scholarly journals Current Market Demand for Core Competencies of Librarianship—A Text Mining Study of American Library Association’s Advertisements from 2009 through 2014

2016 ◽  
Vol 6 (2) ◽  
pp. 48 ◽  
Author(s):  
Qinghong Yang ◽  
Xingzhi Zhang ◽  
Xiaoping Du ◽  
Arlene Bielefield ◽  
Yan Liu
Keyword(s):  
Text Mining ◽  
Core Competencies ◽  
Market Demand ◽  
American Library

Exploring Library Core Competencies: A Text Mining Study of American Library Association’s Job Advertisements From 2006 Through 2017

2021 ◽  
pp. 089443932110272
Author(s):  
Qinghong Yang ◽  
Zehong Shi ◽  
Yan Quan Liu
Keyword(s):  
Language Processing ◽  
Work Experience ◽  
Core Competencies ◽  
Core Competency ◽  
Analytical Investigation ◽  
Market Demand ◽  
American Library ◽  
Job Titles ◽  
Job Advertisements ◽  
Processing Techniques

Are core competency requirements for relevant positions in the library shifting? Applying natural language processing techniques to understand the current market demand for core competencies, this study explores job advertisements issued by the American Library Association (ALA) from 2006 to 2017. Research reveals that the job demand continues to rise at a rate of 13% (2006–2017) and that the requirements for work experience are substantially extended, diversity of job titles becomes prevalent, and rich service experience and continuous lifelong learning skills are becoming more and more predominant for librarians. This analytical investigation informs the emerging demands in the American job market debriefing the prioritization and reprioritization of the current core competency requirements for ALA librarians.

scholarly journals Key competencies for big data analytics professions: a multimethod study

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ajax Persaud
Keyword(s):  
Big Data ◽  
Text Mining ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Educational Institutions ◽  
Market Demand ◽  
Skilled Workers ◽  
Content Type ◽  
Multimethod Approach ◽  
Skills Shortages

PurposeThis study aims to identify the precise competencies that employers are seeking for big data analytics professions and whether higher education big data programs enable students to acquire the competencies.Design/methodology/approachThis study utilizes a multimethod approach involving three data sources: online job postings, executive interviews and big data programs at universities and colleges. Text mining analysis guided by a holistic competency theoretical framework was used to derive insights into the required competencies.FindingsWe found that employers are seeking workers with strong functional and cognitive competencies in data analytics, computing and business combined with a range of social competencies and specific personality traits. The exact combination of competencies required varies with job levels and tasks. Executives clearly indicate that workers rarely possess the competencies and they have to provide additional training.Research limitations/implicationsA limitation is our inability to capture workers' perspectives to determine the extent to which they think they have the necessary competencies.Practical implicationsThe findings can be used by higher educational institutions to design programs to better meet market demand. Job seekers can use it to focus on the types of competencies they need to advance their careers. Policymakers can use it to focus policies and investments to alleviate skills shortages. Industry and universities can use it to strengthen their collaborations.Social implicationsMuch closer collaborations among public institutions, educational institutions, industry, and community organizations are needed to ensure training programs evolve with the evolving need for skills driven by dynamic technological changes.Originality/valueThis is the first study on this topic to adopt a multimethod approach incorporating the perspectives of the key stakeholders in the supply and demand of skilled workers. It is the first to employ text mining analysis guided by a holistic competency framework to derive unique insights.

Science and Technology Text Mining: Mexico Core Competencies

2002 ◽  
Author(s):  
Ronald N. Kostoff ◽  
J. A. del Rio ◽  
Hector D. Cortes ◽  
Charles Smith ◽  
Andrew Smith
Keyword(s):  
Text Mining ◽  
Core Competencies ◽  
Science And Technology

scholarly journals Educating Assessors: Preparing Librarians with Micro and Macro Skills

2016 ◽  
Vol 11 (2) ◽  
pp. 74 ◽  
Author(s):  
Rachel Applegate
Keyword(s):  
Professional Development ◽  
Core Competencies ◽  
American Library Association ◽  
Library Science ◽  
Skill Sets ◽  
American Library ◽  
Library Education ◽  
Library Assessment ◽  
Assessment Skills ◽  
Bodies Of Evidence

Abstract Objective – To examine the fit between libraries’ needs for evaluation skills, and library education and professional development opportunities. Many library position descriptions and many areas of library science education focus on professional skills and activities, such as delivering information literacy, designing programs, and managing resources. Only some positions, some parts of positions, and some areas of education specifically address assessment/evaluation skills. The growth of the Library Assessment Conference, the establishment of the ARL-ASSESS listserv, and other evidence indicates that assessment skills are increasingly important. Method – Four bodies of evidence were examined for the prevalence of assessment needs and assessment education: the American Library Association core competencies; job ads from large public and academic libraries; professional development courses and sessions offered by American Library Association (ALA) divisions and state library associations; and course requirements contained in ALA-accredited Masters of Library Science (MLS) programs. Results – While one-third of job postings made some mention of evaluation responsibilities, less than 10% of conference or continuing education offerings addressed assessment skills. In addition, management as a topic is a widespread requirement in MLS programs (78%), while research (58%) and assessment (15%) far less common. Conclusions – Overall, there seems to be more need for assessment/evaluation skills than there are structured offerings to educate people in developing those skills. In addition, roles are changing: some of the most professional-level activities of graduate-degreed librarians involve planning, education, and assessment. MLS students need to understand that these macro skills are essential to leadership, and current librarians need opportunities to add to their skill sets.

scholarly journals A Review of Text Corpus-Based Tourism Big Data Mining

2019 ◽  
Vol 9 (16) ◽  
pp. 3300 ◽  
Author(s):  
Qin Li ◽  
Shaobo Li ◽  
Sen Zhang ◽  
Jie Hu ◽  
Jianjun Hu
Keyword(s):  
Big Data ◽  
Text Mining ◽  
Language Processing ◽  
Destination Image ◽  
Market Demand ◽  
Text Data ◽  
Value Analysis ◽  
Research Areas ◽  
Massive Growth ◽  
Big Data Applications

With the massive growth of the Internet, text data has become one of the main formats of tourism big data. As an effective expression means of tourists’ opinions, text mining of such data has big potential to inspire innovations for tourism practitioners. In the past decade, a variety of text mining techniques have been proposed and applied to tourism analysis to develop tourism value analysis models, build tourism recommendation systems, create tourist profiles, and make policies for supervising tourism markets. The successes of these techniques have been further boosted by the progress of natural language processing (NLP), machine learning, and deep learning. With the understanding of the complexity due to this diverse set of techniques and tourism text data sources, this work attempts to provide a detailed and up-to-date review of text mining techniques that have been, or have the potential to be, applied to modern tourism big data analysis. We summarize and discuss different text representation strategies, text-based NLP techniques for topic extraction, text classification, sentiment analysis, and text clustering in the context of tourism text mining, and their applications in tourist profiling, destination image analysis, market demand, etc. Our work also provides guidelines for constructing new tourism big data applications and outlines promising research areas in this field for incoming years.

scholarly journals Valuing Reciprocal Synergies in Merger and Acquisition Deals Using the Real Option Analysis

2020 ◽  
Vol 10 (2) ◽  
pp. 27
Author(s):  
Andrejs Čirjevskis
Keyword(s):  
Real Options ◽  
Emerging Market ◽  
Core Competencies ◽  
Merger And Acquisition ◽  
The Body ◽  
The Arctic ◽  
Market Demand ◽  
Body Shop ◽  
Input Variables ◽  
Acquisition Processes

This research explores how global cosmetic players sense emerging market demand for new technologies and products, seize opportunities through the acquisition of core competencies that they needed, and transform their global value chain. The aim of this paper to assess the prerequisites of reciprocal synergies in merger and acquisition (M&A) deals pursuing global growth. To achieve this aim, the author asked a research question: what is the best way to measure the competence-based synergies as added market value in M&A deals? To answer this question, the author researched the latest theoretical findings on the antecedents of synergy in the merger and acquisition processes. The valuation of reciprocal synergies with real options was discussed with a focus on input variables’ values. Based on in-depth content analysis, the ARCTIC (A—Advantage, R—Relatedness, C—Complexity of Competence, T—Time of Integration, I—Implementation Plan, C—Cultural Fit) framework was developed and tested. The author selected three case studies to test the methodology empirically, namely, L’Oréal’s Body Shop acquisition in 2006 and divestiture in 2017, the acquisition of The Body Shop by Brazilian’s Natura Group in 2017, and the acquisition of Avon Products by Natura that was announced in 2019. The model for the valuation of reciprocal synergies used and discussed real options with a special focus on input variables’ values.

An Input–Process–Output Model of Pilot Core Competencies

2017 ◽  
Vol 7 (2) ◽  
pp. 78-85 ◽  
Author(s):  
Heikki Mansikka ◽  
Don Harris ◽  
Kai Virtanen
Keyword(s):  
Path Analysis ◽  
Team Performance ◽  
Core Competencies ◽  
Core Competency ◽  
Principal Component ◽  
Analysis Model ◽  
Input Process ◽  
The Core ◽  
Performance Framework ◽  
Process Output

Abstract. The aim of this study was to investigate the relationship between the flight-related core competencies for professional airline pilots and to structuralize them as components in a team performance framework. To achieve this, the core competency scores from a total of 2,560 OPC (Operator Proficiency Check) missions were analyzed. A principal component analysis (PCA) of pilots’ performance scores across the different competencies was conducted. Four principal components were extracted and a path analysis model was constructed on the basis of these factors. The path analysis utilizing the core competencies extracted adopted an input–process–output’ (IPO) model of team performance related directly to the activities on the flight deck. The results of the PCA and the path analysis strongly supported the proposed IPO model.

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