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Estimators for derivatives associated with a density function can be useful in identifying its modes and inflection points. In addition, these estimators play an important role in plug-in methods associated with bandwidth selection in nonparametric kernel density estimation. In this paper, we extend the nonparametric class of density estimators proposed by Mynbaev and Martins-Filho (2010) to the estimation of m-order density derivatives. Contrary to some existing derivative estimators, the estimators in our proposed class have a full asymptotic characterization, including uniform consistency and asymptotic normality. An expression for the bandwidth that minimizes an asymptotic approximation for the estimators’ integrated squared error is provided. A Monte Carlo study sheds light on the finite sample performance of our estimators and contrasts it with that of density derivative estimators based on the classical Rosenblatt–Parzen approach.

The domain of study on mediated suffering is ensconced within an Orientalist paradigm which ideologically structures our visuality and gaze. The consignment of suffering through bodies of alterity and the geo-politics of the Global South encodes the coloniality of power as a dominant reading. It then naturalizes the West as the voyeur in its consumption of the abject bodies of the Global South. Creating a binary through this East-West polarization in the oeuvre of suffering as a realm of study, it creates the hegemony of the West as the moral guardian of suffering, imbuing it with the right to accord pity and compassion to the lesser Other. Beyond elongating the Orientalist trajectory which lodged the body politic of the Global South as a sustained ideological site of suffering, it hermeneutically seals the East as irredeemable, ordaining it through the gaze over the Other as a mode of coloniality. In countering this Eurocentric proposition, this chapter contends that this coloniality of gaze needs further rumination and new sensibilities in the study of mediated suffering, particularly following 9/11 and the shifting of the geo-politics of suffering in which the West is dispossessed through its own manufactured ideologies of the ‘War on Terror’ such that it is under constant threat of terrorist attacks and through the movement of the displaced Other into the Global North. Besieged and entrapped through its own pathologies of risks and threats, the West is projected through its own victimhood and the politics of the Anthropocene within which risks are seemingly democratized by environmental degradation as an overarching threat for all of humanity. Despite these shifts in the global politics, the scholarship of suffering is locked into this polarity. The chapter interrogates this innate crisis within this field of scholarship.

We provide straightforward new nonparametric methods for testing conditional independence using local polynomial quantile regression, allowing weakly dependent data. Inspired by Hausman's (1978) specification testing ideas, our methods essentially compare two collections of estimators that converge to the same limits under correct specification (conditional independence) and that diverge under the alternative. To establish the properties of our estimators, we generalize the existing nonparametric quantile literature not only by allowing for dependent heterogeneous data but also by establishing a weak consistency rate for the local Bahadur representation that is uniform in both the conditioning variables and the quantile index. We also show that, despite our nonparametric approach, our tests can detect local alternatives to conditional independence that decay to zero at the parametric rate. Our approach gives the first nonparametric tests for time-series conditional independence that can detect local alternatives at the parametric rate. Monte Carlo simulations suggest that our tests perform well in finite samples. We apply our test to test for a key identifying assumption in the literature on nonparametric, nonseparable models by studying the returns to schooling.

To date, the literature on quantile regression and least absolute deviation regression has assumed either explicitly or implicitly that the conditional quantile regression model is correctly specified. When the model is misspecified, confidence intervals and hypothesis tests based on the conventional covariance matrix are invalid. Although misspecification is a generic phenomenon and correct specification is rare in reality, there has to date been no theory proposed for inference when a conditional quantile model may be misspecified. In this paper, we allow for possible misspecification of a linear conditional quantile regression model. We obtain consistency of the quantile estimator for certain “pseudo-true” parameter values and asymptotic normality of the quantile estimator when the model is misspecified. In this case, the asymptotic covariance matrix has a novel form, not seen in earlier work, and we provide a consistent estimator of the asymptotic covariance matrix. We also propose a quick and simple test for conditional quantile misspecification based on the quantile residuals.

This chapter discusses how the real options theory can be useful for understanding the adoption of human resources management (HRM) practices. The authors review how the real options theory has provided insights into the processes through which firms manage uncertainties involved in the adoption of HRM practices. The authors offer propositions for future HRM research from the real options perspective. The authors contend that analyzing HRM practice adoptions through the lens of real options theory can enhance our understanding of the mechanisms through which firms choose which HRM practices to adopt and how they adjust the timing, scale, and methods of investment in these practices. Specifically, the authors suggest that differences in information relevant to valuation of HRM options are the source of distinct choices of HRM options across firms. Finally, the authors propose advancing knowledge on HRM practice adoptions by using a portfolio of options approach, as well as considering factors like competitors, path dependence, and switching options.

Further understanding of how stakeholder marketing explains firm performance through greater customer satisfaction, innovation, and reputation of a firm.

Grounded in stakeholder theory, the study provides a conceptualization of stakeholder orientation based on cultural values that is distinctive from stakeholder responsiveness and examines the relationship of stakeholder responsiveness to firm performance. The study determines the mediating role of marketing outcomes on the impact of stakeholder responsiveness on firm performance. Multiple regression analysis tests hypotheses using a data set consisting of qualitative data obtained from corporate documents and quantitative data from respected secondary sources.

Our findings provide support for stakeholder marketing creating a strong relationship to organizational outcomes. There exists a positive relationship between stakeholder responsiveness and firm performance through customer satisfaction, innovation, and reputation.

Our definition implies that stakeholder responsiveness is acting in the best interests of the stakeholder as a responsible business. This study shows that stakeholder marketing may not always represent socially responsible marketing. Further research could explore how and why firms may not respond ethically and responsibly to stakeholders.

We further the discussion whether stakeholder marketing equates to sustainability. Marketers can build on expertise of managing customer relationship and generating customer value to develop a stakeholder marketing approach that addresses the economic, social, and environmental concerns of multiple stakeholders.

We further the discussion whether stakeholder marketing equates to sustainability. Marketers can build on expertise of managing customer relationship and generating customer value to develop a stakeholder marketing approach that addresses the economic, social, and environmental concerns of multiple stakeholders.

The aspect of economic contrast seen in developing countries shoots primarily from the structure of loan allocation to the micro, small and medium enterprises (MSME) sector, which is essential for job creation and understanding the role of microfinance institutions (MFIs) in meeting the credit demands of the vulnerable but vital sector of less developed economies. The study demonstrates the impact of MSME protection in terms of both fixed and adjustable factor coefficient settings, creating a model of a small open economy with three sectors: a skill-intensive export sector; a capital-intensive import competing sector; and a labour-intensive import competing and intermediate products producing sector. It analyzes the types of protection that aid in the expansion of credit and the alleviation of capital constraints, which further highlights the insufficiencies of tariff protection for the organized sector and simple credit guarantee policies to provide adequate credit flow and thus continued MSME growth. Finally, it considers the importance of priority sector lending policies in ensuring adequate credit distribution to this sector. The results show that protection helps in enhancing flow of credit and thereby works to relax the capital constraint. However, the tariff protection for organized sector may positively or negatively affect the non-traded unorganized sector.

The objective of this study is to investigate how country risk, different political actions from the government and bureaucratic behavior influence the activities in industry supply chains (SCs) in emerging markets. The main objective of this study is to investigate the influence of these external stakeholders’ elements to the demand-side and supply-side drivers and barriers for improving competitiveness of Ready-Made Garment (RMG) industry in the way of analyzing supply chain. Considering the phenomenon of recent change in the RMG business environment and the competitiveness issues this study uses the principles of stakeholder and resource dependence theory and aims to find out some factors which influence to make an efficient supply chain for improving competitiveness. The RMG industry of Bangladesh is the case application of this study. Following a positivist paradigm, this study adopts a two phase sequential mixed-method research design consisting of qualitative and quantitative approaches. A tentative research model is developed first based on extensive literature review. Qualitative field study is then carried out to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. A survey is carried out with sample of top and middle level executives of different garment companies of Dhaka city in Bangladesh and the collected quantitative data are analyzed by partial least square-based structural equation modeling. The findings support eight hypotheses. From the analysis the external stakeholders’ elements like bureaucratic behavior and country risk have significant influence to the barriers. From the internal stakeholders’ point of view the manufacturers’ and buyers’ drivers have significant influence on the competitiveness. Therefore, stakeholders need to take proper action to reduce the barriers and increase the drivers, as the drivers have positive influence to improve competitiveness.

This study has both theoretical and practical contributions. This study represents an important contribution to the theory by integrating two theoretical perceptions to identify factors of the RMG industry’s SC that affect the competitiveness of the RMG industry. This research study contributes to the understanding of both external and internal stakeholders of national and international perspectives in the RMG (textile and clothing) business. It combines the insights of stakeholder and resource dependence theories along with the concept of the SC in improving effectiveness. In a practical sense, this study certainly contributes to the Bangladeshi RMG industry. In accordance with the desire of the RMG manufacturers, the research has shown that some influential constructs of the RMG industry’s SC affect the competitiveness of the RMG industry. The outcome of the study is useful for various stakeholders of the Bangladeshi RMG industry sector ranging from the government to various private organizations. The applications of this study are extendable through further adaptation in other industries and various geographic contexts.