Shift In Preference Research Articles

The Textbook Dilemma: Digital or Print? Evidence from a Selected US University

The increasing price of textbooks impacts students of higher education in the world. E-textbooks are becoming popular among students at all levels of education, especially at the university level. There is a shift in students reading habits and preferences towards e-textbooks. This growing trend has encouraged researchers to gather information about students' experiences, attitudes, and perceptions regarding using e-textbooks and their impact on the learning process. This study surveys undergraduate students in a small mid-western university in the USA. Data is collected from students studying four different colleges. A total of 346 questionnaires were collected. The findings revealed that 34.39% of the current users in the total sample do not want to use e-textbooks in the future. The predominant factors influencing the adoption of e-textbooks over print textbooks are cost, learning and engagement in interactive exercises, convenience, and flexibility. The study suggests some initiatives that educators, technology experts, designers, and universities can take for more students to adopt a digital version of textbooks to solve the problem of affordability.

How false feedback influences decision‐makers' risk preferences

AbstractRecent decision‐making research provides empirical evidence that human risk preferences are constructed “on the fly” during risk elicitation, influenced by the decision‐making context and the method of risk elicitation (Kusev et al., 2020). In this article, we explore the lability of human risk preferences and argue that the most recent choices guide decision‐making. Accordingly, our novel proposal and experimental method provide a psychological tool that measures people's shift in preferences. Specifically, in our experiment (240 participants, registered UK users of an online survey panel), we developed and employed a two‐stage risk elicitation experimental method. The results from the experiment revealed that providing participants with false feedback on their initial decisions (stage 1) changes their risk preferences at the feedback stage of the experiment in the direction of the false feedback. Moreover, participants' final decisions (stage 2) were influenced by the type of feedback (correct or false) and informed by their altered risk preferences at the feedback stage of the experiment. In conclusion, our work provides experimental evidence that human preferences are constructed “on the fly,” influenced by the decision‐making context and recent decision‐making experience (e.g., Kusev et al., 2020; Slovic, 1995).

Identification of New Natural Sources of Flavour and Aroma Metabolites from Solid-State Fermentation of Agro-Industrial By-Products.

Increasing consumer demand for natural flavours and fragrances has driven up prices and increased pressure on natural resources. A shift in consumer preference towards more sustainable and economical sources of these natural additives and away from synthetic production has encouraged research into alternative supplies of these valuable compounds. Solid-state fermentation processes support the natural production of secondary metabolites, which represents most flavour and aroma compounds, while agro-industrial by-products are a low-value waste stream with a high potential for adding value. Accordingly, four filamentous fungi species with a history of use in the production of fermented foods and food additives were tested to ferment nine different agro-industrial by-products. Hundreds of volatile compounds were produced and identified using headspace (HS) solid-phase microextraction (SPME) coupled to gas chromatography–mass spectrometry (GC–MS). Four compounds of interest, phenylacetaldehyde, methyl benzoate, 1-octen-3-ol, and phenylethyl alcohol, were extracted and quantified. Preliminary yields were encouraging compared to traditional sources. This, combined with the low-cost substrates and the high-value natural flavours and aromas produced, presents a compelling case for further optimisation of the process.

Case study on the use and adaptation of SEAT MÓ motorbike sharing service in Barcelona in COVID-19 pandemic year

Worldwide, cities are combating the negative impacts of extensive private motorised vehicle travels and are thus striving to accelerate a shift towards the predominant use of sustainable mobility options. Thereby, shared mobility services are emerging transportation modes, which opt as a complementary mean of transport in urban cities. Amid the current advancements of shared mobility services, the SARS-CoV-2 pandemic accelerated an immense shift in consumer demand and preferences, consequently posing new challenges. In this instance, the testing and validation of implementable hygienic measures has become a key factor for service providers to continuously ensure an increase in clientele. Hence, this research aims to identify the service factors required to accelerate the use of shared micromobility, thereby setting strong focus on hygienic measures. The aforementioned is fulfilled by the means of a quantitative study. Results have indicated an interest in hygiene; however, respondents’ main requirements lie in factors that are not particular to the service provider.

Packaging technology for home meal replacement: Innovations and future prospective

The global demand for home meal replacement (HMR) products has been increasing because of changing consumer behavior toward convenience foods. Although the quality of food products is the most important factor in the decision to purchase, packaging also has a decisive influence on customer choice. Therefore, the importance of packaging technology in the HMR industry has increased significantly. Depending on the packed food requirements, appropriate packaging technology can provide significant benefits to both producers and consumers. Active packaging technology, such as modified atmosphere and antimicrobial packaging, has received considerable attention because of its potential to prolong the product shelf-life, while intelligent packaging technology such as colorimetric indicators and radio-frequency identification labels can monitor the real-time condition of the packed food and communicate with consumers. Packaging technology keeps evolving in response to the growing challenges from industry and society. This review aims to provide information about innovative and commercialized packaging technologies applied to HMR products. Recognized packaging technologies have been discussed, including easy-peel adhesive, microwave susceptor, and intelligent packaging. In addition, the influence of external factors, such as modern consumer behavior, recent global issues such as circular economy and pandemics, and emerging technology on packaging trends, are evaluated and discussed for future development. • Shifts in consumer preferences for convenience foods have increased global demand for HMR products. •Packaging is critical for quality control of HMR products. •Consumers benefit from advanced materials and functional packaging. •Intelligent packaging is becoming more prevalent in chilled and frozen foods. •Greener and safer food packaging is being considered due to global issues.

Preference shifts and wage inequality

This paper analyzes how preference shifts affect wage inequality. We take the Cobb–Douglas preference, the Dixit-Stiglitz preference and the quasi-linear preference into account, and find that there exists preference-driven wage inequality. In the two-type labor (i.e. skilled labor and unskilled labor) models, when the preferences of consumers for skilled products are strengthened, wage inequality will be widened (resp. narrowed down) if there is a relatively low (resp. high) capital intensity in the unskilled sector. We also build a three-type labor (i.e. high-skilled labor, medium-skilled labor, and unskilled labor) model and a model with a non-tradable unskilled sector to strengthen the explanatory power. The role of preferences shifts in changing wage inequality is overlooked by the existing literature.

Why did hunting weapon design change at Abri Pataud? Lithic use-wear data on armature use and hafting around 24,000-22,000 BP.

Projectile technology is commonly viewed as a significant contributor to past human subsistence and, consequently, to our evolution. Due to the allegedly central role of projectile weapons in the food-getting strategies of Upper Palaeolithic people, typo-technological changes in the European lithic record have often been linked to supposed developments in hunting weaponry. Yet, relatively little reliable functional data is currently available that would aid the detailed reconstruction of past weapon designs. In this paper, we take a use-wear approach to the backed tool assemblages from the Recent and Final Gravettian layers (Levels 3 and 2) of Abri Pataud (Dordogne, France). Our use of strict projectile identification criteria relying on combinations of low and high magnification features and our critical view of the overlap between production and use-related fractures permitted us to confidently identify a large number of used armatures in both collections. By isolating lithic projectiles with the strongest evidence of impact and by recording wear attributes on them in detail, we could establish that the hunting equipment used during the Level 3 occupations involved both lithic weapon tips and composite points armed with lithic inserts. By contrast, the Level 2 assemblage reflects a heavy reliance on composite points in hunting reindeer and other game. Instead of an entirely new weapon design, the Level 2 collection therefore marks a shift in weapon preferences. Using recent faunal data, we discuss the significance of the observed diachronic change from the point of view of prey choice, seasonality, and social organisation of hunting activities. Our analysis shows that to understand their behavioural significance, typo-technological changes in the lithic record must be viewed in the light of functional data and detailed contextual information.

TRACE: Travel Reinforcement Recommendation Based on Location-Aware Context Extraction

As the popularity of online travel platforms increases, users tend to make ad-hoc decisions on places to visit rather than preparing the detailed tour plans in advance. Under the situation of timeliness and uncertainty of users’ demand, how to integrate real-time context into dynamic and personalized recommendations have become a key issue in travel recommender system. In this article, by integrating the users’ historical preferences and real-time context, a location-aware recommender system called TRACE ( T ravel R einforcement Recommendations Based on Location- A ware C ontext E xtraction) is proposed. It captures users’ features based on location-aware context learning model, and makes dynamic recommendations based on reinforcement learning. Specifically, this research: (1) designs a travel reinforcing recommender system based on an Actor-Critic framework, which can dynamically track the user preference shifts and optimize the recommender system performance; (2) proposes a location-aware context learning model, which aims at extracting user context from real-time location and then calculating the impacts of nearby attractions on users’ preferences; and (3) conducts both offline and online experiments. Our proposed model achieves the best performance in both of the two experiments, which demonstrates that tracking the users’ preference shifts based on real-time location is valuable for improving the recommendation results.

Bioprosthetic Aortic Valve Degeneration: a Review from a Basic Science Perspective.

IntroductionThe increase in the prevalence of aortic stenosis due to an aging population has led to an increasing number of surgical aortic valve replacements. Over the past 20 years, there has been a major shift in preference from mechanical to bioprosthetic valves. However, despite efforts, there is still no "ideal" bioprosthesis. It is crucial to understand the structure, biology, and function of native heart valves to design more intelligent, strong, durable, and physiological heart valve tissues.MethodsA comprehensive review of the literature was performed to identify articles reporting the basic mechanisms of bioprosthetic valve dysfunction and the biology of native valve cells. Searches were run in PubMed, MEDLINE® (the Medical Literature Analysis and Retrieval System Online), and Google Scholar. Terms for subject heading and keywords search included “biological heart valve dysfunction”, “bioprosthesis dysfunction”, “bioprosthesis degeneration”, and “tissue heart valves”.ResultsAll the relevant findings are summarized in the appropriate subsections. Structural dysfunction is a logical and expected consequence of the chemical, mechanical, and immunological processes that occur during fixation, manufacture, and implantation.ConclusionBiological prosthesis valve dysfunction is a clinically significant process. It has become a major issue considering the growing rate of bioprosthesis implantation and improved long-term patient survival. Understanding bioprosthetic aortic valve degeneration from a basic science perspective is a key point to improve technologic advances and specifications that lead to a new generation of bioprostheses.

Cognitive and behavioural bias in advance care planning.

Background:We explore cognitive and behavioural biases that influence individual’s willingness to engage advance care planning (ACP). Because contexts for the initiation of ACP discussions can be so different, our objective in this study was to identify specific groups, particular preferences or uniform behaviours, that may be prone to cognitive bias in the ACP decision process.Method:We collected data from the Australian general public (n = 1253), as well as general practitioners (GPs) and nurses (n = 117) including demographics, stated preference for ACP decision-making; six cognitive bias tests commonly used in Behavioural Economics; and a framing experiment in the context of ACP.Results:Compared to GPs (M = 57.6 years, SD = 17.2) and the general public (58.1 years, SD = 14.56), nurses on average recommend ACP discussions with patients occur approximately 15 years earlier (M = 42.9 years, SD = 23.1; p < 0.0001 in both cases). There is a positive correlation between the age of the general population and the preferred age for the initial ACP discussion (ρ = 0.368, p < 0.001). Our shared decision-making analysis shows the mean share of doctor’s ACP input is viewed to be approximately 40% by the general public, significantly higher than health professionals (GPs and nurses), who believe doctors should only contribute approximately 20% input. The general public show varying relationships (all p < 0.05) for both first ACP discussion, and shared decision-making for five of six cognitive tests. However, for health professionals, only those who exhibit confirmation bias show differences (8.4% higher; p = 0.035) of patient’s input. Our framing experiment results show that positive versus negative framing can result in as much as 4.9–7.0% shift in preference for factors most relevant to ACP uptake.Conclusion:Understanding how GPs, nurses and patients perceive, engage and choose to communicate ACP and how specific groups, particular preferences or uniform behaviours, may be prone to cognitive bias in the decision process is of critical importance for increasing future uptake and efficient future healthcare provision.

Mapping the clouds: the matter of data centers

ABSTRACT The social spatial geographies of telecommunications and their infrastructures have long interested scholars in the social sciences, and in urban geography specifically. This paper focuses on data centers. Much effort has been placed in preserving the notion that data centers are ‘clouds’, a terminology that obfuscates the real human geographies of cyberplaces. In this map-making exercise, we visualize the sociopolitical human geographies of data centers, and provoke the reader to consider the impacts that data centers have on residents and their environments. The maps shown in this paper suggest four trends. First, hyperscale data center owners are building near large waterways, signifying a shift in location preferences. Second, data centers stress local administrations, financing, and availability of upstream resources, as hyperscale data centers step up their input needs. Third, data center development is state-led. Fourth the competition for data center industries unfolds across a multi-level governance context.

Genome size evolution of the extant lycophytes and ferns

Ferns and lycophytes have remarkably large genomes. However, little is known about how their genome size evolved in fern lineages. To explore the origins and evolution of chromosome numbers and genome size in ferns, we used flow cytometry to measure the genomes of 240 species (255 samples) of extant ferns and lycophytes comprising 27 families and 72 genera, of which 228 species (242 samples) represent new reports. We analyzed correlations among genome size, spore size, chromosomal features, phylogeny, and habitat type preference within a phylogenetic framework. We also applied ANOVA and multinomial logistic regression analysis to preference of habitat type and genome size. Using the phylogeny, we conducted ancestral character reconstruction for habitat types and tested whether genome size changes simultaneously with shifts in habitat preference. We found that 2C values had weak phylogenetic signal, whereas the base number of chromosomes (x) had a strong phylogenetic signal. Furthermore, our analyses revealed a positive correlation between genome size and chromosome traits, indicating that the base number of chromosomes (x), chromosome size, and polyploidization may be primary contributors to genome expansion in ferns and lycophytes. Genome sizes in different habitat types varied significantly and were significantly correlated with habitat types; specifically, multinomial logistic regression indicated that species with larger 2C values were more likely to be epiphytes. Terrestrial habitat is inferred to be ancestral for both extant ferns and lycophytes, whereas transitions to other habitat types occurred as the major clades emerged. Shifts in habitat types appear be followed by periods of genomic stability. Based on these results, we inferred that habitat type changes and multiple whole-genome duplications have contributed to the formation of large genomes of ferns and their allies during their evolutionary history.

Review on materials for making lightweight vehicles

Every material from iron to rubber in vehicle manufacturing has its purpose and these materials have evolved with the shifts in consumer preferences and stricter environmental regulations. These shifts emphasize the automotive industries on enhancing performance and making more fuel-efficient vehicles. This has caught the focus of vehicle makers towards producing lightweight vehicles because vehicle weight directly affects energy consumption. The industries have used various materials to meet the needs for making lightweight vehicles from steel to substituting aluminium and magnesium alloys. The industry is also researching the development of composite materials at a lower cost without compromising the safety and comfort of the consumers and legislations. This article focused on the materials that are being potentially used in making the vehicle bodywork in the automobile industry.

“THE IMPACT OF COVID-19 ON RETAIL INVESTORS' SPENDING AND INVESTMENT BEHAVIOUR”

The extraordinarily infectious sickness corona virus has had a worldwide effect within the twelve months of 2020. This unpredictable and remarkable calamity has pushed economies to battle and strive. Most of the sectors within the financial system were significantly hit, which caused significant financial strain. There is a paradigm shift within the round drift of earnings, which has affected the way of life and modified human beings' spending and funding behaviour. This looks at objectives to understand how the COVID-19 pandemic has encouraged the economic decision-making and funding preferences of retail buyers. This study paper also researches the changes in the spending patterns of human beings for the duration of the lockdown because of COVID-19. A sample survey was performed via a based questionnaire to determine the effect of the pandemic on people's investment choices inside the town of the Pune region. A random sampling technique has been used to acquire the information for the study. The examine's findings display that human beings' existence and spending habits have changed significantly due to the pandemic worry and lockdown. The study additionally suggests that there has been a shift in the spending preferences of people toward healthy products and essentials.

Effect of decisional factors on mutual funds actual purchase behaviour among Indian investors

Indian investors have always shown interest towards savings and investment. Indian economy has shown a shift of preference of investment avenues from traditional avenues like gold and other precious metals to mutual funds. Financial sector is helping Indian economy and mutual fund has emerged as one of the fastest growing sectors. Mutual funds make saving and investment simple, accessible, and affordable. Thus, it has become imperative to study mutual funds from a different angle, which is to focus on investor's perception, expectations, subjective norms and buying behaviour. This research paper is focused on the number of factors that highlights investors' actual purchase behaviour towards mutual funds. This study has included seasoned mutual fund investors as respondents from across India using survey method for collecting data. SPSS Amos 20 was used to analyse data using structural equation modelling (SEM). Results have shown that investor's subjective norms and perceived purchase risk affects purchase decision involvement. It was also found that the role of information search and information processing of mutual funds has a major impact on actual purchase behaviour of an investor.

Rational engineering of cofactor specificity of glutamate dehydrogenase for poly-γ-glutamic acid synthesis in Bacillus licheniformis

Poly-γ-glutamic acid (γ-PGA) is a multifunctional biopolymer mainly produced by Bacillus. The cofactor specificity of enzymes plays a critical role in regulating metabolic process and metabolite production. Here, we present a novel approach for switching cofactor specificity of glutamate dehydrogenase RocG from nicotinamide adenine dinucleotide phosphate (NADPH) to nicotinamide adenine dinucleotide (NADH) to improve γ-PGA production. Firstly, 3D structural modeling and molecular docking were performed to predict the binding modes of NADH and NADPH. Several site-specific mutants based on the conventional and Random Accelerated Molecular Dynamics simulations were obtained to alter cofactor specificity. Then, the effects of RocG variants overexpressions on γ-PGA production were evaluated. Compared to the wild-type, the mutant RocGD276E showed highest increase in γ-PGA yield, increased by 40.50%. Meanwhile, yields of main by-products acetoin and 2,3-butandieol were decreased by 21.70% and 16.53%, respectively. Finally, the results of enzymatic properties confirmed that glutamate dehydrogenase mutant RocGD276E exhibited the higher affinity for NADH, caused a shift in coenzyme preference from NADPH to NADH, with a catalytic efficiency comparable with NADPH-dependent RocG. Taken together, this research demonstrated that switching the cofactor preference of glutamate dehydrogenase via rational design was an effective strategy for high-level production of γ-PGA in Bacillus licheniformis.

Shifts in preference for Natural American Spirit and associated belief that one’s own cigarette brand might be less harmful than other brands: results from Waves 1–4 of the Population Assessment of Tobacco and Health (PATH) Study (2013–2018)

IntroductionPeople believe that cigarettes using ‘organic,’ ‘additive-free’ or similar descriptors are less harmful than other cigarettes. Natural American Spirit (NAS) is the most popular US cigarette brand using these descriptors....

Effects of shifts in response preferences on characteristics of representation and real-time processing: An application to the Hering illusion.

The multidimensional generalization of signal detection theory known as General Recognition Theory (GRT, Ashby & Townsend, Psychological Review, 93, 154-179 1986) has been used to model and characterize the ways in which changes in encoded perceptual information and the application of decisional operators can produce patterns in behavior that are consistent with notions such as configural processing and representation. In particular, a set of studies (e.g., Cornes et al.,, 2011; Wenger & Ingvalson; 2002, 2003) have shown how decisional influences might exert themselves in situations of configural perception, such that effects such as the Thatcher illusion can be obtained by way of shifts in decisional criteria. The present investigation brought to bear the combined tools of GRT and Systems Factorial Technology (SFT, Little et al.,, 2017; Townsend & Nozawa, 1995) with a classical illusion, to show that it is possible to induce a shift in a decisional criterion by way of varying payoffs and that this shift is accompanied by regular changes in the workload capacity statistic. The combined sets of analyses on the same stimuli reveal orderly effects on the decisional criteria (i.e., the signal detection parameter c), report independence (suggesting perceptual independence), invariant measures of sensitivity (i.e., the signal detection parameter [Formula: see text]),and exhaustive parallel processing accompanied by super capacity. We therefore propose wider use of the combined sets of tools, further exploration of the ability of decisional alterations to affect processing times while leaving accuracy largely unscathed, and reaching out to explore more of the information processing mechanisms of classical illusions.

Commodity Shocks and Incumbency Effects

AbstractWhy do incumbents enjoy an electoral advantage in some political settings but suffer from a disadvantage in others? We propose a novel explanation linking variation in incumbency effects with exogenous commodity shocks. While voters attempt to sanction incumbents for economic performance, changes in commodity prices affect their evaluations and condition the electoral fortunes of incumbents vis-à-vis challengers. We test our argument in Brazilian municipalities, combining a plausibly exogenous measure of variation in commodity prices with a close election regression discontinuity design. Our results show that increases in the price of agricultural commodities greatly enhance the prospects of incumbents, while negative shocks exacerbate their incumbency disadvantage, especially in rural municipalities. Further investigation suggests that commodity shocks do not operate via voter learning about candidate quality, changes in the pool of candidates, shifts in voter preferences, or strategic elite investments. Instead, we find suggestive evidence that commodity shocks affect voters' evaluations through their effect on local economic growth.

Polling India via regression and post-stratification of non-probability online samples.

Recent technological advances have facilitated the collection of large-scale administrative data and the online surveying of the Indian population. Building on these we propose a strategy for more robust, frequent and transparent projections of the Indian vote during the campaign. We execute a modified MrP model of Indian vote preferences that proposes innovations to each of its three core components: stratification frame, training data, and a learner. For the post-stratification frame we propose a novel Data Integration approach that allows the simultaneous estimation of counts from multiple complementary sources, such as census tables and auxiliary surveys. For the training data we assemble panels of respondents from two unorthodox online populations: Amazon Mechanical Turks workers and Facebook users. And as a modeling tool, we replace the Bayesian multilevel regression learner with Random Forests. Our 2019 pre-election forecasts for the two largest Lok Sahba coalitions were very close to actual outcomes: we predicted 41.8% for the NDA, against an observed value of 45.0% and 30.8% for the UPA against an observed vote share of just under 31.3%. Our uniform-swing seat projection outperforms other pollsters-we had the lowest absolute error of 89 seats (along with a poll from 'Jan Ki Baat'); the lowest error on the NDA-UPA lead (a mere 8 seats), and we are the only pollster that can capture real-time preference shifts due to salient campaign events.