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To solve the problem of simulation evaluation with small samples, a fresh approach of grey estimation is presented based on classical statistical theory and grey system theory. The purpose of this paper is to make full use of the difference of data distribution and avoid the marginal data being ignored.

Based upon the grey distribution characteristics of small sample data, the definition about a new concept of grey relational similarity measure comes into being. At the same time, the concept of sample weight is proposed according to the grey relational similarity measure. Based on the new definition of grey weight, the grey point estimation and grey confidence interval are studied. Then the improved Bootstrap resampling is designed by uniform distribution and randomness as an important supplement of the grey estimation. In addition, the accuracy of grey bilateral and unilateral confidence intervals is introduced by using the new grey relational similarity measure approach.

The new small sample evaluation method can realize the effective expansion and enrichment of data and avoid the excessive concentration of data. This method is an organic fusion of grey estimation and improved Bootstrap method. Several examples are used to demonstrate the feasibility and validity of the proposed methods to illustrate the credibility of some simulation data, which has no need to know the probability distribution of small samples.

This research has completed the combination of grey estimation and improved Bootstrap, which makes more reasonable use of the value of different data than the unimproved method.

This paper aims to enhance the reliability of self-validating multifunctional sensors.

An effective fault detection, isolation and data recovery (FDIR) strategy by using kernel principal component analysis (KPCA) coupled with gray bootstrap and fault reconstruction methods.

The proposed FDIR strategy is able to the address fault detection, isolation and data recovery problem of self-validating multifunctional sensors efficiently.

A KPCA-based model which can overcome the limitation of existing linear-based models is used to achieve the fault detection task. By using gray bootstrap method, the position of all faulty sensitive units can be calculated even under the multiple faults situation. A reconstruction-based contribution method is adopted to evaluate the amplitudes of the fault signals, and the fault-free output of the faulty sensitive units can be used to replace the fault output.

This paper aims to examine the effect of financial bootstrapping strategies (FBS) and strategic improvisation (SI) on business performance (BP). The study enriches our understanding of the contributions of bootstrapping and improvisation strategies toward resource-constrained small businesses during real economic downturns and crises. The potential moderating effect of SI on the relationship between FBS and its dimensions and performance were also examined.

Using the convenience snowball sampling technique, data were collected from entrepreneurs in Tripoli, Libya. Structural equation modeling by means of partial least square bootstrapping resampling was used for the hypotheses testing of the 147 useable responses.

Statistically significant positive relationships were found in the direct relationships between bootstrapping and improvisation with performance. However, there was no significant association found between the delaying payment related bootstrapping and the owner-related bootstrapping with performance. The moderating effect of improvisation had a significant relationship between bootstrapping as an aggregate construct and its dimensions and performance.

Due to the cross-sectional nature of this study which used a small sample that was randomly selected, generalization to the entire population of business ventures should be made with caution.

The negative moderation effect of improvisation on FBS-BP association suggests that entrepreneurs need to be careful in balancing the two strategies so that efforts are no wasted.

While business performance has been studied in various organizations, its examination with financial bootstrapping strategies as a predictor and strategic improvisation as a moderator contribute nascent theoretical insights.

By using small reference samples, the calculation method of confidence value and prediction method of confidence interval for multi-input system are investigated. The purpose of this paper is to offer effective assessing methods of confidence value and confidence interval for the simulation models used in establishing guidance and control systems.

In this paper, first, an improved cluster estimation method is proposed to guide the selection of the small reference samples. Then, based on analytic hierarchy process method, the new calculation method of the weight of each reference sample is derived. By using the grey relation analysis method, new calculation methods of the correlation coefficient and confidence value are presented. Moreover, the confidence interval of the sample awaiting assessment is defined. A new prediction method is derived to obtain the confidence interval of the sample awaiting assessment which has no reference sample. Subsequently, by using the prediction method and original small reference samples, Bootstrap resampling method is used to obtain more correlation coefficients for the sample to reduce the probability of abandoning the true.

The grey relational analysis is used in assessing the confidence value and interval prediction. The numerical simulations are presented to demonstrate the effectiveness of the theoretical results.

Based on the selected small reference samples, new calculation methods of the correlation coefficient and confidence value are presented to assess the confidence value of model awaiting assessment. The calculation methods of maximum confidence interval, expected confidence interval and other required confidence intervals are presented, which can be used in assessing the validities of controller and guidance system obtained from the model awaiting assessment.

This study aims to accurately evaluate the influence of various error intervals on the performance of the wiper.

The wiper structural system is decomposed into classical four-link planar for kinematics analysis, and it was modeled respectively by using interval method, universal grey number theory and enumeration approach depending on the nature of uncertainty.

The universal grey number theory is a viable methodology for the accurate analysis of uncertain structural system.

(1) The model of uncertain wiper structural system is established. (2) Universal grey number theory and new parameters are adopted to analyze the presence of uncertain wiper structural system. (3) Comparative analysis of response quantities is obtained by interval method, universal grey number theory and enumeration method.

The purpose of this paper is to introduce error ellipse into the bootstrap method to improve the reliability of small samples and the credibility of the S-N curve.

Based on the bootstrap method and the reliability of the original samples, two error ellipse models are proposed. The error ellipse model reasonably predicts that the discrete law of expanded virtual samples obeys two-dimensional normal distribution.

By comparing parameters obtained by the bootstrap method, improved bootstrap method (normal distribution) and error ellipse methods, it is found that the error ellipse method achieves the expansion of sampling range and shortens the confidence interval, which improves the accuracy of the estimation of parameters with small samples. Through case analysis, it is proved that the tangent error ellipse method is feasible, and the series of S-N curves is reasonable by the tangent error ellipse method.

The error ellipse methods can lay a technical foundation for life prediction of products and have a progressive significance for the quality evaluation of products.

The ability to analyze social action as it unfolds on micro time scales – particularly the 24-hour day – is central to understanding group processes. This chapter describes a new approach to this undertaking, which treats individuals’ involvement in specific activities at specific times as bases for: (1) sequential linkages between activities; as well as (2) connections to others who engage in similar action sequences. This makes it possible to examine the emergence and internal functioning of groups using existing network analysis techniques.

We illustrate this approach with a specific application – a quantitative and visual comparison of the daily activity patterns of employed and unemployed people. We use data from 13,310 24-hour time diaries from the 2010–2013 American Time Use Surveys.

Employed and unemployed people engage in significantly different types of activities and at different times. Beyond this, network analyses reveal that unemployed individuals experience much lower levels of synchrony with each other than do employed individuals and have much less organized action sequences. In short, there is a chronic lack of prevailing norms regarding how unemployed people organize the 24-hour day.

Future research that uses time-stamped data can employ network methods to analyze and visualize how group members sequence and synchronize social action. These methods make it possible to study how the structure of social action shapes group and individual-level outcomes.

Human beings need shelter as the beginning of their existence. Same holds true for people who live in Turkey as it is a cultural and traditional reason to be the host and endeavor to buy a home even if one has to pay the debt for years. Another factor that is important for individuals and even for countries is the inflation rate. In this context, the purpose of this study is to investigate whether the 26 regions of Turkey are affected by the inflationary pressure, specifically in the housing price index (HPI).

For this purpose, data from 2010:01 to 2019:01 and the consumer price index (CPI), as well as HPI have been used. The causal relationship between the variables is analyzed by Konya Causality (2006) test.

The key results suggest that HPI causes inflationary pressures in some regions.

The study has some limitations in terms of data set and scope. These are as follows: although there are many variables affecting housing prices, this study aims to investigate the causal link between inflation and housing prices. In addition, only the CPI and HPI variables were provided on a monthly basis in the 2010-2019 period for 26 regions due to the aim of making regional propositions in the investigation of this relationship. For these reasons, different macroeconomic variables could not be studied.

This study makes the following contribution to the literature. While the majority of existing literature investigates the relationship between housing prices and inflation from an empirical perspective for country, very few studies have been for the sub-regions and also these studies have focused on only some sub-regions. In other words, in the literature review, a study has observed that Turkey has to examine the relationship between the housing price and inflation variables for all sub-regions in particular. To overcome this deficiency in the literature, this study aims to investigate the relationship between housing price and inflation for 26 regions.

Within the fast-moving consumer goods (FMCG) supply chain, one of the problems facing the distribution channel strategy is the presence of the gray market. The article shows two novel antecedents of the participation of official distributors in this gray channel: Negative impact on distributor performance and the relationship with their supplier. Knowledge of this background helps to preserve the strategy outlined for the official distribution channel.

Data were collected from 172 Spanish wholesale distributors and analyzed using PLS-SEM.

The authors found that the damage through negative affectation in the official distributor's performance and the cooperation provided by the manufacturer, have different effects. While affectation is shown to be a powerful antecedent of participation in the gray market, the effect of perceived manufacturer cooperation does not show strong results.

In business practice, these findings lead the manufacturer to keep transactions carried out in the gray market at low levels and provide cooperation to official distributors to guarantee the official channel strategy aimed at efficiency in the distribution of branded goods.

The background of the gray market discussed in the study has not been previously analyzed in the literature. In this way, the authors contribute to the knowledge of such a common problem as the presence of the gray market in the segmentation of distribution channels of high-demand products.

This paper aims to examine information and communications technology (ICT) adoption among small hotel businesses in South Africa, Botswana and Zimbabwe.

This qualitative research is based on seven case studies that fall within the South African and European Union small and medium enterprises (SMEs) definitions. The case studies are constructed on the basis of 60 semi‐structured interviews and supporting secondary data. The authors adopt the Gibbs et al. model which identifies and brings together ICT adoption factors that include government role, environmental attributes, owner/manager attributes, organisational attributes and social networks. Archer's epistemological bootstrapping technique is applied for analysing the data. In addition, Zappala and Gray's stage model is used to gauge the level of ICT uptake reached by each case study. In this way, the authors incorporate an important additional element for examining ICT adoption.

Apart from providing rich insights into the ICT adoption process, the results highlight the individual distinctive behavioural characteristics as well as the stage of ICT adoption reached by each case study. The paper finds that case studies that operated in a stable business environment; with organisational readiness; financial and owner manager support seemed readily engaged in ICT adoption. Social networks played a crucial role, especially among those small businesses with resource constraints.

The findings from seven individual cases in the three South African Development Community (SADC) countries have limited cross‐case and cross‐national comparisons owing to the distinctive organisational characteristics of the SMEs. Furthermore, the selection of case studies from a single sector of small hotel businesses results in data which only reflect the experiences of SMEs in typical urban locations of Johannesburg, Gaborone and Harare. The implications of these limitations mean that further data are needed from other small firm sectors and more SADC countries in order to gain a better understanding of ICT adoption among SMEs in the region.

The findings contribute to the literature on ICT adoption among SMEs in South Africa, Botswana and Zimbabwe. The results bring new insights from small hotel businesses and help to explain ICT adoption, which is relatively under‐researched in these SADC countries.