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This study aims to explore the role of rebel group legitimacy and ideology in durable peace (DP) following peace agreements to end civil wars. It builds on earlier research showing that justice and civil society involvement are critical in achieving DP. This study adds the impacts of rebel group activities and support on DP. Activities include service delivery and mobilization. Support is gauged with outcomes of presidential and parliamentary elections held following peace agreements.

Five data sets were used to measure the key variables: DP, inclusive commissions (IC), legitimacy symmetry (electoral outcomes), service delivery and ideological mobilization. A measure of rebel group integration in the political system was also constructed. Impacts of the integration, legitimacy and ideology variables were assessed with a hierarchical regression model (HRM). This study begins with a base model drawn from earlier research showing the key predictors were procedural justice (PJ) and IC. The authors ask about the extent to which the rebel group variables contribute additional variance to the prediction of DP.

The main contributors to the prediction of DP were PJ, IC and integration in the political system. None of the legitimacy or mobilization variables added significant variance to the prediction. Only one of the mobilization variables, forced recruitment, was significant. The decision to integrate into the political system following the agreement did not mediate the relationship between PJ in the negotiation process and DP. Results of a factor analysis showed that DP, PJ, IC and integration formed a cluster with strong loadings on the first factor.

The negative results for the legitimacy and mobilization variables may not be the last word on rebel group influences. Lack of support for the key hypotheses spurs attempts to discover other sources that contribute to the survival of rebel group actors in the political system and, in turn, to DP.

The issues raised by this study contribute to debates about ways to attain peaceful relations among competing groups following a civil war. It appears that attention to factors inside and around the negotiation process (PJ, ICs and conversion) may be more important than rebel group activities outside of these processes. The results call attention, in particular, to the important role played by political integration. From a policy perspective, it would be useful to develop levers for encouraging rebel groups to emerge as political actors in the post-agreement environment.

Developing measures of the symmetry of rebel group legitimacy and integration in the context of a comparative case study are the primary original contributions of this study. Furthermore, the mode of analysis (HRM) is novel in this literature. This approach builds on and extends the earlier research on factors influencing DP.

This study operationalizes risks in stakeholder dialog (SD). It conceptualizes SD as co-produced organizational discourse and examines the capacities of organizers' and stakeholders' practices to create a shared understanding of an organization’s risks to their mutual benefit. The meetings and online forum of a German public service media (PSM) organization were used as a case study.

The authors applied corpus-driven linguistic discourse analysis (topic modeling) to analyze citizens' (n = 2,452) forum posts (n = 14,744). Conversation analysis was used to examine video-recorded online meetings.

Organizers suspended actors' reciprocity in meetings. In the forums, topics emerged autonomously. Citizens' articulation of their identities was more diverse than the categories the organizer provided, and organizers did not respond to the autonomous emergence of contextualizations of citizens' perceptions of PSM performance in relation to their identities. The results suggest that risks arise from interactionally achieved occasions that prevent reasoned agreement and from actors' practices, which constituted autonomous discursive formations of topics and identities in the forums.

This study disentangles actors' practices, mutuality orientation and risk enactment during SD. It advances the methodological knowledge of strategic communication research on SD, utilizing social constructivist research methods to examine the contingencies of organization-stakeholder interaction in SD.

Our paper studies a central issue with a long history in economics: the relationship between population and economic growth. We analyze the joint dynamics of economic and demographic growth in 111 countries during the period 1960–2019.

Using the concept of economic regime, the paper introduces the notion of distance between the dynamical paths of different countries. Then, a minimal spanning tree (MST) and a hierarchical tree (HT) are constructed to detect groups of countries sharing similar dynamic performance.

The methodology confirms the existence of three country clubs, each of which exhibits a different dynamic behavior pattern. The analysis also shows that the clusters clearly differ with respect to the evolution of other fundamental variables not previously considered [gross domestic product (GDP) per capita, human capital and life expectancy, among others].

Our results indirectly suggest the existence of dynamic interdependence in the trajectories of economic growth and population change between countries. It also provides evidence against single-model approaches to explain the interdependence between demographic change and economic growth.

We introduce a methodology that allows for a model-free topological and hierarchical description of the interplay between economic growth and population.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

The purpose of the study is to identify the soft skills and abilities that are crucial to success in the fields of operations management (OM) and supply chain management (SCM), using the O*NET database and the classification of a set of professional figures integrating values for task skills and abilities needed to operate successfully in these professions.

The study used the O*NET database to identify the soft skills and abilities required for success in OM and SCM industries. Correlation analysis was conducted to determine the tasks required for the job roles and their characteristics in terms of abilities and soft skills. ANOVA analysis was used to validate the findings. The study aims to help companies define specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the job position.

As a result of the work, a set of soft skills and abilities was defined that allow, through correlation analysis, to explain a large number of activities required to work in the operations and SCM (OSCM) environment.

The work is inherently affected by the database used for the professional figures mapped and the scores that are attributed within O*NET to the analyzed elements.

The information resulting from this study can help companies develop specific assessments and tests for the roles of OM and SCM to measure individual attitudes and correlate them with the requirements of the job position. The study aims to address the need to identify soft skills in the human sphere and determine which of them have the most significant impact on the OM and SCM professions.

The originality of this study lies in its approach to identify the set of soft skills and abilities that determine success in the OM and SCM industries. The study used the O*NET database to correlate the tasks required for specific job roles with their corresponding soft skills and abilities. Furthermore, the study used ANOVA analysis to validate the findings in other sectors mapped by the same database. The identified soft skills and abilities can help companies develop specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the requirements of the job position. In addressing the necessity for enhanced clarity in the domain of human factor, this study contributes to identifying key success factors. Subsequent research can further investigate their practical application within companies to formulate targeted growth strategies and make appropriate resource selections for vacant positions.

This study aims to analyse how consumers' perceptions of justice in a service recovery scenario vary, not only due to the company's actions but also due to the comparisons they make with the experiences of other consumers.

Based on justice theory, social comparison theory and referent cognitions theory, this study describes an eight-scenario experiment with better or worse interactional, procedural and distributive justice (better/worse interactional justice given to other consumers) × 2 (better/worse procedural justice given to other consumers) × 2 (better/worse distributive justice given to other consumers).

First, consumers' perceptions of interactional, procedural and distributive justice vary based on the comparisons they draw with other consumers' experiences. Second, the results confirmed that interactional justice has a moderating effect on procedural justice, whereas procedural justice does not significantly moderate distributive justice.

First, based on justice theory, social comparison theory and referent cognitions theory, we focus on the influence of the treatment received by other consumers on the consumer's perceived justice in the same service recovery situation. Second, it is proposed that the three justice dimensions follow a defined sequence through the service recovery phases. Third, to the best of the authors' knowledge, this study is the first to propose a multistage model in which some justice dimensions influence other justice dimensions.

: 本研究擬探討在服務補救的處境裡, 消費者對公平的看法不但會受公司的行動所影響, 同時也會因他們與其他消費者的經驗作比較而有所改變。

: 本研究根據正義理論、社會比較理論和參照認知理論, 描述一個涵蓋八個處境的實驗, 實驗包含更好的或更差的互動的、程序上的和分配性的公平 (給予其他消費者更好的/更差的互動公平) × 2(給予其他消費者更好的/更差的程序上的公平) × 2 (給予其他消費者更好的/更差的分配性的公平)。

: 研究結果顯示, 消費者對互動的、程序上的和分配性公平的看法, 是會根據他們與其他消費者的體驗所作的比較而有所改變; 研究結果亦確認了互動的公平對程序上的公平會有調節作用, 而程序上的公平對分配性的公平則沒有顯著的調節作用。

: 首先, 我們根據正義理論、社會比較理論和參照認知理論, 把研究焦點放在於相同的服務補救情景中, 其他消費者受到的待遇, 如何影響消費者自身的認知公平; 另外, 我們建議, 這三個公平維度, 在各個服務補救階段裡, 均會跟隨一個清晰的次序。最後, 就研究人員所知, 本研究為首個提出一個公平維度互為影響的多階段模型的研究。

This study aims to propose and evaluate a novel framework of strategic adaptability in dyadic negotiations. The authors define strategic adaptability as a reaction to a cue that leads to shifts between integrative and distributive strategies. Based on the literature on turning points, phase models and strategic negotiations, the authors developed an initial framework identifying five distinct strategic adaptations.

To verify the framework, the authors analyzed two negotiation simulations with a diverse set of negotiation students. Negotiations were content-coded, and adaptations were labeled.

The authors found a consistent pattern across two studies. Overall, 12% (study 1) and 18% (study 2) of all speaking turns were identified as strategic adaptations. The findings empirically confirmed four of their strategic adaptation types: adapt to deadlock, follow adaptation by opponent, adapt to priority of issue under discussion and adapt to new information on issue. Moreover, findings of this study revealed two new types of strategic adaptability: delayed adaptation to opponent and adapt to understand opponent. Study 2 additionally revealed that strategies vary with the negotiation phase, and negotiation outcome seems to benefit more from the constellation rather than the frequency of adaptations. Furthermore, lower-scoring negotiators tended to adapt to the opponent’s strategy instead of initiating a change in strategy.

The findings of this study provide preliminary insights into how strategic adaptations unfold. These findings present future research opportunities to further test the framework's robustness, increase the knowledge of individual and cultural factors, explore the relationship with negotiation outcomes and develop educational interventions to enhance strategic adaptability.

The main purpose of this paper is to introduce the gradient discretisation method (GDM) to a system of reaction diffusion equations subject to non-homogeneous Dirichlet boundary conditions. Then, the authors show that the GDM provides a comprehensive convergence analysis of several numerical methods for the considered model. The convergence is established without non-physical regularity assumptions on the solutions.

In this paper, the authors use the GDM to discretise a system of reaction diffusion equations with non-homogeneous Dirichlet boundary conditions.

The authors provide a generic convergence analysis of a system of reaction diffusion equations. The authors introduce a specific example of numerical scheme that fits in the gradient discretisation method. The authors conduct a numerical test to measure the efficiency of the proposed method.

This work provides a unified convergence analysis of several numerical methods for a system of reaction diffusion equations. The generic convergence is proved under the classical assumptions on the solutions.

Sarcasm is a linguistic expression that usually carries the opposite meaning of what is being said by words, thus making it difficult for machines to discover the actual meaning. It is mainly distinguished by the inflection with which it is spoken, with an undercurrent of irony, and is largely dependent on context, which makes it a difficult task for computational analysis. Moreover, sarcasm expresses negative sentiments using positive words, allowing it to easily confuse sentiment analysis models. This paper aims to demonstrate the task of sarcasm detection using the approach of machine and deep learning.

For the purpose of sarcasm detection, machine and deep learning models were used on a data set consisting of 1.3 million social media comments, including both sarcastic and non-sarcastic comments. The data set was pre-processed using natural language processing methods, and additional features were extracted and analysed. Several machine learning models, including logistic regression, ridge regression, linear support vector and support vector machines, along with two deep learning models based on bidirectional long short-term memory and one bidirectional encoder representations from transformers (BERT)-based model, were implemented, evaluated and compared.

The performance of machine and deep learning models was compared in the task of sarcasm detection, and possible ways of improvement were discussed. Deep learning models showed more promise, performance-wise, for this type of task. Specifically, a state-of-the-art model in natural language processing, namely, BERT-based model, outperformed other machine and deep learning models.

This study compared the performance of the various machine and deep learning models in the task of sarcasm detection using the data set of 1.3 million comments from social media.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.