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This study aims to evaluate enterprise technology innovation capability in prefabricated construction (PC) from an input-output perspective, using six integrated enterprises in China as cases.

An evaluation system for enterprise technology innovation capability in PC was constructed, including total input, technology output (TO) and project output. All the evaluation indexes were quantified, and the subject and object indexes weights were determined using the fuzzy cognitive map and information entropy, respectively. The final scores and ranks were evaluated through gray relational analysis (GRA) based on the combined weights.

It was found that enterprise technology innovation capability in PC was low in China, with its unbalanced development in different dimensions and the poorest performance in TO, currently.

This research has developed an evaluation system for technology innovation capability in PC at the enterprise level and scientifically quantified all the indexes, which is a breakthrough over existing studies. The GRA model based on the combined weights proposed in this study can be applied to other comparable fields and regions, with its easy operation.

This study aims to propose a hybrid technology evaluation process integrating the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique and the analytic network process (ANP) with novel MCDM method for the organic light emitting diode (OLED) technology evaluation. The DEMATEL is used to detect and build the complex network relationship map (NRM) among dimensions/criteria. The ANP is employed to conduct the dependence and feedback among criteria and to decide the relative weights of the criteria by super‐matrix. The combination of DEMATEL technique and ANP with novel MCDM method is used to perform for constructing a technology evaluation structure.

This study proposes a hybrid approach integrating the DEMATEL and the ANP to construct a technology evaluation and decision‐making model for OLED. Taiwan is a research base in this study. This is for the purpose of offering an example as to how a technology firm or even a country can evaluate or position certain emerging technology in the process of resource investment decision‐making.

This study suggests a hybrid technology evaluation approach integrating the DEMATEL technique and the ANP approach. When policy makers and R&D planners design R&D programs in emerging technology fields, the authors' proposed model can help to assess whether it is worth investing in the expected technology or not, for all concerned. Besides, using Taiwan's OLED as an example, this study has generated a conclusion comprising several strategic suggestions and managerial implications.

The whole approach developed by this study can serve as a reference to construct an evaluation framework to evaluate other technology fields in order to propose some guidance for R&D planning or strategy making in the industry applied the aimed technology. The weights distributed to the prospects and the problems can also serve as a reference of whether the R&D investment in the new technology is worthwhile for all concerned. Future research can adopt the approach proposed in this study to evaluate the worth of R&D investment in other targeted technologies.

The purpose of this paper is to establish a maturity evaluation model for the application of construction steel structure welding robotics suitable for the actual situation and specific characteristics of engineering projects in China and then to assess the maturity level of the technology in the application of domestic engineering projects more scientifically.

The research follows a qualitative and quantitative analysis method. In the first stage, the structure of the maturity model is constructed and the evaluation index system is designed by using the ideas of the capability maturity model and WSR methodology for reference. In the second stage, the design of the evaluation process and the selection of evaluation methods (analytic hierarchy process method, multi-level gray comprehensive evaluation method). In the third stage, the data are collected and organized (preparation of questionnaires, distribution of questionnaires, questionnaire collection). In the fourth stage, the established maturity evaluation model is used to analyze the data.

The evaluation model established by using multi-level gray theory can effectively transform various complex indicators into an intuitive maturity level or score status. The conclusion shows that the application maturity of building steel structure welding robot technology in this project is at the development level as a whole. The maturity levels of “WuLi – ShiLi – RenLi” are respectively: development level, development level, between starting level and development level. Comparison of maturity evaluation values of five important factors (from high to low): environmental factors, technical factors, management factors, benefit factors, personnel and group factors.

In this paper, based on the existing research related to construction steel structure welding robot technology, a quantitative and holistic evaluation of the application of construction steel structure welding robot technology in domestic engineering projects is conducted for the first time from a project perspective by designing a maturity evaluation index system and establishing a maturity evaluation model. This research will help the project team to evaluate the application level (maturity) of the welding robot in the actual project, identify the shortcomings and defects of the application of this technology, then improve the weak links pertinently, and finally realize the gradual improvement of the overall application level of welding robot technology for building steel structure.

This paper seeks to propose a collaborative process for evaluating, piloting and selecting, new and emerging educational technologies. It aims to promote discussion about how such an evaluative process can be inclusive of interdisciplinary stakeholders and envision the actual application of these technologies in real teaching and learning contexts across disciplines.

The methodology applied in the piloting and evaluation of new educational technologies involves the design and identification of learning activities, the development of evaluation criteria which map to the goals of the learning activities and stakeholders' needs, and the incorporation of the technology‐enabled activities into the total course design.

Evaluation methodologies that involve interdisciplinary stakeholders collaborating on a software pilot expose participants to multiple perspectives and divergent views. The evaluation of new educational technologies within a teaching and learning context is more effective in exposing the benefits and weaknesses of the technology than a conventional software pilot.

The new educational technologies evaluation methodology proposed in this paper has only been fully applied in three product pilots and is still in its developmental stage. The research is limited to the evaluation of educational software, not the implementation of new educational technologies.

The re‐iterative and time‐consuming process of piloting and evaluating new educational technologies within a course context is one in which academics require pedagogical, technological and administrative support. This paper presents a methodology that ensures each of these varieties of support is included.

With the rapid expansion of new, sometimes costly educational technologies, universities can benefit from employing evaluation techniques based within an educational context, and ensure that their investments in these tools make an effective contribution to the enhancement of teaching and learning.

This study aims to investigate the effectiveness of a theory-driven realist evaluative research approach to better understand complex technology implementations in organizations.

An institution wide e-learning implementation of lecture capture (LC), within a UK University, was chosen, and a realist evaluation framework was used, tailored for educational technology. The research was conducted over four, increasingly focused, evaluation cycles combining engagement analytics, user interviews and theory to refine what works (or does not work), for whom, in which contexts and why.

Despite explicit demand and corresponding investment, overall student engagement is lower than expected. Increased student use appears linked to particular staff attitudes and behaviours and not to specific disciplines or course content. The main benefits of LC are providing reassurance to the majority, aiding revision and understanding for the many and enabling catch-up for the few. Recommendations for future research are based on some unexpected outcomes uncovered, including evolving detrimental student behaviours, policy development based on technological determinism and future learner-centred system development for next-generation LC technologies.

The realist approach taken, and evaluation framework used, can be adopted (and adapted) for future evaluative research. Domain specific reference models, categorizing people and technology, supported analysis across multiple contexts.

This study responds to a call for more theory-based research in the field of educational technology. The authors demonstrate that a theory-driven approach provides real and practical recommendations for institutions and allows for greater insight into the political, economic and social complexity of technology implementation.

There are five factors acting as a barrier to the effective evaluation of educational technology (edtech), which are as follows: premature timing, inappropriate techniques, rapid change, complexity of context and inconsistent terminology. The purpose of this paper is to identify new evaluation approaches that will address these and reflect on the evaluation imperative for complex technology initiatives.

An initial investigation of traditional evaluative approaches used within the technology domain was broadened to investigate the evaluation practices within social and public policy domains. Realist evaluation, a branch of theory-based evaluation, was identified and reviewed in detail. The realist approach was then refined, proposing two additional necessary steps to support mapping the technical complexity of initiatives.

A refined illustrative example of a realist evaluation framework is presented, including two novel architectural edtech domain reference models to support mapping.

Recommendations include building individual evaluator capacity; adopting the realist framework; the use of architectural edtech domain reference models; phased evaluation to first build theories in technology “context” and then iteratively during complex implementation chains; and community contribution to a shared map of technical and organisational complexity.

This paper makes a novel contribution by arguing the imperative for a theory-based realist approach to help redefine evaluative thinking within the IT and complex system domain. It becomes an innovative proposal with the addition of two domain reference models that tailor the approach for edtech. Its widespread adoption will help build a shared evidence base that synthesizes and surfaces “what works, for whom, in which contexts and why”, benefiting educators, IT managers, funders, policymakers and future learners.

The paper's aim is to provide a tool for decision makers to make more informed decisions regarding their investment in advanced technologies.

Selection of an advanced technology for adoption requires evaluation of several competing alternatives. The difficulty in the evaluation process arises when the ranking of the alternatives is not possible from the result of the financial analysis alone. The purpose of this study is to overcome such difficulty by considering other factors that allows distinction among alternatives with similar economic evaluation results. This is accomplished by identifying the risks or undesirable consequences of technology implementation and including them in the evaluation process. These are costs that are not measurable for inclusion in the financial analysis but could have major impact on the final selection. Owing to uncertainties involved with adoption of a new technology, the involvement of human expertise and judgment seems to be essential in the evaluation process. To accomplish this a process is proposed where decision maker's perceptions on the performance of technology alternatives along with the importance of the relevant risks are solicited in linguistic terms. Fuzzy numbers are then used to represent these linguistic perceptions. Fuzzy arithmetic operators are applied to calculate an aggregate fuzzy score for each alternative. These fuzzy scores are then converted to crisp scores to allow the ranking and selection of the best alternative.

Addition of subjective perceptions to the purely quantitative approach provides a more realistic evaluation process.

The proposed procedure can help practitioners with their technology adoption decisions.

The value of the paper is the inclusion of the decision maker's judgment in the evaluation process by use of fuzzy logic.

Community informatics can be defined as a strategy or discipline that focuses on the use of information and communication technologies by territorial communities. This paper analyzes the emerging community informatics evaluation literature to develop an understanding of the indicators used to gauge project impacts in community networks and community technology centers. This study finds that community networks and community technology center assessments fall into five key areas: strong democracy; social capital; individual empowerment; sense of community; and economic development opportunities. The paper concludes by making recommendations for future community informatics evaluations.

Due to technology advancement or transparency in system, there is a constant inflow and outflow of technology in the business for transparency and efficiency. To seize a competitive advantage, companies have emerged new technological solutions to respond to the change in the organization environment. There is a surge in the requirement of learning opportunities and effective training programs in the organization. The current study has been an effort to understand the potential of blockchain technology that can create better training evaluation.

The electronic-Delphi (e-Delphi) method has been conducted by recording the final consensus and to find a balance for implementation of blockchain technology and measuring training effectiveness. The current research is one of its new types where blockchain-enabled training effectiveness measurement (BETEM) model has been formulated using a qualitative approach.

The study has considered human resource (HR) professionals as the experts and based on their responses, the formulation of theoretical network model has been structured using e-Delphi–BETEM (e-DLH–BETEM) approach. By critically examining the experts’ responses and comments, the study formulated the four major themes and 11 subthemes for the smooth functioning of the BETEM for an organization.

The research aims to aid innovations in BETEMs model for training evaluation. The model will contribute incrementally toward the complete transformation of the training development programs of employees. The goal of BETEMs is to ensure that organizations, specifically HR personals can prepare themselves to have competitive advantage by using blockchain technology.

The application of blockchain technology in measuring the training effectiveness is an addition to existing literature as majority of existing studies have studied the use of technology for measuring training effectiveness.

Visual analytics is increasingly becoming a prominent technology for organizations seeking to gain knowledge and actionable insights from heterogeneous and big data to support decision-making. Whilst a broad range of visual analytics platforms exists, limited research has been conducted to explore the specific factors that influence their adoption in organizations. The purpose of this paper is to develop a framework for visual analytics adoption that synthesizes the factors related to the specific nature and characteristics of visual analytics technology.

This study applies a directed content analysis approach to online evaluation reviews of visual analytics platforms to identify the salient determinants of visual analytics adoption in organizations from the standpoint of practitioners. The online reviews were gathered from Gartner.com, and included a sample of 1,320 reviews for six widely adopted visual analytics platforms.

Based on the content analysis of online reviews, 34 factors emerged as key predictors of visual analytics adoption in organizations. These factors were synthesized into a conceptual framework of visual analytics adoption based on the diffusion of innovations theory and technology–organization–environment framework. The findings of this study demonstrated that the decision to adopt visual analytics technologies is not merely based on the technological factors. Various organizational and environmental factors have also significant influences on visual analytics adoption in organizations.

This study extends the previous work on technology adoption by developing an adoption framework that is aligned with the specific nature and characteristics of visual analytics technology and the factors involved to increase the utilization and business value of visual analytics in organizations.

This study highlights several factors that organizations should consider to facilitate the broad adoption of visual analytics technologies among IT and business professionals.

This study is among the first to use the online evaluation reviews to systematically explore the main factors involved in the acceptance and adoption of visual analytics technologies in organizations. Thus, it has potential to provide theoretical foundations for further research in this important and emerging field. The development of an integrative model synthesizing the salient determinants of visual analytics adoption in enterprises should ultimately allow both information systems researchers and practitioners to better understand how and why users form perceptions to accept and engage in the adoption of visual analytics tools and applications.