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The purpose of this paper is to investigate perceptions of primary education (PE) teachers with respect to evaluation within the framework of Total Quality Management (TQM) and their readiness to engage in the process of quality improvement. Within this context, a relevant measurement instrument is developed and empirically validated.

The instrument developed herein included 30 items distributed across seven dimensions. It was disseminated among public PE units in Greece, yielding a substantial 2,088 responses. Several tests were performed, including principal component analysis, confirmatory factor analysis and structural equation modelling.

The findings supported the validity and reliability of the instrument, confirming that the proposed measures encapsulate actual dimensions that are most suitable for exploring evaluation perception and readiness in the context of TQM in PE. The study explored several correlations between the validated dimensions and independent variables such as gender, level of education, years of teaching experience and age. These analyses yielded additional valuable insights, enriching the depth of understanding provided by the present research.

The fields of TQM and PE lack empirical evidence. However, this study offers valuable insights into teachers’ perceptions of evaluation and broader quality improvement efforts. This can help school managers, policymakers and practitioners refine their implementation strategies for educational excellence.

To the best of the authors’ knowledge, this study is the first to focus on the examination of evaluation as a key aspect of TQM within the context of PE. Through the development and validation of a real-time measurement instrument, it bridges a significant research gap, providing practitioners and researchers with a vital tool to understand and improve educators’ evaluation perceptions, enabling targeted interventions for enhanced performance.

Effective forensic interviewing is crucial, particularly if the interview is the only source of evidence. Whilst there are a number of interview models that advocate for reflective practice, the evaluation of interviews rarely gets the time or attention it deserves. This is concerning, given that interviewer skills drop significantly after six months, and there are limited opportunities for refresher training. This study aims to explore how law enforcement officers reflect upon and evaluate their interviews and seek their insight into what they believe an effective evaluation tool would constitute.

A total of 32 officers from three police forces in England and Wales and six international security organisations completed a qualitative questionnaire that explored their views on how interview evaluation is conducted and the impact on the interview, and how technology could assist in this important stage in terms of usability, efficacy and capability of a new evaluation tool.

Thematic analysis was used, resulting in three overall themes being identified from the data. These focused on current evaluation methods, barriers to conducting evaluations and technological solutions.

The findings are discussed in relation to interviewing and the development of tools to assist in evaluations. Implications for practice include the need for much more effort to be put into (re)introducing the evaluation stage into training to ensure that officers are allowed to reflect upon and evaluate their interview performance.

Green construction is increasingly vital in promoting sustainability within the construction industry. The development and promotion of green construction technologies are central to this endeavor. However, existing evaluations mainly target building components, construction projects or certain construction processes. There is a notable absence of research into the greenness of construction technologies. Assessing the greenness of construction technologies is crucial for streamlining resource utilization and reducing waste. To address this gap, this study aims to establish a Greenness of Construction Technologies (GCT) evaluation model using the method of analytic network process (ANP).

Green construction is increasingly vital in promoting sustainability within the construction industry. The development and promotion of green construction technologies are central to this endeavor. However, existing evaluations mainly target building components, construction projects or certain construction processes. There is a notable absence of research into the greenness of construction technologies. Assessing the greenness of construction technologies is crucial for streamlining resource utilization and reducing waste. To address this gap, this study establishes a GCT evaluation model using the method of ANP.

Among the four formwork technologies of plastic, steel, plywood and wooden formwork, the plastic formwork exhibits the best performance in terms of environmental friendliness, economic and social effects, while facing issues like material wastage and low static strength. The results align with practical observations which validates the model’s applicability.

This research contributes to the field by introducing the concept of greenness into construction technology evaluation for the first time. The establishment of the GCT evaluation model promotes the adoption of green construction technologies and advances sustainable practices in the construction industry.

Market evaluation of products is the basis for product innovation, yet traditional expert-based evaluation methods are highly dependent on the specialization of experts. There exist a lot of weak expert-generated texts on the Internet of their own subjective evaluations of products. Analyzing these texts can indirectly extract the opinions of weak experts and transform them into decision-support information that assists product designers in understanding the market.

In social networks, a subset of users, termed “weak experts”, possess specialized knowledge and frequently share their product experiences online. This study introduces a comparative opinion mining framework that leverages the insights of “weak experts” to analyze user opinions.

An automotive product case study demonstrates that evaluations based on weak expert insights offer managerial insights with a 99.4% improvement in timeliness over traditional expert analyses. Furthermore, in the few-shot sentiment analysis module, with only 10% of the sample, the precision loss is just 1.59%. In addition, the quantitative module of specialization weighting balances low-specialization expert opinions and boosts the weight of high-specialization weak expert views. This new framework offers a valuable tool for companies in product innovation and market strategy development.

This study introduces a novel approach to opinion mining by focusing on the underutilized insights of weak experts. It combines few-shot sentiment analysis with specialization weighting and AHP, offering a comprehensive and efficient tool for product evaluation and market analysis.

Evaluating emergency preparedness exercises is crucial for assessing enhanced knowledge, facilitating learning and implementing knowledge in organizations. The cognitive process of motivation for action is a precursor for action, coping behavior and individual learning. This study aims to focus on how guided evaluation of emergency preparedness exercises can enhance cognitive motivation and influence the mental readiness of exercise participants.

This is a conceptual paper with a model approach design. The main conceptual contribution is suggesting a model for guided evaluation in emergency preparedness exercises. We present a theoretical background for understanding the increase in motivation based on social cognitive learning theory. In particular, this study discusses how different evaluation steps contribute to enhanced motivation and learning for exercise participants.

Increased motivation and enhanced personal performance standards could be achieved through using processes that lead to self-efficacy in guided exercise evaluation. Specifically, sources of enhanced motivation, such as repeated coping experiences, self-regulation processes, mastery motivation and performance motivation, would proliferate the readiness of individual crisis managers and teams.

This article suggests an evaluation model for use in emergency preparedness exercises. This approach combines bottom-up and top-down processes for debriefing, reflection and feedback, both individually and in teams. This approach aims to enhance exercise participants’ motivation and utilize exercise evaluation for organizational learning.

The conceptual discussion leads to developing implications for evaluation practice, suggesting how to structure evaluation and why. This study is novel for its explanation of how to use evaluation in the learning process.

Objectively evaluating the fairness of the algorithm, exploring in specific scenarios combined with scenario characteristics and constructing the algorithm fairness evaluation index system in specific scenarios.

This paper selects marketing scenarios, and in accordance with the idea of “theory construction-scene feature extraction-enterprise practice,” summarizes the definition and standard of fairness, combs the application link process of marketing algorithms and establishes the fairness evaluation index system of marketing equity allocation algorithms. Taking simulated marketing data as an example, the fairness performance of marketing algorithms in some feature areas is measured, and the effectiveness of the evaluation system proposed in this paper is verified.

The study reached the following conclusions: (1) Different fairness evaluation criteria have different emphases, and may produce different results. Therefore, different fairness definitions and standards should be selected in different fields according to the characteristics of the scene. (2) The fairness of the marketing equity distribution algorithm can be measured from three aspects: marketing coverage, marketing intensity and marketing frequency. Specifically, for the fairness of coverage, two standards of equal opportunity and different misjudgment rates are selected, and the standard of group fairness is selected for intensity and frequency. (3) For different characteristic fields, different degrees of fairness restrictions should be imposed, and the interpretation of their calculation results and the means of subsequent intervention should also be different according to the marketing objectives and industry characteristics.

First of all, the fairness sensitivity of different feature fields is different, but this paper does not classify the importance of feature fields. In the future, we can build a classification table of sensitive attributes according to the importance of sensitive attributes to give different evaluation and protection priorities. Second, in this paper, only one set of marketing data simulation data is selected to measure the overall algorithm fairness, after which multiple sets of marketing campaigns can be measured and compared to reflect the long-term performance of marketing algorithm fairness. Third, this paper does not continue to explore interventions and measures to improve algorithmic fairness. Different feature fields should be subject to different degrees of fairness constraints, and therefore their subsequent interventions should be different, which needs to be continued to be explored in future research.

This paper combines the specific features of marketing scenarios and selects appropriate fairness evaluation criteria to build an index system for fairness evaluation of marketing algorithms, which provides a reference for assessing and managing the fairness of marketing algorithms.

Algorithm governance and algorithmic fairness are very important issues in the era of artificial intelligence, and the construction of the algorithmic fairness evaluation index system in marketing scenarios in this paper lays a safe foundation for the application of AI algorithms and technologies in marketing scenarios, provides tools and means of algorithm governance and empowers the promotion of safe, efficient and orderly development of algorithms.

In this paper, firstly, the standards of fairness are comprehensively sorted out, and the difference between different standards and evaluation focuses is clarified, and secondly, focusing on the marketing scenario, combined with its characteristics, key fairness evaluation links are put forward, and different standards are innovatively selected to evaluate the fairness in the process of applying marketing algorithms and to build the corresponding index system, which forms the systematic fairness evaluation tool of marketing algorithms.

This paper takes the manufacturing cluster supply chain as the research object and explores the evaluation and enhancement strategy of manufacturing cluster supply chain synergy. The purpose of this study was to (1) analyze the mechanism of manufacturing cluster supply chain synergy; (2) construct manufacturing cluster supply chain synergy evaluation model; (3) algorithm realization of manufacturing cluster supply chain synergy evaluation and (4) propose manufacturing cluster-based supply chain synergy enhancement strategy.

Breaking through the limitations of traditional manufacturing cluster supply chain synergy evaluation, we take horizontal synergy and vertical synergy as coupled synergy subsystems, use the complex system synergy model to explore the horizontal synergy between core enterprises and cluster enterprises and the vertical synergy of supply chain enterprises and use the coupling coordination model to construct the coupled synergy evaluation model of manufacturing cluster supply chain, which is an innovation of the evaluation perspective of previous cluster supply chain synergy and also an enrichment and supplementation of the evaluation methodology. This is not only the innovation of the evaluation perspective but also the enrichment and supplementation of the evaluation method.

Using Python software to conduct empirical analysis on the evaluation model, the research shows that the horizontal and vertical synergies of the manufacturing cluster supply chain interact with each other and jointly affect the coupling synergy. On this basis, targeted strategies are proposed to enhance the synergy of the manufacturing cluster supply chain.

This study takes manufacturers, suppliers and sellers in the three-level supply chain as the research object and does not consider the synergistic evaluation between distributors and consumers in the supply chain, which can be further explored in this direction in the future.

Advanced manufacturing clusters, as the main force of manufacturing development, and the synergistic development of supply chain are one of the important driving forces for the high-quality development of China’s manufacturing industry. As a new type of network organization coupling industrial clusters and supply chains, cluster supply chain is conducive not only to improving the competitiveness of cluster supply chains but also to upgrading cluster supply chains through horizontal synergy within the cluster and vertical synergy in the supply chain.

Research can help accelerate the transformation and upgrading of clustered supply chains in the manufacturing industry, promote high-quality development of the manufacturing industry and accelerate the rise of the global value chain position of the manufacturing industry.

(1) Innovation of research perspective. Starting from two perspectives of horizontal synergy and vertical synergy, we take a core enterprise in the cluster supply chain as the starting point, horizontally explore the main enterprises of the cluster as the research object of horizontal synergy, vertically explore the upstream and downstream enterprises of the supply chain as the research object of vertical synergy and explore the coupling synergy of cluster supply chain as two subsystems, which provides new perspectives of evaluation of the degree of synergy and synergy evaluation. (2) Innovation of research content. Nine manufacturing clusters are selected as research samples, and through data collection and model analysis, it is verified that the evaluation model and implementation algorithm designed in this paper have strong practicability, which not only provides methodological reference for the evaluation of manufacturing cluster-type supply chain synergy but also reduces the loss caused by the instability of clusters and supply chains and then provides a theoretical basis for improving the overall performance of cluster-type supply chains.

Product color names related to a consumption setting are commonly used in advertising to persuade. This study aims to use consumption imagery fluency as an underlying mechanism for assessing how such a naming tactic impacts product evaluation.

Three between-subjects experiments examine how product evaluation, in response to the use of color names containing consumption situation information, varies as a function of their accessibility (Study 1), and also test the role of a naming explanation (Study 2). How readily a consumer takes in consumption imagery is evaluated as a mediator. The studies further check if color attribute serves as a moderator of such color naming effect and that the naming factor contributes to consumption imagery fluency directly or indirectly alters such through their impact on comprehension fluency (Study 3).

Marketing products with color names related to the consumption setting is more effective than using generic names. Consumption imagery fluency mediates the results. This positive outcome is reduced when color names are less accessible. Fortunately, including an explanation to facilitate reasoning for product color names is helpful to reverse this disadvantage. The same patterns are not evident for highly accessible names. In addition, the effectiveness of consumption situation-related color names is restricted to the circumstance of color attribute as secondary, as opposed to primary. Furthermore, naming factors influence the ease of consumption of imagery whether or not facilitated by comprehension fluency.

This research provides evidence of consumers’ responses to product color naming that involves consumption situations and identifies consumption imagery fluency as a potential means for mediating the studied effect.

Naming a product color in consumption situation-related terms triggers consumption imagery, driving evaluation when color is the secondary attribute of a product.

This research contributes to understanding the influence of naming a product’s color in promotional communication and correlates to productive tactics for advertising messages.

This study aims to establish a robust evaluation framework for suppliers within the automotive supply chain, specifically in the stamping sector. The primary objectives are to elucidate the performance criteria of suppliers, identify indicators and scales for measuring these criteria and find the importance of the criteria.

The evaluation framework comprises a criteria hierarchy and indicators developed based on the evaluation criteria of major automotive manufacturers. Specific indicators and measurement scales are recommended for assessing suppliers. Importance weights for the criteria are assigned based on the input of nine experts using the Analytic Hierarchy Process (AHP). Finally, four sheet metal stamping tooling (SMST) suppliers are evaluated by four specialists using the proposed evaluation framework.

The study introduces a novel classification of criteria, encompassing financial and commercial perspectives, delivery capability, supplier facility and cultural approaches and business process necessities. The findings underscore the significance of financial and commercial stability in the selection of SMST suppliers, emphasizing their role in mitigating risks associated with disruptions, bankruptcies and unforeseen events. Additionally, several SMST evaluation factors identified in this study contribute to the development of resilience capabilities, highlighting the crucial importance of their inclusion and assessment in the proposed evaluation framework.

This research presents a comprehensive model for evaluating SMST suppliers, which tackles the multidisciplinary challenges within the automotive supply chain. Given the inadequacy or nonexistence of current SMTS selection models, this study bridges the gap by exploring potential and necessary criteria, alongside 116 specific indicators and measurement scales.