Robert Nash, Ramya Srinivasan, Bruno Kenway and James Quinn
The purpose of this paper is to assess whether clinicians have an accurate perception of the preventability of their patients’ mortality. Case note review estimates that…
Abstract
Purpose
The purpose of this paper is to assess whether clinicians have an accurate perception of the preventability of their patients’ mortality. Case note review estimates that approximately 5 percent of inpatient deaths are preventable.
Design/methodology/approach
The design involved in the study is a prospective audit of inpatient mortality in a single NHS hospital trust. The case study includes 979 inpatient mortalities. A number of outcome measures were recorded, including a Likert scale of the preventability of death- and NCEPOD-based grading of care quality.
Findings
Clinicians assessed only 1.4 percent of deaths as likely to be preventable. This is significantly lower than previously published values (p<0.0001). Clinicians were also more likely to rate the quality of care as “good,” and less likely to identify areas of substandard clinical or organizational management.
Research limitations/implications
The implications of objective assessment of the preventability of mortality are essential to drive quality improvement in this area.
Practical implications
There is a wide disparity between independent case note review and clinicians assessing the care of their own patients. This may be due to a “knowledge gap” between reviewers and treating clinicians, or an “objectivity gap” meaning clinicians may not recognize preventability of death of patients under their care.
Social implications
This study gives some insight into deficiencies in clinical governance processes.
Originality/value
No similar study has been performed. This has significant implications for the idea of the preventability of mortality.
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This paper investigates the asymmetric connectedness among the Indian stock market, crude oil price, gold price and the USD–INR exchange rate.
Abstract
Purpose
This paper investigates the asymmetric connectedness among the Indian stock market, crude oil price, gold price and the USD–INR exchange rate.
Design/methodology/approach
We construct a nonlinear autoregressive distributed lag model that contains the four aforementioned variables. We further used the pairwise Granger causality test to identify the direction of causality.
Findings
The results verify an asymmetrical long-run co-movement between the Indian stock market index, exchange rate, international crude oil prices and gold prices. In the long run, the performance of the Indian stock market is mainly affected by both positive as well as negative shocks in the INR–USD exchange rate, positive shocks in gold prices and positive shocks in crude oil prices. Further, a feedback mechanism is observed between positive shocks in the INR–USD exchange rate and Indian stock market performance.
Originality/value
The research paper revisited the linkage among the variables using a novel methodology proposed by Shin et al. (2014).
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Despite the well-recognized importance of recycled water, the study of industry-peer pressure on recycled water is relatively new. This study investigates how organizations…
Abstract
Purpose
Despite the well-recognized importance of recycled water, the study of industry-peer pressure on recycled water is relatively new. This study investigates how organizations experience and react to industry-peer pressure to set recycled water targets. Additionally, this study investigates the role of board chairs involved in sustainability committees in contributing to responses to industry-peer pressure.
Design/methodology/approach
Using Eviews 12, this study employed a pooled logistic regression model to analyze data from 1,346 firms on Taiwan and Taipei exchanges (2017–2020).
Findings
The findings revealed that frequency-based imitation drives recycled water target-setting diffusion. However, there is no direct relationship between outcome-based imitation and recycled water target-setting. Notably, outcome-based imitation drives the adoption of recycled water target-setting of firms with board-chair membership in sustainability committees.
Research limitations/implications
This study faces certain data limitations. First, this study primarily focuses on water recycling. Future research could explore other ways to reduce water usage, such as using water-efficient equipment. Second, this study gathered information solely on the presence or absence of a board chairperson on the sustainability committee. Future researchers could explore the impact of the composition of sustainability committee on recycled water target-setting. Lastly, the sample used in this study is restricted to Taiwan's corporations that existed during 2017–2020. Future researchers may consider adopting a longitudinal design in other economies to address this limitation.
Practical implications
The findings of this study offer several guidelines and implications for recycled water target-setting and the composition of sustainability committees. It responds to an urgent call for solutions to water shortages when pressure from governments and nongovernmental organizations is relatively absent. The number of industry peers that have already set recycled water targets is indispensable for motivating firms to set their own recycled water targets. In terms of insufficient water-related regulatory pressure and normative pressure, this study found evidence suggesting that the direct motivation for setting recycled water targets stems from mimetic pressures via frequency-based imitation. The evidence in this study suggests that policymakers should require companies to disclose their peers’ recycled water target information, as doing so serves as an alternative means to achieving SDG 6.3.
Social implications
Recycled water target-setting might be challenging. Water recycling practices may face strong resistance and require substantial additional resources (Zhang and Tang, 2019; Gao et al., 2019; Gu et al., 2023). Therefore, this study suggests that firms should ensure the mindfulness of board members in promoting the welfare of the natural environment when making recycled water target-setting decisions. To reap the second-mover advantage, firms must consider the conditions in which board members can more effectively play their role. Corporations may help their chairpersons in setting recycled water targets by recruiting them as members of sustainability committees. Meanwhile, chairpersons tend to activate accurate mental models when the water conservation performance of pioneering industry peers is strong enough to indicate the potential benefits of adopting recycled water target-setting. Investors’ and stakeholders’ understanding of how the composition of sustainability committees is related to recycled water target-setting may help to identify the potential drivers of firms’ water responsibility. Investors and stakeholders should distinguish firms in terms of the board chair’s membership of their sustainability committee and focus on water-use reduction outcomes in the industry. This study provides insights into circumstances whereby chairpersons help to restore the water ecosystem.
Originality/value
This study explains how frequency-based and outcome-based imitation are two prominent mechanisms underlying the industry-peer pressure concerning recycled water target-setting. Moreover, this study fills literature gaps related to the moderating roles of board-chair membership in sustainability committees concerning industry-peer pressure on recycled water target-setting.
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The purpose of this study is to examine the effects of banking innovations (INNs) on customer experience (EXP), satisfaction (SAT) and loyalty (LOY).
Abstract
Purpose
The purpose of this study is to examine the effects of banking innovations (INNs) on customer experience (EXP), satisfaction (SAT) and loyalty (LOY).
Design/methodology/approach
The author evaluated the data using a structural equation method-artificial neural network (SEM-ANN) method. The author’s results show the presence of relationship between INN, EXP, SAT and LOY. In this study, the node layers of ANNs add an input layer, hidden layers and an output layer. Each “node” acts as an artificial neuron that communicates with others. The ANN model takes the variables from the SEM analysis as input neurons.
Findings
The author observed the significant effects between INN, EXP, SAT and LOY using the normalised importance generated by the multilayer perceptron used in the feed-forward back propagation of the ANN methodology. In this study, the ANN model can predict LOY through service innovation, with a forecast accuracy of 77.6%.
Originality/value
By applying neural network modelling, this research helps us understand how service innovation affects customer behaviour. For the first time, the author examined service innovations' direct and indirect impact on loyalty through EXP and SAT. The author made a significant conceptual contribution by using a non-compensatory model of ANNs to circumvent the limitations of linear models.
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Ramya Tarakad Venkateswaran and Abhoy K. Ojha
Universalizing approaches to knowledge when combined with a dominating cultural discourse is problematic for management research paradigms as “West meets East”. This study aims to…
Abstract
Purpose
Universalizing approaches to knowledge when combined with a dominating cultural discourse is problematic for management research paradigms as “West meets East”. This study aims to examine the case of the rapidly expanding, mainstream strategic management research in and on emerging economies through a critical perspective.
Design/methodology/approach
The authors analyze the strategic management society’s special conferences and workshops on “Emerging India” that aimed to write a fresh chapter of research on India as an emerging economy, using the methodology of critical discourse analysis (CDA). The authors treat this conference as representative of several such conferences and workshops being organized in emerging economies.
Findings
The results detect some troubling undercurrents of privilege and marginalization. The authors find support for a dominating cultural discourse embedded in the rapidly expanding, universalizing strategic management research perspectives in and on emerging economies.
Research limitations/implications
The implications for indigenous knowledge creation is discussed with a concluding call for academic reflexivity through revisiting different philosophies of science in management research and studying the social mechanisms of international knowledge exchange.
Originality/value
The theoretical framework combining the process of universalizing knowledge (Bourdieu and Wacquant, 1999) with a dominating cultural discourse sustained through a system of pressures and constraints (Said, 1978, 1993) is an original contribution. The choice of an emerging economy site is not very common, and the use of CDA on an event like a conference is valuable to research methodology.
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Sarlaksha Ganesh and Mangadu Paramasivam Ganesh
The purpose of this paper was to attempt to understand the effects of gender, masculinity-femininity and social support from three sources (supervisor, co-worker and family) on…
Abstract
Purpose
The purpose of this paper was to attempt to understand the effects of gender, masculinity-femininity and social support from three sources (supervisor, co-worker and family) on the quality of work life (QWL) of an employee. In addition, the paper tried to explore the moderating effects of gender and social support in the relationship between masculinity-femininity and QWL. Relevant background variables such as age, marital status, parental status and sector have been included as control variables in the study.
Design/methodology/approach
Data were collected from a sample of 307 bank employees in India (208 males and 99 females) working in private and public sector banks using the purposive sampling technique. Prior permission was obtained from the relevant authorities. To test the hypotheses, t-tests and hierarchical regression analyses were performed. In addition, the Baron and Kenny (1986) approach was used to test the moderating effects of gender and social support in the relationship between masculinity-femininity and QWL.
Findings
Masculinity-femininity was not found to be significant predictor of QWL, while gender emerged as a significant predictor of QWL. Also, gender moderated the relationship between masculinity-femininity and QWL. All three sources of social support significantly predicted QWL. Results of t-test showed that female employees experienced better QWL than male employees. Furthermore, supervisory category employees and parent employees reported significantly better QWL than non-supervisory and non-parent employees.
Practical implications
The key implication for organisations is that employees with both masculine and feminine tendencies are required to strike a balance between goal orientation and people orientation within the company. Also, employees should understand that their gender as well as their individual orientations towards masculinity or femininity will affect the dynamics of any interaction. Hence, being aware of the tendencies that are typical of their gender role orientations both while dealing with themselves as well as while dealing with customers, colleagues or supervisors would help in improving the quality of their work, as well as their QWL, especially in customer service professions.
Originality/value
This is one of the few studies that have tried to answer the “why” part of gender differences in QWL. In addition, this study contributes to an understanding of the relative importance of different sources of social support in improving an employee's QWL. Finally, this is the first study to understand the relationship between masculinity-femininity, social support, gender and QWL in the Indian context, where the overall cultural orientation towards gender roles is currently changing.
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G.L. Infant Cyril and J.P. Ananth
The bank is termed as an imperative part of the marketing economy. The failure or success of an institution relies on the ability of industries to compute the credit risk. The…
Abstract
Purpose
The bank is termed as an imperative part of the marketing economy. The failure or success of an institution relies on the ability of industries to compute the credit risk. The loan eligibility prediction model utilizes analysis method that adapts past and current information of credit user to make prediction. However, precise loan prediction with risk and assessment analysis is a major challenge in loan eligibility prediction.
Design/methodology/approach
This aim of the research technique is to present a new method, namely Social Border Collie Optimization (SBCO)-based deep neuro fuzzy network for loan eligibility prediction. In this method, box cox transformation is employed on input loan data to create the data apt for further processing. The transformed data utilize the wrapper-based feature selection to choose suitable features to boost the performance of loan eligibility calculation. Once the features are chosen, the naive Bayes (NB) is adapted for feature fusion. In NB training, the classifier builds probability index table with the help of input data features and groups values. Here, the testing of NB classifier is done using posterior probability ratio considering conditional probability of normalization constant with class evidence. Finally, the loan eligibility prediction is achieved by deep neuro fuzzy network, which is trained with designed SBCO. Here, the SBCO is devised by combining the social ski driver (SSD) algorithm and Border Collie Optimization (BCO) to produce the most precise result.
Findings
The analysis is achieved by accuracy, sensitivity and specificity parameter by. The designed method performs with the highest accuracy of 95%, sensitivity and specificity of 95.4 and 97.3%, when compared to the existing methods, such as fuzzy neural network (Fuzzy NN), multiple partial least squares regression model (Multi_PLS), instance-based entropy fuzzy support vector machine (IEFSVM), deep recurrent neural network (Deep RNN), whale social optimization algorithm-based deep RNN (WSOA-based Deep RNN).
Originality/value
This paper devises SBCO-based deep neuro fuzzy network for predicting loan eligibility. Here, the deep neuro fuzzy network is trained with proposed SBCO, which is devised by combining the SSD and BCO to produce most precise result for loan eligibility prediction.