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The main objective of this study is to examine the impact of audit data analytics (ADA) on audit quality (AQ) and audit review continuity (ARC).

Using 452 CPAs in Thailand as samples, mail questionnaires were used and sent to collect the data. Descriptive analysis, correlation matrix and path analysis were used to analyze the data.

The results of this study indicated that audit data analytics had a positive impact on AQ and ARC. Cybersecurity, used as a moderator in this study, was found to be the interaction between ADA, AQ and review continuity.

Auditors and audit firms can consider using big data in their data analytics to improve AQ and ARC.

Resource advantage theory has been used in this study to explain the impact of ADA on AQ and ARC in Thailand.

Research related to workplace accommodation requests for employees with mental illness is scarce, though evidence suggests that these individuals often fail to request accommodations even when needed. The authors' research study aimed to address these shortcomings by (1) assessing employees' knowledge of Americans with Disabilities Act (ADA) laws and how this knowledge influences employees' perceived need for and requests of accommodations; (2) examining the relationship between employees' perceived need for accommodations and employees' workplace outcomes and (3) examining the relationship between perceived need for accommodations and employees' actual accommodation requests, as well as how stigma influences this relationship.

The authors used two survey studies to investigate their research questions. Study 1 participants were recruited through Amazon's MTurk, and Study 2 participants were recruited through support groups for individuals diagnosed with mood disorders (i.e. depression and bipolar disorder).

The authors found significant gaps in both subjective and objective ADA-related knowledge among participants in their sample. The authors' Study 1 results also revealed an interaction between the perceived need for accommodations and accommodation requests in predicting job satisfaction and turnover intentions. When employees needed accommodations but did not request them, it resulted in worsened workplace outcomes. In Study 2, the authors aimed to identify barriers to requesting accommodations. The authors found that the relationship between perceived need for accommodations and actual accommodation requests was moderated by both public and self-stigma, thereby showing that stigma can impede individuals from requesting needed accommodations at work.

The authors' study sheds light on a population that has been relatively understudied in the workplace accommodations literature, namely those with mental illness. The authors first identify the perceived need for accommodations as an important factor in making accommodations requests at work, as prior work has failed to differentiate how the need for accommodations can vary across individuals. Next, the authors show how workplace outcomes (i.e. job satisfaction and turnover intentions) are negatively affected when employees need accommodations but do not request them. Finally, the authors demonstrate how both public stigma and self-stigma can reduce the likelihood that individuals request accommodations at work, even when needed.

Upon completion of the case study, the students will be able to conceptualize the importance of brand differentiation; suggest the implications of brand differentiation in the context of the traditional Chikan art form; examine the aspect of a brand’s product portfolio management; and critically analyse the competitive advantages of the brand using the VRIO framework.

The Chikankari art form gained worldwide recognition. In fact, it also received a geographical indication (GI) tag which is important for international branding. The case is centred around an entrepreneur, Mr. Vinod Punjabi, who redefined the essence of the existing Chikan art form by value addition in terms of intricate designs, patterns and exclusivity. He founded the brand Ada in 2015 aimed at preserving the traditional art form while curating elegance and exclusivity in its product portfolio. The case outlined Punjabi’s journey. The protagonist carefully analysed the open and unorganized Chikankari market and adopted the strategy of brand differentiation to stand apart from the competitors. Punjabi’s daughter, the chief operations officer of Ada, described the aspects. The journey was arduous, but over the years, Ada emerged as a successful name in the Chikankari market. The brand’s intent of becoming synonymous with Chikankari was successful owing to its authentic and exclusive hand-crafted products in the competitive environment of machine-made replicas. Furthermore, the brand also consistently worked on the aesthetic appearance of its store to attract a wide range of customers. Punjabi ensured that the brand was an amalgamation of all the essential elements for its survival in the long run.

The case is aimed for students pursuing bachelor’s and master’s degrees in business administration/diploma in management, marketing and entrepreneurship. Furthermore, it will assist the management trainees in gaining valuable insights.

Teaching notes are available for educators only.

CSS 8: Marketing.

This study aims to analyze driver risks in the driving environment. A complete analysis of context aware assistive driving techniques. Context awareness in assistive driving by probabilistic modeling techniques. Advanced techniques using Spatio-temporal techniques, computer vision and deep learning techniques.

Autonomous vehicles have been aimed to increase driver safety by introducing vehicle control from the driver to Advanced Driver Assistance Systems (ADAS). The core objective of these systems is to cut down on road accidents by helping the user in various ways. Early anticipation of a particular action would give a prior benefit to the driver to successfully handle the dangers on the road. In this paper, the advancements that have taken place in the use of multi-modal machine learning for assistive driving systems are surveyed. The aim is to help elucidate the recent progress and techniques in the field while also identifying the scope for further research and improvement. The authors take an overview of context-aware driver assistance systems that alert drivers in case of maneuvers by taking advantage of multi-modal human processing to better safety and drivability.

There has been a huge improvement and investment in ADAS being a key concept for road safety. In such applications, data is processed and information is extracted from multiple data sources, thus requiring training of machine learning algorithms in a multi-modal style. The domain is fast gaining traction owing to its applications across multiple disciplines with crucial gains.

The research is focused on deep learning and computer vision-based techniques to generate a context for assistive driving and it would definitely adopt by the ADAS manufacturers.

As context-aware assistive driving would work in real-time and it would save the lives of many drivers, pedestrians.

This paper provides an understanding of context-aware deep learning frameworks for assistive driving. The research is mainly focused on deep learning and computer vision-based techniques to generate a context for assistive driving. It incorporates the latest state-of-the-art techniques using suitable driving context and the driver is alerted. Many automobile manufacturing companies and researchers would refer to this study for their enhancements.

This paper aims to predict the behaviour of the vehicles in a mixed driving scenario. This proposes a deep learning model to predict lane-changing scenarios in highways incorporating current and historical information and contextual features. The interactions among the vehicles are modelled using long-short-term memory (LSTM).

Predicting the surrounding vehicles' behaviour is crucial in any Advanced Driver Assistance Systems (ADAS). To make a decision, any prediction models available in the literature consider the present and previous observations of the surrounding vehicles. These existing models failed to consider the contextual features such as traffic density that also affect the behaviour of the vehicles. To forecast the appropriate driving behaviour, a better context-aware learning method should be able to consider a distinct goal for each situation is more significant. Considering this, a deep learning-based model is proposed to predict the lane changing behaviours using past and current information of the vehicle and contextual features. The interactions among vehicles are modeled using an LSTM encoder-decoder. The different lane-changing behaviours of the vehicles are predicted and validated with the benchmarked data set NGSIM and the open data set Level 5.

The lane change behaviour prediction in ADAS is gaining popularity as it is crucial for safe travel in a mixed driving environment. This paper shows the prediction of maneuvers with a prediction window of 5 s using NGSIM and Level 5 data sets. The proposed method gives a prediction accuracy of 97% on average for all lane-change maneuvers for both the data sets.

This research presents a strategy for predicting autonomous vehicle behaviour based on contextual features. The paper focuses on deep learning techniques to assist the ADAS.

Appearance is part of a person's non-verbal communication, and looks are often associated with the perceived ‘attractiveness’ of individuals for hiring practices in the workplace. As such, physical attractiveness can be a ‘prized possession’ when it comes to leaving a positive impression on managers who are interviewing candidates. In the twenty-first century environment, our society seems to be more obsessed with physical appearance than ever before because society has conditioned us to associate beauty with other favourable characteristics. Of course, such appearance norms, regarding attractiveness, ‘good looks’ and beauty are linked to years of socialisation in culture, cultural norms and materialistic personality standards.

In a business context, managers and employers often make hiring decisions based on the appearance and attractiveness of the job applicants since outward appearance seems to play a significant role in which candidates eventually might get the job. Physically attractive job applicants and candidates tend to benefit from the unearned privilege, which often comes at a cost to others who are equally qualified. Preferring employees who are deemed to be attractive, and consequently discriminating against those who are perceived as unattractive, can present legal and ethical challenges for employers and managers. In this chapter, we provide a discussion and reflection of appearance-based hiring practices in the United States with relevant legal, ethical and practical implications for employers, human resources professionals and managers. We focus on ‘lookism’ or appearance discrimination, which is discrimination in favour of people who are physically attractive. As such, we examine federal, state and local laws regarding appearance discrimination in the American workplace. We also offer sustainable policy recommendations for employers, HR professionals and managers on how they can be fair to all candidates in order to hire, promote and retain the most qualified professionals in their departments and organisations.

According to national surveys, every year approximately 20% of school-age students report bullying victimization. The risk of victimization is even higher for students with disabilities, particularly those whose disabilities are characterized by social–emotional or behavioral traits. To address public concern over bullying, states passed anti-bullying laws and schools implemented bullying prevention programs, with little effect on the frequency of bullying. Consequently, parents of students with disabilities increasingly filed lawsuits to address the harm caused by bullying. Previous research established an increasing trajectory for the frequency of these lawsuits, although the outcomes remained largely favorable to the district defendants. To determine whether these trends continue, this study examined bullying-related court decisions over a 2.5 year period to determine the frequency of cases and claim basis rulings, the representation of disability categories among student plaintiffs, and the outcomes distribution for the claim rulings and cases. The findings noted a continued increasing trajectory for the frequency of cases with an overrepresentation of plaintiffs with ADHD, mental health diagnoses, and autism. Most commonly cited legal bases were Section 504/ADA and negligence, with the overall outcomes distribution more parent plaintiff-favorable than the previous research. To prevent potential liability, educators should strengthen efforts to both comply with reporting and investigation requirements as well as establishing a school culture that accepts differences among students.

Diabetes is a chronic and challenging disease and requires personal daily self-management decisions and skills. For that, it is necessary that patients have sufficient information and health literacy to make the right choices and decisions in their self-care. Sequentially, health literacy has great relevance and influence in the daily lives of people with diabetes, since it encompasses the necessary skills to manage disease and health. Health literacy can be a relevant factor to consider when tackling diabetes self-management. Thus, for the prevention and treatment of diabetes, it is essential to promote individual health literacy. The quality of communication and patient-centred communication style seems to be a key aspect for the health literacy.

We are currently experiencing, in western societies, a new reality in health systems, the emergence of an epidemic of chronic diseases, which test and raise new challenges to the health systems. This exponential increase in chronic diseases has not been accompanied by updated training of health professionals in this area. The chronic illness implies a bilateral relationship, of commitment and compromise for life, in which the involvement of the sick person must be the rule. The scope of therapeutic education (TE) is making the person autonomous and helping them to maintain or improve their quality of life. To treat patients with chronic disease, health professionals need to adapt their knowledge to their new role in the therapeutic relationship. As for the methodology, a participative observational methodology will be carried out with the training of health professionals who work in this area. It is a descriptive work based on studies and works published by the main schools working in this area, with emphasis on the School of Geneve. The purpose is to identify the problem of chronic diseases, the challenges that patients and health professionals face and how to build educational projects, exploring the use of educational tools, including digital technology.

What does special education mean for general education teachers of students with disabilities? In this chapter, we share our approach to advancing values in the classroom placement of special education students in the general education setting. We will take the reader on a journey through time with “Jessie,” a special education student, as we examine the historical exclusion of students with disabilities to their inclusion in general education schools, environments and finally, general education classrooms. In doing so, we will examine the evolution of the general education teacher's role and how the historical perspective impacts current practices. Then, we will elucidate the benefits of inclusion, not only for the special education student but for the nondisabled peers as well. We will recommend values that should be maintained and practices that should be examined. This chapter will conclude with a connection between the values and recommendations of best practices for inclusive instruction.