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1 – 6 of 6Pimtong Tavitiyaman, Tin-Sing Vincent Law, Yuk-Fai Ben Fong and Tommy K.C. Ng
This study aims to explore the influence of health-care service quality on customers’ perceived value, satisfaction, effectiveness and behavioural intention concerning district…
Abstract
Purpose
This study aims to explore the influence of health-care service quality on customers’ perceived value, satisfaction, effectiveness and behavioural intention concerning district health centres (DHCs) in Hong Kong. This research also intends to assess customers’ perception of the subsidy scheme and its influence on the relationships amongst the aforementioned constructs.
Design/methodology/approach
The convenience and snowball sampling approaches were adopted, and the self-administered questionnaire was sent to 309 customers of DHCs.
Findings
Service quality attributes in terms of staffing and procedures positively increased customers’ perceived value and staffing, procedures and operations. Physical facilities positively promoted customers’ satisfaction, consequently improving DHCs’ effectiveness and behavioural intention. However, core treatments and services of DHCs did not impact customers’ perceived value and satisfaction. Furthermore, customers receiving subsidies exhibited a more positive perception than those without subsidies.
Practical implications
Health-care organisations are advised to strategically allocate resources (staffing, facilities and procedures and operations management) to optimise overall performance outcomes. DHC operators could reinforce the core services of DHCs and health-care voucher subsidies to local citizens so as to enhance the effectiveness of DHCs and behavioural intention of customers.
Originality/value
This study integrates the input–process–output approach in measuring the effectiveness of and customers’ behavioural intention towards newly established DHCs.
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Shaohua Yang, Murtaza Hussain, R.M. Ammar Zahid and Umer Sahil Maqsood
In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of…
Abstract
Purpose
In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.
Design/methodology/approach
To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.
Findings
The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.
Originality/value
This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.
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Vincent Kwame Osei-Appiah, Ernest Kissi, Victor Acheamfour Karikari, Prosper Ayeng, Eugene Danquah-Smith and Michael Adesi
Works procurement performance is critical to successful project delivery. However, early supplier involvement (ESI) has been touted in other industries to impact procurement…
Abstract
Purpose
Works procurement performance is critical to successful project delivery. However, early supplier involvement (ESI) has been touted in other industries to impact procurement performance positively. Works procurement has been attracting significant attention from major players due to poor performance characterized by poor performance, budget overruns and incompetence. Hence, the purpose of this study was to assess the impact of ESI on public works procurement performance.
Design/methodology/approach
Based on a thorough review of the literature for a pilot survey, the main questionnaires were administered to 103 public procurement officers. To assess the impact of ESI on public works procurement performance, three constructs that served as factors for implementing ESI and five that measure works procurement performance were validated using partial least square structural equation modelling (PLS-SEM).
Findings
The outcome of this study shows a significant positive impact of ESI on works procurement performance. This included communication, trust and supplier capabilities. The study further showed that even though cost, schedule, quality, health and safety are essential, sustainability measures are also crucial for work procurement.
Research limitations/implications
The results of this study could help firms make better decisions regarding public works procurement by encouraging ESI. This will likely significantly impact the successful project delivery and preservation of sustainability and efficiency objectives.
Originality/value
The application of PLS-SEM analysis in this study provides insights into how ESI can impact the procurement of public works in Ghana.
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Zabih Ghelichi, Monica Gentili and Pitu Mirchandani
This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to…
Abstract
Purpose
This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.
Design/methodology/approach
This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.
Findings
An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.
Originality/value
The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.
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Muhammad Sabbir Rahman, Md Afnan Hossain, Md Rifayat Islam Rushan, Hasliza Hassan and Vishal Talwar
The mental healthcare is experiencing an ever-growing surge in understanding the consumer (e.g., patient) engagement paradox, aiming to vouch for the quality of care. Despite this…
Abstract
Purpose
The mental healthcare is experiencing an ever-growing surge in understanding the consumer (e.g., patient) engagement paradox, aiming to vouch for the quality of care. Despite this surge, scant attention has been given in academia to conceptualize and empirically investigate this particular aspect. Thus, drawing on the Stimulus-Organism-Response (S-O-R) paradigm, the study explores how patients engage with healthcare service providers and how they perceive the quality of the healthcare services.
Design/methodology/approach
Data were collected from 279 respondents, and the derived conceptual model was tested by using Smart PLS 3.2.7 and PROCESS. To complement the findings of partial least squares (PLS)-based structural equation modeling (SEM), the present study also applied fuzzy set qualitative comparative analysis (fsQCA) to identify the necessary and sufficient conditions to explore substitute conjunctive paths that emerge.
Findings
Findings show that patients’ perceived intimacy (PI), cohesion and privacy enhance the quality of mental healthcare service providers. The results also suggest that patients’ PI, cohesion and privacy have indirect effects on the perceived quality of care (PQC) by the service providers through consumer engagement. The fsQCA results derive that the relationship among conditions leading to patients’ perception of the quality of care in regard to mental healthcare service providers is complex and is best reflected as multiple and conjectural causation configurations.
Research limitations/implications
The findings from this research contribute to the advancement of studies on patients’ experiences by empirically examining the unique dynamics of interaction between consumers (patients) and mental healthcare service providers, thereby enriching both the literature on social interactions and the understanding of the consumer–provider relationship.
Practical implications
The results of this study provide practical implications for mental healthcare service providers on how to combine the study variables to enhance the quality of care and satisfy more patients.
Originality/value
A significant research gap has ascertained the inter-relationship between PI, cohesion, privacy, engagement and PQC from the perspective of mental healthcare service providers. This research is one of the primary studies from a managerial and methodological standpoint. The study contributes by combining symmetric and asymmetric statistical tools in service marketing and healthcare research. Furthermore, the application of fsQCA helps to understand the interactions that might not be immediately obvious through traditional symmetric methods.
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William H. Bommer, Sandip Roy, Emil Milevoj and Shailesh Rana
This study integrates previous research on the intention to use Airbnb to determine which antecedents provide a parsimonious explanation.
Abstract
Purpose
This study integrates previous research on the intention to use Airbnb to determine which antecedents provide a parsimonious explanation.
Design/methodology/approach
Meta-analyses based on 61 samples estimate how 8 antecedents are associated with the intention to use Airbnb. Subsequent analyses utilize meta-analyses to estimate a regression model to simultaneously estimate the relationship between the antecedents and the intention to use Airbnb. Relative weight analysis then determined each antecedent’s utility.
Findings
A parsimonious model with only four antecedents (hedonic motivation, price value, effort expectancy and social influence) was nearly as predictive as the full eight-antecedent model. Ten moderating variables were examined, but none were deemed to consistently influence the relationships between the antecedents and the intention to use Airbnb.
Practical implications
Relatively few measures (i.e. four) effectively explain customers’ intentions to use Airbnb. When these measures cannot be readily influenced, alternatives are also presented. Implications for the travel industry are considered and straightforward approaches to increasing users are presented.
Originality/value
This is the first integrative review of customers’ intentions to use Airbnb. We integrate what is currently known about customers’ intentions to use Airbnb and then provide a robust model for Airbnb use intentions that both researchers and practitioners can utilize.
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