Abstract

     Internal audit quality is the foundation for a company’s survival and development across the world. As a result, global efforts have been made to develop a scientific and accurate evaluation index for internal audit quality. However, literature shows that existing internal audit quality evaluation indices have many flaws, such as a lack of systematic internal audit evaluation indicators, poor execution, and inability to identify priority areas. To address gaps in the literature, this study intended to construct an internal audit quality evaluation index utilizing the joint approaches of the Balanced Scorecard, Delphi Process, and Analytical Hierarchy Process. A systematic literature review, examination of companies’ internal audit guidelines, Balanced Scorecard, and Delphi approaches resulted in a multilevel internal audit quality evaluation index with five dimensions (stakeholder satisfaction, stakeholder contribution, financial results, internal audit process, and learning and growth) and 36 indicators. The Analytical Hierarchy Process revealed that the most prioritized dimension is the internal audit process. The consistency ratio and evaluation feedback from the listed companies’ internal auditors, management, and audit committee members revealed that the results are valid and reliable.

Introduction

     Internal audit quality is the foundation for a organization’s survival and development across the world. According to Boskou et al., 2019, internal audit quality (IAQ) is a critical component of an organization’s sustainability since it assists the business in maintaining effective controls and avoiding fraud. Several publications (Ashbaugh-Skaife et al., 2008; Hoai et al., 2022) have shown that effective internal control may improve the quality of financial reporting. It is commonly acknowledged that IAQ is a critical component of successful internal control, on which financial reporting quality is also dependent. It helps the organization’s operations since it is a separate activity that assists a corporation in achieving its goals by employing a well-organized approach to risk management, internal control, and governance efficiency and effectiveness (Stewart and Subramaniam, 2010; El Gharbaoui and Chraibi, 2021). Scholars from all around the world have discovered a link between IAQ and organizational performance (Hazaea et al., 2020; Kaawaase et al., 2021). Hence, IAQ is of interest to managers, shareholders, investors, auditors, and consequently international organizations and nations.

     In line with the usefulness of the IAQ, there have been global efforts in establishing a scientific evaluation index for IAQ. International organizations and regulatory bodies such as the Financial Reporting Council (FRC) and the largest six audit firms in the United Kingdom; the Public Company Accounting Oversight Board (PCAOB) in the United States; the Chartered Accountants of Australia and New Zealand (CAANZ); the Accounting and Corporate Regulatory Authority (ACRA) in Singapore; and the International Organization of Securities Commissions (IOSCO) put forward indicators for evaluating IAQ. For instance, PCAOB published 28 indicators for evaluating audit quality while CAANZ published only nine indicators. The Committee of Sponsoring Organizations of the Treadway Commission (COSO) also published five components of a firm’s internal control system with 17 principles (COSO, 2013).

Conclusion and recommendations

     The need for a scientific and reliable IAQE index to guide companies to improve internal auditing influenced this study. This study constructed the IAQE index by combining literature review, preliminary analysis, and review of companies’ internal audit guidelines, BSC, Delphi Process, and AHP methodologies. A systematic literature review, review of companies’ internal audit guidelines, BSC, and Delphi approaches resulted in a multilevel IAQE index comprising five dimensions and 36 indicators. Eight indicators were selected stakeholder dimension, nine indicators for stakeholder contribution dimension, seven indicators for financial results dimension, six indicators for internal audit process dimension, and six indicators for learning and growth dimension. The AHP results through experts’ judgment of the dimensions and indicators revealed that all the five dimensions are important in the IAQE index system. Overall, “achieving internal audit objectives” had the highest weight while “the number of complaints received by the internal audit department” had the lowest weight in the IAQE index system. The CR and feedback evaluation from the internal auditors and audit committee members of the selected enterprises revealed the acceptability of the results. In line with internal auditing standards, the developed IAQE index fits well with internal audit components since the index offers an independent, objective assurance and consulting among key stakeholders internal auditing for evaluating and improving the efficacy of risk management, control, and governance systems.

Highlights

Abstract

Graphical abstract

Keywords

Introduction

Literature review

Methodology

Results and implications

Conclusion

Declaration of competing interest

Acknowledgements

References

Abstract

The profound impact of the coronavirus disease 2019 (COVID-19) pandemic on global tourism activity has rendered forecasts of tourism demand obsolete. Accordingly, scholars have begun to seek the best methods to predict the recovery of tourism from the devastating effects of COVID-19. In this study, econometric and judgmental methods were combined to forecast the possible paths to tourism recovery in Hong Kong. The autoregressive distributed lag-error correction model was used to generate baseline forecasts, and Delphi adjustments based on different recovery scenarios were performed to reflect different levels of severity in terms of the pandemic’s influence. These forecasts were also used to evaluate the economic effects of the COVID-19 pandemic on the tourism industry in Hong Kong.

Introduction

In many places, tourism has become a strategic pillar industry, given its increasingly significant contributions to the local gross domestic product (GDP). Despite its importance, tourism is also one of the most vulnerable industries. The tourism industry has experienced significant negative effects during so-called “black swan” crisis events, such as the financial crises in 1997 and 2008, the severe acute respiratory syndrome (SARS) epidemic in 2003, and various earthquakes and episodes of social unrest. Business operations are contingent on forecasts. However, forecasts generated using traditional methods might be out-of-date and ineffective in a crisis. Therefore, a useful method that can produce accurate forecasts for both academia and business purposes is urgently needed.

Since late 2019, the coronavirus disease 2019 (COVID-19) pandemic has caused unprecedented global health and social emergencies and profound negative impacts on the global economy. By September 30, 2020, 33,561,077 confirmed cases of COVID-19 and 1,005,004 deaths had been reported worldwide (World Health Organization; WHO, 2020). The United Nations World Tourism Organization (UNWTO) reported that by April 20, 2020, all major tourist destinations had implemented travel restrictions in response to the COVID-19 pandemic (UNWTO, 2020). Tourism is among the industries most negatively affected by this pandemic. Lockdowns in many countries, widespread travel restrictions, and airport and national border closures reduced the number of international tourist arrivals by 67 million during the first quarter of 2020 (2020Q1). This decrease implies a loss of approximately US$80 billion in tourism revenue, compared with the same period in 2019 (UNWTO, 2020).

Hong Kong, which is known as the Pearl of the Orient, blends Eastern and Western cultures and is famous for its gourmet and shopping opportunities. Since the late 1980s, Hong Kong has vigorously developed its service sector. In 1989, the total tourist arrivals in Hong Kong were only 5,361,170 (Census and Statistics Department, 1990). By 2018, this number had increased to 65.15 million, with annual tourist revenues of HK$328.2 billion (Tourism Commission, 2019). In the first half of 2019, Hong Kong welcomed 34,871,856 inbound tourists, and this number represented a 13.9% increase relative to 2018 (Gov. HK, 2020).

A growing majority of the world’s population lives in cities, and the concentration of people and critical services in cities increases their exposure to acute shocks and long-term stresses. Therefore, building resilient cities that are able to resist and absorb threats and are capable of adapting to and recovering from shocks and stresses is vital for the wellbeing of society. Although the literature offers several studies on how city resilience can be improved, operationalizing resilience is still a challenge. This article describes the different phases of the cocreation process followed in the development of a maturity model that can guide cities in assessing and future improving their resilience level. This co-creation process was conducted using different methodologies involving an interdisciplinary group of international experts who contributed their knowledge and experience to the development process of the maturity model. The outcome of this process is the final version of a maturity model that operationalizes the steps that should be taken to build city resilience.

Introduction

The world is experiencing the largest wave of urban growth in history. Over half of the world’s population is now living in cities and according to the United Nations estimates, by 2050, 66% of the total world’s population is expected to be urban (UN, 2014). With this rapid urbanization, cities are facing a variety of acute shocks derived from natural disasters and long-term stresses, such as the effects of climate change (Harrison and Williams, 2016; UNISDR, 2015a). Therefore, there is a need for cities to implement policies for increasing resilience and improving preparedness to cope with both acute shocks and longterm stresses (Spaans and Waterhout, 2017). The concept of resilience has been applied in many different disciplines such as climate change, disaster risk reduction, and planning (Peng et al., 2017). This research considers resilience as a transversal capacity to deal with all kind of threats, expected and unexpected. Resilience goes beyond traditional risk management approach and it does not only take into account the type of threats towards the city is already preparing for but it is also focused on developing preventive and adaptive capacities to deal with any kind of unexpected threats (Park et al., 2013; Risk and Resilience Research Group – Center for Security Studies, 2011). Making cities resilient to shocks and stresses in order to ensure the welfare of society has become a major concern for academics, emergency management practitioners and governments (Chmutina et al., 2016).

Cloud Computing (CC) has become an important milestone information technology that attracts many organizations. With the potential to transform business processes, lower IT expenses, and offer access to unlimited computing resources with minimal management effort, organizations look to cloudbased solutions to achieve business efficiencies. Thus, it would seem that these organizations could easily migrate to CC. However, enterprises are still concerned about moving their business-critical applications to the cloud. Among the reasons are that it is an emerging technology that has not reached a level of maturity; the lack of industry-specific conformity to standards; and a high level of security risks. As a result, there is a big dispute among organizations on the decision of whether it is more business-efficient to embark on the cloud or remain with their interior IT infrastructures. In this paper, we aim to solve this debate by proposing a novel approach that supports decision-making on CC adoption in organizations. Unlike traditional decisionmaking approaches that pay little or no consideration to organizational high-level business objectives, our proposed approach is driven by the business objectives of the organization. First, we identify driving and restraining forces that influence CC adoption in organizations. Second, a formal decision-making model is proposed based on Force Field Analysis (FFA) augmented by pairwise comparison and Delphi methods, this model estimates the values of the driving and restraining forces based on their impacts on the organization’s objectives. By analyzing the forces for and against CC adoption, organizations can decide whether or not to move forward with the adoption. Alternatively, organizations can use the analysis to think about how they can strengthen the forces that support the adoption and weaken the forces opposing it, so that the adoption is more successful. The proposed model is validated for usability and applicability through a use case scenario.

Introduction

Cloud Computing (CC) is an emerging technology that promises many benefits over conventional on-premises computing. It provides vast opportunities for organizations to have more flexible and easy-running business models [9]. As the strategic focus on flexibility, innovation, and economic gains increases, organizations can no longer ignore CC’s benefits. Recently, enterprises have shown increasing interest in the adoption of CC services to support critical business functions. According to Forbes, CC market is projected to reach $411B by 2020 [40]. A survey conducted by LogicMonitor revealed that 83% of enterprise workloads will be in the Cloud by 2020 [43]. CC offers for companies a wide variety of IT services at a low cost. With decreased costs and less effort required to invest in and maintain hardware, license new software, or train new personnel, enterprises have more time to focus on their core business activities. In addition, CC services offer features such as elasticity and scalability that enhance the agility required to carry out the necessary business changes in an innovative and competitive environment [5]. Although several benefits of CC are well known and documented, evidence suggests that not all companies are rushing to adopt cloud-based solutions [6]. As highlighted by Mindshift Technologies, Inc. [41] many small businesses are still setting on the fence contemplating whether to move to or not to move to CC [7]. The reluctance to adopt CC services in organizations is due to different concerns about this technology.

The technological advances taking place in recent years have allowed organisations to improve their management processes. The emergence of the Internet has led to a revolution in the way that individuals, organisations and the Government carry out their tasks (Alawneh et al., 2013). It can also be seen that in recent years there has been an increase in recommendations from international organisations, encouraging Governments to use the new technologies and leading to the modernisation of the Government and an improvement in transparency and the services it provides to the public (European Commission, 2015). Quality management in electronic services has been extensively studied, with definitions, models and measurement instruments being proposed, above all in the for-profit sector (Ladhari, 2010; Park and Gretzel, 2007; Sylvester et al., 2013; Verma et al., 2016). In this context, researchers are relatively unanimous in arguing that for these technological innovations to be effective and of benefit to both parties it is necessary to provide the best quality in the service. To achieve these improvements, it is very important that “managers of businesses with Web presences must first understand how consumers perceive and evaluate online customer service“ (Parasuraman et al., 2005). However, the studies carried out within the public sector have not examined the issue to the same extent (Alawneh et al., 2013; Papadomichelaki and Mentzas, 2012) and as indicated by Gutiérrez Rodríguez et al. (2009), there is an open debate about whether the concept of the quality of the services provided can be transferred from the private sector to the public sector. Whilst scarce, some studies have been carried out on this issue in the areas of local government (Lee and Levy, 2014; Sá et al., 2016a), postal services (Águila-Obra et al., 2013), healthcare (Büyüközkan and Çifçi, 2012), tax management (Barnes and Vidgen, 2006; Belanche et al., 2014; Connolly et al., 2010; Lee et al., 2011), library services (Hernon and Calvert, 2005; O’Neill et al., 2001), etc. All these studies analyse, from the public’s perspective, their relationship with the Government. However, only Alawneh et al. (2013) study the problem from the perspective of the public employee, measuring the satisfaction of university employees in Jordan. Our work aims to look at this area in more depth, specifically focussing on ensuring that the managers of university websites understand how their employees perceive the quality of these service portals, and in this way to contribute to improving the online services that public organisations provide to their employees. The main objective of this article is to make a proposal on the dimensions or characteristics that a Government website must have if it is to be considered by its employees as high quality. To achieve this objective, a qualitative study was carried out using the Delphi method. To do this, surveys were conducted involving experts in the field of quality management in public services. The article is structured as follows; in Section 2 we define and classify the e-Government concept. Section 3 then contains a clarification of the electronic service concept. Section 4 is dedicated to describing the methodology used in the study. Next there is an explanation of how the participants were selected and how the two rounds with the panel of experts were performed. The article continues with a proposal of dimensions and items for measuring quality in the services provided by the Government to its employees, and it ends with the main conclusions, recommendations and limitations of the study.

Electronics industry encounters rapid changes in market, intense competition, fast-paced technological innovations and customer’s environmental awareness increasing. Hence, firms have an essential need to develop the agility for surviving in this rival environment. Agility exists in supply chain network can help firms to achieve the competitive advantage (Hayes and Wheelwright, 1984). Previous studies emphasized that supply chain agility (SCA) focuses on promoting innovation, flexibility and speed, and then reducing the costs of production (Lin and Tseng, 2016; Tseng et al., 2008). In addition, SCA not only consider as a tool to quick respond the changes in the markets (Fayezi et al., 2015; Lin et al., 2006; Wong et al., 2014; Yusuf et al., 1999), but also encourage individual firms to work together for enhancing the environmental credentials in terms of green raw materials, eco-product design, process integration and customer-based measures (Tseng, 2010, 2011; Tseng et al., 2015). Although supply chain network is a collaborative group that formed together to attain the mutual benefit in the economic and environmental performance, it still lacks a logical and crystal structure to guide the group in achieving the competitive advantage through SCA. To address this gap, this study proposes a closed-loop hierarchical decision-making structure to explore the key drivers of SCA for developing the competitive advantage. In addition, SCA has to be structured from multidimensional considerations to reflect the real situation, which might enhance the challenge and complex in the evaluation. Thus, Van der Vorst and Beulens (2002) proposed an evaluation model to reduce the uncertainty and enhancing effectiveness in searching the key drivers. This model contained the information integration, estimating the impact of alternative actions, lean production, organizational agility, quick response and individual actions. DeGroote and Marx (2013) demonstrated that information technology can increases SCA through quick respond market changes and enhance supply chain collaboration, so firms enable to reach the cost reduction, quality improvement and the innovative processes and product design support. Several studies emphasized that developing a set of measurements for exploring the key drivers of SCA is an urgent task (Venkatraman, 1989; Agarwal et al., 2007).

Business affairs between organizations have been present since the origin of commerce. According to Hadjikhani and LaPlaca (2013), the study of Business-to-Business (B2B) marketing can be traced back to the 1890s, but key contributions have been developed only during the last three decades, mainly in specialized journals such as Industrial Marketing Management (IMM), Journal of Business and Industrial Marketing (JBiM) and Journal of Business-to-Business Marketing (JBBM). However, its representation in scientific marketing research is weak (LaPlaca & Katrichis, 2009). What causes this underrepresentation? Not its economic power. B2B transactions accounted for 42% of reported US revenues in 2010 (Lilien, 2016), conforming to the last published US Department of Commerce statistics (2010). Globally, the balance between B2C and B2B seems to hold. This relative economic relevance hasn’t reached equivalent academic attention (Reid & Plank, 2000), and it is far away from equilibrium. The presence of B2B in the top four marketing journals is scarce. For instance, in the last decade only a few B2B articles have been published in the Journal of Marketing, Journal of Marketing Research and Marketing Science, and none in the Journal of Consumer Research due to its focus on Business-to-Consumer (B2C) issues (LaPlaca & Katrichis, 2009). The analysis of 24 marketing journals from 1936 to 2006 showed that, of 17,853 articles published, only 1204 deal with B2B marketing, accounting for 6.7% of the total (LaPlaca & Katrichis, 2009). Several authors advocate for an independent understanding of B2B and B2C marketing (e.g., Hutt & Speh, 2012). The basic distinction between B2B and B2C is the origin of the demand. Whether the demand is derived from subsequent customers or is driven by the choices, emotions and likes of the customer, we are in B2B or B2C contexts, respectively (Lilien, 2016). Another well-established difference concentrates on buyer-seller relationships, which are more predominant in a B2B context than B2C (Hâkansson & Snehota, 1995). In addition, the buying decision process has been characterized as unique in B2B marketing, including the presence of a buying center or decision making unit (Johnston & Bonoma, 1981). Other researchers claim that the divergence in business and consumer marketing isn’t significant and doesn’t deserve specific attention when developing marketing concepts (e.g., Coviello & Brodie, 2001). This stream’s apparent oxymoron promotes the need for evidence regarding the future of B2B marketing theory. We strive to identify the key topics that will drive business marketing. We strongly believe that a deeper comprehension of the B2B marketing theory pillars will contribute to clarifying the essence of business marketing and its uniqueness. More important, our results will help to close the gap between practice and academic research. In order to develop our study, we assert that the underlying philosophical position adopted is constructivism. This epistemological assumption contends that reality is a social construction based on human interpretative view or sense making. More interestingly, our research method is founded on the Delphi approach which requires the selection of “experts in the field,” meaning we openly trust in their experienced vision and interpretation of context, but the findings emerge from the whole. Scholars have failed in the dissemination of knowledge beyond the academic community, probably due to the lack of incentives. The goals of researchers and practitioners are partially distinct in conception (Gummesson, 2014) and diverge towards accomplishment. On the one hand, academics are measured by the amount and quality of publications in scientific and peer-reviewed journals. The total number of citations from the published articles and the relative impact factors of the journals influence the researcher’s career success. On the other hand, business executives are expected to increase revenue and profit of companies, ostensibly through time. Therefore, the impact of both roles is completely different (Gummesson, 2014). We affirm that B2B marketing will become more relevant for business theory if practice and academia are brought together. Specifically, the genesis of B2B marketing theory needs to be rooted in real practitioner problems while applying the rigor of academic research.

مقاله سال 2016

هدف – در سناریوی تجاری به شدت رقابتی امروز، تبلیغات، تبلیغات، حاکی از یکی از فعالیت‌های کلیدی بازاریابی است. هدف این مقاله، شناخت رابطه‌ی بین کارایی تبلیغات و رفتار خرید مصرف کننده برای شرکت‌های مهم خودرو در هند مرکزی است.

طرح/متدلوژی/رویکرد – یک ترکیب عاقلانه‌ی روش‌های تحقیق کیفی (گروه تمرکز و تکنیک دلفی) و کمّی (مرور پرسشنامه‌ی ساختار یافته) برای مطالعه‌ی حاضر استفاده شد.

یافته‌ها – مطالعه نشان داد که برای بخش خودرو، تبلیغات موثر دارای تاثیر مثبتی روی رفتار خرید مصرف کننده است. آن نشان می‌دهد که نگرش مشتری می‌تواند به طور مطلوبی از طریق تبلیغات موثر شکل گیرد. شرکت‌های خودرو باید نشست‌های آموزشی ویژه و برنامه‌های یادگیری را برای نیروی فروش خود به منظور حصول اطمینان از رفتار خرید پشتیبانی کننده‌ی مشتری تنظیم کنند.

محدودیت‌ها/پیامدهای ضمنی تحقیق – حیطه‌ی مطالعه‌ی حاضر محدود به شرکت‌های اصلی خودرو تنها در هند مرکزی است. اگرچه یافته‌ها را می‌توان در یک سناریوی تجاری جهانی تفسیر کرد و تعمیم داد.

اصلیت/ارزش – این کار تحقیقاتی اولین نوع خود است که اقدام به مطالعه‌ی تاثیر تبلیغات موثر روی رفتار خرید مصرف کننده در زمینه‌ی خودروی هندی می‌کند. یافته‌ها و توصیه‌ها را می‌توان برای برنامه‌ریزی استراتژیک جلسات آموزشی و کارگاه‌ها برای سهامداران مختلف در صنعت خودرو استفاده کرد.

مقاله سال 2016

the Delphi technique The source of the expression, ‘‘It’s difficult to make predictions, especially about the future,’’ is uncertain. This saying has been attributed variously to Niels Bohr, Samuel Goldwyn, Yogi Berra, and Mark Twain. Its uncertainty notwithstanding, the maxim is undoubtedly true. Forecasting or predicting what will happen in the future is one of the most difficult tasks humans attempt to accomplish. Yet forecasting is an integral part of a manager’s role and executives are called upon constantly to make decisions and take positions now that will only come to fruition at some time in the future. Will markets develop and grow or wilt and decline? Will a new product succeed or fail? What effects will an advertising campaign have on customer perceptions? What will the best name for a new product be? Will an investment now pay off in 5 or 10 years? What are the most important issues that an organization should focus on and how should these be prioritized?

Some forecasting methods extrapolate data from the past to predict what that same data will be like in the future. Time series analysis relies on various statistical techniques ranging from moving averages and simple linear regression to more sophisticated tools, such as the Box-Jenkins method (Box & Jenkins, 1970). Users of these methods presume that data patterns of the past will extend beyond the present. Whether they will remain stationary, fluctuate, increase, decline, or maintain can be determined by mathematical manipulation. When hard data is unavailable or when environmental conditions are very dynamic, forecasting resorts to opinions and judgments. Traditionally, experts have been sought after for these opinions. After all, who better to foretell the future within a particular domain than those who have truly experienced its past and live in its present? One of the best known and most widely used tools for polling the opinions of experts is the Delphi technique. However, more recently it has been contended that, in some contexts, a very large group of lay people without recognised expertise are collectively as adept as many experts at coming up with insightful answers. This approach, variously known as the wisdom of crowds (Surowiecki, 2005) or crowdsourcing (Howe, 2006), has recently gained prominence because large crowds of individuals can be easily accessed through technology. Within the broad concept of crowdsourcing, the subcategories of prediction markets (Graefe, Luckner, & Weinhardt, 2010; Wolfers & Zitzewitz, 2004) and innovation contests (Boudreau & Lakhani, 2013) provide familiar tools that countless organizations have used profitably. A simple request on a website to provide suggestions or answers, often fueled by tweets or reminders on a Facebook page, can rapidly lead to hundreds or even thousands of responses.

In this article, I describe and compare the Delphi technique and crowdsourcing activities, noting where they are similar and where they differ. I also discuss instances and opportunities where they might be used as forecasting tools and provide a decision tool for managers to aid their choice between these two useful techniques.