemetation trials was upon research in physical sciences, technology, high-tech engineering, computing/IT, and environment, the wider literature study, the methodology design and justification, the methods proposed and used, and the resulting general recommendations and lessons are expected to apply more broadly to many other research areas, where the impact is to be found more widely in the society, economy, government or public sector or within organizations, policies, professions or the public.

Interest in this work is expected from research programme managers, impact managers and assessors, management consultants advising in this area, and government funding managers, all seeking to embed a developing approach to understand, capture, and enhance wider impact.

Food manufacturers are required to meet certain traceability specifications. This research aims at underscoring the relevant needs and expectations of various stakeholders across the entire food supply chain. In this context, firms' decisions on resource allocation and risk mitigation overlap several domains, such as quality, safety, environment, social responsibility and information. Business Intelligence (BI) platforms are specifically conceived to support analytical decision making by providing a centralised view on multiple distributed data sources. However, BI solutions are usually deployed within a single organization, whilst traceability involves multiple actors with potentially divergent interests and diverse levels of willingness to participate. Along this line of thought, integration of management systems within a company and throughout the overall supply chain is suggested to meet the emerging managerial challenges. After a detailed survey of integrated management sys...

In this chapter, the authors described the key issues of Business Intelligence analytics based on the processing of large sets of information using sentiment analysis and computerized Big Data Analytics platforms. In the discussed issue, the authors drew attention to the trends in the development of business analytics based on ICT information technologies. Information technologies, ICT, Industry 4.0, Big Data, and cloud computing as key determinants of the development of computerized business analytics were discussed. An attempt was made to answer the question whether business analytics carried out on Big Data Analytics analytical platforms is a tool facilitating the management of business entities and how can computerized Business Intelligence analytical platforms be used in the enterprise management process. The authors discussed the growing importance of computerized business analytics in the context of studying the ongoing processes of verifying the economic efficiency of enterprises. In recent years, new information technologies, ICT, Internet technologies and technologies of advanced data processing Industry 4.0 have been used in many areas of enterprise activity. Analyzes carried out in the Business Intelligence formula with the use of Big Data Analytics provide the management with new possibilities of analyzing large data sets in real time, which significantly contributes to increasing the efficiency of enterprise management. The continuation of these processes is the improvement of Internet data transfer security systems carried out by constantly updating and adapting the risk management process of IT systems to the changing information technologies, ICT and Industry 4.0.

Modern endüstriyel dönüşümün hemen hemen tüm ders kitaplarında Watt’ın on sekizinci yüzyılda buhar makinesini icat etmesiyle başladığı belirtilir. Elbette buhar makinesinin icadı tarihsel süreç içerisinde endüstriyel devrim niteliği taşıyabilir ancak Lewis Mumford, 1934 yılında yayımladığı “Teknik ve Uygarlık” adlı eserinde, ne kömür ne demir ne de buharın endüstri devrimlerinde anahtar rolü oynamadığını ileri sürmekte ve esas aktörün “saat” olduğunu belirtmektedir2. Bununla beraber “Endüstriyel devrim” teriminin ise ilk kez A.J. Toynbee’nin amcası Arnold Toynbee’nin 1880’li yıllardaki yazılarında onsekizinci yüzyıl ile kendi dönemi arasında ortaya çıkan teknik yeniliklerden bahsederken kullandığını belirtmektedir. Mumford’a göre saat, gelişimin her aşamasında hem makinenin en çok göze çarpan gerçeği hem de tipik sembolüdür. Çünkü esas itibariyle endüstri devrimleri diye adlandırdığımız dönemler feodalizmden kapitalizme geçişi de örtük olarak haber verir. Mumford’un bu savı feodal dönemde zamanı takip etmek yerine zamana uyma, zamana fiyat biçme ve paylara bölme noktasında kapitalizmin de hızla yol almasında ana etkenlerden biri olmuştur. Çünkü kapitalizm ile teknik, her aşamada birbirini şekillendirmiştir girift bir hal almıştır. Belki de bu noktada, Mumford’ın (2017) bu konudaki iddiası endüstri 4.0 diye tanımladığımız bu süreçte daha işlevsel bir bilgi olacaktır. Çünkü endüstri 4.0, zaman algımız üzerinde derin etkiler yaratarak, tabir yerindeyse, hızıyla ve zamanı kullanmamıza sağladığı katkılarla baş döndürmektedir ve Mumford’un dediği gibi sadece saat, zamanı takip etmeye değil, endüstri 4.0 içerisindeki bileşenlerde kendini gösterdiği gibi, insanların eylemlerini senkronize edip takip etme işlevi de görmeye devam etmektedir.

The Web of Data is an open environment consisting of a great number of large inter-linked RDF datasets from various do-mains. In this environment, organizations and companies adopt the Linked Data practices utilizing Semantic Web (SW) tech-nologies, in order to publish their data and offer SPARQL endpoints (i.e., SPARQL-based search services). On the other hand, the dominant standard for information exchange in the Web today is XML. Additionally, many international standards (e.g., Dublin Core, MPEG-7, METS, TEI, IEEE LOM) in several domains (e.g., Digital Libraries, GIS, Multimedia, e-Learning) have been expressed in XML Schema. The aforementioned have led to an increasing emphasis on XML data, accessed using the XQuery query language. The SW and XML worlds and their developed infrastructures are based on different data models, semantics and query languages. Thus, it is crucial to develop interoperability mechanisms that allow the Web of Data users to access XML datasets, using SPARQL, from their own working environments. It is unrealistic to expect that all the existing legacy data (e.g., Relational, XML, etc.) will be transformed into SW data. Therefore, publishing legacy data as Linked Data and providing SPARQL endpoints over them has become a major research challenge. In this direction, we introduce the SPARQL2XQuery Framework which creates an interoperable environment, where SPARQL queries are automatically translated to XQuery queries, in order to access XML data across the Web. The SPARQL2XQuery Framework provides a mapping model for the expression of OWL–RDF/S to XML Schema mappings as well as a method for SPARQL to XQuery translation. To this end, our Framework supports both manual and automatic mapping specification between ontologies and XML Schemas. In the automatic mapping specification scenario, the SPARQL2XQuery exploits the XS2OWL component which transforms XML Sche-mas into OWL ontologies. Finally, extensive experiments have been conducted in order to evaluate the schema transfor-mation, mapping generation, query translation and query evaluation efficiency, using both real and synthetic datasets.

The development of transformation and sharing information via the Internet has been determined by numerous facilities for beneficiaries, clients and those using information services of the public sector institutions. Moreover, there is an opportunity for the entities sharing electronic information via the Internet to significantly reduce transactional costs of their performed financial operations and electronic data transfer. On the other hand, the IT development functioning in the Internet is connected with the risk of losing and theft of information by unentitled entities. The process of sharing information via the Internet generates many threats connected with identity theft crime, taking over secret data by hackers and embezzlement of money in the electronic banking systems. In response to the threats, particular entities, including the institutions of the financial sector, develop security systems of remote information sharing and performing transactions via the Internet. Nowadays, there is a continuity of the technique improvement process providing certain level of the Internet security data transfer. The procedures of safe transforming, stocking and sharing information in the Internet electronic banking have been being improved. National legal regulations considering new occurring technology innovation and electronic transfer technologies in the Internet have been being completed as well. Dissemination of standards of performing financial operations in the cloud as well as those huge data collections allocated in the Big Data platforms are within the fasted developing IT areas that determine further phases of advance of the electronic Internet banking.

La notion de patrimoine informationnel recouvre divers types d’informations sur l’entreprise. Dans notre cas il peut concerner les informations commerciales, financières et technologiques,... Alors, l’entreprise qui souhaite pénétrer le marché de la grande distribution au Maroc doit identifier toutes les menaces potentielles...

Food manufacturers are required to meet certain traceability specifications. This research aims at underscoring the relevant needs and expectations of various stakeholders across the entire food supply chain. In this context, firms' decisions on resource allocation and risk mitigation overlap several domains, such as quality, safety, environment, social responsibility and information. Business Intelligence (BI) platforms are specifically conceived to support analytical decision making by providing a centralised view on multiple distributed data sources. However, BI solutions are usually deployed within a single organization, whilst traceability involves multiple actors with potentially divergent interests and diverse levels of willingness to participate. Along this line of thought, integration of management systems within a company and throughout the overall supply chain is suggested to meet the emerging managerial challenges. After a detailed survey of integrated management sys...

The International Journal of Managing Value and Supply Chains ( IJMVSC ) is a quarterly open access peer-reviewed journal that publishes articles that contribute new results in all areas of value and supply chain management. The journal provides a platform to disseminate new ideas and new research, advance theories, and propagate best practices in the management of value and supply chain management, looking across both product and service-based businesses. This will include works based in service management, logistics and distribution, operations management, process management, flow control, and customer service. The journal offers a forum in which academics, consultants, and practitioners in a variety of fields can exchange ideas to further research and improve practices in all areas of business. The International Journal of Managing Value and Supply Chains ( IJMVSC ) seek to establish new collaborations, new best practices, and new theories in the management of both product and service-based organizations around the world.

In this short paper, I provide an explanation of what criteria I would consider in making a decision for acquiring BI software, including purchasing, leasing, in-house development, and outsourcing development. I also provide an explanation of what I would change if I were looking to apply “green” principles.

La selección de un software soportado por un catálogo de información adaptado a las necesidades concretas del grupo de usuarios es crítico para el éxito de un proyecto de Data Warehouse. Herramientas de acceso de usuario simples e intuitivas y catálogos de informaicón adaptados permitirán acceder fácilmente y rápidamente a la información requerida.

To start any business one need resources (financial resources, energy resources, human resources), Infrastructure, Transportation, Buyers and above all secure and safe place. Here are 5 reasons why Dubai still is a best place for Starting a business.

Currently, business analytics uses computerized platforms containing ready-made reporting formulas in the field of Business Intelligence. In recent years, software companies supporting enterprise management offer advanced applications of information-analytical Business Intelligence class systems consisting of modular development of these systems and combining business intelligence software with platforms that use data warehouse technology, multi-dimensional analytical processing software and data mining and processing applications. This article describes an example of this type of computerized analytical platform for business entities, which is included in analytical applications that allow quick access to necessary, aggregated and multi-criteria processed information. The software allows entrepreneurs and corporate managers as well as entities from the SME sector on the one hand to use embedded patterns of reports or analyzes, and on the other hand to self-develop and configure analyzes carried out, tailored to the specifics of a specific entity. Such analytical applications make it possible to build integrated risk management systems in the organization.

Data exploration and visualization systems are of great importance in the Big Data era, in which the volume and
heterogeneity of available information make it difficult for humans to manually explore and analyse data. Most traditional systems
operate in an offline way, limited to accessing preprocessed (static) sets of data. They also restrict themselves to dealing
with small dataset sizes, which can be easily handled with conventional techniques. However, the Big Data era has realized the
availability of a great amount and variety of big datasets that are dynamic in nature; most of them offer API or query endpoints
for online access, or the data is received in a stream fashion. Therefore, modern systems must address the challenge of on-the-fly
scalable visualizations over large dynamic sets of data, offering efficient exploration techniques, as well as mechanisms for
information abstraction and summarization. Further, they must take into account different user-defined exploration scenarios
and user preferences. In this work, we present a generic model for personalized multilevel exploration and analysis over large
dynamic sets of numeric and temporal data. Our model is built on top of a lightweight tree-based structure which can be efficiently
constructed on-the-fly for a given set of data. This tree structure aggregates input objects into a hierarchical multiscale
model. We define two versions of this structure, that adopt different data organization approaches, well-suited to exploration and
analysis context. In the proposed structure, statistical computations can be efficiently performed on-the-fly. Considering different
exploration scenarios over large datasets, the proposed model enables efficient multilevel exploration, offering incremental construction
and prefetching via user interaction, and dynamic adaptation of the hierarchies based on user preferences. A thorough
theoretical analysis is presented, illustrating the efficiency of the proposed model. The proposed model is realized in a web-based
prototype tool, called SynopsViz that offers multilevel visual exploration and analysis over Linked Data datasets. Finally, we
provide a performance evaluation and a empirical user study employing real datasets.

Data Warehouse y Data Mining a menudo se consideran como áreas distintas, cuando realmente su uso está muy interrelacionado. En este artículo, se extiende esta idea, con ejemplos reales, en los cuales se ha utilizado Data Mining en las fases iniciales de la construcción del Data Warehouse, y en la fase de explotación de la información, incrementando así su rentabilidad, sobre todo para los usuarios finales.

Databases are vulnerable. Public statements by Target, Home Depot, and Anthem following their extremely advertised data breaches are each uniform and succinct on how their breaches unfolded: unauthorized access to those systems that ultimately led to the extraction of sensitive information. A comprehensive strategy to secure a database is over data security. Usually, security events will be related to the later action: illegitimate access to data confidentiality damage, injury to the integrity of knowledge, and loss of data accessibility (Discover). Loss of privacy of data, creating them accessible to others without a right of access is not visible within the database and does not need changes deductible database. This paper addresses these events to confirm database security.

Sports Domain Expending wings for entertainment and humanities race. For the effective
decision making, Information & Communication Technologies is Providing indispensable part for
Performance augmentation and Injury Corrosion and Effective Decision Making. Nowadays, In Future
Sports and Sports Technologies shall be accelerating decision digitally and Extremely Useful for many
reasons as video officials use ICT to Help them make decision which would be hard to see normally.
Technologies is promoting Sport Science and utilizing from range of athlete Technology to live webcasts,
Wireless Technology, Spectators, WAP Phones and Instant Reply‟s. UNSDG Agenda 2030 Goal 03 Advocate
the requirement of sporting in daily life. Technology implementation in sports is working as bridge to make
mankind more fit and healthy by involving individuals in sports. In this Paper we are enlighten on Performance
Augmentation & Injury Corrosion in Sports Domain in Views of Effective decision making through
Technologies.

Előszó
A Magyar Regionális Tudományi Társaság Dél-alföldi Tagozata 2013-ban új
kezdeményezést indított, „Regionális tudományi tapasztalatcsere a Dél-Alföldön”
címmel egy olyan platformot hozott létre a fiatal kutatók számára, amelynek
segítségével évenként más-más helyszínen, a régió más-más településén találkozhatnak
egymással, és a regionális tudomány ismert és elismert tudósaival, gyakorlati
szakembereivel. A fórum lehetőséget biztosít a regionális tudományhoz
kötődő fiatal kutatók számára, hogy megismerhessék egymás eredményeit, illetve
bemutathassák munkájukat a „szakma tapasztalt művelőinek”. A kezdeményezés
eredményeként első alkalommal 2013. júniusában, Békéscsabán került megrendezésre
ez a fórum az „I. Regionális tudományi tapasztalatcsere a Dél-Alföldön. Új
hangsúlyok a területi fejlődésben” címmel. A színvonalas előadások lektorált változata
egy tanulmánykötetben megjelent és online elérhető: http://www.eco.uszeged.
hu/kutatas-tudomany/workshop/workshop.
2014-ben Kecskeméten folytatódott a sorozat, a Magyar Regionális
Tudományi Társaság Dél-alföldi Tagozata, a MTA Szegedi Területi Bizottsága
Gazdaságtudományi Szakbizottsága, valamint a Kecskeméti Főiskola Kertészeti Kar
„II. Regionális tudományi tapasztalatcsere a Dél-Alföldön. A területi fejlődés
dilemmái, 2014-2020” címmel szervezte meg a konferenciát, mely színvonalas
előadásokat, konstruktív vitákat hozott, és kiváló alkalmat teremtett új kapcsolatok
kiépítésére, és a meglevő kapcsolatok ápolására.
A Szegedi Tudományegyetem Gazdaságtudományi Kar Közgazdaságtani
Doktori Iskola célja jelen kötet kiadásával, hogy a széles szakmai kör számára
elérhetővé tegye a tudományos fórumon elhangzott, a szekcióvezetők által színvonalasnak
értékelt, válogatott előadások lektorált változatát.
Az első rész tanulmányai a régiók, térségek fejlődése fő elméleti kérdéseinek
szerteágazó világába kalauzolja el az olvasót. A második rész a társadalmi
folyamatok térbeliségének kérdéseivel foglalkozik. A harmadik rész a vidék fenntarthatóságának
témakörébe tartozó tanulmányokat vonultatja fel.
A szerkesztők ezúton mondanak köszönetet a fórum szervezőinek, a
tanulmányok lektorálását végző szakembereknek, a kötet végső formába öntését
végző kollégáknak, és természetesen az egyes tanulmányok szerzőinek.
Szeged, 2014. november
A szerkesztők

Team working is becoming increasingly important in modern organizations due to its beneficial outcomes. A team's performance levels are determined by complex interactions between the attributes of its individual members, the communication and dynamics between members, the working environment, and the team's work tasks. As organizations evolve, so too does the nature of team working. During the past two decades, product development in engineering organizations has increasingly been undertaken by multidisciplinary integrated product teams. Such increasing complexity means that the nature of research methods for studying teams must also evolve. Accordingly, this paper proposes an agent-based modeling approach for simulating team working within an engineering environment, informed by research conducted in two engineering organizations. The model includes a number of variables at an individual level (competency, motivation, availability, response rate), team level (communication, shared mental models, trust), and task level (difficulty, workflow), which jointly determine team performance (quality, time to complete the task, time spent working on the task). In addition to describing the model's development, the paper also reports the results of various simulation runs that were conducted in response to realistic team working scenarios, together with its validation. Finally, the paper discusses the model's practical applications as a tool for facilitating organizational decision making with respect to optimizing team working.

This article examines the challenge of modifying orthodox ‘case study’ approaches to the growth of firms and inter-organizational networks in the light of recent work on the evolution of business knowledge. We suggest that a modified Penrosian framework, combined with a qualified application of critical realist practices, could contribute to more coherent and insightful theorizing in this area. We begin with a critique of Edith Penrose’s legacy, including her efforts to initiate a historically informed tradition of social scientific research on the growth of the firm. We go on to consider the explanatory potential of critical realism, when adopted as a methodological adjunct to neo-Penrosian theorizing. Our main proposition is illustrated through a superfactual reinterpretation of certain aspects of the historical case study of the Rover Company (1896-1982) conducted by Richard Whipp and Peter Clark (1986).

There is increasing interest of organization for advanced presentation and data analysis for public users. This paper shows how to integrate data from enterprise data warehouse with spatial data warehouse, publish them together to online interactive map, and enable public users to perform analysis in simple web interface. As case study is used Business Intelligence System for Investors, where data comes from different sources, different levels, structured and unstructured. This approach has three phases: creating spatial data warehouse, implementing ETL (extract, transform and load) procedure for data from different sources (spatial and non-spatial) and, finally, designing interface for performing data analysis. The fact, that this is a public site, where users are not known in advanced and not trained, calls for importance of usability design and self-evident interface. Investors are not willing to invest any time in learning the basics of a system. Geographic information providers need geoportals to enable access to spatial data and services via the Internet; and it is a first step in creating Spatial Data Infrastructure (SDI).

The project proposes to build a system which is capable of extracting business intelligence for a manufacturer, from online product reviews. For a particular product, it extracts a list of the discussed features and their associated sentiment scores. Online products reviews and review characteristics are extracted from www.Amazon.com. A two level filtering approach is adapted to choose a set of reviews that are perceived to be useful by customers. The filtering process is based on the concept that the reviewer generated textual content and other characteristics of the review, influence peer customers in making purchasing choices. The filtered reviews are then processed to obtain a relative sentiment score associated with each feature of the product that has been discussed in these reviews. Based on these scores, the customer's impression of each feature of the product can be judged and used for the manufacturers benefit.

The purpose of this paper is to search for the main characteristics of intelligent organizations. Intelligence is one of those concepts that everyone has in mind, but hardly few can define or explain it. Thus, it is even more difficult to extend this concept to organizations, and to talk about organizational intelligence. This paper tries to show the new dimensions of intelligence up to the organizational level, and the new characteristics such intelligent organizations may have. Basically, intelligent organizations are the ones which developed the capability to continuously adapt to changing and unpredictable environments. They are learning organizations in which the human capital, including the individual intelligence, has been integrated into a new cognitive structure at the organization level.

Nigeria has 169 universities approved by National University Commission (NUC) with 43 Federal Universities, 47 State Universities and 79 Private Universities. The universities are located in different geographical areas and collaboration among these universities is difficult and this makes accessibility to data and information resource of the universities a problem. As a result quite a number of knowledge built from these resources are locally managed within each university private network that is not shared with other universities due to lack of virtual collaboration on a grid computing platform. Knowledge building and management in a country is a function of the information that one could have access to with ease but non-collaboration of the universities in a virtual environment is a hindrance to quality national knowledge building and management. Thus the need arises to embrace grid system as platform for all universities to pool their resources together and hence make their information resources available and accessible for knowledge building and management. This report presents an overview of Nigeria universities' operations as regard their research and innovation policies and vis-à-vis governance and resource management across public and private universities. Also we did a systematic review and analysis of knowledge grid (KG) technology vis-à-vis its use for knowledge management in Nigerian universities. We focused on identifying the strengths and challenges of knowledge grid development and implementation vis-à-vis the technological, economic and social implications involved in the process. Our future work is to develop a robust knowledge grid model that will allow collaboration among universities in Nigerian community and hence facilitates information and knowledge sharing and management among the universities.

Purpose This research identifies the forms of tacit knowledge frequently requested in the job descriptions of knowledge workers in a multinational automotive manufacturer's product development department. It then explores how and why the most requested forms of tacit knowledge are used in practice to achieve organizational goals. Design/methodology/approach This study follows a sequential mixed-methods approach to quantify the most frequently requested forms of tacit knowledge within internal job descriptions and then explores how and why this tacit knowledge is used. The first stage applies manifest content analysis to internal job descriptions to highlight the epitomes of tacit knowledge to identify the most frequently requested forms of tacit knowledge. The second stage employs semi-structured interviews to explore the use of the most frequently requested forms of tacit knowledge in practice. Findings The research indicated that the organization most frequently requested tacit knowledge in the form of skills and experience in the job descriptions of knowledge workers in the product development department. When the use and application of tacit knowledge in the form of skills were further explored in practice, it was found that tacit knowledge-based socially-focused skills were used, which was underpinned by the need to bring people together and align them towards a common goal to make things work; by enabling people to work together as a team; by developing and using networks; and acting as a required resource to support the development and integration in product development. Tacit knowledge in the form of experience was applied through the application of personally obtained experience to enhance development work by acting as a pacemaker for increasing efficiency and a sense of upcoming issues.

Current literature stressed on the need to for a deeper understanding on the role of positive emotions needed for sharing knowledge during project collaboration or sharing knowledge in virtual communities. The aim of this article is to express a reviews of current polished literature to map out the landscape of knowledge sharing in relation to the facilitation of positive emotion. This critiques of current literature led to a conceptual framework recognizing the expectations of stakeholders in various sectors, i.e. project management, education, etc., to achieve project progress and problem solution/s through the intention to share knowledge through a reflection of positive emotions within knowledge management tools like virtual communities. There are theoretical and practical implications critiqued out of current literature, thus proposed in this article.