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The current study aims to propose and empirically investigate a conceptual model of the most relevant antecedents and consequences of Corporate Social Responsibility (CSR) attribution, thus providing a practical and concise model as well as examining brand attachment as a mediator explaining the relationship between CSR attribution and its consequences.

A between-subjects experimental design was employed. The study included two experimental conditions; intrinsic and extrinsic CSR attribution and a control condition. An online self-administered survey was utilised for data collection. The sample was a convenience sample of 336 university students. Both one-way between-groups ANOVA and Partial Least Squares-Structural Equation Modelling (PLS-SEM) were utilised for hypotheses testing.

The most significant antecedents of CSR attribution in order of importance are the firm's approach to CSR communication, past corporate social performance, CSR type and the firm's call for customers' participation in its CSR. CSR attribution exerted a significant direct positive impact on brand attachment and trust. Three significant indirect consequences of CSR attribution were PWOM intention, purchase intention and brand loyalty intention. Whereas trust played a significant mediating role between CSR attribution and its three indirect consequences, brand attachment exerted significant mediation only between CSR attribution and brand loyalty intention. Brand attachment might mediate the relationship between CSR attribution and purchase intention. However, brand attachment failed to play a mediating role between CSR attribution and PWOM intention.

Several studies marginally investigated CSR attribution. Despite the vital role of CSR attribution in how consumers receive firms' CSR engagement, the availability of CSR attribution-centric studies is limited. By introducing a model of the most relevant antecedents and consequences of CSR attribution, this study aids in understanding the psychological mechanism underlying consumers' CSR attribution and provides valuable implications.

Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due to limitations in utilizing heterogeneous sensing data and domain knowledge as well as insufficient generalizability resulting from limited data samples. This paper integrates implicit and qualitative expert knowledge into quantifiable values in tunnel condition assessment and proposes a tunnel structure prediction algorithm that augments a state-of-the-art attention-based long short-term memory (LSTM) model with expert rating knowledge to achieve robust prediction results to reasonably allocate maintenance resources.

Through formalizing domain experts' knowledge into quantitative tunnel condition index (TCI) with analytic hierarchy process (AHP), a fusion approach using sequence smoothing and sliding time window techniques is applied to the TCI and time-series sensing data. By incorporating both sensing data and expert ratings, an attention-based LSTM model is developed to improve prediction accuracy and reduce the uncertainty of structural influencing factors.

The empirical experiment in Dalian Road Tunnel in Shanghai, China showcases the effectiveness of the proposed method, which can comprehensively evaluate the tunnel structure condition and significantly improve prediction performance.

This study proposes a novel structure condition prediction algorithm that augments a state-of-the-art attention-based LSTM model with expert rating knowledge for robust prediction of structure condition of complex projects.

Despite the popularity of the entrepreneurial ecosystem (EE) concept, research on its value-adding activities receives less attention. Thus, in this article, the authors investigate the role of EEs in supporting global value chain (GVC) activities.

The authors employ the fuzzy-set qualitative comparative analysis (fsQCA) technique to identify practical configurations of EE’s framework and systemic conditions spurring GVC activities in 80 countries.

The findings suggest different configurations of EE`s framework and systemic conditions necessary for various GVC activities regarding input-output structure, geographical scope, upgrading, and forward and backward participation.

This study contributes to the extant literature by pioneering the EE approach to explaining GVC development. Moreover, the findings provide novel insights for understanding the EE – GVC interplay. As a result, the study offers a more nuanced understanding of how the EE supports GVC activities.

In response to the problem of insufficient traction/braking adhesion force caused by the existence of the third-body medium on the rail surface, this study aims to analyze the utilization of wheel-rail adhesion coefficient under different medium conditions and propose relevant measures for reasonable and optimized utilization of adhesion to ensure the traction/braking performance and operation safety of trains.

Based on the PLS-160 wheel-rail adhesion simulation test rig, the study investigates the variation patterns of maximum utilized adhesion characteristics on the rail surface under different conditions of small creepage and large slip. Through statistical analysis of multiple sets of experimental data, the statistical distribution patterns of maximum utilized adhesion on the rail surface are obtained, and a method for analyzing wheel-rail adhesion redundancy based on normal distribution is proposed. The study analyzes the utilization of traction/braking adhesion, as well as adhesion redundancy, for different medium under small creepage and large slip conditions. Based on these findings, relevant measures for the reasonable and optimized utilization of adhesion are derived.

When the third-body medium exists on the rail surface, the train should adopt the low-level service braking to avoid the braking skidding by extending the braking distance. Compared with the current adhesion control strategy of small creepage, adopting appropriate strategies to control the train’s adhesion coefficient near the second peak point of the adhesion coefficient-slip ratio curve in large slip can effectively improve the traction/braking adhesion redundancy and the upper limit of adhesion utilization, thereby ensuring the traction/braking performance and operation safety of the train.

Most existing studies focus on the wheel-rail adhesion coefficient values and variation patterns under different medium conditions, without considering whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train. Therefore, there is a risk of traction overspeeding/braking skidding. This study analyzes whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train and whether there is redundancy. Based on these findings, relevant measures for the reasonable and optimized utilization of adhesion are derived to further ensure operation safety of the train.

This study analyses configurations of national culture as boundary conditions of countries’ national systems of innovation (NSI). Drawing from the NSI approach, we argue that culture’s role is that of a contingency factor shaping the relationship between investments in innovation and national innovation outputs.

We assessed the moderation effect of national culture through a systematic, two-stage approach using fuzzy-set Qualitative Comparative Analysis (fsQCA), which allows the analysis of changes induced by the moderator variables. Analyses were conducted with a diverse sample of 61 countries over a period spanning 12 years, from 2011 to 2022.

Findings reveal that investments in innovation, but not individual cultural dimensions, is a necessary condition for high innovation outputs. Furthermore, several configurations of cultural dimensions were identified as moderators of the relationship between investments in innovation and innovation outputs.

This study provides insights into cross-national innovation research by exposing the role of cultural configurations, rather than just individual cultural dimensions, as boundary conditions involved in the achievement of high levels of innovation.

Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective maintenance and rehabilitation strategies for water pipes based on reliable deterioration models and cost-effective inspection programs. In the light of foregoing, the paramount objective of this research study is to develop condition assessment and deterioration prediction models for saltwater pipes in Hong Kong.

As a perquisite to the development of condition assessment models, spherical fuzzy analytic hierarchy process (SFAHP) is harnessed to analyze the relative importance weights of deterioration factors. Afterward, the relative importance weights of deterioration factors coupled with their effective values are leveraged using the measurement of alternatives and ranking according to the compromise solution (MARCOS) algorithm to analyze the performance condition of water pipes. A condition rating system is then designed counting on the generalized entropy-based probabilistic fuzzy C means (GEPFCM) algorithm. A set of fourth order multiple regression functions are constructed to capture the degradation trends in condition of pipelines overtime covering their disparate characteristics.

Analytical results demonstrated that the top five influential deterioration factors comprise age, material, traffic, soil corrosivity and material. In addition, it was derived that developed deterioration models accomplished correlation coefficient, mean absolute error and root mean squared error of 0.8, 1.33 and 1.39, respectively.

It can be argued that generated deterioration models can assist municipalities in formulating accurate and cost-effective maintenance, repair and rehabilitation programs.

Almost four years after the COVID-19 pandemic, the changes in the labour market and legislation, but also in people's lives, do not stop. At the same time, employees' perceptions regarding the change in the legislative and contractual framework, as well as in the working conditions and the use of telework, also change. Therefore, the aim of the paper is to identify the perceptions of employees regarding the use of telework in the post-pandemic period.

The research was based on a survey carried out on 128 teleworkers in the post-pandemic period. The statistical hypotheses were tested using Kolmogorov–Smirnov and Kruskal–Wallis tests, multiple linear regression and pairwise comparison analysis.

The results of the study demonstrate that the modification of the legislative and contractual framework and of the working conditions, as well as of the way of using information and communication technology in the post-pandemic era, generates a positive and significant impact on the use of telework by employees. Some of the main advantages valued by teleworkers included the possibility of benefitting from a flexible work schedule and the possibility of reducing transport costs.

The study highlights the need to continuously develop and update labour policies and strategies in line with current and future labour market requirements, considering the implications of telework on the perceptions of employees, so that government organisations and managers who want to protect the rights and interests of teleworkers, aspects of their lives and organise an appropriate work environment manage to do so in order to achieve the expected results.

The aim of this chapter is to introduce a methodology that enables researchers to employ a set of systematic comparative tools and techniques in their multiple case study research that allow them to move from drawing loose comparisons towards a more formalised type of analysis, while simultaneously paying attention to within-case complexities. This methodology stands between the qualitative and the quantitative methods and helps researchers to build middle-range theories (Mjoset, 2001) from small to intermediate numbers of cases. This methodology encompasses a number of techniques including crisp and fuzzy set-theoretic qualitative comparative analyses, which have been used in a wide range of social science disciplines. However, these techniques have not received sufficient attention from higher education scholars.

The purpose of this chapter is to review our findings related to the question “Do outcomes related to dynamic assessment on a cognitive measure predict reading growth?” Our discussion related to the predictive validity of such procedures focused on outcomes related to a battery of memory and reading measures administered over a three-year period to 78 children (11.6 years) with and without reading disabilities (RD). Working memory (WM) tasks were presented under initial, gain, and maintenance testing conditions. The preliminary results suggested that maintenance testing conditions were significant moderators of comprehension and vocabulary growth, whereas probe scores and gain testing conditions were significant moderators of nonword fluency growth. Overall, the results suggested that the dynamic assessment of WM added significant variance in predicting later reading performance.

The purpose of this study is to analyze public perceptions of disability and gain insight into the types of health conditions nondisabled people believe should be protected by the Americans with Disabilities Act (ADA). Understanding how the public interprets the ADA could offer perspective on which disabilities are viewed as legitimate and which are not. Data were gathered from a convenience sample of members from local community groups and college classrooms in a metropolitan university setting. Our analyses evaluate the clustering of health condition types due to similar traits and identify which attributes of the health conditions generate this clustering. Results from a series of quantitative and qualitative analyses (e.g., hierarchical cluster analysis, frequency analysis, discourse analysis, etc.) indicate nondisabled respondents perceive physical and cognitive health conditions that are visible, static, and externally acquired as legitimate disabilities that should be protected by the ADA.