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The purpose of this paper is to construct index system of international cooperation project selection, propose a grey cluster model for project selection and apply propose model for Jiangsu international cooperation key-technology projects selection.

Considering supply of international cooperation project is different with its demand, and regional key cooperation technologies should consider urgency and possibility of project cooperation, the author separately construct index groups for supply and demand. To aggregate assessment information of each cooperation project, whitenization function for each index is constructed and then cluster coefficient of index group could be aggregated by using each index and its weight information. Fixed weight grey cluster model is redefined and applied for selecting international cooperation project. And steps of calculation of model are given out. Real application of Jiangsu international cooperation projects’ selection is used for demonstrating process of the proposed model.

Results show that constructed indexes of international cooperation project selection can be used for selecting regional cooperation projects well. And proposed fixed weight grey cluster model can aggregate all indexes information well. Therefore, proposed indexes and model in this manuscript is effective and also it can be used for solving similar problems.

Jiangsu province is a developed region of China, and its international cooperation is more active than other regions accordingly. Constructed indexes of international cooperation project selection and fixed weight grey cluster model can help government to select needed projects easily.

This manuscript first define a demand as urgency and supply as possibility, and a new index system of international cooperation project selection is constructed with several urgency indexes and several possibility indexes. And a new assessment model, named as fixed weight grey cluster model, is proposed to aggregate indexes’ information.

This paper aims to investigate the linear and nonlinear interactions between the blockchain technology index and the UAE stock market index within the context of the Abu Dhabi and Dubai banking sector.

In this study, linear analysis was performed using the generalized autoregressive conditional heteroscedasticity model (GARCH) (1,1) model, whereas nonlinear analysis was performed using the wavelet coherence model.

Based on the results of the GARCH (1) model, the authors find that the blockchain technology index has a positive significant impact on stock market returns in the Abu Dhabi and Dubai banking sector. In addition, the findings indicate that increasing blockchain integration in the banking industry decreases banks’ stock market volatility and facilitates price stabilization. Additionally, the coherence wavelet analysis reveals that there is a phase relationship between the blockchain technology index and banks’ stock market indices in the banking sector of the UAE. The association was stronger during the global pandemic crisis because they were moving together across different timescales.

With the help of the linear analysis, this study offers a focal point and valuable insights to policymakers, central banks and commercial banks management on how implementing blockchain technology in the banking industry help boost stock market returns, reduce volatility and facilitate price stability. As a result of the nonlinear analysis of the significant long-term degree of co-movement between blockchain technology and banks’ stock markets in UAE, policymakers or the management of banks in UAE should take the growth of the blockchain technology industry into consideration to ensure the continued development of the banking sector. For investors, the findings provide implications for portfolio managers operating in the UAE who are encouraged to take short-term co-movement into account (1–16-week horizons) through both frequency and time when designing their portfolio while keeping long-horizon periods in mind is not recommended.

It is a pioneering study that empirically examines the linear and nonlinear nexus between the blockchain technology index and banks’ stock market returns and price stability.

This study aims to evaluate enterprise technology innovation capability in prefabricated construction (PC) from an input-output perspective, using six integrated enterprises in China as cases.

An evaluation system for enterprise technology innovation capability in PC was constructed, including total input, technology output (TO) and project output. All the evaluation indexes were quantified, and the subject and object indexes weights were determined using the fuzzy cognitive map and information entropy, respectively. The final scores and ranks were evaluated through gray relational analysis (GRA) based on the combined weights.

It was found that enterprise technology innovation capability in PC was low in China, with its unbalanced development in different dimensions and the poorest performance in TO, currently.

This research has developed an evaluation system for technology innovation capability in PC at the enterprise level and scientifically quantified all the indexes, which is a breakthrough over existing studies. The GRA model based on the combined weights proposed in this study can be applied to other comparable fields and regions, with its easy operation.

The purpose of this study is to investigate the correlation between the price return of leading cryptocurrencies, including Bitcoin, Ethereum, Ripple, Litecoin, Monero, Stellar, Peercoin and Dash, and stock return of technology companies' indices that mainly operate on the blockchain platform and provide financial services, including alternative finance, democratized banking, future payments and digital communities.

This study employs a Bayesian asymmetric dynamic conditional correlation multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) (BADCC-MGARCH) model with skewness and heavy tails on daily sample ranging from August 11, 2015, to February 10, 2020, to investigate the dynamic correlation between price return of several cryptocurrencies and stock return of the technology companies' indices that mainly operate on the blockchain platform. Data are collected from multiple sources. For parameter estimation and model comparison, the Markov chain Monte Carlo (MCMC) algorithm is employed. Besides, based on the expected Akaike information criterion (EAIC), Bayesian information criterion (BIC), deviance information criterion (DIC) and weighted Deviance Information Criterion (wDIC), the skewed-multivariate Generalized Error Distribution (mvGED) is selected as an optimal distribution for errors. Finally, some other tests are carried out to check the robustness of the results.

The study results indicate that blockchain-based technology companies' indices' return and price return of cryptocurrencies are positively correlated for most of the sampling period. Besides, the return price of newly invented and more advanced cryptocurrencies with unique characteristics, including Monero, Ripple, Dash, Stellar and Peercoin, positively correlates with the return of stock indices of blockchain-based technology companies for more than 93% of sampling days. The results are also robust to various sensitivity analyses.

The positive correlation between the price return of cryptocurrencies and the return of stock indices of blockchain-based technology companies can be due to the investors' sentiments toward blockchain technology as both cryptocurrencies and these companies are based on blockchain technology. It could also be due to the applicability of cryptocurrencies for these companies, as the price return of more advanced and capable cryptocurrencies with unique features has a positive correlation with the return of stock indices of blockchain-based technology companies for more days compared to the other cryptocurrencies, like Bitcoin, Litecoin and Ethereum, that may be regarded more as speculative assets.

The study results may show the positive role of cryptocurrencies in improving and developing technology companies that mainly operate on the blockchain platform and provide financial services and vice versa, suggesting that managers and regulators should pay more attention to the usefulness of cryptocurrencies and blockchains. This study also has important risk management and diversification implications for investors and companies investing in cryptocurrencies and these companies' stock. Besides, blockchain-based technology companies can add cryptocurrencies to their portfolio as hedgers or diversifiers based on their strategy.

This is the first study analyzing the connection between leading cryptocurrencies and technology companies that mainly operate on the blockchain platform and provide financial services by employing the Bayesian ssymmetric DCC-MGARCH model. The results also have important implications for investors, companies, regulators and researchers for future studies.

The purpose of this paper is to empirically investigate the impact of weather index insurance on agricultural technology adoption in rural China.

A field experiment was conducted with 344 rural households/farmers in Heilongjiang and Jiangsu Provinces, China. DID model was used to evaluate farmers’ technology adoption with and without index insurance.

The results show that weather index insurance has a significant effect on the technology adoption of rural households; there is a regional difference in this effect between Heilongjiang and Jiangsu. Weather index insurance promotes technology adoption of rural households in Heilongjiang, while has limited impact on those in Jiangsu. Weather, planting scale and risk preference are also important factors influencing the technology adoption of rural households.

This research is subject to some limitations. First, the experimental parameters are designed according to the actual situation to simulate reality, but the willingness in the experiment does not mean it will be put into action in reality. Second, due to the diversity of China’s climate, geography and economic environment, rural households are heterogeneous in rural China. Whether the conclusion can be generalized beyond the study area is naturally questionable. A study with more diverse samples is needed to gain a fuller understanding of index insurance’s effects on farmers in China.

This research provides a rigorous empirical analysis on the impact of weather index insurance on farmers’ agricultural technology adoption through a carefully designed field experiment.

The purpose of this paper is to investigate differences between 46 countries, 25 of which are EU members, in their technological communication standards and technological efforts.

Two indexes were developed. The first, labeled Index 1, measures the communication standards of the 46 countries. The second index, labeled Index 2, measures their innovative efforts. Three different dimension variables were employed in each index. Analysis of variance and the coefficient of variation were used to find similarities and differences between and within the groups classified as EU and non‐EU.

Results show overall that there were no statistically significant differences in means when countries were grouped into EU and non‐EU.

The paper uses two indexes composed of indication variables to rate and rank 46 countries for their technological diffusion, considering communication standards and innovative efforts.

The purpose of this paper is to examine the presumed role played by foreign direct investment (FDI) in transferring technology from home country into a host country. This paper uses data from Albanian manufacturing industry; first, to examine whether foreign presence results in technology transfer and, if yes, what type of technology is more prevalent and to what extent? Second, the paper attempts to investigate the purported determinants of technology transfer.

The paper uses two main methodological approaches; first, the technology transfer was determined using an arithmetic index developed using simple arithmetic average. This index is determined using all the industries and taking six key components of technology into consideration. They included: products; production processes; technology and innovation; supplier and customers system; human resource management, training and reporting system; financial management, marketing and organizational structure. Second, assuming a limited dependent relationship between the variables and the technology transfer, a Tobit technique was proposed to examine the significant determinants of technology transfer. Technology transfer was proxied by the technology transfer index developed.

The results clearly demonstrate that FDI plays an important role in technology transfer and that notwithstanding the industrialization of Albania. As per the technology transfer index developed, product-related technology transfer ranked highest followed by the process-related technology. The Tobit results generated indicated that firm age, performance, absorptive capacity, labor mobility, innovation, demonstration effect and systematic support were all key determinants of technology transfer. Surprisingly, size of the firm did not seem to matter.

The results have possible managerial and policy ramifications. First, the government should continue to provide basic infrastructure. Second, the government needs to formulate policies focused on human capital accumulation. Third, policies should be focused on firm learning and innovation in order to build technological and absorptive capabilities. Moreover, there should be increased effort to facilitate and encourage R&D. Fourth, the government should coordinate and support the institutions especially those that play a crucial role in industrial investment promotion. Fifth, the government should encourage systemic interactions among different entities. Sixth, since high competition from foreign firms can crowd out domestic investment, strategic measures to regulate such competition should be enacted.

The novelty in this paper is the broad conceptualization of technology transfer to include not only the direct but also the indirect mode of technology transfer, which often takes place in the form of spillovers. The physical technology transfer, as well as, its actual impact in the economy is examined to ascertain that technology transfer indeed takes place. The analytical framework adopted overlaps international business, technology transfer and technological innovation literature strands to examine the holistic process of technology transfer.

There is a large body of literature on the efficiency and productivity of hospitals. Most studies focus on the effects of environmental pressures on hospital efficiency, such as payment systems (Dismuke & Sena, 1999; Sommersguter-Reichmann, 2000), competition (Rosko, 1999, 2004), Sari, 2003), and property rights (Gruca & Nath, 2001). Other studies pinpoint their attention to economic phenomena, such as economies of scale (Lindrooth, Lo Sasso, & Bazzoli, 2003; Dranove & Lindrooth, 2003), economies of scope (Prior & Sola, 2000; Grosskopf, Margaritis, & Valdmanis, 2001; Li & Rosenman, 2001), chain membership (Menke, 1997), economic behavior (Blank & Merkies, 2004), and expense preference (Rodriguez-Alvarez & Lovell, 2004).

The following classified, annotated list of titles is intended to provide reference librarians with a current checklist of new reference books, and is designed to supplement the RSR review column, “Recent Reference Books,” by Frances Neel Cheney. “Reference Books in Print” includes all additional books received prior to the inclusion deadline established for this issue. Appearance in this column does not preclude a later review in RSR. Publishers are urged to send a copy of all new reference books directly to RSR as soon as published, for immediate listing in “Reference Books in Print.” Reference books with imprints older than two years will not be included (with the exception of current reprints or older books newly acquired for distribution by another publisher). The column shall also occasionally include library science or other library related publications of other than a reference character.

In this section the different types of information source which constitute the management literature are allocated to categories according to their broad function. Within the four categories — tertiary, secondary and primary sources and research in progress, each type of information source will be looked at in terms of the information it supplies and the role it can play in literature searching.