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Although several studies have aimed to present models to predict conflict outcomes, fewer methods have been developed to analyze conflict manageability and provide management strategies based on prediction models. This research pitches into the manageability analysis of conflicts occur during the implementation of a proposed change in construction projects. In this way, a framework has been developed by defining two parameters: the predictability index and the preventability index.

Within this framework, the predictability index determines how many outcomes of the prediction model can be used for conflict management based on the degree of clarity. The preventability index demonstrates how preventive measures for conflict management can be identified. Eventually, three preventive measures can be determined: (1) identifying weaknesses of decision-making patterns and organizational culture, (2) identifying events that may be prevented using soft skills and (3) identifying differences among similar change-implementation scenarios and evaluating causes of the differences. To demonstrate the capabilities of proposed framework, a practical example has been analyzed.

The results show that the behavior of the project parties can be psychologically analyzed, and psychological conflicts can be distinguished from technical conflicts. Moreover, identifying the weaknesses of parties' decision-making patterns and their organizational culture is the most effective measure to prevent the conflicts.

This research contributes to the construction body of knowledge by quantifying the predictability and preventability of conflicts between the project parties in a construction project based on: (1) the certainty level of the conflict occurrence and (2) the level of alignment between predicted outcomes of the conflict occurrence and the issued change request and/or change order.

The authors construct two time-varying political connection (PC) indexes to measure a firm's political tendencies toward ruling and opposing parties and analyze whether a firm with ruling party tendencies obtains better bank loan contracts compared to the contracts obtained by a firm with opposing party tendencies and a firm with fixed PC tendencies.

Linguistic text mining is used to construct the two time-varying PC indexes from news sources that reflect the tone and frequencies of characteristic texts to determine a firm's tendencies to favor the ruling or opposing parties.

The results show that varying PC firms connected to the ruling party receive preferential loan contracts when their political tendencies increase but varying PC firms connected to the opposition party do not. In contrast, fixed PC firms gain similar benefits only when the connection is determined in the presidential election year but not in other years. Firms supporting two parties receive minimal financial rewards in terms of loan terms.

In past studies, once a firm is identified as having a connection with a political party, it is assumed to have PC throughout the sample period (i.e. fixed PC firms). The authors lift this assumption and examine how varying PC affect bank loan contracts. The two time-varying PC indexes can identify a firm's more immediate party tendencies and more precise effects of a firm's party tendencies on bank loan contracts.

This study aims to excoriate, define and delineate the main drivers of “change” in commercial construction projects and generate guidelines on how to minimise exposure to the associated adverse effects upon project stakeholders.

The research adopts mixed doctrines through a combination of epistemological lenses, embracing two primary philosophical stances: interpretivism, to identify the primary drivers of change based on a systematic literature review and a post-positivist, inductive approach to analyse the results of change within a Joint Contracts Tribunal (JCT) Design and Build (D&B) construction project case study.

The causal nexus of change during the construction phase is assessed and delineated; the key affecting factors are thematically grouped under headings: extent and severity; time in relation to implementing; instigating party; individual(s) responsible for managing the change; reason for the change; available resource; recoverable or non-recoverable; contract/project type; and type of client. Following this, the effects of change on key elements of the project are encapsulated and recommendations for adaptations which may provide improved experiences are offered.

The study tackles the common issue of managing the deleterious effects of change on commercial construction projects, defining management techniques to minimise stakeholder tribulation.

Grounded in contingency theory and strategic fit theory, the goal for this research was to determine if managers differentiate in terms of the degree of partnership when allocating resources for planning, joint operating controls, communication and other management components to relationships and if this differentiation is based on the Partnership Model (Lambert et al., 1996).

In total, 381 managers representing 31 relationships participated in one-and-a-half-day partnership meetings, and the authors analyzed how the management components were implemented in each relationship compared to the recommendations in the Partnership Model.

Managers did not differentiate types of partnerships which led to over-resourcing relationships with low potential and under-resourcing those with the highest potential for creating value. The principles of contingency theory and strategic fit were not used for managing relationships.

Contingency theory combined with the relationship view suggests that management components should not be implemented at the same level for all relationships, but in the 31 relationships studied different partnership types were not managed based on their potential.

The research reinforces the need for a formal structure like the Partnership Model to establish joint goals for a relationship and guide management in implementation.

Effective supply chain management depends on the ability of managers to differentiate among partnership types and fit relational mechanisms that are appropriate. However, researchers tend to generalize their findings to all partnerships regardless of potential. The authors found support for the Partnership Model published in IJLM in 1996 as a method to resource different types of partnerships following the contingency perspective and strategic fit theory.

The authors systematically review empirical dyadic service encounter research published in top-tier journals between 1972 and 2022.

The authors employed bibliometric techniques, co-citation analysis and bibliographic coupling analysis to map schools of thought and research frontiers within the dyadic service encounter literature. In total, the authors analyzed 155 articles. To ensure inclusion of high-quality research, the authors screened articles from 139 journals with “4” or “4*” ratings on the 2021 Chartered Association of Business Schools (ABS) journal list, in addition to articles published in three service sector-specific journals: Journal of Service Management, Journal of Services Marketing and Journal of Service Theory and Practice.

The authors' co-citation analysis identified four distinct clusters within the dyadic service encounter literature: (1) shaping and explaining service encounters; (2) emotions in service work; (3) modeling, manipulating and measuring encounter service quality and (4) emotional labor and regulation in dyadic service encounters. Furthermore, the authors' bibliographic coupling analysis generated three research clusters: (1) service encounter characteristics; (2) emotions and emotional labor and (3) service encounter interaction content.

The authors' comprehensive review synthesizes knowledge, summarizing similarities among research clusters within the service encounter realm. Noteworthy are research clusters that clarify the emotion-based underpinnings and reciprocal nature of behaviors and emotions within dyadic encounters. By conducting complementary bibliometric analyses, the authors trace the evolution of the service encounter literature, providing an overview of the present state of dyadic service encounter research. These analyses offer valuable insights into the current landscape of the field, identifying future dyadic service encounter research opportunities.

Modern human society has continuous advancements that have a negative impact on the quality of the air. Daily transportation, industrial and residential operations churn up dangerous contaminants in our surroundings. Addressing air pollution issues is critical for human health and ecosystems, particularly in developing countries such as Egypt. Excessive levels of pollutants have been linked to a variety of circulatory, respiratory and nervous illnesses. To this end, the purpose of this research paper is to forecast air pollution concentrations in Egypt based on time series analysis.

Deep learning models are leveraged to analyze air quality time series in the 6th of October City, Egypt. In this regard, convolutional neural network (CNN), long short-term memory network and multilayer perceptron neural network models are used to forecast the overall concentrations of sulfur dioxide (SO₂) and particulate matter 10 µm in diameter (PM₁₀). The models are trained and validated by using monthly data available from the Egyptian Environmental Affairs Agency between December 2014 and July 2020. The performance measures such as determination coefficient, root mean square error and mean absolute error are used to evaluate the outcomes of models.

The CNN model exhibits the best performance in terms of forecasting pollutant concentrations 3, 6, 9 and 12 months ahead. Finally, using data from December 2014 to July 2021, the CNN model is used to anticipate the pollutant concentrations 12 months ahead. In July 2022, the overall concentrations of SO₂ and PM₁₀ are expected to reach 10 and 127 µg/m³, respectively. The developed model could aid decision-makers, practitioners and local authorities in planning and implementing various interventions to mitigate their negative influences on the population and environment.

This research introduces the development of an efficient time-series model that can project the future concentrations of particulate and gaseous air pollutants in Egypt. This research study offers the first time application of deep learning models to forecast the air quality in Egypt. This research study examines the performance of machine learning approaches and deep learning techniques to forecast sulfur dioxide and particular matter concentrations using standard performance metrics.

This paper aims to fill gap in the literature and explore policy options for resolving the problems of accountability by framing three research questions. The research questions are (i) whether certain elements of Scott’s (2014) institutional pillars attenuate (accentuate) corporate and public accountability; (ii) whether the presence of ruling party-affiliated enterprises (RPAEs) create an increase (decrease) in the degree of corporate (public) accountability; and (iii) whether there is a particular form of ownership change that transforms RPAEs into public investment companies.

Using a qualitative research methodology that involves term frequency and thematic analysis of publicly available textual information, the paper examines Mechkova et al.’s (2019 forms of government accountability. The paper analyzes the gaps between the de jure and de facto accountability using the institutional pillars framework.

The findings of the paper are three. First, there are gaps between de jure and de facto in all three (vertical, horizontal and diagonal) forms of government (public) accountability. Second, the study finds that more than three fourth of the parties that contested the June 2021 election did have regional focus. They did not advocate for accountability. Third, Ethiopia’s RPAEs are unique. They have regional focus and are characterized by severe forms of agency and information asymmetry problems.

The main limitation of the paper is its exploratory nature. Extending this research by using cross-country data could provide a more complete picture of the link between corporate (public) accountability and a country’s institutional pillars.

Academic research documents that instilling modern corporate (public) governance standards in the Sub Sahara Africa (SSA) region has shown mixed results. The analysis made in this paper is likely to inform researchers and policymakers about the type of change that leads to better corporate (and public) accountability outcomes.

The institutional change proposed in the paper is likely to advance the public interest by mitigating agency and information asymmetry problems and enhancing government accountability. The changes make the enterprises investable, save scarce jobs, enhance diversity and put the assets in RPAEs to better use.

To the best of the authors’ knowledge, this is the first paper that uses the institutional pillars analytical framework to examine an SSA country's corporate (public) accountability problem. It demonstrates that accountability is a domestic and a (novel) traveling theory. The paper identifies the complexity of resolving the interlock between political institutions and business enterprises. It theorizes that it is impossible to instill modern corporate (public) accountability standards without changing regulatory, normative and cultural cognitive pillars of institutions. The paper contributes to the change management and public interest literature.

Democratic renewal in Sri Lanka as well as a cross the Global South depends on strengthening democratic social movements within varieties of patrimonial capitalism. Patrimonial capitalism, emphasising patron–client relations, coincide with weakening democratic institutional cultures and practices. The dominant corruption/anti-corruption narrative is bracketed with elite class strategies aimed at negotiating a ‘managed corruption’. The realm of representative politics creating consent for patrimonial capitalism is shaped by: ethnic and class relations; the weakening of working-class parties; patriarchal cultures within parties; links with criminal networks; opaque finances and the integration of mainstream media with party patronage.

Democratising the realm of representative politics points towards democratic social movements. The internal dynamics of social movements, their relationships with political parties and collective learning are significant factors that shapes the strategic orientation of social movements. State repression of social movements highlights the need for demilitarisation and the abolition of prisons. The global sense of this local struggle relates to transforming financial markets and platform economies towards notions of financial and digital commons. The integration of different realms of politics, such as representative, movement, life and emancipatory politics, is vital for reinforcing solidarity as the basis for counter-hegemonic struggles.

Climate change mitigation and adaptation play an important role in overcoming the climate change challenges facing Sri Lanka today. Many initiatives have been undertaken to implement different policies and plans in this regard, which require considerable mobilisation of national and international financing. In acquiring climate finance, many barriers can be identified. This paper aims to investigate such barriers to climate financing in Sri Lanka and proposes strategies to address them.

The qualitative research approach was undertaken in this study by conducting ten semi-structured interviews with experts who are involved in climate change policy implementation activities in Sri Lanka. The collected data were analysed using the content analysis method via Nvivo software.

The empirical findings unveil six key barriers and the corresponding root causes to climate financing in Sri Lanka. Inadequate domestic funding for climate actions was captured as the dominant barrier in this direction. This study also revealed that barriers and their root causes are interconnected, leading to many financial limitations in implementing climate actions. The importance of playing a leading role by the government and enabling an integrated approach between the private and public sector organisations were identified as key strategies to combat climate finance barriers.

Despite there being studies focusing on climate change and related policies, limited research has been carried out with regard to climate financing. Within this context, this study makes an original contribution in the area of climate financing with particular reference to a developing country like Sri Lanka. Further, the identification of barriers to climate financing, their root causes and strategies to address them also provides an original contribution to theory and practice.

This study aims to examine the association between related party transactions and firm value. The study also investigates the impact of several determinants of this relationship as moderating variables.

The paper uses multiple regression models. In the period from 2018 to 2021, a total of 134 non-financial companies listed on the Saudi Stock Exchange were included in the sample, which consisted of 451 firm-year observations.

This paper finds that related party transactions have a significant negative impact on firm value. Moreover, the negative impact of related party transactions on firm value is increased in the presence of changes in the certain presence of certain moderating variables, such as firm size, leverage and return on assets (ROA). The results of the sensitivity analysis concur with the findings of the basic analysis. There is little evidence in the literature regarding related party transactions and their association with the moderating variables considered in this study.

To the best of the authors’ knowledge, there have been no studies conducted in Saudi Arabia to date that examine the effect of firm size, leverage and ROA on the association between firm value and related party transactions. Consequently, this paper contributes to the limited literature by expanding the existing research and analyzing the impact of firm size, leverage and ROA on the association between related party transactions and firm value.