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This paper presents a decision-making framework for e-banking operations, based on the Quality Function Deployment and the Analytic Hierarchy Process. The main research question is the development of a framework and its potential contributions in supporting decision makers in implementing quality strategies that will encourage the usage of e-banking services (EBS).

The introduced framework comprises four distinct stages which include criteria determination, field surveys and EFA, QFD application including AHP and finally sensitivity analysis investigating the dynamic nature of the environment. AHP determines the intensity of the relationship between e-banking quality criteria and customer banking activities. A novel House of Quality (HoQ) is proposed, based on a market mix founded on key e-banking activities, and sensitivity analysis is used to investigate alternative scenarios. To illustrate the steps of applying this framework, the authors use a convenience sample from the Greek e-banking sector.

Through the illustrated example is supported that the proposed approach can reveal valuable information when contemplating strategies to improve e-banking usage and expand its acceptance. In addition, sensitivity analysis leads to purposeful insights regarding the effects of market segmentation and/or target settings on the ranking of e-banking quality/selection criteria provided by the HoQ. In the specific numerical example, the most critical quality factors were “Security and Reliability”, “Convenience”, “Design”, “Pricing” and “Skills,” although different rankings night well appear in different contexts or geographical regions. Moreover, sensitivity analysis showed that these results depend on the specific market mix and targets. As mentioned above, the implementation of the framework in different geographical regions or e-service sectors might certainly reveal different critical factors.

Discussed in the paper body.

Discussed in the paper body.

The paper presents a well-defined four stage framework for improving EBS penetration. It utilizes a structured qualitative and quantitative approach and outlines and ranks e-banking quality factors stemming from the market mix and allows assessment of alternative scenarios through sensitivity analysis.

This study aims to investigate whether auditors compromise their independence for economically important clients in family business settings.

The authors empirically examine the research question based on China for the years 2011 to 2020. The dependent variable is the auditors’ propensity to issue modified audit opinions, which is a proxy for auditor independence. The authors use relative client audit fees as a proxy for client importance. To address endogeneity issues in the selection of family firms, the authors use the two-stage least squares regression model and, subsequently, the propensity score matching and Hausman firm fixed effect modeling.

This study reveals that the propensity to issue modified audit opinions is positively correlated with client importance. Big-N auditors are more likely to issue modified audit opinions for their economically important family firm clients, whereas such evidence is not found for non-Big-N auditors. Results are consistent and robust to endogeneity test and sensitivity analysis.

This study enriches the literature on auditor independence and the effect of family firms’ ownership structure factors on audit reporting behavior for their economically important clients. Findings may prove useful for managers and practitioners interested in family business.

This study aims to investigate whether auditors compromise their independence for economically important clients in countries with a secrecy culture.

The authors empirically examine the research question based on a data set of 33 countries for the period from 1995 to 2018. The dependent variable is the auditors’ propensity to issue modified audit opinions, which is a proxy for auditor independence. The authors use relative client size as a proxy for client importance. The authors adopt the Heckman (1979) two-stage model to mitigate the potential endogeneity issue involved in the selection of Big-N auditors.

Using a large sample of firms and controlling for the firm- and country/region-level factors, this study reveals that both Big-N and non-Big-N auditors are more likely to issue modified audit opinions to clients located in countries with a strong secrecy culture relative to those located in other countries. However, Big-N auditors are more likely to issue modified audit opinions for their economically important clients with a secrecy culture relative to their other clients, while no or weaker evidence is found for non-Big-N auditors. The results are consistent and robust to endogeneity tests and sensitivity analyses.

This study enriches the literature by providing a new perspective on auditor independence that an auditor’s reporting behavior can vary depending on the client’s importance and auditor type, even under the same secrecy culture.

The current era of the fourth industrial revolution has attracted significant research on the use of digital technologies in improving construction project delivery. However, less emphasis has been placed on how these digital tools will influence the management of the construction workforce. To this end, using a review of existing works, this chapter explores the fourth industrial revolution and its associated technologies that can positively impact the management of the construction workforce when implemented. Also, the possible challenges that might truncate the successful deployment of digital technologies for effective workforce management were explored. The chapter submitted that implementing workforce management-specific digital platforms and other digital technologies designed for project delivery can aid effective workforce management within construction organisations. Technologies such as cloud computing, the Internet of Things, big data analytics, robotics and automation, and artificial intelligence, among others, offer significant benefits to the effective workforce management of construction organisations. However, several challenges, such as resistance to change due to fear of job loss, cost of investment in digital tools, organisational structure and culture, must be carefully considered as they might affect the successful use of digital tools and by extension, impact the success of workforce management in the organisations.

Literature has recognised entrepreneurship education as the main conduit through which entrepreneurial behaviours, attitudes and actions can be built, enacted and delivered. Since the founding of new ventures is largely a resourceful founder-driven enterprise, entrepreneurship education has largely centred on galvanising and shifting the mindsets and cognition of the entrepreneur. Yet, despite over 60 years of delivering entrepreneurship education programmes, hard evidence of the generation of high-growth-oriented and sustainable ventures has been scarce as student entrepreneurship intentions do not always translate into successful venture creation. This is largely because of the complexities of the practicality of entrepreneurial education particularly, the dissonance between acquired education in business schools and the knowledge and competencies needed in the entrepreneurial field. Such dissonance can be attributed to the lack of clarity on the pedagogical approach that most resonates with entrepreneurial action, the diversity in assessment methods and the scholarly illusion pertaining to how pedagogical approaches can be channelled to the generation of growth-oriented ventures. Drawing on Girox's concepts of transformative critical pedagogy (including pedagogy of repression), Socratic dialogue, Hegelian dialectic and Yrjö Engeström's transformative expansive agency, I demonstrate how a flipped transformative critical pedagogy can be harnessed in digitally enhanced learning environments to create new entrepreneurial possibilities for facilitating critical inquiry, complex problem-solving, innovation for the market and fostering tolerance for failure in ambiguous entrepreneurial contexts.

The purpose of this paper is to investigate the effect of equity market misvaluation on manager behavior. Using a sample of 535 French-listed over 2000–2018, the authors analyze whether corporate investment decision is sensitive to equity market overvaluation.

The study adopts market-to-book (M/B) decomposition developed by Rhodes-Kropf and Viswanathan (2004, RKV) that proxies for market misvaluation at the firm and industry levels. The authors conducted a long-term performance analysis via a portfolio sorting procedure and a Carhart (1997) four-factor pricing model. The authors tested the relationship between equity misvaluation, corporate investment decisions and equity issuance. The authors ran several robustness tests.

The empirical results show that equity market misvaluation affects corporate investment positively as the stock price deviates further away from its fundamental. Based on market timing theory, the authors find that corporate investment occurs in periods of high valuation motivated by equity issuance to benefit from the low cost of capital. This effect is more prominent for financially constrained firms. Consistent with the catering channel, the authors find that the misvaluation-investment nexus is more pronounced in firms with short-horizon investors. By examining the stocks’ long-term performance of misvalued firms, via a sorting portfolio procedure, the authors find that undervalued firms outperform and generate higher abnormal returns (Jensen’s alpha) than overvalued firms, suggesting that mispricing-driven investment appear to be short-lived and lead to lower return in the long term.

Corporate decision-makers and governance structures should pay attention to the rationality of the corporate investment decision in the context of equity market misvaluation. Managers who focus on maximizing the stock market value in the short-run at the expense of its long-term performance must give preference to value-creating investment, not driven by an external mechanism such as equity market mispricing. More generally, investors and portfolio managers must take into account the market mispricing process in decision-making. Nonetheless, from the portfolio sorting perspective, decision-makers must act in terms of high governance quality to mitigate suboptimal investment due to stock market mispricing (Jensen, 2005). Finally, equity market overvaluation, leading managers to invest via equity financing in particular, should be a signal to attract investors’ attention to seize the window of opportunity and embark on a short-term portfolio strategy. Such a strategy promises high returns in the short term.

This paper investigates jointly two theoretical channels: equity market timing and catering. The authors propose for the analysis three components of the M/B decomposition to dissociate market misvaluation at the firm and industry level from the fundamental component of market value (growth). This procedure provides a better understanding of the role of firm and industry misvaluation in explaining corporate investments. The authors provide evidence of the equity market misvaluation via a portfolio sorting procedure and a Carhart (1997) four-factor pricing model. The authors examine the effect of misvaluation on both the investment and the financing decisions.

The purpose of the study is to analyse the impact of COVID-19 on the hospitality industry during the rise of worldwide pandemic crises using Twitter analysis. The study is based on 57,794 English-language tweets mined from Twitter from 1 April 2020 to 15 October 2020. Based on thematic and sentiment analysis, the study found that overall sentiments expressed on Twitter were negative. This chapter contributes to existing knowledge about the COVID-19 crisis and broadens the respondents’ understanding of the potential impacts of the crisis on the most vulnerable tourism and hospitality industry. This research emphasises the sustainable revival of the hospitality industry.

This study aims to propose novel edge device-tailored federated learning algorithms of local classifiers (stochastic gradient descent, support vector machines), namely, FL-lSGD and FL-lSVM. These algorithms are designed to address the challenge of large-scale ImageNet classification.

The authors’ FL-lSGD and FL-lSVM trains in a parallel and incremental manner to build an ensemble local classifier on Raspberry Pis without requiring data exchange. The algorithms load small data blocks of the local training subset stored on the Raspberry Pi sequentially to train the local classifiers. The data block is split into k partitions using the k-means algorithm, and models are trained in parallel on each data partition to enable local data classification.

Empirical test results on the ImageNet data set show that the authors’ FL-lSGD and FL-lSVM algorithms with 4 Raspberry Pis (Quad core Cortex-A72, ARM v8, 64-bit SoC @ 1.5GHz, 4GB RAM) are faster than the state-of-the-art LIBLINEAR algorithm run on a PC (Intel(R) Core i7-4790 CPU, 3.6 GHz, 4 cores, 32GB RAM).

Efficiently addressing the challenge of large-scale ImageNet classification, the authors’ novel federated learning algorithms of local classifiers have been tailored to work on the Raspberry Pi. These algorithms can handle 1,281,167 images and 1,000 classes effectively.