Search results

The aim of this paper is to provide a narrative review of previous research on tourism demand modelling and forecasting and potential future developments.

A narrative approach is taken in this review of the current body of knowledge.

Significant methodological advancements in tourism demand modelling and forecasting over the past two decades are identified.

The distinct characteristics of the various methods applied in the field are summarised and a research agenda for future investigations is proposed.

本文旨在对先前关于旅游需求建模和预测的研究进行叙述性回顾并对未来潜在发展进行展望。

本文采用叙述性回顾方法对当前知识体系进行了评论。

本文确认了过去二十年旅游需求建模和预测方法论方面的重要进展。

本文总结了该领域应用的各种方法的独特特征, 并对未来研究提出了建议。

El objetivo de este documento es ofrecer una revisión narrativa de la investigación previa sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros.

En esta revisión del marco actual de conocimientos sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros,se adopta un enfoque narrativo.

Se identifican avances metodológicos significativos en la modelización y previsión de la demanda turística en las dos últimas décadas.

Se resumen las características propias de los diversos métodos aplicados en este campo y se propone una agenda de investigación para futuros trabajos.

The primary aim of this research was to investigate the mediating effect of the decision-making structure on the relationship between perceived environmental uncertainty and hospital performance.

Online and manual survey questionnaires were used to collect data in this study. The target population of this study consists of all middle managers within 11 COVID-19 referral hospitals in Surabaya. A total of 189 responses were collected, however, 27 incomplete responses were excluded from the final dataset. Data was analyzed using SEM-PLS.

The study's findings indicate that decision-making structure plays a role in mediating the link between perceived environmental uncertainty and hospital performance assessed via the Balanced Scorecard, highlighting the significance of flexible decision-making processes during uncertain periods. Moreover, based on our supplementary test, respondents' demographic characteristics influence their perceptions of hospital performance.

Hospital administrators can consider the significance of decision-making structures in responding to environmental uncertainties like the COVID-19 pandemic. By fostering adaptable decision-making processes and empowering middle managers, hospitals may enhance their performance and resilience in challenging situations. Additionally, based on supplementary tests, it is found that differences in the perception of the three Balanced Scorecard perspectives imply that hospitals categorized as types A, B, C, and D should prioritize specific areas to improve their overall performance.

This research adds substantial originality and value to the existing body of knowledge by exploring the interplay between decision-making structures, environmental uncertainty, and hospital performance. It contributes to the literature by specifically focusing on the Covid-19 pandemic, a unique and unprecedented global crisis.

We attempt to construct a grey three-way conflict analysis model with constraints to deal with correlated conflict problems with uncertain information.

In order to address these correlated conflict problems with uncertain information, considering the interactive influence and mutual restraints among agents and portraying their attitudes toward the conflict issues, we utilize grey numbers and three-way decisions to propose a grey three-way conflict analysis model with constraints. Firstly, based on the collected information, we introduced grey theory, calculated the degree of conflict between agents and then analyzed the conflict alliance based on the three-way decision theory. Finally, we designed a feedback mechanism to identify key agents and key conflict issues. A case verifies the effectiveness and practicability of the proposed model.

The results show that the proposed model can portray their attitudes toward conflict issues and effectively extract conflict-related information.

By employing this approach, we can provide the answers to Deja’s fundamental questions regarding Pawlak’s conflict analysis: “what are the underlying causes of conflict?” and “how can a viable consensus strategy be identified?”

The gap that this research attempts to fill is to analyse the explanatory factor “industry” when assessing the reputation of a corporate group. In other words, this research attempts to demonstrate the impact of the “industrial halo” on the assessment of corporate reputation, given that, to date, the academic literature has not considered industry as an explanatory variable in the assessment of the reputation of private companies.

A sample of 43 Spanish companies was used to analyse the relationship between the reputation of firms as measured by the Merco Empresas index, and the industries to which they belong, after controlling for company performance, size, turnover, public recognition of their leadership, and corporate responsibility. This involved conducting a cross-sectional analysis of the relationship between the variables for each year in the time period from 2005 to 2016. The available data were taken from the firms' annual financial reports and websites, as well as from the Merco.

The paper shows the existence of industrial halos that account for the corporate reputation of businesses in Spain. It is also shown that industrial halos are not permanent over time, and that they tend to occur in years of crisis.

It would have been desirable for this study to have had sufficient data to include other industries, but this was not possible. As for possible extensions, in addition to expanding the period considered, other analytical techniques, such as panel data models, could be applied to allow comparison with the results obtained here.

The results of this study have some practical implications. Firstly, firms that publish corporate reputation rankings should be aware of the distortion that the industrial halo can produce, especially in times of uncertainty, and seek to correct for it in their measurements. And secondly, corporate groups themselves should assume that the reputation of the industry affects their individual reputation, and consequently, they should see the other companies in the industry not only as competitors but also as “reputational allies”. They should therefore make collective efforts to improve in this respect, especially in the face of reputational crises.

This paper provides a better understanding of the relationship between the reputation of a company and the industry to which it belongs, and of its permanence over time. This relationship has been little studied in the Spanish market to date.

本研究擬分析當企業集團的信譽被評估時的解釋性因素-行業,以填補現時的研究缺口。具體來說,研究人員鑒於學術文獻至今仍未於評估私營企業的信譽時、把行業當作是一個解釋變量來看待,故擬進行研究、以顯示行業光環在評估企業信譽時所產生的影響。

研究使用的樣本為43間西班牙公司。研究人員分析以Merco Empresas 指數來測量的公司信譽與公司所屬行業之間的關係。有關的分析調控了公司的業績、規模、營業額、企業責任、以及企業領導能力的公眾認可程度所帶來的影響。研究人員對有關變量間的關係進行橫向分析 分析於2005年至2016年期間年度性地進行。現有數據取自有關公司的年度財務報表和其網站,也有取自Merco的。

研究結果表明了可解釋西班牙企業信譽的行業光環是存在的。研究結果亦顯示、行業光環不是永恆的,而且,行業光環往往會在營運極其困難的年度內出現。

本文讓我們更深入瞭解公司信譽與公司所屬行業之間的關係,以及其在時間上的永恆性。就這相關的關係而言,探討西班牙市場的研究至今為數不多。

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so they can be appropriately managed in times of crisis. This study aims to examine humanitarian supply chain models.

A new model is developed to pursue the necessary relations in an optimal way that will minimize human, financial and moral losses. In this developed model, in order to optimize the problem and minimize the amount of human and financial losses, the following subjects have been applied: magnitude of the areas in which an accident may occur as obtained by multiple attribute decision-making methods, the distances between relief centers, the number of available rescuers, the number of rescuers required and the risk level of each patient which is determined using previous data and machine learning (ML) algorithms.

For this purpose, a case study in the east of Tehran has been conducted. According to the results obtained from the algorithms, problem modeling and case study, the accuracy of the proposed model is evaluated very well.

Obtaining each injured person's priority using ML techniques and each area's importance or risk level, besides developing a bi-objective mathematical model and using multiple attribute decision-making methods, make this study unique among very few studies that concern ML in the humanitarian supply chain. Moreover, the findings validate the results and the model's functionality very well.

The purpose of this study is to advance a novel evaluation index system and evaluation approach for ability of older adults in China.

This study constructed a comprehensive older adult ability evaluation index system with 4 primary indicators and 17 secondary indicators. Grey clustering analysis and entropy weight method are combined into a robust evaluation model for the ability of older adults.

The result demonstrates that the proposed grey clustering model is readily available to calculate the disability level of elderly individuals. The constructed index system more comprehensively considers all aspects of the disability of the elderly.

This study provides a quantitative method and a more reasonable index system for the determination of the disability level of the elderly.

Small and medium-scale enterprises (SMEs) that operate with modest financial investments and commodities face numerous challenges to remain in business. One major philosophy used by SMEs these days is the implementation of lean manufacturing to get solutions for various issues they encounter. But is lean getting sustained over time? The purpose of this research is to design a Sustainable Lean Performance Index (SLPI) to assess the sustainability of lean systems and to pinpoint the variables that might be present as potential lean system inhibitors which hinder the sustainability of leanness.

A multi-level sustainable lean performance model is constructed and presented based on the literature research, field investigation and survey conducted by administering a questionnaire. Fuzzy logic approach is used to analyse the multi-level model.

SLPI for the SMEs is found using fuzzy logic approach. Additionally, the ranking score system is applied to categorise attributes into weak and strong categories. The performance of the current lean system is determined to be “fair” based on the Euclidean distance approach and the SLPI for SMEs.

This work is concentrated only in South India because of the country’s vast geographical area and rich and wide diversity in industrial culture of the nation. Hence, more work can be done incorporating the other parts of the country and can analyse the lean behaviour in a comparative manner.

The generalised sustainable lean model analysed using fuzzy logic identifies the inhibitors and level of performance of SMEs in South India. This can be implemented to find out the level of performance in the SMEs after a deeper study and analysis around the SMEs of the country.

The sustainable assessment of lean parameters in the SMEs of India is found to be very less in literature, and it lacks profundity. The model established in this study assesses the sustainability of the lean methodology adopted in SMEs by considering the lean and sustainability attributes along with enablers like technology, ethics, customer satisfaction and innovation with the aid of fuzzy logic.

Manufacturers increasingly resort to digital transformation to shape their competitiveness in the digital economy era, while supply chain (SC) collaborative innovation helps them cope with market uncertainties. However, whether and how digital transformation can facilitate SC collaborative innovation remain unclear. To address this gap, we aims to investigate the effects of digital transformation (strategy and capability) on SC collaborative (process and product) innovation and market performance.

We use partial least squares-structural equation modelling (PLS-SEM) with a sample of 210 Chinese manufacturers to investigate the effects of digital transformation (strategy and capability) on SC collaborative (process and product) innovation and market performance.

The results show that digital strategy and capability positively impact SC collaborative process and product innovation, which enhances market performance. In addition, SC collaborative innovation mediates the relationship between digital transformation and market performance.

This study contributes to the literature by identifying how digital transformation drives SC collaborative innovation towards improving market performance and providing practical guidance for enterprises in promoting digital transformation and SC collaborative innovation.

The purpose of this paper is to investigate the impact of the COVID-19 pandemic on company innovation, specifically centering on the quantity and quality of innovation. The paper aims to provide a comprehensive understanding of whether the epidemic inhibits innovation and the role of digital transformation in mitigating this negative impact.

The paper uses a quasi-experimental study of the COVID-19 pandemic and constructs a differential model to analyze the relationship between the epidemic and firm innovation in three dimensions: total, quantity and quality. The paper also uses a difference-in-difference-in-differences model to test whether digital transformation of firms mitigates the negative impact of the epidemic and its mechanism of action.

The results show that COVID-19 significantly reduced the overall level of firm innovation, primarily in terms of quantity rather than quality. Furthermore, this study finds that digital transformation plays a pivotal role in mitigating the pandemic’s adverse impact on innovation. By addressing financing constraints and countering demand insufficiency, digital transformation acts as a catalyst for preserving and fostering innovation during and after the pandemic.

This study extends the current research on the pandemic’s impact on firm innovation at the micro level. It offers valuable insights into strategies for fostering digital transformation among Chinese enterprises in the post-pandemic era.

Based on the cognition–affect–conation pattern, this study explores the factors that affect the intention to use facial recognition services (FRS). The study adopts the driving factor perspective to examine how network externalities influence FRS use intention through the mediating role of satisfaction and the barrier factor perspective to analyze how perceived privacy risk affects FRS use intention through the mediating role of privacy cynicism.

The data collected from 478 Chinese FRS users are analyzed via partial least squares-based structural equation modeling (PLS-SEM).

The study produces the following results. (1) FRS use intention is motivated directly by the positive affective factor of satisfaction and the negative affective factor of privacy cynicism. (2) Satisfaction is affected by cognitive factors related to network externalities. Perceived complementarity and perceived compatibility, two indirect network externalities, positively affect satisfaction, whereas perceived critical mass, a direct network externality, does not significantly affect satisfaction. In addition, perceived privacy risk generates privacy cynicism. (3) Resistance to change positively moderates the relationship between privacy cynicism and intention to use FRS.

This study extends knowledge on people's use of FRS by exploring affect- and cognitive-based factors and finding that the affect-based factors (satisfaction and privacy cynicism) play fully mediating roles in the relationship between the cognitive-based factors and use intention. This study also expands the cognitive boundaries of FRS use by exploring the functional condition between affect-based factors and use intention, that is, the moderating role of resistance to use.