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The purpose of this paper is to present the development of cumulative rainfall deficit (CRD) indices for corn in Shandong Province, China, based on high-resolution weather (county, 1980-2011) and yield data (township, 1989-2010) for five counties in Tai’an prefecture.

A survey with farming households is undertaken to obtain local corn prices and production costs to compute the sum insured. CRD indices are developed for five corn-growth phases. Rainfall is spatially interpolated to derive indices for areas that are outside a 25 km radius from weather stations. To lower basis risk, triggers and exits of the payout functions are statistically determined rather than relying on water requirement levels.

The results show that rainfall deficits in the main corn-growth phases explain yield reductions to a satisfying degree, except for the emergence phase. Correlation coefficients between payouts of the CRD indices and yield reductions reach 0.86-0.96 and underline the performance of the indices with low basis risk. The exception is SA-Xintai (correlation 0.71) where a total rainfall deficit index performs better (0.87). Risk premium rates range from 5.6 percent (Daiyue) to 12.2 percent (SA-Xintai) and adequately reflect the drought risk.

This paper suggests that rainfall deficit indices can be used in the future to complement existing indemnity-based insurance products that do not cover drought for corn in Shandong or for CRD indices to operate as a new insurance product.

This paper aims to expand the emerging literature on COVID-19 and the financial markets by searching for a relationship between the uncertainty of the first phase of the COVID-19 pandemic experienced through social media and the extreme volatility of the Italian stock market.

The authors analyze the relationship between social media and stock market trends during the first phase of the COVID-19 pandemic through the lens of social theory and Baudrillard's simulacra and hyperreality theory. The authors conducted the data analysis in two phases: the emotional and Granger correlation analysis by using the KPI6 software to analyze 3,275,588 tweets for the predominant emotion on each day and observe its relationship with the stock market.

The research results show a significant Granger causality relation between tweets on a particular day and the closing price of the FTSE MIB during the first phase of the COVID-19 epidemic. The results highlight a strong relationship between social media hyperreality and the real world. The study confirms the role of social media in predicting stock market volatility.

The findings have theoretical and practical implications as they reveal the relevance of social media in our society and its relationship with businesses and economies. In an emergency, social media, as an expression of users' feelings and emotions, can generate a state of hyperreality that is strong correlated with reality. Since social media allows users to publish and share messages without any filter and mediation, the hyperreality generated is affected by highly subjective elements.

This research is different from the previous ones on the same topic because unlike previous studies, conducted under normal or simulated scenarios, this study is focused on the first phase of an unpredictable and unforeseen emergency event: the COVID-19 pandemic. This research adopts a multidisciplinary approach and integrates previous studies on the economic and financial effects generated by social media by applying well-known theories to a new and unexplored context. The study reveals the significant impact generated by social media on stock markets during a global pandemic.

The purpose of this paper is to study pressure measurement correlations, as the location of the pressure sensors should enable to capture variation of the drag force depending on the yaw angle and some geometrical modifications.

The present aerodynamical study, performed on a reduced scale mock-up representing a sport utility vehicle, involves both numerical and experimental investigations. Experiments performed in a wind tunnel facility deal with drag and pressure measurements related to the side wind variation. The pressure sensor locations are deduced from wall streamlines computed from large eddy simulation results on the external surfaces of the mock-up.

After validation of the drag coefficient (Cd) values computed with an aerodynamic balance, measurements should only imply pressure tap mounted on the vehicle to perform real driving emission (RDE) tests.

Relation presented in this paper between pressure coefficients measured on a side sensor and the drag coefficient data must enable to better quantify the drag force contribution of a ground vehicle in RDE tests.

The purpose of this paper is to detect abnormal data of complex and sophisticated industrial equipment with sensors quickly and accurately. Due to the rapid development of the Internet of Things, more and more equipment is equipped with sensors, especially more complex and sophisticated industrial equipment is installed with a large number of sensors. A large amount of monitoring data is quickly collected to monitor the operation of the equipment. How to detect abnormal data quickly and accurately has become a challenge.

In this paper, the authors propose an approach called Multiple Group Correlation-based Anomaly Detection (MGCAD), which can detect equipment anomaly quickly and accurately. The single-point anomaly degree of equipment and the correlation of each kind of data sequence are modeled by using multi-group correlation probability model (a probability distribution model which is helpful to the anomaly detection of equipment), and the anomaly detection of equipment is realized.

The simulation data set experiments based on real data show that MGCAD has better performance than existing methods in processing multiple monitoring data sequences.

The MGCAD method can detect abnormal data quickly and accurately, promote the intelligent level of smart articles and ultimately help to project the real world into cyber space in CrowdIntell Network.

In July 1966 John I. Thompson & Company accepted a contract with the Picatinny Arsenal, US Department of the Army, to perform a study aimed at developing ‘Criteria for evaluating the effectiveness of library operations and services’ under the ATLIS Program (Army Technical Library Improvement Studies). The study was divided into three phases aimed at:

The case will test two hypotheses regarding three variables influencing the level of employee satisfaction and organizational citizenship at GAMMA, a manufacturer of plastics. Two hypotheses were developed from a review of the literature and initial results from exploratory research ( H1: low employee satisfaction at GAMMA is a direct result of an autocratic leadership style, low trust environment and weak corporate culture; H2: low employee citizenship is a direct result of low employee satisfaction). Results suggest that although the perception was that employee satisfaction and organizational citizenship were low (from the exploratory research); both quantitative and descriptive data indicated these were not. Moreover, the hypotheses were not conclusively supported quantitatively. High trust was not obtained. Also a specific high leadership style and a specific culture resulting in high employee satisfaction were also questionable. Moreover, it was not observed that a strong correlation existed statistically. H1 is therefore not conclusive quantitatively. H2 does not demonstrate a high level of employee citizenship and employee satisfaction correlation. Despite these results, it is recommended management employ the following action plan: do not change current leadership style; develop an action plan to increase trust starting with increasing accessibility of management to employees; develop an action plan to move from current culture to preferred expressed culture starting by rewarding team activity rather than individual activities; improve employee satisfaction even if the observed level is medium to high.

This paper aims to examine the frequency of co-movements and asymmetric dependencies between bitcoin (BTC), gold, Brent crude oil and the US economic policy uncertainty (EPU) index.

The authors use a wavelet approach and a quantile-on-quantile regression (QQR) method.

The results show a positive interdependence between BTC and commodity price returns at both medium and low frequencies over the sample period. In contrast, the dependence is negative between BTC and EPU index at both medium and low frequencies. Furthermore, the co-movements between markets are more pronounced during crises. The results show that strategic commodities and EPU index have the ability to predict BTC price returns at both medium- and long-terms. The QQR method reveals that higher gold returns tend to predict higher/lower BTC returns when the market is in a bullish/bearish state. Moreover, lower gold returns tend to predict lower (higher) BTC returns when the market is in a bearish (bullish) state (positive (negative) relationship). The lower Brent returns tend to predict higher/lower BTC returns when the market is in a bullish/bearish state. High Brent quantiles tend to predict the lower BTC returns in its extremely bearish states. Finally, higher and lower EPU changes tend to predict lower and higher BTC returns when the market is in a bearish/bullish state (negative relationship).

There is generally a lack of understanding of the linkages between BTC, gold, oil and uncertainty index across multiple frequencies. This is, as far as the authors know, the first attempt to apply both the wavelet approach and a QQR method to examine the multiscale linkages among markets under study. The findings should encourage the relevant policymakers to consider these co-movements which vary over time and in duration when setting up regulations that deem to enhance the market efficiency.

The paper examined the nature of information technology (IT) outsourcing decision making and developed a theoretical framework consisting of five phases of decision making. The phases augmented those of Simon and consisted of intelligence, analysis and planning, strategy selection, action, and evaluation and monitoring. Australia's largest organisations and government agencies were surveyed by questionnaire to establish the importance of tasks and subtasks to be performed when completing each of the five phases. Participants possessed high experiences with IT in general and IT outsourcing in particular. When the importance of phases vis‐à‐vis each other were established, the action phase and evaluation and monitoring phase were found to be more significant than the other phases. For the action phase, which was statistically the most significant phase, the tasks of selecting an IT‐outsourcing vendor and determining a suitable IT‐outsourcing contract were dominant and strongly correlated. Findings from the study should help organisations identify and therefore better manage critical decision‐making activities during IT outsourcing particularly those related to vendors and contracts.

This article aims to investigate the practice adopted by entrepreneurs regarding their use of consultants through the business life cycle.

A representative sample of Danish entrepreneurs was surveyed with response rates of 73 percent and 92 percent. The Danish GEM population survey was merged with own follow‐up surveys and statistically analyzed.

The survey results reveal that involvement of consultants increases as entrepreneurs move forward in the business life cycle. As entrepreneurs gain access to more resources, and as their problems become more fragmented, specialised, discrete and business oriented, the feasibility and benefit of consultant involvement becomes more viable. It was further found that older entrepreneurs have a higher tendency to involve consultants and that entrepreneurs mostly discuss economic and financial issues with consultants to whom they are mostly weakly connected.

Compared to other people in entrepreneurs' social networks, entrepreneurs mostly discuss financial issues with consultants with whom they are mostly relatively weakly connected.

It is suggested that a publicly‐supported advisory system should continue its effort in the early stages where entrepreneurs have only scarce resources. Further it is suggested that this advisory should be even more concentrated towards other issues than financial issues such as marketing, strategy, coordination, and specific opportunity development.

The research extends previous studies by integrating advisory literature and social network literature. The introduction of the business life cycle is also new. The results are based on a very solid research design.

In this chapter, we examine the relationship between the cyclical components of output, the price level and the inflation rate. During the post-war period, there is a negative correlation between output and the price level and a positive correlation between output and the inflation rate. A phase shift in the cyclical component between output and the price level can account for these two facts. The phase shift is consistent with movements in the price level Granger causes movements in output. In addition, we consider time-varying correlations between the two pairs of series. Spectral analysis suggest the price and output have different wavelengths, but the difference is not statistically significant.