Science Research Paradigm Research Articles

Responsible Artificial Intelligence in Healthcare: Predicting and Preventing Insurance Claim Denials for Economic and Social Wellbeing

It is estimated that one out of seven health insurance claims is rejected in the US; hospitals across the country lose approximately $262 billion annually due to denied claims. This widespread problem causes huge cash-flow issues and overburdens patients. Thus, preventing claim denials before claims are submitted to insurers improves profitability, accelerates the revenue cycle, and supports patients’ wellbeing. This study utilizes Design Science Research (DSR) paradigm and develops a Responsible Artificial Intelligence (RAI) solution helping hospital administrators identify potentially denied claims. Guided by five principles, this framework utilizes six AI algorithms – classified as white-box and glass-box – and employs cross-validation to tune hyperparameters and determine the best model. The results show that a white-box algorithm (AdaBoost) model yields an AUC rate of 0.83, outperforming all other models. This research’s primary implications are to (1) help providers reduce operational costs and increase the efficiency of insurance claim processes (2) help patients focus on their recovery instead of dealing with appealing claims.

Public services: a standard process model following a structured process redesign

PurposeDespite widespread adoption of business process reengineering (BPR) for better delivery efficiency of public services, a structured approach continues to elude the most value-adding phase of BPR: business process redesign. From another viewpoint, the rising currency of Whole-of-Government (WoG) and “shared services” initiatives signal an unmissable trend toward resource reuse across public service agencies (PSAs) through business process standardization (BPS). This research invokes BPS into process redesign to produce a process redesign framework (PRF) and deploys the same to build a standard process model (SPM) for services of the government of Albania (GoA).Design/methodology/approachThe methodology follows the design science research (DSR) paradigm, wherein best practices extracted from literature are synthesized with stakeholder inputs to design the PRF and SPM, both of which are then evaluated with case study research.FindingsAdoption of PRF/SPM on a WoG basis will not only reduce service lead time but also enable a variety of public services to share the same process, thereby further saving costs for GoA. The research outputs will accelerate reengineering and subsequent digitalization of public service operations.Research limitations/implicationsImplementing SPM will maximize resource reuse and help offer uniform and integrated public services to GoA's customers. It will also enable demand-driven staff mobilization across GoA agencies. The proposed PRF/SPM have limitations in that they consider only flow aspects of service processes with aspects of conversion being ignored.Originality/valueThis research fulfills the need for a systematic approach to process redesign and prepares GoA for a WoG treatment to its BPR efforts.

From interdisciplinary to interdisciplinarity: American cases and implications

<p indent="0mm">At present, under the complex background of scientific research paradigm change and fierce global competition, interdisciplinary has attracted more and more attention. In 2020, China’s education department and scientific research funding department have added interdisciplinary in their respective discipline layout, which is of landmark significance for China’s scientific development. However, we still lack experience in establishing and operating the system of interdisciplinary in the future. The United States has a relatively advanced system and referable experience in the development of interdisciplinary, so this paper takes the interdisciplinary layout of American National Science Foundation and American Department of Education as cases to organize the institutional setup, functions and proposal mechanism of interdisciplinary in American National Science Foundation, and to summarize the code changes, change criteria and degree awarding of interdisciplinary in Classification of Instructional Programs. From the perspective of the development logic and evolutionary connotation of interdisciplinary: (1) There is tension between the dynamic development and the institutional guarantee about interdisciplinary; (2) strengthening disciplinary collaboration can promote interdisciplinary cooperation; (3) cultivating the concept of multi-agent cooperation is beneficial to problem-oriented research; they are the logical implication of interdisciplinary. Finally, some suggestions are put forward for the future development of interdisciplinary in China. (1) To cultivate interdisciplinary ideas through forward-looking layout; (2) to solve practical problems by summarizing interdisciplinary scientific questions from different fields; (3) to give enough space for development through flexible management; (4) to improve the organizational mechanisms that are conducive to the development of interdisciplinary. They will be helpful for China to gradually move from interdisciplinary to interdisciplinarity.

Reform, application and challenges of utilizing big data in coal mine safety management research

Big data greatly impact current social science research paradigms and traditional safety management. Moreover, widespread big data application in coal mine safety technology has also highlighted the lack of basic coal mine safety management review against the background of big data. Based on the above analysis, the three main article goals are (1) to study the fundamental safety management research changes within the big data context; (2) to analyze big data application in coal mine safety management; and (3) to discuss big data relevance in coal mine safety management development trends and challenges. In summary, integrating big data into coal mine safety management has become a research trend, and the current coal mine safety management theory in the field of big data requires more in-depth research.

Idea Recommendation in Open Innovation Platforms: A Design Science Approach

Collaborative crowdsourcing communities help firms obtain ideas generated by the public at a lower cost compared to those generated in-house. However, the growth of these communities has led to a large influx of ideas of mixed quality, which has made it difficult for firm experts to select and implement ideas. In this paper we propose a novel theoretical framework to (1) extract important features from a collaborative crowdsourcing community and (2) apply them to the practice of recommending ideas that are most likely to be implemented in the future. More specifically, we adopt the design science research paradigm, introduce the knowledge persuasion model as the kernel theory, operate users’ persuasive attempts and firm experts’ persuasive coping, and identify a rich set of features as predictors of the likelihood of idea implementation. We test our prediction framework on a large-scale collaborative crowdsourcing community. The results of our data analysis show that the proposed framework is effective and efficient in predicting the likelihood of idea implementation. To increase the interpretability of the prediction model, we also implement the SHapley Additive exPlanations (SHAP) analysis and discuss the relationships between important features and idea implementation. We conclude by discussing the theoretical and practical implications of these findings.

Enterprise-grade protection against e-mail tracking

E-mail tracking provides companies with fine-grained behavioral data about e-mail recipients, which can be a threat for individual privacy and enterprise security. This problem is especially severe since e-mail tracking techniques often gather data without the informed consent of the recipients. So far e-mail recipients lack a reliable protection mechanism.This article presents a novel protection framework against e-mail tracking that closes an important gap in the field of enterprise security and privacy-enhancing technologies. We conceptualize, implement and evaluate an anti-tracking mail server that is capable of identifying tracking images in e-mails via machine learning with very high accuracy, and can selectively replace them with arbitrary images containing warning messages for the recipient. Our mail protection framework implements a selective prevention strategy as enterprise-grade software using the design science research paradigm. It is flexibly extensible, highly scalable, and ready to be applied under actual production conditions. Experimental evaluations show that these goals are achieved through solid software design, adoption of recent technologies and the creation of novel flexible software components.

Can't touch this? Conceptualizing the customer touchpoint in the context of omni-channel retailing

Due to the rise of omni-channel management, the customer touchpoint concept has become more important. However, research lacks a common understanding of this concept. This article addresses this research gap by conceptualizing the customer touchpoint following the design science research paradigm. As a result, an overview of the constructs and their respective properties, as well as their possible manifestations that collectively define the customer touchpoint, is provided. The conceptualization has implications for researchers and practitioners alike as it comes as a tool to design and evaluate touchpoints in the field as well as to provide fertile soil for future research.

Predictive data analytics for contract renewals: a decision support tool for managerial decision-making

PurposePredictive analytics and artificial intelligence are perceived as significant drivers to improve organizational performance and managerial decision-making. Hiring employees and contract renewals are instances of managerial decision-making problems that can incur high financial costs and long-term impacts on organizational performance. The primary goal of this study is to identify the Major League Baseball (MLB) free agents who are likely to receive a contract.Design/methodology/approachThis study used the design science research paradigm and the cognitive analytics management (CAM) theory to develop the research framework. A dataset on MLB's free agents between 2013 and 2017 was collected. A decision support tool was built using artificial neural networks.FindingsThere are clear links between a player's statistical performance and the decision of the player to sign a new offered contract. “Age,” “Wins above Replacement” and “the team on which a player last played” are the most significant factors in determining if a player signs a new contract.Originality/valueThis paper applied analytical modeling to personnel decision-making using the design science paradigm and guided by CAM as the kernel theory. The study employed machine learning techniques, producing a model that predicts the probability of free agents signing a new contract. Also, a web-based tool was developed to help decision-makers in baseball front offices so they can determine which available free agents to offer contracts.

An Intelligent Framework for the Evaluation of Compliance with the Requirements of ISO 9001:2015

A quality management system (QMS) allows an organization to analyze the needs of its customers and to define the appropriate processes for efficient production and service delivery. Customer satisfaction is an important part of this system, with a significant impact on its corporate sustainability. The purpose of this research is a proposal for assessing whether the QMS of an organization meets the requirements defined in the standard ISO 9001:2015. The development of the proposal follows a methodology based on the paradigm of design science research where we identify the problem and the motivation and the objectives are defined as a solution to the problem, and as a consequence, we developed an expert system based on a previously identified ISO 9001:2015 process map and transferred it to a knowledge base. The system allows the determination of the degree of compliance with the requirements of the standard: this provides valuable information to organizations, allowing them to implement improvement measures. The expert system is limited in terms of the set of identified inputs, outputs, and acceptance criteria, but its effectiveness was demonstrated through the evaluation of the system.

Replay-peak attention chart: A performance measure for improving online video lecture design

The ability to replay selected video segments is a major advantage of online video lectures. Replay is a learning instance that reflects active engagement. This paper develops the ‘replay-peak attention chart’ as a new performance measure of learner’s attention, based on the control chart concept, which is used for Statistical Process Control (SPC) in operations management. This study follows the design science research paradigm and employs a mixed methods methodology, combining quantitative learning analytics with qualitative analysis of notable segment replay instances by viewers of online video lectures. An analysis of a successful Massive Open Online Course (MOOC), titled “Negotiation Management” provides a proof-of-concept for the replay-peak attention chart, as a visual heuristic tool for identifying notable learning instances. The MOOC includes Educational Entertainment (edutainment) in the form of negotiation simulations which are presented as sitcoms, and are meant to increase learner engagement. From an attention economy perspective, the replay-peak attention chart may help instructors and designers to focus their limited attention resources on segments of online video lecture sessions that may require pedagogical interventions. This paper critically discusses the replay-peak attention chart conceptualization and its initial proof-of-concept. It suggests future research directions for substantiating the replay-peak attention chart, and investigating the effect of edutainment on online learning. The replay-peak attention chart is a dynamic descriptive performance measure, which has a promising potential to improve the design of effective online video lectures as an e-learning resource.

Enhancing Traceability in Clinical Research Data through a Metadata Framework

The clinical research data lifecycle, from data collection to analysis results, functions in silos that restrict traceability. Traceability is a requirement for regulated clinical research studies and an important attribute of nonregulated studies. Current clinical research software tools provide limited metadata traceability capabilities and are unable to query variables across all phases of the data lifecycle. To develop a metadata traceability framework that can help query and visualize traceability metadata, identify traceability gaps, and validate metadata traceability to improve data lineage and reproducibility within clinical research studies. This research follows the design science research paradigm where the objective is to create and evaluate an information technology (IT) artifact that explicitly addresses an organizational problem or opportunity. The implementation and evaluation of the IT artifact demonstrate the feasibility of both the design process and the final designed product. We present Trace-XML, a metadata traceability framework that extends standard clinical research metadata models and adapts graph traversal algorithms to provide clinical research study traceability queries, validation, and visualization. Trace-XML was evaluated using analytical and qualitative methods. The analytical methods show that Trace-XML accurately and completely assesses metadata traceability within a clinical research study. A qualitative study used thematic analysis of interview data to show that Trace-XML adds utility to a researcher's ability to evaluate metadata traceability within a study. Trace-XML benefits include features that (1) identify traceability gaps in clinical study metadata, (2) validate metadata traceability within a clinical study, and (3) query and visualize traceability metadata. The key themes that emerged from the qualitative evaluation affirm that Trace-XML adds utility to the task of creating and assessing end-to-end clinical research study traceability.

RETRACTED ARTICLE: Intelligent Crime Prevention and Control Big Data Analysis System Based on Imaging and Capsule Network Model

With the rapid development of China’s national economy, the effects of traditional public security management methods have been greatly weakened, and various new types of criminal activities have continued to occur. Social development has gradually separated from the previous model, and new social contradictions have become prominent. These social contradictions not only impact the lifestyle of ordinary individuals, but also affect the development of society. The data contains the laws of social development and crime governance. How criminal governance adapts to the big data wave has become the key to carrying out the number management in the three-dimensional security prevention and control. The data culture has promoted the transformation of the social governance model and has also led to the transformation of the social science research paradigm. At present, most of the research on big data is only from the perspective of informatics, and there is not much discussion about big data from the legal system level. With the advent of the era of big data, a series of problems have come along. In addition to strengthening the security of the big data operation process at the technical level, it is necessary to strengthen research from a technical level. In this paper, we propose a smart crime prevention and control big data analysis system based on machine Internet of Things and industrial object system. The experimental results show that the proposed method has higher data collection rate and crime prevention and control efficiency.

Cloud computing ecosystem model: evaluation and role clusters

Several significantly different attempts have been undertaken to visualize the complex and opaque cloud computing ecosystem by a descriptive model. Recently, scholars have developed a new role-based cloud ecosystem model (Passau Cloud Computing Ecosystem Model (PaCE model)) based on a systematic analysis and synthesis of the previous models. However, its scientific evaluation is still outstanding. The main goal is therefore to conduct an evaluation regarding its structural equivalence and completeness compared to the real cloud business according to the design science research paradigm. The second goal is to demonstrate the model’s usefulness by using it as an instrument for the identification of role clusters, which are frequently covered by organizations. To this end, a cross-sectional analysis is conducted, in which 758 organizations are manually analysed and matched with the model’s current roles. As a result, roles have been newly added, removed, broken down into sub-roles, abstracted to a meta-role and renamed. The cluster analysis unveiled five role clusters. Whereas some roles were predominantly found as single role, further roles were exclusively or very frequently found in combination with others. Overall, the revised model creates, compared to the common rather technically orientated market overviews by market research institutes, a detailed categorization schema helping to understand and investigate the organizations belonging to the cloud ecosystem.

Traditional Chinese medicine for ulcerative colitis: systematic reviews based on PRIO-harms

This article is aimed to reevaluate the systematic reviews(Meta-analysis) of traditional Chinese medicine in the treatment of ulcerative colitis, and provide reference for evidence-based decision-making of traditional Chinese medicine(TCM). According to the preferred reporting items for overviews(preferred reporting items for overview of systematic reviews, PRIO-harms), the main Chinese and English electronic literature databases(PubMed, Cochrane Library, EMbase, CNKI, CBM, etc.) were retrieved, supplemented by manual retrieval. Systematic reviews for the treatment of ulcerative colitis with Chinese medicine up to February 2019 were included. Two researchers independently performed literature screening and data extraction. The methodology quality, reporting quality and evidence quality of the literature were evaluated by AMSTAR 2 tool, PRISMA scale and GRADE system respectively. Subgroup analysis was performed by using RevMan 5.3 software. A total of 21 systematic reviews were included, and the interventions mainly included TCM internal and external treatment, with 53 outcome indicators. The AMSTAR 2 results showed that 5 articles were of high quality, 9 of medium quality, 4 of low quality, and 3 of extremely low quality. The most problematic items were as follows: the list of excluded documents was not provided; the sources of funding for each study were not reported; and the research methods were not determined before implementation. PRISMA scale had an average score of(20.38±1.43) points, less than 22 points for 15 articles, with certain reporting defects. The GRADE system suggested that the quality of the evidence for the 30 outcome indicators was low or very low. The most important factors leading to degrading was the limitation, followed by publication bias and inconsistency. The results showed that as compared with conventional Western medicine, TCM oral or enema treatment for mild to moderate ulcerative colitis had better clinical efficacy and safety. Due to the quality limitations of the included studies, it is necessary to further strengthen the top-level design and follow the scientific research paradigm to provide a higher level of evidence for the clinical evidence-based decision-making of TCM.

The Fourth Paradigm of Scientific Research and Social Sciences and Humanities

The Fourth Paradigm of Scientific Research and Social Sciences and Humanities

ADOPTION OF SOCIAL MEDIA AND MANAGEMENT OF LESSONS LEARNED IN IT PROJECT

This research explores the gap in the management of lessons learned (MLL) in an Information Technology project (IT), validating a model (named Target) with the support of wiki platform in a medium-sized company in the IT industry. This model supports the following MLL processes: awareness, collection, verification, storage, dissemination and reuse. This study adopts the paradigm of the Design Science Research and the Technical Action Research method to instantiate the Target model in the implementation phase of an IT project. The practical implications can be seen in the company's learning to introduce the MLL, improve design productivity, increase employee collaboration and better disseminate knowledge.

Access to Opioids in Palliative Care in Low-and Middle-Income Countries : The Case of Burkina-Faso -How Can Blockchain and Internet of Things Assist? –

Background: People requesting palliative care or suffering from pain are subjected to adhere to opioid-based treatment in order to alleviate their pain. Commonly, access to opioids is strictly controlled. Access to Healthcare delivery services remains challenging in Low-and Middle-Income Countries (LMIC). In Burkina-Faso (BF), a Sub-Saharan African (SSA) country, patients requiring palliative care (PC) are especially facing poor access to pain drugs such as morphine. Facing poor access to pain-alleviating medicine can severely impact the daily quality of life (QoL). On one hand, patients are experiencing poor opioids access. On another hand opioids abuse, leading to drug addiction is noticed. The question arising here is how can they face poor access and at the same time abuse the given drug? One plausible answer is the counterfeit chain, which provides illegal drugs. Beyond the counterfeit issues faced, the public health care system is also facing, amongst others, prescription falsification, fraud in the distribution, and stock shortage. Method & Design: Mixed-Method-Design was applied to this study. National stipulations, regulations, and the state-of-the-art in the field of palliative care in BF were investigated and analyzed. Based on the investigation‘s outcomes and following the paradigm of design science research, and information system based improvement solution is proposed to tackle the poor access to opioids, improve the supply and distribution chain as well as to efficiently monitor the consumption of opioids in BF, and prevent patients from any health issues, drug addiction, and death. Objectives: The main objectives are to fight against opioid addiction, counterfeits, a stock shortage, and prevent related health safety issues. The main aim is to enable the traceability of any opioids prescription, secure the supply and distribution, and thus early detect any fraud in the system. This editorial paper would, therefore, focus on investigating the reasons underlying the poor access to opioids in palliative care in BF and make suggestions for improvement. A blockchain (BC) and the Internet of Things (IoT) based system to secure and improve opioids supply, distribution, and prescription will be proposed. Results: The contribution analysis reveals the potential of the proposed model to assist in many ways to improve access to opioids and to secure this access. The model could contribute to preventing drug abuse, overprescription, supporting off-label-use of opioids and thus providing a knowledge database for off-label use of opioids. This model shows promise to deliver accurate data and information about the exact opioid’s needs and consumption atlas. This will assist to better distribute the product in the entire country. A proof-of-concept of the proposed model is required. This is ongoing and will be presented in a forthcoming paper. Conclusion: This editorial paper investigates access to opioids in Burkina Faso. It pointed out by analyzing out the computer science perspectives the different causes of the crisis. A contextualized model is provided. A test in situ needs to be performed.

TOWARDS DESIGNING AN ARTEFACT EVALUATION STRATEGY FOR HUMAN FACTORS ENGINEERING: A LEAN IMPLEMENTATION MODEL CASE STUDY

Applying scientific methods to the evaluation of design science research artefacts is necessary to recognise the design process as design science research. Prior work has reported on this crucial evaluation component; however, limited information and guidance are available on the practices that should be followed. In this study, the framework for evaluation in design science and the elaborated action design research method in the design science research paradigm were used to develop an alternative evaluation strategy for a human factors engineering artefact. A different scientific method was used to design an evaluation episode for each of the elaborated action design research iterations: (1) a gap analysis, (2) a systematic literature review, (3) an applied thematic analysis, (4) a design requirements traceability matrix, and (5) the Delphi technique. The validity of the research design was proven using design science research guidelines, action design research principles, and a research validation matrix. This evaluation strategy indicated how the strategic use of different kinds of scientific evaluations assisted in establishing the quality of the knowledge delivered by the design science process. This study has contributed to the field of (human factor) engineering by providing a pragmatic approach to solving abstract, people-related problems in industry.

A Networked Analysis and Engineering Framework for New Business Models

New technological possibilities and paradigm shifts from product-centered to service-centered offerings are one of the main drivers of business models. Business ventures today are more and more networked. Often, various partners are needed to deliver a service or product to frequently cross-linked customers with sometimes bi- or even multi-variant roles. Furthermore, business models are embedded in socio-technical systems where different kinds of needs and values of all actors, including social, ecological, technical and economic values, have to be balanced. The resulting complex network of actors, needs and values requires continuous management in order to create and operate viable and sustainable business models. This paper proposes a multi-layer framework to analyze existing business models as well as to shape new business ventures in a networked and values-based way and to support the identification of tacit network effects within business ecosystems. Based on an existing multi-layered analysis toolkit, focusing on legal and business dynamics aspects, an enhanced visualization and analysis tool is proposed that focuses especially on ethical, social and environmental aspects to foster the creation of (strongly) sustainable business models. The research process to create the presented approach followed the Design Science Research paradigm by applying argumentative-deductive analysis (ADA) and first applications in real-world case studies. A practical case from an international Open Source Software (OSS) project serves as an example to illustrate this values-based visualization and analysis layer and its benefits for managers and decision makers in the area of business model and information system management.

Towards a Stakeholder-Oriented Blockchain-Based Architecture for Electronic Health Records: Design Science Research Study.

BackgroundData security issues still constitute the main reason for the sluggish dissemination of electronic health records (EHRs). Given that blockchain technology offers the possibility to verify transactions through a decentralized network, it may serve as a solution to secure health-related data. Therefore, we have identified stakeholder-specific requirements and propose a blockchain-based architecture for EHRs, while referring to the already existing scientific discussions on the potential of blockchain for use in EHRs.ObjectiveThis study aimed to introduce blockchain technology for EHRs, based on identifying stakeholders and systematically eliciting their requirements, and to discuss the key benefits (KBs) and key challenges (KCs) of blockchain technology in the context of EHRs.MethodsThe blockchain-based architecture was developed in the framework of the design science research paradigm. The requirements were identified using a structured literature review and interviews with nine health care experts. Subsequently, the proposed architecture was evaluated using 4 workshops with 15 participants.ResultsWe identified three major EHR stakeholder groups and 34 respective requirements. On this basis, we developed a five-layer architecture. The subsequent evaluation of the artifact was followed by the discussion of 12 KBs and 12 KCs of a blockchain-based architecture for EHRs. To address the KCs, we derived five recommendations for action for science and practice.ConclusionsOur findings indicate that blockchain technology offers considerable potential to advance EHRs. Improvements to currently available EHR solutions are expected, for instance, in the areas of data security, traceability, and automation by smart contracts. Future research could examine the patient’s acceptance of blockchain-based EHRs and cost-benefit analyses.