The increase in food demand in Indonesia is one of the consequences of the imbalance between population growth and declining food products. One of alternative technologies that can be used in plant breeding programs to increase agricultural production, in order to meet food demands, is genetically modified organism (GMO) technology. This technology presents a lot of pros and cons among the public-related impacts that will be accepted by consumers. The purpose of this study was to determine the level of sustainability between GMO and non-GMO foods. The performance measurement model for GMO and non-GMO foods was considered according to the seven issues of sustainability that represented environmental, social, and economic aspects. The assessment method was conducted by using Adjusted Profit (AP) with Total Price Recovery (TPR) indicators and Total Factor Productivity (TFP) by utilizing the Data Envelopment Analysis (DEA) Method. Assessments made on each supply chain component included agriculture, processing, and transport to wholesalers/retailers. This study used numerical examples of rice production in Indonesia. The research results found that the performance of non-GMO rice chain is better than GMO rice. It indicates that non-GMO rice is more sustainable. The results show that the proposed model can be applied to measure the sustainability of GMO and Non-GMO agri-food supply chain performance.

The innovation of electric motorcycle swap-battery (EMSB) technology encourages the formation of a new ecosystem at the early stage of the supply chain. The EMSB technology has allowed an open innovation system with collaboration between supply-chain players, universities, and the government for finding a thriving solution to enable the faster adoption and diffusion of EMSB in Indonesia. Standardization is seen as a way to accelerate the downstream EMSB technology innovation to leverage the economic benefits and to support the growth of a green economy in Indonesia. This study aimed to propose a model with which to measure the technology readiness of the EMSB’s stakeholders in implementing the swappable battery (SB) standard. We developed the technometric framework and Economic Benefits of Standards—ISO Methodology 2.0. We generated 13 criteria of technoware, humanware, inforware, and orgaware and 21 indicators of the standard’s impacts to be utilized as a measurement model. We interviewed 11 respondents consisting of the standard regulator, research and development center, manufacturer, testing labs, and product-certification bodies. The results show the technology contribution coefficient (TCC) and earnings before interest and taxes (EBIT) value representing the SB standard’s feasibility. The proposed model can evaluate the weak points and propose strategies to leverage the SB standard’s technology readiness and economic benefits.

Indonesia's economic sector continues to rely on carbon-emitting fossil fuels. The government is speeding up electrification by encouraging people to switch from traditional to electric automobiles. Electric motorcycles are one option for lowering CO2 emissions. Many researchers have investigated the value attributes affecting consumers”™ attitudes and behavior around electric motorcycles. The structural model was created using the Partial Least Square ”“ Structural Equation Model (PLS-SEM). The questionnaires were circulated through the internet, and 1,223 valid responses were received. Researching people's interest in environmentally friendly vehicles and the growing ecosystem of electric vehicles will indicate that the electric motorcycle business has a bright future. This research also shows that attitude is a major impact on electric motorcycle purchase intention and infrastructure, and subjective norms and perceived behavioral control have a direct effect on electric motorcycle purchase intention. Cost and technology do not influence a person in determining his desire to buy an electric vehicle.

The purpose of this research is to develop a model for measuring the efficiency of the TTO incubation process performance to accelerate the commercialization of research results in universities. The method of analyzing the efficiency used in this research is the Data Envelopment Analysis (DEA) method based on Banker, Charnes, and Cooper (BCC), which is output-oriented. The software used in analyzing the efficiency of TTO performance is MaxDEA 8. The output of this research is a mathematical model tool for measuring the efficiency of TTO performance by DEA, which considered 17 parameters and proposed recommendations for TTO performance strategies. The limitation of this research is the object of research in one university that has succeeded in the commercialization of research. This research implies that the performance efficiency measurement model is an alternative predictive way to increase the acceleration of commercialization. The practical implications of this research are that it can evaluate performance or inefficient strategies in the incubation process of higher education research results to the Technology Transfer Office (TTO). This research also provides recommendations on strengthening the TTO function that can be used as a reference for improving performance at universities. This research measures the level of performance evaluation of TTO in the incubation process, which refers to the Death Valley framework. This incubation process is the main process accelerating the commercialization of research results in universities.

Many benefits follow from the use of Electric Vehicles (EVs) to replace fossil fuel-based vehicles (FVs), i.e., improved transportation energy efficiency, reduced carbon and noise emissions, and the mitigation of tailpipe emissions. However, replacing conventional FVs with EVs requires the establishment of a suitable charging infrastructure representing a commonplace detail that blends into the landscape and is available in various locations. This research focuses on the infrastructure of Electric Motorcycles (EM), constituting a relatively dense network of charging stations (CS), which is an essential factor in accelerating the commercialization of EM in Indonesia. In this case study, we propose a Charging Infrastructure Optimization approach for placing charging stations to meet the demand posed by motorcycles. This study uses motorcycle user data as the initiation data for electric motorcycle users. The selection of charging station development points uses the calculation methods of the centrality index and scalogram, which describe the density of community activities. After the charging station’s construction point is obtained, the point is validated with the optimization model that has been designed with respect to the Maximal Covering Location Problem. We also analyze the benefits and costs of constructing this charging station to determine its feasibility.