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The purpose of this study is to examine if consumers, after missing a price discount on a desired product, prefer to buy the latter at a smaller discount or prefer to pay full price but offset some of it with windfall money.

In four experiments, participants imagine that they have missed an opportunity to buy a box of chocolates at $50 off and are offered a second chance to buy them at a less attractive discount ($25) or pay full price, but partially offset the full price with various windfall lotteries ($25, $50, $75) and gift cards ($50).

Participants are more likely to buy the chocolates at the less attractive (second) discount rather than pay full price using windfall money. In doing so, they show that they are willing to be more, rather than less, poor from an overall wealth perspective to acquire the chocolates. This anomaly surfaces irrespective of the windfall amounts or preference elicitation methods (joint versus separate evaluation). The negative transaction utility of paying full price mediates the purchase method effect (discount versus windfall) on purchase likelihood, but gift cards are able to reduce the negative transaction utility of paying full price.

The research reveals a judgmental anomaly in how consumers assess product acquisition value following a lost opportunity and suggests that marketing managers may be able to reduce consumer inertia by strategically matching rewards with the source of the lost chance.

The purpose of this paper is to resolve a puzzle in the explanation of organisational change, where change appears to be within-form but results unintendedly in a transition between forms, yet first appearances suggest the absence of “noise” of the kind expected during shifts between forms.

The paper uses qualitative analysis of primary archival and secondary sources on an historical case, analysing the data by coding using categories derived from neo-Durkheimian institutional theory. It examines the case of the cabinet, treated as an organisation, in the British government led by premier Harold Macmillan between 1959 and 1963, when a strategy for increasing hierarchy resulted unintendedly in an isolation dynamic.

It demonstrates that the neo-Durkheimian institutional approach can explain such puzzling cases. Appropriately for a special issue in honour of Mars’ work, it shows that his method of following rule violation and an adapted version of his concept of capture can provide a method of causal process tracing and a causal mechanism for resolving the puzzle.

The argument is presented for purposes of theory development, not testing. It examines a single case study in depth.

The findings demonstrate some of the risks which arise in changing informal institutional ordering, especially within decision-making executives, from the process by which informal institutions shape styles of judgement and decisions driven by those styles then feed back upon those executive bodies.

This is the first examination of puzzling unintended between-form transitions, the first to propose an adaptation of Mars’ concept of capture to resolve such puzzles and the first detailed causal process tracing analysis of such a case using neo-Durkheimian institutional theoretic tools. It therefore offers a significant advance in institutional explanation of organisational change.

The purpose of this paper is to look at the relation between beliefs and action in common sense judgment. The basic aim of the paper is to define and present a rational model of commonsense choice for the individual based on situation, belief, and personal resources. Second, the paper hypothesizes skills needed to make “good” commonsense choices.

This paper is a speculative essay. It draws from psychology, economics and game theory as a basis for its findings.

A schema useful for the modeling of commonsense judgment is developed. Factors that are the basis for belief formation or belief changes are analyzed within the context of the schema. Skills needed for good judgment are proposed.

The model lays a basis for conceptual and empirical study on judgments made by individuals as defined by their situation, beliefs, and resources.

The model has promise for analyzing individual and group decisions in a variety of social and organizational settings.

This paper posits a construct of common sense useful as an operant in modeling and explaining individual judgments.

Algorithms, artificial intelligence (AI), machines, and all emerging digital technologies disrupt traditional auditing, raising many questions and debates. One of the central issues of this debate is the human-algorithms complex duality, which focuses on this investigation. This study aims to investigate the algorithms’ penetration in auditing activities, with a specific focus of a future scenario on the human-algorithms interaction in performing audits as intelligent teams.

The research uses a qualitative reflexive thematic analysis, taking into consideration the academic literature, as well as professional reports and websites of the “Big Four” audit firms and internationally recognized accounting bodies.

The results debate the complex duality between algorithms and human-based actions in the institutional settings of auditing activities by highlighting the actual stage of algorithms, machines and AI emergence in audit and providing real-life examples of their use in the audit. Furthermore, they emphasize the strengths and weaknesses of algorithms compared to human beings. Based on the results, a discussion on the human-algorithms interaction from the lens of the Human-in-the-Loop (HITL) approach concludes that the Auditor-Governing-the-Loop may be a possible scenario for the future of the auditing profession.

This study is exploratory, investigating academia and practitioners’ written debates, analyzes and reports, limiting its applicability. Nonetheless, the paper adds to the ongoing discussion on emerging technologies and auditing research. Finally, the authors address some potential biases associated with the extended use of algorithms and discuss future research implications. Future research should empirically test how the human-algorithms tandem is working and how AI and other emerging technologies will affect auditing activities and the auditing profession.

The study provides valuable insights for audit firms, auditors, professional organizations and standard-setters, and regulators revealing the implication of algorithms’ penetration in auditing activities from the human-algorithms complex duality perspective. Moreover, the academic education and research implications are highlighted, in terms of updating the educational curriculum by including the new technologies issues, as well as the need for further research investigations concerning the human-algorithms interactions issues as, for example, trust, legal restrictions, ethical concerns, security and responsibility.

The research uses HITL as a novel paradigm for responsible AI development in auditing. The study points to the strategic value of a HITL pattern for organizational reflexivity that, according to the study, ensures that the algorithm’s output meets the audit organization’s requirements and changes in the environment.

March 30, 1971 Redundancy — Redundancy payment — Calculation — Contract of employment with normal working hours — Payment of allowance for time and expense for employee travelling from home to remote place of work — Whether to be taken into account — Contracts of Employment Act, 1963 (c. 49), Sch. 2, para. 2(1) (2) — Redundancy Payments Act, 1965 (c. 62),s. 1(1), Sch. 1, para. 5(2).

Context correctness and fault handling are very important to the quality of service in context‐aware applications. However, they are often ignored by researchers and application developers. This paper aims to present a model for context‐aware applications.

This paper proposes a transaction model for context‐aware applications, in order to provide a uniform infrastructure for service quality management.

The paper finds that, in this model, context‐aware applications are organized as a number of logic units and each unit may have a compensation module, which will be executed when errors or exceptions occur during the execution of those applications in order to minimize the bad infection. This model supports nested scopes and the number of levels of subtransactions is unlimited.

The paper also presents an implementation of this transaction model, which is specialized for context‐aware use.

This paper utilized a novel transaction model to manage the quality of context‐aware applications. The authors have not seen similar work on this topic.

This paper aims at the problem of attaching the data of doctors, patients and the real-time sensor data of the exoskeleton to the cloud in intelligent rehabilitation applications. This study designed the exoskeleton cloud-brain platform and validated its safety assessment.

According to the dimension of data and the transmission speed, this paper implements a three-layer cloud-brain platform of exoskeleton based on Alibaba Cloud's Lambda-like architecture. At the same time, given the human–machine safety status detection problem of the exoskeleton, this paper built a personalized machine-learning safety detection module for users with the multi-dimensional sensor data cloned by the cloud-brain platform. This module includes an abnormality detection model, prediction model and state classification model of the human–machine state.

These functions of the exoskeleton cloud-brain and the algorithms based on it were validated by the experiments, they meet the needs of use.

This thesis innovatively proposes a cloud-brain platform for exoskeletons, beginning the digitalization and intelligence of the exoskeletal rehabilitation process and laying the foundation for future intelligent assistance systems.

The purpose of this paper is to examine how financial literacy and demographic variables (gender, age, income level, education, occupation, marital status and investment experience) related to behavioral biases.

The study uses one-way analysis of variance (ANOVA), factor analysis and multiple regression analysis to examine survey data from more than 500 individual investors in India.

The results reveal the presence of different behavioral biases including overconfidence and self-attribution, the disposition effect, anchoring bias, representativeness, mental accounting, emotional biases and herding among Indian investors. Hence, the findings support the view that individual investors do not always act rationally. The results also show that financial literacy has a negative association with the disposition effect and herding bias, a positive relation with mental accounting bias, but no significant relation with overconfidence and emotional biases. Age, occupation and investment experience are the most important demographic variables that relate to the behavioral biases of individual investors in the sample. Regarding gender, males are more overconfident than are females about their knowledge of the stock market.

The study does not test for causality, only association between the variables. Thus, the findings in this study should not be interpreted as suggesting causality. The study may have implications for financial educators in promoting the financial awareness programs for individuals. Financial advisors can potentially become more effective by understanding their clients’ decision-making processes.

Despite an extensive literature on behavioral finance, limited academic research attempts to unravel the relation of how financial literacy and demographic variates relate to behavioral biases. This study contributes to this literature by trying to fill this gap.

Reports on a study investigating the ways in which companies organise their sales forces and research. Outlines one particular area of interest — the potential use to be made of information provided by the representatives to sales managers. Discusses differences between selling and marketing and how companies have attempted to incorporate this fact into their thinking and organisational frameworks, and welcomes this approach. Investigates the salesman's role and how it has altered in the last 20 years. Gives an example of types of salesman and what companies look for in candidates for sales jobs, these include: maintaining good relations with established customers and encouraging source loyalty; cold calls by commando salesmen whose role is to search out and establish new accounts; and specialist salesmen to handle distinctive requirements of various classes of customers. States also that in UK companies' sales structures it is apparent that salesmen are usually deployed on a geographical territory basis. Examines a case example of a hypothetical firm in the softwood timber importing and distribution business, and discusses this in detail, using an analysis sheet for explanation. Concludes that although the case study relates only to a single firm in one industry there is good reason to suspect there are many firms in a similar position, some of who are particularly liable to experience the problems discussed.

This study aims to explore and clarify the mechanism by which recognition-based heuristic biases influence the investment decision-making and performance of individual investors, with the mediating role of fundamental and technical anomalies.

The deductive approach was used, as the research is based on behavioral finance's theoretical framework. A questionnaire and cross-sectional design were employed for data collection from the sample of 323 individual investors trading on the Pakistan Stock Exchange (PSX). Hypotheses were tested through the structural equation modeling (SEM) technique.

The article provides further insights into the relationship between recognition-based heuristic-driven biases and investment management activities. The results suggest that recognition-based heuristic-driven biases have a markedly positive influence on investment decision-making and negatively influence the investment performance of individual investors. The results also suggest that fundamental and technical anomalies mediate the relationships between the recognition-based heuristic-driven biases on the one hand and investment management activities on the other.

The results of the study suggested that investment management activities that rely on recognition-based heuristics would not result in better returns to investors. The article encourages investors to base decisions on investors' financial capability and experience levels and to avoid relying on recognition-based heuristics when making decisions related to investment management activities. The results provides awareness and understanding of recognition-based heuristic-driven biases in investment management activities, which could be very useful for decision-makers and professionals in financial institutions, such as portfolio managers and traders in commercial banks, investment banks and mutual funds. This paper helps investors to select better investment tools and avoid repeating the expensive errors that occur due to recognition-based heuristic-driven biases.

The current study is the first to focus on links recognition-based heuristic-driven biases, fundamental and technical anomalies, investment decision-making and performance of individual investors. This article enhanced the understanding of the role that recognition-based heuristic-driven biases plays in investment management. More importantly, the study went some way toward enhancing understanding of behavioral aspects and the aspects' influence on investment decision-making and performance in an emerging market.