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Public–private partnerships (PPPs) are notoriously prone to disputes among stakeholders, some of which may unduly jeopardize contract performance. Contract disputes arising in Iran are often due to inefficiency of PPP concession agreements and practice. This study presents a causal-predictive model of the root causes and preventive measures for inter-organization disputes to enhance the likelihood of achieving desirable performance in PPP projects.

A theoretical “causal-predictive” model was developed with fourteen hypotheses based on extant literature and contractual agency theory, which resulted in the creation of a pool of 110 published items. Data were obtained from a questionnaire survey with 75 valid responses, completed by 4 stratified groups of Iranian PPP experts. Partial least square structural equation modeling (PLS-SEM) was used for validating the proposed model via a case study.

Results reveal that the main three factors of PPP desirable performance are as follows: on-time project completion, high quality of activities/products and services for public satisfaction. Further, the most influential factors of the lifecycle problems, construction stage, and preferred risk allocation included risk misallocation, improper payment mechanism and failure to facilitate a timely approval process.

For researchers, the findings contribute to the theory of contractual agency; specifically, how different influences among the model's elements lead to better PPP performance. In practical terms, proposed outcome-based strategies will inform PPP stakeholders to avoid dispute occurrence and thus improve the time, quality and services of projects.

The citizen-shareholder approach in the capital market is considered a knowledge-enhancing and emerging concept in financial and accounting offerings. Its reliable background in management and human sciences makes it an essential basis for protecting the interests of shareholders and investors. Shareholders are considered a necessary part of the social platforms that are companies and regulatory institutions in the capital market; beyond being obligated to protect their material and intellectual rights, they are responsible for developing norms and facilitating investment values and gaining trust through mutual interactions based on respect for their interests. The purpose of this paper is to perform interactive qualitative analysis of the requirements for protecting the rights of citizens of capital market shareholders.

The methodology of the research is mixed, so that in the qualitative part, through content screening, the dimensions related to the protection of the citizen rights of the capital market shareholders were identified through a systematic review of 10 research in the period of 2017–2022. Then, the reliability of the specified dimensions was examined through Delphi analysis; in the quantitative part of the research, the criteria identified through the pairwise comparison matrix were first determined by the level of their relationships to determine based on the pattern of systemic representation of drivers and the consequences of requirements to protect the rights of citizens of capital market shareholders.

The research results in the qualitative part indicated the existence of 12 primary themes; during the two stages of Delphi analysis, three themes were removed, and a total of nine themes entered the quantitative phase. The results in a quantitative part indicate the creation of specialized and active committees of the board of directors as the primary driver and the reliability and timely disclosure of information in the long term as a systemic consequence.

To the best of the authors’ knowledge, this is the first research that presents the new concept of citizen shareholders to strengthen the requirements of protecting the rights of shareholders in the capital market while developing new theoretical literature.

The COVID-19 pandemic and recent disruptive events are affecting firms’ operations and supply chain networks on a large scale, causing disturbances in supply, demand, production and logistics activities. Although supply chain resilience (SCR) research has received large attention in recent years, the purpose of this paper is to offer an original contribution by exploring how complex configurations and interactions between SCR strategies and capacities can lead to resilience.

This study investigates the configurations of SCR strategies and capacities using a fuzzy-set qualitative comparative analysis.

First, the findings reveal different SCR strategy configurations through the lens of absorptive, reactive and restorative capacities to achieve resilience. Second, this study applies the contingent resource-based view (CRBV) perspective to interpret how organizations can achieve resilience before, during and after a disruptive event. Third, it offers an analysis of different groups of organizations, based on the adoption of different SCR strategies and capacities.

This study identifies a set of equifinal SCR strategies and capacity configurations that can be implemented to cope with a disruptive event and lead to resilience. It also enriches the research addressing the consecutive phases of SCR investments, developing the CRBV perspective. In our results, five solutions describe organizations that invest in absorptive capacities, representing an ex ante readiness.

The purpose of this study is to identify the situation of spatial inequality in the residential system of Tehran city in terms of housing prices in the year 2021 and to examine its changes over time (1991–2021).

In terms of purpose, this study is applied research and has used a descriptive-analytical method. The statistical population of this research is the residential units in Tehran city 2021. The average per square meter of a residential unit in the level of city neighborhoods was entered in the geographical information system (GIS) in 2021. Moran’s spatial autocorrelation method, map cluster analysis (hot and cold spots) and Kriging interpolation have been used for spatial analysis of points. Then, the change in spatial inequality in the residential system of Tehran city has been studied and measured based on the price per square meter of a residential unit for 30 years in the 22 districts of Tehran by using statistical clustering based on distance with standard deviation.

The result of spatial autocorrelation analysis with a score of 0.873872 and a p-value equal to 0.000000 indicates a cluster distribution of housing prices throughout the city. The results of hot spots show that the highest concentration of hot spots (the highest price) is in the northern part of the city, and the highest concentration of cold spots (the lowest price) is in the southern part of Tehran city. Calculating the area and estimating the quantitative values of data-free points by the use of the Kriging interpolation method indicates that 9.95% of Tehran’s area has a price of less than US$800, 17.68% of it has a price of US$800 to US$1,200, 25.40% has the price of US$1,200 to US$1,600, 17.61% has the price of US$1,600 to US$2,000, 9.54% has the price of US$2,000 to US$2,200, 6.69% has the price of US$2,200 to US$2,600, 5.38% has the price of US$2,600 to US$2,800, 4.59% has the price of US$2,800 to US$3,200 and finally, the 3.16% has a price more than US$3,200. The highest price concentration (above US$3,200) is in five neighborhoods (Zafaranieh, Mahmoudieh, Tajrish, Bagh-Ferdows and Hesar Bou-Ali). The findings from the study of changes in housing prices in the period (1991–2021) indicate that the southern part of Tehran has grown slightly compared to the average range, and the western part of Tehran, which includes the 21st and 22nd regions with much more growth than the average price.

There is massive inequality in housing prices in different areas and neighborhoods of Tehran city in 2021. In the period under study, spatial inequality in the residential system of Tehran intensified. The considerable increase in housing prices in the housing market of Tehran has made this sector a commodity, intensifying the inequality between owners and non-owners. This increase in housing price inequality has caused an increase in the informal living for the population of the southern part. This population is experiencing a living situation that contrasts with the urban plans and policies.

With the emergence of the different Industry 4.0 technologies and the interconnectedness between the physical and cyber components within manufacturing systems, the manufacturing environment is becoming more susceptible to unexpected disruptions, and manufacturing systems need to be even more resilient than before. Hence, the purpose of this work is to explore how does incorporating Industry 4.0 into current manufacturing systems affects (positively or negatively) its resiliency.

A Systematic Literature Review (SLR) was performed with a focus on studying the manufacturing system’s resilience when applying Industry 4.0 technologies. The SLR is composed of four phases, which are (1) questions formulation, (2) determining an adequate search strategy, (3) publications filtering and (4) analysis and interpretation.

From the SLR results’ analysis, four potential research opportunities are proposed related to conducting additional research within the research themes in this field, considering less studied Industry 4.0 technologies or more than one technology, investigating the impact of some technologies on manufacturing system’s resilience, exploring more avenues to incorporate resiliency to preserve the state of the system, and suggesting metrics to quantify the resilience of manufacturing systems.

Although there are a number of publications discussing the resiliency of manufacturing systems, none fully investigated this topic when different Industry 4.0 technologies have been considered. In addition to determining the current research state-of-art in this relatively new research area and identifying potential future research opportunities, the main value of this work is in providing insights about this research area across three different perspectives/streams: (1) Industry 4.0 technologies, (2) resiliency and (3) manufacturing systems and their intersections.

The environmental performance of organizations has come under public policy limelight since the phenomenal increase of natural resource degradation and industrial waste. Thus, green concepts have been put forward, but the implementation of green practices faces many barriers and challenges. These barriers require attention as organizational practices are negatively affecting the environment leading to global warming and climate change. Therefore, this chapter systematically identifies four internal barriers including inadequate management commitment and support, insufficient technology competence and infrastructure, financial constraints, the uncertainty of economic benefits, and eight sub barriers within an organization concerning green concepts implementation. Moreover, this chapter also identifies four external barriers including lack of stakeholder's interest, inadequate environmental administrative support, scarce academic research, and lack of green collaborative practices, and eight sub barriers outside an organizational context concerning green concept implementation. The barriers in this research were identified by reviewing the existing literature on the topic. This chapter advances the green literature by identifying multiple barriers and challenges to the successful implementation of green concepts in organizations. This is of significance as if these barriers are tackled strategically, it would reduce environmental degradation problems and help make financial gains. Moreover, this research can help managers understand the key barriers to green concept implementation and provide guidance to them when attempting to implement green practices in their organizations. This research would also motivate researchers to extend further investigation on how to overcome such barriers and find out strategies to mitigate the barriers to green concept implementation to effectively address environmental issues.

Cracks are prevalent signs of pavement distress found on highways globally. The use of artificial intelligence (AI) and deep learning (DL) for crack detection is increasingly considered as an optimal solution. Consequently, this paper introduces a novel, fully connected, optimised convolutional neural network (CNN) model using feature selection algorithms for the purpose of detecting cracks in highway pavements.

To enhance the accuracy of the CNN model for crack detection, the authors employed a fully connected deep learning layers CNN model along with several optimisation techniques. Specifically, three optimisation algorithms, namely adaptive moment estimation (ADAM), stochastic gradient descent with momentum (SGDM), and RMSProp, were utilised to fine-tune the CNN model and enhance its overall performance. Subsequently, the authors implemented eight feature selection algorithms to further improve the accuracy of the optimised CNN model. These feature selection techniques were thoughtfully selected and systematically applied to identify the most relevant features contributing to crack detection in the given dataset. Finally, the authors subjected the proposed model to testing against seven pre-trained models.

The study's results show that the accuracy of the three optimisers (ADAM, SGDM, and RMSProp) with the five deep learning layers model is 97.4%, 98.2%, and 96.09%, respectively. Following this, eight feature selection algorithms were applied to the five deep learning layers to enhance accuracy, with particle swarm optimisation (PSO) achieving the highest F-score at 98.72. The model was then compared with other pre-trained models and exhibited the highest performance.

With an achieved precision of 98.19% and F-score of 98.72% using PSO, the developed model is highly accurate and effective in detecting and evaluating the condition of cracks in pavements. As a result, the model has the potential to significantly reduce the effort required for crack detection and evaluation.

The proposed method for enhancing CNN model accuracy in crack detection stands out for its unique combination of optimisation algorithms (ADAM, SGDM, and RMSProp) with systematic application of multiple feature selection techniques to identify relevant crack detection features and comparing results with existing pre-trained models.

The study aims to explore the impact of tacit knowledge sharing (TKS) factors and its consequences in the form of technological innovation capabilities (TICs) within Pakistani software small–medium enterprises (SSMEs).

Drawing upon the social exchange theory (SET), the study used a quantitative approach and structural equation modeling (SEM) to test hypotheses with 220 valid data collected from 23 Pakistani software SSMEs.

The peer influence (PI) has positive and significant effect on collaborative culture (CC), willingness to share tacit knowledge (WSTK) and TICs. Organizational trust (OT) has a positive and significant impact on CC and TIC. Whereas, CC possessed positive and significant effect on WSTK and insignificant on TIC. Furthermore, WSTK has positive and significant effect on TIC. Finally, WSTK partially mediates the relationship between PI and TIC whereas WSTK fully mediates the relationship between CC and TIC.

The study enriches the research on knowledge sharing and TIC. This research investigates the precursors of tacit knowledge-sharing willingness and their consequences in software SMEs; future studies need to examine tacit knowledge-seeking willingness and its consequences not only in software enterprises but also in other industrial sectors. Besides, it needs to evaluate types of innovative capabilities in software SMEs.

The study suggested that the practitioners need to strengthen TKS in the form employees’ updated skills and expertise which ultimately fosters software enterprise’s innovative capabilities to attain competitive advantages in a specific industry.

This research is one of the few studies to examine the potential antecedents of WSTK and their final effects within software SMEs in the form of TICs. As currently it is observed, an incredible increase of skills oriented innovations in firms particularly in the software domain and IT industry. Therefore, this study emphasizes how PI, OT and WSTK positively affect TIC of Pakistani software SMEs. However, the study could be considered as a guideline for the academia and practitioners who attempt to strengthen the technological innovations capabilities in software SMEs.

Purpose of This Chapter: This chapter aims to clarify how employee voice (EV) is conceptualized in the extant literature. Then, the present chapter develops a model of EV based on previous studies from 1970 to 2022.

Design / Methodology / Approach: In all, 53 articles were investigated in this study – the focus was on articles in the field of management. The target articles were limited to those which were written in English and were indexed by the Web of Science (WOS).

Findings: The concepts related to EV have been presented in five main dimensions. The content analysis results revealed a theoretical agreement over the central elements reflecting an integrated description of EV.

Research Limitations: The study was limited to the sources published in the WOS database, which could affect the scope of findings.

Research Implications: The conclusion showed that EV is a multi-dimensional, emerging field that has been undergoing a definitional debate in the literature. This concept indicates an ongoing responsibility for the public’s benefit, welcomes different financial activities to supply market forces’ requirements, and investigates society’s existing demands.

Originality: It represents the first attempt to conduct an EV systematic literature review based on the definition of key factors and the complex relations in a typical EV process. Also, according to the review of selected articles from 1970 to 2022, there has been no coherent conceptualization of employees’ voices.

In New Zealand, building information modelling (BIM) prevalence is still in its early stages and faces many challenges. This research aims to develop a BIM adoption framework to determine the key factors affecting the success of a BIM project.

Both primary and secondary data were employed in this research, including 21 semi-structured interviews and industry guidelines from the three most well-known global building excellence models (BEMs). The data were analysed through content analysis due to its recognised benefits as a transparent and reliable approach.

Leadership, clients and other stakeholders, strategic planning, people, resources, process and results were identified as seven main categories along with 39 indicators in the BIM adoption framework. Based on the interviewees' perspectives, leadership is considered the most significant category, impacting all of the remaining categories.

Using the developed framework will enhance comprehension of BIM, offering directives for those embracing BIM. This will aid construction stakeholders in being better equipped for BIM projects. Having a skilled BIM manager can lead to the success of construction projects.

This research contributed to the existing body of knowledge by providing the categories with specific factors that assist BIM practitioners in assessing their BIM performance for further BIM practice improvement.