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The purpose of this paper is to propose a consensus method for multi-attribute group decision-making (MAGDM) problems based on preference-approval structure and regret theory, which can improve the efficiency of decision-making and promote the consensus level among individuals.

First, a new method to obtain the reference points based on regret theory and expert weighting method is proposed. Second, a consensus reaching method based on preference-approval structure is proposed. Then, an adjustment mechanism to further improve the consensus level between individuals is designed. Finally, an example of the assessment of elderly care institutions is used to illustrate the feasibility and effectiveness of the proposed method.

The feasibility and validity of the proposed method are verified by comparing with the advanced two-stage minimum adjustment method. The compared results show that the proposed method is more consistent with the actual situation.

This paper presents a consensus reaching method for MAGDM based on preference-approval structure, which considers the avoidance behaviors of individuals and reference points. Decision makers (DMs) can use this approach to rank and categorize alternatives while further increasing the level of consensus among them. This can further help determine the optimal alternative more efficiently.

A new MAGDM problem based on the combination of regret theory and individual reference points is proposed. Besides, a new method of obtaining experts' weights and a consensus reaching method for MAGDM based on preference-approval structure are designed.

This study aims to propose a consensus model that considers dynamic trust and the hesitation degree of the expert's evaluation, and the model can provide personalized adjustment advice to inconsistent experts.

The trust degree between experts will be affected by the decision-making environment or the behavior of other experts. Therefore, based on the psychological “similarity-attraction paradigm”, an adjustment method for the trust degree between experts is proposed. In addition, we proposed a method to measure the hesitation degree of the expert's evaluation under the multi-granular probabilistic linguistic environment. Based on the hesitation degree of evaluation and trust degree, a method for determining the importance degree of experts is proposed. In the feedback mechanism, we presented a personalized adjustment mechanism that can provide the personalized adjustment advice for inconsistent experts. The personalized adjustment advice is accepted readily by inconsistent experts and ensures that the collective consensus degree will increase after the adjustment.

The results show that the consensus model in this paper can solve the social network group decision-making problem, in which the trust degree among experts is dynamic changing. An illustrative example demonstrates the feasibility of the proposed model in this paper. Simulation experiments have confirmed the effectiveness of the model in promoting consensus.

The authors presented a novel dynamic trust consensus model based on the expert's hesitation degree and a personalized adjustment mechanism under the multi-granular probabilistic linguistic environment. The model can solve a variety of social network group decision-making problems.

Complex cost structures and multiple conflicting objectives make selecting an appropriate cloud service difficult. The purpose of this study is to propose a novel group consensus decision making method for cloud services selection with knowledge deficit by trust functions.

This article proposes a knowledge deficit-based multi-criteria group decision-making (MCGDM) method for cloud-service selection based on trust functions. Firstly, the concept of trust functions and a ranking method is developed to express the decision-making opinions. Secondly, a novel 3D normalized trust degree (NTD) is defined to measure the consensus levels. Thirdly, a knowledge deficit-based interactive consensus model is proposed for the inconsistent experts to modify their decision opinions. Finally, a real case study has been carried out to illustrate the framework and compare it with other methods.

The proposed method is practical and effective which is verified by the real case study. Knowledge deficit is an important concept in cloud service selection which is verified by the comparison of the proposed recommended mechanism based on KDD with the conventional recommended mechanism based on average value. A 3D NTD which considers three values (trust, not trust and knowledge deficit) is defined to measure the consensus levels. A knowledge deficit-based interactive consensus model is proposed to help decision-makers reach group consensus. The proposed group consensus model enables the inconsistent decision-makers to accept the revised opinions of those with less knowledge deficit, rather than accepting the recommended opinions averagely.

The proposed a knowledge deficit-based MCGDM cloud service selection method considers group consensus in cloud service selection. The concept of knowledge deficit is considered in modeling the group consensus measuring and reaching method.

This paper aims to address two fundamental questions: (1) How has Bahrain's industrial policy evolved during the 21st century? and (2) what factors contribute to this evolution?

Utilizing secondary data, this paper identifies key decision-makers responsible for economic policy in Bahrain and delineates the evolution of Bahrain's industrial policy throughout the 21st century. Subsequently, it employs a series of interviews with elite civil servants engaged in the formulation and implementation of Bahrain's economic policies to understand the reasons behind the observed changes.

Since assuming the role of Crown Prince in 1999, Sh. Salman bin Hamad Al Khalifa has been the key economic decision-maker in Bahrain. During the 21st century, Bahrain has shifted away from decisions closely aligned with the Washington Consensus towards those more in line with classical industrial policy. Interviews reveal that the private sector's underperformance in job creation, coupled with fiscal pressures, has driven this departure from the Washington Consensus. Moreover, the early successes of the interventionist Saudi Vision 2030 and Bahrain's own success in technocratically managing the COVID-19 pandemic have accelerated this transition.

Insights into the determinants of Bahrain's industrial policy can guide policymakers in refining future strategies. Recognizing the positive role of intellectual developments in academic economics literature becomes crucial for informed decision-making.

This paper fills a gap in the existing literature by providing answers to its research questions, particularly considering the significant changes witnessed in Bahrain's industrial policy post-pandemic.

Autistic individuals are at increased risk of trauma exposure and post-traumatic stress disorder (PTSD). Diagnostic overshadowing, however, often results in PTSD symptoms being mislabelled as autistic traits. This study aims to develop professional consensus on the identification and assessment of co-occurring PTSD in autistic adults.

An online modified Delphi design was used to gather professionals’ perspectives on key aspects of the identification and assessment of PTSD in autistic adults. Data were gathered qualitatively in Round 1 and then synthesised using content analysis into a list of statements that were rated in Round 2. Statements reaching 60–79% consensus and additional suggestions were sent out for rating in Round 3. Consensus for the final statement list was set at 80% agreement.

Overall, 108 statements reached consensus. These form the basis of professional-informed recommendations to facilitate the identification and assessment of PTSD symptoms in autistic adults.

The final Delphi statements provide a framework to assist with the assessment and recognition of traumatic stress reactions in autistic adults presenting to mental health, diagnostic or social services.

To the best of the authors’ knowledge, this is the first study to explore the presentation and identification of PTSD in autistic adults (with and without intellectual disability), using a bottom-up approach informed by professional consensus.

The study aimed to identify and define core components of Throughcare. The global prison population has reached its highest level to date (11.5 million), with comparative data on recidivism unavailable. Despite the global shift away from punitive and towards rehabilitative approaches, reintegration programming (Throughcare) is limited, ill-resourced or non-existent in many countries.

This study conducted a global e-Delphi consensus study of professionals working in prison and correctional services to define critical components of effective rehabilitation and reintegration programming. Consensus was defined a priori as 70% or more participants scoring an outcome from 7 to 9 and fewer than 15% scoring it 1 to 3.

Following a call for expression of interest circulated to the International Corrections and Prisons Association member list (n = 7282), 175 members agreed to partake in the e-Delphi rounds. In Round One, 130 individuals completed an online survey where 35 statements were scored by importance, each with opportunity to provide written feedback. A total of 33 statements exceeded the set threshold of consensus. Written feedback supported refinement and further development of statements in Round Two. A total of 108 individuals completed Round Two. A total of 39 out of the 40 statements exceeded the set threshold of consensus.

Consensus statements are useful to provide a shared understanding for inter-agency Throughcare partnerships, to inform national prison policies and to expand prison and support staff capacity building and programmes all over the world.

To the best of the authors’ knowledge, to date, this is the first known attempt to elicit consensus from a broad range of professionals working in the field of prison and correctional services on core components of effective rehabilitation and reintegration programming.

A Delphi study was conducted to identify the critical variables of successful implementation of sustainable road infrastructure projects (SRIPs) in developing countries, determine the reasons for the various viewpoints held by infrastructure development professionals, determine what motivates and pushes the infrastructure sector to pursue sustainability, and determine the factors that could impact the implementation of a project for sustainable road infrastructure. Expert feedback was used to determine values for these metrics and indicators, and most of the panellists reached a consensus on the final decision. Statistical methods were used to determine whether there was a general agreement with respect to the statements and questions asked. The findings of the study were presented alongside its overarching principles. The most important criteria for SRIP implementation were socio-cultural sustainability, economic sustainability, environmental sustainability, and engineering performance, with little consensus on environmental sustainability and public participation. The primary purpose of this study was to identify the most crucial determinants of effective SRIP implementation in low-income nations. Interquartile deviation (IQD) values ranged from 7.0 to 8.1, but IQD values varied from 2.00 to 3.00. Thirty-one environmental sustainability indicators were assessed as important or very important, with 26 out of 30 having IQD values between 0.00 and 1.00. Six sub-attributes were deemed extremely significant and four important when experts examined institutional sustainability, with no consensus on the final four indications (IQD 1). Fourteen of twenty-one Public Participation Indicators were deemed ‘major’ by panellists for SRIP implementation, with consensus among experts. Ten factors contribute to diverse perceptions of sustainability, with only 2 deemed crucial and 18 deemed important. The four most essential indicators of successful SRIP implementation are VHI: 9–10). The other seven criteria were crucial because their median scores were between 7.00 and 10. The Delphi survey explained why various individuals in the infrastructure industry have divergent views on what it means to be sustainable. Twenty-one factors were identified as contributors to divergent perspectives on sustainability among infrastructure industry stakeholders. The Delphi survey also established the factors that affect the success of SRIP implementation in low-income countries, leading to the development of the conceptual SRIPI model.

The workforce management model conceptualised for the effective management of the construction workforce was subjected to expert scrutiny to determine the suitability and applicability of the identified practices and their attributed variables to the construction industry. In achieving this, a Delphi approach was adopted using experts from construction organisations in South Africa. These experts comprised workforce management personnel and construction professionals in senior management positions. The data were analysed using appropriate statistical tools such as interquartile deviation, Kendell’s coefficient of concordance, and chi square to determine consensus among these experts. After a two-round Delphi, the seven constructs proposed in the conceptualised workforce management model were adjudged to be important and worthy of adoption by construction organisations seeking to improve workforce management in the current fourth industrial revolution era.

Despite increasing attention to employee development, past research has mostly studied performance management systems (PMSs) in relation to task-related behaviors compared to proactive behaviors. Accordingly, this study addresses the relation between PMSs and innovative work behavior (IWB).

Building on signaling theory and human resource management (HRM) system strength research, the authors designed a factorial survey experiment (n = 444) to examine whether PMSs stimulate IWB under different configurations of distinctiveness, consistency and consensus, as well as in the presence of transformational leadership.

Results show that only strong PMSs foster IWB (high distinctiveness, high consistency and high consensus [HHH]). Additional analyses reveal that the individual meta-features of PMS consistency and consensus can also stimulate innovation. Transformational leadership reinforced the relationship between PMS consensus and IWB relationship, but not the relationships of the other meta-features.

The study’s findings suggest that organizations wishing to unlock employees' innovative potential should design PMSs that are visible, comprehensible and relevant. To further reap the innovative gains of employees, organizations could also invest in the coherent and fair application of planning, feedback and evaluation throughout the organization and ensure organizational stakeholders agree on the approach to PMSs.

The study’s findings show that PMS can also inspire proactivity in employees, in the form of IWB and suggest that particular leadership behaviors can complement certain PMS meta-features, and simultaneously also compete with PMS strength, suggesting the whole (i.e. PMS strength) is more than the sum of the parts (i.e. PMS meta-features).