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The purpose of this paper is to show a comparative study of different direction-of-arrival (DOA) estimation techniques, namely, multiple signal classification (MUSIC) algorithm, delay-and-sum (DAS) beamforming, support vector regression (SVR), multivariate linear regression (MLR) and multivariate curvilinear regression (MCR).

The relative delay between the microphone signals is the key attribute for the implementation of any of these techniques. The machine-learning models SVR, MLR and MCR have been trained using correlation coefficient as the feature set. However, MUSIC uses noise subspace of the covariance-matrix of the signals recorded with the microphone, whereas DAS uses the constructive and destructive interference of the microphone signals.

Variations in root mean square angular error (RMSAE) values are plotted using different DOA estimation techniques at different signal-to-noise-ratio (SNR) values as 10, 14, 18, 22 and 26dB. The RMSAE curve for DAS seems to be smooth as compared to PR1, PR2 and RR but it shows a relatively higher RMSAE at higher SNR. As compared to (DAS, PR1, PR2 and RR), SVR has the lowest RMSAE such that the graph is more suppressed towards the bottom.

DAS has a smooth curve but has higher RMSAE at higher SNR values. All the techniques show a higher RMSAE at the end-fire, i.e. angles near 90°, but comparatively, MUSIC has the lowest RMSAE near the end-fire, supporting the claim that MUSIC outperforms all other algorithms considered.

Grounded on brand equity theory and theory of patronage behavior, this study aims to investigate the moderating effect of consumer involvement and shopping situations in the relationship between consumer-based retailer equity (CBRE) and retail patronage behavior.

The data is collected through a self-administered survey of 338 shoppers in the three biggest shopping centers in Pakistan. Moreover, the data is analyzed through multi-nominal (multiple) regression and interactions analysis.

Results revealed a significant effect of CBRE on patronage behavior and confirmed shopping purpose as a boundary condition in the CBRE-retail patronage behavior relationship. However, the study surprisingly reported that this relationship is not moderated by consumers’ involvement.

Considering our focus on CBRE-based retail patronage behavior, the authors contribute to extant marketing/retailing literature that also yields ample openings for further research. The study offers valuable implications for retailers, especially for evaluating consumers’ behaviors.

This study assists retail-brand managers in best comprehending the CBRE-based patronage behavior paves the way for managers to increase retail patronage behavior.

Regardless of the growing comprehension of consumer-based brand equity and patronage behavior in marketing, more needs to be acknowledged about the relationship between CBRE/retail patronage behavior and related variables, as thus examined in this research.

Basado en la teoría del valor de marca y la teoría del comportamiento de patrocinio, este estudio investiga el efecto moderador de la implicación del consumidor y las situaciones de compra en la relación entre el valor del minorista basado en el consumidor (CBRE) y el comportamiento de patrocinio minorista.

Los datos se recogen mediante una encuesta autoadministrada a 338 compradores en los tres mayores centros comerciales de Pakistán. Además, los datos se analizan mediante regresión multinominal (múltiple) y análisis de interacciones.

Los resultados revelaron un efecto significativo del CBRE en el comportamiento de patrocinio y confirmaron el propósito de compra como una condición límite en la relación CBRE-comportamiento de patrocinio minorista. Sin embargo, el estudio informó sorprendentemente de que esta relación no está moderada por la implicación de los consumidores.

Teniendo en cuenta que nos centramos en el comportamiento de patrocinio minorista basado en el CBRE, contribuimos a la literatura existente sobre marketing/minoristas que también ofrece amplias posibilidades para futuras investigaciones. El estudio ofrece valiosas implicaciones para los minoristas, especialmente para evaluar los comportamientos de los consumidores.

El presente estudio ayuda a los gestores de marcas minoristas a comprender mejor el comportamiento de patrocinio basado en la CBRE y allana el camino para que los gestores aumenten el comportamiento de patrocinio minorista.

A pesar de la creciente comprensión de la equidad de marca basada en el consumidor y el comportamiento de patrocinio en marketing, es necesario reconocer más sobre la relación entre el comportamiento de patrocinio basado en la CBRE y las variables relacionadas, como se examinó en esta investigación.

本研究以品牌资产理论和顾客行为理论为基础, 探讨了消费者参与和购物情境在基于消费者的零售商资产（CBRE）与零售顾客行为之间关系中的调节作用。

数据是通过对巴基斯坦三大购物中心的 338 名购物者进行自填式调查收集的。此外, 还通过多项式（多元）回归和交互分析对数据进行了分析。

结果表明, CBRE 对顾客光顾行为有显著影响, 并证实购物目的是 CBRE 与零售顾客光顾行为关系的边界条件。然而, 令人惊讶的是, 研究报告称这种关系并没有受到消费者参与度的调节。

考虑到我们对基于 CBRE 的零售顾客行为的关注, 我们为现有的市场营销/零售文献做出了贡献, 同时也为进一步研究提供了广阔的空间。本研究为零售商提供了宝贵的启示, 尤其是在评估消费者行为方面。

本研究有助于零售品牌管理者更好地理解基于 CBRE 的顾客行为, 为管理者提高零售顾客行为铺平了道路。

尽管市场营销中对基于消费者的品牌资产和顾客行为的理解不断加深, 但仍需进一步认识 CBRE/零售顾客行为与相关变量之间的关系, 正如本研究中所探讨的那样。

Amidst the scarcity of resources, it is undisputable that an effective public procurement performance measurement system (PMS) is required particularly in county governments, especially for Kenya to realize its ambitions in devolved governance system. County governments cannot be effectively evaluated on their performance if the long-term, strategic impact of public procurement processes and projects is not captured. Arising from this backdrop, this study aims to determine the predictors of strategic procurement performance metrics (SPPM) adoption in public procurement PMS of county governments.

Anchored on institutional theory and public sector scorecard model, a survey research design was adopted where data were collected through census from 115 respondents working in procurement, finance and stores department of Kakamega county government. Data were collected using questionnaire (75.56% response rate) and key informant interviews, and analyzed by using multiple regression model and ordinal logistic regression models.

Multiple regression model and ordinal logistics regression revealed that national government support negatively and significantly, and regulatory framework positively and significantly affects the adoption of SPPM.

There is need for formal mechanism that will enable the national government in partnership with the council of governors to be proactively involved in developing procurement performance measurement capacity of county governments. This study’s findings also provide suggestions for a working regulatory framework required for the adoption of SPPM by county governments.

This work adds value to the prevailing body of knowledge on public procurement PMS in the public sector.

The purpose of this paper is to review the current literature in the field of tourism demand forecasting.

Published papers in the high quality journals are studied and categorized based their used forecasting method.

There is no forecasting method which can develop the best forecasts for all of the problems. Combined forecasting methods are providing better forecasts in comparison to the traditional forecasting methods.

This paper reviews the available literature from 2007 to 2017. There is not such a review available in the literature.

Investor risk perception is a personalized judgement on the uncertainty of returns pertaining to a financial instrument. This study identifies key psychological and demographic factors that influence risk perception. It also unravels the complex relationship between demographic attributes and investor's risk attitude towards equity investment.

Exploratory factor analysis is used to identify factors that define investor risk perception. Multiple regression is used to assess the relationship between demographic traits and factor groups. Kruskal–Wallis test is used to ascertain whether the factors extracted differ across demographic categories. A risk perception framework based on these findings is developed to provide deeper insight.

There is evidence of the relationship and influence of demographic factors on risk propensity and behavioural bias. From this study, it is apparent that return expectation, time horizon and loss aversion, which define the risk propensity construct, vary significantly based on demographic traits. Familiarity, overconfidence, anchoring and experiential biases which define the behavioural bias construct differ across demographic categories. These factors influence the risk perception of an individual with respect to equity investments.

The reference for the framework of this study is limited as there has been no precedence of similar work in academia.

This paper establishes that information seekers make rational decisions. The paper iterates the need for portfolio managers to develop and align investment strategies after evaluation of investors' risk by including these behavioural factors, this can particularly be advantageous during extreme volatility in markets that concedes the possibility of irrational decision making.

This study highlights that regulators need to acknowledge the investor's affective, cognitive and demographic impact on equity markets and align risk control measures that are conducive to market evolution. It also creates awareness among market participants that psychological factors and behavioural biases can have an impact on investment decisions.

This is the only study that looks at a three-dimensional perspective of the investor risk perception framework. The study presents the relationship between risk propensity, behavioural bias and demographic factors in the backdrop of “information” being the mediating variable. This paper covers five characteristics of risk propensity and eight behavioural biases, such a vast coverage has not been attempted within the academic realm earlier with the aforesaid perspective.

The purpose of this paper is to identify the effect of enterprise risk management (ERM) with firm size, ROA and managerial ownership as control variables on firm value that is proxied by Tobin’s Q.

Population of this research was manufacturing companies listed on the Indonesian Stock Exchange (IDX) in 2010–2013. The used method in this research is multiple linear regression-ordinary least square and hypotheses testing using t-test to test the regression coefficients with level of significance of 5 percent.

The results showed that ERM, ROA and size of the company have a significant positive effect on the firm value. While the managerial ownership has a significant negative effect on the firm value.

The results showed that firm value increases as ERM, ROA and size of the company improves. While the managerial ownership has a significant negative effect on the firm value.

Sustainable manufacturing is one of the most important and most challenging issues in present industrial scenario. With the intention of diminish negative effects associated with cutting fluids, the machining industries are continuously developing technologies and systems for cooling/lubricating of the cutting zone while maintaining machining efficiency. In the present study, three regression based machine learning techniques, namely, polynomial regression (PR), support vector regression (SVR) and Gaussian process regression (GPR) were developed to predict machining force, cutting power and cutting pressure in the turning of AISI 1045. In the development of predictive models, machining parameters of cutting speed, depth of cut and feed rate were considered as control factors. Since cooling/lubricating techniques significantly affects the machining performance, prediction model development of quality characteristics was performed under minimum quantity lubrication (MQL) and high-pressure coolant (HPC) cutting conditions. The prediction accuracy of developed models was evaluated by statistical error analyzing methods. Results of regressions based machine learning techniques were also compared with probably one of the most frequently used machine learning method, namely artificial neural networks (ANN). Finally, a metaheuristic approach based on a neural network algorithm was utilized to perform an efficient multi-objective optimization of process parameters for both cutting environment.

The study aims to examine the factors affecting the customers' choice of Bangladeshi banks during the Covid-19 pandemic and the moderating effects of private and public banks on this association.

This study is based on explanatory research, where significant factors have been explored to evaluate the customers' perception of private and public banks in Bangladesh. Primary data are accumulated through an online survey from customers who have an account in a private or public bank in Bangladesh during the past four months, where 318 (non-probability convenience sampling) are usable, and secondary data are collected from various sources. Descriptive statistics, multiple and hierarchical multiple regressions have been conducted.

The results revealed that customers consider safe and secure websites, infrastructural facilities, technological know-how, service, price, time, payment, administrative and psychological factors in choosing Bangladeshi banks during Covid-19. Moreover, the results show that private and public banks have moderated these associations.

During Covid-19, few studies were conducted on Pakistani, Sri Lankan and Ethiopian banking customers, where different factors are significant; however, this study is unique because all factors are significant for Bangladeshi banking customers. The findings will originate the value with several theoretical implications and managerial guidelines.