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The purpose of this paper is to identify the reasons for discharges against medical advice (DAMA) and the possible outcomes among pediatric patients.

A retrospective cohort study was conducted on all children admitted and then discharged against medical advice in two maternity and children’s hospitals in Jeddah, 2014. Phone interviews were conducted, and medical records were reviewed for DAMA and control groups; a semi-structured questionnaire was used to collect this information.

The top three reasons identified for DAMA were parent’s false assumption that their child’s condition had improved (43.8 percent), dissatisfaction with treating/managing team (16.2 percent) and difficulties arranging care for patient’s siblings at home (7.7 percent). The readmission rate was significantly higher among DAMA pediatric patients compared to the control group (28.5 percent vs 11.5 percent) at 30-day follow-up, which highlights the importance for developing interventions aimed at reducing DAMA.

This study helps us to better understand DAMA reasons and outcomes. Understanding these factors can encourage appropriate interventions and policies for reducing DAMA rates. In this way, pediatric patients can be protected from inappropriate discharge consequences.

The case explores the growth of Dastkar Andhra Marketing Association (DAMA) and its relationship with its sister organizations, as it works to articulate an alternate model of production, distribution and retailing. The case attempts to highlight issues around appropriate interventions in a traditional sector providing livelihood to millions, but confronting the challenges of a modern economy and society. The case would be beneficial in emphasizing the role of market and state failures and the role played by social enterprises in addressing them.

The purpose of this paper is to identify the main reasons for discharge against medical advice (DAMA) in the emergency department (ED) of a teaching hospital in Tehran, Iran.

This cross-sectional study was conducted on all the patients who left the ED of a referral teaching hospital against medical advice (AMA) in 2008. A questionnaire was filled out for each patient to determine the reasons behind patient leaving AMA.

In total, 12.8 percent of the patients left the hospital AMA. Dissatisfaction with being observed in the ED, having a feeling of recovery and hospital personnel encouraging patients to leave the hospital were the main reasons for leaving the hospital AMA.

Like many other centers, the results showed that poor communication skill and work overload were the main contributing factors to DAMA. The center managed to improve patient satisfaction and thus lowered DAMA rates following this study. Considering the similarities reported in the reports and that of other studies, it could be concluded that policy makers in other centers can also benefit from the results to adopt effective approaches to reduce DAMA rate.

To the knowledge no study has evaluated the rate and the reasons behind DAMA in the Iranian EDs.

Expected learning objectives students will be able to examine the possible reasons for a company’s poor performance using relevant business tools. Students will be able to critically assess the role of technology and social media in the gem and jewellery industry in Dubai. Students will be able to analyse the customer segmentation approach used by five diamonds and to critically analyse its advantages and disadvantages. Students will be able to use the SWOT framework to identify the key weaknesses of and threats to five diamonds and identify the strengths and opportunities that the company needed to capitalize on, to be more competitive in the industry and generate high profitability. Students will be able to critically analyse the fit between the firm’s current business strategy and its business environment and develop a “turnaround” strategy.

Five diamonds were a trading company that dealt in gems and jewellery, natural pearls and branded watches. The company had been founded by Mustafa Al Fardan in 2003 and was currently run by his son Mohammed Al Fardan who held the position of General Manager. The company was based in Dubai, United Arab Emirates (UAE) with two local branches and eight international branches in China, France, India, Switzerland, Hong Kong and the UK. The branches were located in Palm Strip Jumeirah and in the Jumeirah Al Naseem Hotel, in the Umm Sequim area. The Palm Strip Jumeirah region is one of the largest and crowded areas in Dubai with world-class facilities such as hotels, clinics, restaurants, beaches and clubs, making it a perfect location for tourists. The Umm Sequim region is in the same area where the iconic seven-star hotel, Burj Al Arab, is located. The place is also a “must be” place for tourists and has recorded a significant increase in traffic at different times of the year. Despite their strong presence locally and internationally, the firm was facing fierce competition from the hostile business environment. Industry trends and the business environment were changing the local and global gems and jewellery industry landscape. These changes had offset five diamonds’ business strategy and its long-held business tradition. As a result, the company yearly profit had started to plummet. The company needed to revise its existing business strategy and the way it operated in the market. Failure to do so would have resulted in the firm missing the huge growth opportunity and also put itself into jeopardy.

This case is useful for undergraduate and postgraduate students majoring in marketing, business management and/or strategic management.

Teaching Notes are available for educators only.

CSS 11: Strategy.

Consumption of game meat is growing when compared to other meats. It is susceptible to adulteration because of its cost and availability. Spectroscopy may lead to rapid methodologies for detecting adulteration. The purpose of this study is to detect the adulteration of wild fallow deer (Dama dama) meat with domestic goat (G) (Capra aegagrus hircus) meat, for samples stored for different periods of time using Fourier transform infrared (FTIR) spectroscopy coupled with chemometric.

Meat was cut and mixed in different percentages, transformed into mini-burgers and stored at 3°C from 12 to 432 h and periodically examined for FTIR, pH and microbial analysis. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were applied to detect adulteration.

The PCA model, applied to the spectral region from 1,138 to 1,180, 1,314 to 1,477, 1,535 to 1,556 and from 1,728 to 1,759 cm⁻¹, describes the adulteration using four principal components which explained 95 per cent of variance. For the levels of Adulteration A1 (pure meat), A2 (25 and 50 %w/wG) and A3 (75 and 100 %w/wG) for an external set of samples, the correlation coefficients for prediction were 0.979, 0.941 and 0.971, and the room mean square error were 8.58, 12.46 and 9.47 per cent, respectively.

The PLS-DA model predicted the adulteration for an external set of samples with high accuracy. The proposed method has the advantage of allowing rapid results, despite the storage time of the adulterated meat. It was shown that FTIR combined with chemometrics can be used to establish a methodology for the identification of adulteration of game meat, not only for fresh meat but also for meat stored for different periods of time.

Global building failures, such as the Grenfell Tower fire in London, UK, emphasised the need for trustworthy building handover information for safety. However, a notable gap remains in understanding how reliable handover information can ensure the safety of occupants. This study aims to investigate the use and essential quality of handover information to understand the effects of the quality of information on the management of commercial buildings.

Ninety-four participants from nine organisations who regularly use handover information to manage multiple commercial buildings participated in the semi-structured interviews. Qualitative thematic coding using interview transcripts was performed to identify the utilisation of handover information and its quality requirements.

This study reveals that as-built drawings and product information are predominately used to fulfil statutory obligations, comply with the organisation’s internal policies, evaluate asset valuation and make informed decisions about capital investment and operating expenses. The quality dimensions of “accuracy”, “timeliness”, and “completeness” are preferred in combination to achieve desired outcomes.

This study focused on using handover information in the management of commercial buildings. However, its results can offer valuable perspectives for improving its application across various sectors in the built environment.

The findings affirm the need for quality handover information for safety, compliance and efficient management in commercial buildings.

This research significantly contributes to the current knowledge of handover information in the building sector. Given the study findings, building owners are equipped to define specific handover information requirements and quality requisites.

The real challenge of Alaska's changing telecommunications landscape is approaching the opportunities in an orderly and logical manner. Given the exciting nature of the possibilities that new technology presents, it is all too easy to get wrapped up in what is new, instead of what is truly useful. For that reason, the main focus of the Telecommunications Information Council (TIC) in the near future will be developing and adopting a comprehensive technology plan for the state, and then examining where new technologies fit into that plan. The Knowles/Ulmer administration's first task in this effort was to reinvigorate the TIC and charge it with taking the lead in bringing Alaska back to the forefront of telecommunications technology. Our state has long had a reputation for leading the way in telecommunications. Our climate, geographic size, and location have always forced Alaskans to be innovators in technology. Supercomputers and satellites have operated in and above our state for many years, but much of that momentum was waning. That needed to change.

The purpose of the paper is to propose a reference model describing a holistic view of the master data lifecycle, including strategic, tactical and operational aspects. The Master Data Lifecycle Management (MDLM) map provides a structured approach to analyze the master data lifecycle.

Embedded in a design oriented research process, the paper applies the Component Business Model (CBM) method and suggests a reference model which identifies the business components required to manage the master data lifecycle. CBM is a patented IBM method to analyze the key components of a business domain. The paper uses a participative case study to evaluate the suggested model.

Based on a participative case study, the paper shows how the reference model makes it possible to analyze the master data lifecycle on a strategic, a tactical and an operational level, and how it helps identify areas of improvement.

The paper presents design work and a participative case study. The reference model is grounded in existing literature and represents a comprehensive framework forming the foundation for future analysis of the master data lifecycle. Furthermore, the model represents an abstraction of an organization's master data lifecycle. Hence, it forms a “theory for designing”. More research is needed in order to more thoroughly evaluate the presented model in a variety of real‐life settings.

The paper shows how the reference model enables practitioners to analyze the master data lifecycle and how it helps identify areas of improvement.

The paper reports on an attempt to establish a holistic view of the master data lifecycle, including strategic, tactical and operational aspects, in order to provide more comprehensive support for its analysis and improvement.

To be more effective, artificial intelligence (AI) requires a broad overall view of the design and transformation of enterprise architecture and capabilities. Maturity models (MMs) are the recognized tools to identify strengths and weaknesses of certain domains of an organization. They consist of multiple, archetypal levels of maturity of a certain domain and can be used for organizational assessment and development. In the case of AI, quite a few numbers of MMs have been proposed. Generally, the links between AI technology, AI usage and organizational performance stay unclear. To address these gaps, this paper aims to introduce the complete details of the AI maturity model (AIMM) for AI-driven platform companies. The associated AI-Driven Platform Enterprise Maturity framework proposed here can help to achieve most of the AI-driven platform companies' objectives.

Qualitative research is performed in two stages. In the first stage, a review of the existing literature is performed to identify the types, barriers, drivers, challenges and opportunities of MMs in AI, Advanced Analytics and Big Data domains. In the second stage, a research framework is proposed to align company value chain with AI technologies and levels of the platform enterprise maturity.

The paper proposes a new five level AI-Driven Platform Enterprise Maturity framework by constructing a formal organizational value chain taxonomy model that explains a vast group of MM phenomena related with the AI-Driven Platform Enterprises. In addition, this study proposes a clear and precise description and structuring of the information in the multidimensional Platform, AI, Advanced Analytics and Big Data domains. The AI-Driven Platform Enterprise Maturity framework assists in identification, creation, assessment and disclosure research of AI-driven platform business organizations.

This research is focused on the basic dimensions of AI value chain. The full reference model of AI consists of much more concepts. In the last few years, AI has achieved a notable drive that, if connected appropriately, may deliver the best of expectations over many application sectors across the field. For this to occur shortly in machine learning, especially in deep neural networks, the entire community stands in front of the barrier of explainability. Paradigms underlying this problem fall within the so-called eXplainable AI (XAI) field, which is widely acknowledged as a crucial feature for the practical deployment of AI models in industry. Our prospects lead toward the concept of a methodology for the large-scale implementation of AI methods in platform organizations with fairness, model explainability and accountability at its core.

AI-driven platform enterprise maturity framework can be used for better communicate to clients the value of AI capabilities through the lens of changing human-machine interactions and in the context of legal, ethical and societal norms.

The authors discuss AI in the enterprise platform stack including talent platform, human capital management and recruiting.

The AI value chain and AI-Driven Platform Enterprise Maturity framework are original and represent an effective tools for assessing AI-driven platform enterprises.

In this chapter, I examine how religion can serve as an ideology that has the capacity to bridge people of the same faith who hold divergent political stances. Building on Williams’ work (1996), I propose that religion operates as an ideology when it diagnoses the source of social conflicts, proposes solutions, and justifies action. Yet religious ideological appeals are not always effective at bridging political divides. Thus the key question of this study is: under what social conditions are religiously-based ideological appeals effective at winning people’s support for social and political movements? To address this, I examine the relationship of religious leaders to Latin American movements that aimed to nonviolently overthrow authoritarian states. In particular, I analyze the conditions that led some religious elites to become pro-revolution while others sided with the incumbent regime. Using comparative historical methods, I analyze the different political stances of the Catholic Church hierarchy in the 1970s–1980s in Chile (where the church opposed the dictatorship), Argentina (where the church was largely supportive of the regime), and El Salvador (where the church hierarchy was divided). I argue that ideological appeals for religious leaders’ support are most effective when the religious institution receives no financial or political benefits from the regime and when leaders have relational ties to the aggrieved. Two factors had mixed effects on the decision to remain loyal to the state or not; these include the presence of an armed radical flank, and the state’s use of indiscriminate repression.