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This research paper aims to investigate the effects of internal audit’s (IA) use of data analytics and the performance of consulting activities on perceived IA quality.

The authors conduct a 2 × 2 between-subjects experiment among upper and middle managers where the use of data analytics and the performance of consulting activities by internal auditors are manipulated.

Results highlight the importance of internal auditor use of data analytics and performance of consulting activities to improve perceived IA quality. First, managers perceive internal auditors as more competent when the auditors use data analytics. Second, managers perceive internal auditors’ recommendations as more relevant when the auditors perform consulting activities. Finally, managers perceive an improvement in the quality of relationships with internal auditors when auditors perform consulting activities, which is strengthened when internal auditors combine the use of data analytics and the performance of consulting activities.

From a theoretical perspective, this research builds on the IA quality framework by considering digitalization as a contextual factor. This research focused on the perceptions of one major stakeholder of the IA function: senior management. Future research should investigate the perceptions of other stakeholders and other contextual factors.

This research suggests that internal auditors should prioritize the development of the consulting role in their function and develop their digital expertise, especially expertise in data analytics, to improve perceived IA quality.

This research tests the impacts of the use of data analytics and the performance of consulting activities on perceived IA quality holistically, by testing Trotman and Duncan’s (2018) framework using an experiment.

This case requires students to evaluate alternative dual-share-class corporate structures that allow companies and entrepreneurs to pursue profit with purpose. The case explores Impact Makers, an IT consulting company based in Richmond, Virginia. While original founders of the firm hold all voting rights, the cash flow rights belong to two nonprofits setting the stage for a Newman's Own model of management consulting. The case discusses whether and how the alternative corporate structure aids the firm's overall strategy to attract top-quality employees, pay them competitive salaries, and provide superior service to its clients while donating 100% of its lifetime value to charitable causes, largely through partnerships with various nonprofit organizations. More importantly, the case asks students to evaluate how such a dual-share-class and dual-purpose company can raise capital to fund continued growth.

The case opens with CEO Michael Pirron reminding himself of all the questions he had run through to execute a strategy to further grow Impact Makers' consulting business both through expanding a menu of services and through conquering new geographical markets. To do either, or both, the company needed a cash infusion. Internal cash was limited, as up to 40% of it flowed to charitable partners, demonstrating Impact Makers' commitment to its mission. Raising debt for a company without fixed assets was challenging and time consuming. Complicating it all was that being structured as a nonstock corporation rendered equity raising difficult. Could Impact Makers raise money to grow and stay true to community values at the same time?

Service robots present a new frontier in the provision of services, with far-reaching implications for customers and managers alike. The purpose of this chapter is to examine how service robots impact service providers' current marketing strategies. For this, the authors perform an integrative, nonsystematic review of international gray and academic literature to understand how both practitioners and academics perceive the impacts of the technology. Based on this analysis, the present work identifies three key themes that emerge from the current state of practitioner and academic research, namely (1) service robots demand new core business capabilities and competencies, (2) service robots offer new value propositions, and (3) service robots impact not only service providers' cost structures but also revenue streams. These insights are combined into the Service Robot Innovation Canvas, a visual tool for service providers to identify the impact of service robot implementations on a company's marketing strategy. In addition, based on the analyzed literature, the most pressing questions for researchers are laid out in a research agenda.

Assessing project criticality in a project portfolio (PP) is of great practical significance to improve robustness from damage. While project criticality assessment has increased diversity in approaches, the understanding of vulnerable project impacts is still limited. To promote a better understanding of assessing project criticality, a vulnerability measurement model is constructed.

First, integrating the tasks, projects and corresponding relationships among them, a project portfolio network (PPN) is constructed. Second, the project's vulnerability is measured by combining the topological structure and functional attributes. Third, project criticality is assessed by the vulnerability measurement results. Lastly, the proposed model is applied in a numerical example to illustrate its suitability and effectiveness.

For academia, this study provides a novel perspective on project vulnerability measurement and expands project criticality assessment tools. For practitioners, the straightforward model provides an effective tool for assessing project criticality and contributes to enhancing project portfolio management (PPM).

The impact of the task on the project is considered in this study. Topological structure and functional attributes are also integrated for measuring project vulnerability due to the impact of random attacks in an uncertain environment, providing a new perspective on the requirements of project criticality assessment and the measurement of project vulnerability.

The paper aims at studying the effect of management practices on the extensive and intensive export margins of Egyptian manufacturing firms.

The study relies on the 2020/2021 Egyptian Industrial Firm Behavior Survey (EIFBS) which comprises 2,383 manufacturing firms representing small, medium, and large sized firms located in different regions of Egypt: Urban Governorates, Lower Egypt, and Upper Egypt. It constructs an overall management z score for each firm to estimate its effect on a firm’s probability of exporting and value of exports using Ordinary Least Squares (OLS) regressions.

Results indicate that good management is associated with a higher probability of firm exporting as well as higher export revenues conditional on exporting, robust to controlling for the level of domestic sales. These effects do not differ by firm ownership or type of sector, but rather by firm size, with managerial competence raising the probability of exporting more for large-sized firms. Additionally, good management is associated with higher firm productivity, innovation and worker training propensities which gives evidence that it is both an efficiency and a quality enhancer. Moreover, monitoring and targeting practices have significant positive effects on both margins, while incentives are only significant for the extensive margin.

Firms that aim at enhancing their export prospects and revenues should devote resources to review and upgrade their management systems to boost their product quality and production efficiency. Policy-wise, the government should create a competitive market environment that is open to both domestic and foreign firms’ entry to stimulate the adoption of better management practices.

The paper is the first to explore the link between firm management practices and export outcomes for a MENA country (Egypt). It makes use of a recent survey, the 2020/2021 Egyptian Industrial Firm Behavior Survey (EIFBS). The findings shed light on the importance of different management components (monitoring, targeting and incentives) in driving a manufacturing firm’s export performance.

In recent years, the robotic process automation (RPA) technology has increasingly been used to automate business processes. While a lot of research has been published on the potential and benefits of the technology, only a few studies have conducted research on challenges related to RPA adoption. Hence, this study aims to identify and discuss challenges related to RPA implementation projects.

Following an inductive methodology, interviews have been conducted with consultants who were involved in multiple RPA implementation projects. Hence, their extensive experience and views contribute to a detailed and in-depth understanding of the phenomena under research.

The results suggest that there are various process-related, technical, resource-related, psychological and coordinative challenges that must be considered when conducting an RPA implementation project.

This paper contributes to knowledge by presenting a new typology of challenges, as well as providing an in-depth discussion of the individual challenges that organizations face.

The paper tries to investigate the impact of applications of the resource-based view (RBV) theory in the management field to improve the firm’s profitability. Global firms are innovating and adopting new technology, paving the way to improve their performance.

We have adopted RBV in management practices such as marketing, strategy, finance, and human resources.

RBV has gained researchers' attention with the growing competitive world and new challenges to retaining customers and achieving their pre-defined targets. We attempt to identify the issues related to the usage of RBV in management.

Using RBV in management may help researchers create a competitive mindset and be prepared for uncertain challenges in the business world.

Based on an exploratory case-based approach, the purpose of this paper is to open the KM black box and examine the relationships that link knowledge management (KM) inputs (i.e. knowledge resources and KM practices) via knowledge processes to KM performance. This paper aims to identify the underlying mechanisms and explain how KM performance is enabled.

This in-depth case study conducted at a medium-sized consultancy in the supply chain management industry empirically examines knowledge flows to uncover the relationships between KM inputs, knowledge processes and KM performance. We adopt the viable system model (VSM) as a theoretical lens to identify KM mechanisms.

By identifying six KM mechanisms, we contribute to the theoretical understanding of how KM inputs are interconnected and lead to KM performance via knowledge processes.

Based on the insights gained, we provide propositions that organizations should consider in designing viable KM. Our findings help organizations in understanding their KM with the help of knowledge flow analysis and identifying how critical KM elements are interconnected.

Introduction: According to the existing research, one of the key determinants of a company’s survival and market development is its ability to get bank loans or other external sources of finance for business expansion.

Purpose: The study aims to explore the factors affecting access to finance and their effects on the development of medium- and small-sized businesses. These factors include business size and age, profitability, the length of a company’s association with a commercial bank, and banking sector characteristics.

Need for the study: It is particularly crucial for small- and medium-sized businesses since they often have trouble getting funding from banks because they don’t supply the banks with the information they need to assess their loan application prospects, however, when a company’s economic and financial situation improves, banks get access to more information about the firms, and financing is thus more readily available.

Methodology: This research is based on qualitative methods, focus on an elaborative study of the existing literature, and provide suggestions based on the same.

Findings: The findings show that small- and medium-sized businesses, like those in other European nations, have less access to finance than large businesses. It revealed that the company’s size, liquidity, profitability, and banking industry state significantly influence the availability of bank loans.

The importance of mental wellbeing and the need for organizations to address it is increasing in the post-pandemic context. Although Artificial Intelligence (AI) is increasingly being adopted in HRM functions, its adoption and utility for enabling mental wellbeing is limited. Building on the Open System Theory (OST) and adopting the technology-in-practice lens, the authors examined the roles of human and technology agencies in enabling mental wellbeing.

The study was conducted in two stages; in Stage 1, the authors adopted a case methodology approach to examine the feasibility of a technology company's offerings to assess mental wellbeing. In Stage 2, the authors followed the grounded theory approach and interviewed 22 key stakeholders and HR leaders of diverse organizations. The authors used Gioia's approach to analyze the data.

The study demonstrates the interdependence and inseparability of human activity, technological capability and structured context. Specifically, the authors observe that AI adoption is pushing the boundaries of how organizations could support employees' mental health and wellbeing. These technological advancements and adoption are likely to facilitate the evolution of agentic practices, routines and structures.

This study carries two important implications. While the advent of cutting-edge technologies appears to affect employees' mental wellbeing, the study findings indicate the assistive role of technology in supporting mental wellbeing and facilitating changes in organizational practices. Second, the ontology of technology-in-practice shows how human–machine agencies gain newer relevance from the interactions that unite them. Specifically, per OST, technology (from an external context) can potentially change how mental wellbeing practices in organizations are managed. The authors extend the existing literature by suggesting that both human agents and internal contexts effectively limit the potential of technology agents to change existing structures significantly.

The authors address the need for more research on the technology-management interface, and the boundaries of technology-enabled wellbeing at work. While AI-HRM scholarship has primarily relied on micro-level psychological theories to examine impact and outcomes, the authors borrow from the macro-level theories, such as the OST and the technology-in-practice to explain how AI is shifting the boundaries of human and machine agencies for enabling mental wellbeing.