The Effect of Digital Platform Strategies on Firm Value in the Banking Industry.

After digital platforms have become successful in the information technology (IT) industry, incumbents from traditional industries increasingly implement digital platform strategies. However, there is mixed evidence on whether these incumbents benefit from digital platform strategies. To provide systematic insights, we focus on the banking industry. With the emergence of open banking, banks have begun implementing digital platforms to unlock the innovative power of third-party developers. We conducted an event study based on the announcement of digital platform strategies in a global sample of 165 banks. We show that, on average, investors react positively to the announcements. Contrary to our expectations, this effect is more substantial for banks from emerging markets than those from developed markets. Prior artificial intelligence (AI) orientation only partly contributes to investors' favorable perception of a digital platform strategy. These results point to the complex interplay of AI orientation and digital platform strategies, yielding questions for future research.

The role of information systems in emergency department decision-making-a literature review.

OBJECTIVES: Healthcare providers employ heuristic and analytical decision-making to navigate the high-stakes environment of the emergency department (ED). Despite the increasing integration of information systems (ISs), research on their efficacy is conflicting. Drawing on related fields, we investigate how timing and mode of delivery influence IS effectiveness. Our objective is to reconcile previous contradictory findings, shedding light on optimal IS design in the ED. MATERIALS AND METHODS: We conducted a systematic review following PRISMA across PubMed, Scopus, and Web of Science. We coded the ISs' timing as heuristic or analytical, their mode of delivery as active for automatic alerts and passive when requiring user-initiated information retrieval, and their effect on process, economic, and clinical outcomes. RESULTS: Our analysis included 83 studies. During early heuristic decision-making, most active interventions were ineffective, while passive interventions generally improved outcomes. In the analytical phase, the effects were reversed. Passive interventions that facilitate information extraction consistently improved outcomes. DISCUSSION: Our findings suggest that the effectiveness of active interventions negatively correlates with the amount of information received during delivery. During early heuristic decision-making, when information overload is high, physicians are unresponsive to alerts and proactively consult passive resources. In the later analytical phases, physicians show increased receptivity to alerts due to decreased diagnostic uncertainty and information quantity. Interventions that limit information lead to positive outcomes, supporting our interpretation. CONCLUSION: We synthesize our findings into an integrated model that reveals the underlying reasons for conflicting findings from previous reviews and can guide practitioners in designing ISs in the ED.

Characterization of adults concerning the use of a hypothetical mHealth application addressing stress-overeating: an online survey.

BACKGROUND: About 40% of people respond to stress by consuming more unhealthy foods. This behavior is associated with increased energy intake and the risk of obesity. As mobile health (mHealth) applications (apps) have been shown to be an easy-to-use intervention tool, the characterization of potential app users is necessary to develop target group-specific apps and to increase adherence rates. METHODS: This cross-sectional online survey was conducted in the spring of 2021 in Germany. Sociodemographic data and data on personality (Big Five Inventory, BFI-10), stress-eating (Salzburg Stress Eating Scale, SSES), and technology behavior (Personal Innovativeness in the Domain of Information Technology, PIIT; Technology Acceptance Model 3, TAM 3) were collected. RESULTS: The analysis included 1228 participants (80.6% female, mean age: 31.4 ± 12.8 years, mean body mass index (BMI): 23.4 ± 4.3 kg/m2). Based on the TAM score, 33.3% (409/1228) of the participants had a high intention to use a hypothetical mHealth app to avoid stress-overeating. These persons are characterized by a higher BMI (24.02 ± 4.47 kg/m2, p < 0.001), by being stress-overeaters (217/409, 53.1%), by the personality trait "neuroticism" (p < 0.001), by having specific eating reasons (all p < 0.01), and by showing a higher willingness to adopt new technologies (p < 0.001). CONCLUSION: This study suggests that individuals who are prone to stress-overeating are highly interested in adopting an mHealth app as support. Participants with a high intention to use an mHealth app seem to have a general affinity towards new technology (PIIT) and appear to be more insecure with conflicting motives regarding their diet. TRIAL REGISTRATION: This survey was registered in the German Clinical Trials Register (Registration number: DRKS00023984).

Advantages and disadvantages of mobile applications for workplace health promotion: A scoping review.

Different interventions and methods are used for workplace health promotion (WHP) programmes, including mobile applications (apps), which have proven effective among different health outcomes if properly communicated and developed. However, knowledge is lacking on the potential advantages and disadvantages of using this technology for WHP compared with nontechnical WHP programmes to support employers in their decision making and effective development of such an intervention. To obtain an overview of factors that decision-makers should consider when deciding whether to implement an WHP app, we conducted a scoping review of studies that have evaluated WHP apps. Potential advantages and disadvantages of using mobile apps for WHP were summarised using a strengths, weaknesses, opportunities and threats (SWOT) analysis. Articles were included if they focussed on a WHP app, were published between 2007 and 2022 in German or English, and evaluated an app for the general employee population. Altogether, 38 studies were included in the review, demonstrating WHP apps' effectiveness among various use cases in terms of content, e.g., mindfulness or sleep, and target groups, e.g., office workers, nurses or pilots. Strengths were found in the context of adoption, convenience for users, the targeted employee group's reach and cost-effectiveness. However, the review also identified some disadvantages in apps, including technical difficulties and usage barriers, as well as challenges, e.g., privacy issues and maintenance costs. Generally, our review found that different factors need to be considered when deciding whether to implement a WHP app based on the individual company situation, e.g., shift work, content to be communicated, and expectations for health parameter screening, among many others. By summarising recent literature on WHP apps, this review uses scientific knowledge to give employers an overview of potential factors to consider in their decision making.

Community indicators for mental health in Europe: a scoping review.

Background: Community indicators may predict and influence individuals` mental health, and support or impede mental health management. However, there is no consensus on which indicators should be included in predictions, prognostic algorithms, or management strategies for community-based mental health promotion and prevention approaches. Therefore, this scoping review provides an overview of relevant community-level indicators for mental health in the general as well as risk populations in a European context. Methods: We conducted a scoping review in the following electronic databases: PubMed, Embase, and PsycInfo. Eligible studies focused on context factors such as either the physical or social environment, reporting at least one mental health outcome and referring to a European population. Publications between 2012 and March 8, 2022 are considered. Results: In total, the search yielded 12,200 identified records. After the removal of duplicates, 10,059 records were screened against the eligibility criteria. In total, 169 studies were included in the final analysis. Out of these included studies, 6% focused on pan-European datasets and 94% on a specific European country. Populations were either general or high-risk populations (56 vs. 44%, respectively) with depressive disorder as the main reported outcome (49%), followed by general mental health (33%) and anxiety (23%). Study designs were cross-sectional studies (59%), longitudinal (27%), and others (14%). The final set of indicators consisted of 53 indicators, which were grouped conceptually into 13 superordinate categories of community indicators. These were divided into the domains of the physical and social environment. The most commonly measured and reported categories of community indicators associated with mental health outcomes were social networks (n = 87), attitudinal factors toward vulnerable groups (n = 76), and the characteristics of the built environment (n = 56). Conclusion: This review provides an evidence base of existing and novel community-level indicators that are associated with mental health. Community factors related to the physical and social environment should be routinely recorded and considered as influencing factors or potentially underestimated confounders. The relevance should be analyzed and included in clinical outcomes, data, monitoring and surveillance as they may reveal new trends and targets for public mental health interventions.

Usage of a workplace health promotion app: an evaluation of app usage data and medical check-up results.

Smartphone applications (apps) have been used and evaluated in the context of workplace health promotion (WHP) programs. However, there is a lack of studies analyzing actual app usage data and measuring changes in medical markers to evaluate the effectiveness of WHP apps in terms of health improvements in practice. In this study, we evaluated data from 555 employees of an IT company who participated in a WHP program over the course of one year. Participants of the program received a medical check-up as well as a health app to understand their medical results and receive advice for a healthier lifestyle. In addition, 99 of these employees underwent a follow-up medical check-up. It was found that the smartphone app for healthy lifestyle promotion in combination with onsite medical check-ups was effective in improving various health indicators, for example, BMI, body fat, blood pressure and triglycerides. The study further identified influence factors for sustained app usage, and analyzed different usage behaviors among gender and age groups.

Stress eating: an online survey of eating behaviours, comfort foods, and healthy food substitutes in German adults.

BACKGROUND: In many people, stress is associated with changes in eating behaviour. Food products consumed during stress (comfort foods) are often unhealthy. It is rather unknown what comfort foods are consumed in Germany and what healthier food products are considered as alternatives to support stress-eaters in making healthier food choices. METHODS: This online survey was conducted in spring 2021 throughout Germany. Participants were digitally recruited by newsletters, homepages, social media, and mailing lists. The survey included a standardized questionnaire with items concerning e.g. sociodemography, stress, and nutrition. Comfort foods were pre-selected through literature search and food substitutes were defined and discussed by experts. Analyses examined comfort food consumption and substitute preferences dependent on sex, age, body mass index (BMI), and being a self-identified stress-eater. The statistical analysis was performed using R. RESULTS: Survey participants were mostly female (80.6%, 994/1234), had a mean age of 31.4 ± 12.8 years and a mean BMI of 23.4 ± 4.3 kg/m2. Participants stated, that the two favourite comfort foods were chocolate (consumed often/very often by 48.3%, 596/1234) and coffee (consumed often/very often by 45.9%, 566/1234). Regarding food substitutes, the most frequently named alternative food for chocolate and cookies was fresh fruits (for chocolate: 74.4%, 815/1096, for cookies: 62.6%, 565/902). Tea without added sugar (64.4%, 541/840) was the preferred substitute for coffee. Almost 50% of participants (48.1%, 594/1234) identified themselves as stress-eaters, of which 68.9% (408/592) stated to eat (very) often more than usual in subjective stress situations. CONCLUSIONS: The results from this work suggest that specific comfort foods and substitutes are preferred by the participants in stressful situations. This knowledge about food choices and substitutes should be investigated in further studies to improve eating behaviour in stressful situations. TRIAL REGISTRATION: The survey was registered in the German Register of Clinical Studies (Registration number: DRKS00023984 ).

Value of normative belief in intention to use workplace health promotion apps.

BACKGROUND: Mobile applications (apps) have started to be used for workplace health promotion (WHP). However, the factors that lead to the usage of apps in the workplace from the end-user perspective remain unclear. METHODS: To investigate the research gap, the study evaluates a model for the adoption of WHP apps by combining the theory of planned behavior, the health belief model, and the technology acceptance model. A self-administered questionnaire with validated scales among 354 participants was used to evaluate the proposed model for WHP. RESULTS: Although the study indicated a limited overall model fit, interesting aspects were derived. In particular, the study demonstrated that normative belief (especially), perceived usefulness, and attitudinal belief play important roles in the intention to use WHP apps. CONCLUSION: The study is among the first to validate the theoretical models of mHealth adoption for WHP. Moreover, it shows that not only normative belief but also adjustment to several target groups is a necessary factor to be considered in the development and implementation of an app for WHP.

Stress-induced hyperphagia: empirical characterization of stress-overeaters.

BACKGROUND: Stressful situations can have an impact on an individual's eating behavior. People vulnerable to the influence of stress tend to change the quantity and quality of their food intake. Variables such as sex and body mass index (BMI) seem to be related to this stress-eating behavior, but it is rather unclear what factors account to the parameters associated with stress-eating behavior. The aim of this survey was to identify further characteristics of adults in Germany related to stress-overeating, focusing on stress perception, coping, eating motives and comfort foods as well as personality types. METHODS: This online survey was performed throughout Germany and comprised a 38-item pre-tested questionnaire. Stress-induced overeating was classified based on the Salzburg Stress Eating Scale (SSES). Moreover, validated questionnaires were used to identify additional characteristics of stress eaters. Participants were recruited using a convenience sampling approach, and data were collected between January and April 2021. RESULTS: The overall sample consisted of 1222 participants (female 80.8%, aged 31.5±12.8). 42.1% of participants were identified as stress-overeaters. Among the remaining group, 78.9% stated to eat less, 21.1% to eat equally when stressed. Female participants had a higher mean SSES score compared to male participants. The BMI was positively correlated to SSES, r(1220)=0.28, p>0.005. 'Agreeableness' (BigFive) was found to be a negative predictor of stress-overeating. The most pronounced difference in eating motives (The Eating Motivation Survey, TEMS) was found for 'Affect Regulation' and 'Weight Control'. CONCLUSIONS: The results indicate that stress-overeating affects a large proportion of the surveyed population. BMI, personality and eating motives additionally characterize stress-overeaters and may contribute to develop new approaches to address unhealthy stress-related eating patterns.

ProteomicsDB: toward a FAIR open-source resource for life-science research.

ProteomicsDB (https://www.ProteomicsDB.org) is a multi-omics and multi-organism resource for life science research. In this update, we present our efforts to continuously develop and expand ProteomicsDB. The major focus over the last two years was improving the findability, accessibility, interoperability and reusability (FAIR) of the data as well as its implementation. For this purpose, we release a new application programming interface (API) that provides systematic access to essentially all data in ProteomicsDB. Second, we release a new open-source user interface (UI) and show the advantages the scientific community gains from such software. With the new interface, two new visualizations of protein primary, secondary and tertiary structure as well an updated spectrum viewer were added. Furthermore, we integrated ProteomicsDB with our deep-neural-network Prosit that can predict the fragmentation characteristics and retention time of peptides. The result is an automatic processing pipeline that can be used to reevaluate database search engine results stored in ProteomicsDB. In addition, we extended the data content with experiments investigating different human biology as well as a newly supported organism.

ProteomicsDB: a multi-omics and multi-organism resource for life science research.

ProteomicsDB (https://www.ProteomicsDB.org) started as a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. The data types and contents grew over time to include RNA-Seq expression data, drug-target interactions and cell line viability data. In this manuscript, we summarize new developments since the previous update that was published in Nucleic Acids Research in 2017. Over the past two years, we have enriched the data content by additional datasets and extended the platform to support protein turnover data. Another important new addition is that ProteomicsDB now supports the storage and visualization of data collected from other organisms, exemplified by Arabidopsis thaliana. Due to the generic design of ProteomicsDB, all analytical features available for the original human resource seamlessly transfer to other organisms. Furthermore, we introduce a new service in ProteomicsDB which allows users to upload their own expression datasets and analyze them alongside with data stored in ProteomicsDB. Initially, users will be able to make use of this feature in the interactive heat map functionality as well as the drug sensitivity prediction, but ultimately will be able to use all analytical features of ProteomicsDB in this way.

Smart Glasses in Nursing - Situation Change and Further Usages Exemplified on a Wound Care Application.

Smart Glasses are a promising technology that can be leveraged to improve flexible service processes. Especially in the field of nursing where practitioners are facing complex tasks and challenges. Introducing such pervasive computing devices in service processes may have both positive and negative consequences. This leads us to the following research questions: How does the usage of the Smart Glass applications change the caring situation? Which ideas for future usage of Smart Glasses do nurses have? To answer these questions we followed a design science research approach to design a prototype for support of wound care management in nursing. We evaluated the prototype in a real life situation. Five nurses used the application in a real world setting to perform a wound documentation. Afterwards, we conducted semi-structured interviews with the nurses. The intent of the interviews was not only to get information on the current prototype, but to generate knowledge about dimensions of changing the caring situation which should be considered further. The nurses gave the application an overall positive evaluation. They stated that they would expect an improvement of the quality of the wound documentation when using the device. In addition, they mentioned a change in the communication structure with the patient would be necessary. Furthermore, opinions regarding further use cases did differ.

WESSBAS: extraction of probabilistic workload specifications for load testing and performance prediction-a model-driven approach for session-based application systems.

The specification of workloads is required in order to evaluate performance characteristics of application systems using load testing and model-based performance prediction. Defining workload specifications that represent the real workload as accurately as possible is one of the biggest challenges in both areas. To overcome this challenge, this paper presents an approach that aims to automate the extraction and transformation of workload specifications for load testing and model-based performance prediction of session-based application systems. The approach (WESSBAS) comprises three main components. First, a system- and tool-agnostic domain-specific language (DSL) allows the layered modeling of workload specifications of session-based systems. Second, instances of this DSL are automatically extracted from recorded session logs of production systems. Third, these instances are transformed into executable workload specifications of load generation tools and model-based performance evaluation tools. We present transformations to the common load testing tool Apache JMeter and to the Palladio Component Model. Our approach is evaluated using the industry-standard benchmark SPECjEnterprise2010 and the World Cup 1998 access logs. Workload-specific characteristics (e.g., session lengths and arrival rates) and performance characteristics (e.g., response times and CPU utilizations) show that the extracted workloads match the measured workloads with high accuracy.

Ontology for Semantic Data Integration in the Domain of IT Benchmarking.

A domain-specific ontology for IT benchmarking has been developed to bridge the gap between a systematic characterization of IT services and their data-based valuation. Since information is generally collected during a benchmark exercise using questionnaires on a broad range of topics, such as employee costs, software licensing costs, and quantities of hardware, it is commonly stored as natural language text; thus, this information is stored in an intrinsically unstructured form. Although these data form the basis for identifying potentials for IT cost reductions, neither a uniform description of any measured parameters nor the relationship between such parameters exists. Hence, this work proposes an ontology for the domain of IT benchmarking, available at https://w3id.org/bmontology. The design of this ontology is based on requirements mainly elicited from a domain analysis, which considers analyzing documents and interviews with representatives from Small- and Medium-Sized Enterprises and Information and Communications Technology companies over the last eight years. The development of the ontology and its main concepts is described in detail (i.e., the conceptualization of benchmarking events, questionnaires, IT services, indicators and their values) together with its alignment with the DOLCE-UltraLite foundational ontology.

ProteomicsDB.

ProteomicsDB (https://www.ProteomicsDB.org) is a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. ProteomicsDB was first released in 2014 to enable the interactive exploration of the first draft of the human proteome. To date, it contains quantitative data from 78 projects totalling over 19k LC-MS/MS experiments. A standardized analysis pipeline enables comparisons between multiple datasets to facilitate the exploration of protein expression across hundreds of tissues, body fluids and cell lines. We recently extended the data model to enable the storage and integrated visualization of other quantitative omics data. This includes transcriptomics data from e.g. NCBI GEO, protein-protein interaction information from STRING, functional annotations from KEGG, drug-sensitivity/selectivity data from several public sources and reference mass spectra from the ProteomeTools project. The extended functionality transforms ProteomicsDB into a multi-purpose resource connecting quantification and meta-data for each protein. The rich user interface helps researchers to navigate all data sources in either a protein-centric or multi-protein-centric manner. Several options are available to download data manually, while our application programming interface enables accessing quantitative data systematically.

Determinants of physicians' technology acceptance for e-health in ambulatory care.

BACKGROUND: Germany is introducing a nation-wide telemedicine infrastructure that enables electronic health services. The project is facing massive resistance from German physicians, which has led to a delay of more than five years. Little is known about the actual burdens and drivers for adoption of e-health innovations by physicians. OBJECTIVE: Based on a quantitative study of German physicians who participated in the national testbed for telemedicine, this article extends existing technology acceptance models (TAM) for electronic health (e-health) in ambulatory care settings and elaborates on determinants of importance to physicians in their decision to use e-health applications. METHODS: This study explores the opinions, attitudes, and knowledge of physicians in ambulatory care to find drivers for technology acceptance in terms of information technology (IT) utilization, process and security orientation, standardization, communication, documentation and general working patterns. We identified variables within the TAM constructs used in e-health research that have the strongest evidence to determine the intention to use e-health applications. RESULTS: The partial least squares (PLS) regression model from data of 117 physicians showed that the perceived importance of standardization and the perceived importance of the current IT utilization (p<0.01) were the most significant drivers for accepting electronic health services (EHS) in their practice. Significant influence (p<0.05) was shown for the perceived importance of information security and process orientation as well as the documentation intensity and the e-health-related knowledge. CONCLUSIONS: This study extends work gleaned from technology acceptance studies in healthcare by investigating factors which influence perceived usefulness and perceived ease of use of e-health services. Based on these empirical findings, we derive implications for the design and introduction of e-health services including suggestions for introducing the topic to physicians in ambulatory care and incentive structures for using e-health.

An internet-delivered exercise intervention for workplace health promotion in overweight sedentary employees: a randomized trial.

OBJECTIVE: To evaluate the effect of structured vs. non-structured internet-delivered exercise recommendations on aerobic exercise capacity and cardiovascular risk profile in overweight sedentary employees. METHODS: 140 employees of an automobile company (11% female, median age 48 years (range 25-60), BMI 29.0 kg/m(2) (25.0-34.8)) were randomized in a 3:2 ratio to an intervention group receiving structured exercise schedules or a control group choosing workouts individually via an interactive website. The 12-week intervention took place in Munich, Germany, during summer 2008. Main outcome measure was performance at the lactate anaerobic threshold (P(AT)/kg) during ergometry. RESULTS: 77 participants completed the study. The intervention group (n=50) improved significantly in P(AT)/kg ((mean (SD)) 1.68 (0.31) vs. 1.81 (0.33) W/kg; p=0.002), VO(2)peak (3.21 (0.63) vs. 3.35 (0.74) L/min; p=0.04), and waist circumference (100.5 (7.9) vs. 98.0 (7.8) cm; p=0.001). The control group (n=27) improved significantly in P(AT)/kg (1.59 (0.38) vs. 1.80 (0.49); p<0.001) and waist circumference (101.9 (8.7) vs. 98.3 (8.5) cm; p<0.001), but not in VO(2)peak. No significant between group differences in these outcome measures were noted. CONCLUSION: Structured, internet-delivered exercise recommendations are not superior to internet-delivered non-structured exercise recommendations in a workplace setting. Both lifestyle intervention strategies are, however, limited by high dropout rates.