Third-party Service Providers Research Articles

AIDCT: An AI service development and composition tool for constructing trustworthy intelligent systems

The growing prevalence of AI services on cloud platforms is driving the demand for technologies and tools which enable the integration of multiple AI services to handle intricate tasks.The growing prevalence of AI services on cloud platforms is driving the demand for technologies and tools which enable the integration of multiple AI services to handle intricate tasks. Traditional methods of evaluating intelligent systems focus mainly on the performance of AI components, without providing comprehensive metrics for the system as a whole. Additionally, as these AI components are often sourced from third-party providers, users may face challenges due to inconsistent quality assurance and limitations in further developing AI models, and dealing with third-party service providers’ limitations. These limitations often involve quality assurance and a lack of capability for secondary development and training of services.To address these issues, we have developed a tool based on our previous work. It can autonomously build Intelligent systems from AI services while tackling the issues mentioned above. This tool not only creates service composition solutions that align with user-defined functional requirements and performance metrics but also executes these solutions to verify if the metrics meet user requirements. We have demonstrated the effectiveness of this tool in constructing trustworthy intelligent systems through a series of case studies.

Research on Member Decision-making of Dual-channel Supply Chain with TPL Participation

With the development of the Internet, more and more enterprises choose the dual-channel supply chain for the sale of goods, in which the third-party logistics service provider plays an important role. By adopting the modified hotelling model, this paper constructs a three-level two-channel supply chain model, discusses the influence of centralized and decentralized decision-making on the decision-making of supply chain members, and puts forward corresponding management suggestions.

Account Information and Payment Initiation Services and the Related AML Obligations in the Law of the European Union

Account Information and Payment Initiation Services and the Related AML Obligations in the Law of the European Union

Freshness-keeping effort vs. sustainability: an efficient approach for perishable supply chain system

Last few decades, unwanted climate change and global warming have forced us to think about the world environment. This paper investigates a perishable supply chain system consisting of one manufacturer, one third-party logistics service provider, and multiple retailers. The logistics provider and retailers use cooling technologies to maintain the product's freshness. Here, consumers' demand is evaluated from the utility function based on price, freshness, and sustainability level. The environmental impacts of the system are measured from the amount of energy consumption and carbon emission. Also, the supply chain members are taking their decisions in cooperation, non-cooperation, and coordination decision scenarios to maximise their profit and reduce total environmental impacts. We develop a general model and a particular model under different decision scenarios. The optimal sustainability level, price, and freshness-keeping-effort (FKE) are derived using the Stackelberg game theory. A numerical experiment as well as sensitivity analyses of various important parameters are conducted. It explores that (i) FKEs have more impact than the sustainability level for the consumption of perishable products. (ii) The retailer-leadership scenario is the most effective for reducing carbon emissions and energy consumption whereas the cooperative decision scenario is better for maintaining the freshness level.

Outbreak investigations of Actinobacillus pleuropneumoniae serotype 15 in central Iowa in the winter of 2021-2022

From November 2021 to January 2022, 20 growing-pig sites in central Iowa reported severe clinical respiratory disease and weekly mortality of up to 50%. Actinobacillus pleuropneumoniae serotype 15 was identified as the causative agent of the clinical disease. Given that A pleuropneumoniae serotype 15 has been infrequently diagnosed in the United States, an outbreak investigation was conducted to explore biosecurity hazards and epidemiological aspects associated with the surge of cases. The investigations revealed that all farms had significant gaps in biosecurity and relied heavily on third-party service providers, which may have contributed to the pathogen spread.

E-Government in The Implementation of T-Tax System in Palembang City

Electronic Government, an essential aspect of contemporary governance, harnesses information technology and the internet to optimize governmental activities, fostering enhanced public services and heightened government efficiency and transparency. This research investigates Palembang City's foray into e-government, specifically in regional tax collection, utilizing an online tax application initiated in 2018. Employing a descriptive qualitative research methodology encompassing interviews, observation, documentation, and literature review, the research reveals Palembang City's strategic move to simplify local tax collection through online taxes. Third-party service providers, in collaboration with Bank Sumsel Babel, play a pivotal role in monitoring and facilitating e-tax implementation. Success factors include robust policy support via Mayor Regulations, alongside effective communication strategies utilizing social and electronic media. Challenges persist, such as uneven distribution of tax payment kiosks and low taxpayer compliance with voluntary e-tax adoption. This research offers comprehensive insights into the complexities and opportunities of regional e-government, illuminating the nuanced landscape of digital governance at the local level.

Third Party Assurance: Need More Attention on SOC Reports

<p>According to a Deloitte survey in 2022 , 76 percent of respondents had their IT services delivered through third party models, and more than 90 percent of the respondents will rely on third-party service providers for data analytics and robotic process automation deployment arrangements. However, as these organizations (called user entities) can not directly monitor the service providers’ controls over the outsourced systems that may influence user entities’ business operations and financial reports, whether these service providers establish suitable and effective controls to ensure the data confidentiality and privacy, system integrity, availability becomes an important issue for user entities.</p>

Analysis of Human Resource Management Trends and Innovative Approaches in the Era of Sharing Economy

Based on the analysis of human resource management trends and innovation in the era of sharing economy, this paper discusses the innovation paths in the era of sharing economy through the three aspects of human resource recruitment and selection, human resource training and development, and employee relationship management, and concludes that the trends of human resource management based on the era of sharing economy are mainly reflected in the co-operation with third-party service providers and management, the application of new technologies and tools, flexibility, and the use of new technologies and tools. technologies and tools, flexibility and personalised employee care, and the importance of socialising and networking. The conclusion will provide useful reference for HRM in the era of sharing economy and promote the innovative development of HRM in the new era.

Evaluation of third-party logistics service providers for car manufacturing firms using a novel integrated grey LOPCOW-PSI-MACONT model

Automotive businesses often delegate logistical tasks to third-party logistics (3PLs) service providers to acquire a competitive edge in the dynamic market. Nevertheless, selecting the most suitable third-party logistics (3PL) partner is a multifaceted undertaking that needs careful evaluation of several criteria and alternatives. This research aims to introduce an integrated grey Multiple Criteria Decision Making (MCDM) framework for automotive businesses to deal with the multidimensional 3PL selection decision problem. This framework incorporates an enhanced Preference Selection Index (PSI), Logarithmic Percentage Change-driven Objective Weighting (LOPCOW), and Mixed Aggregation by Comprehensive Normalization Technique (MACONT). The LOPCOW-G and grey PSI (PSI-G) methods extract the criterion weights, whereas the MACONT-G method ranks the alternatives. The suggested framework's practicality is shown by conducting a case study about evaluating and selecting a third-party logistics (3PLs) provider. The findings indicate that the parameters of significant importance are “skilled workforce (0.0977),” “financial strength (0.0901),” and “IT-IS competence (0.0839).” Furthermore, TPL4 has been recognized as the most optimum option with a value of 0.4797. The MACONT-G model is as well compared against other grey MCDM techniques to assess the validity of the proposed model. The Pearson correlation coefficient between MACONT-G and the other models based on grey sets is 0.958, suggesting a significant and positive link. Furthermore, it is worth noting that a sensitivity analysis has been conducted to validate the accuracy and reliability of the created framework. In conclusion, this study has identified managerial and policy implications that might assist policymakers and executives in effectively evaluating 3PL providers.

Is Bangkok Ready for Open Banking? A Research Note on Exploring the Variables that Affect Innovation Adoption

Today, the globe is seeing rapid growth in digital banking. Many financial technologies are vital and have been implemented. The most ground-breaking financial technology is open banking. It is based on the principle that it allows third-party financial service providers access to customer banking, transactional, and other financial data from banks and non-banks. However, the implementation of open banking technology is restricted due to the presence of unclear government regulations. Furthermore, there are many variables that influence the adoption of such technologies by customers. Thus, this article aims to examine the numerous variables that influence the adoption of open banking innovation among customers in Bangkok. We extend the unified theory of acceptance and use of technology 2 by incorporating a conceptual model of perceived security. The hypotheses of the conceptual model were subsequently assessed with partial least squares structural equation modelling using an online survey of 210 Bangkok consumers. Our finding reveals that open banking innovation adoption is directly influenced by performance expectations, social influence, price value, and perceived security. The hypothesis model has a significant amount of predictive ability, with an R2 of 51.3%. In addition, Q2 values demonstrated a moderate to high degree of predictability for open banking adoption.

Development and Practical Application of Hybrid Decision-Making Model for Selection of Third-Party Logistics Service Providers

Abstract In this study a problematic of logistics service provider selection is discussed. Traditional decision-making techniques are functionally limited and must be adjusted. Modern approach must be based on contemporary tools and information. The aim of this study is to develop a modern, industry-oriented decision-making model for selection of strategic logistics service providers. Main tasks of this study include: to perform critical analysis and comparison of multiple-criteria decision-making methods; to adapt decision-making framework for specific needs of selection of third-party logistics service providers; to collect and analyze industry data related to procurement projects; to develop modern decision-making model for selection of logistics service providers; to perform practical application of developed decision-making model based on collected industry data. The key novelties of this study are developed methodology for collection of industry data for decision-making process, developed hybrid decision-making model for selection of third-party logistics service provider, as well as application of the model. As the result, there is developed decision-making model for selection of 3PL service providers that includes 6 steps.

DMCLAEKS: Pairing-free designated-tester multi-recipient certificateless authenticated encryption with keyword search for concealing search patterns

Modern Industrial Internet of Things (IIoT) technologies, such as smart grids, 5G-enabled unmanned aerial vehicles (UAV), and supply chain 4.0, can be leveraged to promote intelligent management. Yet, IIoT systems create enormous volumes of data that must be outsourced to the cloud for storage and to provide end-users with search capabilities. The outsourcing of IIoT data to a third-party cloud service provider (CSP) creates a number of data leakage issues. Recently, Certificateless Authenticated Encryption with Keyword Search (CLAEKS) was proposed to address the issue of encrypted data querying in cloud-assisted IIoT. But so far, the majority of existing techniques depend on expensive bilinear pairing, and they are all single-receiver. In addition, these methods are extremely vulnerable to keyword guessing attacks and do not hide the search pattern, making it simple for an attacker to deduce the search content. In this paper, we present a rapid and trustworthy designed-tester multi-recipient CLAEKS (dMCLAEKS) protocol with the numerous advantages: (1) no expensive bilinear pairing procedures; (2) supporting for ciphertexts with multiple recipients; (3) defending against Inside Keyword Guess Attacks (IKGA); (4) incapability to determine search pattern. A comparative between our suggested scheme and other similar schemes is also offered to demonstrate that the proposed method is stronger overall.

Evaluation of the sustainability of party logistics service providers with failure modes and effects analysis method: its application in a company

Purpose- The purpose of this research is to increase customer satisfaction and business performance in the sector to eliminate failure situations of the processing phases of the departments of the business and to develop the quality of the system. The objective of this research is to enhance customer satisfaction and business performance by addressing and eliminating failure situations in the processing phases of the business departments and improving the quality of the system. To achieve this, the study focuses on evaluating third-party and fourth-party logistics service providers in the context of sustainability. While there are existing approaches to evaluate party logistics under general headings, there is a lack of specific studies focusing on companies operating in a single field. Therefore, this study aims to fill that gap by examining the business evaluation criteria of third-party and fourth-party logistics service providers for a white goods company in Turkey. Methodology- During the research, the concept of third-party logistics has gained attention within the scope of sustainability, the competition among organizations providing this service has become more intense, as have customer expectations. The research utilizes Failure Mode and Effects Analysis (FMEA) and Pareto Analysis (PA) to assess the sustainability of the supply chain and batch logistics for the company. Findings- As a result of the research, the findings in the direction of quality improvement-development within the scope of the service provided by the business are presented. The initial phase of process enhancement for logistics operations begins with the FMEA results. Development initiatives may begin if improvement initiatives are maintained. Development activities and resources ought to be distributed in accordance with this level of priority with regard to the first work that has to be performed to enhance the process. Conclusion- All risk considerations might not be realized inside a particular process since there are only a limited number of possibilities to be assigned for enhancement prosperity. By conducting risk prevention studies in accordance with the priorities that will be decided upon each period, it is intended to produce continuous improvement. Overall, while it may not be possible to address every risk, prioritizing risks and conducting risk prevention studies can help organizations achieve continuous improvement and increase their chances of success. Keywords: Failure Mode and Effects Analysis (FMEA), Pareto Analysis (PA), party logistics, quality, supply chain, sustainability. JEL Codes: 030, N01, L15, L21, L84

Dynamic modelling of cold chain logistics services under budget constraints for the delivery of fresh products in an urban area

The quality of perishable products declines continuously during the transportation process, rendering the delivery of a product with good freshness a challenging task in urban areas. We investigate how to plan activities to preserve the freshness level of products within a specific distance range. To this end, we construct an analytical model consisting of an online retailer and a third-party logistics service provider that loads the product from the retailer's fulfillment center and delivers it to various destinations with cold-chain logistics operations. The retailer seeks an appropriate balance between the delivery of good freshness, the farthest distance of delivery, and a limited budget for cold-chain logistics. We derive the optimal size of the area in which the freshness of products is maintained to the maximum possible level and the farthest distance that the retailer should consider when fulfilling online orders. This study includes three scenarios: in-house operation, outsourcing, and a hybrid mode. In outsourcing, the retailer pays a service fee based on the number of orders fulfilled within a specific area. The primary finding is that the retailer can choose an appropriate combination of the service fee rate and budget to control the scale of the area that guarantees good freshness. This finding has managerial significance, in that the ability to accurately predict and control the freshness by the distance range can reduce the occurrence of customers complaining about the quality of the delivered products.

An Access Control Scheme Based on Blockchain and Ciphertext Policy-Attribute Based Encryption.

Ciphertext policy-attribute-based encryption (CP-ABE), which provides fine-grained access control and ensures data confidentiality, is widely used in data sharing. However, traditional CP-ABE schemes often choose to outsource data to untrusted third-party cloud service providers for storage or to verify users' access rights through third parties, which increases the risk of privacy leakage and also suffers from the problem of opaque permission verification. This paper proposes an access control scheme based on blockchain and CP-ABE, which is based on multiple authorization centers and supports policy updating. In addition, blockchain technology's distributed, decentralized, and tamper-proof features are utilized to solve the trust crisis problem in the data-sharing process. Security analysis and performance evaluation show that the proposed scheme improves the computational efficiency by 18%, 26%, and 68% compared to previous references. The proposed scheme also satisfies the indistinguishability under chosen-plaintext attack (IND-CPA).

Understanding the effects of SMS marketing on consumers' attitude and purchase decision: An Empirical study on Bangladesh

Purpose: Telecom firms and businesses use short message marketing to convey information, advertise their products, and establish customer relationships. This study attempts to understand the effects of SMS marketing on consumer attitudes and purchase decisions from a Bangladeshi perspective. This study extends the Ducoffe model of advertising value (entertainment, informativeness, and irritation) by including two constructs: credibility and personalization. Research methodology: A total of 220 mobile phone users were surveyed using non-probability convenience sampling techniques and data were collected across Dhaka City, Bangladesh. The research model was analyzed using structural equation modeling (SEM). The PLS-SEM (Smart PLS 3.3.9) software was used for path modeling. Before conducting the SEM, this study performed a series of tests to assess the reliability and validity of the data. Results: The findings revealed that informativeness and credibility are the most decisive factors influencing consumer attitudes and purchasing decisions. Limitations: This study neglects privacy concerns, social impact, effort anticipation, and monetary incentives that are crucial to customer attitudes and SMS marketing purchase decisions. This study was conducted using data from a single city in Dhaka, Bangladesh, indicating that the findings are limited to that country's scenario. Contribution: The results of this research provide theoretical contributions to the existing research in this field of study and practical implications for marketing professionals, mobile operators, and third-party service providers in developing appropriate strategies and policies for SMS marketing.

Freshness-Keeping Strategy of Logistics Service Providers: The Role of the Interaction between Blockchain and Overconfidence

As a result of the increasing scrutiny of fresh products, greengrocers are now forced to concern themselves with the deterioration of their products’ freshness and employ blockchain technology as a tracing system. However, in the logistics system, the third-party logistics service provider (LSP) is motivated to be overconfident in order to extract extra profits, thus intensifying the dilemma faced by the fresh agricultural product industry. This paper focuses on the association between blockchain technology and overconfidence, in which the third-party LSP is supposed to overestimate the effect of the retailer’s freshness keeping measures. Differing from the previous literature, we analyze a situation wherein blockchain technology is adopted with explicit execution. Based on the optimal control model, we obtained three main conclusions: First, the overconfidence of a third-party LSP does not damage the logistics system but changes the freshness-keeping strategy of the retailer. Second, interestingly, although blockchain technology performs effectively when it is adopted as an initially established system with a freshness keeping strategy, it is not always a wise decision for managers to adopt a blockchain, especially when adopting it as a countermeasure for overconfidence. Third, we found that blockchain technology has a greater effect on freshness-keeping than overconfidence. Thus, in the fresh agricultural product industry, managers should adopt blockchain technology before overconfidence occurs and pay more attention to exogenous prices and freight to decide whether to adopt blockchain technology.

Identification and prioritization of the factors influencing blockchain adoption in the banking sector: integrating fuzzy AHP with TOE framework

PurposeThe objective of this research is to identify and prioritize the critical factors that influence the adoption of blockchain technology within the banking sector.Design/methodology/approachA well-known theoretical framework, the “Technology Organization Environment (TOE),” was chosen to analyze what criteria and sub-criteria affect blockchain adoption in the banking sector after a thorough assessment of the prior literature. Following that, 3 evaluation criteria and 14 sub-criteria were selected and verified using expert opinion. A survey design was created, and data for the study has been collected from various information technology (IT) managers/officers in the banking sector. A fuzzy analytic hierarchy process (Fuzzy-AHP) was then used to meet the purpose of the research.FindingsThe study identified that the organizational dimension is the most significant criteria for blockchain adoption in the banking sector, followed by the environmental dimension. In contrast, the technological dimension is the least influential criterion. Clientele pressure, IT resources, financial resources, pressure from competitors and relative advantage are the most influential sub-criteria for blockchain adoption.Research limitations/implicationsThis study provides valuable insights to bank managers, blockchain and IT developers, third-party service providers and policymakers. For instance, adopting the same blockchain platform is easier for both large and small banks for banking operations by using third-party service provider. At the same time, banks should have the banks' own core team to implement the blockchain-based systems or to have control over the third-party service providers during the adoption stage.Originality/valueTo the best of the authors' knowledge, no empirical studies have used a holistic organizational context to understand the factors influencing the adoption of blockchain technology from traditional to blockchain-based banking systems.

Fuzzy-based Misbehavior Detection for Internet of Things in Multi-access Edge Computing Environment

Today, an emerging paradigm of edge computing, called Multi-Access Edge Computing (MEC), is widely used in a broad range of applications. MEC has been recently used as a driving technology for 5G networks. However, MEC encompasses some security problems, such as communicating with untrusted third-party service providers commonly known as location-based service (LBS) providers. In this paper, we propose a novel fuzzy-based misbehavior detection system for Internet of Things (IoT) in a 5G-based MEC environment to solve the previous problems. Our proposed system is comprised of a multi-tier architecture that is linked by IoT gateways and mobile core network. In our architecture, we employ a novel mechanism that embeds a security entity called Regional Certificate Authority in a 5G macro base station. This security entity acts as a passport for the IoT gateway to communicate with other security entities present in our system that are located in the core infrastructure. Besides that, our system utilizes a distributed certificate revocation mechanism for malicious LBS providers via simultaneously updating the internal blocklists employed by more than one system entity. In addition, we adopt in our architecture a novel penalty system for malicious LBS providers, which is used for penalizing providers in case proved to be malicious as well as actively isolating them from the network. On the other hand, our system provides conditional anonymity for the incident’s reporter. Also, we present various security features maintained by the proposed system to thwart well-known attacks as well as we demonstrate efficiency and robustness of our system. Finally, we provide the overhead of our system and compare it with other state-of-the-art approaches where results show that the proposed system relatively incurs the least overhead.

CAMiSE: Content Addressable Memory-Integrated Searchable Encryption

Searchable symmetric encryption (SSE) is a special class of encryption schemes for computing directly over encrypted data. SSE aims to be significantly more efficient as compared to other solutions, such as fully homomorphic encryption (FHE), while leaking only minimal information to the adversary. SSE is particularly efficient and scalable for Boolean queries over large encrypted relational databases outsourced to third-party cloud service providers. However, practical implementations of SSE often suffer from performance bottlenecks due to randomised memory accesses for reads/writes and computation-intensive cryptographic operations. As a result, a gap exists today between theoretically efficient SSE algorithms and practically efficient SSE systems for real-world databases. In this paper, we address this longstanding open question that has otherwise hindered the widespread deployment of SSE over real cloud computing platforms. We propose –a fully associative memory-integrated framework for designing SSE systems with fast query processing over extremely large databases. We show a novel usage of custom-designed Content Addressable Memory (), together with robust data access policies, to bridge the memory wall in traditional SSE implementations by minimising storage-access latencies due to randomised look-up operations during searches. Coupled with dedicated hardware accelerators for cryptographic operations, achieves extremely fast and scalable query processing over encrypted relational databases. We prototype multiple well-known SSE algorithms and SSE data structures within our proposed framework. Our experiments show that these implementations achieve around <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5\times$</tex-math> </inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$7\times$</tex-math> </inline-formula> speed-up over traditional software-based implementations while scaling smoothly to extensive real-world databases with millions of records.