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This paper aims to evaluate innovation capability of companies based on comprehensive methods.

This paper used principal component analysis (PCA), kernel principal component analysis (KPCA) and principal component cluster (PCC) analysis to analyze the listed companies’ innovation capability. On these bases, mean method, Borda method, Copeland method, alienation coefficient method and fuzzy Borda method were used separately for the comprehensive evaluation.

The results show that the comprehensive evaluation can overcome the shortage of the single method and improve the reliability of the innovation ability evaluation. In addition, the method also reveals that the innovation ability of the listed companies is closely related to the innovation investment and their industry and further regional economic development level of each province (city and area).

This paper uses PCA, KPCA and PCC to evaluate and study their innovation ability. On the basis of these, five methods (mean method, Copeland method, Borda method, divorced coefficient method and fuzzy Borda method) are applied respectively to combine the sort results of PCA, KPCA and PCC. The results show that combination methods have better theoretical and practical significance for innovation ability.

The purpose of this paper is to examine the status of the supply reliability of groundwater irrigation, and discuss how it is affected by climate change and tubewell density in rural China.

This study is based on a nine-province village survey and secondary climate data. A Tobit model (or censored regression model) was used to estimate the determinants of supply reliability of groundwater irrigation.

Results show that the supply reliability of groundwater irrigation was 89 percent on average in the past three years. The non-linear relationship in the econometric results revealed that the 30-year annual temperature significantly influenced the supply reliability of groundwater irrigation. When the temperature rises above the turning point (6.30°C), it shifts from a positive to a negative relationship with the supply reliability of groundwater irrigation. The 30-year annual temperature in eight of the nine provinces (i.e. except for Jilin Province) was higher than the turning point. If the temperature increases by 20°C in the future, other factors being constant, the supply reliability of groundwater irrigation will decline by 20 percent. However, if precipitation increases by 10 percent, the supply reliability of groundwater irrigation could improve by 3 percent, while reducing precipitation by 10 percent will lower the supply reliability of groundwater irrigation by 3 percent. Increasing the density of tubewells considerably improves the supply reliability of groundwater irrigation. However, although increasing the density of tubewells may yield enough groundwater for irrigation, this one-sided approach raises sustainability concerns.

Although increasing the density of tubewells may ensure that enough groundwater is available for irrigation, such a conclusion is one sided, and sustainability concerns should be raised in assessing this method of creating supply reliability.

This paper improves the understanding of the impact of climate variables on agriculture irrigation and water supply reliability in the micro scale, and provides a scientific basis for relevant policy making.

The purpose of this paper is to review the agriculture supply chain (ASC) literature along many dimensions which include but are not restricted to scope, objective, wastages, driver, obstacle, outcome, etc.

In total, 203 relevant and scholarly articles of various researchers and practitioners during 2000-2016 were reviewed. The information related to definition, research methodology, global research spread, supply chain strategy, various types of produce, author profile and year of publication of ASC were collected and analysed.

The information related to empirical research and viewpoint of various ASC drivers were captured, studied and analysed in detail. Although inventory policy, demand forecasting and ASC integration were found to be important areas of ASC, they were less focused, studied and researched.

Mainly post-harvest ASC of different agricultural produces were considered whereas products such as dairy, fishery and meat supply chains were not included in the study.

The paper provides an insight into various aspects of ASC in general and one can get a deeper and richer knowledge on it which will help in formulating effective strategies to design of an effective and efficient ASC. It uncovers the research gaps for the new future research paths. This systemic review is strongly felt to fill the gap in the ASC literature.

This study provides valuable insights to managers aiming to increase the effectiveness of their diversification and growth portfolios. The purpose of this paper is to examine the value of utilizing a neural networks (NNs) approach using mergers and acquisition (M&A) data confined in the US technology domain.

Using data from Bloomberg for the period 2000–2016, the results confirm that an NN approach provides more explanation between financial variables in the model than a traditional regression model where the NN approach of this study is then compared with linear classifier, logistic regression. The empirical results show that NN is a promising method of evaluating M&A takeover targets in terms of their predictive accuracy and adaptability.

The findings emphasize the value alternative methodologies provide in high-technology industries in order to achieve the screening and explorative performance objectives, given the technological complexity, market uncertainty and the divergent skill sets required for breakthrough innovations in these sectors.

NN methods do not provide for a fuller analysis of significance for each of the autonomous variables in the model as traditional regression methods do. The generalization breadth of this study is limited within a specific sector (technology) in a specific country (USA) covering a specific period (2000–2016).

Investors value firms before investing in them to identify their true stock price; yet, technology firms pose a great valuation challenge to investors and analysts alike as the latest information technology stock price bubbles, Silicon Valley and as the recent stratospheric rise of financial technology companies have also demonstrated.

Numerous studies have shown that M&As are more often than not destroy value rather than create it. More than 50 percent of all M&As lead to a decline in relative total shareholder return after one year. Hence, effective target identification must be built on the foundation of a credible strategy that identifies the most promising market segments for growth, assesses whether organic or acquisitive growth is the best way forward and defines the commercial and financial hurdles for potential deals.

Technology firm value is directly dependent on growth, consequently most of the value will originate from future customers or products not from current assets that makes it challenging for investors to measure a firm’s beta (risk) where the value of a technology is only known after its commercialization to the market. A differentiated methodological approach used is the use of NNs, machine learning and data mining to predict bankruptcy or takeover targets.

The evaluation of both tourism and tourist resources in China remains problematic. On the macro‐level, only the positive contributions of tourism have been evaluated, ignoring the aspects of disparities between the east coast and the inland area, inbound tourism and domestic tourism, nature‐based and city‐based tourism, positive and negative effects from tourism and so on. On the micro‐ and site‐ specific level, tourist resources characterised by non‐marketable and non‐use values are not properly evaluated, exposing these fragile resources to the plight of exploitation. Commercialisation of tourist resources, including natural environment and ethnic cultures, threatens further development of tourism in China. The limited applicability of the travel cost and the contingent valuation method in measuring the value of recreation sites in China is discussed.