Search results

The purpose of this research is to investigate the effects of market pressure on organisational innovation performance through commitment and resource to innovate and manager innovation capability.

A quantitative study was conducted with 273 participants working in different organisations. These participants were drawn from the LinkedIn network of one of the researchers. The data were collected using a survey questionnaire uploaded onto www.surveymonkey.com. The data were analysed using SPSS and AMOS, and structural equation modelling techniques were used to test the hypotheses.

We found that market pressure has a positive effect on both commitment to innovate and resource to innovate. In turn, both commitment to innovate and resource to innovate influence manager innovation capability. We also found that manager innovation capability positively affects organisational innovation performance. Furthermore, manager innovation capability is a mediator in the relationship between commitment to innovate and organisational innovation performance as well as in the relationship between resource to innovate and organisational innovation performance. Finally, the relationship between manager innovation capability and organisational innovation performance is moderated by both extrinsic and intrinsic motivations to innovate.

Our study provides empirical evidence of the roles of commitment to innovate, resource to innovate and manager innovation capability in enhancing the innovation performance of organisations. Therefore, organisations should show their commitment to innovate, provide resources to innovate, develop managers’ capabilities to innovate and use a mix of intrinsic and extrinsic motivators to boost their innovation performance.

This study offers new insights into the dynamics of how market pressure leads to innovation within organisations.

This study aims to develop a novel diagnostic methodology for implementing ISO13485:2016 and test its applicability to improve quality management systems (QMS) in the medical devices industry context.

First, a literature review on the topic was conducted. Second, insights gained from the literature and expert interviews were employed to develop the new maturity assessment methodology. Subsequently, the methodology was tested on a medical device manufacturer. Next, based on the evaluation of the intervention, actions were recommended to improve the QMS.

Research findings have developed a maturity assessment methodology comprising 52 certifiable requirements structured into four macro-requirements derived from ISO 13485:2016. Findings show that the methodology is valuable for aiding QMS implementation, and the diagnosed maturity levels corresponded with the company’s empirical perceptions of the requirement’s maturity.

Empirical evidence validates the significance and practical utility of the proposed methodology, as evidenced by the company’s attainment of FDA (US Food and Drug Administration) approval after the intervention. Findings suggest that the methodology could be replicated within the medical products industry or adapted to assess other QMS, leveraging the organizational alignment with the international regulations of the sector and the ISO 9000 requirements.

The developed methodology fills existing gaps in both literature and practice within the medical devices industry, providing a valuable contribution by addressing the limited research on diagnostic methodologies designed for ISO 13485:2016 implementation. The article assists medical device enterprises in addressing QMS maturity levels as a metric for evaluating QMS requirements, which is an underexplored avenue in existing QMS evaluation approaches.

The COVID-19 epidemic caused significant disruptions to numerous supply chains. In order to enhance the resilience of supply chains, Collaboration (CO), Information Alignment (IA), and Big Data Analytics Capability (BDAC) have emerged as contemporary strategies within the humanitarian context. This study was conducted to explore the mechanism via which the effect of BDAC, IA and CO on Humanitarian Supply Chain Resilience (HSCR) in the humanitarian space could be optimized through Organizational Flexibility (OF).

A model of six hypotheses was developed based on the Organizational Information Processing Theory (OIPT). Data from 127 supply chain managers in humanitarian organizations were used to test the hypotheses. The analysis employed both descriptive and inferential statistics using SPSS version 26 and Smart-PLS version 3.

The study revealed that BDAC, IA, and CO individually influence supply chain resilience in the humanitarian setting while OF did not moderate the relationship between BDAC, IA, CO, and HSCR.

It is essential that humanitarian stakeholders prioritize factors that could increase supply chain resilience by employing contemporary BDA technologies, effective information flow, and collaborative strategies to set up a robust humanitarian SC system that could help lessen the impact of disasters.

This presents interesting insights that advance theoretical debates on how CO, IA, and BDAC under varying levels of OF could influence SCR in the humanitarian context. The paper further offers some useful guidance to managers in relief organizations who desire to build resilient supply chains by leveraging BDAC, collaboration and information alignment. Finally, the paper may also provoke future humanitarian scholars to replicate the study using different approaches.

This article problematizes the concept of freedom rooted in liberalism, examining the detention of historian Ilan Pappe by the Federal Bureau of Investigation (FBI) at Detroit Airport in the United States as an emblematic case study.

The research adopts a methodological triangulation approach, based on an analysis that combines data about the event and theories about the concept of freedom, problematizing authors who focused on the relationship between the individual and society in a liberal context, where individualism serves as the basis for specific conceptions of social relations.

Through the use of authors such as John Stuart Mill and John Locke, as well as the contributions of authors like Norbert Elias, it is argued that true freedom is relational, rooted in social interdependencies and the social construction of an individuality that is not individualistic but intrinsically linked to collective aspects.

Pappe’s case illustrates the tensions between individual freedom and collective interests, highlighting the need to reassess freedom of expression in complex political and social contexts.

This article proposes a more inclusive and interconnected view of human freedom, where individual and collective interests are negotiated within a dynamic web of social relations.

The purpose of this paper is to present an integrated data-driven framework for processing and analyzing large-scale vehicle maintenance records to get more comprehensive understanding on vehicle quality.

We propose a framework for vehicle quality analysis based on maintenance record mining and Bayesian Network. It includes the development of a comprehensive dictionary for efficient classification of maintenance items, and the establishment of a Bayesian Network model for vehicle quality evaluation. The vehicle design parameters, price and performance of functional systems are modeled as node variables in the Bayesian Network. Bayesian Network reasoning is then used to analyze the influence of these nodes on vehicle quality and their respective importance.

A case study using the maintenance records of 74 sport utility vehicle (SUV) models is presented to demonstrate the validity of the proposed framework. Our results reveal that factors such as vehicle size, chassis issues and engine displacement, can affect the chance of vehicle failures and accidents. The influence of factors such as price and performance of engine and chassis show explicit regional differences.

Previous research usually focuses on limited maintenance records from a single vehicle producer, while our proposed framework enables efficient and systematic processing of larger-scale maintenance records for vehicle quality analysis, which can support auto companies, consumers and regulators to make better decisions in purchase choice-making, vehicle design and market regulation.

This paper aims to systematically review the application of artificial intelligence (AI) in the tourism industry. By integrating human–computer interaction, machine learning, big data and other relevant technologies, the study establishes a comprehensive research framework that explores the systematic connections between AI and various facets of tourism.

This paper conducts a keyword co-occurrence analysis of 4,048 articles related to AI in tourism. The analysis identifies and classifies dominant topics, which are further refined through thematic literature review and manual coding for detailed discussion.

The analysis reveals five main topics: AI’s impact on tourist experience, AI in tourism marketing and prediction, AI in destination management, AI’s role in tourism enterprises and AI integration in strategic and regulatory framework. Each topic is reviewed to construct an integrated discussion that maps the current landscape and suggests directions for future research.

This paper transcends the fragmented discourse commonly found in the literature by establishing a unified framework that not only enhances understanding of the existing methodologies, theories and applications of AI in tourism but also identifies critical areas for breakthroughs, aiming to inspire a more humane and sustainable integration of AI in the tourism industry.

本文旨在系统回顾人工智能（AI）在旅游业中的应用。通过整合人机交互、机器学习、大数据和其他相关技术, 本研究建立了一个全面的研究框架, 探索人工智能与旅游业各方面之间的系统联系。

本文对4048篇与旅游业人工智能相关的文章进行了关键词共现分析。分析确定了主要议题并对其进行了分类, 然后通过主题文献梳理和手动编码对其进行了进一步完善, 以便进行详细讨论。

分析揭示了五个主要主题：人工智能与旅游体验、人工智能与旅游营销和预测、人工智能与目的地管理、人工智能与旅游企业, 以及人工智能在战略和监管框架中的整合。每个主题都进行了回顾, 以构建一个综合讨论, 勾勒出当前的研究格局, 并提出了未来的研究方向。

研究力图突破目前关于旅游与人工智能的碎片化讨论, 建立了一个统一的框架, 旨在加强对旅游业中人工智能现有方法、理论和应用的理解, 还点明了需要突破的关键领域, 以助力旅游业与人工智能共同创造更加人性化和可持续发展的前景。

Este artículo pretende revisar sistemáticamente la aplicación de la inteligencia artificial (IA) en el sector turístico. Mediante la integración de la interacción humano-ordenador, el aprendizaje automático, big data y otras tecnologías relevantes, el estudio establece un marco de investigación exhaustivo que explora las conexiones sistemáticas entre la IA y diversas facetas del turismo.

Este trabajo realiza un análisis de co-ocurrencia de palabras clave de 4.048 artículos relacionados con la IA en el turismo. El análisis identifica y clasifica los temas dominantes, sobre los que se profundiza mediante una revisión temática de la literatura y una codificación manual para su discusión detallada.

El análisis presenta cinco temas principales: El impacto de la IA en la experiencia turística, la IA en el marketing y la predicción turística, la IA en la gestión de destinos, el papel de la IA en las empresas turísticas y la integración de la IA en el marco estratégico y normativo. Cada tema se revisa para construir un debate integrado que trace el panorama actual y sugiera direcciones para futuras investigaciones.

Este artículo expande el análisis fragmentado que suele encontrarse en la bibliografía al establecer un marco unificado que no sólo mejora la comprensión de las metodologías, teorías y aplicaciones existentes de la IA en el turismo, sino que también identifica las áreas críticas para los avances, con el objetivo de inspirar una integración más humana y sostenible de la IA en la industria turística.

This study was inspired by research of strategists on strategic innovation (SI), aiming to provide a unique model to enhance the digitization of small and medium-sized enterprises (SMEs) in Bangladesh to fill the gap toward a digital economy.

A survey was used to collect data from 180 SMEs in the manufacturing industry for this research. The results indicate that strategic innovativeness (SI), human capital (HC), infrastructure and technology and resistance to change significantly influence the digitalization in Bangladesh SMEs.

The link between SI and SMEs' digitalization in Bangladesh is mediated by HC. The results show that HC plays a big role in the connection between SI and the digitalization of SMEs. This study may be valuable for SMEs managers, researchers and policymakers in Bangladesh and other developing nations, who want to learn more about SI in adopting digitalization.

The specialized knowledge and abilities of strategists allow them to establish parallels between the past and present, enabling them to make a sustained forecast about the digital economy. This study encourages small and medium-sized businesses to develop their SI and advance their HC, which could further deject resistance to change toward enhancing and adopting digitalization in SMEs sectors.

The purpose of this paper is to compile a comprehensive status report on pipes/piping networks across different industrial sectors, along with specifications of materials and sizes, and showcase welding avenues. It further extends to highlight the promising friction stir welding as a single solid-state pipe welding procedure. This paper will enable all piping, welding and friction stir welding stakeholders to identify scope for their engagement in a single window.

The paper is a review paper, and it is mainly structured around sections on materials, sizes and standards for pipes in different sectors and the current welding practice for joining pipe and pipe connections; on the process and principle of friction stir welding (FSW) for pipes; identification of main welding process parameters for the FSW of pipes; effects of process parameters; and a well-carved-out concluding summary.

A well-carved-out concluding summary of extracts from thoroughly studied research is presented in a structured way in which the avenues for the engagement of FSW are identified.

The implications of the research are far-reaching. The FSW is currently expanding very fast in the welding of flat surfaces and has evolved into a vast number of variants because of its advantages and versatility. The application of FSW is coming up late but catching up fast, and as a late starter, the outcomes of such a review paper may support stake holders to expand the application of this process from pipe welding to pipe manufacturing, cladding and other high-end applications. Because the process is inherently inclined towards automation, its throughput rate is high and it does not need any consumables, the ultimate benefit can be passed on to the industry in terms of financial gains.

To the best of the authors’ knowledge, this is the only review exclusively for the friction stir welding of pipes with a well-organized piping specification detailed about industrial sectors. The current pipe welding practice in each sector has been presented, and the avenues for engaging FSW have been highlighted. The FSW pipe process parameters are characteristically distinguished from the conventional FSW, and the effects of the process parameters have been presented. The summary is concise yet comprehensive and organized in a structured manner.

This study aims to explore the impact of artificial intelligence-powered personalised recommendations (AI-PPRs) on user engagement, browsing behaviour and purchase intentions on TikTok (Douyin in China), focusing on how these recommendations affect user satisfaction and purchase intention, while also addressing potential privacy concerns. In addition, the research investigates the influence of AI-recommended product presentation, timing and placement, as well as social factors such as key opinion leaders’ (KOLs) influence on consumer decision-making.

Using the expectancy-value theory and the stimulus-organism-response model, this research used a qualitative methodology through interviews with Douyin users to explore their experiences and perceptions of AI-PPRs.

The findings indicate that Douyin’s proactive “push” mechanism of AI-PPRs enhances user engagement by effortlessly integrating product discovery into the entertainment experience. Content-driven AI-PPRs align with user preferences, decrease search time and increase satisfaction and purchase intentions through engaging short videos and live streaming. However, privacy concerns emerge when personalisation is perceived as excessively intrusive, leading to negative emotions and avoidance behaviours. Recommendation timing and cultural context significantly influence receptiveness, with inappropriate timing (e.g. during holidays) causing negative reactions. Technical challenges, such as network issues during live streaming, negatively impact user experience and engagement. Content quality is crucial, and poor or irrelevant content leads to negative perceptions and disengagement. While KOLs face scepticism due to perceived commercialisation, endorsements from trusted figures and authentic influencers are better received. Innovative payment methods, like “Douyin Monthly Payment”, enhance financial flexibility and promote customer loyalty. This study highlights the need to balance personalisation with privacy, emphasising the importance of content quality and authenticity in influencer marketing. For businesses using AI-PPRs, maintaining this balance is essential for preserving trust and sustaining consumer engagement and loyalty.

This study contributes valuable insights to the field by unravelling the intricate dynamics between AI-PPRs, user preferences and social influences. The findings provide practical implications for companies aiming to optimise personalised recommendation algorithms and enhance user engagement, thereby facilitating business growth in the dynamic short video e-commerce market.

This study aims to examine if relational attachment could be considered as a mediator in the relationship between social support and career regret. The theoretical framework is based on Kahn’s (2007) work on meaningful connections.

The authors used a three-part survey for data collection, spread over two months from 368 employees for co-worker social support and 324 employees for supervisor social support working in different sectors in India.

The results indicate that for co-workers, relational attachment acts as a mediator between instrumental support and career regret; but for personal support, the mediation effect is absent. However, instrumental support is not directly related to career regret. Notably, in case of social support from the supervisor, there does not seem to be any mediation effect for personal or instrumental support. But social support is related to career regret for both categories of support.

The authors contribute to literature that examines the mechanism, driving social support and career regret. By understanding how these factors interact and impact one another, researchers can develop interventions and strategies to help individuals navigate career decisions, improve their personal relationships and increase their access to social support. Ultimately, this research can lead to improved well-being and career satisfaction for individuals. As the sample is generalized, there is scope to examine if the relationships differ based on the work structures and idiosyncrasies of the industries.

This study examines the unmapped mechanism that mediates the social support and career regret relationship, and in the process, provides new directions for research.