Abstract This study examines whether the Framework to Assess Challenges in Virtual Education (FACVE), C1 dimension (challenges to virtual education quality), covering teaching quality, interaction, and assessment challenges, is associated with students’ perceived learning outcomes and satisfaction. Self-reported survey data were collected from graduate business students at one of Peru’s top universities between September 17, 2021, and February 6, 2022, following an initial emergency transition and during a stable term in which courses were delivered through institutionally standardized online modalities. Using PLS-SEM, FACVE-C1 was modeled as a higher-order construct, and its relationships with students’ perceived learning outcomes (LO) and student satisfaction (SS) were estimated. Virtual instruction quality challenges were negatively related to perceived learning (β = −0.470; R² = 0.221) and to student satisfaction (β = −0.116), while perceived learning was strongly related to student satisfaction (β = 0.821; R² = 0.777). Among the FACVE-C1 components, interaction challenges contributed most strongly, indicating that strengthening student–instructor and student–student interaction structures is a high-leverage target in online graduate business education. The findings provide empirical support for FACVE-C1 as a parsimonious diagnostic lens for identifying quality-related constraints that shape students’ experience and perceived learning in planned virtual instruction contexts.

This research presents an exploratory study on the use of Generative AI in structuring problems in a decision-making class. Employing a survey approach, 71 students reported on the experience of using Generative AI for decision-making structuring, in addition to widely used methods (e.g., literature reviews, interviews). The student experience was evaluated using sentiment analysis. The findings reveal that the proper use of Generative AI for problem structuring (e.g., before or after widely used methods) still needs to be determined. Also, while most students expressed a positive attitude toward the use of Generative AI, the sentiment analysis needs to be conducted with caution, given that commonly used approaches still fail to grasp both the subtleties and context of human responses.

Using an integration-monitoring theoretical framework, which assesses the alignment of internal and external perspectives along with performance evaluation, this research demonstrates how suitable political, regulatory, and societal contexts, effective stakeholder engagement, and an active role for middle managers (even in the absence of a clear mandate) are essential for embedding sustainable goals in the development and public transfer of sustainable technologies and innovation. The proposed integration-monitoring framework is applied to the case of university Technology Transfer Offices (TTOs) to explore how they can strengthen sustainability-oriented innovation systems. Additionally, it examines the role of TTOs in promoting economic development and commercializing new technologies and innovations while integrating socio-environmental sustainability dimensions. Two university TTOs, one in the USA and one in Spain, were studied using a two-level analysis. This analysis reflects on the understanding and integration of social and environmental sustainability in their activities and evaluates a framework for monitoring their sustainability-oriented efforts. Importantly, this study highlights a fundamental lack of assessment and performance evaluation indicators in the development of sustainable technologies, even in the case of institutions that have fully embraced sustainable innovation goals. The proposed framework and findings from this research can extend beyond the TTO context, providing insights applicable to other organizations tasked with the development and public diffusion of sustainable innovative technologies.

This study investigates how university-based Entrepreneurship Centers (ECs) integrate sustainability values within various political and regulatory contexts. More specifically, examines the role of these centers in promoting economic development while incorporating socio-environmental sustainability dimensions. Employing an inductive approach, the study focuses on two universities in the United States and Spain, utilizing a two-level analysis to understand and integrate social and environmental sustainability into their activities. Both cases revealed organizational dynamics that facilitated an examination of current practices and identified what is necessary for further integration of socio-environmental sustainability. Despite a clear alignment with some sustainability values, the study found that achieving a fully integrated approach in ECs faces important challenges, such as developing measures to monitor socio-environmental actions. Results identify a surprising lack of sustainability-related assessment items and highlights the importance of middle-level managers, institutional support, stakeholder relationships, and the political and regulatory context as key enablers for advancing sustainable development in innovation.

Consistency indices quantify the degree of transitivity and proportionality violations in a pairwise comparison matrix (PCM), forming a cornerstone of the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP). Several methods have been proposed to compute consistency, including those based on the maximum eigenvalue, dot product, Jaccard index, and the Bose index. However, these methods often overlook two critical aspects: (i) vector projection or directional alignment, and (ii) the weight or importance of individual elements within a pointwise evaluative structure. The first limitation is particularly impactful. Adjustments made during the consistency improvement process affect the final priority vector disproportionately when heavily weighted elements are involved. Although consistency may improve numerically through such adjustments, the resulting priority vector can deviate significantly, especially when the true vector is known. This indicates that approaches neglecting projection and weighting considerations may yield internally consistent yet externally incompatible vectors, thereby compromising the validity of the analysis. This study builds on the idea that consistency and compatibility are intrinsically related; they are two sides of the same coin and should be considered complementary. To address these limitations, it introduces a novel metric, the Consistency Index G (CI-G) based on the compatibility index G. This measure evaluates how well the columns of a PCM align with its principal eigenvector, using CI-G as a diagnostic component. The proposed approach not only refines consistency measurement but also enhances the accuracy and reliability of derived priorities.

This study delves into the flow and structure of knowledge prevalent in Analytic Network Process (ANP) literature. It traces the evolutionary pathway of ANP research, spotlighting seminal works and unfolding the development of topics over time. Analysing 4583 ANP literature records from 1986 to 2022, this research utilizes two pivotal data sources: Web of Science (WoS) and Dimensions. This main path analysis (MPA) approach is coupled with techniques such as citation analysis, social network analysis, and centrality measures to identify most influential papers, as well as using a search path algorithm (SPC) to provide higher weights to papers that serve as bridges connecting different research paths rather than simply counting all citations equally. Key works emerged as focal points in both datasets, including notable contributions from Lee, Kheybari and B & uuml;y & uuml;k & ouml;zkan, with the Dimensions dataset uniquely highlighting Saaty as the initial conceptual knowledge source of the ANP. The centrality measures unearthed persistent bridge roles undertaken by key contributors such as Saaty and Sarkis over different time periods. Furthermore, a detailed topic analysis discerned eight distinctive thematic clusters among the two data sources: analytical network process, network process, fuzzy analytic, evaluation laboratory, supply chain, quality function, hierarchy process, and information systems. These clusters emerged, providing a comprehensive map of ANP topics and their evolution. The study offers a comprehensive framework for scholars to navigate the expansive domain of ANP research. Identifying pivotal works and emergent themes provides direction for future research endeavours. It allows practitioners to gain invaluable insights into the foundational and transformative works in the ANP realm, enhancing their understanding and application of the methodology. This paper proposes of a dual methodological strategy: First, by using traditional academic data sources (WoS) along with a more encompassing Dimensions database; and second, by using a SPC algorithm to weight MPA papers based on their connecting role among different research paths. At the discipline level, this study carves out a novel vantage point in understanding the ANP research landscape. It offers an integrated portrayal of the field's conceptual evolution, identifying specific cluster topics as an indispensable resource for scholars, practitioners, and students.

While the importance of explicitly identifying and considering contingent factors such as decision content and context is widely accepted as a way to ensure the validity of the decision analysis for the specific task at hand, few studies include this. This research uses a contingency theoretical approach to study factors affecting the emigration decision of medical doctors (MDs) for the specific case of Turkey. The motivation for conducting this study arises from the observation that the growing trend in emigration among MDs from Turkey is having a significant impact on the country’s healthcare system. Dealing with the emigration of MDs is crucial for ensuring an effective and sustainable healthcare system, especially in terms of the availability of services, satisfaction, and employment of the healthcare staff. Contextual factors were explicitly identified through consultation with experts, while the generic factors were retrieved from the specialized medical migration literature. The Analytic Hierarchy Process method was utilized to prioritize the factors. Seventy-three participants were surveyed about their intention to either study or work abroad. The findings reveal that low remuneration and anxiety about their future due to the political situation in the country constitute the two most important factors driving the decision to emigrate.

This study explores the recent use of the Analytic Network Process (ANP) in the decision process in the areas of economics, finance and management to identify common contingency factors, current trends, representative studies and directions for further research applications in the target areas. A systematic literature review of 434 ANP studies for a 10-year period (2012-2021) within the Scopus database was conducted using the keyword "Analytic Network Process" in articles indexed in the following two categories: (1) Business, Management and Accounting, and (2) Economics, Econometrics and Finance. Further analysis using a citation-based graph and contingency analysis approaches was performed to identify usage trends. Our findings indicate that the most common ANP applications are with sustainable supply chain management and business evaluation frameworks. There is also a trend of applications engaging stakeholders in the decision-making process. Finally, it was found that the ANP is most commonly used as part of a multicriteria multi-method (a method followed by others) or integrated decision-making (hybridization of methods) approach rather than alone. The most common use (>80%) of the ANP is as part of a multi-method or integrated method with other tools such as DEMATEL, which suggests these approaches, in particular integrated ones (>50%), are becoming the preferred method of analysis to simplify the ANP process. From a practical point of view, it was found that the ANP is particularly utilized in sustainable projects to facilitate the participation of various stakeholders. This is the first focused review of the use of the ANP in the areas of economics, finance and management with an emphasis on its application as well as its contingent factors. Also, representative studies have been highlighted in each area. Traditional reviews have not delved deeply into the areas and contingent factors that this study explores.

A composite indicator (CI) is the mathematical aggregation of sub-dimension (local) indicators used to provide an overall score for the multidimensional concept being measured. CIs are widely used to assess the benefits or risks in human endeavors, such as by creating life satisfaction indices or disaster risk indicators. One important aspect of the development of CIs is setting up value thresholds for taking action, such as in determining the minimum acceptable level of life satisfaction in a community or the maximum acceptable flood risk value beyond which people should be ordered to evacuate from the area in danger. The analytic hierarchy/network process (AHNP) is widely used for the development of CIs. In a review of 111 AHP/ANP CI studies, fewer than 10% discussed any threshold. This means that about 90% of the developed CIs were theoretically sound but lacked the actionable thresholds necessary to be of practical use. Furthermore, for the few studies that set thresholds, the values were typically set arbitrarily or using inadequate statistical approaches. To address this important concern, this study first discusses the most commonly used approaches to setting up thresholds, as well as their inadequacies, and proposes the development of AHP/ANP CI thresholds using a mathematical approach based on the rate of change and center of gravity (RCCG) concepts. Using this approach, a virtual reference alternative, i.e., a threshold profile (TP) made up of the local thresholds of each indicator, is calculated. The key advantage of the proposed method is that it not only provides a non-arbitrary way to set up a CI threshold; more importantly, it is independent of the data and/or alternatives to be evaluated; that is, a threshold calculated with the proposed approach constitutes an absolute reference value, outside the dataset.

In this study, the validity and use of a recently developed evaluation Framework to Assess Challenges To Virtual Education (FACVE) were tested and refined using a comparative perspective between students from Peru and Spain. The findings provide a limited endorsement for the validity of the assessment framework while also highlighting interesting similarities and differences between the students from both countries in terms of the challenges faced in the context of virtual education. This study demonstrates that the FACVE is a valid assessment instrument and can be used in any country or institutional context by selecting the relevant dimensions and sub-dimensions of interest.

In their excellent recounting of the development of multiple criteria decision making (MCDM) from its early history to the 21st century, Koksalan et al. (2011) proposed that MCDM is both old and new. It is old because decision makers have always had to make tradeoffs with objectives when making decisions; the authors refer to Benjamin Franklin’s approach to making decisions by trading off benefits and costs during the 1700’s. However, MCDM as an important sub-field of Management Science or Operations research is rather new and began in the late 1950s. The elements of decision making fundamentally consist of the “decision”, a “decision-maker” and a “decision analysis methodology.” This is the reason that the MCDM field is inherently interdisciplinary.

ISAHP 2022 was an excellent meeting! We secured quite a few special issues for conference participants. Yet, these reflections are confined to the Journal of Enterprise Information Management (JEIM) and the Journal of Multiple Criteria Decision Analysis (JMCDA). JEIM will be guest edited by Birsen Karpak, Emel Aktas and Ilker Topcu; we are pleased with this international cooperation among the USA, the UK, and Turkey. The guest editors for JMCDA will be Birsen Karpak and Enrique Mu. Even though we are reflecting upon submissions for the two journals (JEIM and JMCDA), quite a few of the following suggestions are useful for any special issue of IJAHP.

There are two upcoming conferences with either tracks or sessions where you can submit decision-making papers. These upcoming conferences are: The 33rd Central European Conference on Information and Intelligent Systems CECIIS 2022 that will take place from September 21st to 23rd in Dubrovnik, Croatia. The 21st international conference on Economy, Finance and Management, in its first Polish-Peruvian edition and entitled “New challenges in economic policy, business, and management,” will take place on October 23- 25 in Wieliczka, Poland.

The journal has made several important changes this year. First, we moved to a rolling article publication mode; that is, articles are published as soon as they are fully reviewed, accepted and copyedited. This allows quicker diffusion of the studies and authors’ work. Our second innovation has been removing the need to register as a reader to access the journal contents. The original rationale for this was to assess the number of readers of the journal; however, it is now possible to obtain this information with many other tools. Even though registration was free, it was still one more step to access the article and many people preferred to just skip registration and move to any other article in their Google search.

IJAHP has adopted a rolling article publication format as well as removed the registration requirement for our readers...

Addressing the contingent dimensions (content and context) in multi-criteria decision-making is very important to ensure the validity of a study. While this approach is widely accepted in the strategic decision-making community, it is argued here that this practice is not properly addressed and/or reported in many cases and that it must be applied in all MCDM decisions to ensure the rigor and relevance of the outcome. To explore the extent to which contingent factors are addressed in the literature, a sample of 46 MCDM group decision-making papers from a single year of publication was examined with regard to a well-known contingent dimension: group decision-making. More specifically, the following four critical variables were examined: group membership, group process, aggregation of perspectives, and group engagement. The study found that the percentage of papers that addressed these variables in a reasonable way was 23.9%, 17.4%, 26.1%, and 19.6%, respectively. These results suggest that MCDM analysts are not, for the most part, properly addressing (or reporting) group decision-making and similar contingent dimensions. For this reason, this research is a call to authors and journal editors to include and properly address all MCDM applicable contingent dimensions to improve MCDM rigor and relevance; that is, the overall validity of MCDM studies.

How long does it take to learn and use AHP for managerial decision making? Based on a recent experience, it can take a surprisingly short time! Students from the University of Pittsburgh competed in the first TL Saaty Decision Making for Leaders Hackathon March 18 to 20, 2022.

The COVID-19 pandemic forced most countries' higher-education systems to shift to distance learning, which has been called either "Corona Teaching" or, more formally, "Emergency Remote Teaching (ERT)." Students were suddenly faced with a new class format delivery and the many challenges of virtual education. The present study aims to identify and measure the challenges in three stages: (1) a qualitative method approach was used to gather the opinions of 50 students that were then analyzed and coded to identify their perceived major challenges; (2) a survey was completed by 165 students to prioritize the relative importance of the previously identified challenges using the AHP as the weighting approach; (3) an assessment framework was developed, using statistical techniques to measure the extent of the challenges for specific stakeholders based on survey responses. The main challenges students face are inadequate physical facilities at home, difficulties with the learning platforms, and financial concerns. These results are applicable beyond the present research context. For the first time, an ERT assessment framework of the challenges was developed using composite indicators derived from students' opinions and perspectives. This ERT framework allows for the exploration of a community of students' vulnerability to the challenges within the context of an emergency remote environment.