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This article is the second part of the research on the institutional evaluation of the open universities. The title of the first one was ‘Evaluation Standards for Institutional Evaluation of Open Universities,’ which was presented at the 22nd AAOU Annual Conference, Tianjin, China. In the previous study we discussed the definition of university evaluation and some of the controversial points in the existing evaluation. The focal point was that the existing standards and indexes are not appropriate for Korea National Open University (KNOU) as an open university, and that it is necessary to establish a new evaluating system for the university. We believe it is true of the other open universities throughout Asia and the world. In short, the present research provides the practical and effective data on the evaluation standard. It also includes some new qualitative, quantitative and modified evaluation indexes reflecting the distinctive features of the open universities. The main part of this article elaborates on 5 evaluation domains, 23 evaluation sections, 81 evaluation items and 229 evaluation indexes. These evaluation domains, sections, items and indexes result from the practical surveys and AHP and Swing analyses. The result of this research will prove a good and essential element for ranking indicators in ODE universities. At the end of the paper we add some new standards and indexes for evaluating regional campuses of the open universities, which is another important agenda for upgrading the learner support throughout the country.

This paper explores the roles of institutional research (IR) units in higher education, examining both internal and external responsibilities and demands. The purpose of this paper is to encourage a broader strategic discussion of the missions and capacities of such academic institutional entities.

The methodology employed begins with a review of relevant literature, followed by critical observations of an experienced reflective practitioner. Beginning with the premise that academic institutions are central, the paper discusses the external environment of institutions and the requirements placed on their internal IR operations. A core question is presented: research for whom? Both traditional and alternative organizational models are discussed in this light. The paper then explores ways in which data needs might be aligned in order to provide accountable, useful and transparent information to all stakeholders, internal and external.

Findings show that the linking of internal information needs with those of external actors is key to effective operations; that IR units should seek to be a bridge between their institution and its environment so that effective information can be provided to all who need it. The paper is not designed as a detailed operational roadmap, but rather to highlight issues for examination within the context of specific institutional and agency situations.

Its originality stems from the focus on such linkages and the call for organizational leaders to recognize the full value of IR both within and across organizational boundaries.

This study delves into the psychological processes underlying sport fans' post-purchase innovativeness behaviour. This exploratory research aims to establish a theoretical framework that elucidates the formation of sport fans' word-of-mouth (WOM) behaviours, particularly emphasising the structural relationship between motivated consumer innovativeness and satisfaction in using AR live-streaming services.

Utilising an online survey and convenience sampling, the study garnered a total of 243 usable responses from three online baseball fan communities in South Korea. Confirmatory factor analysis was employed to assess the psychometric properties of the constructs. Subsequently, a structural equation model was used to probe the influence of motivated consumer innovativeness on WOM, with a particular focus on the mediating role of satisfaction.

Three dimensions of motivated sport fans innovativeness – functional, hedonic and cognitive – showed a positive association with WOM, partly mediated by satisfaction. In contrast, socially motivated sport fans innovativeness did not directly lead to WOM but influenced it solely through satisfaction. The full mediating role of satisfaction in the relationship between socially motivated fans innovativeness and WOM was found.

This research stands out as one of the scant studies exploring motivated sport fans innovativeness in the context of AR live sport streaming. The findings not only corroborate but also augment the extant literature by empirically confirming that three dimensions of motivated fans innovativeness, coupled with satisfaction, are pivotal antecedents to WOM intention.

This paper is motivated by the need to assess the risk profiles associated with the substantial number of items within military supply chains. The scale of supply chain management processes creates difficulties in both the complexity of the analysis and in performing risk assessments that are based on the manual (human analyst) assessment methods. Thus, analysts require methods that can be automated and that can incorporate on-going operational data on a regular basis.

The approach taken to address the identification of supply chain risk within an operational setting is based on aspects of multiobjective decision analysis (MODA). The approach constructs a risk and importance index for supply chain elements based on operational data. These indices are commensurate in value, leading to interpretable measures for decision-making.

Risk and importance indices were developed for the analysis of items within an example supply chain. Using the data on items, individual MODA models were formed and demonstrated using a prototype tool.

To better prepare risk mitigation strategies, analysts require the ability to identify potential sources of risk, especially in times of disruption such as natural disasters.

To recover the growing deficit between American and near-peer mobile artillery ranges, the US Army is exploring the use of the M982 Excalibur munition, a family of long-range precision projectiles. This paper aims to analyze the effectiveness of the M982 in comparison to the M795 and M549A1 projectiles to further the understanding of what this new asset contributes.

Based upon doctrinal scenarios for target destruction, a statistical analysis is performed using Monte Carlo simulation to identify a likely probability of kill ratio for the M982. A values-based hierarchical modeling approach is then used to differentiate the M982 from similar-type projectiles quantitatively in terms of several different attributes. Finally, sensitivity analyzes are presented for each of the value attributes, to identify areas where measures may lack robustness in precision.

Based upon a set of seven value measures, such as maximum range, effective range, the expected number of rounds to destroy a target, and the unit cost of a munition, the M982 1a-2 was found to be best suited for engaging point and small area targets. It is noted, however, that the M795 and M549A1 projectiles are likely better munition options for large area targets. Hence, an integrated targeting plan may best optimize the force’s weapon systems against a near-peer adversary.

The findings provide initial evidence that doctrinal adjustments in how the Army uses its artillery systems may be beneficial in facing near-peer adversaries. In addition, the values-based modeling approach offered in this research provides a framework for which similar technological advances may be examined.

Data has become a factor of production. This occurs when history enters the era of big data, in which technologies such as artificial intelligence, cloud computing and blockchain are used to collect, manipulate, mine and process data. Data is a special product of labor, a sub-derivative of other production factors.

The data factor has a dual attribute: being physical (technical) and social. The social attribute of the data factor can not only materialize the technical attribute but also amplify it. In other words, the data has a multiplication effect on the allocation efficiency of other production factors. The social attribute of the data is brought out via the technical attribute as the medium. From a technical perspective, this medium is strongly adhesive, and after being bonded with other factors of production, it will only lead to a physical reaction and not change the nature of other factors.

However, once these two attributes interact with each other, especially when data is combined with capital, the most adhesive factor in the market economy, a series of new social relations will then be produced based on the technical attribute, resulting in significant adjustments in social relations, involving both positive and negative externalities.

Therefore, to get a scientific understanding of the dual attribute and its interaction effects on the data factor, it is necessary to take the following steps. We should promote institutional design that amplifies the positive externality, with a focus on facilitating public data sharing and improving the value of commercial data development. Also, we need to strengthen institutional arrangements that prevent and control the negative externality by emphasizing data supervision based on data types and levels as well as the rule of law.