Open data is becoming increasingly important in research. While individual researchers are slowlybecoming aware of the value, funding agencies are taking the lead by requiring data be made available, and also by requiring data management plans to ensure the data is available in a useable form. Some journals also require that data be made available. However, in most cases, “available upon request” is considered sufficient. We describe a number of historical examples of data use and discovery, then describe two current test cases at the University of New Mexico. The lessons learned suggest that an instituional data services program needs to not only facilitate fulfilling the mandates of granting agencies but to realize the true value of open data. Librarians and institutional archives should actively collaborate with their researchers. We should also work to find ways to make open data enhance a researchers career. In the long run, better quality data and metadata will result if researchers are engaged and willing participants in the dissemination of their data.

Aim/Purpose: This study was designed to examine the effectiveness of mentor’s work with immigrant children and adolescents at risk, using the Elements Way. Background: The New Media offers our “screen kids” a lot of information, many behavioral models, and a new type of social communication. The Elements Way is an educational method designed to enhance openness, development, breakthroughs, goal achievement, and transformation in the age of media and social networks. Methodology: The Elements Way was developed following research on communication in the diversified media, especially new media such as Facebook, WhatsApp, and television reality shows, and the study is an examination of the effectiveness of mentors’ work with immigrant children and adolescents at risk, using the Elements Way. All mentors had been trained in the Elements Way. The study population included 640 mentors working with immigrants’ children in Israel. The work was conducted in 2010-2013. The mixed-methods approach was selected to validate findings. Contribution: Empowering children and enhancing their ability to cope; Creating openness and sharing, making children more attentive to the significant adults in their lives; Supporting children who face the complex reality that characterizes our age. Findings: Significant differences were found in the mentors’ conduct with the children. Work programs were designed and implemented with care and consistency, and mentors succeeded in generating change within the children and achieving desired goals. Of the 640 participating mentors, 62 were not able to promote the child, and interviews with them revealed that their work with the children was not consistent with the Elements Way and began from a different vantage point. Recommendations for Practitioners: Success factors: Self-awareness and awareness of one’s surroundings. Empathy. Willingness to engage in significant interactions. Self-cleansing and self-reflection. Ability to engage in a personal and interpersonal dialogue. Ability to accept and contain the child. Cooperation with the child in creating a work program and assisting the child to achieve the goals that were set in the program. Recommendation for Researchers: Future studies should focus on analyzing the discussions of children and adolescents, to add depth to our insights regarding children and adolescents’ perception of the mentors’ work from their perspective. Impact on Society: Finding the “keys” to openness, development, goal achievement, and transformation in our work with “screen kids.” Future Research: Studies that are designed to examine the effectiveness of mentor’s work with immigrant children and adolescents at risk, using the Elements Way.

Aim/Purpose: Little is known of the cultural competence or leadership styles of a minority owned newspaper. This autoethnography serves to benchmark one early 1990s example. Background: I focused on a series of flashbacks to observe an African American weekly newspaper editor-in-chief for whom I reported to 25 years ago. In my reflections I sought to answer these questions: How do minorities in entrepreneurial organizations view their own identity, their cultural competence? What degree of this perception is conveyed fairly and equitably in the community they serve? Methodology: Autoethnography using both flashbacks and article artifacts applied to the leadership of an early 1990s African American weekly newspaper. Contribution: Since a literature gap of minority newspaper cultural competence examples is apparent, this observation can serve as a benchmark to springboard off older studies like that of Barbarin (1978) and that by examining the leadership styles and editorial authenticity as noted by The Chicago School of Media Theory (2018), these results can be used for comparison to other such minority owned publications. Findings: By bringing people together, mixing them up, and conducting business any other way than routine helped the Afro-American Gazette, Grand Rapids, proudly display a confidence sense of cultural competence. The result was a potentiating leadership style, and this style positively changed the perception of culture, a social theory change example. Recommendations for Practitioners: For the minority leaders of such publications, this example demonstrates effective use of potentiating leadership to positively change the perception of the quality of such minority owned newspapers. Recommendations for Researchers: Such an autoethnography could be used by others to help document other examples of cultural competence in other minority owned newspapers. Impact on Society: The overall impact shows that leadership at such minority owned publications can influence the community into a positive social change example. Future Research: Research in the areas of culture competence, leadership, within minority owned newspapers as well as other minority alternative publications and websites can be observed with a focus on what works right as well as examples that might show little social change model influence. The suggestion is to conduct the research while employed if possible, instead of relying on flashbacks.

Aim/Purpose. The aim of this study is to propose a teaching approach based on AI-based chatbot agents and to determine whether the use of this approach increases the students’ motivation. Background. Today, chatbots are an integral part of students’ lives where they are used in various contexts. Therefore, we are interested in incorporating these tools into our teaching process in order to profit from their benefits, assist and guide students while working with to prevent issues such as plagiarism and mainly to boost students’ motivation. Methodology. Using the proposed approach, new chatbot based learning activities were de-signed in three different courses for computer science engineering students. A mixed-method experimental study was conducted to evaluate students’ impression and satisfaction. Survey results of the students (N=58) who participated in the experiment (experimental group) were compared to the results of the students from the control group (N=60). Contribution. Trending AI conversational agents can be engaged in daily teaching activities as a learning assistant and coach to boost students motivation and skills development. Findings. Our study focuses on the impact of chatbots on student’s motivation. The study aimed to analyze the benefits and drawbacks associated with these conversational chatbots. Our findings revealed the significant role that chatbots can play in enhancing student motivation and improving teaching practices.

Efficient knowledge and information management is essential for companies to prosper in the rapidly changing global environment. This article presents challenges of a large Finnish multinational company relating to their current knowledge and information management practices and systems. The focus is on New Product Introduction (NPI) process. The study is based on interviews and facilitated workshops in the Research and Development (R&D) and Production departments. Furthermore, the identified challenges are reflected to the findings presented in knowledge and information management literature. The results gained from the company case study were well in line with the findings in the literature. Three main topics, which can be generalized to cause challenges for knowledge and information management in most companies, were recognized: 1) Issues related to human behavior, individual characteristics and capabilities, different backgrounds, and professional vocabulary; 2) Codifying tacit knowledge into explicit information, which can be saved to company information system; 3) Lack of interoperability between different information systems. The study provides the management of the case company, and other similar organizations, focus points while seeking for better knowledge and information management. From a scientific perspective, the main contribution of this article is to give practical examples of how the theoretical findings presented in literature manifest themselves in real industrial practices.

Aim/Purpose: In this research, we examined the influence of the information system (IS) quality dimensions proposed by Wixom and Todd on reading satisfaction of online newspaper readers in Bangladesh, especially the readers’ intention to revisit and recommendations through electronic word-of-mouth (eWOM). Background: We identified the top 50 most visited websites, of which 13 were online newspapers, although their ranking among Bangladesh online newspapers varies from month to month. The literature illustrates that, despite the wide availability of online news portals and the fluctuations in frequency of visits, little is known about the factors that affect the satisfaction, word-of-mouth, and frequency of visits of readers. An understanding of reader satisfaction will help to gain richer insights into the phenomenon of readers’ intention to revisit and recommendation by eWOM. Stakeholders of online newspapers can then focus on those factors to increase visits to their websites, which will help them attract online advertisements from different organisations. Methodology: Data were collected using a structured questionnaire, from 217 people who responded to the survey. We used SmartPLS 3 to analyze the data collected, as it is based on second-generation analysis, which in turn is based on structural equation modeling (SEM). Contribution: This research explores the impacts of technological dimensions on readers’ satisfaction, as most of the previous research has focused on cultural or social dimensions. Findings: The results supported all of the hypothesized relationships between technological dimensions and reader satisfaction with online newspapers, except for one. The first, information, was predicted with accuracy and completeness, while the second object-based belief, system quality, was predicted by its accessibility, flexibility, reliability, and timeliness. Overall, quality factors influencing readers’ satisfaction were shown to lead to word-of-mouth revisit intentions. Our proposed model was empirically tested and has contributed to a nascent body of knowledge about readers’ revisit intentions and eWOM recommendations regarding online newspapers. It was also shown that strong satisfaction leads to higher revisit intention and eWOM. Recommendations for Practitioners: To keep the users satisfied, online newspapers need to focus on improving information quality (IQ) and system quality (SQ). If they do this well, they will be rewarded with higher revisit intention and recommendations by eWOM. Recommendation for Researchers: This study extends Oh’s customer loyalty model by integrating the Wixom-Todd model. This study reinforces an alternative rationale of the construct satisfaction. Future Research: We ignored negative stimulus like technostress, which can have an impact on satisfaction. In future, we will test the relationship between technostress and its impact on online newspaper reading.

Aim/Purpose: The aim of this study was to analyze various performance metrics and approaches to their classification. The main goal of the study was to develop a new typology that will help to advance knowledge of metrics and facilitate their use in machine learning regression algorithms Background: Performance metrics (error measures) are vital components of the evaluation frameworks in various fields. A performance metric can be defined as a logical and mathematical construct designed to measure how close are the actual results from what has been expected or predicted. A vast variety of performance metrics have been described in academic literature. The most commonly mentioned metrics in research studies are Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), etc. Knowledge about metrics properties needs to be systematized to simplify the design and use of the metrics. Methodology: A qualitative study was conducted to achieve the objectives of identifying related peer-reviewed research studies, literature reviews, critical thinking and inductive reasoning. Contribution: The main contribution of this paper is in ordering knowledge of performance metrics and enhancing understanding of their structure and properties by proposing a new typology, generic primary metrics mathematical formula and a visualization chart Findings: Based on the analysis of the structure of numerous performance metrics, we proposed a framework of metrics which includes four (4) categories: primary metrics, extended metrics, composite metrics, and hybrid sets of metrics. The paper identified three (3) key components (dimensions) that determine the structure and properties of primary metrics: method of determining point distance, method of normalization, method of aggregation of point distances over a data set. For each component, implementation options have been identified. The suggested new typology has been shown to cover a total of over 40 commonly used primary metrics Recommendations for Practitioners: Presented findings can be used to facilitate teaching performance metrics to university students and expedite metrics selection and implementation processes for practitioners Recommendation for Researchers: By using the proposed typology, researchers can streamline development of new metrics with predetermined properties Impact on Society: The outcomes of this study could be used for improving evaluation results in machine learning regression, forecasting and prognostics with direct or indirect positive impacts on innovation and productivity in a societal sense Future Research: Future research is needed to examine the properties of the extended metrics, composite metrics, and hybrid sets of metrics. Empirical study of the metrics is needed using R Studio or Azure Machine Learning Studio, to find associations between the properties of primary metrics and their “numerical” behavior in a wide spectrum of data characteristics and business or research requirements

Aim/Purpose: The purpose of this study is to investigate the mechanism of the front/back-office structure affecting new service development (NSD) performance and examine the role of knowledge transfer in the relationship between front/back-office structure and NSD. Background: The separation of front and back-office has become the prevailing trend of the organizational transformation of modern service enterprises in the digital era. Yet, the influence of front and back-office separation dealing with new service development has not been widely researched. Methodology: Building on the internal social capital perspective, a multivariate regression analysis was conducted to investigate the impact of front/back-office structure on the NSD performance through knowledge transfer as an intermediate variable. The data was collected through a survey questionnaire from 198 project-level officers in the commercial banking industry of China. Contribution: This study advances the understanding of front/back-office structure’s influence mechanism on new service development activity. It reveals that knowledge transfer plays a critical role in bridging the impact of front and back-office separation to NSD performance under the trend of digitalization of service organizations. Findings: This study verified the positive effects of front/back-office social capital on NSD performance. Moreover, knowledge transfer predicted the variation in NSD performance and fully mediated the effect of front/back-office social capital on NSD performance. Recommendations for Practitioners: Service organizations should optimize knowledge transfer by promoting the social capital between front and back-office to overcome the negative effect organizational separation brings to NSD. Service and other organizations could explore developing an internal social network management platform, by which the internal social network could be visualized and dynamically managed. Recommendation for Researchers: The introduction of information and communications technology not only divides the organization into front and back-office, but also reduces the face-to-face customer contact. The impacts of new forms of customer contact to new service development and knowledge transfer between customer and service organizations call for further research. Along with the digital servitization, some manufacturing organizations also separate front and back-offices. The current model can be applied and assessed further in manufacturing and other service sectors. Impact on Society: The conclusion of this study guides us to pay attention to the construction of social capital inside organizations with front/back-office structure and implicates introducing and developing sociotechnical theory in front/back-office issue undergoing technological revolution. Future Research: As this study is based on the retail banking industry, similar studies are called upon in other service sectors to identify differences and draw more general conclusions. In addition, as the front and back-offices are being replaced increasingly by information technology such as artificial intelligence (AI), it is necessary to advance the research on front/back-office research with a new theoretical perspective, such as sociotechnical theory.

Aim/Purpose: In this study, the research proposes and experiments with a new model of collecting, storing, and analyzing big data on customer feedback in the tourism industry. The research focused on the Vietnam market. Background: Big Data describes large databases that have been “silently” built by businesses, which include product information, customer information, customer feedback, etc. This information is valuable, and the volume increases rapidly over time, but businesses often pay little attention or store it discretely, not centrally, thereby wasting an extremely large resource and partly causing limitations for business analysis as well as data. Methodology: The study conducted an experiment by collecting customer feedback data in the field of tourism, especially tourism in Vietnam, from 2007 to 2022. After that, the research proceeded to store and mine latent topics based on the data collected using the Topic Model. The study applied cloud computing technology to build a collection and storage model to solve difficulties, including scalability, system stability, and system cost optimization, as well as ease of access to technology. Contribution: The research has four main contributions: (1) Building a model for Big Data collection, storage, and analysis; (2) Experimenting with the solution by collecting customer feedback data from huge platforms such as Booking.com, Agoda.com, and Phuot.vn based on cloud computing, focusing mainly on tourism Vietnam; (3) A Data Lake that stores customer feedback and discussion in the field of tourism was built, supporting researchers in the field of natural language processing; (4) Experimental research on the latent topic mining model from the collected Big Data based on the topic model. Findings: Experimental results show that the Data Lake has helped users easily extract information, thereby supporting administrators in making quick and timely decisions. Next, PySpark big data processing technology and cloud computing help speed up processing, save costs, and make model building easier when moving to SaaS. Finally, the topic model helps identify customer discussion trends and identify latent topics that customers are interested in so business owners have a better picture of their potential customers and business. Recommendations for Practitioners: Empirical results show that facilities are the factor that customers in the Vietnamese market complain about the most in the tourism/hospitality sector. This information also recommends that practitioners reduce their expectations about facilities because the overall level of physical facilities in the Vietnamese market is still weak and cannot be compared with other countries in the world. However, this is also information to support administrators in planning to upgrade facilities in the long term. Recommendation for Researchers: The value of Data Lake has been proven by research. The study also formed a model for big data collection, storage, and analysis. Researchers can use the same model for other fields or use the model and algorithm proposed by this study to collect and store big data in other platforms and areas. Impact on Society: Collecting, storing, and analyzing big data in the tourism sector helps government strategists to identify tourism trends and communication crises. Based on that information, government managers will be able to make decisions and strategies to develop regional tourism, propose price levels, and support innovative programs. That is the great social value that this research brings. Future Research: With each different platform or website, the study had to build a query scenario and choose a different technology approach, which limits the ability of the solution’s scalability to multiple platforms. Research will continue to build and standardize query scenarios and processing technologies to make scalability to other platforms easier.

The emergence of service ecosystems can accelerate the industrial renewal required because of urgent global challenges. However, existing research has not sufficiently grasped the social dynamics of coevolution in ecosystems that enhance industrial renewal. This study aimed to advance ecosystem research through a practice lens and to present the key characteristics of industrial service ecosystem practice involved in industrial renewal. Consequently, its three characteristics - <i>accomplishment</i>, <i>attractiveness</i> and <i>actionability</i> - were configured based on an abductive study derived from the ecosystem literature, three practice-oriented approaches to learning, and two case ecosystem examinations. These features created the logic for resource integration and enhanced ecosystems to evolve as units, thus exceeding the actors' independent avenues of renewal. The findings of this study provided a deeper understanding of the coevolution in ecosystems needed to accelerate industrial renewal as well as a novel conceptualisation of an <i>ecosystem-as-practice</i> for further studies.

In recent years, schools (as well as universities) have added cyber security to their computer science curricula. This topic is still new for most of the current teachers, who would normally have a standard computer science background. Therefore the teachers are trained and then teaching their students what they have just learned. In order to explore differences in both populations’ learning, we compared measures of software quality and security between high-school teachers and students. We collected 109 source files, written in Python by 18 teachers and 31 students, and engineered 32 features, based on common standards for software quality (PEP 8) and security (derived from CERT Secure Coding Standards). We use a multi-view, data-driven approach, by (a) using hierarchical clustering to bottom-up partition the population into groups based on their code-related features and (b) building a decision tree model that predicts whether a student or a teacher wrote a given code (resulting with a LOOCV kappa of 0.751). Overall, our findings suggest that the teachers’ codes have a better quality than the students’ – with a sub-group of the teachers, mostly males, demonstrate better coding than their peers and the students – and that the students’ codes are slightly better secured than the teachers’ codes (although both populations show very low security levels). The findings imply that teachers might benefit from their prior knowledge and experience, but also emphasize the lack of continuous involvement of some of the teachers with code-writing. Therefore, findings shed light on computer science teachers as lifelong learners. Findings also highlight the difference between quality and security in today’s programming paradigms. Implications for these findings are discussed.

Aim/Purpose: In the modern world, simulation has become a new phenomenon in education, which conveys new and innovative ideas of curriculum, instruction, and classroom management. It makes certain of Aristotle’s words when he said that “The things we have to learn before we do them, we must learn by doing them”. One might think that simulation in education is one of these technologies. This study examined preservice and new teachers’ perceptions about the con-cept of conflict and educational conflict management in a simulation workshop conducted at the Academic Arab College’s Simulation Center in Haifa, Israel. Background: Simulation engages learners in “deep learning” and empowers their understanding. In other words, simulation provides an alternative real world experience. As part of our work at the Educational Simulation Center in the Arab Academic College in Haifa, Israel, we examined the performance and contribution of educators who visit the center and participate in educational conflict management simulation workshops. Methodology: A mixed methods study was conducted. A total of 237 participants of preservice teachers from diverse professions were divided into 15 groups to examine the research question: How does the experience of participating in a simulation workshop affect preservice teachers’ perception about the concept of conflict? Contribution: This study seeks to contribute to simulation and conflict management in education. This contribution to the body of literature can help researchers, scholars, students, and education technology professionals to advance simulation research studies. Findings: The study findings indicate that there is a high degree of satisfaction (more than 90%) among preservice teachers in participating in the workshop. It also indicates a positive and significant change in participants’ perceptions of the concept of conflict and the management of conflict situations. Recommendations for Practitioners: In light of the study findings, it is recommended that new teachers be exposed to simulation workshops with a variety of scenarios dealing with different conflict situations. This exposure could contribute to their professional development and conduct in a more efficient and convenient manner in schools.

Aim/Purpose: In the light of the recent attention to the role of social media in the dissemination of fake news, it is important to understand the relationship between the characteristics of the social media content and re-sharing behavior. This study seeks to examine individual level antecedents of information re-sharing behavior including individual beliefs about the quality of information available on social network sites (SNSs), attitude towards SNS use and risk perceptions and attitudes. Methodology: Testing the research model by data collected through surveys that were adminis-tered to test the research model. Data was collected from undergraduate students in a public university in the US. Contribution: This study contributes to theory in Information Systems by addressing the issue of information quality in the context of information re-sharing on social media. This study has important practical implications for SNS users and providers alike. Ensuring that information available on SNS is of high quality is critical to maintaining a healthy user base. Findings: Results indicate that attitude toward using SNSs and intention to re-share infor-mation on SNSs is influenced by perceived information quality (enjoyment, rele-vance, and reliability). Also, risk-taking propensity and enjoyment influence the intention to re-share information on SNSs in a positive direction. Future Research: In the dynamic context of SNSs, the role played by quality of information is changing. Understanding changes in quality of information by conducting longitudinal studies and experiments and including the role of habits is necessary.

The present paper identifies a variety of conceptual schemes that have emerged within informing science and consider how they might be applied to fake news. The paper begins with a brief overview of fake news. This is followed presentations of various models identified in a two-volume survey of informing science. The models presented include those dealing with extrinsic (i.e., environmental) complexity, informing transitions, and individual resonance. The potential implications for informing science research into fake news are discussed and questions that may warrant future research are raised. The paper then concludes by describing what current informing science may already be telling us about fake news, its spread and its influence. Through its analysis of the fake news and informing science literature, a number of questions are identified where informing science can possibly contribute to our understanding of fake news. These include: • Does fake news need to disinform its clients if it is to be effective? • Why are certain groups of individuals particularly credible when it comes to communicating fake news? • Under what circumstances will the emotional and social motivations to accept fake news exceed our concern for its truth? • How does the nature of the fake news content and objectives impact the disinformer’s choice of channel? • What are the circumstances under which radically transitional fake news might have an impact?

Aim/Purpose: Many disciplines have addressed the issue of “fake news.” This topic is of central concern to the transdiscipline of Informing Science, which endeavors to understand all issues related to informing. This paper endeavors to build a model to address not only fake news but all informing and misin-forming. To do this, it explores how errors get into informing systems, the issue of bias, and the models previously created to explore the complexity of informing. That is, this paper examines models and frameworks proposed to explore informing in the presence of bias, misinformation, disinformation, and fake news from the perspective of Informing Science. It concludes by intro-ducing a more nuanced model that considers some of the topics explored in the paper Methodology: The issue of informing and disinforming crosses many disciplinary perspectives. Each discipline puts on blinders that limit what it can contribute to its understanding of research topics. It is like trying to study a forest by seeing only the trees and not the animals or the animals but not the trees. Research perspectives that cross disciplinary boundaries are needed to more fully understand complex phenomena. This paper lays out some fundamental cross-disciplinary issues including how errors find their way into informing systems, the issue of bias, and the frameworks used to model this phenomenon. Contribution: The paper introduces the competition framework for understanding informing and misinforming. This framework addresses many of the limitation of prior frameworks. Future Research: The concluding framework offers insights into understanding informing and disinforming. But this framework offers no insights into other forms of informing that are less well explored, such as song, dance, physical art, and architecture. Likewise, this framework does nothing to help the un-derstanding of informing via fideism or psychedelic revelation.

Aim/Purpose: This series of papers on Fake News: Bias, Misinformation, and Disinformation examines fake news from an Informing Science perspective. As such, the papers in this special series make novel con-tributions to the field by viewing the issues through the transdisciplinary lens of informing science. This series makes no claim to summarize or review all that has been written on this topic. Rather it provides a glimpse into this immense literature from the perspective of informing science. Background: It is one small step on the 20+ year quest by the editor to explore better ways to inform from an approach that transcends academic disciplines (Cohen, 1998, 1999) and a 20 year quest to under-stand the issues of how we become misinformed and disinformed (Cohen, 2000). The series pro-vided here gains thrust for two reasons. One reason is that the study has become more popular with academicians due to the blathering of politicians and the attacks by national powers on de-mocracy. The second reason is more mundane; without the deadline that the end-of-year affords, the papers would become richer, fuller, and more detailed. Recommendation for Researchers: Taken together, the results brought forth across these papers is truly scary. Due to their biases, when presented with information, people can and do generate their own misinformation. People tend to communicate such misinformation that they self-generated with others in groups sharing their beliefs, strengthening the misinformation by some and silencing those do not share these thoughts. This process creates divisions in society. How can humanity seek wise decisions when we cannot agree even upon the facts. We see the results of this syndrome in Operation SIG and cur-rent divisions within politics in the West.

Aim/Purpose: Cyberbullying (CB) is an ongoing phenomenon that affects youth in negative ways. Using online news articles to provide information to schools can help with the development of comprehensive cyberbullying prevention campaigns, and in restoring faith in news reporting. The inclusion of online news also allows for increased awareness of cybersafety issues for youth. Background: CB is an inherent problem of information delivery and security. Textual analysis provides input into prevention and training efforts to combat the issue. Methodology: Text extraction and text analysis methods of term and concept extraction; text link analysis and sentiment analysis are performed on a body of news articles. Contribution: News articles are determined to be a major source of information for comprehensive cyberbullying prevention campaigns. Findings: Online news articles are relatively neutral in their sentiment; terms and topic extraction provide fertile ground for information presentation and context. Recommendation for Researchers: Researchers should seek support for research projects that extract timely information from online news articles. Future Research: Refinement of the terms and topics analytic model, as well as a system development approach for information extraction of online CB news.

Data envelopment analysis (DEA) is widely used in various fields and for various models. Inverted data envelopment analysis (inverted DEA) is an extended model of DEA. Regression analysis (RA) is a statistical process for estimating the relationships among variables based on the model of averaged image. There are no essential relations among DEA and RA and inverted DEA. We creatively combine DEA, RA and inverted DEA to propose a new model: DEA-RA-Inverted DEA model. The model realises the efficiency estimation and evaluation through a discussion of the residual variables and the residual ratio coefficients. In addition, we will demonstrate the effectiveness of the model by applying it to efficiency estimation and evaluation of 16 Chinese logistics enterprises.

Product innovation has become a crucial part of the sustainability of the coconut agro-industry in Indonesia, covering upstream and downstream sides. To overcome this challenge, it is necessary to create several model stages using a hybrid method that combines machine learning based on multiple criteria decision making and mass balance analysis. The research case study was conducted in Tembilahan district, Riau province, Indonesia, one of the primary coconut producers in Indonesia. The analysis results showed that potential products for domestic customers included coconut milk, coconut cooking oil, coconut chips, coconut jelly, coconut sugar, and virgin coconut oil. Furthermore, considering the experts, the most potential product to be developed was coconut sugar with a weight of 0.26. Prediction of coconut sugar demand reached 13,996,607 tons/year, requiring coconut sap as a raw material up to 97,976,249.

N/A -- no abstracts in FTEs I believe