Platforming for industrialized building: a comparative case study of digitally-enabled product platforms

Digitally-enabled product platforms are becoming prominent approaches for industrialized building. Such a platform is a collection of common and stable modules and interfaces that can derive products effectively using digital delivery. The usage of construction product platforms has been studied in the existing buildings literature; however, there is relatively less on firms’ strategies of platform elements for platforming, which encompasses both the development and deployment of a digitally-enabled product platform. This paper examines how construction firms strategize for platforming, through a comparative case study approach with nine international case firms. Findings indicate that three typologies platforms that firms implemented: those rely on a kit of parts only; those have also developed structured interfaces; and those have also established design rules. Inferring from findings, this paper articulates the influential role of customer requirement certainties across multiple market segments in shaping these strategies. By offering a novel classification of platforming strategies under varied certainties of customer requirements across market segments, this paper contributes to the research on construction product platforming strategies. This has implications for practitioners and opens new areas for research, taking the characteristics of customer requirements within or across market segments into account in strategic decision-making on digitally-enabled product platforms

Quality Management in Hospitals: Does it Contribute to High Quality of Care?

Health policy-makers all around the world are facing the problem of ever-increasing costs in health care. In additio n, the demand for high quality care is greater than ever. Since there is no indication that these trends will stop in the near future, the policy-makers have to find methods to mitigate these problems. One possible solution is the development of efficient quality strategies, including external quality assessment and improvement systems that focus on clinical effectiveness, the implementation of evidence based practice, patient safety programs and clinical audit. The aim of this paper is to identify and summ arize research studies which investigate the impact of different quality strategies and quality improvement methods on healthcare activities and outcomes, and to determine if these are effective clinical methods or not. For this reason, a systematic search was carried out in various databases. The literature suggests that having an external quality assessment system does contribute to better health care. However, most of the studies focus on accreditation alone, and only three relatively low sample studies compare accreditation with ISO certification. Related to clinical-effectiveness, limited relevant results were found. Health policy-makers should consider different quality models as valid methods to provide high quality of care in hospitals, but they should also be aware that the clinical effectiveness of these has not yet been proven. More outcome-oriented, high sample studies should be carried out which compare one technique to another and find out if some of them could be implemented simultaneously

5g and Iot digital era: the transformation of mobile network operators into end-to-end solution providers

The forthcoming 5G and IoT large-scale implementation reveals new business opportunities in completely new sectors that mobile network operators should seize. This survey paper wants to identify the necessary transformations such operators must undergo to build a sustainable competitive advantage in the future industry. A qualitative research composed of semi-structured interviews incumbents’stronger intent of diversification and creates the base for strategic recommendations.A sample of recent actions carried out by mobile network operators to improve their position in the 5G and IoT environments is shown at the end of the work

Database of Video Games and Their Therapeutic Properties

There are reported to be 2.96 billion video game players in the world as of 2021 and this number is expected to grow to 3.32 billion by the year 2024. Of that total, 215.5 million video game players live in the United States with a reported average age of 33 years old. Thousands of commercial video games are released every year. There is evidence to support video game technology use as therapeutic media however it predominately utilizes outdated technology or technology designed for a specific purpose also called “serious games.” The problem is that OT practitioners are unaware of the potential therapeutic properties of video games they have not played, so are unable to integrate unfamiliar video games as therapeutic media in clinical practice. The purpose of this capstone project is to develop an online database of commercial video games, and their therapeutic properties, to facilitate their use as therapeutic media in OT practice. To address this problem a webpage was developed in partnership with the Family Gaming Database that cataloged 10 commercial video games from commercially available video game subscription services and the Nintendo Switch. The 10 games were subject to an activity analysis based on the AMPS to determine their therapeutic potential. The resulting webpage contains three main lists in which filters can be applied in order to display games that meet a specific desired criterion. Applicable filters include platform, age rating, difficulty, and specific accessibility features. Keywords: database, occupational therapy, video game, video game

Design perspectives on diabetes management games

For decades, there has been scholarly interest in the use of serious digital games to assist individuals suffering from diabetes with the self-management of that disease. However, previous research in this area has not effectively integrated the knowledge of the expert game designer. This dissertation aims to further understandings of design approaches to serious games for diabetics by confronting both the arguments of the diabetes games literature and the diabetes games themselves with the experiences and opinions of expert game designers. The arguments of the diabetes games literature were synthesized into a design template composed of twenty-four interrelated desirable elements. This template was then used by three focus groups consisting of a total of twelve expert game designers to both evaluate six diabetes self-management games and respond to the assertions of the diabetes games literature. The findings from these three empirical studies indicate both that the diabetes games themselves are of uniformly unsuitable quality and that the diabetes games literature is rife with what the expert game designers consider to be problematic assumptions. The problems identified by the focus groups include those that fundamentally cripple the functionality of the game artifact, those that are embedded in a game’s rules and themes, and those to those that exist at superficial levels. Furthermore, the focus groups had an overall negative reaction to the arguments about games that they found to be deeply embedded in the design template’s elements. Tensions exist, however, between the reasons for the diabetes games literature’s demand for certain game features and the beliefs of the expert game designers. The findings strongly suggest that additional research is necessary and that an interdisciplinary effort, including both health care professionals and expert game designers, is necessary for the development of new, superior design scenarios for diabetes self-management games.Informatio

Information Privacy and the Inference Economy

Information privacy is in trouble. Contemporary information privacy protections emphasize individuals’ control over their own personal information. But machine learning, the leading form of artificial intelligence, facilitates an inference economy that pushes this protective approach past its breaking point. Machine learning provides pathways to use data and make probabilistic predictions—inferences—that are inadequately addressed by the current regime. For one, seemingly innocuous or irrelevant data can generate machine learning insights, making it impossible for an individual to anticipate what kinds of data warrant protection. Moreover, it is possible to aggregate myriad individuals’ data within machine learning models, identify patterns, and then apply the patterns to make inferences about other people who may or may not be part of the original dataset. The inferential pathways created by such models shift away from “your” data and towards a new category of “information that might be about you.” And because our law assumes that privacy is about personal, identifiable information, we miss the privacy interests implicated when aggregated data that is neither personal nor identifiable can be used to make inferences about you, me, and others. This Article contends that accounting for the power and peril of inferences requires reframing information privacy governance as a network of organizational relationships to manage—not merely a set of dataflows to constrain. The status quo magnifies the power of organizations that collect and process data, while disempowering the people who provide data and who are affected by data-driven decisions. It ignores the triangular relationship among collectors, processors, and people and, in particular, disregards the codependencies between organizations that collect data and organizations that process data to draw inferences. It is past time to rework the structure of our regulatory protections. This Article provides a framework to move forward. Accounting for organizational relationships reveals new sites for regulatory intervention and offers a more auspicious strategy to contend with the impact of data on human lives in our inference economy

Interpretive Structural Model of Key Performance Indicators for Sustainable Manufacturing Evaluation in Cement Industry

This paper aims to analyze the relationships among the Key Performance Indicators (KPIs) for sustainable manufacturing evaluation in the cement industry. The initial KPIs have been identified and derived from literature, and then validated by industry survey. As a result, three factors dividing into a total of thirteen indicators have been proposed as the KPIs for sustainable manufacturing evaluation in cement industry. Interpretive structural modeling (ISM) methodology is applied to develop a network structure model of the KPIs. The results show the indicators of economic factor are regarded as the basic indicator, while the indicators of environmental factor are indicated to be the leading indicator. Of those indicators, raw material substitution is regarded as the most influencing indicator. The ISM model can aid the cement companies by providing a better insight in evaluating sustainable manufacturing performance