Two-step Clustering Procedure Research Articles

Digital Empowerment: How Small B to B Companies Remodel the Value Chain Through Digital Platforms

ABSTRACT Purpose Digital platforms represent a major technological change that affects the entire value chain of a company and requires digital resources and a flexible organizational structure. Given the resource limitations that SMEs have, it is interesting to find out to what extent they have adopted digital platforms. The aim of this paper is to explore the level of SMEs’ digitalization and how sophisticated these businesses are in using various digital platforms in primary and secondary value creation activities. Additionally, we set out to identify clusters with different needs and behaviors when considering digital platforms. Methodology/Approach To address these research questions, we conducted a survey using a quota sampling procedure to reflect the SMEs’ structure in size and industry. We analyzed the data collected from 194 respondents using a two-step clustering procedure to identify different groups of SMEs with respect to the use of digital platforms. For business activities, we used Porter’s value chain and for assessing the adoption rate, we applied the Moore and Benbasat scale to measure adopters’ perceptions of the technology. Findings Most SMEs use general digital platforms while less than 20% have developed their own platforms or use the platforms of business partners. Organizations with a hybrid structure use the largest number of digital platforms, while enterprises with a fluid structure use the fewest. Companies are using their own platforms or partners’ platforms for primary activities while for support activities are employing general platforms. The most important factor which influences the adoption rate of digital platforms is the image and then comes the advantages they bring. Regarding the clusters, four distinct groups were identified with specific value creation behaviors Digital Pathfinders, Basic Techies, Tech Blend, and Flexible Adopters. Practical implications Practical implications concern both the companies that use digital platforms and the companies that develop them. From the user perspective, this study sets a benchmark for different industries and presents the most common practices Regarding the companies that develop digital platforms, it is important to know the main deterrence factors, namely the lack of testing possibilities and the difficulty in choosing the most suitable solution. Taking into account the specific needs of the four clusters, developers can adapt their product and value proposition to stimulate the adoption of the digital platform. Originality/Value/Contribution This paper contributes to research on digital platforms in the context of transformational entrepreneurship related to crisis or catastrophic events such as pandemics or wars. Furthermore, it adds to existing literature on digital transformation by providing recommendations considering specific value chain activities. Although there are numerous studies on digital platforms, most of them come from developed countries, which makes them less relevant for developing/underdeveloped ones.

Original Research: Exploring U.S. Nurses' Perceived Duty to Care During the COVID-19 Pandemic.

Duty to care is both an integral concept in health care and a fundamental nursing obligation. But nurses' perceptions of duty to care can be moderated by their experiences in the practice setting. Research examining nurses' perceptions of their duty to care during the COVID-19 pandemic could shed light on how the pandemic is affecting the nursing workforce. This study aimed to examine nurses' sense of duty to care during the early months of the pandemic, using the Nash Duty to Care Scale (NDCS), and to compare the high-scoring nurses with the low-scoring nurses. This quantitative study used a descriptive, cross-sectional design. It was conducted among licensed RNs enrolled at two accredited nursing programs in the Northeast region of the United States. Data were collected via a demographics questionnaire and the NDCS. A two-step cluster procedure was used to categorize participants into two groups: those with high perceived duty to care (HPDC) and those with low perceived duty to care (LPDC). Independent t tests were performed to compare NDCS results between the two groups. Nearly two-thirds (61%) of the participants had total NDCS scores indicating an HPDC, while 39% had scores indicating an LPDC. Of the NDCS's four subscales, perceived obligation and perceived risk were the most important in separating participants into the low- and high-scoring groups. This study adds to the literature about the components that affected nurses' perceived duty to care and willingness to report to work during the early months of the pandemic. Just as nurses have a duty to care, health care organizations have an obligation to provide a safe working environment so that nurses can fulfill that duty without sacrificing personal safety. The study findings may guide health care leaders, systems, and organizations regarding how to create safer work environments that support the nurse's duty to care during disasters.

A cluster differences unfolding method for large datasets of preference ratings on an interval scale: Minimizing the mean squared centred residuals.

Clustering and spatial representation methods are often used in combination, to analyse preference ratings when a large number of individuals and/or object is involved. When analysed under an unfolding model, row-conditional linear transformations are usually most appropriate when the goal is to determine clusters of individuals with similar preferences. However, a significant problem with transformations that include both slope and intercept is the occurrence of degenerate solutions. In this paper, we propose a least squares unfolding method that performs clustering of individuals while simultaneously estimating the location of cluster centres and object locations in low-dimensional space. The method is based on minimising the mean squared centred residuals of the preference ratings with respect to the distances between cluster centres and object locations. At the same time, the distances are row-conditionally transformed with optimally estimated slope parameters. It is computationally efficient for large datasets, and does not suffer from the appearance of degenerate solutions. The performance of the method is analysed in an extensive Monte Carlo experiment. It is illustrated for a real data set and the results are compared with those obtained using a two-step clustering and unfolding procedure.

Who is motivated to accept a booster and annual dose? A dimensional and person-centered approach.

The transmissibility of new COVID-19 variants and decreasing efficacy of vaccines led authorities to recommend a booster and even an annual dose. However, people's willingness to accept new doses varied considerably. Using two independent longitudinal samples of 4596 (Mean age = 53.6) and 514 (Mean age = 55.9) vaccinated participants, we examined how people's (lack of) vaccination motivation for their first dose was associated with their intention to get a booster (Sample 1) and an annual dose (Sample 2) several months later (Aim 1). We also aimed to capture the impact of the motivational heterogeneity on these intentions by capitalizing on participants' different motivational profiles collected at baseline (Aim 2). Across both samples, autonomous motivation, controlled motivation, and distrust-based amotivation were uniquely related to, respectively, higher, lower, and even lower booster and annual dose intentions. Further, a two-step clustering procedure revealed five profiles, with the profiles characterized by higher autonomous motivation (i.e. Good Quality and High Quantity profiles) reporting the highest vaccination intentions and the profile characterized by the highest number of obstacles (i.e. Global Amotivated profile) yielding the lowest vaccination intentions. These results stress the critical need to support citizens' volitional endorsement of vaccination to harvest long-term benefits with respect to COVID-19.

Holiday Preferences and Travel Behavior of German Motorcyclists. A Cluster Analysis

Abstract Motorcycle tourism offers tourist destinations the opportunity to diversify their offer and pursue competitive advantage and economic success. However, motorcyclists’ holidaymaking practices remain underexplored so far and there is an assumption of homogeneity within the riders’ community. This paper argues that, despite common features, differences might stand out in riders’ motivations and local practices. To investigate these differences, cluster analysis is used to segment German motorcycle tourists, with the aim to identify sub-groups of travellers. Using a convenience sample of n=441 bikers, the paper discriminates three types of motorcycling tourists: the pleasure-seekers, the drifters and the focused bikers. The two-step clustering procedure is based on behavioral patterns (i. e. type of accommodation, group type and length of stay) and the results are later enriched using additional descriptors related to the attractiveness of local offers and the probability of undertaking non-riding activities. Theoretical and managerial implications are ultimately derived, acknowledging the exploratory nature of the research design.

Is Gen Z really that different? Environmental attitudes, travel behaviours and sustainability practices of international tourists to Canterbury, New Zealand

Age has a significant influence on environmental attitudes and behaviour but there is no consensus on the effect that generational cohort has on these attitudes and behaviour. Using the New Environmental Paradigm (NEP) as the theoretical lens, this study evaluates whether Gen Z is similar or different to three other generations (Gen X, Y and Baby Boomers) on their environmental attitudes toward travel. The sustainability practices that these generational cohorts undertake during their travel are also evaluated. Based on 615 useable surveys of international visitors to the Canterbury region of New Zealand, we identify segments of visitors based on environmental attitudes and behaviour toward travel and generational cohort using a two-step clustering procedure. The results confirm inter-generational differences in environmental attitudes and travel behaviours but also highlight intra-generational differences. Gen Z tourists are more likely to belong to “Environmental” or “Mixed-Bag Environmental” segments that are more likely engage in sustainable practices related to resource saving and buying local food compared to other generations. The findings have implications for destination marketing and management.

O5-3 Behavioural risk patterns among overweight and obese adolescents participating in the PRALIMAP-INES trial

BackgroundIt has been suggested that risk behaviours including diet, physical activity (PA), sedentary behaviour (SB), smoking and alcohol consumption cluster among adolescents. Our objective was to investigate clustering of risk behaviours in overweight and obese adolescents from the French PRALIMAP-InèS trial and to identify their socioeconomic correlates.MethodsInformation on diet (fruit, vegetables, sugary products and beverages), PA, SB (week and week-end days), smoking and alcohol consumption (current frequency and intoxication episodes) and socio-demographical data were collected using self-reported questionnaires at the trial inclusion. Behavioural risk factors were entered as categorical variables in a two-step clustering procedure: multiple correspondence analyses followed by a two-way clustering procedure based on hierarchical methods. Associations between cluster membership and socio-economic variables were investigated using multivariable multinomial logistic regression.ResultsA total of 1391 participants were included in analyses and four clusters were identified: (1) “Moderate to high PA, low soft drinkers, low alcohol consumers low SB, non-smokers” (n = 543; 39.0%), (2) “High SB and low fruits and vegetables consumers” (n = 376; 26.8%), (3) “Smokers and alcohol consumers” (n = 247; 17.7%) and (4) “High fruits and vegetable consumers, soft drinkers and low PA” (n = 229; 16.5%). Compared to the healthiest cluster (cluster 1), adolescents from cluster 2&3 (unhealthy clusters) were more likely boys, older, attending vocational high school and not living with their two parents. Adolescents from cluster 4 were more socially advantaged (according to the WHO family affluence scale) than those of cluster 1.ConclusionsRisk behaviour patterns in adolescents were shown to be clustered in both healthier and less healthy ways, with a complex interplay with socio-economic factors. Adapted to cluster Public health interventions may bring some benefits.

Behavioural risk patterns in adolescents with excess weight participating in the PRALIMAP-INÈS trial.

To investigate clustering of risk behaviours in adolescents with excess weight. Cross-sectional analysis of baseline data from the PRALIMAP-INÈS trial. Information on food frequency consumption (fruit, vegetables, sugary products and beverages), physical activity, sedentary behaviour (week and weekend days), smoking and alcohol consumption (current frequency and intoxication episodes) and socio-demographic data was collected using self-reported questionnaires. Behavioural risk factors were entered as categorical variables in a two-step clustering procedure: multiple correspondence analysis followed by hierarchical clustering. Associations between cluster membership and socio-demographic variables were investigated using multivariable multinomial logistic regression. French PRALIMAP-INÈS trial. Adolescents with excess weight. A total of 1391 participants (13-18 years old, 58·2 % female) were included in the analysis, which resulted in the identification of four groups of participants, including, respectively, 543 (39·0 %), 373 (26·8 %), 246 (17·7 %) and 229 (16·5 %) participants. Clusters 1 and 4 showed associations of rather healthy behaviours (high physical activity and low consumption of sugary products; high consumption of fruit and vegetables, respectively), while clusters 2 and 3 showed associations of rather unhealthy behaviours (high sedentary behaviour and low consumption of fruit and vegetables; smoking and alcohol consumption, respectively). Both social status and family structure were associated with cluster membership. Risk behaviour patterns in adolescents with excess weight were clustered in both healthier and less healthy ways, with a complex interplay with socio-demographic factors.

Identification and Temporal Characteristics of Earthquake Clusters in Selected Areas in Greece

The efficiency of earthquake clustering investigation is improved as we gain access to larger datasets due to the increase of earthquake detectability. We aim to demonstrate the robustness of a new clustering method, MAP-DBSCAN, and to present a comprehensive analysis of the clustering properties in three major seismic zones of Greece during 2012–2019. A time-dependent stochastic point model, the Markovian Arrival Process (MAP), is implemented for the detection of change-points in the seismicity rate and subsequently, a density-based clustering algorithm, DBSCAN, is used for grouping the events into spatiotemporal clusters. The two-step clustering procedure, MAP-DBSCAN, is compared with other existing methods (Gardner-Knopoff, Reasenberg, Nearest-Neighbor) on a simulated earthquake catalog and is proven highly competitive as in most cases outperforms the tested algorithms. Next, the earthquake clusters in the three areas are detected and the regional variability of their productivity rates is investigated based on the generic estimates of the Epidemic Type Aftershock Sequence (ETAS) model. The seismicity in the seismic zone of Corinth Gulf is characterized by low aftershock productivity and high background rates, indicating the dominance of swarm activity, whereas in Central Ionian Islands seismic zone where main shock-aftershock sequences dominate, the aftershock productivity rates are higher. The productivity in the seismic zone of North Aegean Sea vary significantly among clusters probably due to the co-existence of swarm activity and aftershock sequences. We believe that incorporating regional variations of the productivity into forecasting models, such as the ETAS model, it might improve operational earthquake forecasting.

Sperm kinetics and motility subpopulation in XY and YY Nile tilapia (Oreochromis niloticus) males

Incorporation of YY males into the commercial farming of Nile tilapia could generate populations composed of 100% males, but first, it is necessary to evaluate the quality parameters of the spermatozoa produced by a male with two Y chromosomes. The aim of the present study was to evaluate and compare the quality, kinetics and population structure of milt samples obtained from XY and YY Nile tilapia males. We used 60 males divided by sexual genotype into two groups, XY and YY. Milt volume, sperm concentration and several parameters of motility were measured by computer-assisted sperm analysis (CASA). Motility subpopulations were identified using a principal component analysis followed by a two-step cluster procedure. The values obtained for milt volume and sperm concentration showed significant differences (p < 0.05) with YY males showing the higher values. For motility parameters, linearity and straightness index showed significantly higher (p < 0.05) values for YY males while wobble index and mean amplitude of lateral head displacement were significantly higher (p < 0.05) for XY males. Four subpopulations were identified, two for each sexual genotype. Our results suggest that sperm quality of YY males is not negatively affected by the presence of two Y chromosomes.

Driving factors for the utilisation of healthcare services by people with osteoarthritis in Portugal: results from a nationwide population-based study

BackgroundWorldwide, the current management of knee osteoarthritis appears heterogeneous, high-cost and often not based on current best evidence. The absence of epidemiological data regarding the utilisation of healthcare services may conceal the need for improvements in the management of osteoarthritis. The aim of this study is to explore the profiles of healthcare services utilisation by people with knee osteoarthritis, and to analyse their determinants, according to Andersen’s behavioural model.MethodsWe analysed a sample of 978 participants diagnosed with knee osteoarthritis from the population-based study EpiReumaPt, in Portugal. Data was collected with a structured interview, and the diagnosis of knee osteoarthritis was validated by a rheumatologist team. With the Two-step Cluster procedure, we primarily identified different profiles of healthcare utilisation according to the services most used by patients with knee osteoarthritis. Secondly, we analysed the determinants of each profile, using multinomial logistic regression, according to the predisposing characteristics, enabling factors and need variables.ResultsIn our sample, a high proportion of participants are overweight or obese (82,6%, n = 748) and physically inactive (20,6%, n = 201) and a small proportion had physiotherapy management (14,4%, n = 141). We identified three profiles of healthcare utilisation: “HighUsers”; “GPUsers”; “LowUsers”. “HighUsers” represents more than 35% of the sample, and are also the participants with higher utilisation of medical appointments. “GPUsers” represent the participants with higher utilisation of general practitioner appointments. Within these profiles, age and geographic location – indicated as predisposing characteristics; employment status and healthcare insurance - as enabling factors; number of comorbidities, physical function, health-related quality of life, anxiety and physical exercise - as need variables, showed associations (p < 0,05) with the higher utilisation of healthcare services profiles.ConclusionsHealthcare utilisation by people with knee osteoarthritis is not driven only by clinical needs. The predisposing characteristics and enabling factors associated with healthcare utilisation reveal inequities in the access to healthcare and variability in the management of people with knee osteoarthritis. Research and implementation of whole-system strategies to improve equity in the access and quality of care are paramount in order to diminish the impact of osteoarthritis at individual-, societal- and economic-level.

High perceived isolation and reduced social support affect headache impact levels in migraine after the Covid-19 outbreak: A cross sectional survey on chronic and episodic patients.

ABSTRACTBackgroundPsychosocial variables are key factors influencing psycho-physical equilibrium in migraine patients. Social isolation and vulnerability to stressors may prevent efficient psychological adjustment negatively affecting adaptation to life changes, as that imposed during Covid-19 lockdown. Here, we explored psychosocial dimensions and changes in clinical condition during Covid-19 lockdown in migraine patients, with regard to migraine type and headache impact.MethodsSixty-four migraine patients (32 episodic and 32 chronic) and 64 healthy control subjects were included in a case-control cross-sectional study. A two-step clustering procedure split patients into two clusters, based on the Headache Impact Test. Perceived global distress, loneliness, empathy, and coping levels were compared in groups, as well as changes in clinical condition.ResultsMigraine patients reported higher general loneliness and lower social support compared to healthy control subjects. Emotional loneliness was more marked in patients with higher headache impact. This subgroup of patients more frequently reported changes in the therapeutic and care paths as the perceived cause of the occurrence of motor or extra-motor symptomatology.ConclusionsMigraine patients, especially those more severely affected, proved more vulnerable than healthy control subjects to Covid-19 lockdown. Long-lasting interruption of social interactions may be detrimental in fragile patients that are in need of structured support interventions to maintain psycho-physical wellbeing.

An emotion-based typology of wine consumers

Product consumption is a sensory experience that can evoke a wide range of emotional responses; and accordingly, the emotional component of food consumption has been widely addressed and has appeared in marketing literature with increasing frequency.To date, there is abundant literature on emotions elicited by product consumption, but there is little research concerning emotions and wine. In this context, we develop an emotion-based segmentation based on the emotions that consumers experience when consuming wine, both considering the valence and arousal dimensions of emotions. In addition, we profile and characterize the emotion-based obtained segments.For this purpose, an emotion-based cluster analysis is conducted through a two-step cluster procedure, followed by a MANOVA test on data from 1269 wine consumers.Our findings show that the average wine consumer does not exist, and that wine consumers cannot be seen as a homogenous group. More precisely, four clusters emerge from our results experiencing different emotions in wine consumption: “emotionally unattached”, “negatives”, “contented circumspects” and “wine lovers”. Results suggest that “wine lovers” is the most attractive segment due to their strong wine emotional bond; being the “negatives” the most challenging segment for wine makers. One useful insight for wineries is that it may not be possible to satisfy all these segments with one single wine.

Characterization of Buffalo Dairy Production Systems in Egypt Using Cluster Analysis Procedure

The study objective was to characterize and classify buffalo dairy production systems in Egypt. Ten governorates having high buffalo population density were selected as the study area. The data were collected from 1811 dairy buffalo farms using survey. Buffalo holders were face to face interviewed by constructed questionnaire. The survey was applied in two years (2010 and 2011). Two-Step Cluster procedure (CA) was used and analysis was repeated several times until the cluster quality came good (average silhouette ≥0.5). The algorithm selected the number of clusters, after calculating the Akaike’s information criterion (AIC). Statistics of CA showed that the numbers of farm in each cluster were 43 (2.4%) in cluster1 (CL1), 1364 (75.3%) in cluster2 (CL2) and 404 (22.3%) in cluster3 (CL3). CL1 farms had a good availability of facilities. The management practices were the higher in comparison with the farms in the other clusters. Management and feeding systems practices in CL1 ranged from medium to high. CL2 was the largest, with 1364 farms located in all the ten governorates. The availability of facilities and equipment were low or lacking. The management practices were the lowest in comparison with farms in other clusters. CL3 facilities availability were low to medium. The management practices were medium when compared with the farms in the other clusters. The results of the current study demonstrate the existence of a large variability among buffalo dairy production systems in Egypt. These systems variability should be taken into consideration for sustainable system development.

O3.8. DORSOLATERAL PREFRONTAL CORTEX IN DRUG-NAïVE FIRST EPISODE SCHIZOPHRENIA: DYNAMIC PHASE COHERENCE OF INFRASLOW OSCILLATIONS

BackgroundDorsolateral Prefrontal Cortex (DLPFC) has been identified as the seat of many synaptic changes in schizophrenia. Functional neuroimaging studies indicate inefficient recruitment of DLPFC, often termed as hypofrontality, that appears in conjunction with disrupted connectivity of DLPFC with other brain regions. Very Low Frequency Oscillations (VLFO or infraslow oscillations) stem from AMPA currents, and are thought to represent a slow, cyclic modulation of cortical gross excitability. These oscillations are phase-synchronised enabling long-distance communication. This synchrony fluctuates across time (dynamic), indicating state-shifts. Dynamic synchrony can be captured using variance of phase coherence (vPC). We aimed to isolate the brain regions showing abnormal vPC with right DLPFC in drug-naïve first episode schizophrenia compared to healthy controls. Based on our prior work indicating fronto-insular dysconnectivity, we hypothesized that anterior insula would show the most disrupted dynamic phase coherence with DLPFC among all other brain regions.Methods129 drug-naïve patients with first episode of schizophrenia (FES) and 197 age- sex- and education-level matched healthy controls (HC) were recruited. Based on Dosenbach’s atlas applied to 7.67 minutes (230 timepoints with TR=2 s) of eyes-open resting fMRI scan, we extracted timeseries of 160 functional network nodes, and identified right DLPFC with MNI coordinates (x=40,y=36,z=29). Wavelet-transformation was done to enable time-frequency analysis that decomposed the timeseries data into 3 bins of very low frequency oscillations (0.02–0.04 Hz, 0.04–0.06 Hz, 0.06–0.08 Hz). We then estimated phase coherence between DLPFC and other 159 regions at each timepoint, and the variance (vPC) across the entire acquisition. Regions showing aberrant vPC with right DLPFC were identified using FDR corrected 2-tailed p<0.05 as the threshold of statistical significance in a two-sample t test comparing HC and FES groups. A two-step clustering procedure using likelihood-distance measure was employed to stratify sub-groups of FES with or without vPC disruption. The resulting subgroups were compared based on clinical symptom scores using van der Gaag’s 5-factor PANSS model.ResultsThe FES group showed a significant reduction (FDR corrected p = 0.03) in vPC between right DLPFC and left anterior insula within the frequency band: 0.02 - 0.04 Hz. The rDLPFC-lAI path can be termed as a long-distance connection based on anatomical distance measure (82.6 mm, compared to a median of 75mm) when compared to HCs. FES group was split into 2 subgroups using the clustering procedure. FES-2 (n=51) had higher vPC of rDLPFC-lAI connectivity compared to HC (Hedges’ g: -2.0, p=0.001) while FES-1 (n=78) had lower vPC compared to HC (Hedges’ g: 0.47, p=0.009). FES-1 had more ‘emotional’ and ‘positive symptoms’ but had similar symptom loadings in other PANSS domains compared to FES-2.DiscussionReduced variability of phase coherence between anterior insula and DLPFC in schizophrenia confirms our prior hypothesis of Salience Executive Loop dysfunction in this illness. Current results indicate that aberrant connectivity with anterior insula is the major lateral prefrontal disruption even in a drug naïve state at rest. Further, this aberration seems to be specific to infraslow rather than other frequency bands, raising the possibility that this may be a key mechanism of modulating overall cortical excitability in schizophrenia. It is possible that this dysfunction is specific to a subgroup with more psychotic symptoms at first presentation.

Patterning of writing style evolution by means of dynamic similarity

This paper suggests a new methodology for patterning writing style evolution using dynamic similarity. We divide a text into sequential, disjoint portions (chunks) of the same size and exploit the Mean Dependence measure, aspiring to model the writing process via association between the current text chunk and its predecessors. To expose the evolution of a style, a new two-step clustering procedure is applied. In the first phase, a distance based on the Mean Dependence between each pair of chunks is evaluated. All document chunks in a pair are embedded in a high dimensional space using a Kuratowski-type embedding procedure and clustered by means of the introduced distance. In the next phase, the rows of the binary cluster classification documents matrix are clustered via the hierarchical single linkage clustering algorithm. By this way, a visualization of the inner stylistic structure of a texts’ collection, the resulting classification tree, is provided by the appropriate dendrogram. The approach applied to studying writing style evolution in the “Foundation Universe” by Isaac Asimov, the “Rama” series by Arthur C. Clarke, the “Forsyte Saga” of John Galsworthy, “The Lord of the Rings” by John Ronald Reuel Tolkien and a collection of books prescribed to Romain Gary demonstrates that the suggested methodology is capable of identifying style development over time. Additional numerical experiments with author determination and author verification tasks exhibit the high ability of the method to provide accurate solutions.

Design principles for protected area certificates: a case study on strategic investor groups

Biological capacity of earth is limited. While it is obvious at first glance, it has been ignored for decades. Policy makers attempt to overcome the persistent depletion of the human livelihood base through the establishment of protected areas. However, the financial means to sustainably manage a representative network of protected areas on a global scale do not yet exist, and particularly, private sector investment is extremely modest. One option for increasing private investment flows is the development of a market place for protected area certificates (PACs) issued for geographical areas managed according to social and environmental best practices. This paper utilizes semi-structured expert interviews with 39 German companies to analyze major product and market requirements for the sound implementation of an international certification scheme for PACs. Based on a triangulation approach that combines quantitative and qualitative evaluations with the two-step clustering procedure for strategic investor groups, seven design principles are determined that might encourage voluntary investment funds from the private sector, and thus support the sustainable management of protected areas. Having a look at existing markets for protected areas, one scheme provides a good foundation for the defined design principles: the LifeWeb initiative—an online clearing house for protected area developers and potential investors.

Are All My Volunteers Here to Help Out? Clustering Event Volunteers by Their Motivations

Posed as a question that an event organizer might contemplate in terms of how best to attract and retain event volunteers, this study adds to the event volunteering literature by cluster analyzing volunteers sampled at four sports events using items from the Special Event Volunteer Motivation Scale (SEVMS). The 28 items were first subjected to Exploratory Factor Analysis resulting in four factors (Solidary, Purposive, External Traditions/Commitments, and Spare Time), followed by a two-step clustering procedure and a series of post hoc tests to describe and validate the clusters. As a result of this procedure, three distinct clusters were formed: the Altruists, Socials, and Indifferents. The Altruists and Socials were primarily driven by two distinct internal factors, which respectively represented the Purposive and Solidary factors. The Indifferents appeared to be pushed into volunteering by external forces, rather than intrinsic motivations. Validation revealed that the Indifferents were significantly less satisfied with their volunteer experience than the other two clusters and were also less likely to volunteer in the future. Across the four events sampled, there were distinct patterns of cluster representation, with one event in particular substantially overrepresented by the more negatively inclined Indifferents. The management and research implications of these findings are discussed.

Elevated peripheral cytokines characterize a subgroup of people with schizophrenia displaying poor verbal fluency and reduced Broca's area volume.

Previous studies on schizophrenia have detected elevated cytokines in both brain and blood, suggesting neuroinflammation may contribute to the pathophysiology in some cases. We aimed to determine the extent to which elevated peripheral cytokine messenger RNA (mRNA) expression: (1) characterizes a subgroup of people with schizophrenia and (2) shows a relationship to cognition, brain volume and/or symptoms. Forty-three outpatients with schizophrenia or schizoaffective disorder and matched healthy controls were assessed for peripheral cytokine mRNAs (interleukin (IL)-1β, IL-2, IL-6, IL-8 and IL-18), intelligence quotient, memory and verbal fluency, symptom severity and cortical brain volumes integral to language (that is, Broca's and Wernicke's areas). IL-1β mRNA levels were 28% increased in schizophrenia compared with controls (t(82)=2.64, P<0.01). Using a two-step clustering procedure, we identified a subgroup of people displaying relatively elevated cytokine mRNA levels (17/43 people with schizophrenia and 9/42 controls). Individuals with schizophrenia in the elevated cytokine subgroup performed significantly worse than the low-cytokine subgroup on verbal fluency (F(1,40)=15.7, P<0.001). There was a 17% volume reduction of the left pars opercularis (POp) (Broca's area) in patients with elevated cytokines compared with patients with lower cytokines (F(1,29)=9.41, P=0.005). Negative linear relationships between IL-1β mRNA levels and both verbal fluency and left POp volume were found in schizophrenia. This study is among the first to link blood biomarkers of inflammation with both cognitive deficits and brain volume reductions in people with schizophrenia, supporting that those with elevated cytokines represent a neurobiologically meaningful subgroup. These findings raise the possibility that targeted anti-inflammatory treatments may ameliorate cognitive and brain morphological abnormalities in some people with schizophrenia.

Elderly patients attended in emergency health services in Brazil: a study for victims of falls and traffic accidents.

The article aims to describe the profile of elderly victims of falls and traffic accidents from the data of the Surveillance Survey of Violence and Accidents (VIVA). The VIVA Survey was conducted in the emergency health-services of the Unified Health System in the capitals of Brazil in 2011. The sample of elderly by type of accident was subjected to the two-step cluster procedure. Of the 2463 elderly persons in question, 79.8% suffered falls and 20.2% were the victims of traffic accidents. The 1812 elderly who fell were grouped together into 4 clusters: Cluster 1, in which all had disabilities; Cluster 2, all were non-white and falls took place in the home; Cluster 3, younger and active seniors; and Cluster 4, with a higher proportion of seniors 80 years old or above who were white. Among cases of traffic accidents, 446 seniors were grouped into two clusters: Cluster 1 of younger elderly, drivers or passengers; Cluster 2, with higher age seniors, mostly pedestrians. The main victims of falls were women with low schooling and unemployed; traffic accident victims were mostly younger and male. Complications were similar in victims of falls and traffic accidents. Clusters allow adoption of targeted measures of care, prevention and health promotion.