6 research outputs found
THE IMPACT OF BRAND TRUST AND BRAND RELATIONSHIP QUALITY ON BRAND LOYALTY IN THE CONTEXT OF EMERGING MARKET LIKE PAKISTAN
No full textPurpose:
The concept of brand loyalty is of critical importance to the business as it plays a dominant role in providing competitive advantages for the companies and brands in devising their marketing strategies. With the advent of modern digital platforms of consumer interaction with the brands, the focus of marketing is shifting towards relationships from the traditional approach of marketing mix. So, the emphasis is made by researchers on the determinants and approaches of building relationships between consumer and brand that eventually foster brand loyalty.
Methodology:
Sample size for this study was 160 with a respondent response rate of 94.3 %. Survey method through questionnaire was adopted to collect data for this study. Constructs were adopted from relevant and established literature. It had 5 items related to demographic based on nominal scale. Additionally, it had 42 items related to the prime objectives of the study. It was based on 7 points grading scale. After preliminary analysis including normality, validity and reliability, an analysis of multiple regression was carried out to test the desired hypothesis. Findings:
The study found that brand trust was the strongest predictor of consumers’ brand loyalty towards a particular preferred brand, followed by brand relationship quality, perceived quality and brand identification. The study has taken a narrow perspective with limited number of variables. Further studies would incorporate higher number of variables. Additionally, other studies could incorporate the mediating and moderating roles of independent variables and demographic & other factors.
Conclusion:
The firm should focus to enhance the trust related to brand among customers to stabilize the consumers’ brand loyalty
LINKING ABUSIVE SUPERVISION TO TURNOVER INTENTIONS: THE ROLE OF A PSYCHOLOGICAL CONTRACT BREACH AND POTENTIAL ADVANCEMENT
No full textThis paper proposes pathways through which abusive supervisor behavior influences employee outcomes. Specifically, we propose that abusive supervision influence turnover intentions. Further, abusive supervision will indirectly influence employee outcomes through breach of psychological contract and advancement potential. A total of 100 responses were gathered for the analysis of study. The analysis was done through filling up questionnaires from the respondents Statistical Package of Social Sciences (SPSS) was implemented to get the results. The results find that Psychological Contract Breach, Advancement potential mediates and moderates between abusive supervision and turnover intention respectively
ORGANIZATIONAL CONTEXT AND PERFORMANCE EVALUATION PROCESS REACTION: A STUDY OF TELECOM SECTOR EMPLOYEES OF ISLAMABAD
No full textThe present study scrutinizes the relationship among organizational context (job resource adequacy, co-worker relationship and organizational communication) and performance evaluation process reaction through moderation of procedural justice in the telecom sector of Islamabad, Pakistan. The cross-sectional survey is conducted through adaptation of structured questionnaire as a primary source of data collection. A structured questionnaire was floated among 192 employees working in telecom sector. The study expands on applicable research in this region and stretches out the research in the Pakistani context. To test the hypotheses, multivariate analysis, descriptive statistics, correlation, factor analysis and linear regression is used to analyze the impact, Structured Equation Modeling (SEM) is used to identify multiple relationship effects. The structural model was assessed by using Smart PLS 2.0. The study reveals that reactions to performance evaluation process are positively and significant associated with the independent variables, job resource adequacy, organizational communication and co-worker relationship
The impact of knowledge management’s practices on supply chain performance of the dairy sector in Central Punjab: a mediating role of decentralization
No full textIn this study an attempt has been made to solve a problematic
phenomenon regarding how a decentralised environment mediates
the effect on supply chain performance (SCP) – by taking various
dimensions of knowledge management (KM) – specifically in the dairy
sector of Lahore, Pakistan. This study also explores the relationship
between KM practices and SCP in the presence of a general system
theory; the theory claims that every system is has sub-parts, and
every sub-part is surrounded by other sub-parts. Decentralisation
has a mediating role which influences the relationship between KM
practices and SCP in the dairy sector of Pakistan. A self-administered
questionnaire was developed, and data were collected through a
random sampling of 355 supply chain members of different dairy
organisations in central Punjab. The data was analysed by AMOS
software and through structure equation modelling (SEM). The
underlying study reveals that the hypothesis is accepted, that
decentralisation mediates the relationship between KM practices
and SCP at a 1% level of significance; it also reveals that KM practices
(with the exceptions of knowledge creation and knowledge sharing)
have a direct relationship with SCP. Meanwhile, statistical analysis
also indicates that KM practices (with the exception of knowledge
creation) have a significant positive relationship with decentralisation
at the 1% significance level
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No full textA prognostic model for use before elective surgery to estimate the risk of postoperative pulmonary complications (GSU-Pulmonary Score): a development and validation study in three international cohorts
No full textBackground: Pulmonary complications are the most common cause of death after surgery. This study aimed to derive and externally validate a novel prognostic model that can be used before elective surgery to estimate the risk of postoperative pulmonary complications and to support resource allocation and prioritisation during pandemic recovery. Methods: Data from an international, prospective cohort study were used to develop a novel prognostic risk model for pulmonary complications after elective surgery in adult patients (aged ≥18 years) across all operation and disease types. The primary outcome measure was postoperative pulmonary complications at 30 days after surgery, which was a composite of pneumonia, acute respiratory distress syndrome, and unexpected mechanical ventilation. Model development with candidate predictor variables was done in the GlobalSurg-CovidSurg Week dataset (global; October, 2020). Two structured machine learning techniques were explored (XGBoost and the least absolute shrinkage and selection operator [LASSO]), and the model with the best performance (GSU-Pulmonary Score) underwent internal validation using bootstrap resampling. The discrimination and calibration of the score were externally validated in two further prospective cohorts: CovidSurg-Cancer (worldwide; February to August, 2020, during the COVID-19 pandemic) and RECON (UK and Australasia; January to October, 2019, before the COVID-19 pandemic). The model was deployed as an online web application. The GlobalSurg-CovidSurg Week and CovidSurg-Cancer studies were registered with ClinicalTrials.gov, NCT04509986 and NCT04384926. Findings: Prognostic models were developed from 13 candidate predictor variables in data from 86 231 patients (1158 hospitals in 114 countries). External validation included 30 492 patients from CovidSurg-Cancer (726 hospitals in 75 countries) and 6789 from RECON (150 hospitals in three countries). The overall rates of pulmonary complications were 2·0% in derivation data, and 3·9% (CovidSurg-Cancer) and 4·7% (RECON) in the validation datasets. Penalised regression using LASSO had similar discrimination to XGBoost (area under the receiver operating curve [AUROC] 0·786, 95% CI 0·774-0·798 vs 0·785, 0·772-0·797), was more explainable, and required fewer covariables. The final GSU-Pulmonary Score included ten predictor variables and showed good discrimination and calibration upon internal validation (AUROC 0·773, 95% CI 0·751-0·795; Brier score 0·020, calibration in the large [CITL] 0·034, slope 0·954). The model performance was acceptable on external validation in CovidSurg-Cancer (AUROC 0·746, 95% CI 0·733-0·760; Brier score 0·036, CITL 0·109, slope 1·056), but with some miscalibration in RECON data (AUROC 0·716, 95% CI 0·689-0·744; Brier score 0·045, CITL 1·040, slope 1·009). Interpretation: This novel prognostic risk score uses simple predictor variables available at the time of a decision for elective surgery that can accurately stratify patients' risk of postoperative pulmonary complications, including during SARS-CoV-2 outbreaks. It could inform surgical consent, resource allocation, and hospital-level prioritisation as elective surgery is upscaled to address global backlogs. Funding: National Institute for Health Research
