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This study addresses the problems of market exclusion and the digital divide in Nigeria by examining the smartphone innovation dynamics of Chinese companies, aiming to map consumer-centric adaptation and recommend an integrated framework for sustainable product development in emerging economies. The Disruptive Innovation Theory, Triple Helix Model, and frugal innovation principles were the theoretical frameworks used in the study, which employed a quantitative survey method based on data from 420 Nigerian respondents and 10 in-depth interviews with key industry stakeholders. Market disruption advantage ($\beta~$=~0.265) and product adaptation strategies ($\beta~$=~0.287) turned out to be substantial drivers of innovation performance which signified the need for consumer-oriented and localized product designs. The paper proposes an integration of Disruptive Innovation Theory with modern frugal innovation and responsible disruption frameworks, as it addresses both the sustainability imperatives and data sovereignty issues. The study goes beyond previous research by pointing out that localization strategies not only support digital inclusion but also increase the risk of data privacy in the contexts of Anglophone West Africa. The researchers argue that innovation in emerging countries, particularly in Nigeria, can only thrive if local contexts, informal networks, data sovereignty, and regulatory constraints are considered. The results are far-reaching and apply to both the government and the business sectors, highlighting the importance of tiered regulatory frameworks, data localization mandates, and stronger links between formal institutions and grassroots innovation networks. This study, which emphasizes the necessity of two-way knowledge flows and cultural immersion in product development, not only provides context-specific insights for Anglophone West Africa but also contributes to broader discussions of digital colonialism and technology governance.

This paper establishes a high-quality development (HQD) evaluation index system for the emergency industry to analyze its spatio-temporal evolution. The entropy weighting method is applied to comprehensively assess the development level of China's emergency industry during the observation period. Results indicate that the overall HQD index follows an upward trajectory, although it remains relatively low (rising from 0.211 to 0.255). The 2020 regional analysis highlights a hierarchical pattern in industrial development: coastal regions (0.321)\,$>$\,inland regions (0.246)\,$>$\,border regions (0.153). The overall Gini coefficient has remained stable at 0.22. Specifically, coastal areas (0.19) and inland areas (0.16) exhibit notable disparities, whereas border regions show minimal variation (0.10). The Gini coefficient between coastal and Border regions increased from 0.31 to 0.36, whereas that between coastal and inland areas declined after 2011, falling from 0.29 to 0.23. Regional variation, accounting for 59% of the total, emerges as the primary source of inequality. The Moran index identifies a significant spatial autocorrelation, indicating clear spatial self-correlation in the development levels of China's emergency industry. Kernel density analysis further illustrates that the national development level has steadily improved. However, the industry as a whole does not exhibit $\sigma$-convergence. The novelty of this study lies in constructing an HQD index system for China's emergency industry and employing multiple analytical methods to examine its spatiotemporal evolution.

Amidst growing concerns over research misconduct in academic institutions, this study examines the complex causal mechanisms that influence research integrity among university faculty. In this article, we explore how the interplay between personal attributes and institutional environments influences ethical research behavior, drawing on perspectives from both individual and organizational dimensions. We analyzed data from 109 university teachers across six key conditions, including factors related to individual endowment and the organizational environment, using fuzzy-set Qualitative Comparative Analysis (fsQCA). The results revealed that no single factor is a necessary condition for ensuring research integrity. Four distinct causal pathways were identified as sufficient to promote integrity, reflecting the principle of equifinality. These findings revealed the various combinations of internal and external factors that can yield similar positive outcomes. Based on the results, promoting research integrity requires a contextualized approach, where universities should tailor interventions and institutional policies to the specific characteristics and needs of their faculty members. This configurational understanding enhances theoretical insights into ethical behavior in academic settings and offers practical guidance for fostering a culture of integrity in higher education.

This book is dedicated to addressing the central challenge of making informed business decisions within an environment characterized by uncertainty, employing Multiple Criteria Decision-Making (MCDM) methodologies. Chapter 1 provides an overview of the related concepts of grey systems theory. Chapter 2 proposes evaluation criteria for five major themes, including human resource information systems and contractor selection problems. Chapters 3–6 present four improved grey hybrid weighting methods: the grey rank order centroid method, the grey regulatory focus theory method, the grey step-wise weight analysis ratio evaluation, and the grey point allocation weighting method. Chapters 710 introduce four improved hybrid grey evaluation methods: the grey weighted sum model, grey relational analysis, the grey regime method, and the grey integer linear programming method. Chapters 1–1 and 12 discuss additional grey decision-making methods, and conclusions are drawn along with future prospects.

Investing in urban scenic spots is a complex process that requires careful consideration of multiple criteria to ensure sustainability and efficiency. In the post-pandemic era, the uncertainty of future trends necessitates effective risk management and informed investment decisions. Revitalizing urban scenic spots while maintaining profitability, along with the construction of multi-purpose activity centers, requires a thorough evaluation of construction companies. This study addresses the selection of the most suitable contractor for constructing multi-purpose activity chain centers as a Multi-Criteria Decision-Making (MCDM) problem. We address the intricacies of contractor selection by integrating MCDM and system thinking approaches, emphasizing the alignment of investment strategies with broader urban development goals. First, a time delay was introduced between the first and second rounds of administering the weighting questionnaire to capture decision-makers' preferences for the evaluation criteria as System-2 thinking, then the Grey System-2 Thinking (GS2T) weighting method was proposed for group decision-making. Second, the Compromise Ranking of Alternatives from Distance to Ideal Solution (CRADIS) method was incorporated into the Grey Systems Theory (GST), resulting in the development of the Grey-CRADIS method, which was applied to rank seven contractors for constructing activity centers across four urban scenic spots. Using the proposed GS2T with the developed Grey-CRADIS method in conjunction with the decision-makers' preferences, Company-2 was found to be the best contractor for the construction project. Finally, classical MCDM methods such as theWeighted Sum Model (WSM) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were employed to confirm the top-ranking contractor.

Renovating old buildings is a strategic approach to resource optimization and sustainability. However, dormitory design decisions are often made by a limited panel of experts, which risks excluding student preferences-key to the design process. Expert assumptions about student needs can lead to biased outcomes, and attempts to gather student input may suffer from respondent bias and inconsistent engagement, introducing data noise. This paper presents the Grey Trimmed Preferences Selection Index (GTPSI) Multi-Criteria Decision Making (MCDM) method, an improved preference selection index MCDM method that integrates expert weights and refines student feedback by filtering outliers, using interval grey numbers to address uncertainty. Applied to dormitory renovation proposals, GTPSI provides a stable ranking framework, as confirmed by whitening sensitivity analysis, ensuring consistency across grey bounds. To further validate the selected alternative, results are cross-verified with TOPSIS and ELECTRE-III, reinforcing GTPSI's robustness in aligning renovation designs with actual student needs. The GTPSI method thus offers a comprehensive solution for integrating user-centered preferences into expert evaluations, promoting designs that better meet stakeholder expectations.

This article addresses the problem of subcontractor selection in an uncertain decision-making environment by proposing a new hybrid method and improving a classical multicriteria decision-making (MCDM) method. First, the proposed hybrid method combines subjective and objective weighting methods to estimate the weights of criteria that are represented as grey numbers. The subjective weighting method is the PA weighting method. The objective weighting method is the rank order centroid with slacks (ROCS) weighting method used to compensate for the limitation of the rank order centroid weighting method. Second, grey relational analysis (GRA) is improved by introducing both positive and negative reference (PNR) alternatives instead of a single reference alternative as in the classical GRA. Subsequently, the proposed hybrid grey-point allocation-ROCS weighting method and the GRA-PNR evaluation method are applied to select the most suitable subcontractor for the supply of heliostats for photothermal power station construction. Sensitivity analysis is conducted to verify the robustness of the results. Finally, the technique for order preferences by similarity to an ideal solution with grey values, simple additive weighting with grey relations, and additive ratio assessment with grey criteria scores is applied to validate the participation of the selected subcontractor in the project.

As China's economy becomes more robust, the government has emphasized the need to increase the civil aviation industry's rapid development and reduce civil aviation's technological gap compared to other advanced aircraft manufacturers. The use of the appropriate technologies in the aviation industry can help achieve the government's plan of creating more jobs and increasing its revenue through the civil aviation industry. However, emerging technologies' uncertainty and dynamic nature have led to significant challenges when these technologies are applied to the aviation manufacturing industry. This article applies the principles and methods of system dynamics based on the gradual-change factors of emerging technologies as identified through expert interviews to construct conceptual models depicting the gradual-change of emerging technologies in the aviation manufacturing field. Historical data from Shaanxi province were used to simulate and analyze the gradual development of emerging technologies. An analysis of the simulation results revealed that the rapid growth of competitive technologies in the growth process inhibits the gradual-change of emerging technologies. Also, increasing enterprise innovation capabilities, market demand expansion, and technology optimization significantly promote emerging technologies' development and application. Furthermore, the research result shows that competitive products and technologies influence the gradual development of emerging technologies. Finally, the results indicate that the civil aviation industry should optimize the performance and function of emerging technologies during the early development stage instead of at the market application stage.

Researchers have addressed uncertainty in multicriteria decision making from the perspective of the performance values of the alternatives, weighting of the evaluation criteria, and the evaluation methods. Still, they are yet to address the uncertainty caused by the normalization approach. In this paper, we show that different normalization methods, namely sum normalization, min--max normalization, vector normalization, and maximization normalization, can result in different rankings of the alternatives while the performance values and weights are unchanged. We applied the grey system theory to address the problem of uncertainty in this study from three aspects: alternative performance values measurement, criteria weighting, and decision matrix/table normalization within a period. The grey hybrid normalization method is proposed as the main contribution in this paper. Then, we present the rankings of 48 cities under uncertainty to decide the location of a branch office of a Chinese electric vehicle manufacturer as a practical example based on the grey entropy weighting method and grey relational analysis with positive and negative references (GRA-PNR) within the period from the year 2019 to 2021. The research results using this approach ranked New York City the best, with a stock market capitalization of economy validity as the top contributor in terms of weighting. Finally, we used simple additive weighting with grey value and the technique for order of preference by similarity to ideal solution with grey value methods to validate the study results.

$$We present an effective hybrid metaheuristic of integrating reinforcement learning with a tabu-search (RLTS) algorithm for solving the max--mean dispersion problem. The innovative element is to design using a knowledge strategy from the $\backslash$begin\textbraceleft document\textbraceright\$ Q \$\textbackslash end\textbraceleft document\textbraceright$$-learning mechanism to locate promising regions when the tabu search is stuck in a local optimum. Computational experiments on extensive benchmarks show that the RLTS performs much better than state-of-the-art algorithms in the literature. From a total of 100 benchmark instances, in 60 of them, which ranged from 500 to 1, 000, our proposed algorithm matched the currently best lower bounds for all instances. For the remaining 40 instances, the algorithm matched or outperformed. Furthermore, additional support was applied to present the effectiveness of the combined RL technique. The analysis sheds light on the effectiveness of the proposed RLTS algorithm.$$

This paper focuses on a new model called fuzzy exchange economy (FXE), which integrates fuzzy consumption, fuzzy initial endowment and the agent's fuzzy preference (vague attitude) in the fuzzy consumption set. Also, the existence of the fuzzy competitive equilibrium for the FXE is verified through a related pure exchange economy. We define a core-like concept (called weak fuzzy core) of the FXE and prove that any fuzzy competitive allocation belongs to the weak fuzzy core. The fuzzy replica economy, which is the \$r\$-fold repetition of the FXE, is considered. Finally, we show that the weak fuzzy core of the \$r\$-fold fuzzy replica economy, i. e., the set of all fuzzy allocations which cannot be blocked by any coalition of agents, converges to the set of fuzzy competitive allocations of the FXE as \$r\$ becomes large.

The purpose of this study was to identify the factors that influenced university choice in Vietnam. Survey data was collected from 167 students studying in Industrial University of HCM City, Vietnam. The research model was proposed from the study of university choice in the context of education in Vietnam. The reliability and validity of the scale were tested by Cronbach's Alpha, Average Variance Extracted (Pvc) and Composite Reliability (Pc). The analysis results of structural equation model (SEM) showed that the tested relationship between university choice and the four components of the University Choice included University Advertising, Student Expectation, Reference (Family and Friend) and University Reputation. Student Ability, University Characteristics and Enroll to university were not influenced University Choice of Student.

As the Chinese economy becomes stronger and stronger, there is increasing interest by some countries to adopt the Chinese approach to grow. The outstanding Chinese growth can be partly attributed to the education quality that is obtainable from the universities in China. The need to evaluate the reputation of Chinese universities is essential. In this paper, a hierarchical model for evaluating universities is proposed. Also, the Integral Linear Programming with Grey Possibility (ILP-GP) method is presented, which does not require the assumption of 0.5 for the grey distinguishing coefficient ( $\zeta$ = 0.5 ) in Grey Relational Analysis (GRA). In this paper, a numerical example for evaluating the reputation of five universities based on the sample data from 1,565 students in Shaanxi Province, China, is presented, and the most reputable university in this research is consistent with rankings in the literature.

As West Africa investments grow, the decision in which country to begin investment is of great importance to investors. The complexity of the criteria involved draws us to use a Multicriteria Decision-Making (MCDM) approach to address this problem. In this paper, we use grey numbers in representing ranges of data and propose Grey Weighted Sum Model (GWSM) for evaluating and ranking of alternatives. Sensitivity analysis is carried out considering wide ranges of uncertainties to verify the changes that can affect the results. The Gambia is ranked the best country in West Africa. The GWSM is highly recommended for long-term investors because GWSM considers the uncertainty of a business environment over a period of years. Finally, GWSM can be used in conjunction with various weighting techniques putting the preferences of the investors into consideration.