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Entrepreneurship plays a key role in society and is important for economic growth. Despite prior studies of entrepreneurial behavior, no research has been conducted to examine the influence of monetary and personality factors on the entrepreneurial start up of Certified Public Accountant (CPA) firms in Hong Kong. The purpose of this paper is to investigate into factors influencing Hong Kong CPAs in becoming entrepreneurial public practitioners.

Data are collected through a questionnaire survey and analyzed by binomial logistic regression. A total of 212 CPAs of Chinese origin are randomly selected in Hong Kong. Social capital theory derived from the sociology literature is employed for analysing the findings.

Results indicate that “profit motivation” and “education level” variables have no significant influence on the entrepreneurial start up, and contradict findings in prior literature. Results further reveal that “social networking” and “internal locus of control” variables could positively influence on the entrepreneurial start up of CPA practices. Results support the validity of social capital theory that reveals social networks have values and productive benefits. Gender plays a role in the entrepreneurial start up of CPA practices, with males predominate has entrepreneurs of CPA practices.

This study could add new contributions to the accounting literature on the study of the entrepreneurial start up of CPA practices in Hong Kong. With the booming Hong Kong economy and the vast supports from China's prosperous market, Hong Kong CPAs are more inclined to become entrepreneurs of CPA practices in the long run. Implications of this study could enable accounting bodies and education institutions focusing on CPAs' personality development and education.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting‐edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Business is riddled with bad bosses. Some are greedy, egotistical or corrupt, some merely ineffective or incompetent, while others display inappropriate behavior towards employees. So what can be done about it?

The paper provides strategic insights and practical thinking that have influenced some of the world's leading organizations.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy‐to digest format.

The purpose of this paper is to demonstrate how generational differences impact America’s workforce as it changes and to provide strategies for companies to address aging Millennials (born 1982-2000), Generation X (born 1961-1981) and Baby Boomers (born 1943-1960).

The author's approach was based on research on behalf of the US Senate Special Committee on Aging; insights and expertise from her 20 years at the helm of Generational Targeted Marketing, LLC; her teaching at New York University; her experience working with clients and organizations in a wide range of diverse industries; and the insights from her book Marketing to the Millennial Woman.

Every generation is unique. Practitioners, employers and managers of human resources (HR) who understand and respect the differences between Millennials, Generation X and Baby Boomers can develop strategies from a generational point of view and thereby enable these employees to perform at their peak regardless of age.

Practical examples are given for HR practices in employee retention, benefits, performance management and review, work-life balance, digital and technology applications and for meaningful corporate outreaches.

This tried and true approach to dealing with distinct generations in the workplace leads to increased employee motivation and satisfaction, so that employees not only remain longer at a job but also are eager and happy to report to work each day; they are more productive; and the company’s bottom line benefits as a result.

For studies in educational data mining or learning Analytics, the prediction of student’s performance or early warning is one of the most popular research topics. However, research gaps indicate a paucity of research using machine learning and deep learning (DL) models in predictive analytics that include both behaviors and text analysis.

This study combined behavioral data and discussion board content to construct early warning models with machine learning and DL algorithms. In total, 680 course sections, 12,869 students and 14,951,368 logs were collected from a K-12 virtual school in the USA. Three rounds of experiments were conducted to demonstrate the effectiveness of the proposed approach.

The DL model performed better than machine learning models and was able to capture 51% of at-risk students in the eighth week with 86.8% overall accuracy. The combination of behavioral and textual data further improved the model’s performance in both recall and accuracy rates. The total word count is a more general indicator than the textual content feature. Successful students showed more words in analytic, and at-risk students showed more words in authentic when text was imported into a linguistic function word analysis tool. The balanced threshold was 0.315, which can capture up to 59% of at-risk students.

The results of this exploratory study indicate that the use of student behaviors and text in a DL approach may improve the predictive power of identifying at-risk learners early enough in the learning process to allow for interventions that can change the course of their trajectory.

This study aims at proposing and testing a model delineating how and when the quality of a special B2B professional service, investment relations (IR), would drive corporate intangible value.

This study employs a proprietary dataset on voting records of an annual investment relations (IR) awards event and the corresponding company-level archival data for analysis. Regression analysis is used to test hypotheses.

IR service quality not only directly enhances corporate intangible value, but also indirectly boosts it via information transparency. While competitive intensity does not moderate the relationship between IR service quality and corporate intangible value, its moderating effect on the relationship between information transparency and this value is negative.

The findings advance academic understanding of the mechanism and boundary conditions underlying the complex and dynamic relationships among IR service quality, information transparency, corporate intangible value and competitive intensity. Future research endeavors to verify the present findings in other service and/or geographic settings would help establish their external validity.

The findings advise companies to expand the traditional role of IR by taking it as a powerful communication and relationship marketing tool to improve their visibility and attract investors.

The findings suggest that superior IR service would strengthen the company’s social bonding with institutional investors and effectively signal to them its commitment to good corporate governance practices.

Matching a proprietary dataset on IR voting records with the corresponding company-level archival data over a five-year period to investigate the performance implications of IR service quality within the Hong Kong context rectifies methodological limitation and geographic confinement of prior IR research.

The paper aims to focus on institutional initiatives to embed e‐learning in a university in Hong Kong, from 2006‐12, through large‐scale funding of 43 e‐learning projects. It outlines the guiding principles behind the university's e‐learning development and discusses the significance of various procedures and practices in project planning, development and implementation.

This longitudinal study combines historical perspectives with process description, analysis and personal observations. Its approach is based in action research. The authors are engaged both as participants/learning designers in particular projects and in management, administration and evaluation of the projects at the institutional level.

It is proposed that e‐learning projects need careful planning, scaffolding and managing. Also that piloting, evaluation and formal reporting as well as the availability of professional, technical and instructional design support are significant factors in success.

This paper is preliminary work. Further findings and analysis are expected at the final completion of all projects. A wealth of data is available in accumulated project documentation and reports, including individual project evaluations with quantitative and qualitative data.

Given the commonly acknowledged difficulties in helping e‐learning projects continue to completion and actually be implemented, this study can offer strategies that may be widely applied in different contexts. The scale and timeframe of the study and the amount of funding available in one institution are unusual so emerging implications are potentially significant.

The rapid proliferation of mobile context aware applications has resulted in an increased research interest towards developing specialized context data management strategies for mobile entities. The purpose of this paper is to aim to develop a new way to model mobile entities and manage their contexts accordingly.

This paper proposes the concept of “Mobile Space” to model mobile entities and presents strategies to manage the various contexts associated therein. To handle availability related issues, two system services are designed: the “Availability Updating Service” which is an identifier based mechanism and is designed to keep track of mobile objects and handle availability related issues, and the “Application Callback Service” which is a publish/subscribe based mechanism to handle application disruptions and interruptions arising due to mobility.

The paper presents a detailed study of the proposed framework and a description of the underlying services and the components therein to validate the framework. Experimental results carried out in WiFi and 3G environments indicate that the proposed techniques can support mobile applications and minimize application disruptions with minimal overhead.

The proposed context management framework is generic in nature and is not designed for a specific class of applications. Any mobile context aware application can leverage on the framework and utilize the provided functionalities to manage application disruptions. Also, the decoupling of mobile application layer and the underlying context data management layer renders context data management layer transparent to the application design.

Beyond traditional brand endorsement, many celebrities have in recent years decided to launch their own product lines, which may be used to promote their own celebrity brand. Which product categories or social causes match a celebrity’s brand personality? This study aims to investigate the antecedents of celebrity–product degree of fit and willingness to pay (WTP)/make a donation in different scenarios. The manipulation of the scenarios aims to capture the role of celebrity attributes, perceived personality profiles, product involvement and acceptance of social causes.

In total, 335 respondents answered an online questionnaire with a factorial plan corresponding to 20 different matching scenarios: five celebrities/perceived personalities (Emma Watson, Jennifer Lawrence, Kim Kardashian, Natalie Portman and Scarlet Johansson) × four types of branding scenarios (a lipstick for low involvement; a watch for high involvement; an eco-foundation for “high social acceptance” and vodka for “low social acceptance/controversial”).

Scarlett Johansson obtained the highest degree of fit, both for launching her own brand of lipstick or a watch. Kim Kardashian had the best degree of fit for launching her own vodka brand, while Emma Watson’s attributes confirmed that she would be seen as the ideal founder of an eco-foundation. Significant predictors of WTP/make a donation were assessed by multiple linear regression for each type of product.

The paper provides recommendations that may help guide celebrity brand managers through the celebrity–product matching process.

Celebrity branding in relation to social causes is also discussed in this paper.

This study explores a gap found in the literature as it explores the product match-up hypotheses within a celebrity branding context and moreover extends this investigation to social causes and products with different degrees of involvement and social acceptance.

This paper aims to understand the factors of the exchange relationship that influence a target-partner’s decisions to adopt virtual governance strategies.

Hypotheses are tested using an online panel of 259 key informants from manufacturing firms that sell goods to retailers. Data are analyzed using structural equation modeling.

The study confirms the hypotheses that the target partner’s trust in the initiating partner is a significant driver of supply chain management system (SCMS) adoption intention. While trust fully mediates the adverse effects of technological uncertainty on adoption intentions, asset specificity directly influences both trust and adoption intentions. Additionally, the initiating-partner’s incentive orientation mitigates these effects and encourages SCMS adoption.

This paper contributes to the study of virtual governance and interorganizational adoption decisions in two primary ways. First, it elucidates the relationship between transaction costs and relational norms. Second, it examines the role that the shadow of past incentives has on the target-partner’s decisions to electronically integrate with the initiating partner.

The findings from this study contribute to the virtual governance and interorganizational technology adoption literature by demonstrating the relevance of characteristics of the exchange relationship in the target-partner’s decision to adopt the SCMS technologies necessary for electronic integration. This study provides a better understanding of the function of transaction costs and relational norms that paves the way for further exploration of the choice to adopt virtual governance strategies.

Given that SCMSs enable virtual governance, the findings of this study make important contributions to understanding how transactional and relational elements of the exchange relationship influence a target-partner’s decisions to participate in vertical control strategies with an initiating-partner.

The purpose of this paper is to address the role of social robots in the education industry, specifically within special developmental schools, as a part of an innovation technology portfolio. It identifies critical success factors (CSFs) arising from the development, adoption and implementation of social robots to educate students with special needs and assist their teachers.

The study engaged in longitudinal research over 12 months, tracking the role of the Matilda robot in providing educational services to students with special needs.

The results propose a three-faceted framework for social robot application in special education: development, adoption and implementation.

The study has shown the willingness of students and teachers to embrace social robot technology, and the CSF that arise from this adoption. It has also found that social robots achieve the greatest success within the development, adoption and implementation framework when championed by executive management, and peer teacher support.