What do the business employers want? A sequential mixed methods exploration of information professionals’ competencies

Abstract

PurposeThe job market of library and information professionals has expanded from academic to industrial, special and business libraries. The unique nature of the organizations, their data and clientele demand a different set of competencies. The purpose of this study is to explore the competencies of information professionals from the perspectives of business employers – a comparatively new job place for the library and information management professionals.Design/Methodology/ApproachExploratory sequential mixed methods approach was used to meet objectives of this study in two phases. In the first phase, qualitative data was extracted from panel discussion. Themes were extracted from this qualitative data. In the second phase, a questionnaire was designed which was based on qualitative themes. The instrument contained the nine-point Likert type scale and was filled by the business and industry human resource managers. The quantitatively gathered data were analysed while using descriptive and inferential statistical techniques in the Statistical Package for Social Sciences SPSS version 22.FindingsThe findings of this study indicate that work coordination, knowledge of intellectual property rights, online searching ability, leadership qualities, trustworthiness and background knowledge of the prospective organizations are the basic competencies required by the business employers.Practical ImplicationsThis study will guide the students on which qualities they are required to obtain to qualify for jobs of information professionals in the current employment sector. Additionally, it will provide guidelines to the continuous education programme designers, prompting them to include in their trainings the vital qualities of candidates required by the current job market.Originality ValueThis is the maiden study that has explored the competencies of library and information management professionals through exploratory sequential mixed methods.