Showing papers on "Service level objective published in 2022"

COSCO: Container Orchestration Using Co-Simulation and Gradient Based Optimization for Fog Computing Environments

Abstract: Intelligent task placement and management of tasks in large-scale fog platforms is challenging due to the highly volatile nature of modern workload applications and sensitive user requirements of low energy consumption and response time. Container orchestration platforms have emerged to alleviate this problem with prior art either using heuristics to quickly reach scheduling decisions or AI driven methods like reinforcement learning and evolutionary approaches to adapt to dynamic scenarios. The former often fail to quickly adapt in highly dynamic environments, whereas the latter have run-times that are slow enough to negatively impact response time. Therefore, there is a need for scheduling policies that are both reactive to work efficiently in volatile environments and have low scheduling overheads. To achieve this, we propose a Gradient Based Optimization Strategy using Back-propagation of gradients with respect to Input (GOBI). Further, we leverage the accuracy of predictive digital-twin models and simulation capabilities by developing a Coupled Simulation and Container Orchestration Framework (COSCO). Using this, we create a hybrid simulation driven decision approach, GOBI*, to optimize Quality of Service (QoS) parameters. Co-simulation and the back-propagation approaches allow these methods to adapt quickly in volatile environments. Experiments conducted using real-world data on fog applications using the GOBI and GOBI* methods, show a significant improvement in terms of energy consumption, response time, Service Level Objective and scheduling time by up to 15, 40, 4, and 82 percent respectively when compared to the state-of-the-art algorithms.

Service Value and Repurchase Intention in the Egyptian Fast-Food Restaurants: Toward a New Measurement Model

Abstract: Service value is a crucial dominant indicator in customer decision-making. However, there is a lack of hospitality literature that investigates the multi-dimensional service value in emerging markets. Thus, this study aims to create a multi-dimensional scale for service value and to analyze how different service value dimensions affect customers repurchase intentions at fast-food restaurants. We make a conceptual framework with eight constructs, including service value and repurchase intention. A self-administrated questionnaire is used to gather empirical data from fast-food restaurant customers in Egypt. We employ confirmatory factor analysis to extract the model’s reliability and validity. Moreover, we use a structural equation model to extract the model regressions and correlations using AMOS software. We find that each of the eight proposed service value variables impacts fast-food restaurant customers’ repurchase intention. However, the factors that strongly influence customers’ preferences to make more purchases are service equity, confidence benefits, service quality, and service reputation. We contribute to the literature on hospitality customer value and repurchasing intentions by presenting a comprehensive multi-dimensional service value framework that affects customers’ repurchase intentions in fast-food restaurants. Practically, eight service value variables can help managers of fast-food restaurants meet customer needs and gain a competitive advantage. We suggest many crucial recommendations to restaurant managers regarding the priority of the service value constructs. For example, managers should consider service equity, service quality, and service reputations as a priority of the restaurant service value.

Service Level Agreement Monitoring as a Service: An Independent Monitoring Service for Service Level Agreements in Clouds.

Abstract: The cloud network is rapidly growing due to a massive increase in interconnected devices and the emergence of different technologies such as the Internet of things, fog computing, and artificial intelligence. In response, cloud computing needs reliable dealings among the service providers, brokers, and consumers. The existing cloud monitoring frameworks such as Amazon Cloud Watch, Paraleap Azure Watch, and Rack Space Cloud Kick work under the control of service providers. They work fine; however, this may create dissatisfaction among customers over Service Level Agreement (SLA) violations. Customers' dissatisfaction may drastically reduce the businesses of service providers. To cope with the earlier mentioned issue and get in line with cloud philosophy, Monitoring as a Service (MaaS), completely independent in nature, is needed for observing and regulating the cloud businesses. However, the existing MaaS frameworks do not address the comprehensive SLA for customer satisfaction and penalties management. This article proposes a reliable framework for monitoring the provider's services by adopting third-party monitoring services with clearcut SLA and penalties management. Since this framework monitors SLA as a cloud monitoring service, it is named as SLA-MaaS. On violations, it penalizes those who are found in breach of terms and condition enlisted in SLA. Simulation results confirmed that the proposed framework adequately satisfies the customers (as well as service providers). This helps in developing a trustworthy relationship among cloud partners and increases customer attention and retention.

Optimal Scheduling of Proactive Service with Customer Deterioration and Improvement

Abstract: Service systems are typically limited resource environments where scarce capacity is reserved for the most urgent customers. However, there has been a growing interest in the use of proactive service when a less urgent customer may become urgent while waiting. On one hand, providing service for customers when they are less urgent could mean that fewer resources are needed to fulfill their service requirement. On the other hand, using limited capacity for customers who may never need the service in the future takes the capacity away from other more urgent customers who need it now. To understand this tension, we propose a multiserver queueing model with two customer classes: moderate and urgent. We allow customers to transition classes while waiting. In this setting, we characterize how moderate and urgent customers should be prioritized for service when proactive service for moderate customers is an option. We identify an index, the modified [Formula: see text]-index, which plays an important role in determining the optimal scheduling policy. This index lends itself to an intuitive interpretation of how to balance holding costs, service times, abandonments, and transitions between customer classes. This paper was accepted by David Simchi-Levi, stochastic models and simulation.

On the Participation, Competition and Welfare at Customer-Intensive Discretionary Service Platforms

Abstract: Problem definition: We investigate the participation, competition, and welfare at platforms that focus on customer-intensive discretionary services, such as healthcare, legal, and business consulting. Academic/practical relevance: Such platforms have recently emerged in practice to provide a venue for independent professionals and service seekers to match online. Methodology: We develop a strategic queueing model, where the platform sets the commission rate, upon which service providers decide participation, service quality, and price, and consumers make service acquisition. Results: First, our study reveals that with heterogeneous consumers, the participating service providers may engage in both price and service competitions if the number of them is either small or large. They compete for attractive consumers in the former and for market share in the latter. In these regions, more service providers joining the platform can result in a lower service price and a higher service quality. Whereas, if the number of participating service providers is intermediate, only service competition arises, so that a higher service quality is associated with a higher service price. Second, we find that in our main model, the platform may set the commission rate sufficiently high to limit the number of participating service providers, so as to prevent intense price competition. In contrast, if the platform also controls the service price, it may set a higher service price and a lower commission rate, which boosts the participation of service providers and improves their service quality. As a result, platform price intervention may not only benefit the platform and the service providers, but also the consumers. Managerial implications: These insights not only complement prior literature, but are also useful for understanding and the design of such service platforms in practice.

Developing a service quality scale for artificial intelligence service agents

Abstract: Purpose Service providers and consumers alike are increasingly adopting artificial intelligence service agents (AISA) for service. Yet, no service quality scale exists that can fully capture the key factors influencing AISA service quality. This study aims to address this shortcoming by developing a scale for measuring AISA service quality (AISAQUAL). Design/methodology/approach Based on extant service quality research and established scale development techniques, the study constructs, refines and validates a multidimensional AISAQUAL scale through a series of pilot and validation studies. Findings AISAQUAL contains 26 items across six dimensions: efficiency, security, availability, enjoyment, contact and anthropomorphism. The new scale demonstrates good psychometric properties and can be used to evaluate service quality across AISA, providing a means of examining the relationships between AISA service quality and satisfaction, perceived value as well as loyalty. Research limitations/implications Future research should validate AISAQUAL with other AISA types, as they diffuse throughout the service sector. Moderating factors related to services, the customer and the AISA can be investigated to uncover the boundary conditions under which AISAQUAL is likely to influence service outcomes. Longitudinal studies can be carried out to assess how ongoing use of AISA can change service outcomes. Practical implications Service managers can use AISAQUAL to effectively monitor, diagnose and improve services provided by AISA while enhancing their understanding of how AISA can deliver better service quality and customer loyalty outcomes. Originality/value Anthropomorphism is identified as a new service quality dimension. AISAQUAL facilitates theory development by providing a reliable scale to improve the current understanding of consumers’ perspectives concerning AISA services.

Dynamic pricing for online information services considering service duration and quality level

Abstract: Although online information services have significant advantages compared to traditional services in terms of information delivery, service efficiency, and customer convenience, they lack effective pricing strategies. In this research, we analyze customer behavior using an optimal control model, and propose a dynamic pricing mechanism for a newly developed online information service. In particular, we study the influence of user feedback, service duration, and service quality level on optimal decisions of the service provider (SP). First, we derive the optimal pricing, the free information referral rate, and the number of service pricing periods for different combinations of service quality levels and service durations. Second, we discuss the necessity and duration of the “free-charge” period. Third, we find that although higher-quality service with a longer duration can lead to higher profit and consumer surplus, it entails larger preliminary capital investment. Furthermore, in view of the maximum average profit, we discuss the optimal service duration and service quality level. Based on this, we provide managerial suggestions for the SP to choose an appropriate service duration and service quality level. Finally, we present a practically-applicable method for the SP to determine the service price as well as its duration by estimating the number of interested customers. Our findings enable the SP to determine the optimal strategies for its services in real business. Moreover, our results can be extended to similar online applications, thereby widening the scope of our research and providing avenues for further studies.

Bribing for Public Service: What Drives the Service Users?

Abstract: ABSTRACT With the data (N = 9718) from Nepal National Governance Survey 2017/18 of those who took public services in a year, this article examined the factors that drove service users to pay bribes to service providers. The result showed that the perception of service users that service providers comply with the rules; they are responsive to inform/listen/respond to the service users’ concerns; they simplify the process of the service; they receive adequate salary for their jobs; they have prior connections/networks to the service users have a negative effect on paying a bribe whereas the perceptions of service users that service providers deliver services to them on time; they require additional income, they deliver services in multiple attempts; they work in the land revenue office have a positive effect on paying a bribe. Therefore, it is high time to consider the factors for corruption-free service delivery.

Privacy Management in Service Systems

Abstract: Problem definition: We study customer-centric privacy management in service systems. Academic/practical relevance: We explore the consequences of extended control over personal information by customers in such systems. Methodology: We adopt a stylized queueing model to capture a service environment that features a service provider and customers who are strategic in deciding whether to disclose personal information to the service provider—that is, customers’ privacy or information disclosure strategy. A customer’s service request can be one of two types, which affects service time but is unknown when customers commit to a privacy strategy. The service provider can discriminate among customers based on their disclosed information by offering different priorities. Results: Our analysis reveals that, when given control over their personal data, strategic customers do not always choose to withhold them. We find that control over information gives customers a tool they can use to hedge against the service provider’s will, which might not be aligned with the interests of customers. More importantly, we find that under certain conditions, giving customers full control over information (e.g., by introducing a privacy regulation) may not only distort already efficiently operating service system but might also backfire by leading to inferior system performance (i.e., longer average wait time), and it can hurt customers themselves. We demonstrate how a regulator can correct information disclosure inefficiencies through monetary incentives to customers and show that providing such incentives makes economic sense in some scenarios. Finally, the service provider itself can benefit from customers being in control of their personal information by enticing more customers joining the service. Managerial implications: Our findings yield insights into how customers’ individually rational actions concerning information disclosure (e.g., granted by a privacy regulation) can lead to market inefficiencies in the form of longer wait times for services. We provide actionable prescriptions, for both service providers and regulators, that can guide their choices of a privacy and information management approach based on giving customers the option of controlling their personal information.

Three-phase service level agreements and trust management model for monitoring and managing the services by trusted cloud broker

Abstract: Cloud computing is an environment where everything is provided as a service based on demand. It follows pay as per the used model in which the service consumer needs to pay for what they have consumed. Due to the increased dependence on digitalization, the number of consumers and providers tends to grow tremendously. The consumer who needs the service from the provider is not sure about the specified service outcome, and it is too hard for them to monitor and manage the service. Hence, a trusted third party called a trusted cloud broker (TCB) is introduced for managing the services. The service level agreements (SLA) management and reputation estimation framework is proposed, which includes three phases such as (i) SLA establishment between the three parties, (ii) violation detection by comparing the observed value of the TCB and (iii) the reputation and penalty estimation of the service. The novel TCB is created to monitor the deployed services, ensuring the achievement of SLA. The TCB observes the values and estimates the reputation value for each service. It is compared with the provider log-based reputation value and found that the proposed model provides a more precise reputation value for the service providers.

Application of ROC and CODAS Techniques for Cloud Service Provider Selection

Abstract: Due to the widespread use of cloud services, the choice of cloud service providers has become an important problem for companies. It is a strategic decision-making problem for companies to determine the most suitable service provider that can meet their expectations and needs. Choosing the most effective service provider for a firm depends on numerous criteria based on the firm's strategies, needs and resources. Therefore, in the present study, an integrated decision model based on Rank Order Centroid (ROC) and Combinative Distance-Based Assessment (CODAS) techniques has been developed. In the first stage of the application, the criteria were evaluated using the ROC method, and the service providers were listed using the CODAS technique in the second stage. The effectiveness of the proposed model has been tested by a software company that wants to select a cloud service provider. The results of the research are expected to contribute to service providers and firms that want to select cloud service providers that can meet their needs.

An Integrated Multi Criteria Decision Making Model for Cloud Service Provider Selection

Abstract: In the present scenario, it is inevitable for organizations to use the services offered through the cloud. As there are numerous cloud service providers, the users have a vast number of choices to get the desired service. For the long term success of any organization, it is important to choose the right cloud service provider. This paper focuses on proposing a new framework to select the best cloud service provider. While selecting the best service provider, using an appropriate method for finding out the weight of each criterion is very important as it directly impacts the ranking of candidate service providers. In this work, the Full Consistency Method (FUCOM) is employed for finding the weight of each criterion and Multi-Objective Optimization by Ratio Analysis (MOORA) is proposed for ranking the service provider. The integration of FUCOM with MOORA results in computing the reliable values of criteria weight and a simpler procedure for computing the overall score of the service provider. Hence a rational decision making is possible in selecting the best cloud service provider.

Impact of self‐service technology in designing a service delivery system

Abstract: Self-service technologies (SSTs) have been widely adopted in industries that require the delivery of physical products by services, in which consumers evaluate a product for both the product value and the service value. A typical service delivery system usually involves sales agents and/or self-service technologies, for example, online services and kiosks, to serve consumers by a coproduction process. In other words, both the sales agent (or self-service machine) and the consumer should exert effort, with corresponding service costs. By modeling the coproduction output with a Cobb–Douglas production function, we establish a principal–agent model to study the value of self-service technologies in designing a service delivery system wherein the sales agent's service cost is private information. We first characterize the main trade-off between the sales agent and the self-service machine when the firm provides only one service channel. Then, we analyze the value of the self-service machine when the firm can provide both service channels. We find that, interestingly, the firm may possibly provide both service channels, that is, services offered by the sales agent and the self-service machine, when the level of information uncertainty is high, and the self-service machine's service cost is intermediate. Moreover, when both service channels are offered, only the efficient sales agent will be contracted, and the inefficient sales agents are screened out of the market by the self-service machine; that is, the self-service machine can help the firm eliminate the information rent. We also investigate how the firm's service weight in the coproduction process and information uncertainty influence the consumer surplus, firm's choices, contract parameters, and resulting profits. Our results are shown to be robust when our model is extended to consider a single-contract strategy, contracting on effort, a continuous sales agent type, and a general coproduction function.

Are you willing to forgive AI? Service recovery from medical AI service failure

Abstract: PurposeAs an emerging technology, medical artificial intelligence (AI) plays an important role in the healthcare system. However, the service failure of medical AI causes severe violations to user trust. Different from other services that do not involve vital health, customers' trust toward the service of medical AI are difficult to repair after service failure. This study explores the links among different types of attributions (external and internal), service recovery strategies (firm, customer, and co-creation), and service recovery outcomes (trust).Design/methodology/approachEmpirical analysis was carried out using data (N = 338) collected from a 2 × 3 scenario-based experiment. The scenario-based experiment has three stages: service delivery, service failure, and service recovery. The attribution of service failure was divided into two parts (customer vs. firm), while the recovery of service failure was divided into three parts (customer vs. firm vs. co-creation), making the design full factorial.FindingsThe results show that (1) internal attribution of the service failure can easily repair both affective-based trust (AFTR) and cognitive-based trust (CGTR), (2) co-creation recovery has a greater positive effect on AFTR while firm recovery is more effective on cognitive-based trust, (3) a series of interesting conclusions are found in the interaction between customers' attribution and service recovery strategy.Originality/valueThe authors' findings are of great significance to the strategy of service recovery after service failure in the medical AI system. According to the attribution type of service failure, medical organizations can choose a strategy to more accurately improve service recovery effect.

Effects of Perceived Value, Service Quality and Customer Trust in Home Delivery Service Staff on Customer Satisfaction: Evidence from Pakistan

Abstract: Since e-commerce has expanded rapidly in recent years, it's clear that reliable delivery services are crucial to keeping customers happy. Supplying items on time, providing better service to customers, charging reasonable prices, and enhancing the supplier's reputation are all significant means of retaining existing customers and attracting new ones. The study's key research question is, "How important is the quality of home service?" The value that the customer attributes to the product or service has a direct impact on how satisfied they are with the purchase. Islamabad, the capital of Pakistan, will serve as the venue for the gathering. Four hundred users of the home delivery service were polled via email. The Smart PLS framework analyzes conceptual models using partial least squares structural equation models (PLS-SEM). These findings highlight the importance of service quality, the perceived value of the service, and trust in determining customer satisfaction. Trust allows for a connection to be created between a customer's happiness and their perception of the service's value, as well as between a customer's satisfaction and how much they like using the service. These findings, grounded in Expectation Rejection Theory, expand the SERVQUAL model by factoring in perceived value in the presence of trust and so aid in the creation and validation of trust-based models of customer satisfaction. Managers can tell their service providers how to be more reliable and trustworthy by using the study's results.

Handle with care! Service contract termination as a service delivery task

Abstract: Purpose Profitability considerations lead service providers to terminate service contracts with low-value customers. However, customers targeted by service contract terminations often take revenge through negative word-of-mouth (NWOM). Presently, it is unclear how service contract termination initiatives prevent this harmful side effect. The purpose of this study is to compare the effectiveness of common service contract termination initiatives for reducing NWOM of customers whose service contracts are being cancelled. The study results provide guidance for minimizing the downside of service contract termination. Design/methodology/approach This study distinguishes between service contract termination initiatives common in practice (preannouncement, explanation, financial compensation, apology and support in finding an alternative provider). Drawing on a multi-industry survey of 245 customers who have experienced service contract terminations in real life, the authors estimate regression models to link perceived service contract termination initiatives to NWOM. Findings All else equal, only preannouncement and support in finding an alternative are effective to reduce NWOM. This study also shows that the right choice of service contract termination initiatives depends on the context of the termination. Making a preannouncement, offering an explanation and providing support in finding an alternative are more effective in reducing NWOM when these actions are aligned with the contextual factors of relationship duration and competitive intensity. Research limitations/implications This study shows that service contract termination needs to address several aspects of the service termination experience. The key implication for future research is that it matters in terms of NWOM how service contract terminations are performed. Practical implications This research identifies the service contract termination initiatives that are most effective to reduce NWOM after service contract termination in general and under consideration of the moderating roles of relationship duration and competitive intensity. Originality/value While most related studies have considered customer responses to the cancellation of other customers’ contracts, this study contributes to the scarce literature on the undesirable customer responses (such as NWOM) to the termination of their own contract. To the best of the authors’ knowledge, it is the first study in this emerging stream of research that accounts for the effects of process- and outcome-oriented contract termination initiatives on NWOM. To the best of the authors’ knowledge, it is also the first study to account for moderators of the effect of contract termination initiatives on NWOM, namely, relationship duration and competitive intensity.

Examining service triad operations: Formation, functioning, and feedback exchanges

Abstract: We study service triads by examining the member-to-member exchanges underpinning service formation, functioning, and feedback. A service triad comprises two serviced customers from the supplier's standpoint and two service providers from the end user's standpoint, which can cause operational complexity and challenges. We view the service triad as an operating entity and study four information-rich cases to improve our understanding of this operational complexity. Leveraging scholarly knowledge related to service operations management and ecosystems theory, we uncover several interesting patterns related to the formation, functioning, and feedback exchanges. First, the formation exchanges depend on the value creation goal of the service triad. Second, the service buyer engages in operational coordination, despite delegating the delivery of services to the supplier. Third, feedback exchanges allow the service triad to monitor service performance for further improvement and innovation. Our qualitative inquiry focusing on the visualization and codification of members’ participation in exchanges advances our collective understanding of service triads beyond the dominant focus on structure and governance.

The impact of service quality and service transparency on customer satisfaction

Abstract: High-quality services that satisfy customers improve a company's capacity to compete in the market. It is crucial for the business professionals to encourage the practices that can enhance service quality and service transparency. High service quality and transparency can be attained by identifying service concerns and developing strategies for service performances, and customer satisfaction. To create and investigate a conceptual model and to study the factors with a systematic review, this research area is being provided.

Revenue Management of Group Service Considering Different Quality Levels and Stochastic Customer Patience

Abstract: We consider a service that provides different quality levels to customers who are served in groups (referred to as “group service” (GS)). We consider stochastic customer patience and build a multitype service model to maximize service profit. First, we consider a fixed number of service personnel and decompose the model into several subproblems. We then transform the model into a service personnel allocation problem that can be efficiently solved. Furthermore, we use the water-filling theory, together with a dichotomy approach, to design the numerical algorithm to conduct a numerical test based on actual data. The main contributions of this study are as follows. First, we provide the service provider with a service capacity allocation mechanism that can determine the optimal choice of service quality levels, number of service groups of different quality levels, time length of the service registration period, and service prices. Second, we find that under scarce service capacity, the single-type service can be more profitable than the multitype service, and low-quality services have higher marginal profits than high-quality services. However, when service capacity increases to a certain level, the multitype service can be more profitable than the single-type service. Third, we construct a service capacity decision mechanism and demonstrate the influence of service quality on the total number of service personnel and service groups. The conclusions are potentially useful to GS service providers to effectively make better managerial decisions and improve service profits.

MERENjE KVALITETA USLUGE KAO STRATEŠKI INSTRUMENT BUDUĆNOSTI USLUŽNOG PRAVA

Abstract: This paper aims to point out the importance of service quality for the future of service law. Namely, the quality of service is a key distinctive factor that will divide the service sector into two parts: successful and unsuccessful. Quality is a property of service that determines the extent to which service is excellent. As such, this feature of the service can be graded, depending on the extent to which it achieves the satisfaction of service users. In this regard, measuring the quality of service is a strategic instrument that will trace the path to success for all those companies in the service economy that put the satisfaction of service users at the center of their business activities. Therefore, the creators of the service law norm, in the infrastructure of the laws governing service activities, should incorporate the principle of user-oriented service, especially within specific service sectors where the needs of service users can be best understood.