Showing papers on "Service system published in 2018"

On-Demand Service Platforms

Abstract: An on-demand service platform connects waiting-time-sensitive customers with independent service providers (agents). This paper examines how two defining features of an on-demand service platform—d...

Big Data and Service Operations

Abstract: This study discusses how the tremendous volume of available data collected by firms has been transforming the service industry. The focus is primarily on services in the following sectors: finance/banking, transportation and hospitality, and online platforms (e.g., subscription services, online advertising, and online dating). We report anecdotal evidence borrowed from various collaborations and discussions with executives and data analysts who work in management consulting or finance, or for technology/startup companies. Our main goals are (i) to present an overview of how big data is shaping the service industry, (ii) to describe several mechanisms used in the service industry that leverage the potential information hidden in big data, and (iii) to point out some of the pitfalls and risks incurred. On one hand, collecting and storing large amounts of data on customers and on past transactions can help firms improve the quality of their services. For example, firms can now customize their services to unprecedented levels of granularity, which enables the firms to offer targeted personalized offers (sometimes, even in real‐time). On the other hand, collecting this data may allow some firms to utilize the data against their customers by charging them higher prices. Furthermore, data‐driven algorithms may often be biased toward illicit discrimination. The availability of data on sensitive personal information may also attract hackers and gives rise to important cybersecurity concerns (e.g., information leakage, fraud, and identity theft).

Omnichannel Service Operations with Online and Offline Self-Order Technologies

Abstract: Many restaurants have recently implemented self-order technologies across both online and offline channels. Online technology, through websites and mobile apps, allows customers to order and pay before coming to the store; offline technology, such as self-service kiosks, allows store customers to place orders without interacting with a human employee. In this paper, we develop a stylized theoretical model to study the impact of self-order technologies on customer demand, employment levels, and restaurant profits. Our main results follow. First, customers using self-order technologies experience reduced waiting cost and increased demand, and moreover, these benefits may even carry over to customers who do not use these technologies. Second, although public opinion suggests that self-order technologies facilitate job cuts, we find instead that some firms should increase employment levels, and, paradoxically, this recommendation holds for firms with high labor costs. Finally, we find that firms should implement online offline self-order technology when customers have high low wait sensitivity. The supplementary appendix is available at https://doi.org/10.1287/mnsc.2017.2787 . This paper was accepted by Serguei Netessine, operations management.

Service operations: what’s next?

Abstract: The purpose of this paper is to present exciting and innovative research questions in service operations that are aligned with eight key themes and related topics determined by the Journal of Service Management (JOSM) Service Operations Expert Research Panel. By offering a good number of such research questions, this paper provides a broad range of ideas to spur conceptual and empirical research related to service operations and encourage the continued creation of deep knowledge within the field, as well as collaborative research across disciplines that develops and incorporates insights from service operations.,Based on a Delphi study, described in the companion article, “Service Operations: What Have We Learned?,” the panel identified eight key research themes in service operations where leading-edge research is being done or has yet to be done (Victorino et al., 2018). In this paper, three or four topics within each theme are selected and multiple questions for each topic are proposed to guide research efforts. The topics and questions, while wide-ranging, are only representative of the many ongoing research opportunities related to service operations.,The field of service operations has many interesting research topics and questions that are largely unexplored. Furthermore, these research areas are not only increasingly integrative across multiple themes within operations but often transcend functional disciplines. This creates opportunities for ever more impactful research with a greater reach throughout the service system and suggests that service researchers, regardless of functional affiliation, can contribute to the ongoing conversation on the role of service operations in value creation.,Leveraging the collective knowledge of the JOSM Service Operations Expert Research Panel to expand on the research themes generated from the Delphi study, novel questions for future study are put forward. Recognizing that the number of potential research questions is virtually unlimited, summary questions by theme and topic are also provided. These questions represent a synopsis of the individual questions and can serve as a quick reference guide for researchers interested in pursuing new directions in conceptual and empirical research in service operations. This summary also serves as a framework to facilitate the formulation of additional research topics and questions.

Rafiki: machine learning as an analytics service system

Abstract: Big data analytics is gaining massive momentum in the last few years. Applying machine learning models to big data has become an implicit requirement or an expectation for most analysis tasks, especially on high-stakes applications. Typical applications include sentiment analysis against reviews for analyzing on-line products, image classification in food logging applications for monitoring user's daily intake, and stock movement prediction. Extending traditional database systems to support the above analysis is intriguing but challenging. First, it is almost impossible to implement all machine learning models in the database engines. Second, expert knowledge is required to optimize the training and inference procedures in terms of efficiency and effectiveness, which imposes heavy burden on the system users. In this paper, we develop and present a system, called Rafiki, to provide the training and inference service of machine learning models. Rafiki provides distributed hyper-parameter tuning for the training service, and online ensemble modeling for the inference service which trades off between latency and accuracy. Experimental results confirm the efficiency, effectiveness, scalability and usability of Rafiki.

Automated Quantitative Verification for Service-Based System Design: A Visualization Transform Tool Perspective

Abstract: Service-based systems are a new software mode for distributed business processes integration. It is difficult for traditional testing methods to verify the functional and nonfunctional requirements...

Recombinant Service Systems Engineering

Abstract: Although many methods have been proposed for engineering service systems and customer solutions, most of these approaches give little consideration to recombinant service innovation. Recombinant innovation refers to reusing and integrating resources that were previously unconnected. In an age of networked products and data, we can expect that many service innovations will be based on adding, dissociating, and associating existing value propositions by accessing internal and external resources instead of designing them from scratch. The purpose of this paper is to identify if current service engineering approaches account for the mechanisms of recombinant innovation and to design a method for recombinant service systems engineering. In a conceptual analysis of 24 service engineering methods, the study identified that most methods (1) focus on designing value propositions instead of service systems, (2) view service independent of physical goods, (3) are either linear or iterative instead of agile, and (4) do not sufficiently address the mechanisms of recombinant innovation. The paper discusses how these deficiencies can be remedied and designs a revised service systems engineering approach that reorganizes service engineering processes according to four design principles. The method is demonstrated with the recombinant design of a service system for predictive maintenance of agricultural machines.

Exploring the innovation modes and evolution of the cloud-based service using the activity theory on the basis of big data

Abstract: With the cooperation between hospitals and advanced technologies such as mobile Internet, big data and cloud computing, emerging technologies and new service models have been applied in precaution, diagnosis, treatment and other medical services. As a result, people’s medical practices have been dramatically changed. On the basis of activity theory and service supply chain, the paper discusses hospital’s innovation in medical, health and care service by using cloud computing. It also explores the model and evolution of hospital’s internal activity and external supply chain.Cases in this paper from the year 2000 till now are our secondary data related to the cloud service innovation in hospitals. The study adopts textual analysis to interpret and analyze the data. Then, in-depth interviews would be taken on the basis of analytical result. Through the above-mentioned process, we find that homogeneities between different cases include treatment service cloud ranking first, community as the main promoter, substantial service innovation being emphasized, care service cloud as future trend, service innovation featured client-service model, eight procedures for service supply chain, improvement of suppliers’ self-design, and pluralism of medical care service etc. Differences of the cases include government policies versus industrial policies, multipoint distribution versus centralized organizational structure, regional institutionalization versus large-scale centralization, Substantive services application versus development of service value, market orientation versus industry orientation, service provider orientation versus service design orientation, physical customer versus invisible customer. In the end, the study offers relevant theories, management implications, and recommendations.

VCG Auction-Based Dynamic Pricing for Multigranularity Service Composition

Abstract: When a single service on its own cannot fulfill a sophisticated application, a composition of services is required. Existing methods mostly use a fixed-price scheme for service pricing and determine service allocation for composition based on a first-price auction. However, in a dynamic service market, it is difficult for service providers to determine a fixed price that is profitable while attractive to customers. Meanwhile, this mechanism cannot ensure that the providers who require the least cost to provide services would win the auction, because the pricing strategy of service providers is unpredictable. To address such issues, in this paper, we propose Vickrey–Clarke–Groves auction-based dynamic pricing for a generalized service composition. We consider fine-grained services as candidates for composition as well as coarse-grained ones. In our approach, service providers bid for services of different granularities in the composite service and based on received bids, a user decides a composition that minimizes the social cost while meeting quality constraints. Experimental results at last verify the feasibility and effectiveness of the proposed approach. Note to Practitioners —Motivated by the popular auction-based dynamic pricing in the modern Internet business, this paper proposes a Vickrey–Clarke–Groves auction-based approach for multigranularity service composition in order to overcome the shortcomings of existing approaches, e.g., unpredictability in service pricing, and lack of economic efficiency. The proposed approach instantiates a composite service in an economically efficient way and it offers service providers with the incentives to honestly declare the true costs of their concrete services in the bids. In the experiments, compared with fine-grained service composition, the proposed approach reduces the social cost and user payment of service composition by 6.8% and 11.2% on average, respectively, and it also shows superiority over the first-price auction-based approach.

Attendance and information system using RFID and web-based application for academic sector

Abstract: Recently, students attendance have been considered as one of the crucial elements or issues that reflects the academic achievements and the performance contributed to any university compared to the traditional methods that impose time-consuming and inefficiency Diverse automatic identification technologies have been more in vogue such as Radio Frequency Identification (RFID) An extensive research and several applications are produced to take maximum advantage of this technology and bring about some concerns RFID is a wireless technology which uses to a purpose of identifying and tracking an object via radio waves to transfer data from an electronic tag, called RFID tag or label to send data to RFID reader The current study focuses on proposing an RFID based Attendance Management System (AMS) and also information service system for an academic domain by using RFID technology in addition to the programmable Logic Circuit (such as Arduino), and web-based application The proposed system aims to manage student’s attendance recording and provides the capabilities of tracking student absentee as well, supporting information services include students grading marks, daily timetable, lectures time and classroom numbers, and other student-related instructions provided by faculty department staff Based on the results, the proposed attendance and information system is time-effective and it reduces the documentation efforts as well as, it does not have any power consumption Besides, students attendance RFID based systems that have been proposed are also analyzed and criticized respect to systems functionalities and main findings Future directions for further researchers are focused and identified

Overload Control for Scaling WeChat Microservices

Abstract: Effective overload control for large-scale online service system is crucial for protecting the system backend from overload. Conventionally the design of overload control is ad-hoc for individual service. However, service-specific overload control could be detrimental to the overall system due to intricate service dependencies or flawed implementation of service. Service developers usually have difficulty to accurately estimate the dynamics of actual workload during the development of service. Therefore, it is essential to decouple the overload control from service logic. In this paper, we propose DAGOR, an overload control scheme designed for the account-oriented microservice architecture. DAGOR is service agnostic and system-centric. It manages overload at the microservice granule such that each microservice monitors its load status in real time and triggers load shedding in a collaborative manner among its relevant services when overload is detected. DAGOR has been used in the WeChat backend for five years. Experimental results show that DAGOR can benefit high success rate of service even when the system is experiencing overload, while ensuring fairness in the overload control.

Operationalisation of service innovation: a systems thinking approach

Abstract: This paper initialises an effort to explore the impact of an innovative systems thinking approach for service operations design on creating innovation. A qualitative exploratory case study approach...

Possibility of Digital Twins Technology for Improving Efficiency of the Branded Service System

Abstract: Nowadays, the concept of digital economy along with market competition requires constant modification of current business models and logistic services. Since branded service companies directly interact with customers, the efficiency of the vehicle maintenance strongly influences on the company's level of service. Digital Twins helps to track data of failures throughout the whole transportation and to predict failures of each particular vehicle and plan the full capacity. By the example of the KAMAZ company we analyze the efficiency of such technology for the final customer. The comparison of the predicted number of failures, obtained from Digital Twin, shows a high level of flexibility that could be achieved with such a system, showing a potential towards leasing market.

Operating without operations: how is technology changing the role of the firm?

Abstract: Purpose The purpose of this paper is to analyze the history and future of service operations, with the goal to identify key theoretical and technological advances, as well as fundamental themes that can help to imagine the future of service operations in 2050 Design/methodology/approach A review of the service operations literature was undertaken to inform a discussion regarding the role that technology will play in the future of service operations Findings The future of service operations is framed in terms of three key themes – complexity, orchestration, and elasticity The paper makes three contributions to the service science literature by: reviewing key themes underpinning extant service operations research to frame future trajectories of service operations research; elaborating a vision of service operations in 2050 based on history and technology; and outlining a research agenda for future service operations Practical implications The case of service automation is used to provide an illustration of how the three themes converge to define future service operations, and in particular, to show how technology is recasting the role of the firm Originality/value Service operations in the next 30 years will be very different from what it was in the past 30 years This paper differs from other review papers by identifying three key themes that will characterize and instill new insights into the future of service operations research

Online reliability time series prediction via convolutional neural network and long short term memory for service-oriented systems

Abstract: With the development of Web service technology, more and more enterprises choose to publish their own services on the Internet. However, with the increasing demands of users, it is difficult for a single service to meet the complex user requirements. To address this challenge, multiple services can be integrated by leveraging the service-oriented architecture (SOA) to generate a value-added service, referred to a service composition, where the component services are loosely coupled. However, due to the dynamic running environment, the performance of each component service (including reliability) may fluctuate. This will introduce cascading effects, which could cause the entire service system to fail. Since component services run in a dynamic environment, the parameters used to conduct reliability prediction are difficult to obtain. Therefore, online reliability prediction that ensures the runtime quality poses a grand challenge. This paper analyzes the historical response time series and throughput time series of component services, and predicts the reliability in the near future. To guarantee the stable and continuous operation of a service system, we proposed an online reliability time series prediction method by combining a Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM). The proposed approach, referred to as CL-ROP, is able to predict the reliability of a service system in the near future. We conducted a series of experiments over real service data and compared with other competitive approaches to demonstrate the effectiveness of the proposed approach.

LibSEAL: revealing service integrity violations using trusted execution

Abstract: Users of online services such as messaging, code hosting and collaborative document editing expect the services to uphold the integrity of their data. Despite providers' best efforts, data corruption still occurs, but at present service integrity violations are excluded from SLAs. For providers to include such violations as part of SLAs, the competing requirements of clients and providers must be satisfied. Clients need the ability to independently identify and prove service integrity violations to claim compensation. At the same time, providers must be able to refute spurious claims. We describe LibSEAL, a SEcure Audit Library for Internet services that creates a non-repudiable audit log of service operations and checks invariants to discover violations of service integrity. LibSEAL is a drop-in replacement for TLS libraries used by services, and thus observes and logs all service requests and responses. It runs inside a trusted execution environment, such as Intel SGX, to protect the integrity of the audit log. Logs are stored using an embedded relational database, permitting service invariant violations to be discovered using simple SQL queries. We evaluate LibSEAL with three popular online services (Git, ownCloud and Dropbox) and demonstrate that it is effective in discovering integrity violations, while reducing throughput by at most 14%.

Rafiki: Machine Learning as an Analytics Service System

Abstract: Big data analytics is gaining massive momentum in the last few years. Applying machine learning models to big data has become an implicit requirement or an expectation for most analysis tasks, especially on high-stakes applications.Typical applications include sentiment analysis against reviews for analyzing on-line products, image classification in food logging applications for monitoring user's daily intake and stock movement prediction. Extending traditional database systems to support the above analysis is intriguing but challenging. First, it is almost impossible to implement all machine learning models in the database engines. Second, expertise knowledge is required to optimize the training and inference procedures in terms of efficiency and effectiveness, which imposes heavy burden on the system users. In this paper, we develop and present a system, called Rafiki, to provide the training and inference service of machine learning models, and facilitate complex analytics on top of cloud platforms. Rafiki provides distributed hyper-parameter tuning for the training service, and online ensemble modeling for the inference service which trades off between latency and accuracy. Experimental results confirm the efficiency, effectiveness, scalability and usability of Rafiki.

Introduction to the Special Issue on Perspectives on Big Data

Abstract: Big data has the potential of offering valuable insights into the way organizations function, and it is changing the way organizations make decisions. Nine invited essays provide a wide range of perspectives on the role of big data in customer‐driven supply chains, healthcare operations, retail operations, demand planning and manufacturing, environmental and social issues, humanitarian operations, agriculture supply chains, and service operations. Decision makers should have clean, valid, and reliable data, and they should have a thorough understanding of the contexts of applications. Big data shorten virtual distance to customers, and thus facilitate personalization of products and services. Successful implementation of big data applications requires sharing the data with appropriate stakeholders.

The Dilemma of Service Productivity and Service Innovation: An Empirical Exploration in Financial Services

Abstract: We conduct a systematic exploratory investigation of the effects of firms' existing service productivity on the success of their new service innovations. Although previous research extensively addresses service productivity and service innovation, this is the first empirical study that bridges the gap between these two research streams and examines the links between the two concepts. Based on a comprehensive data set of new service introductions in a financial services market over a 14-year period, we empirically explore the relationship between a firm's existing service productivity and the firm's success in introducing new services to the market. The results unveil a fundamental service productivity-service innovation dilemma: Being productive in existing services increases a firm's willingness to innovate new services proactively but decreases the firm's capabilities of bringing these services to the market successfully. We provide specific insights into the mechanism underlying the complex relationship between a firm's productivity in existing services, its innovation proactivity, and its service innovation success. For managers, we not only unpack and elucidate this dilemma but also demonstrate that a focused customer scope and growth market conditions may enable firms to mitigate the dilemma and successfully pursue service productivity and service innovation simultaneously.

Do accountabilities change when public organisations transform to service systems: A new conceptual approach

Abstract: In this conceptual paper, we discuss from the service systems perspective how accountabilities differ from a hierarchic and organisational perspective within the domain of New Public Management, looking to shed new light upon accountability as a research topic. The concept of service systems and their accountabilities are scrutinised and the role of integrated social and health care services is discussed in particular. The main argument in the text is the changing nature of accountabilities as the public organisations are being transformed into service systems. To date, the understanding of accountability has remained structural by nature – such is the case also for productivity measurement – but the shift from organisations towards services systems means that accountability ought to be considered as processual by nature. By processual it is meant that accountability should be considered as flows within systems – that is: flows between agents the content of which we argue includes not only knowledge on the outputs of public services, but also values, empathy and thus multi‐layered understanding of accountability. The paper concludes with practical insights for managerial purposes on the basis for this accountability shift.

Identity authentication system and identity authentication method based on block chain smart contract

Abstract: The invention discloses an identity authentication system based on a block chain smart contract. An application layer middleware module provides a universal unified external interface; a universal authority management module manages a user role authority of the identity authentication system and verifies the user authority according to specified rules and policies; a general account management module manages a relevant operation of a user on account information in the identity authentication system, verifies the validity of an access account, and meanwhile, provides an asynchronous message push service to complete real-time updating of the account cache information; and a service system management module manages a service system, completes the registration of an access service system, stores relevant information and an identifier of the service system in the block chain smart contract, and provides a single sign-on scheme for the service system. The identity authentication system provided by the invention has very good reliability, stability and safety.

Can a Humanoid Robot Engage in Heartwarming Interaction Service at a Hotel

Abstract: While more and more robots have been employed in the service industry, the impact of the human--robot social interaction on a heartwarming interaction service mostly remains an open question. For the purpose of exploring the possibility that a humanoid robot engages in a heartwarming interaction service, we developed herein the first prototype of the service system through a humanoid robot and conducted a field study, where a humanoid robot engages in the service for a customer at a hotel to collect a customer's impression of the service by questionnaire. The results demonstrate a humanoid robot's potential of engaging in a heartwarming interaction service that enhances customer satisfaction of the whole service. An exploratory analysis suggests the differences of the impact in sex and long-term interaction. Finally, we discuss the possibility of another application, namely, effective advertisement through a heartwarming interaction with a humanoid robot.

Service Pricing with Loss-Averse Customers

Abstract: We consider a service system in which customers are loss averse toward both price and delay attributes. That is, customers compare these two attributes with their rational expectations of outcomes,...

Availability of comprehensive services in permanent supportive housing in Los Angeles.

Abstract: Studies have often described a specific model or models of permanent supportive housing (PSH), yet few studies have systematically examined what services are typically offered to PSH tenants in any given service system and how those services are offered. Using telephone surveys from 23 PSH agency supervisors and qualitative data collected from 11 focus groups with 60 frontline providers and 17 individual interviews with supervisors from a subset of surveyed agencies-all of which were completed between July 2014 and December 2015-the goal of this study is to better understand what services are being offered in PSH organisations located in Los Angeles and what barriers frontline providers face in delivering these services. Survey findings using statistical frequencies suggest the existence of robust support services for a high-needs population and that single-site providers may offer more services than scatter-site providers. Qualitative thematic analysis of interview and focus group transcripts suggests services may be less comprehensive than they appear. If PSH is to be regarded as an intervention capable of more than "just" ending homelessness, further consideration of the provision of supportive services is needed.