Do Consumers Care about How Prices Are Set?

Using a survey approach, we ask consumers to reveal their preferences over pricing schemes that may differ in terms of the average price of consumption, the amount of price variation, and the probability of being rationed. We find that consumers dislike pricing schemes that vary prices more but that they are willing to trade off price variation and rationing. Surprisingly, they are not willing to trade off an increase in price variation for a decrease in expected prices. We discuss the implications of these findings for firm pricing policies.Consumer demand, rationing, demand fluctuation, antagonism, fairness

Predicting pilot error on the flight deck: Validation of a new methodology and a multiple methods and analysts approach to enhancing error prediction sensitivity

The Human Error Template (HET) is a recently developed methodology for predicting designed induced pilot error. This article describes a validation study undertaken to compare the performance of HET against three contemporary Human Error Identification (HEI) approaches when used to predict pilot errors for an approach and landing task and also to compare individual analyst error predictions to an approach to enhancing error prediction sensitivity: the multiple analysts and methods approach, whereby multiple analyst predictions using a range of HEI technique are pooled. The findings indicate that, of the four methodologies used in isolation, analysts using the HET methodology offered the most accurate error predictions, and also that the multiple analysts and methods approach was more successful overall in terms of error prediction sensitivity than the three other methods but not the HET approach. The results suggest that when predicting design induced error, it is appropriate to use domain specific approaches and also a toolkit of different HEI approaches and multiple analysts in order to heighten error prediction sensitivity

Test data generation from UML state machine diagrams using GAs

Automatic test data generation helps testers to validate software against user requirements more easily. Test data can be generated from many sources; for example, experience of testers, source program, or software specification. Selecting a proper test data set is a decision making task. Testers have to decide what test data that they should use, and a heuristic technique is needed to solve this problem automatically. In this paper, we propose a framework for generating test data from software specifications. The selected specification is Unified Modeling Language (UML) state machine diagram. UML state machine diagram describes a system in term of state which can be changed when there is an action occurring in the system. The generated test data is a sequence of these actions. These sequences of action help testers to know how they should test the system. The quality of generated test data is measured by the number of transitions which is fired using the test data. The more transitions test data can fire, the better quality of test data is. The number of coverage transitions is also used as a feedback for a heuristic search for a better test set. Genetic algorithms (GAs) are selected for searching the best test data. Our experimental results show that the proposed GA-based approach can work well for generating test data for some types of UML state machine diagrams

Internet of Things Based Smart Vending Machine using Digital Payment System

The advent of the Internet envisions a cashless society by enabling financial transactions through digital payments. Significantly, the emergence of coronavirus (COVID-19) disrupted our traditional cash handling means and triggered an inflection point for switching towards contactless digital payments from physical cash payments. Furthermore, Internet of Things (IoT) technology escalates digital payments to the next level by enabling devices to render goods and services without requiring any human interaction. This research proposed an IoT-enabled cashless vending machine that incorporates both cloud computing and payment gateway for ordering and purchasing items through digital payment systems by using a mobile application. The system enables a pre-installed mobile application to scan the Quick Response (QR) code attached to the body of a vending machine, opens the portal of a web-based virtual machine through the code, allows user to choose and order items from the virtual vending, initiates and authorizes a digital payment through an IoT gateway installed inside the physical vending machine by establishing a connection between user's and vendor's financial entities, and finally, dispenses the ordered items by unlocking the shelves of the vending machine after the successful payment transaction. It operates in the Arduino platform with an ATmega 2560 Microcontroller and Esp8266 Wi-fi module as hardware components, mobile application software, and payment gateway API. The system performed an average response time of 14500 milliseconds to pick a product after running 150 consecutive API test calls. This result shows a satisfying time for enhancing customers' buying experiences with digital payment systems and a customizable and cost-effective IoT-based intelligent vending machine to introduce for mass production

Sustainable packaging in the healthcare industry

The recycling of plastics tends to lag behind other packaging materials. The research investigates opportunities to improve the capture of valuable packaging polymers and to preserve their specification during recycle operations, thus increasing second user opportunity. The legislative and policy drivers on the sustainable use of plastics are described and discussed with particular reference to achieving sustainability, reuse and recycle of healthcare packaging materials. Four strategic methods of achieving improvements in sustainability, reuse and recycle are developed to represent aspects of sorting of materials, collection of recyclables, replacement of unsustainable packaging materials and measurement of the environmental impacts of packaging and changes in packaging, using examples of packaging from GlaxoSmithKline consumer healthcare and medical products. The use of radio frequency identification methodology as a means of separating high quality plastics and individual reusable devices from mixed waste streams has been developed and trialled under simulated materials recycling and separation conditions. The use of Reverse Vending Machines (RVM's) designed to capture high quality polyethylene terephthalate polymers is described along with results of successful trials on this method of capture in the out of home consumption sector. Recovered material is suitable for reuse in food grade applications after reprocessing. A novel biodegradable packaging material has been successfully developed from sources of green waste as an alternative to existing polymer packaging materials for transport of vaccines, and provides results that are extendable to the replacement of other types of packaging over a wide range of consumer goods. The material also offers intangible benefits to a business in terms of claims that can be made within a corporate social responsibility (CSR) report. Life cycle analysis methodologies have been used to illustrate the environmental benefits that can be achieved by reuse of polypropylene as an example of a widely used packaging polymer with potential for reuse in other industrial sectors. The implications of the results obtained in this work should be of value in the future eco-design of polymer products designed to make end-of-life recovery and recycle more efficient and environmentally beneficial

Analysis of Feature Models Using Alloy: A Survey

Feature Models (FMs) are a mechanism to model variability among a family of closely related software products, i.e. a software product line (SPL). Analysis of FMs using formal methods can reveal defects in the specification such as inconsistencies that cause the product line to have no valid products. A popular framework used in research for FM analysis is Alloy, a light-weight formal modeling notation equipped with an efficient model finder. Several works in the literature have proposed different strategies to encode and analyze FMs using Alloy. However, there is little discussion on the relative merits of each proposal, making it difficult to select the most suitable encoding for a specific analysis need. In this paper, we describe and compare those strategies according to various criteria such as the expressivity of the FM notation or the efficiency of the analysis. This survey is the first comparative study of research targeted towards using Alloy for FM analysis. This review aims to identify all the best practices on the use of Alloy, as a part of a framework for the automated extraction and analysis of rich FMs from natural language requirement specifications.Comment: In Proceedings FMSPLE 2016, arXiv:1603.0857

Design and semantics of form and movement (DeSForM 2006)

Design and Semantics of Form and Movement (DeSForM) grew from applied research exploring emerging design methods and practices to support new generation product and interface design. The products and interfaces are concerned with: the context of ubiquitous computing and ambient technologies and the need for greater empathy in the pre-programmed behaviour of the ‘machines’ that populate our lives. Such explorative research in the CfDR has been led by Young, supported by Kyffin, Visiting Professor from Philips Design and sponsored by Philips Design over a period of four years (research funding £87k). DeSForM1 was the first of a series of three conferences that enable the presentation and debate of international work within this field: • 1st European conference on Design and Semantics of Form and Movement (DeSForM1), Baltic, Gateshead, 2005, Feijs L., Kyffin S. & Young R.A. eds. • 2nd European conference on Design and Semantics of Form and Movement (DeSForM2), Evoluon, Eindhoven, 2006, Feijs L., Kyffin S. & Young R.A. eds. • 3rd European conference on Design and Semantics of Form and Movement (DeSForM3), New Design School Building, Newcastle, 2007, Feijs L., Kyffin S. & Young R.A. eds. Philips sponsorship of practice-based enquiry led to research by three teams of research students over three years and on-going sponsorship of research through the Northumbria University Design and Innovation Laboratory (nuDIL). Young has been invited on the steering panel of the UK Thinking Digital Conference concerning the latest developments in digital and media technologies. Informed by this research is the work of PhD student Yukie Nakano who examines new technologies in relation to eco-design textiles