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This study aims to identify and analyse energy intensity in Indonesia’s manufacturing industry based on industrial sub-sector, island region, technology intensity, firm size, type of ownership and exporter status to determine which of these characteristics have the highest potential to decrease energy intensity.

Using firm characteristics data from statistics of large and medium industries in Indonesia, this study decomposed energy consumption of Indonesian firms into economic activity, economic structure and energy intensity for the period 2010–2014 through the logarithmic mean Divisia index (LMDI).

The results showed the decomposed energy intensity based on the six sub-categories. From the sub-categories, several characteristics which induced the most increases in energy intensity are highlighted. Several industrial sub-sectors were classified as highly energy-consuming, including rubber and plastic products, glass and non-metal mineral products, food, electrical machinery and apparatus, chemical, paper, motor vehicles and trailers and tobacco. Results from other sub-categories indicated that firms with high energy intensity were located in the Java--Bali region, had medium technology intensity and were exporters. Meanwhile, firm size and ownership type sub-categories did not show clear differences in energy intensity.

This study provides more focused policy recommendations for related policymakers and stakeholders to emphasise the most energy-inefficient and energy-intensive firm based on the results from each sub-category and hence policy priorities to reduce energy consumption can be well-targeted.

This study contributes to the field through a more thorough energy intensity analysis based on the classification of Indonesian firm characteristics to provide a more detailed insight on the cause of the ever-increasing energy intensity level in the country.

The challenge of unforeseen uncertainties in exploratory projects requires the lead firm in a project alliance to effectively manage exploratory co-innovation. The purpose of this paper is to investigate the types of capabilities a lead firm required in exploratory projects and how these capabilities enable the exploratory innovation of the project alliance.

A multiple-case study was done to provide empirical evidence for the rationale of the capabilities of the lead firm. The provided analysis used abductive reasoning of two typical exploratory projects in China.

This paper identifies two types of capabilities: innovation-related capabilities and network-related capabilities. Furthermore, a process model of the capabilities of the lead firm is developed that enables exploratory co-innovation in a project alliance. The capabilities of the lead firm input varied at four different stages.

Innovation-related capabilities and network-related capabilities could form the foundation for the lead firm in an exploratory project alliance. This will enable an exploratory co-innovation and collaboratively overcome the barriers of exploratory projects.

Although exploratory project attracts extensive attention for its unique characteristics and universal value, there is limited amount of research on the context of joint exploratory projects. This study starts from the role of lead firm in an exploratory project alliance, contributes toward the comprehension of the link between the lead firm’s capabilities and the process of exploratory co-innovation. The findings will be of value in supporting the management of exploratory innovation in a project alliance.

To investigate the relationship between technological diversification and firm performance as a function of varying levels of technological coupling and internal technological change.

A longitudinal study of US-based bio-pharmaceutical companies.

Technological diversification improves invention performance. However, high levels of technological coupling reduce this effect.

Firms with highly diversified technological portfolios should strive to keep their technologies at low levels of technological coupling.

This is the first study to show that technological coupling reduces the positive effect of technological diversification on firms' invention performance.

The purpose of this paper is to propose a quantitative method for identifying multiple and hierarchical knowledge trajectories within a specific technological domain (TD).

The proposed method as a patent-based data-driven approach is basically based on patent classification systems and patent citation information. Specifically, the method first analyzes hierarchical structure under a specific TD based on patent co-classification and hierarchical relationships between patent classifications. Then, main paths for each sub-TD and overall-TD are generated by knowledge persistence-based main path approach. The all generated main paths at different level are integrated into the hierarchical main paths.

This paper conducted an empirical analysis by using Genome sequencing technology. The results show that the proposed method automatically identifies three sub-TDs, which are major functionalities in the TD, and generates the hierarchical main paths. The generated main paths show knowledge flows across different sub-TDs and the changing trends in dominant sub-TD over time.

To the best of the authors’ knowledge, the proposed method is the first attempt to automatically generate multiple hierarchical main paths using patent data. The generated main paths objectively show not only knowledge trajectories for each sub-TD but also interactive knowledge flows among sub-TDs. Therefore, the method is definitely helpful to reduce manual work for TD decomposition and useful to understand major trajectories for TD.

Early fault detection of bearing plays an increasingly important role in the operation of rotating machinery. Based on the properties of early fault signal of bearing, this paper aims to describe a novel hybrid early fault detection method of bearings.

In adaptive variational mode decomposition (AVMD), an adaptive strategy is proposed to select the optimal decomposition level K of variational mode decomposition. Then, a criterion based on envelope entropy is applied to select the optimal intrinsic mode functions (OIMF), which contains most useful fault information. Afterwards, local tangent space alignment (LTSA) is used to denoising of OIMF. The envelope spectrum of the OIMF is used to analyze the fault frequency, thereby detecting the fault. Experiments are conducted in a simulated signal and two experimental vibration signals of bearings to verify the effect of the new method.

The results show that the proposed method yields a good capability of detecting bearing fault at an early stage. The new method can extract more useful information and can reduce noise, which can provide better detection accuracy compared with the other two methods.

An adaptive strategy based on center frequency is proposed to select the optimal decomposition level of variational mode decomposition. Envelope entropy is used to fault feature selection. Combining the advantage of the AVMD-envelope entropy and LTSA, which suits the nature of the early fault signal. So, the proposed method has better detection accuracy, which provides a good alternative for early fault detection of bearings.

This study aims to analyse the scientific relationship between technological innovation and carbon emissions. Taking the Chinese electric power industry as the empirical research object, this study examined the effect of power technological innovation on carbon emissions and proposed policy recommendations for the development of technological innovation in China.

This study first calculated the energy consumption and carbon emission level of the Chinese electric power industry from 2005 to 2018. Secondly, this study built an evaluation index system for technological innovation of electric power with six indicators: average utilisation hours of power generation equipment; power consumption rate of power plant; line loss rate; standard coal consumption for power generation; standard coal consumption for power supply; and number of patent applications granted for generation, conversion or distribution of electric power in China. Finally, from a practical point of view, the relationship between technological innovation and carbon emissions of the Chinese electric power industry from 2005 to 2018 is evaluated and analysed.

Power technology innovation has been found to have a long-term and relatively large effect on carbon emissions, and carbon emissions have a short-term and insignificant impact on power technology innovation.

This study puts forward relevant suggestions for developing technological innovation and technology transfer, which is essential to establishing a low-carbon or zero-carbon power system in China.

This study provides empirical evidence for clarifying the relationship between technological innovation and carbon emissions in the power industry and further develops research theories on technological innovation and carbon emissions.

Relevant authorities will adopt measures to promote technological innovation and development in the power sector to reduce carbon emissions.

This study built an evaluation index system with six indicators for technological innovation of electric power. The evaluation method was used to measure the technological innovation level of the Chinese electric power industry. The causal link between technological innovation and carbon emissions in China was analysed.

The purpose of this paper is to present an integrated analysis of determining factors of farmers’ genetically modified (GM) technology adoption behavior, with a special emphasis on information acquisition, knowledge accumulation, product attributes and technology traits.

Extending the expected profit maximization framework into a random utility model which accommodates joint decisions of information acquisition and technology adoption, the authors use the full information maximum likelihood method to yield both consistent and efficient estimates. The model is applied to a field survey collecting a sample of 141 randomly selected bananas farmers.

The empirical results indicate information acquired through social network will increase the probability of adoption. Knowledge accumulation as depicted by education and farming experience is found to play a role in farmers’ technology adoption, whereas disease-resistant technology trait and flavor-enriching product attribute of GM bananas also appear to be important determinants for GM seeds adoption in Taiwan.

Empirical evidence supports significance of technology traits and product attributes in farmer's GM technology adoption, suggesting the close collaboration between industry, government and academia is the key to successful commercialization of GM crops.

Understanding the determinants of farmers’ GM technology adoption can serve as the basis for promoting new biotechnology, and thus can facilitate the establishment of tenable solutions to food security issues.

This paper is the first attempt to incorporate information acquisition into the behavioral analysis of GM technology adoption. The present study also extends previous literature by considering influential factors related to both consumers’ and producers’ preferences in modeling technology adoption.

Describes the important role of decomposition strategy in parallel computing, and its influence is illustrated with the example of a very frequently used parallel algorithm for matrix multiplication. On the basis of the performed analysis of the parallel computers used worldwide divides them into the two basic groups which are considered from the programmer‐developer point of view to be very different. They also introduce the typical principal structures for both these groups of parallel computers and also their models. The paper then in an illustrative way describes the development of concrete parallel algorithm for matrix multiplication on various parallel systems. For each individual practical implementation of matrix multiplication there is introduced the derivation of its calculation complexity. The individual ways of developing parallel matrix multiplication and their implementations are compared, analysed and discussed from the point of view of the programmer‐developer and user. The very important role of the decomposition strategies that are mainly of the class of asynchronous parallel computers is highlighted.