Designing Recommendation or Suggestion Systems: looking to the future

2021 | Electronic Markets | Citations: 1

Authors: Sharma, Ravi S.; Shaikh, Aijaz A.; Li, Eldon

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Topics: user experience electronic market crowdsourcing social bookmark recommender system

Methods: design principle literature sample qualitative interview

Theories: theory of affordance

If you Build it, They Won’t Come: What Motivates Employees to Create and Share Tagged Content: A Theoretical Model and Empirical Validation

2020 | International Journal of Information Management | Citations: 0

Authors: Allam, Hesham; Bliemel, Michael; Ali-Hassan, Hossam; Blustein, James; Spiteri, Louise

Abstract: The purpose of this paper is to investigate factors influencing employees’ knowl ... Expand

Abstract: The purpose of this paper is to investigate factors influencing employees’ knowledge-sharing behavior on social tagging supported systems. Using the strong theoretical background of the well-known technology acceptance model (TAM), this paper proposes and empirically validates a model that fits the social and technical nature of social tagging tools within the public sector. The analyses in this paper were based on data collected from a large survey of more than 480 respondents working for two public organizations in the United States. The findings demonstrate a significant impact of the role of social presence in encouraging employees to create and share content. Further, there is a strong relationship between the benefits employees receive from using tagging tools and their creation and sharing of tagged content. Specifically, the following factors showed a significant impact on employees’ creation and sharing behavior, specifically their attitudes towards and intentions to create and share tags: perceived ease of use, perceived usefulness, social presence, and pro-sharing norms. For researchers, the paper offers an opportunity to further study knowledge-sharing behavior regarding social media technologies. The findings should motivate practitioners to inject these tools with a social aspect so that employees are encouraged to share content. Collapse

Topics: social bookmark social presence knowledge sharing social media perceived ease of use

Methods: survey chi squared test theory development SEM tool literature study

Theories: technology acceptance model motivation theory unified theory of acceptance and use of technology

Applying a multi-dimensional hedonic concept of intrinsic motivation on social tagging tools: A theoretical model and empirical validation

2019 | International Journal of Information Management | Citations: 0

Authors: Allam, Hesham; Bliemel, Michael; Spiteri, Louise; Blustein, James; Ali-Hassan, Hossam

Abstract: A B S T R A C TParticipation in and adding content to social tagging tools is i ... Expand

Abstract: A B S T R A C TParticipation in and adding content to social tagging tools is important for these tools to achieve their purpose of classifying and organizing information. Users of social tagging tools are driven to participate and add tags by extrinsic and intrinsic motivation. Extrinsic motivation is dominating research as a main predictor of why users use information systems. Social tagging tools, as a subset of social media tools, are distinguished by their unique social aspect that makes intrinsic motivation a potential driver for users to add tags to content. Intrinsic motivation, when applied to social tagging tools, could entail many shades that represent different users' motives for using such tools. In this paper, we add a rich concept of intrinsic motivation to include hedonism as a main predictor of users' behavior on social tagging tools. We empirically validate a previously proposed theoretical model of three dimensional concepts of hedonism with three components describing individuals' hedonic state when interacting with social tagging tools: explorability, curiosity, and enjoyment. After a robust and thorough data analysis using structured equation modeling, the results confirm our theoretical model and suggest using a richer concept of enjoyment to reflect a hedonic dimension when investigating intrinsic motivation with interactive social media tools. Our validated model could be the spark of new factors that have the potential to influence user acceptance of information systems in general and in social media tools. This research contributes to the development of attitude-behavior theories that could explain users' acceptance of dynamic web Collapse

Topics: social bookmark intrinsic motivation social media usage intention user acceptance

Methods: survey structural equation modeling partial least squares regression chi squared test theory development

Theories: technology acceptance model motivation theory

Investigating Users’ Tagging Behavior in Online Academic Community Based on Growth Model: Difference between Active and Inactive Users

2019 | Information Systems Frontiers | Citations: 0

Authors: Xu, Yunhong; Yin, Dehu; Zhou, Duanning

Abstract: With the development of social interaction techniques and social tagging mechani ... Expand

Abstract: With the development of social interaction techniques and social tagging mechanisms, online academic community as a new platform has greatly changed the way users organize and share knowledge. The large amount of social tagging data occurred on online academic community provides us a channel to systematically understand users’ tagging behavior. Based on data collected from a specific online academic community, this research first classifies users into two categories: active and inactive users. After that, growth models (damped exponential model, normal model and fluctuating model) are employed to investigate tagging behavior for both active and inactive users. Factors that might influence the likelihood of the growth models are also identified based on multinomial logistic regression. This research expands our understanding on users’ tagging behavior and factors that may affect their tagging behavior in the context of online academic community. Collapse

Topics: social bookmark strategic management user behavior

Methods: multinomial logistic regression descriptive statistic literature study theoretical contribution time series analysis

Why do young people tag photos on social networking sites? Explaining user intentions

2018 | International Journal of Information Management | Citations: 23

Authors: Dhir, Amandeep; Kaur, Puneet; Rajala, Risto

Abstract: Scholars have emphasized an urgent need to investigate the determinants of user ... Expand

Abstract: Scholars have emphasized an urgent need to investigate the determinants of user intentions to share content on social networking sites (SNS). A growing share of the content in social media is visual − including Photos − which users can share by tagging. To improve the understanding of the determinants of social media users’ behavioral intention to share content, this study investigates why people tag photos on SNS. A comprehensive research model was developed based on the Unified Theory of Acceptance and Use of Technology (UTAUT2) and Social Cognitive Theory (SCT). The validity of the extended UTAUT2 model was tested on a new form of technology use which is not only timely but is much desired by the scholars engaged in information systems research. The research model investigates the role of habit, hedonic motivation, facilitating conditions, social influence, effort expectancy, performance expectancy, social presence, social status, and self-efficacy in influencing the user intentions to engage in photo-tagging. The research model was tested using a cross-sectional study of 780 adolescent Facebook users. The findings suggest that only habit and hedonic motivation have a significant direct influence on the user’s intentions to tag photos. The study contributes to the theorizing of the role of habits and hedonic motivations in user behaviors in the SNS and provides new insights into these factors for the managers of social media sites. Collapse

Topics: Facebook self efficacy social presence usage intention information system use

Methods: survey cross sectional research SEM tool structural equation modeling theory development

Theories: extended unified theory of acceptance and use of technology technology acceptance model information systems theory unified theory of acceptance and use of technology social cognitive theory

Enhancing information source selection using a genetic algorithm and social tagging

2017 | International Journal of Information Management | Citations: 4

Authors: Lebib, Fatma Zohra; Mellah, Hakima; Drias, Habiba

Abstract: The selection of information sources in a distributed information retrieval envi ... Expand

Abstract: The selection of information sources in a distributed information retrieval environment remains a critical issue. In this context, it is known that a distributed information retrieval system consists of a huge number of sources. Ensuring retrieval effectiveness is to search only sources which are likely to contain relevant information for a query. An important number of heuristics exist among which we quote genetic algorithm that is used to solve the above problem. The proposed genetic algorithm consists in finding the best selection in large space of potential solutions; where a solution is represented as a combination of a set of sources. The improvement of selection accuracy is assured based on the user’s track through the use of sources, to say that source description is enriched with tags from the tagging history. Collapse

Topics: social bookmark information retrieval cloud computing database system open source

Methods: computational algorithm experiment optimization model term frequency–inverse document frequency simulation

Special section on data science and business intelligence

2017 | International Journal of Information Management | Citations: 0

Authors: de Vasconcelos, José Braga; Rocha, Álvaro

Abstract: Effective knowledge management practices in organizations are focused on knowle ... Expand

Abstract: Effective knowledge management practices in organizations are focused on knowledge creation and knowledge transfer activities, and this is why intelligence and competencies matters at the organizational workplace, and drive the workplaces more intelligent, productive, and innovative. For most knowledge intensive organisations, the continuous availability and development of domain expertise is fundamental. In this context, the collection, integration, storage, processing and systematic analysis of data is a key challenge, and Big Data, Data Mining, and Machine Learning systems are applied to create new software solutions and decision support systems to reduce the uncertainty and discover new patterns of organisational behaviour.The problem of managing knowledge in large companies has grown with the increasing complexity of organisations and quantity of data and information that flows within and among organisations. An organisation's knowledge is built upon the experience of their human resources and the lessons they learn. The dynamic nature of organisational work in such companies requires rich computer models to support information technology. Research on Data Science incorporates new and old approaches, combining Knowledge Data Discovery techniques from the nineties and new research trends concerning Big Data, Machine Learning and Computational Statistics.The areas of information systems, knowledge management and engineering, artificial intelligence, data mining, and business process modelling are closely connected. Knowledge management deals with the development of corporate information systems in which knowledge and artificial intelligence reasoning techniques play important roles in the creation of new knowledge assets and related intellectual capital for knowledge intensive organisations. This editorial argues that effective knowledge management and engineering are based on the dynamic nature of the organisational knowledge, and predictive data analysis and insights identification can transform and add value to the organization. Data Science and Business Intelligence research presents knowledge management perspectives for the application of data mining tools and predictive analysis at the organizational workplace.This special section on Data Science and Business Intelligence aims to investigate data mining and machine learning approaches for network analysis and evaluation towards corporate knowledge modelling and representation. The articles included in this special section apply a set of Data Science techniques, such as data mining, machine learning and big data approaches for network analysis and corporate knowledge management practices. The goal of this special section is to bring together the areas of knowledge management, data science and business intelligence by drawing on papers from researchers and practitioners to recent and relevant work in the field. We present research challenges and practical outcomes of applying business intelligence and data science techniques to knowledge management in the context of knowledge intensive organizations.The manuscripts are extended versions of selected papers from the fifth World Conference on Information Systems and Technologies (WorldCIST 2017), which was held at Porto Santo, Madeira, Portugal. The WorldCIST conferences have become an important forum for researchers and professionals to exchange ideas and experiences about research problems and corporate solutions related to information systems, technologies, software engineering and computer science in general. This special section is composed by five research papersThe first entitled of "A Framework for Social Well-Being and Skills Management at the Workplace" presents a research concerning knowledge management practices for skills development. This research combines the perception of well-being at the workplace with gamification techniques. The proposed solution incorporates an intelligent system to keep the user (employee) aware of their well-being status.The second paper "The Data Scientist Profile and its Representativeness in the European e-Competence Framework and the Skills Framework for the Information Age" deals with knowledge and activities that are mainly supported by data-driven web applications, making extensive use of databases and data services. This led to the rise of Data Scientists as professionals of major relevance, which extract value from data and create stateof-the-art data artefacts that generate even more increased value for knowledge intensive organisations.The third one entitled: "A Knowledge Management Approach to Capture Organizational Learning Networks" presents a research work on knowledge management which describes a research project to develop an organizational knowledge architecture that is being specified and developed to support collaboration tasks as well as design and model predictive data analysis and insights for organizational development. This research presents a knowledge management perspective at the organizational workplace towards the development of an organizational learning network.The forth research paper: "Enhancing Information Source Selection using a Genetic Algorithm and Social Tagging" presents an approach to minimise the source selection problem in a context of a large number of sources. These sources are generally diverse and distributed and can be http://dx. MARKdatabases, web applications, academic research libraries, specialized e-commerce sites, and search engines. This research searches the solution, which maximizing the similarity between sources, composing a selection and the user query. The solution architecture applies an intelligent system, in particular Genetic Algorithms.The fifth and last paper: "A Big Data System supporting Bosch Braga Industry 4.0 Strategy" examines a new trend in the industry: the Industry 4.0 and the Factories of the Future. In this context, the collection, integration, storage, processing and analysis of data is a key challenge, and Big Data systems are the link for the entities and data needs in the industry and related business processes. This paper addresses this key challenge, proposing and implementing a Big Data analytics architecture in a multinational organisation. Collapse

Topics: knowledge management big data social bookmark organization learning business intelligence

Methods: computational algorithm

IMPROVING THE CAPABILITIES OF EMAIL FOR BUSINESSES – THE CASE OF SOCIAL TAGGING

2016 | European Conference On Information Systems | Citations: 0

Authors: Alimam, Mayla; Bertin, Emmanuel; Crespi, Noël

Abstract: Email is one of the most used tools in enterprises for various purposes. However ... Expand

Abstract: Email is one of the most used tools in enterprises for various purposes. However, the enterprise transformation programs are focusing today on social media tools rather than email. This paper discusses the properties of email in enterprises and whether further research is yet necessary on this tool. We provide a set of capabilities to compare between social media tools and email. As email is still affording some distinctive capabilities, we suggest improving this tool by applying a social bookmarking service to email messages. An experiment on the prototyped service highlights the perceived utility of email social tagging service for socializing employees’ activities. The paper details, finally, future implications of this research. Collapse

Topics: electronic mail social bookmark social media PHP affordance

Methods: experiment design artifact literature study qualitative interview computational algorithm

Theories: theory of affordance

How Social Software Can Support Business Process Management – Developing a Frame- work

2015 | Americas Conference on Information Systems | Citations: 0

Authors: Kettenbohrer, Janina; Beimborn, Daniel; Fischer, Dorit; Kloppenburg, Mirko

Abstract: Solving complex tasks by collaborative teams is an important organizational capa ... Expand

Abstract: Solving complex tasks by collaborative teams is an important organizational capability. Beside traditional team work, an organization’s collective intelligence can be supported by social software technologies. Within business process management (BPM), social software can be used to support the different lifecycle steps of a business process. In this paper, we introduce a framework which shows possible opportunities for social software to contribute to effective BPM. An expert workshop was conducted to receive a first evaluation of the framework. The combination of social software and BPM is supposed to improve the functional performance of IT systems for BPM and the employees’ acceptance for BPM systems. Collapse

Topics: social media social network business process management organizational context brainstorming

Methods: qualitative interview literature study

Drivers and Obviations for using Social Media in companies – Insights from an online-survey on Firms in German-speaking Countries

2014 | Americas Conference on Information Systems | Citations: 0

Authors: Lattemann, Christoph; Pollock, Ariane; Beinhold, Frank

Abstract: This paper critically reflects predictions that social and mobile media will rev ... Expand

Abstract: This paper critically reflects predictions that social and mobile media will revolutionize internal and external corporate processes and collaboration approaches by analyzing the current usage of social software and mobile media in various firm’s operational fields in German-speaking countries. It further aims at identifying some of factors that influence the implementation and application of social software and mobile media in SMEs. Collapse

Topics: social media marketing management knowledge management social bookmark blog

Methods: survey literature study