How to democratize Internet of Things devices. A participatory design research

The global introduction of affordable Internet of Things (IoT) devices offers an opportunity to empower a large variety of users with different needs. However, many off-the-shelf digital products are still not widely adopted by people who are hesitant technology users or by older adults, notwithstanding that the design and user-interaction of these devices is recognized to be user-friendly. In view of the potential of IoT-based devices, how can we reduce the obstacles of a cohort with low digital literacy and technology anxiety and enable them to be equal participants in the digitalized world? This article shows the method and results achieved in a community-stakeholder workshop, developed through the participatory design methodology, aiming at brainstorming problems and scenarios through a focus group and a structured survey. The research activity focused on understanding factors to increase the usability of off-the-shelf IoT devices for hesitant users and identify strategies for improving digital literacy and reducing technology anxiety. A notable result was a series of feedback items pointing to the importance of creating learning resources to support individuals with different abilities, age, gender expression, to better adopt off-the-shelf IoT-based solutions.Comment: 8 pages, 5 figure

Selecting Forecasting Methods

I examined six ways of selecting forecasting methods: Convenience, “what’s easy,” is inexpensive, but risky. Market popularity, “what others do,” sounds appealing but is unlikely to be of value because popularity and success may not be related and because it overlooks some methods. Structured judgment, “what experts advise,” which is to rate methods against prespecified criteria, is promising. Statistical criteria, “what should work,” are widely used and valuable, but risky if applied narrowly. Relative track records, “what has worked in this situation,” are expensive because they depend on conducting evaluation studies. Guidelines from prior research, “what works in this type of situation,” relies on published research and offers a low-cost, effective approach to selection. Using a systematic review of prior research, I developed a flow chart to guide forecasters in selecting among ten forecasting methods. Some key findings: Given enough data, quantitative methods are more accurate than judgmental methods. When large changes are expected, causal methods are more accurate than naive methods. Simple methods are preferable to complex methods; they are easier to understand, less expensive, and seldom less accurate. To select a judgmental method, determine whether there are large changes, frequent forecasts, conflicts among decision makers, and policy considerations. To select a quantitative method, consider the level of knowledge about relationships, the amount of change involved, the type of data, the need for policy analysis, and the extent of domain knowledge. When selection is difficult, combine forecasts from different methods

Estimating the Effects of Immigration Status on Mental Health Care Utilizations in the United States

Immigration status is a likely deterrent of mental health care utilization in the United States. Using the Medical Expenditure Panel Survey and National Health Interview survey from 2002 to 2006, multivariable logistic regressions were used to estimate the effects of immigration status on mental health care utilization among patients with depression or anxiety disorders. Multivariate regressions showed that immigrants were significantly less likely to take any prescription drugs, but not significantly less likely to have any physician visits compared to US-born citizens. Results also showed that improving immigrants’ health care access and health insurance coverage could potentially reduce disparities between US-born citizens and immigrants by 14–29% and 9–28% respectively. Policy makers should focus on expanding the availability of regular sources of health care and immigrant health coverage to reduce disparities on mental health care utilization. Targeted interventions should also focus on addressing immigrants’ language barriers, and providing culturally appropriate services

Temporal, seasonal and weather effects on cycle volume: an ecological study

<p>Abstract</p> <p>Background</p> <p>Cycling has the potential to provide health, environmental and economic benefits but the level of cycling is very low in New Zealand and many other countries. Adverse weather is often cited as a reason why people do not cycle. This study investigated temporal and seasonal variability in cycle volume and its association with weather in Auckland, New Zealand's largest city.</p> <p>Methods</p> <p>Two datasets were used: automated cycle count data collected on Tamaki Drive in Auckland by using ZELT Inductive Loop Eco-counters and weather data (gust speed, rain, temperature, sunshine duration) available online from the National Climate Database. Analyses were undertaken using data collected over one year (1 January to 31 December 2009). Normalised cycle volumes were used in correlation and regression analyses to accommodate differences by hour of the day and day of the week and holiday.</p> <p>Results</p> <p>In 2009, 220,043 bicycles were recorded at the site. There were significant differences in mean hourly cycle volumes by hour of the day, day type and month of the year (<it>p </it>< 0.0001). All weather variables significantly influenced hourly and daily cycle volumes (<it>p </it>< 0.0001). The cycle volume increased by 3.2% (hourly) and 2.6% (daily) for 1°C increase in temperature but decreased by 10.6% (hourly) and 1.5% (daily) for 1 mm increase in rainfall and by 1.4% (hourly) and 0.9% (daily) for 1 km/h increase in gust speed. The volume was 26.2% higher in an hour with sunshine compared with no sunshine, and increased by 2.5% for one hour increase in sunshine each day.</p> <p>Conclusions</p> <p>There are temporal and seasonal variations in cycle volume in Auckland and weather significantly influences hour-to-hour and day-to-day variations in cycle volume. Our findings will help inform future cycling promotion activities in Auckland.</p

A Measure of Perceived Performance to Assess Resource Allocation

The final publication is available at Springer via http://dx.doi.org/10.1007/s00500-015-1696-3Performance measurement is a key issue when a company is designing new strategies to improve resource allocation. This paper offers a new methodology inspired by classic importance-performance analysis (IPA) that provides a global index of importance versus performance for firms. This index compares two rankings of the same set of features regarding importance and performance, taking into account underperforming features. The marginal contribution of each feature to the proposed global index defines a set of iso-curves that represents an improvement in the IPA diagram. The defined index, together with the new version of the diagram, will enable the assessment of a firm's overall performance and, therefore, enhance decision making in the allocation of resources. The proposed methodology has been applied to a Taiwanese multi-format retailer and managerial perceptions of performance and importance are compared to assess the firm's overall performance.Peer ReviewedPostprint (author's final draft

EMPIRICAL GENERALIZATIONS ABOUT THE IMPACT OF ADVERTISING ON PRICE SENSITIVITY AND PRICE

Consumers' sensitivities to price changes are an important input to strategic and tactical decisions. It has been argued that price sensitivities depend on factors such as advertising Prior studies on the effect of advertising on consumer price sensitivity have found seemingly conflicting results. We analyze the characteristics of previous studies in marketing and generate a set of three empirical generalizations. These are (1) an increase in price advertising leads to higher price sensitivity among consumers, (2) the use of price advertising leads to lower prices, and (3) an increase in nonprice advertising leads to lower price sensitivity among consumers. These generalizations have important implications for managers and researchers. Managers need to coordinate their advertising and pricing decisions to attain maximum profits. For researchers, our summary and discussion of empirical results provide directions for future