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Understanding the factors that impact the audit quality of work performed by affiliated offshore entities has become imperative for US accounting firms. The purpose of this paper is to gain a better understanding of the role that cultural differences have on the trait professional skepticism mindset of future auditors in the USA and India.

The authors use the Hurtt (2010) Professional Skepticism Scale (HPSS) to evaluate the role that culture has on the trait professional skepticism mindset of a sample of future auditors in the USA and India.

The authors identify three distinct dimensions of trait professional skepticism embedded in the HPSS. The research finds no significant differences between USA and Indian auditing students on the evidential “trust but verify” dimension of trait professional skepticism; however, US students score higher on the behavioral “presumptive doubt” and self-reliance dimensions.

Given culture significantly influences trait professional skepticism, firms and regulators should be highly cognizant of the type of work that is being sent offshore. Firms using affiliated offshore entities should also ensure that robust integration practices are used to facilitate the level of professional skepticism necessary to perform a quality audit.

By identifying three separate dimensions in the HPSS, the research takes an important step in understanding the factors that impact the quality of audit procedures performed in a critical affiliated offshore entity for US-based accounting firms.

To develop, test and implement a sampling strategy for equipment auditing for a Fortune 100 company.

Regression analysis is applied to auditing of equipment for a large US corporation. Empirical data and test data sets are used to evaluate the efficacy of using regression for auditing and to determine reasonable and efficient sample sizes to be employed across more than 5,000 locations.

Regression is a viable and useful method for equipment auditing when there is anticipated high correlation between pre‐ and post‐audit equipment value. Recommended sample size is dependent upon the size of the location as measured by total pieces of equipment. Decision rules combining acceptable tolerance limits, desired confidence level and sample size are provided.

The method, recommended sample sizes and decision rules are particularly applicable to instances where high correlation is expected between pre‐ and post‐audit equipment values. Standard regression assumptions are not all met in all instances, especially with small sample sizes.

The regression approach and model, sample size recommendations and decision rules for passing or failing an equipment audit described herein have been implemented at a Fortune 100 company, and are generally applicable to equipment and inventory auditing when high correlation between pre‐ and post‐audit equipment is expected.

This paper provides a practical and useful regression‐based approach to sampling for equipment auditing. Recommended sample sizes and decision rules for passing or failing the audit are explicitly defined.

To explore how store brand personality might play a role in consumer perceptions towards store brands and how such personalities might vary when consumers are allowed to experience the product.

Two different store brand products from high selling categories were compared with their leading national brands. A total of 139 respondents took the survey. Respondents were divided into four groups, each group representing a different experimental condition. Respondents rated the personality attributes on a seven point Likert scale.

Results show that national brands have stronger brand personality traits when compared to store brands; however, such differences diminished when consumers were allowed to taste and experience the products.

Retailers would be better off to let consumers experience and taste the products to drive consumer perceptions of store brands. Retailers should also focus on those categories where the differential in personality traits between store brands and national brands are small and where the profit margins are higher to drive the store brand image.

This paper presents a slightly different approach in understanding store brands and argues that store brands do have a personality and that such personality could be further influenced by allowing consumers to experience the product.

To date there is little understanding of the factors that impact the survival of foreign IPOs after they list on US stock exchanges. In this study, we examine how foreign IPO survival is contingent on institutional factors associated with the firm’s home country. We also explore how corporate governance and organizational identity influence the survival of foreign IPOs in the United States. Results suggest that the US institutional environment supports foreign firms with more independent and professional leadership, and that knowledge-intense organizations have higher chances of long-term success after listing on US exchanges.

This study aims to investigate the customers’ behavioral intention and actual usage (AUE) of artificial intelligence (AI)-powered chatbots for hospitality and tourism in India by extending the technology adoption model (TAM) with context-specific variables.

To understand the customers’ behavioral intention and AUE of AI-powered chatbots for tourism, the mixed-method design was used whereby qualitative and quantitative techniques were combined. A total of 36 senior managers and executives from the travel agencies were interviewed and the analysis of interview data was done using NVivo 8.0 software. A total of 1,480 customers were surveyed and the partial least squares structural equation modeling technique was used for data analysis.

As per the results, the predictors of chatbot adoption intention (AIN) are perceived ease of use, perceived usefulness, perceived trust (PTR), perceived intelligence (PNT) and anthropomorphism (ANM). Technological anxiety (TXN) does not influence the chatbot AIN. Stickiness to traditional human travel agents negatively moderates the relation of AIN and AUE of chatbots in tourism and provides deeper insights into manager’s commitment to providing travel planning services using AI-based chatbots.

This research presents unique practical insights to the practitioners, managers and executives in the tourism industry, system designers and developers of AI-based chatbot technologies to understand the antecedents of chatbot adoption by travelers. TXN is a vital concern for the customers; so, designers and developers should ensure that chatbots are easily accessible, have a user-friendly interface, be more human-like and communicate in various native languages with the customers.

This study contributes theoretically by extending the TAM to provide better explanatory power with human–robot interaction context-specific constructs – PTR, PNT, ANM and TXN – to examine the customers’ chatbot AIN. This is the first step in the direction to empirically test and validate a theoretical model for chatbots’ adoption and usage, which is a disruptive technology in the hospitality and tourism sector in an emerging economy such as India.

This paper aims to investigate how professionals such as accountants, auditors, senior civil servants and academics perceive the use of audit sampling strategies adopted by professionals to increase detection rates of frauds and corruption within the public sector in Africa. It also examines the respondents’ perceived values regarding the reasons for committing frauds, types of fraud and corruption, as well as the aspects of audit sampling strategies to tackle frauds.

This research uses non-parametric statistics and logistic regression to analyse the respondents’ opinions regarding the state of frauds and corruption in Africa (particularly in Tunisia and non-Tunisia countries), the common factors behind people committing frauds, including the types of frauds and corruption and the respondents’ opinions on the use of audit sampling strategies (non-random and random) to examine the instances of frauds and corruption.

The findings indicate that most respondents prefer to use non-probabilistic audit sampling rather than more robust sampling strategies such as random sampling and systematic random sampling to detect frauds and corruption. In addition, although there are some minor statistical differences between the countries in terms of the respondents’ perceived values on skimming fraud and on the use of audit random sampling to tackle rampant corruption in Africa, the overall findings indicate that opinions do not significantly differ between the respondents from Tunisia and other countries in terms of the types of fraud, the reasons for committing fraud and the auditing sampling strategies used to investigate the frauds.

This research serves as an analytical exploratory study to instigate further audit sampling research to combat rampant fraud and corruption in the public sector in Africa.

There are few or non-existent studies investigating the application of audit sampling strategies in Africa countries, particularly to examine the application of audit random sampling and audit non-random sampling strategies to detect fraudulent activities and corruption. Correspondingly, this research carries strategic implications for accountants and auditors to successfully detect fraudulent activities and corruption in Africa.

The disruptive human resource management (HRM) technologies are now considered a significant facilitator to change and benefit the entire HRM landscape. This view needs to be further verified by reviewing the knowledge on the subject in the empirical research landscape. Thus, the study's objectives were to find (1) the current knowledge and (2) the areas where empirical research is lacking in disruptive HRM technologies.

The article is a literature review that was followed by the systematic literature review and the preferred reporting items for systematic reviews and meta-analyses (PRISMA). The review considered 45 articles published during the 2008–2021 period extracted from the Scopus database, and bibliometric analysis was performed to achieve the research objectives.

The results found that scholarly attention has been given to electronic HRM (E-HRM) rather than the disruptive HRM technologies. The areas investigated include the determinants of intention, adoptions and use of E-HRM and the outcomes of E-HRM adoptions and use. These outcomes can be further divided into general outcomes and HRM outcomes.

The findings reveal gaps in E-HRM research and disruptive HRM technologies remain untapped in the empirical research landscape. Hence, the study findings provide some implications for future research and applications.

The study found empirically proven determinants of E-HRM intention, adoptions and use and E-HRM adoptions and use outcomes. These were found in the studies conducted during the 2008–2021 period.

顛覆性人力資源管理技術被認為是一個可改變、並幫助整個人力資源管理格局的重要誘導者; 這個看法、需透過檢核在實證研究範疇裡就有關議題的資料、才能作進一步的核實。因此，本研究擬了解 (1): 我們目前對有關議題的認知，以及 (2): 就顛覆性人力資源管理所進行的實證研究有哪些不足之處。

本文是一個文獻探討。研究人員採用系統文獻綜述研究法，以及系統綜述和 meta分析的首選報告項目。研究涵蓋45篇於2008年至2021年期間發表的學術文章; 這些文章均取自 Scopus資料庫。研究人員進行文獻計量分析，以達到研究的目標。

研究結果顯示、被研究探索的是電子化人力資源管理 (E-HRM) ，而不是顛覆性人力資源管理技術。被研究的範疇包括使用電子化人力資源管理的決定因素，以及使用後的結果。使用後的結果再細分為一般性的結果、和與人力資源管理有關的結果。

研究結果顯示、在實證研究的範疇裡，電子化人力資源管理和顛覆性人力資源管理技術的研究均存在未被探索的研究缺口。因此，研究結果為今後的研究和有關的應用提供了啟示。

本研究發現並確認經實證證明的使用電子化人力資源管理的決定因素，以及使用後的結果。研究結果乃基於檢核於2008年至2021年期間進行的學術研究而得來的。

顛覆性人力資源管理技術、系統文獻綜述、系統綜述和meta分析的首選報告項目 (PRISMA)

Disruptive technologies for human resource management (HRM) lack evidence about synthesizing its antecedents and outcomes in the empirical research landscape. This review study was conducted addressing two objectives: (1) to identify the themes of HRM technology empirically researched and (2) to develop a conceptual framework for the antecedents and outcomes of disruptive technologies for HRM.

This article was positioned as a literature review based on the systematic literature review (SLR) methodology. Seventeen articles published between 2000 and 2020 were included for the review from Scopus and LENS.ORG databases. The article screening, inclusion and analysis and findings reporting were based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA).

In addressing the first objective, the review found that the electronic human resource management (E-HRM) intention and communication technology support impact E-HRM adoption, resulting in many outcomes. The outcomes include HRM service quality, organizational effectiveness, employee productivity and competitive advantage. In addressing the study's second objective, a conceptual framework was developed based on the gaps identified regarding the determinants and positive outcomes of disruptive technologies for HRM. Thus, the conceptual framework was presented from two perspectives. The perspectives were deduced with review results and theoretical grounds.

The findings related to the two objectives provide theoretical and practical implications. One significant practical implication is that action and work-based learning of managers and employees in organizations may suggest adopting disruptive technologies for HRM. Thus future studies can focus on them as determinants of adopting disruptive technologies for HRM to conduct empirical tests. Besides, the findings provide some other future research directions.

The study found empirically proven determinants of E-HRM intention and communication technology support impact E-HRM adoption, which results in many positive outcomes. These were synthesized based on the studies conducted during the period 2000–2020. This synthesis and theoretical grounding deduced a conceptual framework for determinants and outcomes of disruptive technologies for HRM.