Weak Predictor Research Articles

Encouraging green product purchase: Green value and environmental knowledge as moderators of attitude and behavior relationship

AbstractGreen purchase behavior is evolving and is of growing interest to academic and business circles. To encourage the adoption of green products, it is important to identify moderators that can enhance the consistency between attitude and behavior in the consumption of green products. Within this scope, the moderating effect of psychological factors, that is, green value and environmental knowledge on the link between green purchase attitude and behavior, is investigated. More specifically, this study proposed that green value and environmental knowledge simultaneously moderated the effect of attitude on behavior in relation to green purchase. A data set of 447 samples in Thailand collected through a personal survey method was analyzed. The results from Hayes' PROCESS technique shows that attitude toward green purchase is a weak predictor of green purchasing behavior. However, with low degree of green value and high degree environmental knowledge, green purchase attitude elicited the strongest effect on behavior.

Preliminary Evidence-Based Method of Medical Kit Design for Wilderness Expeditions Modeled by a High-Altitude Expedition to Mount Kilimanjaro

BackgroundWilderness expeditions require extensive planning and the correct medical supplies to ensure clinical care is possible in the event of illness or injury. There are gaps in the literature regarding evidence-based methods for medical kit design. ObjectivesThis report describes a preliminary method for predicting medical events to determine medical supply requirements for a wilderness expedition. The performance of this method was evaluated using data from the 2017 Equal Playing Field (EPF) expedition to Mount Kilimanjaro. MethodsEight reports documenting medical events during wilderness expeditions were reviewed. Incidence data were consolidated into a new dataset, and a subset of data from adventure race expeditions (ARS) was created. The cumulative incidence of medical events was then predicted for the 9-day EPF expedition. The medical supply list was determined based on indication. The effectiveness of the full dataset and ARS to predict the cumulative incidence of medical events by category during the EPF expedition was evaluated using regression analysis. ResultsThe ARS predicted a higher incidence rate of medical events than the full dataset did but underestimated the EPF expedition incidence rate. The full dataset was a weak predictor of the cumulative incidence of medical events by category during the EPF expedition, while the ARS was a strong predictor. The finalized medical kit overestimated all nonreusable supplies. ConclusionsThe medical kit created using this method managed all medical events in the field. This report demonstrates the potential utility of using a tailored, evidence-based approach to design a medical kit for wilderness expeditions.

The Effect of Ad Authenticity on Advertising Value and Consumer Engagement: A Case Study of COVID-19 Video Ads

This study explored the role of ad authenticity in influencing consumers’ ad evaluations and their engagement intention in the context of COVID-19 video advertising. Results showed that aside from informativeness and entertainment, three dimensions of ad authenticity—brand essence, realistic plot, and message credibility—were positively related to consumers’ evaluation of ad value, which further increased ad attitude and social media engagement intention. Interestingly, a realistic plot was the strongest predictor of advertising value, with informativeness as the weakest predictor. Our findings suggest that such a shift of emphasis on content-specific ad authenticity would increase the effectiveness of pandemic-related brand communication on social media. Implications, limitations, and future research directions are discussed.

Age-based differences in quantity and frequency of consumption when screening for harmful alcohol use.

Background and aimsSurvey questions on usual quantity and frequency of alcohol consumption are regularly used in screening tools to identify drinkers requiring intervention. The aim of this study was to measure age‐based differences in quantity and frequency of alcohol consumption on the Alcohol Use Disorders Identification Test (AUDIT) and how this relates to the prediction of harmful or dependent drinking.DesignCross‐sectional survey.SettingAustralia.ParticipantsData were taken from 17 399 respondents who reported any alcohol consumption in the last year and were aged 18 and over from the 2016 National Drug Strategy Household Survey, a broadly representative cross‐sectional survey on substance use.MeasurementRespondents were asked about their frequency of consumption, usual quantity per occasion and the other items of the AUDIT.FindingsIn older drinkers, quantity per occasion [β = 0.53, 95% confidence interval (CI) = 0.43, 0.64 in 43–47‐year‐olds as an example] was a stronger predictor of dependence than frequency per occasion (β = 0.24, 95% CI = 0.17, 0.31). In younger drinkers the reverse was true, with frequency a stronger predictor (β = 0.54, 95% CI = 0.39, 0.69 in 23–27‐year‐olds) than quantity (β = 0.26, 95% CI = 0.18, 0.34 in 23–27‐year‐olds). Frequency of consumption was not a significant predictor of dependence in respondents aged 73 years and over (β = −0.03, 95% CI = −0.08, 0.02). Similar patterns were found when predicting harmful drinking. Despite this, as frequency of consumption increased steadily with age, the question on frequency was responsible for at least 65% of AUDIT scores in drinkers aged 53 years and over.ConclusionsIn younger drinkers, frequent drinking is more strongly linked to dependence and harmful drinking subscale scores on the Alcohol Use Disorders Identification Test (AUDIT) than quantity per occasion, yet quantity per occasion has a stronger influence on the overall AUDIT score in this group. In older drinkers, frequency of consumption is not always a significant predictor of the AUDIT dependence subscale and is a weak predictor of the harmful drinking subscale.

Young forests and fire: Using lidar–imagery fusion to explore fuels and burn severity in a subalpine forest reburn

AbstractAnticipating fire behavior as climate change and fire activity accelerate is an increasingly pressing management challenge in fire‐prone landscapes. In subalpine forests adapted to infrequent, stand‐replacing fire, self‐limitation of burn severity in short‐interval fire is incompletely understood. Spatially explicit fuels data can support assessments of landscape‐scale fire risk and fuel feedbacks on burn severity. For a ~1450‐km2 largely forested landscape in the US Northern Rocky Mountains, we used airborne lidar and imagery to predict and map canopy and surface fuels. In a fire that burned mature (>125‐year‐old) and also reburned young (~30‐year‐old) subalpine forest, we then asked: (1) How do prefire fuels and burn severity compare between young and mature forests that burned under similar fire weather conditions? (2) How well do prefire fuels and forest structure predict burn severity under extreme versus moderate fire weather? Lidar–imagery fusion predicted fuel characteristics with high accuracy across forest and shrubland vegetation. Young postfire forests had abundant, densely packed canopy fuels, and both young and mature forests had similar canopy fuel loads and coarse wood biomass. Under similar weather conditions, young and mature forests burned at similar severity. Overall, fuels were weak predictors of burn severity and, surprisingly, better predicted severity under extreme rather than moderate fire weather. Our findings are relevant for subalpine landscapes increasingly dominated by young lodgepole pine (Pinus contorta var. latifolia) forests vulnerable to short‐interval fire and provide a benchmark to assess how fuels influence burn severity in future fires. Fire managers should continually reassess fuels and update expectations about fire behavior as landscapes change. Although recovering postfire forests can limit fire spread and severity for a period of time, our results suggest that young subalpine forests in the Northern Rocky Mountains have sufficient fuel loads to burn at high severity and should not be considered effective fire breaks.

Acute Kidney Injury Following Mannitol Infusion in Neurosurgical Patients

Background: To evaluate the acute kidney injury (AKI) predictors and their predictive performance during mannitol infusion, and the impact of AKI on in-hospital mortality of neurocritically ill patients.Methods: This was a retrospective, observational study of patients who were admitted at a tertiary university hospital, Seoul, Republic of Korea, neurosurgical intensive care unit (ICU) from January 2013 to December 2019. We included neurosurgical patients on mannitol infusion admitted in the ICU The primary endpoint was the occurrence of AKI.Results: A total of 3,964 patients were included in the final analysis. AKI was detected in 540 (13.6%) patients on mannitol infusion. Measured osmolality and osmolar gap were significantly higher in patients with AKI than those without (both p< 0.001). However, the predictive power of the two indicators was similar and were both weak predictors of AKI (both C-statistic <0.650). In the multivariable analysis, maximal measured osmolality, chronic kidney disease, Acute Physiology and Chronic Health Evaluation 2 score on ICU admission, use of vasopressor, use of glycerin, mechanical ventilation, and invasive ICP monitoring were significantly associated with AKI. In-hospital mortality was significantly higher in patients with AKI than those without (11.1% vs. 1.4%, p< 0.001).Conclusions: Based on our findings, kidney injury may be associated with poor clinical outcomes in neurosurgical and neurocritically ill patients, and monitoring serum osmolality and OG remains important in the prevention of kidney injury for patients on mannitol infusion. Moreover, clinical factors related to ICU management and pre-existing renal disease may aggravate AKI during mannitol infusion.

Rabbit Elastase Aneurysm Model Mimics the Recurrence Rate of Human Intracranial Aneurysms following Platinum Coil Embolization.

Intracranial aneurysms treated with coils have been associated with incomplete occlusion, particularly in large or wide-neck aneurysms. This study aimed to validate the accuracy of the rabbit elastase model in predicting aneurysm recurrence in humans treated with platinum coils. Elastase-induced saccular aneurysms were induced in rabbits and embolized with conventional platinum coils. The recurrence rates of aneurysms were retrospectively analyzed. Morphologic characteristics of aneurysms, angiographic outcomes, and histologic healing were evaluated. A total of 28 (15.3%) of 183 aneurysms recurred. The aneurysm recurrence rate observed in this study (15.3%) is similar to those reported in multiple analyses of aneurysm recurrence rates in humans (7%-27%). The rate of recurrence was higher in aneurysms treated without balloon assistance (19/66, 28.8%) compared with those treated with balloon assistance (9/117, 7.7%). Aneurysms treated with balloon-assisted coiling had a lower recurrence rate (OR = 0.17; 95% CI, 0.05-0.47; P = .001) and higher occlusion rate (OR = 6.88; 95% CI, 2.58-20.37; P < .001) compared with those treated without balloon-assisted coiling. In this rabbit elastase-induced aneurysm model, packing density and aneurysm volume were weak predictors of aneurysm recurrence; however, the packing density was a good predictor of the occlusion rate (OR = 1.05; 95% CI, 1.02-1.10; P = .008). The rabbit elastase aneurysm model may mimic aneurysm recurrence rates observed in humans after platinum coil embolization. Moreover, balloon assistance and high packing densities were significant predictors of aneurysm recurrence and occlusion.

Factors affecting consumer attitudes to fungi-based protein: A pilot study

Meat substitutes using alternative proteins can facilitate sustainable diets without compromising animal welfare. The fungal protein, also called mycoprotein is the biomass that results from the fermentation of a filamentous fungus. This paper reports the results of a consumer acceptance study of fungal protein-based meat substitutes using a mixed-method design with a web-based survey and a series of semi-structured interviews amongst European participants. Based on the description provided in the survey, 56% of participants were not directly familiar with fungal proteins but they understood its potential societal benefits. The overall Food Technology Neophobia Score (FTNS) of the sample was moderate (M = 40.0, range = 19–62), with more neophilic participants (52.9%) than neophobic (47.1%). FTN was a significant but weak predictor of Perceived Benefits (PB) and Purchase Intentions (PI). Younger participants perceived fungal proteins more positively, and city-dwellers had higher PI than rural dwellers. Reducetarians were more likely to purchase fungal proteins, compared to unrestricted omnivores. Participants with lower acceptance of fungal proteins’ association with mould had significantly lower PI than those who were comfortable with it. In turn, familiarity with fungal protein was positively associated with mould acceptance. The qualitative data suggested that the sensory attributes were the most important factor in the acceptance of meat substitutes. The participants also valued clean label products which were perceived as healthier. Familiarity with other products containing mould seemed to assuage concerns and drive acceptance of fungal protein. The findings suggest that the overall acceptance of fungal protein is still rather low. This may be attributed to the perceived low appeal and tastiness of available fungal protein products.

Facilitating free and paid vaccine acceptance in Malaysia: effectiveness of vaccine and fear of COVID-19

PurposeThis study aims to examine how demographic and psychological predictors of free and paid vaccine acceptance operate within an infectious environment. The psychological predictors were derived from the protection motivation theory (PMT), including the appraised effectiveness of vaccine in containing the pandemic and the fear of COVID-19.Design/methodology/approachA representative data set that consists of responses from 2,850 Malaysians was used in this study. Multi-level modelling was used to analyse the data.FindingsResults indicated that the acceptance of free and paid vaccination did not differ by region. This suggests that the effects of the included psychological predictors on vaccine acceptance are independent from the environment. Malaysians are more likely to endorse both free and paid vaccination when it is perceived as effective in controlling the pandemic. When the vaccine is deemed as an effective preventive of COVID-19, Malaysians tend to seek free vaccination. Although fear of COVID-19 did significantly predict the endorsement of vaccination, it is a weaker predictor than the perceived effectiveness of vaccine.Originality/valueThis research used a large representative data set and the PMT framework in addressing vaccine acceptance in Malaysia.

Factors Influencing Cloud Computing Adoption Among SMEs: The Jordanian Context

Cloud computing technology has proved to be an important technological solution, especially for small and medium- sized businesses (SMEs), by providing many opportunities for companies to enhance their operations, reduce cost, improve scalability and flexibility, and make more efficient use of technology. Despite its benefits, most SMEs are still hesitant about adopting cloud computing. The purpose of this study is to assess the factors that influence cloud computing adoption among SMEs in Jordan. This study does so by developing a research model based on the Technology Organization Environment (TOE) and Diffusion of Innovation (DOI) .These theories overlap in terms of the characteristics that strengthen the explanation of adoption. An online questionnaire was used to collect data from 244 SMEs registered in Jordan. A multiple regression test was implemented to examine the proposed model. The results indicate that seven factors significantly affect cloud computing adoption among SMEs. Among these factors, cost reduction was found to be the strongest predictor, while the weakest predictor was firm size. However, the firm’s scope insignificantly influenced cloud computing adoption among SMEs in Jordan. This finding could provide insights for SMEs decision- makers when it comes to adopting cloud computing. In addition, it provides insights for practitioners in terms of recognizing the important factors that encourage or prevent SMEs from adopting cloud computing.

Targeting predictors in random forest regression

Random forest (RF) regression is an extremely popular tool for analyzing high-dimensional data. Nonetheless, its benefits may be lessened in sparse settings due to weak predictors, and a pre-estimation dimension reduction (targeting) step is required. We show that proper targeting controls the probability of placing splits along strong predictors, thus providing an important complement to RF’s feature sampling. This is supported by simulations using finite representative samples. Moreover, we quantify the immediate gain from targeting in terms of the increased strength of individual trees. Macroeconomic and financial applications show that the bias–variance trade-off implied by targeting, due to increased correlation among trees in the forest, is balanced at a medium degree of targeting, selecting the best 5%–30% of commonly applied predictors. Improvements in the predictive accuracy of targeted RF relative to ordinary RF are considerable, up to 21%, occurring both in recessions and expansions, particularly at long horizons.

Biomarker clustering in autosomal dominant Alzheimer's disease.

As the number of biomarkers used to study Alzheimer's disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others. We used hierarchical clustering to group 19 cross-sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO). Biomarkers identified included clinical assessments, neuroimaging, cerebrospinal fluid amyloid, and tau, and emerging biomarkers of neuronal integrity and inflammation. Three primary clusters were identified: neurodegeneration, amyloid/tau, and emerging biomarkers. Feature selection identified amyloid and tau measures as the primary predictors of mutation status and EYO. Emerging biomarkers of neuronal integrity and inflammation were relatively weak predictors. These results provide novel insight into our understanding of the relationships among biomarkers and the staging of biomarkers based on disease progression.

Predictors of Deformity in Patients with Progressive Collapsing Foot Deformity and Valgus of the Ankle

Category:Hindfoot; Ankle; Ankle Arthritis; Midfoot/ForefootIntroduction/Purpose:Markers used for diagnosis and severity grading are well studied in patients with Progressive Collapsing Foot Deformity (PCFD). Medial facet subluxation (MFS) in weight-bearing computerized tomography (WBCT) has been established as an early indicator of peritalar subluxation (PTS). When the disease affects the ankle leading to a valgus talar tilt (class E), structures distal to this topography may behave differently, trying to compensate for proximal deformity. The aim of this study is to assess predictors of deformity in PCFD patients with and without valgus of the ankle. Our hypothesis is that MFS cannot be used in Class E patients as an accurate marker for the evaluation and staging of PCFD.Methods:In this IRB-approved retrospective case-control study, we analyzed WBCT imaging of 21 consecutive patients with PCFD with valgus of the ankle and 64 controls (flexible PCFD without ankle involvement). MFS (defined by the percentage of uncoverage), middle facet incongruence angle, middle cuneiform-to-floor distance, forefoot arch angle, talonavicular uncoverage angle, hindfoot moment arm (HMA), Foot and Ankle Offset (FAO), and talar tilt angle (TTA) were obtained and compared between groups using one-way ANOVA. A multivariate regression analysis was performed to evaluate which of the measurements influenced the alignment. A partition prediction model was constructed to assess how the variables contributed to the deformity. P values <0.05 indicated statistical significance.Results:Differences between groups were found for MFS, HMA, FAO, and TTA, with a lower mean value of MFS in PCFD patients with valgus of the ankle. An inverse relation between MFS and TTA was found, which was demonstrated by an increase in the talar tilt and a decrease in middle facet uncoverage. FAO values were affected by MFS in the control group (R2: 0.25) but not in the ankle valgus group (R2: 0.001), which was influenced mainly by the TTA (R2: 0.53). Additionally, a FAO value higher than 12.14 was found to be a strong predictor of deformity at the ankle.Conclusion:Medial facet subluxation was lower in patients with PCFD and valgus of the ankle (Class E), which demonstrates that MFS is a weak predictor of deformity severity. Therefore, this suggests that talar tilt angle and Foot and Ankle Offset should be used as disease markers in this group of patients. Furthermore, a FAO value above 12.14 may be an indicator of ankle involvement in PCFD patients.

Immediate side effects of Comirnaty COVID-19 vaccine: A nationwide survey of vaccinated people in Israel, December 2020 to March 2021.

BackgroundCOVID-19 vaccine safety is of major interest worldwide, since there is no prior experience with it. Israel was one of the first countries to widely use the Comirnaty vaccine.AimWe aimed to assess the vaccine's short-term side effects directly from a large population and to predict influencing factors for self-reporting side effects.MethodsIn a retrospective cohort study, we investigated self-reported systemic vaccine side-effects using electronic surveys sent to vaccinated individuals between 20 December 2020 and 11 March 2021, within 3 days following administration of the first and second dose. We determined predictors for reporting systemic side effects by logistic regression.ResultsA total of 1,213,693 patients received at least one vaccine dose and 301,537 (24.8%) answered at least one survey. Among them, 68,162 (30.4%) and 89,854 (59.9%) individuals filled the first and the second dose surveys, respectively, and reported one or more side effects. Most common side effects were fatigue, headache and myalgia. Several respondents reported facial paraesthesia after first and second dose, respectively (n = 1,675; 0.7% and n = 1,601; 1.1%). Individuals younger than 40 years and women reported side effects more frequently than others, but pregnant women reported less. Pregnancy was a weak predictor for reporting any side effect in general and in particular fatigue, myalgia, headache, chills and fever.ConclusionsWe found further support for minor short-term side effects, within 3 days of receiving the Comirnaty vaccine. These findings from vaccine recipients in general and pregnant women in particular can improve vaccine acceptance.

Morphometry of Human Trachea in Male and Female using Computerized Tomography- A Comparative Study

Background: The architecture of the trachea can help doctors choose the right size of the endotracheal tube for patients. Non-invasive procedures like cadaveric dissection (CD) and Computed Tomography (CT) scans can also be used in the investigation. Objective: to describe the morphometry of a normal human trachea on CT scans and compare it to data from other studies Methodology: The normal CT scan pictures of 110 patients (69 males and 41 females) were analyzed in this prospective investigation. A 64-slice CT scanner was used to do chest CT scans. DICOM, a program for digital imaging and communication in medicine, was used to collect the data. For each parameter, the research population's lowest and maximum values were established. The correlation between all research variables and height and weight was determined using Pearson's correlation method. Height and weight were used as predictors in a regression analysis of substantially correlated factors. Results: In males, the AP and transverse diameters were substantially linked with height. The diameter of the AP and the CSA were found to be substantially linked with weight. A-P diameter, cross-sectional area, and volume were shown to be poorly predicted by weight. Weak predictors of length and transverse diameter were found to be height. In females, there was no association between height or weight with any of the research parameters. It was discovered that neither body mass index (BMI) nor height (or weight) could predict the dependent variables. Conclusion: The data might be valuable in the setup and design of tracheostomy tubes and endotracheal tubes in the future. Keywords: Trachea, diameters, Cross-sectional area, Volume, Computerized tomography.

Proximal Junction Kyphosis in Adult Scoliosis: Best Postoperative Radiological Predictors-A Retrospective Cohort Study.

Background Proximal junction kyphosis (PJK) is the postsurgical radiographic event seen in the surgical plane after the fusion of a spinal deformity. Unfavorable health outcomes have been reported in symptomatic PJK patients compared to non-PJK patients. Methods The data for adult scoliosis patients who underwent curve correction were extracted from the hospital database. Pelvic and spinal parameters were measured and calculated to compare four predictive formulae for occurrences of PJK. Formula 1. Restoration of hypothetical values of lumbar lordosis (LL) and thoracic kyphosis (TK) according to pelvic incidence (PI). Formula 2. Evaluation of global sagittal alignment. Formula 3. Restoration of the apex of LL to its hypothetical position according to the spine shape. Formula 4. Evaluation of positive-sum and negative-sum of (LL + TK). Results A total number of cases were 52. There were 14 cases of PJK. The incidence of PJK was 26.9%, and the mean age for PJK cases was 63.2 ± 5.2. The excellent predictor for occurrences of PJK was formula 3. Postsurgical sagittal apexes of lumbar lordosis were located in their hypothetical position in 24 cases, and 12.5% of these cases developed PJK. While sagittal apexes were not located in their hypothetical position in 28 patients, PJK occurred in 39.3% of them (P=0.03, OR: 4.53, (95% CI: 1.09–18.9)). The second good predictor for occurrences of PJK was formula 2 (GSA >45° versus GSA <45° OR = 2.5, (95% CI: 0.67–9.38), P=0.17). The other two formulae (1 and 4) were not good predictors for occurrences of PJK. Conclusion Among the four proposed formulae for predicting occurrences of PJK, the position of the sagittal apex of lumbar lordosis is an excellent predictor of the development of PJK, followed by GSA. Hypothetical values of LL and TK, and positive or negative-sum of (LL + TK), are weak predictors for occurrences of PJK.

Religious Exclusivism and Mass Beliefs about the Religion v. Science Debate: A Cross-National Study

When religion and science are in conflict, who supports religion? Using data from 71 diverse societies in the World Values Survey (n = 120,728), this study assesses the relative predictive strength of science optimism, moral concerns about science, religiosity, and religious exclusivism. Perhaps counterintuitively, science beliefs (science optimism, in particular) are weak predictors of the outcome, even in wealthy societies with high levels of scientific productivity. In contrast, believing that only one’s religion is acceptable is the strongest predictor of choosing religion over science; this is generally consistent across religious groups, regions, and specific countries/territories. These findings suggest that making the public more aware of major scientific advances will not, by itself, increase the cultural authority of science—especially if it is explicitly contested by another influential social institution. The implications for social scientific theories of modernization and secularization are discussed.

Strong Declines of the White Stork Ciconia ciconia Population in South-Western Poland: A Differentiated Importance of Altitude and Land Use Changes

Studies of long-term trends in avian populations require large-scale data not available for most bird species. The White Stork Ciconia ciconia is unique being monitored for over a century and well-reflecting modern environmental changes. Its worldwide and national populations are estimated every 10 years thanks to the International White Stork Censuses (IWSC). We present the yet unpublished data of the last IWSC 2014 from the main species stronghold, Poland. We assessed the population size and compared its changes with the previous IWSC 2004 in 23% of the country area, including mountains. We looked for potential drivers of trends among land use transformations, checked population changes along altitudinal gradient, and compared the long-term trends in the global, national and regional populations. In 2014, 2560 pairs (3.61 pairs/100 km2) bred in south-western Poland, a decline by 35.5% compared to 2004. Decreases were strongly inversely related to the altitude, i.e. declines in lowlands were twice as high as in the mountains. Changes in area of grasslands, croplands, forests, and built-up areas were all weak predictors of the decline. Stork decrease in south-western Poland contradicts a stable country-wide trend in 2004–2014 (although the latest countrywide data also suggest a decline), which is inconsistent with the increase of the global population. Heterogeneity in trends indicates that Poland could be currently viewed as a transitional area, lying between large breeding areas inhabited by increasing stork populations. Notably, the western border between areas of increases and decreases coincides with the division into two migratory populations suggesting that the heterogeneity of trends may be related to migration paths and wintering grounds. Overall, our data confirm recent range shift of the species, and show difficulties in drawing general conclusions on stork demography based on regional data.

When firms go international: deliberate or random?

PurposeThe net outward investment position (NOIP) indicator is insufficient for the purposes of understanding firms’ internationalization decision-making behaviour. The indicator does not allow for the withdrawal of insights into the structure of an economy and is a weak predictor of the degree of foreign direct investment. The purpose of this paper is to argue that a typology of firms aggregated according to intrinsic characteristics of those firms is a better predictor of the degree of internationalization of an economy than the NOIP.Design/methodology/approachThis paper uses a database of 2,133 firms located in Portugal with international operations, made available by AICEP, a government agency. This paper uses multiple correspondence and cluster analyses to build a typology of firms and obtains evidence of common characteristics of the constituent groups.FindingsThis paper identifies a typology of firms characterized by five types differentiated by firm age, length of internationalization process, sector of economic activity, legal status and psychological/cultural proximity. These variables suggest an evolutionary, iterative, self-learning approach to internationalization, which can be better explained by the combined use of the investment development path (IDP) framework, the Uppsala Evolutionary School and Vernon’s product life cycle theory. Additionally, this paper finds that the most striking differences between developed and developing host countries are in terms of the economic sector, legal status of the firm and belonging (or not) to an economic group.Originality/valueThis paper establishes a link between the IDP framework, the Uppsala Evolutionary School and Vernon’s product life cycle theory, using a categorization of firms made according to selected characteristics to understand the internationalization of firms.

What Factors Make Online Travel Reviews Credible? The Consumers’ Credibility Perception-CONCEPT Model

Online reviews have become a fundamental element in searching for and buying a tourism service. In particular, in the phase of post-pandemic caused by the COVID-19, social media are important channels of inspiration of dreams and encouragement to begin envisioning future trips. However, the growing trend of fake reviews is becoming a big issue for consumers. This study proposes and empirically validates a new model that enables predicting consumers’ Credibility Perception of Online Reviews (CPOR) related to tourism, considering all integrated factors of the communication process. A survey was carried out via a structured questionnaire. In particular, 615 answers from Italian travel groups were collected, and correlation and regression analyses were conducted. Results show that the website brand, advisor’s expertise, reviews’ sidedness and consistency, and consumer experience are significant predictors of CPOR. Website usability and reputation are instead weak predictors. This study provides the design and test of a credibility model, contributing to the theoretical and empirical advancement of the literature and enhancing the knowledge on consumer behavior.