Showing papers on "Service provider published in 2022"

Innovation-oriented dynamic capabilities of logistics service providers, dynamic resilience and firm performance during the COVID-19 pandemic

Abstract: PurposeThe purpose of this paper is to use a theoretical framework to investigate the relationships between different innovation-oriented dynamic capabilities, dynamic resilience and firm performance among logistics service providers (LSPs) and in-house logistics departments of industrial companies during the coronavirus disease 2019 (COVID-19) pandemic.Design/methodology/approachThe conceptual theoretical framework relies on the dynamic capabilities framework (DCF) and the relational view (RV), which are rooted in the resource-based view (RBV). It is hypothesized that the dynamic capability to innovate reinforces the dynamic capability to adapt and to recover in highly dynamic and vulnerable environments during the pandemic. This allows LSPs to successfully create new services and respond to the changing market circumstances in terms of logistics service quality (LSQ) and firm performance. Data were collected from 83 LSPs and 30 in-house logistics departments via an online survey. The study determined the general strength and direction of the relationships between latent variables. A correlation analysis was utilized to establish statistical significance of the results.FindingsIn this study, a range of innovation-oriented capabilities for achieving more dynamic resilience were bundled in a conceptual framework and were found to be statistically significant for LSQ and firm performance. They are the capability to distribute new knowledge, to train employees effectively, to develop cross-functional collaboration within the firm, to develop inter-firm relationships with business partners on a long-term basis as well as to learn from rivals, and to pursue a win-win relationship with them.Research limitations/implicationsThe results of the study do not imply that the identified capabilities are the only ones relevant to increasing dynamic resilience during the pandemic. In October 2020, the COVID-19 pandemic was at different stages in different countries, so that the level to which firms were affected varied, and although the data were collected during one month only, due to the high dynamics of the pandemic, data were collected during different stages of disruptions, even among respondents in the same country. This study was set in the context of COVID-19, and it could not be proved whether the conceptual framework is generalizable to other crises or particular industries, but it would be worthwhile to examine this in the future. Finally, it was not tested whether LSQ mediates the relationship between innovative capabilities and firm performance during the pandemic.Practical implicationsThe results help managers with regard to their strategic and operational decisions in relation with COVID-19. These findings are useful for executives and logistics managers to improve these capabilities to gain a competitive advantage during pandemic and to find their strengths and weaknesses to develop critical capabilities for situations with a high turbulence and dynamic in their environment, and therefore provide a path for improvement.Originality/valueThis paper operationalizes a multi-theoretical conceptual framework in the context of logistics management (LM) and supply chain management (SCM). This conceptual framework was empirically tested.

How guest-host interactions affect consumer experiences in the sharing economy: New evidence from a configurational analysis based on consumer reviews

Abstract: This study examines the complexity of consumer experiences in the sharing economy (SE) from the perspective of the level of interaction between consumers and service providers. Consistent with service-dominant logic, the joint efforts of consumers and service providers co-create value. In the context of accommodation-sharing, this means not just the room that guests seek but, rather, the authentic local experience they co-create with their hosts. This study proposes a text-analytics framework to extract important service dimensions directly from consumer reviews. The results indicate that the importance of service dimensions, on which consumers focus in reviews, varies with levels of interaction. To better understand the complex nature of consumer experiences in the SE, the framework integrates text analytics with fuzzy-set Qualitative Comparative Analysis (fsQCA), to shift attention from individual service dimensions to service-dimension configurations. Drawing on complexity theory, this study examines the service-dimension configurations that lead to positive and negative sentiment. The fsQCA results reveal that the causal recipes for sentiment differ for various interaction mechanisms. This is the first study to integrate topic modeling, sentiment analysis, and fsQCA, framing service-provider decision support for responding to consumers' needs.

Prosumers as active market participants: A systematic review of evolution of opportunities, models and challenges

Abstract: The possibility of onsite production and flexible consumption is transforming consumers from passive users to active service providers in power systems with the large share of renewable energy sources. The prosumer-centric paradigm brings diverse possibilities by introducing real-time (RT) pricing, enabling easy and fast change of the supplier, creating opportunities for aggregation, enabling local energy production and local energy exchange, as well as the provision of ancillary services. The paper brings a comprehensive review of the evolution of the diverse options for prosumer to exploit their potential. It starts with the analysis of models and opportunities for a single end-user who decided to invest in Photovoltaic (PV), electric vehicles, and flexible devices. Aside from the review, the paper challenges the logic of the prosumer responding to dynamic prices and providing power system flexibility and compares it with the logic of lowering only their electricity bill. It further analyses different types of aggregation, such as energy communities or microgrids, combined market participation with RES, but also decentralization models designed to stimulate internal energy exchange and solve network problems locally. Finally, it discusses the possibility of providing service to both Transmission and Distribution System Operator and the complexity such coordination requires when procuring flexibility services from resources connected to the distribution network or aggregated prosumers. In addition to a comprehensive review and discussion, the paper brings easy-to-understand models and belong results for the reviewed cases of a) single prosumer flexibility, b) aggregated multiple flexible prosumers, c) energy community with the possibility of peer-to-peer trading.

A Blockchain-Based Multi-Cloud Storage Data Auditing Scheme to Locate Faults

Abstract: Network storage services have benefited countless users worldwide due to the notable features of convenience, economy and high availability. Since a single service provider is not always reliable enough, more complex multi-cloud storage systems are developed for mitigating the data corruption risk. While a data auditing scheme is still needed in multi-cloud storage to help users confirm the integrity of their outsourced data. Unfortunately, most of the corresponding schemes rely on trusted institutions such as the centralized third-party auditor (TPA) and the cloud service organizer, and it is difficult to identify malicious service providers after service disputes. Therefore, we present a blockchain-based multi-cloud storage data auditing scheme to protect data integrity and accurately arbitrate service disputes. We not only introduce the blockchain to record the interactions among users, service providers, and organizers in data auditing process as evidence, but also employ the smart contract to detect service dispute, so as to enforce the untrusted organizer to honestly identify malicious service providers. We also use the blockchain network and homomorphic verifiable tags to achieve the low-cost batch verification without TPA. Theoretical analyses and experiments reveal that the scheme is effective in multi-cloud environments and the cost is acceptable.

The Effects of Types of Service Providers on Experience Economy, Brand Attitude, and Brand Loyalty in the Restaurant Industry

Abstract: This study was designed to understand the relationships among the experience economy, brand attitude, and brand loyalty based on the type of service providers, such as robot servers and human servers in the restaurant industry. The data were collected from 296 people who experienced robot servers and from 294 people who experienced human servers and was analyzed through structural equation modeling (SEM), which indicated that the four sub-dimensions of the experience economy: education, entertainment, esthetics, and escapism, positively affect brand attitude, which in turn has a significant positive impact on brand loyalty. In addition, statistical differences were found with the average value of the six constructs based on the type of service providers, such as robot servers and human servers.

The rise of online food delivery culture during the COVID-19 pandemic: an analysis of intention and its associated risk

Abstract: PurposeThis study aims to understand consumer behaviour in the context of online food delivery (OFD), especially given the mandatory lockdown imposed in some countries that have modified the behaviour of consumers. Using model goal-directed behaviour (MGB), this study was conducted to investigate consumer perceived risk on the use of OFD services.Design/methodology/approachResponses of food delivery services users were collected online throughout April 2020 to understand their risk profile and behaviour. A total of 339 responses were collected and subsequently analysed using partial least square (PLS). Both measurement and structural model were evaluated to ensure that the structural equation modelling (SEM) is valid.FindingsThe results revealed that attitude (ATT), subjective norm (SN), positive anticipated emotion (PAE) and negative anticipated emotion (NAE) and perceived behavioural control (PBC) significantly influenced users' desire. It was also found that PBC significantly influenced users' intention. The empirical result suggests that performance, privacy, financial, physical and the risk of contracting COVID-19 negatively influenced users' desire. In contrast, only physical and the risk of contracting COVID-19 negatively influenced users' intention to use OFD services.Practical implicationsThese findings provide OFD service providers and scholars with significant insights into what compels urbanites to adopt OFD services amid a health pandemic. It also allows OFD companies to realign their operation in addressing these concerns and changes in consumer behaviour.Originality/valueAgainst the backdrop of the pandemic, this study provides insights for OFD providers in developing new strategies and approaches for business development and consumer retention in a post-pandemic world.

How Smart Should a Service Robot Be?

Abstract: Service robots are taking over the frontline. They can possess three types of artificial intelligence (AI): mechanical, thinking, and feeling AI. Although these intelligences determine how service robots can help customers, not much is known about how customers respond to robots of different intelligence. This paper addresses this gap, builds on the appraisal theory of emotions, and employs three online experiments and one field study to demonstrate that customers have different emotional responses to the three types of AI. Particularly, the influence of AI on positive emotions becomes stronger as the AI type becomes more sophisticated. That is, feeling AI relates more strongly to positive emotions than mechanical AI. Also, feeling AI and thinking AI increase spending and loyalty intention through customers’ positive emotions. We also identify important contingency effects of service tiers: mechanical AI is more suitable for low-cost firms, whereas feeling AI mainly benefits full-service providers. Remarkably, none of the three intelligences are directly related to negative emotions; perceived robot autonomy is an important mediator in these relationships. The findings yield concrete managerial guidance as to how smart a service robot should be by pinpointing the right type of AI given the market segment of the service provider.

Sharing with perfect strangers: The effects of self-disclosure on consumers’ trust, risk perception, and behavioral intention in the sharing economy

Abstract: The transactional and disposable nature of liquid consumption has placed trust as the lifeblood of sharing economy service innovation, enabling billions of strangers across the globe to connect and share in the face of transaction risks. However, managers and service providers may not realize that self-disclosure acts as a basis to build trust and mitigate risk in the sharing economy. In four studies across different nations, we demonstrate that service providers’ self-disclosure not only generates consumer trust but also reduces their risk perception, which subsequently encourages legitimate transactions on sharing platforms. The findings reveal that when consumers and service providers are objectively similar, consumers do not pay much attention to service providers’ disclosed information. Conversely, in the case of objective dissimilarity, consumers are more attentive to personal and intimate information shared by service providers. Consumer self-esteem plays differential moderating roles in the link between service providers’ self-disclosure and consumer responses.

COVID-19 Networking Demand: An Auction-Based Mechanism for Automated Selection of Edge Computing Services.

Abstract: Network and cloud service providers are facing an unprecedented challenge to meet the demand of end-users during the COVID-19 pandemic. Currently, billions of people around the world are ordered to stay at home and use remote connection technologies to prevent the spread of the disease. The COVID-19 crisis brought a new reality to network service providers that will eventually accelerate the deployment of edge computing resources to attract the massive influx of users' traffic. The user can elect to procure its resource needs from any edge computing provider based on a variety of attributes such as price and quality. The main challenge for the user is how to choose between the price and multiple quality of service deals when such offerings are changing continually. This problem falls under multi-attribute decision-making. This paper investigates and proposes a novel auction mechanism by which network service brokers would be able to automate the selection of edge computing offers to support their end-users. We also propose a multi-attribute decision-making model that allows the broker to maximize its utility when several bids from edge-network providers are present. The evaluation and experimentation show the practicality and robustness of the proposed model.

Using supervised machine learning for B2B sales forecasting: A case study of spare parts sales forecasting at an after-sales service provider

Abstract: In this paper, we present a method to use advance demand information (ADI), taking the form of request for quotation (RFQ) data, in B2B sales forecasting. We apply supervised machine learning and Natural Language Processing techniques to analyze and learn from RFQs. We apply and test our approach in a case study at a large after-sales service and maintenance provider. After evaluation we found that our approach identifies ∼ 70% of actual sales (recall) with a precision rate of ∼ 50%, which represents a performance improvement of slightly more than a factor 2.5 over the current labor-intensive manual process at the service and maintenance provider. Our research contributes to literature by giving step-by-step guidance on incorporating artificial intelligence in B2B sales forecasting and revealing potential pitfalls along the way. Furthermore, our research gives an indication of the performance improvement that can be expected when adopting supervised machine learning into B2B sales forecasting.

Evaluation of Electronic Service-Learning (e-Service-Learning) Projects in Mainland China under COVID-19

Abstract: The use of electronic service-learning (e-Service-Learning or e-SL) is valuable under COVID-19 because we can provide the service without physical contact. Unfortunately, evaluation of e-SL is not widespread and there is no known study in different Chinese societies. Besides, there are many methodological limitations of the existing studies in the field. In this paper, we evaluated e-SL projects implemented in summer 2020 and 2021 in three sites in China. First, we examined service providers' changes based on pretest and posttest scores (i.e., objective outcome evaluation) and their perceptions of the e-SL projects (i.e., subjective outcome evaluation based on the service providers). Second, graduate student assessors in Chinese mainland universities and teachers of primary school students (i.e., service recipients) rated the SL program quality, service providers' performance and benefits to the service recipients after program completion (i.e., subjective outcome evaluation of SL projects based on other stakeholders). Third, trained graduate student assessors evaluated service quality during the implementation process (i.e., process evaluation). We found that university students (i.e., service providers) showed higher posttest scores in positive youth development attributes, leadership attributes and life satisfaction relative to pretest scores. Besides, service providers showed positive perceptions of their learning experience, own performance, benefits to the service recipients and themselves in the SL projects. Similarly, other stakeholders also had positive evaluation of the SL projects and related benefits. Finally, trained graduate student assessors had positive assessment of the quality of program implementation. The findings underscore the utility of e-SL involving both online teaching and learning as well as online service, particularly in a Chinese context.

Evaluation of Electronic Service-Learning (e-Service-Learning) Projects in Mainland China under COVID-19

Abstract: The use of electronic service-learning (e-Service-Learning or e-SL) is valuable under COVID-19 because we can provide the service without physical contact. Unfortunately, evaluation of e-SL is not widespread and there is no known study in different Chinese societies. Besides, there are many methodological limitations of the existing studies in the field. In this paper, we evaluated e-SL projects implemented in summer 2020 and 2021 in three sites in China. First, we examined service providers' changes based on pretest and posttest scores (i.e., objective outcome evaluation) and their perceptions of the e-SL projects (i.e., subjective outcome evaluation based on the service providers). Second, graduate student assessors in Chinese mainland universities and teachers of primary school students (i.e., service recipients) rated the SL program quality, service providers' performance and benefits to the service recipients after program completion (i.e., subjective outcome evaluation of SL projects based on other stakeholders). Third, trained graduate student assessors evaluated service quality during the implementation process (i.e., process evaluation). We found that university students (i.e., service providers) showed higher posttest scores in positive youth development attributes, leadership attributes and life satisfaction relative to pretest scores. Besides, service providers showed positive perceptions of their learning experience, own performance, benefits to the service recipients and themselves in the SL projects. Similarly, other stakeholders also had positive evaluation of the SL projects and related benefits. Finally, trained graduate student assessors had positive assessment of the quality of program implementation. The findings underscore the utility of e-SL involving both online teaching and learning as well as online service, particularly in a Chinese context.

Who will want to use shared autonomous vehicle service and how much? A consumer experiment in South Korea

Abstract: Autonomous driving technologies are expected to affect shared mobility; therefore, the discussions on new business models using shared autonomous vehicles (SAVs) and their feasibilities are underway. This study analyzes consumer preference and willingness to pay for an SAV service, focusing on the automation level of the shared vehicle and liability for an accident, to investigate who will use the SAV service and how much. For this, we conducted a conjoint survey with 1,000 South Koreans and estimated the consumer utility function for an SAV service using a multiple discrete–continuous extreme value (MDCEV) model. The results show that consumer utility increases when the SAV automation level is higher and the liability for an accident lies with the SAV service provider. Moreover, we find that potential consumers have different preferences regarding the liability of a car accident according to their sociodemographic characteristics. We also analyze choice probability and usage of SAV services according to autonomous driving technology levels and who is held liable for an accident. The results show that people with a higher income prefer to use SAV service if service providers are responsible for an accident. Contrarily, older people, drivers, and people with a low income prefer to use SAV service if the accident’s liability lies with the automobile manufacturer. We also find that SAV service usage increases when the level of autonomous driving technology is high or liability for an accident lies with the SAV service provider or automobile manufacturer.

Social prescribing during the COVID-19 pandemic: a qualitative study of service providers’ and clients’ experiences

Abstract: COVID-19 public health restrictions, such as social distancing and self-isolation, have been particularly challenging for vulnerable people with health conditions and/or complex social needs. Link worker social prescribing is widespread in the UK and elsewhere and is regarded as having the potential to provide support to vulnerable people during the pandemic. This qualitative study explores accounts of how an existing social prescribing service adapted to meet clients' needs in the first wave of the pandemic, and of how clients experienced these changes.Data were collected in a deprived urban area of North East England via remote interviews with clients (n = 44), link workers (n = 5) and service provider managerial staff (n = 8) from May-September 2020. Thematic data analysis was conducted.The research found that service providers quickly adapted to remote intervention delivery aiming to serve existing clients and other vulnerable groups. Service providers experienced improved access to some existing clients via telephone in the first months of remote delivery and in some cases were able to engage clients who had previously not attended appointments at GP surgeries. However, link workers also experienced challenges in building rapport with clients, engaging clients with the aims of the intervention and providing a service to digitally excluded people. Limited link worker capacity meant clients experienced variable contact with link workers with only some experiencing consistent support that was highly valued for helping to manage their conditions and mental wellbeing. Limited access to linked services also adversely affected clients. Clients living in less affluent circumstances and/or with worse health were more likely to experience negative impacts on their long-term condition. Some found their health and progress with social prescribing was 'on hold' or 'going backwards', which sometimes negatively affected their health.Social prescribing offered valued support to some during the pandemic, but remote support sometimes had limited impact for clients and findings highlight the vulnerability of social prescribing's success when linked services are disrupted. Findings also show the need for more to be done in the upscaling of social prescribing to provide support to digitally excluded populations.

Determinants of patient behavioural loyalty on primary health centres: Evidence from a cross-sectional study in Indonesia.

Abstract: Background: Patients' loyalty to visit and use the services provided by the primary health centers (PHCs) is an important requirement of a patient referral system in many countries. The aim of this study was to examine the influence of internal service factors (service provider, service process, and service environment) on service quality and behavioural loyalty of patients in Indonesian PHCs ( Puskesmas). Methods: A cross-sectional study was conducted in 14 districts in Aceh Province, Indonesia between September and December 2020. Data were collected in 102 PHCs that were selected randomly from 137 PHCs that have an Inpatient Unit in the province. The demographic data, three components of internal service factors (service provider, service process, and service environment), the service quality and behavioural loyalty were assessed using a validated questionnaire. Hypothesis testing was conducted by using the structural equation model (SEM). Results: Our data suggested that two elements of internal service factors (service provider and service environment) had a positive and significant influence on service quality of the PHCs with p<0.001 and p=0.021, respectively. Service quality had a positive and significant influence of behavioural loyalty of patients to the PHCs (p=0.003). Service quality however did not serve as an intervening variable between internal service factors (service provider, service process, and service environment) and behavioural loyalty of patients, with p=0.091, p=0.230 and p=0.260, respectively. Conclusions: Service provider and service environment are two main factors that influence the service quality and the service quality directly influence the behavioural loyalty on PHC users. Therefore, to increase the patients' loyalty to use the PHC services, the quality of the services should be improved by levelling up the quality of providers and both physical and social environments in the PHCs.

Cloud Risk Management With OWA-LSTM and Fuzzy Linguistic Decision Making

Abstract: In a cloud environment, the indemnity of service level agreement (SLA) violations has an adverse effect on the service provider. It leads to the penalty fee, credit amount, license extension, and reputation decline that could significantly impact future business outcomes. Existing approaches are unable to handle complex predictions that can accommodate the temporal influence of Quality of Service (QoS) data. Moreover, no method in a cloud environment considers all possible attitudinal behavior of the service provider to mitigate the risk of an actual violation. This article proposes an SLA violation risk mitigation model that uses ordered weighted average (OWA) in long short-term memory for complex QoS prediction. The OWA operator is weighted with a minimax disparity approach to manage the risk of SLA violation. The approach intelligently predicts deviation in custom prioritized QoS parameter and recommend exigency of mitigating action by considering all possible attitudinal behavior of the service provider. This article uses linguistic variables, fuzzy and interval numbers to handle imprecise information. The analysis results demonstrate the applicability and efficiency of the proposed approach to address complex risk mitigation actions.

The Utility of Blockchain Technology in the Electronic Commerce of Tourism Services: An Exploratory Study on Romanian Consumers

Abstract: Blockchain technology is considered one of the most revolutionary innovations that has much to offer the tourism industry, having a positive impact among consumers with the help of interactive applications but also easy to use. Tourist services must constantly evolve in a society where the consumer has everything a click away and his requirements are demanding when it comes to quality leisure. Blockchain technology has the power to change the course of the travel experience, offering the customer more autonomy, but the applications developed by the providers can offer transparency and trust to the customers from the moment T0, when the desire to go on a trip is born, until the end at which it should provide feedback. So far, digital and tourism specialists have not agreed on the development of blockchain-based applications, although the benefits are great for both consumers and tourism service providers, as in this publication we can see a series of advantages that blockchain technology can offer the tourism field. This paper also investigates the satisfaction that the Romanian consumer has after purchasing tourist services through e-commerce applications, a satisfaction that can be an additional motivation for specialists to implement blockchain technology. Following the research in this paper, it can be seen how important it is to develop a series of easy-to-use applications, because if the consumer does not manage to use the applications, this affects the degree of satisfaction and the intention to continue using the online applications for the purchase of tourism services.

A Novel Three-Factor Authentication Protocol for Multiple Service Providers in 6G-Aided Intelligent Healthcare Systems

Abstract: 6G technology is now attracting many scientific researchers due to its prominent features including high mobility, high data rate, high operating frequency, and ultra-low end-to-end delay. Compared to the 5G, 6G has certain advantages that can transform smart healthcare to a new advanced intelligent healthcare system, where multiple issues and concerns of the services (e.g., slow ambulance response) are effectively resolved. In such a communication system, patients and service providers communicate with each other via an open internet channel. Since the healthcare data is important and very sensitive, security and privacy in the healthcare network become prominent. In this paper, we introduce a 6G-aided intelligent healthcare environment. Our work also proposes a solution called Centerless User-Controlled Single Sign-On (CL-UCSSO) for achieving a convenient and cost-saving communication in a multi-server system constructed. A three-factor mechanism (combining smart card, password and biometrics) and time bound property are integrated to design the protocol with fast authentication that allows patients and providers to efficiently establish secure communications. Security proof of the proposed protocol is provided using well-known verification tools including RoR model, AVISPA simulation and BAN logic. Results of performance comparisons on various aspects show that our work provides more functionalities and incurs less cost compared with the related works.

Responsive and Responsible: Customizing Management Responses to Online Traveler Reviews:

Abstract: The helpfulness of online reviews greatly facilitates travelers’ information searches, and helpful reviews can popularize travel service providers within a virtual environment. This study examines ...