Not just what they want, but why they want it: Traditional market research to deep customer insights

Purpose This paper explores advantages and disadvantages of both traditional market research and deep customer insight methods in order to lay the platform for revealing how a relationship between these two domains could be optimised during firm-based innovation. Design/methodology/approach The paper reports on an empirical research study conducted with thirteen Australian based firms engaged in a design-led approach to innovation. Firms were facilitated through a design-led approach where the process of gathering deep customer insights was isolated and investigated further in comparison to traditional market research methods. Findings Results show that deep customer insight methods are able to provide fresh, non-obvious ways of understanding customer needs, problems and behaviours that can become the foundation of new business opportunities. Findings concluded that deep customer insights methods provide the critical layer to understand why customers do and don’t engage with businesses. Revealing why was not accessible in traditional market research methods. Research limitations/implications The theoretical outcome of this study is a complementary methods matrix, providing guidance on appropriate implementation of research methods in accordance with a project’s timeline to optimise the complementation of traditional market research methods with design-led customer engagement methods. Practical implications Deep customer insight methods provide fresh, non-obvious ways of understanding customer needs, problems and behaviours that can become the foundation of new business opportunities. It is hoped that those in a position of data collection are encouraged to experiment and use deep customer insight methods to connect with their customers on a meaningful level and translate these insights into value. Originality/value This paper provides original value to a new understanding how design techniques can be applied to compliment and strengthen existing market research strategies. This is crucial in an era where business competition hinges on a subtle and often intimate understanding of customer needs and behaviours.

Capnography monitoring during procedural sedation and analgesia: A systematic review protocol

Background An important potential clinical benefit of using capnography monitoring during procedural sedation and analgesia (PSA) is that this technology could improve patient safety by reducing serious sedation-related adverse events, such as death or permanent neurological disability, which are caused by inadequate oxygenation. The hypothesis is that earlier identification of respiratory depression using capnography leads to a change in clinical management that prevents hypoxaemia. As inadequate oxygenation/ventilation is the most common reason for injury associated with PSA, reducing episodes of hypoxaemia would indicate that using capnography would be safer than relying on standard monitoring alone. Methods/design The primary objective of this review is to determine whether using capnography during PSA in the hospital setting improves patient safety by reducing the risk of hypoxaemia (defined as an arterial partial pressure of oxygen below 60 mmHg or percentage of haemoglobin that is saturated with oxygen [SpO2] less than 90 %). A secondary objective of this review is to determine whether changes in the clinical management of sedated patients are the mediating factor for any observed impact of capnography monitoring on the rate of hypoxaemia. The potential adverse effect of capnography monitoring that will be examined in this review is the rate of inadequate sedation. Electronic databases will be searched for parallel, crossover and cluster randomised controlled trials comparing the use of capnography with standard monitoring alone during PSA that is administered in the hospital setting. Studies that included patients who received general or regional anaesthesia will be excluded from the review. Non-randomised studies will be excluded. Screening, study selection and data extraction will be performed by two reviewers. The Cochrane risk of bias tool will be used to assign a judgment about the degree of risk. Meta-analyses will be performed if suitable. Discussion This review will synthesise the evidence on an important potential clinical benefit of capnography monitoring during PSA within hospital settings. Systematic review registration: PROSPERO CRD42015023740

Commentary on the article by Swanenburg et al. ‘Validity and reliability of a German version of the Neck Disability Index (NDI-G)’

We commend Swanenburg et al. (2013) on translation, development, and clinimetric analysis of the NDI-G. However, the dual-factor structure with factor analysis and the high level of internal consistency (IC) highlighted in their discussion were not emphasized in the abstract or conclusion. These points may imply some inconsistencies with the final conclusions since determination of stable point estimates with the study's small sample are exceedingly difficult.

Room-temperature tilted-target sputtering deposition of highly transparent and low sheet resistance Al doped ZnO electrodes

Target-tilted room temperature sputtering of aluminium doped zinc oxide (AZO) provides transparent conducting electrodes with sheet resistances of <10 Ω □-1 and average transmittance in the visible region of up to 84%. The properties of the AZO electrode are found to be strongly dependent on the target-tilting angle and film thickness. The AZO electrodes showed comparable performance to commercial indium tin oxide (ITO) electrodes in organic photovoltaic (OPV) devices. OPV devices containing a bulk heterojunction active layer comprised of poly(3-n-hexylthiophene) (P3HT):phenyl-C61-butyric acid methyl ester (PCBM) and an AZO transparent conducting electrode had a power conversion efficiency (PCE) of up to 2.5% with those containing ITO giving a PCE of 2.6%. These results demonstrate that AZO films are a good alternative to ITO for transparent conducting electrodes.

Improving deep convultional neural networks with unsupervised feature learning

The latest generation of Deep Convolutional Neural Networks (DCNN) have dramatically advanced challenging computer vision tasks, especially in object detection and object classification, achieving state-of-the-art performance in several computer vision tasks including text recognition, sign recognition, face recognition and scene understanding. The depth of these supervised networks has enabled learning deeper and hierarchical representation of features. In parallel, unsupervised deep learning such as Convolutional Deep Belief Network (CDBN) has also achieved state-of-the-art in many computer vision tasks. However, there is very limited research on jointly exploiting the strength of these two approaches. In this paper, we investigate the learning capability of both methods. We compare the output of individual layers and show that many learnt filters and outputs of the corresponding level layer are almost similar for both approaches. Stacking the DCNN on top of unsupervised layers or replacing layers in the DCNN with the corresponding learnt layers in the CDBN can improve the recognition/classification accuracy and training computational expense. We demonstrate the validity of the proposal on ImageNet dataset.

Matters Arising: Zhu et al, "A novel gene variation of TNFα associated with ankylosing spondylitis: A reconfirmed study"

In a recently published study1 involving 79 ankylosing spondylitis (AS) patients and 132 unrelated healthy blood donors, Zhu et al report association of a tumour necrosis factor α (TNFα) single nucleotide polymorphism (SNP), rs1799724, with AS.1 I have many concerns with this paper and its conclusions...

Omission of author name in the article by Davidson et al (Arthritis Rheum, July 2013)

This article corrects: Brief Report: High-Throughput Sequencing of IL23R Reveals a Low-Frequency, Nonsynonymous Single-Nucleotide Polymorphism That Is Associated With Ankylosing Spondylitis in a Han Chinese Population Vol. 65, Issue 7, 1747–1752, Article first published online: 2 JUL 2013

Letter Reply: Distribution of TNFA haplotypes in healthy Caucasians: Comment on the articles by Newton et al and Zeggini et al

We thank Ploski and colleagues for their interest in our study. The explanation for the difference in our findings is a typographic error in Table 2 of our article, whereby the alleles for marker TNF ⫺1031 were labeled incorrectly...

Respite & Recoery at Al Wakra

International Design Competition for Qatar Psychiatric Hospital. The scheme for the Al Wakra Respite and Recovery Centre delivers on an all-in attitude toward evidence-based design. It sets new benchmarks in so many ways: the way it allows excellent separation between patient cohorts without unnecessary or visible restrictions; the way it allows sharing of most of the clinical kit and spaces; the way services reticulation and facilities management takes place without compromising security and safety; the ways It abandons the institutional axioms that are still so ubiquitous elsewhere, so it can appear as the friendly, welcoming and wholesome; the way it allows incredible flexibility to allow changes or flexion on the fly; the way it has such ‘good bones’ for more structural changes as the future unfolds. But most importantly, the scheme will be exemplary in the way the building itself plays a role in promoting the recovery and mental well-being of its residents. Like no other, the Centre will rise to the challenges of supporting and inspiring an exemplary mental health service and promote the well-being of the patients. The 160 bed scheme allows for 43,000m2 of landscape, packed with wholesome things to do and experience. The Aspire zone even has stables and a falconry, both to celebrate the love that Qatari people have for horses and birds.

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Adolescent sexual behavioral intentions measurement: A gender approach in the Colombian Caribbean region [Medición de la Intención en la Actividad Sexual en Adolescentes: una Aproximación de Acuerdo al Género del Caribe Colombiano]

The study of 1777 male and female adolescent students of 11-19 years in the Colombian Caribbean had two objectives: development and validation of two reproductive health intention scales and analyze gender differences. The pilot of the scale consisted of 8 items and was reduced to 6, to check the reliability and validity using factor analysis and principal components with VARIMAX rotation yielded two factors: Intention and Intention Risk Protection, explained between 69.4% and 70% respectively. In the male Protection Intent (M = 3.87 and SD = 1.29) and risk (M = 2.56 and SD = 1.18) obtained an alpha between 0.74 and 0.86, and in Protection of Intent to female (M = 3.49 and SD = 1.35) and risk (M = 1.50 and SD = 0.89) ranged between 0.78 and 086. In conclusion, the reliability and structural stability are adequate and there are gender differences in the scales.