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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 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 paper aims to deepen the understanding of the relationship between global economic uncertainty and price volatility, specifically focusing on commodity, industrial materials and energy price indices as proxies for global inflation, analyzing data from 1997 to 2020.

The dynamic conditional correlation generalized autoregressive conditional heteroscedasticity model is used to study the dynamic relationship between variables over a while.

The results demonstrated a positive relationship between commodity prices and the global economic policy uncertainty (GEPU). Except for 1999–2000 and 2006–2008, the results of the energy price index model were very similar to those of the commodity price index. A predominant positive relationship is observed focusing on the connection between GEPU and the industrial material price index. The results of the pairwise Granger causality reveal a unidirectional relationship between the GEPU – the Global Commodity Price Index – and the GEPU – the Global Industrial Material Price Index. However, there is bidirectional causality between the GEPU – the Global Energy Price Index. In sum, changes in price indices can be driven by GEPU as a political factor indicating unfavorable economic conditions.

This paper provides a deeper understanding of the role of global uncertainty in the global inflation process. It fills the gap in the literature by empirically investigating the dynamic movements of global uncertainty and the three most important groups of prices.

This study reinvestigates the validity of the Phillips curve in Nigeria for the period 1980–2020 by considering the asymmetric nexus between unemployment and inflation.

The nonlinear autoregressive distributed lag (NARDL) technique was used to decompose the unemployment variable into two components: tight and loosened labour markets.

The empirical outcome shows that unemployment has a significant negative effect on inflation when the labour market is tight and a weakly negative and significant effect on inflation when the labour market is loose. The study confirms an asymmetric Phillips curve in Nigeria since the positive (tight) unemployment rate exerts a greater effect on inflation than the negative (loosened) unemployment rate.

The findings of this study have important implications for implementing monetary policy in Nigeria.

To the best of the authors’ knowledge, this is the first study to investigate the existence of a nonlinear Phillip curve in Nigeria.

The study focuses on examining the impact of the supply shock on the Indian macroeconomic variables during the COVID-19 period.

Time-varying factor augmented vector autoregressive model has been employed to study the asymmetry in transmission of supply shock on Indian economy during pre- and post-COVID-19 times.

The authors find that with supply shock, retail food inflation outpaced in COVID-19 times. Production levels reported by IIP fell to abysmally low levels in the post-COVID-19 times when the economy stalled. The liquidity stimulus provided by the central bank led to the negative response of policy rates to the supply shocks during the COVID-19 times.

The study stands novel in examining the impact of COVID-19 pandemic on Indian economy through the lenses of asymmetric transmission of supply shock during pre- and post-COVID-19 times.

This study aims to examine the symmetric and asymmetric impact of external debt on inflation in Sudan from 1970 to 2020 within a multivariate framework by including money supply and the nominal effective exchange rate as additional inflation determinants.

The authors utilize an Auto Regressive Distributed Lag (ARDL) model to examine the symmetric impact of external debt on inflation, while the asymmetric impact is examined using a Nonlinear ARDL (NARDL) model. The existence of a long-run relationship between inflation and external debt is tested using the bounds-testing approach to cointegration, and a vector error-correction model is estimated to determine the short parameters of equilibrium dynamics.

The linear ARDL model results show that external debt has no statistically significant impact on inflation in the long run. On the contrary, the results of the NARDL model show that positive and negative external debt shocks statistically affect inflation in the long run. The estimated long-run elasticity coefficients of the linear and nonlinear ARDL models reveal that the domestic money supply has a statistically significant positive impact on inflation. In contrast, the nominal effective exchange rate has a statistically significant negative impact on inflation.

The reliance on symmetric analysis may not be sufficient to uncover the existence of a linkage between external debt and inflation. Proper external debt management is crucial to control inflation rates in Sudan.

To date, no empirical study has assessed the external debt-inflation nexus and its potential asymmetry in Sudan, and the current study aims to fill this gap in the literature.

The labor market responds in a differentiated manner during recessions and expansions, and it is of vital importance to know the magnitude asymmetries. The purpose of this paper is to evaluate the effects of the disinflationary monetary policy (2005Q1–2022Q4) through the sacrifice rate measured in terms of unemployment and rate of critical labor conditions (RCLC) with nonlinear auto regressive distributed lag (NLARDL; Shin et al., 2014), which allows to efficiently estimate asymmetric effects in short and long terms in the presence of variables of different integration orders.

The authors estimate an asymmetric accelerationist Phillips curve, augmented with labor precariousness for Mexico (2005Q1–2022Q4) following the NLARDL approach (Shin et al., 2014).

The authors prove that the increase in the unemployment gap has greater disinflationary effects than the RCLC in both the short and the long term; the expansionary phases of the business cycle, which reduce U^Gap, do not have inflationary effects either in the short or in the long run, but improvements in the labor market do, when RCLC is reduced; raising RCLC appears to have been the companies’ main survival strategy since 2015; and these asymmetries can generate a low unemployment trap with high and growing precariousness, with huge dynamic costs for well-being, economic growth, inequality and poverty.

As labor precariousness grows, the implications are several both in the short and long run. In the short run, the most notorious example of the effects on workers has to do with unstable and insecure situations, that disrupt all their life planning options, and health issues. Bohle et al. (2004) found in the Organization for Economic Cooperation and Development countries that casual employees had less desirable and predictable working hours, greater work–life conflict and more associated health complaints than people with permanent jobs.

The approach includes the labor precariousness variable, which describes a new phenomenon in the labor market. Nowadays, workers are facing a new threat since firms are employing a new labor cost reduction strategy in which they do not lay off workers but rather paying them less, working them more hours, or reducing benefits. The asymmetries between the effects of precarity and unemployment can generate a poverty trap in the long run. This problem is, once again, of great relevance in the context of global high inflation.