Theories Of Human Behavior Research Articles

Targeted interception theory of behaviour change as a basis for developing effective behaviour change interventions in tourism

ABSTRACT The ability to change human behaviour is crucial to solving some of the most existential problems of humanity. Yet, despite the long history of theories of human behaviour, no comprehensive theory of behaviour change exists to guide the development of effective interventions. This article proposes a comprehensive theory of behaviour change that can guide behaviour change intervention development for sustainable tourism. We synthesise existing theories of human behaviour, theories of behaviour change, and intervention studies that generate insights into human behaviour and drivers of change. Based on this collective knowledge, we develop the Targeted Interception Theory of Behaviour Change. It postulates that the effectiveness of different types of intervention varies systematically in dependence on the extent of mental processing associated with the target behaviour. Providing information works for considered but not for habitual and scripted behaviours, the new theory posits. To change such behaviours, some form of active interference or passive disturbance is required. Uniquely, the new theory views behaviour change as a long-term process (not an isolated incident) and assumes the extent of mental processing preceding a behaviour varies from zero to 100% (rather than being binary).

Analysing public goods games using reinforcement learning: effect of increasing group size on cooperation.

Electricity competition, restrictions on carbon dioxide (CO2) emissions and arm races between nations are examples of social dilemmas within human society. In the presence of social dilemmas, rational choice in game theory leads to the avoidance of cooperative behaviour owing to its cost. However, in experiments using public goods games that simulate social dilemmas, humans have often exhibited cooperative behaviour that deviates from individual rationality. Despite extensive research, the alignment between human cooperative behaviour and game theory predictions remains inconsistent. This study proposes an alternative approach to solve this problem. We used Q-learning, a form of artificial intelligence that mimics decision-making processes of humans who do not possess the rationality assumed in game theory. This study explores the potential for cooperation by varying the number of participants in public goods games using deep Q-learning. The simulations demonstrate that agents with Q-learning can acquire cooperative behaviour similar to that of humans. Moreover, we found that cooperation is more likely to occur as the group size increases. These results support and reinforce existing experiments involving humans. In addition, they have potential applications for creating cooperation without sanctions.

Predecisional information search adaptively reduces three types of uncertainty

How do people search for information when they are given the opportunity to freely explore their options? Previous research has suggested that people focus on reducing uncertainty before making a decision, but it remains unclear how exactly they do so and whether they do so consistently. We present an analysis of over 1,000,000 information-search decisions made by over 2,500 individuals in a decisions-from-experience setting that cleanly separates information search from choice. Using a data-driven approach supported by a formal measurement framework, we examine how people allocate samples to options and how they decide to terminate search. Three major insights emerge. First, predecisional information search has at least three drivers that can be interpreted as reducing three types of uncertainty: structural, estimation, and computational. Second, the selection of these drivers of information search is adaptive, sequential, and guided by environmental knowledge that integrates prior expectations, task instructions, and personal experiences. Third, predecisional information search exhibits substantial interindividual heterogeneity, with individuals recruiting different drivers of information search. Together, these insights suggest that human information search is complex in ways that cannot be fully explained by monolithic accounts of information search, including proposals focused on estimation uncertainty or cost-benefit analysis. We conclude that broader theories of human information-search behavior are necessary.

Human-like dissociations between confidence and accuracy in convolutional neural networks.

Prior research has shown that manipulating stimulus energy by changing both stimulus contrast and variability results in confidence-accuracy dissociations in humans. Specifically, even when performance is matched, higher stimulus energy leads to higher confidence. The most common explanation for this effect, derived from cognitive modeling, is the positive evidence heuristic where confidence neglects evidence that disconfirms the choice. However, an alternative explanation is the signal-and-variance-increase hypothesis, according to which these dissociations arise from changes in the separation and variance of perceptual representations. Because artificial neural networks lack built-in confidence heuristics, they can serve as a test for the necessity of confidence heuristics in explaining confidence-accuracy dissociations. Therefore, we tested whether confidence-accuracy dissociations induced by stimulus energy manipulations emerge naturally in convolutional neural networks (CNNs). We found that, across three different energy manipulations, CNNs produced confidence-accuracy dissociations similar to those found in humans. This effect was present for a range of CNN architectures from shallow 4-layer networks to very deep ones, such as VGG-19 and ResNet-50 pretrained on ImageNet. Further, we traced back the reason for the confidence-accuracy dissociations in all CNNs to the same signal-and-variance increase that has been proposed for humans: higher stimulus energy increased the separation and variance of evidence distributions in the CNNs' output layer leading to higher confidence even for matched accuracy. These findings cast doubt on the necessity of the positive evidence heuristic to explain human confidence and establish CNNs as promising models for testing cognitive theories of human behavior.

Data, not documents: Moving beyond theories of information‐seeking behavior to advance data discovery

AbstractMany theories of human information behavior (HIB) assume that information objects are in text document format. This paper argues four important HIB theories are insufficient for describing users' search strategies for data because of assumptions about the attributes of objects that users seek. We first review and compare four HIB theories: Bates' berrypicking, Marchionni's electronic information search, Dervin's sense‐making, and Meho and Tibbo's social scientist information‐seeking. All four theories assume that information‐seekers search for text documents. Next, we compare these theories to search behavior by analyzing Google Analytics data from the Inter‐university Consortium for Political and Social Research (ICPSR). Users took direct, scenic, and orienting paths when searching for data. We also interviewed ICPSR users (n = 20), and they said they needed dataset documentation and contextual information to find data. However, Dervin's sense‐making alone cannot explain the information‐seeking behaviors that we observed. Instead, what mattered most were object attributes determined by the type of information that users sought (i.e., data, not documents). We conclude by suggesting an alternative frame for building user‐centered data discovery tools.

Practice of Educational Administration Theories in Secondary School of Bangladesh

The efficient execution of educational programs in schools has made the position of educational administrators increasingly important. Theories offer a conceptual structure that facilitates comprehending, forecasting, and managing behavior within organizational settings. The purpose of this study is to explore the practice of educational administration (EA) theories in secondary school of Bangladesh, and the role of educational administrators. A qualitative approach is used for gaining in-depth understanding in the real-life-situation. Semi-Structure Interview and Focus Group Discussion have been used to collect data. Data have been analyzed using thematic analysis technique. Findings show that secondary schools of Bangladesh are practicing the Scientific Management Theory and System Theory collaboratively through maintaining formal structure. Human Relationship and Behavioral Approach Theory have been practiced in the shadow of formal structure. As well a hybrid approach is being practiced in the schools. The administrators find the challenges to practice these theories. The challenges are lack of infrastructure, scarcity of teaching learning resources, teacher-student-ratio, local conflict, and school managing committee’s internal clash. The findings of this study would be useful for educators, educational administrators and researchers in advancing EA theories in education. Teacher’s World: Journal of Education and Res arch, 50(1): 135-154

A behavioral signature for quantifying the social value of interpersonal relationships with specific others

The idea that individuals ascribe value to social phenomena, broadly construed, is well-established. Despite the ubiquity of this concept, defining social value in the context of interpersonal relationships remains elusive. This is notable because while prominent theories of human social behavior acknowledge the role of value-based processes, they mostly emphasize the value of individual actions an agent may choose to take in a given environment. Comparatively little is known about how humans value their interpersonal relationships. To address this, we devised a method for engineering a behavioral signature of social value in several independent samples (total N = 1111). Incorporating the concept of opportunity cost from economics and data-driven quantitative methods, we derived this signature by sourcing and weighting a range of social behaviors based on how likely individuals are to prioritize them in the face of limited resources. We examined how strongly the signature was expressed in self-reported social behaviors with specific relationship partners (a parent, close friend, and acquaintance). Social value scores track with other aspects of these relationships (e.g., relationship quality, aversion to losing relationship partners), are predictive of decision preferences on a range of tasks, and display good psychometric properties. These results provide greater mechanistic specificity in delineating human value-based behavior in social contexts and help parse the motivational relevance of the different facets that comprise interpersonal relationships.

On the Importance of Field Studies for Testing Theory-Driven Behavioral Change Interventions in (Sustainable) Tourism

Practical measures to entice tourists to behave in environmentally sustainable ways are urgently needed. The effectiveness of such measures is typically tested in survey experiments. This study demonstrates that this approach can be misleading. We test two messages aimed at reducing buffet food waste. One builds on established theories of human behavior (theory of planned behavior, value-belief-norm theory); it assumes that changing beliefs by providing information triggers behavior change. The second message builds on hedonic psychology; it attempts to change behavior through humor, presenting the pro-environmental behavior as enjoyable. In the survey experiment, the belief-based message significantly increases intentions to reduce plate waste; but both messages fail to change behavior in a real hotel. These insights have methodological and practical implications: the effectiveness of new practical measures developed to trigger specific tourist behaviors must be tested in the field before reliable managerial recommendations can be derived.

Combining theories to investigate the acceptance of accrual accounting

PurposeThis paper develops and tests a theoretical model that draws on the Diffusion Contingency Model and the Theory of Human Behavior to explain the factors influencing users’ acceptance of accrual accounting in terms of two distinct dimensions: behavioral intention and usage behavior.Design/methodology/approachBased on surveyed data from financial departments and directorates of different Greek general government entities, the paper uses factor analysis to build a theoretical model that assesses the factors influencing behavioral intention to adopt and usage behavior of accrual accounting. Then, it tests the relationship between behavioral intention and usage behavior through structural equation modeling.FindingsThe theoretical model suggests that the expected improvement of the quality of financial information and political and financial support are the most important determinants of behavioral intention. Usage behavior is mainly influenced by the compatibility between the existing legal framework and the new accounting system. The structural equation modeling identifies a statistically significant positive influence of behavioral intention on usage behavior.Practical implicationsThe study provides valuable insights regarding the timing and focus of the actions taken by policymakers when designing accounting reforms. Special attention is drawn to the factors influencing behavioral intentions, as these are found to influence usage behavior significantly.Originality/valueThe study extends prior research on the diffusion of accounting innovations by breaking down the diffusion process into intentions-oriented actions aiming to promote accrual accounting and increase acceptance and implementation-oriented actions aiming to facilitate successful implementation.

Virtual reality usage intention in an intradialysis exercise program: Predictive analysis through a structural equation model

ABSTRACT In recent years several exercise programs have begun to use technology, the most used has been virtual reality (VR). Technology-based programs must first be accepted by the population, since, if they do not see the need, the probability of rejection is high. Therefore, it is necessary to first evaluate the intention to use technology to ensure the effectiveness of the intervention. The study aimed to determine the predictive capacity of variables associated with theories of human behavior, on the intention to use VR in an intradialysis exercise program. A sample of 324 hemodialysis patients (F = 140; M = 184) from Chile, filled out a questionnaire. Before this, information was provided regarding VR and the exercise program. Structural equation modeling was used to analyze results through SmartPLS. Results showed that the dependent variable had a good amount of variance explained by the model. The latent variables that strongly influenced the intention to use were perceived enjoyment, perceived utility, and social influence. It can be predicted that users will intend to use VR to perform intradialysis exercises if they consider that it´s entertaining, useful, and validated by their peers.

Cultivation of human centered artificial intelligence: culturally adaptive thinking in education (CATE) for AI.

Artificial Intelligence (AI) has become ubiquitous in human society, and yet vast segments of the global population have no, little, or counterproductive information about AI. It is necessary to teach AI topics on a mass scale. While there is a rush to implement academic initiatives, scant attention has been paid to the unique challenges of teaching AI curricula to a global and culturally diverse audience with varying expectations of privacy, technological autonomy, risk preference, and knowledge sharing. Our study fills this void by focusing on AI elements in a new framework titled Culturally Adaptive Thinking in Education for AI (CATE-AI) to enable teaching AI concepts to culturally diverse learners. Failure to contextualize and sensitize AI education to culture and other categorical human-thought clusters, can lead to several undesirable effects including confusion, AI-phobia, cultural biases to AI, increased resistance toward AI technologies and AI education. We discuss and integrate human behavior theories, AI applications research, educational frameworks, and human centered AI principles to articulate CATE-AI. In the first part of this paper, we present the development a significantly enhanced version of CATE. In the second part, we explore textual data from AI related news articles to generate insights that lay the foundation for CATE-AI, and support our findings. The CATE-AI framework can help learners study artificial intelligence topics more effectively by serving as a basis for adapting and contextualizing AI to their sociocultural needs.

Why People Commit Crimes: Theoretical Explanations

The reasons behind criminal behavior and the impacts on individual developmental outcomes are important research questions in the field of criminal psychology. Researchers often investigate the causes of individual criminal behavior by examining both individual characteristics and environmental factors. This study explores, from a theoretical perspective, why people engage in criminal activities. Four theories of human behavior seek to explain the decision-making process behind criminal actions. Among these, the rational choice theory stands out with its emphasis on cost-benefit analysis. This approach suggests that individuals commonly base their decisions on a weighing of potential costs and benefits. However, certain factors, like low self-control, can significantly disrupt one's ability to focus on the decision's elements, potentially causing an undue fixation on perceived benefits. Amidst the increasing complexity of human interactions, the social learning theory highlights the impact of delinquent individuals on the general populace. Factors such as media exposure, obedience to authority, and the loss of individual identity in group settings are shown to wield considerable influence. Delving into the intricacies of human personality and emotions, the trait-state approach zeroes in on individual disparities and adopts a dynamic perspective. Furthermore, contemporary law enforcement plays a significant role in maintaining public order, with punitive measures targeting offending conduct. This aligns with the deterrence theory's emphasis on the pivotal role of punishment and the perceived costs that individuals weigh when contemplating criminal acts.

메타버스 내 스페이스텔링을 위한 흥미유발 선행조직자 모델 기반 스마트관광 개념지도 설계

Users who want to experience the metaverse for tourism are exposed to strategic planning in space for the purpose of cultural content. In addition, users learn integrated cultural content in the process of proceeding according to the virtual environment. and Along with the meaning of time and space, users will experience space-telling. It is important to induce interest from the beginning of the experience to continue the experience. However, obstacles arise in this process. This is because developers should promote connections with new information to users who do not have sufficient prior knowledge and only have keywords of interest. Therefore, efficient design methods to enhance interest should be studied in advance. But so far, there has been no research on how to systematically design prior organizers to induce interest in virtual space. This study is an interest-inducing design method that occurs in the process of developing the meaning of virtual space and storytelling of cultural content, and can be seen as a basic study using conceptual guidance-based prior organizer education and learning techniques. First, virtual space elements and human behavior theories were considered. Subsequently, five representative examples of previous organizers currently used were explored, and redesigned and proposed based on a conceptual map for information access and delivery purposes. Through this research process, it was possible to confirm that spatial attributes and cognitive interest elements were effectively transmitted to meaningful learning leading to storytelling learning and elements of service design design method through conceptual guidance.

Developing a Framework of Citizen’s Engagement in Open Government Data’s Website

Website is one of the OGD initiatives that provide input and spread information to the public. This research’s objective is to develop a framework for citizen engagement in using OGD’s website, i.e. Ministry’s websites. This research proposes a few combinations of determinants from the Theory of Human Behavior, Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB), Theory of Reasoned Action (TRA), and Information System Success Model (ISSM). This research will provide input and information on how the implementation of OGD in Malaysia can become a sustainable innovation in developing a user-friendly website to attract engagement from the public.

Influence of Spatial Attributes on Human Behavior in Complying with COVID-19 Health Protocols in The City Park of Puputan Badung Denpasar Bali

The study aims to determine the most effective spatial setting for the fitness spots with pandemic mitigation in the city park of Puputan Badung Denpasar Bali as well as to identify various responses of human behavior in complying with health protocols. A mixed-method strategy was utilized, where a quantitative technique was used to determine the level of compliance. A qualitative inquiry with a case study method was also used to assess the influence of spatial attributes on human behavior. The respondents were selected using accidental sampling during peak times for a week. The sport activities observed were fitness, which was available in several spots of parks. Based on human behavior theories, the fitness space equipped with COVID-19 mitigation measures has not provided optimal stimuli to the people in complying with health protocols, leading to low compliance levels. The results of this study can be used as a reference to evaluate the effectiveness of implementing pandemic mitigation in the city park of Puputan Badung and other city parks with similar characteristics from an architectural perspective.

Economic model of community-based falls prevention: seeking methodological solutions in evaluating the efficiency and equity of UK guideline recommendations

BackgroundFalls significantly harm geriatric health and impose substantial costs on care systems and wider society. Decision modelling can inform the commissioning of falls prevention but face methodological challenges, including: (1) capturing non-health outcomes and societal intervention costs; (2) considering heterogeneity and dynamic complexity; (3) considering theories of human behaviour and implementation; and (4) considering issues of equity. This study seeks methodological solutions in developing a credible economic model of community-based falls prevention for older persons (aged 60 +) to inform local falls prevention commissioning as recommended by UK guidelines.MethodsA framework for conceptualising public health economic models was followed. Conceptualisation was conducted in Sheffield as a representative local health economy. Model parameterisation used publicly available data including English Longitudinal Study of Ageing and UK-based falls prevention trials. Key methodological developments in operationalising a discrete individual simulation model included: (1) incorporating societal outcomes including productivity, informal caregiving cost, and private care expenditure; (2) parameterising dynamic falls-frailty feedback loop whereby falls influence long-term outcomes via frailty progression; (3) incorporating three parallel prevention pathways with unique eligibility and implementation conditions; and (4) assessing equity impacts through distributional cost-effectiveness analysis (DCEA) and individual-level lifetime outcomes (e.g., number reaching ‘fair innings’). Guideline-recommended strategy (RC) was compared against usual care (UC). Probabilistic sensitivity, subgroup, and scenario analyses were conducted.ResultsRC had 93.4% probability of being cost-effective versus UC at cost-effectiveness threshold of £20,000 per QALY gained under 40-year societal cost-utility analysis. It increased productivity and reduced private expenditure and informal caregiving cost, but productivity gain and private expenditure reduction were outstripped by increases in intervention time opportunity costs and co-payments, respectively. RC reduced inequality delineated by socioeconomic status quartile. Gains in individual-level lifetime outcomes were small. Younger geriatric age groups can cross-subsidise their older peers for whom RC is cost-ineffective. Removing the falls-frailty feedback made RC no longer efficient or equitable versus UC.ConclusionMethodological advances addressed several key challenges associated with falls prevention modelling. RC appears cost-effective and equitable versus UC. However, further analyses should confirm whether RC is optimal versus other potential strategies and investigate feasibility issues including capacity implications.

A self-heuristic inquiry: Unpacking the use of "Decolonization" in therapy and mental health care with and for racialized communities.

As a registered psychotherapist and art therapist, my clinical training was primarily based on North American clinical approaches influenced by traditional Euro and western-centric clinical theories of human behavior. I completed my training feeling certain that traditional clinical mental health practices were not an appropriate fit for racialized communities and could have negative implications for their healing and well-being. As clinicians, it is our moral obligation to support and enhance the quality of life for marginalized groups. We can do this by challenging our values and knowledge that have been defined and influenced by structures (i.e., education, training, etc.) embedded in these colonial teachings.For this paper, I used a heuristic self-inquiry research method to investigate these concerns. I interviewed other racialized psychotherapists practicing in Turtle Island (currently mostly occupied by the political entities of Canada and the United States) with the aim to learn how and if decolonization can be used in therapy practice. With this research, I (1) identified a gap in care for racialized communities, (2) questioned if or how a decolonizing approach to care should be considered, (3) explored my discomfort with practitioners in the field that claim their position on decolonizing therapy, practice, and approaches, and lastly (4) propose other ways of knowing that can inform new ways of practicing therapy. The results of this research helped to problematize the language and use of decolonizing therapeutic practices while learning about other concepts that may be relevant yet distinct, such as principles of coloniality/decoloniality. Those of us, therapists or researchers, wanting to disrupt the current practice of therapy need to work together, share knowledge, and challenge each other, so that we can transform the way we practice as psychotherapists. This paper is my contribution to this conversation.

Two Theorists on Work Systems: Murray Bowen and Barry Oshry

This paper explores the development of two theories of human behavior as they relate to work systems. Both Murray Bowen and Barry Oshry formulated theories of how people operate in groups. Bowen developed his theory through observation of families and extended his thinking to apply more broadly. Oshry observed work systems in his lab and thought what he saw there could also be true in families and society at large. Practitioners have applied both theories in their work with groups. However, neither theory has received much attention in terms of the theoretical concepts they contain or the processes the theoreticians used to generate them. The purpose of this paper is to examine the methods these two theorists use to create their frameworks, compare and contrast the theories they posited as a result, and consider the possible future development for them.

Exploring motivating factors and constraints of using and adoption of shared autonomous vehicles (SAVs)

Self-driving vehicles are expected to reduce mobility barriers; however, it is still unclear how individuals will use them and how they will benefit the urban transportation system overall. This research aims to evaluate self-driving technology diffusion by applying and testing a conceptual model that was designed to unpack the possible determinants of the adoption of shared autonomous vehicles (SAVs). The study framework was developed based on the principles of socio-psychological theories of human behavior and investigates the adoption of SAVs by two groups of people: users and non-users. Structural equation modeling (SEM) was utilized to analyze the effects of motivational and restriction-related factors on SAV use and adoption, and the results indicated that perceived usefulness and restriction-related factors can positively motivate individuals to use SAVs more frequently. Ultimately, however, their adoption will depend on the public’ attitudes towards technology and as their perceptions of the inherent risks. This study provides new insights into the identification of potential SAV users and non-users and shows how their behavioral intentions differ.

Understanding the Continuance Intention of Omnichannel: Combining TAM and TPB

Nowadays, consumers use information devices to use products and services through various channels. Omnichannel promotes sales improvement by allowing businesses to secure multiple channels. It provides consumers with a wider range of choices and monetary advantages. As such, omnichannel facilitates economic sustainability as a major platform for commerce. The purpose of this study is to identify the determinants of consumers’ continuous intention to use omnichannel. This research collected data from 262 consumers who had used omnichannel. Partial lease square structural equation modeling was employed to analyze the empirical data. The results found that accessibility positively affects perceived ease of use, perceived usefulness, and relative advantage. Monetary saving positively influences relative advantage. Perceived risk has a negative association with relative advantage. Continuance intention is influenced by relative advantage, attitude, subjective norms, and perceived behavioral control. This study offers an academic contribution in that the model was expanded by combining the theories of both technology and human behavior. It provides practical implications that omnichannel practitioners should prioritize money saving, perceived risks, and relative advantages. To enhance the generality of the results, future research needs to survey consumers in more countries. This work would be a useful guide to the sustainability of the economy.