Employer branding: design and development of a scale

et al. 2023

IJST

Objectives: The purpose of this paper is to examine the role of Green Behaviour (GB) in relationship amid Green Human Resource Management (GHRM) and Employer Branding (EB) in Selected Green Hospitals. Methods: This empirical research examines dual directions of considered variables The GHRM is studied by adopting the 24-item scale with 6 factors (scale reliability varies from 0.804 to 0.814). GB is measured by adopting 6 item scale with 2 factors (reliability ranges from 0.821 to 0.834). To examine perceived EB, 23 item scale with 6 factors (reliability varies from 0.813 to 0.817) were applied. The responses were collected using convenience sampling through the e-mail survey and 384 valid responses (Health Care Professionals in Selected Green Hospitals) were considered. Data Analysis is carried out in dual stages viz., scale validation for all considered variables and Sobel test is carried out to examine the mediating role of GB amid GHRM and EB. Findings: The results of the analysis explored that mediation investigation were satisfied and reinforced, it also noted that after removal of mediating variables (GB), the β weight of the GB is reduced from 0.899 to 0.706 which is significant. Hence, GB acts as a partial mediator in relationship amid GB and EB which is confirmed by sobel test. Novelty: The examination of the GB practices as a mediating role amid GHRM and EB in a single study is a uniqueness of this research.

Section: Mediation Analysissupporting

confidence: 88%

The Green Behaviour Role in Relationship Amid Green Human Resource Management and Employer Branding in Green Hospitals

Tharanatha¹,

Shashidhar²,

et al. 2023

IJST

“…Thus, in a strategic context, digital shopkeepers need to design and implement the effective CRM process to align the DBB considering RF. CRM has a positive impact on RF significantly, which is in line with (14) . The Digital Marketing and CRM have a significant relationship.…”

Section: Mediation Analysissupporting

confidence: 82%

“…Hence, CRM act as a partial mediator in relationship amid DBB and RF. https://www.indjst.org/ The CRM act as a partial mediator amid DBB and RF similar to the findings of (14) which indicates a full mediating role. Thus, in a strategic context, digital shopkeepers need to design and implement the effective CRM process to align the DBB considering RF.…”

Section: Mediation Analysissupporting

confidence: 70%

“…The structured questionnaire consists of four sections, the first section on the demographic information, second section on Digital Buying Behaviour (DBB), third section on Risk Factors (RF) associated with digital buying and fourth section on Customer Relationship Management (CRM). The designed instrument (Likert Scale) was validated with the help of an exploratory factor analysis and confirmed the items by confirmatory factor analysis and the model fitness is verified by measuring fit indexes using AMOS (11) . The digital buying behaviour is studied by adopting the 19-item scale with 6 factors (scale reliability ranges from 0.817 to 0.864).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Mediating Role of Customer Relationship Management between Buying Behavior and Critical Risk Factors via Digital Buying

Sangameshwara¹,

Nagesh²,

et al. 2023

IJST

Purpose: To examine the mediating effect of Customer Relationship Management (CRM) amid Digital Buying Behaviour (DBB) and Risk Factors (RF). Methods: The structured questionnaire was adopted to analyse critical factors of DBB, RF and CRM. The instrument was designed and validated with the help of exploratory factor analysis and confirmed the items by confirmatory factor analysis. The model fitness is verified. The reliability of the scale was tested along with CR. The field testing is done to remove ambiguity. The nativity changes were incorporated to align the current study. The responses were collected using convenience sampling method through the e-mail survey and 410 valid responses (digital consumers) considered. The data were collected during August -November 2022. Quantitative approach is used to examine both directions of the considered variables. First, the direct effect of DBB on RF is examined. Secondly, the direct effect of CRM is studied. Further, mediating effect of CRM in relationship amid DBB and RF is established. Findings: The DBB is significant and directly connected with RF (β = 0.952, p < .001), CRM is significant and positively allied with RF (β = 0.471, p < .001). DBB is significant and positively related to CRM (β = 0.779, p < 0.001), after removal of mediating variable (CRM), β weight of DBB is reduced from 0.952 to 0.703. Sobel test is steered to confirm the significance of the mediation effect of CRM, test statistic (z= 3.09, p <.001). Thus, CRM act as a partial mediator amid DBB and RF. Novelty: The present study integrates DBB, RF and CRM features associated in digital buying in solitary manner unlike sliced approach. The study of CRM role especially in digital buying is a uniqueness of the present research. Further, studying the partial mediating effect of CRM amid DBB and RF itself is a new attempt.

“…The instrument has been designed having 5 drivers with 40 items. The Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were used to validate the instrument using SPSS software and AMOS (10) . The CFA confirms 15 items with 5 drivers.…”

Section: Methodsmentioning

confidence: 99%

Critical Risk Features of Digital Buying: A Quantitative Assessment

Sangameshwara¹,

Nagesh²,

2022

IJST

Objective:The purpose of this study is to analyse Critical Risk Features via Digital Buying and to quantify the Risk Factor Score (RFS) during COVID 19 Pandemic. Methods: Theory of Planned Behaviour (TPB), Perceived Risk Theory (PRT) and Theory of Acceptance Model (TAM) were considered as a base models for selection the of variables. The survey instrument used in the present study was designed and validated using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Three hundred and twenty-two sample responses from Mysore city, Karnataka, India, were obtained through e-mail survey from digital buyers during May 2021-July 2021. The EFA, CFA and Linear regression models were adopted for quantitative assessment of risk features associated with digital buying. Findings: The critical risk features associated with digital buying were identified as; Contractual Risk (CR), Financial Risk (FR), Psychological Risk (PR), Perceived Quality Risk (PQR) and Social Risk (SR). The Risk Factor Score (RFS) for male and female digital buyers were noted as 3.7056 and 3.663 respectively. Thus, risk taking via digital buying by male is higher comparatively. The RFS for the group 31-45 years is 3.697, lesser than age group 15-30 (3.699), while the age group 46-60 RFS is noted as 3.827 which is higher comparatively. Novelty: The attempts were made to identify the risks features associated with digital buying during the pandemic. The present study outcome helps digital shopkeepers to respond positively to the needs of digital buyers during pandemic.