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Previous literature reviews mainly focus on green supply chain, however, there is surprisingly little effort made in the systematic literature review to focus on a specific function of green supply chain, i.e. green procurement (GP). Regarding research methodology, most reviews are qualitative and inductive generalizations. Quantitative methods such as bibliometrics have started to be applied in recent years. This paper responds to this trend by counting the largest amount of literature with 238 articles in the last 24 years from 2000 to 2023 to visually analyze different theoretical perspectives and research topics into a comprehensive framework and identify future research directions and opportunities in the GP field.

Based on CiteSpace and in-depth content analysis, this paper attempts to visually analyze 238 valid papers to identify key literature and analyze the evolution of research hot spots and frontier development trends.

Combined with the visualization results and the content analysis of key references, we identify key literature and examine the evolution of research hotspots and frontier development trends. The bibliometric analysis mainly includes knowledge mapping to identify key themes, co-occurrence and clustering analysis of keywords, cooperation networks in researchers' countries. An overall GP research model is presented and our research suggests future avenues for GP research, such as low carbon, digitalization, servitization and ecosystem perspectives.

Firstly, in terms of time and volume of literature, we have counted the most comprehensive and up-to-date literature in the field of GP research, which is conducive to further expanding and enriching GP research. Secondly, this study clearly describes the theoretical evolution of GP research from bilateral and multilateral to ecosystem perspectives, and constructs a new and comprehensive research framework of “driver-practice-outcome”. Thirdly, based on the bibliometric analysis results, our research suggests future avenues for GP research, such as low-carbon, digitalization, servitization, and ecosystem perspectives, which can contribute to expanding our understanding of GP development.

This study aims to conduct a systematic literature review on mobile application experience, recognizing its growing importance in research and practical applications. The purpose is to address the factors influencing customer mobile application experience in this dynamic environment.

The study uses the theories, context, characteristics, methodology (TCCM) review framework. This research meticulously analyzes 42 articles published between 2015 and 2023. The selected articles are sourced from prominent journals in widely recognized databases, including Scopus and the Australian Business Deans Council.

The examination of the pertinent literature culminates in the formulation of the TCCM framework, shedding light on the antecedents, mediators, moderators and outcomes, related to the mobile application experience.

This study pioneers a unified framework for mobile application experience, shedding light on unexplored territories and shaping the trajectory of future mobile application experience investigations. Its emphasis on a strong academic foundation enriches technological marketing literature, offering managers actionable insights aligned with TCCM. This study marks a pivotal contribution, bridging theoretical advancements with practical strategies for the dynamic landscape of mobile applications experience.

This research uncovers overlooked areas and proposes discerning research directions to advance the understanding of mobile applications experience. It addresses a crucial gap in current knowledge and motivates further investigation into the intricate dynamics of mobile application experience.

This study aims to investigate how source attractiveness (including platform credibility, product appeal and streamer attractiveness) and information quality impact viewers’ cognition and flow state. Additionally, it examines how these factors influence the development of consumer attitudes and behaviors toward livestreamed tourism shopping, as well as the moderating roles of perceived risk and personal characteristics.

A sequential mixed-methods research design was used. In addition to a literature review, 15 interviews were conducted to identify measurement items for the subsequent questionnaire survey. Sample 1 (n = 209) was used to refine these measurement items, whereas Sample 2 (n = 227) was used to evaluate the measurement model and test the proposed hypotheses.

Findings reveal that source attractiveness (streamer attractiveness, tourism product attractiveness and platform credibility) and information quality significantly influence customers’ behavior formation, with cognition and flow state acting as mediators. Findings further confirm the moderating effect of perceived risk in a livestreamed shopping environment.

The findings provide new insights into how consumers select livestreamed shopping platforms. As viewers assess the credibility and trustworthiness of each component to form their perception of the overall platform’s credibility, companies should market their products through credible platforms, studios and stores with extensive reach. It is also critical to collaborate with streamers who are sincere, trustworthy, knowledgeable and professional. Since perceived risk lowers consumer behavioral intentions, live streamers, platforms and merchants should offer convincing and credible arguments to alleviate viewers’ perceived risks.

This study advances the literature on livestreamed shopping by broadening the conceptualization of source attractiveness to include three dimensions: streamer attractiveness, product attractiveness and platform attractiveness. Furthermore, it differentiates itself from existing studies by integrating and adopting multidimensional measurements of cognition (perceived usefulness and ease of use) and flow state (control, enjoyment, curiosity and concentration).

本研究旨在探讨信息源吸引力(平台可信度、产品吸引力和主播吸引力)和信息质量如何影响旅游购物直播观众的认知和心流体验。本研究进一步探讨了这些因素如何影响旅游直播购物消费者的态度与行为。本研究还检验了感知风险和个人特征的调节作用。

采用顺序混合研究方法。基于文献和15次深度访谈确定了问卷调查中使用的测量项目。样本1 (n= 209)用于净化测量项目。样本2 (n= 227)用于评估测量模型并验证假设。

信息源吸引力(主播吸引力、旅游产品吸引力和平台可信度)和信息质量显著影响消费者行为, 其中认知和心流起中介作用。研究结果进一步证实了感知风险的调节作用。

研究结果为消费者如何选择直播购物平台提供了新的见解。由于观众对每个组成部分的可信度进行评估, 从而形成他们对整个平台可信度的看法, 因此公司应该通过可靠的平台、直播间和具有广泛影响力的店铺来营销他们的产品。与真诚、值得信赖、知识渊博、专业的主播合作也至关重要。由于感知风险会降低消费者的行为意愿, 因此主播、平台和商家应该提供令人信服和可信的论据, 以减轻观众的感知风险。

本研究将信息源吸引力的概念扩展到三个维度：主播吸引力、产品吸引力和平台可信度, 从而丰富了直播购物相关研究。通过整合并采用认知（感知有用性和感知易用性）和心流体验（控制、愉悦、好奇和沉浸）的多维测量, 本研究进一步区别于现有研究。

Este estudio investiga cómo el atractivo de la fuente (incluida la credibilidad de la plataforma, el atractivo del producto y el atractivo del emisor) y la calidad de la información influyen en la cognición y el estado de flujo de los espectadores. Además, examina cómo influyen estos factores en el desarrollo de las actitudes y los comportamientos de los consumidores hacia las compras turísticas retransmitidas en directo, así como los papeles moderadores del riesgo percibido y las características personales.

Se empleó un método de investigación mixto secuencial. Además de una revisión bibliográfica, se realizaron 15 entrevistas para identificar los ítems de medición para la posterior encuesta por cuestionario. La muestra 1 (n = 209) se utilizó para refinar estos ítems de medición, mientras que la muestra 2 (n = 227) se utilizó para evaluar el modelo de medición y probar las hipótesis propuestas.

Resultados revelan que el atractivo de la fuente (atractivo del emisor, atractivo del producto turístico y credibilidad de la plataforma) y la calidad de la información influyen significativamente en la formación del comportamiento de los clientes, con la cognición y el estado de flujo actuando como mediadores. Resultados confirman además el efecto moderador del riesgo percibido en el entorno de las compras en directo.

Los Resultados aportan nuevos conocimientos sobre cómo seleccionan los consumidores las plataformas de compras en directo. Dado que los espectadores evalúan la credibilidad y la fiabilidad de cada componente para formarse su percepción de la credibilidad global de la plataforma, las empresas deberían comercializar sus productos a través de plataformas, estudios y tiendas creíbles con un amplio alcance. También es fundamental colaborar con streamers que sean sinceros, dignos de confianza, informados y profesionales. Dado que el riesgo percibido disminuye las intenciones de comportamiento de los consumidores, los streamers en directo, las plataformas y los comerciantes deben ofrecer argumentos convincentes y creíbles para aliviar los riesgos percibidos por los espectadores.

Este estudio hace avanzar la literatura sobre las compras en directo ampliando la conceptualización del atractivo de la fuente para incluir tres dimensiones: el atractivo del streamer, el atractivo del producto y el atractivo de la plataforma. Además, se diferencia de los estudios existentes al integrar y adoptar mediciones multidimensionales de la cognición (utilidad percibida y facilidad de uso) y el estado de flujo (control, disfrute, curiosidad y concentración).

This study aims to provide a timely review of hospitality and tourism live streaming (HTLS) research, aiming to understand the intellectual foundation in the past and identify opportunities for future research.

This study collected 56 papers from journals in the Social Science Citation Index database or the Australian Business Deans Council journal quality list and adopted a hybrid systematic literature review combining bibliometric analysis and the theory-context-characteristics-method framework-based approach. Additionally, a cross-tabulation analysis was conducted to compare the research on two specific forms of HTLS – tourism e-commerce live streaming (TEcLS) and travel live streaming.

The study found that the current research lacks in-depth theoretical insights, focuses on China as the national context and viewers as the research subject, mainly uses online surveys and lacks first-order knowledge. Moreover, it identified five research themes, including the impact of HTLS on viewer behavior, purchase behavior in HTLS and introduction of HTLS, within which eight categories of research constructs, such as viewer-related, streamer-related and relationship-related, are applied.

In terms of research, the study reveals various gaps in the existing literature and provides potential research directions to advance the field. As for practice, it offers valuable strategies for practitioners to optimize their marketing efforts using HTLS.

This study provides an up-to-date review of the HTLS field through a systematic and reproducible method. It offers critical discussions and suggestions for academic research and industry practices.

As the current Coronavirus 2019 pandemic eases, international tourism, which was greatly affected by the outbreak, is gradually recovering. The attraction of countries to overseas tourists is related to their overall performance in the pandemic. This research integrates the data of vaccination of different countries, border control policy and holidays to explore their differential impacts on the overseas tourists’ intention during the pandemic. This is crucial for destinations to built their tourism resilience. It will also help countries and industry organizations to promote their own destinations to foreign tourism enterprises.

This study proposes an analysis based on panel data for ten countries over 1,388 days. The coefficient of variation is used to measure monthly differences of Chinese tourists’ intention to visit overseas country destinations.

Results show that, for tourist intention of going abroad: border control of the destination country has a significant negative impact; daily new cases in the destination country have a significant negative impact; domestic daily new cases have a significant positive impact; holidays have significant negative impact; daily vaccination of the destination countries has significant positive impact; and domestic daily vaccination have negative significant impact.

First, there is a large uncertainty in studying consumers’ willingness to travel abroad in this particular period because of unnecessary travel abroad caused by the control of the epidemic. Second, there are limitations in studying only Chinese tourists, and future research should be geared toward a broader range of research pairs.

First, from the government perspective, a humane response can earn the respect and trust of tourists. Second, for tourism industry, to encourage the public take vaccine would be beneficial for both the tourism destination and foreign tourism companies. The same effect can be achieved by helping tourists who are troubled by border control.

First, this research provides suggestions for the government and the tourism industry to deal with such a crisis in the future. Second, this study found that vaccination has a direct impact on tourism. This provides a basis for improving people’s willingness to vaccinate. Thirdly, this study proves suggestion for the destinations to build tourism resilience.

This study analyzes the unique control measures and vaccination in different countries during the pandemic, then provides suggestions for the tourism industry to prepare for the upcoming postpandemic tourism recovery. This study is valuable for improving the economic resilience of tourism destinations. Additionally, it helps to analyze the advantages and disadvantages of different restrain policies around the world.

This paper aims to study the joint decision making of advance selling and service cancelation for service provides with limited capacity when consumers are overconfident.

For the case in which consumers encounter uncertainties about product valuation and consumption states in the advance period and are overconfident about the probability of a good state, we study how the service provider chooses the optimal sales strategy among the non-advance selling strategy, the advance selling and disallowing cancelation strategy, and the advance selling and allowing cancelation strategy. We also discuss how overconfidence influences the service provider’s decision making.

The results show that when service capacity is sufficient, the service provider should adopt advance selling and disallow cancelation; when service capacity is insufficient, the service provider should still implement advance selling but allow cancelation; and when service capacity is extremely insufficient, the service provider should offer spot sales. Moreover, overconfidence weakens the necessity to allow cancelation under sufficient service capacity and enhances it under insufficient service capacity but is always advantageous to advance selling.

The obtained results provide managerial insights for service providers to make advance selling decisions.

This paper is among the first to explore the effect of consumers’ overconfidence on the joint decision of advance selling and service cancelation under capacity constraints.

This paper aims to conduct a systematic literature review on the fintech services and financial inclusion of the developing nations that particularly focuses on lower middle-income group nations (LMIGN) and upper middle-income group nations (UMIGN) to highlight the research areas that have not received attention and present opportunities for future research.

This paper adopts a systematic approach to examine 65 research articles published from 2016 to 2021, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

The study identifies research gaps in two key themes: backward and outward linkages. In backward linkages, the literature on UMIGN should pay attention to the behavioural patterns associated with lending, investment and market provision-related fintech services. Further research is needed to understand the relationship between fintech services on the usage and quality dimension of financial inclusion in both LMIGN and UMIGN. For outward linkages, future research work should explore the role of fintech and financial inclusion in the development of LMIGN. This study provides valuable insights and guides future research directions by comprehensively mapping the existing studies.

This study does not use quantitative tools, such as meta and bibliometric analysis, to validate the findings.

This research paper offers new perspectives that introduce a novel framework for analysing literature on fintech, financial inclusion and its impact on the overall development of UMIGN and LMIGN.

This paper aims to demonstrate that, in line with the emerging trend of multifunctional yarn development, cotton yarn can effectively harness renewable solar energy to achieve photothermal conversion and thermochromism. This innovation not only maintains the comfort associated with natural fiber cotton yarn but also enhances its ultraviolet (UV) light resistance.

In this work, 4% zirconium carbide (ZrC) and thermochromic powder were adhered to cotton yarn through polyurethane (PU) by sizing coating method. After sizing, the two cotton yarns are twisted by ring spinning to obtain composite yarns with photothermal conversion and thermochromic functions.

The yarn obtained by cotton/6%PU/8% thermochromic dye single yarn and cotton/6%PU/4% ZrC single yarn composite is the best match. After 5 min of infrared light, the temperature of the composite yarn rose to the maximum, increasing by 36.1°C. The ΔE* value before and after irradiation of infrared lamp is 26.565, which proves that the thermochromic function is good. The yarn dryness unevenness was significantly reduced by 27.2%. The composite yarn has a UPF value of up to 89.22, and its performance characteristics remain stable after 100 minutes of washing.

The composite yarn’s photothermal conversion and thermochromism functions are mutually reinforcing. Using sunlight can simultaneously achieve heating and discoloration effects without consuming additional energy. The cotton yarn used in this application is versatile, and suitable for a wide range of uses including clothing, temperature visualization detection and other scenarios.

In the era of artificial intelligence (AI), algorithms have gained unprecedented importance. Scientific studies have shown that algorithms are frequently mentioned in papers, making mention frequency a classical indicator of their popularity and influence. However, contemporary methods for evaluating influence tend to focus solely on individual algorithms, disregarding the collective impact resulting from the interconnectedness of these algorithms, which can provide a new way to reveal their roles and importance within algorithm clusters. This paper aims to build the co-occurrence network of algorithms in the natural language processing field based on the full-text content of academic papers and analyze the academic influence of algorithms in the group based on the features of the network.

We use deep learning models to extract algorithm entities from articles and construct the whole, cumulative and annual co-occurrence networks. We first analyze the characteristics of algorithm networks and then use various centrality metrics to obtain the score and ranking of group influence for each algorithm in the whole domain and each year. Finally, we analyze the influence evolution of different representative algorithms.

The results indicate that algorithm networks also have the characteristics of complex networks, with tight connections between nodes developing over approximately four decades. For different algorithms, algorithms that are classic, high-performing and appear at the junctions of different eras can possess high popularity, control, central position and balanced influence in the network. As an algorithm gradually diminishes its sway within the group, it typically loses its core position first, followed by a dwindling association with other algorithms.

To the best of the authors’ knowledge, this paper is the first large-scale analysis of algorithm networks. The extensive temporal coverage, spanning over four decades of academic publications, ensures the depth and integrity of the network. Our results serve as a cornerstone for constructing multifaceted networks interlinking algorithms, scholars and tasks, facilitating future exploration of their scientific roles and semantic relations.

This paper aims to develop a demand scale from the perspective of scientific data providers and to analyze their demands, offering references for research and practice in scientific data sharing.

The initial scale was designed based on a literature review. A total of 479 valid responses from data providers were collected via questionnaires. Exploratory and confirmatory factor analyses were conducted using SPSS21.0 and AMOS23.0, followed by a discussion on practical implications.

Providers exhibit significant demands in all dimensions, with data security being the most urgent, followed by data management platforms and self-value realization. Additionally, the prioritization of providers’ demands varies according to their intentions to share.

The study developed a scale of providers’ demands in scientific data sharing that comprises 21 items across five dimensions: data security, data management platform, self-value realization, social and benefits return and analyzed the demand degree of providers for the above items. Finally, the paper proposes strategies from stakeholders’ perspectives to meet providers’ demands and facilitate scientific data sharing.