Purpose The current explanations in the cyber incivility and knowledge hoarding literature suffer from two problems. The first is a lack of cogent explanation of cyber incivility and knowledge hoarding from social exchange theory (SET) perspective. The second is the unexplained attenuating propensity of justice on the connection between cyber incivility and knowledge hoarding, more specifically, interactional justice. Design/methodology/approach This paper uses a simple random sampling method to obtain cross-sectional data from 223 employees working in IT and telecommunication service companies in Jordan. The obtained data were analyzed using partial least squares structural equation modeling (PLS-SEM) technique also known as variance-based structural equation modeling. Findings By applying SET theoretical lens and PLS-SEM, the authors show that cyber incivility exerts strong impact on knowledge hoarding, and interactional justice may not always function as a buffer. That is, the association between cyber incivility and knowledge hoarding is not impacted by interactional justice levels. Originality/value The contribution of this paper builds on the lack of practical comprehension on the association between cyber incivility and knowledge hoarding and the role played by interactional justice. Implications for theory and practice are discussed.
Preparing an optimal exam timetable in universities is challenging for head of departments, especially for colleges with multiple number of departments, courses, and students. Harmony search algorithm is used by many researchers to solve this problem but none of them could get an optimal solution. In this paper, a new algorithm which is called optimised harmony search algorithm with distributed selections is proposed by optimising the harmony search algorithm and the genetic algorithm. The new algorithm could satisfy hard, soft, and general constraints and generate an optimal exam timetable for a huge number of courses and students. The proposed algorithm is implemented and applied on Jadara University, the algorithm uses an upper triangular matrix to reduce relationships and memory usage, a three-dimensional matrix to ease the exams timetable management a deterministic number generators to eliminate timeslots conflicts, and backtracking algorithm to enhance the population selections. Lecturers and students’ feedback showed a good satisfaction as well the system results.
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