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The purpose of this paper is to help China's science and technology (abbr. as S&T) managers and related policy makers to allocate S&T human resources, optimize organizational systems of laboratories, design and plan some grant projects, and manage other S&T‐related work in the field of nanoscience and nanotechnology, by measuring and mapping of technology‐fields correlation, with nanotechnology as an example.

Methodologies such as co‐occurrence analysis, correlation analysis, multidimensional scaling (abbr. as MDS) analysis, dendrogram (tree‐like) analysis, etc. are employed to measure and map technology‐fields correlation.

It is found that the exact relevance degree of any two technology‐fields exists among the top 33 technology‐fields with high frequencies. There are three industrial clusters in Multidimentional Scaling View, that is, nanotechnology used in bio‐medical industry, nanotechnology used in new material industry and nanotechnology used in electronic industry. Hierarchy of any two technology‐fields can be found out in the dendrogram view of the top 33 technology‐fields.

This paper could be of great significance to China's S&T managers and related policy makers, especially in the area of nanotechnology, in selecting and managing generic technology and the findings in this paper can be applied in some other fields of science and technology management in China. Both technology‐fields correlation analysis and MDS and dendrogram view analysis could benefit China's policy makers in managing nanotechnology research and development activities.

This study explores the best strategies for regional economic development to attract highly skilled populations, regardless of whether the region is a multisector or unisector economic hub. It also determines the development variables affecting the success of integrated regional economic hubs to achieve spatial equality, enhance economic productivity and attain environmental sustainability.

In addition to a qualitative analysis, this study employed quantitative techniques using SPSS software. This allowed amplification of the most significant explanatory variables affecting the weaknesses and strengths of economic hubs.

The results highlight approaches that can be used to achieve socio-economic sustainability in regional hubs. These include multisectors or main centralised hubs (smart economic regional capital), which provide new services to regions and act as a unidevelopment sector or as a regional, economic capital.

The study analyses the effect of economic strategies and integration of natural resources and the required core services in regional economic development.

Case studies of successful economic hubs are discussed. The most important services proposed in such hubs promote human development and increase the standard of living.

Integration between the hubs in a region is fundamental to attracting direct investments that can benefit the local population.

The results could help governments, economists and planners implement multisector developmental hubs to achieve sustainable development.

This study aims to validate the English version of a WHO-adapted questionnaire: Zika infection awareness/knowledge questionnaire using a unique dual-approach validation model.

A cross-sectional pilot study of 30 adult respondents in Malaysia completed the self-administered questionnaire on knowledge and perception to Zika infection. Construct validity was assessed by exploratory factor analysis (EFA) of SPSS and Rasch partial credit. Reliability is tested using pKR20 and Cronbach’s alpha.

Knowledge construct was unidimensional, good model fit, easy to endorse and well discriminative. Five-rating Likert scale for perception domain was appropriate. Knowledge domain should be separated into 6 level of difficulties. Perception domain should remain as one construct. Knowledge domain was highly reliability (pKR20 = 0.96), perception domain was fairly reliable (Cronbach’s alpha = 0.641). Respondent's ability to answer knowledge domain and perception domain were separated into 3 and 4 levels.

Small sample size may affect factor analysis.

The questionnaire has good psychometric properties to measure the knowledge and perception of Zika infection among Malaysian community.

The questionnaire helped to gauge knowledge and perception of the general community in Malaysia to aid preparation of health education tool for Zika infection.

This paper validated questionnaire with two biostatistical software programs in bidirectional approach – items difficulty and respondents' ability – is the first field test of WHO questionnaire among general population in Southeast Asia.

Measures of personality and organizational climate were subjected to three different analytical methods that extract patterns from data: Discriminant, Classification and Regression Trees, and neural network classification analysis. Risk, openness, rewards, and neuroticism (rather than conscientiousness) emerged as key variables in differentiating among three similar work groups. Results of the analyses support the central hypothesis of ASA theory of greater variance in personality across compared to within organizations and an interactionist paradigm between person and environment. Implications for ASA theory and for personnel selection are discussed.

Recent studies indicate that exposure to physical punishment is associated with both aggressive behavior and peer victimization at school. The purpose of this paper is to explore the bidirectional relationship between aggressive behavior and peer victimization as outcomes of physical punishment, as well as the role of depressive symptoms.

A sample of 2,424 Finnish upper primary school pupils (1,282 girls, 1,148 boys, mean age=14.2, SD=1.0) completed an online survey during class. Two conditional process models were applied using a macro for SPSS developed by Hayes (2012).

Exposure to physical punishment was found to be associated with both aggressive behavior and peer victimization at school. The effect on victimization was partially mediated by aggressive behavior and depressive symptoms, whereas the effect on aggressive behavior was partially mediated by peer victimization experiences but not by depressive symptoms. The relationship between physical punishment and peer victimization was somewhat stronger for girls than for boys, but this effect was not accounted for by gender differences in depressive symptoms or aggressive behavior.

Few studies to date have addressed the connection between aggressive behavior and peer victimization as outcomes of physical punishment. In addition, the study expands on the concept of “victim personality” by examining the mediating role of depressive symptoms. Methodologically, the study is an example of how the statistical software SPSS can be used for multiple mediation and conditional process analysis as an alternative to SEM analyses.

This paper aims to examine selected similar Greek highway projects to create artificial neural network-based models to predict their actual construction duration based on data available at the bidding stage.

Relevant literature review is presented that highlights similar research approaches. Thirty-seven highway projects, constructed in Greece, with similar type of available data, were examined. Considering each project’s characteristics and the actual construction duration, correlation analysis is implemented, with the aid of SPSS. Correlation analysis identified the most significant project variables toward predicting actual duration. Furthermore, the WEKA application, through its attribute selection function, highlighted the most important subset of variables. The selected variables through correlation analysis and/or WEKA and appropriate combinations of these are used as input neurons for a neural network. Fast Artificial Neural Network (FANN) Tool is used to construct neural network models in an effort to predict projects’ actual duration.

Variables that significantly correlate with actual time at completion include initial cost, initial duration, length, lanes, technical projects, bridges, tunnels, geotechnical projects, embankment, landfill, land requirement (expropriation) and tender offer. Neural networks’ models succeeded in predicting actual completion time with significant accuracy. The optimum neural network model produced a mean squared error with a value of 6.96E-06 and was based on initial cost, initial duration, length, lanes, technical projects, tender offer, embankment, existence of bridges, geotechnical projects and landfills.

The sample size is limited to 37 projects. These are extensive highway projects with similar work packages, constructed in Greece.

The proposed models could early in the planning stage predict the actual project duration.

The originality of the current study focuses both on the methodology applied (combination of Correlation Analysis, WEKA, FannTool) and on the resulting models and their potential application for future projects.

The objective of this study is to identify the optimal product design attributes for a range of chilled probiotic orange juice beverages, and to evaluate the contribution of market‐oriented research methodologies to the development and strategic marketing of innovative functional beverages.

A conjoint‐based survey was administered to 400 purchasers of chilled orange juice in both Dublin and Cork between May and September 2004.

New product development (NPD) opportunities exist for probiotic juice‐based beverages, although functionality should not be relied on solely to leverage a competitive advantage.

The survey sample only included primary purchasers of chilled orange juice, owing to the increased importance of the chilled orange juice category in Ireland. Further research that would incorporate purchasers of ambient orange juice, and end‐users of both chilled and ambient orange juice in Ireland, as well as across European states for a cross‐cultural perspective, would prove beneficial to both manufacturers and retailers.

Advanced market‐oriented research methodologies during the concept stage of the NPD process can assist both food and beverage firms and retailers to develop and market functional foods and beverages that more closely meet consumers' needs and values.

This research can assist beverage manufacturers to optimally design a range of chilled probiotic orange juice beverages targeted at specific market segments, and provide guidance for effective positioning, communication and pricing strategies of innovative functional beverages.

The purpose of this paper is to use relevant financial information of private medium‐sized failed and non‐failed manufacturing firms in the UK, during the period 1994‐2004 to determine whether corporate failure can be predicted by developing a Z‐score model.

Multiple discriminant analysis is used to develop the Z‐score to support the notion that Z‐score is an innovation to overcome the numerous difficulties associated with using single ratios to measure companies' health or risk of failure.

This paper advances the notion that the net profit margin is superior to the gross profit margin in discriminating between failed and non‐failed UK manufacturing companies in terms of its significant contribution to the Z‐score, though the latter exceeds the former slightly using the univariate analysis.

This research contributes to the area of benchmarking by providing a method to more accurately predict corporate failure.

The authors are committed to providing the Chinese government with a foundation for making decisions that will protect black land and ensure long-term agricultural development.

Using the grounded theory approach, this study investigates the influencing factors affecting the quality of black land in Northeast China and proposes a hypothetical model for the mechanism of the influencing factors on the quality of black land in Northeast China.

The factors influencing the quality of black land include not only soil quality, ecological quality and environmental quality, but also economic quality and management quality, and can be classified into five categories. There are complex influence relationships between various factors and black land quality, with soil quality, ecological quality, environmental quality and management quality having a positive influence on economic quality. Soil quality, ecological quality and environmental quality are all improved as a result of good management. Black land quality is influenced positively by environmental quality, economic quality and management quality.

The quality of black land is a major concern in terms of food production and long-term agricultural development. The black land in Northeast China was chosen as the subject of this study, and the research findings have some limitations. The next step will be to expand from studying the black land in Northeast China to the black land worldwide.

In Northeast China, the quality of the five dimensions of black land must be improved in a coordinated and consistent manner.

This literature review explores the definitions and characteristics of cluster analysis, a machine-learning technique that is frequently implemented to identify groupings in big datasets and its applicability to library and information science (LIS) research. This overview is intended for researchers who are interested in expanding their data analysis repertory to include cluster analysis, rather than for existing experts in this area.

A review of LIS articles included in the Library and Information Source (EBSCO) database that employ cluster analysis is performed. An overview of cluster analysis in general (how it works from a statistical standpoint, and how it can be performed by researchers), the most popular cluster analysis techniques and the uses of cluster analysis in LIS is presented.

The number of LIS studies that employ a cluster analytic approach has grown from about 5 per year in the early 2000s to an average of 35 studies per year in the mid- and late-2010s. The journal Scientometrics has the most articles published within LIS that use cluster analysis (102 studies). Scientometrics is the most common subject area to employ a cluster analytic approach (152 studies). The findings of this review indicate that cluster analysis could make LIS research more accessible by providing an innovative and insightful process of knowledge discovery.

This review is the first to present cluster analysis as an accessible data analysis approach, specifically from an LIS perspective.