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This study examines public budgeting experts' perception on the viability and adoptability of the proposed line-item veto. The study reveals that: (1) the line-item veto is not considered by the experts as the most favored budgetary reform idea from both measurements of viability and adoptability; (2) the experts believe that the line-item veto may not be adopted in the near future even though they agree it is a viable idea; and (3) there are no significant correlations between the experts' views and their personal characteristics.

This paper aims to “identify,” “analyse” and “categorise” the readiness factors of lean sustainability in health-care organisation using total interpretive structural modelling (TISM).

To obtain the data, a closed-ended questionnaire was used in addition to a scheduled interview. To identify how the factors interact, the TISM approach was used, and the matriced’ impacts croise’s multiplication applique’e a UN classement (MICMAC) analysis was used to rank and categorise the lean sustainability readiness factors.

This study identified ten lean sustainability readiness factors for health-care organisation. The identified factors are resources utilization practice (F1), management commitment and leadership (F2), operational flexibility (F3), workforce engagement and time commitment (F4), sustainability motivational factors (F5), awareness of lean and sustainable practice (F6), hospital design (F7), energy efficiency practices in hospitals (F8), responsible autonomy (F9) and new system adoptability training (F10). The key/driving factors are identified in this study are operational flexibility, sustainability motivational factors, management commitment and leadership, new system adoptability training.

The study focussed primarily on lean sustainability factors for the health-care sector.

This research will aid key stakeholders and academics in the better understanding the readiness factors that influence lean sustainability in health-care organisation. This study emphasises the factors that must be considered when applying lean sustainable practices in health care as a real-world application in a health-care organisation. These readiness factors for lean sustainability can be used by an organization to comprehend more about the concept and the components that contribute to health-care lean sustainability.

This study proposes the TISM technique for health care, which is a novel attempt in the subject of lean sustainability in this sector.

The purpose of this study was to demonstrate a cloud business intelligence model for industrial SMEs. An initial model was developed to accomplish this, followed by validation and finalization of the cloud business intelligence model. Additionally, this research employs a mixed-techniques approach, including both qualitative and quantitative methods. This paper aims to achieve the following objectives: (1) Recognize the Cloud business intelligence concepts. (2) Identify the role of cloud BI in SMEs. (3) Identify the factors that affect the design and presenting a Cloud business intelligence model based on critical factors affecting SMEs during pandemic COVID-19. (4) Discuss the importance of Cloud BI in pandemic COVID-19 for SMEs. (5) Provide managerial implications for using Cloud BI effectively in Iran’s SMEs.

In the current study, an initial model was first proposed, and the cloud business intelligence model was then validated and finalized. Moreover, this study uses a mixed-methods design in which both qualitative and quantitative methods are used. The fuzzy Delphi Method has been applied for parameter validation purposes, and eventually, the Cloud business intelligence model has been presented through exploiting the interpretive structural modeling. The partial least squares method was also applied to validate the model. Data were also analyzed using the MAXQDA and Smart PLS software package.

In this research, from the elimination of synonym and frequently repeated factors and classification of final factors, six main factors, 24 subfactors and 24 identifiers were discovered from the texts of the relevant papers and interviews conducted with 19 experts in the area of BI and Cloud computing. The main factors of our research include drivers, enablers, competencies, critical success factors, SME characteristics and adoption. The subfactors of included competitors pressure, decision-making time, data access, data analysis and calculations, budget, clear view, clear missions, BI tools, data infrastructure, information merging, business key sector, data owner, business process, data resource, data quality, IT skill, organizational preparedness, innovation orientation, SME characteristics, SME activity, SME structure, BI maturity, standardization, agility, balances between BI systems and business strategies. Then, the quantitative part continued with the fuzzy Delphi technique in which two factors, decision-making time and agility, were deleted in the first round, and the second round was conducted for the rest of the factors. In that step, 24 factors were assessed based on the opinions of 19 experts. In the second round, none of the factors were removed, and thus the Delphi analysis was concluded. Next, data analysis was carried out by building the structural self-interaction matrix to present the model. According to the results, adoptability is a first-level or dependent variable. Regarding the results of interpretive structural modeling (ISM), the variable of critical success factors is a second-level variable. Enablers, competencies and SME characteristics are the third-level and most effective variables of the model. Accordingly, the initial model of Cloud BI for SMEs is presented as follows: The results of ISM revealed the impact of SME characteristics on BI critical success factors and adoptability. Since this category was not an underlying category of BI; thus, it played the role of a moderating variable for the impact of critical success factors on adoptability in the final model.

Since this study is limited to about 100 SMEs in the north of Iran, results should be applied cautiously to SMEs in other countries. Generalizing the study's results to other industries and geographic regions should be done with care since management perceptions, and financial condition of a business vary significantly. Additionally, the topic of business intelligence in SMEs constrained the sample from the start since not all SMEs use business intelligence systems, and others are unaware of their advantages. BI tools enable the effective management of companies of all sizes by providing analytic data and critical performance indicators. In general, SMEs used fewer business intelligence technologies than big companies. According to studies, SMEs understand the value of simplifying their information resources to make critical business choices. Additionally, they are aware of the market's abundance of business intelligence products. However, many SMEs lack the technical knowledge necessary to choose the optimal tool combination. In light of the frequently significant investment required to implement BI approaches, a viable alternative for SMEs may be to adopt cloud computing solutions that enable organizations to strengthen their systems and information technologies on a pay-per-use basis while also providing access to cutting-edge BI technologies at a reasonable price.

Before the implementation of Cloud BI in SMEs, condition of driver, competency and critical success factor of SMEs should also be considered. These will help to define the significant resources and skills that form the strategic edge and lead to the success of Cloud BI projects.

Most of the previous studies have been focused on factors such as critical success factors in cloud business intelligence and cloud computing in small and medium-sized enterprises, cloud business intelligence adoption models, the services used in cloud business intelligence, the factors involved in acceptance of cloud business intelligence, the challenges and advantages of cloud business intelligence, and drivers and barriers to cloud business intelligence. None of the studied resources proposed any comprehensive model for designing and implementing cloud business intelligence in small and medium-sized enterprises; they only investigated some of the aspects of this issue.

Peer coaching has been described as an effective form of teacher professional development. Consequently, different aspects of the peer coaching process have been examined. However, no international comparative studies focusing on the differences between the applicability and adoptability of peer coaching in different educational systems were found. This paper seeks to address these issues.

This quantitative study examined cross‐national differences in educators’ beliefs about peer coaching by comparing survey responses of American and Turkish educators.

Data analysis showed that both American and Turkish educators found peer coaching adoptable at a high level in their school systems. However, on the applicability level there were statistically significant differences found at all subscales of peer coaching survey showing that American participants believed that peer coaching was much more applicable than did the Turkish participants.

While limited by the small sample size not representative of the overall populations in the USA and Turkey, this study contributes to the international discourse on the different types of teacher professional development by examining cross‐national differences in educators’ beliefs about peer coaching.

The results of this study inform practitioners and researchers about the ways peer coaching is perceived by educators in different countries. Given the findings, school districts can examine more contextually and culturally appropriate ways inherent in the post‐observation conference to increase the effectiveness of the peer coaching process.

The findings of this study enrich the body of research on peer coaching, particularly focusing on the teachers’ and leaders’ beliefs and perceptions about the adoption and applicability of peer coaching as a form of teacher professional development and calls for further empirical research on teacher peer coaching in the national and international contexts.

Blockchain technology (BT) is setting world-shattering standard in all type of transactions in business. BT has the prospective to drastically transform supply chain (SC). The main challenge is to enhance trust among the SC stakeholders. This paper aims to identify and prioritize the factors and its challenges that influence the adoptability of BT in SC. The prioritization of these factors will be helpful to the practitioners to decide the strategy of implementing the BT in SC.

The factors influencing adoption of BT are identified from the review of literature and expert opinion is used to rank the factors influencing the adoptability of BT in SC using grey relational analysis (GRA).

We identified and prioritized key factors: inter-organizational trust and relational governance as organizational challenge, data transparency and data immutability as technological challenge, interoperability and product type as operational challenge and social influence and behavioral intention as social challenge that influences adoptability of BT in SC.

The priority of these factors will guide future researchers and industry practitioners to plan rational and financial strategy for implementing BT in SC.

Japanese‐focused management papers were examined to answer four questions: (1) Has there been a relative increase in the proportion of Japanese‐focused papers published? (2) Has there been a relative increase in the proportion of Japanese‐focused Organizational Behavior (OB) papers published? (3) What is the nature of Japanese‐focused OB papers? and (4) Are there “gaps” in the Japanese‐focused OB literature? The paper particularly reports current content appearing between 1994 and 2001 juxtaposed with that reported earlier by Godkin, Endoh, and Cahill (1995) appearing between 1981 and 1993.

The purpose of this paper is to identify the enablers and barriers to the adoption of green leasing in Sri Lanka and propose probable solutions.

As an in-depth investigation was required, the case study method with a qualitative approach was selected as the research methodology. A documentary review and semi-structured interviews on three selected green buildings were conducted to study their leasing processes. QSR NVivo statistical analysis software was used for the content analysis.

Enablers and barriers to the adoption of green leasing under different categories such as those related to processes, institutions and government and also to legal, economic and social factors were determined along with probable solutions identified through a comprehensive framework that was developed.

The findings can be used as a basis to evaluate the current leasing processes that have adopted this emerging and important approach toward the sustainable operation and management of green buildings.

The little attention paid to this latest concept makes it important to evaluate the adoptability of green leasing in developing countries. Hence, the determination of key enablers, barriers and solutions was the focal point of this research.

Open innovation communities are a growing trend across diverse industries because they provide opportunities of collaborating with customers and exploiting their knowledge effectively. Although open innovation communities can be strategic assets that can help firms innovate, firms nonetheless face the challenge of information overload incurred due to the characteristic of the community. The purpose of this paper is to mitigate the problem of information overload in an open innovation environment.

This study chose MyStarbucksIdea.com (MSI) as a target open innovation community in which customers share their ideas. The authors analyzed a large data set collected from MSI utilizing text mining techniques including TF-IDF and sentiment analysis, while considering both term and non-term features of the data set. Those features were used to develop classification models to calculate the adoption probability of each idea.

The results showed that term and non-term features play important roles in predicting the adoptability of ideas and the best classification accuracy was achieved by the hybrid classification models. In most cases, the precisions of classification models decreased as the number of recommendations increased, while the models’ recalls and F1s increased.

This research dealt with the problem of information overload in an open innovation context. A large amount of customer opinions from an innovation community were examined and a recommendation system to mitigate the problem was proposed. Using the proposed system, the firm can get recommendations for ideas that could be valuable for its business innovation in the idea generation phase, thereby resolving the information overload and enhancing the effectiveness of open innovation.

The purpose of this paper is to review and identify the dominating paradigms within management control theories in order to investigate adoptability of the European excellence model (EEM) as an alternative management control model or a framework.

The paper has conceptual character based on a literature survey.

The six dominating paradigms are identified within management control theories and based on the analysis it is concluded that EEM can be adapted as a management control model if its limitations are supplemented with other ideas or frameworks.

This is the first study which investigates adaptability and adoptability of EEM as a management control model.

This paper aims to contribute significantly to the empirical investigations on adopting Industry 4.0–circular economy in the Malaysian palm oil industry. The paper also aims to theorise and empirically assess a comprehensive model incorporating three aspects and 51 criteria.

A two-stage methodology is proposed using the fuzzy Delphi method and the fuzzy-based analytical network process. Twenty-seven criteria on adoptability of industry 4.0–circular economy were selected for the first-stage methodology, followed by identifying each criteria's intersection with the overall objectives.

The findings indicate that financial constraints, the lack of a collaborative I4.0–CE model, laws and policy, low management support and the training of dedicated employers in I4.0–CE-application are the top five criteria requiring critical attention from the POI.

The overall sustainability advantages of the POI are identified and discussed in depth to establish criteria for industry 4.0–circular economy applications.

This study fills the previous research gap by theoretically explaining POI's industry 4.0 adoption–circular economy from the perspective of two underpinning theories. Due to the pressure towards sustainability, the industry must be ready to adopt industry 4.0–circular economy applications, and resources must be managed appropriately and effectively by sharing and integrating. Advanced industry 4.0 technologies and pragmatic practices such as a circular economy are needed to achieve optimal sustainable development while retaining commercial success.