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The study's purpose is to conduct an evaluation of the opportunities and challenges of cooperatives in the industrial era 4.0 by strengthening the role of human resource management in dealing with economic changes in the market environment facing the 4.0 competition battle in the Indonesian economy in 2045, which causes changes in all aspects of digitalization that occur in cooperative organizations. Changes in cooperative digitalization necessarily require business intelligence in evaluating high-tech advances in information technologies in the exchange of knowledge related to product design and innovation, as well as information obtained from suppliers and customer behavior, which will be continuously communicated in Industry 4.0. The research method is the troubling method in which it explores causal links in depth, attentively listening to feedback from multiple parties, and identifies the proper solution ideas through a narrative study that is articulated qualitatively. According to the findings, cooperative development in Indonesia still needs to be enhanced in order to grow stronger in planning and funding. This development will serve as the foundation for the Indonesian economy to attain mutually beneficial economic goals by 2045. As a result, cooperatives must secure their position in the digital platform shift ecosystem, which necessitates tight collaboration in design and innovation that is mutually advantageous for suppliers and customers.
Programs to improve the performance of micro and small enterprises (MSEs) through clustering is now becoming the design of industrial and innovation policies which is implemented by policy makers in Indonesia. There has been a common perception that clusters are able to encourage entrepreneurship, learning, and productivity improvements for MSEs more effectively. This common perception, however, should be further explored whether clustered MSEs successfully obtain "collective efficiency" from clusters or they even suffer from "collective failure". This book is an attempt to reveal such issues of MSEs clustering by presenting a case study on small industrial clusters in Central Java which is well known as the "heartland" of MSEs operate in clusters. While supporting programs are persistently introduced to such clusters, in fact, to obtain "the collective efficiency of clustering" is not so easy. Unfair competition accompanied by ineffective cooperation might be factors that cause to clustered MSEs failed to gain the benefit of clustering.