EDUKASI DAN PENGETAHUAN TERHADAP PENTINGNYA KARAKTERISTIK BERWIRAUSAHA

Individual entrepreneurial characteristics, especially as seen from generation to generation, have distinct differences. For example, the younger generation has entrepreneurial characteristics such as wanting to succeed quickly, focusing on instant processes, and easily "following along" with existing trends. This is the primary concern of the implementing team, and it necessitates additional knowledge in developing entrepreneurial characteristics. This training was provided to 20 partner participants from the Amanah Cordova Entrepreneurship School in Pondok Jati Village, South Tangerang. This activity took place on December 11, 2022 and was carried out through face-to-face discussions. This activity's outcomes focused on three key areas: the quality of the material provided, the quality of the activity process, and the quality of the resource persons. According to the indicators of the quality of the material provided, the participants thought the material was good enough to be used later in entrepreneurship. Furthermore, the participants felt that the activity was going well overall, based on the quality of the activity process indicators, and that it was able to provide them with additional knowledge about the characteristics of entrepreneurship. The good manner and attitude of the resource persons in conveying the material was an important point that was highly rated by all participants in terms of the quality of the resource persons. Characteristic formation and improvement are dynamic, mirroring the dynamics of business competition. As a result, this activity can be performed on a regular and continuous basis

Competitive Advantages as a Complete Mediator Variable in Strategic Resources, Dynamic Capabilities and Performance Relations in the Car Sales Sector

Taking the resource-based view –RBV- and the dynamic capability view –DCV- as an orientation, the main aim of this study is to develop the mediator role that competitive advantages play in the relations between strategic resources, dynamic capabilities and performance. The study takes place in a dynamic and changing sector: the sale of new cars in Portugal. The results show that (a) achieving competitive advantages, which are decisive for business results, depends on the available strategic resources and the generating of dynamic capabilities, (b) in dynamic and changing sectors strategic resources are essential to generate dynamic capabilities, (c) firms must center their attention on, more than results, the generating of sustainable competitive advantages as these act as a mediator variable of the effect of strategic resources and dynamic capabilities on performance. The data scrutiny uses structural equation modeling (SEM) through PLS as the statistical instrument. The sample comprises 89 firms which sell new cars in Portugal

Multi-product cost and value stream modelling in support of business process analysis

To remain competitive, most Manufacturing Enterprises (MEs) need cost effective and responsive business processes with capability to realise multiple value streams specified by changes in customer needs. To achieve this, there is the need to provide reusable computational representations of organisational structures, processes, information, resources and related cost and value flows especially in enterprises realizing multiple products. Current best process mapping techniques do not suitably capture attributes of MEs and their systems and thus dynamics associated with multi-product flows which impact on cost and value generation cannot be effectively modelled and used as basis for decision making. Therefore, this study has developed an integrated multiproduct dynamic cost and value stream modelling technique with the embedded capability of capturing aspects of dynamics associated with multiple product realization in MEs. The integrated multiproduct dynamic cost and value stream modelling technique rests on well experimented technologies in the domains of process mapping, enterprise modelling, system dynamics and discrete event simulation modelling. The applicability of the modelling technique was tested in four case study scenarios. The results generated out of the application of the modelling technique in solving key problems in case study companies, showed that the derived technique offers better solutions in designing, analysing, estimating cost and values and improving processes required for the realization of multiple products in MEs, when compared with current lean based value stream mapping techniques. Also the developed technique provides new modelling constructs which best describe process entities, variables and business indicators in support of enterprise systems design and business process (re) engineering. In addition to these benefits, an enriched approach for translating qualitative causal loop models into quantitative simulation models for parametric analysis of the impact of dynamic entities on processes has been introduced. Further work related to this research will include the extension of the technique to capture relevant strategic and tactical processes for in-depth analysis and improvements. Also further research related to the application of the dynamic producer unit concept in the design of MEs will be required

Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP: Evidence for Switzerland

This study utilizes the dynamic factor model of Giannone et al. (2008) in order to make now-/forecasts of GDP quarter-on-quarter growth rates in Switzerland. It also assesses the informational content of macroeconomic data releases for forecasting of the Swiss GDP. We find that the factor model offers a substantial improvement in forecast accuracy of GDP growth rates compared to a benchmark naive constant-growth model at all forecast horizons and at all data vintages. The largest forecast accuracy is achieved when GDP nowcasts for an actual quarter are made about three months ahead of the official data release. We also document that both business tendency surveys as well as stock market indices possess the largest informational content for GDP forecasting although their ranking depends on the underlying transformation of monthly indicators from which the common factors are extracted.Business tendency surveys, Forecasting, Nowcasting, Real-time data, Dynamic factor model

The integrated use of enterprise and system dynamics modelling techniques in support of business decisions

Enterprise modelling techniques support business process re-engineering by capturing existing processes and based on perceived outputs, support the design of future process models capable of meeting enterprise requirements. System dynamics modelling tools on the other hand are used extensively for policy analysis and modelling aspects of dynamics which impact on businesses. In this paper, the use of enterprise and system dynamics modelling techniques has been integrated to facilitate qualitative and quantitative reasoning about the structures and behaviours of processes and resource systems used by a Manufacturing Enterprise during the production of composite bearings. The case study testing reported has led to the specification of a new modelling methodology for analysing and managing dynamics and complexities in production systems. This methodology is based on a systematic transformation process, which synergises the use of a selection of public domain enterprise modelling, causal loop and continuous simulationmodelling techniques. The success of the modelling process defined relies on the creation of useful CIMOSA process models which are then converted to causal loops. The causal loop models are then structured and translated to equivalent dynamic simulation models using the proprietary continuous simulation modelling tool iThink

An engineering approach to business model experimentation – an online investment research startup case study

Every organization needs a viable business model. Strikingly, most of current literature is focused on business model design, whereas there is almost no attention for business model validation and implementation and related business model experimentation. The goal of the research as described in this paper is to develop a business model engineering tool for supporting business model management as a continuous design, validation and implementation cycle. The tool is applied to an online investment research startup in roll out and market phase. This paper describes the research as performed in a case study setting by focusing on the design, implementation and evaluation of the business model engineering tool. We also analyze the actual implementation and usage of the business model tool by the online investment research startup by focusing on the most critical actions related to actual business model implementation – i.e. actions with so-called ‘Lollapalooza tendencies’

Knowledge-generating Efficiency in Innovation Systems: The relation between structural and temporal effects

Using time series of US patents per million inhabitants, knowledge-generating cycles can be distinguished. These cycles partly coincide with Kondratieff long waves. The changes in the slopes between them indicate discontinuities in the knowledge-generating paradigms. The knowledge-generating paradigms can be modeled in terms of interacting dimensions (for example, in university-industry-government relations) that set limits to the maximal efficiency of innovation systems. The maximum values of the parameters in the model are of the same order as the regression coefficients of the empirical waves. The mechanism of the increase in the dimensionality is specified as self-organization which leads to the breaking of existing relations into the more diversified structure of a fractal-like network. This breaking can be modeled in analogy to 2D and 3D (Koch) snowflakes. The boost of knowledge generation leads to newly emerging technologies that can be expected to be more diversified and show shorter life cycles than before. Time spans of the knowledge-generating cycles can also be analyzed in terms of Fibonacci numbers. This perspective allows for forecasting expected dates of future possible paradigm changes. In terms of policy implications, this suggests a shift in focus from the manufacturing technologies to developing new organizational technologies and formats of human interaction