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There has been an increasing amount of research on personnel selection in many business disciplines (Hough & Oswald, 2000; Breaugh & Starke, 2000). Research on internal auditor…
Abstract
There has been an increasing amount of research on personnel selection in many business disciplines (Hough & Oswald, 2000; Breaugh & Starke, 2000). Research on internal auditor selection, however, has had limited exposure in the auditing literature (Bailey, Gramling, & Ramamoorti, 2003). Recently, Seol and Sarkis (2005) introduced an analytic hierarchy process (AHP) model that used a decision hierarchy based on the CFIA (competency framework for internal auditing) framework. A limitation of AHP, however, is the assumption of strict hierarchical relationship that needs to exist among factors.
The purpose of this paper is an introduction of a more robust model, the analytical network process (ANP), which relaxes the strict hierarchical and decomposition levels of the hierarchy and incorporates possible interrelationships and interdependencies of various personnel selection criteria, factors, and alternatives. In illustrating the application, we return to the CFIA model framework, describe how and where interdependencies exist amongst the CFIA factors/attributes, and how ANP is used in the internal auditor selection process. The illustration will also describe some sensitivity analysis for the ANP approach. The tool is not without its limitations that include the potential for geometrically more questions and information elicitation from the decision makers. Finally managerial and research implications associated with the technique and results are described.
Ida Marie Tvedt and Kine Agnethe Dyb
This paper aims to highlight the need to place focus on ensuring soft factors in construction projects’ design management and to discuss whether soft factors are hidden success…
Abstract
Purpose
This paper aims to highlight the need to place focus on ensuring soft factors in construction projects’ design management and to discuss whether soft factors are hidden success factors.
Design/Methodology/Approach
The presented data is a result of findings from two master theses. The approach is qualitative research and consists of nine semi-structured interviews with design managers and two case studies involving document analyses, meeting observations and descriptions of seven interviews.
Findings
This empirical study demonstrates that soft factors are considered important for design managers’ achievement of a successful design process. Focus on soft factors promotes good communication and will improve team performances. Factors are hidden because they are invisible and immeasurable. Furthermore, soft factors are not defined as assigned tasks and are, therefore, easily neglected. Designers are hesitant to explore the possibilities of new technology owing to the fear that they will forfeit human interaction.
Research Limitations/Implications
This paper is limited to the presentation of empirical findings. Therefore, theory is not a basis for the study but rather a framework for the discussion.
Practical Implications
The results in this paper broaden the understanding of human behaviour during the design phase. This knowledge should be considered when the project’s delivery model is designed as it will safeguard actor concerns during the ongoing technological transformation.
Originality/Value
This paper contributes knowledge of the view regarding soft factors among project actors. It expands the traditional understanding of value by adding soft factors to the traditional success measures of time, quality and cost.
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This study aimed to identify and analyse the key factors influencing the adoption of e-government services and to discern their implications for various stakeholders, from…
Abstract
Purpose
This study aimed to identify and analyse the key factors influencing the adoption of e-government services and to discern their implications for various stakeholders, from policymakers to platform developers.
Design/methodology/approach
Through a comprehensive review of existing literature and detailed analysis of multiple studies, this research organised the influential factors based on their effect: highest, direct and indirect. The study also integrated findings to present a consolidated view of e-government adoption drivers.
Findings
The research found that users' behaviour, attitude, optimism bias and subjective norms significantly shape their approach to e-government platforms. Trust in e-Government (TEG) emerged as a critical determinant, with security perceptions being of paramount importance. Additionally, non-technical factors, such as cultural, religious and social influences, play a substantial role in e-government adoption decisions. The study also highlighted the importance of performance expectancy, effect expectancy and other determinants influencing e-government adoption.
Originality/value
While numerous studies have explored e-government adoption, this research offers a novel classification based on the relative effects of each determinant. Integrating findings from diverse studies and emphasising non-technical factors introduce an interdisciplinary approach, bridging the gap between information technology and fields like sociology, anthropology and behavioural sciences. This integrative lens provides a fresh perspective on the topic, encouraging more holistic strategies for enhancing e-government adoption globally.
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The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.
Abstract
Purpose
The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.
Design/methodology/approach
A multi-criteria decision-making best-worst method (BWM) is employed to quantitatively identify the most critical risk factors. The grey causal modeling (GCM) technique is employed to identify the causal and consequence factors and to effectively quantify them. The data used in this study consisted of two types – quantitative periodical data of critical factors taken from their respective government departments (e.g. Indian Meteorological Department, The Central Water Commission etc.) and the expert responses collected from professionals working in the Indian electric power sector.
Findings
The results of analysis for a case application in the Indian context shows that temperature dominates as the critical risk factor for electrical power grids, followed by humidity and crop production.
Research limitations/implications
The study helps to understand the contribution of factors in electricity grids operational disruptions. Considering the cause consequences from the GCM causal analysis, rainfall, temperature and dam water levels are identified as the causal factors, while the crop production, stock prices, commodity prices are classified as the consequence factors. In practice, these causal factors can be controlled to reduce the overall effects.
Practical implications
From the results of the analysis, managers can use these outputs and compare the risk factors in electrical power grids for prioritization and subsequent considerations. It can assist the managers in efficient allocation of funds and manpower for building safeguards and creating risk management protocols based on the severity of the critical factor.
Originality/value
The research comprehensively analyses the risk factors of electrical power grids in India. Moreover, the study apprehends the cause-consequence pair of factors, which are having the maximum effect. Previous studies have been focused on identification of risk factors and preliminary analysis of their criticality using autoregression. This research paper takes it forward by using decision-making methods and causal analysis of the risk factors with blend of quantitative and expert response based data analysis to focus on the determination of the criticality of the risk factors for the Indian electric power grid.
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Maziar Moradi-Lakeh, Salime Goharinezhad, Ali Amirkafi, Seyed Mohsen Zahraei, Arash Tehrani-Banihashemi and Abdolreza Esteghamati
Despite significant progress in Iran's immunization programs, vaccine policymaking in the country still faces various challenges and shortcomings. To address these issues and…
Abstract
Purpose
Despite significant progress in Iran's immunization programs, vaccine policymaking in the country still faces various challenges and shortcomings. To address these issues and ensure sustained progress toward achieving comprehensive vaccination policies, it is essential to identify the critical factors influencing vaccine policies in Iran. Our study aims to provide evidence-based insights that can inform the development of effective and equitable vaccine strategies, leading to a more sustainable and efficient approach to vaccination in the country.
Design/methodology/approach
This mixed-method study aimed to analyze the factors influencing the future of human vaccine policy using Cross Impact Analysis. Firstly, a scoping review was conducted to identify the factors affecting the future of human vaccine development. Secondly, a semi-structured interview was conducted with experts in this field to add more factors and confirm the identified factors within the Iranian context. Finally, a Cross-Impact Analysis (CIA) approach was applied to comprehend the complex relationships between the identified factors. Thematic analysis was used for the qualitative data, and MICMAC analysis was applied to characterize the relationships between the factors.
Findings
Seventeen key driving force factors were identified through comprehensive review and interviews. These factors were assigned weighted values ranging from zero to three and subsequently analyzed using MICMAC software. Employing the Cross-Impact Analysis (CIA) technique, the study characterized the impact of each factor on vaccine policy and elucidated the intricate interactions between them. The findings underscored that robust leadership and governance, an innovative ecosystem, and well-established immunization information systems emerged as pivotal driving forces shaping vaccine policy in Iran.
Research limitations/implications
While this study contributes valuable insights into the driving factors influencing vaccine policy in Iran, it is important to acknowledge several limitations. The results rely on the subjective perceptions of a diverse group of specialists, and future research could delve into additional factors in other countries to identify common themes and differences.
Practical implications
This study provides evidence to assist policymakers in making informed decisions regarding vaccines in Iran. The findings suggest that enhancing access to vaccines, fostering trust in the healthcare system, and prioritizing equity in distribution can contribute to increased vaccination rates and a reduction in vaccine-preventable diseases.
Originality/value
This study provides a unique contribution to the field of vaccine policy by utilizing the cross-impact analysis to examine the complex interactions among various factors. The results of this analysis demonstrate that these interactions can significantly impact the overall system, highlighting the need for policymakers to consider multiple factors when formulating effective strategies. By revealing the significance of these interactions, this research offers valuable insights into the development of successful policies that can shape a desirable future for vaccine policy in Iran. Future studies could ratify the findings from this research by applying other methodological approaches.
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Shamsuddin Ahmed and Rayan Hamza Alsisi
A new triage method, MBCE (Medical Bio Social Ethics), is presented with social justice, bio, and medical ethics for critical resource distribution during a pandemic. Ethical…
Abstract
Purpose
A new triage method, MBCE (Medical Bio Social Ethics), is presented with social justice, bio, and medical ethics for critical resource distribution during a pandemic. Ethical triage is a complex and challenging process that requires careful consideration of medical, social, cultural, and ethical factors to guide the decision-making process and ensure fair and transparent allocation of resources. When assigning priorities to patients, a clinician would evaluate each patient’s medical condition, age, comorbidities, and prognosis, as well as their cultural and social background and ethical factors.
Design/methodology/approach
A statistical analysis shows no interactions among the ethical triage factors. It implies the ethical components have no moderation effect; hence, each is independent. The result also points out that medical and bioethics may have an affinity for interactions. In such cases, there seem to be some ethical factors related to bio and medical ethics that are correlated. Therefore, the triage team should be careful in evaluating patient cases. The algorithm is explained with case histories of the selected patient. A group of triage nurses and general medical practitioners assists with the triage.
Findings
The MBCE triage algorithm aims to allocate scarce resources fairly and equitably. Another ethical principle in this triage algorithm is the principle of utility. In a pandemic, the principle of utility may require prioritizing patients with a higher likelihood of survival or requiring less medical care. The research presents a sensitivity analysis of a patient’s triage score to show the algorithm’s robustness. A weighted score of ethical factors combined with an assessment of triage factors combines multiple objectives to assign a fair triage score. These distinctive features of the algorithm are reasonably easy to implement and a new direction for the unbiased triage principle.
Originality/value
The idea is to make decisions about distributing and using scarce medical resources. Triage algorithms raise ethical issues, such as discrimination and justice, guiding medical ethics in treating patients with terminal diseases or comorbidity. One of the main ethical principles in triage algorithms is the principle of distributive justice.
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Ansita Aggarwal and Nisarg Joshi
This article presents a comprehensive analysis of innovation in micro, small and medium enterprises (MSMEs) in India, focusing on the barriers and facilitators within their…
Abstract
Purpose
This article presents a comprehensive analysis of innovation in micro, small and medium enterprises (MSMEs) in India, focusing on the barriers and facilitators within their internal and external ecosystems.
Design/methodology/approach
A self-administered questionnaire was used to collect data from 1430 MSMEs across India, employing Structural Equation Modeling (SEM) to analyze the relationships between internal and external factors and innovation adaptation.
Findings
The findings indicate that factors such as top management and organization structure, communication, technological capability and adaptation and organizational culture have a positive impact on innovation adaptation within the internal environment. Conversely, employee and market orientation, as well as financial factors, have a negative influence. Regarding the external environment, industry and competitive analysis, internationalization and partner alliances were found to positively affect innovation adaptation, whereas the country's infrastructure and policies had a negative impact.
Originality/value
The study emphasizes that MSMEs have the potential to leverage their internal and external environments to foster innovation within their organizations.
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Mohammadreza Tavakoli Baghdadabad
We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.
Abstract
Purpose
We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.
Design/methodology/approach
We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.
Findings
We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.
Originality/value
We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.
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Andrew Miller and Adam Vanhove
Drawing on organismic integration theory, we aim to examine whether the reasons independent contractors choose contract work are related to their on-the-job motivation and job…
Abstract
Purpose
Drawing on organismic integration theory, we aim to examine whether the reasons independent contractors choose contract work are related to their on-the-job motivation and job satisfaction and whether their perceived support enhances positive (or buffers negative) effects.
Design/methodology/approach
We collected data at three separate time points from 241 adjunct instructors to test a moderated mediation model using bootstrapping analyses.
Findings
The positive relationship between pull factors (e.g. autonomy) and job satisfaction is fully mediated by the autonomous motivation contractors experienced at work. The inverse relationship between push factors (e.g. inability to secure desired work role) and job satisfaction is not mediated by autonomous nor controlled motivation experienced at work. Contractors' perceived organizational support does not moderate the relationship between either push or pull factors and autonomous motivation. Post hoc analysis shows a moderating effect of perceived supervisor support on the nonlinear relationship between push factors and autonomous motivation.
Practical implications
Recruiting individuals drawn to the benefits of contract work may have important implications for worker motivation, job satisfaction and potentially beyond. Moreover, organizations may consider whether existing support resources and infrastructure are appropriate for contractors.
Originality/value
Despite the abundance of evidence demonstrating the benefits of organizational and supervisor support among traditional employee populations, such support may be of limited value to those drawn to contract work.
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