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The purpose of this study is to formulate a new class of vehicle routing problem with an objective to minimise the total cost of raw material collection and derive a new approach to solve optimization problems. This study can help to select the optimum number of suppliers based on cost.

To model the raw material vehicle routing problem, a mixed integer linear programming (MILP) problem is formulated. An interesting phenomenon added to the proposed problem is that there is no compulsion to visit all suppliers. To guarantee the demand of semiconductor industry, all visited suppliers should reach a given raw material capacity requirement. To solve the proposed model, the authors developed a novel hybrid approach that is a combination of block and edge recombination approaches. To avoid bias, the authors compare the results of the proposed methodology with other known approaches, such as genetic algorithms (GAs) and ant colony optimisation (ACO).

The findings indicate that the proposed model can be useful in industries, where multiple suppliers are used. The proposed hybrid approach provides a better sequence of suppliers compared to other heuristic techniques.

The data used in the proposed model is generated based on previous literature. The problem derives from the assumption that semiconductor industries use a variety of raw materials.

This study provides a new model and approach that can help practitioners and policymakers select suppliers based on their logistics costs.

This study provides two important contributions in the context of the supply chain. First, it provides a new variant of the vehicle routing problem in consideration of raw material collection; and second, it provides a new approach to solving optimisation problems.

The purpose of this paper is to explore a new grey relational analysis model to measure the coupling relationship between the indicators for the water environment status assessment. Meanwhile, the model deals with the problem that the changing of indicator order may result in the changing of the degree of grey relation.

The binary index submatrix of the sample matrix is given first. Then the product of the matrix and its own transpose is used to measure the characteristics of the index and the coupling relationship between the indicators. Thirdly, the grey relational coefficient is defined based on the matrix norm, and a grey coupling relational analysis model is proposed.

The paper provides a novel grey relational analysis model based on the norm of matrix. The properties, normalization, symmetry, relational order invariance to the multiplicative, are studied. The paper also shows that the model performs very well on the water environment status assessment in the eight cities along the Yangtze River.

The model in this paper has supplemented and improved the grey relational analysis theory for panel data.

This paper aims to explore the causal relationship of user-generated content (UGC) on trust in UGC (TUGC), destination image (DI) and tourist visit intention (VI) guided by the stimulus-organism-response (SOR) theory. This work further examined the mediating effect of TUGC and DI between UGC and VI.

Data were collected through online and personal-administered surveys and randomized sampling. This work employed partial least squares structural equation modeling (PLS-SEM) to test the proposed model empirically.

In line with the SOR Theory, this work found UGCs that induce positive emotions and connection to the users motivate VI rather than UGCs that are predominantly factual. Furthermore, UGCs are considered reliable, authentic and less biased than brand-generated content. The findings of this work contribute to the theoretical understanding of UGC to VI in a destination.

This work proposes that destination marketers prioritize UGC that evokes positive emotions and connections with users, as it is more effective in encouraging VI. Strategies such as incentivizing content creators, improving online presence and engaging influencers can maximize UGC. Enhancing online traffic quality, visibility and interaction and implementing content policies are crucial for UGC's effectiveness. Marketers should align destination products with tourists' interests and collaborate with influencers for affiliate marketing to increase tourist-generated UGC. Furthermore, improved connectivity encourages UGCs about the destination.

In tourism marketing, UGC has become a valuable information source for tourists in making informed travel decisions. UGC is a tourist-generated content that offers factual information and authentic experiences through images, videos or text posted through social media platforms. UGC is considered more reputable than travel firms and the mainstream media as an information source. Due to the limited works on UGC in the literature, the influence of UGC on tourists' VIs has remained unexplored at the time of writing. This work bridges this gap by empirically examining the impact of UGC on Gen Z tourists' VI guided by the SOR theory.

Innovation in financing processes, enabled by the advent of new technologies, has supported the development of alternative finance funding tools. In this context, the study analyses the growing importance of alternative finance instruments (such as equity crowdfunding, peer-to-peer (P2P) lending, venture capital, and others) in addressing the small and medioum enterprises' (SMEs) financing needs beyond traditional bank and market-based funding channels. By providing more flexible terms and faster approval times, these instruments are gradually reshaping the traditional bank-firm relationship.

To comprehensively understand this innovation shift in funding processes, the study employs a novel approach that merges three MCDA methods: Spherical Fuzzy Entropy, ARAS and TOPSIS. These methodologies allow for handling ambiguity and subjectivity in financial decision-making processes, examining the effects of multiple criteria, including interest rate, flexibility, accessibility, support, riskiness, and approval time, on the appeal of various financial alternatives.

The study’s results have significant theoretical and practical implications, supporting SMEs in carefully evaluate financing alternatives and enables banks to better identify the main “competitors” according to the “financial need” of the firm. Moreover, the rise of alternative finance, notably P2P lending, indicates a shift towards more efficient capital access, suggesting banks must innovate their funding channels to remain competitive, especially in offering flexible solutions for restructuring and high-risk scenarios.

The study advises top management that SMEs prefer traditional loans for their reliability and accessibility, necessitating banks to enhance transparency, innovate, and adopt digital solutions to meet evolving financing needs and improve customer satisfaction.

The study introduces a novel integration of Spherical Fuzzy TOPSIS, Entropy, and ARAS methodologies to face the complexities of financial decision-making for SME financing, addressing ambiguity and multiple criteria like interest rates, flexibility, and riskiness. It emphasizes the importance of traditional loans, the rising significance of alternative financing such as P2P lending, and the necessity for banks to innovate, thereby enriching the literature on bank-firm relationships and SME funding strategies.

The corona virus outbreak has affected the entrepreneurial ecosystem adversely. This in particular has impacted on females. This study aims to identify the factors affecting the entrepreneurial intention (EI) of females under post-COVID adverse conditions.

A total of 340 articles were screened applying the preferred reporting items for systematic reviews and meta-analyses method. The EI of individuals undertaking different professional courses from three top National Institute Ranking Framework (NIRF) government institutes were then analyzed. In the expert analysis, the nominal group technique (NGT) and analytic hierarchy process (AHP) were used to identify and rank the crucial factors. Subsequently, in the exploratory analysis, a 19-item questionnaire was framed. The data was analyzed using SmartPLS 3.

Resilience, entrepreneurial education, self-concept and self-efficacy, social influence and opportunity perception were identified as critical indicators. Resilience was identified as the most significant factor. The partial least square structural equation modeling (PLS-SEM) revealed that all the factors except social influence had significant effect on the EI of females.

This study focuses primarily on factors affecting females in India. As ecosystems and support vary by region and country, the authors suggest that this study be replicated in different regions/countries in the future.

The potential entrepreneurs can use this study's reference to identify the abilities they need. The government and academic institutions can have skill/training programs to enhance the effect of important factors identified in the study.

While there is growing research of entrepreneurship and entrepreneurial marketing post-pandemic, there are a lack of Indian studies and female entrepreneurship studies.

Conceptual and empirical research over the past 20 years has moved the social media (SM) literature beyond the embryotic stage to a well-developed academic discipline. As the lead article in the special issue in the Journal of Research in Interactive Marketing on Cutting-Edge Research in Social Media and Interactive Marketing, this review and agenda article has two key goals: (1) to review key SM and interactive marketing research over the past three years and (2) to identify the next wave of high priority challenges and research opportunities.

Given the “cutting-edge” research focus of the special issue, this review and research agenda paper focused on articles published in 25 key marketing journals between January 2021 and March 2024. Initially, the search request was for articles with “social media, social selling, social commerce” located in the article title, author-selected key words and journal-selected keywords. Later, we conducted searches based on terminology from articles presented in the final review. In total, over 1,000 articles were reviewed across the 25 journals, plus additional ones that were cited in those journals that were not on the initial list.

Our review uncovered eight key content areas: (1) data sources, methodology and scale development; (2) emergent SM technologies; (3) artificial intelligence; (4) virtual reality; (5) sales and sales management; (6) consumer welfare; (7) influencer marketing; and (8) social commerce. Table I provides a summer of key articles and research findings for each of the content areas.

As a literature review and research agenda article, this paper is one of the most extensive to date on SM marketing, and particularly with regard to emergent research over the past three years. Recommendations for future research are integrated through the paper and summarized in Figure 2.

Consumer welfare is one of the eight emergent content areas uncovered in the literature review. Specific focus is on SM privacy, misinformation, mental health and misbehavior.

This study aims to investigate the causal complexity of ECF investors’ peer effect through two different paths of structural social influence.

Using the fuzzy-set qualitative comparative analysis (fsQCA) approach, we employ 157 samples from a Chinese ECF source to explore how peer-effect are caused by both informational and normative mechanisms.

The findings suggests that there are multiple configurations could lead to ECF investors’ high level peer-effect through both informational and normative mechanisms, and the informational mechanism' role depends on the normative mechanism, while the normative mechanism could lead to peer-effect independently.

The findings enrich the literature on ECF investors’ behaviors by revealing the diverse configurations resulting in investors’ peer-effect and shedding new light on investigating the decision-making driven by information asymmetry and relationship settings for individuals at a disadvantage.

This is the first study that investigates the multiple-driven of ECF investors’ decision-making and the importance of mutual norms in individuals' decision-making by complex network analysis approach and qualitative comparative analysis from the perspective of complexity. The results reveal the complexity of investors’ decision-making in ECF.

This paper aims to define the efficiency achieved by urban transport companies in Spain concerning the resources they use, considering the type of management used for implementation, public-private, and size.

This study consisted of an analysis of the efficiency of 229 public-private urban transport operators during the period 2012–2021 using Data Envelopment Analysis, the Malmquist Index and inference estimators to determine productivity, efficiency change into Pure Technical Efficiency Change (PTECH), and scale efficiency change.

Based on the efficiency analysis, the authors concluded that of the 229 companies studied, more than 35 were inefficient in all analysed periods. Considering the sample used, direct management is considered significantly more efficient. It cannot be concluded that the size of these companies influences their efficiency, as the data show unequal development behaviours in the studied years.

This study provides arguments on whether there is a significant difference between the two types of management in the urban transport sector. It also includes firm size as a study variable, which has not been previously considered in other studies related to urban transport efficiency. Efficiency should be a crucial factor in determining funding allocation in this sector, as it encourages operators to optimize and improve their services.

This study aims to assess the digital literacy competencies among students in higher learning institutions in Kazakhstan.

A survey design was used. Simple random sampling was used to draw sample. Primary data were collected using Web/online questionnaires (Google Form). A total of 370 online questionnaires were disseminated to the respondents to their email addresses. Quantitative data collected were analyzed using MS Excel 2010. Thus, descriptive statistics were computed and the results were further presented in tables, charts and figures.

Results reveal that students are very competent in using digital technologies to communicate and share their educational digital contents, whereas they indicate moderate competence and incompetence in other essential digital literacy skills crucial for their academic pursuits. Furthermore, this study revealed that students frequently use digital technologies for educational purposes, with statistical analysis [t(381) = 4.562, p < 0.00001, two-tailed] indicating a significant difference between the extent and purpose of their digital usage. Moreover, findings identified health issues, technical issues and the constantly changing of hardware and software as primary challenges faced students when engaging with digital technologies.

This study is new in the context of Kazakhstan analyzing the digital literacy competencies among students, with a particular focus on elucidating the five fundamental facets of such competencies. This study therefore, recommends the implementation of comprehensive and consistent training programs aimed at imparting necessary digital literacy skills to students.