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Electronic word-of-mouth (eWOM) has become one of the most influential information sources for consumers' purchase decision-making. Based on construal-level theory and from the perspective of cognitive effort, this study investigated the effects of eWOM social media types and conflicting eWOM on consumers' purchase intentions and validated the mediation role of social psychological distance, perceived value, and perceived cognitive effort.

Two scenario-based experiments were conducted to validate the research model. Specifically, a 2 (eWOM social media type: strong-tie vs weak-tie) × 2 (conflicting eWOM: with vs without) between-subjects design was used. ANOVA, multiple regression analysis with PROCESS, and partial least squares (PLS) were employed to test the hypotheses.

The results showed that eWOM social media types had significant effects on both social psychological distance and perceived value. The significant chain mediating effects of social psychological distance and perceived value between eWOM social media types and consumers' purchase intentions were found. In addition, conflicting eWOM had significant effects on both perceived value and perceived cognitive effort. Indirect effects of conflicting eWOM on purchase intention through perceived cognitive effort were discovered.

These results contribute to the eWOM literature by investigating the influences of eWOM social media types and conflicting eWOM on consumers' purchase intentions. They also contribute to construal-level theory by extending its applicability to the field of eWOM.

This study examines the effect of using a computerized decision aid on student cognitive effort and learning in the first tax course. Students at a mid-western university in the United States prepared a 1040 tax return using either paper or tax software from a given set of taxpayer information. Students using paper forms reported higher levels of cognitive effort than did students using the tax software, however, no association between self-efficacy and cognitive effort was found. A test for association between decision aid type and inferential (higher-level) learning (the third level of Bloom's taxonomy) found cognitive effort to be statistically significant. The study also found a significant interaction between cognitive effort and experience. These results suggest that paper forms, which require students to work through task processes, may be better instructional tools for helping students acquire a deeper understanding of subject matter. Although tax software provides potential benefits of increased accuracy and speed, practitioners should be aware of its limitations as a learning tool.

Through the lens of self-determination theory (SDT), the purpose of this paper is to examine the influence of autonomous and controlled motivational regulations in driving consumer participation in social brand engagement (SBE) practices. In addition, the moderating effects of cognitive effort and consumer demographic variables (age and gender) are examined.

The proposed model is tested by employing a quantitative survey design consisting of 832 consumers with prior experience in engaging with brands on social media. The respondents were conveniently interviewed using online questionnaire. The model estimation was done through structural equation modelling with AMOS 23.0.

The findings indicate that intrinsic, integrated, introjected and external motivational regulations significantly influence consumer participation in SBE activities, whereas identified regulation does not. Furthermore, while age and gender presented mixed interaction effects on the paths examined, cognitive effort does not moderate the influence of autonomous and controlled motivational regulations on SBE participation.

This study employed a cross-sectional survey to explore consumer motivation and cognitive effort in SBE practices. As an exploratory study, the findings may be limited and not conclusive, which could limit the generalisation of the results reported.

This study demonstrates a need for retailing managers to understand customers’ varying intentions or needs in participating in online SBE activities As a result, retail managers need to adopt social media strategies that could elicit interest and curiosity on the part of the customer to excite them to participate in the brand social interactions.

This research contributes to the conceptual understanding of SBE through the application of SDT, and contends that cognitive effort does not moderate consumer participation in SBE practices. Also, the mixed findings resulting from the moderation test of age and gender sheds light on specific types of regulated motivations that are either moderated or not in relation to these demographic variables.

To provide better services to customers, especially immediate responses and 24/7 availability, businesses are implementing text-based automated conversational agents, i.e. chatbots on their social platforms and websites. Chatbots are required to not only provide customers with necessary consultancy and guidance but also communicate friendly and socially. Based on the cognitive fit theory, this study attempts to examine the role of chatbot as a decision aid and how the match between information presentation in forms of decisional guidance and communication style and the shopping task influences consumers' perceived cognitive fit and decision performance outcomes.

A 2 x 2 x 2 between subject online experiment was conducted to identify which kind of decisional guidance (suggestive and informative guidance) and communication style (task-oriented vs social-oriented style) are the most appropriate for each type of shopping task (searching vs browsing task).

The findings show that when customers interact with chatbots, they will perceive higher cognitive fit if the chatbots provide them with suggestive guidance and communicate in a friendly style especially when they perform a searching task.

This study is the first attempt to understand the role of chatbots as a decision aid to customers using the communicative language. This study also tries to explore the cognitive fit theory in a novel way, and we propose the information presentation in forms of communicative language rather than matrices, tables and graphs.

Recent years have witnessed the development of a variety of rating systems but the authors have little knowledge about their impact on users’ perceptions of information quality, cognitive decision effort, and enjoyment. The purpose of this paper is to understand the potential cognitive fit underlining the relationship between rating systems types (i.e. five-star, binary-visual, and binary-textual) and tasks (i.e. purchase-decision and browsing tasks) in the context of shopping websites.

A total of 191 subjects were obtained. This study conducted an experiment with a 2×3 between-subject factorial design. The first dimension is a task that has two conditions (purchasing vs browsing). The second dimension is a type of rating system that has three different types (binary-textual, binary-visual, and five-star).

The results show that the cognitive fit may occur when individuals use a five-star rating system to help them make a purchasing decision and when they use a binary-visual rating system while browsing. This fit might increase perceived information quality while decrease cognitive decision efforts, and in turn raise intention to adopt the systems. Moreover, five-star rating systems can make users feel more fun and enjoyment than binary-textual and visual rating systems, regardless of task type.

This study focuses on three main rating systems that are popular on shopping websites. Nevertheless, few other rating systems exist in the market such as unitary or ten-star rating systems. Further studies can consider other types of rating systems and address, in addition to representation, the issue of information granularity (i.e. unitary, binary, five-star, and ten-star rating systems).

The results of this study could provide design principles for web designers in determining which rating systems best match the websites they are developing. If the websites or specific webpages are more utilitarian oriented (hedonic oriented), five-star rating systems (binary-visual rating systems) are more appropriate.

This study contributes to the rating system literature by examining the cognitive fit underlining the relationship between rating systems types and tasks. Importantly, this study extends cognitive fit theory by considering affective responses, that is, perceived enjoyment and intention to continue to use.

Building on the theoretical paradigms of consumer free-riding and cognitive dissonance, this study aims to evaluate whether consumers’ cognitive effort when making a purchase decision impacts upon the relationship between free-riding habits and postpurchase cognitive dissonance.

To explore the relationship between cross-channel free-riding, cognitive efforts and cognitive dissonance, a framework was conceptualized and empirically tested on a sample of 518 Italian consumers. Covariance-based structural equation modeling and bootstrapped mediation analysis was performed with the PROCESS macro.

Results show that the more cognitively involved a free-riding consumer is, the more he/she will experience postpurchase cognitive dissonance.

Modern consumers habitually finalize their purchase activities through multiple different channels. The abundance of e-commerce/online platforms does indeed offer consumers a plethora of alternatives to physical/offline stores. Hence, consumers have been seen to act as “free-riders.” It is becoming more and more common for consumers to seek information in physical stores and then purchase a product online more conveniently. This notwithstanding, it has emerged that free-riding consumers tend to experience cognitive dissonance – which is a sensation of emotional discomfort – after making their purchases. The causes of this phenomenon are yet to be fully unpacked.

This study aims to draw the attention of business process management (BPM) research and practice to the textual data generated in the processes and the potential of meaningful insights extraction. The authors apply standard natural language processing (NLP) approaches to gain valuable knowledge in the form of business process (BP) complexity concept suggested in the study. It is built on the objective, subjective and meta-knowledge extracted from the BP textual data and encompassing semantics, syntax and stylistics. As a result, the authors aim to create awareness about cognitive, attention and reading efforts forming the textual data-based BP complexity. The concept serves as a basis for the development of various decision-support solutions for BP workers.

The starting point is an investigation of the complexity concept in the BPM literature to develop an understanding of the related complexity research and to put the textual data-based BP complexity in its context. Afterward, utilizing the linguistic foundations and the theory of situation awareness (SA), the concept is empirically developed and evaluated in a real-world application case using qualitative interview-based and quantitative data-based methods.

In the practical, real-world application, the authors confirmed that BP textual data could be used to predict BP complexity from the semantic, syntactic and stylistic viewpoints. The authors were able to prove the value of this knowledge about the BP complexity formed based on the (1) professional contextual experience of the BP worker enriched by the awareness of cognitive efforts required for BP execution (objective knowledge), (2) business emotions enriched by attention efforts (subjective knowledge) and (3) quality of the text, i.e. professionalism, expertise and stress level of the text author, enriched by reading efforts (meta-knowledge). In particular, the BP complexity concept has been applied to an industrial example of Information Technology Infrastructure Library (ITIL) change management (CHM) Information Technology (IT) ticket processing. The authors used IT ticket texts from two samples of 28,157 and 4,625 tickets as the basis for the analysis. The authors evaluated the concept with the help of manually labeled tickets and a rule-based approach using historical ticket execution data. Having a recommendation character, the results showed to be useful in creating awareness regarding cognitive, attention and reading efforts for ITIL CHM BP workers coordinating the IT ticket processing.

While aiming to draw attention to those valuable insights inherent in BP textual data, the authors propose an unconventional approach to BP complexity definition through the lens of textual data. Hereby, the authors address the challenges specified by BPM researchers, i.e. focus on semantics in the development of vocabularies and organization- and sector-specific adaptation of standard NLP techniques.

Pew and Mavor (1998) called for an integrative representation of human behavior for use in models of individual combatants and organizations. Models with integrated representation of behavior have only been achieved at rudimentary levels according to those performing the studies (e.g. Pew & Mavor, 1998; Tulving, 2002) and those building the models (e.g. Warwick et al., 2002). This chapter will address aspects of cognitive performance that are important to incorporate into models of combat based on acceptance of theory, strength of empirical data, or for other reasons such as to bridge gaps where incomplete knowledge exists about cognitive behavior and performance. As a starting point, this chapter will assess which of Pew and Mavor’s recommendations are still appropriate as determined by a review of selected literature on cognition and its representation. We will also provide some review and extensions of key literature on cognition and modeling and suggest a way ahead to close the remaining gaps. Different aspects of cognition are described with recent findings, and most are followed by an example of how they have been represented in computer models or a discussion of challenges to their representation in modeling.

Prior literature indicates conflicting effects of online product information, which may complicate or simplify consumer purchase decisions. Therefore, the purpose of this paper is to investigate how different online product information (i.e. the choice set size and the popularity information and its presentation) affect consumers’ decision making and the related market outcomes.

This research relies on information-processing theories and social learning theory. By stepwise conducting two 2×2 within-subject factorial design experiments, this research examines the effects of the choice set size, product popularity information and product presentation on consumers’ decision making and the aggregated market outcomes.

The results show that product popularity information led consumers to either simplify or complicate their decision strategy, depending on the size of the choice sets. Additionally, presenting products by their popularity in descending order resulted in consumers making decisions with a larger decision bias. The results also show that the presence of product popularity was more likely to forge a “superstar” structure in a large market.

The research suggests that e-retailers and e-marketplace operators should carefully utilize product popularity information. Multiple mechanisms that shape different shopping environments with different orders are necessary to create a long-tailed market structure.

This study found the mixed effects of product popularity information when it is presented in different environments (i.e. the large/small choice set and the sorted/randomized product presentation). The overuse of popularity information may induce consumers’ decision bias.

Business model innovation (BMI) constitutes a priority for managers across industries, but it represents a notoriously difficult innovation, with several challenges, many of which are cognitive in nature. The received literature has variously suggested that one way to overcome challenges to BMI, including cognitive ones, and support the cognitive tasks is using visual representations. Against this background, we aim at offering a contribution to the emerging line of inquiry at the nexus between business models (BMs), cognition and visual representations. Specifically, we develop a new method for visual representation of the BM in support of simplification of the cognitive effort and neutralisation of cognitive barriers. The resulting representation – a network-based representation, anchored on the activity-system perspective and offering complementarity and centrality/periphery measures – allows to visually represent an existing BM as a network (nodes and linkages) of interdependent activities and to express information related to the degree of centrality/periphery of single activities (nodes) with respect to the rest of a BM configuration. This information, we argue, is potentially very valuable in supporting the cognitive tasks involved in business model reconfiguration (BMR). We guide the reader to progressively appreciate how the development of the proposed method for visual representation is anchored to two main characteristics of BMR, namely the discovery-driven nature of BMR and the path-dependent nature of BMR. We offer initial insights on the cognitive value of such a type of representation in relationship to the simplification of the cognitive effort and the neutralisation of cognitive barriers in BMR.