Measuring the performance of business processes is already a main concern for both faculty and enterprise players, since organizations are motivated to reach the productivity stage. Employing a performance achievement framework for the relationship between business incubator success factors will guarantee connection with commercial schemes, which support a high level of performance indicators in successful business incubator models. This research employs a quantitative approach, with the data analyzed using the IBM SPSS version 23 and Smart PLS version 3 statistical software packages. Employing a sample of 95 incubator managers from 19 universities which geographically located in Indonesia, it is shown that the image of business incubator factors has a positive effect on incubator performance. The study investigates the relationship between incubator performance and business incubator success factors in Indonesia. It was found that IT, as part of the business incubators’ facets/abilities, partially supports their performance; that the entry criteria directly support the performance of the incubators; that mentoring networks also support the performance, with good infrastructure systems as a moderating factor; that funding supports the performance of business incubators, also with good infrastructure systems as a moderating factor; and that university regulations and government support and protection enhance the performance of business incubators, with credits and rewards as a moderating factor. In addition, a variety of indicators from the local context affiliate positively to promote a community that highlighted the incubators’ strategies.

This research was conducted on industrial agriculture in Indonesia. Risk analysis was carried out based on previous research. One source of risk was obtained, namely raw materials that did not meet specifications, which was then proposed to be mitigated by evaluating supplier performance. This activity involves a lot of data, requiring efficient and effective data storage and access. The level in the simulation layout includes analysing system needs, using problem diagrams, compiling activity diagrams, deciding subprocesses, and filtering information. The analysis is carried out by comparing the use of supply chains with Blockchain and without Blockchain, which is then obtained to determine whether there is an increase. A sequentially stored data scenario describes a situation when the transaction process is in progress and is stored sequentially according to the process that occurs. Storing data in groups explains a problem when a transaction has been completed and stored in groups with similar data, making it easier to track specific data. In this regard, a simulation will be carried out using a website, namely a blockchain demo. The design stage starts with identifying system requirements, creating use case diagrams, compiling activity diagrams, determining subprocesses, and selecting information. The simulation results obtained will be analysed to determine the feasibility of Blockchain as a means of supporting risk mitigation related to data using aspects, including security, trust, traceability, sustainability, and costs.

Purpose: This research studies the development of the evolving dynamic system model and explores the important elements or factors and what detailed attributes are the main influences model in achieving the success of a business, industry and management. It also identifies the real and major differences between static and dynamic business management models and the detailed factors that influence them. Later, this research investigates the benefits/advantages and limitations/disadvantages of some research studies. The studies conducted in this research put more emphasis on the capabilities of system dynamics (SD) in modeling and the ability to measure, analyse and capture problems in business, industry, manufacturing etc.Design/methodology/approach: The research presented in this work is a qualitative research based on a literature review. Publicly available research publications and reports have been used to create a research foundation, identify the research gaps and develop new analyses from the comparative studies. As the literature review progressed, the scope of the literature search was further narrowed down to the development of SD models. Often, references to certain selected literature have been examined to find other relevant literature. To do so, a supporting tool (that connects related articles) provided by Google Scholar, Scopus, and particular journals has been used.Findings: The dynamic business and management model is very different from the static business model in complexity, formality, flexibility, capturing, relationships, advantages, innovation model, new goals, updated information, perspective and problem-solving abilities. The initial approach of a static system was applied in the canvas business model, but further developments can be continued with a dynamic system approach.Research limitations/implications: Based on this study, which shows that businesses are developing more towards digitalisation, wanting the ability to keep up with the era that is moving so fast and the desire to increase profits, an instrument is needed that can help describe the difficulties of the needs and developments of the future world. This instrument, or tool of SD, is also expected to assist in drawing future models and in building a business with complex variables that can be predicted from the beginning.Practical implications: This study will contribute to the SD study for many business incubator research studies. Many practical in business incubator management to have a benefit how to achieve the business performance management (BPM) in SD review.Originality/value: The significant differences between static and dynamics to be used for business research and strategic performance management. This comparative study analyses some SD models from many authors worldwide. Their goals behind their strategic business models and encounter for their respective progress.

This study aims to examine the effect of critical success and moderating factors in Indonesian public universities' business incubators. The study of business incubators benefits university professors in their roles as managers and advisors, university faculty entrepreneurs and startups/tenants in the knowledge transfer and entrepreneurship learning processes, and government officials in effective policy making. For the universities, the incubators serve as a platform for the commercialization of their research efforts. The incubators assist the universities' stakeholders in fulfilling their newly identified responsibilities towards building the nation's economy and giving the faculty members and graduate students the chance to conduct research. Regarding the economic environment, the incubators help create job opportunities, increase the country's economic value, and reduce poverty. This research employed the quantitative method approach, and the data were analyzed using the IBM SPSS version 23 and Smart PLS version 3 statistical software packages. The samples of this research were comprised of 31 business incubator managers from Indonesian public universities. Although there have been previous models about critical success and moderating factors for business incubators in other countries, this study is the first that was conducted in Indonesia and found direct and indirect relationships between critical success factors and moderating success factors for Indonesian Public University Business Incubators. The results of the research demonstrated that good system and infrastructure showed a strong direct relationship with success factors and that information technology showed a strong relationship with the moderating factors, namely age and quality of facilities. Furthermore, mentoring and networking showed a strong relationship with the moderating factors good system and infrastructure and that university regulation had a strong relationship with moderating factor credit and rewards. Entry criteria, exit criteria, and funding support showed strong direct relationships to success factors. These findings could improve the management of business incubators in Indonesian Public Universities and allow them to more successful.

Universities play an important role in motivating young graduates to become technology entrepreneurs. The objectives of this research are to investigate the success factors for business incubators and to develop and propose a framework of successful business incubators for public universities in Indonesia. Indonesian public universities that have business incubators were considered for this research. A preliminary study was conducted with a panel of experts who have the necessary insights and experiences in managing both the incubators and the relationships within the incubators with the tenant firms. This research examines some significant measures with reference to the unique features of university business incubators in order to better understand the manner in which incubators can be assessed in a developing country. The result of this research includes a framework of successful business incubators in Indonesian public universities. This framework is developed on the basis of previous studies and the preliminary study conducted with ten business incubator experts. Keywords: incubator; Framework; Public university; Successful factors; Indonesia Published at: IJTech Vol 7, No 6 (2016) DOI: https://doi.org/10.14716/ijtech.v7i6.3351

PT Hartekprima Listrindo is a manufacturer that produces silent, open and mobile/trailer types of diesel-powered generators, along with AMF/ATS panels and synchronous panels with the HARTECH brand. The generators produce eight Kva power variants up to 3000 Kva power. PT Hartekprima Listrindo plans to increase the production capacity by relocating its factories to a new place. The production capacity of the new plant is planned to achieve 20 generators/year in a 5184 m2 total land area of production. This relocation design uses Systematic Layout Planning (SLP) method, and the layout design is simulated. The SLP method is carried out by describing material flow in the production process using a Multi-Product Process Chart (MPPC), and then continued by using Activity Relationship Chart (ARC) which illustrates the relationship among the activities of the departments. The next stage of layout design is describing the Activity Relationship Diagram (ARD) and Area Allocation Diagram (AAD). The comparison layout design resulted in 2 alternative layouts that are better than the initial layout. The chosen layout design is alternative design 1 because it reduces transportation time and increases movement efficiency.