Self-other agreement for improving communication in libraries and information services

Purpose – This paper aims to examine the Self-Other Agreement between leaders and employees in the sector of Libraries and Information Services (LIS) to construct a sustainable and strategic communicational process among library directors and staff. Design/methodology/approach – A sample of 135 leaders-employees of 17 organisations of LIS in more than five countries answered on a quantitative methodological research instrument in a multiplicity of variables. Statistical analysis of independent samples t-test was used to testify our research hypotheses. Findings – Results indicated that there is a difference in means between the two independent samples (leaders-employees). There are library leaders who rate themselves quite high, and there are employees who rate their leaders with lower evaluations. Research limitations/implications – This research extends and improves the matter of Self-Other Agreement in the sector of LIS through the collection of data that indicated a possible gap of communication and trustworthiness between leaders and employees. Practical implications – Regardless of the difference or the consensus of ratings among leaders and employees, the results of this research could be served as a stimulus plus as a starting point for library leaders by correcting or developing relations of communication and trustworthiness between them and their followers. Originality/value – Self-Other Agreement is one of the major factors that positively or negatively affect the overall operation of the organization in the way a leader could perceive the additional feedback. In the sector of LIS, the study of Self-Other Agreement is a rich and unexplored research area which deserves further analysis

Self-other agreement for improving communication in libraries and information services

Purpose – This paper aims to examine the Self-Other Agreement between leaders and employees in the sector of Libraries and Information Services (LIS) to construct a sustainable and strategic communicational process among library directors and staff. Design/methodology/approach – A sample of 135 leaders-employees of 17 organisations of LIS in more than five countries answered on a quantitative methodological research instrument in a multiplicity of variables. Statistical analysis of independent samples t-test was used to testify our research hypotheses. Findings – Results indicated that there is a difference in means between the two independent samples (leaders-employees). There are library leaders who rate themselves quite high, and there are employees who rate their leaders with lower evaluations. Research limitations/implications – This research extends and improves the matter of Self-Other Agreement in the sector of LIS through the collection of data that indicated a possible gap of communication and trustworthiness between leaders and employees. Practical implications – Regardless of the difference or the consensus of ratings among leaders and employees, the results of this research could be served as a stimulus plus as a starting point for library leaders by correcting or developing relations of communication and trustworthiness between them and their followers. Originality/value – Self-Other Agreement is one of the major factors that positively or negatively affect the overall operation of the organization in the way a leader could perceive the additional feedback. In the sector of LIS, the study of Self-Other Agreement is a rich and unexplored research area which deserves further analysis

Improving the Visibility and the Accessibility of Web Services. A User-Centric Approach.

The World Wide Web provides a well standing environment in any kind of organizations for exposing online products and services. However, no one ensures that web products or services which provided by organizations or enterprises, would receive the proper visibility and accessibility by the internet users. The process of Search Engine Optimization examines usability in design, architecture and content that an internet-based system has, for improving its visibility and accessibility in the web. Successful SEO process in an internet-based system, which is set under the paternity of an organization, ensures higher recognition, visibility and accessibility for the web services that the system provides to internet users. The aim of this study characterized with a trinity of axes. In the first axe, an internet-based system and the web services that provides is examined in order to understand its initial situation regarding its visibility and accessibility in the web. In the second axe, the study follows a user-centric approach on how and in what way the examined system could be improved based on its users’ needs and desires. After the encapsulation of needs and desires that the users expressed as regards the usability of the system in design, architecture and content, the third axe takes place. In the third axe, the extracted needs and desires of users are implemented in the under-examined system, in order to understand if its visibility and accessibility has improved in the World Wide Web.For the completion of this trinity of axes, the Soft Systems Methodology approach is adopted. SSM is an action-oriented process of inquiry which deals with a problematic situation from the Finding Out about the situation through the Taking Action to improve it. Following an interpretative research approach, ten semi-structured interviews take place in order to capture all the participants’ perceptions and different worldviews regarding of what are the changes that they need and desire from the examined system. Moreover, in this study, the conduction of three Workshops, constitute a cornerstone for implementing systemically desirable and culturally feasible changes where all participants can live with, in order to improve system’s visibility and accessibility in the internet world. The results indicate that the adoption of participants’ needs and desires, improved the levels of usability, visibility and accessibility of the under examined internet-based system. Overall, this study firstly contributes to expand the knowledge as regards the process of improving the visibility and accessibility of internet-based systems and their web services in the internet world, based on a user-centric approach. Secondly, this study works as a practical toolbox for any kind of organization which intends to improve the visibility and accessibility of its current or potential web services in the World Wide Web

Big Data Analytics for Search Engine Optimization

In the Big Data era, search engine optimization deals with the encapsulation of datasets that are related to website performance in terms of architecture, content curation, and user behavior, with the purpose to convert them into actionable insights and improve visibility and findability on the Web. In this respect, big data analytics expands the opportunities for developing new methodological frameworks that are composed of valid, reliable, and consistent analytics that are practically useful to develop well-informed strategies for organic traffic optimization. In this paper, a novel methodology is implemented in order to increase organic search engine visits based on the impact of multiple SEO factors. In order to achieve this purpose, the authors examined 171 cultural heritage websites and their retrieved data analytics about their performance and user experience inside them. Massive amounts of Web-based collections are included and presented by cultural heritage organizations through their websites. Subsequently, users interact with these collections, producing behavioral analytics in a variety of different data types that come from multiple devices, with high velocity, in large volumes. Nevertheless, prior research efforts indicate that these massive cultural collections are difficult to browse while expressing low visibility and findability in the semantic Web era. Against this backdrop, this paper proposes the computational development of a search engine optimization (SEO) strategy that utilizes the generated big cultural data analytics and improves the visibility of cultural heritage websites. One step further, the statistical results of the study are integrated into a predictive model that is composed of two stages. First, a fuzzy cognitive mapping process is generated as an aggregated macro-level descriptive model. Secondly, a micro-level data-driven agent-based model follows up. The purpose of the model is to predict the most effective combinations of factors that achieve enhanced visibility and organic traffic on cultural heritage organizations’ websites. To this end, the study contributes to the knowledge expansion of researchers and practitioners in the big cultural analytics sector with the purpose to implement potential strategies for greater visibility and findability of cultural collections on the Web

How to Utilize My App Reviews? A Novel Topics Extraction Machine Learning Schema for Strategic Business Purposes

Acquiring knowledge about users’ opinion and what they say regarding specific features within an app, constitutes a solid steppingstone for understanding their needs and concerns. App review utilization helps project management teams to identify threads and opportunities for app software maintenance, optimization and strategic marketing purposes. Nevertheless, app user review classification for identifying valuable gems of information for app software improvement, is a complex and multidimensional issue. It requires foresight and multiple combinations of sophisticated text pre-processing, feature extraction and machine learning methods to efficiently classify app reviews into specific topics. Against this backdrop, we propose a novel feature engineering classification schema that is capable to identify more efficiently and earlier terms-words within reviews that could be classified into specific topics. For this reason, we present a novel feature extraction method, the DEVMAX.DF combined with different machine learning algorithms to propose a solution in app review classification problems. One step further, a simulation of a real case scenario takes place to validate the effectiveness of the proposed classification schema into different apps. After multiple experiments, results indicate that the proposed schema outperforms other term extraction methods such as TF.IDF and χ2 to classify app reviews into topics. To this end, the paper contributes to the knowledge expansion of research and practitioners with the purpose to reinforce their decision-making process within the realm of app reviews utilization

Strategic communication process for sustainable entrepreneurial environment in nonprofit organizations

Online Publication Date: 27 September 2016This research process is focused on the analysis of three axes which are Fair Treatment, Team Effectiveness, and Job Satisfaction of employees and decision-makers who are occupied in Nonprofit Organizations. Nowadays, the reduced financial flexibility imposes a careful delimitation of strategic communication that is implemented by Nonprofit Organizations. The aim is to examine a strategic communication process for a sustainable entrepreneurial environment. More specifically, this research attempts to find a possible correlation between the personal perception of each employee regarding the level he treated fairly in the working environment (Fair Treatment) and the existence of an effective team into which the employee feels he is a part of (Team Effectiveness). The purpose is to draw conclusions on how these two factors impact on the Job Satisfaction of the employee or decision-maker. The possibility to have correlations among the above axes can be operated as a feedback to highlight strengths and weaknesses of Nonprofit Organizations to their decision-makers

Social Media Analytics and Metrics for Improving Users Engagement

Social media platforms can be used as a tool to expand awareness and the consideration of cultural heritage organizations and their activities in the digital world. These platforms produce daily behavioral analytical data that could be exploited by the administrators of libraries, archives and museums (LAMs) to improve users’ engagement with the provided published content. There are multiple papers regarding social media utilization for improving LAMs’ visibility of their activities on the Web. Nevertheless, there are no prior efforts to support social media analytics to improve users’ engagement with the content that LAMs post to social network platforms. In this paper, we propose a data-driven methodology that is capable of (a) providing a reliable assessment schema regarding LAMs Facebook performance page that involves several variables, (b) examining a more extended set of LAMs social media pages compared to other prior investigations with limited samples as case studies, and (c) understanding which are the administrators’ actions that increase the engagement of users. The results of this study constitute a solid stepping-stone both for practitioners and researchers, as the proposed methods rely on data-driven approaches for expanding the visibility of LAMs services on the Social Web