The influence of online professional social media in human resource management: A systematic literature review

Professional social media platforms (PSMs), including LinkedIn, have created better opportunities for students and employees to advance their career aspirations. Though PSMs seem to be an effective human resource management (HRM) tool, in order to leverage PSMs effectively, it is strategically essential to incorporate research inputs from both the employers' and the individuals’ perspectives. Realizing this, academic researchers have been interested in PSMs since the previous decade. However, research on PSMs and their effectiveness continues to be in the embryonic stage. To catalyze scholarly interest and provide a foundation for formulating sound theoretical propositions for the efficient use of PSMs, it is imperative to aggregate and critically evaluate prior findings and provide avenues for future research. Addressing this need, the current study undertakes a systematic literature review to comprehensively understand the influence of PSMs on one particular aspect of HRM—namely, hiring processes. Forty-five studies were selected from existing literature to examine the accumulated knowledge, assess current research boundaries, and derive ways to enrich this area of research further. The study is motivated by the fact that given the short life cycle of social media platforms and information systems, PSMs need to innovate and continuously offer value to their users. The study makes a concrete contribution to PSM literature by generating actionable research avenues for future researchers and providing practical insights for managers and service providers.</p

Applied (Meta)-Heuristic in Intelligent Systems

Engineering and business problems are becoming increasingly difficult to solve due to the new economics triggered by big data, artificial intelligence, and the internet of things. Exact algorithms and heuristics are insufficient for solving such large and unstructured problems; instead, metaheuristic algorithms have emerged as the prevailing methods. A generic metaheuristic framework guides the course of search trajectories beyond local optimality, thus overcoming the limitations of traditional computation methods. The application of modern metaheuristics ranges from unmanned aerial and ground surface vehicles, unmanned factories, resource-constrained production, and humanoids to green logistics, renewable energy, circular economy, agricultural technology, environmental protection, finance technology, and the entertainment industry. This Special Issue presents high-quality papers proposing modern metaheuristics in intelligent systems