Consistent Quality Of Service Research Articles

Impact of Employee Training Programs on Service Performance in Restaurants

Purpose: The aim of the study was to assess the impact of employee training programs on service performance in restaurants. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study indicated that trained employees are more adept at handling customer complaints and special requests, leading to a more seamless dining experience. Moreover, training fosters a sense of confidence and motivation among staff, reducing turnover rates and promoting a more consistent service quality. Effective training programs also contribute to higher operational standards, ensuring that health, safety, and hygiene regulations are meticulously followed. Consequently, restaurants that invest in comprehensive training programs for their employees often experience increased customer loyalty, positive reviews, and overall better financial performance. Implications to Theory, Practice and Policy: Human capital theory, resource-based view (RBV) and social learning theory may be used to anchor future studies on assessing impact of employee training programs on service performance in restaurants. Restaurants should adopt a culture of continuous training rather than one-time initiatives. Local governments and industry bodies should develop policies that incentivize restaurants to invest in employee training. This could include tax breaks or grants for establishments that demonstrate commitment to staff development.

Hybrid intelligent system for channel allocation and packet transmission in CR-IoT networks

The proliferation of interconnected devices is driving a surge in the demand for wireless spectrum. Meeting the need for wireless channel access for every device, while also ensuring consistent quality of service (QoS), poses significant challenges. This is particularly true for resource-limited heterogeneous devices within Internet of Things (IoT) networks. Cognitive radio (CR) technology addresses the shortcomings of traditional fixed channel allocation policies by enabling unlicensed users to opportunistically access unused spectrum belonging to licensed users. This facilitates timely and reliable transmission of mission-critical data packets. A cognitive radio-enabled IoT (CR-IoT) network is poised to better accommodate the growing demands of diverse applications and services within the smart city framework, spanning areas such as healthcare, agriculture, manufacturing, logistics, transportation, environment, public safety, and pharmaceuticals. To minimize switching delays and ensure energy and spectral efficiency, this study proposes a hybrid intelligent system for efficient channel allocation and packet transmission in CR-IoT networks. Leveraging Support Vector Machine (SVM) and Adaptive Neuro-Fuzzy Inference System (ANFIS), the system dynamically manages spectrum resources to minimize handoffs while upholding QoS. A Java-based simulation integrates system outputs with interference temperature data to accommodate service demands across 2G–4G spectrums. Evaluation reveals SVM’s 98.8% accuracy in detecting spectrum holes and ANFIS’s 90.4% accuracy in channel allocation. These results demonstrate significant potential for enhancing spectrum utilization in various IoT applications.

Concept analysis of health system resilience

BackgroundThere are several definitions of resilience in health systems, many of which share some characteristics, but no agreed-upon framework is universally accepted. Here, we review the concept of resilience, identifying its definitions, attributes, antecedents and consequences, and present the findings of a concept analysis of health system resilience.MethodsWe follow Schwarz-Barcott and Kim’s hybrid model, which consists of three phases: theoretical, fieldwork and final analysis. We identified the concept definitions, attributes, antecedents and consequences of health system resilience and constructed an evidence-informed framework on the basis of the findings of this review. We searched PubMed, PsycINFO, CINAHL Complete, EBSCOhost-Academic Search and Premier databases and downloaded identified titles and abstracts on Covidence. We screened 3357 titles and removed duplicate and ineligible records; two reviewers then screened each title, and disagreements were resolved by discussion with the third reviewer. From the 130 eligible manuscripts, we identified the definitions, attributes, antecedents and consequences using a pre-defined data extraction form.ResultsResilience antecedents are decentralization, available funds, investments and resources, staff environment and motivation, integration and networking and finally, diversification of staff. The attributes are the availability of resources and funds, adaptive capacity, transformative capacity, learning and advocacy and progressive leadership. The consequences of health system resilience are improved health system performance, a balanced governance structure, improved expenditure and financial management of health and maintenance of health services that support universal health coverage (UHC) throughout crises.ConclusionA resilient health system maintains quality healthcare through times of crisis. During the coronavirus disease 2019 (COVID-19) epidemic, several seemingly robust health systems were strained under the increased demand, and services were disrupted. As such, elements of resilience should be integrated into the functions of a health system to ensure standardized and consistent service quality and delivery. We offer a systematic, evidence-informed method for identifying the attributes of health system resilience, intending to eventually be used to develop a measuring tool to evaluate a country’s health system resilience performance.

Determination of Customer Loyalty in the International Cargo Company

The purpose of this research is to understand the Factors Influencing Customer Loyalty: This study probably aims to investigate the factors that most influence customer loyalty in the freight forwarding sector. This can include aspects such as the relationship between the company and customers, service quality, customer satisfaction, price, and other relevant factors and measure the level of customer loyalty to freight forwarding companies in East Jakarta. This can be done through surveys, interviews, or analysis of historical data. The study used quantitative methods, which used random sampling for respondents to find data, the population is a user of freight forwarders in the East Jakarta Area by disseminating online and directly. Data analysis was processed using SEM PLS series 4 to find a definite answer from the results of the questionnaire distribution that lasted for two months. In this study, only the relationship between relationship and customer loyalty showed statistical significance, but the direction of the relationship did not match initial predictions. The relationship between Customer Satisfaction and Customer Loyalty has not been shown to be statistically significant. Recommendations in the freight forwarding sector, increasing customer loyalty can be achieved through improved customer relationships, consistent service quality, and ensuring customer satisfaction. By focusing on these aspects, companies can strengthen long-term relationships with customers and improve their performance in the freight forwarding industry

Enhancing QoS Performance for Cell Edge Users Through Adaptive Modulation and Coding in IEEE 802.11ac WLANs

Wireless communication networks, such as IEEE 802.11ac Wireless Local Area Networks (WLANs), often encounter challenges in providing consistent Quality of Service (QoS) to users situated at the cell edge. The inherent variations in channel conditions, particularly lower signal-to-noise ratios (SNRs) in these regions, lead to compromised data rates and reliability, resulting in significant degradation of throughput. This study presents an innovative solution in the form of an Adaptive Modulation and Coding Scheme (AMCS) algorithm tailored to enhance QoS performance for cell edge users. The primary objective of the AMCS algorithm is to optimize QoS by dynamically adjusting the transmission data rate based on the observed channel conditions, quantified using SNR as a channel state indicator. Conventional approaches might unilaterally select the lowest data rate in challenging conditions, prioritizing reliability at the expense of throughput. However, the proposed AMCS algorithm takes a distinct approach by intelligently determining the Modulation and Coding Scheme (MCS) that offers an optimal balance between throughput and reliability for the given SNR level. To achieve this, the algorithm utilizes real-time SNR measurements to select an MCS that ensures a stable connection while also maintaining an acceptable data rate. By adapting the MCS based on the current SNR, the algorithm aims to mitigate the adverse effects of poor channel conditions experienced by cell edge users. The innovation of the AMCS algorithm lies in its ability to make dynamic adjustments, allowing users to experience improved data rates without compromising connection stability. Through extensive simulations and evaluations, the proposed AMCS algorithm showcases its efficacy in enhancing QoS performance at the cell edge. The algorithm's adaptive approach successfully achieves higher data rates and improved reliability by selecting appropriate MCS configurations tailored to the observed SNR levels. This innovative technique provides a promising solution to the challenge of striking the right balance between throughput and reliability in wireless communication networks, ultimately leading to an improved user experience for those at the network's periphery.

CSIMH: Design of an Efficient Security-Aware Customized Sidechaining Model via Iterative Meta-Heuristics

Blockchains are a secure alternative for long-length data storage & security deployments. Though blockchains are unbounded, their quality of service (QoS) performance reduces after adding a certain number of blocks. Thus, sidechains have become essential for making the system decentralized, secure, and effective for use thereby improving their scalability & QoS performance. Sidechains reduce data storage and extraction delays. However, all sidechains of a single blockchain are the same in size, capacity, and security. This limits their application to real-world use cases that require dynamic security. To overcome this limitation, the authors propose a meta-heuristic approach to design a system that produces customized sidechains based on the quantity and quality of data stored on the chain. The model uses a machine-learning approach to find the best possible sidechain configuration for different data types. It makes the system fast and scalable and improves storage & memory efficiency. The proposed model is tested on multiple data sets and compared with various state-of-art sidechain deployments. An improvement of 18% in terms of mining speed, 27% in terms of energy efficiency, 10% with regards to throughput, and 8% concerning packet delivery ratio is observed. The model is tested under various attacks and faulty nodes to validate its security performance. A consistent QoS performance is observed for the proposed model under these attack types, thereby validating its resiliency for different attacks. This enhancement in performance makes the proposed model eligible for deployment in high-speed, low-energy, and high-security applications like IoT, mobile ad-hoc networks, and sensor networks.

MADDPG-empowered slice reconfiguration approach for 5G multi-tier system

With the advancement of fifth-generation (5G) communication technology, plenty of vertical applications have emerged. These applications usually center on highly different quality of service (QoS) requirements, posing challenges for the supporting communication network. To address these challenges, network slicing has been proposed to partition the underlying network into multiple tailored logical networks, called as network slices. Each slice corresponds to a specific application. However, fluctuations in user activities for applications may lead to workload variation across corresponding slices, which compromising the consistent QoS provisioning. In this context, slice reconfiguration becomes imperative to ensure satisfactory user experiences. In this work, we introduce the multi-agent deep reinforcement learning method to tackle the slice reconfiguration problem and propose the multi-agent deep deterministic policy gradient-empowered slice reconfiguration (MADDPG-SR) algorithm. In MADDPG-SR, each network function is abstracted as an agent that learns to optimize its own migration in the multi-layer network to minimize the preference-weighted processing resource cost while adhering QoS and resource constraints. The proposed method is compared with four other benchmarks, and the comparison results demonstrate that MADDPG-SR can significantly reduce both the preference-weighted resource cost, and the running time for acquiring slice reconfiguration decisions while ensuring the QoS performance of slices.

OPTIMIZATION OF CUSTOMER LOYALTY AT COFFEE SHOPS IN SURABAYA

The main key to winning in competition for companies is to provide value and satisfaction to consumers through the delivery of quality products and services. This can be achieved by providing products and services that are more satisfying than those of competitors, resulting in satisfied consumers, consistent service quality, and consumer loyalty. This research aims to analyze sales optimization strategies by increasing service quality and customer loyalty of coffee shops in Surabaya, using a causal research design with quantitative methods. Data was collected through questionnaires distributed to people in Surabaya who had visited and bought from coffee shops. The data analysis technique used was Structural Equation Modeling analysis with Partial Least Square. Results showed that store location and store image had a significant positive effect on service quality, and store location, store image, and service quality had a significant positive effect on customer loyalty. The recommended strategies include improving store location by making signs that are easy to reach, and improving store image through endorsements and other promotions to attract customer attention.

Hospital energy demand forecasting for prioritisation during periods of constrained supply

Purpose: Sustaining healthcare operations without adequate energy capacity creates significant challenges, especially during periods of constrained energy supply. This research develops a clinical and non-clinical activity-based hospital energy model for electrical load prioritization during periods of constrained energy supply.Design/methodology/approach: Discrete event modelling is adopted for development of the hospital energy model (HEM). The basis of the HEM is business process mapping of the hospitals clinical and non-clinical activities. The model prioritizes the electrical load demand as Priority 1, 2 and 3; with Priority 1 activities essential to the survival of patients, Priority 2 activities are critical activities that are required after one to four hours, and Priority 3 activities can run for several hours without electricity.Findings: The model was applied to a small, medium, and large hospital. The results demonstrate that Priority 2 activities have the highest energy demand, followed by Priority 1 and Priority 3 activities, respectively for all hospital sizes. For the medium and large hospitals, the top three contributors to energy demand are lighting, HVAC, and patient services. For the small hospital, it is patient services, lighting, and HVAC, respectively.Research limitations/implications: The model is specific to hospitals but can be modified for other healthcare facilities.Practical implications: The resolution of the electrical energy demand down to the business activity level, enables hospitals to evaluate current practices for optimization. It facilitates multiple energy supply scenarios, enabling hospital management to conduct feasibility studies based on available power supply optionsSocial implications: Improved planning of capital expenditure and operational budgets and during constrained energy supply. This reduces risk to hospitals and ensures consistent quality of service. Originality/value: Current hospital energy models are limited, especially for operations management under constrained energy supply. A simple to use model is proposed to assist in planning of activities based on available supply.

Effects of Online Distribution for Marketing of Budget Accommodation Segment in Kolkata, India

The budget accommodation segment has witnessed a significant shift with the rise of online distribution channels. While these platforms offer vast opportunities, they also bring forth a set of substantial challenges. This paper discusses the primary challenges faced by budget accommodation providers in the online distribution sphere and proposes solutions to address them. The key challenges include market saturation and competition, revenue management complexity, and the critical role of online reputation and reviews. The intense competition among numerous online travel agencies and accommodation platforms has made it challenging for budget accommodations to differentiate themselves and maintain profitability. Revenue management complexities arise from dynamic pricing and rate parity issues, which can lead to revenue leakage. Additionally, online reviews and reputation management are critical, as negative feedback can severely impact bookings and revenue. To address these challenges, budget accommodation providers can focus on differentiation through personalized experiences and value-added services. They can also utilize revenue management tools and data analytics to optimize pricing strategies and ensure rate parity. Active engagement with guests and prompt response to reviews, along with maintaining consistent service quality, can help manage online reputation effectively. In summary, while online distribution presents challenges for budget accommodations, innovative strategies and technology adoption can empower providers to thrive in a competitive landscape, ensuring sustainable growth and guest satisfaction.

Ambidextrous Leadership and Service Recovery Performance Under B2B Selling Context: An Examination Through Service Innovation Capability

In order to build consistent service quality, managers should encourage salespeople to deal with customers and improve service errors for their overall benefit. Our study seeks to understand the role of ambidextrous leadership in promoting service innovation capability and service recovery performance (SRP) under a business-to-business (B2B) selling environment. The study evaluates 286 responses from pharmaceutical salespeople by using structural equation modeling. The results report a significant association between opening leader behavior and service recovery performance, whereas closing leader behavior is not significantly related to service recovery performance. In addition, opening and closing leader behaviors have a positive and significant impact on service innovation capability. Consequently, service innovation capability is positively and significantly related to value-based selling, adaptive selling, and service recovery performance. Finally, our results contribute to the previous research that has explored the significant mediation effect of service innovation capability between opening leader behavior and service recovery performance linkage.

A business class for autonomous mobility-on-demand: Modeling service quality contracts in dynamic ridesharing systems

With the popularization of transportation network companies (TNCs) (e.g., Uber, Lyft) and the rise of autonomous vehicles (AVs), even major car manufacturers are increasingly considering themselves as autonomous mobility-on-demand (AMoD) providers rather than individual vehicle sellers. However, matching the convenience of owning a vehicle requires providing consistent service quality, taking into account individual expectations. Typically, different classes of users have different service quality (SQ) expectations in terms of responsiveness, reliability, and privacy. Nonetheless, AMoD systems presented in the literature do not enable active control of service quality in the short term, especially in light of unusual demand patterns, sometimes allowing extensive delays and user rejections. This study proposes a method to control the daily operations of an AMoD system that uses the SQ expectations of heterogeneous user classes to dynamically distribute service quality among riders. Additionally, we consider an elastic vehicle supply, that is, privately-owned freelance AVs (FAVs) can be hired on short notice to help providers meeting user service-level expectations. We formalize the problem as the dial-a-ride problem with service quality contracts (DARP-SQC) and propose a multi-objective matheuristic to address real-world requests from Manhattan, New York City. Applying the proposed service-level constraints, we improve user satisfaction (in terms of reached service-level expectations) by 53% on average compared to conventional ridesharing systems, even without hiring additional vehicles. By deploying service-quality-oriented on-demand hiring, our hierarchical optimization approach allows providers to adequately cater to each segment of the customer base without necessarily owning large fleets.

Scheduling Design and Performance Analysis of Carrier Aggregation in Satellite Communication Systems

Carrier Aggregation is one of the vital approaches to achieve several orders of magnitude increase in peak data rates. While carrier aggregation benefits have been extensively studied in cellular networks, its application to satellite systems has not been thoroughly explored yet. Carrier aggregation can offer an enhanced and more consistent quality of service for users throughout the satellite coverage via combining multiple carriers, utilizing the unused capacity at other carriers, and enabling effective interference management. Furthermore, carrier aggregation can be a prominent solution to address the issue of the spatially heterogeneous satellite traffic demand. This paper investigates introducing carrier aggregation to satellite systems from a link layer perspective. Deployment of carrier aggregation in satellite systems with the combination of multiple carriers that have different characteristics requires effective scheduling schemes for reliable communications. To this end, a novel load balancing scheduling algorithm has been proposed to distribute data packets across the aggregated carriers based on channel capacities and to utilize spectrum efficiently. Moreover, in order to ensure that the received data packets are delivered without perturbing the original transmission order, a perceptive scheduling algorithm has been developed that takes into consideration channel properties along with the instantaneous available resources at the aggregated carriers. The proposed modifications have been carefully designed to make carrier aggregation transparent above the medium access control (MAC) layer. Additionally, the complexity analysis of the proposed algorithms has been conducted in terms of the computational loads. Simulation results are provided to validate our analysis, demonstrate the design tradeoffs, and to highlight the potentials of carrier aggregation applied to satellite communication systems.

Impacts of Job Standardisation on Restaurant Frontline Employees: Mediating Effect of Emotional Labour

Managers of food service operations standardise various aspects of operations to sustain consistent service quality. Frontline employees in these operations are expected to carry out tasks as per standards. Standards demand that frontline employees regulate their behaviours and emotions to complete their duties. Therefore, referring to the organisational role theory and the emotion regulation theory as the directing basis, this study examined the impact of job standardisation on emotional labour, as well as the effect of emotional labour on emotional exhaustion and job satisfaction of frontline employees in the hospitality sector. This study also examined the mediating effect of emotional labour on the relation between job standardisation, on one hand, and emotional exhaustion and job satisfaction on the other hand. The data collection was carried out in food service operations in Lebanon. Structural equation modelling (SEM) was used to assess the relations. The results showed that job standardisation negatively affected emotional labour and that emotional labour had a positive effect on emotional exhaustion and a negative effect on job satisfaction. Furthermore, emotional labour mediated the relation between job standardisation and emotional exhaustion and job satisfaction. Practical and theoretical implications and directions for future research are also provided.

Preserving Continuity of Behavioral Health Clinical Care to Patients Using Mobile Devices

The current model for treating behavioral health patients requires that providers and patients be in the same location for appointments. However, deploying warfighters present a challenge to this current model. Recent advances in technology make telehealth or virtual visits a viable option to replace the current model. This project leveraged mobile technology to see if performing tele-behavioral health visits presented a viable option to the current in-person model for future deployed warfighters. At the time of this publication, the authors note the current pandemic lends all the more urgency to the need for enhancing our video communication platforms for remote monitoring with the Military Health System. The research team assessed existing Internet protocol-based desktop teleconferencing solutions, generically known as a Web Real-Time Communications (WebRTC) system, for establishing a secure connection to a Service Members personal mobile device outside of the Department of Defense (DoD) network. Of the five existing WebRTC systems evaluated, only the backbone component to the existing Defense Information Systems Agency Global Video Services (DISA GVS) known as Vidyo, was suitable to meet DoD security requirements and still connect with both major operating systems (OS) on mobile devices. An existing DoD program of record mobile application, mCare, was integrated with Vidyo desktop technologies to form what the research team called "Mobile Connect." Deployment of the Mobile Connect product yielded distinct differences and high levels or variability between the .osd.mil and the army.mil network connections over time. These network differences impacted quality of service solution where Mobile Connect could not be used to provide care between the .mil and patient's personal mobile devices from a osd.mil domain connection. The current DoD WebRTC systems offer potential solutions but presently cannot connect with personal mobile devices in their current configurations. Additionally, any WebRTC system used by the DoD for future connections to personal mobile device must leverage commercial Single Socket Layer certificates (e.g., not DoD issued), or the communications with the mobile device will fail as a result of an authentication error. It is technically feasible to provide desktop Video Tele-Conference capabilities from a .mil computer to a personal mobile device without compromising DoD security and information assurance requirements using future WebRTC systems. Approved ports, protocols, and system settings must be configured to accept both inbound and outbound, encrypted traffic to/from personal mobile devices to maintain consistent quality of service with all DoD networks. Of the current DoD WebRTC options, working with the DISA GVS Program Manager to expand services to support commercial mobile devices has the highest probability of future success.

Quality of Service- and Fairness-Aware Resource Allocation Techniques for IEEE802.11ac WLAN

Increased demand for high-quality multimedia applications over IEEE802.11 networks has further motivated service providers to improve the QoS (quality of service) for all types of network services. IEEE802.11ac is one of the advanced WLAN standards that provides wideband transmission channels and higher data rates, which are vital to support very high-throughput services. However, due to the use of the CSMA/CA-based random access packet transmission technique, the QoS and service fairness criteria cannot always be maintained, particularly for variable bit rate services. This paper proposes new packet scheduling algorithms to support consistently high QoS and intra-service fairness for high data rate video streams. We name the proposed algorithms FRA - TXOP (Flow Rate Adaptive Transmission Opportunity) and EAS (Enhanced Access Scheduler). These algorithms offer appropriate QoS and fairness to video services in a CSMA/CA network. The FRA - TXOP algorithm allocates the transmission resources according to the channel congestion levels experienced by video flows to improve and maintain consistent QoS values. At the same time, the EAS algorithm offers service fairness among the video streams by appropriately scheduling them on the downlink channel. The EAS algorithm is implemented on top of the FRA - TXOP algorithm to achieve high QoS and service fairness among video streams. An NS-3 simulation model is developed to evaluate the performance of the proposed algorithms. The performance analysis shows that the proposed algorithms enhance the video flow QoS in terms of throughput and packet delay as well as improve the fairness among the video flows compared to other TXOP algorithms.

A Node-Regulated Deflection Routing Framework for Contention Minimization

Optical Burst Switching (OBS) paradigm coupled with Dense Wavelength Division Multiplexing (DWDM) has become a practical candidate solution for the next-generation optical backbone networks. In its practical deployment only the edge nodes are provisioned with buffering capabilities, whereas all interior (core) nodes remain buffer-less. In that way the implementation becomes quite simple as well as cost effective as there will be no need for optical buffers in the interior. However, the buffer-less nature of the interior nodes makes such networks prone to data burst contention occurrences that lead to a degradation in overall network performance as a result of sporadic heavy burst losses. Such drawbacks can be partly countered by appropriately dimensioning available network resources and reactively by way of deflecting excess as well as contending data bursts to available least-cost alternate paths. However, the deflected data bursts (traffic) must not cause network performance degradations in the deflection routes. Because minimizing contention occurrences is key to provisioning a consistent Quality of Service (QoS), we therefore in this paper propose and analyze a framework (scheme) that seeks to intelligently deflect traffic in the core network such that QoS degradations caused by contention occurrences are minimized. This is by way of regulated deflection routing (rDr) in which neural network agents are utilized in reinforcing the deflection route choices at core nodes. The framework primarily relies on both reactive and proactive regulated deflection routing approaches in order to prevent or resolve data burst contentions. Simulation results show that the scheme does effectively improve overall network performance when compared with existing contention resolution approaches. Notably, the scheme minimizes burst losses, end-to-end delays, frequency of contention occurrences, and burst deflections.

Physicians' satisfaction with clinical laboratory services at public hospitals in Ethiopia: A national survey.

Physician is a central figure in the client list of clinical laboratory. Monitoring physicians' satisfaction with laboratory service is an important indicator of the quality management system and required by international laboratory standards. However, there is no national data on physician satisfaction with laboratory services in Ethiopia. Therefore, the aim of this national survey was to assess satisfaction level of physicians with laboratory services at public hospitals in Ethiopia. Institutional based cross-sectional study design was employed from November 1-30/2017. A total of 327 physicians were randomly selected from 60 public hospitals from all regions of Ethiopia. Data was collected using pre-tested self-administered questionnaire and analyzed with SPSS version 23 software. Logistic regression model was fitted to identify predictors of physician satisfaction with laboratory services. A p-value of less than 0.05 was taken as statistically significant. Overall, 55% of physicians were satisfied with the clinical laboratory services. More than half of the physicians were satisfied with the existing laboratory request form (69%), legibility and completeness of laboratory report (61%), notification of new test (78%) and test interruption (70%). On the other hand, many physicians were dissatisfied with the absence of laboratory hand book (87.5%), the existing test menu (68%), lab-physician interface (62%), availability of referral and/or back up service (62%), notification of Turn Around Time (TAT) (54%), timely notification of panic result (55%), long TAT (33.1%), provision of urgent service (67%), and timely advisory service (57%). Most of the physicians perceived that consistent quality of service was not delivered at all working shifts (71%). At 5% level of significance, we did not find enough evidence to conclude that sex, age, marital status, education level, and experience were statistically associated with physician satisfaction (p-values > 0.05). This national survey revealed nearly half of the physicians were unsatisfied with laboratory service at public hospitals in Ethiopia, which mainly related to lack of adequate test menu, laboratory hand book, on time notification of panic result, provision of urgent service, timely advisory service, delivery of quality services in all working shifts and weak lab-physician interface. Therefore, hospital management should address the gaps and improve the needs of physicians for better patient health care. In addition, laboratories should evaluate and monitor physician satisfaction level at regular interval.

Dynamic Flow Migration for Embedded Services in SDN/NFV-Enabled 5G Core Networks

Software defined networking (SDN) and network function virtualization (NFV) are key enabling technologies in fifth generation (5G) communication networks for embedding service-level customized network slices in a network infrastructure, based on statistical resource demands to satisfy long-term quality of service (QoS) requirements. However, traffic loads in different slices are subject to changes over time, resulting in challenges for consistent QoS provisioning. In this paper, a dynamic flow migration problem for embedded services is studied, to meet end-to-end (E2E) delay requirements with time-varying traffic. A multi-objective mixed integer optimization problem is formulated, addressing the trade-off between load balancing and reconfiguration overhead. The problem is transformed to a tractable mixed integer quadratically constrained programming (MIQCP) problem. It is proved that there is no optimality gap between the two problems; hence, we can obtain the optimum of the original problem by solving the MIQCP problem with some post-processing. To reduce time complexity, a heuristic algorithm based on redistribution of hop delay bounds is proposed to find an efficient solution. Numerical results are presented to demonstrate the aforementioned trade-off, the benefit from flow migration in terms of E2E delay guarantee, as well as the effectiveness and efficiency of the heuristic solution.

A comparative study of self-service technology with service employees: a qualitative analysis of hotels in China

The rise of self-service technology (SST) has transformed the lodging industry. Clarifying how hotels and customers can use SST offers insights for hoteliers and fills a research gap regarding SST and the service employees such technology replaces. To accomplish these aims, the researchers held 4 focus groups followed by 60 in-depth interviews with hoteliers and customers, respectively, to explore the role of SST relative to service employees and their influences on SST use. Findings revealed seven comparison dimensions between SST and service employees along with employees’ influences on SST use. SST were more effective than service employees in terms of cost savings, consistent service quality, and provision of high-tech customer experiences. However, service personnel tended to outperform SST in communication, ease of use, usefulness, and high-touch experiences. The merits and disadvantages of SST are dynamic and related to interactions among SST, users (hotels), end users (customers), and alternative service agents (employees).