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The Impact of Age and Cognitive Style on E-Commerce Decisions: The Role of Cognitive Bias Susceptibility
Abstract
The aging associated declines in cognitive abilities could render older adults more susceptible to cognitive biases that are detrimental to their e-commerce decisions’ quality. Additionally, certain cognitive styles can lead online consumers to rely on decision heuristics which makes them less meticulous and more prone to bias. In this research-in-progress paper we introduce cognitive bias susceptibility as a potential mediator between age and cognitive style on one end, and decisional outcomes on the other. An experimental design to validate our proposed model is outlined. Both psychometric and eye-tracking methodologies are utilized to achieve a more holistic understanding of the relationships in the proposed model. Potential contributions and implications for future research are outlined.
... With a wide variety of products and offerings available on the internet, too much choice tends to lead to decision fatigue, a mental state of fatigue causing decreased judgment and satisfaction [6], [1]. This effect is compounded by cognitive biases, including choice overload, anchoring, and confirmation bias, which skew rational choice and lower consumer satisfaction overall [9][12] [13] [14] [16]. For example, El Shamy and Hassanein [9] emphasized the ways in which age and cognitive styles affect users' vulnerability to cognitive biases in e-commerce environments. ...
... This effect is compounded by cognitive biases, including choice overload, anchoring, and confirmation bias, which skew rational choice and lower consumer satisfaction overall [9][12] [13] [14] [16]. For example, El Shamy and Hassanein [9] emphasized the ways in which age and cognitive styles affect users' vulnerability to cognitive biases in e-commerce environments. Likewise, Moser et al. [6] refute the traditional choice overload assumption by presenting evidence that, in some contexts, users may not necessarily have negative consequences because of being exposed to too many choices. ...
... Too many options for products lead to choose overload, reducing the quality of the decision and the satisfaction of consumers [6]. Additionally, both age and cognitive style affect the susceptibility to bias, with user segments having higher tendencies for indecision and error [9]. ...
The role of cognitive bias and decision fatigue in shaping consumer behavior on the internet and how psychological factors impair rational choices in the world of e-commerce. Based on a multidisciplinary literature review and empirical research, the article outlines how over choice of products, influential design strategies, and insufficient cognitive relief overwhelm customers and result in less than optimal purchase choices. The influence of heuristics like anchoring and framing is also investigated in-depth, highlighting how they affect user preference and purchase behavior. Furthermore, the study investigates decision fatigue, a psychological phenomenon where continued decision-making saps mental resources, lowering user satisfaction and confidence. The research introduces user experience (UX) tactics to neutralize these influences e.g., streamlined interfaces, smart product suggestions, and adaptive personalization to nudge users toward rational, confident decisions. Results indicate that properly designed UX improves conversion rates as well as fosters long-term consumer loyalty by aligning with psychological comfort. The research provides actionable implications for UX designers, e-commerce developers, and digital marketers interested in designing frictionless, user-centric online buying experiences. It also promotes ethical design practices reducing cognitive overload and promoting digital well-being in today's retail environments.
... Deeper adaptation of existing e-commerce systems to the needs and limitations of older adults has only recently been considered. El Shamy et al. [8] proposed an experiment to measure the impact of recommender systems and comparison matrices on older adults' e-commerce decisions' quality, but no final results have been published yet. Paw lowska et al. [24] used multi-agent simulation to verify the existence of harmful feedback loop in typical recommendation algorithms, if used by older adults with cognitive limitations. ...
The number of older consumers making e-commerce purchasing decisions is constantly rising. We examined the impact of age-related cognitive limitations on older adults’ choices in a series of multi-attribute choice tasks designed to mimic the process of products comparison and selection on e-commerce platforms. 135 older, middle-aged and younger adults were asked to participate in an on-line experiment. We found significant age-related limitations in solving simple and moderately difficult tasks, especially in the older adults group. The mediational model indicated an interplay between the age-related limitation and the role of additional variables (Helplessness of Contracting an Infectious Disease and Numeracy) in explaining the relationship between aging and performance in the multi-attribute choice task.
The number of older adults using e-commerce platform has grown rapidly in recent years. This has created a whole lot of challenges and research problems in the field of adapting e-commerce systems and algorithms to the needs of older adults. In the current study We have conducted an experiment involving 60 older adults whose task was to participate in realistically modeled Dutch auctions. Results show that more advanced age has a clear, statistically significant adverse impact on the overall performance in Dutch auctions, and that need for cognitive closure is correlated with decreased performance in auctions.
Mobile technologies have dramatically increased the number of work-related interruptions. In many organizations, employees must remain accessible and respond to these technology-mediated (T-M) interruptions even after regular work hours. Thus, demands from work interruptions can spill over into workers’ evening and family time, entailing role stress. Ultimately, workers can shy away from using the technologies they deem responsible, with negative impacts for organizations. This implies an indirect effect of demands from T-M interruptions through workers’ experiences of role stress on the use of mobile technology for work. At the same time, the workforce is aging rapidly, and there is a strong reason to assume that older workers may be significantly more susceptible to the negative impacts of interruptions than their younger counterparts. Therefore, the focus of this research is on examining whether the indirect effect of demands from T-M interruptions via workers’ experiences of role stress on the use of mobile technology depends on age such that it is stronger for older workers. Data collected from 135 younger and 137 older knowledge workers supported this idea. The data also show that experience with mobile devices can help older users manage the consequences of interruptions more effectively. Implications for research and practice are discussed.
I report results from an experiment on the relationship between visual website complexity and users’ mental workload. Applying a pupillary based workload assessment as a NeuroIS methodology, I found indications that a balanced level of navigation complexity, i.e., the number of (sub)menus, in combination with a balanced level of information complexity, is the best choice from a user’s mental workload perspective.
Human cognition and decision-making related to information systems (IS) is a major area of interest in IS research. However, despite being explored since the mid-seventies in psychology, the phenomenon of cognitive bias has only recently gained attention among IS researchers. This fact is reflected in a comparatively sparse set of mostly disconnected publications, sometimes using inconsistent theory, methodology, and terminology. We address these issues in our scientometric analysis by providing the first review of cognitive bias-related research in IS. Our systematic literature review of 12 top IS outlets covering the past 20 years identifies 84 publications related to cognitive bias. A subsequent content analysis shows a strong increase of interest in cognitive bias research in the IS discipline in the observed timeframe, yet uncovers a highly unequal distribution across IS fields and industry contexts. While previous research on perception and decision biases has already led to valuable contributions in IS, there is still considerable potential for further research regarding social, memory and interest biases. Our study reveals research gaps in bias-related IS research and highlights common practices in how biases are identified and measured. We conclude with promising future research avenues with the intent to encourage cumulative knowledge-building.
The World Wide Web has become a ubiquitous information source and communication channel. With such an extensive user population, it is imperative to understand how web users view different web pages. Based on an eye tracking study of 30 subjects on 22 web pages from 11 popular web sites, this research intends to explore the determinants of ocular behavior on a single web page: whether it is determined by individual differences of the subjects, different types of web sites, the order of web pages being viewed, or the task at hand. The results indicate that gender of subjects, the viewing order of a web page, and the interaction between page order and site type influences online ocular behavior. Task instruction did not significantly affect web viewing behavior. Scanpath analysis revealed that the complexity of web page design influences the degree of scanpath variation among different subjects on the same web page. The contributions and limitations of this research, and future research directions are discussed.
Effective visual design of e-commerce websites enhances website aesthetics and emotional appeal for the user. To gain insight into how Internet users perceive human images as one element of website design, a controlled experiment was conducted using a questionnaire, interviews, and eye-tracking methodology. Three conditions of human images were created including human images with facial features, human images without facial features, anda control condition with no human images. It was expected that human images with facial features would induce a user to perceive the website as more appealing, having warmth or social presence, and as more trustworthy. In turn, higher levels of image appeal and perceived social presence were predicted to result in trust. All expected relationships in the model were supported except no direct relationship was found between the human image conditions and trust. Additional analyses revealed subtle differences in the perception of human images across cultures (Canada, Germany, and Japan). While the general impact of human images seems universal across country groups, based on interview data four concepts emerged-aesthetics, symbolism, affective property, and functional property-with participants from each culture focusing on different concepts as applied to website design. Implications for research and practice are discussed.
Cognitive decline is inherent with age. Despite known cognitive limitations, older adults are generally not taken into account during website design. Understanding age-related differences in website navigation is instructive for website design, especially considering the growing number of older adults who use the Internet. This article presents usability and eye-tracking data from five independent website usability studies that included younger and older participants. Overall results revealed age-dependent differences in eye movement and performance during website navigation on some of the sites. In particular, older participants had lower accuracy in one study and took longer to complete tasks in two studies compared to younger participants, they looked at the central part of the screen more frequently than younger participants in two studies, and they looked at the peripheral left part of the screen less frequently and took longer to first look at the peripheral top part of the screen than younger participants in one study. These data highlight the potential for age-related differences in performance while navigating websites and provide motivation for further exploration. Implications for website design and for usability practitioners are discussed.
This paper reviews studies on eye movements in decision making, and compares their observations to theoretical predictions concerning the role of attention in decision making. Four decision theories are examined: rational models, bounded rationality, evidence accumulation, and parallel constraint satisfaction models. Although most theories were confirmed with regard to certain predictions, none of the theories adequately accounted for the role of attention during decision making. Several observations emerged concerning the drivers and down-stream effects of attention on choice, suggesting that attention processes plays an active role in constructing decisions. So far, decision theories have largely ignored the constructive role of attention by assuming that it is entirely determined by heuristics, or that it consists of stochastic information sampling. The empirical observations reveal that these assumptions are implausible, and that more accurate assumptions could have been made based on prior attention and eye movement research. Future decision making research would benefit from greater integration with attention research.
Age differences in affective/experiential and deliberative processes have important theoretical implications for judgment and decision theory and important pragmatic implications for older-adult decision making. Age-related declines in the efficiency of deliberative processes predict poorer-quality decisions as we age. However, age-related adaptive processes, including motivated selectivity in the use of deliberative capacity, an increased focus on emotional goals, and greater experience, predict better or worse decisions for older adults depending on the situation. The aim of the current review is to examine adult age differences in affective and deliberative information processes in order to understand their potential impact on judgments and decisions. We review evidence for the role of these dual processes in judgment and decision making and then review two representative life-span perspectives (based on aging-related changes to cognitive or motivational processes) on the interplay between these processes. We present relevant predictions for older-adult decisions and make note of contradictions and gaps that currently exist in the literature. Finally, we review the sparse evidence about age differences in decision making and how theories and findings regarding dual processes could be applied to decision theory and decision aiding. In particular, we focus on prospect theory (Kahneman & Tversky, 1979) and how prospect theory and theories regarding age differences in information processing can inform one another.
© 2007 Association for Psychological Science.
Conducted 2 studies, involving a total of 460 adults between 18 and 87 yrs of age, to determine which of several hypothesized processing components was most responsible for age-related declines in working memory functioning. Significant negative correlations between age and measures of working memory (i.e., from –.39 to –.52) were found in both studies, and these relations were substantially attenuated by partialing measures hypothesized to reflect storage capacity, processing efficiency, coordination effectiveness, and simple comparison speed. Because the greatest attenuation of the age relations occurred with measures of simple processing speed, it was suggested that many of the age differences in working memory may be mediated by age-related reductions in the speed of executing elementary operations. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Over the past half century, research on human decision making has expanded from a purely behaviorist approach that focuses on decision outcomes, to include a more cognitive approach that focuses on the decision processes that occur prior to the response. This newer approach, known as process tracing, has employed various methods, such as verbal protocols, information search displays, and eye movement monitoring, to identify and track psychological events that occur prior to the response (such as cognitive states, stages, or processes). In the present article, we review empirical studies that have employed eye movement monitoring as a process tracing method in decision making research, and we examine the potential of eye movement monitoring as a process tracing methodology. We also present an experiment that further illustrates the experimental manipulations and analysis techniques that are possible with modern eye tracking technology. In this experiment, a gaze-contingent display was used to manipulate stimulus exposure during decision making, which allowed us to test a specific hypothesis about the role of eye movements in preference decisions (the Gaze Cascade model; Shimojo, Simion, Shimojo, & Scheier, 2003). The results of the experiment did not confirm the predictions of the Gaze Cascade model, but instead support the idea that eye movements in these decisions reflect the screening and evaluation of decision alternatives. In summary, we argue that eye movement monitoring is a valuable tool for capturing decision makers' information search behaviors, and that modern eye tracking technology is highly compatible with other process tracing methods such as retrospective verbal protocols and neuroimaging techniques, and hence it is poised to be an integral part of the next wave of decision research.
This article aims to discuss the use of common neurophysiological tools, such as psychophysiological tools (e.g., EKG, eye tracking) and neuroimaging tools (e.g., fMRI, EEG) in Information Systems (IS) research. There is much interest in the social sciences in capturing objective data directly from the human body, and this interest has also been gaining momentum in IS research (termed NeuroIS). This article first introduces several commonly-used neurophysiological tools, and it then discusses several application areas and research questions where IS researchers can benefit from neurophysiological data toward developing a research agenda for NeuroIS. The proposed research areas are presented within four fundamental levels of analysis - individuals, groups, organizations, and markets - that are typically used to examine the use of IT.The article concludes with a set of recommendations on how to use neurophysiological tools in IS research along with practical suggestions for establishing NeuroIS as a viable sub-field in the IS literature.
Simple Heuristics That Make Us Smart invites readers to embark on a new journey into a land of rationality that differs from the familiar territory of cognitive science and economics. Traditional views of rationality tend to see decision makers as possessing superhuman powers of reason, limitless knowledge, and all of eternity in which to ponder choices. To understand decisions in the real world, we need a different, more psychologically plausible notion of rationality, and this book provides it. It is about fast and frugal heuristics--simple rules for making decisions when time is pressing and deep thought an unaffordable luxury. These heuristics can enable both living organisms and artificial systems to make smart choices, classifications, and predictions by employing bounded rationality. But when and how can such fast and frugal heuristics work? Can judgments based simply on one good reason be as accurate as those based on many reasons? Could less knowledge even lead to systematically better predictions than more knowledge? Simple Heuristics explores these questions, developing computational models of heuristics and testing them through experiments and analyses. It shows how fast and frugal heuristics can produce adaptive decisions in situations as varied as choosing a mate, dividing resources among offspring, predicting high school drop out rates, and playing the stock market. As an interdisciplinary work that is both useful and engaging, this book will appeal to a wide audience. It is ideal for researchers in cognitive psychology, evolutionary psychology, and cognitive science, as well as in economics and artificial intelligence. It will also inspire anyone interested in simply making good decisions.
Individuals often use several different strategies such as the expected value rule, conjunctive rule, and elimination-by-aspects, to make decisions. It has been hypothesized that strategy selection is, in part, a function of (1) the ability of a strategy to produce an accurate response and (2) the strategy's demand for mental resources or effort. We examine effort and accuracy and their role in strategy selection. Several strategies that may be used to make choices under risk are simulated using a production system framework. This framework allows the estimation of the effort required to use the strategy in a choice environment, while simultaneously measuring its accuracy relative to a normative model. A series of Monte-Carlo studies varied several aspects of the choice environments, including the complexity of the task and the presence or absence of dominated alternatives. These simulations identify strategies which approximate the accuracy of normative procedures while requiring substantially less effort. These results, however, are highly contingent upon characteristics of the task environment. The potential of production system models in understanding task effects in decisions is stressed.
This paper introduces the idea of drawing upon the cognitive neuroscience literature to inform IS research (herein termed “NeuroIS”). Recent advances in cognitive neuroscience are uncovering the neural bases of cognitive, emotional, and social processes, and they offer new insights into the complex interplay between IT and information processing, decision making, and behavior among people, organizations, and markets.
The paper reviews the emerging cognitive neuroscience literature to propose a set of seven opportunities that IS researchers can use to inform IS phenomena, namely (1) localizing the neural correlates of IS constructs, (2) capturing hidden mental processes, (3) complementing existing sources of IS data with brain data, (4) identifying antecedents of IS constructs, (5) testing consequences of IS constructs, (6) inferring the temporal ordering among IS constructs, and (7) challenging assumptions and enhancing IS theories.
The paper proposes a framework for exploring the potential of cognitive neuroscience for IS research and offers examples of potentially fertile intersections of cognitive neuroscience and IS research in the domains of design science and human-computer interaction. This is followed by an example NeuroIS study in the context of e-commerce adoption using fMRI, which spawns interesting new insights. The challenges of using functional neuroimaging tools are also discussed. The paper concludes that there is considerable potential for using cognitive neuroscience theories and functional brain imaging tools in IS research to enhance IS theories.
Program comprehension processes have previously been studied using methodologies such as think-aloud or comprehension summary analysis. Eye-tracking, however, has not been previously widely applied to studies of behavioral aspects of programming. We present a study in which program comprehension was investigated with a help of a remote eye-tracker. Novice and intermediate programmers used a program visualization tool to aid their comprehension while the location of fixations, fixation durations and attention switching between the areas of interest were recorded.In this paper 1) we propose an approach how to investigate trends in repeated-measures sparse-data of few cases captured by an eye-tracker and 2) using this technique, we characterize the development of program comprehension strategies during dynamic program visualization with help of eye-movement data.
Recommendation agents (RAs) are software agents that elicit the interests or preferences of individual consumers for products, either explicitly or implicitly, and make recommendations accordingly. RAs have the potential to support and improve the quality of the decisions consumers make when searching for and selecting products online. They can reduce the information overload facing consumers, as well as the complexity of online searches. Prior research on RAs has focused mostly on developing and evaluating different underlying algorithms that generate recommendations. This paper instead identifies other important aspects of RAs, namely RA use, RA characteristics, provider credibility, and factors related to product, user, and user-RA interaction, which influence users' decision-making processes and outcomes, as well as their evaluation of RAs. It goes beyond generalized models, such as TAM, and identifies the RA-specific features, such as RA input, process, and output design characteristics, that affect users' evaluations, including their assessments of the usefulness and ease-of-use of RA applications. Based on a review of existing literature on e-commerce RAs, this paper develops a conceptual model with 28 propositions derived from five theoretical perspectives. The propositions help answer the two research questions: (1) How do RA use, RA characteristics, and other factors influence consumer decision making processes and outcomes? (2) How do RA use, RA characteristics, and other factors influence users' evaluations of RAs? By identifying the critical gaps between what we know and what we need to know, this paper identifies potential areas of future research for scholars. It also provides advice to information systems practitioners concerning the effective design and development of RAs.
This paper extends the effort-accuracy framework of cognition by taking into account the perceived strategy restrictiveness of decision aids, and tests the extended framework in a context in which online decision aids are used to elicit consumers’ preferences, automate the processing of the preferences, and provide product advice for consumers. Three types of decision aids with different decision strategy support capabilities (an additive-compensatory based aid, an elimination- based aid, and a hybrid aid supporting both strategies) are compared in terms of users’ perceptions of strategy restrictiveness, advice quality, and cognitive effort. These comparisons are grounded on the properties of normativeness and complementarity of decision strategy(ies) employed by the aids. A normative strategy takes into account both the users’ attribute preferences and the relative importance of such preferences, and allows for trade-offs among preferences (e.g., additive- compensatory). Strategy complementarity indicates support for decision rules based on multiple strategies (e.g., both additive-compensatory and elimination strategies).The experimental results support the validity of the extended effort-accuracy-restrictiveness framework and the effects of strategy normativeness, but not the effects of strategy complementarity. In addition to the perceptions of cognitive effort and advice quality, perceived strategy restrictiveness exerts a significant influence on consumers’ intentions to use online decision aids. The additive-compensatory aid is perceived to be less restrictive, of higher quality, and less effortful than the elimination aid, whereas the hybrid aid is not perceived to be any different from the additive-compensatory aid.
about the potential of multimedia to alleviate the limitations of text-based information in the context of individual decision makers utilizing organi- zational data and test them in a laboratory experi- ment. Results support the task-representation fit relationships predicted. For analyzable tasks, text-based representation and multimedia repre- sentation are equally effective in reducing per- ceived equivocality levels. For less-analyzable tasks, only multimedia representation was instru- mental in reducing perceived equivocality levels. Abstract V\/ith the advent of multimedia and intranet tech- nologies, managers and information systems designers face a new challenge: how to capture and present information using a variety of repre- sentation formats (text, graphics, audio, video, and animations) so that merDbers of an organiza- tion can make better sense out of the information avaitable. In this study, we develop a task-repre- sentation fit model to generate several predictions
Consumers who use electronic decision aids such as comparison-shopping agents may be overwhelmed by the amount of choice information available to them, leading to an inability to choose or dissatisfaction with the ultimate choice, a state of "choice overload." Two experiments were designed to test the choice overload hypothesis. Eight choice tasks of different sizes were presented to subjects. By observing the decision quality, decision time, and decision confidence, we confirmed our hypothesis that choice overload exists when the comparison matrix exceeds a certain size (24 choices and 10 attributes for each choice in this research). Subjects were then given different combinations of decision-making tools (sorting and short-listing) and conditions (refreshing of information) to deal with the same choice task within the choice overload range obtained from the initial experiment. The use of both decision-making tools unexpectedly required more decision-making effort and resulted in less decision satisfaction than when only one decision-making tool was provided. We believe these findings are relevant to the future development of electronic decision aids. Further research is needed in this direction to extend our understanding of decision-making in electronic decision aids mediated environment.
From a broad perspective, our research can be viewed as investigating the fit of technology to task, the user's view of the fit between technology and task, and the relative importance of each to problem-solving or decision-making performance.
The technology investigated in this research is the mode of information presentation. Although there has been a considerable amount of research into problem solving using graphs and tables, until recently the circumstances in which each is more effective have been largely unresolved. Recent research has suggested that performance benefits accrue when cognitive fit occurs, i.e., when factors such as the problem representation and problem solving tools match the characteristics of the task. In this paper, we investigate the effects of the basic paradigm of cognitive fit and extensions to the paradigm in a laboratory experiment that examined the nature of subjects' mental representations as well as problem-solving performance. The experiment, using 128 MBA students in two identical, repeated measures designs, produced the following results:
• Performance improved markedly for symbolic tasks when the problem representation matched the task.
Performance effects also resulted from matching specific problem-solving skills to the problem representation and the task, and to a lesser extent when the skills matched the task alone.
• The incremental effects of matching skills to the problem representation and/or the task were small compared with the primary effects of cognitive fit-that of matching problem representation to task.
• A large proportion of problem solvers have insight into the concept of supporting tasks with certain types of problem representation and vice versa.
• Participants preferred to use tables rather than graphs; they also preferred to solve symbolic rather than spatial problems.
Finally, the problem representation more significantly influenced the mental representation than did task conceptualization.
This research suggests that providing decision support systems to satisfy individual managers' desires will not have a large effect on either the efficiency or the effectiveness of problem solving. Designers should, instead, concentrate on determining the characteristics of the tasks that problem solvers must address, and on supporting those tasks with the appropriate problem representations and support tools. Sufficient evidence now exists to suggest that the notion of cognitive fit may be one aspect of a general theory of problem solving. Suggestions are made for extending the notion of fit to more complex problem-solving environments.
To facilitate online consumer decision making, a number of e-commerce businesses are augmenting their Web site features. The Web-based decision support for consumers is often provided by eliciting consumer preferences directly or indirectly to generate a set of product recommendations. The software that captures consumer preferences and provides recommendations is called a Web-based decision support system (WebDSS). It is important for WebDSS to support consumers’ decision strategies. These decision strategies could be compensatory or non-compensatory in nature. Based on a synthesis of previous research, the authors argue that compensatory based WebDSS are perceived by consumers to be better than non-compensatory WebDSS in terms of decision quality, satisfaction, effort, and confidence. This chapter presents a study that examined the level of online support provided to the consumers’ execution of compensatory and non-compensatory strategies. The results based on investigating 375 e-commerce websites indicate that moderate levels of support exists for consumers to implement non-compensatory choice strategies, and virtually no support exists for executing multi-attribute based compensatory choice strategies. The results of this study suggest that there is an opportunity in waiting for e-commerce businesses to implement compensatory WebDSS to improve the decision making capabilities of their consumers.
This article discusses the role of commonly used neurophysiological tools such as psychophysiological tools (e.g., EKG, eye tracking) and neuroimaging tools (e.g., fMRI, EEG) in Information Systems research. There is heated interest now in the social sciences in capturing presumably objective data directly from the human body, and this interest in neurophysiological tools has also been gaining momentum in IS research (termed NeuroIS). This article first reviews commonly used neurophysiological tools with regard to their major strengths and weaknesses. It then discusses several promising application areas and research questions where IS researchers can benefit from the use of neurophysiological data. The proposed research topics are presented within three thematic areas: (1) development and use of systems, (2) IS strategy and business outcomes, and (3) group work and decision support. The article concludes with recommendations on how to use neurophysiological tools in IS research along with a set ofpractical suggestions for developing a research agenda for NeuroIS and establishing NeuroIS as a viable subfield in the IS literature.
This authored volume presents the fundamentals of NeuroIS, which is an emerging subfield within the Information Systems discipline that makes use of neuroscience and neurophysiological tools and knowledge to better understand the development, use, and impact of information and communication technologies. This book is an initial guide to this new research domain. The target audience primarily comprises PhD students and researchers, but the book may also be beneficial for graduate students and practitioners.
The workforce is aging rapidly, with the number of older workers increasing sharply (older being defined as 60 and over). At the same time, interruptions mediated by modern information technologies are proliferating in organizations. These interruptions include email notifications and instant messages, amongst others, which have been shown to have hazardous consequences for employees in terms of stress. Older workers might be especially affected by these interruptions, implying major problems for this fast-growing user group with regard to their well-being and work performance. The present study tests a research model suggesting that older workers experience more interruption-based technostress than their younger counterparts because of differences in inhibitory control between older and younger adults. In doing so, this study answers recent calls for examining age as a substantive variable in IS research, and it contributes to the literature on technostress by showing how technostress affects different user groups to different extents.
Recent research has made a strong case for the importance of NeuroIS methods for IS research. It has suggested that NeuroIS contributes to an improved explanation and prediction of IS phenomena. Yet, such research is unclear on the source of this improvement; while some studies indicate that NeuroIS constitutes an alternative to psychometrics, implying that the two methods assess the same dimension of an underlying IS construct, other studies indicate that NeuroIS constitutes a complement to psychometrics, implying that the two methods assess different dimensions of an IS construct. To clarify the role of NeuroIS in IS research and its contribution to IS research, in this study, we examine whether NeuroIS and psychometrics/psychological methods constitute alternatives or complements. We conduct this examination in the context of technostress, an emerging IS phenomenon to which both methods are relevant. We use the triangulation approach to explore the relationship between physiological and psychological/self-reported data. Using this approach, we argue that both kinds of data tap into different aspects of technostress and that, together, they can yield a more complete or holistic understanding of the impact of technostress on a theoretically-related outcome, rendering them complements. Then, we test this proposition empirically by probing the correlation between a psychological and a physiological measure of technostress in combination with an examination of their incremental validity in explaining performance on a computer-based task. The results show that the physiological stress measure (salivary alpha-amylase) explains and predicts variance in performance on the computer-based task over and above the prediction afforded by the self-reported stress measure. We conclude that NeuroIS is a critical complement to IS research. © 2014, Association for Information Systems. All rights reserved.
The genesis of the Neuro-Information Systems (NeuroIS) field took place in 2007. Since then, a considerable number of IS scholars and academics from related disciplines have started to use theories, methods, and tools from neuroscience and psychophysiology to better understand human cognition, emotion, and behavior in IS contexts, and to develop neuro-adaptive information systems (i.e., systems that recognize the physiological state of the user and that adapt, based on that information, in real-time). However, because the NeuroIS field is still in a nascent stage, IS scholars need to become familiar with the methods, tools, and measurements that are used in neuroscience and psychophysiology. Against the background of the increased importance of methodological discussions in the NeuroIS field, the Journal of the Association for Information Systems published a special issue call for papers entitled “Methods, tools, and measurement in NeuroIS research” in 2012. We, the special issue’s guest editors, accepted three papers after a stringent review process, which appear in this special issue. In addition to these three papers, we hope to intensify the discussion on NeuroIS research methodology, and to this end we present the current paper. Importantly, our observations during the review process (particularly with respect to methodology) and our own reading of the literature and the scientific discourse during conferences served as input for this paper. Specifically, we argue that six factors, among others that will become evident in future discussions, are critical for a rigorous NeuroIS research methodology; namely, reliability, validity, sensitivity, diagnosticity, objectivity, and intrusiveness of a measurement instrument. NeuroIS researchers—independent from whether their role is editor, reviewer, or author—should carefully give thought to these factors. We hope that the discussion in this paper instigates future contributions to a growing understanding towards a NeuroIS research methodology.
This paper provides an empirical typology of online decision-making purchasing behaviour. The study explores how the online purchase process is affected by individual decision-making style and knowledge of product. Drawing from the decision analysis and consumer behaviour literatures, we present a typology of online purchase decision-making behaviour and introduce four archetypes of online consumers. A number of experiments have been conducted in two online settings: retail banking and mobile networks. Based on an extensive video analysis, we have captured four process-related dimensions (number of cycles, duration, number of alternatives and number of criteria) using a business process modelling approach. Significant differences in all process-related dimensions were found across the four archetypes. The study improves understanding of the different types of online consumers and their process outcomes. The findings are useful for online retailers seeking to improve the way they support the four archetypes of online shoppers throughout the decision-making purchasing process.
As the workforce ages rapidly in industrialized countries, a phenomenon known as the graying of the workforce, new challenges arise for firms as they have to juggle this dramatic demographical change (Trend 1) in conjunction with the proliferation of increasingly modern information and communication technologies (ICTs) (Trend 2). Although these two important workplace trends are pervasive, their interdependencies have remained largely unexplored. While Information Systems (IS) research has established the pertinence of age to IS phenomena from an empirical perspective, it has tended to model the concept merely as a control variable with limited understanding of its conceptual nature. In fact, even the few IS studies that used the concept of age as a substantive variable have mostly relied on stereotypical accounts alone to justify their age-related hypotheses. Further, most of these studies have examined the role of age in the same phenomenon (i.e., initial adoption of ICTs), implying a marked lack of diversity with respect to the phenomena under investigation. Overall, IS research has yielded only limited insight into the role of age in phenomena involving ICTs. In this essay, we argue for the importance of studying age-related impacts more carefully and across various IS phenomena, and we enable such research by providing a research agenda that IS scholars can use. In doing so, we hope that future research will further both our empirical and conceptual understanding of the managerial challenges arising from the interplay of a graying workforce and rapidly evolving ICTs.
The use of the Internet by older adults is growing at a substantial rate. They are becoming an increasingly important potential market for electronic commerce. However, previous researchers and practitioners have focused mainly on the youth market and paid less attention to issues related to the online behaviors of older consumers. To bridge the gap, the purpose of this study is to increase a better understanding of the drivers and barriers affecting older consumers’ intention to shop online. To this end, this study is developed by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) and innovation resistance theory. By comparing younger consumers with their older counterparts, in terms of gender the findings indicate that the major factors driving older adults toward online shopping are performance expectation and social influence which is the same with younger. On the other hand, the major barriers include value, risk, and tradition which is different from younger. Consequently, it is notable that older adults show no gender differences in regards to the drivers and barriers.
Consumers often face emotion-laden choices involving conflicting goals of personal importance (e.g., safety). Research suggests that consumers cope with the negative emotion associated with these choices by avoiding certain behaviors, in particular attribute trade-off making. This research investigates a factor that moderates these coping effects. Four experiments show that simple cognitive load can make consumers less averse to making attribute trade-offs. This research demonstrates, counterintuitively, that a reduction of cognitive resources through increased load can result in more normative decision behavior. Load apparently disinhibits trade-off making by disrupting consumers' abilities to consider relevant self goal information and the negative emotional consequences of trading off something of personal importance, thereby reducing consumers' need to cope.
Three studies suggest that individuals see the existence and operation of cognitive and motivational biases much more in others than in themselves. Study 1 provides evidence from three surveys that people rate themselves as less subject to various biases than the “average American,” classmates in a seminar, and fellow airport travelers. Data from the third survey further suggest that such claims arise from the interplay among availability biases and self-enhancement motives. Participants in one follow-up study who showed the better-than-average bias insisted that their self-assessments were accurate and objective even after reading a description of how they could have been affected by the relevant bias. Participants in a final study reported their peer’s self-serving attributions regarding test performance to be biased but their own similarly self-serving attributions to be free of bias. The relevance of these phenomena to naïve realism and to conflict, misunderstanding, and dispute resolution is discussed.
Introduction, 99. — I. Some general features of rational choice, 100.— II. The essential simplifications, 103. — III. Existence
and uniqueness of solutions, 111. — IV. Further comments on dynamics, 113. — V. Conclusion, 114. — Appendix, 115.
Older adults need to maintain strong decision-making capabilities as they age. However, we know little about how age-related physical and psychological changes affect older adults' judgment and decision processes. This paper reports the results of research comparing older versus younger adults' performance on evaluation and choice tasks about health-plan options. In particular, comprehension and consistency in judgments (across separate versus joint evaluation contexts) were examined. Results indicated that increasing age was related to greater comprehension errors and inconsistent preferences, even when covariates (education, income, gender, self-perceived skill and health, decision style, and attitude toward delegation) were taken into account. Discussion of the results emphasizes difficulties in interpreting the meaning of age differences in performance on decision tasks and the need for research that ascertains the seriousness of the consequences of age differences in real-life tasks. The implications for providing decision-aiding interventions for older adults are highlighted. Copyright © 2002 John Wiley & Sons, Ltd.
Consumers use a variety of decision-making styles. This paper conceptualizes eight basic characteristics of these styles and develops a Consumer Styles Inventory to measure them empirically. Factor analysis of the Consumer Styles Inventory validates these eight consumer characteristics. A valid and reliable method for presenting a Profile of Consumer Style, based on measures of the eight style characteristics, is described. Unique findings of the research are discussed, and applications of the Consumer Styles Inventory in consumer education, consumer research, and family financial counseling are suggested.
Research has recently focused on the effort-reduction or minimization role of computerized decision aids, and how users may employ aids to manage their effort, which in turn affects their choice of decision strategies. In this paper, it is argued that consideration of effort reduction or minimization by itself is not sufficient for inducing changes in decision strategy. Instead, decision aid effects on effort must be considered jointly with the decision quality associated with the various decision strategies. This is true even if the decision aid has no effect on decision quality. We adapt and extend a theoretical framework that can be used to evaluate the joint effects of effort and quality on decision strategy choice. In addition, we reinterpret past research results in light of the framework and present new experimental evidence on the descriptive validity of the framework.
Almost 1000 adults participated in the development of the Cognitive Style Index (CSI), a new measure designed specifically for use with managerial and professional groups. the objectives of the study were, first, to produce a psychome-trically sound instrument suitable for application in large-scale organizational studies, and second, through its development, to confirm empirically the generic intuition-analysis dimension of cognitive style. Findings suggest that each objective was largely fulfilled. At a time when there is a burgeoning interest in intuition as a basis for decision making and problem solving in organizations, the CSI would appear to be a notable addition to the small collection of measures appropriate for survey research.
Despite the explosive growth of electronic commerce and the rapidly increasing number of consumers who use interactive media (such as the World Wide Web) for prepurchase information search and online shopping, very little is known about how consumers make purchase decisions in such settings. A unique characteristic of online shopping environments is that they allow vendors to create retail interfaces with highly interactive features. One desirable form of interactivity from a consumer perspective is the implementation of sophisticated tools to assist shoppers in their purchase decisions by customizing the electronic shopping environment to their individual preferences. The availability of such tools, which we refer to as interactive decision aids for consumers, may lead to a transformation of the way in which shoppers search for product information and make purchase decisions. The primary objective of this paper is to investigate the nature of the effects that interactive decision aids may have on consumer decision making in online shopping environments.
While making purchase decisions, consumers are often unable to evaluate all available alternatives in great depth and, thus, tend to use two-stage processes to reach their decisions. At the first stage, consumers typically screen a large set of available products and identify a subset of the most promising alternatives. Subsequently, they evaluate the latter in more depth, perform relative comparisons across products on important attributes, and make a purchase decision. Given the different tasks to be performed in such a two-stage process, interactive tools that provide support to consumers in the following respects are particularly valuable: (1) the initial screening of available products to determine which ones are worth considering further, and (2) the in-depth comparison of selected products before making the actual purchase decision. This paper examines the effects of two decision aids, each designed to assist consumers in performing one of the above tasks, on purchase decision making in an online store.
The first interactive tool, a recommendation agent (RA), allows consumers to more efficiently screen the (potentially very large) set of alternatives available in an online shopping environment. Based on self-explicated information about a consumer's own utility function (attribute importance weights and minimum acceptable attribute levels), the RA generates a personalized list of recommended alternatives. The second decision aid, a comparison matrix (CM), is designed to help consumers make in-depth comparisons among selected alternatives. The CM allows consumers to organize attribute information about multiple products in an alternatives × attributes matrix and to have alternatives sorted by any attribute.
Based on theoretical and empirical work in marketing, judgment and decision making, psychology, and decision support systems, we develop a set of hypotheses pertaining to the effects of these two decision aids on various aspects of consumer decision making. In particular, we focus on how use of the RA and CM affects consumers' search for product information, the size and quality of their consideration sets, and the quality of their purchase decisions in an online shopping environment.
A controlled experiment using a simulated online store was conducted to test the hypotheses. The results indicate that both interactive decision aids have a substantial impact on consumer decision making. As predicted, use of the RA reduces consumers' search effort for product information, decreases the size but increases the quality of their consideration sets, and improves the quality of their purchase decisions. Use of the CM also leads to a decrease in the size but an increase in the quality of consumers' consideration sets, and has a favorable effect on some indicators of decision quality.
In sum, our findings suggest that interactive tools designed to assist consumers in the initial screening of available alternatives and to facilitate in-depth comparisons among selected alternatives in an online shopping environment may have strong favorable effects on both the quality and the efficiency of purchase decisions—shoppers can make much better decisions while expending substantially less effort. This suggests that interactive decision aids have the potential to drastically transform the way in which consumers search for product information and make purchase decisions.
This exploratory research investigates the nature of explanation use and factors that influence it during users' interaction with a knowledge-based system (KBS) for decision-making. It draws upon several cognitive perspectives to help understand when, why, and how explanations are used. A verbal protocol analysis was conducted based on a laboratory experiment involving a KBS for financial analysis. Major categories of explanation use were identified, and accounted for with relevant cognitive perspectives. Results show that explanations were requested to deal with comprehension difficulties caused by various types of perceived anomalies in KBS output. There were qualitative and quantitative differences in the nature and extent of explanation use between novices and experienced professionals. These results offer new insights to why explanations are useful and important, what factors influence explanation use, and what information should be included in explanations.
The purpose of this study was to explore the relations between individual decision-making styles as measured by the General Decision-making Style (GDMS) test, developed by Scott and Bruce (1995), and some mental abilities theoretically related to decision-making. Participants were 206 Swedish military officers from all services. The multiple regression analysis showed that the Rational, Dependent and Avoidant, but not the Intuitive and Spontaneous decision-making styles could be partly predicted from scores on the Self-esteem Scales (Forsman & Johnson, 1996) and from scores on the Action Control Scales (Kuhl, 1994). The result indicates that decision-making style is not only reflective of habits and thinking practices as proposed in earlier research. Decision-making style also involves basic self-evaluation and the general ability to initiate and maintain intentions (i.e. self-regulation). This calls for a wider definition of the term decision-making style, a holistic definition that takes the whole individual into consideration.
With the proliferation of Internet-based applications for collaborative work such as group decision support system (GDSS), traditional face-to-face (FTF) interactions are being augmented or replaced by screen-to-face (STF) technology. Extant research results find that some individuals prefer FTF mode for interaction and would feel frustrated under an STF mode, but others may feel very comfortable using electronic STF applications. This paper evaluates the influence of cognitive style on the perception of individuals negotiating over FTF or STF communication modes. Cognitive style explains how individuals prefer to receive information and what methods they use to process that information. The results suggest that when individuals are faced with a mixed-motive negotiation task, some cognitive styles mitigate the effects of communication modes while other cognitive styles are not sensitive to it. Hence, cognitive style and communication modes have interaction effects.
This paper integrates a number of strands of a long-term project that is critically analysing the academic field of decision support systems (DSS). The project is based on the content analysis of 1093 DSS articles published in 14 major journals from 1990 to 2004. An examination of the findings of each part of the project yields eight key issues that the DSS field should address for it to continue to play an important part in information systems scholarship. These eight issues are: the relevance of DSS research, DSS research methods and paradigms, the judgement and decision-making theoretical foundations of DSS research, the role of the IT artifact in DSS research, the funding of DSS research, inertia and conservatism of DSS research agendas, DSS exposure in general “A” journals, and discipline coherence. The discussion of each issue is based on the data derived from the article content analysis. A number of suggestions are made for the improvement of DSS research. These relate to case study research, design science, professional relevance, industry funding, theoretical foundations, data warehousing, and business intelligence. The suggestions should help DSS researchers construct high quality research agendas that are relevant and rigorous.
In the context of online comparison shopping, the phenomenon of order effect and its impact has profound theoretical and practical significance, as many search engines and shopping portals offer paid placement and paid inclusion in search results. In this study, we investigate how order effects and other market competitive factors work together to attract consumers’ attention to online vendors, which is manifested by the time spent on collecting more vendor information, and the probability of a vendor being included in a consumer’s consideration set. We found that the effect of serial position of a vendor in a list is mediated by consumers’ attention which in turn affects the probability of the vendor being accepted.
As the populations of most of the world’s developed nations experience an increase in average age, a similar trend is being observed in the population of computer and Internet users. In many cases, older adults are the fastest growing computer and Internet user group in both personal and workplace contexts. However, the needs and concerns of older adults as computer users differ from those of younger users as a result of the natural changes associated with the aging process. Much research has been conducted in a variety of fields in order to understand how these changes experienced by older adults impact their use of computers and the Internet. This article reviews this existing research and provides a holistic view of the field. Since the study of computer use by older adults is a multi-disciplinary topic by nature, we provide a synthesis of the findings across these many disciplines, and attempt to highlight any gaps that exist. We use Social Cognitive Theory as a lens to view and organize the literature, as well as illustrate means through which computer use by this user group can be encouraged. Finally, suggestions for future research are proposed, and implications for research and practice are discussed.
This paper presents design science research that aims to improve decision support systems (DSS) development in organizations. Evolutionary development has been central to DSS theory and practice for decades, but a significant problem for DSS analysts remains how to conceptualize the improvement of a decision task during evolutionary DSS development. The objective of a DSS project is to improve the decision process and outcome for a manager making an important decision. The DSS analyst needs to have a clear idea of the nature of the target decision task and a clear strategy of how to support the decision process. Existing psychological research was examined for help with the conceptualization problem, and the theory of cognitive bias is proposed as a candidate for this assistance. A taxonomy of 37 cognitive biases that codifies a complex area of psychological research is developed. The core of the project involves the construction of a design artefact – an evolutionary DSS development methodology that uses cognitive bias theory as a focusing construct, especially in its analysis cycles. The methodology is the major contribution of the project. The feasibility and effectiveness of the development methodology are evaluated in a participatory case study of a strategic DSS project where a managing director is supported in a decision about whether to close a division of a company.
The traditional assumption in the decision support systems (DSS) literature is that if decision makers are provided with expanded processing capabilities they will use them to analyze problems in more depth and, as a result, make better decisions. Empirical studies investigating the relationship between DSS and decision quality have not borne this out. The explanation for such outcomes could be found in behavioral decision-making theories. The literature on behavioral decision making indicates that the conservation of effort may be more important than increased decision quality in some cases. If ths is so, then the use of a decision aid may result in effort savings but not improved decision performance. The two experiments reported here use verbal protocol analysis to compare the extent of information use by unaided decision makers and users of a decision aid designed to support preferential choice problems. The results of the two studies indicate that subjects with a decision aid did not use more information than those without one. Overall, subjects behaved as if effort minimization was an important consideration. For DSS researchers these studies indicate that to understand the DSS-decision quality relationship, it is necessary to consider the decision maker's tradeoff between improving decision quality and conserving effort. For DSS designers these results imply a need to focus on the moderating role that effort will play in determining DSS effectiveness.
This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness,
which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process
B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a
class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical
prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead
to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could
improve judgements and decisions in situations of uncertainty.