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Recent years have witnessed a significant rise in Indian healthcare establishments (HCEs) which indicate that there is a constant need to improve the healthcare quality services through the adoption and implementation of TQM enablers. The purpose of this paper is to identify such enablers and then propose a ranking model for TQM implementation in Indian HCEs for improved performance.

The study identifies 20 TQM enablers through comprehensive literature survey and expert’s opinion, and classifies them into five main categories. The prominence of these enablers is established using a recently developed novel multi-criteria decision making (MCDM) method, i.e. best-worst method (BWM). The importance of the various main category and sub-category enablers is decided on the basis of their weights which are determined by the BWM. In comparison to other MCDM methods, such as analytical hierarchy process, BWM requires relatively lesser comparison data and also provides consistent comparisons which results in both optimal and reliable weights of the enablers considered in this paper. Further, a sensitivity analysis is also carried out to ensure that the ranking (based on the optimal weights) of the various enablers is reliable and robust.

The results of this study reveal that out of five main category enablers, the “leadership-based enablers (E1)” and the “continuous improvement based enablers (E5)” are the most and the least important enablers, respectively. Similarly, among the 20 sub-category enablers, “quality leadership and role of physicians (E14)” and “performing regular survey of customer satisfaction and quality audit (E52)” are the most and the least dominating sub-category enablers, respectively.

This study does not explore the interrelationship between the various TQM enablers and also does not evaluate performance of the various HCEs based on the weights of the enablers.

The priority of the TQM enablers determined in this paper enables decision makers to understand their influence on successful implementation of the TQM principles and policies in HCEs leading to an overall improvement in the system’s performance.

This study identifies the various TQM enablers in HCEs and categorizes them into five main categories and ranks them using the BWM. The findings of this research are quite useful for management of the HCEs to properly understand the relative importance of these enablers so that managers can formulate an effective and efficient strategy for their easy and smooth implementation which is necessary for continuous improvement.

This paper seeks to explore the applicability and implications of Bourdieu's field‐capital theory for marketing using original research with a typical European society. Bourdieu's field‐capital theory proposes that people acquire economic, social and cultural capital which they deploy in social arenas known as “fields” in order to compete for positions of distinction and status. This exploratory study aims to examine how Bourdieu's theory may explain competitive behavior in fields of interest to marketers.

A total of 61 in‐depth interviews were completed with respondents that were representative of each of 61 geodemographic “types” – clusters that enable marketers to segment an entire population.

The findings suggest that examining human behaviour through the lens of field and capital theory highlights the importance of the competition motive in explaining consumers' behaviour. New “fields” were identified which seem to have assumed primary importance, particularly in middle‐class people's lives.

Viewing consumer behaviour as social competition implies that new segmentation approaches may yield successful marketing outcomes, and opens consumer psychology and behaviour itself to new interpretations.

Very few research papers that apply field‐capital theory to marketing are present in the literature. It is hoped that this work addresses an important area, and one that is particularly prevalent in twenty‐first century consumerism.

The purpose of this study was to evaluate the influence of knowledge management (KM) drivers on perceived KM results in a public higher education institution. A structured theoretical model based on leadership, people, processes, knowledge processes, technology, learning and KM results was developed and tested.

A survey was conducted with the employees of a public higher education institution where an administrative reform was initiated. A valid sample of 257 respondents was obtained. The data were obtained from the application of a structured questionnaire based on the KM drivers and their results. A five-point Likert-type scale was used to measure respondents' answers. The main data analysis technique was structural equation modeling.

The results indicate knowledge processes, leadership and people factors have a positive and significant impact on KM results. On the other hand, organizational processes, technology and learning factors were not significant. However, the service length of servants in the institution influences the perception of knowledge drivers.

Public institutions should be attentive to people with more time of service because they may have difficulties with technological advances, reorganization of processes and adaptation to new ways of sharing knowledge.

This study advances on the analysis of KM results in the public sector and tests the moderation effect of time of service.

The purpose of this paper is to determine best practices of aid agencies for outsourcing logistics to commercial logistics service providers (LSPs) in disaster relief. Moreover, it evaluates the application of the Delphi method for research in humanitarian logistics.

The paper is based on a two-round Delphi study with 31 experts from aid agencies and a complementary full-day focus group with 12 experts from aid agencies and LSPs.

The study revealed 12 best practices for outsourcing logistics in disaster relief and a compilation of more than 100 activities for putting these practices into action. Experts consider a proper balance between efficiency and compliance, a detailed contract and a detailed service request most important. Additionally, the Delphi method was found to be a promising technique for research on humanitarian logistics.

By critically examining the Delphi method, this study establishes the basis for a wider application of the technique in the field of humanitarian logistics. Furthermore, it can help to prioritize future research as the ranking of practices reflects the priorities of practitioners.

The paper provides guidance to practitioners at aid agencies in charge of outsourcing logistics.

This research is one of the first in the field of humanitarian logistics to apply the Delphi method. Moreover, it addresses the lack of literature dealing with approaches for building successful cross-sectoral partnerships.

Special attention will be given in this part to the process of decline, which is to be seen as antipodal to development, and which nowadays is all too often neglected. By “decline” we mean here the decline of a whole society. But this definition is not yet sufficient to provide us with a very clear understanding. The statement that a whole society is in decline remains void of real meaning until we possess some concrete conception of what a “whole society” and the process of “decline” are. Since the meanings of both these terms are problematical, further explanation and closer precision are called for.

Libraries need to develop information processing systems for evaluation, budgeting, planning, and operations. Electronic spreadsheets lend themselves to a variety of applications, but are time‐consuming to create. A model template and macros that can be used in many different types of library data analysis have been developed here. The procedures demonstrated here can build an essential set of tools for meeting fundamental goals of administrative efficiency, effective use of library resources, staff motivation, and rational policy making.

This study aims to investigate the conditional volatility of the Asian stock market concerning Bitcoin and global crude oil price movement.

This study uses the newest Dynamic Conditional Correlation (DCC)-Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to examine the conditional volatility of the stock market for Bitcoin and crude oil prices in the Asian perspective. The sample stock market includes Chinese, Indian, Japanese, Malaysian, Pakistani, Singaporean, South Korean and Turkish stock exchanges, with daily time series data ranging from 4 April 2015−31 July 2023.

The outcome reveals the presence of volatility clustering on the return series of crude oil, Bitcoin and all selected stock exchanges of the current study. Secondly, the outcome of DCC, manifests that there is no short-run volatility spillover from crude oil to the Malaysian, Pakistani and South Korean and Turkish stock markets, whereas Chinese, Indian, Japanese, Singapore stock exchanges show the short-run volatility spillover from crude oil in the short run. On the other hand, in the long run, there is a volatility spillover effect from crude oil to all the stock exchanges. Thirdly, the findings suggest that there is no immediate spillover of volatility from Bitcoin to the stock markets return volatility of China, India, Malaysia, Pakistan, South Korea and Singapore. In contrast, both the Japanese and Turkish stock exchanges exhibit a short-term volatility spillover from Bitcoin. In the long term, a volatility spillover effect from Bitcoin is observed in all stock exchanges except for Malaysia. Lastly, based on the outcome of conditional variance, it can be concluded that there was increase in the return volatility of stock exchanges during the period of the COVID-19 pandemic.

The analysis below does not account for the bias induced due to certain small sample properties of DCC-GARCH model. There exists a huge literature that suggests other methodologies for small sample corrections such as the DCC connectedness approach. On the other hand, decisive corollaries of the conclusions drawn above have been made purely based on a comprehensive investigation of eight Asian stock exchange economies. However, there is scope for inclusive examination by considering other Nordic and Western financial markets with panel data approach to get more robust inferences about the reality.

Most of the empirical analysis in this perspective skewed towards the Nordic and Western countries. In addition to that many empirical investigations examine either the impact of crude oil price movement or Bitcoin performance on the stock market return volatility. However, none of the examinations quests the crude oil and Bitcoin together to unearth their implication on the stock market return volatility in a single study, especially in the Asian context. Hence, current investigation endeavours to examine the ramifications of Bitcoin and crude oil price movement on the stock market return volatility from an Asian perspective, which has significant implications for the investors of the Asian financial market.

This study aims to investigate the effect of CBDC issuance on economic growth rate and inflation rate in Nigeria. We are interested in determining whether the rate of economic growth and inflation changed significantly after the issuance of a non-interest bearing CBDC in Nigeria.

Two-stage least squares regression and granger causality test were used to analyze the data.

Inflation significantly increased in the CBDC period, implying that CBDC issuance did not decrease the rate of inflation in Nigeria. Economic growth rate significantly increased in the CBDC period, implying that CBDC issuance improved economic growth in Nigeria. The financial sector, agricultural sector and manufacturing sector witnessed a much stronger contribution to gross domestic product (GDP) after CBDC issuance. There is one-way granger causality between CBDC issuance and monthly inflation, implying that CBDC issuance causes a significant change in monthly inflation in Nigeria. The implication of the result is that the non-interest bearing eNaira CBDC is not able to solve the twin economic problem of “controlling inflation which stifles economic growth” and “stimulating economic growth which leads to more inflation.” Policy makers should therefore use the eNaira CBDC alongside other monetary policy tools at their disposal to control inflation while stimulating growth in the economy.

There are no empirical studies on the effect of CBDC issuance on economic growth or inflation using real-world data. We add to the monetary economics literature by analyzing the effect of CBDC issuance on economic growth and inflation.

The liberalization initiative commenced in India from 1991 onwards, replacing the four-decade long import substitution policy. The primary objective was to enhance the role of foreign and private investment, in line with the newly embraced outward-oriented growth model. The government had undertaken several policy initiatives since then, especially to strengthen the manufacturing sector which plays an important role in the economic development of any country. The current study evaluates the effects of the liberalization policy in India on industrial outcomes. Recent studies have found that when firm heterogeneity is present in trade models, reforms will lead to a decrease in the number of firms and a rise in their average size (Melitz, 2003). A dataset of 24 manufacturing industries had been used in the current study. We test empirically whether liberalization had led to a rise in the average size of establishments as stated in the literature. We also attempt to analyze the magnitude of trade costs in terms of the impact of reforms on wages and prices. The empirical analysis based on the difference-in-difference (DID) estimation method shows that on average, trade reforms do not lead to an increase in the real wages and average size of establishments. In addition, prices appear to increase in the long run due to liberalization, with potential ramifications.

Financial liberalization is assumed to be the integration of a country's local financial system with international financial markets and institutions. This integration usually requires that governments liberalize the domestic financial sector and the capital account. Financial sectors were liberalized in most of the developing countries in Asia, Africa, and Latin America within the early 1990s. Among these countries, emerging economies are those who promise huge potential for growth but also pose significant political, monetary, and social risks. Brazil and India are often compared among the major emerging economies. Despite these general similarities between them, there are notable differences in various aspects of opening the balance of payments capital account in both countries. In this chapter, we have tried to analyze the long-run as well as short-run relationship between quarterly growth rate of GDP with the stock market, real market, and money market macroeconomic variables in India and Brazil during the period from the first quarter of 1996–1997 to the second quarter of 2018–2019. To estimate the cointegration relationship between growth rate of GDP and its determinants, we employ the bounds testing procedure (modified-ARDL) developed by Pesaran, Shin, and Smith (2001, Journal of Applied Econometrics, 16(3), 289–326). According to our results, stock market plays a positive role in long-term growth in India. Although during the beginning period of the neoliberal reforms, India faced strong domestic political opposition, our study shows that liberalizing the financial market has been fruitful for long-term growth. Our results in case of Brazil show that inflation has a negative and significant impact on long-run growth rate of GDP. The results further show that the share of gross fixed capital formation in GDP in Brazil has a positive and significant long-run relation with the growth rate of GDP. The empirical results further indicate that just like India, liberalization of the financial market and allowing foreign capital inflows have been beneficial for the economy of Brazil in the long run.